What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.

Adsorption properties of subtropical and tropical variable charge soils: Implications from climate change and biochar amendment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Ren-Kou; Qafoku, Nikolla; Van Ranst, Eric

2016-01-25

This review paper attempts to summarize the progress made in research efforts conducted over the last years to study the surface chemical properties of the tropical and subtropical soils, usually called variable charge soils, and the way they response to different management practices. The paper is composed of an introductory section that provides a brief discussion on the surface chemical properties of these soils, and five other review sections. The focus of these sections is on the evolution of surface chemical properties during the development of the variable charge properties (second section), interactions between oppositely charged particles and the resultingmore » effects on the soil properties and especially on soil acidity (third section), the surface effects of low molecular weight organic acids sorbed to mineral surfaces and the chemical behavior of aluminum (fourth section), and the crop straw derived biochar induced changes of the surface chemical properties of these soils (fifth section). A discussion on the effect of climate change variables on the properties of the variable charge soils is included at the end of this review paper (sixth section).« less

Evapotranspiration from nonuniform surfaces - A first approach for short-term numerical weather prediction

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1988-01-01

Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.

Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography

NASA Astrophysics Data System (ADS)

Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.

2016-12-01

Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.

Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

NASA Astrophysics Data System (ADS)

Rahmati, Mehdi

2017-08-01

Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed that Ks exclusion from input variables list caused around 30 percent decrease in PTFs accuracy for all applied procedures. However, it seems that Ks exclusion resulted in more practical PTFs especially in the case of GMDH network applying input variables which are less time consuming than Ks. In general, it is concluded that GMDH provides more accurate and reliable estimates of cumulative infiltration (a non-readily available characteristic of soil) with a minimum set of input variables (2-4 input variables) and can be promising strategy to model soil infiltration combining the advantages of ANN and MLR methodologies.

Simulation of changes in heavy metal contamination in farmland soils of a typical manufacturing center through logistic-based cellular automata modeling.

PubMed

Qiu, Menglong; Wang, Qi; Li, Fangbai; Chen, Junjian; Yang, Guoyi; Liu, Liming

2016-01-01

A customized logistic-based cellular automata (CA) model was developed to simulate changes in heavy metal contamination (HMC) in farmland soils of Dongguan, a manufacturing center in Southern China, and to discover the relationship between HMC and related explanatory variables (continuous and categorical). The model was calibrated through the simulation and validation of HMC in 2012. Thereafter, the model was implemented for the scenario simulation of development alternatives for HMC in 2022. The HMC in 2002 and 2012 was determined through soil tests and cokriging. Continuous variables were divided into two groups by odds ratios. Positive variables (odds ratios >1) included the Nemerow synthetic pollution index in 2002, linear drainage density, distance from the city center, distance from the railway, slope, and secondary industrial output per unit of land. Negative variables (odds ratios <1) included elevation, distance from the road, distance from the key polluting enterprises, distance from the town center, soil pH, and distance from bodies of water. Categorical variables, including soil type, parent material type, organic content grade, and land use type, also significantly influenced HMC according to Wald statistics. The relative operating characteristic and kappa coefficients were 0.91 and 0.64, respectively, which proved the validity and accuracy of the model. The scenario simulation shows that the government should not only implement stricter environmental regulation but also strengthen the remediation of the current polluted area to effectively mitigate HMC.

A global map of mangrove forest soil carbon at 30 m spatial resolution

NASA Astrophysics Data System (ADS)

Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

2018-05-01

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

A simplified regional-scale electromagnetic induction - Salinity calibration model using ANOCOVA modeling techniques

USDA-ARS?s Scientific Manuscript database

Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (ECa) is a potential means of characterizing the spatial variability of any soil property that influences ECa including soil salinity, water content, texture, bulk density, organic matter, and cation exc...

[Relationships between soil and rocky desertification in typical karst mountain area based on redundancy analysis].

PubMed

Long, Jian; Liao, Hong-Kai; Li, Juan; Chen, Cai-Yun

2012-06-01

Redundancy analysis (RDA) was employed to reveal the relationships between soil and rocky desertification through vegetation investigation and analysis of soil samples collected in typical karst mountain area of southwest Guizhou Province. The results showed that except TP, TK and ACa, all other variables including SOC, TN, MBC, ROC, DOC, available nutrients and basal respiration showed significant downward trends during the rocky desertification process. RDA results showed significant correlations between different types of desertification and soil variables, described as non-degraded > potential desertification > light desertification > moderate desertification > severe desertification. Moreover, RDA showed that using SOC, TN, AN, and BD as soil indicators, 74.4% of the variance information on soil and rocky desertification could be explained. Furthermore, the results of correlation analysis showed that soil variables were significantly affected by surface vegetation. Considering the ecological function of the aboveground vegetation and the soil quality, Zanthoxylum would be a good choice for restoration of local vegetation in karst mountain area.

Assessing soil compaction on Forest Inventory & Analysis phase 3 field plots using a pocket penetrometer

Treesearch

Michael C. Amacher; Katherine P. O' Neill

2004-01-01

Soil compaction is an important indicator of soil quality, yet few practical methods are available to quantitatively measure this variable. Although an assessment of the areal extent of soil compaction is included as part of the soil indicator portion of the Forest Inventory & Analysis (FIA) program, no quantitative measurement of the degree of soil compaction...

Soil-Site Factors Affecting Southern Upland Oak Managment and Growth

Treesearch

John K. Francis

1980-01-01

Soil supplies trees with physical support, moisture, oxygen, and nutrients. Amount of moisture most limits tree growth; and soil and topographic factors such as texture and aspect, which influence available soil moisture. are most useful in predicting growth. Equations that include soil and topographic variables can be used to predict site index. Foresters can also...

The past, present, and future of soils and human health studies

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Sauer, T. J.

2015-01-01

The idea that human health is tied to the soil is not a new one. As far back as circa 1400 BC the Bible depicts Moses as understanding that fertile soil was essential to the well-being of his people. In 400 BC the Greek philosopher Hippocrates provided a list of things that should be considered in a proper medical evaluation, including the properties of the local ground. By the late 1700s and early 1800s, American farmers had recognized that soil properties had some connection to human health. In the modern world, we recognize that soils have a distinct influence on human health. We recognize that soils influence (1) food availability and quality (food security), (2) human contact with various chemicals, and (3) human contact with various pathogens. Soils and human health studies include investigations into nutrient supply through the food chain and routes of exposure to chemicals and pathogens. However, making strong, scientific connections between soils and human health can be difficult. There are multiple variables to consider in the soil environment, meaning traditional scientific studies that seek to isolate and manipulate a single variable often do not provide meaningful data. The complete study of soils and human health also involves many different specialties such as soil scientists, toxicologists, medical professionals, anthropologists, etc. These groups do not traditionally work together on research projects, and do not always effectively communicate with one another. Climate change and how it will affect the soil environment/ecosystem going into the future is another variable affecting the relationship between soils and health. Future successes in soils and human health research will require effectively addressing difficult issues such as these.

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

Missouri Ozark forest soils: perspectives and realities

Treesearch

R. David. Hammer

1997-01-01

Ozark forest soils are dynamic in space and time, and most formed in multiple parent materials. Erosion and mass movement have been variable and extensive. Soil attributes including texture, cation exchange capacity, and mineralogy are related to geologic strata and to geomorphic conditions. Soil organic carbon content is influenced by surface shape, position in...

Spatial Irrigation Management Using Remote Sensing Water Balance Modeling and Soil Water Content Monitoring

NASA Astrophysics Data System (ADS)

Barker, J. Burdette

Spatially informed irrigation management may improve the optimal use of water resources. Sub-field scale water balance modeling and measurement were studied in the context of irrigation management. A spatial remote-sensing-based evapotranspiration and soil water balance model was modified and validated for use in real-time irrigation management. The modeled ET compared well with eddy covariance data from eastern Nebraska. Placement and quantity of sub-field scale soil water content measurement locations was also studied. Variance reduction factor and temporal stability were used to analyze soil water content data from an eastern Nebraska field. No consistent predictor of soil water temporal stability patterns was identified. At least three monitoring locations were needed per irrigation management zone to adequately quantify the mean soil water content. The remote-sensing-based water balance model was used to manage irrigation in a field experiment. The research included an eastern Nebraska field in 2015 and 2016 and a western Nebraska field in 2016 for a total of 210 plot-years. The response of maize and soybean to irrigation using variations of the model were compared with responses from treatments using soil water content measurement and a rainfed treatment. The remote-sensing-based treatment prescribed more irrigation than the other treatments in all cases. Excessive modeled soil evaporation and insufficient drainage times were suspected causes of the model drift. Modifying evaporation and drainage reduced modeled soil water depletion error. None of the included response variables were significantly different between treatments in western Nebraska. In eastern Nebraska, treatment differences for maize and soybean included evapotranspiration and a combined variable including evapotranspiration and deep percolation. Both variables were greatest for the remote-sensing model when differences were found to be statistically significant. Differences in maize yield in 2015 were attributed to random error. Soybean yield was lowest for the remote-sensing-based treatment and greatest for rainfed, possibly because of overwatering and lodging. The model performed well considering that it did not include soil water content measurements during the season. Future work should improve the soil evaporation and drainage formulations, because of excessive precipitation and include aerial remote sensing imagery and soil water content measurement as model inputs.

Evaluating soil carbon in global climate models: benchmarking, future projections, and model drivers

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Randerson, J. T.; Post, W. M.; Allison, S. D.

2012-12-01

The carbon cycle plays a critical role in how the climate responds to anthropogenic carbon dioxide. To evaluate how well Earth system models (ESMs) from the Climate Model Intercomparison Project (CMIP5) represent the carbon cycle, we examined predictions of current soil carbon stocks from the historical simulation. We compared the soil and litter carbon pools from 17 ESMs with data on soil carbon stocks from the Harmonized World Soil Database (HWSD). We also examined soil carbon predictions for 2100 from 16 ESMs from the rcp85 (highest radiative forcing) simulation to investigate the effects of climate change on soil carbon stocks. In both analyses, we used a reduced complexity model to separate the effects of variation in model drivers from the effects of model parameters on soil carbon predictions. Drivers included NPP, soil temperature, and soil moisture, and the reduced complexity model represented one pool of soil carbon as a function of these drivers. The ESMs predicted global soil carbon totals of 500 to 2980 Pg-C, compared to 1260 Pg-C in the HWSD. This 5-fold variation in predicted soil stocks was a consequence of a 3.4-fold variation in NPP inputs and 3.8-fold variability in mean global turnover times. None of the ESMs correlated well with the global distribution of soil carbon in the HWSD (Pearson's correlation <0.40, RMSE 9-22 kg m-2). On a biome level there was a broad range of agreement between the ESMs and the HWSD. Some models predicted HWSD biome totals well (R2=0.91) while others did not (R2=0.23). All of the ESM terrestrial decomposition models are structurally similar with outputs that were well described by a reduced complexity model that included NPP and soil temperature (R2 of 0.73-0.93). However, MPI-ESM-LR outputs showed only a moderate fit to this model (R2=0.51), and CanESM2 outputs were better described by a reduced model that included soil moisture (R2=0.74), We also found a broad range in soil carbon responses to climate change predicted by the ESMs, with changes of -480 to 230 Pg-C from 2005-2100. All models that reported NPP and heterotrophic respiration showed increases in both of these processes over the simulated period. In two of the models, soils switched from a global sink for carbon to a net source. Of the remaining models, half predicted that soils were a sink for carbon throughout the time period and the other half predicted that soils were a carbon source.. Heterotrophic respiration in most of the models from 2005-2100 was well explained by a reduced complexity model dependent on soil carbon, soil temperature, and soil moisture (R2 values >0.74). However, MPI-ESM (R2=0.45) showed only moderate fit to this model. Our analysis shows that soil carbon predictions from ESMs are highly variable, with much of this variability due to model parameterization and variations in driving variables. Furthermore, our reduced complexity models show that most variation in ESM outputs can be explained by a simple one-pool model with a small number of drivers and parameters. Therefore, agreement between soil carbon predictions across models could improve substantially by reconciling differences in driving variables and the parameters that link soil carbon with environmental drivers. However it is unclear if this model agreement would reflect what is truly happening in the Earth system.

Spatial variability structure of soil CO2 emission and soil physical and chemical properties characterized by fractal dimension in sugarcane areas

NASA Astrophysics Data System (ADS)

Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.

2012-04-01

Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.

Some aspects of interrelations between fungi and other biota in forest soil.

PubMed

Krivtsov, Vladimir; Griffiths, Bryan S; Salmond, Ross; Liddell, Keith; Garside, Adam; Bezginova, Tanya; Thompson, Jacqueline A; Staines, Harry J; Watling, Roy; Palfreyman, John W

2004-08-01

Interrelations of fungal mycelium with other soil biota are of paramount importance in forestry and soil ecology. Here we present the results of statistical analysis of a comprehensive data set collected in the first (and the only) British fungus sanctuary over a period of four months. The variables studied included a number of soil properties, bacteria, protozoan flagellates, ciliates and amoebae, microbial and plant feeding nematodes, various microarthropods, and two fungal biomarkers--glomalin and ergosterol. One way ANOVA showed that the dynamics of the microbiota studied was influenced by seasonal changes. Superimposed on these changes, however, was variability due to biological interactions and habitat characteristics. Two fungal biomarkers, ergosterol and glomalin, were differently influenced by other biota and abiotic variables. The results indicate that the dynamics of soil fungi is influenced not only by soil microarthropods, but also by those found in forest litter. The overall outcome, therefore, is likely to be very complex and will depend upon specific conditions of any particular ecosystem.

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

Predicting surface vibration from underground railways through inhomogeneous soil

NASA Astrophysics Data System (ADS)

Jones, Simon; Hunt, Hugh

2012-04-01

Noise and vibration from underground railways is a major source of disturbance to inhabitants near subways. To help designers meet noise and vibration limits, numerical models are used to understand vibration propagation from these underground railways. However, the models commonly assume the ground is homogeneous and neglect to include local variability in the soil properties. Such simplifying assumptions add a level of uncertainty to the predictions which is not well understood. The goal of the current paper is to quantify the effect of soil inhomogeneity on surface vibration. The thin-layer method (TLM) is suggested as an efficient and accurate means of simulating vibration from underground railways in arbitrarily layered half-spaces. Stochastic variability of the soil's elastic modulus is introduced using a K-L expansion; the modulus is assumed to have a log-normal distribution and a modified exponential covariance kernel. The effect of horizontal soil variability is investigated by comparing the stochastic results for soils varied only in the vertical direction to soils with 2D variability. Results suggest that local soil inhomogeneity can significantly affect surface velocity predictions; 90 percent confidence intervals showing 8 dB averages and peak values up to 12 dB are computed. This is a significant source of uncertainty and should be considered when using predictions from models assuming homogeneous soil properties. Furthermore, the effect of horizontal variability of the elastic modulus on the confidence interval appears to be negligible. This suggests that only vertical variation needs to be taken into account when modelling ground vibration from underground railways.

Climate Prediction Center - Seasonal Outlook

Science.gov Websites

SEASONAL CLIMATE VARIABILITY, INCLUDING ENSO, SOIL MOISTURE, AND VARIOUS STATE-OF-THE-ART DYNAMICAL MODEL ACROSS PARTS OF THE EAST-CENTRAL CONUS CENTERED ON THE MISSISSIPPI RIVER. THIS IS DUE TO VERY HIGH SOIL TRENDS, NEGATIVE SOIL MOISTURE ANOMALIES, LAGGED ENSO REGRESSIONS, AND DYNAMICAL MODEL GUIDANCE ARE ALL

Soil properties of mangroves in contrasting geomorphic settings within the Zambezi River Delta, Mozambique

Treesearch

Christina E. Stringer; Carl C. Trettin; Stan Zarnoch

2016-01-01

Mangroves are well-known for their numerous ecosystem services, including sequestering a significant carbon stock, with soils accounting for the largest pool. The soil carbon pool is dependent on the carbon content and bulk density. Our objective was to assess the spatial variability of mangrove soil physical and chemical properties within the Zambezi River Delta and...

Implementing and Evaluating Variable Soil Thickness in the Community Land Model, Version 4.5 (CLM4.5)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brunke, Michael A.; Broxton, Patrick; Pelletier, Jon

2016-05-01

One of the recognized weaknesses of land surface models as used in weather and climate models is the assumption of constant soil thickness due to the lack of global estimates of bedrock depth. Using a 30 arcsecond global dataset for the thickness of relatively porous, unconsolidated sediments over bedrock, spatial variation in soil thickness is included here in version 4.5 of the Community Land Model (CLM4.5). The number of soil layers for each grid cell is determined from the average soil depth for each 0.9° latitude x 1.25° longitude grid cell. Including variable soil thickness affects the simulations most inmore » regions with shallow bedrock corresponding predominantly to areas of mountainous terrain. The greatest changes are to baseflow, with the annual minimum generally occurring earlier, while smaller changes are seen in surface fluxes like latent heat flux and surface runoff in which only the annual cycle amplitude is increased. These changes are tied to soil moisture changes which are most substantial in locations with shallow bedrock. Total water storage (TWS) anomalies do not change much over most river basins around the globe, since most basins contain mostly deep soils. However, it was found that TWS anomalies substantially differ for a river basin with more mountainous terrain. Additionally, the annual cycle in soil temperature are affected by including realistic soil thicknesses due to changes to heat capacity and thermal conductivity.« less

Spatial and temporal variability of soil temperature, moisture and surface soil properties

NASA Technical Reports Server (NTRS)

Hajek, B. F.; Dane, J. H.

1993-01-01

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.

Ecological Drivers of Biogeographic Patterns of Soil Archaeal Community

PubMed Central

Zheng, Yuan-Ming; Cao, Peng; Fu, Bojie; Hughes, Jane M.; He, Ji-Zheng

2013-01-01

Knowledge about the biogeography of organisms has long been a focus in ecological research, including the mechanisms that generate and maintain diversity. In this study, we targeted a microbial group relatively underrepresented in the microbial biogeographic literature, the soil Archaea. We surveyed the archaeal abundance and community composition using real-time quantitative PCR and T-RFLP approaches for 105 soil samples from 2 habitat types to identify the archaeal distribution patterns and factors driving these patterns. Results showed that the soil archaeal community was affected by spatial and environmental variables, and 79% and 51% of the community variation was explained in the non-flooded soil (NS) and flooded soil (FS) habitat, respectively, showing its possible biogeographic distribution. The diversity patterns of soil Archaea across the landscape were influenced by a combination of stochastic and deterministic processes. The contribution from neutral processes was higher than that from deterministic processes associated with environmental variables. The variables pH, sample depth and longitude played key roles in determining the archaeal distribution in the NS habitat, while sampling depth, longitude and NH4 +-N were most important in the FS habitat. Overall, there might be similar ecological drivers in the soil archaeal community as in macroorganism communities. PMID:23717418

A soil-landscape framework for understanding spatial and temporal variability in biogeochemical processes in catchments

NASA Astrophysics Data System (ADS)

McGuire, K. J.; Bailey, S. W.; Ross, D. S.

2017-12-01

Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.

Impact of understory vegetation on soil carbon and nitrogen dynamic in aerially seeded Pinus massoniana plantations.

PubMed

Pan, Ping; Zhao, Fang; Ning, Jinkui; Zhang, Ling; Ouyang, Xunzhi; Zang, Hao

2018-01-01

Understory vegetation plays a vital role in regulating soil carbon (C) and nitrogen (N) characteristics due to differences in plant functional traits. Different understory vegetation types have been reported following aerial seeding. While aerial seeding is common in areas with serious soil erosion, few studies have been conducted to investigate changes in soil C and N cycling as affected by understory vegetation in aerially seeded plantations. Here, we studied soil C and N characteristics under two naturally formed understory vegetation types (Dicranopteris and graminoid) in aerially seeded Pinus massoniana Lamb plantations. Across the two studied understory vegetation types, soil organic C was significantly correlated with all measured soil N variables, including total N, available N, microbial biomass N and water-soluble organic N, while microbial biomass C was correlated with all measured variables except soil organic C. Dicranopteris and graminoid differed in their effects on soil C and N process. Except water-soluble organic C, all the other C and N variables were higher in soils with graminoids. The higher levels of soil organic C, microbial biomass C, total N, available N, microbial biomass N and water-soluble organic N were consistent with the higher litter and root quality (C/N) of graminoid vegetation compared to Dicranopteris. Changes in soil C and N cycles might be impacted by understory vegetation types via differences in litter or root quality.

Impact of understory vegetation on soil carbon and nitrogen dynamic in aerially seeded Pinus massoniana plantations

PubMed Central

Pan, Ping; Zhao, Fang; Ning, Jinkui; Ouyang, Xunzhi; Zang, Hao

2018-01-01

Understory vegetation plays a vital role in regulating soil carbon (C) and nitrogen (N) characteristics due to differences in plant functional traits. Different understory vegetation types have been reported following aerial seeding. While aerial seeding is common in areas with serious soil erosion, few studies have been conducted to investigate changes in soil C and N cycling as affected by understory vegetation in aerially seeded plantations. Here, we studied soil C and N characteristics under two naturally formed understory vegetation types (Dicranopteris and graminoid) in aerially seeded Pinus massoniana Lamb plantations. Across the two studied understory vegetation types, soil organic C was significantly correlated with all measured soil N variables, including total N, available N, microbial biomass N and water-soluble organic N, while microbial biomass C was correlated with all measured variables except soil organic C. Dicranopteris and graminoid differed in their effects on soil C and N process. Except water-soluble organic C, all the other C and N variables were higher in soils with graminoids. The higher levels of soil organic C, microbial biomass C, total N, available N, microbial biomass N and water-soluble organic N were consistent with the higher litter and root quality (C/N) of graminoid vegetation compared to Dicranopteris. Changes in soil C and N cycles might be impacted by understory vegetation types via differences in litter or root quality. PMID:29377926

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Temporal and spatial variability of soil biological activity at European scale

NASA Astrophysics Data System (ADS)

Mallast, Janine; Rühlmann, Jörg

2015-04-01

The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. Soil biological activity was investigated using two model concepts: a) Re_clim parameter within the ICBM (Introductory Carbon Balance Model) (Andrén & Kätterer 1997) states a climatic factor summarizing soil water storage and soil temperature and its influence on soil biological activity. b) BAT (biological active time) approach derived from model CANDY (CArbon and Nitrogen Dynamic) (Franko & Oelschlägel 1995) expresses the variation of soil moisture, soil temperature and soil aeration as a time scale and an indicator of biological activity for soil organic matter (SOM) turnover. During an earlier stage both model concepts, Re_clim and BAT, were applied based on a monthly data to assess spatial variability of turnover conditions across Europe. This hampers the investigation of temporal variability (e.g. intra-annual). The improved stage integrates daily data of more than 350 weather stations across Europe presented by Klein Tank et al. (2002). All time series data (temperature, precipitation and potential evapotranspiration and soil texture derived from the European Soil Database (JRC 2006)), are used to calculate soil biological activity in the arable layer. The resulting BAT and Re_clim values were spatio-temporal investigated. While "temporal" refers to a long-term trend analysis, "spatial" includes the investigation of soil biological activity variability per environmental zone (ENZ, Metzger et al. 2005 representing similar conditions for precipitation, temperature and relief) to identify ranges and hence turnover conditions for each ENZ. We will discuss the analyzed results of both concepts to assess SOM turnover conditions across Europe for historical weather data and for Spain focusing on climate scenarios. Both concepts help to separate different turnover activities and to indicate organic matter input in order to maintain the given SOM. The assessment could provide recommendations for adaptations of soil management practices. CATCH-C is funded within the 7th Framework Programme for Research, Technological Development and Demonstration, Theme 2 - Biotechnologies, Agriculture & Food (Grant Agreement N° 289782).

Characterization of soil spatial variability for site-specific management using soil electrical conductivity and other remotely sensed data

NASA Astrophysics Data System (ADS)

Bang, Jisu

Field-scale characterization of soil spatial variability using remote sensing technology has potential for achieving the successful implementation of site-specific management (SSM). The objectives of this study were to: (i) examine the spatial relationships between apparent soil electrical conductivity (EC a) and soil chemical and physical properties to determine if EC a could be useful to characterize soil properties related to crop productivity in the Coastal Plain and Piedmont of North Carolina; (ii) evaluate the effects of in-situ soil moisture variation on ECa mapping as a basis for characterization of soil spatial variability and as a data layer in cluster analysis as a means of delineating sampling zones; (iii) evaluate clustering approaches using different variable sets for management zone delineation to characterize spatial variability in soil nutrient levels and crop yields. Studies were conducted in two fields in the Piedmont and three fields in the Coastal Plain of North Carolina. Spatial measurements of ECa via electromagnetic induction (EMI) were compared with soil chemical parameters (extractable P, K, and micronutrients; pH, cation exchange capacity [CEC], humic matter or soil organic matter; and physical parameters (percentage sand, silt, and clay; and plant-available water [PAW] content; bulk density; cone index; saturated hydraulic conductivity [Ksat] in one of the coastal plain fields) using correlation analysis across fields. We also collected ECa measurements in one coastal plain field on four days with significantly different naturally occurring soil moisture conditions measured in five increments to 0.75 m using profiling time-domain reflectometry probes to evaluate the temporal variability of ECa associated with changes in in-situ soil moisture content. Nonhierarchical k-means cluster analysis using sensor-based field attributes including vertical ECa, near-infrared (NIR) radiance of bare-soil from an aerial color infrared (CIR) image, elevation, slope, and their combinations was performed to delineate management zones. The strengths and signs of the correlations between ECa and measured soil properties varied among fields. Few strong direct correlations were found between ECa and the soil chemical and physical properties studied (r2 < 0.50), but correlations improved considerably when zone mean ECa and zone means of selected soil properties among ECa zones were compared. The results suggested that field-scale ECa survey is not able to directly predict soil nutrient levels at any specific location, but could delimit distinct zones of soil condition among which soil nutrient levels differ, providing an effective basis for soil sampling on a zone basis. (Abstract shortened by UMI.)

Evaluation of gravimetric ground truth soil moisture data collected for the agricultural soil moisture experiment, 1978 Colby, Kansas, aircraft mission

NASA Technical Reports Server (NTRS)

Arya, L. M.; Phinney, D. E. (Principal Investigator)

1980-01-01

Soil moisture data acquired to support the development of algorithms for estimating surface soil moisture from remotely sensed backscattering of microwaves from ground surfaces are presented. Aspects of field uniformity and variability of gravimetric soil moisture measurements are discussed. Moisture distribution patterns are illustrated by frequency distributions and contour plots. Standard deviations and coefficients of variation relative to degree of wetness and agronomic features of the fields are examined. Influence of sampling depth on observed moisture content an variability are indicated. For the various sets of measurements, soil moisture values that appear as outliers are flagged. The distribution and legal descriptions of the test fields are included along with examinations of soil types, agronomic features, and sampling plan. Bulk density data for experimental fields are appended, should analyses involving volumetric moisture content be of interest to the users of data in this report.

Comparison of broiler litter and commercial fertilizer at equivalent N rates on soil quality

USDA-ARS?s Scientific Manuscript database

A 3-year study was conducted to determine the effects of variable rates of broiler litter relative to inorganic fertilizer at equivalent N rates on soil nutrient content and quality in an upland Granada silt loam (fine-silty, mixed, active, Thermic, Fraglossudalfs) soil. Treatments included annual b...

Introduction to the special section ‘Applications of electromagnetic induction to digital soil mapping’

USDA-ARS?s Scientific Manuscript database

Use of electromagnetic induction (EMI) instruments has increased as a tool to map soils because it provides a means of locating suitable sampling sites that provide the basis for mapping the spatial variability of various soil properties either directly or indirectly measured with EMI, including sa...

Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water.

PubMed

Franz, Eelco; Schijven, Jack; de Roda Husman, Ana Maria; Blaak, Hetty

2014-06-17

The extent to which pathogenic and commensal E. coli (respectively PEC and CEC) can survive, and which factors predominantly determine the rate of decline, are crucial issues from a public health point of view. The goal of this study was to provide a quantitative summary of the variability in E. coli survival in soil and water over a broad range of individual studies and to identify the most important sources of variability. To that end, a meta-regression analysis on available literature data was conducted. The considerable variation in reported decline rates indicated that the persistence of E. coli is not easily predictable. The meta-analysis demonstrated that for soil and water, the type of experiment (laboratory or field), the matrix subtype (type of water and soil), and temperature were the main factors included in the regression analysis. A higher average decline rate in soil of PEC compared with CEC was observed. The regression models explained at best 57% of the variation in decline rate in soil and 41% of the variation in decline rate in water. This indicates that additional factors, not included in the current meta-regression analysis, are of importance but rarely reported. More complete reporting of experimental conditions may allow future inference on the global effects of these variables on the decline rate of E. coli.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data

NASA Astrophysics Data System (ADS)

Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.

2017-04-01

The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.

Controls on Soil Organic Matter in Blue Carbon Ecosystems along the South Florida Coast

NASA Astrophysics Data System (ADS)

Smoak, J. M.; Rosenheim, B. E.; Moyer, R. P.; Radabaugh, K.; Chambers, L. G.; Lagomasino, D.; Lynch, J.; Cahoon, D. R.

2017-12-01

Coastal wetlands store disproportionately large amounts of carbon due to high rates of net primary productivity and slow microbial degradation of organic matter in water-saturated soils. Wide spatial and temporal variability in plant communities and soil biogeochemistry necessitate location-specific quantification of carbon stocks to improve current wetland carbon inventories and future projections. We apply field measurements, remote sensing technology, and spatiotemporal models to quantify regional carbon storage and to model future spatial variability of carbon stocks in mangroves and coastal marshes in Southwest Florida. We examine soil carbon accumulation and accretion rates on time scales ranging from decadal to millennial to project responses to climate change, including variations in inundation and salinity. Once freshwater and oligohaline wetlands are exposed to increased duration and spatial extent of inundation and salinity from seawater, soil redox potential, soil respiration, and the intensification of osmotic stress to vegetation and the soil microbial community can affect the soil C balance potentially increasing rates of mineralization.

Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century

NASA Astrophysics Data System (ADS)

Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.

2017-12-01

Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.

Spatial variability of soil total and DTPA-extractable cadmium caused by long-term application of phosphate fertilizers, crop rotation, and soil characteristics.

PubMed

Jafarnejadi, A R; Sayyad, Gh; Homaee, M; Davamei, A H

2013-05-01

Increasing cadmium (Cd) accumulation in agricultural soils is undesirable due to its hazardous influences on human health. Thus, having more information on spatial variability of Cd and factors effective to increase its content on the cultivated soils is very important. Phosphate fertilizers are main contamination source of cadmium (Cd) in cultivated soils. Also, crop rotation is a critical management practice which can alter soil Cd content. This study was conducted to evaluate the effects of long-term consumption of the phosphate fertilizers, crop rotations, and soil characteristics on spatial variability of two soil Cd species (i.e., total and diethylene triamine pentaacetic acid (DTPA) extractable) in agricultural soils. The study was conducted in wheat farms of Khuzestan Province, Iran. Long-term (27-year period (1980 to 2006)) data including the rate and the type of phosphate fertilizers application, the respective area, and the rotation type of different regions were used. Afterwards, soil Cd content (total or DTPA extractable) and its spatial variability in study area (400,000 ha) were determined by sampling from soils of 255 fields. The results showed that the consumption rate of di-ammonium phosphate fertilizer have been varied enormously in the period study. The application rate of phosphorus fertilizers was very high in some subregions with have extensive agricultural activities (more than 95 kg/ha). The average and maximum contents of total Cd in the study region were obtained as 1.47 and 2.19 mg/kg and DTPA-extractable Cd as 0.084 and 0.35 mg/kg, respectively. The spatial variability of Cd indicated that total and DTPA-extractable Cd contents were over 0.8 and 0.1 mg/kg in 95 and 25 % of samples, respectively. The spherical model enjoys the best fitting and lowest error rate to appraise the Cd content. Comparing the phosphate fertilizer consumption rate with spatial variability of the soil cadmium (both total and DTPA extractable) revealed the high correlation between the consumption rate of P fertilizers and soil Cd content. Rotation type was likely the main effective factor on variations of the soil DTPA-extractable Cd contents in some parts (eastern part of study region) and could explain some Cd variation. Total Cd concentrations had significant correlation with the total neutralizing value (p < 0.01), available P (p < 0.01), cation exchange capacity (p < 0.05), and organic carbon (p < 0.05) variables. The DTPA-extractable Cd had significant correlation with OC (p < 0.01), pH, and clay content (p < 0.05). Therefore, consumption rate of the phosphate fertilizers and crop rotation are important factors on solubility and hence spatial variability of Cd content in agricultural soils.

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE PAGES

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.; ...

2018-05-18

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Predicting active-layer soil thickness using topographic variables at a small watershed scale

PubMed Central

Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

2017-01-01

Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters. PMID:28877196

Between and within-field variation in physico-chemical soil properties of vineyards: implications for terroir zoning and management in Heuvelland, Belgium

NASA Astrophysics Data System (ADS)

Tavernier, Emma; Verdoodt, Ann; Cornelis, Wim; Delbecque, Nele; Tiebergijn, Lynn; Seynnaeve, Marleen; Gabriels, Donald

2015-04-01

The 'Heuvelland' region with a surface area of 94 km² is situated in the Province of West Flanders, Belgium, bordering with France. The region comprises a number of hills ("heuvel") on which a fast growing 'wine culture' is developing. Both professional as well as non-professional wine makers together cultivate about 19 ha of vineyards, and are still expanding. Grapes cultivated include Chardonnay, Pinot gris and Pinot noir among others. The small-scale, strongly dispersed vineyards are located in different landscape positions of variable aspect. The objective of our preliminary study was to assess the between-field and within-field variation in physico-chemical soil properties of these vineyards with the aim to better characterise the terroir(s) in Heuvelland and provide guidelines for soil management. Fourteen vineyards from five different wineries were selected for detailed soil sampling. Twenty-five sampling sites were chosen according to the topography, soil map units and observed variability in grape growth. The soil was sampled using 15 cm depth increments up to a depth of 60 cm or a shallower lithic contact. Composite samples of 5 sampling locations along the contour lines were taken per within-field zone. Besides the texture, pH, organic carbon, total nitrogen, available phosphorous and exchangeable base cations (Ca, Mg, K), also some micronutrients (Fe, B, Cu, Mn) were determined using standard laboratory procedures. The soils developed on Quaternary niveo-eolian sandy loam and loamy sediments of variable thickness covering marine sandy and clayey sediments of the Tertiary. Where the Tertiary clayey sediments occur at shallow depth, they can strongly influence the internal drainage. At higher positions in the landscape, iron-rich sandstone layers are found at shallow depth. Fragments of this iron-rich sandstone can also be found at lower positions (colluvial material). This iron sandstone is claimed to contribute to the unique character of this wine growing region. According to the soil map of Belgium (scale 1:20,000), the soils are characterized by variable depth, texture, internal drainage and profile development. As such, the 23 vineyards in Heuvelland are found on 21 different soil types; of which 12 different soil types are included within our sampling strategy. Our sampling furthermore revealed an even greater variability in physico-chemical soil properties than reflected by the soil map. This leads to a 'tentative' conclusion that Heuvelland cannot be considered as one natural terroir as such and that the wine growers can potentially improve their production by adapting their management to local soil properties using the improved knowledge on the vineyard soils.

High Temporal and Spatial Variability of Atmospheric-Methane Oxidation in Alpine Glacier Forefield Soils

PubMed Central

Chiri, Eleonora; Nauer, Philipp A.; Rainer, Edda-Marie; Zeyer, Josef

2017-01-01

ABSTRACT Glacier forefield soils can provide a substantial sink for atmospheric CH4, facilitated by aerobic methane-oxidizing bacteria (MOB). However, MOB activity, abundance, and community structure may be affected by soil age, MOB location in different forefield landforms, and temporal fluctuations in soil physical parameters. We assessed the spatial and temporal variability of atmospheric-CH4 oxidation in an Alpine glacier forefield during the snow-free season of 2013. We quantified CH4 flux in soils of increasing age and in different landforms (sandhill, terrace, and floodplain forms) by using soil gas profile and static flux chamber methods. To determine MOB abundance and community structure, we employed pmoA gene-based quantitative PCR and targeted amplicon sequencing. Uptake of CH4 increased in magnitude and decreased in variability with increasing soil age. Sandhill soils exhibited CH4 uptake rates ranging from −3.7 to −0.03 mg CH4 m−2 day−1. Floodplain and terrace soils exhibited lower uptake rates and even intermittent CH4 emissions. Linear mixed-effects models indicated that soil age and landform were the dominating factors shaping CH4 flux, followed by cumulative rainfall (weighted sum ≤4 days prior to sampling). Of 31 MOB operational taxonomic units retrieved, ∼30% were potentially novel, and ∼50% were affiliated with upland soil clusters gamma and alpha. The MOB community structures in floodplain and terrace soils were nearly identical but differed significantly from the highly variable sandhill soil communities. We concluded that soil age and landform modulate the soil CH4 sink strength in glacier forefields and that recent rainfall affects its short-term variability. This should be taken into account when including this environment in future CH4 inventories. IMPORTANCE Oxidation of methane (CH4) in well-drained, “upland” soils is an important mechanism for the removal of this potent greenhouse gas from the atmosphere. It is largely mediated by aerobic, methane-oxidizing bacteria (MOB). Whereas there is abundant information on atmospheric-CH4 oxidation in mature upland soils, little is known about this important function in young, developing soils, such as those found in glacier forefields, where new sediments are continuously exposed to the atmosphere as a result of glacial retreat. In this field-based study, we investigated the spatial and temporal variability of atmospheric-CH4 oxidation and associated MOB communities in Alpine glacier forefield soils, aiming at better understanding the factors that shape the sink for atmospheric CH4 in this young soil ecosystem. This study contributes to the knowledge on the dynamics of atmospheric-CH4 oxidation in developing upland soils and represents a further step toward the inclusion of Alpine glacier forefield soils in global CH4 inventories. PMID:28687652

High temporal and spatial variability of atmospheric-methane oxidation in Alpine glacier-forefield soils.

PubMed

Chiri, Eleonora; Nauer, Philipp A; Rainer, Edda-Marie; Zeyer, Josef; Schroth, Martin H

2017-07-07

Glacier-forefield soils can provide a substantial sink for atmospheric CH 4 , facilitated by aerobic methane-oxidizing bacteria (MOB). However, MOB activity, abundance, and community structure may be affected by soil age, location in different forefield landforms, and temporal fluctuations in soil-physical parameters. We assessed spatial and temporal variability of atmospheric CH 4 oxidation in an Alpine glacier forefield during the snow-free season 2013. We quantified CH 4 flux in soils of increasing age and in different landforms (sandhill, terrace, floodplain) using soil-gas-profile and static flux-chamber methods. To determine MOB abundance and community structure, we employed pmoA -gene-based quantitative PCR and targeted-amplicon sequencing. Uptake of CH 4 increased in magnitude and decreased in variability with increasing soil age. Sandhill soils exhibited CH 4 uptake ranging from -0.03- -3.7 mg CH 4 m -2 d -1 Floodplain and terrace soils exhibited smaller uptake and even intermittent CH 4 emissions. Linear mixed-effect models indicated that soil age and landform were dominating factors shaping CH 4 flux, followed by cumulative rainfall (weighted sum ≤ 4 d prior to sampling). Of 31 MOB operational taxonomic units retrieved, ∼30% were potentially novel, and ∼50% were affiliated with Upland Soil Clusters gamma and alpha. The MOB community structures in floodplain and terrace soils were nearly identical, but differed significantly from highly variable sandhill-soil communities. We conclude that soil age and landform modulate the soil CH 4 sink strength in glacier forefields, and recent rainfall affects its short-term variability. This should be taken into account when including this environment in future CH 4 inventories. Importance Oxidation of methane (CH 4 ) in well-drained, "upland" soils is an important mechanism for the removal of this potent greenhouse gas from the atmosphere. It is largely mediated by aerobic, methane-oxidizing bacteria (MOB). Whereas there is abundant information on atmospheric CH 4 oxidation in mature upland soils, little is known about this important function in young, developing soils such as those found in glacier forefields, where new sediments are continuously exposed to the atmosphere as a result of glacial retreat.In this field-based study we investigated spatial and temporal variability of atmospheric CH 4 oxidation and associated MOB communities in Alpine glacier-forefield soils, aiming at better understanding factors that shape the sink for atmospheric CH 4 in this young soil ecosystem. The study contributes to the knowledge on the dynamics of atmospheric CH 4 oxidation in developing upland soils, and represents a further step towards the inclusion of Alpine glacier-forefield soils in global CH 4 inventories. Copyright © 2017 American Society for Microbiology.

Assessment of restoration measures efficiency for soil contamination in Mediterranean Ecosystem. The case study of Guadiamar Green Corridor in the context of RECARE project

NASA Astrophysics Data System (ADS)

Anaya-Romero, Maria; José Blanco-Velázquez, Francisco; Muñoz-Vallés, Sara

2017-04-01

Restoration of soil ecosystems contaminated by heavy metals requires their characterization and the assessment of measures for risk reduction. Particular soil traits and history define different levels of resilience, so soil contamination assessment needs to take into account a site-by-site approach, which considers both the particular environmental characteristics of soils and the human activities. Nevertheless, current approaches for soil contamination assessment developed as academy and market solutions continue to be rather qualitative, and they do not allow as far the selection of efficient remediation measures to solve soil contamination at the long-term and extensively over larger áreas. In this context, under the framework of RECARE (Preventing and Remediating degradation of Soils in Europe through Land Care) project, we are designing a Decision Support System (DSS) which automatically assess soil contamination values by heavy metals in the topsoil and evaluate the efficiency of soil remediation measures under scenarios of climate and land-use change. The DSS works by simulating the spatio-temporal efficiency of three widely applied remediation measures (compost, sugar beet lime and iron-rich clayey materials). Input variables are divided into: (I) climate variables (mainly precipitation and temperature), (II) site variables (elevation, slope and erodibility), (III) soil (heavy metal content, pH, sand/clay content, soil organic carbon and bulk density), (IV) land use and (V) remediation measures. The predictor variables are related to soil functions expressed by % of change of heavy metal content (Currently the DSS consider cadmium dynamics due to the worldwide distribution in agricultural system and toxicity impact on health and plants), soil carbon and erosion dynamics. The pilot study area is the Guadiamar valley (SW Spain) where the main threat is soil contamination, after a mine spill occurred on April 1998. Since that time, a huge soil databse of more than 30 Gbytes, has been produced by different stakeholders (administration, scientist and private sector), which covered the spatial-temporal evolution of soil contamination by specific soil remediation measures, so the affected area has become the "virtual lab" to develop and test the DSS. Further development of the DSS tool includes its validation/calibration in other European climate zones, such as Copsa Mica in Romania, and the inclusion of new input and output variables to improve the accurancy of results.

Temporal variability of soil water repellency in field conditions under humid Mediterranean climate (South of Spain)

NASA Astrophysics Data System (ADS)

Martinez-Murillo, Juan F.; Gabarron-Galeote, Miguel A.; Ruiz-Sinoga, Jose D.

2013-04-01

Soil water repellency (SWR) has become an important field of scientific study because of its effects on soil hydrological behavior, including reduced matrix infiltration, development of fingered flow in structural or textural preferential flow paths, irregular wetting fronts, and increased runoff generation and soil erosion. The aim of this study is to evaluate the temporal variability of SWR in Mediterranean rangeland under humid Mediterranean climatic conditions (Tª=14.5 °C; P=1,010 mm y-1) in South of Spain. Every month from September 2008 to May 2009 (rainy season), soil moisture and SWR was measured in field conditions by means of gravimetric method and Water Drop Penetration Test, respectively. The entire tests were performed in differente eco-geomorphological conditions in the experimental site: North and South aspect hillslopes and beneath shrub and bare soil in every of them. The results indicate that: i) climatic conditions seem to be more transcendent than the vegetal cover for explaining the temporal variability of SWR in field conditions; ii) thus, SWR appears to be controlled by the antecedent rainfall and soil moisture; iii) more severity SWR were observed in patches characterized by sandier soils and/or greater organic matter contents; and iv) the factor 'hillslope aspect' was not found very influential in the degree of SWR.

Regional investigations of soil and overburden analysis and plant uptake of metals

USGS Publications Warehouse

Gough, L.P.

1984-01-01

Regional studies on the bioavailability of metals at native and disturbed sites were conducted over the past seven years by the USGS. The work was concentrated in the Fort Union, Powder River, and Green River coal resource regions where measures of extractable metals in soils were found to have limited use in predicting metal levels in plants. Correlations between Cu, Fe, and Zn in plants and extractable (DTPA, EDTA, and oxalate) or total levels in native A- and C-horizons of soil were occasionally significant. A simple linear model is generally not adequate, however, in estimating element uptake by plants. Prediction capabilities were improved when a number of soil chemical and physical parameters were included as independent variables in a stepwise linear multiple regression analysis; however, never more than 54% of the total variability in the data was explained by the equations for these metals. Soil pH was the most important variable relating soil chemistry to plant chemistry. This relation was always positive and apparently a response to soil levels of metal carbonates and not Fe and Mn oxides. Studies that compared the metal uptake by rehabilitation species to extractable (DTPA) metal levels in mice soils produced similar results. ?? 1984 Science and Technology Letters.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

Linking annual N2O emission in organic soils to mineral nitrogen input as estimated by heterotrophic respiration and soil C/N ratio.

PubMed

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted.

Discerning environmental factors affecting current tree growth in Central Europe.

PubMed

Cienciala, Emil; Russ, Radek; Šantrůčková, Hana; Altman, Jan; Kopáček, Jiří; Hůnová, Iva; Štěpánek, Petr; Oulehle, Filip; Tumajer, Jan; Ståhl, Göran

2016-12-15

We examined the effect of individual environmental factors on the current spruce tree growth assessed from a repeated country-level statistical landscape (incl. forest) survey in the Czech Republic. An extensive set of variables related to tree size, competition, site characteristics including soil texture, chemistry, N deposition and climate was tested within a random-effect model to explain growth in the conditions of dominantly managed forest ecosystems. The current spruce basal area increment was assessed from two consecutive landscape surveys conducted in 2008/2009 and six years later in 2014/2015. Tree size, age and competition within forest stands were found to be the dominant explanatory variables, whereas the expression of site characteristics, environmental and climatic drives was weaker. The significant site variables affecting growth included soil C/N ratio and soil exchangeable acidity (pH KCl; positive response) reflecting soil chemistry, long-term N-deposition (averaged since 1975) in combination with soil texture (clay content) and Standardized Precipitation Index (SPI), a drought index expressing moisture conditions. Sensitivity of growth to N-deposition was positive, although weak. SPI was positively related to and significant in explaining tree growth when expressed for the growth season. Except SPI, no significant relation of growth was determined to altitude-related variables (temperature, growth season length). We identified the current spruce growth optimum at elevations about 800ma.s.l. or higher in the conditions of the country. This suggests that at lower elevations, limitation by a more pronounced water deficit dominates, whereas direct temperature limitation may concern the less frequent higher elevations. The mixed linear model of spruce tree growth explained 55 and 65% of the variability with fixed and random effects included, respectively, and provided new insights on the current spruce tree growth and factors affecting it within the environmental gradients of the country. Copyright © 2016 Elsevier B.V. All rights reserved.

Climate Controls AM Fungal Distributions from Global to Local Scales

NASA Astrophysics Data System (ADS)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.

Time Series Analysis of Photovoltaic Soiling Station Data: Version 1.0, August 2017

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micheli, Leonardo; Muller, Matthew T.; Deceglie, Michael G.

The time series data from PV soiling stations, operating in the USA, at different time periods are analyzed and presented. The current version of the paper includes twenty stations operating between 2013 and 2016, but the paper is intended to be periodically updated as more stations and more data become available. The challenges in working with soiling stations data are discussed, including measurement methodology, quality controls, and measurement uncertainty. The soiling profiles of the soiling stations are made available so that the PV community can make use of this data to guide operations and maintence decisions, estimate soiling derate inmore » performance models, and more generally come to a better understanding of the challenges associated with the variability of PV soiling.« less

Alteration of natural (37)Ar activity concentration in the subsurface by gas transport and water infiltration.

PubMed

Guillon, Sophie; Sun, Yunwei; Purtschert, Roland; Raghoo, Lauren; Pili, Eric; Carrigan, Charles R

2016-05-01

High (37)Ar activity concentration in soil gas is proposed as a key evidence for the detection of underground nuclear explosion by the Comprehensive Nuclear Test-Ban Treaty. However, such a detection is challenged by the natural background of (37)Ar in the subsurface, mainly due to Ca activation by cosmic rays. A better understanding and improved capability to predict (37)Ar activity concentration in the subsurface and its spatial and temporal variability is thus required. A numerical model integrating (37)Ar production and transport in the subsurface is developed, including variable soil water content and water infiltration at the surface. A parameterized equation for (37)Ar production in the first 15 m below the surface is studied, taking into account the major production reactions and the moderation effect of soil water content. Using sensitivity analysis and uncertainty quantification, a realistic and comprehensive probability distribution of natural (37)Ar activity concentrations in soil gas is proposed, including the effects of water infiltration. Site location and soil composition are identified as the parameters allowing for a most effective reduction of the possible range of (37)Ar activity concentrations. The influence of soil water content on (37)Ar production is shown to be negligible to first order, while (37)Ar activity concentration in soil gas and its temporal variability appear to be strongly influenced by transient water infiltration events. These results will be used as a basis for practical CTBTO concepts of operation during an OSI. Copyright © 2016 Elsevier Ltd. All rights reserved.

Linking Annual N2O Emission in Organic Soils to Mineral Nitrogen Input as Estimated by Heterotrophic Respiration and Soil C/N Ratio

PubMed Central

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted. PMID:24798347

[Evaluation of soil heavy metals accumulation in the fast economy development region].

PubMed

Zhong, Xian-Lan; Zhou, Sheng-Lu; Li, Jiang-Tao; Zhao, Qi-Guo

2010-06-01

Evaluation of soil heavy metals accumulation was studied in Kunshan City, a typical region of the fast economy development region in China. 126 soil samples were collected and analyzed, and evaluation indexes of soil heavy metal accumulation, which including total concentration of soil heavy metal index (THMI), soil available heavy metal index (AHMI) and fractionation of soil heavy metal index (FHMI), were established, and the heavy metal accumulation conditions of soil in this region were also discussed. Results showed as follows: the spatial variability of THMI was relative lower, with a mean value of 42.57%, whereas strong variability was found in AHMI and FHMI (especially active fraction of soil heavy metals), with the average value of 82.75% and 77.83%, respectively. Judging by each index reference standard of C Horizon, THMI was low-grade with a mean value of 1.01, while the AHMI and FHMI reached to medium accumulation and serious accumulation, with the average values of 2.46 and 4.32, respectively. The synthetic accumulation index of soil heavy metals (SHMI) was 2.56, reaching to medium grade level and with strong variability. 21.54% land area was in low-grade accumulation and 54.70% land area was in medium grade accumulation, while 23.76% land area was in serious accumulation under SHMI evaluation system. All the accumulation evaluation indexes in livestock breeding zone were the lowest, while the indexes in the smelting and plating zone were the highest, but the indexes difference between two zones were unobvious. There were markedly differences in soil types, which the accumulation indexes in Wushan soil were significantly higher than those in Huangni soil and Qingni soil.

Water vapour fluxes trends on different time scales and their relationship with weather and soil drivers: a case study from a dehesa site in South Spain

NASA Astrophysics Data System (ADS)

Polo, María José; Egüen, Marta; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; Patrocinio González-Dugo, María

2017-04-01

Water vapour fluxes between the soil surface and the atmosphere constitute one of the most important components of the water cycle in the continental areas. Their regime directly affect the availability of water to plants, water storage in surface bodies, air humidity in the boundary layer, snow persistence… among others, and the list of indirectly affected processes comprises a large number of components. Water potential or wetness gradients are some of the main drivers of water vapour fluxes to the atmosphere; soil humidity is usually monitored as key variable in many hydrological and environmental studies, and its estimated series are used to calibrate and validate the modelling of certain hydrological processes. However, such results may differ when water fluxes are used instead of water state variables, such as humidity. This work shows the analysis of high resolution water vapour fluxes series from a dehesa area in South Spain where a complete energy and water fluxes/variables monitoring site has been operating for the last four years. The results include pasture and tree vegetated control points. The daily water budget calculation on both types of sites has been performed from weather and energy fluxes measurements, and soil moisture measurements, and the results have been aggregated on a weekly, monthly and seasonal basis. Comparison between observed trends of soil moisture and calculated trends of water vapour fluxes is included to show the differences arising in terms of the regime of the dominant weather variables in this type of ecosystems. The results identify significant thresholds for each weather variable driver and highlight the importance of the wind regime, which is the somehow forgotten variable in future climate impacts on hydrology. Further work is being carried out to assess water cycle potential trends under future climate conditions and their impacts on the vegetation in dehesa ecosystems.

Predicting the particle size distribution of eroded sediment using artificial neural networks.

PubMed

Lagos-Avid, María Paz; Bonilla, Carlos A

2017-03-01

Water erosion causes soil degradation and nonpoint pollution. Pollutants are primarily transported on the surfaces of fine soil and sediment particles. Several soil loss models and empirical equations have been developed for the size distribution estimation of the sediment leaving the field, including the physically-based models and empirical equations. Usually, physically-based models require a large amount of data, sometimes exceeding the amount of available data in the modeled area. Conversely, empirical equations do not always predict the sediment composition associated with individual events and may require data that are not always available. Therefore, the objective of this study was to develop a model to predict the particle size distribution (PSD) of eroded soil. A total of 41 erosion events from 21 soils were used. These data were compiled from previous studies. Correlation and multiple regression analyses were used to identify the main variables controlling sediment PSD. These variables were the particle size distribution in the soil matrix, the antecedent soil moisture condition, soil erodibility, and hillslope geometry. With these variables, an artificial neural network was calibrated using data from 29 events (r 2 =0.98, 0.97, and 0.86; for sand, silt, and clay in the sediment, respectively) and then validated and tested on 12 events (r 2 =0.74, 0.85, and 0.75; for sand, silt, and clay in the sediment, respectively). The artificial neural network was compared with three empirical models. The network presented better performance in predicting sediment PSD and differentiating rain-runoff events in the same soil. In addition to the quality of the particle distribution estimates, this model requires a small number of easily obtained variables, providing a convenient routine for predicting PSD in eroded sediment in other pollutant transport models. Copyright © 2017 Elsevier B.V. All rights reserved.

Environmental forcing does not induce diel or synoptic variation in the carbon isotope content of forest soil respiration

DOE PAGES

Bowling, D. R.; Egan, J. E.; Hall, S. J.; ...

2015-08-31

Recent studies have examined temporal fluctuations in the amount and carbon isotope content (δ 13C) of CO 2 produced by the respiration of roots and soil organisms. These changes have been correlated with diel cycles of environmental forcing (e.g., sunlight and soil temperature) and with synoptic-scale atmospheric motion (e.g., rain events and pressure-induced ventilation). We used an extensive suite of measurements to examine soil respiration over 2 months in a subalpine forest in Colorado, USA (the Niwot Ridge AmeriFlux forest). Observations included automated measurements of CO 2 and δ 13C of CO 2 in the soil efflux, the soil gasmore » profile, and forest air. There was strong diel variability in soil efflux but no diel change in the δ 13C of the soil efflux (δ R) or the CO 2 produced by biological activity in the soil (δ J). Following rain, soil efflux increased significantly, but δ R and δ J did not change. Temporal variation in the δ 13C of the soil efflux was unrelated to measured environmental variables, and we failed to find an explanation for this unexpected result. Measurements of the δ 13C of the soil efflux with chambers agreed closely with independent observations of the isotopic composition of soil CO 2 production derived from soil gas well measurements. Deeper in the soil profile and at the soil surface, results confirmed established theory regarding diffusive soil gas transport and isotopic fractionation. Deviation from best-fit diffusion model results at the shallower depths illuminated a pump-induced ventilation artifact that should be anticipated and avoided in future studies. There was no evidence of natural pressure-induced ventilation of the deep soil. However, higher variability in δ 13C of the soil efflux relative to δ 13C of production derived from soil profile measurements was likely caused by transient pressure-induced transport with small horizontal length scales.« less

Temporary vs. Permanent Sub-slab Ports: A Comparative ...

EPA Pesticide Factsheets

Vapor intrusion (VI) is the migration of subsurface vapors, including radon and volatile organic compounds (VOCs), from the subsurface to indoor air. The VI exposure pathway extends from the contaminant source, which can be impacted soil, non-aqueous phase liquid, or contaminated groundwater, to indoor air-exposure points. Therefore, contaminated matrices may include groundwater, soil, soil gas, and indoor air. VOC contaminants of concern typically include halogenated solvents such as trichloroethene, tetrachloroethene, and chloroform, as well as petroleum hydrocarbons, such as the aromatic VOCs benzene, toluene, and xylenes. Radon is a colorless radioactive gas that is released by radioactive decay of radionuclides in rock and soil that migrate into homes through VI in a similar fashion to VOCs. This project focused on the performance of permanent versus temporary sub-slab sampling ports for the determination of VI of halogenated VOCs and radon into an unoccupied house. VOC and radon concentrations measured simultaneously in soil gas using collocated temporary and permanent ports appeared to be independent of the type of port. The variability between collocated temporary and permanent ports was much less than the spatial variability between different locations within a single residential duplex. The agreement of the majority of VOC and radon concentrations, 0–36% relative percent difference, and 2–19% relative standard deviation respectively, of each sub-sl

Structure, functions and interguild relationships of the soil nematode assemblage in organic vegetable production

USDA-ARS?s Scientific Manuscript database

The abundance and metabolic footprints of soil nematodes were quantified during four of eight years of an intensive organic vegetable production system. Treatment variables included cover crop mixtures and frequency, and compost application rates. The abundances of bacterivore and fungivore nematode...

An evaluation of soil chemistry in human cadaver decomposition islands: Potential for estimating postmortem interval (PMI).

PubMed

Fancher, J P; Aitkenhead-Peterson, J A; Farris, T; Mix, K; Schwab, A P; Wescott, D J; Hamilton, M D

2017-10-01

Soil samples from the Forensic Anthropology Research Facility (FARF) at Texas State University, San Marcos, TX, were analyzed for multiple soil characteristics from cadaver decomposition islands to a depth of 5centimeters (cm) from 63 human decomposition sites, as well as depths up to 15cm in a subset of 11 of the cadaver decomposition islands plus control soils. Postmortem interval (PMI) of the cadaver decomposition islands ranged from 6 to 1752 days. Some soil chemistry, including nitrate-N (NO 3 -N), ammonium-N (NH 4 -N), and dissolved inorganic carbon (DIC), peaked at early PMI values and their concentrations at 0-5cm returned to near control values over time likely due to translocation down the soil profile. Other soil chemistry, including dissolved organic carbon (DOC), dissolved organic nitrogen (DON), orthophosphate-P (PO 4 -P), sodium (Na + ), and potassium (K + ), remained higher than the control soil up to a PMI of 1752days postmortem. The body mass index (BMI) of the cadaver appeared to have some effect on the cadaver decomposition island chemistry. To estimate PMI using soil chemistry, backward, stepwise multiple regression analysis was used with PMI as the dependent variable and soil chemistry, body mass index (BMI) and physical soil characteristics such as saturated hydraulic conductivity as independent variables. Measures of soil parameters derived from predator and microbial mediated decomposition of human remains shows promise in estimating PMI to within 365days for a period up to nearly five years. This persistent change in soil chemistry extends the ability to estimate PMI beyond the traditionally utilized methods of entomology and taphonomy in support of medical-legal investigations, humanitarian recovery efforts, and criminal and civil cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Theoretical Relationships between Luminescence and Hillslope Soil Vertical Diffusivity: a Numerical Modeling Approach

NASA Astrophysics Data System (ADS)

Gray, H. J.; Tucker, G. E.; Mahan, S.

2017-12-01

Luminescence is a property of matter that can be used to obtain depositional ages from fine sand. Luminescence generates due to exposure to background ionizing radiation and is removed by sunlight exposure in a process known as bleaching. There is evidence to suggest that luminescence can also serve as a sediment tracer in fluvial and hillslope environments. For hillslope environments, it has been suggested that the magnitude of luminescence as a function of soil depth is related to the strength of soil mixing. Hillslope soils with a greater extent of mixing will have previously surficial sand grains moved to greater depths in a soil column. These previously surface-exposed grains will contain a lower luminescence than those which have never seen the surface. To attempt to connect luminescence profiles with soil mixing rate, here defined as the soil vertical diffusivity, I conduct numerical modelling of particles in hillslope soils coupled with equations describing the physics of luminescence. I use recently published equations describing the trajectories of particles under both exponential and uniform soil velocity soils profiles and modify them to include soil diffusivity. Results from the model demonstrates a strong connection between soil diffusivity and luminescence. Both the depth profiles of luminescence and the total percent of surface exposed grains will change drastically based on the magnitude of the diffusivity. This suggests that luminescence could potentially be used to infer the magnitude of soil diffusivity. However, I test other variables such as the soil production rate, e-folding length of soil velocity, background dose rate, and soil thickness, and I find these other variables can also affect the relationship between luminescence and diffusivity. This suggests that these other variables may need to be constrained prior to any inferences of soil diffusivity from luminescence measurements. Further field testing of the model in areas where the soil vertical diffusivity and other parameters are independently known will provide a test of this potential new method.

Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

PubMed Central

Dechesne, Arnaud; Badawi, Nora; Aamand, Jens; Smets, Barth F.

2014-01-01

Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays non-random spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modeling and experimental systems that do not include soil's full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil. PMID:25538691

Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

NASA Technical Reports Server (NTRS)

Brunet, Y.; Vauclin, M.

1985-01-01

The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

[Soil and forest structure in the Colombian Amazon].

PubMed

Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon

2011-09-01

Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.

Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

NASA Astrophysics Data System (ADS)

Mahanama, S. P.; Koster, R. D.; Liu, P.

2006-05-01

Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

EVALUATING THE ROLE OF HABITAT QUALITY ON ESTABLISHMENT OF GM AGROSTIS STOLONIFERA PLANTS IN NON-AGRONOMIC SETTINGS

EPA Science Inventory

We compared soil chemistry and plant community data at non-agronomic mesic locations that either did or did not contain genetically modified (GM) Agrostis stolonifera. The best two-variable logistic regression model included soil Mn content and A. stolonifera cover and explained...

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: STATSGO Soil Characteristics

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents estimated soil variables compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The variables included are cation exchange capacity, percent calcium carbonate, slope, water-table depth, soil thickness, hydrologic soil group, soil erodibility (k-factor), permeability, average water capacity, bulk density, percent organic material, percent clay, percent sand, and percent silt. The source data set is the State Soil ( STATSGO ) Geographic Database (Wolock, 1997). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

NASA Astrophysics Data System (ADS)

Ibrahim, Hesham M.; Huggins, David R.

2011-07-01

SummarySpatio-temporal patterns of soil water are major determinants of crop yield potential in dryland agriculture and can serve as the basis for delineating precision management zones. Soil water patterns can vary significantly due to differences in seasonal precipitation, soil properties and topographic features. In this study we used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water at the Washington State University Cook Agronomy Farm (CAF) near Pullman, WA. During the period 1999-2006, the CAF was divided into three roughly equal blocks (A, B, and C), and soil water at 0.3 m intervals to a depth of 1.5 m measured gravimetrically at approximately one third of the 369 geo-referenced points on the 37-ha watershed. These data were combined with terrain attributes, soil bulk density and apparent soil conductivity (EC a). The first EOF generated from the three blocks explained 73-76% of the soil water variability. Field patterns of soil water based on EOF interpolation varied between wet and dry conditions during spring and fall seasons. Under wet conditions, elevation and wetness index were the dominant factors regulating the spatial patterns of soil water. As soil dries out during summer and fall, soil properties (EC a and bulk density) become more important in explaining the spatial patterns of soil water. The EOFs generated from block B, which represents average topographic and soil properties, provided better estimates of soil water over the entire watershed with larger Nash-Sutcliffe Coefficient of Efficiency (NSCE) values, especially when the first two EOFs were retained. Including more than the first two EOFs did not significantly increase the NSCE of soil water estimate. The EOF interpolation method to estimate soil water variability worked slightly better during spring than during fall, with average NSCE values of 0.23 and 0.20, respectively. The predictable patterns of stored soil water in the spring could serve as the basis for delineating precision management zones as yield potential is largely driven by water availability. The EOF-based method has the advantage of estimating the soil water variability based on soil water data from several measurement times, whereas in regression methods only soil water measurement at a single time are used. The EOF-based method can also be used to estimate soil water at any time other than measurement times, assuming the average soil water of the watershed is known at that time.

Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.

2015-01-01

The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes.

Seasonality of semi-arid and savanna-type ecosystems in an Earth system model

NASA Astrophysics Data System (ADS)

Dahlin, K.; Swenson, S. C.; Lombardozzi, D.; Kamoske, A.

2016-12-01

Recent work has identified semi-arid and savanna-type (SAST) ecosystems as a critical component of interannual variability in the Earth system (Poulter et al. 2014, Ahlström et al. 2015), yet our understanding of the spatial and temporal patterns present in these systems remains limited. There are three major factors that contribute to the complex behavior of SAST ecosystems, globally. First is leaf phenology, the timing of the appearance, presence, and senescence of plant leaves. Plants grow and drop their leaves in response to a variety of cues, including soil moisture, rainfall, day length, and relative humidity, and alternative phenological strategies might often co-exist in the same location. The second major factor in savannas is soil moisture. The complex nature of soil behavior under extremely dry, then extremely wet conditions is critical to our understanding of how savannas function. The third factor is fire. Globally, virtually all savanna-type ecosystems operate with some non-zero fire return interval. Here we compare model output from the Community Land Model (CLM5-BGC) in SAST regions to remotely sensed data on these three variables - phenology (MODIS LAI), soil moisture (SMAP), and fire (GFED4) - assessing both annual spatial patterns and intra-annual variability, which is critical in these highly variable systems. We present new SAST-specific first- and second-order benchmarks, including numbers of annual LAI peaks (often >1 in SAST systems) and correlations between soil moisture, LAI, and fire. Developing a better understanding of how plants respond to seasonal patterns is a critical first step in understanding how SAST ecosystems will respond to and influence climate under future scenarios.

The influence of land-use and land-management on Soil Organic Carbon concentrations: Limitations of making predictions using only soil order data

NASA Astrophysics Data System (ADS)

Bell, M. J.; Worrall, F.

2009-04-01

In light of recent concern over the extent of global warming and the role of soil carbon as a potential store of atmospheric carbon, there is increasing demand for regions to estimate their current soil organic carbon (SOC) stocks with the greatest possible accuracy. Several previous attempts at calculating SOC baselines at global, national or regional scale have used mean values for soil orders and multiplied these values by the mapped areas of the soils they represent. Other methods have approached the task from a land cover point of view, making estimates using only land-use, or soil order/land-use combinations and others have included variables such as altitude, climate and soil texture. This study aimed to assess the major controls on SOC concentrations (%SOC) at the National Trust Wallington estate in Northumberland, NE England (area = 55km2) where an extensive soil sampling campaign was used to test what level of accuracy could be achieved in modelling the %SOC values on the Estate. Mapped %SOC values were compared to the values predicted from The National Soils Resources Institute (NSRI) representative soil profile data for major soil group, soil series and land-use corrected soil series values, as well as land-use/major soil group combinations from the Countryside Survey database. The results of this study can be summarised as follows: When only soil series or land-use were used as predictors only 48% and 44% of the variation in the dataset were explained. When soil series/land-use combinations were used explanatory power increased to 57% both altitude and soil pH are major controls on %SOC and including these variables gave an improvement to 59% A further improvement from 59% to 66% in the ability to predict %SOC levels at point locations when farm tenancy was included indicates that differences in land-management practices between farm tenancies explained more of the variation than either soil series or land-use in %SOC. Further work will involve a verification site in another area of the UK where the results of this sampling campaign will be used to confirm the greater predictive value of using land-use and management information in combination with soil series in correctly identifying %SOC at specific locations.

Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere.

PubMed

Loizeau, Vincent; Ciffroy, Philippe; Roustan, Yelva; Musson-Genon, Luc

2014-09-15

Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport-deposition-reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the 'reemission' output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty. Copyright © 2014 Elsevier B.V. All rights reserved.

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

Geophysics and Nanosciences: Nano to Micro to Meso to Macro Scale Swelling Soils

NASA Astrophysics Data System (ADS)

Cushman, J.

2003-04-01

We use statistical mechanical simulations of nanoporous materials to motivate a choice of independent constitutive variables for a multiscale mixture theory of swelling soils. A video will illustrate the structural behavior of fluids in nanopores when they are adsorbed from a bulk phase vapor to form capillaries on the nanoscale. These simulations suggest that when a swelling soil is very dry, the full strain tensor for the liquid phase should be included in the list of independent variables in any mixture theory. We use this information to develop a three-scale (micro, meso, macro) mixture theory for swelling soils. For a simplified case, we present the underlying multiscale field equations and constitutive theory, solve the resultant well posed system numerically, and present some graphical results for a drying and shrinking body.

Soil Erodibility Parameters Under Various Cropping Systems of Maize

NASA Astrophysics Data System (ADS)

van Dijk, P. M.; van der Zijp, M.; Kwaad, F. J. P. M.

1996-08-01

For four years, runoff and soil loss from seven cropping systems of fodder maize have been measured on experimental plots under natural and simulated rainfall. Besides runoff and soil loss, several variables have also been measured, including rainfall kinetic energy, degree of slaking, surface roughness, aggregate stability, soil moisture content, crop cover, shear strength and topsoil porosity. These variables explain a large part of the variance in measured runoff, soil loss and splash erosion under the various cropping systems. The following conclusions were drawn from the erosion measurements on the experimental plots (these conclusions apply to the spatial level at which the measurements were carried out). (1) Soil tillage after maize harvest strongly reduced surface runoff and soil loss during the winter; sowing of winter rye further reduced winter erosion, though the difference with a merely tilled soil is small. (2) During spring and the growing season, soil loss is reduced strongly if the soil surface is partly covered by plant residues; the presence of plant residue on the surface appeared to be essential in achieving erosion reduction in summer. (3) Soil loss reductions were much higher than runoff reductions; significant runoff reduction is only achieved by the straw system having flat-lying, non-fixed plant residue on the soil surface; the other systems, though effective in reducing soil loss, were not effective in reducing runoff.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Oribatid mites in soil toxicity testing-the use of Oppia nitens (C.L. Koch) as a new test species.

PubMed

Princz, Juliska I; Behan-Pelletier, Valerie M; Scroggins, Richard P; Siciliano, Steven D

2010-04-01

Few soil invertebrate species are available for the toxic assessment of soils from boreal or other northern ecozones, yet these soils cover the majority of Canada's landmass as well as significant portions of Eurasia. Oppia nitens (C.L. Koch) is an herbivorous and fungivorous oribatid mite found in soil throughout Holarctic regions, including Canada. Soil tests using O. nitens were performed using 15 different forest soil types and horizons to investigate test variability in adult survival and reproduction. Adult survival (86.1 +/- 1.1%) was consistent across soil types, with a coefficient of variation (CV) of 15%. However, reproduction varied significantly, ranging from 2.9 (+/-1.1) to 86.2 (+/-11.7) individuals, with a corresponding CV of 118 and 30%, respectively. Of the soil factors assessed (NH(3), NO(3), pH, phosphorus [P], organic matter content (OM), carbon:nitrogen (C:N), sand, silt, clay, and sodium adsorption ratio), soil organic matter (OM) explained 68% of the variation observed for reproduction. Increasing the OM using Sphagnum sp. peat moss resulted in optimal reproduction at 7% OM (8% peat content) with the lowest variability (CV of 20%). When assessing the toxicity of a reference chemical, boric acid, the effect of peat amendment reduced lethality to adults with no observable difference on reproduction. The use an age-synchronized culture reduced the test variability for reproduction relative to the use of unsynchronized cultures. Oppia nitens is a good candidate species for a standardized test design, with adult survival easily assessed in a relatively simple design. A long-term reproduction test with O. nitens will require the use of a synchronized population and, on occasion, OM amendment when testing soils with low organic matter content. (c) 2009 SETAC.

Spectral-agronomic relationships of corn, soybean and wheat canopies

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Daughtry, C. S. T.; Vanderbilt, V. C.

1981-01-01

During the past six years several thousand reflectance spectra of corn, soybean, and wheat canopies were acquired and analyzed. The relationships of biophysical variables, including leaf area index, percent soil cover, chlorophyll and water content, to the visible and infrared reflectance of canopies are described. The effects on reflectance of cultural, environmental, and stress factors such as planting data, seeding rate, row spacing, cultivar, soil type and nitrogen fertilization are also examined. The conclusions are that several key agronomic variables including leaf area index, development stage and degree of stress are strongly related to spectral reflectance and that it should be possible to estimate these descriptions of crop condition from satellite acquired multispectral data.

Quantifying Forest Soil Physical Variables Potentially Important for Site Growth Analyses

Treesearch

John S. Kush; Douglas G. Pitt; Phillip J. Craul; William D. Boyer

2004-01-01

Accurate mean plot values of forest soil factors are required for use as independent variables in site-growth analyses. Adequate accuracy is often difficult to attain because soils are inherently widely variable. Estimates of the variability of appropriate soil factors influencing growth can be used to determine the sampling intensity required to secure accurate mean...

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Working with soils: soil science continuing professional development

NASA Astrophysics Data System (ADS)

Hannam, Jacqueline; Thompson, Dick

2017-04-01

The British Society of Soil Science launched the Working with Soils professional competency programme in 2011. This was in response to concerns from practitioners and professionals of a significant skills gap in various sectors that require soil science skills. The programme includes one and two day courses that cover the qualifications, knowledge and skills required of a professional scientist or engineer conducting a range of contract work. All courses qualify for continuing professional development points with various professional practice schemes. Three courses cover the foundations of soil science namely; describing a soil profile, soil classification and understanding soil variability in the field and landscape. Other tailored courses relate to specific skills required from consultants particularly in the planning process where land is assessed for agricultural quality (agricultural land classification). New courses this year include soil handling and restoration that provides practitioners with knowledge of the appropriate management of large volumes of soil that are disturbed during development projects. The courses have so far successfully trained over 100 delegates ranging from PhD students, environmental consultants and government policy advisors.

How does agricultural management for soil health in the southern plains impact a suite of soil health indicators?

USDA-ARS?s Scientific Manuscript database

Producers across the Southern Plains are expected to experience a number of impacts on their operations as a result of climate change, including more variable and extreme precipitation events, higher seasonal and annual temperatures, and more prolonged and intense droughts. One possible way of buffe...

Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study

NASA Astrophysics Data System (ADS)

Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.

2015-12-01

The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.

Relation of agronomic and multispectral reflectance characteristics of spring wheat canopies

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Ahlrichs, J. S.

1982-01-01

The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

NASA Technical Reports Server (NTRS)

Eagleson, Peter S.; Jasinski, Michael F.

1988-01-01

This work focuses on the characterization of natural, spatially variable, semivegetated landscapes using a linear, stochastic, canopy-soil reflectance model. A first application of the model was the investigation of the effects of subpixel and regional variability of scenes on the shape and structure of red-infrared scattergrams. Additionally, the model was used to investigate the inverse problem, the estimation of subpixel vegetation cover, given only the scattergrams of simulated satellite scale multispectral scenes. The major aspects of that work, including recent field investigations, are summarized.

Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

NASA Astrophysics Data System (ADS)

Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

2017-04-01

Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description of the variability in soil physical parameters. Agronomic management impact on SOC stocks is important near the soil surface, but is mainly attributable to land-use and not to other management factors on this large regional scale. The importance of historical land-use practices as well as anthropogenic soil transformations to SOC stocks highlights the need for prudent soil management and conservation policies.

Modeling impacts of human footprint and soil variability on the potential distribution of invasive plant species in different biomes

NASA Astrophysics Data System (ADS)

Wan, Ji-Zhong; Wang, Chun-Jing; Yu, Fei-Hai

2017-11-01

Human footprint and soil variability may be important in shaping the spread of invasive plant species (IPS). However, until now, there is little knowledge on how human footprint and soil variability affect the potential distribution of IPS in different biomes. We used Maxent modeling to project the potential distribution of 29 IPS with wide distributions and long introduction histories in China based on various combinations of climatic correlates, soil characteristics and human footprint. Then, we evaluated the relative importance of each type of environmental variables (climate, soil and human footprint) as well as the difference in range and similarity of the potential distribution of IPS between different biomes. Human footprint and soil variables contributed to the prediction of the potential distribution of IPS, and different types of biomes had varying responses and degrees of impacts from the tested variables. Human footprint and soil variability had the highest tendency to increase the potential distribution of IPS in Montane Grasslands and Shrublands. We propose to integrate the assessment in impacts of human footprint and soil variability on the potential distribution of IPS in different biomes into the prevention and control of plant invasion.

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

PubMed

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between Cr and Cd, Cu and Zn in multiple regression; and between Cr and Cd in SVM regression. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of different interpolation methods for spatial distribution of soil organic carbon and some soil properties in the Black Sea backward region of Turkey

NASA Astrophysics Data System (ADS)

Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat

2017-10-01

The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.

Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS)

NASA Astrophysics Data System (ADS)

Liu, H.; Jin, Y.; Devine, S.; Dahlgren, R. A.; Covello, S.; Larsen, R.; O'Geen, A. T.

2017-12-01

California rangelands cover 23 million hectares and support a $3.4 billion annual cattle industry. Rangeland forage production varies appreciably from year-to-year and across short distances on the landscape. Spatially explicit and near real-time information on forage production at a high resolution is critical for effective rangeland management, especially during an era of climatic extremes. We here integrated a multispectral MicaSense RedEdge camera with a 3DR solo quad-copter and acquired time-series images during the 2017 growing season over a topographically complex 10-hectare rangeland in San Luis Obispo County, CA. Soil moisture and temperature sensors were installed at 16 landscape positions, and vegetation clippings were collected at 36 plots to quantify forage dry biomass. We built four centimeter-level models for forage production mapping using time series of sUAS images and ground measurements of forage biomass and soil temperature and moisture. The biophysical model based on Monteith's eco-physiological plant growth theory estimated forage production reasonably well with a coefficient of determination (R2) of 0.86 and a root-mean-square error (RMSE) of 424 kg/ha when the soil parameters were included, and a R2 of 0.79 and a RMSE of 510 kg/ha when only remote sensing and topographical variables were included. We built two empirical models of forage production using a stepwise variable selection technique, one with soil variables. Results showed that cumulative absorbed photosynthetically active radiation (APAR) and elevation were the most important variables in both models, explaining more than 40% of the spatio-temporal variance in forage production. Soil moisture accounted for an additional 29% of the variance. Illumination condition was selected as a proxy for soil moisture in the model without soil variables, and accounted for 18% of the variance. We applied the remote sensing-based models to map daily forage production at 30-cm resolution for the whole study area during the 2017 growing season. The forage maps captured similar seasonal and spatial patterns of forage production as ground measured dry biomass. This study demonstrated a near real-time monitoring tool for ranchers to estimate forage production with sUAS technology and improved watershed-scale rangeland management.

Assessing the Habitat of Coccidioides posadasii, the Valley Fever Pathogen: A Study of Environmental Variables and Human Incidence Data in Arizona

NASA Astrophysics Data System (ADS)

Mann, Sarina N.

Coccidioidomycosis, or Valley Fever, is an infectious disease caused by inhalation of soil-dwelling fungus Coccidioides posadasii spores in the Lower Sonoran Life Zone (LSLZ) in Arizona. In the context of climate change, the habitat of environmentally-mediated infectious diseases, such as Valley Fever, are expected to change. Connections have been drawn between climate and Valley Fever infection. The operational scale of the organism is still unknown. Here, we use climatic variables, including precipitation, soil moisture, and temperature. We use PRISM precipitation and temperature data, and Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) as a measure of soil moisture for the entire state of Arizona, divided into 126 primary care areas (PCA). These data are analyzed and regressed with Valley Fever incidence to determine the effects of climatic variability on disease distribution and timing. This study confirms that Valley Fever occurrence is clustered in the LSLZ. Seasonal Valley Fever outbreak was found to be variable year-to-year based on climatic variability. The inconclusive regression analyses indicate that the operational scale of Coccidioides is smaller than the PCA region. All variables are related to Valley Fever infection, but one variable was not found to hold more predictive power than others.

High spatial variability in biogeochemical rates and microbial communities across Louisiana salt marsh landscapes

NASA Astrophysics Data System (ADS)

Roberts, B. J.; Chelsky, A.; Bernhard, A. E.; Giblin, A. E.

2017-12-01

Salt marshes are important sites for retention and transformation of carbon and nutrients. Much of our current marsh biogeochemistry knowledge is based on sampling at times and in locations that are convenient, most often vegetated marsh platforms during low tide. Wetland loss rates are high in many coastal regions including Louisiana which has the highest loss rates in the US. This loss not only reduces total marsh area but also changes the relative allocation of subhabitats in the remaining marsh. Climate and other anthropogenic changes lead to further changes including inundation patterns, redox conditions, salinity regimes, and shifts in vegetation patterns across marsh landscapes. We present results from a series of studies examining biogeochemical rates, microbial communities, and soil properties along multiple edge to interior transects within Spartina alterniflora across the Louisiana coast; between expanding patches of Avicennia germinans and adjacent S. alterniflora marshes; in soils associated with the four most common Louisiana salt marsh plants species; and across six different marsh subhabitats. Spartina alterniflora marsh biogeochemistry and microbial populations display high spatial variability related to variability in soil properties which appear to be, at least in part, regulated by differences in elevation, hydrology, and redox conditions. Differences in rates between soils associated with different vegetation types were also related to soil properties with S. alterniflora soils often yielding the lowest rates. Biogeochemical process rates vary significantly across marsh subhabitats with individual process rates differing in their hotspot habitat(s) across the marsh. Distinct spatial patterns may influence the roles that marshes play in retaining and transforming nutrients in coastal regions and highlight the importance of incorporating spatial sampling when scaling up plot level measurements to landscape or regional scales.

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Soil fertility and plant diversity enhance microbial performance in metal-polluted soils.

PubMed

Stefanowicz, Anna M; Kapusta, Paweł; Szarek-Łukaszewska, Grażyna; Grodzińska, Krystyna; Niklińska, Maria; Vogt, Rolf D

2012-11-15

This study examined the effects of soil physicochemical properties (including heavy metal pollution) and vegetation parameters on soil basal respiration, microbial biomass, and the activity and functional richness of culturable soil bacteria and fungi. In a zinc and lead mining area (S Poland), 49 sites were selected to represent all common plant communities and comprise the area's diverse soil types. Numerous variables describing habitat properties were reduced by PCA to 7 independent factors, mainly representing subsoil type (metal-rich mining waste vs. sand), soil fertility (exchangeable Ca, Mg and K, total C and N, organic C), plant species richness, phosphorus content, water-soluble heavy metals (Zn, Cd and Pb), clay content and plant functional diversity (based on graminoids, legumes and non-leguminous forbs). Multiple regression analysis including these factors explained much of the variation in most microbial parameters; in the case of microbial respiration and biomass, it was 86% and 71%, respectively. The activity of soil microbes was positively affected mainly by soil fertility and, apparently, by the presence of mining waste in the subsoil. The mining waste contained vast amounts of trace metals (total Zn, Cd and Pb), but it promoted microbial performance due to its inherently high content of macronutrients (total Ca, Mg, K and C). Plant species richness had a relatively strong positive effect on all microbial parameters, except for the fungal component. In contrast, plant functional diversity was practically negligible in its effect on microbes. Other explanatory variables had only a minor positive effect (clay content) or no significant influence (phosphorus content) on microbial communities. The main conclusion from this study is that high nutrient availability and plant species richness positively affected the soil microbes and that this apparently counteracted the toxic effects of metal contamination. Copyright © 2012 Elsevier B.V. All rights reserved.

The influence of use-related, environmental, and managerial factors on soil loss from recreational trails.

PubMed

Olive, Nathaniel D; Marion, Jeffrey L

2009-03-01

Recreational uses of unsurfaced trails inevitably result in their degradation, with the type and extent of resource impact influenced by factors such as soil texture, topography, climate, trail design and maintenance, and type and amount of use. Of particular concern, the loss of soil through erosion is generally considered a significant and irreversible form of trail impact. This research investigated the influence of several use-related, environmental, and managerial factors on soil loss on recreational trails and roads at Big South Fork National River and Recreation Area, a unit of the U.S. National Park Service. Regression modeling revealed that trail position, trail slope alignment angle, grade, water drainage, and type of use are significant determinants of soil loss. The introduction of individual and groups of variables into a series of regression models provides improved understanding and insights regarding the relative influence of these variables, informing the selection of more effective trail management actions. Study results suggest that trail erosion can be minimized by avoiding "fall-line" alignments, steep grades, and valley-bottom alignments near streams, installing and maintaining adequate densities of tread drainage features, applying gravel to harden treads, and reducing horse and all-terrain vehicle use or restricting them to more resistant routes. This research also sought to develop a more efficient Variable Cross-Sectional Area method for assessing soil loss on trails. This method permitted incorporation of CSA measures in a representative sampling scheme applied to a large (24%) sample of the park's 526 km trail system. The variety of soil loss measures derived from the Variable CSA method, including extrapolated trail-wide soil loss estimates, permit an objective quantification of soil erosion on recreational trails and roads. Such data support relational analyses to increase understanding of trail degradation, and long-term monitoring of the natural and recreational integrity of the trail system infrastructure.

The influence of use-related, environmental, and managerial factors on soil loss from recreational trails

USGS Publications Warehouse

Olive, Nathaniel D.; Marion, Jeffrey L.

2009-01-01

Recreational uses of unsurfaced trails inevitably result in their degradation, with the type and extent of resource impact influenced by factors such as soil texture, topography, climate, trail design and maintenance, and type and amount of use. Of particular concern, the loss of soil through erosion is generally considered a significant and irreversible form of trail impact. This research investigated the influence of several use-related, environmental, and managerial factors on soil loss on recreational trails and roads at Big South Fork National River and Recreation Area, a unit of the U.S. National Park Service. Regression modeling revealed that trail position, trail slope alignment angle, grade, water drainage, and type of use are significant determinants of soil loss. The introduction of individual and groups of variables into a series of regression models provides improved understanding and insights regarding the relative influence of these variables, informing the selection of more effective trail management actions. Study results suggest that trail erosion can be minimized by avoiding “fall-line” alignments, steep grades, and valley-bottom alignments near streams, installing and maintaining adequate densities of tread drainage features, applying gravel to harden treads, and reducing horse and all-terrain vehicle use or restricting them to more resistant routes.This research also sought to develop a more efficient Variable Cross-Sectional Area method for assessing soil loss on trails. This method permitted incorporation of CSA measures in a representative sampling scheme applied to a large (24%) sample of the park's 526 km trail system. The variety of soil loss measures derived from the Variable CSA method, including extrapolated trail-wide soil loss estimates, permit an objective quantification of soil erosion on recreational trails and roads. Such data support relational analyses to increase understanding of trail degradation, and long-term monitoring of the natural and recreational integrity of the trail system infrastructure.

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

Selected meteorological data for an arid climate over bare soil near Beatty, Nye County, Nevada, November 1977 through May 1980

USGS Publications Warehouse

Brown, Robin G.; Nichols, William D.

1990-01-01

Meteorological data were collected over bare soil at a site for low-level radioactive-waste burial near Beatty, Nevada, from November 1977 to May 1980. The data include precipitation, windspeed, wind direction, incident solar radiation, reflected solar radiation, net radiation, dry- and wet-bulb air temperatures at three heights, soil temperature at five depths, and soil-heat flux at three depths. Mean relative humidity was computed for each day of the collection period for which data are available.A discussion is presented of the study site and the instrumentation and procedures used for collecting and processing the data. Selected data from November 1977 to May 1980 are presented in tabular form. Diurnal fluctuations of selected meteorological variables for representative summer and winter periods are graphically presented. The effects on selected variables of a partial solar eclipse are also discussed

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

2014-05-01

Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.

Selection harvests in Amazonian rainforests: long-term impacts on soil properties

Treesearch

K.L. McNabb; M.S. Miller; B.G. Lockaby; B.J. Stokes; R.G. Clawson; John A. Stanturf; J.N.M. Silva

1997-01-01

Surface soil properties were compared among disturbance classes associated with a single-tree selection harvest study installed in 1979 in the Brazilian Amazon. Response variables included pH, total N, total organic C, extractable P, exchangeable K, Ca, Mg, and bulk density. In general, concentrations of all elements displayed residual effects 16 years after harvests...

Can Managed Grazing be Part of Healthy Agroecosystems? Impacts of Various Systems on Soil Water and other Ecosystem Services

NASA Astrophysics Data System (ADS)

DeLonge, M. S.; Basche, A.; Gonzalez, J.

2016-12-01

Due to the vast extent of grazing lands, value of grassland ecosystems, and environmental impacts of the agricultural sector, it is becoming increasingly important to understand to what extent managed grazing can be part of healthy agroecosystems. For example, grazing systems can degrade soils, pollute water, and result in substantial direct and indirect animal emissions. On the other hand, well-managed grasslands can store more carbon, support more biodiversity, and require fewer inputs than croplands or other land uses. Systems analyses are needed to evaluate how much grazing management (e.g., altering stocking rate intensity or regime, integrating versus separating crops and livestock, adopting silvopasture techniques) can affect agroecosystem properties and farm viability. As a result of climate change and likely increases to rainfall variability, the effects of grazing systems on soil water properties are particularly important. The primary goal of this study is to use meta-analytic techniques to better understand how changes to grazing systems affect soil water properties, focusing on soil water infiltration rates. Another goal is to conduct a literature survey to assess how similar changes to grazing have influenced other ecosystem services (e.g., soil carbon, farm profitability) and to identify gaps in knowledge. To date, our meta-analysis includes over 100 paired comparisons (>30 studies) related to grazing. The analysis is a subset of a broader study of agroecological practices that to date includes >350 paired observations. Preliminary results point to significant variability, but suggest that integrating livestock into croplands decreases infiltration (12%), whereas other changings to grazing (decreasing stocking rates, moving from continuous to rotational grazing, or converting to a silvopasture system) can improve infiltration (by an average of 223% including all practices). Findings also suggest that removing livestock tends to increase infiltration rates over time. In cases where infiltration rates are negatively affected by grazing, soil conservation practices such as planting perennials or rotating crops) might mitigate those effects. However, the magnitude of these effects may depend on variables such as time since management change and rainfall regime.

Combined effects of short-term rainfall patterns and soil texture on nitrogen cycling -- A Modeling Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, C.; Riley, W.J.

2009-11-01

Precipitation variability and magnitude are expected to change in many parts of the world over the 21st century. We examined the potential effects of intra-annual rainfall patterns on soil nitrogen (N) transport and transformation in the unsaturated soil zone using a deterministic dynamic modeling approach. The model (TOUGHREACT-N), which has been tested and applied in several experimental and observational systems, mechanistically accounts for microbial activity, soil-moisture dynamics that respond to precipitation variability, and gaseous and aqueous tracer transport in the soil. Here, we further tested and calibrated the model against data from a precipitation variability experiment in a tropical systemmore » in Costa Rica. The model was then used to simulate responses of soil moisture, microbial dynamics, nitrogen (N) aqueous and gaseous species, N leaching, and N trace-gas emissions to changes in rainfall patterns; the effect of soil texture was also examined. The temporal variability of nitrate leaching and NO, N{sub 2}, and N{sub 2}O effluxes were significantly influenced by rainfall dynamics. Soil texture combined with rainfall dynamics altered soil moisture dynamics, and consequently regulated soil N responses to precipitation changes. The clay loam soil more effectively buffered water stress during relatively long intervals between precipitation events, particularly after a large rainfall event. Subsequent soil N aqueous and gaseous losses showed either increases or decreases in response to increasing precipitation variability due to complex soil moisture dynamics. For a high rainfall scenario, high precipitation variability resulted in as high as 2.4-, 2.4-, 1.2-, and 13-fold increases in NH{sub 3}, NO, N{sub 2}O and NO{sub 3}{sup -} fluxes, respectively, in clay loam soil. In sandy loam soil, however, NO and N{sub 2}O fluxes decreased by 15% and 28%, respectively, in response to high precipitation variability. Our results demonstrate that soil N cycling responses to increasing precipitation variability depends on precipitation amount and soil texture, and that accurate prediction of future N cycling and gas effluxes requires models with relatively sophisticated representation of the relevant processes.« less

Field-scale apparent soil electrical conductivity

USDA-ARS?s Scientific Manuscript database

Soils are notoriously spatially heterogeneous and many soil properties (e.g., salinity, water content, trace element concentration, etc.) are temporally variable, making soil a complex media. Spatial variability of soil properties has a profound influence on agricultural and environmental processes ...

The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

1985-01-01

Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

Coccidioides niches and habitat parameters in the southwestern United States: A matter of scale

USGS Publications Warehouse

Fisher, F.S.; Bultman, M.W.; Johnson, S.M.; Pappagianis, D.; Zaborsky, E.; ,

2007-01-01

To determine habitat attributes and processes suitable for the growth of Coccidioides, soils were collected from sites in Arizona, California, and Utah where Coccidioides is known to have been present. Humans or animals or both have been infected by Coccidioides at all of the sites. Soil variables considered in the upper 20 cm of the soil profile included pH, electrical conductivity, salinity, selected anions, texture, mineralogy, vegetation types and density, and the overall geomorphologic and ecological settings. Thermometerswere buried to determine the temperature range in the upper part of the soil where Coccidioides is often found. With the exception of temperature regimes and soil textures, it is striking that none of the other variables or group of variables that might be definitive are indicative of the presence of Coccidioides. Vegetation ranges from sparse to relatively thick cover in lower Sonoran deserts, Chaparral-upper Sonoran brush and grasslands, and Mediterranean savannas and forested foothills. No particular grass, shrub, or forb is definitive. Material classified as very fine sand and silt is abundant in all of the Coccidioides-bearing soils and may be their most common shared feature. Clays are not abundant (less than 10%). All of the examined soil locations are noteworthy as generally 50% of the individuals who were exposed to the dust or were excavating dirt at the sites were infected. Coccidioides has persisted in the soil at a site in Dinosaur National Monument, Utah for 37 years and at a Tucson, Arizona site for 41 years. ?? 2007 New York Academy of Sciences.

Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production

NASA Astrophysics Data System (ADS)

Lipiec, Jerzy; Usowicz, Boguslaw

2017-04-01

Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

NASA Astrophysics Data System (ADS)

Mikhailova, E. A.; Stiglitz, R. Y.; Post, C. J.; Schlautman, M. A.; Sharp, J. L.; Gerard, P. D.

2017-12-01

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro™ color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model's prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination ( R 2, adjusted R 2) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC ( R 2 = 0.987, Adj. R 2 = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN ( R 2 = 0.980 Adj. R 2 = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC ( R 2 = 0.959 Adj. R 2 = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN ( R 2 = 0.912 Adj. R 2 = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.

Variable rate application of nematicides on cotton fields: A promising site-specific management strategy.

USDA-ARS?s Scientific Manuscript database

Field tests were conducted to determine if differences in response to nematicide application (i.e., root-knot nematode (RKN) population levels, cotton yield, and profitability) occurred among RKN management zones (MZ). The MZ were delineated using variables related to soil texture, including appare...

Multiscale variability of soil aggregate stability: implications for rangeland hydrology and erosion

USDA-ARS?s Scientific Manuscript database

Conservation of soil and water resources in rangelands is a crucial step in stopping desertification processes. The formation of water-stable soil aggregates reduces soil erodibility and can increase infiltration capacity in many soils. Soil aggregate stability is highly variable at scales ranging f...

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

Complexity in Soil Systems: What Does It Mean and How Should We Proceed?

NASA Astrophysics Data System (ADS)

Faybishenko, B.; Molz, F. J.; Brodie, E.; Hubbard, S. S.

2015-12-01

The complex soil systems approach is needed fundamentally for the development of integrated, interdisciplinary methods to measure and quantify the physical, chemical and biological processes taking place in soil, and to determine the role of fine-scale heterogeneities. This presentation is aimed at a review of the concepts and observations concerning complexity and complex systems theory, including terminology, emergent complexity and simplicity, self-organization and a general approach to the study of complex systems using the Weaver (1948) concept of "organized complexity." These concepts are used to provide understanding of complex soil systems, and to develop experimental and mathematical approaches to soil microbiological processes. The results of numerical simulations, observations and experiments are presented that indicate the presence of deterministic chaotic dynamics in soil microbial systems. So what are the implications for the scientists who wish to develop mathematical models in the area of organized complexity or to perform experiments to help clarify an aspect of an organized complex system? The modelers have to deal with coupled systems having at least three dependent variables, and they have to forgo making linear approximations to nonlinear phenomena. The analogous rule for experimentalists is that they need to perform experiments that involve measurement of at least three interacting entities (variables depending on time, space, and each other). These entities could be microbes in soil penetrated by roots. If a process being studied in a soil affects the soil properties, like biofilm formation, then this effect has to be measured and included. The mathematical implications of this viewpoint are examined, and results of numerical solutions to a system of equations demonstrating deterministic chaotic behavior are also discussed using time series and the 3D strange attractors.

The relative roles of environment, history and local dispersal in controlling the distributions of common tree and shrub species in a tropical forest landscape, Panama

USGS Publications Warehouse

Svenning, J.-C.; Engelbrecht, B.M.J.; Kinner, D.A.; Kursar, T.A.; Stallard, R.F.; Wright, S.J.

2006-01-01

We used regression models and information-theoretic model selection to assess the relative importance of environment, local dispersal and historical contingency as controls of the distributions of 26 common plant species in tropical forest on Barro Colorado Island (BCI), Panama. We censused eighty-eight 0.09-ha plots scattered across the landscape. Environmental control, local dispersal and historical contingency were represented by environmental variables (soil moisture, slope, soil type, distance to shore, old-forest presence), a spatial autoregressive parameter (??), and four spatial trend variables, respectively. We built regression models, representing all combinations of the three hypotheses, for each species. The probability that the best model included the environmental variables, spatial trend variables and ?? averaged 33%, 64% and 50% across the study species, respectively. The environmental variables, spatial trend variables, ??, and a simple intercept model received the strongest support for 4, 15, 5 and 2 species, respectively. Comparing the model results to information on species traits showed that species with strong spatial trends produced few and heavy diaspores, while species with strong soil moisture relationships were particularly drought-sensitive. In conclusion, history and local dispersal appeared to be the dominant controls of the distributions of common plant species on BCI. Copyright ?? 2006 Cambridge University Press.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Land susceptibility to soil erosion in Orashi Catchment, Nnewi South, Anambra State, Nigeria

NASA Astrophysics Data System (ADS)

Odunuga, Shakirudeen; Ajijola, Abiodun; Igwetu, Nkechi; Adegun, Olubunmi

2018-02-01

Soil erosion is one of the most critical environmental hazards that causes land degradation and water quality challenges. Specifically, this phenomenon has been linked, among other problems, to river sedimentation, groundwater pollution and flooding. This paper assesses the susceptibility of Orashi River Basin (ORB) to soil erosion for the purpose of erosion control measures. Located in the South Eastern part of Nigeria, the ORB which covers approximately 413.61 km2 is currently experiencing one of the fastest population growth rate in the region. Analysis of the soil erosion susceptibility of the basin was based on four factors including; rainfall, Land use/Land cover change (LULC), slope and soil erodibility factor (k). The rainfall was assumed to be a constant and independent variable, slope and soil types were categorised into ten (10) classes each while the landuse was categorised into five classes. Weight was assigned to the classes based on the degree of susceptibility to erosion. An overlay of the four variables in a GIS environment was used to produce the basin susceptibility to soil erosion. This was based on the weight index of each factors. The LULC analysis revealed that built-up land use increased from 26.49 km2 (6.4 %) in year 1980 to 79.24 km2 (19.16 %) in 2015 at an average growth rate of 1.51 km2 per annum while the light forest decreased from 336.41 km2 (81.33 %) in 1980 to 280.82 km2 (67.89 %) in 2015 at an average rate 1.59 km2 per annum. The light forest was adjudged to have the highest land cover soil erosion susceptibility. The steepest slope ranges between 70 and 82° (14.34 % of the total land area) and was adjudged to have the highest soil susceptibility to erosion. The total area covered of the loamy soil is 112.37 km2 (27.07 %) with erodibility of 0.7. In all, the overlay of all the variables revealed that 106.66 km2 (25.70 %) and 164.80 km2 (39.7 %) of the basin has a high and very high susceptibility to soil erosion. The over 50 % high susceptibility of catchment has serious negative implications on the surface water in terms of water quality and downstream siltation with great consequences on biodiversity and ecosystem services including domestic and industrial usage.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

Effect of soil type and soil management on soil physical, chemical and biological properties in commercial organic olive orchards in Southern Spain

NASA Astrophysics Data System (ADS)

Gomez, Jose Alfonso; Auxiliadora Soriano, Maria; Montes-Borrego, Miguel; Navas, Juan Antonio; Landa, Blanca B.

2014-05-01

One of the objectives of organic agriculture is to maintain and improve soil quality, while simultaneously producing an adequate yield. A key element in organic olive production is soil management, which properly implemented can optimize the use of rainfall water enhancing infiltration rates and controlling competition for soil water by weeds. There are different soil management strategies: eg. weed mowing (M), green manure with surface tillage in spring (T), or combination with animal grazing among the trees (G). That variability in soil management combined with the large variability in soil types on which organic olive trees are grown in Southern Spain, difficult the evaluation of the impact of different soil management on soil properties, and yield as well as its interpretation in terms of improvement of soil quality. This communications presents the results and analysis of soil physical, chemical and biological properties on 58 soils in Southern Spain during 2005 and 2006, and analyzed and evaluated in different studies since them. Those 58 soils were sampled in 46 certified commercial organic olive orchards with four soil types as well as 12 undisturbed areas with natural vegetation near the olive orchards. The four soil types considered were Eutric Regosol (RGeu, n= 16), Eutric Cambisol (CMeu, n=16), Calcaric Regosol (RGca, n=13 soils sampled) and Calcic Cambisol (CMcc), and the soil management systems (SMS) include were 10 light tillage (LT), 16 sheep grazing (G), 10 tillage (T), 10 mechanical mowing (M), and 12 undisturbed areas covered by natural vegetation (NV-C and NV-S). Our results indicate that soil management had a significant effect on olive yield as well as on key soil properties. Among these soil properties are physical ones, such as infiltration rate or bulk density, chemical ones, especially organic carbon concentration, and biological ones such as soil microbial respiration and bacterial community composition. Superimpose to that soil management induced variability, there was a strong interaction with soil type and climate conditions. There was also a relatively high variability within the same soil management and soil type class, indicating farm to farm variability in conditions and history of soil management. Based on this dataset two different approaches were taken to: A) evaluate the risk of soil degradation based on a limited set of soil properties, B) assess the effect of changes in SMS on soil biodiversity by using terminal restriction profiles (TRFs) derived from T-RFLP analysis of amplified 16S rDNA as. The results indicates the potential of both approaches to assess the risk of soil degradation (A) and the impact on soil biodiversity (B) upon appropriate benchmarking to characterize the interaction between soil management and soil type References Álvarez, S., Soriano, M.A., Landa, B.B., and Gómez, J.A. 2007. Soil properties in organic olive orchards compared with that in natural areas in a mountainous landscape in southern Spain. Soil Use Manage 23:404-416. Gómez, J.A., Álvarez, S., and Soriano, M.A. 2009. Development of a soil degradation assessment tool for organic olive groves in southern Spain. Catena 79:9-17. Landa, B.B., Montes-Borrego, M., Aranda, S., Soriano, M.A., Gómez, J.A., and Navas-Cortés, J.A. 2013. Soil factors involved in the diversity and structure of soil bacterial communities in commercial organic olive orchards in Southern Spain. Environmental Microbiology Reports (accepted) Soriano, M.A., Álvarez, S., Landa, B.B., and Gómez, J.A. 2013. Soil properties in organic olive orchards following different weed management in a rolling landscape of Andalusia, Spain. Renew Agr Food Syst (in press), doi:10.1017/S1742170512000361.

Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Forman, Barton A.; Draper, Clara S.; Liu, Qing

2013-01-01

A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surface hydrological conditions, including soil moisture, snow, and terrestrial water storage (TWS), into a numerical model of land surface processes. In theory, the output from such a system is superior to estimates based on the observations or the model alone, thereby enhancing our ability to understand, monitor, and predict key elements of the terrestrial water cycle. In practice, however, satellite observations do not correspond directly to the water cycle variables of interest. The present paper addresses various aspects of this seeming mismatch using examples drawn from recent research with the ensemble-based NASA GEOS-5 LDAS. These aspects include (1) the assimilation of coarse-scale observations into higher-resolution land surface models, (2) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (3) the forward modeling of microwave brightness temperatures over land for radiance-based soil moisture and snow assimilation, and (4) the selection of the most relevant types of observations for the analysis of a specific water cycle variable that is not observed (such as root zone soil moisture). The solution to these challenges involves the careful construction of an observation operator that maps from the land surface model variables of interest to the space of the assimilated observations.

Ground water contamination and costs of pesticide restrictions in the southeastern coastal plain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danielson, L.E.; Carlson, G.A.; Liu, S.

The project developed new methodology for estimating: (1) groundwater contamination potential (GWCP) in the Southeast Coastal Plain, and (2) the potential economic impacts of selected policies that restrict pesticide use. The potential for ground water contamination was estimated by use of a simple matrix for combining ratings for both soil leaching potential and pesticide leaching potential. Key soil variables included soil texture, soil acidity and organic matter content. Key pesticide characteristics included Koc, pesticide half-life, the rate of application and the fraction of the pesticide hitting the soil. Comparisons of pesticide use from various farmer and expert opinion surveys weremore » made for pesticide groups and for individual pesticide products. Methodology for merging the GWCP changes and lost benefits from selected herbicide cancellations was developed using corn production in the North Carolina Coastal Plain. Economic evaluations of pesticide cancellations for corn included national and Coastal Plain estimates for atrazine; metolachlor; dicamba; dicamba and atrazine; and dicamba, atrazine and metolachlor.« less

Relation of pH and other soil variables to concentrations of Pb, Cu, Zn, Cd, and Se in earthworms

USGS Publications Warehouse

Beyer, W.N.; Hensler, G.L.; Moore, J.

1987-01-01

Various soil treatments (clay, composted peat, superphosphate, sulfur, calcium carbonate, calcium chloride, zinc chloride, selenous acid) were added to experimental field plots to test the effect of different soil variables on the concentrations of 5 elements in earthworms (Pb, Cu, Zn, Cd, Se). Concentrations of the 5 elements were related to 9 soil variables (soil Pb, soil Cu, soil Zn, pH, organic matter, P, K, Mg, and Ca) with linear multiple regression. Lead concentrations in earthworms were positively correlated with soil Pb and soil organic matter, and negatively correlated with soil pH and soil Mg, with an R2 of 64%. Se concentrations were higher in earthworms from plots amended with Se, and Zn concentrations were higher in earthworms from plots amended with Zn. However, none of the other soil variables had important effects on the concentrations of Cu, Zn, Cd and Se in earthworms. Although some significant statistical relations were demonstrated, the values of r2 of all relations (> 20%) were so low that they had little predictive value.

Unsaturated flow processes in structurally-variable pathways in wildfire-affected soils and ash

NASA Astrophysics Data System (ADS)

Ebel, B. A.

2016-12-01

Prediction of flash flood and debris flow generation in wildfire-affected soils and ash hinges on understanding unsaturated flow processes. Water resources issues, such as groundwater recharge, also rely on our ability to quantify subsurface flow. Soil-hydraulic property data provide insight into unsaturated flow processes and timescales. A literature review and synthesis of existing data from the literature for wildfire-affected soils, including ash and unburned soils, facilitated calculating metrics and timescales of hydrologic response related to infiltration and surface runoff generation. Sorptivity (S) and the Green-Ampt wetting front parameter (Ψf) were significantly lower in burned soils compared to unburned soils, while field-saturated hydraulic conductivity (Kfs) was not significantly different. The magnitude and duration of the influence of capillarity was substantially reduced in burned soils, leading to faster ponding times in response to rainfall. Ash had large values of S and Kfs compared to unburned and burned soils but intermediate values of Ψf, suggesting that ash has long ponding times in response to rainfall. The ratio of S2/Kfs was nearly constant ( 100 mm) for unburned soils, but was more variable in burned soils. Post-wildfire changes in this ratio suggested that unburned soils had a balance between gravity and capillarity contributions to infiltration, which may depend on soil organic matter, while burning shifted infiltration more towards gravity contributions by reducing S. Taken together, the changes in post-wildfire soil-hydraulic properties increased the propensity for surface runoff generation and may have enhanced subsurface preferential flow through pathways altered by wildfire.

Effect of soil properties on the toxicity of Pb: assessment of the appropriateness of guideline values.

PubMed

Romero-Freire, A; Martin Peinado, F J; van Gestel, C A M

2015-05-30

Soil contamination with lead is a worldwide problem. Pb can cause adverse effects, but its mobility and availability in the terrestrial environment are strongly controlled by soil properties. The present study investigated the influence of different soil properties on the solubility of lead in laboratory spiked soils, and its toxicity in three bioassays, including Lactuca sativa root elongation and Vibrio fischeri illumination tests applied to aqueous extracts and basal soil respiration assays. Final aim was to compare soil-dependent toxicity with guideline values. The L. sativa bioassay proved to be more sensitive to Pb toxicity than the V. fischeri and soil respiration tests. Toxicity was significantly correlated with soil properties, with soil pH, carbonate and organic carbon content being the most important factors. Therefore, these variables should be considered when defining guideline values. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

NASA Astrophysics Data System (ADS)

Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

2010-05-01

Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes. Topographic features showed the strongest correlation with soil moisture during dry periods, indicating that the control of topography on the soil moisture pattern depends on the soil water status. Interpolation using the external drift kriging method demonstrated that the high sampling density allows capturing the key patterns of soil moisture variation in the Wüstebach catchment. References: [1] Bogena, H.R., J.A. Huisman, C. Oberdörster, H. Vereecken (2007): Evaluation of a low-cost soil water content sensor for wireless network applications. Journal of Hydrology: 344, 32- 42. [2] Rosenbaum, U., Huisman, J.A., Weuthen, A., Vereecken, H. and Bogena, H.R. (2010): Quantification of sensor-to-sensor variability of the ECH2O EC-5, TE and 5TE sensors in dielectric liquids. Accepted for publication in Vadose Zone Journal (09/2009). [3] Famiglietti J.S., D. Ryu, A. A. Berg, M. Rodell and T. J. Jackson (2008), Field observations of soil moisture variability across scales, Water Resour. Res. 44, W01423, doi:10.1029/2006WR005804.

Mapping Spatial Variability of Soil Salinity in a Coastal Paddy Field Based on Electromagnetic Sensors

PubMed Central

Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

2015-01-01

In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles. PMID:26020969

Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

PubMed

Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

2015-01-01

In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

NASA Technical Reports Server (NTRS)

Sullivan, Dana; Shaw, Joey; Rickman, Doug

2005-01-01

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Assessment of crop growth and soil water modules in SWAT2000 using extensive field experiment data in an irrigation district of the Yellow River Basin

USGS Publications Warehouse

Luo, Y.; He, C.; Sophocleous, M.; Yin, Z.; Hongrui, R.; Ouyang, Z.

2008-01-01

SWAT, a physically-based, hydrological model simulates crop growth, soil water and groundwater movement, and transport of sediment and nutrients at both the process and watershed scales. While the different versions of SWAT have been widely used throughout the world for agricultural and water resources applications, little has been done to test the performance, variability, and transferability of the parameters in the crop growth, soil water, and groundwater modules in an integrated way with multiple sets of field experimental data at the process scale. Using an multiple years of field experimental data of winter wheat (Triticum aestivum L.) in the irrigation district of the Yellow River Basin, this paper assesses the performance of the plant-soil-groundwater modules and the variability and transferability of SWAT2000. Comparison of the simulated results by SWAT to the observations showed that SWAT performed quite unsatisfactorily in LAI predictions during the senescence stage, in yield predictions, and in soil-water estimation under dry soil-profile conditions. The unsatisfactory performance in LAI prediction might be attributed to over-simplified senescence modeling; in yield prediction to the improper computation of the harvest index; and in soil water under dry conditions to the exclusion of groundwater evaporation from the soil water balance in SWAT. In this paper, improvements in crop growth, soil water, and groundwater modules in SWAT were implemented. The saturated soil profile was coupled to the oscillating groundwater table. A variable evaporation coefficient taking into account soil water deficit index, groundwater depth, and crop root depth was used to replace the fixed coefficient in computing groundwater evaporation. The soil water balance included the groundwater evaporation. The modifications improved simulations of crop evapotranspiration and biomass as well as soil water dynamics under dry soil-profile conditions. The evaluation shows that the crop growth and soil water components of SWAT could be further refined to better simulate the hydrology of agricultural watersheds. ?? 2008 Elsevier B.V. All rights reserved.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Variability, drivers, and effects of atmospheric nitrogen inputs across an urban area: Emerging patterns among human activities, the atmosphere, and soils.

PubMed

Decina, Stephen M; Templer, Pamela H; Hutyra, Lucy R; Gately, Conor K; Rao, Preeti

2017-12-31

Atmospheric deposition of nitrogen (N) is a major input of N to the biosphere and is elevated beyond preindustrial levels throughout many ecosystems. Deposition monitoring networks in the United States generally avoid urban areas in order to capture regional patterns of N deposition, and studies measuring N deposition in cities usually include only one or two urban sites in an urban-rural comparison or as an anchor along an urban-to-rural gradient. Describing patterns and drivers of atmospheric N inputs is crucial for understanding the effects of N deposition; however, little is known about the variability and drivers of atmospheric N inputs or their effects on soil biogeochemistry within urban ecosystems. We measured rates of canopy throughfall N as a measure of atmospheric N inputs, as well as soil net N mineralization and nitrification, soil solution N, and soil respiration at 15 sites across the greater Boston, Massachusetts area. Rates of throughfall N are 8.70±0.68kgNha -1 yr -1 , vary 3.5-fold across sites, and are positively correlated with rates of local vehicle N emissions. Ammonium (NH 4 + ) composes 69.9±2.2% of inorganic throughfall N inputs and is highest in late spring, suggesting a contribution from local fertilizer inputs. Soil solution NO 3 - is positively correlated with throughfall NO 3 - inputs. In contrast, soil solution NH 4 + , net N mineralization, nitrification, and soil respiration are not correlated with rates of throughfall N inputs. Rather, these processes are correlated with soil properties such as soil organic matter. Our results demonstrate high variability in rates of urban throughfall N inputs, correlation of throughfall N inputs with local vehicle N emissions, and a decoupling of urban soil biogeochemistry and throughfall N inputs. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

NASA Astrophysics Data System (ADS)

Payo, Andrés.; Lázár, Attila N.; Clarke, Derek; Nicholls, Robert J.; Bricheno, Lucy; Mashfiqus, Salehin; Haque, Anisul

2017-05-01

Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (˜20,000 km2). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh.

Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China

NASA Astrophysics Data System (ADS)

Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng

2009-05-01

Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.

Improved ground hydrology calculations for global climate models (GCMs) - Soil water movement and evapotranspiration

NASA Technical Reports Server (NTRS)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-01-01

A physically based ground hydrology model is presented that includes the processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff. Data from the Goddard Institute for Space Studies GCM were used as inputs for off-line tests of the model in four 8 x 10 deg regions, including Brazil, Sahel, Sahara, and India. Soil and vegetation input parameters were caculated as area-weighted means over the 8 x 10 deg gridbox; the resulting hydrological quantities were compared to ground hydrology model calculations performed on the 1 x 1 deg cells which comprise the 8 x 10 deg gridbox. Results show that the compositing procedure worked well except in the Sahel, where low soil water levels and a heterogeneous land surface produce high variability in hydrological quantities; for that region, a resolution better than 8 x 10 deg is needed.

Comparison of crop stress and soil maps to enhance variable rate irrigation prescriptions

USDA-ARS?s Scientific Manuscript database

Soil textural variability within many irrigated fields diminishes the effectiveness of conventional irrigation management, and scheduling methods that assume uniform soil conditions may produce less than satisfactory results. Furthermore, benefits of variable-rate application of agrochemicals, seeds...

REGIONAL SOIL WATER RETENTION IN THE CONTIGUOUS US: SOURCES OF VARIABILITY AND VOLCANIC SOIL EFFECTS

EPA Science Inventory

Water retention of mineral soil is often well predicted using algorithms (pedotransfer functions) with basic soil properties but the spatial variability of these properties has not been well characterized. A further source of uncertainty is that water retention by volcanic soils...

Synergistic Utilization of Microwave Satellite Data and GRACE-Total Water Storage Anomaly for Improving Available Water Capacity Prediction in Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Gupta, M.; Bolten, J. D.; Lakshmi, V.

2015-12-01

The Mekong River is the longest river in Southeast Asia and the world's eighth largest in discharge with draining an area of 795,000 km² from the eastern watershed of the Tibetan Plateau to the Mekong Delta including three provinces of China, Myanmar, Lao PDR, Thailand, Cambodia and Viet Nam. This makes the life of people highly vulnerable to availability of the water resources as soil moisture is one of the major fundamental variables in global hydrological cycles. The day-to-day variability in soil moisture on field to global scales is an important quantity for early warning systems for events like flooding and drought. In addition to the extreme situations the accurate soil moisture retrieval are important for agricultural irrigation scheduling and water resource management. The present study proposes a method to determine the effective soil hydraulic parameters directly from information available for the soil moisture state from the recently launched SMAP (L-band) microwave remote sensing observations. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the physically based land surface model. This work addresses the improvement of available water capacity as the soil hydraulic parameters are optimized through the utilization of satellite-retrieved near surface soil moisture. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on FAO. The optimization process is divided into two steps: the state variable are optimized and the optimal parameter values are then transferred for retrieving soil moisture and streamflow. A homogeneous soil system is considered as the soil moisture from sensors such as AMSR-E/SMAP can only be retrieved for the top few centimeters of soil. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Modelling carbon and nitrogen turnover in variably saturated soils

NASA Astrophysics Data System (ADS)

Batlle-Aguilar, J.; Brovelli, A.; Porporato, A.; Barry, D. A.

2009-04-01

Natural ecosystems provide services such as ameliorating the impacts of deleterious human activities on both surface and groundwater. For example, several studies have shown that a healthy riparian ecosystem can reduce the nutrient loading of agricultural wastewater, thus protecting the receiving surface water body. As a result, in order to develop better protection strategies and/or restore natural conditions, there is a growing interest in understanding ecosystem functioning, including feedbacks and nonlinearities. Biogeochemical transformations in soils are heavily influenced by microbial decomposition of soil organic matter. Carbon and nutrient cycles are in turn strongly sensitive to environmental conditions, and primarily to soil moisture and temperature. These two physical variables affect the reaction rates of almost all soil biogeochemical transformations, including microbial and fungal activity, nutrient uptake and release from plants, etc. Soil water saturation and temperature are not constants, but vary both in space and time, thus further complicating the picture. In order to interpret field experiments and elucidate the different mechanisms taking place, numerical tools are beneficial. In this work we developed a 3D numerical reactive-transport model as an aid in the investigation the complex physical, chemical and biological interactions occurring in soils. The new code couples the USGS models (MODFLOW 2000-VSF, MT3DMS and PHREEQC) using an operator-splitting algorithm, and is a further development an existing reactive/density-dependent flow model PHWAT. The model was tested using simplified test cases. Following verification, a process-based biogeochemical reaction network describing the turnover of carbon and nitrogen in soils was implemented. Using this tool, we investigated the coupled effect of moisture content and temperature fluctuations on nitrogen and organic matter cycling in the riparian zone, in order to help understand the relative sensitivity of biological transformations to these processes.

Urban soil geochemistry in Athens, Greece: The importance of local geology in controlling the distribution of potentially harmful trace elements.

PubMed

Argyraki, Ariadne; Kelepertzis, Efstratios

2014-06-01

Understanding urban soil geochemistry is a challenging task because of the complicated layering of the urban landscape and the profound impact of large cities on the chemical dispersion of harmful trace elements. A systematic geochemical soil survey was performed across Greater Athens and Piraeus, Greece. Surface soil samples (0-10cm) were collected from 238 sampling sites on a regular 1×1km grid and were digested by a HNO3-HCl-HClO4-HF mixture. A combination of multivariate statistics and Geographical Information System approaches was applied for discriminating natural from anthropogenic sources using 4 major elements, 9 trace metals, and 2 metalloids. Based on these analyses the lack of heavy industry in Athens was demonstrated by the influence of geology on the local soil chemistry with this accounting for 49% of the variability in the major elements, as well as Cr, Ni, Co, and possibly As (median values of 102, 141, 16 and 24mg kg(-1) respectively). The contribution to soil chemistry of classical urban contaminants including Pb, Cu, Zn, Sn, Sb, and Cd (medians of 45, 39, 98, 3.6, 1.7 and 0.3mg kg(-1) respectively) was also observed; significant correlations were identified between concentrations and urbanization indicators, including vehicular traffic, urban land use, population density, and timing of urbanization. Analysis of soil heterogeneity and spatial variability of soil composition in the Greater Athens and Piraeus area provided a representation of the extent of anthropogenic modifications on natural element loadings. The concentrations of Ni, Cr, and As were relatively high compared to those in other cities around the world, and further investigation should characterize and evaluate their geochemical reactivity. Copyright © 2014 Elsevier B.V. All rights reserved.

Soil water content assessment: critical issues concerning the operational application of the triangle method.

PubMed

Maltese, Antonino; Capodici, Fulvio; Ciraolo, Giuseppe; La Loggia, Goffredo

2015-03-19

Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperature is unknown, to mitigate the effects of calibration inaccuracies or to account for the temporal admittance of the soil. However, if applied over a limited area, a characterization of both dry and wet edges could not be properly achieved; thus, a multi-temporal analysis can be exploited to include outer extremes in soil water content. A diachronic empirical approach introduces the need to assume a constancy of other meteorological forcing variables that control thermal features. Airborne images were acquired on a Sicilian vineyard during most of an entire irrigation period (fruit-set to ripening stages, vintage 2008), during which in situ soil water content was measured to set up the triangle method. Within this framework, we tested the triangle method by employing alternative thermal forcing. The results were inaccurate when air temperature at airborne acquisition was employed. Sonic and aerodynamic air temperatures confirmed and partially explained the limits of simultaneous meteorological forcing, and the use of proxy variables improved model accuracy. The analysis indicates that high spatial resolution does not necessarily imply higher accuracies.

Soil Water Content Assessment: Critical Issues Concerning the Operational Application of the Triangle Method

PubMed Central

Maltese, Antonino; Capodici, Fulvio; Ciraolo, Giuseppe; La Loggia, Goffredo

2015-01-01

Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperature is unknown, to mitigate the effects of calibration inaccuracies or to account for the temporal admittance of the soil. However, if applied over a limited area, a characterization of both dry and wet edges could not be properly achieved; thus, a multi-temporal analysis can be exploited to include outer extremes in soil water content. A diachronic empirical approach introduces the need to assume a constancy of other meteorological forcing variables that control thermal features. Airborne images were acquired on a Sicilian vineyard during most of an entire irrigation period (fruit-set to ripening stages, vintage 2008), during which in situ soil water content was measured to set up the triangle method. Within this framework, we tested the triangle method by employing alternative thermal forcing. The results were inaccurate when air temperature at airborne acquisition was employed. Sonic and aerodynamic air temperatures confirmed and partially explained the limits of simultaneous meteorological forcing, and the use of proxy variables improved model accuracy. The analysis indicates that high spatial resolution does not necessarily imply higher accuracies. PMID:25808771

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area

NASA Astrophysics Data System (ADS)

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-02-01

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors.

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area

PubMed Central

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-01-01

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors. PMID:26916152

Effects of soil and topographic factors on vegetation restoration in opencast coal mine dumps located in a loess area.

PubMed

Wang, Jinman; Wang, Hongdan; Cao, Yingui; Bai, Zhongke; Qin, Qian

2016-02-26

Vegetation plays an important role in improving and restoring fragile ecological environments. In the Antaibao opencast coal mine, located in a loess area, the eco-environment has been substantially disturbed by mining activities, and the relationship between the vegetation and environmental factors is not very clear. Therefore, it is crucial to understand the effects of soil and topographic factors on vegetation restoration to improve the fragile ecosystems of damaged land. An investigation of the soil, topography and vegetation in 50 reclamation sample plots in Shanxi Pingshuo Antaibao opencast coal mine dumps was performed. Statistical analyses in this study included one-way ANOVA and significance testing using SPSS 20.0, and multivariate techniques of detrended correspondence analysis (DCA) and redundancy analysis (RDA) using CANOCO 4.5. The RDA revealed the environmental factors that affected vegetation restoration. Various vegetation and soil variables were significantly correlated. The available K and rock content were good explanatory variables, and they were positively correlated with tree volume. The effects of the soil factors on vegetation restoration were higher than those of the topographic factors.

Metsulfuron-methyl sorption/desorption behavior on volcanic ash-derived soils. effect of phosphate and pH.

PubMed

Cáceres, Lizethly; Fuentes, Roxana; Escudey, Mauricio; Fuentes, Edwar; Báez, María E

2010-06-09

Metsulfuron-methyl sorption/desorption behavior was studied through batch sorption experiments in three typical volcanic ash-derived soils belonging to Andisol and Ultisol orders. Their distinctive physical and chemical properties are acidic pH and variable surface charge. Organic matter content and mineral composition affected in different ways sorption of metsulfuron-methyl (K(OC) ranging from 113 to 646 mL g(-1)): organic matter and iron and aluminum oxides mainly through hydrophilic rather than hydrophobic interactions in Andisols, and Kaolinite group minerals, as major constituents of Ultisols, and iron and aluminum oxides only through hydrophilic interactions. The Freundlich model described metsulfuron-methyl behavior in all cases (R(2) > 0.992). K(f) values (3.1-14.4 microg(1-1/n) mL(1/n) g(-1)) were higher than those reported for different class of soils including some with variable charge. Hysteresis was more significant in Ultisols. A strong influence of pH and phosphate was established for both kinds of soil, intensive soil fertilization and liming being the most probable scenario for leaching of metsulfuron-methyl, particularly in Ultisols.

Microbial Diversity in Soil, Sand Dune and Rock Substrates of the Thar Monsoon Desert, India.

PubMed

Rao, Subramanya; Chan, Yuki; Bugler-Lacap, Donnabella C; Bhatnagar, Ashish; Bhatnagar, Monica; Pointing, Stephen B

2016-03-01

A culture-independent diversity assessment of archaea, bacteria and fungi in the Thar Desert in India was made. Six locations in Ajmer, Jaisalmer, Jaipur and Jodhupur included semi-arid soils, arid soils, arid sand dunes, plus arid cryptoendolithic substrates. A real-time quantitative PCR approach revealed that bacteria dominated soils and cryptoendoliths, whilst fungi dominated sand dunes. The archaea formed a minor component of all communities. Comparison of rRNA-defined community structure revealed that substrate and climate rather than location were the most parsimonious predictors. Sequence-based identification of 1240 phylotypes revealed that most taxa were common desert microorganisms. Semi-arid soils were dominated by actinobacteria and alpha proteobacteria, arid soils by chloroflexi and alpha proteobacteria, sand dunes by ascomycete fungi and cryptoendoliths by cyanobacteria. Climatic variables that best explained this distribution were mean annual rainfall and maximum annual temperature. Substrate variables that contributed most to observed diversity patterns were conductivity, soluble salts, Ca(2+) and pH. This represents an important addition to the inventory of desert microbiota, novel insight into the abiotic drivers of community assembly, and the first report of biodiversity in a monsoon desert system.

[Spatial variability of soil nutrients based on geostatistics combined with GIS--a case study in Zunghua City of Hebei Province].

PubMed

Guo, X; Fu, B; Ma, K; Chen, L

2000-08-01

Geostatistics combined with GIS was applied to analyze the spatial variability of soil nutrients in topsoil (0-20 cm) in Zunghua City of Hebei Province. GIS can integrate attribute data with geographical data of system variables, which makes the application of geostatistics technique for large spatial scale more convenient. Soil nutrient data in this study included available N (alkaline hydrolyzing nitrogen), total N, available K, available P and organic matter. The results showed that the semivariograms of soil nutrients were best described by spherical model, except for that of available K, which was best fitted by complex structure of exponential model and linear with sill model. The spatial variability of available K was mainly produced by structural factor, while that of available N, total N, available P and organic matter was primarily caused by random factor. However, their spatial heterogeneity degree was different: the degree of total N and organic matter was higher, and that of available P and available N was lower. The results also indicated that the spatial correlation of the five tested soil nutrients at this large scale was moderately dependent. The ranges of available N and available P were almost same, which were 5 km and 5.5 km, respectively. The range of total N was up to 18 km, and that of organic matter was 8.5 km. For available K, the spatial variability scale primarily expressed exponential model between 0-3.5 km, but linear with sill model between 3.5-25.5 km. In addition, five soil nutrients exhibited different isotropic ranges. Available N and available P were isotropic through the whole research range (0-28 km). The isotropic range of available K was 0-8 km, and that of total N and organic matter was 0-10 km.

Associations between soil variables and vegetation structure and composition of Caribbean dry forests

Treesearch

Elvia M. Melendez-Ackerman; Julissa Rojas-Sandoval; Danny S. Fernandez; Grizelle Gonzalez; Hana Lopez; Jose Sustache; Mariely Morales; Miguel Garcia-Bermudez; Susan Aragon

2016-01-01

Soil–vegetation associations have been understudied in tropical dry forests when compared to the amount of extant research on this issue in tropical wet forests. Recent studies assert that vegetation in tropical dry forests is highly heterogeneous and that soil variability may be a contributing factor. In this study, we evaluated the relationship between soil variables...

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Improved chemometric methodologies for the assessment of soil carbon sequestration mechanisms

NASA Astrophysics Data System (ADS)

Jiménez-González, Marco A.; Almendros, Gonzalo; Álvarez, Ana M.; González-Vila, Francisco J.

2016-04-01

The factors involved soil C sequestration, which is reflected in the highly variable content of organic matter in the soils, are not yet well defined. Therefore, their identification is crucial for understanding Earth's biogeochemical cycle and global change. The main objective of this work is to contribute to a better qualitative and quantitative assessment of the mechanisms of organic C sequestration in the soil, using omic approaches not requiring the detailed knowledge of the structure of the material under study. With this purpose, we have carried out a series of chemometric approaches on a set of widely differing soils (35 representative ecosystems). In an exploratory phase, we used multivariate statistical models (e.g., multidimensional scaling, discriminant analysis with automatic backward variable selection…) to analyze arrays of more than 200 independent soil variables (physicochemical, spectroscopic, pyrolytic...) in order to select those factors (descriptors or proxies) that explain most of the total system variance (content and stability of the different C forms). These models showed that the factors determining the stabilization of organic material are greatly dependent on the soil type. In some cases, the molecular structure of organic matter seemed strongly correlated with their resilience, while in other soil types the organo-mineral interactions played a significant bearing on the accumulation of selectively preserved C forms. In any case, it was clear that the factors driving the resilience of organic matter are manifold and not exclusive. Consequently, in a second stage, prediction models of the soil C content and their biodegradability (laboratory incubation experiments) were carried out by massive data processing by partial least squares (PLS) regression of data from Py-GC-MS and Py-MS. In some models, PLS was applied to a matrix of 150 independent variables corresponding to major pyrolysis compounds (peak areas) from the 35 samples of whole soils. The variable importance in the projection (VIP) histogram obtained from this treatment (total C and total mineralization coefficients as dependent variables) illustrated the contribution of the individual compounds to the total inertia of the models (e.g., carbohydrate-derived compounds, methoxyphenols, or specific alkylbenzenes were relevant in explaining the total quality and the biodegradation rates of the organic matter). Further simplified models consisting of direct PLS analysis of the debugged ion matrix calculated by averaging all ions (45 - 250 amu) in the whole chromatographic area in the 5-60 min range (here referred to as 'rebuilt MS spectra' or 'Py-MS spectra' when obtained connecting directly the pyrolyser to the MS detector through suitable interfaces) were carried out. The above three approaches coincided in pointing out that C sequestration behave as an emergent soil property depending on the complexity of its progressive molecular levels. Most of the total variance is explained by specific assemblages of variables, strongly depending on the soil types. On the other hand, chemical biodiversity (e.g., Shannon indices or coefficients from multivariate data models) behaved as a common background in the prediction models including very different soil types. In fact, assessment of chemodiversity of the pyrolytic compound assemblages (or the Py-MS ion data) would represent a valid clue for the assessment of the extent to which the original biomass has been diagenetically reworked into chaotic structures with non-repeatable units, providing a useful proxy to forecast at least a portion of the total variance in the soil organic matter biodegradability.

Agriculture at the Edge: Landscape Variability of Soil C Stocks and Fluxes in the Tropical Andes

NASA Astrophysics Data System (ADS)

Riveros-Iregui, D. A.; Peña, C.

2015-12-01

Paramos, or tropical alpine grasslands occurring right above the forest tree-line (2,800 - 4,700 m), are among the most transformed landscapes in the humid tropics. In the Tropical Andes, Paramos form an archipelago-like pattern from Northern Colombia to Central Peru that effectively captures atmospheric moisture originated in the Amazon-Orinoco basins, while marking the highest altitude capable of sustaining vegetation growth (i.e., 'the edge'). This study investigates the role of land management on mediating soil carbon stocks and fluxes in Paramo ecosystems of the Eastern Cordillera of Colombia. Observations were collected at a Paramo site strongly modified by land use change, including active potato plantations, pasture, tillage, and land abandonment. Results show that undisturbed Paramos soils have high total organic carbon (TOC), high soil water content (SWC), and low soil CO2 efflux (RS) rates. However, Paramo soils that experience human intervention show lower TOC, higher and more variable RS rates, and lower SWC. This study demonstrates that changes in land use in Paramos affect differentially the accumulation and exchange of soil carbon with the atmosphere and offers implications for management and protection strategies of what has been deemed the fastest evolving biodiversity ecosystem in the world.

Relationships among environmental variables and distribution of tree species at high elevation in the Olympic Mountains

USGS Publications Warehouse

Woodward, Andrea

1998-01-01

Relationships among environmental variables and occurrence of tree species were investigated at Hurricane Ridge in Olympic National Park, Washington, USA. A transect consisting of three plots was established down one north-and one south-facing slope in stands representing the typical elevational sequence of tree species. Tree species included subalpine fir (Abies lasiocarpa), Douglas-fir (Pseudotsuga menziesii), mountain hemlock (Tsuga mertensiana), and Pacific silver fir (Abies amabilis). Air and soil temperature, precipitation, and soil moisture were measured during three growing seasons. Snowmelt patterns, soil carbon and moisture release curves were also determined. The plots represented a wide range in soil water potential, a major determinant of tree species distribution (range of minimum values = -1.1 to -8.0 MPa for Pacific silver fir and Douglas-fir plots, respectively). Precipitation intercepted at plots depended on topographic location, storm direction and storm type. Differences in soil moisture among plots was related to soil properties, while annual differences at each plot were most often related to early season precipitation. Changes in climate due to a doubling of atmospheric CO2 will likely shift tree species distributions within, but not among aspects. Change will be buffered by innate tolerance of adult trees and the inertia of soil properties.

Sample sizes to control error estimates in determining soil bulk density in California forest soils

Treesearch

Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber

2016-01-01

Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...

Soil microbial community successional patterns during forest ecosystem restoration.

PubMed

Banning, Natasha C; Gleeson, Deirdre B; Grigg, Andrew H; Grant, Carl D; Andersen, Gary L; Brodie, Eoin L; Murphy, D V

2011-09-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

Soil Microbial Community Successional Patterns during Forest Ecosystem Restoration ▿†

PubMed Central

Banning, Natasha C.; Gleeson, Deirdre B.; Grigg, Andrew H.; Grant, Carl D.; Andersen, Gary L.; Brodie, Eoin L.; Murphy, D. V.

2011-01-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables. PMID:21724890

Northern Eurasian Heat Waves and Droughts

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Wang, Hailan; Koster, Randal; Suarez, Max; Groisman, Pavel

2013-01-01

This article reviews our understanding of the characteristics and causes of northern Eurasian summertime heat waves and droughts. Additional insights into the nature of temperature and precipitation variability in Eurasia on monthly to decadal time scales and into the causes and predictability of the most extreme events are gained from the latest generation of reanalyses and from supplemental simulations with the NASA GEOS-5 AGCM. Key new results are: 1) the identification of the important role of summertime stationary Rossby waves in the development of the leading patterns of monthly Eurasian surface temperature and precipitation variability (including the development of extreme events such as the 2010 Russian heat wave), 2) an assessment of the mean temperature and precipitation changes that have occurred over northern Eurasia in the last three decades and their connections to decadal variability and global trends in SST, and 3) the quantification (via a case study) of the predictability of the most extreme simulated heat wave/drought events, with some focus on the role of soil moisture in the development and maintenance of such events. A literature survey indicates a general consensus that the future holds an enhanced probability of heat waves across northern Eurasia, while there is less agreement regarding future drought, reflecting a greater uncertainty in soil moisture and precipitation projections. Substantial uncertainties remain in our understanding of heat waves and drought, including the nature of the interactions between the short-term atmospheric variability associated with such extremes and the longer-term variability and trends associated with soil moisture feedbacks, SST anomalies, and an overall warming world.

The use of crop rotation for mapping soil organic content in farmland

NASA Astrophysics Data System (ADS)

Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi

2017-04-01

Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.

NASA applications project in Miami County, Indiana

NASA Technical Reports Server (NTRS)

Fernandez, R. Norberto; Lozano-Garcia, D. Fabian; Wyss, Phillip J.; Johannsen, Chris J.

1989-01-01

The study site selection is intended to serve all of the different research areas within the project, i.e., soil conditions, soil management, etc. There are seven major soil associations or soils formed on similar landscapes in the Miami Co., and over 38 soil series that were mapped. Soil sampling was conducted in some sites because of its variability in soils and cover types, variable topography, and presence of erosion problems. Results from analysis of these soil data is presented.

Human land-use and soil change

USGS Publications Warehouse

Wills, Skye A.; Williams, Candiss O.; Duniway, Michael C.; Veenstra, Jessica; Seybold, Cathy; Pressley, DeAnn

2017-01-01

Soil change refers to the alteration of soil and soil properties over time in one location, as opposed to soil variability across space. Although soils change with pedogensis, this chapter focuses on human caused soil change. Soil change can occur with human use and management over long or short time periods and small or large scales. While change can be negative or positive; often soil change is observed when short-term or narrow goals overshadow the other soil’s ecosystem services. Many soils have been changed in their chemical, physical or biological properties through agricultural activities, including cultivation, tillage, weeding, terracing, subsoiling, deep plowing, manure and fertilizer addition, liming, draining, and irrigation. Assessing soil change depends upon the ecosystem services and soil functions being evaluated. The interaction of soil properties with the type and intensity of management and disturbance determines the changes that will be observed. Tillage of cropland disrupts aggregates and decreases soil organic carbon content which can lead to decreased infiltration, increased erosion, and reduced biological function. Improved agricultural management systems can increase soil functions including crop productivity and sustainability. Forest management is most intensive during harvesting and seedling establishment. Most active management in forests causes disturbance of the soil surface which may include loss of forest floor organic materials, increases in bulk density, and increased risk of erosion. In grazing lands, pasture management often includes periods of biological, chemical and physical disturbance in addition to the grazing management imposed on rangelands. Grazing animals have both direct and indirect impacts on soil change. Hoof action can lead to the disturbance of biological crusts and other surface features impairing the soil’s physical, biological and hydrological function. There are clear feedbacks between vegetative systems and soil properties; when vegetation is altered because of grazing or other disturbances, soil property changes often follow. Some soils are very sensitive to management and disturbance and can undergo rapid change: cropping led to massive gully formation in the southeastern USA, exposure of acid-sulfate soils led to irreversible changes in soil minerology and thawing of cold soils has created thermokarst features. These soil changes alter soil properties and functions and may impact soil ecosystem services far into the future.

Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.

1995-09-01

Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less

Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils.

PubMed

Zornoza, R; Guerrero, C; Mataix-Solera, J; Scow, K M; Arcenegui, V; Mataix-Beneyto, J

2008-07-01

The potential of near infrared (NIR) reflectance spectroscopy to predict various physical, chemical and biochemical properties in Mediterranean soils from SE Spain was evaluated. Soil samples (n=393) were obtained by sampling thirteen locations during three years (2003-2005 period). These samples had a wide range of soil characteristics due to variations in land use, vegetation cover and specific climatic conditions. Biochemical properties also included microbial biomarkers based on phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r(2)) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r(2)>0.90 and RPD>3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81

Increased sensitivity and variability of phytotoxicity responses in Arctic soils to a reference toxicant, boric acid.

PubMed

Anaka, Alison; Wickstrom, Mark; Siciliano, Steven Douglas

2008-03-01

Industrial and human activities in the Arctic regions may pose a risk to terrestrial Arctic ecosystem functions. One of the most common terrestrial toxicological end points, primary productivity, typically is assessed using a plant phytotoxicity test. Because of cryoturbation, a soil mixing process common in polar regions, we hypothesized that phytotoxicity test results in Arctic soils would be highly variable compared to other terrestrial ecosystems. The variability associated with phytotoxicity tests was evaluated using Environment Canada's standardized plant toxicity test in three cryoturbated soils from Canada's Arctic exposed to a reference toxicant, boric acid. Northern wheatgrass (Elymus lanceolatus) not only was more sensitive to toxicants in Arctic soils, its response to toxicants was more variable compared to that in temperate soils. The phytotoxicity of boric acid in cryosols was much greater than commonly reported in other soils, with a boric acid concentration of less than 150 microg/g soil needed to inhibit root and shoot growth by 20%. Large variability also was found in the phytotoxicity test results, with coefficients of variation for 10 samples ranging from 160 to 79%. The increased toxicity of boric acid in cryosols and variability in test response was not explained by soil properties. Based on our admittedly limited data set of three different Arctic soils, we recommend that more than 30 samples be taken from each control and potentially impacted area to accurately assess contaminant effects at sites in northern Canada. Such intensive sampling will insure that false-negative results for toxicant impacts in Arctic soils are minimized.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Simulating maize yield and biomass with spatial variability of soil field capacity

USDA-ARS?s Scientific Manuscript database

Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...

Integrating auxiliary data and geophysical techniques for the estimation of soil clay content using CHAID algorithm

NASA Astrophysics Data System (ADS)

Abbaszadeh Afshar, Farideh; Ayoubi, Shamsollah; Besalatpour, Ali Asghar; Khademi, Hossein; Castrignano, Annamaria

2016-03-01

This study was conducted to estimate soil clay content in two depths using geophysical techniques (Ground Penetration Radar-GPR and Electromagnetic Induction-EMI) and ancillary variables (remote sensing and topographic data) in an arid region of the southeastern Iran. GPR measurements were performed throughout ten transects of 100 m length with the line spacing of 10 m, and the EMI measurements were done every 10 m on the same transect in six sites. Ten soil cores were sampled randomly in each site and soil samples were taken from the depth of 0-20 and 20-40 cm, and then the clay fraction of each of sixty soil samples was measured in the laboratory. Clay content was predicted using three different sets of properties including geophysical data, ancillary data, and a combination of both as inputs to multiple linear regressions (MLR) and decision tree-based algorithm of Chi-Squared Automatic Interaction Detection (CHAID) models. The results of the CHAID and MLR models with all combined data showed that geophysical data were the most important variables for the prediction of clay content in two depths in the study area. The proposed MLR model, using the combined data, could explain only 0.44 and 0.31% of the total variability of clay content in 0-20 and 20-40 cm depths, respectively. Also, the coefficient of determination (R2) values for the clay content prediction, using the constructed CHAID model with the combined data, was 0.82 and 0.76 in 0-20 and 20-40 cm depths, respectively. CHAID models, therefore, showed a greater potential in predicting soil clay content from geophysical and ancillary data, while traditional regression methods (i.e. the MLR models) did not perform as well. Overall, the results may encourage researchers in using georeferenced GPR and EMI data as ancillary variables and CHAID algorithm to improve the estimation of soil clay content.

Predictor variable resolution governs modeled soil types

USDA-ARS?s Scientific Manuscript database

Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

Land agroecological quality assessment in conditions of high spatial soil cover variability at the Pereslavskoye Opolye.

NASA Astrophysics Data System (ADS)

Morev, Dmitriy; Vasenev, Ivan

2015-04-01

The essential spatial variability is mutual feature for most natural and man-changed soils at the Central region of European territory of Russia. The original spatial heterogeneity of forest soils has been further complicated by a specific land-use history and human impacts. For demand-driven land-use planning and decision making the quantitative analysis and agroecological interpretation of representative soil cover spatial variability is an important and challenging task that receives increasing attention from private companies, governmental and environmental bodies. Pereslavskoye Opolye is traditionally actively used in agriculture due to dominated high-quality cultivated soddy-podzoluvisols which are relatively reached in organic matter (especially for conditions of the North part at the European territory of Russia). However, the soil cover patterns are often very complicated even within the field that significantly influences on crop yield variability and have to be considered in farming system development and land agroecological quality evaluation. The detailed investigations of soil regimes and mapping of the winter rye yield have been carried in conditions of two representative fields with slopes sharply contrasted both in aspects and degrees. Rye biological productivity and weed infestation have been measured in elementary plots of 0.25 m2 with the following analysis the quality of the yield. In the same plot soil temperature and moisture have been measured by portable devices. Soil sampling was provided from three upper layers by drilling. The results of ray yield detailed mapping shown high differences both in average values and within-field variability on different slopes. In case of low-gradient slope (field 1) there is variability of ray yield from 39.4 to 44.8 dt/ha. In case of expressed slope (field 2) the same species of winter rye grown with the same technology has essentially lower yield and within-field variability from 20 to 29.6 dt/ha. The variability in crop yield between two fields is determined by their differences in mesorelief, A-horizon average thickness and slightly changes in soil temperature. The within-field crop yield variability is determined by microrelief and connected differences in soil moisture. Higher soil cover variability reflects in higher variability of winter ray yield and its quality that could be predicted and planed in conditions of concrete field and year according to principal limiting factors evaluation.

Forest thinning and soil respiration in a ponderosa pine plantation in the Sierra Nevada.

PubMed

Tang, Jianwu; Qi, Ye; Xu, Ming; Misson, Laurent; Goldstein, Allen H

2005-01-01

Soil respiration is controlled by soil temperature, soil water, fine roots, microbial activity, and soil physical and chemical properties. Forest thinning changes soil temperature, soil water content, and root density and activity, and thus changes soil respiration. We measured soil respiration monthly and soil temperature and volumetric soil water continuously in a young ponderosa pine (Pinus ponderosa Dougl. ex P. Laws. & C. Laws.) plantation in the Sierra Nevada Mountains in California from June 1998 to May 2000 (before a thinning that removed 30% of the biomass), and from May to December 2001 (after thinning). Thinning increased the spatial homogeneity of soil temperature and respiration. We conducted a multivariate analysis with two independent variables of soil temperature and water and a categorical variable representing the thinning event to simulate soil respiration and assess the effect of thinning. Thinning did not change the sensitivity of soil respiration to temperature or to water, but decreased total soil respiration by 13% at a given temperature and water content. This decrease in soil respiration was likely associated with the decrease in root density after thinning. With a model driven by continuous soil temperature and water time series, we estimated that total soil respiration was 948, 949 and 831 g C m(-2) year(-1) in the years 1999, 2000 and 2001, respectively. Although thinning reduced soil respiration at a given temperature and water content, because of natural climate variability and the thinning effect on soil temperature and water, actual cumulative soil respiration showed no clear trend following thinning. We conclude that the effect of forest thinning on soil respiration is the combined result of a decrease in root respiration, an increase in soil organic matter, and changes in soil temperature and water due to both thinning and interannual climate variability.

Measuring spatial variability in soil characteristics

DOEpatents

Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

2002-01-01

The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

Comparing soil functions for a wide range of agriculture soils focusing on production for bioenergy using a combined isotope-based observation and modelling approach

NASA Astrophysics Data System (ADS)

Leistert, Hannes; Herbstritt, Barbara; Weiler, Markus

2017-04-01

Increase crop production for bioenergy will result in changes in land use and the resulting soil functions and may generate new chances and risks. However, detailed data and information are still missing how soil function may be altered under changing crop productions for bioenergy, in particular for a wide range of agricultural soils since most data are currently derived from individual experimental sites studying different bioenergy crops at one location. We developed a new, rapid measurement approach to investigate the influence of bioenergy plants on the water cycle and different soil functions (filter and buffer of water and N-cycling). For this approach, we drilled 89 soil cores (1-3 m deep) in spring and fall at 11 sites with different soil properties and climatic conditions comparing different crops (grass, corn, willow, poplar, and other less common bioenergy crops) and analyzing 1150 soil samples for water content, nitrate concentration and stable water isotopes. We benchmarked a soil hydrological model (1-D numerical Richards equation, ADE, water isotope fractionation including liquid and vapor composition of isotopes) using longer-term climate variables and water isotopes in precipitation to derive crop specific parameterization and to specifically validate the differences in water transport and water partitioning into evaporation, transpiration and groundwater recharge among the sites and crops using the water isotopes in particular. The model simulation were in good agreement with the observed isotope profiles and allowed us to differentiate among the different crops. We defined different indicators for the soil functions considered in this study. These indicators included the proportion of groundwater recharge, transit time of water (different percentiles) though the upper 2m and nutrient leaching potential (e.g. nitrate) during the dormant season from the rooting zone. The parameterized model was first used to calculate the indicators for the sampled locations and to derive the changes in soil functions by altering the land cover among the different bioenergy crops in comparison to the grassland as a reference. We could show that percolation is strongly influenced by the crops and climate, the transit time is influenced by a combination of soil type, climate and land use, but the effect of soil type is very strong and the nitrate leaching is strongly influenced by soil type. The high variability of transit times and nitrate leaching are due to high variability of the temporal distribution of precipitation. Finally, the model was used to regionalized the indicators to a wide range of soils in the state of Baden-Württemberg and to assess if there are locations where bioenergy crops may improve the considered soil function. Our idea behind this was to propose location where specific bioenergy crops may be highly suitable to improve the current soil function to increase for example the protection of groundwater for drinking water, reduce erosion risk or increase water availability. The proposed method allows to assess the influence of different bioenergy crops on soil functions without costly multi-year measurement systems for assessing the soil functions using soil water content measurements or/and soil water suction devices.

Assessing agricultural management effects on structure related soil hydraulic properties by tension infiltrometry

NASA Astrophysics Data System (ADS)

Bodner, G.; Loiskandl, W.; Kaul, H.-P.

2009-04-01

Soil structure is a dynamic property subject to numerous natural and human influences. It is recognized as fundamental for sustainable functioning of soil. Therefore knowledge of management impacts on the sensitive structural states of soil is decisive in order to avoid soil degradation. The stabilization of the soil's (macro)pore system and eventually the improvement of its infiltrability are essential to avoid runoff and soil erosion, particularly in view of an increasing probability of intense rainfall events. However structure-related soil properties generally have a high natural spatiotemporal variability that interacts with the potential influence of agricultural land use. This complicates a clear determination of management vs. environmental effects and requires adequate measurement methods, allowing a sufficient spatiotemporal resolution to estimate the impact of the targeted management factors within the natural dynamics of soil structure. A common method to assess structure-related soil hydraulic properties is tension infiltrometry. A major advantage of tension infiltrometer measurements is that no or only minimum soil disturbance is necessary and several structure-controlled water transmission properties can readily be derived. The method is more time- and cost-efficient compared to laboratory measurements of soil hydraulic properties, thus enabling more replications. Furthermore in situ measurements of hydraulic properties generally allow a more accurate reproduction of field soil water dynamics. The present study analyses the impact of two common agricultural management options on structure related hydraulic properties based on tension infiltrometer measurements. Its focus is the identification of the role of management within the natural spatiotemporal variability, particularly in respect to seasonal temporal dynamics. Two management approaches are analysed, (i) cover cropping as a "plant-based" agro-environmental measure, and (ii) tillage with different intensities including conventional tillage with a mouldboard plough, reduced tillage with a chisel plough and no-tillage. The results showed that the plant-based management measure of cover cropping had only minor influence on near-saturated hydraulic conductivity (kh) and flow weighted mean pore radius (λm). Substantial over-winter changes were found with a significant increase in kh and a reduction in the pore radius. A spatial trend in soil texture along the cover cropped slope resulted in a higher kh at lower pressure heads at the summit with higher fractions of coarse particles, while kh tended to be highest at the toeslope towards saturation. Cover crop management accounted for a maximum of 9.7% of the total variability in kh, with a decreasing impact towards the unsaturated range. A substantial difference to bare soil in the cover cropped treatments could be identified in relation to a stabilization of macro-pores over winter. The different tillage treatments had a substantial impact on near-saturated kh and pore radius. Although conventional tillage showed the highest values in kh and λm, settling of the soil after the ploughing event tended to reduce differences over time compared to the other tillage methods. The long-term no-tillage (10 years) however had the lowest values of kh at all measurement dates. The high contents of silt and fine sand probably resulted in soil densification that was not counterbalanced sufficiently by biological structure forming agents. The study could show that soil structure related hydraulic properties are subject to a substantial seasonal variability. A comprehensive assessment of agricultural measures such as tillage or cover cropping requires an estimate of these temporal dynamics and their interaction with the management strategies. Particularly for plant-based management measures such as cover cropping, which represent a less intense intervention in the structural states of the soil compared to tillage, this was evident, as the main mechanism revealed for this measure was structure stabilization over time. While spatial variability is mostly controlled in designed experiments, the role of temporal variability is often underestimated. From our study we concluded that (i) a proper understanding of processes involved in management effects on soil structure must take into consideration the dynamic nature of the respective soil properties, (ii) experimental planning for studies regarding management impacts on soil structure should allow an estimation of temporal variability, and (iii) for this purpose tension infiltrometry provides an efficient measurement tool to assess structure related soil hydraulic properties.

Quantification of spatial distribution and spread of bacteria in soil at microscale

NASA Astrophysics Data System (ADS)

Juyal, Archana; Eickhorst, Thilo; Falconer, Ruth; Baveye, Philippe; Otten, Wilfred

2015-04-01

Soil bacteria play an essential role in functioning of ecosystems and maintaining of biogeochemical cycles. Soil is a complex heterogeneous environment comprising of highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of resident microbiota including bacteria and fungi. Bacteria occupy a very small portion of available pore space in soil which demonstrates that their spatial arrangement in soil has a huge impact on the contact to their target and on the way they interact to carry out their functions. Due to limitation of techniques, there is scant information on spatial distribution of indigenous or introduced bacteria at microhabitat scale. There is a need to understand the interaction between soil structure and microorganisms including fungi for ecosystem-level processes such as carbon sequestration and improving the predictive models for soil management. In this work, a combination of techniques was used including X-ray CT to characterize the soil structure and in-situ detection via fluorescence microscopy to visualize and quantify bacteria in soil thin sections. Pseudomonas fluorescens bacteria were introduced in sterilized soil of aggregate size 1-2 mm and packed at bulk-densities 1.3 g cm-3 and 1.5 g cm-3. A subset of samples was fixed with paraformaldehyde and subsequently impregnated with resin. DAPI and fluorescence in situ hybridization (FISH) were used to visualize bacteria in thin sections of soil cores by epifluorescence microscopy to enumerate spatial distribution of bacteria in soil. The pore geometry of soil was quantified after X-ray microtomography scanning. The distribution of bacteria introduced locally reduced significantly (P

Relevant magnetic and soil parameters as potential indicators of soil conservation status of Mediterranean agroecosystems

NASA Astrophysics Data System (ADS)

Quijano, Laura; Chaparro, Marcos A. E.; Marié, Débora C.; Gaspar, Leticia; Navas, Ana

2014-09-01

The main sources of magnetic minerals in soils unaffected by anthropogenic pollution are iron oxides and hydroxides derived from parent materials through soil formation processes. Soil magnetic minerals can be used as indicators of environmental factors including soil forming processes, degree of pedogenesis, weathering processes and biological activities. In this study measurements of magnetic susceptibility are used to detect the presence and the concentration of soil magnetic minerals in topsoil and bulk samples in a small cultivated field, which forms a hydrological unit that can be considered to be representative of the rainfed agroecosystems of Mediterranean mountain environments. Additional magnetic studies such as isothermal remanent magnetization (IRM), anhysteretic remanent magnetization (ARM) and thermomagnetic measurements are used to identify and characterize the magnetic mineralogy of soil minerals. The objectives were to analyse the spatial variability of the magnetic parameters to assess whether topographic factors, soil redistribution processes, and soil properties such as soil texture, organic matter and carbonate contents analysed in this study, are related to the spatial distribution pattern of magnetic properties. The medians of mass specific magnetic susceptibility at low frequency (χlf) were 36.0 and 31.1 × 10-8 m3 kg-1 in bulk and topsoil samples respectively. High correlation coefficients were found between the χlf in topsoil and bulk core samples (r = 0.951, p < 0.01). In addition, volumetric magnetic susceptibility was measured in situ in the field (κis) and values varied from 13.3 to 64.0 × 10-5 SI. High correlation coefficients were found between χlf in topsoil measured in the laboratory and volumetric magnetic susceptibility field measurements (r = 0.894, p < 0.01). The results obtained from magnetic studies such as IRM, ARM and thermomagnetic measurements show the presence of magnetite, which is the predominant magnetic carrier, and hematite. The predominance of superparamagnetic minerals in upper soil layers suggests enrichment in pedogenic minerals. The finer soil particles, the organic matter content and the magnetic susceptibility values are statistically correlated and their spatial variability is related to similar physical processes. Runoff redistributes soil components including magnetic minerals and exports fine particles out the field. This research contributed to further knowledge on the application of soil magnetic properties to derive useful information on soil processes in Mediterranean cultivated soils.

Lots of legacy soil data are available, but which data do we need to collect for regional land use analysis?

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2015-04-01

In the past, soil surveying techniques were mainly developed for qualitative regional land use analysis (RLUA) like land evaluation and land use planning. Conventional soil survey techniques usually describe soil types according to a soil classification scheme (e.g. Soil Taxonomy and World Reference Base). These soil surveys met the requirements of qualitative land evaluation and land use planning. However, during the last decades there is an increased need for quantitative RLUA resulting in an increased demand for quantitative soil data. The rapid developments in computing technology and the availability of auxiliary information (e.g. remote sensing and digital elevation models) allowed for the development of new soil surveying techniques like digital soil mapping. These new soil surveying techniques aim to produce continuous maps of quantitative functional soil properties. However, RLUA nowadays requires soil data that include a description of the spatial variability of the entire pedon in which correlations between soil properties are retained. Current surveying techniques do not fully fulfil these requirements resulting in a gap between the supply and demand of soil data in RLUA. The gap is caused by the fact that legacy soil data are collected for different purposes and inherently have different assumptions on e.g., soil variability. In this study, some of these assumptions are tested and verified using primary soil data collected during a recent field survey in Machakos and Makueni County (Kenya). Subsequently an ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, is taken as a case study to evaluate the effect of different sources of soil data on the results of the RLUA. The results of the study show that various assumptions underlying the soil survey hamper the quality requirements of soil data for the specific objectives of the RLUA. To give a few examples: mapping soil properties individually ignores correlations between them, soil properties differed significantly between natural and agricultural land, discrete soil mapping units described by a representative soil profile showed internal variability. None of the legacy datasets fitted the requirements of the RLUA. However, resources to collect additional primary soil data are limited. Evaluating legacy data allows us to identify the soil data that we need to collect. Legacy data lack information on e.g. soil management and effective rooting depth, while these data are often required for RLUA. This results in the use of assumptions, estimations and simplifications in a RLUA. The choice of legacy data has a profound effect on the results of a RLUA. The GYGA case study shows for example that different sources of soil input data can lead to differences in simulated water-limited maize yields of up to 3 ton/ha.

Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

NASA Astrophysics Data System (ADS)

Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

2017-04-01

Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP) statistics was used to quantitatively assess the predictors most relevant for response variable estimation and then for variable selection (Andersen and Bro, 2010). PCA and SDA returned TOC and RFC as influential variables both on the set of chemical and physical data analyzed separately as well as on the whole dataset (Stellacci et al., 2016). Highly weighted variables in PCA were also TEC, followed by K, and AC, followed by Pmac and BD, in the first PC (41.2% of total variance); Olsen P and HA-FA in the second PC (12.6%), Ca in the third (10.6%) component. Variables enabling maximum discrimination among treatments for SDA were WEOC, on the whole dataset, humic substances, followed by Olsen P, EC and clay, in the separate data analyses. The highest PLS-VIP statistics were recorded for Olsen P and Pmac, followed by TOC, TEC, pH and Mg for chemical variables and clay, RFC and AC for the physical variables. Results show that different methods may provide different ranking of the selected variables and the presence of a response variable, in regressive techniques, may affect variable selection. Further investigation with different response variables and with multi-year datasets would allow to better define advantages and limits of single or combined approaches. Acknowledgment The work was supported by the projects "BIOTILLAGE, approcci innovative per il miglioramento delle performances ambientali e produttive dei sistemi cerealicoli no-tillage", financed by PSR-Basilicata 2007-2013, and "DESERT, Low-cost water desalination and sensor technology compact module" financed by ERANET-WATERWORKS 2014. References Andersen C.M. and Bro R., 2010. Variable selection in regression - a tutorial. Journal of Chemometrics, 24 728-737. Armenise et al., 2013. Developing a soil quality index to compare soil fitness for agricultural use under different managements in the mediterranean environment. Soil and Tillage Research, 130:91-98. de Paul Obade et al., 2016. A standardized soil quality index for diverse field conditions. Sci. Total Env. 541:424-434. Pulido Moncada et al., 2014. Data-driven analysis of soil quality indicators using limited data. Geoderma, 235:271-278. Stellacci et al., 2016. Comparison of different multivariate methods to select key soil variables for soil quality indices computation. XLV Congress of the Italian Society of Agronomy (SIA), Sassari, 20-22 September 2016.

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane

2007-01-01

The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less

Multiple indices of soil nitrogen status and temperature regulate microbial C allocation to CO2, substrate choices, and contributions to SOM

NASA Astrophysics Data System (ADS)

Billings, S. A.; Ziegler, S. E.

2012-12-01

The response of microbial resource demand to many environmental variables, including temperature and natural organic and inorganic N variability, remains poorly understood. Furthermore, we do not understand how these variables can influence CO2 release vs. C retention in cell walls, which as microbial necromass can generate long-lived soil organic matter (SOM). We explore microbial resource demand and C retention vs. release in one temperate forest and two boreal forests along a climate gradient. We characterized SOM C:N and inorganic N, extracellular enzyme activity (E), and phospholipid fatty acid (PLFA) concentration and δ13C. Experimental warming permitted us to assess how interactions between soil N status and warming influence resource demand and C flows through microbes in the two boreal soils. For all soils, we used δ13C of respired CO2 and δ13CPLFA to generate indices of C allocation to biomass vs. to respiratory costs (Δ), useful for cross-site comparisons. Decreasing values of Δ indicate a greater proportion of 13C-enriched C allocated to respiration relative to PLFA-C; changes in Δ with warming or N status thus imply that these variables can influence the physiological mechanisms determining the fate of microbial C after it is imported into the cell. We thus were able to assess the influence of soil N status and warming on substrate decay via E, the fate of microbial C from diverse substrates via Δ, and one index of microbial composition relevant to SOM formation [PLFA]. In all soils, E often varied with N status in ways predicted by stoichiometric theory. For example, the ratio of exo-enzymes associated with labile C decay to those linked to organic N decay (EC:N) increased with inorganic N, and EC:N declined as substrate C:N increased. In contrast to measures of decay, all soils exhibited distinct responses of microbial composition and C allocation to N status and warming. In the temperate forest soils, Gram+ bacteria responded positively to organic N availability and Gram- bacteria to inorganic N, while fungi responded positively to declines in both measures of soil N status. In the more northern boreal soils, actinomycete [PLFA] increased with inorganic N, while that of more southern boreal soils increased with substrate C:N; in both boreal soils, Gram+ bacteria increased with temperature. Given that cell walls of these microbes exhibit distinct propensities for forming long-lived SOM, our work illustrates how similar variation in N status and temperature can drive divergent patterns of biomass relevant to SOM formation. Sensitivity of patterns of C allocation to these variables also contrasted between these soils. In the temperate soils, Δ did not vary with soil N status nor with E, implying that microbes' C allocation patterns were not driven N status or by the C's organic precursor. In both boreal soils, Δ declined with warming, and as EC or EC:N increased. Though N status of the boreal soils drove resource demand similarly as in the temperate forest, the fate of boreal microbial C varied with N status and temperature. Because microbial C substrate use varied with warming in the boreal soils, Δ highlights how the fate of microbial C may vary with the identity of its organic precursor, which in turn is influenced by environmental conditions like temperature and soil N status.

Selection of Optimal Auxiliary Soil Nutrient Variables for Cokriging Interpolation

PubMed Central

Song, Genxin; Zhang, Jing; Wang, Ke

2014-01-01

In order to explore the selection of the best auxiliary variables (BAVs) when using the Cokriging method for soil attribute interpolation, this paper investigated the selection of BAVs from terrain parameters, soil trace elements, and soil nutrient attributes when applying Cokriging interpolation to soil nutrients (organic matter, total N, available P, and available K). In total, 670 soil samples were collected in Fuyang, and the nutrient and trace element attributes of the soil samples were determined. Based on the spatial autocorrelation of soil attributes, the Digital Elevation Model (DEM) data for Fuyang was combined to explore the coordinate relationship among terrain parameters, trace elements, and soil nutrient attributes. Variables with a high correlation to soil nutrient attributes were selected as BAVs for Cokriging interpolation of soil nutrients, and variables with poor correlation were selected as poor auxiliary variables (PAVs). The results of Cokriging interpolations using BAVs and PAVs were then compared. The results indicated that Cokriging interpolation with BAVs yielded more accurate results than Cokriging interpolation with PAVs (the mean absolute error of BAV interpolation results for organic matter, total N, available P, and available K were 0.020, 0.002, 7.616, and 12.4702, respectively, and the mean absolute error of PAV interpolation results were 0.052, 0.037, 15.619, and 0.037, respectively). The results indicated that Cokriging interpolation with BAVs can significantly improve the accuracy of Cokriging interpolation for soil nutrient attributes. This study provides meaningful guidance and reference for the selection of auxiliary parameters for the application of Cokriging interpolation to soil nutrient attributes. PMID:24927129

Fatty acid methyl ester analysis to identify sources of soil in surface water.

PubMed

Banowetz, Gary M; Whittaker, Gerald W; Dierksen, Karen P; Azevedo, Mark D; Kennedy, Ann C; Griffith, Stephen M; Steiner, Jeffrey J

2006-01-01

Efforts to improve land-use practices to prevent contamination of surface waters with soil are limited by an inability to identify the primary sources of soil present in these waters. We evaluated the utility of fatty acid methyl ester (FAME) profiles of dry reference soils for multivariate statistical classification of soils collected from surface waters adjacent to agricultural production fields and a wooded riparian zone. Trials that compared approaches to concentrate soil from surface water showed that aluminum sulfate precipitation provided comparable yields to that obtained by vacuum filtration and was more suitable for handling large numbers of samples. Fatty acid methyl ester profiles were developed from reference soils collected from contrasting land uses in different seasons to determine whether specific fatty acids would consistently serve as variables in multivariate statistical analyses to permit reliable classification of soils. We used a Bayesian method and an independent iterative process to select appropriate fatty acids and found that variable selection was strongly impacted by the season during which soil was collected. The apparent seasonal variation in the occurrence of marker fatty acids in FAME profiles from reference soils prevented preparation of a standardized set of variables. Nevertheless, accurate classification of soil in surface water was achieved utilizing fatty acid variables identified in seasonally matched reference soils. Correlation analysis of entire chromatograms and subsequent discriminant analyses utilizing a restricted number of fatty acid variables showed that FAME profiles of soils exposed to the aquatic environment still had utility for classification at least 1 wk after submersion.

Environmental stochasticity controls soil erosion variability

PubMed Central

Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone

2016-01-01

Understanding soil erosion by water is essential for a range of research areas but the predictive skill of prognostic models has been repeatedly questioned because of scale limitations of empirical data and the high variability of soil loss across space and time scales. Improved understanding of the underlying processes and their interactions are needed to infer scaling properties of soil loss and better inform predictive methods. This study uses data from multiple environments to highlight temporal-scale dependency of soil loss: erosion variability decreases at larger scales but the reduction rate varies with environment. The reduction of variability of the geomorphic response is attributed to a ‘compensation effect’: temporal alternation of events that exhibit either source-limited or transport-limited regimes. The rate of reduction is related to environment stochasticity and a novel index is derived to reflect the level of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (enhanced predictability at the aggregated temporal scales) with respect to the mean hydrologic forcing, offering a promising indicator for estimating the degree of uncertainty of erosion assessments. PMID:26925542

The Past, Present, and Future of Soils and Human Health Studies

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Sauer, T. J.

2012-04-01

The idea that human health is tied to the soil is not a new one. As far back as approximately 1400 B.C. the Bible depicts Moses as understanding that fertile soil was essential to the well-being of his people. While exploring Canaan, Moses charged the men he sent to evaluate the fertility of the soil. In 400 B.C. the Greek philosopher Hippocrates provided a list of things that should be considered in a proper medical evaluation, including the ground. By the late 1700 and early 1800s, American farmers had recognized that soil properties had some connection to human health. In "Letters from an American Farmer", published in 1792, J. Hector St. John De Crèvecoeur stated "Men are like plants; the goodness and flavor of the fruit proceeds from the peculiar soil and exposition in which they grow". And in "Larding the Lean Earth", published in 2002, S. Stoll noted that North American farmers in the early 1800s recognized a link between an enduring agriculture and an enduring society, leading them to become concerned about the fertility of their soils and to seek ways of improving the soil in order to insure a healthy society. Continuing into the first half of the 20th Century, a 1940 publication by the International Harvester Company noted that poor soils lead to "stoop-shouldered, poverty-stricken people." Then, in 1947, Sir Albert Howard published his landmark work "The Soil and Health: A Study of Organic Agriculture", a work that took a critical look at modern production agriculture and at the link between soil fertility and health. Despite these various lines of evidence of some earlier level of understanding that healthy soils are required for healthy people, the scientific study of the relationship between soils and human health is a fairly new undertaking. In his 1997 work "Soil and Human Health: A Review", M.A. Oliver states "… there is a dearth of quantitative information on the relations between elements in the soil and human health;…there is much speculation and anecdotal evidence." So, the scientific study of soils and human health is a recent undertaking, but the idea that healthy soils are required for healthy people is not a particularly new one. In the modern world, we recognize that soils have a distinct influence on human health. We recognize that soils influence 1) food availability and quality (food security), 2) human contact with various chemicals, and 3) human contact with various pathogens. Soils and human health studies include investigations into nutrient supply through the food web and routes of exposure to chemicals and pathogens. However, making strong, scientific connections between soils and human health can be difficult. There are multiple variables to consider in the soil environment, meaning traditional scientific studies that seek to isolate and manipulate a single variable often do not provide meaningful data. The complete study of soils and human health also involves many different specialties such as soil scientists, toxicologists, medical professionals, anthropologists, etc. These groups do not traditionally work together on research projects, and do not always effectively communicate with one another. Climate change and how it will affect the soil environment/ecosystem going into the future is another variable we need to get a better understanding of. Future successes in soils and human health research will require effectively addressing difficult issues such as these.

Informing soil models using pedotransfer functions: challenges and perspectives

NASA Astrophysics Data System (ADS)

Pachepsky, Yakov; Romano, Nunzio

2015-04-01

Pedotransfer functions (PTFs) are empirical relationships between parameters of soil models and more easily obtainable data on soil properties. PTFs have become an indispensable tool in modeling soil processes. As alternative methods to direct measurements, they bridge the data we have and data we need by using soil survey and monitoring data to enable modeling for real-world applications. Pedotransfer is extensively used in soil models addressing the most pressing environmental issues. The following is an attempt to provoke a discussion by listing current issues that are faced by PTF development. 1. As more intricate biogeochemical processes are being modeled, development of PTFs for parameters of those processes becomes essential. 2. Since the equations to express PTF relationships are essentially unknown, there has been a trend to employ highly nonlinear equations, e.g. neural networks, which in theory are flexible enough to simulate any dependence. This, however, comes with the penalty of large number of coefficients that are difficult to estimate reliably. A preliminary classification applied to PTF inputs and PTF development for each of the resulting groups may provide simple, transparent, and more reliable pedotransfer equations. 3. The multiplicity of models, i.e. presence of several models producing the same output variables, is commonly found in soil modeling, and is a typical feature in the PTF research field. However, PTF intercomparisons are lagging behind PTF development. This is aggravated by the fact that coefficients of PTF based on machine-learning methods are usually not reported. 4. The existence of PTFs is the result of some soil processes. Using models of those processes to generate PTFs, and more general, developing physics-based PTFs remains to be explored. 5. Estimating the variability of soil model parameters becomes increasingly important, as the newer modeling technologies such as data assimilation, ensemble modeling, and model abstraction, become progressively more popular. The variability PTFs rely on the spatio-temporal dynamics of soil variables, and that opens new sources of PTF inputs stemming from technology advances such as monitoring networks, remote and proximal sensing, and omics. 6. Burgeoning PTF development has not so far affected several persisting regional knowledge gaps. Remarkably little effort was put so far into PTF development for saline soils, calcareous and gypsiferous soils, peat soils, paddy soils, soils with well expressed shrink-swell behavior, and soils affected by freeze-thaw cycles. 7. Soils from tropical regions are quite often considered as a pseudo-entity for which a single PTF can be applied. This assumption will not be needed as more regional data will be accumulated and analyzed. 8. Other advances in regional PTFs will be possible due to presence of large databases on region-specific useful PTF inputs such as moisture equivalent, laser diffractometry data, or soil specific surface. 9. Most of flux models in soils, be it water, solutes, gas, or heat, involve parameters that are scale-dependent. Including scale dependencies in PTFs will be critical to improve PTF usability. 10. Another scale-related matter is pedotransfer for coarse-scale soil modeling, for example, in weather or climate models. Soil hydraulic parameters in these models cannot be measured and the efficiency of the pedotransfer can be evaluated only in terms of its utility. There is a pressing need to determine combinations of pedotransfer and upscaling procedures that can lead to the derivation of suitable coarse-scale soil model parameters. 11. The spatial coarse scale often assumes a coarse temporal support, and that may lead to including in PTFs other environmental variables such as topographic, weather, and management attributes. 12. Some PTF inputs are time- or space-dependent, and yet little is known whether the spatial or temporal structure of PTF outputs is properly predicted from such inputs 13. Further exploration is needed to use PTF as a source of hypotheses on and insights into relationships between soil processes and soil composition as well as between soil structure and soil functioning. PTFs are empirical relationships and their accuracy outside the database used for the PTF development is essentially unknown. Therefore they should never be considered as an ultimate source of parameters in soil modeling. Rather they strive to provide a balance between accuracy and availability. The primary role of PTF is to assist in modeling for screening and comparative purposes, establishing ranges and/or probability distributions of model parameters, and creating realistic synthetic soil datasets and scenarios. Developing and improving PTFs will remain the mainstream way of packaging data and knowledge for applications of soil modeling.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

[Correlation between soil-transmitted nematode infections and children's growth].

PubMed

Wang, Xiao-Bing; Wang, Guo-Fei; Zhang, Lin-Xiu; Luo, Ren-Fu; Wang, Ju-Jun; Medina, Alexis; Eggleston, Karen; Rozelle, Scott; Smith, Scott

2013-06-01

To understand the infection status of soil-transmitted nematodes in southwest China and the correlation between soil-transmitted nematode infections and children's growth. The prevalence of soil-transmitted nematode infections was determined by Kato-Katz technique, and in part of the children, the examination of Enterobius vermicularis eggs was performed by using the cellophane swab method. The influencing factors were surveyed by using a standardized questionnaire. The relationship between soil-transmitted nematode infections and children's growth was analyzed by the ordinary least square (OLS) method. A total of 1 707 children were examined, with a soil-transmitted nematode infection rate of 22.2%. The results of OLS analysis showed that there existed the negative correlation between soil-transmitted nematode infections and the indexes of children's growth including BMI, the weight-for-age Z score and height-for-age Z score. Furthermore, other correlated variables included the age, gender, educational level of mother and raising livestock and poultry, etc. Children' s retardation is still a serious issue in the southwest poor areas of China and correlated with the infections of soil-transmitted nematodes. For improving children's growth, it is greatly significant to enhance the deworming and health education about parasitic diseases in mothers.

Searching for biogeochemical hot spots in three dimensions: Soil C and N cycling in hydropedologic settings in a northern hardwood forest

NASA Astrophysics Data System (ADS)

Morse, J. L.; Werner, S. F.; Gillin, C. P.; Goodale, C. L.; Bailey, S. W.; McGuire, K. J.; Groffman, P. M.

2014-08-01

Understanding and predicting the extent, location, and function of biogeochemical hot spots at the watershed scale is a frontier in environmental science. We applied a hydropedologic approach to identify (1) biogeochemical differences among morphologically distinct hydropedologic settings and (2) hot spots of microbial carbon (C) and nitrogen (N) cycling activity in a northern hardwood forest in Hubbard Brook Experimental Forest, New Hampshire, USA. We assessed variables related to C and N cycling in spodic hydropedologic settings (typical podzols, bimodal podzols, and Bh podzols) and groundwater seeps during August 2010. We found that soil horizons (Oi/Oe, Oa/A, and B) differed significantly for most variables. B horizons (>10 cm) accounted for 71% (±11%) of C pools and 62% (±10%) of microbial biomass C in the sampled soil profile, whereas the surface horizons (Oi/Oe and Oa/A; 0-10 cm) were dominant zones for N-cycle-related variables. Watershed-wide estimates of C and N cycling were higher by 34 to 43% (±17-19%) when rates, horizon thickness, and areal extent of each hydropedologic setting were incorporated, versus conventionally calculated estimates for typical podzols that included only the top 10 cm of mineral soil. Despite the variation in profile development in typical, bimodal, and Bh podzols, we did not detect significant differences in C and N cycling among them. Across all soil horizons and hydropedologic settings, we found strong links between biogeochemical cycling and soil C, suggesting that the accumulation of C in soils may be a robust indicator of microbial C and N cycling capacity in the landscape.

A structural equation model of soil metal bioavailability to earthworms: confronting causal theory and observations using a laboratory exposure to field-contaminated soils.

PubMed

Beaumelle, Léa; Vile, Denis; Lamy, Isabelle; Vandenbulcke, Franck; Gimbert, Frédéric; Hedde, Mickaël

2016-11-01

Structural equation models (SEM) are increasingly used in ecology as multivariate analysis that can represent theoretical variables and address complex sets of hypotheses. Here we demonstrate the interest of SEM in ecotoxicology, more precisely to test the three-step concept of metal bioavailability to earthworms. The SEM modeled the three-step causal chain between environmental availability, environmental bioavailability and toxicological bioavailability. In the model, each step is an unmeasured (latent) variable reflected by several observed variables. In an exposure experiment designed specifically to test this SEM for Cd, Pb and Zn, Aporrectodea caliginosa was exposed to 31 agricultural field-contaminated soils. Chemical and biological measurements used included CaC12-extractable metal concentrations in soils, free ion concentration in soil solution as predicted by a geochemical model, dissolved metal concentration as predicted by a semi-mechanistic model, internal metal concentrations in total earthworms and in subcellular fractions, and several biomarkers. The observations verified the causal definition of Cd and Pb bioavailability in the SEM, but not for Zn. Several indicators consistently reflected the hypothetical causal definition and could thus be pertinent measurements of Cd and Pb bioavailability to earthworm in field-contaminated soils. SEM highlights that the metals present in the soil solution and easily extractable are not the main source of available metals for earthworms. This study further highlights SEM as a powerful tool that can handle natural ecosystem complexity, thus participating to the paradigm change in ecotoxicology from a bottom-up to a top-down approach. Copyright © 2016 Elsevier B.V. All rights reserved.

Soil-Water Balance (SWB) model estimates of soil-moisture variability and groundwater recharge in the South Platte watershed, Colorado

NASA Astrophysics Data System (ADS)

Anderson, A. M.; Walker, E. L.; Hogue, T. S.; Ruybal, C. J.

2015-12-01

Unconventional energy production in semi-arid regions places additional stress on already over-allocated water systems. Production of shale gas and oil resources in northern Colorado has rapidly increased since 2010, and is expected to continue growing due to advances in horizontal drilling and hydraulic fracturing. This unconventional energy production has implications for the availability of water in the South Platte watershed, where water demand for hydraulic fracturing of unconventional shale resources reached ~16,000 acre-feet in 2014. Groundwater resources are often exploited to meet water demands for unconventional energy production in regions like the South Platte basin, where surface water supply is limited and allocated across multiple uses. Since groundwater is often a supplement to surface water in times of drought and peak demand, variability in modeled recharge estimates can significantly impact projected availability. In the current work we used the Soil-Water Balance Model (SWB) to assess the variability in model estimates of actual evapotranspiration (ET) and soil-moisture conditions utilized to derive estimates of groundwater recharge. Using both point source and spatially distributed data, we compared modeled actual ET and soil-moisture derived from several potential ET methods, such as Thornthwaite-Mather, Jense-Haise, Turc, and Hargreaves-Samani, to historic soil moisture conditions obtained through sources including the Gravity Recovery and Climate Experiment (GRACE). In addition to a basin-scale analysis, we divided the South Platte watershed into sub-basins according to land cover to evaluate model capabilities of estimating soil-moisture parameters with variations in land cover and topography. Results ultimately allow improved prediction of groundwater recharge under future scenarios of climate and land cover change. This work also contributes to complementary subsurface groundwater modeling and decision support modeling in the South Platte.

Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

NASA Astrophysics Data System (ADS)

Wang, Qiufeng; Tian, Jing; Yu, Guirui

2014-05-01

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

Variations in soil detachment rates after wildfire as a function of soil depth, flow properties, and root properties

USGS Publications Warehouse

Moody, John A.; Nyman, Peter

2013-01-01

Wildfire affects hillslope erosion through increased surface runoff and increased sediment availability, both of which contribute to large post-fire erosion events. Relations between soil detachment rate, soil depth, flow and root properties, and fire impacts are poorly understood and not represented explicitly in commonly used post-fire erosion models. Detachment rates were measured on intact soil cores using a modified tilting flume. The cores were mounted flush with the flume-bed and a measurement was made on the surface of the core. The core was extruded upward, cut off, and another measurement was repeated at a different depth below the original surface of the core. Intact cores were collected from one site burned by the 2010 Fourmile Canyon (FMC) fire in Colorado and from one site burned by the 2010 Pozo fire in California. Each site contained contrasting vegetation and soil types. Additional soil samples were collected alongside the intact cores and were analyzed in the laboratory for soil properties (organic matter, bulk density, particle-size distribution) and for root properties (root density and root-length density). Particle-size distribution and root properties were different between sites, but sites were similar in terms of bulk density and organic matter. Soil detachment rates had similar relations with non-uniform shear stress and non-uniform unit stream power. Detachment rates within single sampling units displayed a relatively weak and inconsistent relation to flow variables. When averaged across all clusters, the detachment rate displayed a linear relation to shear stress, but variability in soil properties meant that the shear stress accounted for only a small proportion of the overall variability in detachment rates (R2 = 0.23; R2 is the coefficient of determination). Detachment rate was related to root-length density in some clusters (R2 values up to 0.91) and unrelated in others (R2 values 2 value improved and the range of exponents became narrower by applying a multivariate regression model where boundary shear stress and root-length density were included as explanatory variables. This suggests that an erodibility parameter which incorporates the effects of both flow and root properties on detachment could improve the representation of sediment availability after wildfire.

Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

NASA Astrophysics Data System (ADS)

Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

2001-08-01

An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

CO2 Flux From Antarctic Dry Valley Soils: Determining the Source and Environmental Controls

NASA Astrophysics Data System (ADS)

Risk, D. A.; Macintyre, C. M.; Shanhun, F.; Almond, P. C.; Lee, C.; Cary, C.

2014-12-01

Soils within the McMurdo Dry Valleys are known to respire carbon dioxide (CO2), but considerable debate surrounds the contributing sources and mechanisms that drive temporal variability. While some of the CO2 is of biological origin, other known contributors to variability include geochemical sources within, or beneath, the soil column. The relative contribution from each of these sources will depend on seasonal and environmental drivers such as temperature and wind that exert influence on temporal dynamics. To supplement a long term CO2­ surface flux monitoring station that has now recorded fluxes over three full annual cycles, in January 2014 an automated flux and depth concentration monitoring system was installed in the Spaulding Pond area of Taylor Valley, along with standard meteorological sensors, to assist in defining source contributions through time. During two weeks of data we observed marked diel variability in CO2 concentrations within the profile (~100 ppm CO2 above or below atmospheric), and of CO2 moving across the soil surface. The pattern at many depths suggested an alternating diel-scale transition from source to sink that seemed clearly correlated with temperature-driven changes in the solubility of CO2 in water films. This CO2 solution storage flux was very highly coupled to soil temperature. A small depth source of unknown origin also appeared to be present. A controlled laboratory soil experiment was conducted to confirm the magnitude of fluxes into and out of soil water films, and confirmed the field results and temperature dependence. Ultimately, this solution storage flux needs to be well understood if the small biological fluxes from these soils are to be properly quantified and monitored for change. Here, we present results from the 2013/2014 field season and these supplementary experiments, placed in the context of 3 year long term continuous measurement of soil CO2 flux within the Dry Valleys.

Forty years experience in developing and using rainfall simulators under tropical and Mediterranean conditions

NASA Astrophysics Data System (ADS)

Pla-Sentís, Ildefonso; Nacci, Silvana

2010-05-01

Rainfall simulation has been used as a practical tool for evaluating the interaction of falling water drops on the soil surface, to measure both stability of soil aggregates to drop impact and water infiltration rates. In both cases it is tried to simulate the effects of natural rainfall, which usually occurs at very different, variable and erratic rates and intensities. One of the main arguments against the use of rainfall simulators is the difficulty to reproduce the size, final velocity and kinetic energy of the drops in natural rainfall. Since the early 70´s we have been developing and using different kinds of rainfall simulators, both at laboratory and field levels, and under tropical and Mediterranean soil and climate conditions, in flat and sloping lands. They have been mainly used to evaluate the relative effects of different land use and management, including different cropping systems, tillage practices, surface soil conditioning, surface covers, etc. on soil water infiltration, on runoff and on erosion. Our experience is that in any case it is impossible to reproduce the variable size distribution and terminal velocity of raindrops, and the variable changes in intensity of natural storms, under a particular climate condition. In spite of this, with the use of rainfall simulators it is possible to obtain very good information, which if it is properly interpreted in relation to each particular condition (land and crop management, rainfall characteristics, measurement conditions, etc.) may be used as one of the parameters for deducing and modelling soil water balance and soil moisture regime under different land use and management and variable climate conditions. Due to the possibility for a better control of the intensity of simulated rainfall and of the size of water drops, and the possibility to make more repeated measurements under very variable soil and land conditions, both in the laboratory and specially in the field, the better results have been obtained with small size 500-1000 cm2, easily dismantled, drop former simulators, than with larger, nozzle, or more sophisticated equipments. In this contribution there are presented some of the rainfall simulators developed and used by the main author, and some of the results obtained in different studies of practical problems under tropical and Mediterranean conditions. References Pla, I.,G.Campero, y R.Useche.1974.Physical degradación of agricultural soils in the Western Plains of Venezuela. "Trans.10th Int.Cong.Soil.Sci.Soc". 1:231-240. .Moscú Pla, I. 1975.Effects of bitumen emulsion and polyacrilamide on some physical properties of Venezuelan soils. En "Soil Sci. Soc. Am. Special Publication"• 7. 35-46. Madison. Wisconsin . (USA). Pla, I. 1977.Aggregate size and erosion control on sloping land treated with hydrophobic bitumen emulsion."Soil Conservation and Management in the Humid Tropics".109-115. John Wiley & Sons. Pla, I.1981.Simuladores de lluvia para el estudio de relaciones suelo-agua bajo agricultura de secano en los trópicos. Rev. Fac. Agron. XII(1-2):81-93.Maracay (Venezuela) Pla, I. 1986.A routine laboratory index to predict the effects of soil sealing on soil and water conservation. En "Assesment of Soil Surface Sealing and Crusting". 154-162.State Univ. of Ghent.Gante (Bélgica Pla, I., M.C. Ramos, S. Nacci, F. Fonseca y X. Abreu. 2005. Soil moisture regime in dryland vineyards of Catalunya (Spain) as influenced by climate, soil and land management. "Integrated Soil and Water Management for Orchard Development". FAO Land and Water Bulletin 10. 41-49. Roma (Italia).

Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Cao, W.; Sheng, Y.

2017-12-01

The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions. It is very critical to protect the alpine ecology and hydrologic cycle in Qinghai-Tibet Plateau. Especially, it becomes one of the key problems to reveal the spatial-temporal variability of soil moisture movement and its main influence factors in earth system science. Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study. The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree (CART) is adopted to identify the main controlling factors influencing the soil moisture movement. And the relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis (CCA). The results show that: 1) the change of the soil moisture on the permafrost slope is divided into 4 stages, including the freezing stability phase, the rapid thawing phase, the thawing stability phase and the fast freezing phase; 2) this greatly enhances the horizontal flow in the freezing period due to the terrain slope and the freezing-thawing process. Vertical migration is the mainly form of the soil moisture movement. It leads to that the soil-moisture content in the up-slope is higher than that in the down-slope. On the contrary, the soil-moisture content in the up-slope is lower than that in the down-slope during the melting period; 3) the main environmental factors which affect the slope-permafrost soil-moisture are elevation, soil texture, soil temperature and vegetation coverage. But there are differences in the impact factors of the soil moisture in different freezing-thawing stages; 4) the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20cm are slope, elevation and vegetation coverage. And the main factors influencing the soil moisture at the middle and lower depth are complex.

Spatiotemporal Variability of Soil Hydraulic Properties from Field Data and Remote Sensing in the Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Becker, R.; Gebremichael, M.; Marker, M.

2015-12-01

Soil moisture is one of the main input variables for hydrological models. However due to the high spatial and temporal variability of soil properties it is often difficult to obtain accurate soil information at the required resolution. The new satellite SMAP promises to deliver soil moisture information at higher resolutions and could therefore improve the results of hydrological models. Nevertheless it still has to be investigated how precisely the SMAP soil moisture data can be used to delineate rainfall-runoff generation processes and if SMAP imagery can significantly improve the results of surface runoff models. Important parameters to understand the spatiotemporal distribution of soil humidity are infiltration and hydraulic conductivities apart from soil texture and macrostructure. During the SMAPVEX15-field campaign data on hydraulic conductivity and infiltration rates is collected in the Walnut Gulch Experimental Watershed (WGEW) in Southeastern Arizona in order to analyze the spatiotemporal variability of soil hydraulic properties. A Compact Constant Head Permeameter is used for in situ measurements of saturated hydraulic conductivity within the soil layers and a Hood Infiltrometer is used to determine infiltration rates at the undisturbed soil surface. Sampling sites were adjacent to the USDA-ARS meteorological and soil moisture measuring sites in the WGEW to take advantage of the long-term database of soil and climate data. Furthermore a sample plot of 3x3km was selected, where the spatial variability of soil hydraulic properties within a SMAP footprint was investigated. The results of the ground measurement based analysis are then compared with the remote sensing data derived from SMAP and aircraft-based microwave data to determine how well these spatiotemporal variations are captured by the remotely sensed data with the final goal of evaluating the use of future satellite soil moisture products for the improvement of rainfall runoff models. The results reveal several interesting features on the spatiotemporal variability of soil moisture at multiple scales, and the capabilities and limitations of remote sensing derived products in reproducing them.

Linking crop structure, throughfall, soil surface conditions, runoff and soil detachment: 10 land uses analyzed in Northern Laos.

PubMed

Lacombe, Guillaume; Valentin, Christian; Sounyafong, Phabvilay; de Rouw, Anneke; Soulileuth, Bounsamai; Silvera, Norbert; Pierret, Alain; Sengtaheuanghoung, Oloth; Ribolzi, Olivier

2018-03-01

In Montane Southeast Asia, deforestation and unsuitable combinations of crops and agricultural practices degrade soils at an unprecedented rate. Typically, smallholder farmers gain income from "available" land by replacing fallow or secondary forest by perennial crops. We aimed to understand how these practices increase or reduce soil erosion. Ten land uses were monitored in Northern Laos during the 2015 monsoon, using local farmers' fields. Experiments included plots of the conventional system (food crops and fallow), and land uses corresponding to new market opportunities (e.g. commercial tree plantations). Land uses were characterized by measuring plant cover and plant mean height per vegetation layer. Recorded meteorological variables included rainfall intensity, throughfall amount, throughfall kinetic energy (TKE), and raindrop size. Runoff coefficient, soil loss, and the percentage areas of soil surface types (free aggregates and gravel; crusts; macro-faunal, vegetal and pedestal features; plant litter) were derived from observations and measurements in 1-m 2 micro-plots. Relationships between these variables were explored with multiple regression analyses. Our results indicate that TKE induces soil crusting and soil loss. By reducing rainfall infiltration, crusted area enhances runoff, which removes and transports soil particles detached by splash over non-crusted areas. TKE is lower under land uses reducing the velocity of raindrops and/or preventing an increase in their size. Optimal vegetation structures combine minimum height of the lowest layer (to reduce drop velocity at ground level) and maximum coverage (to intercept the largest amount of rainfall), as exemplified by broom grass (Thysanolaena latifolia). In contrast, high canopies with large leaves will increase TKE by enlarging raindrops, as exemplified by teak trees (Tectona grandis), unless a protective understorey exists under the trees. Policies that ban the burning of multi-layered vegetation structure under tree plantations should be enforced. Shade-tolerant shrubs and grasses with potential economic return could be promoted as understorey. Copyright © 2017 Elsevier B.V. All rights reserved.

Environmental and physical controls on northern terrestrial methane emissions across permafrost zones

USGS Publications Warehouse

Olefeldt, David; Turetsky, Merritt R.; Crill, Patrick M.; McGuire, A. David

2013-01-01

Methane (CH4) emissions from the northern high-latitude region represent potentially significant biogeochemical feedbacks to the climate system. We compiled a database of growing-season CH4 emissions from terrestrial ecosystems located across permafrost zones, including 303 sites described in 65 studies. Data on environmental and physical variables, including permafrost conditions, were used to assess controls on CH4 emissions. Water table position, soil temperature, and vegetation composition strongly influenced emissions and had interacting effects. Sites with a dense sedge cover had higher emissions than other sites at comparable water table positions, and this was an effect that was more pronounced at low soil temperatures. Sensitivity analysis suggested that CH4 emissions from ecosystems where the water table on average is at or above the soil surface (wet tundra, fen underlain by permafrost, and littoral ecosystems) are more sensitive to variability in soil temperature than drier ecosystems (palsa dry tundra, bog, and fen), whereas the latter ecosystems conversely are relatively more sensitive to changes of the water table position. Sites with near-surface permafrost had lower CH4 fluxes than sites without permafrost at comparable water table positions, a difference that was explained by lower soil temperatures. Neither the active layer depth nor the organic soil layer depth was related to CH4 emissions. Permafrost thaw in lowland regions is often associated with increased soil moisture, higher soil temperatures, and increased sedge cover. In our database, lowland thermokarst sites generally had higher emissions than adjacent sites with intact permafrost, but emissions from thermokarst sites were not statistically higher than emissions from permafrost-free sites with comparable environmental conditions. Overall, these results suggest that future changes to terrestrial high-latitude CH4 emissions will be more proximately related to changes in moisture, soil temperature, and vegetation composition than to increased availability of organic matter following permafrost thaw.

Development of Tier 1 screening tool for soil and groundwater vulnerability assessment in Korea using classification algorithm in a neural network

NASA Astrophysics Data System (ADS)

Shin, K. H.; Kim, K. H.; Ki, S. J.; Lee, H. G.

2017-12-01

The vulnerability assessment tool at a Tier 1 level, although not often used for regulatory purposes, helps establish pollution prevention and management strategies in the areas of potential environmental concern such as soil and ground water. In this study, the Neural Network Pattern Recognition Tool embedded in MATLAB was used to allow the initial screening of soil and groundwater pollution based on data compiled across about 1000 previously contaminated sites in Korea. The input variables included a series of parameters which were tightly related to downward movement of water and contaminants through soil and ground water, whereas multiple classes were assigned to the sum of concentrations of major pollutants detected. Results showed that in accordance with diverse pollution indices for soil and ground water, pollution levels in both media were strongly modulated by site-specific characteristics such as intrinsic soil and other geologic properties, in addition to pollution sources and rainfall. However, classification accuracy was very sensitive to the number of classes defined as well as the types of the variables incorporated, requiring careful selection of input variables and output categories. Therefore, we believe that the proposed methodology is used not only to modify existing pollution indices so that they are more suitable for addressing local vulnerability, but also to develop a unique assessment tool to support decision making based on locally or nationally available data. This study was funded by a grant from the GAIA project(2016000560002), Korea Environmental Industry & Technology Institute, Republic of Korea.

Investigating local controls on soil moisture temporal stability using an inverse modeling approach

NASA Astrophysics Data System (ADS)

Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

2013-04-01

A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

Can we quantify the variability of soil moisture across scales using Electromagnetic Induction ?

NASA Astrophysics Data System (ADS)

Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan

2017-04-01

Soil moisture is a key variable in many natural processes. Therefore, technological and methodological advancements are of primary importance to provide accurate measurements of spatial and temporal variability of soil moisture. In that context, ElectroMagnetic Induction (EMI) instruments are often cited as a hydrogeophysical method with a large potential, through the measurement of the soil apparent electrical conductivity (ECa). To our knowledge, no studies have evaluated the potential of EMI to characterize variability of soil moisture on both agricultural and forested land covers in a (sub-) tropical environment. These differences in land use could be critical as differences in temperature, transpiration and root water uptake can have significant effect, notably on the electrical conductivity of the pore water. In this study, we used an EMI instrument to carry out a first assessment of the impact of deforestation and agriculture on soil moisture in a subtropical region in the south of Brazil. We selected slopes of different topographies (gentle vs. steep) and contrasting land uses (natural forest vs. agriculture) within two nearby catchments. At selected locations on the slopes, we measured simultaneously ECa using EMI and a depth-weighted average of the soil moisture using TDR probes installed within soil pits. We found that the temporal variability of the soil moisture could not be measured accurately with EMI, probably because of important temporal variations of the pore water electrical conductivity and the relatively small temporal variations in soil moisture content. However, we found that its spatial variability could be effectively quantified using a non-linear relationship, for both intra- and inter-slopes variations. Within slopes, the ECa could explained between 67 and 90% of the variability of the soil moisture, while a single non-linear model for all the slopes could explain 55% of the soil moisture variability. We eventually showed that combining a specific relationship for the most degraded slope (steep slope under agriculture) and a single relationship for all the other slopes, both non-linear relations, yielded the best results with an overall explained variance of 90%. We applied the latter model to measurements of the ECa along transects at the different slopes, which allowed us to highlight the strong control of topography on the soil moisture content. We also observed a significant impact of the land use with higher moisture content on the agricultural slopes, probably due to a reduced evapotranspiration.

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

NASA Technical Reports Server (NTRS)

Batista, G. T.; Hixson, M. M.; Bauer, M. E.

1982-01-01

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Different composition and distribution patterns of mineral-protected versus hydrolyzable lipids in shrubland soils

NASA Astrophysics Data System (ADS)

Cai, Yue; Tang, Zhiyao; Xiong, Gaoming; Xie, Zongqiang; Liu, Zongguang; Feng, Xiaojuan

2017-09-01

Mineral protection is known as an important mechanism stabilizing soil organic carbon (SOC). However, the composition, sources, and variations of mineral-protected SOC remain poorly constrained. To fill this knowledge gap, we used hydrofluoric acid to demineralize soil matrix and compared the sources and distribution of mineral-protected lipids (ML) versus hydrolyzable lipids (HL) of four typical Chinese shrubland soils. ML was found to represent a sizable fraction (9-32%) of total aliphatic lipids (including n-alkanols; n-alkanoic acids; α,ω-alkanedioic acids; hydroxyalkanoic acids; and midchain-substituted acids) in all soils. Based on carbon chain length and branch positions, microbe- and plant-derived lipids were distinguished. No significant difference was found in the ratio of microbe- to plant-derived lipids in ML versus HL, implying that plant and microbial inputs are equally important for the mineral-associated soil lipids. However, ML contained a higher proportion of nonspecific lipids, especially at depths. Furthermore, to evaluate key environmental variable(s) controlling the distribution of different lipid components, a multiple stepwise regression analysis was conducted. Notably, ML was mainly affected by SOC-to-nitrogen ratio instead of mineralogical properties, implying that the accrual of mineral-associated soil lipids relies strongly on organic matter properties. Collectively, our findings provide novel insights on sources and accumulation mechanisms of mineral-protected soil lipids. SOC decomposition and subsequent accretion of degradation products appear to be vital for the sequestration of mineral-associated soil lipids and warrant better recognition in the investigations of stable soil carbon accumulation mechanisms.

Enhancing SMAP Soil Moisture Retrievals via Superresolution Techniques

NASA Astrophysics Data System (ADS)

Beale, K. D.; Ebtehaj, A. M.; Romberg, J. K.; Bras, R. L.

2017-12-01

Soil moisture is a key state variable that modulates land-atmosphere interactions and its high-resolution global scale estimates are essential for improved weather forecasting, drought prediction, crop management, and the safety of troop mobility. Currently, NASA's Soil Moisture Active/Passive (SMAP) satellite provides a global picture of soil moisture variability at a resolution of 36 km, which is prohibitive for some hydrologic applications. The goal of this research is to enhance the resolution of SMAP passive microwave retrievals by a factor of 2 to 4 using modern superresolution techniques that rely on the knowledge of high-resolution land surface models. In this work, we explore several super-resolution techniques including an empirical dictionary method, a learned dictionary method, and a three-layer convolutional neural network. Using a year of global high-resolution land surface model simulations as training set, we found that we are able to produce high-resolution soil moisture maps that outperform the original low-resolution observations both qualitatively and quantitatively. In particular, on a patch-by-patch basis we are able to produce estimates of high-resolution soil moisture maps that improve on the original low-resolution patches by on average 6% in terms of mean-squared error, and 14% in terms of the structural similarity index.

Detection of soil erosion within pinyon-juniper woodlands using Thematic Mapper (TM) data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, K.P.

1993-09-01

Multispectral measurements collected by Landsat Thematic Mapper (TM) were correlated with field measurements, direct soil loss estimates, and Universal Soil Loss Equation (USLE) estimates to determine the sensitivity of TM data to varying degrees of soil erosion in pinyon-juniper woodland in central Utah. TM data were also evaluated as a predictor of the USLE Crop Management C factor for pinyon-juniper woodlands. Correlation analysis showed that TM Band 4 (near infrared) accounted for 78% of the variability in percent trees (r=[minus] 0.88). In multiple regression, percent trees, total soil loss, and percent total nonliving cover together accounted for nearly 70% ofmore » the variability in TM Bands 2, 3, 4, and 5. TM spectral data were consistently better predictors of soil erosion factors than any combination of field factors. TM data were more sensitive to vegetation variations than the USLE C factor. USLE estimates showed low annual rates of erosion which varied little among the study sites. A number of hypotheses have been advanced to explain the apparent accelerated rate of pinyon-juniper spread in the western United States. These include removal of natural plant competition by livestock overgrazing, reduction of wildfires, climatic change, and reinvasion of sites cleared of trees by 19th century settlers.« less

Soil nitrate reducing processes – drivers, mechanisms for spatial variation, and significance for nitrous oxide production

PubMed Central

Giles, Madeline; Morley, Nicholas; Baggs, Elizabeth M.; Daniell, Tim J.

2012-01-01

The microbial processes of denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are two important nitrate reducing mechanisms in soil, which are responsible for the loss of nitrate (NO3−) and production of the potent greenhouse gas, nitrous oxide (N2O). A number of factors are known to control these processes, including O2 concentrations and moisture content, N, C, pH, and the size and community structure of nitrate reducing organisms responsible for the processes. There is an increasing understanding associated with many of these controls on flux through the nitrogen cycle in soil systems. However, there remains uncertainty about how the nitrate reducing communities are linked to environmental variables and the flux of products from these processes. The high spatial variability of environmental controls and microbial communities across small sub centimeter areas of soil may prove to be critical in determining why an understanding of the links between biotic and abiotic controls has proved elusive. This spatial effect is often overlooked as a driver of nitrate reducing processes. An increased knowledge of the effects of spatial heterogeneity in soil on nitrate reduction processes will be fundamental in understanding the drivers, location, and potential for N2O production from soils. PMID:23264770

Soil nitrate reducing processes - drivers, mechanisms for spatial variation, and significance for nitrous oxide production.

PubMed

Giles, Madeline; Morley, Nicholas; Baggs, Elizabeth M; Daniell, Tim J

2012-01-01

The microbial processes of denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are two important nitrate reducing mechanisms in soil, which are responsible for the loss of nitrate ([Formula: see text]) and production of the potent greenhouse gas, nitrous oxide (N(2)O). A number of factors are known to control these processes, including O(2) concentrations and moisture content, N, C, pH, and the size and community structure of nitrate reducing organisms responsible for the processes. There is an increasing understanding associated with many of these controls on flux through the nitrogen cycle in soil systems. However, there remains uncertainty about how the nitrate reducing communities are linked to environmental variables and the flux of products from these processes. The high spatial variability of environmental controls and microbial communities across small sub centimeter areas of soil may prove to be critical in determining why an understanding of the links between biotic and abiotic controls has proved elusive. This spatial effect is often overlooked as a driver of nitrate reducing processes. An increased knowledge of the effects of spatial heterogeneity in soil on nitrate reduction processes will be fundamental in understanding the drivers, location, and potential for N(2)O production from soils.

Erosion of soil organic carbon: implications for carbon sequestration

USGS Publications Warehouse

Van Oost, Kristof; Van Hemelryck, Hendrik; Harden, Jennifer W.; McPherson, B.J.; Sundquist, E.T.

2009-01-01

Agricultural activities have substantially increased rates of soil erosion and deposition, and these processes have a significant impact on carbon (C) mineralization and burial. Here, we present a synthesis of erosion effects on carbon dynamics and discuss the implications of soil erosion for carbon sequestration strategies. We demonstrate that for a range of data-based parameters from the literature, soil erosion results in increased C storage onto land, an effect that is heterogeneous on the landscape and is variable on various timescales. We argue that the magnitude of the erosion term and soil carbon residence time, both strongly influenced by soil management, largely control the strength of the erosion-induced sink. In order to evaluate fully the effects of soil management strategies that promote carbon sequestration, a full carbon account must be made that considers the impact of erosion-enhanced disequilibrium between carbon inputs and decomposition, including effects on net primary productivity and decomposition rates.

A global data set of soil particle size properties

NASA Technical Reports Server (NTRS)

Webb, Robert S.; Rosenzweig, Cynthia E.; Levine, Elissa R.

1991-01-01

A standardized global data set of soil horizon thicknesses and textures (particle size distributions) was compiled. This data set will be used by the improved ground hydrology parameterization designed for the Goddard Institute for Space Studies General Circulation Model (GISS GCM) Model 3. The data set specifies the top and bottom depths and the percent abundance of sand, silt, and clay of individual soil horizons in each of the 106 soil types cataloged for nine continental divisions. When combined with the World Soil Data File, the result is a global data set of variations in physical properties throughout the soil profile. These properties are important in the determination of water storage in individual soil horizons and exchange of water with the lower atmosphere. The incorporation of this data set into the GISS GCM should improve model performance by including more realistic variability in land-surface properties.

Assessment of soil pollution based on total petroleum hydrocarbons and individual oil substances.

PubMed

Pinedo, J; Ibáñez, R; Lijzen, J P A; Irabien, Á

2013-11-30

Different oil products like gasoline, diesel or heavy oils can cause soil contamination. The assessment of soils exposed to oil products can be conducted through the comparison between a measured concentration and an intervention value (IV). Several national policies include the IV based on the so called total petroleum hydrocarbons (TPH) measure. However, the TPH assessment does not indicate the individual substances that may produce contamination. The soil quality assessment can be improved by including common hazardous compounds as polycyclic aromatic hydrocarbons (PAHs) and aromatic volatile hydrocarbons like benzene, toluene, ethylbenzene and xylenes (BTEX). This study, focused on 62 samples collected from different sites throughout The Netherlands, evaluates TPH, PAH and BTEX concentrations in soils. Several indices of pollution are defined for the assessment of individual variables (TPH, PAH, B, T, E, and X) and multivariables (MV, BTEX), allowing us to group the pollutants and simplify the methodology. TPH and PAH concentrations above the IV are mainly found in medium and heavy oil products such as diesel and heavy oil. On the other hand, unacceptable BTEX concentrations are reached in soils contaminated with gasoline and kerosene. The TPH assessment suggests the need for further action to include lighter products. The application of multivariable indices allows us to include these products in the soil quality assessment without changing the IV for TPH. This work provides useful information about the soil quality assessment methodology of oil products in soils, focussing the analysis into the substances that mainly cause the risk. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of spatial variability of soil hydraulic properties on water dynamics

NASA Astrophysics Data System (ADS)

Gumiere, Silvio Jose; Caron, Jean; Périard, Yann; Lafond, Jonathan

2013-04-01

Soil hydraulic properties may present spatial variability and dependence at the scale of watersheds or fields even in man-made single soil structures, such as cranberry fields. The saturated hydraulic conductivity (Ksat) and soil moisture curves were measured at two depths for three cranberry fields (about 2 ha) at three different sites near Québec city, Canada. Two of the three studied fields indicate strong spatial dependence for Ksat values and soil moisture curves both in horizontal and vertical directions. In the summer of 2012, the three fields were equipped with 55 tensiometers installed at a depth of 0.10 m in a regular grid. About 20 mm of irrigation water were applied uniformly by aspersion to the fields, raising soil water content to near saturation condition. Soil water tension was measured once every hour during seven days. Geostatistical techniques such as co-kriging and cross-correlograms estimations were used to investigate the spatial dependence between variables. The results show that soil tension varied faster in high Ksat zones than in low Ksatones in the cranberry fields. These results indicate that soil water dynamic is strongly affected by the variability of saturated soil hydraulic conductivity, even in a supposed homogenous anthropogenic soil. This information may have a strong impact in irrigation management and subsurface drainage efficiency as well as other water conservation issues. Future work will involve 3D numerical modeling of the field water dynamics with HYDRUS software. The anticipated outcome will provide valuable information for the understanding of the effect of spatial variability of soil hydraulic properties on soil water dynamics and its relationship with crop production and water conservation.

Impact Assessment of Salinization Affected Soil on Greenhouse Crops using SALTMED

NASA Astrophysics Data System (ADS)

Pappa, Polyxeni; Daliakopoulos, Ioannis; Tsanis, Ioannis; Varouchakis, Emmanouil

2015-04-01

Here we assess the effects of soil salinization on greenhouse crops and the potential benefits of rainwater harvesting as a soil amelioration technology. The study deals with the following scenarios: (a) variation of irrigation water salinity from 3,000 μS/cm to 500 μS/cm through mixing with rainwater, (b) crop substitution for increased tolerance and (c) climatic variability to account for the impact of climate change. In order to draw meaningful conclusions, a model that takes into account vegetation interaction, soil, irrigation water and climate variables is required. The SALTMED model is a reliable and tested physical process model that simulates evapotranspiration, plant water uptake, water and solute transport to estimate crop yield and biomass production under all irrigation systems. SALTMED is tested with the above scenarios in the RECARE FP7 Project Case Study of Timpaki, in the Island of Crete, Greece. Simulations are conducted for typical cultivations of Solanum lycopersicum, Capsicum anuumm and Solanum melongena. Preliminary results indicate the optimal combination from a set of solutions concerning the soil and water parameters can be beneficial against the salinization threat. Future research includes the validation of the results with field experiments. Keywords: salinization, greenhouse, tomato, SALTMED, rainwater, RECARE

When and where does preferential flow matter - from observation to large scale modelling

NASA Astrophysics Data System (ADS)

Weiler, Markus; Leistert, Hannes; Steinbrich, Andreas

2017-04-01

Preferential flow can be of relevance in a wide range of soils and the interaction of different processes and factors are still difficult to assess. As most studies (including our own studies) focusing on the effect of preferential flow are based on relatively high precipitation rates, there is always the question how relevant preferential flow is under natural conditions, considering the site specific precipitation characteristics, the effect of the drying and wetting cycle on the initial soil water condition and shrinkage cracks, the site specific soil properties, soil structure and rock fragments, and the effect of plant roots and soil fauna (e.g. earthworm channels). In order to assess this question, we developed the distributed, process-based model RoGeR (Runoff Generation Research) to include a large number relevant features and processes of preferential flow in soils. The model was developed from a large number of process based research and experiments and includes preferential flow in roots, earthworm channels, along rock fragments and shrinkage cracks. We parameterized the uncalibrated model at a high spatial resolution of 5x5m for the whole state of Baden-Württemberg in Germany using LiDAR data, degree of sealing, landuse, soil properties and geology. As the model is an event based model, we derived typical event based precipitation characteristics based on rainfall duration, mean intensity and amount. Using the site-specific variability of initial soil moisture derived from a water balance model based on the same dataset, we simulated the infiltration and recharge amounts of all event classes derived from the event precipitation characteristics and initial soil moisture conditions. The analysis of the simulation results allowed us to extracts the relevance of preferential flow for infiltration and recharge considering all factors above. We could clearly see a strong effect of the soil properties and land-use, but also, particular for clay rich soils a strong effect of the initial conditions due to the development of soil cracks. Not too surprisingly, the relevance of preferential flow was much lower when considering the whole range of precipitation events as only considering events with a high rainfall intensity. Also, the influence on infiltration and recharge were different. Despite the model can still be improved in particular considering more realistic information about the spatial and temporal variability of preferential flow by soil fauna and plants, the model already shows under what situation we need to be very careful when predicting infiltration and recharge with models considering only longer time steps (daily) or only matrix flow.

Key indicator tools for shallow slope failure assessment using soil chemical property signatures and soil colour variables.

PubMed

Othman, Rashidi; Hasni, Shah Irani; Baharuddin, Zainul Mukrim; Hashim, Khairusy Syakirin Has-Yun; Mahamod, Lukman Hakim

2017-10-01

Slope failure has become a major concern in Malaysia due to the rapid development and urbanisation in the country. It poses severe threats to any highway construction industry, residential areas, natural resources and tourism activities. The extent of damages that resulted from this catastrophe can be lessened if a long-term early warning system to predict landslide prone areas is implemented. Thus, this study aims to characterise the relationship between Oxisols properties and soil colour variables to be manipulated as key indicators to forecast shallow slope failure. The concentration of each soil property in slope soil was evaluated from two different localities that consist of 120 soil samples from stable and unstable slopes located along the North-South Highway (PLUS) and East-West Highway (LPT). Analysis of variance established highly significant difference (P < 0.0001) between the locations, the total organic carbon (TOC), soil pH, cation exchange capacity (CEC), soil texture, soil chromaticity and all combinations of interactions. The overall CIELAB analysis leads to the conclusion that the CIELAB variables lightness L*, c* (Chroma) and h* (Hue) provide the most information about soil colour and other related soil properties. With regard to the relationship between colour variables and soil properties, the analysis detected that soil texture, organic carbon, iron oxide and aluminium concentration were the key factors that strongly correlate with soil colour variables at the studied area. Indicators that could be used to predict shallow slope failure were high value of L*(62), low values of c* (20) and h* (66), low concentration of iron (53 mg kg -1 ) and aluminium oxide (37 mg kg -1 ), low soil TOC (0.5%), low CEC (3.6 cmol/kg), slightly acidic soil pH (4.9), high amount of sand fraction (68%) and low amount of clay fraction (20%).

Distribution of soil organic carbon in the conterminous United States

USGS Publications Warehouse

Bliss, Norman B.; Waltman, Sharon; West, Larry T.; Neale, Anne; Mehaffey, Megan; Hartemink, Alfred E.; McSweeney, Kevin M.

2014-01-01

The U.S. Soil Survey Geographic (SSURGO) database provides detailed soil mapping for most of the conterminous United States (CONUS). These data have been used to formulate estimates of soil carbon stocks, and have been useful for environmental models, including plant productivity models, hydrologic models, and ecological models for studies of greenhouse gas exchange. The data were compiled by the U.S. Department of Agriculture Natural Resources Conservation Service (NRCS) from 1:24,000-scale or 1:12,000-scale maps. It was found that the total soil organic carbon stock in CONUS to 1 m depth is 57 Pg C and for the total profile is 73 Pg C, as estimated from SSURGO with data gaps filled from the 1:250,000-scale Digital General Soil Map. We explore the non-linear distribution of soil carbon on the landscape and with depth in the soil, and the implications for sampling strategies that result from the observed soil carbon variability.

Biogeographic patterns in below-ground diversity in New York City's Central Park are similar to those observed globally

PubMed Central

Ramirez, Kelly S.; Leff, Jonathan W.; Barberán, Albert; Bates, Scott Thomas; Betley, Jason; Crowther, Thomas W.; Kelly, Eugene F.; Oldfield, Emily E.; Shaw, E. Ashley; Steenbock, Christopher; Bradford, Mark A.; Wall, Diana H.; Fierer, Noah

2014-01-01

Soil biota play key roles in the functioning of terrestrial ecosystems, however, compared to our knowledge of above-ground plant and animal diversity, the biodiversity found in soils remains largely uncharacterized. Here, we present an assessment of soil biodiversity and biogeographic patterns across Central Park in New York City that spanned all three domains of life, demonstrating that even an urban, managed system harbours large amounts of undescribed soil biodiversity. Despite high variability across the Park, below-ground diversity patterns were predictable based on soil characteristics, with prokaryotic and eukaryotic communities exhibiting overlapping biogeographic patterns. Further, Central Park soils harboured nearly as many distinct soil microbial phylotypes and types of soil communities as we found in biomes across the globe (including arctic, tropical and desert soils). This integrated cross-domain investigation highlights that the amount and patterning of novel and uncharacterized diversity at a single urban location matches that observed across natural ecosystems spanning multiple biomes and continents. PMID:25274366

The identification of 'hotspots' of heavy metal pollution in soil-rice systems at a regional scale in eastern China.

PubMed

Li, Wanlu; Xu, Binbin; Song, Qiujin; Liu, Xingmei; Xu, Jianming; Brookes, Philip C

2014-02-15

Chinese agricultural soils and crops are suffering from increasing damage from heavy metals, which are introduced from various pollution sources including agriculture, traffic, mining and especially the flourishing private metal recycling industry. In this study, 219 pairs of rice grain and corresponding soil samples were collected from Wenling in Zhejiang Province to identify the spatial relationship and pollution hotspots of Cd, Cu, Ni and Zn in the soil-rice system. The mean soil concentrations of heavy metals were 0.316 mg kg(-1) for Cd, 47.3 mg kg(-1) for Cu, 31.7 mg kg(-1) for Ni and 131 mg kg(-1) for Zn, and the metal concentrations in rice grain were 0.132 mg kg(-1) for Cd, 2.46 mg kg(-1) for Cu, 0.223 mg kg(-1) for Ni and 17.4 mg kg(-1) for Zn. The coefficient of variability (CV) of soil Cd, Cu and rice Cd were 147%, 146% and 180%, respectively, indicating an extensive variability. While the CVs of other metals ranged from 23.4% to 84.3% with a moderate variability. Kriging interpolation procedure and the Local Moran's I index detected the locations of pollution hotspots of these four metals. Cd and Cu had a very similar spatial pattern, with contamination hotspots located simultaneously in the northwestern part of the study area, and there were obvious hotspots for soil Zn in the north area, while in the northeast for soil Ni. The existence of hotspots may be due to industrialization and other anthropogenic activities. An Enrichment Index (EI) was employed to measure the uptake of heavy metals by rice. The results indicated that the accumulation and availability of heavy metals in the soil-rice system may be influenced by both soil heavy metal concentrations and soil physico-chemical properties. Cross-correlograms quantitatively illustrated that EIs were significantly correlated with soil properties. Soil pH and organic matter were the most important factors controlling the uptake of heavy metals by rice. As results, positive measures should be taken into account to control soil pollution and to curtail metal contamination to the food chain in the areas of Wenling, which were the most polluted by toxic metals. Copyright © 2013 Elsevier B.V. All rights reserved.

Plant Uptake of Organic Pollutants from Soil: A Critical Review ofBioconcentration Estimates Based on Modelsand Experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKone, Thomas E.; Maddalena, Randy L.

2007-01-01

The role of terrestrial vegetation in transferring chemicals from soil and air into specific plant tissues (stems, leaves, roots, etc.) is still not well characterized. We provide here a critical review of plant-to-soil bioconcentration ratio (BCR) estimates based on models and experimental data. This review includes the conceptual and theoretical formulations of the bioconcentration ratio, constructing and calibrating empirical and mathematical algorithms to describe this ratio and the experimental data used to quantify BCRs and calibrate the model performance. We first evaluate the theoretical basis for the BCR concept and BCR models and consider how lack of knowledge and datamore » limits reliability and consistency of BCR estimates. We next consider alternate modeling strategies for BCR. A key focus of this evaluation is the relative contributions to overall uncertainty from model uncertainty versus variability in the experimental data used to develop and test the models. As a case study, we consider a single chemical, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and focus on variability of bioconcentration measurements obtained from 81 experiments with different plant species, different plant tissues, different experimental conditions, and different methods for reporting concentrations in the soil and plant tissues. We use these observations to evaluate both the magnitude of experimental variability in plant bioconcentration and compare this to model uncertainty. Among these 81 measurements, the variation of the plant/soil BCR has a geometric standard deviation (GSD) of 3.5 and a coefficient of variability (CV-ratio of arithmetic standard deviation to mean) of 1.7. These variations are significant but low relative to model uncertainties--which have an estimated GSD of 10 with a corresponding CV of 14.« less

Pedological memory in forest soil development

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2004-01-01

Individual trees may have significant impacts on soil morphology. If these impacts are non-random such that some microsites are repeatedly preferentially affected by trees, complex local spatial variability of soils would result. A model of self-reinforcing pedologic influences of trees (SRPIT) is proposed to explain patterns of soil variability in the Ouachita...

Spatio-Temporal Analysis of Surface Soil Moisture in Evaluating Ground Truth Monitoring Sites for Remotely Sensed Observations

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. Although soil moisture is highly variable, repeated measurements of soil moisture at the field or small watershed scale can often reveal certain locations as being temporally stable and representative of the are...

Vegetation and environmental controls on soil respiration in a pinon-juniper woodland

Treesearch

Sandra A. White

2008-01-01

Soil respiration (RS) responds to changes in plant and microbial activity and environmental conditions. In arid ecosystems of the southwestern USA, soil moisture exhibits large fluctuations because annual and seasonal precipitation inputs are highly variable, with increased variability expected in the future. Patterns of soil moisture, and periodic severe drought, are...

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

PubMed

Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope

2013-11-01

Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

Digital mapping of soil properties in Canadian managed forests at 250 m of resolution using the k-nearest neighbor method

NASA Astrophysics Data System (ADS)

Mansuy, N. R.; Paré, D.; Thiffault, E.

2015-12-01

Large-scale mapping of soil properties is increasingly important for environmental resource management. Whileforested areas play critical environmental roles at local and global scales, forest soil maps are typically at lowresolution.The objective of this study was to generate continuous national maps of selected soil variables (C, N andsoil texture) for the Canadian managed forest landbase at 250 m resolution. We produced these maps using thekNN method with a training dataset of 538 ground-plots fromthe National Forest Inventory (NFI) across Canada,and 18 environmental predictor variables. The best predictor variables were selected (7 topographic and 5 climaticvariables) using the Least Absolute Shrinkage and Selection Operator method. On average, for all soil variables,topographic predictors explained 37% of the total variance versus 64% for the climatic predictors. Therelative root mean square error (RMSE%) calculated with the leave-one-out cross-validation method gave valuesranging between 22% and 99%, depending on the soil variables tested. RMSE values b 40% can be considered agood imputation in light of the low density of points used in this study. The study demonstrates strong capabilitiesfor mapping forest soil properties at 250m resolution, compared with the current Soil Landscape of CanadaSystem, which is largely oriented towards the agricultural landbase. The methodology used here can potentiallycontribute to the national and international need for spatially explicit soil information in resource managementscience.

Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas.

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Stochastical analysis of surfactant-enhanced remediation of denser-than-water nonaqueous phase liquid (DNAPL)-contaminated soils.

PubMed

Zhang, Renduo; Wood, A Lynn; Enfield, Carl G; Jeong, Seung-Woo

2003-01-01

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.

[Interrelationships between soil fauna and soil environmental factors in China: research advance].

PubMed

Wang, Yi; Wei, Wei; Yang, Xing-zhong; Chen, Li-ding; Yang, Lei

2010-09-01

Soil fauna has close relations with various environmental factors in soil ecosystem. To explore the interrelationships between soil fauna and soil environmental factors is of vital importance to deep understand the dynamics of soil ecosystem and to assess the functioning of the ecosystem. The environmental factors affecting soil fauna can be classified as soil properties and soil external environment. The former contains soil basic physical and chemical properties, soil moisture, and soil pollution. The latter includes vegetation, land use type, landform, and climate, etc. From these aspects, this paper summarized the published literatures in China on the interrelationships between soil fauna and soil environmental factors. It was considered that several problems were existed in related studies, e.g., fewer researches were made in integrating soil fauna's bio-indicator function, research methods were needed to be improved, and the studies on the multi-environmental factors and their large scale spatial-temporal variability were in deficiency. Corresponding suggestions were proposed, i.e., more work should be done according to the practical needs, advanced experiences from abroad should be referenced, and comprehensive studies on multi-environmental factors and long-term monitoring should be conducted on large scale areas.

Soil property effects on wind erosion of organic soils

NASA Astrophysics Data System (ADS)

Zobeck, Ted M.; Baddock, Matthew; Scott Van Pelt, R.; Tatarko, John; Acosta-Martinez, Veronica

2013-09-01

Histosols (also known as organic soils, mucks, or peats) are soils that are dominated by organic matter (OM > 20%) in half or more of the upper 80 cm. Forty two states have a total of 21 million ha of Histosols in the United States. These soils, when intensively cropped, are subject to wind erosion resulting in loss of crop productivity and degradation of soil, air, and water quality. Estimating wind erosion on Histosols has been determined by USDA-Natural Resources Conservation Service (NRCS) as a critical need for the Wind Erosion Prediction System (WEPS) model. WEPS has been developed to simulate wind erosion on agricultural land in the US, including soils with organic soil material surfaces. However, additional field measurements are needed to understand how soil properties vary among organic soils and to calibrate and validate estimates of wind erosion of organic soils using WEPS. Soil properties and sediment flux were measured in six soils with high organic contents located in Michigan and Florida, USA. Soil properties observed included organic matter content, particle density, dry mechanical stability, dry clod stability, wind erodible material, and geometric mean diameter of the surface aggregate distribution. A field portable wind tunnel was used to generate suspended sediment and dust from agricultural surfaces for soils ranging from 17% to 67% organic matter. The soils were tilled and rolled to provide a consolidated, friable surface. Dust emissions and saltation were measured using an isokinetic vertical slot sampler aspirated by a regulated suction source. Suspended dust was sampled using a Grimm optical particle size analyzer. Particle density of the saltation-sized material (>106 μm) was inversely related to OM content and varied from 2.41 g cm-3 for the soil with the lowest OM content to 1.61 g cm-3 for the soil with highest OM content. Wind erodible material and the geometric mean diameter of the surface soil were inversely related to dry clod stability. The effect of soil properties on sediment flux varied among flux types. Saltation flux was adequately predicted with simple linear regression models. Dry mechanical stability was the best single soil property linearly related to saltation flux. Simple linear models with soil properties as independent variables were not well correlated with PM10E values (mass flux). A second order polynomial equation with OM as the independent variable was found to be most highly correlated with PM10E values. These results demonstrate that variations in sediment and dust emissions can be linked to soil properties using simple models based on one or more soil properties to estimate saltation mass flux and PM10E values from organic and organic-rich soils.

Estimating plant available water content from remotely sensed evapotranspiration

NASA Astrophysics Data System (ADS)

van Dijk, A. I. J. M.; Warren, G.; Doody, T.

2012-04-01

Plant available water content (PAWC) is an emergent soil property that is a critical variable in hydrological modelling. PAWC determines the active soil water storage and, in water-limited environments, is the main cause of different ecohydrological behaviour between (deep-rooted) perennial vegetation and (shallow-rooted) seasonal vegetation. Conventionally, PAWC is estimated for a combination of soil and vegetation from three variables: maximum rooting depth and the volumetric water content at field capacity and permanent wilting point, respectively. Without elaborate local field observation, large uncertainties in PAWC occur due to the assumptions associated with each of the three variables. We developed an alternative, observation-based method to estimate PAWC from precipitation observations and CSIRO MODIS Reflectance-based Evapotranspiration (CMRSET) estimates. Processing steps include (1) removing residual systematic bias in the CMRSET estimates, (2) making spatially appropriate assumptions about local water inputs and surface runoff losses, (3) using mean seasonal patterns in precipitation and CMRSET to estimate the seasonal pattern in soil water storage changes, (4) from these, calculating the mean seasonal storage range, which can be treated as an estimate of PAWC. We evaluate the resulting PAWC estimates against those determined in field experiments for 180 sites across Australia. We show that the method produces better estimates of PAWC than conventional techniques. In addition, the method provides detailed information with full continental coverage at moderate resolution (250 m) scale. The resulting maps can be used to identify likely groundwater dependent ecosystems and to derive PAWC distributions for each combination of soil and vegetation type.

Variability in urban soils influences the health and growth of native tree seedlings

Treesearch

Clara C. Pregitzer; Nancy F. Sonti; Richard A. Hallett

2016-01-01

Reforesting degraded urban landscapes is important due to the many benefits urban forests provide. Urban soils are highly variable, yet little is known about how this variability in urban soils influences tree seedling performance and survival. We conducted a greenhouse study to assess health, growth, and survival of four native tree species growing in native glacial...

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

USGS Publications Warehouse

Thomas, Matthew A.; Mirus, Benjamin B.; Collins, Brian D.; Lu, Ning; Godt, Jonathan W.

2018-01-01

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

Soil moisture and soil temperature variability among three plant communities in a High Arctic Lake Basin

NASA Astrophysics Data System (ADS)

Davis, M. L.; Konkel, J.; Welker, J. M.; Schaeffer, S. M.

2017-12-01

Soil moisture and soil temperature are critical to plant community distribution and soil carbon cycle processes in High Arctic tundra. As environmental drivers of soil biochemical processes, the predictability of soil moisture and soil temperature by vegetation zone in High Arctic landscapes has significant implications for the use of satellite imagery and vegetation distribution maps to estimate of soil gas flux rates. During the 2017 growing season, we monitored soil moisture and soil temperature weekly at 48 sites in dry tundra, moist tundra, and wet grassland vegetation zones in a High Arctic lake basin. Soil temperature in all three communities reflected fluctuations in air temperature throughout the season. Mean soil temperature was highest in the dry tundra community at 10.5±0.6ºC, however, did not differ between moist tundra and wet grassland communities (2.7±0.6 and 3.1±0.5ºC, respectively). Mean volumetric soil moisture differed significantly among all three plant communities with the lowest and highest soil moisture measured in the dry tundra and wet grassland (30±1.2 and 65±2.7%), respectively. For all three communities, soil moisture was highest during the early season snow melt. Soil moisture in wet grassland remained high with no significant change throughout the season, while significant drying occurred in dry tundra. The most significant change in soil moisture was measured in moist tundra, ranging from 61 to 35%. Our results show different gradients in soil moisture variability within each plant community where: 1) soil moisture was lowest in dry tundra with little change, 2) highest in wet grassland with negligible change, and 3) variable in moist tundra which slowly dried but remained moist. Consistently high soil moisture in wet grassland restricts this plant community to areas with no significant drying during summer. The moist tundra occupies the intermediary areas between wet grassland and dry tundra and experiences the widest range of soil moisture variability. As climate projections predict wetter summers in the High Arctic, expansion of areas with seasonally inundated soils and increased soil moisture variability could result in an expansion of wet grassland and moist tundra communities with a commensurate decrease in dry tundra area.

Assessment of soil nitrogen variability related to N doses applied through fertirrigation system.

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Ribas, F.; Cabello, M. J.; Arce, A.; Cartagena, M. C.

2009-04-01

The knowledge of water and nitrogen dynamics in soils under drip irrigation and fertilizer application is essential to optimizing water and nitrogen management. Recent studies of water and nitrogen distribution in the soil under drip irrigation focus on water and inorganic nitrogen distribution around the drip emitters. Results of the studies are not verified with field experimental data. Reasons might include difficulties in obtaining field experimental data under irrigation and nitrogen fertilization [1]. N is an element which produces a stronger crop response, accelerates vegetative growth, plant development and yield increase. Accumulation and redistribution of N within the soil varies depending on management practices, soil characteristics, and growing season precipitation. Soil N high content at post-harvest is usually provided as evidence that N fertilizer had been applied in excess. The aim of this study is to characterize mineral N distribution in the soil profile measured at 5, 15, 25, 35, 45 and 55 cm of depth at the end of melon crop that received three N treatments: 93 (N93), 243 (N243) and 393 kg N ha-1(N393). The agronomic practices created a higher variability in soil Nitrogen content. NH4- N reduction in the soil profile can also be explained by the nitrification process. The high absorption and rapid nitrification of NH4+ ions in the plot layer are the main reason of a reduce movement downstream. NO3- ions present higher mobility in the soil profile. [1] Rahil, M.H.; Antonopoulos, V.Z. 2007. Simulating soil water flow and nitrogen dynamics in a sunflower field irrigated with reclaimed wastewater. Agricultural Water Management 92, 142 - 150. Acknowledgements: This project has been supported by INIA-RTA04-111

Comparing different approaches - data mining, geostatistic, and deterministic pedology - to assess the frequency of WRB Reference Soil Groups in the Italian soil regions

NASA Astrophysics Data System (ADS)

Lorenzetti, Romina; Barbetti, Roberto; L'Abate, Giovanni; Fantappiè, Maria; Costantini, Edoardo A. C.

2013-04-01

Estimating frequency of soil classes in map unit is always affected by some degree of uncertainty, especially at small scales, with a larger generalization. The aim of this study was to compare different possible approaches - data mining, geostatistic, deterministic pedology - to assess the frequency of WRB Reference Soil Groups (RSG) in the major Italian soil regions. In the soil map of Italy (Costantini et al., 2012), a list of the first five RSG was reported in each major 10 soil regions. The soil map was produced using the national soil geodatabase, which stored 22,015 analyzed and classified pedons, 1,413 soil typological unit (STU) and a set of auxiliary variables (lithology, land-use, DEM). Other variables were added, to better consider the influence of soil forming factors (slope, soil aridity index, carbon stock, soil inorganic carbon content, clay, sand, geography of soil regions and soil systems) and a grid at 1 km mesh was set up. The traditional deterministic pedology assessed the STU frequency according to the expert judgment presence in every elementary landscape which formed the mapping unit. Different data mining techniques were firstly compared in their ability to predict RSG through auxiliary variables (neural networks, random forests, boosted tree, supported vector machine (SVM)). We selected SVM according to the result of a testing set. A SVM model is a representation of the examples as points in space, mapped so that examples of separate categories are divided by a clear gap that is as wide as possible. The geostatistic algorithm we used was an indicator collocated cokriging. The class values of the auxiliary variables, available at all the points of the grid, were transformed in indicator variables (values 0, 1). A principal component analysis allowed us to select the variables that were able to explain the largest variability, and to correlate each RSG with the first principal component, which explained the 51% of the total variability. The principal component was used as collocated variable. The results were as many probability maps as the estimated WRB classes. They were summed up in a unique map, with the most probable class at each pixel. The first five more frequent RSG resulting from the three methods were compared. The outcomes were validated with a subset of the 10% of the pedons, kept out before the elaborations. The error estimate was produced for each estimated RSG. The first results, obtained in one of the most widespread soil region (plains and low hills of central and southern Italy) showed that the first two frequency classes were the same for all the three methods. The deterministic method differed from the others at the third position, while the statistical methods inverted the third and fourth position. An advantage of the SVM was the possibility to use in the same elaboration numeric and categorical variable, without any previous transformation, which reduced the processing time. A Bayesian validation indicated that the SVM method was as reliable as the indicator collocated cokriging, and better than the deterministic pedological approach.

Assessing Soil Organic C Stability at the Continental Scale: An Analysis of Soil C and Radiocarbon Profiles Across the NEON Sites

NASA Astrophysics Data System (ADS)

Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; McKnight, D. M.; Strahm, B. D.; Sanclements, M.

2017-12-01

Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of physicochemical parameters on soil C stocks and turnover, and their relative importance in comparison to climatic variables. Soils were cored at NEON sites, sampled by genetic horizon, and density separated into light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon abundance was correlated with pH, with variance also grouping by dominate vegetation type. Soil order was also identified as an important proxy variable for C and radiocarbon abundance. Preliminary results suggest that both integrative proxies as well as physicochemical properties may be needed to account for variation in soil C abundance and stability at the continental scale.

High resolution digital soil mapping as a future instrument for developing sustainable landuse strategies

NASA Astrophysics Data System (ADS)

Gries, Philipp; Funke, Lisa-Marie; Baumann, Frank; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2016-04-01

Climate change, increase in population and intensification of land use pose a great challenge for sustainable handling of soils. Intelligent landuse systems are able to minimize and/or avoid soil erosion and loss of soil fertility. A successful application of such systems requires area-wide soil information with high resolution. Containing three consecutive steps, the project INE-2-H („innovative sustainable landuse") at the University of Tuebingen is about creating high-resolution soil information using Digital Soil Mapping (DSM) techniques to develop sustainable landuse strategies. Input data includes soil data from fieldwork (texture and carbon content), the official digital soil and geological map (1:50.000) as well as a wide selection of local, complex and combined terrain parameters. First, soil maps have been created using the DSM approach and Random Forest (RF). Due to high resolution (10x10 m pixels), those maps show a more detailed spatial variability of soil information compared to the official maps used. Root mean square errors (RMSE) of the modelled maps vary from 2.11 % to 6.87 % and the coefficients of determination (R²) go from 0.42 to 0.68. Second, soil erosion potentials have been estimated according to the Universal Soil Loss Equation (USLE). Long-term average annual soil loss ranges from 0.56 to 24.23 [t/ha/a]. Third, combining high-resolution erosion potentials with expert-knowledge of local farmers will result in a landuse system adapted to local conditions. This system will include sustainable strategies reducing soil erosion and conserving soil fertility.

Combination of a Fast Cleanup Procedure and a DR-CALUX® Bioassay for Dioxin Surveillance in Taiwanese Soils

PubMed Central

Lin, Ding-Yan; Lee, Yi-Pin; Li, Chiu-Ping; Chi, Kai-Hsien; Liang, Bo-Wei P.; Liu, Wen-Yao; Wang, Chih-Cheng; Lin, Susana; Chen, Ting-Chien; Yeh, Kuei-Jyum C.; Hsu, Ping-Chi; Hsu, Yi-Chyun; Chao, How-Ran; Tsou, Tsui-Chun

2014-01-01

Our goal was to determine dioxin levels in 800 soil samples collected from Taiwan. An in vitro DR-CALUX® assay was carried out with the help of an automated Soxhlet system and fast cleanup column. The mean dioxin level of 800 soil samples was 36.0 pg-bioanalytical equivalents (BEQs)/g dry weight (d.w.). Soil dioxin-BEQs were higher in northern Taiwan (61.8 pg-BEQ/g d.w.) than in central, southern, and eastern Taiwan (22.2, 24.9, and 7.80 pg-BEQ/g d.w., respectively). Analysis of multiple linear regression models identified four major predictors of dioxin-BEQs including soil sampling location (β = 0.097, p < 0.001), land use (β = 0.065, p < 0.001), soil brightness (β = 0.170, p < 0.001), and soil moisture (β = 0.051, p = 0.020), with adjusted R2 = 0.947 (p < 0.001) (n = 662). An univariate logistic regression analysis with the cut-off point of 33.4 pg-BEQ/g d.w. showed significant odds ratios (ORs) for soil sampling location (OR = 2.43, p < 0.001), land use (OR = 1.47, p < 0.001), and soil brightness (OR = 2.83, p = 0.009). In conclusion, four variables, including soil sampling location, land use, soil brightness, and soil moisture, may be related to soil-dioxin contamination. Soil samples collected in northern Taiwan, and especially in Bade City, soils near industrial areas, and soils with darker color may contain higher dioxin-BEQ levels. PMID:24806195

Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands

NASA Astrophysics Data System (ADS)

Anne, Naveen J. P.; Abd-Elrahman, Amr H.; Lewis, David B.; Hewitt, Nicole A.

2014-12-01

Developing spectral models of soil properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the partitioning of mineral and organic soil between particulate (>53 μm) and fine size classes, and the partitioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD > 1.4) predicted particulate organic matter (POM), silt + clay, labile carbon (C), and labile nitrogen (N) (where RPD = ratio of standard deviation to root mean square error of cross-validation [RMSECV]). The SR (0.53 μm, 2.11 μm) model of labile N with R2 = 0.81, RMSECV= 0.28, and RPD = 1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense canopy cover.

On the temporal and spatial variability of near-surface soil moisture for the identification of representative in situ soil moisture monitoring stations

USDA-ARS?s Scientific Manuscript database

The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in-situ monitoring stations. Therefore, a standard methodology for selecting the most repre- sentative stations for the purpose of validating satellites and land surface ...

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

Soil texture and climatc conditions for biocrust growth limitation: a meta analysis

NASA Astrophysics Data System (ADS)

Fischer, Thomas; Subbotina, Mariia

2015-04-01

Along with afforestation, attempts have been made to combat desertification by managing soil crusts, and is has been reported that recovery rates of biocrusts are dependent on many factors, including the type, severity, and extent of disturbance; structure of the vascular plant community; conditions of adjoining substrates; availability of inoculation material; and climate during and after disturbance (Belnap & Eldridge 2001). Because biological soil crusts are known to be more stable on and to prefer fine substrates (Belnap 2001), the question arises as to how successful crust management practices can be applied to coarser soil. In previous studies we observed similar crust biomasses on finer soils under arid and on coarser soils under temperate conditions. We hypothesized that the higher water holding capacity of finer substrates would favor crust development, and that the amount of silt and clay in the substrate that is required for enhanced crust development would vary with changes in climatic conditions. In a global meta study, climatic and soil texture threshold values promoting BSC growth were derived. While examining literature sources, it became evident that the amount of studies to be incorporated into this meta analysis was reversely related to the amount of common environmental parameters they share. We selected annual mean precipitaion, mean temperature and the amount of silt and clay as driving variables for crust growth. Response variable was the "relative crust biomass", which was computed per literature source as the ratio between each individual crust biomass value of the given study to the study maximum value reported. We distinguished lichen, green algal, cyanobacterial and moss crusts. To quantify threshold conditions at which crust biomass responded to differences in texture and climate, we (I) determined correlations between bioclimatic variables, (II) calculated linear models to determine the effect of typical climatic variables with soil clay content and with study site as a random effect. (III) Threshold values of texture and climatc effects were identified using a regression tree. Three mean annual temperature classes for texture dependent BSC growth limitation were identified: (1) <9 °C with a threshold value of 25% silt and clay (limited growth on coarser soils), (2) 9-19 °C, where texture did have no influence on relative crust biomass, and (3) >19 °C at soils with <4 or >17% silt and clay. Because biocrust development is limited under certain climatic and soil texture conditions, it is suggested to consider soil texture for biocrust rehabilitation purposes and in biogeochemical modeling of cryptogamic ground covers. References Belnap, J. & Eldridge, D. 2001. Disturbance and Recovery of Biological Soil Crusts. In: Belnap, J. & Lange, O. (eds.) Biological Soil Crusts: Structure, Function, and Management, Springer, Berlin. Belnap, J. 2001. Biological Soil Crusts and Wind Erosion. In: Belnap, J. & Lange, O. (eds.) Fischer, T., Subbotina, M. 2014. Climatic and soil texture threshold values for cryptogamic cover development: a meta analysis. Biologia 69/11:1520-1530,

Including the spatial variability of metal speciation in the effect factor in life cycle impact assessment: Limits of the equilibrium partitioning method.

PubMed

Tromson, Clara; Bulle, Cécile; Deschênes, Louise

2017-03-01

In life cycle assessment (LCA), the potential terrestrial ecotoxicity effect of metals, calculated as the effect factor (EF), is usually extrapolated from aquatic ecotoxicological data using the equilibrium partitioning method (EqP) as it is more readily available than terrestrial data. However, when following the AMI recommendations (i.e. with at least enough species that represents three different phyla), there are not enough terrestrial data for which soil properties or metal speciation during ecotoxicological testing are specified to account for the influence of soil property variations on metal speciation when using this approach. Alternatively, the TBLM (Terrestrial Biotic Ligand Model) has been used to determine an EF that accounts for speciation, but is not available for metals; hence it cannot be consistently applied to metals in an LCA context. This paper proposes an approach to include metal speciation by regionalizing the EqP method for Cu, Ni and Zn with a geochemical speciation model (the Windermere Humic Aqueous Model 7.0), for 5213 soils selected from the Harmonized World Soil Database. Results obtained by this approach (EF EqP regionalized ) are compared to the EFs calculated with the conventional EqP method, to the EFs based on available terrestrial data and to the EFs calculated with the TBLM (EF TBLM regionalized ) when available. The spatial variability contribution of the EF to the overall spatial variability of the characterization factor (CF) has been analyzed. It was found that the EFs EqP regionalized show a significant spatial variability. The EFs calculated with the two non-regionalized methods (EqP and terrestrial data) fall within the range of the EFs EqP regionalized . The EFs TBLM regionalized cover a larger range of values than the EFs EqP regionalized but the two methods are not correlated. This paper highlights the importance of including speciation into the terrestrial EF and shows that using the regionalized EqP approach is not an acceptable proxy for terrestrial ecotoxicological data even if it can be applied to all metals. Copyright © 2016. Published by Elsevier B.V.

Factors Controlling Diffusive CO2 Transport and Production in the Cedarburg Bog, Saukville, Wisconsin

NASA Astrophysics Data System (ADS)

Joynt, E.; Grundl, T.; Han, W. S.; Gulbranson, E. L.

2016-12-01

Wetlands are vital components of the carbon cycle containing an estimated 20-30% of the global soil carbon store. The Cedarburg Bog of southeastern Wisconsin contains multiple wetland types, including the southernmost string bog found in North America. Carbon dioxide (CO2) behavior in wetland systems respond to multiple interdependent variables that are collectively not well understood. Modeling CO2 behavior in wetland environments requires a detailed representation of these variables. In 2014 a LI-COR 8100A automated soil gas flux system was installed in the string bog, measuring CO2 concentration and flux. Groundwater data, soil temperature, and weather data (temperature, pressure, precipitation, etc.) were included to reveal correlations between soil CO2 flux/concentration and external forces. In 2015 field data were complemented with soil moisture data and depth profiles of pore water chemistry and stable carbon isotopes from peat and soil gas to discern source and evolution of CO2 at depth. Initial gaseous δ13C(CO2) average -18‰ and deplete overnight suggesting increasing microbial metabolic efficiency. δ13C soil microbial biomass measure roughly -21‰ to -22‰. LI-COR data show diurnal and seasonal trends; CO2 concentration builds overnight while flux increases during the day. CO2 flux magnitude and CO2 concentration range peak in mid-summer, but frequency of increased CO2 flux events varies seasonally each year. Flux averages 7.55 mgCO2/min-m2 during the day but reaches 530 mgCO2/min-m2. Increased atmospheric and soil temperatures and decreasing atmospheric pressure prelude increasing CO2 flux intensity, though correlation strengths vary. Water level may influence CO2 flux, but observations suggest a mobile peat surface with the water table. 2016 imagery from trail cameras will determine extent of peat/well casing movement with water level changes. Further interpretation of data trends will utilize HYDRUS-1D to quantify relationships under changing environmental conditions.

A Comparison of Selected Statistical Techniques to Model Soil Cation Exchange Capacity

NASA Astrophysics Data System (ADS)

Khaledian, Yones; Brevik, Eric C.; Pereira, Paulo; Cerdà, Artemi; Fattah, Mohammed A.; Tazikeh, Hossein

2017-04-01

Cation exchange capacity (CEC) measures the soil's ability to hold positively charged ions and is an important indicator of soil quality (Khaledian et al., 2016). However, other soil properties are more commonly determined and reported, such as texture, pH, organic matter and biology. We attempted to predict CEC using different advanced statistical methods including monotone analysis of variance (MONANOVA), artificial neural networks (ANNs), principal components regressions (PCR), and particle swarm optimization (PSO) in order to compare the utility of these approaches and identify the best predictor. We analyzed 170 soil samples from four different nations (USA, Spain, Iran and Iraq) under three land uses (agriculture, pasture, and forest). Seventy percent of the samples (120 samples) were selected as the calibration set and the remaining 50 samples (30%) were used as the prediction set. The results indicated that the MONANOVA (R2= 0.82 and Root Mean Squared Error (RMSE) =6.32) and ANNs (R2= 0.82 and RMSE=5.53) were the best models to estimate CEC, PSO (R2= 0.80 and RMSE=5.54) and PCR (R2= 0.70 and RMSE=6.48) also worked well and the overall results were very similar to each other. Clay (positively correlated) and sand (negatively correlated) were the most influential variables for predicting CEC for the entire data set, while the most influential variables for the various countries and land uses were different and CEC was affected by different variables in different situations. Although the MANOVA and ANNs provided good predictions of the entire dataset, PSO gives a formula to estimate soil CEC using commonly tested soil properties. Therefore, PSO shows promise as a technique to estimate soil CEC. Establishing effective pedotransfer functions to predict CEC would be productive where there are limitations of time and money, and other commonly analyzed soil properties are available. References Khaledian, Y., Kiani, F., Ebrahimi, S., Brevik, E.C., Aitkenhead-Peterson, J. 2016. Assessment and monitoring of soil degradation during land use change using multivariate analysis. Land Degradation and Development. doi: 10.1002/ldr.2541.

Climate and Edaphic Controls on Humid Tropical Forest Tree Height

NASA Astrophysics Data System (ADS)

Yang, Y.; Saatchi, S. S.; Xu, L.

2014-12-01

Uncertainty in the magnitude and spatial variations of forest carbon density in tropical regions is due to under sampling of forest structure from inventory plots and the lack of regional allometry to estimate the carbon density from structure. Here we quantify the variation of tropical forest structure by using more than 2.5 million measurements of canopy height from systematic sampling of Geoscience Laser Altimeter System (GLAS) satellite observations between 2004 to 2008 and examine the climate and edaphic variables influencing the variations. We used top canopy height of GLAS footprints (~ 0.25 ha) to grid the statistical mean and 90 percentile of samples at 0.5 degrees to capture the regional variability of large trees in tropics. GLAS heights were also aggregated based on a stratification of tropical regions using soil, elevation, and forest types. Both approaches provided consistent patterns of statistically dominant large trees and the least heterogeneity, both as strong drivers of distribution of high biomass forests. Statistical models accounting for spatial autocorrelation suggest that climate, soil and spatial features together can explain more than 60% of the variations in observed tree height information, while climate-only variables explains about one third of the first-order changes in tree height. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as organic matters, all present independent but statistically significant relationships to tree height variations. The results confirm other landscape and regional studies that soil fertility, geology and climate may jointly control a majority of the regional variations of forest structure in pan-tropics and influencing both biomass stocks and dynamics. Consequently, other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.

Response to elevated CO2 in the temperate C3 grass Festuca arundinaceae across a wide range of soils

PubMed Central

Nord, Eric A.; Jaramillo, Raúl E.; Lynch, Jonathan P.

2015-01-01

Soils vary widely in mineral nutrient availability and physical characteristics, but the influence of this variability on plant responses to elevated CO2 remains poorly understood. As a first approximation of the effect of global soil variability on plant growth response to CO2, we evaluated the effect of CO2 on tall fescue (Festuca arundinacea) grown in soils representing 10 of the 12 global soil orders plus a high-fertility control. Plants were grown in small pots in continuously stirred reactor tanks in a greenhouse. Elevated CO2 (800 ppm) increased plant biomass in the high-fertility control and in two of the more fertile soils. Elevated CO2 had variable effects on foliar mineral concentration—nitrogen was not altered by elevated CO2, and phosphorus and potassium were only affected by CO2 in a small number of soils. While leaf photosynthesis was stimulated by elevated CO2 in six soils, canopy photosynthesis was not stimulated. Four principle components were identified; the first was associated with foliar minerals and soil clay, and the second with soil acidity and foliar manganese concentration. The third principle component was associated with gas exchange, and the fourth with plant biomass and soil minerals. Soils in which tall fescue did not respond to elevated CO2 account for 83% of global land area. These results show that variation in soil physical and chemical properties have important implications for plant responses to global change, and highlight the need to consider soil variability in models of vegetation response to global change. PMID:25774160

Influence of tillage in soil penetration resistance variability in an olive orchard

NASA Astrophysics Data System (ADS)

López de Herrera, Juan; Herrero Tejedor, Tomas; Saa-Requejo, Antonio; Tarquis, Ana M.

2015-04-01

Soil attributes usually present a high degree of spatial variation due to a combination of physical, chemical, biological or climatic processes operating at different scales. The quantification and interpretation of such variability is a key issue for site-specific soil management (Brouder et al., 2001). The usual geostatistical approach studies soil variability by means of the semi-variograms. However, recently a multiscaling approach has been applied on the determination of the scaling data properties (Kravechenko et al., 1999; Caniego et al., 2005; Tarquis et al., 2008). This work focus in the multifractal analysis as a way to characterize the variability of field data in a case study of soil penetrometer resistance (SPR) in two olive orchards, one applying tillage for 20 years and the other one non. The field measurements and soil data were obtained at the village of Puebla de Almenara (Cuenca, Spain) (39o 47'42.37'N, 2o 49'29.23'W) with 869 m of elevation approximately. The characteristic of the soil at the surface is classified as clay loam texture according to Guidelines for soil description of FAO. The soil consists of clays and red silts with some clusters of limestone's and sands. Two transect data were collected from 128 points between the squared of the olive tree, tillage and no tillage area, for SPR readings with a sampling interval of 50 cm. In each sampling, readings were obtained from 0 cm till 20 cm of depth, with an interval of 5 cm. The multifractal spectrum for each area and depth was estimated showing a characteristic pattern and differentiating both treatments. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Kravchenko, A.N., Boast, C.W., Bullock, D.G., 1999. Multifractal analysis of soil spatial variability. Agron. J. 91, 1033-1041. Caniego, F.J., R. Espejo, M.A. Martín, F. San José, 2005. Multifractal scaling of soil spatial variability. Ecological Modelling, 182, 291-303. Tarquis, A.M., N. Bird, M.C. Cartagena, A. Whitmore and Y. Pachepsky, 2008. Multiscale entropy-based analyses of soil transect data. Vadose Zone Journal, 7(2), 563-569.

Exploring the spatial variability of soil properties in an Alfisol Catena

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

Cokriging of Electromagnetic Induction Soil Electrical Conductivity Measurements and Soil Textural Properties to Demarcate Sub-field Management Zones for Precision Irrigation.

NASA Astrophysics Data System (ADS)

Ding, R.; Cruz, L.; Whitney, J.; Telenko, D.; Oware, E. K.

2017-12-01

There is the growing need for the development of efficient irrigation management practices due to increasing irrigation water scarcity as a result of growing population and changing climate. Soil texture primarily controls the water-holding capacity of soils, which determines the amount of irrigation water that will be available to the plant. However, while there are significant variabilities in the textural properties of the soil across a field, conventional irrigation practices ignore the underlying variability in the soil properties, resulting in over- or under-irrigation. Over-irrigation leaches plant nutrients beyond the root-zone leading to fertilizer, energy, and water wastages with dire environmental consequences. Under-irrigation, in contrast, causes water stress of the plant, thereby reducing plant quality and yield. The goal of this project is to leverage soil textural map of a field to create water management zones (MZs) to guide site-specific precision irrigation. There is increasing application of electromagnetic induction methods to rapidly and inexpensively map spatially continuous soil properties in terms of the apparent electrical conductivity (ECa) of the soil. ECa is a measure of the bulk soil properties, including soil texture, moisture, salinity, and cation exchange capacity, making an ECa map a pseudo-soil map. Data for the project were collected from a farm site at Eden, NY. The objective is to leverage high-resolution ECa map to predict spatially dense soil textural properties from limited measurements of soil texture. Thus, after performing ECa mapping, we conducted particle-size analysis of soil samples to determine the textural properties of soils at selected locations across the field. We cokriged the high-resolution ECa measurements with the sparse soil textural data to estimate a soil texture map for the field. We conducted irrigation experiments at selected locations to calibrate representative water-holding capacities of each estimated soil textural unit. Estimated soil units with similar water-holding characteristics were merged to create sub-field water MZs to guide precision irrigation of each MZ, instructed by each MZ's calibrated water-holding properties.

Bacteria as Emerging Indicators of Soil Condition

PubMed Central

Hermans, Syrie M.; Buckley, Hannah L.; Case, Bradley S.; Curran-Cournane, Fiona; Taylor, Matthew

2016-01-01

ABSTRACT Bacterial communities are important for the health and productivity of soil ecosystems and have great potential as novel indicators of environmental perturbations. To assess how they are affected by anthropogenic activity and to determine their ability to provide alternative metrics of environmental health, we sought to define which soil variables bacteria respond to across multiple soil types and land uses. We determined, through 16S rRNA gene amplicon sequencing, the composition of bacterial communities in soil samples from 110 natural or human-impacted sites, located up to 300 km apart. Overall, soil bacterial communities varied more in response to changing soil environments than in response to changes in climate or increasing geographic distance. We identified strong correlations between the relative abundances of members of Pirellulaceae and soil pH, members of Gaiellaceae and carbon-to-nitrogen ratios, members of Bradyrhizobium and the levels of Olsen P (a measure of plant available phosphorus), and members of Chitinophagaceae and aluminum concentrations. These relationships between specific soil attributes and individual soil taxa not only highlight ecological characteristics of these organisms but also demonstrate the ability of key bacterial taxonomic groups to reflect the impact of specific anthropogenic activities, even in comparisons of samples across large geographic areas and diverse soil types. Overall, we provide strong evidence that there is scope to use relative taxon abundances as biological indicators of soil condition. IMPORTANCE The impact of land use change and management on soil microbial community composition remains poorly understood. Therefore, we explored the relationship between a wide range of soil factors and soil bacterial community composition. We included variables related to anthropogenic activity and collected samples across a large spatial scale to interrogate the complex relationships between various bacterial community attributes and soil condition. We provide evidence of strong relationships between individual taxa and specific soil attributes even across large spatial scales and soil and land use types. Collectively, we were able to demonstrate the largely untapped potential of microorganisms to indicate the condition of soil and thereby influence the way that we monitor the effects of anthropogenic activity on soil ecosystems into the future. PMID:27793827

Bacteria as Emerging Indicators of Soil Condition.

PubMed

Hermans, Syrie M; Buckley, Hannah L; Case, Bradley S; Curran-Cournane, Fiona; Taylor, Matthew; Lear, Gavin

2017-01-01

Bacterial communities are important for the health and productivity of soil ecosystems and have great potential as novel indicators of environmental perturbations. To assess how they are affected by anthropogenic activity and to determine their ability to provide alternative metrics of environmental health, we sought to define which soil variables bacteria respond to across multiple soil types and land uses. We determined, through 16S rRNA gene amplicon sequencing, the composition of bacterial communities in soil samples from 110 natural or human-impacted sites, located up to 300 km apart. Overall, soil bacterial communities varied more in response to changing soil environments than in response to changes in climate or increasing geographic distance. We identified strong correlations between the relative abundances of members of Pirellulaceae and soil pH, members of Gaiellaceae and carbon-to-nitrogen ratios, members of Bradyrhizobium and the levels of Olsen P (a measure of plant available phosphorus), and members of Chitinophagaceae and aluminum concentrations. These relationships between specific soil attributes and individual soil taxa not only highlight ecological characteristics of these organisms but also demonstrate the ability of key bacterial taxonomic groups to reflect the impact of specific anthropogenic activities, even in comparisons of samples across large geographic areas and diverse soil types. Overall, we provide strong evidence that there is scope to use relative taxon abundances as biological indicators of soil condition. The impact of land use change and management on soil microbial community composition remains poorly understood. Therefore, we explored the relationship between a wide range of soil factors and soil bacterial community composition. We included variables related to anthropogenic activity and collected samples across a large spatial scale to interrogate the complex relationships between various bacterial community attributes and soil condition. We provide evidence of strong relationships between individual taxa and specific soil attributes even across large spatial scales and soil and land use types. Collectively, we were able to demonstrate the largely untapped potential of microorganisms to indicate the condition of soil and thereby influence the way that we monitor the effects of anthropogenic activity on soil ecosystems into the future. Copyright © 2016 American Society for Microbiology.

1100 years of human impact on woodland and soils in Kjarardalur, West Iceland

NASA Astrophysics Data System (ADS)

Gísladóttir, Guðrún; Erlendsson, Egill; Lal, Rattan

2013-04-01

Prior to the Norse settlement of Iceland around AD 874 climate was the principal control of ecosystem variability. Since then, drastic changes have been imposed on the island's ecosystem through human activities. Unsustainable land use has reduced vegetation coverage, altered floral composition and accelerated soil erosion, especially in conjunction with harsh climate. Healthy ecosystem, soil and vegetation, is not only an important resource to meet human demands but also a prominent sink of atmospheric CO2. In contrast, soil erosion and land degradation are major sources of atmospheric CO2. This study discusses the impact of human activities and climate change on vegetation, soil erosion, and soil organic carbon (SOC) in West Iceland. Analyses conducted include pollen in Histosols, soil properties, soil accumulation rates and SOC in Histosols and Andosols. Our data demonstrate a pre-settlement landscape that was not entirely stable, where relatively small differences in climate may have caused subtle changes to the terrestrial environment. However, the early colonists and subsequent occupants altered the environment significantly. The magnitude of alteration was spatially variable depending on land management. The vegetation and soil data demonstrate a swift transformation of environmental conditions across AD 874. The most profound impacts include reduction in birch woodland and concurrent decline of important habitat for fragile understory, which facilitated soil exposure and reduced soil quality. After about 300 years, land degradation-anticipated management towards enhanced sustainability was probably adopted at one of the farming properties in the study area, allowing for soil recovery after a period of drastic decline. At other properties unsustainable land use continued to degrade the terrestrial ecosystem. The late-Medieval climatic change and introduction of the Little-Ice age exerted added strain on the environments over the entire area, resulting in further soil degradation. The property where sustainable land use had been adopted preserved woodland cover and maintained greater soil quality than elsewhere in the valley, where thresholds of ecosystem resilience were crossed. Unsustainable land use over 1100 years caused vegetation denudation that accelerated soil erosion, with attendant redistribution of soil over the landscape, and decline in its quality. Vegetated areas became important sinks for wind-transported soils, as evidenced by increase in deposition rate and higher bulk density. This led to an increase in susceptibility to soil erosion, and decline in SOC content. Despite decrease in SOC content, the high sedimentation rate and elevated bulk weight resulted in higher SOC sequestration at these sites, even though soil quality declined. The potential soil C sequestration in adjacent sparsely or devegetated soils were highly impaired and along with soil mass losses these areas became sources of anthropogenic CO2.

A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu

2017-04-01

Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various Fluxnet sites across Europe, we find the model has good skill and can particularly capture periods of low soil moisture well. We illustrate the relevance of the dependence structure of these Y variables to soil moisture and show how it may be generalised to offer information of soil moisture on a widespread scale where few observations of soil moisture exist. We then present results from a validation study of a selection of EURO CORDEX climate models where we demonstrate the skill of these models in representing these dependencies and so offer insight into the skill seen in the representation of soil moisture in these models.

Soil eco-physiological indicators from a coal mining area in El Bierzo District (Spain).

NASA Astrophysics Data System (ADS)

Díaz Puente, Fco. Javier; Mejuto Mendieta, Marcos; Cardona García, Ana Isabel; Rodríguez Gallego, Vergelina; García Álvarez, Avelino

2010-05-01

CIEMAT. Avda. Complutense, 22. 28040 Madrid. Spain. The El Bierzo carboniferous basin (León, N.W. of Spain) is placed in a tenth of the surface of this district, in the area called "Bierzo Alto". Coal has been mined in El Bierzo from the late XVIII century, having been intensely exploited during the XX century. The mining activity has left a heritage of withdrawed mining structures. Nowadays some mining activity remains in the area, and new exploitations based on open pit processes, cause the burial of natural soil with overlaying mine tailings. Characterization and study of the edaphic landscapes in the area is a necessary activity within the framework of its overall restoration planning, also providing fundamental information for the design and monitoring of waste coal recovery activities. For this work eight zones were chosen, representing the spatial variability within the upper basin of the Rodrigatos river, into the Bierzo Alto, including reference areas not affected by mining activities. In addition three mine tailings outside the area are included in this work to cover the variability of restoration processes. After a first study, based on physical, physico-chemical and chemical characteristics of soils, we have continued the study including some eco-physiological parameters. The objective of this work is to identify potential soil disruption, its extent and causes. Soil microbial activity is influenced by a wide set of soil characteristics. Eco-physiological parameters analysed in this work are: • Microbial Biomass carbon • Basal Respirometry • Maximum respiratory rate Microbial biomass carbon was analysed according the Substrate Induced Respirometry (SIR) method. Relational parameters such as metabolic quotient (CO2-C/Cmic) and the Cmic/Corg ratio have been obtained from these variables. Our results shown that soil microbial biomass carbon is strongly influenced by the water holding capacity (WHC) of the samples (R=0,895) as well as by organic matter (O.M.) content (R=0,801), in addition, WHC and O.M. are also strongly related (R=0,794), so O.M. seems to be the key variable in the soils studied. Recovery stage of the studied plots may be stablished with each of the mentioned parameters. All the correlations mentioned were significant at P<0.001 level. Maximum respiratory rate as well as Metabolic quotient data also allow to identify most stressed soils, corresponding with coal mine tailings in the Rodrigatos river basin. Results obtained for Cmic/Corg ratio show difficulties to be interpreted in the case of mine tailings. The practice of burying soils with coal mining debris has provided this new surface with relatively high inputs of organic carbon, in excess of this provided from fresh organic matter. In our study eco-physiological parameters are usefull tools in order to clasify the restoration level of mine tailings, specially those parameters having a high correlation with the organic matter content, Nevertheless some of those parameters then present some added difficulties to be interpreted that will be discussed in this work. Acknowledgement: We appreciate technical support in the field from Mr. Luis del Riego Celada, as well as the financial support from the Fundación Ciudad de la Energía.

[Spatial variability of surface soil nutrients in the landslide area of Beichuan County, South- west China, after 5 · 12 Wenchuan Earthquake].

PubMed

Mai, Ji-shan; Zhao, Ting-ning; Zheng, Jiang-kun; Shi, Chang-qing

2015-12-01

Based on grid sampling and laboratory analysis, spatial variability of surface soil nutrients was analyzed with GS⁺ and other statistics methods on the landslide area of Fenghuang Mountain, Leigu Town, Beichuan County. The results showed that except for high variability of available phosphorus, other soil nutrients exhibited moderate variability. The ratios of nugget to sill of the soil available phosphorus and soil organic carbon were 27.9% and 28.8%, respectively, showing moderate spatial correlation, while the ratios of nugget to sill of the total nitrogen (20.0%), total phosphorus (24.3%), total potassium (11.1%), available nitrogen (11.2%), and available potassium (22.7%) suggested strong spatial correlation. The total phosphorus had the maximum range (1232.7 m), followed by available nitrogen (541.27 m), total nitrogen (468.35 m), total potassium (136.0 m), available potassium (128.7 m), available phosphorus (116.6 m), and soil organic carbon (93.5 m). Soil nutrients had no significant variation with the increase of altitude, but gradually increased from the landslide area, the transition area, to the little-impacted area. The total and available phosphorus contents of the landslide area decreased by 10.3% and 79.7% compared to that of the little-impacted area, respectively. The soil nutrient contents in the transition area accounted for 31.1%-87.2% of that of the little-impacted area, with the nant reason for the spatial variability of surface soil nutrients.

Variation in Soil Respiration across Soil and Vegetation Types in an Alpine Valley

PubMed Central

Rubin, Aurélie

2016-01-01

Background and Aims Soils of mountain regions and their associated plant communities are highly diverse over short spatial scales due to the heterogeneity of geological substrates and highly dynamic geomorphic processes. The consequences of this heterogeneity for biogeochemical transfers, however, remain poorly documented. The objective of this study was to quantify the variability of soil-surface carbon dioxide efflux, known as soil respiration (Rs), across soil and vegetation types in an Alpine valley. To this aim, we measured Rs rates during the peak and late growing season (July-October) in 48 plots located in pastoral areas of a small valley of the Swiss Alps. Findings Four herbaceous vegetation types were identified, three corresponding to different stages of primary succession (Petasition paradoxi in pioneer conditions, Seslerion in more advanced stages and Poion alpinae replacing the climactic forests), as well as one (Rumicion alpinae) corresponding to eutrophic grasslands in intensively grazed areas. Soils were developed on calcareous alluvial and colluvial fan deposits and were classified into six types including three Fluvisols grades and three Cambisols grades. Plant and soil types had a high level of co-occurrence. The strongest predictor of Rs was soil temperature, yet we detected additional explanatory power of sampling month, showing that temporal variation was not entirely reducible to variations in temperature. Vegetation and soil types were also major determinants of Rs. During the warmest month (August), Rs rates varied by over a factor three between soil and vegetation types, ranging from 2.5 μmol m-2 s-1 in pioneer environments (Petasition on Very Young Fluvisols) to 8.5 μmol m-2 s-1 in differentiated soils supporting nitrophilous species (Rumicion on Calcaric Cambisols). Conclusions Overall, this study provides quantitative estimates of spatial and temporal variability in Rs in the mountain environment, and demonstrates that estimations of soil carbon efflux at the watershed scale in complex geomorphic terrain have to account for soil and vegetation heterogeneity. PMID:27685955

Rethinking Soils: an under-investigated commons?

NASA Astrophysics Data System (ADS)

Short, Chrisopher; Mills, Jane; Ingram, Julie

2015-04-01

In a number of global contexts there is a re-awakening of interest in soils in both increasing the resilience of complex social-ecological systems (SES) and as a result of the threats to them, as shown by the UN International Year of Soils in 2015. Consequently the management of soils and their wider role within property regimes and natural resource management might need to be reassessed. At the heart of this is the rise in awareness regarding the connectedness of SES, and in frameworks such as the Ecosystem Approach and the identification and analysis of Ecosystem Services. Whilst not new to some, it has widened the understanding among many, that soils have a valuable role to play in complex SES because they are a slow variable crucial to underlying structure of the SES. The conventional approach that soils are linked to the ecosystem services category of provisioning services (production of food, timber and fibre) remains valid. Not surprisingly this link is strong within natural resource management and property rights regimes but soils remain at risk for a range of threats, for example soil erosion and compaction, salinization, sealing, desertification, loss of organic matter and biodiversity and contamination. However, soils are increasingly seen as a slow variable that can lead to increased resilience within a SES and have a profound importance to human life through a range of regulating services including water quality and purification, water flow and attenuation and , pest and disease control. Given the long-standing importance of soil as a natural resource there are also accompanying legal systems, property regimes, societal values, knowledge, custom and traditions. However, in the light of the wider understanding soil functions are these social frameworks appropriate and fit for purpose or would a shared resource of commons approach be more appropriate. To some extent this examination would also extend to the presence of soils within the cultural services category of ecosystem services. As a result of the increasing evidence regarding soil threats, there is concern that the knowledge relating to soils is fragmented and incomplete. This is particular true regarding the complexity and functioning of soil systems and their interaction with human activities and the effectiveness of governance arrangements to promote resilience in the management of soils. Therefore discussions concerning soils needs to be taken from an interdisciplinary perspectives that embraces both natural and social sciences. This paper will seek to examine soils from a multi-scale governance/complex commons perspective. It will also consider how a commons perspective might be useful in reducing soil threats and in the development of effective prevention, remediation and restoration measures. This often requires a change in thinking about soil, perhaps considering it as a 'slow variable', able to drive long-term change or as a 'cultural asset' and 'knowledge resource'.

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

NASA Astrophysics Data System (ADS)

Wang, Tao; Ottlé, Catherine; Boone, Aaron; Ciais, Philippe; Brun, Eric; Morin, Samuel; Krinner, Gerhard; Piao, Shilong; Peng, Shushi

2013-06-01

Snow plays an important role in land surface models (LSM) for climate and model applied over Fran studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

Soil Greenhouse Gas Emissions from a Subtropical Mangrove in Hong Kong

NASA Astrophysics Data System (ADS)

Lai, D. Y. F.; Xu, J.

2014-12-01

The concept of "blue carbon" has received increasing attention recently, which points to the potential role of vegetated coastal wetlands in carbon sequestration. Yet, the magnitude and controls of greenhouse gas emissions from coastal wetland ecosystems, especially mangroves in the subtropical regions, are still largely unknown. In this study, we conducted chamber measurements in the Mai Po Marshes Nature Reserve of Hong Kong at monthly intervals to characterize the spatial and temporal variability of the emission of greenhouse gases, including CO2, CH4 and N2O from mangrove soils, and examine the influence of environmental and biotic variables on greenhouse gas fluxes. We found the highest mean CH4 and N2O emissions in autumn and the highest CO2 flux in summer. Along the tidal gradient, we observed significantly higher CH4 and N2O emissions from the middle zones and landward zones, respectively, while no clear spatial variation of CO2 emissions was observed. There were significantly higher soil greenhouse gas emissions from sites dominated by Avicennia marina than those dominated by Kandelia obovata, which might be due to the presence of pneumatophores which facilitated gas transport. We found a significant, negative correlation between CH4 flux and soil NO3-N concentration, while CO2 flux was positively correlation with total Kjeldahl nitrogen content. Soil temperature was positively correlated with the emissions of all three greenhouse gases, while water table depth was positively and negatively correlated with CH4 and N2O emissions, respectively. Our findings demonstrate the high spatial and temporal variability of greenhouse gas emissions from mangrove soils which could be attributed in part to the differences in environmental conditions and dominant plant species.

Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

NASA Astrophysics Data System (ADS)

Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

2017-12-01

Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.

The Temperature Sensitivity (Q10) of Soil Respiration: Controlling Factors and Spatial Prediction at Regional Scale Based on Environmental Soil Classes

NASA Astrophysics Data System (ADS)

Meyer, N.; Welp, G.; Amelung, W.

2018-02-01

The temperature sensitivity of heterotrophic soil respiration is crucial for modeling carbon dynamics but it is variable. Presently, however, most models employ a fixed value of 1.5 or 2.0 for the increase of soil respiration per 10°C increase in temperature (Q10). Here we identified the variability of Q10 at a regional scale (Rur catchment, Germany/Belgium/Netherlands). We divided the study catchment into environmental soil classes (ESCs), which we define as unique combinations of land use, aggregated soil groups, and texture. We took nine soil samples from each ESC (108 samples) and incubated them at four soil moisture levels and five temperatures (5-25°C). We hypothesized that Q10 variability is controlled by soil organic carbon (SOC) degradability and soil moisture and that ESC can be used as a widely available proxy for Q10, owing to differences in SOC degradability. Measured Q10 values ranged from 1.2 to 2.8 and were correlated with indicators of SOC degradability (e.g., pH, r = -0.52). The effect of soil moisture on Q10 was variable: Q10 increased with moisture in croplands but decreased in forests. The ESC captured significant parts of Q10 variability under dry (R2 = 0.44) and intermediate (R2 = 0.36) moisture conditions, where Q10 increased in the order cropland

On the importance of variable soil depth and process representation in the modeling of shallow landslide initiation

NASA Astrophysics Data System (ADS)

Fatichi, S.; Burlando, P.; Anagnostopoulos, G.

2014-12-01

Sub-surface hydrology has a dominant role on the initiation of rainfall-induced landslides, since changes in the soil water potential affect soil shear strength and thus apparent cohesion. Especially on steep slopes and shallow soils, loss of shear strength can lead to failure even in unsaturated conditions. A process based model, HYDROlisthisis, characterized by high resolution in space and, time is developed to investigate the interactions between surface and subsurface hydrology and shallow landslide initiation. Specifically, 3D variably saturated flow conditions, including soil hydraulic hysteresis and preferential flow, are simulated for the subsurface flow, coupled with a surface runoff routine. Evapotranspiration and specific root water uptake are taken into account for continuous simulations of soil water content during storm and inter-storm periods. The geotechnical component of the model is based on a multidimensional limit equilibrium analysis, which takes into account the basic principles of unsaturated soil mechanics. The model is applied to a small catchment in Switzerland historically prone to rainfall-triggered landslides. A series of numerical simulations were carried out with various boundary conditions (soil depths) and using hydrological and geotechnical components of different complexity. Specifically, the sensitivity to the inclusion of preferential flow and soil hydraulic hysteresis was tested together with the replacement of the infinite slope assumption with a multi-dimensional limit equilibrium analysis. The effect of the different model components on model performance was assessed using accuracy statistics and Receiver Operating Characteristic (ROC) curve. The results show that boundary conditions play a crucial role in the model performance and that the introduced hydrological (preferential flow and soil hydraulic hysteresis) and geotechnical components (multidimensional limit equilibrium analysis) considerably improve predictive capabilities in the presented case study.

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

2000-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

1997-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or "time to drying" (t(sub d)), is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage 1 drying (as water is removed from storage), and then become more or less constant during soil limited, or "stage 2" drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

Treesearch

Tana Wood; M. Detto; W.L. Silver

2013-01-01

Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal...

Biomechanical effects, lithological variations, and local pedodiversity in some forest soils of Arkansas

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2005-01-01

A high degree of soil variability over short distances and small areas is common, particularly in forest soils. This variability is sometimes, but not always, related to readily apparent variations in the environmental factors that control soil formation. This study examines the potential role of biomechanical effects of trees and of lithological variations within the...

Nitrate and dissolved organic carbon mobilization in response to soil freezing variability

Treesearch

Colin B. Fuss; Charles T. Driscoll; Peter M. Groffman; John L. Campbell; Lynn M. Christenson; Timothy J. Fahey; Melany C. Fisk; Myron J. Mitchell; Pamela H. Templer; Jorge Durán; Jennifer L. Morse

2016-01-01

Reduced snowpack and associated increases in soil freezing severity resulting from winter climate change have the potential to disrupt carbon (C) and nitrogen (N) cycling in soils. We used a natural winter climate gradient based on elevation and aspect in a northern hardwood forest to examine the effects of variability in soil freezing depth, duration, and frequency on...

Electrical resistivity tomography to delineate greenhouse soil variability

NASA Astrophysics Data System (ADS)

Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.

2013-03-01

Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

Spatial-temporal variability in GHG fluxes and their functional interpretation in RusFluxNet

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Meshalkina, Julia; Sarzhanov, Dmitriy; Mazirov, Ilia; Yaroslavtsev, Alex; Komarova, Tatiana; Tikhonova, Maria

2016-04-01

High spatial and temporal variability is mutual feature for most modern boreal landscapes in the European Territory of Russia. This variability is result of their relatively young natural and land-use age with very complicated development stories. RusFluxNet includes a functionally-zonal set of representative natural, agricultural and urban ecosystems from the Central Forest Reserve in the north till the Central Chernozemic Reserve in the south (more than 1000 km distance). Especial attention has been traditionally given to their soil cover and land-use detailed variability, morphogenetic and functional dynamics. Central Forest Biosphere Reserve (360 km to North-West from Moscow) is the principal southern-taiga one in the European territory of Russia with long history of mature spruce ecosystem structure and dynamics investigation. Our studies (in frame of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) have been concentrated on the soil carbon stocks and GHG fluxes spatial variability and dynamics due to dominated there windthrow and fallow-forest successions. In Moscow RTSAU campus gives a good possibility to develop the ecosystem and soil monitoring of GHG fluxes in the comparable sites of urban forest, field crops and lawn ecosystems taking especial attention on their meso- and micro-relief, soil cover patterns and subsoil, vegetation and land-use technologies, temperature and moisture spatial and temporal variability. In the Central Chernozemic Biosphere Reserve and adjacent areas we do the comparative analysis of GHG fluxes and balances in the virgin and mowed meadow-steppe, forest, pasture, cropland and three types of urban ecosystems with similar subsoil and relief conditions. The carried out researches have shown not only sharp (in 2-5 times) changes in GHG ecosystem and soil fluxes and balances due to seasonal and daily microclimate variation, vegetation and crop development but their essential (in 2-4 times) spatial variability due to different meso- or micro-relief forms, natural or man-made succession studies, topsoil texture or organic matter state, subsoil or perched groundwater features. Zonal, seasonal and functional subdividing the monitoring data allows essentially increase the regression links between GHG fluxes and air or soil temperature and moisture (to 0.75-0.87) that is very important for their modeling and prediction. In taiga and mix-forest zones usually there is stronger effect on GHG fluxes by air temperature than soil one due to comparatively thin (from 3 till 10 cm) layer of principal soil organic and/or humus-accumulative horizons with maximum biological activity that usually determines the total rate of GHG soil fluxes. Unfavorable seasonal conditions (dry season or low temperature) determine essential (in 1.5-2 times) decreasing not only in soil GHG fluxes but in level of their spatial variability, intraseasonal and daily dynamics too. These trends are most obvious in case of more open and sensitive to the external factors ecosystems, for example in case of industrial area lawns or at the first stages of the windthrow or fallow-forest successions. Understanding the principal regional and land-use-determined regularities of spatial and temporal changes in ecosystem and soil GHG fluxes help better modeling them in the process of spatial intra- and extrapolations, seasonal and interseasonal predictions, taking into attention basic and current principal ecological factors limiting GHG fluxes and balances. Their introduction in the ecological or agroecological models and land-use decision support systems allows improve the quality of environmental/agroecological monitoring and control not only for GHG emission but also for soil organic matter conservation, manure and nitrogen fertilizer application that is often crucially important for sustainable rural development and profitable farming.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Young Children's Thinking About Decomposition: Early Modeling Entrees to Complex Ideas in Science

NASA Astrophysics Data System (ADS)

Ero-Tolliver, Isi; Lucas, Deborah; Schauble, Leona

2013-10-01

This study was part of a multi-year project on the development of elementary students' modeling approaches to understanding the life sciences. Twenty-three first grade students conducted a series of coordinated observations and investigations on decomposition, a topic that is rarely addressed in the early grades. The instruction included in-class observations of different types of soil and soil profiling, visits to the school's compost bin, structured observations of decaying organic matter of various kinds, study of organisms that live in the soil, and models of environmental conditions that affect rates of decomposition. Both before and after instruction, students completed a written performance assessment that asked them to reason about the process of decomposition. Additional information was gathered through one-on-one interviews with six focus students who represented variability of performance across the class. During instruction, researchers collected video of classroom activity, student science journal entries, and charts and illustrations produced by the teacher. After instruction, the first-grade students showed a more nuanced understanding of the composition and variability of soils, the role of visible organisms in decomposition, and environmental factors that influence rates of decomposition. Through a variety of representational devices, including drawings, narrative records, and physical models, students came to regard decomposition as a process, rather than simply as an end state that does not require explanation.

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

Global Soil Respiration: Interaction with Environmental Variables and Response to Climate Change

NASA Astrophysics Data System (ADS)

Jian, J.; Steele, M.

2016-12-01

Background, methods, objectivesTerrestrial ecosystems take up around 1.7 Pg C per year; however, the role of terrestrial ecosystems as a carbon sink may change to carbon source by 2050, as a result of positive feedback of soil respiration response to global warming. Nevertheless, limited evidence shows that soil carbon is decreasing and the role of terrestrial ecosystems is changing under warming. One possibility is the positive feedback may slow due to the acclimation of soil respiration as a result of decreasing temperature sensitivity (Q10) with warming. To verify and quantify the uncertainty in soil carbon cycling and feedbacks to climate change, we assembled soil respiration observations from 1961 to 2014 from 724 publications into a monthly global soil respiration database (MSRDB), which included 13482 soil respiration measurements together with 38 other ancillary measurements from 538 sites. Using this database we examined macroscale variation in the relationship between soil respiration and air temperature, precipitation, leaf area index and soil properties. We also quantified global soil respiration, the sources of uncertainty, and its feedback to warming based on climate region-oriented models with variant Q10function. Results and ConclusionsOur results showed substantial heterogeneity in the relationship between soil respiration and environmental factors across different climate regions. For example, soil respiration was strongly related to vegetation (via leaf area index) in colder regions, but not in tropical region. Only in tropical and arid regions did soil properties explain any variation in soil respiration. Global annual mean soil respiration from 1961 to 2014 was estimated to be 72.41 Pg C yr-1 based on monthly global soil respiration database, 25 Pg lower than estimated based on yearly soil respiration database. By using the variable Q10 models, we estimated that global soil respiration increased at a rate of 0.03 Pg C yr-1 from 1961 to 2014, smaller than previous studies ( 0.1 Pg C yr-1). The substantial variations in these relationships suggest that regional scales is important for understanding and prediction of global carbon cycling and how it response to climate change.

Application of manures to mitigate the harmful effects of electrokinetic remediation of heavy metals on soil microbial properties in polluted soils.

PubMed

Tahmasbian, Iman; Safari Sinegani, Ali Akbar; Nguyen, Thi Thu Nhan; Che, Rongxiao; Phan, Thuc D; Hosseini Bai, Shahla

2017-12-01

Ethylenediaminetetraacetic acid (EDTA) used with electrokinetic (EK) to remediate heavy metal-polluted soils is a toxic chelate for soil microorganisms. Therefore, this study aimed to evaluate the effects of alternative organic chelates to EDTA on improving the microbial properties of a heavy metal-polluted soil subjected to EK. Cow manure extract (CME), poultry manure extract (PME) and EDTA were applied to a lead (Pb) and zinc (Zn)-polluted calcareous soil which were subjected to two electric intensities (1.1 and 3.3 v/cm). Soil carbon pools, microbial activity, microbial abundance (e.g., fungal, actinomycetes and bacterial abundances) and diethylenetriaminepentaacetic acid (DTPA)-extractable Pb and Zn (available forms) were assessed in both cathodic and anodic soils. Applying the EK to soil decreased all the microbial variables in the cathodic and anodic soils in the absence or presence of chelates. Both CME and PME applied with two electric intensities decreased the negative effect of EK on soil microbial variables. The lowest values of soil microbial variables were observed when EK was combined with EDTA. The following order was observed in values of soil microbial variables after treating with EK and chelates: EK + CME or EK + PME > EK > EK + EDTA. The CME and PME could increase the concentrations of available Pb and Zn, although the increase was less than that of EDTA. Overall, despite increasing soil available Pb and Zn, the combination of EK with manures (CME or PME) mitigated the negative effects of using EK on soil microbial properties. This study suggested that the synthetic chelates such as EDTA could be replaced with manures to alleviate the environmental risks of EK application.

The contribution of hydroxylamine content to spatial variability of N2O formation in soil of a Norway spruce forest

NASA Astrophysics Data System (ADS)

Liu, Shurong; Herbst, Michael; Bol, Roland; Gottselig, Nina; Pütz, Thomas; Weymann, Daniel; Wiekenkamp, Inge; Vereecken, Harry; Brüggemann, Nicolas

2016-04-01

Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions.

Polychlorinated biphenyl concentrations, accumulation rates in soil from atmospheric deposition and analysis of their affecting landscape variables along an urban-rural gradient in Shanghai, China.

PubMed

Fang, Shubo; Cui, Qu; Matherne, Brian; Hou, Aixin

2017-11-01

This study initiated an in-situ soil experimental system to quantify the annual dynamics of polychlorinated biphenyl (PCB) congener's concentrations and accumulation rates in soil from atmosphere deposition in a rural-urban fringe, and correlated them by landscape physical and demographic variables in the area. The results showed that the concentrations of all PCB congeners significantly increased with the sampling time (p < 0.05); nearly all the PCB congener concentrations decreased while moving outwards from the urban center. The moderate average concentrations along the gradient for PCB 8, 18, and 28 were 31.003, 18.825, and 19.505 ng g-1, respectively. Tetra-CBs including PCB 44, 52, 66, and 77 were 10.243, 31.214, 8.330 and 9.530 ng g-1, respectively. Penta-CBs including PCB 101, 105, 118, and 126 were 9.465, 7.896, 17.703, and 6.363 ng g-1, respectively. Hexa-CBs including PCB 128, 138, 153, 170, 180, and 187 were 6.798, 11.522, 4.969, 6.722, 6.317, and 8.243 ng g-1 respectively. PCB 195, 206, and 209 were 8.259, 9.506, and 14.169 ng g-1, respectively. Most of the PCB congeners had a higher accumulation rate approximately 28 km from the urban center. The computed variables were found to affect the soil PCB concentrations with a threshold effect (p < 0.05). Regression analysis showed that the thresholds were 10-20 km, 1 km/km 2 , 30%, and 20% for distance, road density, population change index, and built-up area percentage, respectively. It was concluded that factors related to industrial development, traffic, and urban sprawling (i.e. built-up areas expanding) were the sources of PCBs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe.

PubMed

Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T

2018-05-01

The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.

Soil ionomic and enzymatic responses and correlations to fertilizations amended with and without organic fertilizer in long-term experiments.

PubMed

Feng, Xumeng; Ling, Ning; Chen, Huan; Zhu, Chen; Duan, Yinghua; Peng, Chang; Yu, Guanghui; Ran, Wei; Shen, Qirong; Guo, Shiwei

2016-04-15

To investigate potential interactions between the soil ionome and enzyme activities affected by fertilization with or without organic fertilizer, soil samples were collected from four long-term experiments over China. Irrespective of variable interactions, fertilization type was the major factor impacting soil ionomic behavior and accounted for 15.14% of the overall impact. Sampling site was the major factor affecting soil enzymatic profile and accounted for 34.25% of the overall impact. The availabilities of Pb, La, Ni, Co, Fe and Al were significantly higher in soil with only chemical fertilizer than the soil with organic amendment. Most of the soil enzyme activities, including α-glucosidase activity, were significantly activated by organic amendment. Network analysis between the soil ionome and the soil enzyme activities was more complex in the organic-amended soils than in the chemical fertilized soils, whereas the network analysis among the soil ions was less complex with organic amendment. Moreover, α-glucosidase was revealed to generally harbor more corrections with the soil ionic availabilities in network. We concluded that some of the soil enzymes activated by organic input can make the soil more vigorous and stable and that the α-glucosidase revealed by this analysis might help stabilize the soil ion availability.

Soil ionomic and enzymatic responses and correlations to fertilizations amended with and without organic fertilizer in long-term experiments

PubMed Central

Feng, Xumeng; Ling, Ning; Chen, Huan; Zhu, Chen; Duan, Yinghua; Peng, Chang; Yu, Guanghui; Ran, Wei; Shen, Qirong; Guo, Shiwei

2016-01-01

To investigate potential interactions between the soil ionome and enzyme activities affected by fertilization with or without organic fertilizer, soil samples were collected from four long-term experiments over China. Irrespective of variable interactions, fertilization type was the major factor impacting soil ionomic behavior and accounted for 15.14% of the overall impact. Sampling site was the major factor affecting soil enzymatic profile and accounted for 34.25% of the overall impact. The availabilities of Pb, La, Ni, Co, Fe and Al were significantly higher in soil with only chemical fertilizer than the soil with organic amendment. Most of the soil enzyme activities, including α-glucosidase activity, were significantly activated by organic amendment. Network analysis between the soil ionome and the soil enzyme activities was more complex in the organic-amended soils than in the chemical fertilized soils, whereas the network analysis among the soil ions was less complex with organic amendment. Moreover, α-glucosidase was revealed to generally harbor more corrections with the soil ionic availabilities in network. We concluded that some of the soil enzymes activated by organic input can make the soil more vigorous and stable and that the α-glucosidase revealed by this analysis might help stabilize the soil ion availability. PMID:27079657

Attributing spatial and temporal changes in soil C in the UK to environmental drivers

NASA Astrophysics Data System (ADS)

Thomas, Amy; Cosby, Bernard; Quin, Sam; Henrys, Pete; Robinson, David; Emmett, Bridget

2015-04-01

The largest terrestrial pool of carbon is found in soils. Understanding how soil C responds to drivers of change (land use and management, atmospheric deposition, climate change) and how these responses are modified by inherent soil properties is crucial if we are to manage soils more sustainably in the future. Here we attempt to attribute spatial and temporal changes in UK soil C to environmental drivers using data from the UK Countryside Survey (CS), a national soil survey across England, Scotland and Wales repeated in 1978, 1998 and 2007. A mixed model approach was used to model soil C concentration (g C kg-1) and density (t C ha-1) and their absolute changes for the time periods 1978-1998, 1998-2007 and 1978-2007 across the CS sites using a variety of explanatory variables: soil (parent material, pH, moisture, Olsen-P, Shannon Diversity Index); atmospheric deposition (nitrogen and sulphur); climate (growing degree days and rain); and land use (aggregate vegetation class). Spatially, prediction of soil C concentration was good; soil moisture, pH, vegetation class and dominant grain size were all significant predictors. Field capacity also appeared to be important; however this data was only collected for a fraction of sites. N% was also strongly related to soil C concentration and density, as would be expected due to coupling of C and N in soil OM pools. Although N may drive soil C through impact on plant productivity, this cannot be separated from correlated C and N losses with OM decomposition, and hence N was not included as a driver for modelling. Predictive power for C density is not as strong as for concentration, which may reflect nonlinear relationships not represented by the modelling approach. Temporally, change in soil C is more difficult to explain, and model predictive power was lower. Change in soil pH was important in explaining change in C concentration and density, along with change in atmospheric deposition; decrease in deposition and associated soil acidity (increase in pH) was associated with a decrease in soil C concentration and density. Change in soil moisture or rainfall was also important. Inherent soil and site properties such as soil texture, vegetation class and parent material appeared to contribute most to the prediction of soil C change through modulation of the relationship between change in soil C and change in pH. Including anthropogenic and natural drivers in models of soil C stocks and changes in the UK enables assessment of the relative importance of each across the UK CS sites, however interactions among the drivers are more difficult to disentangle. Given the statistical significance of a number of drivers and soil variables in predicting soil C stocks and changes in the UK, it is important that these continue to be measured to allow better model development and more reliable predictions of future soil C conditions.

Influence of management history and landscape variables on soil organic carbon and soil redistribution

USGS Publications Warehouse

Venteris, E.R.; McCarty, G.W.; Ritchie, J.C.; Gish, T.

2004-01-01

Controlled studies to investigate the interaction between crop growth, soil properties, hydrology, and management practices are common in agronomy. These sites (much as with real world farmland) often have complex management histories and topographic variability that must be considered. In 1993 an interdisiplinary study was started for a 20-ha site in Beltsville, MD. Soil cores (271) were collected in 1999 in a 30-m grid (with 5-m nesting) and analyzed as part of the site characterization. Soil organic carbon (SOC) and 137Cesium (137Cs) were measured. Analysis of aerial photography from 1992 and of farm management records revealed that part of the site had been maintained as a swine pasture and the other portion as cropped land. Soil properties, particularly soil redistribution and SOC, show large differences in mean values between the two areas. Mass C is 0.8 kg m -2 greater in the pasture area than in the cropped portion. The pasture area is primarily a deposition site, whereas the crop area is dominated by erosion. Management influence is suggested, but topographic variability confounds interpretation. Soil organic carbon is spatially structured, with a regionalized variable of 120 m. 137Cs activity lacks spatial structure, suggesting disturbance of the profile by animal activity and past structures such as swine shelters and roads. Neither SOC nor 137Cs were strongly correlated to terrain parameters, crop yields, or a seasonal soil moisture index predicted from crop yields. SOC and 137Cs were weakly correlated (r2 ???0.2, F-test P-value 0.001), suggesting that soil transport controls, in part, SOC distribution. The study illustrates the importance of past site history when interpreting the landscape distribution of soil properties, especially those strongly influenced by human activity. Confounding variables, complex soil hydrology, and incomplete documentation of land use history make definitive interpretations of the processes behind the spatial distributions difficult. Such complexity may limit the accuracy of scaling approaches to mapping SOC and soil redistribution.

Uncertainty evaluation of a regional real-time system for rain-induced landslides

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

2015-04-01

A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

Methane and CO2 fluxes from peat soil, palm stems and field drains in two oil palm plantations in Sarawak, Borneo, on different tropical peat soil types.

NASA Astrophysics Data System (ADS)

Manning, Frances; Lip Khoon, Kho; Hill, Tim; Arn Teh, Yit

2017-04-01

Oil palm plantations have been expanding rapidly on tropical peat soils in the last 20 years, with 50 % of SE Asian peatlands now managed as industrial or small-holder plantations, up from 11% in 1990. Tropical peat soils are an important carbon (C) store, containing an estimated 17 % of total peatland C. There are large uncertainties as to the soil C dynamics in oil palm plantations on peat due to a shortage of available data. It is therefore essential to understand the soil C cycle in order to promote effective management strategies that optimise yields, whilst maintaining the high C storage capacity of the soil. Here we present CO2 and CH4 fluxes from two oil palm plantations in Sarawak, Malaysia on peat soils. Data were collected from different surface microforms within each plantation that experienced different surface management practices. These included the area next to the palm, in bare soil harvest paths, beneath frond piles, underneath cover crops, from the surface of drains, and from palm stems. Data were collected continuously over one year and analysed with different environmental variables, including soil temperature, WTD, O2, soil moisture and weather data in order to best determine the constraints on the dataset. Total soil respiration (Rtot) varied between 0.09 and 1.59 g C m-2 hr-1. The largest fluxes (0.59 - 1.59 g C m-2 hr-1) were measured next to the palms. Larger CO2 fluxes were observed beneath the cover crops than in the bare soil. This trend was attributed to priming effects from the input of fresh plant litter and exudates. Peat soil type was shown to have significantly different fluxes. The different plantations also had different environmental drivers best explaining the variation in Rtot - with soil moisture being the most significant variable on Sabaju series soil and soil temperature being the most significant environmental variable in the plantation with the Teraja series soil. Rtot was shown to reduce significantly with increasing distance from the palm. The relationship between Rtot and root biomass, which also decreased significantly with increasing distance from the palm, allowed for the partitioning of Rtot into peat oxidation and Ra. Here rates of peat oxidation were estimated to be 0.11 g C m-2 hr-1 following partitioning, and 0.16 g C m-2 hr-1 without partitioning. Methane fluxes varied between 0 and 1.95 g C m-2 hr-1. The largest methane fluxes were emitted from collection drains. Methane oxidation was occasionally observed in field drains, when the water table dropped below the depth of the drain. Soil methane fluxes were lower than those from collection drains. The highest methane fluxes were observed next to palms (0.02 mg C m-2 hr-1) and the lowest under frond piles (0.08 mg C m-2 hr-1). Methane emissions were measured from the palm stems. Preliminary data gives a range between 0.005 and 0.27 µg C m-2 hr-1. These results show wide ranges in both CO2 and CH4 emissions from different sources within the plantations, with the collection drains being the largest source of C fluxes.

A biological quality index for volcanic Andisols and Aridisols (Canary Islands, Spain): variations related to the ecosystem degradation.

PubMed

Armas, Cecilia María; Santana, Bayanor; Mora, Juan Luis; Notario, Jesús Santiago; Arbelo, Carmen Dolores; Rodríguez-Rodríguez, Antonio

2007-05-25

The aim of this work is to identify indicators of biological activity in soils from the Canary Islands, by studying the variation of selected biological parameters related to the processes of deforestation and accelerated soil degradation affecting the Canarian natural ecosystems. Ten plots with different degrees of maturity/degradation have been selected in three typical habitats in the Canary Islands: laurel forest, pine forest and xerophytic scrub with Andisols and Aridisols as the most common soils. The studied characteristics in each case include total organic carbon, field soil respiration, mineralized carbon after laboratory incubation, microbial biomass carbon, hot water-extractable carbon and carboxymethylcellulase, beta-d-glucosidase and dehydrogenase activities. A Biological Quality Index (BQI) has been designed on the basis of a regression model using these variables, assuming that the total soil organic carbon content is quite stable in nearly mature ecosystems. Total carbon in mature ecosystems has been related to significant biological variables (hot water-extractable carbon, soil respiration and carboxymethylcellulase, beta-d-glucosidase and dehydrogenase activities), accounting for nearly 100% of the total variance by a multiple regression analysis. The index has been calculated as the ratio of the value calculated from the regression model and the actual measured value. The obtained results show that soils in nearly mature ecosystems have BQI values close to unit, whereas those in degraded ecosystems range between 0.24 and 0.97, depending on the degradation degree.

Epizootiology of cranial abscess disease in white-tailed deer (Odocoileus virginianus) of Georgia, USA

USGS Publications Warehouse

Cohen, Bradley S.; Belser, Emily H.; Killmaster, Charlie H.; Bowers, John W.; Irwin, Brian J.; Yabsley, Michael J.; Miller, Karl V.

2015-01-01

Intracranial abscess disease is a cause of natural mortality for mature male white-tailed deer (Odocoileus virginianus). Most cases of abscesses are associated with bacterial infection byTrueperella (Arcanobacterium) pyogenes, but a complete understanding of the epidemiology of this disease is lacking. We quantified the effects of individual characteristics, site-specific herd demographics, land cover, and soil variables in estimating the probability of this disease. We examined 7,545 white-tailed deer from 60 sites throughout Georgia US for signs of cranial abscesses, the predecessor of intracranial abscesses, and recorded the presence or absence of cranial abscesses for each individual examined. We detected no cranial abscesses in 2,562 female deer but 91 abscesses in 4,983 male deer examined (1.8%). A generalized linear mixed model, treating site as a random effect, was used to examine several potential explanatory risk factors including site-level landscape and soil characteristics (soil and forest type), demographic factors (deer density and male to female ratio), and individual host factors (deer sex and age). Model results indicated that the probability of a male having a cranial abscess increased with age and that adult sex ratio (male:female) was positively associated with this disease. Site-specific variables for land cover and soil types were not strongly associated with observations of the disease at the scale measured and a large amount of among-site variability remained. Given the demonstrated effect of age, gender, and local sex ratios but the remaining unexplained spatial variability, additional investigation into spatiotemporal variation of the presumed bacterial causative agent of cranial abscesses appears warranted.

Composition variability of spent mushroom compost in Ireland.

PubMed

Jordan, S N; Mullen, G J; Murphy, M C

2008-01-01

Spent mushroom compost (SMC) has proven to be an attractive material for improving soil structure in tilled soils and increasing dry matter production in grassland soils, owing to its high organic matter content and availability of essential plant nutrients. Because of this, it is important to identify the variability in composition of SMC in order to evaluate its merit as a fertilizer/soil conditioner. For this reason, a study was carried out involving the analysis of SMC samples obtained from five mushroom growers using compost from each of the 13 mushroom composting yards currently operating in both Northern Ireland (5 yd) and the Republic of Ireland (8 yd). The selected parameters measured include dry matter, organic matter, total N, P and K, C/N ratio; plant-available P and K, pH, EC, total Ca, Mg, Na, Cu, Zn, Fe, Mn, Cd, Cr, Ni, Pb; and cellulose, hemicellulose and lignin constituents. Yield of mushroom data were also collected from the selected growers. There were significant differences (P<0.05) within two compost production yards for some parameters, therefore, for the most part, the uniformity of SMC within each yard is relatively consistent. However, significant differences (P<0.05) were evident when comparing SMC obtained from growers supplied with compost from Northern Ireland and the Republic of Ireland independently, particularly among total and available phosphorus and potassium values. The results obtained show that, while SMC has fertilizer merit, its variability of composition must be taken into account when assessing this value. The variability of composition is also of particular interest in the context of recent emphasis on plant nutrient management in agriculture.

Relationship between cotton yield and soil electrical conductivity, topography, and landsat imagery

USDA-ARS?s Scientific Manuscript database

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this stu...

Selected micrometeorological, soil-moisture, and evapotranspiration data at Amargosa Desert Research Site in Nye County near Beatty, Nevada, 2001-05

USGS Publications Warehouse

Johnson, Michael J.; Mayers, C. Justin; Garcia, C. Amanda; Andraski, Brian J.

2007-01-01

Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada, 2001-05. Evapotranspiration data were collected from February 2002 through the end of December 2005. Data were col-lected in support of ongoing research to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, precipitation, near-surface soil temperature, soil-heat flux and soil-water content. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily and hourly mean values. Daily maximum and minimum values are based on hourly mean values. Precipitation data output includes daily and hourly totals. Selected soil-moisture profiles at depth include periodic measurements of soil volumetric water-content measurements at nine neutron-probe access tubes to depths ranging from 5.25 to 29.25 meters. Evapotranspiration data include measurement of daily evapotranspiration and 15-minute fluxes of the four principal energy budget components of latent-heat flux, sensible-heat flux, soil-heat flux, and net radiation. Other data collected and used in equations to determine evapotranspiration include temperature and water content of soil, temperature and vapor pressure of air, and covariance values. Evapotranspiration and flux estimates during 15-minute intervals were calculated at a 0.1-second execution interval using the eddy covariance method. Data files included in this report contain the complete micrometeorological, soil-moisture, and evapotranspiration field data sets. These data files are presented in tabular Excel spreadsheet format. This report highlights selected data contained in the computer generated data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological, soil-water content, and evapotranspiration data.

Quantifying agricultural drought impacts using soil moisture model and drought indices in South Korea

NASA Astrophysics Data System (ADS)

Nam, W. H.; Bang, N.; Hong, E. M.; Pachepsky, Y. A.; Han, K. H.; Cho, H.; Ok, J.; Hong, S. Y.

2017-12-01

Agricultural drought is defined as a combination of abnormal deficiency of precipitation, increased crop evapotranspiration demands from high-temperature anomalies, and soil moisture deficits during the crop growth period. Soil moisture variability and their spatio-temporal trends is a key component of the hydrological balance, which determines the crop production and drought stresses in the context of agriculture. In 2017, South Korea has identified the extreme drought event, the worst in one hundred years according to the South Korean government. The objective of this study is to quantify agricultural drought impacts using observed and simulated soil moisture, and various drought indices. A soil water balance model is used to simulate the soil water content in the crop root zone under rain-fed (no irrigation) conditions. The model used includes physical process using estimated effective rainfall, infiltration, redistribution in soil water zone, and plant water uptake in the form of actual crop evapotranspiration. Three widely used drought indices, including the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Self-Calibrated Palmer Drought Severity Index (SC-PDSI) are compared with the observed and simulated soil moisture in the context of agricultural drought impacts. These results demonstrated that the soil moisture model could be an effective tool to provide improved spatial and temporal drought monitoring for drought policy.

Adsorption of phthalic acid and salicylic acid and their effect on exchangeable Al capacity of variable-charge soils.

PubMed

Li, Jiuyu; Xu, Renkou

2007-02-01

Low-molecular-weight (LMW) organic acids may be adsorbed by soils and the adsorption could affect their biodegradation and efficiency in many soil processes. In the present study, the adsorption of phthalic acid and salicylic acid and their effect on the exchangeable Al capacity of variable-charge soils were investigated. The results indicated that phthalic acid and salicylic acid were adsorbed by four variable-charge soils to some extent, oxisols showed a greater adsorption capacity for organic acids than ultisols, and the ability of the four variable-charge soils to adsorb the organic acids at different pH generally followed the order Kunming oxisol > Xuwen oxisol > Jinxian ultisol > Lechang ultisol, which was closely related to their content of free iron oxides and amorphous iron and aluminum oxides. The adsorption of organic acids induced a decrease in the zeta potentials of soils and oxides. Goethite has greater adsorption capacity for organic acid than Xuwen oxisol and the adsorption of organic acids resulted in a bigger decrease in the zeta potential of goethite suspensions. After free iron oxides were removed, less organic acid was adsorbed by Xuwen oxisol and no change was observed in zeta potential for the soil suspension after organic acid was added. The presence of phthalic acid increased the capacity of exchangeable Al and the increment in the four variable-charge soils also followed the order Kunming oxisol > Xuwen oxisol > Lechang ultisol and Jinxian ultisol. The presence of salicylic acid increased the capacity of exchangeable Al in Kunming oxisol, Xuwen oxisol, and Jinxian ultisol, but decreased it in Lechang ultisol due to less adsorption of the acid and formation of soluble Al-salicylate complexes in solution. After free iron oxides were removed, less effect of organic acid on exchangeable Al was observed for Xuwen oxisol, which further confirmed that the iron oxides played a significant role in organic acid adsorption and had a consequent effect on the capacity of exchangeable Al in variable-charge soils. Therefore, the higher the content of iron oxides, the greater the adsorption of organic acids by soils and the greater the increase in soil exchangeable Al induced by the organic acids.

Interannual Variability in Global Soil Respiration on a 0.5 Degree Grid Cell Basis (1980-1994)

DOE Data Explorer

Raich, James W. [Iowa State University, Ames, IA (USA); Potter, Christopher S. [NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States); Bhagawat, Dwipen [Iowa State Univ., Ames, IA (United States); Olson, L. M. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN

2003-08-01

The Principal Investigators used a climate-driven regression model to develop spatially resolved estimates of soil-CO2 emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil-to-atmosphere CO2 fluxes. The mean annual global soil-CO2 flux over this 15-y period was estimated to be 80.4 (range 79.3-81.8) Pg C. Monthly variations in global soil-CO2 emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil-CO2 emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreen broad-leaved forests contributed more soil-derived CO2 to the atmosphere than did any other vegetation type (~30% of the total) and exhibited a biannual cycle in their emissions. Soil-CO2 emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil-CO2 production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO2 concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands, and deserts), interannual variability in soil-CO2 emmissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil-CO2 fluxes correlated with mean annual temperature, with a slope of 3.3 PgCY-1 per degree Celsius. Although the distribution of precipitation influences seasonal and spatial patterns of soil-CO2 emissions, global warming is likely to stimulate CO2 emissions from soils.

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

Soil Carbon Recovery of Degraded Steppe Ecosystems of the Mongolian Plateau

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Togtohyn, C.; Qi, J.

2013-12-01

Mongolian steppe grassland systems are critical source of ecosystem services to societal groups in temperate East Asia. These systems are characterized by their arid and semiarid environments where rainfall tends to be too variable or evaporative losses reduce water availability to reliably support cropping systems or substantial forest cover. These steppe ecosystems have supported land use practices to accommodate the variable rainfall patterns, and seasonal and spatial patterns of forage production displayed by the nomadic pastoral systems practiced across Asia. These pastoral systems are dependent on grassland ecosystem services, including forage production, wool, skins, meat and dairy products, and in many systems provide critical biodiversity and land and water protection services which serve to maintain pastoral livelihoods. Precipitation variability and associated drought conditions experienced frequently in these grassland systems are key drivers of these systems. However, during the past several decades climate change and grazing and land use conversion have resulted in degradation of ecosystem services and loss of soil organic matter. Recent efforts in China and Mongolia are investigating different grazing management practices to restore soil organic matter in these degraded systems. Simulation modeling is being applied to evaluate the long-term benefits of different grazing management regimes under various climate scenarios.

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

NASA Technical Reports Server (NTRS)

Kim, J.-H.; Sud, Y. C.

1993-01-01

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Global distribution of soil organic carbon, based on the Harmonized World Soil Database - Part 1: Masses and frequency distribution of SOC stocks for the tropics, permafrost regions, wetlands, and the world

NASA Astrophysics Data System (ADS)

Köchy, M.; Hiederer, R.; Freibauer, A.

2014-09-01

The global soil organic carbon (SOC) mass is relevant for the carbon cycle budget. We review current estimates of soil organic carbon stocks (mass/area) and mass (stock × area) in wetlands, permafrost and tropical regions and the world in the upper 1 m of soil. The Harmonized World Soil Database (HWSD) v.1.2 provides one of the most recent and coherent global data sets of SOC, giving a total mass of 2476 Pg. Correcting the HWSD's bulk density of organic soils, especially Histosols, results in a mass of 1062 Pg. The uncertainty of bulk density of Histosols alone introduces a range of -56 to +180 Pg for the estimate of global SOC in the top 1 m, larger than estimates of global soil respiration. We report the spatial distribution of SOC stocks per 0.5 arc minutes, the areal masses of SOC and the quantiles of SOC stocks by continents, wetland types, and permafrost types. Depending on the definition of "wetland", wetland soils contain between 82 and 158 Pg SOC. Incorporating more detailed estimates for permafrost from the Northern Circumpolar Soil Carbon Data Base (496 Pg SOC) and tropical peatland carbon, global soils contain 1324 Pg SOC in the upper 1 m including 421 Pg in tropical soils, whereof 40 Pg occur in tropical wetlands. Global SOC amounts to just under 3000 Pg when estimates for deeper soil layers are included. Variability in estimates is due to variation in definitions of soil units, differences in soil property databases, scarcity of information about soil carbon at depths > 1 m in peatlands, and variation in definitions of "peatland".

Combined Effects of Soil Biotic and Abiotic Factors, Influenced by Sewage Sludge Incorporation, on the Incidence of Corn Stalk Rot

PubMed Central

Fortes, Nara Lúcia Perondi; Navas-Cortés, Juan A; Silva, Carlos Alberto; Bettiol, Wagner

2016-01-01

The objectives of this study were to evaluate the combined effects of soil biotic and abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two types of sewage sludge into soil in a 5-years field assay under tropical conditions and to predict the effects of these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. A multiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil. PMID:27176597

Identifying Factors Causing Variability in Greenhouse Gas (GHG) Fluxes in a Polygonal Tundra Landscape

NASA Astrophysics Data System (ADS)

Arora, B.; Wainwright, H. M.; Vaughn, L. S.; Curtis, J. B.; Torn, M. S.; Dafflon, B.; Hubbard, S. S.

2017-12-01

Greenhouse gas (GHG) flux variations in Arctic tundra environments are important to understand because of the vast amount of soil carbon stored in these regions and the potential of these regions to convert from a global carbon sink to a source under warmer conditions. Multiple factors potentially contribute to GHG flux variations observed in these environments, including snowmelt timing, growing season length, active layer thickness, water table variations, and temperature fluctuations. The objectives of this study are to investigate temporal variability in CO2 and CH4 fluxes at Barrow, AK over three successive growing seasons (2012-14) and to determine the factors influencing this variability using a novel entropy-based classification scheme. We analyzed soil, vegetation, and climate parameters as well as GHG fluxes at multiple locations within low-, flat- and high-centered polygons at Barrow, AK as part of the Next Generation Ecosystem Experiment (NGEE) Arctic project. Entropy results indicate that different environmental factors govern variability in GHG fluxes under different spatiotemporal settings. In particular, flat-centered polygons are more likely to become significant sources of CO2 during warm and dry years as opposed to high-centered polygons that contribute considerably to CO2 emissions during cold and wet years. In contrast, the highest CH4 emissions were always associated with low-centered polygons. Temporal variability in CO2 fluxes was primarily associated with factors affecting soil temperature and/or vegetation dynamics during early and late season periods. Temporal variability in CH4 fluxes was primarily associated with changes in vegetation cover and its covariability with primary controls such as seasonal thaw—rather than direct response to changes in soil moisture. Overall, entropy results document which factors became important under different spatiotemporal settings, thus providing clues concerning the manner in which ecosystem properties may be altered regionally in a future climate.

Spatial analysis of trace elements in a moss bio-monitoring data over France by accounting for source, protocol and environmental parameters.

PubMed

Lequy, Emeline; Saby, Nicolas P A; Ilyin, Ilia; Bourin, Aude; Sauvage, Stéphane; Leblond, Sébastien

2017-07-15

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigating spatial variability in gas-flux dynamics within Big Cypress National Preserve, Florida using hydrogeophysical methods

NASA Astrophysics Data System (ADS)

Sirianni, M.; Comas, X.; Shoemaker, B.; Job, M. J.; Cooper, H.

2016-12-01

Globally, wetland soils play an important role in regulating climate change by functioning as a source or sink for atmospheric carbon, particularly in terms of methane and carbon dioxide. While many historic studies defined the function of wetland soils in the global carbon budget, the gas-flux dynamics of subtropical wetlands is largely unknown. Big Cypress National Preserve is a collection of subtropical wetlands in southwestern Florida, including extensive forested (cypress, pine, hardwood) and sawgrass ecosystems that dry and flood annually in response to rainfall. The U.S. Geological Survey employs eddy covariance methods at several locations within the Preserve to quantify carbon and methane exchanges at ecosystem scales. While eddy covariance towers are a convenient tool for measuring gas fluxes, their footprint is spatially extensive (hundreds of meters); and thus spatial variability at smaller scales is masked by averaging or even overlooked. We intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a combination of geophysical, hydrologic and ecologic techniques. Preliminary results suggest that gas releases from flooded calcitic soils are much greater than organic soils. These results - and others - will help build a better understanding of the role of subtropical wetlands in the global carbon budget.

Canopy management in rainfed vineyards (cv. Tempranillo) for optimising water use and enhancing wine quality.

PubMed

Pascual, Miquel; Romero, María-Paz; Rufat, Josep; Villar, Josep M

2015-12-01

Rainfed viticulture, mainly in semi-arid environments, is limited by environmental variability, particularly precipitation and its seasonal distribution, and soil water availability, thus ultimately determining the final quality of grape and wine. Studies on the feasibility of practices such as canopy management to adapt plant growth and yield to soil water availability open up possibilities to preserve wine quality and reinforce the characteristics of the terroir. Principal components analysis was used to identify the relationships between a large set of variables, including soil, plant, canopy management, and wine characteristics. Canopy management was found to have a predominant influence on plant response to soil water by modifying plant water status, changing the amino acid profile in berries and, concomitantly, altering the sensorial attributes of the wine obtained. Grapevine canopy management strategies, such as reiterate shoot trimming to restrict growth during early phases, are effective in adapting plant response to soil water availability. Such strategies affect berry and wine quality, mainly the amino acid profile and sensorial attributes of the wine, without changing yield or grape harvest quality control parameters. Also, in such conditions, nitrogen does not make a significant contribution to grapevine growth or yield or to grape quality. © 2015 Society of Chemical Industry.

Dr. Kenneth Sudduth: A giant pioneering precision agriculture

USDA-ARS?s Scientific Manuscript database

Dr. Ken Sudduth is nationally and internationally recognized for his precision agriculture research and leadership, especially in the areas of soil sensing and assessment of spatial variability for site-specific management. His many noteworthy contributions include novel techniques and methodology f...

Seasonal variability of near surface soil water and groundwater tables in Florida : phase II.

DOT National Transportation Integrated Search

2008-01-01

The seasonal high groundwater table (SHGWT) is a critical measure for design projects requiring : surface water permits including roadway design and detention or retention pond design. Accurately : measuring and, more importantly, predicting water ta...

Biogeographic patterns in below-ground diversity in New York City's Central Park are similar to those observed globally.

PubMed

Ramirez, Kelly S; Leff, Jonathan W; Barberán, Albert; Bates, Scott Thomas; Betley, Jason; Crowther, Thomas W; Kelly, Eugene F; Oldfield, Emily E; Shaw, E Ashley; Steenbock, Christopher; Bradford, Mark A; Wall, Diana H; Fierer, Noah

2014-11-22

Soil biota play key roles in the functioning of terrestrial ecosystems, however, compared to our knowledge of above-ground plant and animal diversity, the biodiversity found in soils remains largely uncharacterized. Here, we present an assessment of soil biodiversity and biogeographic patterns across Central Park in New York City that spanned all three domains of life, demonstrating that even an urban, managed system harbours large amounts of undescribed soil biodiversity. Despite high variability across the Park, below-ground diversity patterns were predictable based on soil characteristics, with prokaryotic and eukaryotic communities exhibiting overlapping biogeographic patterns. Further, Central Park soils harboured nearly as many distinct soil microbial phylotypes and types of soil communities as we found in biomes across the globe (including arctic, tropical and desert soils). This integrated cross-domain investigation highlights that the amount and patterning of novel and uncharacterized diversity at a single urban location matches that observed across natural ecosystems spanning multiple biomes and continents. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Selenium deficiency risk predicted to increase under future climate change

PubMed Central

Jones, Gerrad D.; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P.; Seneviratne, Sonia I.; Smith, Pete; Winkel, Lenny H. E.

2017-01-01

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change. PMID:28223487

Selenium deficiency risk predicted to increase under future climate change.

PubMed

Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E

2017-03-14

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

NASA Astrophysics Data System (ADS)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

NASA Technical Reports Server (NTRS)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

NASA Technical Reports Server (NTRS)

Kim, Edward

2012-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

Site-specific cotton management: Soil measurements

USDA-ARS?s Scientific Manuscript database

oil variability within fields has a large effect on crop growth and yield, often due to variations in soil texture and water holding capacity. This is particularly true in the alluvial soils of the Mississippi Delta, where profile sand contents can range from 20% to 90% within a field. Variable-rate...

Lead and Arsenic Uptake by Leafy Vegetables Grown on Contaminated Soils: Effects of Mineral and Organic Amendments

PubMed Central

McBride, Murray B.; Simon, Tobi; Tam, Geoffrey; Wharton, Sarah

2015-01-01

To assess strategies for mitigating Pb and As transfer into leafy vegetables from contaminated garden soils, we conducted greenhouse experiments using two field-contaminated soils amended with materials expected to reduce metal phytoavailability. Lettuce and mustard greens grown on these soils were analysed by ICP-MS, showing that some Pb and As transfer into the vegetables occurred from both soils tested, but plant Pb concentrations were highly variable among treatment replicates. Soil-to-plant transfer was more efficient for As than for Pb. Contamination of the leaves by soil particles probably accounted for most of the vegetable Pb, since plant Pb concentrations were correlated to plant tissue concentrations of the immobile soil elements Al and Fe. This correlation was not observed for vegetable As concentrations, evidence that most of the soil-to-plant transfer for this toxic metal occurred by root uptake and translocation into the above-ground tissues. A follow-up greenhouse experiment with lettuce on one of the two contaminated soils revealed a lower and less variable foliar Pb concentration than observed in the first experiment, with evidence of less soil particle contamination of the crop. This reduced transfer of Pb to the crop appeared to be a physical effect attributable to the greater biomass causing reduced overall exposure of the above-ground tissues to the soil surface. Attempts to reduce soil Pb and As solubility and plant uptake by amendment at practical rates with stabilizing materials including composts, peat, Ca phosphate, gypsum and Fe oxide, were generally unsuccessful. Only Fe oxide reduced soluble As in the soil, but this effect did not persist. Phosphate amendment rapidly increased soil As solubility but had no measurable effect on either soil Pb solubility or concentrations of Pb or As in the leafy vegetables. The ineffectiveness of these amendments in reducing Pb transfer into leafy vegetables is attributed in this study to the low initial Pb solubility of the studied soils and the fact that the primary mechanism of Pb transfer is physical contamination. PMID:26884640

Influence of Multiple Environmental Factors on Organic Matter Chlorination in Podsol Soil.

PubMed

Svensson, Teresia; Montelius, Malin; Andersson, Malin; Lindberg, Cecilia; Reyier, Henrik; Rietz, Karolina; Danielsson, Åsa; Bastviken, David

2017-12-19

Natural chlorination of organic matter is common in soils. The abundance of chlorinated organic compounds frequently exceeds chloride in surface soils, and the ability to chlorinate soil organic matter (SOM) appears widespread among microorganisms. Yet, the environmental control of chlorination is unclear. Laboratory incubations with 36 Cl as a Cl tracer were performed to test how combinations of environmental factors, including levels of soil moisture, nitrate, chloride, and labile organic carbon, influenced chlorination of SOM from a boreal forest. Total chlorination was hampered by addition of nitrate or by nitrate in combination with water but enhanced by addition of chloride or most additions including labile organic matter (glucose and maltose). The greatest chlorination was observed after 15 days when nitrate and water were added together with labile organic matter. The effect that labile organic matter strongly stimulated the chlorination rates was confirmed by a second independent experiment showing higher stimulation at increased availability of labile organic matter. Our results highlight cause-effect links between chlorination and the studied environmental variables in podsol soil-with consistent stimulation by labile organic matter that did overrule the negative effects of nitrate.

GLEAM v3: updated land evaporation and root-zone soil moisture datasets

NASA Astrophysics Data System (ADS)

Martens, Brecht; Miralles, Diego; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard; Fernández-Prieto, Diego; Verhoest, Niko

2016-04-01

Evaporation determines the availability of surface water resources and the requirements for irrigation. In addition, through its impacts on the water, carbon and energy budgets, evaporation influences the occurrence of rainfall and the dynamics of air temperature. Therefore, reliable estimates of this flux at regional to global scales are of major importance for water management and meteorological forecasting of extreme events. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to the limited global coverage of in situ measurements. Remote sensing techniques can help to overcome the lack of ground data. However, evaporation is not directly observable from satellite systems. As a result, recent efforts have focussed on combining the observable drivers of evaporation within process-based models. The Global Land Evaporation Amsterdam Model (GLEAM, www.gleam.eu) estimates terrestrial evaporation based on daily satellite observations of meteorological drivers of terrestrial evaporation, vegetation characteristics and soil moisture. Since the publication of the first version of the model in 2011, GLEAM has been widely applied for the study of trends in the water cycle, interactions between land and atmosphere and hydrometeorological extreme events. A third version of the GLEAM global datasets will be available from the beginning of 2016 and will be distributed using www.gleam.eu as gateway. The updated datasets include separate estimates for the different components of the evaporative flux (i.e. transpiration, bare-soil evaporation, interception loss, open-water evaporation and snow sublimation), as well as variables like the evaporative stress, potential evaporation, root-zone soil moisture and surface soil moisture. A new dataset using SMOS-based input data of surface soil moisture and vegetation optical depth will also be distributed. The most important updates in GLEAM include the revision of the soil moisture data assimilation system, the evaporative stress functions and the infiltration of rainfall. In this presentation, we will highlight the changes of the methodology and present the new datasets, their validation against in situ observations and the comparisons against alternative datasets of terrestrial evaporation, such as GLDAS-Noah, ERA-Interim and previous GLEAM datasets. Preliminary results indicate that the magnitude and the spatio-temporal variability of the evaporation estimates have been slightly improved upon previous versions of the datasets.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

Spatial variability of specific surface area of arable soils in Poland

NASA Astrophysics Data System (ADS)

Sokolowski, S.; Sokolowska, Z.; Usowicz, B.

2012-04-01

Evaluation of soil spatial variability is an important issue in agrophysics and in environmental research. Knowledge of spatial variability of physico-chemical properties enables a better understanding of several processes that take place in soils. In particular, it is well known that mineralogical, organic, as well as particle-size compositions of soils vary in a wide range. Specific surface area of soils is one of the most significant characteristics of soils. It can be not only related to the type of soil, mainly to the content of clay, but also largely determines several physical and chemical properties of soils and is often used as a controlling factor in numerous biological processes. Knowledge of the specific surface area is necessary in calculating certain basic soil characteristics, such as the dielectric permeability of soil, water retention curve, water transport in the soil, cation exchange capacity and pesticide adsorption. The aim of the present study is two-fold. First, we carry out recognition of soil total specific surface area patterns in the territory of Poland and perform the investigation of features of its spatial variability. Next, semivariograms and fractal analysis are used to characterize and compare the spatial variability of soil specific surface area in two soil horizons (A and B). Specific surface area of about 1000 samples was determined by analyzing water vapor adsorption isotherms via the BET method. The collected data of the values of specific surface area of mineral soil representatives for the territory of Poland were then used to describe its spatial variability by employing geostatistical techniques and fractal theory. Using the data calculated for some selected points within the entire territory and along selected directions, the values of semivariance were determined. The slope of the regression line of the log-log plot of semi-variance versus the distance was used to estimate the fractal dimension, D. Specific surface area in A and B horizons was space-dependent, with the range of spatial dependence of about 2.5°. Variogram surfaces showed anisotropy of the specific surface area in both horizons with a trend toward the W to E directions. The smallest fractal dimensions were obtained for W to E directions and the highest values - for S to N directions. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.

Effects of Combined Application of Biogas Slurry and Chemical Fertilizer on Soil Aggregation and C/N Distribution in an Ultisol.

PubMed

Zheng, Xuebo; Fan, Jianbo; Xu, Lei; Zhou, Jing

2017-01-01

Unreasonable use of chemical fertilizer (CF) on agricultural soil leads to massive losses of soil organic carbon (SOC) and total nitrogen (TN) in tropical and subtropical areas, where soil conditions are unfavorable for aggregate formation. This study evaluated the effects of combined application of biogas slurry (BS) plus CF on soil aggregation and aggregate-associated C/N concentration and storage in an Ultisol. Six treatments included: no fertilizer (T1), CF only (T2), partial (15% (T3), 30% (T4) and 45% (T5)) substitution of TN with BS and BS only (T6). Soil mechanical-stable aggregates (MSAs) formation and stability as well as MSAs-associated C/N concentration and storage were observed in different aggregate sizes (>5, 5-2, 2-1, 1.0-0.5, 0.50-0.25 and <0.25 mm). The proportion of MSAs >5 mm significantly increased with BS substitution (T5), while the proportions of MSAs 1.0-0.5 mm, MSAs 0.50-0.25 mm and MSAs <0.25 mm significantly decreased. Both mean weight diameter and geometric mean diameter were highest in T5, which improved soil aggregation stability as well as resulted in significantly higher SOC and TN concentrations and storage in MSAs >0.5 mm that constituted 72-82% of MSAs. Stepwise regression analysis showed that MSAs >5 mm, SOC in MSAs >5 mm and TN in MSAs >5 mm were the dominant variables affecting aggregate stability. Meanwhile SOC in MSAs <0.25 mm and TN in MSAs 2-1 mm were independent variables affecting SOC and TN concentrations in bulk soils. Therefore, certain rate of combined application of BS plus CF is an effective, eco-friendly way to improve soil quality in an Ultisol.

Short-term effect of the soil amendments activated carbon, biochar, and ferric oxyhydroxide on bacteria and invertebrates.

PubMed

Hale, Sarah E; Jensen, John; Jakob, Lena; Oleszczuk, Patryk; Hartnik, Thomas; Henriksen, Thomas; Okkenhaug, Gudny; Martinsen, Vegard; Cornelissen, Gerard

2013-08-06

The aim of the present study was to evaluate the secondary ecotoxicological effects of soil amendment materials that can be added to contaminated soils in order to sequester harmful pollutants. To this end, a nonpolluted agricultural soil was amended with 0.5, 2, and 5% of the following four amendments: powder activated carbon (PAC), granular activated carbon, corn stover biochar, and ferric oxyhydroxide powder, which have previously been proven to sequester pollutants in soil. The resulting immediate effects (i.e., without aging the mixtures before carrying out tests) on the springtail Folsomia candida, the earthworm species Aporectodea caliginosa and Eisenia fetida, the marine bacteria Vibrio fischeri, a suite of ten prokaryotic species, and a eukaryote (the yeast species Pichia anomalia) were investigated. Reproduction of F. candida was significantly increased compared to the unamended soil when 2% biochar was added to it. None of the treatments caused a negative effect on reproduction. All amendments had a deleterious effect on the growth of A. caliginosa when compared to the unamended soil, except the 0.5% amendment of biochar. In avoidance tests, E. fetida preferred biochar compared to all other amendments including the unamended soil. All amendments reduced the inhibition of luminescence to V. fischeri, i.e., were beneficial for the bacteria, with PAC showing the greatest improvement. The effects of the amendments on the suite of prokaryotic species and the eukaryote were variable, but overall the 2% biochar dose provided the most frequent positive effect on growth. It is concluded that the four soil amendments had variable but never strongly deleterious effects on the bacteria and invertebrates studied here during the respective recommended experimental test periods.

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

Effects of biotic and abiotic indices on long term soil moisture data in a grassland biodiversity experiment

NASA Astrophysics Data System (ADS)

Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke

2015-04-01

Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.

Environmental fate and effects of granular pesta formulation from strains of Pseudomonas aeruginosa C1501 and Lasiodiplodia pseudotheobromae C1136 on soil activity and weeds.

PubMed

Adetunji, Charles Oluwaseun; Oloke, Julius Kola; Osemwegie, Osarenkhoe Omorefosa

2018-03-01

This work investigated the effect of variably formulated pesta granules containing wild and UV mutated Pseudomonas aeruginosa and Lasiodiplodia pseudotheobromae on the rate of CO 2 evolution, organic carbon content, enzymatic activity (acidic and alkaline phosphatase, dehydrogenases, urease and protease) and representative soil microorganisms in the soils using different assay techniques. After the 35th day period of experiment, the pesta granule formulation BH4 showed the best evolution of CO 2 (824 ± 6.2 mg CO 2 kg -1 soil hr -1 ) as against control treatment (689 ± 3.7 mg CO 2 kg -1 soil hr -1 ). Enzymes activities, organic carbon content of 3.8% on the 15th day of study and stable representation of microorganisms that include actinomycetes, fungi, heterogenous as well as soil nitrogen-mediatory bacteria were equally at their maximum level BH4 treatments. The phytotoxic assay showed no inhibitory effect on Solanum lycopersicum seeds and seedlings compared to the observed growth inhibition on the tested weeds (Amaranthus hybridus and Echinocholoa crus-galli) which corresponds with positive control glyphosate treatment. The glyphosate treated soil had the least critical results on parameters investigated during the study. The order of bioherbicidal activity is BH4>BH2>BH6>BH3>BH1>BH5>positive control. Results from this study confirmed the target efficacy of variably formulated pesta granules which is sustainable, cheap, ecologically suitable and recent. This is in addition to recognizing the microbial-derived formulations as characteristically potent alternative to chemical herbicides utility in agrosystems practice. Further study of the underlining factor responsible for the bioherbicidal performances of the variably formulated pesta granules and field trials are critical for their future commercialization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microbial biomass and ATP in smelter-polluted forest humus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baath, E.; Arnebrant, K.; Nordgren, A.

Many aspects of microbial activity in soil have been studied in connection with heavy metal pollution, but few investigations have included microbial biomass. To study how biomass-C and ATP were affected over a wide range of metal concentrations, these variables have been measured around the Gusum brass mill in south Sweden. Near the smelter more than 20,000 ppm Cu + Zn g{sup {minus}1} dry soil have been found. This area has been extensively studied form microbiological, zoological and botanical points of view.

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

The assessment of source attribution of soil pollution in a typical e-waste recycling town and its surrounding regions using the combined organic and inorganic dataset.

PubMed

Luo, Jie; Qi, Shihua; Xie, Xianming; Gu, X W Sophie; Wang, Jinji

2017-01-01

Guiyu is a well-known electronic waste dismantling and recycling town in south China. Concentrations and distribution of the 21 mineral elements and 16 polycyclic aromatic hydrocarbons (PAHs) collected there were evaluated. Principal component analyses (PCA) applied to the data matrix of PAHs in the soil extracted three major factors explaining 85.7% of the total variability identified as traffic emission, coal combustion, and an unidentified source. By using metallic or metalloid element concentrations as variables, five principal components (PCs) were identified and accounted for 70.4% of the information included in the initial data matrix, which can be denoted as e-waste dismantling-related contamination, two different geological origins, anthropogenic influenced source, and marine aerosols. Combining the 21 metallic and metalloid element datasets with the 16 PAH concentrations can narrow down the coarse source and decrease the unidentified contribution to soil in the present study and therefore effectively assists the source identification process.

Windthrow and fallow-forest successions impacts in soil carbon stocks and GHG fluxes spatial variability and dynamics in the Central Russia' reserve spruce ecosystems

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Ivanov, Alexey; Komarova, Tatyana; Valentini, Riccardo

2015-04-01

High spatial and temporal variability is mutual feature for most forest soils that is especially obvious in case of their carbon stocks and GHG fluxes. This phenomenon is generally well-known but not so often becomes the object of special precision investigation in detail and small scales so there are still serious gaps in its principal factors understanding due to their high bioclimatic, regional, landscape, tree species and temporal variability. Southern taiga is one of the most environmentally important world zonal forest ecosystems due to its still comparatively intensive carbon biogeochemical cycle and huge area in the northern Eurasia with strong anthropogenic impacts by Western & Central European and Southern & Eastern Asian regions. Central Forest Biospheric Reserve (Tver region, 360 km to North-West from Moscow) is the principal southern-taiga reserve in the European territory of Russia. Since start of its research activity in 1939 the reserve became the regional center of mature spruce ecosystem structure and dynamics investigation. In 1970-1980-s there have been done complex investigations of windthrow soil patterns and fallow-forest successions. Since middle of 1990-s the ecosystem-level GHG fluxes have been observed by eddy covariance method. Since 2012 the detailed year-round monitoring is running in the southern-taiga zonal station of the regional system RusFluxNet with especial attention on the soil carbon stocks and GHG fluxes spatial variability and dynamics due to windthrow and fallow-forest successions (in frame of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266). Soil carbon dynamics is investigated in decades-hundred-year chronosequences of dominated parcels and different-size windthrow soil cover patterns, including direct investigation during last 33 years with detailed mapping, soil profile morphometrics and bulk density, morphogenetic and statistical analysis of mass data. Morphogenetic analysis of microrelief, soil profile and cover have been accompanied by researches of soil regimes (temperature, moisture, pH, oxidation-reduction potential, microbiological activity) and transformations of representative topsoil materials at the different stages of windthrow soil successions. Since 2012 soil CO2 fluxes have been analyzed every ten days in situ by method of exposition chambers with infra red gas analyzer (Li-Cor 820). At the same periods soil gas fluxes have been sampled from the exposition chambers into vials with the following CH4 and N2O analysis by gas chromatograph. The carried out researches have shown sharp increase of rates of typomorphic soil forming processes within windthrow hole and mound soil successions: (a) lateral input of organic matter in soils of fresh holes - up to 2-3 kg m-2y-1; (b) fulvic acid formation - up to 100-200 g m-2y-1 in soils of young holes and mounds; (c) Al-Fe-humus migration - up to 0.7-1.2 kg cm m-2y-1; (d) humus-accumulated and eluvial horizon development - up to 1-2 mm y-1. The conducted researches have shown high temporal and spatial variability of CO2 fluxes due to soil cover and windthrow complex patterns, windthrow or fallow-forest succession stage and age, air and soil temperature (up to R = 0.64 for taiga, and R = 0.75 for fallow), soil moisture (up to R = -0.65/0.66 both for taiga and fallow) and some other characteristics of the studied objects. Soil CO2 emission is essentially decreased with fallow-forest age. Maximum CO2 fluxes have been observed between 12:00 and 16:00. Within fallow-forest succession the maximum CH4 emission has been fixed in first (grass) stage, and N2O fluxes increase due to temperature rise and moisture decreasing. Usually there is stronger effect on GHG fluxes by air temperature than soil one due to comparatively thin layer of soil organic and/or humus-accumulative subhorizons with maximum biological activity that usually determines the total rate of GHG principal soil fluxes. Unfavorable seasonal climatic conditions (dry season or low temperature) determine essential (in 1.5-2 times) decreasing not only in soil GHG fluxes but in level of their spatial variability, seasonal and daily dynamics too. These trends are most obvious in case of more open ecosystems at the first stages of the fallow-forest succession. Understanding the principal regularities of spatial and temporal changes in soil GHG fluxes help better modelling them in the process of spatial intra- and extrapolations, seasonal and interseasonal predictions, taking into attention basic and current principal factors limiting GHG fluxes.

Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed

NASA Astrophysics Data System (ADS)

Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.

2015-04-01

The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

Spatial variability of soil properties and soil erodibility in the Alqueva dam watershed, Portugal

NASA Astrophysics Data System (ADS)

Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.

2015-01-01

The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this, three areas representative of different land uses (agroforestry grassland, Lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while K factor increased with intensive cultivation. The HJ-biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

Self-organizing biochemical cycle in dynamic feedback with soil structure

NASA Astrophysics Data System (ADS)

Vasilyeva, Nadezda; Vladimirov, Artem; Smirnov, Alexander; Matveev, Sergey; Tyrtyshnikov, Evgeniy; Yudina, Anna; Milanovskiy, Evgeniy; Shein, Evgeniy

2016-04-01

In the present study we perform bifurcation analysis of a physically-based mathematical model of self-organized structures in soil (Vasilyeva et al., 2015). The state variables in this model included microbial biomass, two organic matter types, oxygen, carbon dioxide, water content and capillary pore size. According to our previous experimental studies, organic matter affinity to water is an important property affecting soil structure. Therefore, organic matter wettability was taken as principle distinction between organic matter types in this model. It considers general known biological feedbacks with soil physical properties formulated as a system of parabolic type non-linear partial differential equations with elements of discrete modeling for water and pore formation. The model shows complex behavior, involving emergence of temporal and spatial irregular auto-oscillations from initially homogeneous distributions. The energy of external impact on a system was defined by a constant oxygen level on the boundary. Non-linear as opposed to linear oxygen diffusion gives possibility of modeling anaerobic micro-zones formation (organic matter conservation mechanism). For the current study we also introduced population competition of three different types of microorganisms according to their mobility/feeding (diffusive, moving and fungal growth). The strongly non-linear system was solved and parameterized by time-optimized algorithm combining explicit and implicit (matrix form of Thomas algorithm) methods considering the time for execution of the evaluated time-step according to accuracy control. The integral flux of the CO2 state variable was used as a macroscopic parameter to describe system as a whole and validation was carried out on temperature series of moisture dependence for soil heterotrophic respiration data. Thus, soil heterotrophic respiration can be naturally modeled as an integral result of complex dynamics on microscale, arising from biological processes formulated as a sum of state variables products, with no need to introduce any saturation functions, such as Mikhaelis-Menten type kinetics, inside the model. Analyzed dynamic soil model is being further developed to describe soil structure formation and its effect on organic matter decomposition at macro-scale, to predict changes with external perturbations. To link micro- and macro-scales we additionally model soil particles aggregation process. The results from local biochemical soil organic matter cycle serve as inputs to aggregation process, while the output aggregate size distributions define physical properties in the soil profile, these in turn serve as dynamic parameters in local biochemical cycles. The additional formulation is a system of non-linear ordinary differential equations, including Smoluchowski-type equations for aggregation and reaction kinetics equations for coagulation/adsorption/adhesion processes. Vasilyeva N.A., Ingtem J.G., Silaev D.A. Nonlinear dynamical model of microbial growth in soil medium. Computational Mathematics and Modeling, vol. 49, p.31-44, 2015 (in Russian). English version is expected in corresponding vol.27, issue 2, 2016.

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

NASA Technical Reports Server (NTRS)

Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.

2006-01-01

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Spectroscopic characteristics of soil organic matter as a tool to assess soil physical quality in Mediterranean ecosystems

NASA Astrophysics Data System (ADS)

Recio Vázquez, Lorena; Almendros, Gonzalo; Knicker, Heike; López-Martín, María; Carral, Pilar; Álvarez, Ana

2014-05-01

In Mediterranean areas, the loss of soil physical quality is of particular concern due to the vulnerability of these ecosystems in relation to unfavourable climatic conditions, which usually lead to soil degradation processes and severe decline of its functionality. As a result, increasing scientific attention is being paid on the exploration of soil properties which could be readily used as quality indicators, including organic matter which, in fact, represents a key factor in the maintenance of soil physical status. In this line, the present research tackles the assessment of the quality of several soils from central Spain with the purpose of identifying the physical properties most closely correlated with the organic matter, considering not only the quantity but also the quality of the different C-forms. The studied attributes consist of a series of physical properties determined in field and laboratory conditions-total porosity, aggregate stability, available water capacity, air provision, water infiltration rate and soil hydric saturation-.The bulk organic matter was characterised by solid-state 13C NMR spectroscopy and the major organic fractions (lipids, free particulate organic matter, fulvic acids, humic acids and humin) were quantified using standard procedures. The humic acids were also analysed by visible and infrared spectroscopies. The use of multidimensional scaling to classify physical properties in conjunction with molecular descriptors of soil organic matter, suggested significant correlations between the two set of variables, which were confirmed with simple and canonical regression models. The results pointed to two well-defined groups of physical attributes in the studied soils: (i) those associated with organic matter of predominantly aromatic character (water infiltration descriptors), and (ii) soil physical variables related to organic matter with marked aliphatic character, high preservation of the lignin signature and comparatively low degree of humification (properties involved in the maintenance of physical support, water storage and air provision functions). From the practical viewpoint, the results support the idea that the detailed structural study of the different soil C-forms is useful for accurately monitoring soil physical status. The quantification of total soil organic carbon ought to be complemented with qualitative analyses of the organic matter, at least at the spectroscopic level, which can be used for the early diagnosis of possible degradation processes. Moreover, in already degraded soils, the knowledge of the sources of variability for each physical property provides valuable information for the restoration of these ecosystems by adapting inputs of organic matter with specific features (aliphatic nature, oxidation degree, humification stage, etc.) to particular soil degradation problems (i.e. soil compaction, waterlogging, water erosion, etc.).

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

NASA Technical Reports Server (NTRS)

Whiting, Michael L.; Li, Lin; Ustin, Susan L.

2004-01-01

Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

Degradation of chlorpyrifos in tropical rice soils.

PubMed

Das, Subhasis; Adhya, Tapan K

2015-04-01

Chlorpyrifos [O,O-diethyl O-(3,5,6-trichloro-2-pyridinol) phosphorothioate] is used worldwide as an agricultural insecticide against a broad spectrum of insect pests of economically important crops including rice, and soil application to control termites. The insecticide mostly undergoes hydrolysis to diethyl thiophosphoric acid (DETP) and 3,5,6-trichloro-2-pyridinol (TCP), and negligible amounts of other intermediate products. In a laboratory-cum-greenhouse study, chlorpyrifos, applied at a rate of 10 mg kg(-1) soil to five tropical rice soils of wide physico-chemical variability, degraded with a half-life ranging from 27.07 to 3.82 days. TCP was the major metabolite under both non-flooded and flooded conditions. Chlorpyrifos degradation had significant negative relationship with electrical conductivity (EC), cation exchange capacity (CEC), clay and sand contents of the soils under non-flooded conditions. Results indicate that degradation of chlorpyrifos was accelerated with increase in its application frequency, across the representative rice soils. Management regimes including moisture content and presence or absence of rice plants also influenced the process. Biotic factors also play an important role in the degradation of chlorpyrifos as demonstrated by its convincing degradation in mineral salts medium inoculated with non-sterile soil suspension. Copyright © 2015 Elsevier Ltd. All rights reserved.

Vadose zone controls on damping of climate-induced transient recharge fluxes in U.S. agroecosystems

NASA Astrophysics Data System (ADS)

Gurdak, Jason

2017-04-01

Understanding the physical processes in the vadose zone that link climate variability with transient recharge fluxes has particular relevance for the sustainability of groundwater-supported irrigated agriculture and other groundwater-dependent ecosystems. Natural climate variability on interannual to multidecadal timescales has well-documented influence on precipitation, evapotranspiration, soil moisture, infiltration flux, and can augment or diminish human stresses on water resources. Here the behavior and damping depth of climate-induced transient water flux in the vadose zone is explored. The damping depth is the depth in the vadose zone that the flux variation damps to 5% of the land surface variation. Steady-state recharge occurs when the damping depth is above the water table, and transient recharge occurs when the damping depth is below the water table. Findings are presented from major agroecosystems of the United States (U.S.), including the High Plains, Central Valley, California Coastal Basin, and Mississippi Embayment aquifer systems. Singular spectrum analysis (SSA) is used to identify quasi-periodic signals in precipitation and groundwater time series that are coincident with the Arctic Oscillation (AO) (6-12 mo cycle), Pacific/North American oscillation (PNA) (<1-4 yr cycle), El Niño/Southern Oscillation (ENSO) (2-7 yr cycle), North Atlantic Oscillation (NAO) (3-6 yr cycle), Pacific Decadal Oscillation (PDO) (15-30 yr cycle), and Atlantic Multidecadal Oscillation (AMO) (50-70 yr cycle). SSA results indicate that nearly all of the quasi-periodic signals in the precipitation and groundwater levels have a statistically significant lag correlation (95% confidence interval) with the AO, PNA, ENSO, NAO, PDO, and AMO indices. Results from HYDRUS-1D simulations indicate that transient water flux through the vadose zone are controlled by highly nonlinear interactions between mean infiltration flux and infiltration period related to the modes of climate variability and the local soil textures, layering, and depth to the water table. Simulation results for homogeneous profiles generally show that shorter-period climate oscillations, smaller mean fluxes, and finer-grained soil textures generally produce damping depths closer to land surface. Simulation results for layered soil textures indicate more complex responses in the damping depth, including the finding that finer-textured layers in a coarser soil profile generally result in damping depths closer to land surface, while coarser-textured layers in coarser soil profile result in damping depths deeper in the vadose zone. Findings from this study improve understanding of how vadose zone properties influences transient recharge flux and damp climate variability signals in groundwater systems, and have important implications for sustainable management of groundwater resources and coupled agroecosystems under future climate variability and change.

Generic reactive transport codes as flexible tools to integrate soil organic matter degradation models with water, transport and geochemistry in soils

NASA Astrophysics Data System (ADS)

Jacques, Diederik; Gérard, Fréderic; Mayer, Uli; Simunek, Jirka; Leterme, Bertrand

2016-04-01

A large number of organic matter degradation, CO2 transport and dissolved organic matter models have been developed during the last decades. However, organic matter degradation models are in many cases strictly hard-coded in terms of organic pools, degradation kinetics and dependency on environmental variables. The scientific input of the model user is typically limited to the adjustment of input parameters. In addition, the coupling with geochemical soil processes including aqueous speciation, pH-dependent sorption and colloid-facilitated transport are not incorporated in many of these models, strongly limiting the scope of their application. Furthermore, the most comprehensive organic matter degradation models are combined with simplified representations of flow and transport processes in the soil system. We illustrate the capability of generic reactive transport codes to overcome these shortcomings. The formulations of reactive transport codes include a physics-based continuum representation of flow and transport processes, while biogeochemical reactions can be described as equilibrium processes constrained by thermodynamic principles and/or kinetic reaction networks. The flexibility of these type of codes allows for straight-forward extension of reaction networks, permits the inclusion of new model components (e.g.: organic matter pools, rate equations, parameter dependency on environmental conditions) and in such a way facilitates an application-tailored implementation of organic matter degradation models and related processes. A numerical benchmark involving two reactive transport codes (HPx and MIN3P) demonstrates how the process-based simulation of transient variably saturated water flow (Richards equation), solute transport (advection-dispersion equation), heat transfer and diffusion in the gas phase can be combined with a flexible implementation of a soil organic matter degradation model. The benchmark includes the production of leachable organic matter and inorganic carbon in the aqueous and gaseous phases, as well as different decomposition functions with first-order, linear dependence or nonlinear dependence on a biomass pool. In addition, we show how processes such as local bioturbation (bio-diffusion) can be included implicitly through a Fickian formulation of transport of soil organic matter. Coupling soil organic matter models with generic and flexible reactive transport codes offers a valuable tool to enhance insights into coupled physico-chemical processes at different scales within the scope of C-biogeochemical cycles, possibly linked with other chemical elements such as plant nutrients and pollutants.

The Use of Electromagnetic Induction Techniques for Soil Mapping

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Doolittle, Jim

2015-04-01

Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.

Effects of golf course management on subsurface soil properties in Iowa

NASA Astrophysics Data System (ADS)

Streeter, Matthew T.; Schilling, Keith E.

2018-05-01

Currently, in the USA and especially in the Midwest region, urban expansion is developing turfgrass landscapes surrounding commercial sites, homes, and recreational areas on soils that have been agriculturally managed for decades. Often, golf courses are at the forefront of conversations concerning anthropogenic environmental impacts as they account for some of the most intensively managed soils in the world. Iowa golf courses provide an ideal location to evaluate whether golf course management is affecting the quality of soils at depth. Our study evaluated how soil properties relating to soil health and resiliency varied with depth at golf courses across Iowa and interpreted relationships of these properties to current golf course management, previous land use, and inherent soil properties. Systematic variation in soil properties including sand content, NO3, and soil organic matter (SOM) were observed with depth at six Iowa golf courses among three landform regions. Variability in sand content was identified between the 20 and 50 cm depth classes at all courses, where sand content decreased by as much as 37 %. Highest concentrations of SOM and NO3 were found in the shallowest soils, whereas total C and P variability was not related to golf course management. Sand content and NO3 were found to be directly related to golf course management, particularly at shallow depths. The effects of golf course management dissipated with depth and deeper soil variations were primarily due to natural geologic conditions. The two abovementioned soil properties were very noticeably altered by golf course management and may directly impact crop productivity, soil health, and water quality, and while NO3 may be altered relatively quickly in soil through natural processes, particle size of the soil may not be altered without extensive mitigation. Iowa golf courses continue to be developed in areas of land use change from historically native prairies and more recently agriculture to urban landscapes. As soils are continually altered by human impacts, it is imperative that we monitor the changes, both physical and chemical, in order to establish management practices that maintain environmental sustainability and productivity.

Liming impacts on soils, crops and biodiversity in the UK: A review.

PubMed

Holland, J E; Bennett, A E; Newton, A C; White, P J; McKenzie, B M; George, T S; Pakeman, R J; Bailey, J S; Fornara, D A; Hayes, R C

2018-01-01

Fertile soil is fundamental to our ability to achieve food security, but problems with soil degradation (such as acidification) are exacerbated by poor management. Consequently, there is a need to better understand management approaches that deliver multiple ecosystem services from agricultural land. There is global interest in sustainable soil management including the re-evaluation of existing management practices. Liming is a long established practice to ameliorate acidic soils and many liming-induced changes are well understood. For instance, short-term liming impacts are detected on soil biota and in soil biological processes (such as in N cycling where liming can increase N availability for plant uptake). The impacts of liming on soil carbon storage are variable and strongly relate to soil type, land use, climate and multiple management factors. Liming influences all elements in soils and as such there are numerous simultaneous changes to soil processes which in turn affect the plant nutrient uptake; two examples of positive impact for crops are increased P availability and decreased uptake of toxic heavy metals. Soil physical conditions are at least maintained or improved by liming, but the time taken to detect change varies significantly. Arable crops differ in their sensitivity to soil pH and for most crops there is a positive yield response. Liming also introduces implications for the development of different crop diseases and liming management is adjusted according to crop type within a given rotation. Repeated lime applications tend to improve grassland biomass production, although grassland response is variable and indirect as it relates to changes in nutrient availability. Other indicators of liming response in grassland are detected in mineral content and herbage quality which have implications for livestock-based production systems. Ecological studies have shown positive impacts of liming on biodiversity; such as increased earthworm abundance that provides habitat for wading birds in upland grasslands. Finally, understanding of liming impacts on soil and crop processes are explored together with functional aspects (in terms of ecosystems services) in a new qualitative framework that includes consideration of how liming impacts change with time. This holistic approach provides insights into the far-reaching impacts that liming has on ecosystems and the potential for liming to enhance the multiple benefits from agriculturally managed land. Recommendations are given for future research on the impact of liming and the implications for ecosystem services. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Magnetic minerals in soils across the forest-prairie ecotone in NW Minnesota

NASA Astrophysics Data System (ADS)

Maxbauer, D.; Feinberg, J. M.; Fox, D. L.; Nater, E. A.

2016-12-01

Soil pedogenesis results in a complex assemblage of iron oxide minerals that can be disentangled successfully using sensitive magnetic techniques to better delineate specific soil processes. Here, we evaluate the variability in soil processes within forest, prairie, and transitional soils along an 11 km transect of anthropogenically unaltered soils that span the forest-to-prairie ecotone in NW Minnesota. All soils in this study developed on relatively uniform topography, similar glacial till parent material, under a uniform climate, and presumably over similar time intervals. The forest-to-prairie transition zone in this region is controlled by naturally occurring fires, affording the opportunity to evaluate differences in soil processes related to vegetation (forest versus prairie) and burning (prairie and transitional soils). Results suggest that the pedeogenic fraction of magnetite/maghemite in soils is similar in all specimens and is independent of soil type, vegetation, and any effects of burning. Magnetically enhanced horizons have 45% of remanence held by a low-coercivity pedogenic component (likely magnetite/maghemite) regardless of vegetation cover and soil type. Enhancement ratios for magnetic susceptibility and low-field remanences, often used as indicators of pedogenic magnetic minerals, are more variable but remain statistically equivalent across the transect. These results support the hypothesis that pedogenic magnetic minerals in soils mostly reflect ambient climatic conditions regardless of the variability in soil processes related to vegetation and soil type. The non-pedogenic magnetic mineral assemblage shows clear distinctions between the forest, prairie, and transitional soils in hysteresis properties (remanence and coercivity ratios; Mr/Ms and Bc/Bcr, respectively), suggesting that variable processes in these settings influence the local magnetic mineral assemblage, and that it may be possible to use magnetic minerals in paleosols to constrain these processes. This work highlights the importance of isolating the magnetic behavior of pedogenic and non-pedogenic minerals in environmental magnetism studies in order to provide the most rigorous interpretation of past environmental conditions.

Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modeling approach

NASA Astrophysics Data System (ADS)

Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.

2013-12-01

Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.

Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models

NASA Astrophysics Data System (ADS)

Chadburn, Sarah E.; Krinner, Gerhard; Porada, Philipp; Bartsch, Annett; Beer, Christian; Belelli Marchesini, Luca; Boike, Julia; Ekici, Altug; Elberling, Bo; Friborg, Thomas; Hugelius, Gustaf; Johansson, Margareta; Kuhry, Peter; Kutzbach, Lars; Langer, Moritz; Lund, Magnus; Parmentier, Frans-Jan W.; Peng, Shushi; Van Huissteden, Ko; Wang, Tao; Westermann, Sebastian; Zhu, Dan; Burke, Eleanor J.

2017-11-01

It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.

Native temperature regime influences soil response to simulated warming

Treesearch

Timothy G. Whitby; Michael D. Madritch

2013-01-01

Anthropogenic climate change is expected to increase global temperatures and potentially increase soil carbon (C) mineralization, which could lead to a positive feedback between global warming and soil respiration. However the magnitude and spatial variability of belowground responses to warming are not yet fully understood. Some of the variability may depend...

Amplification and dampening of soil respiration by changes in temperature variability

Treesearch

C.A. Sierra; M.E. Harmon; E.A. Thomann; S.S. Perakis; H.W. Loescher

2011-01-01

Accelerated release of carbon from soils is one of the most important feedbacks related to anthropogenically induced climate change. Studies addressing the mechanisms for soil carbon release through organic matter decomposition have focused on the effect of changes in the average temperature, with little attention to changes in temperature variability. Anthropogenic...

Assessing doses to terrestrial wildlife at a radioactive waste disposal site: inter-comparison of modelling approaches.

PubMed

Johansen, M P; Barnett, C L; Beresford, N A; Brown, J E; Černe, M; Howard, B J; Kamboj, S; Keum, D-K; Smodiš, B; Twining, J R; Vandenhove, H; Vives i Batlle, J; Wood, M D; Yu, C

2012-06-15

Radiological doses to terrestrial wildlife were examined in this model inter-comparison study that emphasised factors causing variability in dose estimation. The study participants used varying modelling approaches and information sources to estimate dose rates and tissue concentrations for a range of biota types exposed to soil contamination at a shallow radionuclide waste burial site in Australia. Results indicated that the dominant factor causing variation in dose rate estimates (up to three orders of magnitude on mean total dose rates) was the soil-to-organism transfer of radionuclides that included variation in transfer parameter values as well as transfer calculation methods. Additional variation was associated with other modelling factors including: how participants conceptualised and modelled the exposure configurations (two orders of magnitude); which progeny to include with the parent radionuclide (typically less than one order of magnitude); and dose calculation parameters, including radiation weighting factors and dose conversion coefficients (typically less than one order of magnitude). Probabilistic approaches to model parameterisation were used to encompass and describe variable model parameters and outcomes. The study confirms the need for continued evaluation of the underlying mechanisms governing soil-to-organism transfer of radionuclides to improve estimation of dose rates to terrestrial wildlife. The exposure pathways and configurations available in most current codes are limited when considering instances where organisms access subsurface contamination through rooting, burrowing, or using different localised waste areas as part of their habitual routines. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Effects of Short Term Bioturbation by Common Voles on Biogeochemical Soil Variables

PubMed Central

Wilske, Burkhard; Eccard, Jana A.; Zistl-Schlingmann, Marcus; Hohmann, Maximilian; Methler, Annabel; Herde, Antje; Liesenjohann, Thilo; Dannenmann, Michael; Butterbach-Bahl, Klaus; Breuer, Lutz

2015-01-01

Bioturbation contributes to soil formation and ecosystem functioning. With respect to the active transport of matter by voles, bioturbation may be considered as a very dynamic process among those shaping soil formation and biogeochemistry. The present study aimed at characterizing and quantifying the effects of bioturbation by voles on soil water relations and carbon and nitrogen stocks. Bioturbation effects were examined based on a field set up in a luvic arenosol comprising of eight 50 × 50 m enclosures with greatly different numbers of common vole (Microtus arvalis L., ca. 35–150 individuals ha–1 mth–1). Eleven key soil variables were analyzed: bulk density, infiltration rate, saturated hydraulic conductivity, water holding capacity, contents of soil organic carbon (SOC) and total nitrogen (N), CO2 emission potential, C/N ratio, the stable isotopic signatures of 13C and 15N, and pH. The highest vole densities were hypothesized to cause significant changes in some variables within 21 months. Results showed that land history had still a major influence, as eight key variables displayed an additional or sole influence of topography. However, the δ15N at depths of 10–20 and 20–30 cm decreased and increased with increasing vole numbers, respectively. Also the CO2 emission potential from soil collected at a depth of 15–30 cm decreased and the C/N ratio at 5–10 cm depth narrowed with increasing vole numbers. These variables indicated the first influence of voles on the respective mineralization processes in some soil layers. Tendencies of vole activity homogenizing SOC and N contents across layers were not significant. The results of the other seven key variables did not confirm significant effects of voles. Thus overall, we found mainly a first response of variables that are indicative for changes in biogeochemical dynamics but not yet of those representing changes in pools. PMID:25954967

Effects of short term bioturbation by common voles on biogeochemical soil variables.

PubMed

Wilske, Burkhard; Eccard, Jana A; Zistl-Schlingmann, Marcus; Hohmann, Maximilian; Methler, Annabel; Herde, Antje; Liesenjohann, Thilo; Dannenmann, Michael; Butterbach-Bahl, Klaus; Breuer, Lutz

2015-01-01

Bioturbation contributes to soil formation and ecosystem functioning. With respect to the active transport of matter by voles, bioturbation may be considered as a very dynamic process among those shaping soil formation and biogeochemistry. The present study aimed at characterizing and quantifying the effects of bioturbation by voles on soil water relations and carbon and nitrogen stocks. Bioturbation effects were examined based on a field set up in a luvic arenosol comprising of eight 50 × 50 m enclosures with greatly different numbers of common vole (Microtus arvalis L., ca. 35-150 individuals ha-1 mth-1). Eleven key soil variables were analyzed: bulk density, infiltration rate, saturated hydraulic conductivity, water holding capacity, contents of soil organic carbon (SOC) and total nitrogen (N), CO2 emission potential, C/N ratio, the stable isotopic signatures of 13C and 15N, and pH. The highest vole densities were hypothesized to cause significant changes in some variables within 21 months. Results showed that land history had still a major influence, as eight key variables displayed an additional or sole influence of topography. However, the δ15N at depths of 10-20 and 20-30 cm decreased and increased with increasing vole numbers, respectively. Also the CO2 emission potential from soil collected at a depth of 15-30 cm decreased and the C/N ratio at 5-10 cm depth narrowed with increasing vole numbers. These variables indicated the first influence of voles on the respective mineralization processes in some soil layers. Tendencies of vole activity homogenizing SOC and N contents across layers were not significant. The results of the other seven key variables did not confirm significant effects of voles. Thus overall, we found mainly a first response of variables that are indicative for changes in biogeochemical dynamics but not yet of those representing changes in pools.

The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.

2011-12-01

Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.

Variations in thematic mapper spectra of soil related to tillage and crop residue management - Initial evaluation

NASA Technical Reports Server (NTRS)

Seeley, M. W.; Ruschy, D. L.; Linden, D. R.

1983-01-01

A cooperative research project was initiated in 1982 to study differences in thematic mapper spectral characteristics caused by variable tillage and crop residue practices. Initial evaluations of radiometric data suggest that spectral separability of variably tilled soils can be confounded by moisture and weathering effects. Separability of bare tilled soils from those with significant amounts of corn residue is enhanced by wet conditions, but still possible under dry conditions when recent tillage operations have occurred. In addition, thematic mapper data may provide an alternative method to study the radiant energy balance at the soil surface in conjunction with variable tillage systems.

Influence of soil conditions on dissolved organic matter leached from forest and wetland soils: a controlled growth chamber study.

PubMed

Kim, Eun-Ah; Nguyen, Hang Vo-Minh; Oh, Hae Sung; Hur, Jin; Choi, Jung Hyun

2016-03-01

This study investigated the effects of various soil conditions, including drying-rewetting, nitrogen deposition, and temperature rise, on the quantities and the composition of dissolved organic matter leached from forest and wetland soils. A set of forest and wetland soils with and without the nitrogen deposition were incubated in the growth chambers under three different temperatures. The moisture contents were kept constant, except for two-week drying intervals. Comparisons between the original and the treated samples revealed that drying-rewetting was a crucial environmental factor driving changes in the amount of dissolved organic carbon (DOC). The DOC was also notably increased by the nitrogen deposition to the dry forest soil and was affected by the temperature of the dry wetland soil. A parallel factor (PARAFAC) analysis identified three sub-fractions of the fluorescent dissolved organic matter (FDOM) from the fluorescence excitation-emission matrices (EEMs), and their compositions depended on drying-rewetting. The data as a whole, including the DOC and PARAFAC components and other optical indices, were possibly explained by the two main variables, which were closely related with the PARAFAC components and DOC based on principal component analysis (PCA). Our results suggested that the DOC and PARAFAC component information could provide a comprehensive interpretation of the changes in the soil-leached DOM in response to the different environmental conditions.

Spatial and temporal variability of soil hydraulic properties of topsoil affected by soil erosion

NASA Astrophysics Data System (ADS)

Nikodem, Antonin; Kodesova, Radka; Jaksik, Ondrej; Jirku, Veronika; Klement, Ales; Fer, Miroslav

2014-05-01

This study is focused on the comparison of soil hydraulic properties of topsoil that is affected by erosion processes. In order to include variable morphological and soil properties along the slope three sites - Brumovice, Vidim and Sedlčany were selected. Two transects (A, B) and five sampling sites along each one were chosen. Soil samples were taken in Brumovice after the tillage and sowing of winter wheat in October 2010 and after the wheat harvest in August 2011. At locality Vidim and Sedlčany samples were collected in May and August 2012. Soil hydraulic properties were studied in the laboratory on the undisturbed 100-cm3 soil samples placed in Tempe cells using the multi-step outflow test. Soil water retention data points were obtained by calculating water balance in the soil sample at each pressure head step of the experiment. The single-porosity model in HYDRUS-1D was applied to analyze the multi-step outflow and to obtain the parameters of soil hydraulic properties using the numerical inversion. The saturated hydraulic conductivities (Ks) and unsaturated hydraulic conductivities (Kw) for the pressure head of -2 cm of topsoil were also measured after the harvest using Guelph permeameter and Minidisk tensiometer, respectively. In general soil water retention curves measured before and after vegetation period apparently differed, which indicated soil material consolidation and soil-porous system rearrangement. Soil water retention curves obtained on the soil samples and hydraulic conductivities measured in the field reflected the position at the elevation transect and the effect of erosion/accumulation processes on soil structure and consequently on the soil hydraulic properties. The highest Ks values in Brumovice were obtained at the steepest parts of the elevation transects, that have been the most eroded. The Ks values at the bottom parts decreased due to the sedimentation of eroded soil particles. The change of the Kw values along transects didn't show similar trends. However, the variability of values within both transects was low. Higher values were obtained in transect B, where the soil was more affected by erosion. The highest values of Ks as well as the value of Kw were also obtained in the steepest part of transect A in Vidim. This trend was not observed in transect B. The results corresponded with measured retention curves. Two different trends were shown in Sedlčany. While the highest values of Ks and Kw were found in the upper part of transect A, in the case of transect B the highest values were measured at the bottom of transect. Differences observed at both localities were caused by the different terrain attributes of both transects and extent of soil erosion. Acknowledgement: Authors acknowledge the financial support of the Ministry of Agriculture of the Czech Republic (QJ1230319).

Estimating soil turnover rate from tree uprooting during hurricanes in Puerto Rico

USGS Publications Warehouse

Lenart, M.T.; Falk, D.A.; Scatena, F.N.; Osterkamp, W.R.

2010-01-01

Soil turnover by tree uprooting in primary and secondary forests on the island of Puerto Rico was measured in 42 study plots in the months immediately after the passage of a Category 3 hurricane. Trunk basal area explained 61% of the variability of mound volume and 53% of the variability of mound area. The proportion of uprooted trees, the number of uprooted trees, or the proportion of uprooted basal area explained 84-85% of the variation in hurricane-created mound area. These same variables explain 79-85% of the variation in mound volume. The study indicates that the soil turnover period from tree uprooting by Puerto Rican hurricanes is between 1600 and 4800 years. These rates are faster than soil turnover by landslides and background treefall in the same area and provide a useful age constraint on soil profile development and soil carbon sequestration in these dynamic landscapes. ?? 2009 Elsevier B.V.

Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

PubMed

El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

2007-02-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

Use of clay to remediate cadmium contaminated soil under different water management regimes.

PubMed

Li, Jianrui; Xu, Yingming

2017-07-01

We examined in situ remediation of sepiolite on cadmium-polluted soils with diverse water regimes, and several variables including brown rice Cd, exchangeable Cd, pH, and available Fe/P. pH, available Fe/P in soils increased gradually during continuous flooding, which contributed to Cd absorption on colloids. In control group (untreated soils), compared to conventional irrigation, brown rice Cd in continuous flooding reduced by 37.9%, and that in wetting irrigation increased by 31.0% (p<0.05). In contrast to corresponding controls, brown rice Cd in sepiolite treated soils reduced by 44.4%, 34.5% and 36.8% under continuous flooding, conventional irrigation and wetting irrigation (p<0.05), and exchangeable Cd in amended soils reduced by 27.5-49.0%, 14.3-40.5%, and 24.9-32.8% under three water management regimes (p<0.05). Compared to corresponding controls, decreasing amplitudes of exchangeable Cd and brown rice Cd in sepiolite treated soils were higher in continuous flooding than in conventional irrigation and wetting irrigation. Continuous flooding management promoted soil Cd immobilization by sepiolite. Copyright © 2017. Published by Elsevier Inc.

BOREAS RSS-8 BIOME-BGC Model Simulations at Tower Flux Sites in 1994

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Kimball, John

2000-01-01

BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.

Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange

NASA Astrophysics Data System (ADS)

Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.

2017-12-01

Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional-to-global land-atmosphere CO2 exchange.

Plant Trait Diversity Buffers Variability in Denitrification Potential over Changes in Season and Soil Conditions

PubMed Central

McGill, Bonnie M.; Sutton-Grier, Ariana E.; Wright, Justin P.

2010-01-01

Background Denitrification is an important ecosystem service that removes nitrogen (N) from N-polluted watersheds, buffering soil, stream, and river water quality from excess N by returning N to the atmosphere before it reaches lakes or oceans and leads to eutrophication. The denitrification enzyme activity (DEA) assay is widely used for measuring denitrification potential. Because DEA is a function of enzyme levels in soils, most ecologists studying denitrification have assumed that DEA is less sensitive to ambient levels of nitrate (NO3 −) and soil carbon and thus, less variable over time than field measurements. In addition, plant diversity has been shown to have strong effects on microbial communities and belowground processes and could potentially alter the functional capacity of denitrifiers. Here, we examined three questions: (1) Does DEA vary through the growing season? (2) If so, can we predict DEA variability with environmental variables? (3) Does plant functional diversity affect DEA variability? Methodology/Principal Findings The study site is a restored wetland in North Carolina, US with native wetland herbs planted in monocultures or mixes of four or eight species. We found that denitrification potentials for soils collected in July 2006 were significantly greater than for soils collected in May and late August 2006 (p<0.0001). Similarly, microbial biomass standardized DEA rates were significantly greater in July than May and August (p<0.0001). Of the soil variables measured—soil moisture, organic matter, total inorganic nitrogen, and microbial biomass—none consistently explained the pattern observed in DEA through time. There was no significant relationship between DEA and plant species richness or functional diversity. However, the seasonal variance in microbial biomass standardized DEA rates was significantly inversely related to plant species functional diversity (p<0.01). Conclusions/Significance These findings suggest that higher plant functional diversity may support a more constant level of DEA through time, buffering the ecosystem from changes in season and soil conditions. PMID:20661464

Detection of Soil Nitrogen Using Near Infrared Sensors Based on Soil Pretreatment and Algorithms

PubMed Central

Nie, Pengcheng; Dong, Tao; He, Yong; Qu, Fangfang

2017-01-01

Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly by using a near-infrared sensor. The data can be analyzed in the detection process, which is nondestructive and non-polluting. In order to investigate the effect of soil pretreatment on nitrogen content by near infrared sensor, 16 nitrogen concentrations were mixed with soil and the soil samples were divided into three groups with different pretreatment. The first group of soil samples with strict pretreatment were dried, ground, sieved and pressed. The second group of soil samples were dried and ground. The third group of soil samples were simply dried. Three linear different modeling methods are used to analyze the spectrum, including partial least squares (PLS), uninformative variable elimination (UVE), competitive adaptive reweighted algorithm (CARS). The model of nonlinear partial least squares which supports vector machine (LS-SVM) is also used to analyze the soil reflectance spectrum. The results show that the soil samples with strict pretreatment have the best accuracy in predicting nitrogen content by near-infrared sensor, and the pretreatment method is suitable for practical application. PMID:28492480

Modern Timber Harvesting Practices Have Little Short-Term Effect on Soil Carbon Stores in Industrial Forests of Western Oregon and Washington, U.S.A.

NASA Astrophysics Data System (ADS)

Holub, S. M.; Hatten, J. A.

2017-12-01

Soil carbon represents a large, but slowly changing pool of carbon in forests and understanding its response to forest management, including harvesting, is critical for determining overall stand/landscape carbon balance. Past studies have observed mixed effects of harvesting on soil carbon possibly due, in part, to imprecise sampling methods and high variability within soils. Weyerhaeuser Company has led a major effort to examine the effect of conventional timber harvesting on long-term soil carbon stores in western Oregon and Washington Douglas-fir forests using a highly-replicated longitudinal study design that enables precise estimation of variability found in these systems. In 2010, we randomly selected nine harvest units from Weyerhaeuser's 2012 harvest plan. At each non-harvested unit, a uniform, non-rocky area of about 3-6 hectares was selected for the study. Pre-harvest soil samples were collected at 300 sample points from each unit on a fixed square grid, targeting an intensity that would allow detection of >5% change in soil carbon stores. We measured soil carbon concentration and soil bulk density in depth increments to 1 m to allow for the calculation of total soil carbon per hectare. Other ecosystem pools of carbon, such as trees and downed wood, also have been measured to complete the whole-site carbon budget. All units were harvested from late 2011 through mid-year 2012. In 2015, 3-3.5 years post-harvest, we resampled the same areas in an identical manner as the pre-harvest collection to evaluate changes in soil carbon following harvest. Across all sites combined, we estimated a +2% change (-2% to +6%, 95% confidence interval) in mineral soil carbon following harvest, which is consistent with small-to-no change. Individual sites varied in direction of response; only one site showed evidence of a slight decrease in soil carbon, while two sites showed slight gains. These early results indicate that Weyerhaeuser's conventional timber harvesting methods in the Pacific Northwest do not cause substantial short-term losses in soil carbon. Continued monitoring is necessary, however, to document the longer-term trajectory of soil carbon levels through stand development.

Soil erodibility variability in laboratory and field rainfall simulations

NASA Astrophysics Data System (ADS)

Szabó, Boglárka; Szabó, Judit; Jakab, Gergely; Centeri, Csaba; Szalai, Zoltán

2017-04-01

Rainfall simulation experiments are the most common way to observe and to model the soil erosion processes in in situ and ex situ circumstances. During modelling soil erosion, one of the most important factors are the annual soil loss and the soil erodibility which represent the effect of soil properties on soil loss and the soil resistance against water erosion. The amount of runoff and soil loss can differ in case of the same soil type, while it's characteristics determine the soil erodibility factor. This leads to uncertainties regarding soil erodibility. Soil loss and soil erodibility were examined with the investigation of the same soil under laboratory and field conditions with rainfall simulators. The comparative measurement was carried out in a laboratory on 0,5 m2, and in the field (Shower Power-02) on 6 m2 plot size where the applied slope angles were 5% and 12% with 30 and 90 mm/h rainfall intensity. The main idea was to examine and compare the soil erodibility and its variability coming from the same soil, but different rainfall simulator type. The applied model was the USLE, nomograph and other equations which concern single rainfall events. The given results show differences between the field and laboratory experiments and between the different calculations. Concerning for the whole rainfall events runoff and soil loss, were significantly higher at the laboratory experiments, which affected the soil erodibility values too. The given differences can originate from the plot size. The main research questions are that: How should we handle the soil erodibility factors and its significant variability? What is the best solution for soil erodibility determination?

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2015-04-01

Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.

VARIABLE CHARGE SOILS: MINERALOGY AND CHEMISTRY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Ranst, Eric; Qafoku, Nikolla; Noble, Andrew

2016-09-19

Soils rich in particles with amphoteric surface properties in the Oxisols, Ultisols, Alfisols, Spodosols and Andisols orders (1) are considered to be variable charge soils (2) (Table 1). The term “variable charge” is used to describe organic and inorganic soil constituents with reactive surface groups whose charge varies with pH and ionic concentration and composition of the soil solution. Such groups are the surface carboxyl, phenolic and amino functional groups of organic materials in soils, and surface hydroxyl groups of Fe and Al oxides, allophane and imogolite. The hydroxyl surface groups are also present on edges of some phyllosilicate mineralsmore » such as kaolinite, mica, and hydroxyl-interlayered vermiculite. The variable charge is developed on the surface groups as a result of adsorption or desorption of ions that are constituents of the solid phase, i.e., H+, and the adsorption or desorption of solid-unlike ions that are not constituents of the solid phase. Highly weathered soils and subsoils (e.g., Oxisols and some Ultisols, Alfisols and Andisols) may undergo isoelectric weathering and reach a “zero net charge” stage during their development. They usually have a slightly acidic to acidic soil solution pH, which is close to either the point of zero net charge (PZNC) (3) or the point of zero salt effect (PZSE) (3). They are characterized by high abundances of minerals with a point of zero net proton charge (PZNPC) (3) at neutral and slightly basic pHs; the most important being Fe and Al oxides and allophane. Under acidic conditions, the surfaces of these minerals are net positively charged. In contrast, the surfaces of permanent charge phyllosilicates are negatively charged regardless of ambient conditions. Variable charge soils therefore, are heterogeneous charge systems.« less

Geochemical variability of natural soils and reclaimed minespoil soils in the San Juan Basin, New Mexico

USGS Publications Warehouse

Gough, L.P.; Severson, R.C.

1981-01-01

An inventory of total-and extractable-element concentrations in soils was made for three areas of the San Juan Basin in New Mexico: (1) the broad area likely to be affected by energy-related development. (2) an area of soils considered to have potential for use as topsoil in mined-land reclamation. and (3) an area of the San Juan coal mine that has been regraded. topsoiled, and revegetated. Maps made of concentrations of 16 elements in area 1 soils show no gradational pattern across the region. Further. these maps do not correspond to those showing geology or soil types. Sodic or saline problems, and a possible but unproven deficiency of zinc available to plants. may make some of the soils in this area undesirable for use as topsoil in mined-land reclamation. Taxonomic great groups of soil in this area cannot be distinguished because each great group tends to have a large within-group variability if compared to the between-group variability. In area 2 the major soils sampled were of the Sheppard. Shiprock. and Doak association. These soils are quite uniform in chemical composition and are not greatly saline or sodic. As in area 1 soils. zinc deficiency may cause a problem in revegetating most of these soils. It is difficult to distinguish soil taxonomic families by using their respective chemical compositions. because of small between-family variability. Topsoil from a reclaimed area of the San Juan mine (area 3) most closely resembles the chemical composition of natural C horizons of soil from area 1. Spoil material that has not been topsoiled is likely to cause sodic-and saline-related problems in revegetation and may cause boron toxicity in plants. Topsoiling has apparently ameliorated these potential problems for plant growth on mine spoil. Total and extractable concentrations for elements and other parameters for each area of the San Juan Basin provide background information for the evaluation of the chemical quality of soils in each area.

Adsorption of glyphosate on variable-charge, volcanic ash-derived soils.

PubMed

Cáceres-Jensen, L; Gan, J; Báez, M; Fuentes, R; Escudey, M

2009-01-01

Glyphosate (N-phosphonometylglycine) is widely used due to its broad spectrum of activity and nonselective mode of action. In Chile it is the most used herbicide, but its adsorption behavior in the abundant and widespread variable charge soils is not well understood. In this study, three volcanic ash-derived soils were selected, including Andisols (Nueva Braunau and Diguillin) and Ultisols (Collipulli), to evaluate the adsorption kinetics, equilibrium isotherms, and the effect of pH in glyphosate adsorption. The influence of glyphosate on soil phosphorus retention was also studied. Glyphosate was rapidly and strongly adsorbed on the selected soils, and adsorption isotherms were well described by the Freundlich relationship with strong nonlinearity (n(fads) < 0.5). The n(fads) values were consistently higher than n(fdes) values, suggesting strong hysteresis. Adsorption (K(ads)) increased strongly when pH decreased. The presence of glyphosate (3200 mug mL(-1)) changed the adsorption behavior of phosphate at its maximum adsorption capacity. Andisol soils without the addition of glyphosate had similar mean K(ads) values for Nueva Braunau (5.68) and Diguillin (7.38). Collipulli had a mean K(ads) value of 31.58. During the successive desorption steps, glyphosate at the highest level increased K(ads) values for phosphate in the Andisol soils but had little effect in the Ultisol soil. This different behavior was probably due to the irreversible occupation of some adsorption sites by glyphosate in the Ultisol soil attributed to the dominant Kaolinite mineral. Results from this study suggest that in the two types of volcanic soils, different mechanisms are involved in glyphosate and phosphate adsorption and that long-term use of glyphosate may impose different effects on the retention and availability of phosphorus. Volcanic ash-derived soils have a particular environmental behavior in relation to the retention of organic contaminants, representing an environmental substrate that may become highly polluted over time due to intensive agronomic uses.

The Effect of Selected Cleaning Techniques on Berkshire Lee Marble: A Scientific Study at Philadelphia City Hall

USGS Publications Warehouse

Mossotti, Victor G.; Eldeeb, A. Raouf; Fries, Terry L.; Coombs, Mary Jane; Naude, Virginia N.; Soderberg, Lisa; Wheeler, George S.

2002-01-01

This report describes a scientific investigation of the effects of eight different cleaning techniques on the Berkshire Lee marble component of the facade of the East Center Pavilion at Philadelphia City Hall; the study was commissioned by the city of Philadelphia. The eight cleaning techniques evaluated in this study were power wash (proprietary gel detergent followed by water rinse under pressure), misting (treatment with potable, nebulized water for 24-36 hours), gommage (proprietary Thomann-Hanry low-pressure, air-driven, small-particle, dry abrasion), combination (gommage followed by misting), Armax (sodium bicarbonate delivered under pressure in a water wash), JOS (dolomite powder delivered in a low-pressure, rotary-vortex water wash), laser (thermal ablation), and dry ice (powdered-dry-ice abrasion delivered under pressure). In our study approximately 160 cores were removed from the building for laboratory analysis. We developed a computer program to analyze scanning-electron-micrograph images for the microscale surface roughness and other morphologic parameters of the stone surface, including the near-surface fracture density of the stone. An analysis of more than 1,100 samples cut from the cores provided a statistical basis for crafting the essential elements of a reduced-form, mixed-kinetics conceptual model that represents the deterioration of calcareous stone in terms of self-organized soiling and erosion patterns. This model, in turn, provided a basis for identifying the variables that are affected by the cleaning techniques and for evaluating the extent to which such variables influence the stability of the stone. The model recognizes three classes of variables that may influence the soiling load on the stone, including such exogenous environmental variables as airborne moisture, pollutant concentrations, and local aerodynamics, and such endogenous stone variables as surface chemistry and microstructure (fracturing, roughness, and so on). This study showed that morphologic variables on the mesoscale to macroscale are not generally affected by the choice of a cleaning technique. The long-term soiling pattern on the building is independent of the cleaning technique applied. This study also showed that soluble salts do not play a significant role in the deterioration of Berkshire Lee marble. Although salts were evident in cracks and fissures of the heavily soiled stone, such salts did not penetrate the surface to a depth of more than a few hundred micrometers. The criteria used to differentiate the cleaning techniques were ultimately based on the ability of each technique to remove soiling without altering the texture of the stone surface. This study identified both the gommage and JOS techniques as appropriate for cleaning ashlar surfaces and the combination technique as appropriate for cleaning highly carved surfaces at the entablatures, cornices, and column capitals.

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

Linking the climatic and geochemical controls on global soil carbon cycling

NASA Astrophysics Data System (ADS)

Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal

2015-04-01

Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.

Estimating wetland methane emissions from the northern high latitudes from 1990 to 2009 using artificial neural networks

NASA Astrophysics Data System (ADS)

Zhu, Xudong; Zhuang, Qianlai; Qin, Zhangcai; Glagolev, Mikhail; Song, Lulu

2013-04-01

Methane (CH4) emissions from wetland ecosystems in nothern high latitudes provide a potentially positive feedback to global climate warming. Large uncertainties still remain in estimating wetland CH4 emisions at regional scales. Here we develop a statistical model of CH4 emissions using an artificial neural network (ANN) approach and field observations of CH4 fluxes. Six explanatory variables (air temperature, precipitation, water table depth, soil organic carbon, soil total porosity, and soil pH) are included in the development of ANN models, which are then extrapolated to the northern high latitudes to estimate monthly CH4 emissions from 1990 to 2009. We estimate that the annual wetland CH4 source from the northern high latitudes (north of 45°N) is 48.7 Tg CH4 yr-1 (1 Tg = 1012 g) with an uncertainty range of 44.0 53.7 Tg CH4 yr-1. The estimated wetland CH4 emissions show a large spatial variability over the northern high latitudes, due to variations in hydrology, climate, and soil conditions. Significant interannual and seasonal variations of wetland CH4 emissions exist in the past 2 decades, and the emissions in this period are most sensitive to variations in water table position. To improve future assessment of wetland CH4 dynamics in this region, research priorities should be directed to better characterizing hydrological processes of wetlands, including temporal dynamics of water table position and spatial dynamics of wetland areas.

Mapping soil particle-size fractions: A comparison of compositional kriging and log-ratio kriging

NASA Astrophysics Data System (ADS)

Wang, Zong; Shi, Wenjiao

2017-03-01

Soil particle-size fractions (psf) as basic physical variables need to be accurately predicted for regional hydrological, ecological, geological, agricultural and environmental studies frequently. Some methods had been proposed to interpolate the spatial distributions of soil psf, but the performance of compositional kriging and different log-ratio kriging methods is still unclear. Four log-ratio transformations, including additive log-ratio (alr), centered log-ratio (clr), isometric log-ratio (ilr), and symmetry log-ratio (slr), combined with ordinary kriging (log-ratio kriging: alr_OK, clr_OK, ilr_OK and slr_OK) were selected to be compared with compositional kriging (CK) for the spatial prediction of soil psf in Tianlaochi of Heihe River Basin, China. Root mean squared error (RMSE), Aitchison's distance (AD), standardized residual sum of squares (STRESS) and right ratio of the predicted soil texture types (RR) were chosen to evaluate the accuracy for different interpolators. The results showed that CK had a better accuracy than the four log-ratio kriging methods. The RMSE (sand, 9.27%; silt, 7.67%; clay, 4.17%), AD (0.45), STRESS (0.60) of CK were the lowest and the RR (58.65%) was the highest in the five interpolators. The clr_OK achieved relatively better performance than the other log-ratio kriging methods. In addition, CK presented reasonable and smooth transition on mapping soil psf according to the environmental factors. The study gives insights for mapping soil psf accurately by comparing different methods for compositional data interpolation. Further researches of methods combined with ancillary variables are needed to be implemented to improve the interpolation performance.

Plant δ15 N reflects the high landscape-scale heterogeneity of soil fertility and vegetation productivity in a Mediterranean semiarid ecosystem.

PubMed

Ruiz-Navarro, Antonio; Barberá, Gonzalo G; Albaladejo, Juan; Querejeta, José I

2016-12-01

We investigated the magnitude and drivers of spatial variability in soil and plant δ 15 N across the landscape in a topographically complex semiarid ecosystem. We hypothesized that large spatial heterogeneity in water availability, soil fertility and vegetation cover would be positively linked to high local-scale variability in δ 15 N. We measured foliar δ 15 N in three dominant plant species representing contrasting plant functional types (tree, shrub, grass) and mycorrhizal association types (ectomycorrhizal or arbuscular mycorrhizal). This allowed us to investigate whether δ 15 N responds to landscape-scale environmental heterogeneity in a consistent way across species. Leaf δ 15 N varied greatly within species across the landscape and was strongly spatially correlated among co-occurring individuals of the three species. Plant δ 15 N correlated tightly with soil δ 15 N and key measures of soil fertility, water availability and vegetation productivity, including soil nitrogen (N), organic carbon (C), plant-available phosphorus (P), water-holding capacity, topographic moisture indices and normalized difference vegetation index. Multiple regression models accounted for 62-83% of within-species variation in δ 15 N across the landscape. The tight spatial coupling and interdependence of the water, N and C cycles in drylands may allow the use of leaf δ 15 N as an integrative measure of variations in moisture availability, biogeochemical activity, soil fertility and vegetation productivity (or 'site quality') across the landscape. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

On the role of "internal variability" on soil erosion assessment

NASA Astrophysics Data System (ADS)

Kim, Jongho; Ivanov, Valeriy; Fatichi, Simone

2017-04-01

Empirical data demonstrate that soil loss is highly non-unique with respect to meteorological or even runoff forcing and its frequency distributions exhibit heavy tails. However, all current erosion assessments do not describe the large associated uncertainties of temporal erosion variability and make unjustified assumptions by relying on central tendencies. Thus, the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. In this study, we attempt to reveal that the high variability in soil losses can be attributed to two sources: (1) 'external variability' referring to the uncertainties originating at macro-scale, such as climate, topography, and land use, which has been extensively studied; (2) 'geomorphic internal variability' referring to the micro-scale variations of pedologic properties (e.g., surface erodibility in soils with multi-sized particles), hydrologic properties (e.g., soil structure and degree of saturation), and hydraulic properties (e.g., surface roughness and surface topography). Using data and a physical hydraulic, hydrologic, and erosion and sediment transport model, we show that the geomorphic internal variability summarized by spatio-temporal variability in surface erodibility properties is a considerable source of uncertainty in erosion estimates and represents an overlooked but vital element of geomorphic response. The conclusion is that predictive frameworks of soil erosion should embed stochastic components together with deterministic assessments, if they do not want to largely underestimate uncertainty. Acknowledgement: This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).

Temporal variability of carbon and nutrient burial, sediment accretion, and mass accumulation over the past century in a carbonate platform mangrove forest of the Florida Everglades.

USGS Publications Warehouse

Breithaupt, Josh L.; Smoak, Joseph M.; Smith, Thomas J.; Sanders, Christian J.

2014-01-01

The objective of this research was to measure temporal variability in accretion and mass sedimentation rates (including organic carbon (OC), total nitrogen (TN), and total phosphorous (TP)) from the past century in a mangrove forest on the Shark River in Everglades National Park, USA. The 210Pb Constant Rate of Supply model was applied to six soil cores to calculate annual rates over the most recent 10, 50, and 100 year time spans. Our results show that rates integrated over longer timeframes are lower than those for shorter, recent periods of observation. Additionally, the substantial spatial variability between cores over the 10 year period is diminished over the 100 year record, raising two important implications. First, a multiple-decade assessment of soil accretion and OC burial provides a more conservative estimate and is likely to be most relevant for forecasting these rates relative to long-term processes of sea level rise and climate change mitigation. Second, a small number of sampling locations are better able to account for spatial variability over the longer periods than for the shorter periods. The site average 100 year OC burial rate, 123 ± 19 (standard deviation) g m-2yr-1, is low compared with global mangrove values. High TN and TP burial rates in recent decades may lead to increased soil carbon remineralization, contributing to the low carbon burial rates. Finally, the strong correlation between OC burial and accretion across this site signals the substantial contribution of OC to soil building in addition to the ecosystem service of CO2 sequestration.

Evaluation of Ten Methods for Initializing a Land Surface Model

NASA Technical Reports Server (NTRS)

Rodell, M.; Houser, P. R.; Berg, A. A.; Famiglietti, J. S.

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).

A system for comparison of boring parameters of mini-HDD machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunsaulis, F.R.

A system has been developed to accurately evaluate changes in performance of a mini-horizontal directional drilling (HDD) system in the backreaming/pullback portion of a bore as the parameters influencing the backream are changed. Parameters incorporated in the study include spindle rotation rate, rate of pull, fluid flow rate, and backreamer design. The boring system is able to run at variable, operator-determined rates of spindle rotation and pullback speed utilizing electronic feedback controls for regulation. Spindle torque and pullback force are continuously measured and recorded giving an indication of the performance of the unit. A method has also been developed tomore » measure the pull load on the installed service line to determine the effect of the boring parameters on the service line. Variability of soil along the bore path is measured and quantified using a soil sampling system developed for the study. Sample results obtained with the system are included in the report. 2 refs., 5 figs., 2 tabs.« less

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

Predicting anthropogenic soils across the Amazonia

NASA Astrophysics Data System (ADS)

Mcmichael, C.; Palace, M. W.; Bush, M. B.; Braswell, B. H.; Hagen, S. C.; Silman, M.; Neves, E.; Czarnecki, C.

2012-12-01

Hidden under the forest canopy in lowland Amazonia are nutrient-enriched soils, called terra pretas (or Amazonian black earths), which were formed by prehistoric indigenous populations. These anthrosols are in stark contrast to typical nutrient-poor Amazonian soils, and have retained increased nutrient levels for hundreds of years. Because of their long-term nutrient retaining ability, terra pretas may be crucial for developing sustainable agricultural practices in Amazonia, especially given the deforestation necessary for traditional slash-and-burn systems. However, the frequency and distribution of terra preta soils across the landscape remains debatable, and archaeologists have estimated that terra pretas cover anywhere from 0.1% to 10% of the lowland Amazonian forests. The highest concentration of terra preta soils has been found along the central and eastern portions of the Amazon River and its major tributaries, but whether this is a true pattern or simply reflects sampling bias remains unknown. A possible explanation is that specific environmental or biotic conditions were preferred for human settlement and terra preta formation. Here, we use environmental parameters to predict the probabilities of terra preta soils across lowland Amazonian forests. We compiled a database of 2708 sites across Amazonia, including locations that contain terra pretas (n = 917), and those that are known to be terra preta-free (n = 1791). More than 20 environmental variables, including precipitation, elevation, slope, soil fertility, and distance to river were converted into 90-m resolution raster images across Amazonia and used to model the probability of terra preta occurrence. The relationship between the predictor variables and the occurrence of terra preta was examined using three modeling techniques: logistic regression, auto-logistic regression, and maximum entropy estimations. All three techniques provided similar predictions for terra preta distributions and the amount of area covered by terra preta. Distance to river, locations of bluffs, elevation, and soil fertility were important factors in determining distributions of terra preta, while other environmental variables had less effect. Terra pretas were most likely to be found in central and eastern Amazonia near the confluences of the Amazon River and its major tributaries. Within this general area of higher probability, terra pretas are most likely found atop the bluffs overlooking the rivers as opposed to lying on the floodplain. Interestingly, terra pretas are more probable in areas with less-fertile and more highly weathered soils. Although all three modeling techniques provided similar predictions of terra preta across Amazonia, we suggest that maximum entropy modeling is the best technique to predict anthropogenic soils across the vast Amazonian landscape. The auto-logistic regression corrects for spatial autocorrelation inherent to archaeological surveys, but still requires absence data, which was collected at different times and on different spatial scales than the presence data. The maximum entropy model requires presence only data, accounts for spatial autocorrelation, and is not affected by the differential soil sampling techniques.

Relations that affect the probability and prediction of nitrate concentration in private wells in the glacial aquifer system in the United States

USGS Publications Warehouse

Warner, Kelly L.; Arnold, Terri L.

2010-01-01

Nitrate in private wells in the glacial aquifer system is a concern for an estimated 17 million people using private wells because of the proximity of many private wells to nitrogen sources. Yet, less than 5 percent of private wells sampled in this study contained nitrate in concentrations that exceeded the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level (MCL) of 10 mg/L (milligrams per liter) as N (nitrogen). However, this small group with nitrate concentrations above the USEPA MCL includes some of the highest nitrate concentrations detected in groundwater from private wells (77 mg/L). Median nitrate concentration measured in groundwater from private wells in the glacial aquifer system (0.11 mg/L as N) is lower than that in water from other unconsolidated aquifers and is not strongly related to surface sources of nitrate. Background concentration of nitrate is less than 1 mg/L as N. Although overall nitrate concentration in private wells was low relative to the MCL, concentrations were highly variable over short distances and at various depths below land surface. Groundwater from wells in the glacial aquifer system at all depths was a mixture of old and young water. Oxidation and reduction potential changes with depth and groundwater age were important influences on nitrate concentrations in private wells. A series of 10 logistic regression models was developed to estimate the probability of nitrate concentration above various thresholds. The threshold concentration (1 to 10 mg/L) affected the number of variables in the model. Fewer explanatory variables are needed to predict nitrate at higher threshold concentrations. The variables that were identified as significant predictors for nitrate concentration above 4 mg/L as N included well characteristics such as open-interval diameter, open-interval length, and depth to top of open interval. Environmental variables in the models were mean percent silt in soil, soil type, and mean depth to saturated soil. The 10-year mean (1992-2001) application rate of nitrogen fertilizer applied to farms was included as the potential source variable. A linear regression model also was developed to predict mean nitrate concentrations in well networks. The model is based on network averages because nitrate concentrations are highly variable over short distances. Using values for each of the predictor variables averaged by network (network mean value) from the logistic regression models, the linear regression model developed in this study predicted the mean nitrate concentration in well networks with a 95 percent confidence in predictions.

Evaluating topsoil depth effects on phosphorus and potassium nutrient dynamics of grain and switchgrass production systems

USDA-ARS?s Scientific Manuscript database

Understanding the effects of fertilizer addition and crop removal on long-term change in soil test phosphorus (STP) and soil test potassium (STK) is crucial for maximizing the use of grower inputs on claypan soils. Due to variable nutrient supply from subsoils and variable crop removal across fields...

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

[Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

PubMed

Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan

2015-06-01

Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Drivers of small scale variability in soil-atmosphere fluxes of CH4, N2O and CO2 in a forest soil

NASA Astrophysics Data System (ADS)

Maier, Martin; Nicolai, Clara; Wheeler, Denis; Lang, Friedeike; Paulus, Sinikka

2016-04-01

Soil-atmosphere fluxes of CH4, N2O and CO2 can vary on different spatial scales, on large scales between ecosystems but also within apparently homogenous sites. While CO2 and CH4 consumption is rather evenly distibuted in well aerated soils, the production of N2O and CH4 seems to occur at hot spots that can be associated with anoxic or suboxic conditions. Small-scale variability in soil properties is well-known from field soil assesment, affecting also soil aeration and thus theoretically, greenhouse gas fluxes. In many cases different plant species are associated with different soil conditions and vegetation mapping should therefor combined with soil mapping. Our research objective was explaining the small scale variability of greenhouse gas fluxes in an apparently homogeneous 50 years old Scots Pine stand in a former riparian flood plain.We combined greenhouse gas measurements and soil physical lab measurments with field soil assessment and vegetation mapping. Measurements were conducted with at 60 points at a plot of 30 X 30 m at the Hartheim monitoring site (SW Germany). For greenhouse gas measurements a non-steady state chamber system and laser analyser, and a photoacoustic analyser were used. Our study shows that the well aerated site was a substantial sink for atmospheric CH4 (-2.4 nmol/m² s) and also a for N2O (-0.4 nmol/m² s), but less pronounced, whereas CO2 production was a magnitude larger (2.6 μmol/m² s). The spatial variability of the CH4 consumption of the soils could be explained by the variability of the soil gas diffusivity (measured in situ + using soil cores). Deviations of this clear trend were only observed at points where decomposing woody debris was directly under the litter layer. Soil texture ranged from gravel, coarse sand, fine sand to pure silt, with coarser texture having higher soil gas diffusivity. Changes in texture were rather abrupt at some positions or gradual at other positions, and were well reflected in the vegetation structure. On patches of gravel and coarse sand there was hardly any ground vegatation, and a shrublayer was found only at silty patches Our results indicate that a stratification and regionalisation approach based on vegetation structure and soil texture represents a promising tool for the adjustment of sampling designs for soil gas flux measurement. Acknowledgement This research was financially supported by the project DFG (MA 5826/2-1).

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

2016-04-01

Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the soil profile. Future research should focus on spatial patterns on soil pH, electrical conductivity and sodium adsorption ratio. Keywords: geostatistics, semivariogram, interpolation models, soil chemical properties

Characterization of hot spots for natural chloroform formation: Relevance for groundwater quality

NASA Astrophysics Data System (ADS)

Jacobsen, Ole S.; Albers, Christian N.; Laier, Troels

2015-04-01

Chloroform soil hot spot may deteriorate groundwater quality and may even result in chloroform concentration exceeding the Danish maximum limit of 1 µg/L in groundwater for potable use. In order to characterize the soil properties important for the chloroform production, various ecosystems were examined with respect to soil air chloroform and soil organic matter type and content. Coniferous forest areas, responsible for highest chloroform concentrations, were examined on widely different scales from km to cm scale. Furthermore, regular soil gas measurements including chloroform were performed during 4 seasons at various depths, together with various meteorological measurements and soil temperature recordings. Laboratory incubation experiments were also performed on undisturbed soil samples in order to examine the role of various microbiota, fungi and bacteria. To identify hot spots responsible for the natural contamination we have measured the production of chloroform in the upper soil from different terrestrial systems. Field measurements of chloroform in top soil air were used as production indicators. The production was however not evenly distributed at any scale. The ecosystems seem to have quite different net-productions of chloroform from very low in grassland to very high in some coniferous forests. Within the forest ecosystem we found large variation in chloroform concentrations depending on vegetation. In beech forest we found the lowest values, somewhat higher in an open pine forest, but the highest concentrations were detected in spruce forest without any vegetation beneath. Within this ecotype, it appeared that the variation was also large; hot spots with 2-4 decades higher production than the surrounding area. These hot spots were not in any way visually different from the surroundings and were of variable size from 3 to 20 meters in diameter. Besides this, measurements within a seemingly homogenous hot spot showed that there was still high variability at 10 cm level. We suggest that the mechanism behind the formation of chloroform is an unspecific chlorination of organic matter, caused by microbial activity in the soil forming trichloroacetyl compounds. Laboratory measurements on intact soil cores have identified that the F and H horizons in the forest soil are the main producers of chloroform. Despite various attempts to identify the mechanisms responsible for the variability within a visually and chemically homogeneous area we have not yet succeeded. Parameters like soil respiration, inorganic and total organic chlorine, organic matter and soil structure were studied without any significant difference in favour of hot spots. By the use of 13C-isotopes we could identify the natural origin of the chloroform, and over a three years period we could conclude that the hot spots were permanent on the sites. At the same time a significant seasonal variation were measured depending on temperature and soil moisture.

Instrumenting an upland research catchment in Canterbury, New Zealand to study controls on variability of soil moisture, shallow groundwater and streamflow

NASA Astrophysics Data System (ADS)

McMillan, Hilary; Srinivasan, Ms

2015-04-01

Hydrologists recognise the importance of vertical drainage and deep flow paths in runoff generation, even in headwater catchments. Both soil and groundwater stores are highly variable over multiple scales, and the distribution of water has a strong control on flow rates and timing. In this study, we instrumented an upland headwater catchment in New Zealand to measure the temporal and spatial variation in unsaturated and saturated-zone responses. In NZ, upland catchments are the source of much of the water used in lowland agriculture, but the hydrology of such catchments and their role in water partitioning, storage and transport is poorly understood. The study area is the Langs Gully catchment in the North Branch of the Waipara River, Canterbury: this catchment was chosen to be representative of the foothills environment, with lightly managed dryland pasture and native Matagouri shrub vegetation cover. Over a period of 16 months we measured continuous soil moisture at 32 locations and near-surface water table (< 2 m) at 14 locations, as well as measuring flow at 3 stream gauges. The distributed measurement sites were located to allow comparisons between North and South facing locations, near-stream versus hillslope locations, and convergent versus divergent hillslopes. We found that temporal variability is strongly controlled by the climatic seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of their distributions. Groundwater is a larger water storage component than soil moisture, and the difference increases with catchment wetness. The spatial standard deviation of both soil moisture and groundwater is larger in winter than in summer. It peaks during rainfall events due to partial saturation of the catchment, and also rises in spring as different locations dry out at different rates. The most important controls on spatial variability are aspect and distance from stream. South-facing and near-stream locations have higher water tables and more, larger soil moisture wetting events. Typical hydrological models do not explicitly account for aspect, but our results suggest that it is an important factor in hillslope runoff generation. Co-measurement of soil moisture and water table level allowed us to identify interrelationships between the two. Locations where water tables peaked closest to the surface had consistently wetter soils and higher water tables. These wetter sites were the same across seasons. However, temporary patterns of strong soil moisture response to summer storms did not correspond to the wetter sites. Total catchment spatial variability is composed of multiple variability sources, and the dominant type is sensitive to those stores that are close to a threshold such as field capacity or saturation. Therefore, we classified spatial variability as 'summer mode' or 'winter mode'. In summer mode, variability is controlled by shallow processes e.g. interactions of water with soils and vegetation. In winter mode, variability is controlled by deeper processes e.g. groundwater movement and bypass flow. Double flow peaks observed during some events show the direct impact of groundwater variability on runoff generation. Our results suggest that emergent catchment behaviour depends on the combination of these multiple, time varying components of variability.

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies

NASA Astrophysics Data System (ADS)

Tootle, G.; Anderson, S.; Grissino-Mayer, H.

2012-12-01

Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

Assessing Vulnerability of Lake Erie Landscapes to Soil Erosion: Modelled and Measured Approaches

NASA Astrophysics Data System (ADS)

Joosse, P.; Laamrani, A.; Feisthauer, N.; Li, S.

2017-12-01

Loss of soil from agricultural landscapes to Lake Erie via water erosion is a key transport mechanism for phosphorus bound to soil particles. Agriculture is the dominant land use in the Canadian side of the Lake Erie basin with approximately 75% of the 2.3 million hectares under crop or livestock production. The variable geography and diversity of agricultural production systems and management practices makes estimating risk of soil erosion from agricultural landscapes in the Canadian Lake Erie basin challenging. Risk of soil erosion depends on a combination of factors including the extent to which soil remains bare, which differs with crop type and management. Two different approaches of estimating the vulnerability of landscapes to soil erosion will be compared among Soil Landscapes of Canada in the Lake Erie basin: a modelling approach incorporating farm census and soil survey data, represented by the 2011 Agriculture and Agri-Food Canada Agri-Environmental Indicator for Soil Erosion Risk; and, a measured approach using remotely sensed data that quantifies the magnitude of bare and covered soil across the basin. Results from both approaches will be compared by scaling the national level (1:1 million) Soil Erosion Risk Indicator and the remotely sensed data (30x30 m resolution) to the quaternary watershed level.

Interannual Variability in Global Soil Respiration on a 0.5 Degree Grid Cell Basis (1980-1994)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raich, J.W.

2003-09-15

We used a climate-driven regression model to develop spatially resolved estimates of soil-CO{sub 2} emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil-to-atmosphere CO{sub 2} fluxes. The mean annual global soil-CO{sub 2} flux over this 15-y period was estimated to be 80.4 (range 79.3-81.8) Pg C. Monthly variations in global soil-CO{sub 2} emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil-CO{sub 2} emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreenmore » broad-leaved forests contributed more soil-derived CO{sub 2} to the atmosphere than did any other vegetation type ({approx}30% of the total) and exhibited a biannual cycle in their emissions. Soil-CO{sub 2} emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil-CO{sub 2} production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO{sub 2} concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands, and deserts), interannual variability in soil-CO{sub 2} emissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil-CO{sub 2} fluxes correlated with mean annual temperature, with a slope of 3.3 PgCY{sup -1} per degree Celsius. Although the distribution of precipitation influences seasonal and spatial patterns of soil-CO{sub 2} emissions, global warming is likely to stimulate CO{sub 2} emissions from soils.« less

Effects of biochar produced from different feedstocks on soil properties and sunflower growth

NASA Astrophysics Data System (ADS)

Alburquerque, J. A.; Calero, J. M.; Villar, R.; Barrón, V.; Torrent, J.; del Campillo, M. C.; Gallardo, A.

2012-04-01

The use of biochar obtained from biomass pyrolysis as a soil amendment has potential benefits, such as reduction in gas emissions, increase in soil carbon sequestration and improvements in soil fertility and crop yield. These constitute a great incentive for the implementation of biochar-based strategies, which could contribute to improvement of the sustainability of agricultural systems. However, to date, the results of research studies show great variability as a result of differences in both the raw materials and the pyrolysis conditions used to produce biochar, as well as in the experimental setting (crop, soil type, pedo-climatic conditions, etc.). The aim of this study was to evaluate the effects of five types of biochar produced from representative agricultural and forestry wastes (olive husk, almond shell, wheat straw, pine woodchips and olive tree prunings), and applied to soil at different rates, on soil properties and sunflower (Helianthus annuus L.) growth. The biochars had a high organic matter content, alkaline pH, variable soluble salt content and non-phytotoxic properties. The addition of biochar to soil increased pH, electrical conductivity and water retention capacity, and decreased soil bulk density compared to control (unamended soil). However, these effects differed depending on biochar type. In contrast, no consistent effects on sunflower growth variables were observed due to the addition of biochar: increases were observed in some variables (plant dry weight, leaf area and height), but these increases were, in general, not statistically significant when compared to the unamended soil. This can be explained by the nature of biochar, being rich in carbon but relatively poor in nutrients. In summary, our results indicate that biochar is capable of improving soil properties which can impact positively on soil-plant water relations, without negative effects on sunflower growth, and therefore it is suitable for use as a long-term carbon sink in agricultural soils, with both agricultural and environmental benefits.

Soil variability in engineering applications

NASA Astrophysics Data System (ADS)

Vessia, Giovanna

2014-05-01

Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random Finite Element Method (RFEM). This method has been used to investigate the random behavior of soils in the context of a variety of classical geotechnical problems. Afterward, some following studies collected the worldwide variability values of many technical parameters of soils (Phoon and Kulhawy 1999a) and their spatial correlation functions (Phoon and Kulhawy 1999b). In Italy, Cherubini et al. (2007) calculated the spatial variability structure of sandy and clayey soils from the standard cone penetration test readings. The large extent of the worldwide measured spatial variability of soils and rocks heavily affects the reliability of geotechnical designing as well as other uncertainties introduced by testing devices and engineering models. So far, several methods have been provided to deal with the preceding sources of uncertainties in engineering designing models (e.g. First Order Reliability Method, Second Order Reliability Method, Response Surface Method, High Dimensional Model Representation, etc.). Nowadays, the efforts in this field have been focusing on (1) measuring spatial variability of different rocks and soils and (2) developing numerical models that take into account the spatial variability as additional physical variable. References Cherubini C., Vessia G. and Pula W. 2007. Statistical soil characterization of Italian sites for reliability analyses. Proc. 2nd Int. Workshop. on Characterization and Engineering Properties of Natural Soils, 3-4: 2681-2706. Griffiths D.V. and Fenton G.A. 1993. Seepage beneath water retaining structures founded on spatially random soil, Géotechnique, 43(6): 577-587. Mandelbrot B.B. 1983. The Fractal Geometry of Nature. San Francisco: W H Freeman. Matheron G. 1962. Traité de Géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 p. Phoon K.K. and Kulhawy F.H. 1999a. Characterization of geotechnical variability. Can Geotech J, 36(4): 612-624. Phoon K.K. and Kulhawy F.H. 1999b. Evaluation of geotechnical property variability. Can Geotech J, 36(4): 625-639. Terzaghi K. 1943. Theoretical Soil Mechanics. New York: John Wiley and Sons. Turcotte D.L. 1986. Fractals and fragmentation. J Geophys Res, 91: 1921-1926. Vanmarcke E.H. 1977. Probabilistic modeling of soil profiles. J Geotech Eng Div, ASCE, 103: 1227-1246. Vanmarcke E.H. 1983. Random fields: analysis and synthesis. MIT Press, Cambridge.

The Role of Mycorrhizal Associations in Controlling Biogenic Volatile Organic Carbon Flux From a Temperate Deciduous Forest

NASA Astrophysics Data System (ADS)

Cook, A. A.; Trowbridge, A.; Jacobs, L. M.; Stoy, P. C.; Stevens, P. S.; Phillips, R.

2016-12-01

The sources of and controls over biogenic volatile organic compound (bVOC) fluxes between terrestrial ecosystems and the atmosphere remains poorly understood. Ecosystem bVOC flux models rarely include contributions from leaf litter and soils despite recent findings demonstrating that they can be nontrivial components of total ecosystem bVOC flux. Other recent studies have demonstrated the central role of arbuscular (AM) versus ectomycorrhizal (ECM) fungi in determining litter quality and soil biogeochemistry. Here, we quantify the role of mycorrhizal associations in controlling soil and leaf litter bVOC flux during the growing to non-growing season transition at the Morgan Monroe State Forest Ameriflux Core research site in Indiana, USA. We hypothesize that (1) total bVOC emissions will be greater from ECM plots due to larger belowground microbial biomass, and (2) fast-decomposing litter within the AM-dominated plots will result in an ephemeral pulse in bVOC emissions later in the season. AM and ECM-dominated forest soils were a net bVOC sink early in the growing season following leaf-out, but were net sources during the leaf-fall period in October. In the absence of leaf litter, soils dominated by ECM were a large sink of bVOCs, but leaf litter inputs resulted in a net source, suggesting that leaf litter and not merely soil microbial biomass is critical for understanding hypothesis (1). Temperature explains 57% (21%) of the variability of methanol flux - the bVOC of greatest quantity - in ECM (AM)-dominated plots. Non-methanol bVOC flux is only related to soil temperature in the Fall in ECM-dominated plots, where it explains 71% of the variability. Results are consistent with large methanol efflux with fresh litter after leaf-fall, especially in ECM plots (contrary to hypothesis 2), but net uptake with strong temperature-dependence during the growing season. Seasonality, phenology (including leaf litter dynamics) and mycorrhizal associations should be taken into account to accurately determine the relative contribution of forest soils to ecosystem bVOC fluxes in temperate forests and their sensitivity to environmental drivers.

Last-Century Increases in Intrinsic Water-Use Efficiency of Grassland Communities Have Occurred over a Wide Range of Vegetation Composition, Nutrient Inputs, and Soil pH.

PubMed

Köhler, Iris H; Macdonald, Andy J; Schnyder, Hans

2016-02-01

Last-century climate change has led to variable increases of the intrinsic water-use efficiency (Wi; the ratio of net CO2 assimilation to stomatal conductance for water vapor) of trees and C3 grassland ecosystems, but the causes of the variability are not well understood. Here, we address putative drivers underlying variable Wi responses in a wide range of grassland communities. Wi was estimated from carbon isotope discrimination in archived herbage samples from 16 contrasting fertilizer treatments in the Park Grass Experiment, Rothamsted, England, for the 1915 to 1929 and 1995 to 2009 periods. Changes in Wi were analyzed in relation to nitrogen input, soil pH, species richness, and functional group composition. Treatments included liming as well as phosphorus and potassium additions with or without ammonium or nitrate fertilizer applications at three levels. Wi increased between 11% and 25% (P < 0.001) in the different treatments between the two periods. None of the fertilizers had a direct effect on the change of Wi (ΔWi). However, soil pH (P < 0.05), species richness (P < 0.01), and percentage grass content (P < 0.01) were significantly related to ΔWi. Grass-dominated, species-poor plots on acidic soils showed the largest ΔWi (+14.7 μmol mol(-1)). The ΔWi response of these acidic plots was probably related to drought effects resulting from aluminum toxicity on root growth. Our results from the Park Grass Experiment show that Wi in grassland communities consistently increased over a wide range of nutrient inputs, soil pH, and plant community compositions during the last century. © 2016 American Society of Plant Biologists. All Rights Reserved.

Last-Century Increases in Intrinsic Water-Use Efficiency of Grassland Communities Have Occurred over a Wide Range of Vegetation Composition, Nutrient Inputs, and Soil pH1[OPEN

PubMed Central

Köhler, Iris H.; Macdonald, Andy J.; Schnyder, Hans

2016-01-01

Last-century climate change has led to variable increases of the intrinsic water-use efficiency (Wi; the ratio of net CO2 assimilation to stomatal conductance for water vapor) of trees and C3 grassland ecosystems, but the causes of the variability are not well understood. Here, we address putative drivers underlying variable Wi responses in a wide range of grassland communities. Wi was estimated from carbon isotope discrimination in archived herbage samples from 16 contrasting fertilizer treatments in the Park Grass Experiment, Rothamsted, England, for the 1915 to 1929 and 1995 to 2009 periods. Changes in Wi were analyzed in relation to nitrogen input, soil pH, species richness, and functional group composition. Treatments included liming as well as phosphorus and potassium additions with or without ammonium or nitrate fertilizer applications at three levels. Wi increased between 11% and 25% (P < 0.001) in the different treatments between the two periods. None of the fertilizers had a direct effect on the change of Wi (ΔWi). However, soil pH (P < 0.05), species richness (P < 0.01), and percentage grass content (P < 0.01) were significantly related to ΔWi. Grass-dominated, species-poor plots on acidic soils showed the largest ΔWi (+14.7 μmol mol−1). The ΔWi response of these acidic plots was probably related to drought effects resulting from aluminum toxicity on root growth. Our results from the Park Grass Experiment show that Wi in grassland communities consistently increased over a wide range of nutrient inputs, soil pH, and plant community compositions during the last century. PMID:26620525

Relationship between plant biodiversity and heavy metal bioavailability in grasslands overlying an abandoned mine.

PubMed

Hernández, A J; Pastor, J

2008-04-01

Abandoned metal mines in the Sierra de Guadarrama, Madrid, Spain, are often located in areas of high ecological value. This is true of an abandoned barium mine situated in the heart of a bird sanctuary. Today the area sustains grasslands, interspersed with oakwood formations of Quercus ilex and heywood scrub (Retama sphaerocarpa L.), used by cattle, sheep and wild animals. Our study was designed to establish a relationship between the plant biodiversity of these grasslands and the bioavailability of heavy metals in the topsoil layer of this abandoned mine. We conducted soil chemical analyses and performed a greenhouse evaluation of the effects of different soil heavy metal concentrations on biodiversity. The greenhouse bioassays were run for 6 months using soil samples obtained from the mine polluted with heavy metals (Cu, Zn, Pb and Cd) and from a control pasture. Soil heavy metal and Na concentrations, along with the pH, had intense negative effects on plant biodiversity, as determined through changes in the Shannon index and species richness. Numbers of grasses, legumes, and composites were reduced, whilst other species (including ruderals) were affected to a lesser extent. Zinc had the greatest effect on biodiversity, followed by Cd and Cu. When we compared the sensitivity of the biodiversity indicators to the different metal content variables, pseudototal metal concentrations determined by X-ray fluorescence (XRF) were the most sensitive, followed by available and soluble metal contents. Worse correlations between biodiversity variables and metal variables were shown by pseudototal contents obtained by plasma emission spectroscopy (ICP-OES). Our results highlight the importance of using as many different indicators as possible to reliably assess the response shown by plants to heavy metal soil pollution.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

NASA Technical Reports Server (NTRS)

Gulden, L. E.; Rosero, E.; Yang, Z.-L.; Rodell, Matthew; Jackson, C. S.; Niu, G.-Y.; Yeh, P. J.-F.; Famiglietti, J. S.

2007-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set.

Using the Rasch model as an objective and probabilistic technique to integrate different soil properties

NASA Astrophysics Data System (ADS)

Rebollo, Francisco J.; Jesús Moral García, Francisco

2016-04-01

Soil apparent electrical conductivity (ECa) is one of the simplest, least expensive soil measurements that integrates many soil properties affecting crop productivity, including, for instance, soil texture, water content, and cation exchange capacity. The ECa measurements obtained with a 3100 Veris sensor, operating in both shallow (0-30 cm), ECs, and deep (0-90 cm), ECd, mode, can be used as an additional and essential information to be included in a probabilistic model, the Rasch model, with the aim of quantifying the overall soil fertililty potential in an agricultural field. This quantification should integrate the main soil physical and chemical properties, with different units. In this work, the formulation of the Rasch model integrates 11 soil properties (clay, silt and sand content, organic matter -OM-, pH, total nitrogen -TN-, available phosphorus -AP- and potassium -AK-, cation exchange capacity -CEC-, ECd, and ECs) measured at 70 locations in a field. The main outputs of the model include a ranking of all soil samples according to their relative fertility potential and the unexpected behaviours of some soil samples and properties. In the case study, the considered soil variables fit the model reasonably, having an important influence on soil fertility, except pH, probably due to its homogeneity in the field. Moreover, ECd, ECs are the most influential properties on soil fertility and, on the other hand, AP and AK the less influential properties. The use of the Rasch model to estimate soil fertility potential (always in a relative way, taking into account the characteristics of the studied soil) constitutes a new application of great practical importance, enabling to rationally determine locations in a field where high soil fertility potential exists and establishing those soil samples or properties which have any anomaly; this information can be necessary to conduct site-specific treatments, leading to a more cost-effective and sustainable field management. Furthermore, from the measures of soil fertility potential at sampled locations, estimates can be computed using, for instance, a geostatistical algorithm, and these estimates can be utilized to map soil fertility potential and delineate with a rational basis the management zones in the field. Keywords: Rasch model; soil management; soil electrical conductivity; probabilistic algorithm.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Geospatial variability of soil CO2-C exchange in the main terrestrial ecosystems of Keller Peninsula, Maritime Antarctica.

PubMed

Thomazini, A; Francelino, M R; Pereira, A B; Schünemann, A L; Mendonça, E S; Almeida, P H A; Schaefer, C E G R

2016-08-15

Soils and vegetation play an important role in the carbon exchange in Maritime Antarctica but little is known on the spatial variability of carbon processes in Antarctic terrestrial environments. The objective of the current study was to investigate (i) the soil development and (ii) spatial variability of ecosystem respiration (ER), net ecosystem CO2 exchange (NEE), gross primary production (GPP), soil temperature (ST) and soil moisture (SM) under four distinct vegetation types and a bare soil in Keller Peninsula, King George Island, Maritime Antarctica, as follows: site 1: moss-turf community; site 2: moss-carpet community; site 3: phanerogamic antarctic community; site 4: moss-carpet community (predominantly colonized by Sanionia uncinata); site 5: bare soil. Soils were sampled at different layers. A regular 40-point (5×8 m) grid, with a minimum separation distance of 1m, was installed at each site to quantify the spatial variability of carbon exchange, soil moisture and temperature. Vegetation characteristics showed closer relation with soil development across the studied sites. ER reached 2.26μmolCO2m(-2)s(-1) in site 3, where ST was higher (7.53°C). A greater sink effect was revealed in site 4 (net uptake of 1.54μmolCO2m(-2)s(-1)) associated with higher SM (0.32m(3)m(-3)). Spherical models were fitted to describe all experimental semivariograms. Results indicate that ST and SM are directly related to the spatial variability of CO2 exchange. Heterogeneous vegetation patches showed smaller range values. Overall, poorly drained terrestrial ecosystems act as CO2 sink. Conversely, where ER is more pronounced, they are associated with intense soil carbon mineralization. The formations of new ice-free areas, depending on the local soil drainage condition, have an important effect on CO2 exchange. With increasing ice/snow melting, and resulting widespread waterlogging, increasing CO2 sink in terrestrial ecosystems is expected for Maritime Antarctica. Copyright © 2016 Elsevier B.V. All rights reserved.

How do peat type, sand addition and soil moisture influence the soil organic matter mineralization in anthropogenically disturbed organic soils?

NASA Astrophysics Data System (ADS)

Säurich, Annelie; Tiemeyer, Bärbel; Don, Axel; Burkart, Stefan

2017-04-01

Drained peatlands are hotspots of carbon dioxide (CO2) emissions from agriculture. As a consequence of both drainage induced mineralization and anthropogenic sand mixing, large areas of former peatlands under agricultural use contain soil organic carbon (SOC) at the boundary between mineral and organic soils. Studies on SOC dynamics of such "low carbon organic soils" are rare as the focus of previous studies was mainly either on mineral soils or "true" peat soil. However, the variability of CO2 emissions increases with disturbance and therefore, we have yet to understand the reasons behind the relatively high CO2 emissions of these soils. Peat properties, soil organic matter (SOM) quality and water content are obviously influencing the rate of CO2 emissions, but a systematic evaluation of the hydrological and biogeochemical drivers for mineralization of disturbed peatlands is missing. With this incubation experiment, we aim at assessing the drivers of the high variability of CO2 emissions from strongly anthropogenically disturbed organic soil by systematically comparing strongly degraded peat with and without addition of sand under different moisture conditions and for different peat types. The selection of samples was based on results of a previous incubation study, using disturbed samples from the German Agricultural Soil Inventory. We sampled undisturbed soil columns from topsoil and subsoil (three replicates of each) of ten peatland sites all used as grassland. Peat types comprise six fens (sedge, Phragmites and wood peat) and four bogs (Sphagnum peat). All sites have an intact peat horizon that is permanently below groundwater level and a strongly disturbed topsoil horizon. Three of the fen and two of the bog sites have a topsoil horizon altered by sand-mixing. In addition the soil profile was mapped and samples for the determination of soil hydraulic properties were collected. All 64 soil columns (including four additional reference samples) will be installed in a microcosm system under a constant temperature of 10°C. The water-saturated soil columns will be drained via suction plates at the bottom of the columns by stepwise increase of the suction. The head space of the soil columns will be permanently flushed with moistened synthetic air and CO2 concentrations will be measured via online gas chromatography. First results will be presented.

Role of vegetation in interplay of climate, soil and groundwater recharge in a global dataset

NASA Astrophysics Data System (ADS)

Kim, J. H.; Jackson, R. B.

2010-12-01

Groundwater is an essential resource for people and ecosystems worldwide. Our capacity to ameliorate predicted global water shortages and to maintain sustainable water supplies depend on a better understanding of the controls of recharge and how vegetation change may affect recharge mechanisms. The goals of this study are to quantify the importance of vegetation as a dominant control on recharge globally and to compare the importance of vegetation with other hydrologically important variables, including climate and soil. We based our global analysis on > 500 recharge estimates from the literature that contained information on vegetation, soil and climate or location. Plant functional types significantly affected groundwater recharge rates substantially. After climatic factors (water inputs, PET, and seasonality), vegetation types explained about 15% of the residuals in the dataset. Across all climatic factors, croplands had the highest recharge rates, followed by grasslands, scrublands and woodlands (average recharge: 75, 63, 30, 22 mm/yr respectively). Recharge under woodlands showed the most nonlinear response to water inputs. Differences in recharge between the vegetation types were more exaggerated at arid climates and in clay soils, indicating greater biological control on soil water fluxes in these conditions. Our results shows that vegetation greatly affects recharge rates globally and alters relationship between recharge and physical variables allowing us to better predict recharge rates globally.

Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development

NASA Astrophysics Data System (ADS)

Xu, Fei; Zhang, Yaning; Jin, Guangri; Li, Bingxi; Kim, Yong-Song; Xie, Gongnan; Fu, Zhongbin

2018-04-01

A three-phase model capable of predicting the heat transfer and moisture migration for soil freezing process was developed based on the Shen-Chen model and the mechanisms of heat and mass transfer in unsaturated soil freezing. The pre-melted film was taken into consideration, and the relationship between film thickness and soil temperature was used to calculate the liquid water fraction in both frozen zone and freezing fringe. The force that causes the moisture migration was calculated by the sum of several interactive forces and the suction in the pre-melted film was regarded as an interactive force between ice and water. Two kinds of resistance were regarded as a kind of body force related to the water films between the ice grains and soil grains, and a block force instead of gravity was introduced to keep balance with gravity before soil freezing. Lattice Boltzmann method was used in the simulation, and the input variables for the simulation included the size of computational domain, obstacle fraction, liquid water fraction, air fraction and soil porosity. The model is capable of predicting the water content distribution along soil depth and variations in water content and temperature during soil freezing process.

The search for integrated management of common scab

USDA-ARS?s Scientific Manuscript database

Common scab (CS), caused by several species of Streptomyces, is a soil-borne bacterial disease of potato and other root and tuber crops. Frustratingly, CS severity is highly variable (and unpredictable) from year to year and location to location. Symptoms include superficial, raised, or pitted lesio...

Tightly-Coupled Plant-Soil Nitrogen Cycling: Comparison of Organic Farms across an Agricultural Landscape

PubMed Central

Bowles, Timothy M.; Hollander, Allan D.; Steenwerth, Kerri; Jackson, Louise E.

2015-01-01

How farming systems supply sufficient nitrogen (N) for high yields but with reduced N losses is a central challenge for reducing the tradeoffs often associated with N cycling in agriculture. Variability in soil organic matter and management of organic farms across an agricultural landscape may yield insights for improving N cycling and for evaluating novel indicators of N availability. We assessed yields, plant-soil N cycling, and root expression of N metabolism genes across a representative set of organic fields growing Roma-type tomatoes (Solanum lycopersicum L.) in an intensively-managed agricultural landscape in California, USA. The fields spanned a three-fold range of soil carbon (C) and N but had similar soil types, texture, and pH. Organic tomato yields ranged from 22.9 to 120.1 Mg ha-1 with a mean similar to the county average (86.1 Mg ha-1), which included mostly conventionally-grown tomatoes. Substantial variability in soil inorganic N concentrations, tomato N, and root gene expression indicated a range of possible tradeoffs between yields and potential for N losses across the fields. Fields showing evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which high crop yields are supported by adequate N availability but low potential for N loss, had the highest total and labile soil C and N and received organic matter inputs with a range of N availability. In these fields, elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, confirmed that plant N assimilation was high even when inorganic N pools were low. Thus tightly-coupled N cycling occurred on several working organic farms. Novel combinations of N cycling indicators (i.e. inorganic N along with soil microbial activity and root gene expression for N assimilation) would support adaptive management for improved N cycling on organic as well as conventional farms, especially when plant-soil N cycling is rapid. PMID:26121264

Risk factors for faecal sand excretion in Icelandic horses.

PubMed

Husted, L; Andersen, M S; Borggaard, O K; Houe, H; Olsen, S N

2005-07-01

Sandy soil is often mentioned as a risk factor in the development of sand-related gastrointestinal disease (SGID) in the horse. There are other variables, but few studies confirm any of these. To investigate soil type, pasture quality, feeding practice in the paddock, age, sex and body condition score as risk factors for sand intake in the horse. Faeces were collected from 211 Icelandic horses on 19 different studs in Denmark together with soil samples and other potential risk factors. Sand content in faeces determined by a sand sedimentation test was interpreted as evidence of sand intake. Soil types were identified by soil analysis and significance of the data was tested using logistic analysis. Of horses included in the study, 56.4% showed sand in the faeces and 5.7% had more than 5 mm sand as quantified by the rectal sleeve sedimentation test. Soil type had no significant effect when tested as main effect, but there was interaction between soil type and pasture quality. Significant interactions were also found between paddock feeding practice and pasture quality. To evaluate the risk of sand intake it is important to consider 3 variables: soil type, pasture quality and feeding practice. Pasture quality was identified as a risk factor of both short and long grass in combination with sandy soil, while clay soil had the lowest risk in these combinations. Feeding practice in the paddock revealed feeding directly on the ground to be a risk factor when there was short (1-5 cm) or no grass. Also, no feeding outdoors increased the risk on pastures with short grass, while this had no effect in paddocks with no grass. More than 50% of all horses investigated in this study had sand in the faeces. The identification of risk factors is an important step towards prevention of SGID. Further research is necessary to determine why some horses exhibit more than 5 mm sand in the sedimentation test and whether this is correlated with geophagic behaviour.

Tightly-Coupled Plant-Soil Nitrogen Cycling: Comparison of Organic Farms across an Agricultural Landscape.

PubMed

Bowles, Timothy M; Hollander, Allan D; Steenwerth, Kerri; Jackson, Louise E

2015-01-01

How farming systems supply sufficient nitrogen (N) for high yields but with reduced N losses is a central challenge for reducing the tradeoffs often associated with N cycling in agriculture. Variability in soil organic matter and management of organic farms across an agricultural landscape may yield insights for improving N cycling and for evaluating novel indicators of N availability. We assessed yields, plant-soil N cycling, and root expression of N metabolism genes across a representative set of organic fields growing Roma-type tomatoes (Solanum lycopersicum L.) in an intensively-managed agricultural landscape in California, USA. The fields spanned a three-fold range of soil carbon (C) and N but had similar soil types, texture, and pH. Organic tomato yields ranged from 22.9 to 120.1 Mg ha-1 with a mean similar to the county average (86.1 Mg ha-1), which included mostly conventionally-grown tomatoes. Substantial variability in soil inorganic N concentrations, tomato N, and root gene expression indicated a range of possible tradeoffs between yields and potential for N losses across the fields. Fields showing evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which high crop yields are supported by adequate N availability but low potential for N loss, had the highest total and labile soil C and N and received organic matter inputs with a range of N availability. In these fields, elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, confirmed that plant N assimilation was high even when inorganic N pools were low. Thus tightly-coupled N cycling occurred on several working organic farms. Novel combinations of N cycling indicators (i.e. inorganic N along with soil microbial activity and root gene expression for N assimilation) would support adaptive management for improved N cycling on organic as well as conventional farms, especially when plant-soil N cycling is rapid.

Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

NASA Astrophysics Data System (ADS)

Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

2014-07-01

Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

Joint Multifractal Analysis of penetration resistance variability in an olive orchard.

NASA Astrophysics Data System (ADS)

Lopez-Herrera, Juan; Herrero-Tejedor, Tomas; Saa-Requejo, Antonio; Villeta, Maria; Tarquis, Ana M.

2016-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. We used descriptive statistics and multifractal analysis for characterizing the spatial patterns of soil penetrometer resistance (PR) distributions and compare them at different soil depths and soil water content to investigate the tillage effect in soil compactation. The study was conducted on an Inceptisol dedicated to olive orchard for the last 70 years. Two parallel transects of 64 m were selected as different soil management plots, conventional tillage (CT) and no tillage (NT). Penetrometer resistance readings were carried out at 50 cm intervals within the first 20 cm of soil depth (López de Herrera et al., 2015a). Two way ANOVA highlighted that tillage system, soil depth and their interaction are statistically significant to explain the variance of PR data. The comparison of CT and NT results at different depths showed that there are significant differences deeper than 10 cm but not in the first two soil layers. The scaling properties of each PR profile was characterized by τ(q) function, calculated in the range of moment orders (q) between -5 and +5 taken at 0.5 lag increments. Several parameters were calculated from this to establish different comparisons (López de Herrera et al., 2015b). While the multifractal analysis characterizes the distribution of a single variable along its spatial support, the joint multifractal analysis can be used to characterize the joint distribution of two or more variables along a common spatial support (Kravchenko et al., 2000; Zeleke and Si, 2004). This type of analysis was performed to study the scaling properties of the joint distribution of PR at different depths. The results showed that this type of analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets in all the soil layers. References Kravchenko AN, Bullock DG, Boast CW (2000) Joint multifractal analysis of crop yield and terrain slope. Agro. j. 92: 1279-1290. López de Herrera, J., Tomas Herrero Tejedor, Antonio Saa-Requejo and Ana M. Tarquis (2015a) Influence of tillage in soil penetration resistance variability in an olive orchard. Geophysical Research Abstracts, 17, EGU2015-15425. López de Herrera, J., Tomás Herrero Tejedor, Antonio Saa-Requejo, A.M. Tarquis. Influence of tillage in soil penetration resistance variability in an olive orchard. Soil Research, accepted, 2015b. doi: SR15046 Zeleke TB, Si BC (2004) Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agro. j. 96: 1082-1090.

Integrated soil fertility management in sub-Saharan Africa: unravelling local adaptation

NASA Astrophysics Data System (ADS)

Vanlauwe, B.; Descheemaeker, K.; Giller, K. E.; Huising, J.; Merckx, R.; Nziguheba, G.; Wendt, J.; Zingore, S.

2014-12-01

Intensification of smallholder agriculture in sub-Saharan Africa is necessary to address rural poverty and natural resource degradation. Integrated Soil Fertility Management (ISFM) is a means to enhance crop productivity while maximizing the agronomic efficiency (AE) of applied inputs, and can thus contribute to sustainable intensification. ISFM consists of a set of best practices, preferably used in combination, including the use of appropriate germplasm, the appropriate use of fertilizer and of organic resources, and good agronomic practices. The large variability in soil fertility conditions within smallholder farms is also recognised within ISFM, including soils with constraints beyond those addressed by fertilizer and organic inputs. The variable biophysical environments that characterize smallholder farming systems have profound effects on crop productivity and AE and targeted application of limited agro-inputs and management practices is necessary to enhance AE. Further, management decisions depend on the farmer's resource endowments and production objectives. In this paper we discuss the "local adaptation" component of ISFM and how this can be conceptualized within an ISFM framework, backstopped by analysis of AE at plot and farm level. At plot level, a set of four constraints to maximum AE is discussed in relation to "local adaptation": soil acidity, secondary nutrient and micro-nutrient (SMN) deficiencies, physical constraints, and drought stress. In each of these cases, examples are presented whereby amendments and/or practices addressing these have a significantly positive impact on fertilizer AE, including mechanistic principles underlying these effects. While the impact of such amendments and/or practices is easily understood for some practices (e.g., the application of SMNs where these are limiting), for others, more complex interactions with fertilizer AE can be identified (e.g., water harvesting under varying rainfall conditions). At farm scale, adjusting fertilizer applications within-farm soil fertility gradients has the potential to increase AE compared with blanket recommendations, in particular where fertility gradients are strong. In the final section, "local adaption" is discussed in relation to scale issues and decision support tools are evaluated as a means to create a better understanding of complexity at farm level and to communicate best scenarios for allocating agro-inputs and management practices within heterogeneous farming environments.

Integrated soil fertility management in sub-Saharan Africa: unravelling local adaptation

NASA Astrophysics Data System (ADS)

Vanlauwe, B.; Descheemaeker, K.; Giller, K. E.; Huising, J.; Merckx, R.; Nziguheba, G.; Wendt, J.; Zingore, S.

2015-06-01

Intensification of smallholder agriculture in sub-Saharan Africa is necessary to address rural poverty and natural resource degradation. Integrated soil fertility management (ISFM) is a means to enhance crop productivity while maximizing the agronomic efficiency (AE) of applied inputs, and can thus contribute to sustainable intensification. ISFM consists of a set of best practices, preferably used in combination, including the use of appropriate germplasm, the appropriate use of fertilizer and of organic resources, and good agronomic practices. The large variability in soil fertility conditions within smallholder farms is also recognized within ISFM, including soils with constraints beyond those addressed by fertilizer and organic inputs. The variable biophysical environments that characterize smallholder farming systems have profound effects on crop productivity and AE, and targeted application of agro-inputs and management practices is necessary to enhance AE. Further, management decisions depend on the farmer's resource endowments and production objectives. In this paper we discuss the "local adaptation" component of ISFM and how this can be conceptualized within an ISFM framework, backstopped by analysis of AE at plot and farm level. At plot level, a set of four constraints to maximum AE is discussed in relation to "local adaptation": soil acidity, secondary nutrient and micronutrient (SMN) deficiencies, physical constraints, and drought stress. In each of these cases, examples are presented whereby amendments and/or practices addressing these have a significantly positive impact on fertilizer AE, including mechanistic principles underlying these effects. While the impact of such amendments and/or practices is easily understood for some practices (e.g. the application of SMNs where these are limiting), for others, more complex processes influence AE (e.g. water harvesting under varying rainfall conditions). At farm scale, adjusting fertilizer applications to within-farm soil fertility gradients has the potential to increase AE compared with blanket recommendations, in particular where fertility gradients are strong. In the final section, "local adaption" is discussed in relation to scale issues and decision support tools are evaluated as a means to create a better understanding of complexity at farm level and to communicate appropriate scenarios for allocating agro-inputs and management practices within heterogeneous farming environments.

New Mexico Tech landmine, UXO, IED detection sensor test facility: measurements in real field soils

NASA Astrophysics Data System (ADS)

Hendrickx, Jan M. H.; Alkov, Nicole; Hong, Sung-ho; Van Dam, Remke L.; Kleissl, Jan; Shannon, Heather; Meason, John; Borchers, Brian; Harmon, Russell S.

2006-05-01

Modeling studies and experimental work have demonstrated that the dynamic behavior of soil physical properties has a significant effect on most sensors for the detection of buried land mines. An outdoor test site has been constructed allowing full control over soil water content and continuous monitoring of important soil properties and environmental conditions. Time domain reflectometry sensors and thermistors measure soil water1 content and temperature, respectively, at different depths above and below the land mines as well as in homogeneous soil away from the land mines. During the two-year operation of the test-site, the soils have evolved to reflect real field soil conditions. This paper compares visual observations as well as ground-penetrating radar and thermal infrared measurements at this site taken immediately after construction in early 2004 with measurements from early 2006. The visual observations reveal that the 2006 soil surfaces exhibit a much higher spatial variability due to the development of mini-reliefs, "loose" and "connected" soil crusts, cracks in clay soils, and vegetation. Evidence is presented that the increased variability of soil surface characteristics leads to a higher natural spatial variability of soil surface temperatures and, thus, to a lower probability to detect landmines using thermal imagery. No evidence was found that the soil surface changes affect the GPR signatures of landmines under the soil conditions encountered in this study. The New Mexico Tech outdoor Landmine Detection Sensor Test Facility is easily accessible and anyone interested is welcome to use it for sensor testing.

Modeling global annual N2O and NO emissions from fertilized fields

NASA Astrophysics Data System (ADS)

Bouwman, A. F.; Boumans, L. J. M.; Batjes, N. H.

2002-12-01

Information from 846 N2O emission measurements in agricultural fields and 99 measurements for NO emissions was used to describe the influence of various factors regulating emissions from mineral soils in models for calculating global N2O and NO emissions. Only those factors having a significant influence on N2O and NO emissions were included in the models. For N2O these were (1) environmental factors (climate, soil organic C content, soil texture, drainage and soil pH); (2) management-related factors (N application rate per fertilizer type, type of crop, with major differences between grass, legumes and other annual crops); and (3) factors related to the measurements (length of measurement period and frequency of measurements). The most important controls on NO emission include the N application rate per fertilizer type, soil organic-C content and soil drainage. Calculated global annual N2O-N and NO-N emissions from fertilized agricultural fields amount to 2.8 and 1.6 Mtonne, respectively. The global mean fertilizer-induced emissions for N2O and NO amount to 0.9% and 0.7%, respectively, of the N applied. These overall results account for the spatial variability of the main N2O and NO emission controls on the landscape scale.

Modeling Stand-Scale Patterns in Evapotranspiration and Soil Moisture in a Heterogeneous Plant Canopy: A Coupled Subsurface-Land Surface Approach

NASA Astrophysics Data System (ADS)

Miller, G. R.; Gou, S.; Ferguson, I. M.; Maxwell, R. M.

2011-12-01

Savanna ecosystems present a well-known modeling challenge; understory grasses and overstory woody vegetation combine to form an open, heterogeneous canopy that creates strong spatial differences in soil moisture and evapotranspiration rates. In this analysis, we used ParFlow.CLM to create a stand-scale model of the Tonzi Ranch oak savanna, based on extensive topography, vegetation, soil, and hydrogeology data collected at the site. Measurements included canopy distribution and ground surface elevation from airborne Lidar, depth to groundwater from deep piezometers, soil and rock hydraulic conductivity, and leaf area index. We then compared the results to the site's long-term data records of radiative flux partitioning, obtained using the eddy-covariance method, and soil moisture, collected via a distributed network of capacitance probes. In order to obtain good agreement between the measured and modeled values, we identified several necessary modifications to the current CLM parameterization. These changes included the addition of a "winter grass" type and the alteration of the root structure and water stress functions to accommodate uptake of groundwater by deep roots. Finally, we compared variograms of site parameters and response variables and performed a scaling analysis relating ET and soil moisture variance to sampling size.

Landscape structure control on soil CO2 efflux variability in complex terrain: Scaling from point observations to watershed scale fluxes

Treesearch

Diego A. Riveros-Iregui; Brian L. McGlynn

2009-01-01

We investigated the spatial and temporal variability of soil CO2 efflux across 62 sites of a 393-ha complex watershed of the northern Rocky Mountains. Growing season (83 day) cumulative soil CO2 efflux varied from ~300 to ~2000 g CO2 m-2, depending upon landscape position, with a median of 879.8 g CO2 m-2. Our findings revealed that highest soil CO2 efflux rates were...

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Effect of mineralogical, geochemical and biological properties on soils reflectance to assess temporal and spatial dynamics of BSCs in Sahelian ecosystems

NASA Astrophysics Data System (ADS)

Bourguignon, A.; Cerdan, O.; Desprats, J. F.; Marin, B.; Malam Issa, O.; Valentin, C.; Rajot, J. L.

2012-04-01

Land degradation and desertification are among the major environmental problems, resulting in reduced productivity and development of bare surfaces in arid and semi-arid areas of the world. One important factor that acts to increase soil stability and nutrient content, and thus to prevent water and wind erosion and enhance soil productivity of arid environment, is the presence of biological soil crusts (BSCs). They are the dominant ground cover and a key component of arid environments built up mainly by cyanobacteria. They enhance degraded soil quality by providing a stable and water-retaining substratum and increasing fertility by N and C fixations. The BioCrust project, funded by ANR (VMCS 2008), focuses on BSCs in the Sahelian zone of West Africa (Niger), a highly vulnerable zone facing soil degradation due to the harsh climatic conditions, with variable rainfall, and high anthropic pressure on land use. Unlike arid areas of developed countries (USA, Australia and Israel) or China where BSCs have been extensively studied, studies from Sahelian zone (Africa) are limited (neither the inventory of their different form nor the estimation of their spatial extension has been carried out). The form, structure and composition of BSCs vary depending on characteristics related to soils and biological composition. This study focuses on the soils characterisation using ground-based spectroradiometry. An extensive database was built included spectral measurements on BSCs, bare soils and vegetation that occur in the same area, visual criteria, in situ and laboratory measurements on the physical, chemical and biological characteristics of BSCs and their substratum. The work is carried out on geo-statistical processing of data acquired in sites along a north-south climatic gradient and three types of representative land uses. The investigated areas are highly vulnerable zone facing soil degradation due to the harsh climatic conditions, with variable rainfall, and high anthropic pressure on land use Soil surface disturbances due to the intensification of human activities. Spectral field and laboratory data were acquired in 2009, 2010 and 2011 with the FieldSpec Pro®. The spectra of soils with respect to different parameters are studied in details and their separability from BSCs, vegetation and vegetation residue as well are be analysed. First, the effect of the mineralogy and the geochemical variables on the soil reflectance properties is studied and then the feasibility to resolve some of these effects with satellite imagery (e. g., ASTER) will be tested in order to define the potential capability for identifying the locations of sensitive areas affected by soil degradation and appearance of BSCs.

State-Space Estimation of Soil Organic Carbon Stock

NASA Astrophysics Data System (ADS)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Relative spatial soil geochemical variability along two transects across the United States and Canada

USGS Publications Warehouse

Garrett, Robert G.

2009-01-01

The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.

Soil reinforcement with recycled carpet wastes.

PubMed

Ghiassian, Hossein; Poorebrahim, Gholamreza; Gray, Donald H

2004-04-01

A root or fibre-reinforced soil behaves as a composite material in which fibres of relatively high tensile strength are embedded in a matrix of relatively plastic soil. Shear stresses in the soil mobilize tensile resistance in the fibres, which in turn impart greater strength to the soil. A research project has been undertaken to study the influence of synthetic fibrous materials for improving the strength characteristics of a fine sandy soil. One of the main objectives of the project is to explore the conversion of fibrous carpet waste into a value-added product for soil reinforcement. Drained triaxial tests were conducted on specimens, which were prepared in a cylindrical mould and compacted at their optimum water contents. The main test variables included the aspect ratio and the weight percentage of the fibrous strips. The results clearly show that fibrous inclusions derived from carpet wastes improve the shear strength of silty sands. A model developed to simulate the effect of the fibrous inclusions accurately predicts the influence of strip content, aspect ratio and confining pressure on the shear strength of reinforced sand.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Pedodiversity and Its Significance in the Context of Modern Soil Geography

NASA Astrophysics Data System (ADS)

Krasilnikov, P. V.; Gerasimova, M. I.; Golovanov, D. L.; Konyushkova, M. V.; Sidorova, V. A.; Sorokin, A. S.

2018-01-01

Methodological basics of the study and quantitative assessment of pedodiversity are discussed. It is shown that the application of various indices and models of pedodiversity can be feasible for solving three major issues in pedology: a comparative geographical analysis of different territories, a comparative historical analysis of soil development in the course of landscape evolution, and the analysis of relationships between biodiversity and pedodiversity. Analogous geographic concepts of geodiversity and landscape diversity are also discussed. Certain limitations in the use of quantitative estimates of pedodiversity related to their linkage to the particular soil classification systems and with the initial soil maps are considered. Problems of the interpretation of the results of pedodiversity assessments are emphasized. It is shown that scientific explanations of biodiversity cannot be adequately applied in soil studies. Promising directions of further studies of pedodiversity are outlined. They include the assessment of the functional diversity of soils on the basis of data on their properties, integration with geostatistical methods of evaluation of soil variability, and assessment of pedodiversity on different scales.

Evaluating Spatial Heterogeneity and Environmental Variability Inferred from Branched Glycerol Dialkyl Glycerol Tetraethers (GDGTs) Distribution in Soils from Valles Caldera, New Mexic

NASA Astrophysics Data System (ADS)

Contreras Quintana, S. H.; Werne, J. P.; Brown, E. T.; Halbur, J.; Sinninghe Damsté, , J.; Schouten, S.; Correa-Metrio, A.; Fawcett, P. J.

2014-12-01

Branched glycerol dialkyl glycerol tetraethers (GDGTs) are recently discovered bacterial membrane lipids, ubiquitously present in peat bogs and soils, as well as in rivers, lakes and lake sediments. Their distribution appears to be controlled mainly by soil pH and annual mean air temperature (MAT) and they have been increasingly used as paleoclimate proxies in sedimentary records. In order to validate their application as paleoclimate proxies, it is essential evaluate the influence of small scale environmental variability on their distribution. Initial application of the original soil-based branched GDGT distribution proxy to lacustrine sediments from Valles Caldera, New Mexico (NM) was promising, producing a viable temperature record spanning two glacial/interglacial cycles. In this study, we assess the influence of analytical and spatial soil heterogeneity on the concentration and distribution of 9 branched GDGTs in soils from Valles Caldera, and show how this variability is propagated to MAT and pH estimates using multiple soil-based branched GDGT transfer functions. Our results show that significant differences in the abundance and distribution of branched GDGTs in soil can be observed even within a small area such as Valles Caldera. Although the original MBT-CBT calibration appears to give robust MAT estimates and the newest calibration provides pH estimates in better agreement with modern local soils in Valles Caldera, the environmental heterogeneity (e.g. vegetation type and soil moisture) appears to affect the precision of MAT and pH estimates. Furthermore, the heterogeneity of soils leads to significant variability among samples taken even from within a square meter. While such soil heterogeneity is not unknown (and is typically controlled for by combining multiple samples), this study quantifies heterogeneity relative to branched GDGT-based proxies for the first time, indicating that care must be taken with samples from heterogeneous soils in MAT and pH reconstructions.

Description and validation of the Simple, Efficient, Dynamic, Global, Ecological Simulator (SEDGES v.1.0)

NASA Astrophysics Data System (ADS)

Paiewonsky, Pablo; Elison Timm, Oliver

2018-03-01

In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.

Modelling the water balance of irrigated fields in tropical floodplain soils using Hydrus-1D

NASA Astrophysics Data System (ADS)

Beyene, Abebech; Frankl, Amaury; Verhoest, Niko E. C.; Tilahun, Seifu; Alamirew, Tena; Adgo, Enyew; Nyssen, Jan

2017-04-01

Accurate estimation of evaporation, transpiration and deep percolation is crucial in irrigated agriculture and the sustainable management of water resources. Here, the Hydrus-1D process-based numerical model was used to estimate the actual transpiration, soil evaporation and deep percolation from irrigated fields of floodplain soils. Field experiments were conducted from Dec 2015 to May 2016 in a small irrigation scheme (50 ha) called 'Shina' located in the Lake Tana floodplains of Ethiopia. Six experimental plots (three for onion and three for maize) were selected along a topographic transect to account for soil and groundwater variability. Irrigation amount (400 to 550 mm during the growing period) was measured using V-notches installed at each plot boundary and daily groundwater levels were measured manually from piezometers. There was no surface runoff observed in the growing period and rainfall was measured using a manual rain gauge. All daily weather data required for the evapotranspiration calculation using Pen Man Monteith equation were collected from a nearby metrological station. The soil profiles were described for each field to include the vertical soil heterogeneity in the soil water balance simulations. The soil texture, organic matter, bulk density, field capacity, wilting point and saturated moisture content were measured for all the soil horizons. Soil moisture monitoring at 30 and 60 cm depths was performed. The soil hydraulic parameters for each horizon was estimated using KNN pedotransfer functions for tropical soils and were effectively fitted using the RETC program (R2= 0.98±0.011) for initial prediction. A local sensitivity analysis was performed to select and optimize the most important hydraulic parameters for soil water flow in the unsaturated zone. The most sensitive parameters were saturated hydraulic conductivity (Ks), saturated moisture content (θs) and pore size distribution (n). Inverse modelling using Hydrus-1D further optimized these parameters (R2 =0.74±0.13). Using the optimized hydraulic parameters, the soil water dynamics were simulated using Hydrus-1D. The atmospheric boundary conditions with surface runoff was used as upper boundary condition with measured rainfall and irrigation input data. The variable pressure head was selected as lower boundary conditions with daily records of groundwater level as time-variable input data. The Hydrus-1D model was successfully applied and calibrated in the study area. The average seasonal actual transpiration values are 310±13 mm for onion and 429±24.7 mm for maize fields. The seasonal average soil evaporation ranges from 12±2.05 mm for maize fields to 38±2.85 mm for onion fields. The seasonal deep percolation from irrigation appeared to be 12 to 40% of applied irrigation. The Hydrus-1D model was able to simulate the temporal and the spatial variations of soil water dynamics in the unsaturated zone of tropical floodplain soils. Key words: floodplains, hydraulic parameters, parameter optimization, small-scale irrigation

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Spatial variability and response of soil organic carbon stocks to land abandonment and erosion in mountainous drylands (Invited)

NASA Astrophysics Data System (ADS)

De Baets, S. L.; Meersmans, J.; Vanacker, V.; Quine, T. A.; van oost, K.

2013-12-01

This research focuses on understanding the impact of human activities on C dynamics in a mountainous and semi-arid environment. Despite the low C status of drylands, soil organic carbon (SOC) is the largest C pool in these systems and hence possess a large restoration capacity. Still, regional estimates of SOC stocks and insights in their determining factors are lacking. This study therefore aims 1) to interpret the variability of soil organic carbon in relation to key soil, topographical and land use variables and 2) to quantify the effects of land regeneration following abandonment on SOC stocks. Soil profiles were taken in the Sierra de los Filabres (SE Spain) in different land units along geomorphic and degradation gradients. SOC contents were modelled using recovery period, soil and topographical variables. Sample depth, topographical position, altitude, recovery period and stone content are identified as the main factors for predicting SOC concentrations. SOC stocks in 1 m depth of soil vary between 3.16 and 76.44 t ha-1. Recovery period (years since abandonment), topographical position and altitude were used to predict and map SOC stocks in the top 0.2 m. The results show that C accumulates fast during the first 10-50 years following abandonment, whereafter the stocks evolve towards a steady state level. The erosion zones in the study area demonstrate a higher potential to increase their SOC stocks when abandoned. Deposition zones have higher SOC stocks, although their C accumulation rate is lower compared to erosion dominated landscapes in the first 10-50 years following abandonment. Therefore, full understanding of the C sequestration potential of land use change in areas of complex topography requires knowledge of spatial variability in soil properties and in particular SOC.

Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Vanessa L.; Bond-Lamberty, Ben; DeAngelis, Kristen

The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully consideredmore » in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.« less

Including climate variability in determination of the optimum rate of N fertilizer application using a crop model: A case study for rainfed corn in eastern Canada

NASA Astrophysics Data System (ADS)

Mesbah, M.; Pattey, E.; Jégo, G.; Geng, X.; Tremblay, N.; Didier, A.

2017-12-01

Identifying optimum nitrogen (N) application rate is essential for increasing agricultural production while limiting potential environmental contaminations caused by release of reactive N, especially for high demand N crops such as corn. The central question of N management is then how the optimum N rate is affected by climate variability for given soil. The experimental determination of optimum N rates involve the analyses of variance on the mean value of crop yield response to various N application rates used by factorial plot based experiments for a few years in several regions. This traditional approach has limitations to capture 1) the non-linear response of yield to N application rates due to large incremental N rates (often more than 40 kg N ha-1) and 2) the ecophysiological response of the crop to climate variability because of limited numbers of growing seasons considered. Modeling on the other hand, does not have such limitations and hence we use a crop model and propose a model-based methodology called Finding NEMO (N Ecophysiologically Modelled Optimum) to identify the optimum N rates for variable agro-climatic conditions and given soil properties. The performance of the methodology is illustrated using the STICS crop model adapted for rainfed corn in the Mixedwood Plains ecozone of eastern Canada (42.3oN 83oW-46.8oN 71oW) where more than 90% of Canadian corn is produced. The simulations were performed using small increment of preplant N application rate (10 kg N ha -1), long time series of daily climatic data (48 to 61 years) for 5 regions along the ecozone, and three contrasting soils per region. The results show that N recommendations should be region and soil specific. Soils with lower available water capacity required more N compared to soil with higher available water capacity. When N rates were at their ecophysiologically optimum level, 10 to 17 kg increase in dry yield could be achieved by adding 1 kg N. Expected yield also affected the optimum N rates for the region and soil. For instance, the probability to achieve a yield of 9.2 t ha-1 at 15% grain moisture on a loamy soil varied from 0 to 73% along the ecozone. For this level of expected yield, the recommended N rates ranged from 64 to 155 kg ha-1, which are relatively less than current provincial recommendations in Ontario and Quebec (120-170 kg ha-1).

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Changes in photosynthesis and soil moisture drive the seasonal soil respiration-temperature hysteresis relationship

USDA-ARS?s Scientific Manuscript database

In nearly all large-scale models, CO2 efflux from soil (i.e., soil respiration) is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable at the local scale, and there is often a pronounced hysteresis in the soil resp...

A statistical method for estimating rates of soil development and ages of geologic deposits: A design for soil-chronosequence studies

USGS Publications Warehouse

Switzer, P.; Harden, J.W.; Mark, R.K.

1988-01-01

A statistical method for estimating rates of soil development in a given region based on calibration from a series of dated soils is used to estimate ages of soils in the same region that are not dated directly. The method is designed specifically to account for sampling procedures and uncertainties that are inherent in soil studies. Soil variation and measurement error, uncertainties in calibration dates and their relation to the age of the soil, and the limited number of dated soils are all considered. Maximum likelihood (ML) is employed to estimate a parametric linear calibration curve, relating soil development to time or age on suitably transformed scales. Soil variation on a geomorphic surface of a certain age is characterized by replicate sampling of soils on each surface; such variation is assumed to have a Gaussian distribution. The age of a geomorphic surface is described by older and younger bounds. This technique allows age uncertainty to be characterized by either a Gaussian distribution or by a triangular distribution using minimum, best-estimate, and maximum ages. The calibration curve is taken to be linear after suitable (in certain cases logarithmic) transformations, if required, of the soil parameter and age variables. Soil variability, measurement error, and departures from linearity are described in a combined fashion using Gaussian distributions with variances particular to each sampled geomorphic surface and the number of sample replicates. Uncertainty in age of a geomorphic surface used for calibration is described using three parameters by one of two methods. In the first method, upper and lower ages are specified together with a coverage probability; this specification is converted to a Gaussian distribution with the appropriate mean and variance. In the second method, "absolute" older and younger ages are specified together with a most probable age; this specification is converted to an asymmetric triangular distribution with mode at the most probable age. The statistical variability of the ML-estimated calibration curve is assessed by a Monte Carlo method in which simulated data sets repeatedly are drawn from the distributional specification; calibration parameters are reestimated for each such simulation in order to assess their statistical variability. Several examples are used for illustration. The age of undated soils in a related setting may be estimated from the soil data using the fitted calibration curve. A second simulation to assess age estimate variability is described and applied to the examples. ?? 1988 International Association for Mathematical Geology.

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

NASA Astrophysics Data System (ADS)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.

Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

NASA Astrophysics Data System (ADS)

Drusch, M.

2007-02-01

Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

Deriving site-specific soil clean-up values for metals and metalloids: Rationale for including protection of soil microbial processes

PubMed Central

Kuperman, Roman G; Siciliano, Steven D; Römbke, Jörg; Oorts, Koen

2014-01-01

Although it is widely recognized that microorganisms are essential for sustaining soil fertility, structure, nutrient cycling, groundwater purification, and other soil functions, soil microbial toxicity data were excluded from the derivation of Ecological Soil Screening Levels (Eco-SSL) in the United States. Among the reasons for such exclusion were claims that microbial toxicity tests were too difficult to interpret because of the high variability of microbial responses, uncertainty regarding the relevance of the various endpoints, and functional redundancy. Since the release of the first draft of the Eco-SSL Guidance document by the US Environmental Protection Agency in 2003, soil microbial toxicity testing and its use in ecological risk assessments have substantially improved. A wide range of standardized and nonstandardized methods became available for testing chemical toxicity to microbial functions in soil. Regulatory frameworks in the European Union and Australia have successfully incorporated microbial toxicity data into the derivation of soil threshold concentrations for ecological risk assessments. This article provides the 3-part rationale for including soil microbial processes in the development of soil clean-up values (SCVs): 1) presenting a brief overview of relevant test methods for assessing microbial functions in soil, 2) examining data sets for Cu, Ni, Zn, and Mo that incorporated soil microbial toxicity data into regulatory frameworks, and 3) offering recommendations on how to integrate the best available science into the method development for deriving site-specific SCVs that account for bioavailability of metals and metalloids in soil. Although the primary focus of this article is on the development of the approach for deriving SCVs for metals and metalloids in the United States, the recommendations provided in this article may also be applicable in other jurisdictions that aim at developing ecological soil threshold values for protection of microbial processes in contaminated soils. PMID:24376192

Impact of climate variability on N and C flux within the life cycle of biofuels produced from crop residues

NASA Astrophysics Data System (ADS)

Pourhashem, G.; Block, P. J.; Adler, P. R.; Spatari, S.

2013-12-01

Biofuels from agricultural feedstocks (lignocellulose) are under development to meet national policy objectives for producing domestic renewable fuels. Using crop residues such as corn stover as feedstock for biofuel production can minimize the risks associated with food market disruption; however, it demands managing residue removal to minimize soil carbon loss, erosion, and to ensure nutrient replacement. Emissions of nitrous oxide and changes to soil organic carbon (SOC) are subject to variability in time due to local climate conditions and cultivation practices. Our objective is to investigate the effect of climate inputs (precipitation and temperature) on biogeochemical greenhouse gas (GHG) emissions (N2O and SOC expressed as CO2) within the life cycle of biofuels produced from agricultural residues. Specifically, we investigate the impact of local climate variability on soil carbon and nitrogen fluxes over a 20-year biorefinery lifetime where biomass residue is used for lignocellulosic ethanol production. We investigate two cases studied previously (Pourhashem et al, 2013) where the fermentable sugars in the agricultural residue are converted to ethanol (biofuel) and the lignin byproduct is used in one of two ways: 1) power co-generation; or 2) application to land as a carbon/nutrient-rich amendment to soil. In the second case SOC losses are mitigated through returning the lignin component to land while the need for fertilizer addition is also eliminated, however in both cases N2O and SOC are subject to variability due to variable climate conditions. We used the biogeochemical model DayCent to predict soil carbon and nitrogen fluxes considering soil characteristics, tillage practices and local climate (e.g. temperature and rainfall). We address the impact of climate variability on the soil carbon and nitrogen fluxes by implementing a statistical bootstrap resampling method based on a historic data set (1980 to 2000). The ensuing probabilistic outputs from the DayCent model provide an increased understanding of expected ranges in fluxes attributable to climate variability. DayCent results for soil carbon change from the developed input datasets indicate that SOC is more strongly influenced by management practices than by variability in local climate even though the magnitude of this impact could depend on the local soil characteristics. Unlike carbon fluxes, soil N2O emissions are more sensitive to local climate variability than management practices suggesting that the difference in N2O emissions from the two management cases is not statistically significant. Therefore application of the high lignin byproduct material to land is a more efficient strategy in reducing soil carbon loss. However, although soil nitrogen fluxes might not be very sensitive to local climate when comparing synthetic to bio-based fertilizer applications, implementing the latter will eliminate the fertilizer production emissions on a biofuel production life cycle basis. Reference Pourhashem, G.; Adler, P., R.; McAloon, A. J.; Spatari, S., Cost and greenhouse gas emission tradeoffs of alternative uses of lignin for second generation ethanol. Env. Res. Let. 2013, 8, 025021

Towards an understanding of coupled physical and biological processes in the cultivated Sahel - 1. Energy and water

NASA Astrophysics Data System (ADS)

Ramier, David; Boulain, Nicolas; Cappelaere, Bernard; Timouk, Franck; Rabanit, Manon; Lloyd, Colin R.; Boubkraoui, Stéphane; Métayer, Frédéric; Descroix, Luc; Wawrzyniak, Vincent

2009-08-01

SummaryThis paper presents an analysis of the coupled cycling of energy and water by semi-arid Sahelian surfaces, based on two years of continuous vertical flux measurements from two homogeneous recording stations in the Wankama catchment, in the West Niger meso-site of the AMMA project. The two stations, sited in a millet field and in a semi-natural fallow savanna plot, sample the two dominant land cover types in this area typical of the cultivated Sahel. The 2-year study period enables an analysis of seasonal variations over two full wet-dry seasons cycles, characterized by two contrasted rain seasons that allow capturing a part of the interannual variability. All components of the surface energy budget (four-component radiation budget, soil heat flux and temperature, eddy fluxes) are measured independently, allowing for a quality check through analysis of the energy balance closure. Water cycle monitoring includes rainfall, evapotranspiration (from vapour eddy flux), and soil moisture at six depths. The main modes of observed variability are described, for the various energy and hydrological variables investigated. Results point to the dominant role of water in the energy cycle variability, be it seasonal, interannual, or between land cover types. Rainfall is responsible for nearly as much seasonal variations of most energy-related variables as solar forcing. Depending on water availability and plant requirements, evapotranspiration pre-empts the energy available from surface forcing radiation, over the other dependent processes (sensible and ground heat, outgoing long wave radiation). In the water budget, pre-emption by evapotranspiration leads to very large variability in soil moisture and in deep percolation, seasonally, interannually, and between vegetation types. The wetter 2006 season produced more evapotranspiration than 2005 from the fallow but not from the millet site, reflecting differences in plant development. Rain-season evapotranspiration is nearly always lower at the millet site. Higher soil moisture at this site suggests that this difference arises from lower vegetation requirements rather than from lower infiltration/higher runoff. This difference is partly compensated for during the next dry season. Effects of water and vegetation on the energy budget appear to occur more through latent heat than through albedo. A large part of albedo variability comes from soil wetting and drying. Prior to the onset of monsoon rain, the change in air mass temperature and wind produces, through modulation of sensible heat, a marked chilling effect on the components of the surface energy budget.

Dissolved and Particulate Organic Carbon Transport, Loads and Relationships from Catchments in the Dryland Agricultural Region of the Inland Pacific Northwest

NASA Astrophysics Data System (ADS)

Boylan, R. D.; Brooks, E. S.

2012-12-01

It has long been understood that soil organic matter (SOM) plays important role in the chemistry of agricultural soils. Promoting both cation exchange capacity and water retention, SOM also has the ability to sequester atmospheric carbon adding to a soils organic carbon content. Increasing soil organic carbon in the dryland agricultural region of the Inland Pacific Northwest is not only good for soil health, but also has the potential to mitigate greenhouse gas emissions. Implementing strategies that minimizing the loss of soil carbon thus promoting carbon sequestration require a fundamental understanding of the dominant hydrologic flow paths and runoff generating processes in this landscape. Global fluxes of organic carbon from catchments range from 0.4-73,979 kg C km-2 year-1 for particulate organic carbon and 1.2-56,946 kg C km-2 year-1 for dissolved organic carbon (Alvarez-Cobelas, 2010). This small component of the global carbon cycle has been relatively well studied but there have yet to be any studies that focus on the dryland agricultural region of the Inland Pacific Northwest. In this study event based samples were taken at 5 sites across the Palouse Basin varying in land use and management type as well as catchment size, ranging from 1km2 to 7000 km2. Data collection includes streamflow, suspended sediment, dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), particulate organic carbon (POC), dissolved organic nitrogen (TN), and nitrate concentrations as well as soil organic carbon (SOC) from distributed source areas. It is predicted that management type and streamflow will be the main drivers for DOC and POC concentrations. Relationships generated and historic data will then be used in conjunction with the Water Erosion Prediction Project (WEPP) to simulate field scale variability in the soil moisture, temperature, surface saturation, and soil erosion. Model assessment will be based on both surface runoff and sediment load measured at the outlet of these field catchments and distributed measurements capturing spatial variability within the catchments. We demonstrate how the accurate representation of the field scale variability in hydrology is an essential first step in the development of full scale cropping models capable of evaluating precision-based mitigation strategies.

Soil microbial diversity in the vicinity of desert shrubs.

PubMed

Saul-Tcherkas, Vered; Unc, Adrian; Steinberger, Yosef

2013-04-01

Water and nutrient availability are the major limiting factors of biological activity in arid and semiarid ecosystems. Therefore, perennial plants have developed different ecophysiological adaptations to cope with harsh conditions. The chemical profile of the root exudates varies among plant species and this can induce variability in associated microbial populations. We examined the influence of two shrubs species, Artemisia sieberi and Noaea mucronata, on soil microbial diversity. Soil samples were collected monthly, from December 2006 to November 2007, near canopies of both shrubs (0-10-cm depth). Samples were used for abiotic tests and determination of soil bacterial diversity. No significant differences were found in the abiotic variables (soil moisture, total organic matter, and total soluble nitrogen (TSN)) between soil samples collected from under the two shrubs during the study period. No obvious differences in the Shannon-Weaver index, evenness values, or total phylogenetic distances were found for the soil microbial communities. However, detailed denaturing gradient gel electrophoresis (DGGE) clustering as well as taxonomic diversity analyses indicated clear shifts in the soil microbial community composition. These shifts were governed by seasonal variability in water availability and, significantly, by plant species type.

Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

The effect of soil moisture anomalies on maize yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

2018-03-01

Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

Variability in soil CO2 efflux across distinct urban land cover types

NASA Astrophysics Data System (ADS)

Weissert, Lena F.; Salmond, Jennifer A.; Schwendenmann, Luitgard

2015-04-01

As a main source of greenhouse gases urban areas play an important role in the global carbon cycle. To assess the potential role of urban vegetation in mitigating carbon emissions we need information on the magnitude of biogenic CO2 emissions and its driving factors. We examined how urban land use types (urban forest, parklands, sportsfields) vary in their soil CO2 efflux. We measured soil CO2 efflux and its isotopic signature, soil temperature and soil moisture over a complete growing season in Auckland, New Zealand. Soil physical and chemical properties and vegetation characteristics were also measured. Mean soil CO2 efflux ranged from 4.15 to 12 μmol m-2 s-1. We did not find significant differences in soil CO2 efflux among land cover types due to high spatial variability in soil CO2 efflux among plots. Soil (soil carbon and nitrogen density, texture, soil carbon:nitrogen ratio) and vegetation characteristics (basal area, litter carbon density, grass biomass) were not significantly correlated with soil CO2 efflux. We found a distinct seasonal pattern with significantly higher soil CO2 efflux in autumn (Apr/May) and spring (Oct). In urban forests and sportsfields over 80% of the temporal variation was explained by soil temperature and soil water content. The δ13C signature of CO2 respired from parklands and sportsfields (-20 permil - -25 permil) were more positive compared to forest plots (-29 permil) indicating that parkland and sportsfields had a considerable proportion of C4 grasses. Despite the large intra-urban variability, our results compare to values reported from other, often climatically different cities, supporting the hypothesis of homogenization across urban areas as a result of human management practices.

Application of nanoparticle of rock phosphate and biofertilizer in increasing some soil chemical characteristics of variable charge soil

NASA Astrophysics Data System (ADS)

Devnita, Rina; Joy, Benny; Arifin, Mahfud; Hudaya, Ridha; Oktaviani, Nurul

2018-02-01

Soils in Indonesia are dominated by variable charge soils where the technology like fertilization did not give the same result as the soils with permanent charge. The objectives of this research is to increase some chemical characteristic of variable charge soils by using the high negative charge ameliorations like rock phosphate in nanoparticle combined with biofertilizer. The research used a complete randomized experimental design in factorial with two factors. The first factor was nanoparticle of rock phosphate consists of four doses on soil weight percentage (0%, 2.5%, 5.0% and 7.5%). The second factor was biofertilizer consisted of two doses (without biofertilizer and 1 g.kg-1 soil biofertilizer). The combination treatments replicated three times. Variable charge soil used was Andisol. Andisol and the treatments were incubated for 4 months. Soil samples were taken after one and four months during incubation period to be analyzed for P-retention, available P and potential P. The result showed that all combinations of rock phosphate and biofertilizer decreased the P-retention to 75-77% after one month. Independently, application of 7.5% of rock phosphate decreased P-retention to 87.22% after four months, increased available P (245.37 and 19.12 mg.kg-1) and potential P (1354.78 and 3000.99 mg/100) after one and four months. Independently, biofertilizer increased the P-retention to 91.66% after four months, decreased available P to 121.55 mg.kg-1 after one month but increased to 12.55 mg.kg-1 after four months, decreased potential P to 635.30 after one month but increased to 1810.40 mg.100 g-1 after four months.

Influence of spatial and temporal variability of subsurface soil moisture and temperature on vapour intrusion

NASA Astrophysics Data System (ADS)

Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu

2014-05-01

A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface soil moisture and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in moisture and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface soil properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be affected by spatial and temporal variability of subsurface soil moisture and temperature. The monthly monitoring of soil-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. Soil-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the soil-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of soil-gas monitoring wells for human risk assessment is a site specific decision. Subsurface soil-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface soil properties such as temperature and moisture that fluctuate with the seasons of the year.

Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates

NASA Astrophysics Data System (ADS)

Mohanty, B.; Neelam, M.

2017-12-01

The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Phosphorus in agricultural soils: drivers of its distribution at the global scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ringeval, Bruno; Augusto, Laurent; Monod, Herve

Phosphorus (P) availability in soils limits crop yields in many regions of the world, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global datasets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analyzed both the labile inorganic P (P ILAB), a proxy of the pool involved in plant nutrition and themore » total soil P (P TOT). We found that the soil biogeochemical background (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P TOT vs P ILAB. Indeed, 97% of the P TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 41% and 58% of P ILAB spatial variability, respectively. Other drivers such as climate, soil erosion, atmospheric P deposition and soil buffering capacity made only very small contribution. Lastly, our study is a promising approach to investigate the potential effect of P as a limiting factor for agricultural ecosystems and for global food production. Additionally, we quantified the anthropogenic perturbation of P cycle and demonstrated how the different drivers are combined to explain the global distribution of agricultural soil P.« less

Climatic variability of soil water in the American Midwest: Part 2. Spatio-temporal analysis

NASA Astrophysics Data System (ADS)

Georgakakos, Konstantine P.; Bae, Deg-Hyo

1994-11-01

A study of the model-estimated soil water, aggregated over three large drainage basins of the Midwestern USA, is reported. The basin areas are in the range from 2000 km 2 to 3500 km 2, and allow the study of mesoscale (1000-10000 km 2) soil water features. In each case, a conceptual hydrologic model was used to produce upper and lower soil water estimates that are consistent with the atmospheric forcing of daily precipitation, potential evapotranspiration and air temperature, and with the observed daily streamflow divergence over a 40 year period. It is shown that the water contents of the upper and lower soil reach peaks in different months, with the soil column being most saturated in June, when the area is prone to serious flooding. Temporal and spatial features of the variability of model-estimated soil water content are identified. The autocorrelation function of monthly averaged soil water shows that the upper soil water remains persistent for about a season, whereas the persistence of the lower soil water extends to several seasons. The soil water estimates of the three study basins exhibit strong similarities in annual cycles and interannual variability. It is shown that the frequency of significant positive (wet) soil water anomalies that extend over a 2° × 2° region is lower than that of significant negative (dry) ones of the same extent in this region of the USA.

Intra- and interspecific trait variations reveal functional relationships between specific leaf area and soil niche within a subtropical forest.

PubMed

He, Dong; Chen, Yongfa; Zhao, Kangning; Cornelissen, J H C; Chu, Chengjin

2018-02-03

How functional traits vary with environmental conditions is of fundamental importance in trait-based community ecology. However, how intraspecific variability in functional traits is connected to species distribution is not well understood. This study investigated inter- and intraspecific variation of a key functional trait, i.e. specific leaf area (leaf area per unit dry mass; SLA), in relation to soil factors and tested if trait variation is more closely associated with specific environmental regimes for low-variability species than for high-variability species. In a subtropical evergreen forest plot (50 ha, southern China), 106 700 leaves from 5335 individuals of 207 woody species were intensively collected, with 30 individuals sampled for most species to ensure a sufficient sample size representative of intraspecific variability. Soil conditions for each plant were estimated by kriging from more than 1700 observational soil locations across the plot. Intra- and interspecific variation in SLA were separately related to environmental factors. Based on the species-specific variation of SLA, species were categorized into three groups: low-, intermediate- and high-intraspecific variability. Intraspecific habitat ranges and the strength of SLA-habitat relationships were compared among these three groups. Interspecific variation in SLA overrides the intraspecific variation (77 % vs. 8 %). Total soil nitrogen (TN, positively) and total organic carbon (TOC, negatively) are the most important explanatory factors for SLA variation at both intra- and interspecific levels. SLA, both within and between species, decreases with decreasing soil nitrogen availability. As predicted, species with low intraspecific variability in SLA have narrower habitat ranges with respect to soil TOC and TN and show a stronger SLA-habitat association than high-variability species. For woody plants low SLA is a phenotypic and probably adaptive response to nitrogen stress, which drives the predominance of species with ever-decreasing SLA towards less fertile habitats. Intraspecific variability in SLA is positively connected to species' niche breadth, suggesting that low-variability species may play a more deterministic role in structuring plant assemblages than high-variability species. This study highlights the importance of quantifying intraspecific trait variation to improve our understanding of species distributions across a vegetated landscape. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Preliminary response of primary production and community composition to precipitation variation in a temperate grassland

USDA-ARS?s Scientific Manuscript database

a) Background/Questions/Methods Grassland ecosystems are water-limited and show the highest interannual ANPP variability across biomes. Changes in annual amounts or seasonality of rainfall may interact with soil texture to impact grassland ecosystem functions including net primary productivity (NPP...

PARTIAL LEAST SQUARE ANALYSES FOR ASSOCIATION OF LANDSCAPE METRICS WITH WATER BIOLOGICAL AND CHEMICAL PROPERTIES IN THE SAVANNAH RIVER BASIN

EPA Science Inventory

Surface water quality is related to conditions in the surrounding geophysical environment, including soils, landcover, and anthropogenic activities. A number of statistical methods may be used to analyze and explore relationships among variables. Single-, multiple- and multivaria...

Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

Treesearch

James E. Smith; Linda S. Heath

2015-01-01

Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

The response of arid soil communities to climate change: Chapter 8

USGS Publications Warehouse

Steven, Blaire; McHugh, Theresa Ann; Reed, Sasha C.

2017-01-01

Arid and semiarid ecosystems cover approximately 40% of Earth’s terrestrial surface and are present on each of the planet’s continents [1]. Drylands are characterized by their aridity, but there is substantial geographic, edaphic, and climatic variability among these vast ecosystems, and these differences underscore substantial variation in dryland soil microbial communities, as well as in the future climates predicted among arid and semiarid systems globally. Furthermore, arid ecosystems are commonly patchy at a variety of spatial scales [2,3]. Vascular plants are widely interspersed in drylands and bare soil, or soil that is covered with biological soil crusts, fill these spaces. The variability acts to further enhance spatial heterogeneity, as these different zones within dryland ecosystems differ in characteristics such as water retention, albedo, and nutrient cycling [4–6]. Importantly, the various soil patches of an arid landscape may be differentially sensitive to climate change. Soil communities are only active when enough moisture is available, and drylands show large spatial variability in soil moisture, with potentially long dry periods followed by pulses of moisture. The pulse dynamics associated with this wetting and drying affect the composition, structure, and function of dryland soil communities, and integrate biotic and abiotic processes via pulse-driven exchanges, interactions, transitions, and transfers. Climate change will likely alter the size, frequency, and intensity of future precipitation pulses, as well as influence non-rainfall sources of soil moisture, and aridland ecosystems are known to be highly sensitive to such climate variability. Despite great heterogeneity, arid ecosystems are united by a key parameter: a limitation in water availability. This characteristic may help to uncover unifying aspects of dryland soil responses to global change. The dryness of an ecosystem can be described by its aridity index (AI). Several AIs have been proposed, but the most widely used metrics determine the difference between average precipitation and potential evapotranspiration, where evapotranspiration is the sum of evaporation and plant transpiration, both of which move water from the ecosystem to the atmosphere [7–9]. Because evapotranspiration can be affected by various environmental factors such as temperature and incident radiation (Fig. 10.1), regions that receive the same average precipitation may have significantly different AI values [10,11]. Multiple studies have documented that mean annual precipitation, and thus AI, is highly correlated with biological diversity and net primary productivity [12–15]. Accordingly, AI is considered to be a central regulator of the diversity, structure, and productivity of an ecosystem, playing an especially influential role in arid ecosystems. Thus, the climate parameters that drive alterations in the AI of a region are likely to play an disproportionate role in shaping the response of arid soil communities to a changing climate. In this chapter we consider climate parameters that have been shown to be altered through climate change, with a focus on how these parameters are likely to affect dryland soil communities, including microorganisms and invertebrates. In particular, our goal is to highlight dryland soil community structure and function in the context of climate change, and we will focus on community relationships with increased atmospheric CO2 concentrations (a primary driver of climate change), temperature, and sources of soil moisture.

Variability in soil CO2 production and surface CO2 efflux across riparian-hillslope transitions

Treesearch

Vincent Jerald Pacific

2007-01-01

The spatial and temporal controls on soil CO2 production and surface CO2 efflux have been identified as an outstanding gap in our understanding of carbon cycling. I investigated both the spatial and temporal variability of soil CO2 concentrations and surface CO2 efflux across eight topographically distinct riparian-hillslope transitions in the ~300 ha subalpine upper-...

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

Response of three soil water sensors to variable solution electrical conductivity in different soils

USDA-ARS?s Scientific Manuscript database

Commercial dielectric soil water sensors may improve management of irrigated agriculture by providing continuous field soil water information. Use of these sensors is partly limited by sensor sensitivity to variations in soil salinity and texture, which force expensive, time consuming, soil specific...

Effects of Nutrient Enrichment on Microbial Communities and Carbon Cycling in Wetland Soils

NASA Astrophysics Data System (ADS)

Hartman, W.; Neubauer, S. C.; Richardson, C. J.

2013-12-01

Soil microbial communities are responsible for catalyzing biogeochemical transformations underlying critical wetland functions, including cycling of carbon (C) and nutrients, and emissions of greenhouse gasses (GHG). Alteration of nutrient availability in wetland soils may commonly occur as the result of anthropogenic impacts including runoff from human land uses in uplands, alteration of hydrology, and atmospheric deposition. However, the impacts of altered nutrient availability on microbial communities and carbon cycling in wetland soils are poorly understood. To assess these impacts, soil microbial communities and carbon cycling were determined in replicate experimental nutrient addition plots (control, +N, +P, +NP) across several wetland types, including pocosin peat bogs (NC), freshwater tidal marshes (GA), and tidal salt marshes (SC). Microbial communities were determined by pyrosequencing (Roche 454) extracted soil DNA, targeting both bacteria (16S rDNA) and fungi (LSU) at a depth of ca. 1000 sequences per plot. Wetland carbon cycling was evaluated using static chambers to determine soil GHG fluxes, and plant inclusion chambers were used to determine ecosystem C cycling. Soil bacterial communities responded to nutrient addition treatments in freshwater and tidal marshes, while fungal communities did not respond to treatments in any of our sites. We also compared microbial communities to continuous biogeochemical variables in soil, and found that bacterial community composition was correlated only with the content and availability of soil phosphorus, while fungi responded to phosphorus stoichiometry and soil pH. Surprisingly, we did not find a significant effect of our nutrient addition treatments on most metrics of carbon cycling. However, we did find that several metrics of soil carbon cycling appeared much more related to soil phosphorus than to nitrogen or soil carbon pools. Finally, while overall microbial community composition was weakly correlated with soil carbon cycling, our work did identify a small number of individual taxonomic groups that were more strongly correlated with soil CO2 flux. These results suggest that a small number of microbial groups may potentially serve as keystone taxa (and functional indicators), which simple community fingerprinting approaches may overlook. Our results also demonstrate strong effects of soil phosphorus availability on both microbial communities and soil carbon cycling, even in wetland types traditionally considered to be nitrogen limited.

Quantitative Analysis of Relevant Soil, Land-use and Climate Characteristics on Landscape Degradation in Hungary

NASA Astrophysics Data System (ADS)

Kertesz, Adam; Mika, Janos; Jakab, Gergely; Palinkas, Melinda

2017-04-01

The objective of our research is to survey degradation processes acting in each micro-region of Hungary in connection with geographical and climatic characteristics. A survey of land degradation processes has been carried out at medium scale (1:50 000) to identify the affected areas of the region. Over 18,000 rectangles of Hungary have been digitally characterised for several types of land degradation. Water-flow type gully erosion and soil-loss (RUSLE, 2015: Esdac-data) are studied for dependent variables in this study. USDA textural classes, available water capacity, bulk density, clay content, coarse fragments, silt content, sand content, soil parent material, soil texture, land-use type (Corine, 2012) are used for non-climatic variables. Some of these characteristics are quantified in a non-scalable way, so the first step was to arrange these qualitative codes or pseudo-numbers into monotonous order for including them into the following multi-regression analyses. Data available from the CarpatClim Project (www.carpatclim-eu.org/pages/home) for 1961-2010 are also used in their 50 years averages is seasonal and annual resolution. The selected variables from this gridded data set are global radiation, daily mean temperature, maximum and minimum temperature, number of extreme cold days (< 20 C), precipitation, extreme wet days (>20 mm), days with utilizable precipitation (>1mm/d), potential evapotranspiration, Palmer Index (PDSI), Palfai Index (PAI), relative humidity and wind speed at 10 m height. The gully erosion processes strongly depend on the investigated non-climatic variables, mostly on parent material and slope. The group of further climatic factors is formed by winter relative humidity, wind speed and all-year round Palmer index. Besides leading role of the above non-climatic factors, additional effects of the significant climate variables are difficult to interpret. Nevertheless, the partial effects of these climate variables are combined with future climate scenarios available from GCM and RCM studies for Hungary. The real climate change effects may likely be stronger, than those obtained by this combination, due to inter-dependences between the non-climatic factors and climate variations. The study has been supported by the OTKA-K108755 project.

Misrepresentation of hydro-erosional processes in rainfall simulations using disturbed soil samples

NASA Astrophysics Data System (ADS)

Thomaz, Edivaldo L.; Pereira, Adalberto A.

2017-06-01

Interrill erosion is a primary soil erosion process which consists of soil detachment by raindrop impact and particle transport by shallow flow. Interill erosion affects other soil erosion sub-processes, e.g., water infiltration, sealing, crusting, and rill initiation. Interrill erosion has been widely studied in laboratories, and the use of a sieved soil, i.e., disturbed soil, has become a standard method in laboratory experiments. The aims of our study are to evaluate the hydro-erosional response of undisturbed and disturbed soils in a laboratory experiment, and to quantify the extent to which hydraulic variables change during a rainstorm. We used a splash pan of 0.3 m width, 0.45 m length, and 0.1 m depth. A rainfall simulation of 58 mm h- 1 lasting for 30 min was conducted on seven replicates of undisturbed and disturbed soils. During the experiment, several hydro-physical parameters were measured, including splashed sediment, mean particle size, runoff, water infiltration, and soil moisture. We conclude that use of disturbed soil samples results in overestimation of interrill processes. Of the nine assessed parameters, four displayed greater responses in the undisturbed soil: infiltration, topsoil shear strength, mean particle size of eroded particles, and soil moisture. In the disturbed soil, five assessed parameters displayed greater responses: wash sediment, final runoff coefficient, runoff, splash, and sediment yield. Therefore, contextual soil properties are most suitable for understanding soil erosion, as well as for defining soil erodibility.

Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrington, Stephen P.

Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Study Variability of Seasonal Soil Moisture in Ensemble of CMIP5 Models Over South Asia During 1950-2005

NASA Astrophysics Data System (ADS)

Fahim, A. M.; Shen, R.; Yue, Z.; Di, W.; Mushtaq Shah, S.

2015-12-01

Moisture in the upper most layer of soil column from 14 different models under Coupled Model Intercomparison Project Phase-5 (CMIP5) project were analyzed for four seasons of the year. Aim of this study was to explore variability in soil moisture over south Asia using multi model ensemble and relationship between summer rainfall and soil moisture for spring and summer season. GLDAS (Global Land Data Assimilation System) dataset set was used for comparing CMIP5 ensemble mean soil moisture in different season. Ensemble mean represents soil moisture well in accordance with the geographical features; prominent arid regions are indicated profoundly. Empirical Orthogonal Function (EOF) analysis was applied to study the variability. First component of EOF explains 17%, 16%, 11% and 11% variability for spring, summer, autumn and winter season respectively. Analysis reveal increasing trend in soil moisture over most parts of Afghanistan, Central and north western parts of Pakistan, northern India and eastern to south eastern parts of China, in spring season. During summer, south western part of India exhibits highest negative trend while rest of the study area show minute trend (increasing or decreasing). In autumn, south west of India is under highest negative loadings. During winter season, north western parts of study area show decreasing trend. Summer rainfall has very week (negative or positive) spatial correlation, with spring soil moisture, while possess higher correlation with summer soil moisture. Our studies have significant contribution to understand complex nature of land - atmosphere interactions, as soil moisture prediction plays an important role in the cycle of sink and source of many air pollutants. Next level of research should be on filling the gaps between accurately measuring the soil moisture using satellite remote sensing and land surface modelling. Impact of soil moisture in tracking down different types of pollutant will also be studied.

Global distribution of soil organic carbon - Part 1: Masses and frequency distributions of SOC stocks for the tropics, permafrost regions, wetlands, and the world

NASA Astrophysics Data System (ADS)

Köchy, M.; Hiederer, R.; Freibauer, A.

2015-04-01

The global soil organic carbon (SOC) mass is relevant for the carbon cycle budget and thus atmospheric carbon concentrations. We review current estimates of SOC stocks and mass (stock × area) in wetlands, permafrost and tropical regions and the world in the upper 1 m of soil. The Harmonized World Soil Database (HWSD) v.1.2 provides one of the most recent and coherent global data sets of SOC, giving a total mass of 2476 Pg when using the original values for bulk density. Adjusting the HWSD's bulk density (BD) of soil high in organic carbon results in a mass of 1230 Pg, and additionally setting the BD of Histosols to 0.1 g cm-3 (typical of peat soils), results in a mass of 1062 Pg. The uncertainty in BD of Histosols alone introduces a range of -56 to +180 Pg C into the estimate of global SOC mass in the top 1 m, larger than estimates of global soil respiration. We report the spatial distribution of SOC stocks per 0.5 arcminutes; the areal masses of SOC; and the quantiles of SOC stocks by continents, wetland types, and permafrost types. Depending on the definition of "wetland", wetland soils contain between 82 and 158 Pg SOC. With more detailed estimates for permafrost from the Northern Circumpolar Soil Carbon Database (496 Pg SOC) and tropical peatland carbon incorporated, global soils contain 1325 Pg SOC in the upper 1 m, including 421 Pg in tropical soils, whereof 40 Pg occurs in tropical wetlands. Global SOC amounts to just under 3000 Pg when estimates for deeper soil layers are included. Variability in estimates is due to variation in definitions of soil units, differences in soil property databases, scarcity of information about soil carbon at depths > 1 m in peatlands, and variation in definitions of "peatland".

CPT-based probabilistic and deterministic assessment of in situ seismic soil liquefaction potential

USGS Publications Warehouse

Moss, R.E.S.; Seed, R.B.; Kayen, R.E.; Stewart, J.P.; Der Kiureghian, A.; Cetin, K.O.

2006-01-01

This paper presents a complete methodology for both probabilistic and deterministic assessment of seismic soil liquefaction triggering potential based on the cone penetration test (CPT). A comprehensive worldwide set of CPT-based liquefaction field case histories were compiled and back analyzed, and the data then used to develop probabilistic triggering correlations. Issues investigated in this study include improved normalization of CPT resistance measurements for the influence of effective overburden stress, and adjustment to CPT tip resistance for the potential influence of "thin" liquefiable layers. The effects of soil type and soil character (i.e., "fines" adjustment) for the new correlations are based on a combination of CPT tip and sleeve resistance. To quantify probability for performancebased engineering applications, Bayesian "regression" methods were used, and the uncertainties of all variables comprising both the seismic demand and the liquefaction resistance were estimated and included in the analysis. The resulting correlations were developed using a Bayesian framework and are presented in both probabilistic and deterministic formats. The results are compared to previous probabilistic and deterministic correlations. ?? 2006 ASCE.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Impact of runoff infiltration on contaminant accumulation and transport in the soil/filter media of Sustainable Urban Drainage Systems: A literature review.

PubMed

Tedoldi, Damien; Chebbo, Ghassan; Pierlot, Daniel; Kovacs, Yves; Gromaire, Marie-Christine

2016-11-01

The increasing use of Sustainable Urban Drainage Systems (SUDS) for stormwater management raises some concerns about the fate of ubiquitous runoff micropollutants in soils and their potential threat to groundwater. This question may be addressed either experimentally, by sampling and analyzing SUDS soil after a given operating time, or with a modeling approach to simulate the fate and transport of contaminants. After briefly reminding the processes responsible for the retention, degradation, or leaching of several urban-sourced contaminants in soils, this paper presents the state of the art about both experimental and modeling assessments. In spite of noteworthy differences in the sampling protocols, the soil parameters chosen as explanatory variables, and the methods used to evaluate the site-specific initial concentrations, most investigations undoubtedly evidenced a significant accumulation of metals and/or hydrocarbons in SUDS soils, which in the majority of the cases appears to be restricted to the upper 10 to 30cm. These results may suggest that SUDS exhibit an interesting potential for pollution control, but antinomic observations have also been made in several specific cases, and the inter-site concentration variability is still difficult to appraise. There seems to be no consensus regarding the level of complexity to be used in models. However, the available data deriving from experimental studies is generally limited to the contamination profiles and a few parameters of the soil, as a result of which "complex" models (including colloid-facilitated transport for example) appear to be difficult to validate before using them for predictive evaluations. Copyright © 2016 Elsevier B.V. All rights reserved.

Shallow soil moisture - ground thaw interactions and controls - Part 2: Influences of water and energy fluxes

NASA Astrophysics Data System (ADS)

Guan, X. J.; Spence, C.; Westbrook, C. J.

2010-01-01

The companion paper (Guan et al., 2010) demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the key control in variable soil moisture and frost table interactions among the sites was the presence of surface water. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to conductive ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.

Shallow soil moisture - ground thaw interactions and controls - Part 2: Influences of water and energy fluxes

NASA Astrophysics Data System (ADS)

Guan, X. J.; Spence, C.; Westbrook, C. J.

2010-07-01

The companion paper (Guan et al., 2010) demonstrated variable interactions and correlations between shallow soil moisture and ground thaw in soil filled areas along a wetness spectrum in a subarctic Canadian Precambrian Shield landscape. From wetter to drier, these included a wetland, peatland and soil filled valley. Herein, water and energy fluxes were examined for these same subarctic study sites to discern the key controlling processes on the found patterns. Results showed the presence of surface water was the key control in variable soil moisture and frost table interactions among sites. At the peatland and wetland sites, accumulated water in depressions and flow paths maintained soil moisture for a longer duration than at the hummock tops. These wet areas were often locations of deepest thaw depth due to the transfer of latent heat accompanying lateral surface runoff. Although the peatland and wetland sites had large inundation extent, modified Péclet numbers indicated the relative influence of external and internal hydrological and energy processes at each site were different. Continuous inflow from an upstream lake into the wetland site caused advective and conductive thermal energies to be of equal importance to ground thaw. The absence of continuous surface flow at the peatland and valley sites led to dominance of conductive thermal energy over advective energy for ground thaw. The results suggest that the modified Péclet number could be a very useful parameter to differentiate landscape components in modeling frost table heterogeneity. The calculated water and energy fluxes, and the modified Péclet number provide quantitative explanations for the shallow soil moisture-ground thaw patterns by linking them with hydrological processes and hillslope storage capacity.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

NASA Astrophysics Data System (ADS)

Shi, Fang; Peng, Xiang; Liu, Huan; Hu, Yafei; Liu, Zheng; Li, Eric

2018-03-01

Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.

Quantifying the Influence of Near-Surface Water-Energy Budgets on Soil Thermal Properties Using a Network of Coupled Meteorological and Vadose Zone Instrument Arrays in Indiana, USA

NASA Astrophysics Data System (ADS)

Naylor, S.; Gustin, A. R.; Ellett, K. M.

2012-12-01

Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.

2008-01-01

Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.

Within-field variability of plant and soil parameters

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Brisco, B.; Dobson, C.

1981-01-01

The variability of ground truth data collected for vegetation experiments was investigated. Two fields of wheat and one field of corn were sampled on two different dates. The variability of crop and soil parameters within a field, between two fields of the same type, and within a field over time were compared statistically. The number of samples from each test site required in order to be able to determine with confidence the mean and standard deviations for a given variable was determined. Eight samples were found to be adequate for plant height determinations, while twenty samples were required for plant moisture and soil moisture characterization. Eighteen samples were necessary for detecting within field variability over time and for between field variability for the same crop. The necessary sample sites vary according to the physiological growth stage of the crop and recent weather events that affect the moisture and/or height characteristics of the field in question.