Effects of rainfall partitioning in the seasonal and spatial variability of soil water content in a Mediterranean downy oak forest

NASA Astrophysics Data System (ADS)

Garcia-Estringana, P.; Latron, J.; Molina, A. J.; Llorens, P.

2012-04-01

Rainfall partitioning fluxes (throughfall and stemflow) have a large degree of temporal and spatial variability and may consequently lead to significant changes in the volume and composition of water that reach the understory and the soil. The objective of this work is to study the effect of rainfall partitioning on the seasonal and spatial variability of the soil water content in a Mediterranean downy oak forest (Quercus pubescens), located in the Vallcebre research catchments (42° 12'N, 1° 49'E). The monitoring design, started on July 2011, consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. One hundred hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover, in leaf and leafless periods, as well as biometric characteristics of the plot, are also regularly measured. This work presents the first results describing throughfall and soil moisture spatial variability during both the leaf and leafless periods. The main drivers of throughfall variability, as canopy structure and meteorological conditions are also analysed.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

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.

SPATIAL AND TEMPORAL VARIABILITY AND DRIVERS OF NET ECOSYSTEM METABOLISM IN WESTERN GULF OF MEXICO ESTUARIES

EPA Science Inventory

Net ecosystem metabolism (NEM) is becoming a commonly used ecological indicator of estuarine ecosystem metabolic rates. Estuarine ecosystem processes are spatially and temporally variable, but the corresponding variability in NEM has not been properly assessed. Spatial and temp...

Temporal and spatial variability in North Carolina piedmont stream temperature

Treesearch

J.L. Boggs; G. Sun; S.G. McNulty; W. Swartley; Treasure E.; W. Summer

2009-01-01

Understanding temporal and spatial patterns of in-stream temperature can provide useful information to managing future impacts of climate change on these systems. This study will compare temporal patterns and spatial variability of headwater in-stream temperature in six catchments in the piedmont of North Carolina in two different geological regions, Carolina slate...

Estimating spatial variations in water content of clay soils from time-lapse electrical conductivity surveys

USDA-ARS?s Scientific Manuscript database

Soil water content (theta) is one of the most important drivers for many biogeochemical fluxes at different temporal and spatial scales. Hydrogeophysical non-invasive sensors that measure the soil apparent electrical conductivity (ECa) have been widely used to infer spatial and temporal patterns of...

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2010-01-01

Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

Spatial and temporal variability of soil moisture on the field with and without plants*

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Usowicz, J. B.

2012-04-01

Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * 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", AO-3275.

Simultaneous application of multiple platforms (Glider, Scanfish, profiling mooring, CTD) to improve detection and quantification of temporal ocean dynamics

NASA Astrophysics Data System (ADS)

Meyer, D.; Prien, R. D.; Lips, U.; Naumann, M.; Liblik, T.; Schulz-Bull, D. E.

2016-02-01

Ocean dynamics are difficult to observe given the broad spectrum of temporal and spatial scales. Robotic technology can be used to address this issue, and help to investigate the variability of physical and biogeochemical processes. This work focuses on ocean robots and in particular on glider technology which seems to be one of the most promising oceanographic tools for future marine research. In this context, we present the results of an observational program conducted in the Baltic Sea combining a profiling mooring (GODESS - Gotland Deep Environmental Sampling Station) and glider technology (Slocum). The temporal variability is captured by the mooring, while the spatial variability is obtained from the glider sampling the surrounding area. Furthermore, classical CTD-measurements and an underwater vehicle (Scanfish) are used simultaneously by two different research vessels to validate and complement the observing network. The main aim of the study is to identify possible synergies between the different platforms and to get a better understanding of maximizing the information content of the data collected by this network. The value and the quality of the data of each individual platform is analyzed and their contribution to the performance of the network itself evaluated.

Spatial variability in the soil water content of a Mediterranean agroforestry system with high soil heterogeneity

NASA Astrophysics Data System (ADS)

Molina, Antonio Jaime; Llorens, Pilar; Aranda, Xavier; Savé, Robert; Biel, Carmen

2013-04-01

Variability of soil water content is known to increase with the size of spatial domain in which measurements are taken. At field scale, heterogeneity in soil, vegetation, topography, water input volume and management affects, among other factors, hydrologic plot behaviour under different mean soil water contents. The present work studies how the spatial variability of soil water content (SWC) is affected by soil type (texture, percentage of stones and the combination of them) in a timber-orientated plantation of cherry tree (Prunus avium) under Mediterranean climatic conditions. The experimental design is a randomized block one with 3 blocks * 4 treatments, based on two factors: irrigation (6 plots irrigated versus 6 plots not irrigated) and soil management (6 plots tillaged versus 6 plots not tillaged). SWC is continuously measured at 25, 50 and 100 cm depth with FDR sensors, located at two positions in each treatment: under tree influence and 2.5 m apart. This study presents the results of the monitoring during 2012 of the 24 sensors located at the 25 cm depth. In each of the measurement point, texture and percentage of stones were measured. Sandy-loam, sandy-clay-loam and loam textures were found together with a percentage of stones ranging from 20 to 70 %. The results indicated that the relationship between the daily mean SWC and its standard deviation, a common procedure used to study spatial variability, changed with texture, percentage of stones and the estimation of field capacity from the combination of both. Temporal stability analysis of SWC showed a clear pattern related to field capacity, with the measurement points of the sandy-loam texture and the high percentage of stones showing the maximun negative diference with the global mean. The high range in the mean relative difference observed (± 75 %), could indicate that the studied plot may be considered as a good field-laboratory to extrapolate results at higher spatial scales. Furthermore, the pattern in the temporal stability of tree growth was clearly related to that one in SWC. Nevertheless, the treatments that represent the mean conditions in growth were not exactly the same than those in SWC, which could be attributable to other characteristics than soil.

Spatio-temporal Variability of Stratified Snowpack Cold Content Observed in the Rocky Mountains

NASA Astrophysics Data System (ADS)

Schmidt, J. S.; Sexstone, G. A.; Serreze, M. C.

2017-12-01

Snowpack cold content (CCsnow) is the energy required to bring a snowpack to an isothermal temperature of 0.0°C. The spatio-temporal variability of CCsnow is complex as it is a measure that integrates the response of a snowpack to each component of the snow-cover energy balance. Snow and ice at high elevation is climate sensitive water storage for the Western U.S. Therefore, an improved understanding of the spatio-temporal variability of CCsnow may provide insight into snowpack dynamics and sensitivity to climate change. In this study, stratified snowpit observations of snow water equivalent (SWE) and snow temperature (Tsnow) from the USGS Rocky Mountain Snowpack network (USGS RMS) were used to evaluate vertical CCsnow profiles over a 16-year period in Montana, Idaho, Wyoming, Colorado and New Mexico. Since 1993, USGS RMS has collected snow chemistry, snow temperature, and SWE data throughout the Rocky Mountain region, making it well positioned for Anthropocene cryosphere benchmarking and climate change interpretation. Spatial grouping of locations based on similar CCsnow characteristics was evaluated and trend analyses were performed. Additionally, we evaluated the regional relation of CCsnow to snowmelt timing. CCsnow was more precisely calculated and more representative using vertically stratified field observed values than bulk values, which highlights the utility of the snowpack dataset presented here. Location specific annual and 16 year mean stratified snowpit profiles of SWE, Tsnow, and CCsnow well represent the physical geography and past weather patterns acting on the snowpack. Observed trends and spatial variability of CCsnow profiles explored by this study provides an improved understanding of changing snowpack behavior in the western U.S., and will be useful for assessing the regional sensitivity of snowpacks to future climate change.

Spatial and temporal variability of guinea grass (Megathyrsus maximus) fuel loads and moisture on Oahu, Hawaii

Treesearch

Lisa M. Ellsworth; Creighton M. Litton; Andrew D. Taylor; J. Boone Kauffman

2013-01-01

Frequent wildfires in tropical landscapes dominated by non-native invasive grasses threaten surrounding ecosystems and developed areas. To better manage fire, accurate estimates of the spatial and temporal variability in fuels are urgently needed. We quantified the spatial variability in live and dead fine fuel loads and moistures at four guinea grass (...

Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data

USGS Publications Warehouse

Li, Yan; Wagner, Tyler; Jiao, Yan; Lorantas, Robert M.; Murphy, Cheryl

2018-01-01

Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.

Spatial and temporal variation of moisture content in the soil profiles of two different agricultural fields of semi-arid region.

PubMed

Baskan, Oguz; Kosker, Yakup; Erpul, Gunay

2013-12-01

Modeling spatio-temporal variation of soil moisture with depth in the soil profile plays an important role for semi-arid crop production from an agro-hydrological perspective. This study was performed in Guvenc Catchment. Two soil series that were called Tabyabayir (TaS) and Kervanpinari (KeS) and classified as Leptosol and Vertisol Soil Groups were used in this research. The TeS has a much shallower (0-34 cm) than the KeS (0-134 cm). At every sampling time, a total of geo-referenced 100 soil moisture samples were taken based on horizon depths. The results indicated that soil moisture content changed spatially and temporally with soil texture and profile depth significantly. In addition, land use was to be important factor when soil was shallow. When the soil conditions were towards to dry, higher values for the coefficient of variation (CV) were observed for TaS (58 and 43% for A and C horizons, respectively); however, the profile CV values were rather stable at the KeS. Spatial variability range of TaS was always higher at both dry and wet soil conditions when compared to that of KeS. Excessive drying of soil prevented to describe any spatial model for surface horizon, additionally resulting in a high nugget variance in the subsurface horizon for the TaS. On the contrary to TaS, distribution maps were formed all horizons for the KeS at any measurement times. These maps, depicting both dry and wet soil conditions through the profile depth, are highly expected to reduce the uncertainty associated with spatially and temporally determining the hydraulic responses of the catchment soils.

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

PubMed

Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Integrating spatial and temporal variability into the analysis of fish food web linkages in Tijuana Estuary.

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

West, Janelle M.; Williams, Greg D.; Madon, Sharook P.

2003-05-14

Our understanding of fish feeding interactions at Tijuana Estuary was improved by incorporating estimates of spatial and temporal variability into diet analyses. We examined the stomach contents of 7 dominant species (n=579 total fish) collected between 1994 and 1999. General feeding patterns pooled over time produced a basic food web consisting of 3 major trophic levels: (1) primary consumers (Atherinops affinis, Mugil cephalus) that ingested substantial amounts of plant material and detritus; (2) benthic carnivores (Clevelandia ios, Hypsopsetta guttulata, Gillichthys mirabilis, and Fundulus parvipinnis) that ingested high numbers of calanoid copepods and exotic amphipods (Grandidierella japonica); and (3) piscivores (Paralichthysmore » californicus and Leptocottus armatus) that often preyed on smaller gobiids. Similarity-based groupings of individual species' diets were identified using nonmetric multidimensional scaling to characterize their variability within and between species, and in s pace and time. This allowed us to identify major shifts and recognize events (i.e., modified prey abundance during 1997-98 El Nino floods) that likely caused these shifts.« less

Spatial and temporal analysis of the total electron content over China during 2011-2014

NASA Astrophysics Data System (ADS)

Zheng, Jianchang; Zhao, Biqiang; Xiong, Bo; Wan, Weixing

2016-06-01

In the present work we investigate variations of ionospheric total electron content (TEC) with empirical orthogonal function (EOF) analysis, the four-year TEC data are derived from ∼250 GPS observations of the crustal movement observation network of China (CMONOC) over East Asian area (30-55°N, 70-140°E) during the period from 2011, January to 2014, December. The first two EOF components together account for ∼93.78% of total variance of the original TEC data set, and it is found that the first EOF component represents a spatial variability of semi-annual variation and the second EOF component exhibits pronounced east-west longitudinal difference with respect to zero valued geomagnetic declination line. In addition, climatology of the vertical plasma drift velocity vdz induced by HWM zonal wind field (∼300 km) are studied in the paper. Results shows vdz displays significant east-west longitudinal difference at 10:00 LT and 20:00 LT, and its daytime temporal variation is consistent with the second EOF principal component, which suggests that the east-west longitudinal variability is partly caused by the thermospheric zonal wind and geomagnetic declination. It is expected that with this dense GPS network, local ionospheric variability can be described more accurately and a more realistic ionospheric model can be constructed and used for the satellite navigation and radio propagation.

Temporal and spatial variability of wind resources in the United States as derived from the Climate Forecast System Reanalysis

Treesearch

Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman

2015-01-01

This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the...

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Soil internal drainage: temporal stability and spatial variability in succession bean-black oat

NASA Astrophysics Data System (ADS)

Salvador, M. M. S.; Libardi, P. L.; Moreira, N. B.; Sousa, H. H. F.; Neiverth, C. A.

2012-04-01

There are a variety of studies considering the soil water content, but those who consider the flow of water, which are translated by deep drainage and capillary rise are scarce, especially those who assess their spatio-temporal variability, due to its laborious obtaining. Large areas have been considered homogeneous, but show considerable spatial variability inherent in the soil, causing the appearance of zones of distinct physical properties. In deep, sandy soils where the groundwater level is far below the root zone of interference, internal drainage is one of the factors limiting the supply of water to the soil surface, and possibly one of the biggest factors that determines what kinds satisfactory development of plants present in a given landscape. The forms of relief may also be indicators of changes in soil properties, because this variability is caused by small changes that affect the slope of the pedogenetic processes and the transport and storage of water in the soil profile, i.e., the different trajectories of water flow in different forms of the landscape, is the cause of variability. The objectives of this research were: i) evaluate the spatial and temporal stability of internal soil water drainage in a place near and another distant from the root system in a bean-black-oat succession and ii) verify their spatial variability in relation to relief. With the hydraulic conductivity obtained by the instantaneous profile method and the total potential gradient obtained from the difference in readings of tensiometers installed at depths of 0.35 and 0.45 and 0.75 and 0.85 m in 60 sampling points totaling 1680 and 1200 observations during the cultivation of beans and oats, respectively, was obtained so the internal drainage / capillary rise through the Darcy-Buckingham equation. To evaluate the temporal stability the method used was the relative difference and Spearman correlation test and the spatial variability was analyzed as geostatistical methodology. During the period when the water flow in soil is higher, there is strong temporal stability in the depth of 0.40 m, which is the opposite for the periods of drying. The lowest relative difference and standard deviation for the internal drainage obtained during the cultivation of beans and depth of 0.40 m confirm the hypothesis that the research carried out during periods of soil water recharge have less variability than those in the drying period. Temporal stability was due to the topographic position of selected points, since the points chosen for the depth of 0.40 m in both growing seasons, are located on the lower portion of the relief, and the nominees for the depth of 0,80 m, the highest portion. There were differences in the spatial pattern of water flow in the soil along the crop succession, i.e. the seasonal demand for water by plants and evaporation from the soil at the time of drying, changed their distribution model with internal drainage phases and stages capillary rise.

Spatial-temporal and cancer risk assessment of selected hazardous air pollutants in Seattle.

PubMed

Wu, Chang-fu; Liu, L-J Sally; Cullen, Alison; Westberg, Hal; Williamson, John

2011-01-01

In the Seattle Air Toxics Monitoring Pilot Program, we measured 15 hazardous air pollutants (HAPs) at 6 sites for more than a year between 2000 and 2002. Spatial-temporal variations were evaluated with random-effects models and principal component analyses. The potential health risks were further estimated based on the monitored data, with the incorporation of the bootstrapping technique for the uncertainty analysis. It is found that the temporal variability was generally higher than the spatial variability for most air toxics. The highest temporal variability was observed for tetrachloroethylene (70% temporal vs. 34% spatial variability). Nevertheless, most air toxics still exhibited significant spatial variations, even after accounting for the temporal effects. These results suggest that it would require operating multiple air toxics monitoring sites over a significant period of time with proper monitoring frequency to better evaluate population exposure to HAPs. The median values of the estimated inhalation cancer risks ranged between 4.3 × 10⁻⁵ and 6.0 × 10⁻⁵, with the 5th and 95th percentile levels exceeding the 1 in a million level. VOCs as a whole contributed over 80% of the risk among the HAPs measured and arsenic contributed most substantially to the overall risk associated with metals. Copyright © 2010 Elsevier Ltd. All rights reserved.

Spatial and temporal variability in rates of landsliding in seismically active mountain ranges

NASA Astrophysics Data System (ADS)

Parker, R.; Petley, D.; Rosser, N.; Densmore, A.; Gunasekera, R.; Brain, M.

2012-04-01

Where earthquake and precipitation driven disasters occur in steep, mountainous regions, landslides often account for a large proportion of the associated damage and losses. This research addresses spatial and temporal variability in rates of landslide occurrence in seismically active mountain ranges as a step towards developing better regional scale prediction of losses in such events. In the first part of this paper we attempt to explain reductively the variability in spatial rates of landslide occurrence, using data from five major earthquakes. This is achieved by fitting a regression-based conditional probability model to spatial probabilities of landslide occurrence, using as predictor variables proxies for spatial patterns of seismic ground motion and modelled hillslope stability. A combined model for all earthquakes performs well in hindcasting spatial probabilities of landslide occurrence as a function of readily-attainable spatial variables. We present validation of the model and demonstrate the extent to which it may be applied globally to derive landslide probabilities for future earthquakes. In part two we examine the temporal behaviour of rates of landslide occurrence. This is achieved through numerical modelling to simulate the behaviour of a hypothetical landscape. The model landscape is composed of hillslopes that continually weaken, fail and reset in response to temporally-discrete forcing events that represent earthquakes. Hillslopes with different geometries require different amounts of weakening to fail, such that they fail and reset at different temporal rates. Our results suggest that probabilities of landslide occurrence are not temporally constant, but rather vary with time, irrespective of changes in forcing event magnitudes or environmental conditions. Various parameters influencing the magnitude and temporal patterns of this variability are identified, highlighting areas where future research is needed. This model has important implications for landslide hazard and risk analysis in mountain areas as existing techniques usually assume that susceptibility to failure does not change with time.

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.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

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.

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

NASA Astrophysics Data System (ADS)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA).

PubMed

Reichenau, Tim G; Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI.

Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PubMed Central

Korres, Wolfgang; Montzka, Carsten; Fiener, Peter; Wilken, Florian; Stadler, Anja; Waldhoff, Guido; Schneider, Karl

2016-01-01

The ratio of leaf area to ground area (leaf area index, LAI) is an important state variable in ecosystem studies since it influences fluxes of matter and energy between the land surface and the atmosphere. As a basis for generating temporally continuous and spatially distributed datasets of LAI, the current study contributes an analysis of its spatial variability and spatial structure. Soil-vegetation-atmosphere fluxes of water, carbon and energy are nonlinearly related to LAI. Therefore, its spatial heterogeneity, i.e., the combination of spatial variability and structure, has an effect on simulations of these fluxes. To assess LAI spatial heterogeneity, we apply a Comprehensive Data Analysis Approach that combines data from remote sensing (5 m resolution) and simulation (150 m resolution) with field measurements and a detailed land use map. Test area is the arable land in the fertile loess plain of the Rur catchment on the Germany-Belgium-Netherlands border. LAI from remote sensing and simulation compares well with field measurements. Based on the simulation results, we describe characteristic crop-specific temporal patterns of LAI spatial variability. By means of these patterns, we explain the complex multimodal frequency distributions of LAI in the remote sensing data. In the test area, variability between agricultural fields is higher than within fields. Therefore, spatial resolutions less than the 5 m of the remote sensing scenes are sufficient to infer LAI spatial variability. Frequency distributions from the simulation agree better with the multimodal distributions from remote sensing than normal distributions do. The spatial structure of LAI in the test area is dominated by a short distance referring to field sizes. Longer distances that refer to soil and weather can only be derived from remote sensing data. Therefore, simulations alone are not sufficient to characterize LAI spatial structure. It can be concluded that a comprehensive picture of LAI spatial heterogeneity and its temporal course can contribute to the development of an approach to create spatially distributed and temporally continuous datasets of LAI. PMID:27391858

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Structure of mangrove meiofaunal assemblages associated with local sediment conditions in subtropical eastern australia

NASA Astrophysics Data System (ADS)

Abdullah, Maizah M.; Lee, S. Y.

2017-11-01

Meiofauna are ubiquitous but poorly-studied components of soft-bottom marine habitats around the world, including mangroves. The dynamic environmental conditions and heterogeneous sediments of mangroves present challenges to understanding the structure of mangrove meiofaunal assemblages at various spatial and temporal scales. In this study, we investigated the meiofaunal assemblage structure of sediments colonised by three mangrove species, namely, Avicennia marina, Rhizophora stylosa and Aegiceras corniculatum, at three locations in subtropical eastern Australia. Spatial and temporal variations were tested by sampling at the three mangrove locations (i.e. Tallebudgera, Currumbin and Terranora) in autumn, with samplings repeated at Tallebudgera at two other times broadly representing during dry/cool winter and wet/hot summer seasons. We examined the variability of the sediment environments within each of the different mangrove species, and investigated how meiofaunal assemblages would respond to the particular changes in their habitats to result in differences in assemblage structure between and within sites. Total meiofaunal density was highest in Tallebudgera and Currumbin and lowest in Terranora (mean density of 424, 393 and 239 ind.10 cm-2, respectively). In Tallebudgera, the density was higher in winter and summer (mean density of 546 and 530 ind.10 cm-2, respectively). The meiofaunal assemblage in this study shows a trend and association with the environmental variables. High availability of food proxies such phaeopigments, Chl a or TOC, with moderate tannin content and appropriate habitat structure (sediment particle size, belowground root biomass and/or moisture content provide the best condition for the meiofauna to achieve the highest density. However, given the complex dynamic habitats and the spatial heterogeneity of the mangrove environments across different locations and seasons, no clear generalization could be made regarding the key environmental variables that predominantly shape the meiofaunal assemblages' structure.

Footprint radius of a cosmic-ray neutron probe for measuring soil-water content and its spatiotemporal variability in an alpine meadow ecosystem

NASA Astrophysics Data System (ADS)

Zhu, Xuchao; Cao, Ruixue; Shao, Mingan; Liang, Yin

2018-03-01

Cosmic-ray neutron probes (CRNPs) have footprint radii for measuring soil-water content (SWC). The theoretical radius is much larger at high altitude, such as the northern Tibetan Plateau, than the radius at sea level. The most probable practical radius of CRNPs for the northern Tibetan Plateau, however, is not known due to the lack of SWC data in this hostile environment. We calculated the theoretical footprint of the CRNP based on a recent simulation and analyzed the practical radius of a CRNP for the northern Tibetan Plateau by measuring SWC at 113 sampling locations on 21 measuring occasions to a depth of 30 cm in a 33.5 ha plot in an alpine meadow at 4600 m a.s.l. The temporal variability and spatial heterogeneity of SWC within the footprint were then analyzed. The theoretical footprint radius was between 360 and 420 m after accounting for the influences of air humidity, soil moisture, vegetation and air pressure. A comparison of SWCs measured by the CRNP and a neutron probe from access tubes in circles with different radii conservatively indicated that the most probable experimental footprint radius was >200 m. SWC within the CRNP footprint was moderately variable over both time and space, but the temporal variability was higher. Spatial heterogeneity was weak, but should be considered in future CRNP calibrations. This study provided theoretical and practical bases for the application and promotion of CRNPs in alpine meadows on the Tibetan Plateau.

Soil Temperature Variability in Complex Terrain measured using Distributed a Fiber-Optic Distributed Temperature Sensing

NASA Astrophysics Data System (ADS)

Seyfried, M. S.; Link, T. E.

2013-12-01

Soil temperature (Ts) exerts critical environmental controls on hydrologic and biogeochemical processes. Rates of carbon cycling, mineral weathering, infiltration and snow melt are all influenced by Ts. Although broadly reflective of the climate, Ts is sensitive to local variations in cover (vegetative, litter, snow), topography (slope, aspect, position), and soil properties (texture, water content), resulting in a spatially and temporally complex distribution of Ts across the landscape. Understanding and quantifying the processes controlled by Ts requires an understanding of that distribution. Relatively few spatially distributed field Ts data exist, partly because traditional Ts data are point measurements. A relatively new technology, fiber optic distributed temperature system (FO-DTS), has the potential to provide such data but has not been rigorously evaluated in the context of remote, long term field research. We installed FO-DTS in a small experimental watershed in the Reynolds Creek Experimental Watershed (RCEW) in the Owyhee Mountains of SW Idaho. The watershed is characterized by complex terrain and a seasonal snow cover. Our objectives are to: (i) evaluate the applicability of fiber optic DTS to remote field environments and (ii) to describe the spatial and temporal variability of soil temperature in complex terrain influenced by a variable snow cover. We installed fiber optic cable at a depth of 10 cm in contrasting snow accumulation and topographic environments and monitored temperature along 750 m with DTS. We found that the DTS can provide accurate Ts data (+/- .4°C) that resolves Ts changes of about 0.03°C at a spatial scale of 1 m with occasional calibration under conditions with an ambient temperature range of 50°C. We note that there are site-specific limitations related cable installation and destruction by local fauna. The FO-DTS provide unique insight into the spatial and temporal variability of Ts in a landscape. We found strong seasonal trends in Ts variability controlled by snow cover and solar radiation as modified by topography. During periods of spatially continuous snow cover Ts was practically homogeneous throughout. In the absence of snow cover, Ts is highly variable, with most of the variability attributable to different topographic units defined by slope and aspect. During transition periods when snow melts out, Ts is highly variable within the watershed and within topographic units. The importance of accounting for these relatively small scale effects is underscored by the fact that the overall range of Ts in study area 600 m long is similar to that of the much large RCEW with 900 m elevation gradient.

Variability of Soil Temperature: A Spatial and Temporal Analysis.

ERIC Educational Resources Information Center

Walsh, Stephen J.; And Others

1991-01-01

Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

Analysis of the spatial and temporal variability of terrestrial water storage and snowpack in the Pacific Northwestern United States

EPA Science Inventory

The spatial and temporal variability of terrestrial water storage and snowpack in the Pacific Northwest (PNW) was analyzed for water years 2001–2010 using measurements from the Gravity Recovery and Climate Experiment (GRACE) instrument. GRACE provides remotely-sensed measurements...

Spatial and Temporal Monitoring of Dissolved Oxygen in NJ Coastal Waters using AUVs (Presentation)

EPA Science Inventory

The coastal ocean is a highly variable system with processes that have significant implications on the hydrographic and oxygen characteristics of the water column. The spatial and temporal variability of these fields can cause dramatic changes to water quality and in turn the h...

SPATIAL AND TEMPORAL VARIABILITY IN ZOOPLANKTON COMMUNITY DYNAMICS IN THREE URBANIZED BAYOUS OF THE PENSACOLA BAY SYSTEM, FLORIDA, USA

EPA Science Inventory

Spatial and temporal patterns in zooplankton community composition and abundance in near-coastal areas of the Gulf of Mexico are not well understood. This survey provides information on spatial and temporal differences in zoolplankton community composition and abundance for a coa...

Optimal Spectral Decomposition (OSD) for Ocean Data Assimilation

DTIC Science & Technology

2015-01-01

tropical North Atlantic from the Argo float data (Chu et al. 2007 ), and temporal and spatial variability of global upper-ocean heat content (Chu 2011...O. V. Melnichenko, and N. C. Wells, 2007 : Long baro- clinic Rossby waves in the tropical North Atlantic observed fromprofiling floats. J...Harrison, and D. Stammer , D., Eds., Vol. 2, ESA Publ. WPP- 306, doi:10.5270/OceanObs09.cwp.86. Tang, Y., and R. Kleeman, 2004: SST assimilation

Investigating carbon flux variability in subtropical peat soils of the Everglades using hydrogeophysical methods

NASA Astrophysics Data System (ADS)

Comas, Xavier; Wright, William

2014-08-01

The spatial and temporal variability in accumulation and release of greenhouse gases (mainly methane and carbon dioxide) to the atmosphere from peat soils remains very uncertain. The use of near-surface geophysical methods such as ground penetrating radar (GPR) has proven useful during the last decade to expand scales of measurement as related to in situ gas distribution and dynamics beyond traditional methods (i.e., gas chambers). However, this approach has focused exclusively on boreal peatlands, while no studies in subtropical systems like the Everglades using these techniques exist. In this paper GPR is combined with gas traps, time-lapse cameras, gas chromatography, and surface deformation measurements to explore biogenic gas dynamics (mainly gas buildup and release) in two locations in the Everglades. Similar to previous studies in northern peatlands, our data in the Everglades show a statistically significant correlation between the following: (1) GPR-estimated gas content and gas fluxes, (2) GPR-estimated gas content and surface deformation, and (3) atmospheric pressure and both GPR-estimated gas content and gas flux. From these results several gas-releasing events ranging between 33.8 and 718.8 mg CH4 m-2 d-1 were detected as identified by the following: (1) decreases in GPR-estimated gas content within the peat matrix, (2) increases in gas fluxes captured by gas traps and time-lapse cameras, and (3) decreases in surface deformation. Furthermore, gas-releasing events corresponded to periods of high atmospheric pressure. Changes in gas accumulation and release were attributed to differences in seasonality and peat soil type between sites. These results suggest that biogenic gas releases in the Everglades are spatially and temporarily variable. For example, flux events measured at hourly scales were up to threefold larger when compared to daily fluxes, therefore suggesting that flux measurements decline when averaged over longer time spans. This research therefore questions what the appropriate spatial and temporal scale of measurement is necessary to properly capture the dynamics of biogenic gas release in subtropical peat soils.

Groundwater-fed irrigation impacts spatially distributed temporal scaling behavior of the natural system: a spatio-temporal framework for understanding water management impacts

NASA Astrophysics Data System (ADS)

Condon, Laura E.; Maxwell, Reed M.

2014-03-01

Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.

Application of a fully integrated surface-subsurface physically based flow model for evaluating groundwater recharge from a flash flood event

NASA Astrophysics Data System (ADS)

Pino, Cristian; Herrera, Paulo; Therrien, René

2017-04-01

In many arid regions around the world groundwater recharge occurs during flash floods. This transient spatially and temporally concentrated flood-recharge process takes place through the variably saturated zone between surface and usually the deep groundwater table. These flood events are characterized by rapid and extreme changes in surface flow depth and velocity and soil moisture conditions. Infiltration rates change over time controlled by the hydraulic gradients and the unsaturated hydraulic conductivity at the surface-subsurface interface. Today is a challenge to assess the spatial and temporal distribution of groundwater recharge from flash flood events under real field conditions at different scales in arid areas. We apply an integrated surface-subsurface variably saturated physically-based flow model at the watershed scale to assess the recharge process during and after a flash flood event registered in an arid fluvial valley in Northern Chile. We are able to reproduce reasonably well observed groundwater levels and surface flow discharges during and after the flood with a calibrated model. We also investigate the magnitude and spatio-temporal distribution of recharge and the response of the system to variations of different surface and subsurface parameters, initial soil moisture content and groundwater table depths and surface flow conditions. We demonstrate how an integrated physically based model allows the exploration of different spatial and temporal system states, and that the analysis of the results of the simulations help us to improve our understanding of the recharge processes in similar type of systems that are common to many arid areas around the world.

Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard

NASA Astrophysics Data System (ADS)

Hubbard, S.; Pierce, L.; Grote, K.; Rubin, Y.

2003-12-01

Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.

Spatial and Temporal Monitoring of Dissolved Oxygen (DO) in New Jersey Coastal Waters Using Autonomous Gliders

EPA Science Inventory

The coastal ocean is a highly variable system with processes that have significant implications on the hydrographic and oxygen characteristics of the water column. The spatial and temporal variability of these fields can cause dramatic changes to water quality and in turn the h...

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

Price, Bronwyn; McAlpine, Clive A; Kutt, Alex S; Ward, Doug; Phinn, Stuart R; Ludwig, John A

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

Price, Bronwyn; McAlpine, Clive A.; Kutt, Alex S.; Ward, Doug; Phinn, Stuart R.; Ludwig, John A.

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1–100 ha) and landscape (100–1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes. PMID:24066138

Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

PubMed

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-11-01

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

PubMed Central

Batterman, Stuart

2015-01-01

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21, 33, 24 and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than noncommercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity. PMID:26688671

Phytoplankton plasticity drives large variability in carbon fixation efficiency

NASA Astrophysics Data System (ADS)

Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier

2014-12-01

Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

Growns, Ivor; Astles, Karen; Gehrke, Peter

2006-03-01

We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.

Extreme precipitation variability, forage quality and large herbivore diet selection in arid environments

USGS Publications Warehouse

Cain, James W.; Gedir, Jay V.; Marshal, Jason P.; Krausman, Paul R.; Allen, Jamison D.; Duff, Glenn C.; Jansen, Brian; Morgart, John R.

2017-01-01

Nutritional ecology forms the interface between environmental variability and large herbivore behaviour, life history characteristics, and population dynamics. Forage conditions in arid and semi-arid regions are driven by unpredictable spatial and temporal patterns in rainfall. Diet selection by herbivores should be directed towards overcoming the most pressing nutritional limitation (i.e. energy, protein [nitrogen, N], moisture) within the constraints imposed by temporal and spatial variability in forage conditions. We investigated the influence of precipitation-induced shifts in forage nutritional quality and subsequent large herbivore responses across widely varying precipitation conditions in an arid environment. Specifically, we assessed seasonal changes in diet breadth and forage selection of adult female desert bighorn sheep Ovis canadensis mexicana in relation to potential nutritional limitations in forage N, moisture and energy content (as proxied by dry matter digestibility, DMD). Succulents were consistently high in moisture but low in N and grasses were low in N and moisture until the wet period. Nitrogen and moisture content of shrubs and forbs varied among seasons and climatic periods, whereas trees had consistently high N and moderate moisture levels. Shrubs, trees and succulents composed most of the seasonal sheep diets but had little variation in DMD. Across all seasons during drought and during summer with average precipitation, forages selected by sheep were higher in N and moisture than that of available forage. Differences in DMD between sheep diets and available forage were minor. Diet breadth was lowest during drought and increased with precipitation, reflecting a reliance on few key forage species during drought. Overall, forage selection was more strongly associated with N and moisture content than energy content. Our study demonstrates that unlike north-temperate ungulates which are generally reported to be energy-limited, N and moisture may be more nutritionally limiting for desert ungulates than digestible energy.

Ocean Spectral Data Assimilation Without Background Error Covariance Matrix

DTIC Science & Technology

2016-01-01

float data (Chu et al. 2007 ), and 97 temporal and spatial variability of the global upper ocean heat content (Chu 2011) from the data 98 of the Global...Melnichenko OV, Wells NC ( 2007 ) Long baroclinic Rossby waves in the 558 tropical North Atlantic observed from profiling floats. J Geophys Res...Hall, J, Harrison D.E. and Stammer , D., Eds., ESA Publication WPP-610 306. 611 612 Tang Y, Kleeman R (2004) SST assimilation experiments in a

A descriptive analysis of temporal and spatial patterns of variability in Puget Sound oceanographic properties

Treesearch

Stephanie Moore; Nathan J. Mantua; Jan A. Newton; Mitsuhiro Kawase; Mark J. Warner; Jonathan P. Kellogg

2008-01-01

Temporal and spatial patterns of variability in Puget Sound's oceanographic properties are determined using continuous vertical profile data from two long-term monitoring programs; monthly observations at 16 stations from 1993 to 2002, and biannual observations at 40 stations from 1998 to 2003. Climatological monthly means of temperature, salinity, and density...

Soil organic carbon dynamics as related to land use history in the northwestern Great Plains

USGS Publications Warehouse

Tan, Z.; Liu, S.; Johnston, C.A.; Loveland, Thomas R.; Tieszen, L.L.; Liu, J.; Kurtz, R.

2005-01-01

Strategies for mitigating the global greenhouse effect must account for soil organic carbon (SOC) dynamics at both spatial and temporal scales, which is usually challenging owing to limitations in data and approach. This study was conducted to characterize the SOC dynamics associated with land use change history in the northwestern Great Plains ecoregion. A sampling framework (40 sample blocks of 10 × 10 km2 randomly located in the ecoregion) and the General Ensemble Biogeochemical Modeling System (GEMS) were used to quantify the spatial and temporal variability in the SOC stock from 1972 to 2001. Results indicate that C source and sink areas coexisted within the ecoregion, and the SOC stock in the upper 20-cm depth increased by 3.93 Mg ha−1 over the 29 years. About 17.5% of the area was evaluated as a C source at 122 kg C ha−1 yr−1. The spatial variability of SOC stock was attributed to the dynamics of both slow and passive fractions, while the temporal variation depended on the slow fraction only. The SOC change at the block scale was positively related to either grassland proportion or negatively related to cropland proportion. We concluded that the slow C pool determined whether soils behaved as sources or sinks of atmospheric CO2, but the strength depended on antecedent SOC contents, land cover type, and land use change history in the ecoregion.

Audio-Visual Temporal Recalibration Can be Constrained by Content Cues Regardless of Spatial Overlap.

PubMed

Roseboom, Warrick; Kawabe, Takahiro; Nishida, Shin'ya

2013-01-01

It has now been well established that the point of subjective synchrony for audio and visual events can be shifted following exposure to asynchronous audio-visual presentations, an effect often referred to as temporal recalibration. Recently it was further demonstrated that it is possible to concurrently maintain two such recalibrated estimates of audio-visual temporal synchrony. However, it remains unclear precisely what defines a given audio-visual pair such that it is possible to maintain a temporal relationship distinct from other pairs. It has been suggested that spatial separation of the different audio-visual pairs is necessary to achieve multiple distinct audio-visual synchrony estimates. Here we investigated if this is necessarily true. Specifically, we examined whether it is possible to obtain two distinct temporal recalibrations for stimuli that differed only in featural content. Using both complex (audio visual speech; see Experiment 1) and simple stimuli (high and low pitch audio matched with either vertically or horizontally oriented Gabors; see Experiment 2) we found concurrent, and opposite, recalibrations despite there being no spatial difference in presentation location at any point throughout the experiment. This result supports the notion that the content of an audio-visual pair alone can be used to constrain distinct audio-visual synchrony estimates regardless of spatial overlap.

Audio-Visual Temporal Recalibration Can be Constrained by Content Cues Regardless of Spatial Overlap

PubMed Central

Roseboom, Warrick; Kawabe, Takahiro; Nishida, Shin’Ya

2013-01-01

It has now been well established that the point of subjective synchrony for audio and visual events can be shifted following exposure to asynchronous audio-visual presentations, an effect often referred to as temporal recalibration. Recently it was further demonstrated that it is possible to concurrently maintain two such recalibrated estimates of audio-visual temporal synchrony. However, it remains unclear precisely what defines a given audio-visual pair such that it is possible to maintain a temporal relationship distinct from other pairs. It has been suggested that spatial separation of the different audio-visual pairs is necessary to achieve multiple distinct audio-visual synchrony estimates. Here we investigated if this is necessarily true. Specifically, we examined whether it is possible to obtain two distinct temporal recalibrations for stimuli that differed only in featural content. Using both complex (audio visual speech; see Experiment 1) and simple stimuli (high and low pitch audio matched with either vertically or horizontally oriented Gabors; see Experiment 2) we found concurrent, and opposite, recalibrations despite there being no spatial difference in presentation location at any point throughout the experiment. This result supports the notion that the content of an audio-visual pair alone can be used to constrain distinct audio-visual synchrony estimates regardless of spatial overlap. PMID:23658549

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Spatial and temporal variability of throughfall and soil moisture in a deciduous forest in the low mountain ranges (Hesse, Germany)

NASA Astrophysics Data System (ADS)

Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin

2017-04-01

Spatial and temporal patterns of throughfall can affect the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying soil. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the soil moisture. Therefore, in the present study, the measurements of throughfall and soil moisture in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the soil moisture, 2) to examine the temporal stability of the spatial patterns of the throughfall and soil moisture and 3) relate the soil moisture patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for soil genesis is greywacke and clay shale from Devonian deposits. The soil type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the soil moisture (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each investigated parameter. The spearmen and pearson correlation coefficients were applied to detect the relationship between the different investigated parameters. First results show that the spatial variability of throughfall decreases if the total amount of the throughfall increases. The soil moisture shows a similar behavior. It`s spatial variability decreases if higher soil moisture values were measured. Concerning the temporal stability of throughfall it can be shown that it is very high during the leaf-free period, although the rainfall events have different total througfall amounts. The soil moisture patterns consists of a low temporal stability and additionally only during one event a significant correlations between throughfall and soil moisture patterns exists. This implies that other factors than the throughfall patterns control the spatial patterns of soil moisture.

Chlorophyll dynamic accounts for spatial and temporal variabilities in terrestrial carbon uptake and evapotranspiration

NASA Astrophysics Data System (ADS)

Croft, H.; Luo, X.; Chen, J. M.

2017-12-01

Terrestrial carbon and water fluxes are driven by a range of abiotic and biotic factors. State-of-art terrestrial biosphere models (TBMs) use numerical representations of these factors in conjunction with concise descriptions of biogeochemical processes to estimate terrestrial fluxes (i.e. gross primary productivity (GPP) and evapotranspiration(ET)). Leaf maximum carboxylation rate (Vcmax25) is a key biotic factor prescribed in TBM to determine CO2 assimilation rates and leaf stomatal conductivity for water transport, but the paucity of its measurements has long plagued the simulation of fluxes. This study uses leaf chlorophyll content (LCC) derived from remotely sensed data to account for spatial and temporal variations in Vcmax25 within a TBM framework. Results from the TBM with and without LCC were validated against measurements from 124 eddy-covariance towers (554 site-years) of FLUXNET. TBM using LCC reduced the biases of estimated GPP in 61% of the site-years and 59% for ET, with especially large improvements for biomes with strong seasonal cycles (e.g. deciduous forest, croplands and grasslands). In addition to the Vcmax25 adjustment imposed by LCC seasonal patterns, the spatial variability of LCC acts as an equally important part in reducing the errors of estimated fluxes by capturing the spatial variations of Vcmax25, especially during the summer. This study presents the first case of integrating satellite-derived LCC into a TBM at the global scale. Our results demonstrate the critical role of LCC in describing the variabilities in the terrestrial carbon uptake and ET and the necessity of including LCC in future TBMs.

Temporal and spatial variability of dissolved organic and inorganic phosphorus, and metrics of phosphorus bioavailability in an upwelling-dominated coastal system

NASA Astrophysics Data System (ADS)

Ruttenberg, Kathleen C.; Dyhrman, Sonya T.

2005-10-01

High-frequency temporal and spatial shifts in the various dissolved P pools (total, inorganic, and organic) are linked to upwelling/relaxation events and to phytoplankton bloom dynamics in the upwelling-dominated Oregon coastal system. The presence and regulation of alkaline phosphatase activity (APA) is apparent in the bulk phytoplankton population and in studies of cell-specific APA using Enzyme Labeled Fluorescence (ELF®). Spatial and temporal variability are also evident in phytoplankton community composition and in APA. The spatial pattern of dissolved phosphorus and APA variability can be explained by bottom-controlled patterns of upwelling, and flushing times of different regions within the study area. The presence of APA in eukaryotic taxa indicates that dissolved organic phosphorus (DOP) may contribute to phytoplankton P nutrition in this system, highlighting the need for a more complete understanding of P cycling and bioavailability in the coastal ocean.

Biomonitoring approach with mussel Mytilus galloprovincialis (Lmk) and clam Ruditapes philippinarum (Adams and Reeve, 1850) in the Lagoon of Venice.

PubMed

Moschino, Vanessa; Delaney, Eugenia; Meneghetti, Francesca; Ros, Luisa Da

2011-06-01

Transplanted Mytilus galloprovincialis and native Ruditapes philippinarum were deployed in 10 sampling stations with different pollution impact within the Lagoon of Venice to evaluate the temporal variations and the suitability of the following cytochemical and histochemical biomarkers just as indicators of environmental stress: lysosomal membrane stability, lipofuscins, neutral lipids and lysosome to cytoplasm volume ratio. The physiological status of the organisms was also investigated by determining the survival in air capability and the reburrowing rate (clams). The biological parameters were assessed in June and October. Furthermore, for a better definition of the environmental aspects of the study sites, heavy metal, PAH and PCB concentrations were also evaluated in the sediments. As a whole, the biological responses examined in both species from all the sampling sites showed significant differences between the two seasonal campaigns, only lysosomal membrane stability exhibited less variability. Pollutants in sediments generally showed low-intermediate contamination levels, few hotspots persisting mostly in the inner areas of the lagoon, the most influenced by the industrial zone. Transplanted mussels were more responsive than native clams and the biological responses of both species varied temporally. The range of the spatial variability was always narrow and reflected only partially the broader variability shown by the chemical content in the sediments. In this sense, biological responses seemed to be particularly influenced by the high temporal and spatial heterogeneity that characterise the Lagoon of Venice, as well as most of the transitional environments.

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

Sea-level rise impacts on the temporal and spatial variability of extreme water levels: A case study for St. Peter-Ording, Germany

NASA Astrophysics Data System (ADS)

Santamaria-Aguilar, S.; Arns, A.; Vafeidis, A. T.

2017-04-01

Both the temporal and spatial variability of storm surge water level (WL) curves are usually not taken into account in flood risk assessments as observational data are often scarce. In addition, sea-level rise (SLR) can further affect the variability of WLs. We analyze the temporal and spatial variability of the WL curve of 75 historical storm surge events that have been numerically simulated for St. Peter-Ording at the German North Sea coast, considering the effects induced by three SLR scenarios (RCP 4.5, RCP 8.5, and a RCP 8.5 high end scenario). We assess potential impacts of these scenarios on two parameters related to flooding: overflow volumes and fullness. Our results indicate that due to both the temporal and spatial variability of those events the resulting overflow volume can be two or even three times greater. We observe a steepening of the WL curve with an increase of the tidal range under the three SLR scenarios, although SLR induced effects are relatively higher for the RCP 4.5. The steepening of the WL curve with SLR produces a reduction of the fullness, but the changes in overflow volumes also depend on the magnitude of the storm surge event.

Ocean carbon and heat variability in an Earth System Model

NASA Astrophysics Data System (ADS)

Thomas, J. L.; Waugh, D.; Gnanadesikan, A.

2016-12-01

Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.

Patterns in Temporal Variability of Temperature, Oxygen and pH along an Environmental Gradient in a Coral Reef

PubMed Central

Guadayol, Òscar; Silbiger, Nyssa J.; Donahue, Megan J.; Thomas, Florence I. M.

2014-01-01

Spatial and temporal environmental variability are important drivers of ecological processes at all scales. As new tools allow the in situ exploration of individual responses to fluctuations, ecologically meaningful ways of characterizing environmental variability at organism scales are needed. We investigated the fine-scale spatial heterogeneity of high-frequency temporal variability in temperature, dissolved oxygen concentration, and pH experienced by benthic organisms in a shallow coastal coral reef. We used a spatio-temporal sampling design, consisting of 21 short-term time-series located along a reef flat-to-reef slope transect, coupled to a long-term station monitoring water column changes. Spectral analyses revealed sharp gradients in variance decomposed by frequency, as well as differences between physically-driven and biologically-reactive parameters. These results highlight the importance of environmental variance at organismal scales and present a new sampling scheme for exploring this variability in situ. PMID:24416364

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Dielectric Constant products: (the dielectric constant products are delivered together with soil moisture products, with the same averaging periods and generation frequency): maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation.

Research on the degradation of tropical arable land soil: Part II. The distribution of soil nutrients in eastern part of Hainan Island

NASA Astrophysics Data System (ADS)

Wang, Dengfeng; Wei, Zhiyuan; Qi, Zhiping

Research on the temporal and spatial distribution of soil nutrients in tropical arable land is very important to promote the tropical sustainable agriculture development. Take the Eastern part of Hainan as research area, applying GIS spatial analysis technique, analyzing the temporal and spatial variation of soil N, P and K contents in arable land. The results indicate that the contents of soil N, P and K were 0.28%, 0.20% and 1.75% respectively in 2005. The concentrations of total N and P in arable land soil increased significantly from 1980s to 2005. The variances in contents of soil nutrients were closely related to the application of chemical fertilizers in recent years, and the uneven distribution of soil nutrient contents was a reflection of fertilizer application in research area. Fertilization can be planned based on the distribution of soil nutrients and the spatial analysis techniques, so as to sustain balance of soil nutrients contents.

Utility of computer simulations in landscape genetics

Treesearch

Bryan K. Epperson; Brad H. McRae; Kim Scribner; Samuel A. Cushman; Michael S. Rosenberg; Marie-Josee Fortin; Patrick M. A. James; Melanie Murphy; Stephanie Manel; Pierre Legendre; Mark R. T. Dale

2010-01-01

Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to...

Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.

Temporal, Spatial, and Spectral Variability at Ivanpah Playa Vicarious Calibration Site

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

Villa-Aleman, E.

2003-01-07

The Savannah River Technology Center (SRTC) conducted four reflectance vicarious calibrations at Ivanpah Playa, California since July 2000 in support of the MTI satellite. The multi-year study shows temporal, spatial and spectral variability at the playa. The temporal variability in the wavelength dependent reflectance and emissivity across the playa suggests a dependency with precipitation during the winter and early spring seasons. Satellite imagery acquired on September and November 2000, May 2001 and March 2002 in conjunction with ground truth during the September, May and March campaigns and water precipitation records were used to demonstrate the correlation observed at the playa

Size-frequency distribution, growth, and mortality of snow crab (Chionoecetes opilio) and arctic lyre crab (Hyas coarctatus) in the chukchi sea from 2009 to 2013

NASA Astrophysics Data System (ADS)

Groß, Jasmin; Konar, Brenda; Brey, Thomas; Grebmeier, Jacqueline M.

2017-10-01

The snow crab Chionoecetes opilio and Arctic lyre crab Hyas coarctatus are prominent members of the Chukchi Sea epifaunal community. A better understanding of their life history will aid in determining their role in this ecosystem in light of the changing climate and resource development. In this study, the size frequency distribution, growth, and mortality of these two crab species was examined in 2009, 2010, 2012, and 2013 to determine temporal and spatial patterns within the eastern Chukchi Sea, and to identify potential environmental drivers of the observed patterns. Temporally, the mean size of both sexes of C. opilio and H. coarctatus decreased significantly from 2009 to 2013, with the number of rare maximum sized organisms decreasing significantly to near absence in the latter two study years. Spatially, the mean size of male and female crabs of both species showed a latitudinal trend, decreasing from south to north in the investigation area. Growth of both sexes of C. opilio and H. coarctatus was linear over the sampled size range, and mortality was highest in the latter two study years. Life history features of both species related to different environmental parameters in different years, ranging from temperature, the sediment carbon to nitrogen ratio of the organic content, and sediment grain size distribution. Likely explanations for the observed temporal and spatial variability are ontogenetic migrations of mature crabs to warmer areas possibly due to cooler water temperatures in the latter two study years, or interannual fluctuations, which have been reported for C. opilio populations in other areas where successful waves of recruitment were estimated to occur in eight year intervals. Further research is suggested to determine if the spatial and temporal patterns found in this study are part of the natural variability in this system or if they are an indication of long-term trends.

High variability in spatial and temporal size-based trophodynamics of deep-sea fishes from the Mid-Atlantic Ridge elucidated by stable isotopes

NASA Astrophysics Data System (ADS)

Reid, William D. K.; Sweeting, Christopher J.; Wigham, Ben D.; McGill, Rona A. R.; Polunin, Nicholas V. C.

2013-12-01

Demersal fish play an important role in the deep-sea ecosystem by acting as a link to mobile food in the water column, consuming benthic fauna, breaking down large food parcels and dispersing organic matter over large areas. Poor diet resolution from stomach content analysis often impairs the ability to assess differences in inter- and intra-population trophodynamics and therefore understand resource partitioning among deep-sea fishes. Antimora rostrata (predator-scavenger), Coryphaenoides armatus (predator-scavenger), Coryphaenoides brevibarbis (predator) and Halosauropsis macrochir (predator) were collected from 3 stations on the Mid-Atlantic Ridge (MAR) in 2007 and 2009 to investigate trophic ecology using δ13C and δ15N. Variability in lipid-normalised δ13C (δ13Cn) and δ15N was explained by body length in all species but slope and significance of the isotope-length relationships varied both temporally and spatially. δ15N increases with length were observed in A. rostrata at all stations, C. brevibarbis and H. macrochir at one or more stations but were absent in C. armatus. δ13Cn increased with length in A. rostrata but the slope of δ13Cn-length relationships varied spatially and temporally in C. armatus and C. brevibarbis. The co-occurring δ13Cn and δ15N size-based trends in A. rostrata and H. macrochir suggested that size-based trends were a result of increasing trophic position. In C. armatus and C. brevibarbis the isotope-length trends were difficult to distinguish among trophic position increases, shifts in resource use i.e. benthic to pelagic or internal physiology. However, the overall strength, direction and significance of isotope-length trends varied temporally and spatially which suggested varying degrees of overlap in trophic ecology and feeding plasticity among these species.

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-...

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Variability in Spatially and Temporally Resolved Emissions and Hydrocarbon Source Fingerprints for Oil and Gas Sources in Shale Gas Production Regions.

PubMed

Allen, David T; Cardoso-Saldaña, Felipe J; Kimura, Yosuke

2017-10-17

A gridded inventory for emissions of methane, ethane, propane, and butanes from oil and gas sources in the Barnett Shale production region has been developed. This inventory extends previous spatially resolved inventories of emissions by characterizing the overall variability in emission magnitudes and the composition of emissions at an hourly time resolution. The inventory is divided into continuous and intermittent emission sources. Sources are defined as continuous if hourly averaged emissions are greater than zero in every hour; otherwise, they are classified as intermittent. In the Barnett Shale, intermittent sources accounted for 14-30% of the mean emissions for methane and 10-34% for ethane, leading to spatial and temporal variability in the location of hourly emissions. The combined variability due to intermittent sources and variability in emission factors can lead to wide confidence intervals in the magnitude and composition of time and location-specific emission inventories; therefore, including temporal and spatial variability in emission inventories is important when reconciling inventories and observations. Comparisons of individual aircraft measurement flights conducted in the Barnett Shale region versus the estimated emission rates for each flight from the emission inventory indicate agreement within the expected variability of the emission inventory for all flights for methane and for all but one flight for ethane.

Black Sea spectral bio-optical models based on satellite data and their applications for assessment of spatial and temporal variability in waters transparency, chlorophyll a content and primary production

NASA Astrophysics Data System (ADS)

Churilova, T.; Suslin, V.

2012-04-01

Satellite observations of ocean color provide a unique opportunity in oceanography to assess productivity of the sea on different spatial and temporal scales. However it has been shown that the standard SeaWiFS algorithm generally overestimates summer chlorophyll concentration and underestimates pigment content during spring phytoplankton bloom in comparison with in situ measurements. It is required to develop regional algorithms which are based on biooptical characteristics typical for the Sea and consequently could be used for correct transformation of spectral features of water-leaving radiance to chlorophyll a concentrations (Chl), light absorption features of suspended and dissolved organic matter (CDM), downwelling light attenuation coefficient/euphotic zone depth (PAR1%) and rate of primary synthesis of organic substances (PP). The numerous measurements of light absorption spectra of phytoplankton, non-algal particles and coloured dissolved organic matter carried out since 1996 in different seasons and regions of the Black Sea allowed to make a parameterization of the light absorption by all optically active components. Taking into account regional peculiarities of the biooptical parameters, their difference between seasons, shallow and deep-waters, their depth-dependent variability within photosynthetic zone regional spectral models for estimation of chlorophyll a concentration (Chl Model), colored dissolved and suspended organic matter absorption (CDM Model), downwelling irradiance (PAR Model) and primary production (PP Model) have been developed based on satellite data. Test of validation of models showed appropriate accuracy of the models. The developed models have been applied for estimation of spatial/temporal variability of chlorophyll a, dissolved organic matter concentrations, waters transparency, euphotic zone depth and primary production based on SeaWiFS data. Two weeks averaged maps of spatial distribution of these parameters have been composed for period from 1998 to 2009 (most of them presented on site http://blackseacolor.com/browser3.html). Comparative analysis of long-term series (since 1998) of these parameters with subsurface water temperature (SST) and solar radiance of the sea surface (PAR-0m) revealed the key factors determining the seasonal and inter-annual variations of Chl, PAR1%, CDM, PP. The seasonal dynamics of these parameters were more pronounced compared with inter-annual variability. The later was related to climate effect. In deep-waters region relatively lower SST during cold winters were forcing more intensive winter-spring phytoplankton bloom. In north-western shelf inter-annual variability in river (Danube) run off, which was related to climate change as well, determined year-to-year changing in Chl, CDM, PAR1%, and PP.

Monitoring Spatial Variability and Temporal Dynamics of Phragmites Using Unmanned Aerial Vehicles

PubMed Central

Tóth, Viktor R.

2018-01-01

Littoral zones of freshwater lakes are exposed to environmental impacts from both terrestrial and aquatic sides, while substantial anthropogenic pressure also affects the high spatial, and temporal variability of the ecotone. In this study, the possibility of monitoring seasonal and spatial changes in reed (Phragmites australis) stands using an unmanned aerial vehicle (UAV) based remote sensing technique was examined. Stands in eutrophic and mesotrophic parts of Lake Balaton including not deteriorating (stable) and deteriorating (die-back) patches, were tracked throughout the growing season using a UAV equipped with a Normalized Difference Vegetation Index (NDVI) camera. Photophysiological parameters of P. australis were also measured with amplitude modulated fluorescence. Parameters characterizing the dynamics of seasonal changes in NDVI data were used for phenological comparison of eutrophic and mesotrophic, stable and die-back, terrestrial and aquatic, mowed and not-mowed patches of reed. It was shown that stable Phragmites plants from the eutrophic part of the lake reached specific phenological stages up to 3.5 days earlier than plants from the mesotrophic part of the lake. The phenological changes correlated with trophic (total and nitrate-nitrite nitrogen) and physical (organic C and clay content) properties of the sediment, while only minor relationships with air and water temperature were found. Phenological differences between the stable and die-back stands were even more pronounced, with ~34% higher rates of NDVI increase in stable than die-back patches, while the period of NDVI increase was 16 days longer. Aquatic and terrestrial parts of reed stands showed no phenological differences, although intermediate areas (shallow water parts of stands) were found to be less vigorous. Winter mowing of dried Phragmites sped up sprouting and growth of reed in the spring. This study showed that remote sensing-derived photophysiological and phenological variability within and between reed stands may provide valuable early indicators of environmental stress. The flexibility of the method makes it usable for mapping fine-scale temporal variability and spatial zonation within a stand, revealing ecophysiological hotspots that might require particular attention, and obtaining information vital for conservation and management of plants in the littoral zones. PMID:29915608

Variability of hazardous air pollutants in an urban area

NASA Astrophysics Data System (ADS)

Spicer, Chester W.; Buxton, Bruce E.; Holdren, Michael W.; Smith, Deborah L.; Kelly, Thomas J.; Rust, Steven W.; Pate, Alan D.; Sverdrup, George M.; Chuang, Jane C.

The variability of hazardous air pollutants (HAPs) is an important factor in determining human exposure to such chemicals, and in designing HAP measurement programs. This study has investigated the factors which contribute to HAP variability in an urban area. Six measurement sites separated by up to 12 km collected data with 3 h time resolution to examine spatial variability within neighborhoods and between neighborhoods. The measurements were made in Columbus, OH. The 3 h results also were used to study temporal variability, and duplicate samples collected at each site were used to determine the component of variability attributable to the measurement process. Hourly samples collected over 10 days at one site provided further insight into the temporal resolution needed to capture short-term peak concentrations. Measurements at the 6 spatial sites focused on 78 chemicals. Twenty-three of these species were found in at least 95% of the 3 h samples, and 39 chemicals were present at least 60% of the time. The relative standard deviations for most of these 39 frequently detected chemicals was 1.0 or lower. Variability was segmented into temporal, spatial, and measurement components. Temporal variation was the major contributor to HAP variability for 19 of the 39 frequently detected compounds, based on the 3 h data. Measurement imprecision contributed less than 25% for most of the volatile organic species, but 30% or more of the variability for carbonyl compounds, trace elements, and particle-bound extractable organic mass. Interestingly, the spatial component contributed less than 20% of the total variability for all the chemicals except sulfur. Based on the data with hourly resolution, peak to median ratios (hourly peak to 24 h median) averaged between 2 and 4 for most of the volatile organic compounds, but there were two species with peak to median ratios of about 10.

Mapping the spatial and temporal progression of human dental enamel biomineralization using synchrotron X-ray diffraction.

PubMed

Simmons, Lisa M; Montgomery, Janet; Beaumont, Julia; Davis, Graham R; Al-Jawad, Maisoon

2013-11-01

The complex biological, physicochemical process of human dental enamel formation begins in utero and for most teeth takes several years to complete. Lost enamel tissue cannot regenerate, therefore a better understanding of the spatial and temporal progression of mineralization of this tissue is needed in order to design improved in vivo mineral growth processes for regenerative dentistry and allow the possibility to grow a synthetic whole or partial tooth. Human dental enamel samples across a range of developmental stages available through archaeological collections have been used to explore the spatial and temporal progression of enamel biomineralization. Position sensitive synchrotron X-ray diffraction was used to quantify spatial and temporal variations in crystallite organization, lattice parameters and crystallite thickness at three different stages in enamel maturation. In addition X-ray microtomography was used to study mineral content distributions. An inverse correlation was found between the spatial variation in mineral content and the distribution of crystallite organization and thickness as a function of time during enamel maturation. Combined X-ray microtomography and synchrotron X-ray diffraction results show that as enamel matures the mineral content increases and the mineral density distribution becomes more homogeneous. Starting concurrently but proceeding at a slower rate, the enamel crystallites become more oriented and larger; and the crystallite organization becomes spatially more complex and heterogeneous. During the mineralization of human dental enamel, the rate of mineral formation and mineral organization are not identical. Whilst the processes start simultaneously, full mineral content is achieved earlier, and crystallite organization is slower and continues for longer. These findings provide detailed insights into mineral development in human dental enamel which can inform synthetic biomimetic approaches for the benefit of clinical dentistry. Copyright © 2013 Elsevier Ltd. All rights reserved.

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

Methane Seeps in the Gulf of Mexico: repeat acoustic surveying shows highly temporally and spatially variable venting

NASA Astrophysics Data System (ADS)

Beaumont, B. C.; Raineault, N.

2016-02-01

Scientists have recognized that natural seeps account for a large amount of methane emissions. Despite their widespread occurrence in areas like the Gulf of Mexico, little is known about the temporal variability and site-scale spatial variability of venting over time. We used repeat acoustic surveys to compare multiple days of seep activity and determine the changes in the locus of methane emission and plume height. The Sleeping Dragon site was surveyed with an EM302 multibeam sonar on three consecutive days in 2014 and 4 days within one week in 2015. The data revealed three distinctive plume regions. The locus of venting varied by 10-60 meters at each site. The plume that exhibited the least spatial variability in venting, was also the most temporally variable. This seep was present in one-third of survey dates in 2014 and three quarters of survey dates in 2015, showing high day-to-day variability. The plume height was very consistent for this plume, whereas the other plumes were more consistent temporally, but varied in maximum plume height detection by 25-85 m. The single locus of emission at the site that had high day-to-day variability may be due to a single conduit for methane release, which is sometimes closed off by carbonate or clathrate hydrate formation. In addition to day-to-day temporal variability, the locus of emission at one site was observed to shift from a point-source in 2014 to a diffuse source in 2015 at a nearby location. ROV observations showed that one of the seep sites that closed off temporarily, experienced an explosive breakthrough of gas, releasing confined methane and blowing out rock. The mechanism that causes on/off behavior of certain plumes, combined with the spatial variability of the locus of methane release shown in this study may point to carbonate or hydrate formation in the seep plumbing system and should be further investigated.

CMAQ MODELING FOR AIR TOXICS AT FINE SCALES: A PROTOTYPE STUDY

EPA Science Inventory

Toxic air pollutants (TAPs) or hazardous air pollutants (HAPs) exhibit considerable spatial and temporal variability across urban areas. Therefore, the ability of chemical transport models (CTMs), e.g. Community Multi-scale Air Quality (CMAQ), to reproduce the spatial and tempor...

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.

Space and time in ecology: Noise or fundamental driver? [chapter 2

Treesearch

Samuel A. Cushman

2010-01-01

In this chapter I frame the central issue of the book, namely is spatial and temporal complexity in ecological systems merely noise around the predictions of non-spatial, equilibrium processes? Or, alternatively, do spatial and temporal variability in the environment and autogenic space­time processes in populations fundamentally alter system behavior such that ideal...

Dispersal Ability Determines the Role of Environmental, Spatial and Temporal Drivers of Metacommunity Structure

PubMed Central

Padial, André A.; Ceschin, Fernanda; Declerck, Steven A. J.; De Meester, Luc; Bonecker, Cláudia C.; Lansac-Tôha, Fabio A.; Rodrigues, Liliana; Rodrigues, Luzia C.; Train, Sueli; Velho, Luiz F. M.; Bini, Luis M.

2014-01-01

Recently, community ecologists are focusing on the relative importance of local environmental factors and proxies to dispersal limitation to explain spatial variation in community structure. Albeit less explored, temporal processes may also be important in explaining species composition variation in metacommunities occupying dynamic systems. We aimed to evaluate the relative role of environmental, spatial and temporal variables on the metacommunity structure of different organism groups in the Upper Paraná River floodplain (Brazil). We used data on macrophytes, fish, benthic macroinvertebrates, zooplankton, periphyton, and phytoplankton collected in up to 36 habitats during a total of eight sampling campaigns over two years. According to variation partitioning results, the importance of predictors varied among biological groups. Spatial predictors were particularly important for organisms with comparatively lower dispersal ability, such as aquatic macrophytes and fish. On the other hand, environmental predictors were particularly important for organisms with high dispersal ability, such as microalgae, indicating the importance of species sorting processes in shaping the community structure of these organisms. The importance of watercourse distances increased when spatial variables were the main predictors of metacommunity structure. The contribution of temporal predictors was low. Our results emphasize the strength of a trait-based analysis and of better defining spatial variables. More importantly, they supported the view that “all-or- nothing” interpretations on the mechanisms structuring metacommunities are rather the exception than the rule. PMID:25340577

Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Owe, M.; Ormsby, J. P.; Chang, A. T. C.; Wang, J. R.; Goward, S. N.; Golus, R. E.

1987-01-01

Spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains are quantified in terms of vegetation and soil wetness. The brightness temperatures (TB) are the daytime observations from April to October for five years (1979 to 1983) obtained by the Nimbus-7 Scanning Multichannel Microwave Radiometer at 6.6 GHz frequency, horizontal polarization. The spatial and temporal variabilities of vegetation are assessed using visible and near-infrared observations by the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR), while an Antecedent Precipitation Index (API) model is used for soil wetness. The API model was able to account for more than 50 percent of the observed variability in TB, although linear correlations between TB and API were generally significant at the 1 percent level. The slope of the linear regression between TB and API is found to correlate linearly with an index for vegetation density derived from AVHRR data.

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

PubMed Central

Safavynia, Seyed A.

2012-01-01

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns—or muscle synergies—are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance. PMID:21957219

Diffusional flux of CO2 through snow: Spatial and temporal variability among alpine-subalpine sites

Treesearch

Richard A. Sommerfeld; William J. Massman; Robert C. Musselman

1996-01-01

Three alpine and three subalpine sites were monitored for up to 4 years to acquire data on the temporal and spatial variability of CO2 flux through snowpacks. We conclude that the snow formed a passive cap which controlled the concentration of CO2 at the snow-soil interface, while the flux of CO2 into the atmosphere was controlled by CO2 production in the soil....

Temporal and spatial variability of frost-free seasons in the Great Lakes region of the United States

Treesearch

Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman; Jeffrey A. Andresen

2014-01-01

The frequency and timing of frost events and the length of the growing season are critical limiting factors in many human and natural ecosystems. This study investigates the temporal and spatial variability of the date of last spring frost (LSF), the date of first fall frost (FFF), and the length of the frost-free season (FFS) in the Great Lakes region of the United...

Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds

NASA Astrophysics Data System (ADS)

Morison, Matthew Q.; Macrae, Merrin L.; Petrone, Richard M.; Fishback, LeeAnn

2017-12-01

Across the circumpolar north, the fate of small freshwater ponds and lakes (< 1 km2) has been the subject of scientific interest due to their ubiquity in the landscape, capacity to exchange carbon and energy with the atmosphere, and their potential to inform researchers about past climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely mediated by processes within ponds. This work demonstrates the importance of understanding hydrologically driven chemodynamics in permafrost ponds on multiple scales (seasonal and event scale).

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

NASA Technical Reports Server (NTRS)

Lerner, Jeffrey A.; Jedlovec, Gary J.; Kidder, Stanley Q.

1996-01-01

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

A spatial-temporal regression model to predict daily outdoor residential PAH concentrations in an epidemiologic study in Fresno, CA

NASA Astrophysics Data System (ADS)

Noth, Elizabeth M.; Hammond, S. Katharine; Biging, Gregory S.; Tager, Ira B.

2011-05-01

BackgroundPolycyclic aromatic hydrocarbons (PAHs) are generated as a byproduct of combustion, and are associated with respiratory symptoms and increased risk of asthma attacks. ObjectivesTo assign daily, outdoor exposures to participants in the Fresno Asthmatic Children's Environment Study (FACES) using land use regression models for the sum of 4-, 5- and 6-ring PAHs (PAH456). MethodsPAH data were collected daily at the EPA Supersite in Fresno, CA from 10/2000 through 2/2007. From 2/2002 to 2/2003, intensive air pollution sampling was conducted at 83 homes of participants in the FACES study. These measurement data were combined with meteorological data, source data, and other spatial variables to form a land use regression model to assign daily exposure at all FACES homes for all years of the study (2001-2008). ResultsThe model for daily, outdoor residential PAH456 concentrations accounted for 80% of the between-home variability and 18% of the within-home variability. Both temporal and spatial variables were significant in the model. Traffic characteristics and home heating fuel were the main spatial explanatory variables. ConclusionsBecause spatial and temporal distributions of PAHs vary on an intra-urban scale, the location of the child's home within the urban setting plays an important role in the level of exposure that each child has to PAHs.

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Treesearch

Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell

2010-01-01

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...

Soil water content evaluation considering time-invariant spatial pattern and space-variant temporal change

NASA Astrophysics Data System (ADS)

Hu, W.; Si, B. C.

2013-10-01

Soil water content (SWC) varies in space and time. The objective of this study was to evaluate soil water content distribution using a statistical model. The model divides spatial SWC series into time-invariant spatial patterns, space-invariant temporal changes, and space- and time-dependent redistribution terms. The redistribution term is responsible for the temporal changes in spatial patterns of SWC. An empirical orthogonal function was used to separate the total variations of redistribution terms into the sum of the product of spatial structures (EOFs) and temporally-varying coefficients (ECs). Model performance was evaluated using SWC data of near-surface (0-0.2 m) and root-zone (0-1.0 m) from a Canadian Prairie landscape. Three significant EOFs were identified for redistribution term for both soil layers. EOF1 dominated the variations of redistribution terms and it resulted in more changes (recharge or discharge) in SWC at wetter locations. Depth to CaCO3 layer and organic carbon were the two most important controlling factors of EOF1, and together, they explained over 80% of the variations in EOF1. Weak correlation existed between either EOF2 or EOF3 and the observed factors. A reasonable prediction of SWC distribution was obtained with this model using cross validation. The model performed better in the root zone than in the near surface, and it outperformed conventional EOF method in case soil moisture deviated from the average conditions.

Quantifying spatiotemporal variability of fine particles in an urban environment using combined fixed and mobile measurements

NASA Astrophysics Data System (ADS)

Sullivan, R. C.; Pryor, S. C.

2014-06-01

Spatiotemporal variability of fine particle concentrations in Indianapolis, Indiana is quantified using a combination of high temporal resolution measurements at four fixed sites and mobile measurements with instruments attached to bicycles during transects of the city. Average urban PM2.5 concentrations are an average of ˜3.9-5.1 μg m-3 above the regional background. The influence of atmospheric conditions on ambient PM2.5 concentrations is evident with the greatest temporal variability occurring at periods of one day and 5-10 days corresponding to diurnal and synoptic meteorological processes, and lower mean wind speeds are associated with episodes of high PM2.5 concentrations. An anthropogenic signal is also evident. Higher PM2.5 concentrations coincide with morning rush hour, the frequencies of PM2.5 variability co-occur with those for carbon monoxide, and higher extreme concentrations were observed mid-week compared to weekends. On shorter time scales (

COMPARISON OF DIRECT AND INDIRECT IMPACTS OF FECAL CONTAMINATION IN TWO DIFFERENT WATERSHEDS

EPA Science Inventory

There are many environmental parameters that could affect the accuracy of microbial source tracking (MST) methods. Spatial and temporal determinants are among the most common factors missing in MST studies. To understand how spatial and temporal variability affect the level of fe...

Nitrogen controls spatial and temporal variability of substrate-induced respiration within seven years of bare fallow

NASA Astrophysics Data System (ADS)

Meyer, Nele; Bornemann, Ludger; Welp, Gerhard; Amelung, Wulf

2015-04-01

Bare fallow management goes along with lacking supply of new C sources; yet, little is known on the spatio-temporal controls of microbial adaptation processes. Here we hypothesized that microbial activity parameters decline upon bare fallow but that their spatial patterns are increasingly controlled by nutrient status as fallow management proceeds. To test these hypotheses, we investigated spatial and temporal patterns of substrate-induced respiration (SIR) and basal respiration curves in an arable field after 1, 3, and 7 years of bare fallow but with large within-field heterogeneity of physicochemical soil parameters. The analyses comprised the contents of SOC, mineral nitrogen (Nmin), particulate organic matter (POM), texture of the fine earth, and the proportion of rock fragments as well as basal respiration and several SIR fitting parameters (microbial biomass, microbial growth rates, peak respiration rates, cumulative CO2 release) each with and without additions of mineral N and P. We also repeated substrate (i.e. glucose) additions following the first SIR measurement. The results revealed that most respiration parameters like basal respiration, microbial biomass, and growth rates showed no or inconsistent responses to spatial and temporal patterns of basic soil properties like SOC, Nmin or texture. However, bare fallow changed the shape of the SIR curves; it developed two distinct microbial growth peaks at advanced stages of fallow, i.e. a delayed CO2 release. Likewise, the maximum respiration rate during the first growth phase declined during 7 years of fallow by 47% but its spatial distribution was always correlated with Nmin contents (r = 0.43 - 0.79). The nutrient additions suggested that these changes in SIR curves were caused by N deficiency; the first peak increased after N additions while the second growth phase diminished. Intriguingly, a repeated glucose addition had a similar effect on the SIR curves as the glucose+N addition. Thus, N deficiency apparently subsided during SIR. The results suggested that soil microbes acquire nitrogen from refractory SOM pools (i.e. microbial nitrogen mining). Hence, there was no significant decrease in cumulative CO2 evolution with proceeding time of fallow. As soil microorganisms maintained their functionality there was no overall loss in potential microbial activity, irrespective of the spatial patterns of other soil properties.

The spinal control of locomotion and step-to-step variability in left-right symmetry from slow to moderate speeds

PubMed Central

Dambreville, Charline; Labarre, Audrey; Thibaudier, Yann; Hurteau, Marie-France

2015-01-01

When speed changes during locomotion, both temporal and spatial parameters of the pattern must adjust. Moreover, at slow speeds the step-to-step pattern becomes increasingly variable. The objectives of the present study were to assess if the spinal locomotor network adjusts both temporal and spatial parameters from slow to moderate stepping speeds and to determine if it contributes to step-to-step variability in left-right symmetry observed at slow speeds. To determine the role of the spinal locomotor network, the spinal cord of 6 adult cats was transected (spinalized) at low thoracic levels and the cats were trained to recover hindlimb locomotion. Cats were implanted with electrodes to chronically record electromyography (EMG) in several hindlimb muscles. Experiments began once a stable hindlimb locomotor pattern emerged. During experiments, EMG and bilateral video recordings were made during treadmill locomotion from 0.1 to 0.4 m/s in 0.05 m/s increments. Cycle and stance durations significantly decreased with increasing speed, whereas swing duration remained unaffected. Extensor burst duration significantly decreased with increasing speed, whereas sartorius burst duration remained unchanged. Stride length, step length, and the relative distance of the paw at stance offset significantly increased with increasing speed, whereas the relative distance at stance onset and both the temporal and spatial phasing between hindlimbs were unaffected. Both temporal and spatial step-to-step left-right asymmetry decreased with increasing speed. Therefore, the spinal cord is capable of adjusting both temporal and spatial parameters during treadmill locomotion, and it is responsible, at least in part, for the step-to-step variability in left-right symmetry observed at slow speeds. PMID:26084910

Additive effects of emotional content and spatial selective attention on electrocortical facilitation.

PubMed

Keil, Andreas; Moratti, Stephan; Sabatinelli, Dean; Bradley, Margaret M; Lang, Peter J

2005-08-01

Affectively arousing visual stimuli have been suggested to automatically attract attentional resources in order to optimize sensory processing. The present study crosses the factors of spatial selective attention and affective content, and examines the relationship between instructed (spatial) and automatic attention to affective stimuli. In addition to response times and error rate, electroencephalographic data from 129 electrodes were recorded during a covert spatial attention task. This task required silent counting of random-dot targets embedded in a 10 Hz flicker of colored pictures presented to both hemifields. Steady-state visual evoked potentials (ssVEPs) were obtained to determine amplitude and phase of electrocortical responses to pictures. An increase of ssVEP amplitude was observed as an additive function of spatial attention and emotional content. Statistical parametric mapping of this effect indicated occipito-temporal and parietal cortex activation contralateral to the attended visual hemifield in ssVEP amplitude modulation. This difference was most pronounced during selection of the left visual hemifield, at right temporal electrodes. In line with this finding, phase information revealed accelerated processing of aversive arousing, compared to affectively neutral pictures. The data suggest that affective stimulus properties modulate the spatiotemporal process along the ventral stream, encompassing amplitude amplification and timing changes of posterior and temporal cortex.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

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.

Modeling the spatial and temporal variability in climate and primary productivity across the Luquillo Mountains, Puerto Rico.

Treesearch

Hongqing Wanga; Charles A.S. Halla; Frederick N. Scatenab; Ned Fetcherc; Wei Wua

2003-01-01

There are few studies that have examined the spatial variability of forest productivity over an entire tropical forested landscape. In this study, we used a spatially-explicit forest productivity model, TOPOPROD, which is based on the FORESTBGC model, to simulate spatial patterns of gross primary productivity (GPP), net primary productivity (NPP), and respiration over...

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change? (Invited)

NASA Astrophysics Data System (ADS)

Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.

Spatial and temporal variability of lightings over Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Matsangouras, J. T.

2010-09-01

Lightings are the most powerful and spectacular natural phenomena in the lower atmosphere, being a major cause of storm related deaths. Cloud-to-ground lightning can kill and injure people by direct or indirect means. Lightning affects the many electrochemical systems in the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. In this study, the spatial and temporal variability of recorded lightings over Greece during the period from January 1, 2008 to December 31, 2009, were analyzed. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS) archive dataset. An operational lighting detector network was established in 2007 by HNMS consisted of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. The spatial variability of lightings revealed their incidence within specific geographical sub-regions while the temporal variability concerning the seasonal, monthly and daily distributions resulted in better understanding of the time of lightings’ occurrence. All the analyses were carried out with respect to cloud to cloud, cloud to ground and ground to cloud lightings, within the examined time period.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

PubMed Central

Dias, Daniela; Tchepel, Oxana

2018-01-01

Analyzing individual exposure in urban areas offers several challenges where both the individual’s activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals’ activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual’s time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives. PMID:29558426

Observations on the palynology, petrography and geochemistry of the Western Kentucky number 4 coal bed

USGS Publications Warehouse

Eble, C.F.; Greb, S.F.; Williams, D.A.; Hower, J.C.

1999-01-01

Eight bench-column samples of the Western Kentucky Number 4 coal bed, collected from an area along the southern margin of the Western Kentucky Coal Field, were analyzed palynologically, petrographically, and geochemically to document both temporal and spatial variability among these parameters. The Western Kentucky Number 4 coal occurs near the top of the Tradewater Formation, is of Early Desmoinesian age, and is correlative with the lower part of the Allegheny Formation of the Appalachian Basin, and Late Bolsovian strata of western Europe. Palynologically, the coal is co-dominated by spores that were produced by lycopod trees (Lycospora and Granasporites medius) and tree ferns. Thin-walled tree fern spores (Punctatisporites minutus, P. minutus, P. rotundus) are more abundant than thick-walled forms (Laevigatosporites globosus, P. granifer). Calamitean spores (Calamospora and Laevigatosporites spp.) are locally abundant as is cordaitean pollen (Florinites). Small fern (Granulatisporites) and small lycopod spores (Densosporites, Cirratriradites, Endosporites and Anacanthotriletes spinosus) are present, but occur in minor amounts. Temporal changes in palynomorph composition occur, but are not uniform between columns. Spatial variability among columns is also evident. Petrographically, the coal is dominated by vitrinite macerals, with telinite and telocollinite generally occurring more commonly than desmocollinite and gelocollinite. Basal benches typically contain high percentages of vitrinite; middle benches usually contain higher percentages of liptinite and inertinite. In about half the studied columns, the terminal coal benches show a slight increase in vitrinite. In the study area, the petrography of the Western Kentucky Number 4 coal is more uniform than the palynology. Ash yields and total sulfur contents are temporally uniform in some columns, but variable in others. In the latter case, higher percentages of ash and sulfur occur at the base of the bed and decrease up to the middle of the bed. The terminal benches of these columns often, but not always, show slight increases in ash or sulfur. Both syngenetic and epigenetic forms of sulfur are present in the Western Kentucky Number 4 coal. The high vitrinite contents and moderate to high sulfur contents suggest that the Western Kentucky Number 4 paleomire was mainly planar and rheotrophic throughout its developmental history. Groundwaters carrying dissolved solutes may have helped neutralize the normally acidic interstitial peat waters allowing for the production of sulfide minerals. Several of the columns with high sulfur contents at the base of the bed occur in faulted areas. The faults could have promoted the flow of groundwaters through the peat, providing an increased dissolved load for acid mitigation and sulfide formation. The concentration of sulfur at the base of the bed may be a function of the peat/underclay contact enhancing sulfide formation. The clay layer may also have acted as an impermeable boundary for downward moving groundwaters, causing mainly lateral, rather than vertical movement along the base of the coal bed.Eight bench-column samples of the Western Kentucky Number 4 coal bed were analyzed palynologically, petrographically, and geochemically to study both temporal and spatial variability among these parameters. Palynologically, the coal is co-dominated by spores that were produced by lycopod trees and tree ferns. Petrographically, the coal is dominated by vitrinite macerals, with telinite and telocollinite generally occurring more commonly than desmocollinite and gelocollinite. The petrography of the coal was found to be more uniform than the palynology.

Time-Lapse Geophysical Measurements targeting Spatial and Temporal Variability in Biogenic Gas Production from Peat Soils in a Hydrologically Controlled Wetland in the Florida Everglades

NASA Astrophysics Data System (ADS)

Wright, W. J.; Shahan, T.; Sharp, N.; Comas, X.

2015-12-01

Peat soils are known to release globally significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. However, uncertainties still remain regarding the spatio-temporal distribution of gas accumulations and triggering mechanisms of gas releasing events. Furthermore, most research on peatland gas dynamics has traditionally been focused on high latitude peatlands. Therefore, understanding gas dynamics in low-latitude peatlands (e.g. the Florida Everglades) is key to global climate research. Recent studies in the Everglades have demonstrated that biogenic gas flux values may vary when considering different temporal and spatial scales of measurements. The work presented here targets spatial variability in gas production and release at the plot scale in an approximately 85 m2 area, and targets temporal variability with data collected during the spring months of two different years. This study is located in the Loxahatchee Impoundment Landscape Assessment (LILA), a hydrologically controlled, landscape scale (30 Ha) model of the Florida Everglades. Ground penetrating radar (GPR) has been used in the past to investigate biogenic gas dynamics in peat soils, and is used in this study to monitor changes of in situ gas storage. Each year, a grid of GPR profiles was collected to image changes in gas distribution in 2d on a weekly basis, and several flux chambers outfitted with time-lapse cameras captured high resolution (hourly) gas flux measurements inside the GPR grid. Combining these methods allows us to use a mass balance approach to estimate spatial variability in gas production rates, and capture temporal variability in gas flux rates.

Impact of atmospheric forcing on heat content variability in the sub-surface layer in the Japan/East Sea, 1948-2009

NASA Astrophysics Data System (ADS)

Stepanov, Dmitry; Gusev, Anatoly; Diansky, Nikolay

2016-04-01

Based on numerical simulations the study investigates impact of atmospheric forcing on heat content variability of the sub-surface layer in Japan/East Sea (JES), 1948-2009. We developed a model configuration based on a INMOM model and atmospheric forcing extracted from the CORE phase II experiment dataset 1948-2009, which enables to assess impact of only atmospheric forcing on heat content variability of the sub-surface layer of the JES. An analysis of kinetic energy (KE) and total heat content (THC) in the JES obtained from our numerical simulations showed that the simulated circulation of the JES is being quasi-steady state. It was found that the year-mean KE variations obtained from our numerical simulations are similar those extracted from the SODA reanalysis. Comparison of the simulated THC and that extracted from the SODA reanalysis showed significant consistence between them. An analysis of numerical simulations showed that the simulated circulation structure is very similar that obtained from the PALACE floats in the intermediate and abyssal layers in the JES. Using empirical orthogonal function analysis we studied spatial-temporal variability of the heat content of the sub-surface layer in the JES. Based on comparison of the simulated heat content variations with those obtained from natural observations an assessment of the atmospheric forcing impact on the heat content variability was obtained. Using singular value decomposition analysis we considered relationships between the heat content variability and wind stress curl as well as sensible heat flux in winter. It was established the major role of sensible heat flux in decadal variability of the heat content of the sub-surface layer in the JES. The research was supported by the Russian Foundation for Basic Research (grant N 14-05-00255) and the Council on the Russian Federation President Grants (grant N MK-3241.2015.5)

Sensitivity of grassland plant community composition to spatial vs. temporal variation in precipitation

USDA-ARS?s Scientific Manuscript database

Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences...

Deriving video content type from HEVC bitstream semantics

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio R.

2014-05-01

As network service providers seek to improve customer satisfaction and retention levels, they are increasingly moving from traditional quality of service (QoS) driven delivery models to customer-centred quality of experience (QoE) delivery models. QoS models only consider metrics derived from the network however, QoE models also consider metrics derived from within the video sequence itself. Various spatial and temporal characteristics of a video sequence have been proposed, both individually and in combination, to derive methods of classifying video content either on a continuous scale or as a set of discrete classes. QoE models can be divided into three broad categories, full reference, reduced reference and no-reference models. Due to the need to have the original video available at the client for comparison, full reference metrics are of limited practical value in adaptive real-time video applications. Reduced reference metrics often require metadata to be transmitted with the bitstream, while no-reference metrics typically operate in the decompressed domain at the client side and require significant processing to extract spatial and temporal features. This paper proposes a heuristic, no-reference approach to video content classification which is specific to HEVC encoded bitstreams. The HEVC encoder already makes use of spatial characteristics to determine partitioning of coding units and temporal characteristics to determine the splitting of prediction units. We derive a function which approximates the spatio-temporal characteristics of the video sequence by using the weighted averages of the depth at which the coding unit quadtree is split and the prediction mode decision made by the encoder to estimate spatial and temporal characteristics respectively. Since the video content type of a sequence is determined by using high level information parsed from the video stream, spatio-temporal characteristics are identified without the need for full decoding and can be used in a timely manner to aid decision making in QoE oriented adaptive real time streaming.

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

New spatial and temporal indices of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Dwivedi, Sanjeev; Uma, R.; Lakshmi Kumar, T. V.; Narayanan, M. S.; Pokhrel, Samir; Kripalani, R. H.

2018-02-01

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Effect of trotting speed on kinematic variables measured by use of extremity-mounted inertial measurement units in nonlame horses performing controlled treadmill exercise.

PubMed

Cruz, Antonio M; Vidondo, Beatriz; Ramseyer, Alessandra A; Maninchedda, Ugo E

2018-02-01

OBJECTIVE To assess effects of speed on kinematic variables measured by use of extremity-mounted inertial measurement units (IMUs) in nonlame horses performing controlled exercise on a treadmill. ANIMALS 10 nonlame horses. PROCEDURES 6 IMUs were attached at predetermined locations on 10 nonlame Franches Montagnes horses. Data were collected in triplicate during trotting at 3.33 and 3.88 m/s on a high-speed treadmill. Thirty-three selected kinematic variables were analyzed. Repeated-measures ANOVA was used to assess the effect of speed. RESULTS Significant differences between the 2 speeds were detected for most temporal (11/14) and spatial (12/19) variables. The observed spatial and temporal changes would translate into a gait for the higher speed characterized by increased stride length, protraction and retraction, flexion and extension, mediolateral movement of the tibia, and symmetry, but with similar temporal variables and a reduction in stride duration. However, even though the tibia coronal range of motion was significantly different between speeds, the high degree of variability raised concerns about whether these changes were clinically relevant. For some variables, the lower trotting speed apparently was associated with more variability than was the higher trotting speed. CONCLUSIONS AND CLINICAL RELEVANCE At a higher trotting speed, horses moved in the same manner (eg, the temporal events investigated occurred at the same relative time within the stride). However, from a spatial perspective, horses moved with greater action of the segments evaluated. The detected changes in kinematic variables indicated that trotting speed should be controlled or kept constant during gait evaluation.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Spatiotemporal predictions of soil properties and states in variably saturated landscapes

NASA Astrophysics Data System (ADS)

Franz, Trenton E.; Loecke, Terrance D.; Burgin, Amy J.; Zhou, Yuzhen; Le, Tri; Moscicki, David

2017-07-01

Understanding greenhouse gas (GHG) fluxes from landscapes with variably saturated soil conditions is challenging given the highly dynamic nature of GHG fluxes in both space and time, dubbed hot spots, and hot moments. On one hand, our ability to directly monitor these processes is limited by sparse in situ and surface chamber observational networks. On the other hand, remote sensing approaches provide spatial data sets but are limited by infrequent imaging over time. We use a robust statistical framework to merge sparse sensor network observations with reconnaissance style hydrogeophysical mapping at a well-characterized site in Ohio. We find that combining time-lapse electromagnetic induction surveys with empirical orthogonal functions provides additional environmental covariates related to soil properties and states at high spatial resolutions ( 5 m). A cross-validation experiment using eight different spatial interpolation methods versus 120 in situ soil cores indicated an 30% reduction in root-mean-square error for soil properties (clay weight percent and total soil carbon weight percent) using hydrogeophysical derived environmental covariates with regression kriging. In addition, the hydrogeophysical derived environmental covariates were found to be good predictors of soil states (soil temperature, soil water content, and soil oxygen). The presented framework allows for temporal gap filling of individual sensor data sets as well as provides flexible geometric interpolation to complex areas/volumes. We anticipate that the framework, with its flexible temporal and spatial monitoring options, will be useful in designing future monitoring networks as well as support the next generation of hyper-resolution hydrologic and biogeochemical models.

Measuring the spatial variation in surface moisture on a coastal beach with an infra-red terrestrial laser scanner

NASA Astrophysics Data System (ADS)

Smit, Yvonne; Donker, Jasper; Ruessink, Gerben

2016-04-01

Coastal sand dunes provide essential protection against marine flooding. Consequently, dune erosion during severe storms has been studied intensively, resulting in well-developed erosion models for use in scientific and applied projects. Nowadays there is growing awareness that similarly advanced knowledge on dune recovery and growth is needed to predict future dune development. For this reason, aeolian sand transport from the beach into the dunes has to be investigated thoroughly. Surface moisture is a major factor limiting aeolian transport on sandy beaches. By increasing the velocity threshold for sediment entrainment, pick-up rates reduce and the fetch length increases. Conventional measurement techniques cannot adequately characterize the spatial and temporal distribution of surface moisture content required to study the effects on aeolian transport. Here we present a new method for detecting surface moisture at high temporal and spatial resolution using the RIEGL VZ-400 terrestrial laser scanner (TLS). Because this TLS operates at a wavelength near a water absorption band (1550 nm), TLS reflectance is an accurate parameter to measure surface soil moisture over its full range. Three days of intensive laser scanning were performed on a Dutch beach to illustrate the applicability of the TLS. Gravimetric soil moisture samples were used to calibrate the relation between reflectance and surface moisture. Results reveal a robust negative relation for the full range of possible surface moisture contents (0% - 25%). This relation holds to about 80 m from the TLS. Within this distance the TLS typically produces O(106-107) data points, which we averaged into soil moisture maps with a 0.25x0.25 m resolution. This grid size largely removes small moisture disturbances induced by, for example, footprints or tire tracks, while retaining larger scale trends. As the next step in our research, we will analyze the obtained maps to determine which processes affect the spatial and temporal surface-moisture variability.

Combined organizational and activational effects of short and long photoperiods on spatial and temporal memory in rats.

PubMed

MacDonald, Christopher J; Cheng, Ruey-Kuang; Williams, Christina L; Meck, Warren H

2007-02-22

The present study examined the effects of photoperiod on spatial and temporal memory in adult Sprague-Dawley rats that were conceived and reared in different day lengths, i.e., short day (SD-8:16 light/dark) and long day (LD-16:8 light/dark). Both male and female LD rats demonstrated increased spatial memory capacity as evidenced by a lower number of choices to criterion in a 12-arm radial maze task relative to the performance of SD rats. SD rats also demonstrated a distortion in the content of temporal memory as evidenced by a proportional rightward shift in the 20 and 60 s temporal criteria trained using the peak-interval procedure that is consistent with reduced cholinergic function. The conclusion is that both spatial and temporal memory are sensitive to photoperiod variation in laboratory rats in a manner similar to that previously observed for reproductive behaviour.

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.

Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

PubMed

Vidon, P; Marchese, S; Welsh, M; McMillan, S

2015-08-01

Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

Ionospheric TEC Weather Map Over South America

NASA Astrophysics Data System (ADS)

Takahashi, H.; Wrasse, C. M.; Denardini, C. M.; Pádua, M. B.; de Paula, E. R.; Costa, S. M. A.; Otsuka, Y.; Shiokawa, K.; Monico, J. F. Galera; Ivo, A.; Sant'Anna, N.

2016-11-01

Ionospheric weather maps using the total electron content (TEC) monitored by ground-based Global Navigation Satellite Systems (GNSS) receivers over South American continent, TECMAP, have been operationally produced by Instituto Nacional de Pesquisas Espaciais's Space Weather Study and Monitoring Program (Estudo e Monitoramento Brasileiro de Clima Especial) since 2013. In order to cover the whole continent, four GNSS receiver networks, (Rede Brasileiro de Monitoramento Contínuo) RBMC/Brazilian Institute for Geography and Statistics, Low-latitude Ionospheric Sensor Network, International GNSS Service, and Red Argentina de Monitoreo Satelital Continuo, in total 140 sites, have been used. TECMAPs with a time resolution of 10 min are produced in 12 h time delay. Spatial resolution of the map is rather low, varying between 50 and 500 km depending on the density of the observation points. Large day-to-day variabilities of the equatorial ionization anomaly have been observed. Spatial gradient of TEC from the anomaly trough (total electron content unit, 1 TECU = 1016 el m-2 (TECU) <10) to the crest region (TECU > 80) causes a large ionospheric range delay in the GNSS positioning system. Ionospheric plasma bubbles, their seeding and development, could be monitored. This plasma density (spatial and temporal) variability causes not only the GNSS-based positioning error but also radio wave scintillations. Monitoring of these phenomena by TEC mapping becomes an important issue for space weather concern for high-technology positioning system and telecommunication.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Cathodal Transcranial Direct Current Stimulation (tDCS) to the Right Cerebellar Hemisphere Affects Motor Adaptation During Gait.

PubMed

Fernandez, Lara; Albein-Urios, Natalia; Kirkovski, Melissa; McGinley, Jennifer L; Murphy, Anna T; Hyde, Christian; Stokes, Mark A; Rinehart, Nicole J; Enticott, Peter G

2017-02-01

The cerebellum appears to play a key role in the development of internal rules that allow fast, predictive adjustments to novel stimuli. This is crucial for adaptive motor processes, such as those involved in walking, where cerebellar dysfunction has been found to increase variability in gait parameters. Motor adaptation is a process that results in a progressive reduction in errors as movements are adjusted to meet demands, and within the cerebellum, this seems to be localised primarily within the right hemisphere. To examine the role of the right cerebellar hemisphere in adaptive gait, cathodal transcranial direct current stimulation (tDCS) was administered to the right cerebellar hemisphere of 14 healthy adults in a randomised, double-blind, crossover study. Adaptation to a series of distinct spatial and temporal templates was assessed across tDCS condition via a pressure-sensitive gait mat (ProtoKinetics Zeno walkway), on which participants walked with an induced 'limp' at a non-preferred pace. Variability was assessed across key spatial-temporal gait parameters. It was hypothesised that cathodal tDCS to the right cerebellar hemisphere would disrupt adaptation to the templates, reflected in a failure to reduce variability following stimulation. In partial support, adaptation was disrupted following tDCS on one of the four spatial-temporal templates used. However, there was no evidence for general effects on either the spatial or temporal domain. This suggests, under specific conditions, a coupling of spatial and temporal processing in the right cerebellar hemisphere and highlights the potential importance of task complexity in cerebellar function.

Spatial and Temporal Evaluation of Soil Erosion with RUSLE: A Case Study in an Olive Orchard Microcathment in Spain

EPA Science Inventory

Soil loss is commonly estimated using the Revised Universal Soil Loss Equation (RUSLE). Since RUSLE is an empirically based soil loss model derived from surveys on plots, the high spatial and temporal variability of erosion in Mediterranean environments and scale effects provoke...

Landscape ecology: Past, present, and future [Chapter 4

Treesearch

Samuel A. Cushman; Jeffrey S. Evans; Kevin McGarigal

2010-01-01

In the preceding chapters we discussed the central role that spatial and temporal variability play in ecological systems, the importance of addressing these explicitly within ecological analyses and the resulting need to carefully consider spatial and temporal scale and scaling. Landscape ecology is the science of linking patterns and processes across scale in both...

Spatial and Temporal Evaluation of Soil Erosion with RUSLE: A case Study in an Olive Orchard Microcathment in Spain

EPA Science Inventory

Soil loss is commonly estimated using the Revised Universal Soil Loss Equation (RUSLE). Since RUSLE is an empirically based soil loss model derived from surveys on plots, the high spatial and temporal variability of erosion in Mediterranean environments and scale effects provo...

Spatial and Temporal Patterns of Throughfall Amounts and Solutes in a Tropical Montane Forest - Comparisons with Findings From Lowland Rain Forests

NASA Astrophysics Data System (ADS)

Zimmermann, A.

2007-05-01

The diverse tree species composition, irregular shaped tree crowns and a multi-layered forest structure affect the redistribution of rainfall in lower montane rain forests. In addition, abundant epiphyte biomass and associated canopy humus influence spatial patterns of throughfall. The spatial variability of throughfall amounts controls spatial patterns of solute concentrations and deposition. Moreover, the living and dead biomass interacts with the rainwater during the passage through the canopy and creates a chemical variability of its own. Since spatial and temporal patterns are intimately linked, the analysis of temporal solute concentration dynamics is an important step to understand the emerging spatial patterns. I hypothesized that: (1) the spatial variability of volumes and chemical composition of throughfall is particularly high compared with other forests because of the high biodiversity and epiphytism, (2) the temporal stability of the spatial pattern is high because of stable structures in the canopy (e.g. large epiphytes) that show only minor changes during the short term observation period, and (3) the element concentrations decrease with increasing rainfall because of exhausting element pools in the canopy. The study area at 1950 m above sea level is located in the south Ecuadorian Andes far away from anthropogenic emission sources and marine influences. Rain and throughfall were collected from August to October 2005 on an event and within-event basis for five precipitation periods and analyzed for pH, K, Na, Ca, Mg, NH4+, Cl-, NO3-, PO43-, TN, TP and TOC. Throughfall amounts and most of the solutes showed a high spatial variability, thereby the variability of H+, K, Ca, Mg, Cl- and NO3- exceeded those from a Brazilian tropical rain forest. The temporal persistence of the spatial patterns was high for throughfall amounts and varied depending on the solute. Highly persistent time stability patterns were detected for K, Mg and TOC concentrations. Time stability patterns of solute deposition were somewhat weaker than for concentrations for most of the solutes. Epiphytes strongly affected time stability patterns in that collectors situated below thick moss mats or arboreal bromeliads were in large part responsible for the extreme persistence with low throughfall amounts and high ion concentrations (H+ showed low concentrations). Rainfall solute concentrations were low compared with a variety of other tropical lowland and montane forest sites and showed a small temporal variability during the study period for both between and within-event dynamics, respectively. Throughfall solute concentrations were more within the range when compared with other sites and showed highly variable within-event dynamics. For most of the solutes, within-event concentrations did not reach low, constant concentrations in later event stages, rather concentrations fluctuated (e.g. Cl-) or increased (e.g. K and TOC). The within-event throughfall solute concentration dynamics in this lower montane rain forest contrast to recent observations from lowland tropical rain forests in Panama and Brazil. The observed within-event patterns are attributed (1) to the influence of epiphytes and associated canopy humus, and (2) to low rainfall intensities.

Trace element concentrations in surface estuarine and marine sediments along the Mississippi Gulf Coast following Hurricane Katrina.

PubMed

Warren, Crystal; Duzgoren-Aydin, Nurdan S; Weston, James; Willett, Kristine L

2012-01-01

Hurricanes are relatively frequent ecological disturbances that may cause potentially long-term impacts to the coastal environment. Hurricane Katrina hit the Mississippi Gulf Coast in August 2005, and caused a storm surge with the potential to change the trace element content of coastal surface sediments. In this study, surface estuarine and marine sediments were collected monthly following the storm from ten sites along the Mississippi Gulf Coast (Mobile Bay, Grand Bay Bayous Heron and Cumbest, Pascagoula, Ocean Springs, Biloxi Gulf, Back Biloxi Bay, Gulfport Gulf, Gulfport Courthouse Rd, and Gulfport Marina). Concentrations of V, Cr, Mn, Fe, Co, Ni, Zn, As, Cd, and Pb were measured by inductively coupled plasma-mass spectrometry to evaluate their temporal and spatial variations in the year following Hurricane Katrina. Sediments were characterized by pH, particle size distribution and total carbon and nitrogen content. Trace element contents of the sediments were determined in both <2 mm and <63 μm grain size fractions. Results revealed no significant temporal and spatial variability in trace element concentrations, in either size fraction. Potential ecological risk of the sediments was assessed by using NOAA SQuiRTs' guideline values; most concentrations remained below probable adverse effects guidelines to marine organisms suggesting that trace elements redistributed by Hurricane Katrina would not cause an adverse impact on resident organisms. Instead, the concentrations of trace elements were site-dependent, with specific contaminants relating to the use of the area prior to Hurricane Katrina.

Ionospheric responses during equinox and solstice periods over Turkey

NASA Astrophysics Data System (ADS)

Karatay, Secil; Cinar, Ali; Arikan, Feza

2017-11-01

Ionospheric electron density is the determining variable for investigation of the spatial and temporal variations in the ionosphere. Total Electron Content (TEC) is the integral of the electron density along a ray path that indicates the total variability through the ionosphere. Global Positioning System (GPS) recordings can be utilized to estimate the TEC, thus GPS proves itself as a useful tool in monitoring the total variability of electron distribution within the ionosphere. This study focuses on the analysis of the variations of ionosphere over Turkey that can be grouped into anomalies during equinox and solstice periods using TEC estimates obtained by a regional GPS network. It is observed that noon time depletions in TEC distributions predominantly occur in winter for minimum Sun Spots Numbers (SSN) in the central regions of Turkey which also exhibit high variability due to midlatitude winter anomaly. TEC values and ionospheric variations at solstice periods demonstrate significant enhancements compared to those at equinox periods.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Yield response to landscape position under variable N for irrigated corn

USDA-ARS?s Scientific Manuscript database

Variable nutrient and water supply can result in spatial and temporal variation in crop yield within a given agricultural field. For the western Corn Belt, irrigated corn accounts for 58% of total annual corn production with the majority grown in Nebraska. Although irrigation decreases temporal yi...

TEMPORAL AND SPATIAL VARIABILITY OF FECAL INDICATOR BACTERIA: IMPLICATIONS FOR THE APPLICATION OF MST METHODOLOGIES TO DIFFERENTIATE SOURCES OF FECAL CONTAMINATION

EPA Science Inventory

Temporal variability in the gastrointestinal flora of animals impacting water resources with fecal material can be one of the factors producing low source identification rates when applying microbial source tracking (MST) methods. Understanding how bacterial species and genotype...

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

Investigating Temporal and Spatial Variations in Near Surface Water Content using GPR

NASA Astrophysics Data System (ADS)

Hubbard, S. S.; Grote, K.; Kowalsky, M. B.; Rubin, Y.

2001-12-01

Using only conventional point or well logging measurements, it is difficult to obtain information about water content with sufficient spatial resolution and coverage to be useful for near surface applications such as for input to vadose zone predictive models or for assisting with precision crop management. Prompted by successful results of a controlled ground penetrating radar (GPR) pilot study, we are investigating the applicability of GPR methods to estimate near surface water content at a study site within the Robert Mondavi vineyards in Napa County, California. Detailed information about soil variability and water content within vineyards could assist in estimation of plantable acreage, in the design of vineyard layout and in the design of an efficient irrigation/agrochemical application procedure. Our research at the winery study site involves investigation of optimal GPR acquisition and processing techniques, modeling of GPR attributes, and inversion of the attributes for water content information over space and time. A secondary goal of our project is to compare water content information obtained from the GPR data with information available from other types of measurements that are being used to assist in precision crop management. This talk will focus on point and spatial correlation estimation of water content obtained using GPR groundwave information only, and comparison of those estimates with information obtained from analysis of soils, TDR, neutron probe and remote sensing data sets. This comparison will enable us to 1) understand the potential of GPR for providing water content information in the very shallow subsurface, and to 2) investigate the interrelationships between the different types of measurements (and associated measurement scales) that are being utilized to characterize the shallow subsurface water content over space and time.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

Variability of 4D flow parameters when subjected to changes in MRI acquisition parameters using a realistic thoracic aortic phantom.

PubMed

Montalba, Cristian; Urbina, Jesus; Sotelo, Julio; Andia, Marcelo E; Tejos, Cristian; Irarrazaval, Pablo; Hurtado, Daniel E; Valverde, Israel; Uribe, Sergio

2018-04-01

To assess the variability of peak flow, mean velocity, stroke volume, and wall shear stress measurements derived from 3D cine phase contrast (4D flow) sequences under different conditions of spatial and temporal resolutions. We performed controlled experiments using a thoracic aortic phantom. The phantom was connected to a pulsatile flow pump, which simulated nine physiological conditions. For each condition, 4D flow data were acquired with different spatial and temporal resolutions. The 2D cine phase contrast and 4D flow data with the highest available spatio-temporal resolution were considered as a reference for comparison purposes. When comparing 4D flow acquisitions (spatial and temporal resolution of 2.0 × 2.0 × 2.0 mm 3 and 40 ms, respectively) with 2D phase-contrast flow acquisitions, the underestimation of peak flow, mean velocity, and stroke volume were 10.5, 10 and 5%, respectively. However, the calculated wall shear stress showed an underestimation larger than 70% for the former acquisition, with respect to 4D flow, with spatial and temporal resolution of 1.0 × 1.0 × 1.0 mm 3 and 20 ms, respectively. Peak flow, mean velocity, and stroke volume from 4D flow data are more sensitive to changes of temporal than spatial resolution, as opposed to wall shear stress, which is more sensitive to changes in spatial resolution. Magn Reson Med 79:1882-1892, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A multi-level analysis of the relationship between environmental factors and questing Ixodes ricinus dynamics in Belgium

PubMed Central

2012-01-01

Background Ticks are the most important pathogen vectors in Europe. They are known to be influenced by environmental factors, but these links are usually studied at specific temporal or spatial scales. Focusing on Ixodes ricinus in Belgium, we attempt to bridge the gap between current “single-sided” studies that focus on temporal or spatial variation only. Here, spatial and temporal patterns of ticks are modelled together. Methods A multi-level analysis of the Ixodes ricinus patterns in Belgium was performed. Joint effects of weather, habitat quality and hunting on field sampled tick abundance were examined at two levels, namely, sampling level, which is associated with temporal dynamics, and site level, which is related to spatial dynamics. Independent variables were collected from standard weather station records, game management data and remote sensing-based land cover data. Results At sampling level, only a marginally significant effect of daily relative humidity and temperature on the abundance of questing nymphs was identified. Average wind speed of seven days prior to the sampling day was found important to both questing nymphs and adults. At site level, a group of landscape-level forest fragmentation indices were highlighted for both questing nymph and adult abundance, including the nearest-neighbour distance, the shape and the aggregation level of forest patches. No cross-level effects or spatial autocorrelation were found. Conclusions Nymphal and adult ticks responded differently to environmental variables at different spatial and temporal scales. Our results can advise spatio-temporal extents of environment data collection for continuing empirical investigations and potential parameters for biological tick models. PMID:22830528

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.

Temporal and spatial variation of terpenoids in eastern hemlock (Tsuga canadensis) in relation to feeding by Adelges tsugae

Treesearch

Anthony F. Lagalante; Nyssa Lewis; Michael E. Montgomery; Kathleen S. Shields

2006-01-01

The terpenoid content of eastern hemlock (Tsuga canadensis) foliage was measured over an annual cycle of development from bud opening, shoot elongation, shoot maturation, to bud-break at the start of the next growing season. The objective was to determine if variation in terpenoid composition is linked with spatial and temporal feeding preferences of...

The Spatial and Temporal Distribution of Lunar Mare Basalts As Deduced From Analysis of Data for Lunar Meteorites

NASA Technical Reports Server (NTRS)

Nyquist, Laurence; Basilevsky, A.; Neukum, G.

2009-01-01

In this work we analyze chronological data for lunar meteorites with emphasis on the spatial and temporal distribution of lunar mare basalts. The data are mostly from the Lunar Meteorite Compendium (http://www-curator.jsc.nasa.gov/antmet/lmc/contents.cfm cited thereafter as Compendium) compiled by Kevin Righter and from the associated literature.

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: sensitivity to climatic variability.

Treesearch

Melisa L. Holman; David L. Peterson

2006-01-01

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Spatial and temporal variability of thermohaline properties in the Bay of Koper (northern Adriatic Sea)

NASA Astrophysics Data System (ADS)

Soczka Mandac, Rok; Žagar, Dušan; Faganeli, Jadran

2013-04-01

In this study influence of fresh water discharge on the spatial and temporal variability of thermohaline (TH) conditions is explored for the Bay of Koper (Bay). The Bay is subject to different driving agents: wind stress (bora, sirocco), tidal and seiches effect, buoyancy fluxes, general circulation of the Adriatic Sea and discharge of the Rizana and Badaševica rivers. These rivers have torrential characteristics that are hard to forecast in relation to meteorological events (precipitation). Therefore, during episodic events the spatial and temporal variability of TH properties in the Bay is difficult to determine [1]. Measurements of temperature, salinity and turbidity were conducted monthly on 35 sampling points in the period: June 2011 - December 2012. The data were processed and spatial interpolated with an objective analysis method. Furthermore, empirical orthogonal function analysis (EOF) [2] was applied to investigate spatial and temporal TH variations. Strong horizontal and vertical stratification was observed in the beginning of June 2011 due to high fresh water discharge of the Rizana (31 m3/s) and Badaševica (2 m3/s) rivers. The horizontal gradient (ΔT = 6°C) was noticed near the mouth of the Rizana river. Similar pattern was identified for salinity field on the boundary of the front where the gradient was ΔS = 20 PSU. Vertical temperature gradient was ΔT = 4°C while salinity gradient was ΔS = 18 PSU in the subsurface layer at depth of 3 m. Spatial analysis of the first principal component (86% of the total variance) shows uniform temperature distribution in the surface layer (1m) during the studied period. Furthermore, temporal variability of temperature shows seasonal variation with a minimum in February and maximum in August. This confirms that episodic events have a negligible effect on spatial and temporal variation of temperature in the subsurface layer. Further analysis will include application of EOF on the salinity, density and total suspended matter. Additionally, we will investigate the cross correlations between the above mentioned parameters with singular value decomposition method. Reference: 1. Faganeli, J., Planinc, R., Pezdic, J., Smodis, B., Stegnar, P., and Ogorelec, B. 1991. Marine geology of Gulf of Trieste (northern Adriatic): Geochemical aspects. Marine Geology, 99: 93-108. 2. Glover, M., Jenkins, J., and Doney, S. C. 2011. Modeling methods for marine science. Cambridge University Press, 571 p.

Temporal-spatial distribution of American bison (Bison bison) in a tallgrass prairie fire mosaic

USGS Publications Warehouse

Schuler, K.L.; Leslie, David M.; Shaw, J.H.; Maichak, E.J.

2006-01-01

Fire and bison (Bison bison) are thought to be historically responsible for shaping prairie vegetation in North America. Interactions between temporal-spatial distributions of bison and prescribed burning protocols are important in current restoration of tallgrass prairies. We examined dynamics of bison distribution in a patch-burned tallgrass prairie in the south-central United States relative to bison group size and composition, and burn age and temporal distribution. Bison formed larger mixed groups during summer and smaller sexually segregated groups the rest of the year, and bison selected dormant-season burn patches in the 1st posture growing season most often during spring and summer. Large bison herds selecting recently burned areas resulted in seasonally variable and concentrated grazing pressure that may substantially alter site-specific vegetation. These dynamics must be considered when reintroducing bison and fire into tallgrass prairie because variable outcomes of floral richness and structural complexity are likely depending on temporal-spatial distribution of bison. ?? 2006 American Society of Mammalogists.

Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow

NASA Astrophysics Data System (ADS)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward R.

2017-04-01

The development of paleoclimate streamflow reconstructions in the conterminous United States (CONUS) has provided water resource managers with improved insights into multidecadal and centennial scale variability that cannot be reliably detected using shorter instrumental records. Paleoclimate streamflow reconstructions have largely focused on individual catchments limiting the ability to quantify variability across the CONUS. The Living Blended Drought Atlas (LBDA), a spatially and temporally complete 555 year long paleoclimate record of summer drought across the CONUS, provides an opportunity to reconstruct and characterize streamflow variability at a continental scale. We explore the validity of the first paleoreconstructions of streamflow that span the CONUS informed by the LBDA targeting a set of U.S. Geological Survey streamflow sites. The reconstructions are skillful under cross validation across most of the country, but the variance explained is generally low. Spatial and temporal structures of streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. Nine spatially coherent clusters are identified. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s) and 1950s droughts. Decadal-scale variability was detected in the late 1900s in the western U.S., however, similar modes of temporal variability were rarely present prior to the 1950s. The twentieth century featured longer wet spells and shorter dry spells compared with the preceding 450 years. Streamflows in the Pacific Northwest and Northeast are negatively correlated with the central U.S. suggesting the potential to mitigate some drought impacts by balancing economic activities and insurance pools across these regions during major droughts.

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

2009-01-01

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Ethnopharmacological studies of Tribulus terrestris (Linn). in relation to its aphrodisiac properties.

PubMed

Mathur, Manish; Sundaramoorthy, S

2012-01-01

Synergism and antagonism impact of different plant metabolites present in crude fruit extract of Tribulus terrestris 'the herbal Viagra' have been studied. Variability in plant composition, biomass and metabolites concentration in different modules was significantly contributed by spatial factor. However the edhaphic parameters also changes with both spatial and temporal factors significantly. Fruit is the officinal part and the fruit production significantly related with soil nitrogen (P<0.01), whereas the soil nitrogen and pH also influenced the alkaloid content in fruit (P<0.05). The linear relation between fruit protein and fruit alkaloid (P<0.01) also observed and the relationship in between different soil parameters were established. Bioassay work confirmed its aphrodisiac properties, and site III is suggested for maximum biomass and high concentration of different metabolites.

Spatial and Temporal Soil Moisture Behavior in a Headwater Watershed of the Mantiqueira Range, Minas Gerais, Brazil

USDA-ARS?s Scientific Manuscript database

The characterization of temporal and spatial variability of soil moisture is highly relevant in watersheds for understanding the many hydrological and erosion processes, to better model the processes and apply them to conservation planning. The goal of this study was to map soil moisture of the surf...

Analysis of the spatial and temporal variability of mountain snowpack and terrestrial water storage in the Upper Snake River, USA

EPA Science Inventory

The spatial and temporal relationships of winter snowpack and terrestrial water storage (TWS) in the Upper Snake River were analyzed for water years 2001–2010 at a monthly time step. We coupled a regionally validated snow model with gravimetric measurements of the Earth’s water...

A spatial model of bird abundance as adjusted for detection probability

USGS Publications Warehouse

Gorresen, P.M.; Mcmillan, G.P.; Camp, R.J.; Pratt, T.K.

2009-01-01

Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: 'i'iwi Vestiaria coccinea and 'apapane Himatione sanguinea. ?? 2009 Ecography.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Spatial heterogeneities and variability of karst hydro-system : insights from geophysics

NASA Astrophysics Data System (ADS)

Champollion, C.; Fores, B.; Lesparre, N.; Frederic, N.

2017-12-01

Heterogeneous systems such as karsts or fractured hydro-systems are challenging for both scientist and groundwater resources management. Karsts heterogeneities prevent the comparison and moreover the combination of data representative of different scales: borehole water level can generally not be used directly to interpret spring flow dynamic for example. The spatial heterogeneity has also an impact on the temporal variability of groundwater transfer and storage. Karst hydro-systems have characteristic non linear relation between precipitation amount and discharge at the outlets with threshold effects and a large variability of groundwater transit times In the presentation, geophysical field experiments conducted in karst hydro-system in the south of France are used to investigate groundwater transfer and storage variability at a scale of a few hundred meters. We focus on the added value of both geophysical time-lapse gravity experiments and 2D ERT imaging of the subsurface heterogeneities. Both gravity and ERT results can only be interpreted with large ambiguity or some strong a priori: the relation between resistivity and water content is not unique; almost no information about the processes can be inferred from the groundwater stock variations. The present study demonstrate how the ERT and gravity field experiments can be interpreted together in a coherent scheme with less ambiguity. First the geological and hydro-meteorological context is presented. Then the ERT field experiment including the processing and the results are detailed in the section about geophysical imaging of the heterogeneities. The gravity double difference (S2D) time-lapse experiment is described in the section about geophysical monitoring of the temporal variability. The following discussion demonstrate the impact of both experiments on the interpretation in terms of processes and heterogeneities.

The Schaake shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields

USGS Publications Warehouse

Clark, M.R.; Gangopadhyay, S.; Hay, L.; Rajagopalan, B.; Wilby, R.

2004-01-01

A number of statistical methods that are used to provide local-scale ensemble forecasts of precipitation and temperature do not contain realistic spatial covariability between neighboring stations or realistic temporal persistence for subsequent forecast lead times. To demonstrate this point, output from a global-scale numerical weather prediction model is used in a stepwise multiple linear regression approach to downscale precipitation and temperature to individual stations located in and around four study basins in the United States. Output from the forecast model is downscaled for lead times up to 14 days. Residuals in the regression equation are modeled stochastically to provide 100 ensemble forecasts. The precipitation and temperature ensembles from this approach have a poor representation of the spatial variability and temporal persistence. The spatial correlations for downscaled output are considerably lower than observed spatial correlations at short forecast lead times (e.g., less than 5 days) when there is high accuracy in the forecasts. At longer forecast lead times, the downscaled spatial correlations are close to zero. Similarly, the observed temporal persistence is only partly present at short forecast lead times. A method is presented for reordering the ensemble output in order to recover the space-time variability in precipitation and temperature fields. In this approach, the ensemble members for a given forecast day are ranked and matched with the rank of precipitation and temperature data from days randomly selected from similar dates in the historical record. The ensembles are then reordered to correspond to the original order of the selection of historical data. Using this approach, the observed intersite correlations, intervariable correlations, and the observed temporal persistence are almost entirely recovered. This reordering methodology also has applications for recovering the space-time variability in modeled streamflow. ?? 2004 American Meteorological Society.

Probabilistic and spatially variable niches inferred from demography

Treesearch

Jeffrey M. Diez; Itamar Giladi; Robert Warren; H. Ronald Pulliam

2014-01-01

Summary 1. Mismatches between species distributions and habitat suitability are predicted by niche theory and have important implications for forecasting how species may respond to environmental changes. Quantifying these mismatches is challenging, however, due to the high dimensionality of species niches and the large spatial and temporal variability in population...

fMR-adaptation indicates selectivity to audiovisual content congruency in distributed clusters in human superior temporal cortex.

PubMed

van Atteveldt, Nienke M; Blau, Vera C; Blomert, Leo; Goebel, Rainer

2010-02-02

Efficient multisensory integration is of vital importance for adequate interaction with the environment. In addition to basic binding cues like temporal and spatial coherence, meaningful multisensory information is also bound together by content-based associations. Many functional Magnetic Resonance Imaging (fMRI) studies propose the (posterior) superior temporal cortex (STC) as the key structure for integrating meaningful multisensory information. However, a still unanswered question is how superior temporal cortex encodes content-based associations, especially in light of inconsistent results from studies comparing brain activation to semantically matching (congruent) versus nonmatching (incongruent) multisensory inputs. Here, we used fMR-adaptation (fMR-A) in order to circumvent potential problems with standard fMRI approaches, including spatial averaging and amplitude saturation confounds. We presented repetitions of audiovisual stimuli (letter-speech sound pairs) and manipulated the associative relation between the auditory and visual inputs (congruent/incongruent pairs). We predicted that if multisensory neuronal populations exist in STC and encode audiovisual content relatedness, adaptation should be affected by the manipulated audiovisual relation. The results revealed an occipital-temporal network that adapted independently of the audiovisual relation. Interestingly, several smaller clusters distributed over superior temporal cortex within that network, adapted stronger to congruent than to incongruent audiovisual repetitions, indicating sensitivity to content congruency. These results suggest that the revealed clusters contain multisensory neuronal populations that encode content relatedness by selectively responding to congruent audiovisual inputs, since unisensory neuronal populations are assumed to be insensitive to the audiovisual relation. These findings extend our previously revealed mechanism for the integration of letters and speech sounds and demonstrate that fMR-A is sensitive to multisensory congruency effects that may not be revealed in BOLD amplitude per se.

Analysis of the spatial and temporal distribution of malaria in an area of Northern Guatemala with seasonal malaria transmission.

PubMed

Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J

2018-06-23

The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.

Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

Treesearch

Jill M. Nakawatase; David L. Peterson

2006-01-01

For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

Characterizing spatial and temporal variability in methane gas-flux dynamics of subtropical wetlands in the Big Cypress National Preserve, Florida

NASA Astrophysics Data System (ADS)

Sirianni, M.; Comas, X.; Shoemaker, B.

2017-12-01

Wetland methane emissions are highly variable both in space and time, and are controlled by changes in certain biogeochemical controls (i.e. organic matter availability; redox potential) and/or other environmental factors (i.e. soil temperature; water level). Consequently, hot spots (areas with disproportionally high emissions) may develop where biogeochemical and environmental conditions are especially conducive for enhancing certain microbial processes such as methanogenesis. The 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. In addition to rainfall, hydroperiod, fire regime, elevation above mean sea level, dominant vegetation type and underlying geological controls contribute to the development and evolution of organic and calcitic soils found throughout the Preserve. Currently, the U.S. Geological Survey employs eddy covariance methods within the Preserve to quantify carbon and methane exchanges over several spatially extensive vegetation communities. While eddy covariance towers are a convenient tool for measuring gas exchanges at the ecosystem scale, their spatially extensive footprint (hundreds of meters) may mask smaller scale spatial variabilities that may be conducive to the development of hot spots. Similarly, temporal resolution (i.e. sampling effort) at scales smaller that the eddy covariance measurement footprint is important since low resolution data may overlook rapid emission events and the temporal variability of discrete hot spots. In this work, we intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a unique combination of ground penetrating radar (GPR), capacitance probes, gas traps, and time-lapse photography. By using an array of methods that vary in spatio-temporal resolution, we hope to better understand the uncertainties associated with measuring wetland methane fluxes across different spatial and temporal scales. Our results have implications for characterizing and refining methane flux estimates in subtropical peat soils that could be used for climate models.

Water availability as a driver of spatial and temporal variability in vegetation in the La Mancha plain (Spain): Implications for the land-surface energy, water and carbon budget

NASA Astrophysics Data System (ADS)

Los, Sietse

2017-04-01

Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.

Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

PubMed

Li, Mingming; Zhang, Xingchang; Zhen, Qing; Han, Fengpeng

2013-01-01

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute

2017-01-01

Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Urban noise functional stratification for estimating average annual sound level.

PubMed

Rey Gozalo, Guillermo; Barrigón Morillas, Juan Miguel; Prieto Gajardo, Carlos

2015-06-01

Road traffic noise causes many health problems and the deterioration of the quality of urban life; thus, adequate spatial noise and temporal assessment methods are required. Different methods have been proposed for the spatial evaluation of noise in cities, including the categorization method. Until now, this method has only been applied for the study of spatial variability with measurements taken over a week. In this work, continuous measurements of 1 year carried out in 21 different locations in Madrid (Spain), which has more than three million inhabitants, were analyzed. The annual average sound levels and the temporal variability were studied in the proposed categories. The results show that the three proposed categories highlight the spatial noise stratification of the studied city in each period of the day (day, evening, and night) and in the overall indicators (L(And), L(Aden), and L(A24)). Also, significant differences between the diurnal and nocturnal sound levels show functional stratification in these categories. Therefore, this functional stratification offers advantages from both spatial and temporal perspectives by reducing the sampling points and the measurement time.

The Ocean's Role in Outlet Glacier Variability: A Case Study from Uummannaq, Greenland

NASA Astrophysics Data System (ADS)

Sutherland, D.; Catania, G. A.; Bartholomaus, T. C.; Nash, J. D.; Shroyer, E.; Walker, R. T.; Stearns, L. A.

2014-12-01

The dynamics controlling the coupling between fjord circulation and outlet glacier movement are poorly understood. Here, we use oceanographic data collected from 2013-2014 from two west Greenland fjords, Rink Isbrae and Kangerdlugssup Sermerssua, to constrain the spatial and temporal variability observed in fjord circulation. We aim to quantify the ocean's role, if any, in explaining the marked differences in glacier behavior from two systems that are in close proximity to one another. Combining time series data from a set of subsurface moorings with repeat transects in each fjord allows an unprecedented look at the temporal and spatial variability in circulation. We find significant differences in the variability in each fjord and discuss the implications for the glaciers.

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content and uncertainties of the hydrologic and climate measurements. Assessment of spatial variations in the model parameters and predictions provides an improved understanding of how much of the hydrologic response to land use, climate, and other properties is unique to specific locations versus more universally observed across catchments of the SRB. This approach advances understanding of water cycle variability at any location throughout the stream network, as a function of both landscape characteristics (e.g., soils, vegetation, land use) and external forcings (e.g., precipitation quantity and frequency). These improvements in predictions of streamflow dynamics will advance the ability to predict spatial and temporal variability in key solutes, such as nutrients, and their delivery to the Chesapeake Bay.

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

Halambage Upul Deepthike; Robin Tecon; Gerry van Kooten

In the wake of the 1989 Exxon Valdez oil spill, spatially and temporally spill-correlated biological effects consistent with polycyclic aromatic hydrocarbon (PAH) exposure were observed. Some works have proposed that confounding sources from local source rocks, prominently coals, are the provenance of the PAHs. Representative coal deposits along the southeast Alaskan coast (Kulthieth Formation) were sampled and fully characterized chemically and geologically. The coals have variable but high total organic carbon content, technically classifying as coals and coaly shale, and highly varying PAH contents. Even for coals with high PAH content (4000 ppm total PAHs), a PAH-sensitive bacterial biosensor demonstratesmore » nondetectable bioavailability as quantified, based on naphthalene as a test calibrant. These results are consistent with studies indicating that materials such as coals strongly diminish the bioavailability of hydrophobic organic compounds and support previous work suggesting that hydrocarbons associated with the regional background in northern Gulf of Alaska marine sediments are not appreciably bioavailable. 44 refs., 4 figs., 2 tabs.« less

Spatio-temporal variability of faunal and floral assemblages in Mediterranean temporary wetlands.

PubMed

Rouissi, Maya; Boix, Dani; Muller, Serge D; Gascón, Stéphanie; Ruhí, Albert; Sala, Jordi; Bouattour, Ali; Ben Haj Jilani, Imtinen; Ghrabi-Gammar, Zeineb; Ben Saad-Limam, Samia; Daoud-Bouattour, Amina

2014-12-01

Six temporary wetlands in the region of Sejenane (Mogods, NW Tunisia) were studied in order to characterize the aquatic flora and fauna and to quantify their spatio-temporal variability. Samplings of aquatic fauna, phytosociological relevés, and measurements of the physicochemical parameters of water were taken during four different field visits carried out during the four seasons of the year (November 2009-July 2010). Despite the strong anthropic pressures on them, these temporary wetlands are home to rich and diversified biodiversity, including rare and endangered species. Spatial and temporal variations affect fauna and flora differently, as temporal variability influences the fauna rather more than the plants, which are relatively more dependent on spatial factors. These results demonstrate the interest of small water bodies for maintaining biodiversity at the regional level, and thus underscore the conservation issues of Mediterranean temporary wetlands that are declining on an ongoing basis currently. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Spatial and temporal relations in conditioned reinforcement and observing behavior

PubMed Central

Bowe, Craig A.; Dinsmoor, James A.

1983-01-01

In Experiment 1, depressing one perch produced stimuli indicating which of two keys, if pecked, could produce food (spatial information) and depressing the other perch produced stimuli indicating whether a variable-interval or an extinction schedule was operating (temporal information). The pigeons increased the time they spent depressing the perch that produced the temporal information but did not increase the time they spent depressing the perch that produced the spatial information. In Experiment 2, pigeons that were allowed to produce combined spatial and temporal information did not acquire the perch pressing any faster or maintain it at a higher level than pigeons allowed to produce only temporal information. Later, when perching produced only spatial information, the time spent depressing the perch eventually declined. The results are not those implied by the statement that information concerning biologically important events is reinforcing but are consistent with an interpretation in terms of the acquisition of reinforcing properties by a stimulus associated with a higher density of primary reinforcement. PMID:16812316

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

Combined use of remote sensing and continuous monitoring to analyse the variability of suspended-sediment concentrations in San Francisco Bay, California

USGS Publications Warehouse

Ruhl, C.A.; Schoellhamer, D.H.; Stumpf, R.P.; Lindsay, C.L.

2001-01-01

Analysis of suspended-sediment concentration data in San Francisco Bay is complicated by spatial and temporal variability. In situ optical backscatterance sensors provide continuous suspended-sediment concentration data, but inaccessibility, vandalism, and cost limit the number of potential monitoring stations. Satellite imagery reveals the spatial distribution of surficial-suspended sediment concentrations in the Bay; however, temporal resolution is poor. Analysis of the in situ sensor data in conjunction with the satellite reflectance data shows the effects of physical processes on both the spatial and temporal distribution of suspended sediment in San Francisco Bay. Plumes can be created by large freshwater flows. Zones of high suspended-sediment concentrations in shallow subembayments are associated with wind-wave resuspension and the spring-neap cycle. Filaments of clear and turbid water are caused by different transport processes in deep channels, as opposed to adjacent shallow water.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

Spatial variability of throughfall in a stand of Scots pine (Pinus sylvestris L.) with deciduous admixture as influenced by canopy cover and stem distance

NASA Astrophysics Data System (ADS)

Kowalska, Anna; Boczoń, Andrzej; Hildebrand, Robert; Polkowska, Żaneta

2016-07-01

Vegetation cover affects the amount of precipitation, its chemical composition and its spatial distribution, and this may have implications for the distribution of water, nutrients and contaminants in the subsurface soil layer. The aim of this study was a detailed diagnosis of the spatio-temporal variability in the amount of throughfall (TF) and its chemical components in a 72-year-old pine stand with an admixture of oak and birch. The spatio-temporal variability in the amount of TF water and the concentrations and deposition of the TF components were studied. The components that are exchanged in canopy (H+, K, Mg, Mn, DOC, NH4+) were more variable than the components whose TF deposition is the sum of wet and dry (including gas) deposition and which undergo little exchange in the canopy (Na, Cl, NO3-, SO42-). The spatial distribution was temporally stable, especially during the leafed period. This study also investigated the effect of the selected pine stand characteristics on the spatial distribution of throughfall and its chemical components; the characteristics included leaf area index (LAI), the proportion of the canopy covered by deciduous species and pine crowns, and the distance from the nearest tree trunk. The LAI measured during the leafed and leafless periods had the greatest effect on the spatial distribution of TF deposition. No relationship was found between the spatial distribution of the amount of TF water and (i) the LAI; (ii) the canopy cover of broadleaf species or pines; or (iii) the distance from the trunks.

Analysis of the historical precipitation in the South East Iberian Peninsula at different spatio-temporal scale. Study of the meteorological drought

NASA Astrophysics Data System (ADS)

Fernández-Chacón, Francisca; Pulido-Velazquez, David; Jiménez-Sánchez, Jorge; Luque-Espinar, Juan Antonio

2017-04-01

Precipitation is a fundamental climate variable that has a pronounced spatial and temporal variability on a global scale, as well as at regional and sub-regional scales. Due to its orographic complexity and its latitude the Iberian Peninsula (IP), located to the west of the Mediterranean Basin between the Atlantic Ocean and the Mediterranean Sea, has a complex climate. Over the peninsula there are strong north-south and east-west gradients, as a consequence of the different low-frequency atmospheric patterns, and he overlap of these over the year will be determinants in the variability of climatic variables. In the southeast of the Iberian Peninsula dominates a dry Mediterranean climate, the precipitation is characterized as being an intermittent and discontinuous variable. In this research information coming from the Spain02 v4 database was used to study the South East (SE) IP for the 1971-2010 period with a spatial resolution of 0.11 x 0.11. We analysed precipitation at different time scale (daily, monthly, seasonal, annual,…) to study the spatial distribution and temporal tendencies. The high spatial, intra-annual and inter-annual climatic variability observed makes it necessary to propose a climatic regionalization. In addition, for the identified areas and subareas of homogeneous climate we have analysed the evolution of the meteorological drought for the same period at different time scales. The standardized precipitation index has been used at 12, 24 and 48 month temporal scale. The climatic complexity of the area determines a high variability in the drought characteristics, duration, intensity and frequency in the different climatic areas. This research has been supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 project for the data provided for this study.

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

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.

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Human Plague Risk: Spatial-Temporal Models

NASA Technical Reports Server (NTRS)

Pinzon, Jorge E.

2010-01-01

This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

Spatially and temporally variable fire regime on Rincon Peak, Arizona, USA

Treesearch

Jose M. Iniguez; Thomas W. Swetnam; Christopher H. Baisa

2009-01-01

Spatial and temporal patterns of fire history are affected by factors such as topography, vegetation, and climate. It is unclear, however, how these factors influenced fire history patterns in small isolated forests, such as that found on Rincon Peak, a "sky island" mountain range in southern Arizona, USA. We reconstructed the fire history of Rincon Peak to...

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

NASA Astrophysics Data System (ADS)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

Prospects and pitfalls of occupational hazard mapping: 'between these lines there be dragons'.

PubMed

Koehler, Kirsten A; Volckens, John

2011-10-01

Hazard data mapping is a promising new technique that can enhance the process of occupational exposure assessment and risk communication. Hazard maps have the potential to improve worker health by providing key input for the design of hazard intervention and control strategies. Hazard maps are developed with aid from direct-reading instruments, which can collect highly spatially and temporally resolved data in a relatively short period of time. However, quantifying spatial-temporal variability in the occupational environment is not a straightforward process, and our lack of understanding of how to ascertain and model spatial and temporal variability is a limiting factor in the use and interpretation of workplace hazard maps. We provide an example of how sources of and exposures to workplace hazards may be mischaracterized in a hazard map due to a lack of completeness and representativeness of collected measurement data. Based on this example, we believe that a major priority for research in this emerging area should focus on the development of a statistical framework to quantify uncertainty in spatially and temporally varying data. In conjunction with this need is one for the development of guidelines and procedures for the proper sampling, generation, and evaluation of workplace hazard maps.

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

PubMed

Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

2018-01-01

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

Spatial variability and temporal changes in the trace metal content of soils: implications for mine restoration plan.

PubMed

Chandra, Rachna; Prusty, B Anjan Kumar; Azeez, P A

2014-06-01

Trace metals in soils may be inherited from the parent materials or added to the system due to anthropogenic activities. In proposed mining areas, trace metals become an integral part of the soil system. Usually, researchers undertake experiments on plant species selection (for the restoration plan) only after the termination of mining activities, i.e. without any pre-mining information about the soil-plant interactions. Though not shown in studies, it is clear that several recovery plans remain unsuccessful while carrying out restoration experiments. Therefore, we hypothesize that to restore the area effectively, it is imperative to consider the pre-mining scenario of metal levels in parent material as well as the vegetation ecology of the region. With these specifics, we examined the concentrations of trace metals in parent soils at three proposed bauxite locations in the Eastern Ghats, India, and compared them at a spatio-temporal scale. Vegetation quantification and other basic soil parameters accounted for establishing the connection between soil and plants. The study recorded significant spatial heterogeneity in trace metal concentrations and the role of vegetation on metal availability. Oxidation reduction potential (ORP), pH and cation exchange capacity (CEC) directly influenced metal content, and Cu and Ni were lithogenic in origin. It implies that for effective restoration plant species varies for each geological location.

Monitoring pasture variability: optical OptRx(®) crop sensor versus Grassmaster II capacitance probe.

PubMed

Serrano, João M; Shahidian, Shakib; Marques da Silva, José Rafael

2016-02-01

Estimation of pasture productivity is an important step for the farmer in terms of planning animal stocking, organizing animal lots, and determining supplementary feeding needs throughout the year. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Two types of sensors were evaluated: an active optical sensor ("OptRx(®)," which measures the NDVI, "Normalized Difference Vegetation Index") and a capacitance probe ("GrassMaster II" which estimates plant mass). The results showed the potential of NDVI for monitoring the evolution of spatial and temporal patterns of vegetative growth of biodiverse pasture. Higher NDVI values were registered as pasture approached its greatest vegetative vigor, with a significant fall in the measured NDVI at the end of Spring, when the pasture began to dry due to the combination of higher temperatures and lower soil moisture content. This index was also effective for identifying different plant species (grasses/legumes) and variability in pasture yield. Furthermore, it was possible to develop calibration equations between the capacitance and the NDVI (R(2) = 0.757; p < 0.01), between capacitance and GM (R(2) = 0.799; p < 0.01), between capacitance and DM (R(2) =0.630; p < 0.01), between NDVI and GM (R(2) = 0.745; p < 0.01), and between capacitance and DM (R(2) = 0.524; p < 0.01). Finally, a direct relationship was obtained between NDVI and pasture moisture content (PMC, in %) and between capacitance and PMC (respectively, R(2) = 0.615; p < 0.01 and R(2) = 0.561; p < 0.01) in Alentejo dryland farming systems.

Entropy of space-time outcome in a movement speed-accuracy task.

PubMed

Hsieh, Tsung-Yu; Pacheco, Matheus Maia; Newell, Karl M

2015-12-01

The experiment reported was set-up to investigate the space-time entropy of movement outcome as a function of a range of spatial (10, 20 and 30 cm) and temporal (250-2500 ms) criteria in a discrete aiming task. The variability and information entropy of the movement spatial and temporal errors considered separately increased and decreased on the respective dimension as a function of an increment of movement velocity. However, the joint space-time entropy was lowest when the relative contribution of spatial and temporal task criteria was comparable (i.e., mid-range of space-time constraints), and it increased with a greater trade-off between spatial or temporal task demands, revealing a U-shaped function across space-time task criteria. The traditional speed-accuracy functions of spatial error and temporal error considered independently mapped to this joint space-time U-shaped entropy function. The trade-off in movement tasks with joint space-time criteria is between spatial error and timing error, rather than movement speed and accuracy. Copyright © 2015 Elsevier B.V. All rights reserved.

Longterm and spatial variability of Aerosol optical properties measured by sky radiometer in Japan sites

NASA Astrophysics Data System (ADS)

Aoki, K.

2016-12-01

Aerosols and cloud play an important role in the climate change. We started the long-term monitoring of aerosol and cloud optical properties since 1990's by using sky radiometer (POM-01, 02; Prede Co. Ltd., Japan). We provide the information, in this presentation, on the aerosol optical properties with respect to their temporal and spatial variability in Japan site (ex. Sapporo, Toyama, Kasuga and etc). The global distributions of aerosols have been derived from earth observation satellite and have been simulated in numerical models, which assume optical parameters. However, these distributions are difficult to derive because of variability in time and space. Therefore, Aerosol optical properties were investigated using the measurements from ground-based and ship-borne sky radiometer. The sky radiometer is an automatic instrument that takes observations only in daytime under the clear sky conditions. Observation of diffuse solar intensity interval was made every ten or five minutes by once. The aerosol optical properties were computed using the SKYRAD.pack version 4.2. The obtained Aerosol optical properties (Aerosol optical thickness, Ångström exponent, Single scattering albedo, and etc.) and size distribution volume clearly showed spatial and temporal variability in Japan area. In this study, we present the temporal and spatial variability of Aerosol optical properties at several Japan sites, applied to validation of satellite and numerical models. This project is validation satellite of GCOM-C, JAXA. The GCOM-C satellite scheduled to be launched in early 2017.

Spatio-Temporal Evolution and Scaling Properties of Human Settlements (Invited)

NASA Astrophysics Data System (ADS)

Small, C.; Milesi, C.; Elvidge, C.; Baugh, K.; Henebry, G. M.; Nghiem, S. V.

2013-12-01

Growth and evolution of cities and smaller settlements is usually studied in the context of population and other socioeconomic variables. While this is logical in the sense that settlements are groups of humans engaged in socioeconomic processes, our means of collecting information about spatio-temporal distributions of population and socioeconomic variables often lack the spatial and temporal resolution to represent the processes at scales which they are known to occur. Furthermore, metrics and definitions often vary with country and through time. However, remote sensing provides globally consistent, synoptic observations of several proxies for human settlement at spatial and temporal resolutions sufficient to represent the evolution of settlements over the past 40 years. We use several independent but complementary proxies for anthropogenic land cover to quantify spatio-temporal (ST) evolution and scaling properties of human settlements globally. In this study we begin by comparing land cover and night lights in 8 diverse settings - each spanning gradients of population density and degree of land surface modification. Stable anthropogenic night light is derived from multi-temporal composites of emitted luminance measured by the VIIRS and DMSP-OLS sensors. Land cover is represented as mixtures of sub-pixel fractions of rock, soil and impervious Substrates, Vegetation and Dark surfaces (shadow, water and absorptive materials) estimated from Landsat imagery with > 94% accuracy. Multi-season stability and variability of land cover fractions effectively distinguishes between spectrally similar land covers that corrupt thematic classifications based on single images. We find that temporal stability of impervious substrates combined with persistent shadow cast between buildings results in temporally stable aggregate reflectance across seasons at the 30 m scale of a Landsat pixel. Comparison of night light brightness with land cover composition, stability and variability yields several consistent relationships that persist across a variety of settlement types and physical environments. We use the multiple threshold method of Small et al (2011) to represent a continuum of settlement density by segmenting both night light brightness and multi-season land cover characteristics. Rank-size distributions of spatially contiguous segments quantify scaling and connectivity of land cover. Spatial and temporal evolution of rank-size distributions is consistent with power laws as suggested by Zipf's Law for city size based on population. However, unlike Zipf's Law, the observed distributions persist to global scales in which the larger agglomerations are much larger than individual cities. The scaling relations observed extend from the scale of cities and smaller settlements up to vast spatial networks of interconnected settlements.

The value of long-term stream invertebrate data collected by citizen scientists

Treesearch

Patrick M. Edwards; Stefano Goffredo

2016-01-01

The purpose of this investigation was to systematically examine the variability associated with temporally-oriented invertebrate data collected by citizen scientists and consider the value of such data for use in stream management. Variability in invertebrate data was estimated for three sources of variation: sampling, within-reach spatial and long-term temporal. Long-...

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 ...

Time and space variability of spectral estimates of atmospheric pressure

NASA Technical Reports Server (NTRS)

Canavero, Flavio G.; Einaudi, Franco

1987-01-01

The temporal and spatial behaviors of atmospheric pressure spectra over the northern Italy and the Alpine massif were analyzed using data on surface pressure measurements carried out at two microbarograph stations in the Po Valley, one 50 km south of the Alps, the other in the foothills of the Dolomites. The first 15 days of the study overlapped with the Alpex Intensive Observation Period. The pressure records were found to be intrinsically nonstationary and were found to display substantial time variability, implying that the statistical moments depend on time. The shape and the energy content of spectra depended on different time segments. In addition, important differences existed between spectra obtained at the two stations, indicating a substantial effect of topography, particularly for periods less than 40 min.

Dispersal kernels and their drivers captured with a hydrodynamic model and spatial indices: A case study on anchovy ( Engraulis encrasicolus) early life stages in the Bay of Biscay

NASA Astrophysics Data System (ADS)

Huret, M.; Petitgas, P.; Woillez, M.

2010-10-01

Dispersal of fish early life stages explains part of the recruitment success, through interannual variability in spawning, transport and survival. Dispersal results from a complex interaction between physical and biological processes acting at different temporal and spatial scales, and at the individual or population level. In this paper we quantify the response of anchovy egg and larval dispersal in the Bay of Biscay to the following sources of variability: vertical larval behaviour, drift duration, adult spawning location and timing, and spatio-temporal variability in the hydrodynamics. We use simulations of Lagrangian trajectories in a 3-dimensional hydrodynamic model, as well as spatial indices describing different properties of the dispersal kernel: the mean transport (distance, direction), its variance, occupation of space by particles and their aggregation. We show that larval drift duration has a major impact on the dispersion at scales of ˜100 km, but that vertical behaviour becomes dominant reducing dispersion at scales of ˜1-10 km. Spawning location plays a major role in explaining connectivity patterns, in conjunction with spawning temporal variability. Interannual variability in the circulation dominates over seasonal variability. However, seasonal patterns become predominant for coastal spawning locations, revealing a recurrent shift in the direction of dispersal during the anchovy spawning season.

The modulation of EEG variability between internally- and externally-driven cognitive states varies with maturation and task performance

PubMed Central

Willatt, Stephanie E.; Cortese, Filomeno; Protzner, Andrea B.

2017-01-01

Increasing evidence suggests that brain signal variability is an important measure of brain function reflecting information processing capacity and functional integrity. In this study, we examined how maturation from childhood to adulthood affects the magnitude and spatial extent of state-to-state transitions in brain signal variability, and how this relates to cognitive performance. We looked at variability changes between resting-state and task (a symbol-matching task with three levels of difficulty), and within trial (fixation, post-stimulus, and post-response). We calculated variability with multiscale entropy (MSE), and additionally examined spectral power density (SPD) from electroencephalography (EEG) in children aged 8–14, and in adults aged 18–33. Our results suggest that maturation is characterized by increased local information processing (higher MSE at fine temporal scales) and decreased long-range interactions with other neural populations (lower MSE at coarse temporal scales). Children show MSE changes that are similar in magnitude, but greater in spatial extent when transitioning between internally- and externally-driven brain states. Additionally, we found that in children, greater changes in task difficulty were associated with greater magnitude of modulation in MSE. Our results suggest that the interplay between maturational and state-to-state changes in brain signal variability manifest across different spatial and temporal scales, and influence information processing capacity in the brain. PMID:28750035

The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters

NASA Astrophysics Data System (ADS)

Webb, R. W.; Williams, M. W.; Erickson, T. A.

2018-02-01

Snowmelt is an important part of the hydrologic cycle and ecosystem dynamics for headwater systems. However, the physical process of water flow through snow is a poorly understood aspect of snow hydrology as meltwater flow paths tend to be highly complex. Meltwater flow paths diverge and converge as percolating meltwater reaches stratigraphic layer interfaces creating high spatial variability. Additionally, a snowpack is temporally heterogeneous due to rapid localized metamorphism that occurs during melt. This study uses a snowmelt lysimeter array at tree line in the Niwot Ridge study area of northern Colorado. The array is designed to address the issue of spatial and temporal variability of basal discharge at 105 locations over an area of 1,300 m2. Observed coefficients of variation ranged from 0 to almost 10 indicating more variability than previously observed, though this variability decreased throughout each melt season. Snowmelt basal discharge also significantly increases as snow depth decreases displaying a cluster pattern that peaks during weeks 3-5 of the snowmelt season. These results are explained by the flow of meltwater along snow layer interfaces. As the snowpack becomes less stratified through the melt season, the pattern transforms from preferential flow paths to uniform matrix flow. Correlation ranges of the observed basal discharge correspond to a mean representative elementary area of 100 m2, or a characteristic length of 10 m. Snowmelt models representing processes at scales less than this will need to explicitly incorporate the spatial variability of snowmelt discharge and meltwater flow paths through snow between model pixels.

Spatial and temporal distribution patterns of benthic foraminifera in the Northeast Water Polynya, Greenland

NASA Astrophysics Data System (ADS)

Ahrens, Michael J.; Graf, Gerhard; Altenbach, Alexander V.

1997-01-01

Abundance, biofacies and ATP content of benthic foraminifera (>63 μm) were studied in the Northeast Water (NEW) Polynya (77-81°N, 5-17°W) over the ice-free summer, 1993, to investigate how a polynya system might influence the underlying benthic community. In the living assemblage, distinguished by Rose Bengal staining, over 60 taxa could be identified. The biofacies identified was similar to that of other Arctic shelf habitats. Foraminifera were counted in 3 size fractions (63-125 μm, 125-250 μm and >250 μm), with 65% of the foraminifera occurring in the smallest size fraction (63-125 μm). Total abundances (>63 μm) in the uppermost 1 cm averaged approximately 200 ind/10 cm 3 and declined down-core, as did the number of species. Abundances and species composition correlated positively with sediment chlorophyll and ATP content, with maxima occurring in the shallower northern regions of the polynya, suggesting a general dependence on food. Foraminera biomass was estimated to be 0.1-0.3 g C org/m 2. Abundances, biomass and ATP content were comparable to ice-free, deep-sea regions in the Norwegian Sea. Temporal changes observed over a 2 month period at one location were difficult to distinguish from spatial and analytical variability. Contrary to expectations, growth was unpronounced at the community and at a species level, implying either a delayed response of the benthic foraminiferal community to food inputs from the overlying water column or the presence of biological limitations other than food, such as predation.

Lunar Meteorites: What They Tell us About the Spatial and Temporal Distribution of Mare Basalts

NASA Technical Reports Server (NTRS)

Basilevsky, A. T.; Neukum, G.; Nyquist, L.

2010-01-01

Here we analyze the chronology and statistical distribution of lunar meteorites with emphasis on the spatial and temporal distribution of lunar mare basalts. The data are mostly from the Lunar Meteorite Compendium (http://www-curator.jsc.nasa.gov/ antmet/ lmc/contents.cfm cited hereafter as Compendium) compiled by Kevin Righter, NASA Johnson Space Center, and from the associated literature. The Compendium was last modified on May 12, 2008.

Remotely Sensed Spatio-Temporal Variability of Snow Cover in Himalayan Region with Perspective of Climate Change

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

Climate change and its impact of water resource have gained tremendous attention among scientific committee, governments and other stakeholders since last couple of decades, especially in Himalayan region. In this study, we purpose remotely sensed measurements to monitor snow cover, both spatially and temporal, and assess climate change impact on water resource. The snow cover data from MODIS satellite (2000-2010) have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions, respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

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.

A review on the sources and spatial-temporal distributions of Pb in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhang, Jie; Wang, Ming; Zhu, Sixi; Wu, Yunjie

2017-12-01

This paper provided a review on the source, spatial-distribution, temporal variations of Pb in Jiaozhou Bay based on investigation of Pb in surface and waters in different seasons during 1979-1983. The source strengths of Pb sources in Jiaozhou Bay were showing increasing trends, and the pollution level of Pb in this bay was slight or moderate in the early stage of reform and opening-up. Pb contents in the marine bay were mainly determined by the strength and frequency of Pb inputs from human activities, and Pb could be moving from high content areas to low content areas in the ocean interior. Surface waters in the ocean was polluted by human activities, and bottom waters was polluted by means of vertical water’s effect. The process of spatial distribution of Pb in waters was including three steps, i.e., 1), Pb was transferring to surface waters in the bay, 2) Pb was transferring to surface waters, and 3) Pb was transferring to and accumulating in bottom waters.

Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia.

PubMed

Zhang, Jianfeng; Huang, Zirui; Chen, Yali; Zhang, Jun; Ghinda, Diana; Nikolova, Yuliya; Wu, Jinsong; Xu, Jianghui; Bai, Wenjie; Mao, Ying; Yang, Zhong; Duncan, Niall; Qin, Pengmin; Wang, Hao; Chen, Bing; Weng, Xuchu; Northoff, Georg

2018-05-01

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC). © 2018 Wiley Periodicals, Inc.

The energy balance of an urban area: Examining temporal and spatial variability through measurements, remote sensing and modeling

NASA Astrophysics Data System (ADS)

Offerle, Brian

Urban environmental problems related to air quality, thermal stress, issues of water demand and quality, all of which are linked directly or indirectly to urban climate, are emerging as major environmental concerns at the start of the 21st century. Thus there are compelling social, political and economic, and scientific reasons that make the study and understanding of the fundamental causes of urban climates critically important. This research addresses these topics through an intensive study of the surface energy balance of Lodz, Poland. The research examines the temporal variability in long-term measurements of urban surface-atmosphere exchange at a downtown location and the spatial variability of this exchange over distinctly different neighborhoods using shorter-term observations. These observations provide the basis for an evaluation of surface energy balance models. Monthly patterns in energy exchange are consistent from year-to-year with variability determined by net radiation and the timing and amount of precipitation. Spatial variability can be determined from plan area fractions of vegetation and impervious surface, though heat storage exerts a strong control on shorter term variability of energy exchange, within and between locations in an urban area. Anthropogenic heat fluxes provide most of the energy driving surface-atmosphere exchange in winter, From a modeling perspective, sensible heat fluxes can be reliably determined from radiometrically sensed surface temperatures and spatially representative surface-atmosphere exchange in an urban area can be determined from satellite remote sensing products. Models of the urban surface energy balance showed good agreement with mean values of energy exchange and under most conditions represented the temporal variability due to synoptic and shorter time scale forcing well.

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.

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.

2018-06-01

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

Exploring the Linkage of Sea Surface Temperature Variability on Three Spatial Scales

NASA Astrophysics Data System (ADS)

Luo, L.; Capone, D. G.; Hutchins, D.; Kiefer, D.

2011-12-01

As part of a project examining climate change in the Southern California Bight at the University of Southern California, we studied the linkage of the variability of sea surface temperature across three nested spatial scales, the north Pacific Basin, the West Coast of North American, and the Southern California Bight. Specifically, we analyzed daily GHRSST images between September 1981 and July 2009. In order to remove seasonal changes in temperature and focus upon differences between years, we calculate weekly mean temperature for each pixel from the time series, and then subjected the anomalies for the 3 spatial scales to empirical orthogonal function (EOF) analysis. The corresponding temporal expansion coefficients and spatial components (eigenvector) for each EOF mode were then generated to examine the temporal and spatial patterns of SST change. The results showed that the El Nino Southern Oscillation (ENSO) has a clear influence on the SST variability across all the three spatial scales, especially the 1st EOF mode which represents the largest variance. The comparison between the time coefficients of the 1st EOF mode and the Oceanic Nino Index (ONI) suggested that the EOF mode 1 of the Pacific Basin region matched well with almost all the El Nino and La Nina signals while the West Coast of North American captured only the strong signals and the Southern California Bight captures still fewer of the signals. This clearly indicated that the Southern California Bight is relatively insensitive to ENSO signal relative to other locations along the West Coast. The 1st EOF Mode for the West Coast of North American was also clearly influenced by upwelling. The cross correlation coefficient between each pair of the EOF mode 1 temporal expansion coefficients for the three spatial scales suggested that they were significantly correlated to each other. The effect of the Pacific Decadal Oscillation (PDO) on the SST change was also demonstrated by the temporal variability of the temporal expansion coefficients of the 2nd EOF mode. However, the correlations of 2nd EOF mode time coefficients between the three scales appeared relatively low compared the 1st EOF mode. In summary sea surface temperature in the Southern California Bight behaves like a node that is relatively insensitive to ENSO, PDO, and upwelling signals.

Spatio-temporal dynamics of ocean conditions and forage taxa reveal regional structuring of seabird–prey relationships.

PubMed

Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J

Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the implementation of protective measures could maintain functions and productivity of central place foraging predators.

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.)

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Spatial and temporal variation of sources contributing to quasi-ultrafine particulate matter PM0.36 in Augsburg, Germany.

PubMed

Li, Fengxia; Schnelle-Kreis, Jürgen; Cyrys, Josef; Wolf, Kathrin; Karg, Erwin; Gu, Jianwei; Orasche, Jürgen; Abbaszade, Gülcin; Peters, Annette; Zimmermann, Ralf

2018-08-01

to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources. 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions. 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby. temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP. Copyright © 2018 Elsevier B.V. All rights reserved.

Global Variability and Changes in Ocean Total Alkalinity from Aquarius Satellite

NASA Astrophysics Data System (ADS)

Fine, R. A.; Willey, D. A.; Millero, F. J., Jr.

2016-02-01

To document effects of ocean acidification it is important to have an understanding of the processes and parameters that influence alkalinity. Alkalinity is a gauge on the ability of seawater to neutralize acids. We use Aquarius satellite data, which allow unprecedented global mapping of surface total alkalinity as it correlates strongly with salinity and to a lesser extent with temperature. Spatial variability in total alkalinity and salinity exceed temporal variability, the latter includes seasonal and differences compared to climatological data. The northern hemisphere has more spatial and monthly variability in total alkalinity and salinity, while less variability in Southern Ocean alkalinity is due to less salinity variability and upwelling of waters enriched in alkalinity. Satellite alkalinity data are providing a global baseline that can be used for comparing with future carbon data, and for evaluating spatial and temporal variability and past trends. For the first time it is shown that recent satellite derived total alkalinity in the subtropics have increased as compared with climatological data; this is reflective of large scale changes in the global water cycle. Total alkalinity increases imply increased dissolution of calcareous minerals and difficulty for calcifying organisms to make their shells.

Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

NASA Astrophysics Data System (ADS)

Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

2010-08-01

An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

Strategies for satellite-based monitoring of CO2 from distributed area and point sources

NASA Astrophysics Data System (ADS)

Schwandner, Florian M.; Miller, Charles E.; Duren, Riley M.; Natraj, Vijay; Eldering, Annmarie; Gunson, Michael R.; Crisp, David

2014-05-01

Atmospheric CO2 budgets are controlled by the strengths, as well as the spatial and temporal variabilities of CO2 sources and sinks. Natural CO2 sources and sinks are dominated by the vast areas of the oceans and the terrestrial biosphere. In contrast, anthropogenic and geogenic CO2 sources are dominated by distributed area and point sources, which may constitute as much as 70% of anthropogenic (e.g., Duren & Miller, 2012), and over 80% of geogenic emissions (Burton et al., 2013). Comprehensive assessments of CO2 budgets necessitate robust and highly accurate satellite remote sensing strategies that address the competing and often conflicting requirements for sampling over disparate space and time scales. Spatial variability: The spatial distribution of anthropogenic sources is dominated by patterns of production, storage, transport and use. In contrast, geogenic variability is almost entirely controlled by endogenic geological processes, except where surface gas permeability is modulated by soil moisture. Satellite remote sensing solutions will thus have to vary greatly in spatial coverage and resolution to address distributed area sources and point sources alike. Temporal variability: While biogenic sources are dominated by diurnal and seasonal patterns, anthropogenic sources fluctuate over a greater variety of time scales from diurnal, weekly and seasonal cycles, driven by both economic and climatic factors. Geogenic sources typically vary in time scales of days to months (geogenic sources sensu stricto are not fossil fuels but volcanoes, hydrothermal and metamorphic sources). Current ground-based monitoring networks for anthropogenic and geogenic sources record data on minute- to weekly temporal scales. Satellite remote sensing solutions would have to capture temporal variability through revisit frequency or point-and-stare strategies. Space-based remote sensing offers the potential of global coverage by a single sensor. However, no single combination of orbit and sensor provides the full range of temporal sampling needed to characterize distributed area and point source emissions. For instance, point source emission patterns will vary with source strength, wind speed and direction. Because wind speed, direction and other environmental factors change rapidly, short term variabilities should be sampled. For detailed target selection and pointing verification, important lessons have already been learned and strategies devised during JAXA's GOSAT mission (Schwandner et al, 2013). The fact that competing spatial and temporal requirements drive satellite remote sensing sampling strategies dictates a systematic, multi-factor consideration of potential solutions. Factors to consider include vista, revisit frequency, integration times, spatial resolution, and spatial coverage. No single satellite-based remote sensing solution can address this problem for all scales. It is therefore of paramount importance for the international community to develop and maintain a constellation of atmospheric CO2 monitoring satellites that complement each other in their temporal and spatial observation capabilities: Polar sun-synchronous orbits (fixed local solar time, no diurnal information) with agile pointing allow global sampling of known distributed area and point sources like megacities, power plants and volcanoes with daily to weekly temporal revisits and moderate to high spatial resolution. Extensive targeting of distributed area and point sources comes at the expense of reduced mapping or spatial coverage, and the important contextual information that comes with large-scale contiguous spatial sampling. Polar sun-synchronous orbits with push-broom swath-mapping but limited pointing agility may allow mapping of individual source plumes and their spatial variability, but will depend on fortuitous environmental conditions during the observing period. These solutions typically have longer times between revisits, limiting their ability to resolve temporal variations. Geostationary and non-sun-synchronous low-Earth-orbits (precessing local solar time, diurnal information possible) with agile pointing have the potential to provide, comprehensive mapping of distributed area sources such as megacities with longer stare times and multiple revisits per day, at the expense of global access and spatial coverage. An ad hoc CO2 remote sensing constellation is emerging. NASA's OCO-2 satellite (launch July 2014) joins JAXA's GOSAT satellite in orbit. These will be followed by GOSAT-2 and NASA's OCO-3 on the International Space Station as early as 2017. Additional polar orbiting satellites (e.g., CarbonSat, under consideration at ESA) and geostationary platforms may also become available. However, the individual assets have been designed with independent science goals and requirements, and limited consideration of coordinated observing strategies. Every effort must be made to maximize the science return from this constellation. We discuss the opportunities to exploit the complementary spatial and temporal coverage provided by these assets as well as the crucial gaps in the capabilities of this constellation. References Burton, M.R., Sawyer, G.M., and Granieri, D. (2013). Deep carbon emissions from volcanoes. Rev. Mineral. Geochem. 75: 323-354. Duren, R.M., Miller, C.E. (2012). Measuring the carbon emissions of megacities. Nature Climate Change 2, 560-562. Schwandner, F.M., Oda, T., Duren, R., Carn, S.A., Maksyutov, S., Crisp, D., Miller, C.E. (2013). Scientific Opportunities from Target-Mode Capabilities of GOSAT-2. NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA, White Paper, 6p., March 2013.

Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective

NASA Astrophysics Data System (ADS)

Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise

2018-06-01

The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC hot spots. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Vegetation-induced spatial variability of soil redox properties in wetlands

NASA Astrophysics Data System (ADS)

Szalai, Zoltán; Jakab, Gergely; Kiss, Klaudia; Ringer, Marianna; Balázs, Réka; Zacháry, Dóra; Horváth Szabó, Kata; Perényi, Katalin

2016-04-01

Vegetation induced land patches may result spatial pattern of on soil Eh and pH. These spatial pattern are mainly emerged by differences of aeration and exudation of assimilates. Present paper focuses on vertical extent and temporal dynamics of these patterns in wetlands. Two study sites were selected: 1. a plain wetland on calcareous sandy parent material (Ceglédbercel, Danube-Tisza Interfluve, Hungary); 2. headwater wetland with calcareous loamy parent material (Bátaapáti, Hungary). Two vegetation patches were studied in site 1: sedgy (dominated by Carex riparia) and reedy (dominated by Phragmites australis). Three patches were studied in site2: sedgy1 (dominated by C vulpina), sedgy 2 (C. riparia); nettle-horsetail (Urtica dioica and Equisetum arvense). Boundaries between patches were studied separately. Soil redox, pH and temperature studied by automated remote controlled instruments. Three digital sensors (Ponsell) were installed in each locations: 20cm and 40cm sensors represent the solum and 100 cm sensor monitors the subsoil). Groundwater wells were installed near to triplets for soil water sampling. Soil Eh, pH and temperature values were recorded in each 10 minutes. Soil water sampling for iron and DOC were carried out during saturated periods. Spatial pattern of soil Eh is clearly caused by vegetation. We measured significant differences between Eh values of the studied patches in the solum. We did not find this kinds horizontal differences in the subsoil. Boundaries of the patches usually had more reductive soil environment than the core areas. We have found temporal dynamics of the spatial redox pattern. Differences were not so well expressed during wintertime. These spatial patterns had influence on the DOC and iron content of porewater, as well. Highest temporal dynamics of soil redox properties and porewater iron could be found in the boundaries. These observations refer to importance patchiness of vegetation on soil chemical properties in wetlands. Authors are grateful to Hungarian Scientific research Fund (K100180)

Soil water sensor response to bulk electrical conductivity

USDA-ARS?s Scientific Manuscript database

Soil water monitoring using electromagnetic (EM) sensors can facilitate observations of water content at high temporal and spatial resolutions. These sensors measure soil dielectric permittivity (Ka) which is largely a function of volumetric water content. However, bulk electrical conductivity BEC c...

Modeling the impacts of phenological and inter-annual changes in landscape metrics on local biodiversity of agricultural lands of Eastern Ontario using multi-spatial and multi-temporal remote sensing data

NASA Astrophysics Data System (ADS)

Alavi-Shoushtari, N.; King, D.

2017-12-01

Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.

Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas

NASA Astrophysics Data System (ADS)

Suo, Lizhu; Huang, Mingbin; Zhang, Yongkun; Duan, Liangxia; Shan, Yan

2018-07-01

Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R2) and goodness of prediction (Q2) were >0.5 and >0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC at the regional scale significantly. Overall, this study indicated that dominant controls of SMC varied among three spatial scales on the Loess Plateau, and VIP was a function of spatial scale and soil depth.

Spatial impacts of inorganic ligand availability and localized microbial community structure on mitigation of zinc laden mine water in sulfate-reducing bioreactors.

PubMed

Drennan, Dina M; Almstrand, Robert; Ladderud, Jeffrey; Lee, Ilsu; Landkamer, Lee; Figueroa, Linda; Sharp, Jonathan O

2017-05-15

Sulfate-reducing bioreactors (SRBRs) represent a passive, sustainable, and long-term option for mitigating mining influenced water (MIW) during release. Here we investigate spatial zinc precipitation profiles as influenced by substrate differentiation, inorganic ligand availability (inorganic carbon and sulfide), and microbial community structure in pilot-scale SRBR columns fed with sulfate and zinc-rich MIW. Through a combination of aqueous sampling, geochemical digests, electron microscopy and energy-dispersive x-ray spectroscopy, we were able to delineate zones of enhanced zinc removal, identify precipitates of varying stability, and discern the temporal and spatial evolution of zinc, sulfur, and calcium associations. These geochemical insights revealed spatially variable immobilization regimes between SRBR columns that could be further contrasted as a function of labile (alfalfa-dominated) versus recalcitrant (woodchip-dominated) solid-phase substrate content. Both column subsets exhibited initial zinc removal as carbonates; however precipitation in association with labile substrates was more pronounced and dominated by metal-sulfide formation in the upper portions of the down flow columns with micrographs visually suggestive of sphalerite (ZnS). In contrast, a more diffuse and lower mass of zinc precipitation in the presence of gypsum-like precipitates occurred within the more recalcitrant column systems. While removal and sulfide-associated precipitation were spatially variable, whole bacterial community structure (ANOSIM) and diversity estimates were comparatively homogeneous. However, two phyla exhibited a potentially selective relationship with a significant positive correlation between the ratio of Firmicutes to Bacteroidetes and sulfide-bound zinc. Collectively these biogeochemical insights indicate that depths of maximal zinc sulfide precipitation are temporally dynamic, influenced by substrate composition and broaden our understanding of bio-immobilized zinc species, microbial interactions and potential operational and monitoring tools in these types of passive bioreactors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biogeochemical characteristics of mesoscale eddies in the generation zone off Valparaíso, Chile

NASA Astrophysics Data System (ADS)

Villegas, Valerie; Cornejo, Marcela; Molina, Verónica; Silva, Nelson; Hormazábal, Samuel

2016-04-01

The coastal area off Valparaiso is characterized by an intense mesoscale activity associated with eddies, which transport highly productive-coastal waters to the oligotrophic areas of the Subtropical Gyre. Among these, the Intrathermocline Anticyclonic Eddies (ITE's) which are forming in the eastern South Pacific, transport low oxygen- and high nutrients- subsurface water of Equatorial Subsurface Water (ESSW). These eddies have been well characterized in terms of generation rate, direction, speed and water transport. However, biogeochemical conditions in their origin and its temporal variability are not well assessed. The present study aims to determine the variability, spatially and temporally, of the biogeochemical properties in the water column at the eddies generation zone, off Punta Ángeles, Valparaíso (33° S). For this, a monthly time series was conducted between January and August 2016 where a cross-shore transect with six-stations was deployed (from coast to 16 nm). Each station was sampled with CTD-OF, while only in station 5 (1300 m depth) was sampled in 16 depth for biogeochemical variables: nutrients (NO3-, NO2-, PO4-3, Si(OH)4), greenhouse gases (CO2, CH4 and N2O), chlorophyll a, stable isotopes in particulate organic material (13C, 15N), content of organic carbon and nitrogen in POM. The spatial and temporal distribution shows the presence of subsurface cores (100 - 300 m) with water with high salinity (> 34.7 psu) and low oxygen content (< 0.5 mLṡL-1), associated with mesoscale subsurface structures. The largest vertical and horizontal extension of these structures was observed in January 2015. These subsurface structures showed a significant deficit of reactive nitrogen (N* < -10 μM), nitrite accumulation (> 0.6 μM) and the highest supersaturations of CO2 (110 - 344%) and N2O (107 - 407%). Along with this, the eddies generation zone presented a temporal variability of air-sea gases fluxes with the highest in the austral summer and autumn (from 67.64 to 9.12 mmolṡm-2ṡd-1, from 3.00 to 0.94 μmolṡm-2ṡd-1, and from 19.62 to 5.77 μmolṡm-2ṡd-1, for CO2, CH4 and N2O, respectively), while between June and August, the ocean-atmosphere flows were close to equilibrium (from 0.09 to -1.93 mmolṡm-2ṡd-1, from 0.40 to 0.03 μmolṡm-2ṡd-1, and from 0,29 to -0.02 μmolṡm-2ṡd-1, for CO2, CH4 and N2O, respectively). Acknowledgment: This work is part of the PIA 037.474 Project (PUCV) and the Instituto Milenio de Oceanografía (IMO-Chile).

Protection Enhances Community and Habitat Stability: Evidence from a Mediterranean Marine Protected Area

PubMed Central

Fraschetti, Simonetta; Guarnieri, Giuseppe; Bevilacqua, Stanislao; Terlizzi, Antonio; Boero, Ferdinando

2013-01-01

Rare evidences support that Marine Protected Areas (MPAs) enhance the stability of marine habitats and assemblages. Based on nine years of observation (2001–2009) inside and outside a well managed MPA, we assessed the potential of conservation and management actions to modify patterns of spatial and/or temporal variability of Posidonia oceanica meadows, the lower midlittoral and the shallow infralittoral rock assemblages. Significant differences in both temporal variations and spatial patterns were observed between protected and unprotected locations. A lower temporal variability in the protected vs. unprotected assemblages was found in the shallow infralittoral, demonstrating that, at least at local scale, protection can enhance community stability. Macrobenthos with long-lived and relatively slow-growing invertebrates and structurally complex algal forms were homogeneously distributed in space and went through little fluctuations in time. In contrast, a mosaic of disturbed patches featured unprotected locations, with small-scale shifts from macroalgal stands to barrens, and harsh temporal variations between the two states. Opposite patterns of spatial and temporal variability were found for the midlittoral assemblages. Despite an overall clear pattern of seagrass regression through time, protected meadows showed a significantly higher shoot density than unprotected ones, suggesting a higher resistance to local human activities. Our results support the assumption that the exclusion/management of human activities within MPAs enhance the stability of the structural components of protected marine systems, reverting or arresting threat-induced trajectories of change. PMID:24349135

Heterogeneous water supply affects growth and benefits of clonal integration between co-existing invasive and native Hydrocotyle species.

PubMed

Wang, Yong-Jian; Bai, Yun-Fei; Zeng, Shi-Qi; Yao, Bin; Wang, Wen; Luo, Fang-Li

2016-07-21

Spatial patchiness and temporal variability in water availability are common in nature under global climate change, which can remarkably influence adaptive responses of clonal plants, i.e. clonal integration (translocating resources between connected ramets). However, little is known about the effects of spatial patchiness and temporal heterogeneity in water on growth and clonal integration between congeneric invasive and native Hydrocotyle species. In a greenhouse experiment, we subjected severed or no severed (intact) fragments of Hydrocotyle vulgaris, a highly invasive species in China, and its co-existing, native congener H. sibthorpioides to different spatial patchiness (homogeneous and patchy) and temporal interval (low and high interval) in water supply. Clonal integration had significant positive effects on growth of both species. In the homogeneous water conditions, clonal integration greatly improved the growth in fragments of both species under low interval in water. However, in the patchy water conditions, clonal integration significantly increased growth in both ramets and fragments of H. vulgaris under high interval in water. Therefore, spatial patchiness and temporal interval in water altered the effects of clonal integration of both species, especially for H. vulgaris. The adaptation of H. vulgaris might lead to invasive growth and potential spread under the global water variability.

Modeling spatiotemporal covariance for magnetoencephalography or electroencephalography source analysis.

PubMed

Plis, Sergey M; George, J S; Jun, S C; Paré-Blagoev, J; Ranken, D M; Wood, C C; Schmidt, D M

2007-01-01

We propose a new model to approximate spatiotemporal noise covariance for use in neural electromagnetic source analysis, which better captures temporal variability in background activity. As with other existing formalisms, our model employs a Kronecker product of matrices representing temporal and spatial covariance. In our model, spatial components are allowed to have differing temporal covariances. Variability is represented as a series of Kronecker products of spatial component covariances and corresponding temporal covariances. Unlike previous attempts to model covariance through a sum of Kronecker products, our model is designed to have a computationally manageable inverse. Despite increased descriptive power, inversion of the model is fast, making it useful in source analysis. We have explored two versions of the model. One is estimated based on the assumption that spatial components of background noise have uncorrelated time courses. Another version, which gives closer approximation, is based on the assumption that time courses are statistically independent. The accuracy of the structural approximation is compared to an existing model, based on a single Kronecker product, using both Frobenius norm of the difference between spatiotemporal sample covariance and a model, and scatter plots. Performance of ours and previous models is compared in source analysis of a large number of single dipole problems with simulated time courses and with background from authentic magnetoencephalography data.

Spatial variability in levels of benzene, formaldehyde, and total benzene, toluene, ethylbenzene and xylenes in New York City: a land-use regression study.

PubMed

Kheirbek, Iyad; Johnson, Sarah; Ross, Zev; Pezeshki, Grant; Ito, Kazuhiko; Eisl, Holger; Matte, Thomas

2012-07-31

Hazardous air pollutant exposures are common in urban areas contributing to increased risk of cancer and other adverse health outcomes. While recent analyses indicate that New York City residents experience significantly higher cancer risks attributable to hazardous air pollutant exposures than the United States as a whole, limited data exist to assess intra-urban variability in air toxics exposures. To assess intra-urban spatial variability in exposures to common hazardous air pollutants, street-level air sampling for volatile organic compounds and aldehydes was conducted at 70 sites throughout New York City during the spring of 2011. Land-use regression models were developed using a subset of 59 sites and validated against the remaining 11 sites to describe the relationship between concentrations of benzene, total BTEX (benzene, toluene, ethylbenzene, xylenes) and formaldehyde to indicators of local sources, adjusting for temporal variation. Total BTEX levels exhibited the most spatial variability, followed by benzene and formaldehyde (coefficient of variation of temporally adjusted measurements of 0.57, 0.35, 0.22, respectively). Total roadway length within 100 m, traffic signal density within 400 m of monitoring sites, and an indicator of temporal variation explained 65% of the total variability in benzene while 70% of the total variability in BTEX was accounted for by traffic signal density within 450 m, density of permitted solvent-use industries within 500 m, and an indicator of temporal variation. Measures of temporal variation, traffic signal density within 400 m, road length within 100 m, and interior building area within 100 m (indicator of heating fuel combustion) predicted 83% of the total variability of formaldehyde. The models built with the modeling subset were found to predict concentrations well, predicting 62% to 68% of monitored values at validation sites. Traffic and point source emissions cause substantial variation in street-level exposures to common toxic volatile organic compounds in New York City. Land-use regression models were successfully developed for benzene, formaldehyde, and total BTEX using spatial indicators of on-road vehicle emissions and emissions from stationary sources. These estimates will improve the understanding of health effects of individual pollutants in complex urban pollutant mixtures and inform local air quality improvement efforts that reduce disparities in exposure.

Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.

PubMed

Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph

2012-12-01

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

A reanalysis dataset of the South China Sea.

PubMed

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992-2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability.

A reanalysis dataset of the South China Sea

PubMed Central

Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

2014-01-01

Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

Children can implicitly, but not voluntarily, direct attention in time.

PubMed

Johnson, Katherine A; Burrowes, Emma; Coull, Jennifer T

2015-01-01

Children are able to use spatial cues to orient their attention to discrete locations in space from around 4 years of age. In contrast, no research has yet investigated the ability of children to use informative cues to voluntarily predict when an event will occur in time. The spatial and temporal attention task was used to determine whether children were able to voluntarily orient their attention in time, as well as in space: symbolic spatial and temporal cues predicted where or when an imperative target would appear. Thirty typically developing children (average age 11 yrs) and 32 adults (average age 27 yrs) took part. Confirming previous findings, adults made use of both spatial and temporal cues to optimise behaviour, and were significantly slower to respond to invalidly cued targets in either space or time. Children were also significantly slowed by invalid spatial cues, demonstrating their use of spatial cues to guide expectations. In contrast, children's responses were not slowed by invalid temporal cues, suggesting that they were not using the temporal cue to voluntarily orient attention through time. Children, as well as adults, did however demonstrate signs of more implicit forms of temporal expectation: RTs were faster for long versus short cue-target intervals (the variable foreperiod effect) and slower when the preceding trial's cue-target interval was longer than that on the current trial (sequential effects). Overall, our results suggest that although children implicitly made use of the temporally predictive information carried by the length of the current and previous trial's cue-target interval, they could not deliberately use symbolic temporal cues to speed responses. The developmental trajectory of the ability to voluntarily use symbolic temporal cues is therefore delayed, relative both to the use of symbolic (arrow) spatial cues, and to the use of implicit temporal information.

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

NASA Technical Reports Server (NTRS)

Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.

2015-01-01

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

Towards integrated assessment of the northern Adriatic Sea sediment budget using remote sensing

NASA Astrophysics Data System (ADS)

Taramelli, A.; Filipponi, F.; Valentini, E.; Zucca, F.; Gutierrez, O. Q.; Liberti, L.; Cordella, M.

2014-12-01

Understanding the factors influencing sediment fluxes is a key issue to interpret the evolution of coastal sedimentation under natural and human impact and relevant for the natural resources management. Despite river plumes represent one of the major gain in sedimentary budget of littoral cells, knowledge of factors influencing complex behavior of coastal plumes, like river discharge characteristics, wind stress and hydro-climatic variables, has not been yet fully investigated. Use of Earth Observation data allows the identification of spatial and temporal variations of suspended sediments related to river runoff, seafloor erosion, sediment transport and deposition processes. Objective of the study is to investigate sediment fluxes in northern Adriatic Sea by linking suspended sediment patterns of coastal plumes to hydrologic and climatic forcing regulating the sedimentary cell budget and geomorphological evolution in coastal systems and continental shelf waters. Analysis of Total Suspended Matter (TSM) product, derived from 2002-2012 MERIS time series, was done to map changes in spatial and temporal dimension of suspended sediments, focusing on turbid plume waters and intense wind stress conditions. From the generated multi temporal TSM maps, dispersal patterns of major freshwater runoff plumes in northern Adriatic Sea were evaluated through spatial variability of coastal plumes shape and extent. Additionally, sediment supply from river distributary mouths was estimated from TSM and correlated with river discharge rates, wind field and wave field through time. Spatial based methodology has been developed to identify events of wave-generated resuspension of sediments, which cause variation in water column turbidity, occurring during intense wind stress and extreme metocean conditions, especially in the winter period. The identified resuspension events were qualitatively described and compared with to hydro-climatic variables. The identification of spatial and temporal pattern variability highlighted the presence of seasonal sediment dynamics linked to the seasonal cycle in river discharge and wind stress. Results suggest that sediment fluxes generate geomorphological variations in northern Adriatic Sea, which are mainly controlled by river discharge rates and modulated by the winds.

Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe

NASA Astrophysics Data System (ADS)

Scheifinger, Helfried; Menzel, Annette; Koch, Elisabeth; Peter, Christian; Ahas, Rein

2002-11-01

A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed decoupling mechanism. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal variability from the influence of the westerly flow regime (local-scale loss of influence). This study corroborates an increasing number of similar investigations that find that vegetation does react in a sensitive way to variations of its atmospheric environment across various temporal and spatial scales.

Spatial and temporal variability of hyperspectral signatures of terrain

NASA Astrophysics Data System (ADS)

Jones, K. F.; Perovich, D. K.; Koenig, G. G.

2008-04-01

Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

Temporal, spatial, and environmental influences on the demographics of grizzly bears in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Schwartz, Charles C.; Haroldson, Mark A.; White, Gary C.; Harris, Richard B.; Cherry, Steve; Keating, Kim A.; Moody, Dave; Servheen, Christopher

2006-01-01

During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded in range. Understanding temporal, environmental, and spatial variables responsible for this change is useful in evaluating what likely influenced grizzly bear demographics in the GYE and where future management efforts might benefit conservation and management. We used recent data from radio-marked bears to estimate reproduction (1983–2002) and survival (1983–2001); these we combined into models to evaluate demographic vigor (lambda [λ]). We explored the influence of an array of individual, temporal, and spatial covariates on demographic vigor.

Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Treesearch

Ying Ouyang; Prem B. Parajuli; Gary Feng; Theodor D. Leininger; Yongshan Wan; Padmanava Dash

2018-01-01

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and...

Temporal, geomagnetic and related attributes of kimberlite magmatism at Ekati, Northwest Territories, Canada

NASA Astrophysics Data System (ADS)

Lockhart, Grant; Grütter, Herman; Carlson, Jon

2004-09-01

This paper outlines the development of a multi-disciplinary strategy to focus exploration for economic kimberlites on the Ekati property. High-resolution aeromagnetic data provide an over-arching spatial and magnetostratigraphic framework for exploration and kimberlite discovery at Ekati, and hence also for this investigation. The temporal, geomagnetic, spatial and related attributes of kimberlites with variable diamond content have been constrained by judiciously augmenting the information gathered during routine exploration with detailed, laboratory-based or field-based investigations. The natural remanent magnetisation of 36 Ekati kimberlites has been correlated with their age as determined by isotopic dating techniques, and placed in the context of a well-constrained geomagnetic polarity timescale. Kimberlite magmatism occurred over the period 75 to 45 Ma, in at least five temporally discrete intrusive episodes. Based on current evidence, the older kimberlites (75 to 59 Ma) have low diamond contents and are distributed throughout the property. Younger kimberlites (56 to 45 Ma) have moderate to high diamond contents and occur in three distinct intrusive corridors with NNE to NE orientations. Economic kimberlite pipes erupted at 55.4±0.4 Ma along the A154-Lynx intrusive corridor, which is 7 km wide and oriented at 015°, and at 53.2±0.3 Ma along the Panda intrusive corridor, which is 1 km wide and oriented at 038°. The intrusion ages straddle a paleopole reversal at Chron C24n, consistent with the observation that the older economic kimberlites present as aeromagnetic "low" anomalies while the younger economic pipes are characterised as aeromagnetic "highs". The aeromagnetic responses for these kimberlites are generally muted because they contain volcaniclastic rock types with low magnetic susceptibility. Kimberlites throughout the Ekati property carry a primary natural magnetic remanence (NRM) vector in Ti-bearing groundmass magnetite, and it dominates over vectors related to induced magnetisation. Magnetostratigraphic correlation of Ekati kimberlites may therefore present a powerful adjunct to existing exploration techniques, mainly because the diamond content of Ekati kimberlites apparently is related more to the age of eruption than to any other parameter investigated in this work.

Leveraging organismal biology to forecast the effects of climate change.

PubMed

Buckley, Lauren B; Cannistra, Anthony F; John, Aji

2018-04-26

Despite the pressing need for accurate forecasts of ecological and evolutionary responses to environmental change, commonly used modelling approaches exhibit mixed performance because they omit many important aspects of how organisms respond to spatially and temporally variable environments. Integrating models based on organismal phenotypes at the physiological, performance and fitness levels can improve model performance. We summarize current limitations of environmental data and models and discuss potential remedies. The paper reviews emerging techniques for sensing environments at fine spatial and temporal scales, accounting for environmental extremes, and capturing how organisms experience the environment. Intertidal mussel data illustrate biologically important aspects of environmental variability. We then discuss key challenges in translating environmental conditions into organismal performance including accounting for the varied timescales of physiological processes, for responses to environmental fluctuations including the onset of stress and other thresholds, and for how environmental sensitivities vary across lifecycles. We call for the creation of phenotypic databases to parameterize forecasting models and advocate for improved sharing of model code and data for model testing. We conclude with challenges in organismal biology that must be solved to improve forecasts over the next decade.acclimation, biophysical models, ecological forecasting, extremes, microclimate, spatial and temporal variability.

Automated support tool for variable rate irrigation prescriptions

USDA-ARS?s Scientific Manuscript database

Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS dat...

Development of a multispectral sensor for crop canopy temperature measurement

USDA-ARS?s Scientific Manuscript database

Quantifying spatial and temporal variability in plant stress has precision agriculture applications in controlling variable rate irrigation and variable rate nutrient application. One approach to plant stress detection is crop canopy temperature measurement by the use of thermographic or radiometric...

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Distribution, abundance, and diversity of stream fishes under variable environmental conditions

Treesearch

Christopher M. Taylor; Thomas L. Holder; Richard A. Fiorillo; Lance R. Williams; R. Brent Thomas; Melvin L. Warren

2006-01-01

The effects of stream size and flow regime on spatial and temporal variability of stream fish distribution, abundance, and diversity patterns were investigated. Assemblage variability and species richness were each significantly associated with a complex environmental gradient contrasting smaller, hydrologically variable stream localities with larger localities...

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.

Dynamic Vertical Profiles of Peat Porewater Chemistry in a Northern Peatland

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

Griffiths, Natalie A.; Sebestyen, Stephen D.

We measured pH, cations, nutrients, and total organic carbon (TOC) over 3 years to examine weekly to monthly variability in porewater chemistry depth profiles (0–3.0 m) in an ombrotrophic bog in Minnesota, USA. We also compared temporal variation at one location to spatial variation in depth profiles at 16 locations across the bog. Most solutes exhibited large gradients with depth. pH increased by two units and calcium concentrations increased over 20 fold with depth, and may reflect peatland development from minerotrophic to ombrotrophic conditions. Ammonium concentrations increased almost 20 fold and TOC concentrations decreased by half with depth, and thesemore » patterns likely reflect mineralization of peat or decomposition of TOC. There was also considerable temporal variation in the porewater chemistry depth profiles. Ammonium, soluble reactive phosphorus, and potassium showed greater temporal variation in near-surface porewater, while pH, calcium, and TOC varied more at depth. This variation demonstrates that deep peat porewater chemistry is not static. Lastly, temporal variation in solute chemistry depth profiles was greater than spatial variation in several instances, especially in shallow porewaters. In conclusion, characterizing both temporal and spatial variability is necessary to ensure representative sampling in peatlands, especially when calculating solute pools and fluxes and parameterizing process-based models.« less

Dynamic Vertical Profiles of Peat Porewater Chemistry in a Northern Peatland

DOE PAGES

Griffiths, Natalie A.; Sebestyen, Stephen D.

2016-10-14

We measured pH, cations, nutrients, and total organic carbon (TOC) over 3 years to examine weekly to monthly variability in porewater chemistry depth profiles (0–3.0 m) in an ombrotrophic bog in Minnesota, USA. We also compared temporal variation at one location to spatial variation in depth profiles at 16 locations across the bog. Most solutes exhibited large gradients with depth. pH increased by two units and calcium concentrations increased over 20 fold with depth, and may reflect peatland development from minerotrophic to ombrotrophic conditions. Ammonium concentrations increased almost 20 fold and TOC concentrations decreased by half with depth, and thesemore » patterns likely reflect mineralization of peat or decomposition of TOC. There was also considerable temporal variation in the porewater chemistry depth profiles. Ammonium, soluble reactive phosphorus, and potassium showed greater temporal variation in near-surface porewater, while pH, calcium, and TOC varied more at depth. This variation demonstrates that deep peat porewater chemistry is not static. Lastly, temporal variation in solute chemistry depth profiles was greater than spatial variation in several instances, especially in shallow porewaters. In conclusion, characterizing both temporal and spatial variability is necessary to ensure representative sampling in peatlands, especially when calculating solute pools and fluxes and parameterizing process-based models.« less

Observations of the Winter Thermal Structure of Lake Superior

NASA Astrophysics Data System (ADS)

Titze, Daniel James

Moored thermistor strings that span the water column have been deployed at up to seven locations throughout Lake Superior from 2005 through present, producing a unique year-round record of the thermal structure of a large lake. This extensive temperature record reveals significant interannual and spatial variability in Lake Superior's winter heat content, thermocline depth, and phenology. Of particular mention is a stark contrast in thermal structure between the cold, icy winter of 2009 and the much warmer winter of 2012, during which especially strong and weak negative stratification was observed, respectively. Significant interannual and spatial variability was also observed in Lake Superior ice cover, as shown through data extracted from Ice Mapping System satellite imagery (NOAA/NESDIS 2004). When water column heat content was estimated from temperature data and analyzed in concert with lake ice-cover data, it was found that ice cover can inhibit heat flux between the lake and the atmosphere, and that spatial variability in ice cover can translate into spatial variability in end-of-winter heat content. Such variability in end-of-winter heat content is found to be preserved through the spring warming season, and is strongly correlated with variability in the timing of the onset of summer stratification, with regions that have warmer end-of-winter water columns stratifying earlier than regions with colder end-of-winter water-columns.

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.

Total ozone trend significance from space time variability of daily Dobson data

NASA Technical Reports Server (NTRS)

Wilcox, R. W.

1981-01-01

Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.

Advancing Analysis of Spatio-Temporal Variations of Soil Nutrients in the Water Level Fluctuation Zone of China’s Three Gorges Reservoir Using Self-Organizing Map

PubMed Central

Ye, Chen; Li, Siyue; Yang, Yuyi; Shu, Xiao; Zhang, Jiaquan; Zhang, Quanfa

2015-01-01

The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR. PMID:25789612

Bayesian spatio-temporal discard model in a demersal trawl fishery

NASA Astrophysics Data System (ADS)

Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

2014-07-01

Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Resolution capacity of geophysical monitoring regarding permafrost degradation induced by hydrological processes

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Hilbich, Christin; Delaloye, Reynald; Hauck, Christian

2017-12-01

Geophysical methods are often used to characterize and monitor the subsurface composition of permafrost. The resolution capacity of standard methods, i.e. electrical resistivity tomography and refraction seismic tomography, depends not only on static parameters such as measurement geometry, but also on the temporal variability in the contrast of the geophysical target variables (electrical resistivity and P-wave velocity). Our study analyses the resolution capacity of electrical resistivity tomography and refraction seismic tomography for typical processes in the context of permafrost degradation using synthetic and field data sets of mountain permafrost terrain. In addition, we tested the resolution capacity of a petrophysically based quantitative combination of both methods, the so-called 4-phase model, and through this analysed the expected changes in water and ice content upon permafrost thaw. The results from the synthetic data experiments suggest a higher sensitivity regarding an increase in water content compared to a decrease in ice content. A potentially larger uncertainty originates from the individual geophysical methods than from the combined evaluation with the 4-phase model. In the latter, a loss of ground ice can be detected quite reliably, whereas artefacts occur in the case of increased horizontal or vertical water flow. Analysis of field data from a well-investigated rock glacier in the Swiss Alps successfully visualized the seasonal ice loss in summer and the complex spatially variable ice, water and air content changes in an interannual comparison.

Spatial and temporal variation in emergency transport during periods of extreme heat in Japan: A nationwide study.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2016-02-15

Several studies have reported the burden of climate change on extreme heat-related mortality or morbidity. However, few studies have investigated the spatial and temporal variation in emergency transport during periods of extreme heat on a national scale. Daily emergency ambulance dispatch data from 2007 to 2010 were acquired from all 47 prefectures of Japan. The temporal variability in the relationship between heat and morbidity in each prefecture was estimated using Poisson regression combined with a distributed lag non-linear model and adjusted for time trends. The spatial variability in the heat-morbidity relationships between prefectures was estimated using a multivariate meta-analysis. A total of 5,289,660 emergency transports were reported during the summer months (June through September) within the study period. The overall cumulative relative risk (RR) at the 99th percentile vs. the minimum morbidity percentile was 1.292 (95% CI: 1.251-1.333) for all causes, 1.039 (95% CI: 0.989-1.091) for cardiovascular diseases, and 1.287 (95% CI: 1.210-1.368) for respiratory diseases. Temporal variation in the estimated effects indicated a non-linear relationship, and there were differences in the temporal variations between heat and all-cause and cause-specific morbidity. Spatial variation between prefectures was observed for all causes (Cochran Q test, p<0.001; I(2)=45.8%); however, there was no significant spatial heterogeneity for cardiovascular (Cochran Q test, p=0.054; I(2)=15.1%) and respiratory (Cochran Q test, p=0.681; I(2)=1.0%) diseases. Our nationwide study demonstrated differences in the spatial and temporal variations in the relative risk for all-cause and cause-specific emergency transport during periods of extreme heat in Japan between 2007 and 2010. Our results suggest that public health strategies aimed at controlling heat-related morbidity should be tailored according to region-specific weather conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

Century-scale Changes in Environmental Synchrony and Variability and their Effects on Populations of Birds and Reproduction of Trees

NASA Astrophysics Data System (ADS)

Koenig, W.

2016-12-01

The ecological impacts of modern global climate change are detectable in a wide variety of phenomena ranging from shifts in species ranges to changes in community composition and human disease dynamics. Thus far, however, little attention has been given to temporal changes in environmental spatial synchrony-the coincident change in abundance or value across the landscape-or environmental variability, despite the importance of these factors as drivers of population rescue and extinction and reproductive dynamics of both animal and plant populations. We quantified spatial synchrony of widespread North American wintering birds species using Audubon Christmas Bird Counts over the past 50 years and seed set variability (mast fruiting) among trees over the past century and found that both spatial synchrony of the birds and seed set variability have significantly increased over these time periods. The first of these results was mirrored by significant increases in spatial synchrony of mean maximum air temperature across North America, primarily during the summer, while the second is consistent with the hypothesis that climate change is resulting in greater seed set variability. These findings suggest the potential for temporal changes in envioronmental synchrony and variability to be affecting a wide range of ecological phenomena by influencing the probability of population rescue and extinction and by affecting ecosystem processes that rely on the resource pulses provided by mast fruiting plants.

Spatial and temporal variability in the structure of invertebrate assemblages in control stream mesocosms.

PubMed

Wong, Diana C L; Maltby, Lorraine; Whittle, Don; Warren, Philip; Dorn, Philip B

2004-01-01

Outdoor stream mesocosm studies conducted between 1992 and 1996 at two facilities enabled the investigation of structural variability in invertebrate assemblages within and between studies. Temporal variability of benthic invertebrate assemblages between eight replicate streams within a study was assessed in a 28-day mesocosm study without chemical treatment. Cluster analysis, non-metric multidimensional scaling, and principal component analysis each showed the untreated assemblages as structurally distinct groups on the three sampling days. The assemblages between the eight replicate streams showed >88% Bray-Curtis similarity at any one time during the study. In addition, pre-treatment data from a series of four studies conducted at one facility were used to examine structural variability in the starting benthic invertebrate assemblages between studies. Invertebrate assemblages were structurally distinct at the start of each mesocosm study conducted in different years at the same facility and the taxa responsible for differences in the assemblages were also different each year. The implications of temporal and spatial variability in benthic invertebrate assemblages within and between mesocosm studies with regards to species sensitivity and study repeatability should be considered when results of such studies are used in risk assessment.

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

An Assessment of the Spatial and Temporal Variability of Biological Responses to Municipal Wastewater Effluent in Rainbow Darter (Etheostoma caeruleum) Collected along an Urban Gradient

PubMed Central

Bragg, Leslie M.; Tetreault, Gerald R.; Bahamonde, Paulina A.; Tanna, Rajiv N.; Bennett, Charles J.; McMaster, Mark E.; Servos, Mark R.

2016-01-01

Municipal wastewater effluent (MWWE) and its constituents, such as chemicals of emerging concern, pose a potential threat to the sustainability of fish populations by disrupting key endocrine functions in aquatic organisms. While studies have demonstrated changes in biological markers of exposure of aquatic organisms to groups of chemicals of emerging concern, the variability of these markers over time has not been sufficiently described in wild fish species. The aim of this study was to assess the spatial and temporal variability of biological markers in response to MWWE exposure and to test the consistency of these responses between seasons and among years. Rainbow darter (Etheostoma caeruleum) were collected in spring and fall seasons over a 5-year period in the Grand River, Ontario, Canada. In addition to surface water chemistry (nutrients and selected pharmaceuticals), measures were taken across levels of biological organization in rainbow darter. The measurements of hormone production, gonad development, and intersex severity were temporally consistent and suggested impaired reproduction in male fish collected downstream of MWWE outfalls. In contrast, ovarian development and hormone production in females appeared to be influenced more by urbanization than MWWE. Measures of gene expression and somatic indices were highly variable between sites and years, respectively, and were inconclusive in terms of the impacts of MWWE overall. Robust biomonitoring programs must consider these factors in both the design and interpretation of results, especially when spatial and temporal sampling of biological endpoints is limited. Assessing the effects of contaminants and other stressors on fish in watersheds would be greatly enhanced by an approach that considers natural variability in the endpoints being measured. PMID:27776151

Spatial and temporal variability of chorus and hiss

NASA Astrophysics Data System (ADS)

Santolik, O.; Hospodarsky, G. B.; Kurth, W. S.; Kletzing, C.

2017-12-01

Whistler-mode electromagnetic waves, especially natural emissions of chorus and hiss, have been shown to influence the dynamics of the Van Allen radiation belts via quasi-linear or nonlinear wave particle interactions, transferring energy between different electron populations. Average intensities of chorus and hiss emissions have been found to increase with increasing levels of geomagnetic activity but their stochastic variations in individual spacecraft measurements are usually larger these large-scale temporal effects. To separate temporal and spatial variations of wave characteristics, measurements need to be simultaneously carried out in different locations by identical and/or well calibrated instrumentation. We use two-point survey measurements of the Waves instruments of the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) onboard two Van Allen Probes to asses spatial and temporal variability of chorus and hiss. We take advantage of a systematic analysis of this large data set which has been collected during 2012-2017 over a range of separation vectors of the two spacecraft. We specifically address the question whether similar variations occur at different places at the same time. Our results indicate that power variations are dominated by separations in MLT at scales larger than 0.5h.

Comparing bulk electrical conductivities spatial series obtained by Time Domain Reflectometry and Electromagnetic Induction sensors

NASA Astrophysics Data System (ADS)

Saeed, Ali; Ajeel, Ali; dragonetti, giovanna; Comegna, Alessandro; Lamaddalena, Nicola; Coppola, Antonio

2016-04-01

The ability to determine and monitor the effects of salts on soils and plants, are of great importance to agriculture. To control its harmful effects, soil salinity needs to be monitored in space and time. This requires knowledge of its magnitude, temporal dynamics, and spatial variability. Conventional ground survey procedures by direct soil sampling are time consuming, costly and destructive. Alternatively, soil salinity can be evaluated by measuring the bulk electrical conductivity (σb) directly in the field. Time domain reflectometry (TDR) sensors allow simultaneous measurements of water content, θ, and σb. They may be calibrated for estimating the electrical conductivity of the soil solution (σw). However, they have a relatively small observation window and thus they are thought to only provide local-scale measurements. The spatial range of the sensors is limited to tens of centimeters and extension of the information to a large area can be problematic. Also, information on the vertical distribution of the σb soil profile may only be obtained by installing sensors at different depths. In this sense, the TDR may be considered as an invasive technique. Compared to the TDR, other geophysical methods based for example on Electromagnetic Induction (EMI) techniques are non-invasive methods and represent a viable alternative to traditional techniques for soil characterization. The problem is that all these techniques give depth-weighted apparent electrical conductivity (σa) measurements, depending on the specific depth distribution of the σb, as well as on the depth response function of the sensor used. In order to deduce the actual distribution of the bulk electrical conductivity, σb, in the soil profile, one needs to invert the signal coming from EMI. Because of their relatively lower observation window, TDR sensors provide quasi-point values and do not adequately integrate the spatial variability of the chemical concentration distribution in the soil solution (and of the water content) induced by natural soil heterogeneity. Thus, the variability of TDR readings is expected to come from a combination of smaller and larger-scale variations. By contrast, an EMI sensor reading partly smoothes the small-scale variability seen by a TDR probe. As a consequence, the variability revealed by profile-integrated EMI and local (within a given depth interval) TDR readings may have completely different characteristics. In this study, a comparison between the variability patterns of σb revealed by TDR and EMI sensors was carried out. The database came from a field experiment conducted in the Mediterranean Agronomic Institute (MAI) of Valenzano (Bari). The soil was pedologically classified as Colluvic Regosol, consisting of a silty loam with an average depth of 60 cm on a shallow fractured calcareous rock. The experimental field (30m x 15.6 m; for a total area of 468 m2) consisted of three transects of 30 m length and 4.2 width, cultivated with green bean and irrigated with three different salinity levels (1 dS/m, 3dS/m, 6dS/m). Each transect consisted of seven crop rows irrigated by a drip irrigation system (dripper discharge q=2 l/h.). Water salinity was induced by adding CaCl2 to the tap water. All crop-soil measurements were conducted along the middle row at 24 monitoring sites, 1m apart. The spatial and temporal evolution of bulk electrical conductivity (σb) of soil was monitored by i) an Electromagnetic Induction method (EM38-DD) and ii) Time Domain Reflectometry (TDR). Herein we will focus on the methodology we used to elaborate the database of this experiment. Mostly, the data elaboration was devoted to make TDR and EMI data actually comparable. Specifically, we analysed the effect of the different observation windows of TDR and EMI sensors on the different spatial and temporal variability observed in the data series coming from the two sensors. After exploring the different patterns and structures of variability of the original EMI and TDR data series the study assessed the potential of applying a Fourier's analysis to filter the original data series to extract the predominant, high-variance signal after removing the small- scale (high frequency) variance observed in the TDR data series.

Heterogeneous source components of intraplate basalts from NE China induced by the ongoing Pacific slab subduction

NASA Astrophysics Data System (ADS)

Chen, Huan; Xia, Qun-Ke; Ingrin, Jannick; Deloule, Etienne; Bi, Yao

2017-02-01

The subduction of oceanic slabs is widely accepted to be a main reason for chemical heterogeneities in the mantle. However, determining the contributions of slabs in areas that have experienced multiple subduction events is often difficult due to possible overlapping imprints. Understanding the temporal and spatial variations of source components for widespread intraplate small volume basalts in eastern China may be a basis for investigating the influence of the subducted Pacific slab, which has long been postulated but never confirmed. For this purpose, we investigated the Chaihe-aershan volcanic field (including more than 35 small-volume Quaternary basaltic volcanoes) in NE China and measured the oxygen isotopes and water content of clinopyroxene (cpx) phenocrysts using secondary ion mass spectrometry (SIMS) and Fourier transform infrared spectroscopy (FTIR), respectively. The water content of magma was then estimated based on the partition coefficient of H2O between cpx and the basaltic melt. The δ18O of cpx phenocrysts (4.28‰ to 8.57‰) and H2O content of magmas (0.19 wt.%-2.70 wt.%) show large variations, reflecting the compositional heterogeneity of the mantle source. The δ18O values and H2O content within individual samples also display considerable variation, suggesting the mixing of magmas and that the magma mixing occurred shortly before the eruption. The relation between the δ18O values of cpx phenocrysts and the H2O/Ce ratio, Ba/Th ratio and Eu anomaly of whole rocks demonstrates the contributions of three components to the mantle source (hydrothermally altered upper oceanic crust and marine sediments, altered lower gabbroic oceanic crust, and ambient mantle). The proportions of these three components have varied widely over time (∼1.37 Ma to ∼0.25 Ma). The Pacific slab is constantly subducted under eastern Asia and continuously transports recycled materials to the deep mantle. The temporal heterogeneity of the source components may be caused by ongoing Pacific slab subduction. Combined with other basalt localities in eastern China (Shuangliao basalts, Taihang basalts and Shangdong basalts), the contributions of recycled oceanic components in their mantle source are heterogeneous. This spatial heterogeneity of mantle sources may be induced by variable alterations and dehydration during the recycling process of the Pacific slab. Our results show that the source components of Cenozoic intraplate small-volume basalts in eastern China are temporally and spatially heterogeneous, which is likely induced by the ongoing subduction of the Pacific slab. This demonstrates that integrating the temporal variations in geochemical characteristics and tectonic history of a study region can identify the subducted oceanic plate that induced enriched components in the mantle source of intraplate basalts.

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

Temporally variable environments maintain more beta-diversity in Mediterranean landscapes

NASA Astrophysics Data System (ADS)

Martin, Beatriz; Ferrer, Miguel

2015-10-01

We examined the relationships between different environmental factors and the alpha and beta-diversity of terrestrial vertebrates (birds, mammals, amphibians and reptiles) in a Mediterranean region at the landscape level. We investigated whether the mechanisms underlying alpha and beta-diversity patterns are influenced by energy availability, habitat heterogeneity and temporal variability and if the drivers of the diversity patterns differed between both components of diversity. We defined alpha-diversity as synonym of species richness whereas beta-diversity was measured as distinctiveness. We evaluated a total of 13 different predictors using generalized linear mixed model (GLMM) analysis. Habitat spatial heterogeneity increased alpha-diversity, but contrastingly, it did not significantly affect beta-diversity among sites. Disturbed landscapes may show higher habitat spatial variation and higher alpha-diversity due to the contribution of highly generalist species that are wide-distributed and do not differ in composition (beta-diversity) among different sites within the region. Contrastingly, higher beta-diversity levels were negatively related to more stable sites in terms of temporal environmental variation. This negative relationship between environmental stability and beta-diversity levels is explained in terms of species adaptation to the local environmental conditions. Our study highlights the importance of temporal environmental variability in maintaining beta-diversity patterns under highly variable environmental conditions.

Direction of unsaturated flow in a homogeneous and isotropic hillslope

USGS Publications Warehouse

Lu, Ning; Kaya, Basak Sener; Godt, Jonathan W.

2011-01-01

The distribution of soil moisture in a homogeneous and isotropic hillslope is a transient, variably saturated physical process controlled by rainfall characteristics, hillslope geometry, and the hydrological properties of the hillslope materials. The major driving mechanisms for moisture movement are gravity and gradients in matric potential. The latter is solely controlled by gradients of moisture content. In a homogeneous and isotropic saturated hillslope, absent a gradient in moisture content and under the driving force of gravity with a constant pressure boundary at the slope surface, flow is always in the lateral downslope direction, under either transient or steady state conditions. However, under variably saturated conditions, both gravity and moisture content gradients drive fluid motion, leading to complex flow patterns. In general, the flow field near the ground surface is variably saturated and transient, and the direction of flow could be laterally downslope, laterally upslope, or vertically downward. Previous work has suggested that prevailing rainfall conditions are sufficient to completely control these flow regimes. This work, however, shows that under time-varying rainfall conditions, vertical, downslope, and upslope lateral flow can concurrently occur at different depths and locations within the hillslope. More importantly, we show that the state of wetting or drying in a hillslope defines the temporal and spatial regimes of flow and when and where laterally downslope and/or laterally upslope flow occurs.

Direction of unsaturated flow in a homogeneous and isotropic hillslope

USGS Publications Warehouse

Lu, N.; Kaya, B.S.; Godt, J.W.

2011-01-01

The distribution of soil moisture in a homogeneous and isotropic hillslope is a transient, variably saturated physical process controlled by rainfall characteristics, hillslope geometry, and the hydrological properties of the hillslope materials. The major driving mechanisms for moisture movement are gravity and gradients in matric potential. The latter is solely controlled by gradients of moisture content. In a homogeneous and isotropic saturated hillslope, absent a gradient in moisture content and under the driving force of gravity with a constant pressure boundary at the slope surface, flow is always in the lateral downslope direction, under either transient or steady state conditions. However, under variably saturated conditions, both gravity and moisture content gradients drive fluid motion, leading to complex flow patterns. In general, the flow field near the ground surface is variably saturated and transient, and the direction of flow could be laterally downslope, laterally upslope, or vertically downward. Previous work has suggested that prevailing rainfall conditions are sufficient to completely control these flow regimes. This work, however, shows that under time-varying rainfall conditions, vertical, downslope, and upslope lateral flow can concurrently occur at different depths and locations within the hillslope. More importantly, we show that the state of wetting or drying in a hillslope defines the temporal and spatial regimes of flow and when and where laterally downslope and/or laterally upslope flow occurs. Copyright 2011 by the American Geophysical Union.

Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data

NASA Astrophysics Data System (ADS)

Huang, X.; Tan, J.

2014-11-01

Commutes in urban areas create interesting travel patterns that are often stored in regional transportation databases. These patterns can vary based on the day of the week, the time of the day, and commuter type. This study proposes methods to detect underlying spatio-temporal variability among three groups of commuters (senior citizens, child/students, and adults) using data mining and spatial analytics. Data from over 36 million individual trip records collected over one week (March 2012) on the Singapore bus and Mass Rapid Transit (MRT) system by the fare collection system were used. Analyses of such data are important for transportation and landuse designers and contribute to a better understanding of urban dynamics. Specifically, descriptive statistics, network analysis, and spatial analysis methods are presented. Descriptive variables were proposed such as density and duration to detect temporal features of people. A directed weighted graph G ≡ (N , L, W) was defined to analyze the global network properties of every pair of the transportation link in the city during an average workday for all three categories. Besides, spatial interpolation and spatial statistic tools were used to transform the discrete network nodes into structured human movement landscape to understand the role of transportation systems in urban areas. The travel behaviour of the three categories follows a certain degree of temporal and spatial universality but also displays unique patterns within their own specialties. Each category is characterized by their different peak hours, commute distances, and specific locations for travel on weekdays.

Climate and climate variability of the wind power resources in the Great Lakes region of the United States

Treesearch

X. Li; S. Zhong; X. Bian; W.E. Heilman

2010-01-01

The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution...

Variability of streambed hydraulic conductivity in an intermittent stream reach regulated by Vented Dams: A case study

NASA Astrophysics Data System (ADS)

Naganna, Sujay Raghavendra; Deka, Paresh Chandra

2018-07-01

The hydro-geological properties of streambed together with the hydraulic gradients determine the fluxes of water, energy and solutes between the stream and underlying aquifer system. Dam induced sedimentation affects hyporheic processes and alters substrate pore space geometries in the course of progressive stabilization of the sediment layers. Uncertainty in stream-aquifer interactions arises from the inherent complex-nested flow paths and spatio-temporal variability of streambed hydraulic properties. A detailed field investigation of streambed hydraulic conductivity (Ks) using Guelph Permeameter was carried out in an intermittent stream reach of the Pavanje river basin located in the mountainous, forested tract of western ghats of India. The present study reports the spatial and temporal variability of streambed hydraulic conductivity along the stream reach obstructed by two Vented Dams in sequence. Statistical tests such as Levene's and Welch's t-tests were employed to check for various variability measures. The strength of spatial dependence and the presence of spatial autocorrelation among the streambed Ks samples were tested by using Moran's I statistic. The measures of central tendency and dispersion pointed out reasonable spatial variability in Ks distribution throughout the study reach during two consecutive years 2016 and 2017. The streambed was heterogeneous with regard to hydraulic conductivity distribution with high-Ks zones near the backwater areas of the vented dam and low-Ks zones particularly at the tail water section of vented dams. Dam operational strategies were responsible for seasonal fluctuations in sedimentation and modifications to streambed substrate characteristics (such as porosity, grain size, packing etc.), resulting in heterogeneous streambed Ks profiles. The channel downstream of vented dams contained significantly more cohesive deposits of fine sediment due to the overflow of surplus suspended sediment-laden water at low velocity and pressure head. The statistical test results accept the hypothesis of significant spatial variability of streambed Ks but refuse to accept the temporal variations. The deterministic and geo-statistical approaches of spatial interpolation provided virtuous surface maps of streambed Ks distribution.

Imaging Variable Stars with HST

NASA Astrophysics Data System (ADS)

Karovska, Margarita

2011-05-01

The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents.I will highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I will describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semi-regular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

Imaging Variable Stars with HST

NASA Astrophysics Data System (ADS)

Karovska, M.

2012-06-01

(Abstract only) The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents. I highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semiregular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

The test-retest reliability and minimal detectable change of spatial and temporal gait variability during usual over-ground walking for younger and older adults.

PubMed

Almarwani, Maha; Perera, Subashan; VanSwearingen, Jessie M; Sparto, Patrick J; Brach, Jennifer S

2016-02-01

Gait variability is a marker of gait performance and future mobility status in older adults. Reliability of gait variability has been examined mainly in community dwelling older adults who are likely to fluctuate over time. The purpose of this study was to compare test-retest reliability and determine minimal detectable change (MDC) of spatial and temporal gait variability in younger and older adults. Forty younger (mean age=26.6 ± 6.0 years) and 46 older adults (mean age=78.1 ± 6.2 years) were included in the study. Gait characteristics were measured twice, approximately 1 week apart, using a computerized walkway (GaitMat II). Participants completed 4 passes on the GaitMat II at their self-selected walking speed. Test-retest reliability was calculated using Intra-class correlation coefficients (ICCs(2,1)), 95% limits of agreement (95% LoA) in conjunction with Bland-Altman plots, relative limits of agreement (LoA%) and standard error of measurement (SEM). The MDC at 90% and 95% level were also calculated. ICCs of gait variability ranged 0.26-0.65 in younger and 0.28-0.74 in older adults. The LoA% and SEM were consistently higher (i.e. less reliable) for all gait variables in older compared to younger adults except SEM for step width. The MDC was consistently larger for all gait variables in older compared to younger adults except step width. ICCs were of limited utility due to restricted ranges in younger adults. Based on absolute reliability measures and MDC, younger had greater test-retest reliability and smaller MDC of spatial and temporal gait variability compared to older adults. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantifying stream thermal regimes at management-pertinent scales: combining thermal infrared and stationary stream temperature data in a novel modeling framework.

USGS Publications Warehouse

Vatland, Shane J.; Gresswell, Robert E.; Poole, Geoffrey C.

2015-01-01

Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.

A full Bayes before-after study accounting for temporal and spatial effects: Evaluating the safety impact of new signal installations.

PubMed

Sacchi, Emanuele; Sayed, Tarek; El-Basyouny, Karim

2016-09-01

Recently, important advances in road safety statistics have been brought about by methods able to address issues other than the choice of the best error structure for modeling crash data. In particular, accounting for spatial and temporal interdependence, i.e., the notion that the collision occurrence of a site or unit times depend on those of others, has become an important issue that needs further research. Overall, autoregressive models can be used for this purpose as they can specify that the output variable depends on its own previous values and on a stochastic term. Spatial effects have been investigated and applied mostly in the context of developing safety performance functions (SPFs) to relate crash occurrence to highway characteristics. Hence, there is a need for studies that attempt to estimate the effectiveness of safety countermeasures by including the spatial interdependence of road sites within the context of an observational before-after (BA) study. Moreover, the combination of temporal dynamics and spatial effects on crash frequency has not been explored in depth for SPF development. Therefore, the main goal of this research was to carry out a BA study accounting for spatial effects and temporal dynamics in evaluating the effectiveness of a road safety treatment. The countermeasure analyzed was the installation of traffic signals at unsignalized urban/suburban intersections in British Columbia (Canada). The full Bayes approach was selected as the statistical framework to develop the models. The results demonstrated that zone variation was a major component of total crash variability and that spatial effects were alleviated by clustering intersections together. Finally, the methodology used also allowed estimation of the treatment's effectiveness in the form of crash modification factors and functions with time trends. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatio-temporal modelling for assessing air pollution in Santiago de Chile

NASA Astrophysics Data System (ADS)

Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

2017-01-01

In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

Coronal energy distribution and X-ray activity in the small scale magnetic field of the quiet sun

NASA Technical Reports Server (NTRS)

Habbal, S. R.

1992-01-01

The energy distribution in the small-scale magnetic field that pervades the solar surface, and its relationship to X-ray/coronal activity are discussed. The observed emission from the small scale structures, at temperatures characteristic of the chromosphere, transition region and corona, emanates from the boundaries of supergranular cells, within coronal bright points. This emission is characterized by a strong temporal and spatial variability with no definite pattern. The analysis of simultaneous, multiwavelength EUV observations shows that the spatial density of the enhanced as well as variable emission from the small scale structures exhibits a pronounced temperature dependence with significant maxima at 100,000 and 1,000,000 K. Within the limits of the spatial (1-5 arcsec) and temporal (1-5 min) resolution of data available at present, the observed variability in the small scale structure cannot account for the coroal heating of the quiet sun. The characteristics of their emission are more likely to be an indicator of the coronal heating mechanisms.

From stage to age in variable environments: life expectancy and survivorship.

PubMed

Tuljapurkar, Shripad; Horvitz, Carol C

2006-06-01

Stage-based demographic data are now available on many species of plants and some animals, and they often display temporal and spatial variability. We provide exact formulas to compute age-specific life expectancy and survivorship from stage-based data for three models of temporal variability: cycles, serially independent random variation, and a Markov chain. These models provide a comprehensive description of patterns of temporal variation. Our formulas describe the effects of cohort (birth) environmental condition on mortality at all ages, and of the effects on survivorship of environmental variability experienced over the course of life. This paper complements existing methods for time-invariant stage-based data, and adds to the information on population growth and dynamics available from stochastic demography.

Soil water content spatial pattern estimated by thermal inertia from air-borne sensors

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Basile, Angelo; Esposito, Marco; Menenti, Massimo; Buonanno, Maurizio

2010-05-01

Remote sensing of soil water content from air- or space-borne platforms offer the possibility to provide large spatial coverage and temporal continuity. The water content can be actually monitored in a thin soil layer, usually up to a depth of 0.05m below the soil surface. To the contrary, difficulties arise in the estimation of the water content storage along the soil profile and its spatial (horizontal) distribution, which are closely connected to soil hydraulic properties and their spatial distribution. A promising approach for estimating soil water contents profiles is the integration of remote sensing of surface water content and hydrological modeling. A major goal of the scientific group is to develop a practical and robust procedure for estimating water contents throughout the soil profile from surface water content. As a first step, in this work, we will show some preliminary results from aircraft images analysis and their validation by field campaigns data. The data extracted from the airborne sensors provided the opportunity of retrieving land surface temperatures with a very high spatial resolution. The surface water content pattern, as deduced by the thermal inertia estimations, was compared to the surface water contents maps measured in situ by time domain reflectometry-based probes.

Single-shot spectro-temporal characterization of XUV pulses from a seeded free-electron laser

PubMed Central

De Ninno, Giovanni; Gauthier, David; Mahieu, Benoît; Ribič, Primož Rebernik; Allaria, Enrico; Cinquegrana, Paolo; Danailov, Miltcho Bojanov; Demidovich, Alexander; Ferrari, Eugenio; Giannessi, Luca; Penco, Giuseppe; Sigalotti, Paolo; Stupar, Matija

2015-01-01

Intense ultrashort X-ray pulses produced by modern free-electron lasers (FELs) allow one to probe biological systems, inorganic materials and molecular reaction dynamics with nanoscale spatial and femtoscale temporal resolution. These experiments require the knowledge, and possibly the control, of the spectro-temporal content of individual pulses. FELs relying on seeding have the potential to produce spatially and temporally fully coherent pulses. Here we propose and implement an interferometric method, which allows us to carry out the first complete single-shot spectro-temporal characterization of the pulses, generated by an FEL in the extreme ultraviolet spectral range. Moreover, we provide the first direct evidence of the temporal coherence of a seeded FEL working in the extreme ultraviolet spectral range and show the way to control the light generation process to produce Fourier-limited pulses. Experiments are carried out at the FERMI FEL in Trieste. PMID:26290320

Spatial and Temporal Variation of Water Quality in the Bertam Catchment, Cameron Highlands, Malaysia.

PubMed

Rasul, M G; Islam, Mir Sujaul; Yunus, Rosli Bin Mohd; Mokhtar, Mazlin Bin; Alam, Lubna; Yahaya, F M

2017-12-01

  The spatio-temporal variability of water quality associated with anthropogenic activities was studied for the Bertam River and its main tributaries within the Bertam Catchment, Cameron Highlands, Malaysia. A number of physico-chemical parameters of collected samples were analyzed to evaluate their spatio-temporal variability. Nonparametric statistical analysis showed significant temporal and spatial differences (p < 0.05) in most of the parameters across the catchment. Parameters except dissolved oxygen and chemical oxygen demand displayed higher values in rainy season. The higher concentration of total suspended solids was caused by massive soil erosion and sedimentation. Seasonal variations in contaminant concentrations are largely affected by precipitation and anthropogenic influences. Untreated domestic wastewater discharge as well as agricultural runoff significantly influenced the water quality. Poor agricultural practices and development activities at slope areas also affected the water quality within the catchment. The analytical results provided a basis for protection of river environments and ecological restoration in mountainous Bertam Catchment.

Time-space variations in infrasound sources related to environmental dynamics around Lützow-Holm Bay, east Antarctica

NASA Astrophysics Data System (ADS)

Murayama, Takahiko; Kanao, Masaki; Yamamoto, Masa-Yuki; Ishihara, Yoshiaki; Matsushima, Takeshi; Kakinami, Yoshihiro; Okada, Kazumi; Miyamachi, Hiroki; Nakamoto, Manami; Takeuchi, Yukari; Toda, Shigeru

2017-12-01

Characteristic features of infrasound waves observed in the Antarctic reflect the physical interaction between the surface environment along the continental margin and the surrounding Southern Ocean. The temporal-spatial variability of the source locations for infrasound excitation during the eight-month period between January and August 2015 was investigated using recordings made by two infrasound arrays deployed along a section of the coast of Lützow-Holm Bay (LHB), Antarctica. The infrasound arrays clearly detected temporal variations in frequency content and propagation direction during this period. A number of infrasound sources were identified, many located north of the arrays. Many of the events had a predominant frequency content of a few Hz, higher than microbaroms from the ocean. A comparison of the results with MODIS satellite images indicated that these infrasound sources were ice-quakes associated with the calving of glaciers, the breaking off of sea ice, and collisions between this sea ice and icebergs around the LHB. Continuous measurements of infrasound in the Antarctic may serve as a proxy for monitoring the regional surface environment in terms of climate change at high southern latitudes.

Compensatory Water Effects Link Yearly Global Land CO2 Sink Changes to Temperature

NASA Technical Reports Server (NTRS)

Jung, Martin; Reichstein, Markus; Tramontana, Gianluca; Viovy, Nicolas; Schwalm, Christopher R.; Wang, Ying-Ping; Weber, Ulrich; Weber, Ulrich; Zaehle, Soenke; Zeng, Ning;

Spatial-temporal analysis of sea level changes in China seas and neighboring oceans by merged altimeter data

NASA Astrophysics Data System (ADS)

Xu, Yao; Zhou, Bin; Yu, Zhifeng; Lei, Hui; Sun, Jiamin; Zhu, Xingrui; Liu, Congjin

2017-01-01

The knowledge of sea level changes is critical important for social, economic and scientific development in coastal areas. Satellite altimeter makes it possible to observe long term and large scale dynamic changes in the ocean, contiguous shelf seas and coastal zone. In this paper, 1993-2015 altimeter data of Topex/Poseidon and its follow-on missions is used to get a time serious of continuous and homogeneous sea level anomaly gridding product. The sea level rising rate is 0.39 cm/yr in China Seas and the neighboring oceans, 0.37 cm/yr in the Bo and Yellow Sea, 0.29 cm/yr in the East China Sea and 0.40 cm/yr in the South China Sea. The mean sea level and its rising rate are spatial-temporal non-homogeneous. The mean sea level shows opposite characteristics in coastal seas versus open oceans. The Bo and Yellow Sea has the most significant seasonal variability. The results are consistent with in situ data observation by the Nation Ocean Agency of China. The coefficient of variability model is introduced to describe the spatial-temporal variability. Results show that the variability in coastal seas is stronger than that in open oceans, especially the seas off the entrance area of the river, indicating that the validation of altimeter data is less reasonable in these seas.

Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate.

PubMed

Ramos, M C; Jones, G V; Yuste, J

2015-12-01

The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27(th), bloom June 17(th), and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Jones, G. V.; Yuste, J.

2015-12-01

The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27th, bloom June 17th, and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

Modeling the Spatial and Temporal Variation of Monthly and Seasonal Precipitation on the Nevada Test Site and Vicinity, 1960-2006

USGS Publications Warehouse

Blainey, Joan B.; Webb, Robert H.; Magirl, Christopher S.

2007-01-01

The Nevada Test Site (NTS), located in the climatic transition zone between the Mojave and Great Basin Deserts, has a network of precipitation gages that is unusually dense for this region. This network measures monthly and seasonal variation in a landscape with diverse topography. Precipitation data from 125 climate stations on or near the NTS were used to spatially interpolate precipitation for each month during the period of 1960 through 2006 at high spatial resolution (30 m). The data were collected at climate stations using manual and/or automated techniques. The spatial interpolation method, applied to monthly accumulations of precipitation, is based on a distance-weighted multivariate regression between the amount of precipitation and the station location and elevation. This report summarizes the temporal and spatial characteristics of the available precipitation records for the period 1960 to 2006, examines the temporal and spatial variability of precipitation during the period of record, and discusses some extremes in seasonal precipitation on the NTS.

Analysis of satellite precipitation over East Africa during last decades

NASA Astrophysics Data System (ADS)

Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

2016-04-01

Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and CWD (maximum number of consecutive wet days) time series do not exhibit a similar behavior and trends are generally weaker with a lower significance level with respect to PRCPTOT and SDII.

Phenology Atlas of Czechia in preparation - aim & content

NASA Astrophysics Data System (ADS)

Hajkova, L.; Nekovar, J.; Novak, M.; Richterova, D.

2009-09-01

The main task is to create Phenology Atlas of Czechia for the period 1991 - 2010 by using geographic information systems. The general outputs will be maps (average phenophase onset at different altitudes), graphs (evaluation of phenophase onset in time) and tables (statistical results) with text, picture and botanical specification. The publication will be divided into 6 main chapters (Introduction, Phenology in Czechia & Europe, Methodology of observation, Field crops & Fruit trees & Wild plants, Phenology regionalisation, Temporal and Spatial variability). The essantial emphasis will be enforced on wild plants especially allergology important plants and phenophases. CHMI phenological and meteorological data will be used as an input data. This publication will be allocated for general public, supposed size B4, 270 - 300 pages. The research project is proposed for 3 years (2009 - 2011). In the presentation will be given several examples of Atlas content (Norway Spruce and Birch phenophases from Transaction of CHMI Nr.50, 2007).

Climatic change by cloudiness linked to the spatial variability of sea surface temperatures

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

An active role in modifying the earth's climate is suggested for low cloudiness over the circumarctic oceans. Such cloudiness, linked to the spatial differences in ocean surface temperatures, was studied. The temporal variations from year to year of ocean temperature patterns can be pronounced and therefore, the low cloudiness over this region should also show strong temporal variations, affecting the albedo of the earth and therefore the climate. Photographs are included.

A Hybrid Model for Spatially and Temporally Resolved Ozone Exposures in the Continental United States

PubMed Central

Di, Qian; Rowland, Sebastian; Koutrakis, Petros; Schwartz, Joel

2017-01-01

Ground-level ozone is an important atmospheric oxidant, which exhibits considerable spatial and temporal variability in its concentration level. Existing modeling approaches for ground-level ozone include chemical transport models, land-use regression, Kriging, and data fusion of chemical transport models with monitoring data. Each of these methods has both strengths and weaknesses. Combining those complementary approaches could improve model performance. Meanwhile, satellite-based total column ozone, combined with ozone vertical profile, is another potential input. We propose a hybrid model that integrates the above variables to achieve spatially and temporally resolved exposure assessments for ground-level ozone. We used a neural network for its capacity to model interactions and nonlinearity. Convolutional layers, which use convolution kernels to aggregate nearby information, were added to the neural network to account for spatial and temporal autocorrelation. We trained the model with AQS 8-hour daily maximum ozone in the continental United States from 2000 to 2012 and tested it with left out monitoring sites. Cross-validated R2 on the left out monitoring sites ranged from 0.74 to 0.80 (mean 0.76) for predictions on 1 km×1 km grid cells, which indicates good model performance. Model performance remains good even at low ozone concentrations. The prediction results facilitate epidemiological studies to assess the health effect of ozone in the long term and the short term. PMID:27332675

Temporal and spatial variation in pharmaceutical concentrations in an urban river system

USGS Publications Warehouse

Burns, Emily E.; Carter, Laura J.; Kolpin, Dana W.; Thomas-Oates, Jane; Boxall, Alistair B.A.

2018-01-01

Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse.

Did hydrographic sampling capture global and regional deep ocean heat content trends accurately between 1990-2010?

NASA Astrophysics Data System (ADS)

Garry, Freya; McDonagh, Elaine; Blaker, Adam; Roberts, Chris; Desbruyères, Damien; King, Brian

2017-04-01

Estimates of heat content change in the deep oceans (below 2000 m) over the last thirty years are obtained from temperature measurements made by hydrographic survey ships. Cruises occupy the same tracks across an ocean basin approximately every 5+ years. Measurements may not be sufficiently frequent in time or space to allow accurate evaluation of total ocean heat content (OHC) and its rate of change. It is widely thought that additional deep ocean sampling will also aid understanding of the mechanisms for OHC change on annual to decadal timescales, including how OHC varies regionally under natural and anthropogenically forced climate change. Here a 0.25˚ ocean model is used to investigate the magnitude of uncertainties and biases that exist in estimates of deep ocean temperature change from hydrographic sections due to their infrequent timing and sparse spatial distribution during 1990 - 2010. Biases in the observational data may be due to lack of spatial coverage (not enough sections covering the basin), lack of data between occupations (typically 5-10 years apart) and due to occupations not closely spanning the time period of interest. Between 1990 - 2010, the modelled biases globally are comparatively small in the abyssal ocean below 3500 m although regionally certain biases in heat flux into the 4000 - 6000 m layer can be up to 0.05 Wm-2. Biases in the heat flux into the deep 2000 - 4000 m layer due to either temporal or spatial sampling uncertainties are typically much larger and can be over 0.1 Wm-2 across an ocean. Overall, 82% of the warming trend below 2000 m is captured by observational-style sampling in the model. However, at 2500 m (too deep for additional temperature information to be inferred from upper ocean Argo) less than two thirds of the magnitude of the global warming trend is obtained, and regionally large biases exist in the Atlantic, Southern and Indian Oceans, highlighting the need for widespread improved deep ocean temperature sampling. In addition to bias due to infrequent sampling, moving the timings of occupations by a few months generates relatively large uncertainty due to intra-annual variability in deep ocean model temperature, further strengthening the case for high temporal frequency observations in the deep ocean (as could be achieved using deep ocean autonomous float technologies). Biases due to different uncertainties can have opposing signs and differ in relative importance both regionally and with depth revealing the importance of reducing all uncertainties (both spatial and temporal) simultaneously in future deep ocean observing design.

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.

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

PubMed Central

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P.; Jansson, Janet K.; Hopkins, David W.; Aspray, Thomas J.; Seely, Mary; Trindade, Marla I.; Cowan, Don A.

2016-01-01

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall. PMID:27680878

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input.

PubMed

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P; Jansson, Janet K; Hopkins, David W; Aspray, Thomas J; Seely, Mary; Trindade, Marla I; Cowan, Don A

2016-09-29

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO 2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Quantifying Uncontrolled Air Emissions from Two Florida Landfills

EPA Science Inventory

Landfill gas emissions, if left uncontrolled, contribute to air toxics, climate change, trospospheric ozone, and urban smog. Measuring emissions from landfills presents unique challenges due to the large and variable source area, spatial and temporal variability of emissions, and...

Mapping field spatial distribution patterns of isoproturon-mineralizing activity over a three-year winter wheat/rape seed/barley rotation.

PubMed

Hussain, S; Devers-Lamrani, M; Spor, A; Rouard, N; Porcherot, M; Beguet, J; Martin-Laurent, F

2013-03-01

The temporal and spatial variability of the activity of soil microorganisms able to mineralize the herbicide isoproturon (IPU) pesticide was investigated over a three-year long crop rotation between 2008 and 2010. Isoproturon mineralization was higher in 2008, when winter wheat was treated with this herbicide, than in 2009 and 2010, when rape seed and barley were treated with different herbicides. Under laboratory conditions, we showed that isoproturon mineralization was not promoted by sulfonylurea herbicide applied on barley crop in 2010. IPU mineralization was shown to be highly variable at the field scale in years 2009 and 2010. Principal component analyses and analyses of similarities revealed that soil pH and equivalent humidity, and to a lesser extent soil organic matter content and cation exchange capacity (CEC) were the main drivers of isoproturon-mineralizing activity variance. Using a rather simple model that yields the rate of isoproturon mineralization as a function of soil pH and equivalent humidity, we explained up to 85% of the variance observed. Mapping field-scale distribution of isoproturon mineralization over the three-year survey indicated higher variability in 2009 and in 2010 as compared to 2008, suggesting that isoproturon treatment applied to winter wheat promoted isoproturon mineralization activity and reduced its spatial variability. Field-scale distribution of isoproturon mineralization showed important similarity to the distribution of soil pH, equivalent humidity and to a lesser extent to soil organic matter and cation exchange capacity (CEC) thereby confirming our model. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Characterization of nano-porosity in molecular layer deposited films.

PubMed

Perrotta, Alberto; Poodt, Paul; van den Bruele, F J Fieke; Kessels, W M M Erwin; Creatore, Mariadriana

2018-06-12

Molecular layer deposition (MLD) delivers (ultra-) thin organic and hybrid materials, with atomic-level thickness control. However, such layers are often reported to be unstable under ambient conditions, due to the interaction of water and oxygen with the hybrid structure, consequently limiting their applications. In this contribution, we investigate the impact of porosity in MLD layers on their degradation. Alucone layers were deposited by means of trimethylaluminium and ethylene glycol, adopting both temporal and spatial MLD and characterized by means of FT-IR spectroscopy, spectroscopic ellipsometry, and ellipsometric porosimetry. The highest growth per cycle (GPC) achieved by spatial MLD resulted in alucone layers with very low stability in ambient air, leading to their conversion to AlOx. Alucones deposited by means of temporal MLD, instead, showed a lower GPC and a higher ambient stability. Ellipsometric porosimetry showed the presence of open nano-porosity in pristine alucone layers. Pores with a diameter in the range of 0.42-2 nm were probed, with a relative content between 1.5% and 5%, respectively, which are attributed to the temporal and spatial MLD layers. We concluded that a correlation exists between the process GPC, the open-porosity relative content, and the degradation of alucone layers.

Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

Treesearch

Travis J. Woolley; Mark E. Harmon; Kari B. O’Connell

2015-01-01

Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a...

[Spatial variation characteristics of surface soil water content, bulk density and saturated hydraulic conductivity on Karst slopes].

PubMed

Zhang, Chuan; Chen, Hong-Song; Zhang, Wei; Nie, Yun-Peng; Ye, Ying-Ying; Wang, Ke-Lin

2014-06-01

Surface soil water-physical properties play a decisive role in the dynamics of deep soil water. Knowledge of their spatial variation is helpful in understanding the processes of rainfall infiltration and runoff generation, which will contribute to the reasonable utilization of soil water resources in mountainous areas. Based on a grid sampling scheme (10 m x 10 m) and geostatistical methods, this paper aimed to study the spatial variability of surface (0-10 cm) soil water content, soil bulk density and saturated hydraulic conductivity on a typical shrub slope (90 m x 120 m, projected length) in Karst area of northwest Guangxi, southwest China. The results showed that the surface soil water content, bulk density and saturated hydraulic conductivity had different spatial dependence and spatial structure. Sample variogram of the soil water content was fitted well by Gaussian models with the nugget effect, while soil bulk density and saturated hydraulic conductivity were fitted well by exponential models with the nugget effect. Variability of soil water content showed strong spatial dependence, while the soil bulk density and saturated hydraulic conductivity showed moderate spatial dependence. The spatial ranges of the soil water content and saturated hydraulic conductivity were small, while that of the soil bulk density was much bigger. In general, the soil water content increased with the increase of altitude while it was opposite for the soil bulk densi- ty. However, the soil saturated hydraulic conductivity had a random distribution of large amounts of small patches, showing high spatial heterogeneity. Soil water content negatively (P < 0.01) correlated with the bulk density and saturated hydraulic conductivity, while there was no significant correlation between the soil bulk density and saturated hydraulic conductivity.

Independent rate and temporal coding in hippocampal pyramidal cells.

PubMed

Huxter, John; Burgess, Neil; O'Keefe, John

2003-10-23

In the brain, hippocampal pyramidal cells use temporal as well as rate coding to signal spatial aspects of the animal's environment or behaviour. The temporal code takes the form of a phase relationship to the concurrent cycle of the hippocampal electroencephalogram theta rhythm. These two codes could each represent a different variable. However, this requires the rate and phase to vary independently, in contrast to recent suggestions that they are tightly coupled, both reflecting the amplitude of the cell's input. Here we show that the time of firing and firing rate are dissociable, and can represent two independent variables: respectively the animal's location within the place field, and its speed of movement through the field. Independent encoding of location together with actions and stimuli occurring there may help to explain the dual roles of the hippocampus in spatial and episodic memory, or may indicate a more general role of the hippocampus in relational/declarative memory.

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.

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

2017-12-01

SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be demonstrated by results obtained while developing the methodology for assessing collective significance of trends in multi-site weather series. The performance of the proposed test statistics is assessed based on large number of realisations of synthetic series produced by WG assuming a given statistical structure and trend of the weather series.

The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3

Treesearch

Samuel A. Cushman; Jeremy Littell; Kevin McGarigal

2010-01-01

In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...

Contrasting spatial patterns in active-fire and fire-suppressed Mediterranean climate old-growth mixed conifer forests

Treesearch

Danny L. Fry; Scott L. Stephens; Brandon M. Collins; Malcolm North; Ernesto Franco-Vizcaino; Samantha J. Gill

2014-01-01

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference...

Spatial patterning of fuels and fire hazard across a central U.S. deciduous forest region

Treesearch

Michael C. Stambaugh; Daniel C. Dey; Richard P. Guyette; Hong S. He; Joseph M. Marschall

2011-01-01

Information describing spatial and temporal variability of forest fuel conditions is essential to assessing overall fire hazard and risk. Limited information exists describing spatial characteristics of fuels in the eastern deciduous forest region, particularly in dry oak-dominated regions that historically burned relatively frequently. From an extensive fuels survey...

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

Vegetation optical depth measured by microwave radiometry as an indicator of tree mortality risk

NASA Astrophysics Data System (ADS)

Rao, K.; Anderegg, W.; Sala, A.; Martínez-Vilalta, J.; Konings, A. G.

2017-12-01

Increased drought-related tree mortality has been observed across several regions in recent years. Vast spatial extent and high temporal variability makes field monitoring of tree mortality cumbersome and expensive. With global coverage and high temporal revisit, satellite remote sensing offers an unprecedented tool to monitor terrestrial ecosystems and identify areas at risk of large drought-driven tree mortality events. To date, studies that use remote sensing data to monitor tree mortality have focused on external climatic thresholds such as temperature and evapotranspiration. However, this approach fails to consider internal water stress in vegetation - which can vary across trees even for similar climatic conditions due to differences in hydraulic behavior, soil type, etc - and may therefore be a poor basis for measuring mortality events. There is a consensus that xylem hydraulic failure often precedes drought-induced mortality, suggesting depleted canopy water content shortly before onset of mortality. Observations of vegetation optical depth (VOD) derived from passive microwave are proportional to canopy water content. In this study, we propose to use variations in VOD as an indicator of potential tree mortality. Since VOD accounts for intrinsic water stress undergone by vegetation, it is expected to be more accurate than external climatic stress indicators. Analysis of tree mortality events in California, USA observed by airborne detection shows a consistent relationship between mortality and the proposed VOD metric. Although this approach is limited by the kilometer-scale resolution of passive microwave radiometry, our results nevertheless demonstrate that microwave-derived estimates of vegetation water content can be used to study drought-driven tree mortality, and may be a valuable tool for mortality predictions if they can be combined with higher-resolution variables.

Spatial Frequency Priming of Scene Perception in Adolescents with and without ASD

ERIC Educational Resources Information Center

Vanmarcke, Steven; Noens, Ilse; Steyaert, Jean; Wagemans, Johan

2017-01-01

While most typically developing (TD) participants have a coarse-to-fine processing style, people with autism spectrum disorder (ASD) seem to be less globally and more locally biased when processing visual information. The stimulus-specific spatial frequency content might be directly relevant to determine this temporal hierarchy of visual…

Should heterogeneity be the basis for conservation? Grassland bird response to fire and grazing

USGS Publications Warehouse

Fuhlendorf, S.D.; Harrell, W.C.; Engle, David M.; Hamilton, R.G.; Davis, C.A.; Leslie, David M.

2006-01-01

In tallgrass prairie, disturbances such as grazing and fire can generate patchiness across the landscape, contributing to a shifting mosaic that presumably enhances biodiversity. Grassland birds evolved within the context of this shifting mosaic, with some species restricted to one or two patch types created under spatially and temporally distinct disturbance regimes. Thus, management-driven reductions in heterogeneity may be partly responsible for declines in numbers of grassland birds. We experimentally altered spatial heterogeneity of vegetation structure within a tallgrass prairie by varying the spatial and temporal extent of fire and by allowing grazing animals to move freely among burned and unburned patches (patch treatment). We contrasted this disturbance regime with traditional agricultural management of the region that promotes homogeneity (traditional treatment). We monitored grassland bird abundance during the breeding seasons of 2001-2003 to determine the influence of altered spatial heterogeneity on the grassland bird community. Focal disturbances of patch burning and grazing that shifted through the landscape over several years resulted in a more heterogeneous pattern of vegetation than uniform application of fire and grazing. Greater spatial heterogeneity in vegetation provided greater variability in the grassland bird community. Some bird species occurred in greatest abundance within focally disturbed patches, while others occurred in relatively undisturbed patches in our patch treatment. Henslow's Sparrow, a declining species, occurred only within the patch treatment. Upland Sandpiper and some other species were more abundant on recently disturbed patches within the same treatment. The patch burn treatment created the entire gradient of vegetation structure required to maintain a suite of grassland bird species that differ in habitat preferences. Our study demonstrated that increasing spatial and temporal heterogeneity of disturbance in grasslands increases variability in vegetation structure that results in greater variability at higher trophic levels. Thus, management that creates a shifting mosaic using spatially and temporally discrete disturbances in grasslands can be a useful tool in conservation. In the case of North American tallgrass prairie, discrete fires that capitalize on preferential grazing behavior of large ungulates promote a shifting mosaic of habitat types that maintain biodiversity and agricultural productivity. ?? 2006 by the Ecological Society of America.

TEMPORAL AND SPATIAL VARIABILITY IN THE ESTROGENICITY OF A MUNICIPAL WASTEWATER EFFLUENT

EPA Science Inventory

Estrogenicity of a municipal wastewater effluent was monitored using the vitellogenin biomarker in adult male fathead minnows (Pimephales promelas). Variability in expression of the vitellogenin biomarker was evident among monitoring periods. Significant increases in plasma vit...

Spatial variability of heating profiles in windrowed poultry litter

USDA-ARS?s Scientific Manuscript database

In-house windrow composting of broiler litter has been suggested as a means to reduce microbial populations between flocks. Published time-temperature goals are used to determine the success of the composting process for microbial reductions. Spatial and temporal density of temperature measurement ...

Spatial variability in denitrification rates in an Oregon tidal salt marsh

EPA Science Inventory

Modeling denitrification (DeN) is particularly challenging in tidal systems, which play a vital role in buffering adjacent coastal waters from nitrogen inputs. These systems are hydrologically and biogeochemically complex, varying on fine temporal and spatial scales. As part of a...

The vertical structure of upper ocean variability at the Porcupine Abyssal Plain during 2012-2013

NASA Astrophysics Data System (ADS)

Damerell, Gillian M.; Heywood, Karen J.; Thompson, Andrew F.; Binetti, Umberto; Kaiser, Jan

2016-05-01

This study presents the characterization of variability in temperature, salinity and oxygen concentration, including the vertical structure of the variability, in the upper 1000 m of the ocean over a full year in the northeast Atlantic. Continuously profiling ocean gliders with vertical resolution between 0.5 and 1 m provide more information on temporal variability throughout the water column than time series from moorings with sensors at a limited number of fixed depths. The heat, salt and dissolved oxygen content are quantified at each depth. While the near surface heat content is consistent with the net surface heat flux, heat content of the deeper layers is driven by gyre-scale water mass changes. Below ˜150m, heat and salt content display intraseasonal variability which has not been resolved by previous studies. A mode-1 baroclinic internal tide is detected as a peak in the power spectra of water mass properties. The depth of minimum variability is at ˜415m for both temperature and salinity, but this is a depth of high variability for oxygen concentration. The deep variability is dominated by the intermittent appearance of Mediterranean Water, which shows evidence of filamentation. Susceptibility to salt fingering occurs throughout much of the water column for much of the year. Between about 700-900 m, the water column is susceptible to diffusive layering, particularly when Mediterranean Water is present. This unique ability to resolve both high vertical and temporal variability highlights the importance of intraseasonal variability in upper ocean heat and salt content, variations that may be aliased by traditional observing techniques.

Assessing How Water Type, Climate, and Landscape Position Correlate with Variability of Methane in Shallow Groundwater in the Marcellus Region

NASA Astrophysics Data System (ADS)

Campbell, A.; Lautz, L.; Hoke, G. D.

2017-12-01

Prior work shows that spatial differences in naturally-occurring methane concentrations in shallow groundwater in the Marcellus Shale region are correlated with water type (e.g. Ca-HCO3 vs Na-HCO3) and landscape position (e.g. valley vs upland). However, little is known about how naturally-occurring methane in groundwater varies through time, particularly on a seasonal or monthly time scale, and how temporal variability is related to seasonal changes in climate. Extensive development of the Marcellus shale gas play in northeastern Pennsylvania limits opportunities for measuring baseline water quality through time. In contrast, a ban on hydraulic fracturing in NY affords an opportunity for characterizing baseline temporal variability in methane concentrations. The objective of this study is to characterize temporal variability of naturally-occurring methane in shallow groundwater in the Marcellus region, and how such temporal variability is correlated to other well characteristics, such as water type, landscape position, and climatic conditions. We worked with homeowners to sample 11 domestic wells monthly in the Marcellus Shale region of NY for methane concentrations and major ions for a full year. Wells were grouped according to the primary source of methane (e.g. thermogenic vs microbial) based upon δ13C-DIC, δ13C-CH4, and δD-CH4 isotopes. The full dataset and the grouped data were analyzed to assess how well climatic conditions, water type, and landscape position correlate with variability of methane concentrations through time. These data provide information on within year and between year variability of methane, as well as spatial variability between wells, which fills a data gap and can be used to inform policy regulations.

The Flora Mission for Ecosystem Composition, Disturbance and Productivity

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Knox, Robert G.; Green, Robert O.; Ungar, Stephen G.

2005-01-01

Global land use and climate variability alter ecosystem conditions - including structure, function, and biological diversity - at a pace that requires unambiguous observations from satellite vantage points. Current global measurements are limited to general land cover, some disturbances, vegetation leaf area index, and canopy energy absorption. Flora is a pathfinding mission that provides new measurements of ecosystem structure, function, and diversity to understand the spatial and temporal dynamics of human and natural disturbances, and the biogeochemical and physiological responses of ecosystems to disturbance. The mission relies upon high-fidelity imaging spectroscopy to deliver full optical spectrum measurements (400-2500 nm) of the global land surface on a monthly time step at 45 meter spatial resolution for three years. The Flora measurement objectives are: (i) fractional cover of biological materials, (ii) canopy water content, (iii) vegetation pigments and light-use efficiency, (iv) plant functional types, (v) fire fuel load and fuel moisture content, and (vi) disturbance occurrence, type and intensity. These measurements are made using a multi-parameter, spectroscopic analysis approach afforded by observation of the full optical spectrum. Combining these measurements, along with additional observations from multispectral sensors, Flora will far advance global studies and models of ecosystem dynamics and change.

Using Actively Heated Fibre Optics (AHFO) to determine soil thermal conductivity and soil moisture content at high spatial and temporal resolution

NASA Astrophysics Data System (ADS)

Ciocca, Francesco; Abesser, Corinna; Hannah, David; Blaen, Philip; Chalari, Athena; Mondanos, Michael; Krause, Stefan

2017-04-01

Optical fibre distributed temperature sensing (DTS) is increasingly used in environmental monitoring and for subsurface characterisation, e.g. to obtain precise measurements of soil temperature at high spatio-temporal resolution, over several kilometres of optical fibre cable. When combined with active heating of metal elements embedded in the optical fibre cable (active-DTS), the temperature response of the soil to heating provides valuable information from which other important soil parameters, such as thermal conductivity and soil moisture content, can be inferred. In this presentation, we report the development of an Actively Heated Fibre Optics (AHFO) method for the characterisation of soil thermal conductivity and soil moisture dynamics at high temporal and spatial resolutions at a vegetated hillslope site in central England. The study site is located within a juvenile forest adjacent to the Birmingham Institute of Forest Research (BIFoR) experimental site. It is instrumented with three loops of a 500m hybrid-optical cable installed at 10cm, 25cm and 40cm depths. Active DTS surveys were undertaken in June and October 2016, collecting soil temperature data at 0.25m intervals along the cable, prior to, during and after the 900s heating phase. Soil thermal conductivity and soil moisture were determined according to Ciocca et al. 2012, applied to both the cooling and the heating phase. Independent measurements of soil thermal conductivity and soil moisture content were collected using thermal needle probes, calibrated capacitance-based probes and laboratory methods. Results from both the active DTS survey and independent in-situ and laboratory measurements will be presented, including the observed relationship between thermal conductivity and moisture content at the study site and how it compares against theoretical curves used by the AHFO methods. The spatial variability of soil thermal conductivity and soil moisture content, as observed using the different methods, will be shown and an outlook will be provided of how the AHFO method can benefit soil sciences, ground source heat pump applications and groundwater recharge estimations. This research is part of the Distributed intelligent Heat Pulse System (DiHPS) project which is funded by the UK Natural Environmental Research Council (NERC). The project is supported by BIFoR, the European Space Agency (ESA), CarbonZero Ltd, the UK Forestry Commission and the UK Soil Moisture Observation Network (COSMOS-UK). This work is distributed under the Creative Commons Attribution 3.0 Unported Licence together with an author copyright. This licence does not conflict with the regulations of the Crown Copyright. Ciocca F., Lunati I., van de Giesen N., and Parlange M.B. 2012. Heated optical fiber for distributed soil-moisture measurements: A lysimeter experiment. Vadose Zone J. 11. doi:10.2136/vzj2011.0177

Temporal and spatial variability of aeolian sand transport: Implications for field measurements

NASA Astrophysics Data System (ADS)

Ellis, Jean T.; Sherman, Douglas J.; Farrell, Eugene J.; Li, Bailiang

2012-01-01

Horizontal variability is often cited as one source of disparity between observed and predicted rates of aeolian mass flux, but few studies have quantified the magnitude of this variability. Two field projects were conducted to evaluate meter-scale spatial and temporal in the saltation field. In Shoalhaven Heads, NSW, Australia a horizontal array of passive-style sand traps were deployed on a beach for 600 or 1200 s across a horizontal span of 0.80 m. In Jericoacoara, Brazil, traps spanning 4 m were deployed for 180 and 240 s. Five saltation sensors (miniphones) spaced 1 m apart were also deployed at Jericoacoara. Spatial variation in aeolian transport rates over small spatial and short temporal scales was substantial. The measured transport rates ( Q) obtained from the passive traps ranged from 0.70 to 32.63 g/m/s. When considering all traps, the coefficient of variation ( CoV) values ranged from 16.6% to 67.8%, and minimum and maximum range of variation coefficient ( RVC) values were 106.1% to 152.5% and 75.1% to 90.8%, respectively. The miniphone Q and CoV averaged 47.1% and 4.1% for the 1260 s data series, which was subsequently sub-sampled at 60-630 s intervals to simulate shorter deployment times. A statistically significant ( p < 0.002), inverselinear relationship was found between sample duration and CoV and between Q and CoV, the latter relationship also considering data from previous studies.

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.

Multiple concurrent temporal recalibrations driven by audiovisual stimuli with apparent physical differences.

PubMed

Yuan, Xiangyong; Bi, Cuihua; Huang, Xiting

2015-05-01

Out-of-synchrony experiences can easily recalibrate one's subjective simultaneity point in the direction of the experienced asynchrony. Although temporal adjustment of multiple audiovisual stimuli has been recently demonstrated to be spatially specific, perceptual grouping processes that organize separate audiovisual stimuli into distinctive "objects" may play a more important role in forming the basis for subsequent multiple temporal recalibrations. We investigated whether apparent physical differences between audiovisual pairs that make them distinct from each other can independently drive multiple concurrent temporal recalibrations regardless of spatial overlap. Experiment 1 verified that reducing the physical difference between two audiovisual pairs diminishes the multiple temporal recalibrations by exposing observers to two utterances with opposing temporal relationships spoken by one single speaker rather than two distinct speakers at the same location. Experiment 2 found that increasing the physical difference between two stimuli pairs can promote multiple temporal recalibrations by complicating their non-temporal dimensions (e.g., disks composed of two rather than one attribute and tones generated by multiplying two frequencies); however, these recalibration aftereffects were subtle. Experiment 3 further revealed that making the two audiovisual pairs differ in temporal structures (one transient and one gradual) was sufficient to drive concurrent temporal recalibration. These results confirm that the more audiovisual pairs physically differ, especially in temporal profile, the more likely multiple temporal perception adjustments will be content-constrained regardless of spatial overlap. These results indicate that multiple temporal recalibrations are based secondarily on the outcome of perceptual grouping processes.

Variability of Relative Sea Level Rise: Spatial and Temporal Correlations in Northwest Gulf of Mexico

NASA Astrophysics Data System (ADS)

Tissot, P.; Reisinger, A. S.; Besonen, M. R.

2017-12-01

While our understanding of global sea level rise and its budget has made great progress over the past decade, the spatial and temporal variability of relative sea level rise along the coasts still needs to be better understood and quantified. We developed a technique to reduce the confidence intervals associated with relative sea level rise (RSLR) estimates for 15 tide gauges located along the Texas coast for the period 1993-2016. Seasonally detrended monthly mean water levels are highly correlated after removal of station-specific RSLR trends, which allows for the quantification of a common, low frequency oceanic signal. RSLR confidence intervals are reduced from over 1.9 mm/yr, on average 2.3mm, to less than 1.1 mm/yr, on average 0.7 mm/yr after removing this common signal. The resulting RSLR rates range from 3.0 to 8.4 mm/yr. The range is wider than the longer-term rates of 5.3, 3.8 and 1.9 mm/yr measured from north to south by the three National Water Level Observation Network (NWLON) stations covering the study area (over different and longer time spans). The results emphasize the importance of the spatial variability of the vertical land motion component of RSLR. The temporal variability of the coherent oceanic signal is not significantly correlated to the ENSO signal for the study period and is only weakly correlated to the AMO and PDO climate indices. The coherence of the signal is further investigated by comparison with other locations along the Gulf of Mexico and along the Northeast Atlantic coast. The results are discussed while considering strong local processes along the Northwest Gulf of Mexico, such as wind forcing and intermittent eddies and the spatially broader influence of the Gulf Stream. The local significance of the RSLR spatial and temporal differences are discussed in terms of the differences in inundation frequency for nuisance type flooding including comparing the time span to reach a probability of at least one nuisance flood event per year.

Trading Space for Time in Design Storm Estimation Using Radar Data

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Berndt, C.

2017-12-01

Intensity-duration-frequency (IDF) curves are frequently used for the derivation of design storms. These curves are usually estimated from rain gauges and are valid for extreme rainfall at local observed points. Two common problems are involved. Regionalization of rainfall statistics for unobserved locations and the use of areal reduction factors (ARF) for the adjustment to larger catchments are required. Weather radar data are available with large spatial coverage and high resolution in space and could be used for a direct derivation of areal design storms for any location and catchment size. However, one problem with radar data is the relatively short observation period for the estimation of extreme events. This study deals with the estimation of area-intensity-duration-frequency (AIDF) curves and areal-reduction-factors (ARF) directly from weather radar data. The main objective is to answer the question if it is possible to trade space for time in the estimation of both characteristics to compensate for the short radar observation periods. In addition, a stratification of the temporal sample according to annual temperature indices is tried to distinguish "colder" and "warmer" climate years. This might eventually show a way for predicting future changes in AIDF curves and ARFs. First, radar data are adjusted with rainfall observations from the daily station network. Thereafter, AIDF curves and ARFs are calculated for different spatial and temporal sample sizes. The AIDF and ARFs are compared regarding their temporal and spatial variability considering also the temperature conditions. In order to reduce spatial variability a grouping of locations according to their climatological and physiographical characteristics is carried out. The data used for this study cover about 20 years of observations from the radar device located near Hanover in Northern Germany and 500 non-recording rain gauges as well as a set of 8 recording rain gauges for validation. AIDF curves and ARFS are analyzed for rainfall durations from 5 minutes to 24 hours and return periods from 1 year to 30 years. It is hypothesized, that the spatial variability of AIDF and ARF characteristics decreases with increasing sample size, grouping and normalization and is finally comparable to temporal variability.

Temporal Dynamics and Persistence of Spatial Patterns: from Groundwater to Soil Moisture to Transpiration

NASA Astrophysics Data System (ADS)

Blume, T.; Hassler, S. K.; Weiler, M.

2017-12-01

Hydrological science still struggles with the fact that while we wish for spatially continuous images or movies of state variables and fluxes at the landscape scale, most of our direct measurements are point measurements. To date regional measurements resolving landscape scale patterns can only be obtained by remote sensing methods, with the common drawback that they remain near the earth surface and that temporal resolution is generally low. However, distributed monitoring networks at the landscape scale provide the opportunity for detailed and time-continuous pattern exploration. Even though measurements are spatially discontinuous, the large number of sampling points and experimental setups specifically designed for the purpose of landscape pattern investigation open up new avenues of regional hydrological analyses. The CAOS hydrological observatory in Luxembourg offers a unique setup to investigate questions of temporal stability, pattern evolution and persistence of certain states. The experimental setup consists of 45 sensor clusters. These sensor clusters cover three different geologies, two land use classes, five different landscape positions, and contrasting aspects. At each of these sensor clusters three soil moisture/soil temperature profiles, basic climate variables, sapflow, shallow groundwater, and stream water levels were measured continuously for the past 4 years. We will focus on characteristic landscape patterns of various hydrological state variables and fluxes, studying their temporal stability on the one hand and the dependence of patterns on hydrological states on the other hand (e.g. wet vs dry). This is extended to time-continuous pattern analysis based on time series of spatial rank correlation coefficients. Analyses focus on the absolute values of soil moisture, soil temperature, groundwater levels and sapflow, but also investigate the spatial pattern of the daily changes of these variables. The analysis aims at identifying hydrologic signatures of the processes or landscape characteristics acting as major controls. While groundwater, soil water and transpiration are closely linked by the water cycle, they are controlled by different processes and we expect this to be reflected in interlinked but not necessarily congruent patterns and responses.

Impacts of cattle grazing on spatio-temporal variability of soil moisture and above-ground live plant biomass in mixed grasslands

NASA Astrophysics Data System (ADS)

Virk, Ravinder

Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB heterogeneity over time was observed for heavy grazing intensity. All grazing intensities showed decrease in spatial range (patch size) over time indicating that grazing is a patchy process. The study demonstrates that cattle grazing with variable intensity can maintain and change the spatial patterns of vegetation in the studied region. Using a modelling approach, the relative degrees to which grazing intensity and soil properties affect grassland productivity and carbon dynamics at longer time-periods were investigated. Both grass productivity and carbon dynamics are sensitive to variability in soil texture and grazing intensity. Moderate grazing is predicted to be the best option in terms of maintaining sufficient heterogeneity to support species diversity, as well as for carbon management in the mixed grassland ecosystem.

Investigatigating inter-/intra-annual variability of surface hydrology at northern high latitude from spaceborne measurements

NASA Astrophysics Data System (ADS)

Kang, K.; Duguay, C. R.

2014-12-01

Lakes encompass a large part of the surface cover in the northern boreal and tundra areas of northern Canada and are therefore a significant component of the terrestrial hydrological system. To understand the hydrologic cycle over subarctic and arctic landscapes, estimating surface parameters such as surface net radiation, soil moisture, and surface albedo is important. Although ground-based field measurements provide a good temporal resolution, these data provide a limited spatial representation and are often restricted to the summer period (from June to August), and few surface-based stations are located in high-latitude regions. In this respect, spaceborne remote sensing provides the means to monitor surface hydrology and to estimate components of the surface energy balance with reasonable spatial and temporal resolutions required for hydrological investigations, as well as for providing more spatially representative lake-relevant information than available from in situ measurements. The primary objective of this study is to quantify the sources of temporal and spatial variability in surface albedo over subarctic wetland from satellite derived albedo measurements in the Hudson Bay Lowlands near Churchill, Manitoba. The spatial variability in albedo within each land-cover type is investigated through optical satellite imagery from Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper Plus, and Landsat-8 Operational Land Imager obtained in different seasons from spring into fall (April and October) over a 30-year period (1984-2013). These data allowed for an examination of the spatial variability of surface albedo under relatively dry and wet summer conditions (i.e. 1984, 1998 versus 1991, 2005). A detailed analysis of Landsat-derived surface albedo (ranging from 0.09 to 0.15) conducted in the Churchill region for August is inversely related to surface water fraction calculated from Landsat images. Preliminary analysis of surface albedo observed between July and August are 0.10 to 0.15, and vary due to differences in meteorological parameters such as rainfall, surface moisture and surface air temperature. Overall, spaceborne optical data are an invaluable source for investigating changes and variability in surface albedo in relation to surface hydrology over subarctic regions.

SPCZ variability in 30 years of high temporal and spatial resolution satellite data

NASA Astrophysics Data System (ADS)

Haffke, C. M.; Magnusdottir, G.

2010-12-01

A recently developed spatial-temporal statistical model for objectively identifying the ITCZ is modified and adapted for the South Pacific Convergence Zone (SPCZ). Using a Bayesian statistical framework along with a Markov random field algorithm, the model determines the presence or absence of the SPCZ in instantaneous satellite observations. From this, SPCZ location, area, and intensity of convection are determined. The model incorporates satellite observations, prior knowledge of typical SPCZ location, and information from neighboring pixels in space and time to determine whether a given pixel is labeled as SPCZ or non-SPCZ. The model ‘learns’ to identify the SPCZ through manual labeling and is ultimately designed to emulate the way a human observer would identify the SPCZ given a sequence of satellite images of different fields. The statistical model has several advantages over previous labeling methods, such as threshholding an observed field (such as IR). Threshholding may identify isolated areas of convection as SPCZ that a human observer would not include. Similarly it may omit areas within a human identified SPCZ region that are not active during the current time frame. The three types of satellite observations that were used as input to the original ITCZ detection model were infrared and visible GOES data as well as total precipitable water. GOES infrared is available every three hours from 1980-present, GOES visible has usable observations every 24 hours from 1995-present, and total precipitable water, a composite of all available microwave data (e.g. SSM/I, TMI, AMSR-E), is available every six hours from 1995-present. We shall describe the model development efforts that are mainly focused on including additional sources of high temporal and spatial resolution satellite observations (such as quikSCAT surface winds and TRMM precipitation). Other products such as sea surface temperature and mixed-layer ocean heat content are used for understanding coupling with the ocean and for model validation. Model output, or identified SPCZ regions, provide the means to track the SPCZ ‘envelope’ and determine variability in location, area, and intensity of convection on diurnal to decadal time scales. The length of the recently archived satellite data set (1980-2009) allows for a thorough examination of seasonal and interannual variability, which will be presented. We also aim to quantify SPCZ interaction with ENSO and the MJO.

Spatial and Temporal Variability of Southern Auroral Emissions in the IR from JIRAM/Juno Data

NASA Astrophysics Data System (ADS)

Mura, A.; Altieri, F.; Moriconi, M. L.; Adriani, A.; Grassi, D.; Migliorini, A.; Gerard, J. C. M. C.; Dinelli, B. M.; Fabiano, F.; Filacchione, G.; Sindoni, G.; Tosi, F.; Piccioni, G.; Noschese, R.; Cicchetti, A.; Sordini, R.; Bolton, S. J.; Connerney, J. E. P.; Atreya, S. K.; Levin, S.; Lunine, J. I.; Turrini, D.; Stefani, S.; Olivieri, A.; Plainaki, C.

2017-12-01

JIRAM (Jupiter Infrared Auroral Mapper) is the infrared imaging spectrometer on board the NASA Juno mission. The data collected since August 2016 on both Northern and Southern polar aurora at Jupiter have an unprecedented spatial. Moreover, the JIRAM scanning mirror allows observations of the same area at serveral adjacent time frames.In this work, we focus on the spatial and temporal variability of the Southern aurora. The JIRAM data of the L imager channel (3.3-3.6 µm) have been averaged in bins of 2.5°Lat × 2°Lon and variations of the signal have been investigated for 17:50 < time < 19:45, 27 August 2016. The time frames have been carefully selected in order to avoid possible instrumental residuals in the signal (Mura et al., 2017). We find that near the South Pole, for -87.5°

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Using Bayesian hierarchical models to better understand nitrate sources and sinks in agricultural watersheds.

PubMed

Xia, Yongqiu; Weller, Donald E; Williams, Meghan N; Jordan, Thomas E; Yan, Xiaoyuan

2016-11-15

Export coefficient models (ECMs) are often used to predict nutrient sources and sinks in watersheds because ECMs can flexibly incorporate processes and have minimal data requirements. However, ECMs do not quantify uncertainties in model structure, parameters, or predictions; nor do they account for spatial and temporal variability in land characteristics, weather, and management practices. We applied Bayesian hierarchical methods to address these problems in ECMs used to predict nitrate concentration in streams. We compared four model formulations, a basic ECM and three models with additional terms to represent competing hypotheses about the sources of error in ECMs and about spatial and temporal variability of coefficients: an ADditive Error Model (ADEM), a SpatioTemporal Parameter Model (STPM), and a Dynamic Parameter Model (DPM). The DPM incorporates a first-order random walk to represent spatial correlation among parameters and a dynamic linear model to accommodate temporal correlation. We tested the modeling approach in a proof of concept using watershed characteristics and nitrate export measurements from watersheds in the Coastal Plain physiographic province of the Chesapeake Bay drainage. Among the four models, the DPM was the best--it had the lowest mean error, explained the most variability (R 2  = 0.99), had the narrowest prediction intervals, and provided the most effective tradeoff between fit complexity (its deviance information criterion, DIC, was 45.6 units lower than any other model, indicating overwhelming support for the DPM). The superiority of the DPM supports its underlying hypothesis that the main source of error in ECMs is their failure to account for parameter variability rather than structural error. Analysis of the fitted DPM coefficients for cropland export and instream retention revealed some of the factors controlling nitrate concentration: cropland nitrate exports were positively related to stream flow and watershed average slope, while instream nitrate retention was positively correlated with nitrate concentration. By quantifying spatial and temporal variability in sources and sinks, the DPM provides new information to better target management actions to the most effective times and places. Given the wide use of ECMs as research and management tools, our approach can be broadly applied in other watersheds and to other materials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Permafrost in vegetated scree slopes below the timberline - characterization of thermal properties and permafrost conditions by temperature measurements and geoelectrical monitoring

NASA Astrophysics Data System (ADS)

Schwindt, Daniel; Kneisel, Christof

2010-05-01

Discontinuous alpine permafrost is expected to exist at altitudes above 2400m a.s.l. at mean annual air temperatures (MAAT) of less than -1°C. Below timberline only a few sites are known, where sporadic permafrost exists in vegetated talus slopes with positive MAAT. Aim of the study is to characterize permafrost-humus interaction, the thermal regime and its influence on temporal and spatial permafrost variability. Results of geophysical and thermal measurements from three talus slopes, located in the Swiss Alps (Engadin, Appenzell) at elevations between 1200 and 1800m a.s.l. with MAAT between 2.8°C and 5.5°C are presented. Parent rock-material of the slopes are granite (Bever Valley, Engadin) and dolomite (Susauna Valley, Engadin; Brüeltobel, Appenzell). Joint application of electrical resistivity tomography (ERT) and refraction seismic tomography (RST) is used to detect and characterize permafrost. To observe temporal and spatial variability in ice content and characteristics year-around geoelectrical monitoring and quasi-3D ERT are used. A forward modeling approach has been applied to validate the results of geoelectrical monitoring. A number of temperature data loggers were installed in different depth of the humus layer and in different positions of the slope to monitor the ground thermal regime. Isolated permafrost has been detected by the combination of ERT and RST in the lower parts of the investigated talus slopes. Results from geophysical measurements and monitoring indicate a high spatial and temporal variability in ice content and ice characteristics (temperature, density, content of unfrozen water) for all sites. A distinct rise of resistivities between November and December indicates a decrease of unfrozen water content, caused by a pronounced cooling in the lower parts of the slope. Decreasing ice content and extent of the permafrost lenses can be observed in decreasing seismic velocities from 2600m/sec in spring to only 1500m/sec in October. Ice characteristics, ice content and extent of permafrost lenses depend on the thermal regime, induced by characteristics of surface (humus, vegetation) and subsurface (parental rock material) material as well as thermal effects, with an inversive air flow inside the talus slope of cold air inflow in winter in the lower parts and cold air outflow in summer through the same vents (chimney effect), a theory that has been proven by temperature measurements in the Brüeltobel and the Susauna Valley. While the dolomitic talus slopes are relatively homogenous concerning surface and subsurface material, showing a consistent thick humus cover, the granitic site shows a small-scale heterogeneity of different humus forms and thicknesses as well as size of granitic boulders, influencing the thermal regime. Temperatures in the humus profile are very constant for the dolomitic sites, reflecting the insulation capability of the humus cover, with temperatures in August around 3°C at 30cm depth (mean air temperature in August 12°C). Humus temperatures (30cm depth) in the Bever Valley vary strongly between areas with consistent humus cover (1-2°C in August) and areas with coarse, uncovered boulders, where temperatures show a stronger coupling to air temperatures. While the chimney effect has strong influence on the ground thermal regime of the dolomitic sites, for some parts of the granitic slope in the Bever Valley the theory has to be expanded towards a continuous air exchange with the atmosphere, for areas where the insulation capability of the humus cover is highly disturbed along large parts of the talus slope.

Spatial and temporal dynamics of root exudation: how important is heterogeneity in allelopathic interactions?

PubMed

Weidenhamer, Jeffrey D; Mohney, Brian K; Shihada, Nader; Rupasinghe, Maduka

2014-08-01

Understanding allelopathy has been hindered by the lack of methods available to monitor the dynamics of allelochemicals in the soil. Previous work has demonstrated the feasibility of using polydimethylsiloxane (PDMS) microtubing (silicone tubing microextraction, or STME) to construct sampling devices to monitor the release of lipophilic allelochemicals from plant roots. The objective of this study was to use such sampling devices to intensively monitor thiophene fluxes beneath marigolds over several weeks to gain insight into the magnitude of temporal and spatial heterogeneity in these fluxes. Marigolds were grown in rhizoboxes (20.5 x 20.5 x 3.0 cm) with 16 individual STME samplers per box. Thiophene sampling and HPLC analysis began 45 days after planting. At the end of the study, roots around each sampler were analyzed by HPLC. Results confirmed the tremendous spatial and temporal heterogeneity in thiophene production seen in our previous studies. STME probes show that thiophene concentrations generally increase over time; however, these effects were sampling-port specific. When sampling ports were monitored at 12 h intervals, fluxes at each port ranged from 0 to 2,510 ng day(-1). Fluxes measured over daylight hr averaged 29 % higher than those measured overnight. Fluxes were less than 1 % on average of the total thiophene content of surrounding roots. While the importance of such heterogeneity, or "patchiness", in the root zone has been recognized for soil nutrients, the potential importance in allelopathic interactions has seldom been considered. The reasons for this variability are unclear, but are being investigated. Our results demonstrate that STME can be used as a tool to provide a more finely-resolved picture of allelochemical dynamics in the root zone than has previously been available.

Variability of tornado occurrence over the continental United States since 1950

NASA Astrophysics Data System (ADS)

Guo, Li; Wang, Kaicun; Bluestein, Howard B.

2016-06-01

The United States experiences the most tornadoes of any country in the world. Given the catastrophic impact of tornadoes, concern has arisen regarding the variation in climatology of U.S. tornadoes under the changing climate. A recent study claimed that the temporal variability of tornado occurrence over the continental U.S. has increased since the 1970s. However, that study ignored the highly regionalized climatology of U.S. tornadoes. To address this issue, we examined the long-term trend of tornado temporal variability in each continental U.S. state. Based on the 64 year tornado records (1950-2013), we found that the trends in tornado temporal variability varied across the U.S., with only one third of the continental area or three out of 10 contiguous states (mostly from the Great Plains and Southeast, but where the frequency of occurrence of tornadoes is greater) displaying a significantly increasing trend. The other two-thirds area, where 60% of the U.S. tornadoes were reported (but the frequency of occurrence of tornadoes is less), however, showed a decreasing or a near-zero trend in tornado temporal variability. Furthermore, unlike the temporal variability alone, the combined spatial-temporal variability of U.S. tornado occurrence has remained nearly constant since 1950. Such detailed information on the climatological variability of U.S. tornadoes refines the claim of previous study and can be helpful for local mitigation efforts toward future tornado risks.

Making Energy-Water Nexus Scenarios more Fit-for-Purpose through Better Characterization of Extremes

NASA Astrophysics Data System (ADS)

Yetman, G.; Levy, M. A.; Chen, R. S.; Schnarr, E.

2017-12-01

Often quantitative scenarios of future trends exhibit less variability than the historic data upon which the models that generate them are based. The problem of dampened variability, which typically also entails dampened extremes, manifests both temporally and spatially. As a result, risk assessments that rely on such scenarios are in danger of producing misleading results. This danger is pronounced in nexus issues, because of the multiple dimensions of change that are relevant. We illustrate the above problem by developing alternative joint distributions of the probability of drought and of human population totals, across U.S. counties over the period 2010-2030. For the dampened-extremes case we use drought frequencies derived from climate models used in the U.S. National Climate Assessment and the Environmental Protection Agency's population and land use projections contained in its Integrated Climate and Land Use Scenarios (ICLUS). For the elevated extremes case we use an alternative spatial drought frequency estimate based on tree-ring data, covering a 555-year period (Ho et al 2017); and we introduce greater temporal and spatial extremes in the ICLUS socioeconomic projections so that they conform to observed extremes in the historical U.S. spatial census data 1790-present (National Historical Geographic Information System). We use spatial and temporal coincidence of high population and extreme drought as a proxy for energy-water nexus risk. We compare the representation of risk in the dampened-extreme and elevated-extreme scenario analysis. We identify areas of the country where using more realistic portrayals of extremes makes the biggest difference in estimate risk and suggest implications for future risk assessments. References: Michelle Ho, Upmanu Lall, Xun Sun, Edward R. Cook. 2017. Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow. Water Resources Research. . doi: 10.1002/2016WR019632

Characterization of the Fire Regime and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2016-12-01

The Upper Guinean forest (UGF), encompassing the tropical regions of West Africa, is a globally significant biodiversity hotspot and a critically important socio-economic and ecological resource for the region. However, the UGF is one of the most human-disturbed tropical forest ecosystems with the only remaining large patches of original forests distributed in protected areas, which are embedded in a hotspot of climate stress & land use pressures, increasing their vulnerability to fire. We hypothesized that human impacts and climate interact to drive spatial and temporal variability in fire, with fire exhibiting distinctive seasonality and sensitivity to drought in areas characterized by different population densities, agricultural practices, vegetation types, and levels of forest degradation. We used the MODIS active fire product to identify and characterize fire activity in the major ecoregions of the UGF. We used TRMM rainfall data to measure climatic variability and derived indicators of human land use from a variety of geospatial datasets. We employed time series modeling to identify the influences of drought indices and other antecedent climatic indicators on temporal patterns of active fire occurrence. We used a variety of modeling approaches to assess the influences of human activities and land cover variables on the spatial pattern of fire activity. Our results showed that temporal patterns of fire activity in the UGF were related to precipitation, but these relationships were spatially heterogeneous. The pattern of fire seasonality varied geographically, reflecting both climatological patterns and agricultural practices. The spatial pattern of fire activity was strongly associated with vegetation gradients and anthropogenic activities occurring at fine spatial scales. The Guinean forest-savanna mosaic ecoregion had the most fires. This study contributes to our understanding of UGF fire regime and the spatio-temporal dynamics of tropical forest fires in response to intense human and climatic drivers.

Models and observations of foam coverage and bubble content in the surf zone

NASA Astrophysics Data System (ADS)

Kirby, J. T.; Shi, F.; Holman, R. A.

2010-12-01

Optical and acoustical observations and communications are hampered in the nearshore by the presence of bubbles and foam generated by breaking waves. Bubble clouds in the water column provide a highly variable (both spatially and temporally) obstacle to direct acoustic and optical paths. Persistent foam riding on the water surface creates a primary occlusion of optical penetration into the water column. In an effort to better understand and predict the level of bubble and foam content in the surfzone, we have been pursuing the development of a detailed phase resolved model of fluid and gaseous components of the water column, using a Navier-Stokes/VOF formulation extended to include a multiphase description of polydisperse bubble populations. This sort of modeling provides a detailed description of large scale turbulent structures and associated bubble transport mechanisms under breaking wave crests. The modeling technique is too computationally intensive, however, to provide a wider-scale description of large surfzone regions. In order to approach the larger scale problem, we are developing a model for spatial and temporal distribution of foam and bubbles within the framework of a Boussinesq model. The basic numerical framework for the code is described by Shi et al (2010, this conference). Bubble effects are incorporated both in the mass and momentum balances for weakly dispersive, fully nonlinear waves, with spatial and temporal bubble distributions parameterized based on the VOF modeling and measurements and tied to the computed rate of dissipation of energy during breaking. A model of a foam layer on the water surface is specified using a shallow water formulation. Foam mass conservation includes source and sink terms representing outgassing of the water column, direct foam generation due to surface agitation, and erosion due to bubble bursting. The foam layer motion in the plane of the water surface arises due to a balance of drag forces due to wind and water column motion. Preliminary steps to calibrate and verify the resulting models will be taken based on results to be collected during the Surf Zone Optics experiment at Duck, NC in September 2010. Initial efforts will focus on an examination of breaking wave patterns and persistent foam distributions, using ARGUS imagery.

Cross-scale interactions drive ecosystem responses to precipitation in the Chihuahuan Desert

USDA-ARS?s Scientific Manuscript database

Regime shifts from grass- to shrub-dominated states are widespread in arid and semiarid regions globally. These patterns of grass production and shifts to shrub dominance are spatially variable and correlate weakly with precipitation, suggesting that processes at different spatial and temporal scale...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of partic...

Tradeoffs between vegetation management goals and livestock production under Adapative Grazing Management

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems are characterized by substantial temporal variability in weather overlaid on spatial variability associated with topography and soils (Fuhlendorf et al. 2012). Semiarid rangelands in particular are characterized by more extreme intra- and inter-annual variation in precipitation ...

Fish Assemblage Structure Under Variable Environmental Conditions in the Ouachita Mountains

Treesearch

Christopher M. Taylor; Lance R. Williams; Riccardo A. Fiorillo; R. Brent Thomas; Melvin L. Warren

2004-01-01

Abstract - Spatial and temporal variability of fish assemblages in Ouachita Mountain streams, Arkansas, were examined for association with stream size and flow variability. Fishes and habitat were sampled quarterly for four years at 12 sites (144 samples) in the Ouachita Mountains Ecosystem Management Research Project, Phase III watersheds. Detrended...

Variability, trends, and drivers of regional fluctuations in Australian fire activity

NASA Astrophysics Data System (ADS)

Earl, Nick; Simmonds, Ian

2017-07-01

Throughout the world fire regimes are determined by climate, vegetation, and anthropogenic factors, and they have great spatial and temporal variability. The availability of high-quality satellite data has revolutionized fire monitoring, allowing for a more consistent and comprehensive evaluation of temporal and spatial patterns. Here we utilize a satellite based "active fire" (AF) product to statistically analyze 2001-2015 variability and trends in Australian fire activity and link this to precipitation and large-scale atmospheric structures (namely, the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD)) known to have potential for predicting fire activity in different regions. It is found that Australian fire activity is decreasing (during summer (December-February)) or stable, with high temporal and spatial variability. Eastern New South Wales (NSW) has the strongest decreasing trend (to the 1% confidence level), especially during the winter (JJA) season. Other significantly decreasing areas are Victoria/NSW, Tasmania, and South-east Queensland. These decreasing fire regions are relatively highly populated, so we suggest that the declining trends are due to improved fire management, reducing the size and duration of bush fires. Almost half of all Australian AFs occur during spring (September-November). We show that there is considerable potential throughout Australia for a skillful forecast for future season fire activity based on current and previous precipitation activity, ENSO phase, and to a lesser degree, the IOD phase. This is highly variable, depending on location, e.g., the IOD phase is for more indicative of fire activity in southwest Western Australia than for Queensland.

Temporal and spatial variabilities of Antarctic ice mass changes inferred by GRACE in a Bayesian framework

NASA Astrophysics Data System (ADS)

Wang, L.; Davis, J. L.; Tamisiea, M. E.

2017-12-01

The Antarctic ice sheet (AIS) holds about 60% of all fresh water on the Earth, an amount equivalent to about 58 m of sea-level rise. Observation of AIS mass change is thus essential in determining and predicting its contribution to sea level. While the ice mass loss estimates for West Antarctica (WA) and the Antarctic Peninsula (AP) are in good agreement, what the mass balance over East Antarctica (EA) is, and whether or not it compensates for the mass loss is under debate. Besides the different error sources and sensitivities of different measurement types, complex spatial and temporal variabilities would be another factor complicating the accurate estimation of the AIS mass balance. Therefore, a model that allows for variabilities in both melting rate and seasonal signals would seem appropriate in the estimation of present-day AIS melting. We present a stochastic filter technique, which enables the Bayesian separation of the systematic stripe noise and mass signal in decade-length GRACE monthly gravity series, and allows the estimation of time-variable seasonal and inter-annual components in the signals. One of the primary advantages of this Bayesian method is that it yields statistically rigorous uncertainty estimates reflecting the inherent spatial resolution of the data. By applying the stochastic filter to the decade-long GRACE observations, we present the temporal variabilities of the AIS mass balance at basin scale, particularly over East Antarctica, and decipher the EA mass variations in the past decade, and their role in affecting overall AIS mass balance and sea level.

Digital Archive Issues from the Perspective of an Earth Science Data Producer

NASA Technical Reports Server (NTRS)

Barkstrom, Bruce R.

2004-01-01

Contents include the following: Introduction. A Producer Perspective on Earth Science Data. Data Producers as Members of a Scientific Community. Some Unique Characteristics of Scientific Data. Spatial and Temporal Sampling for Earth (or Space) Science Data. The Influence of the Data Production System Architecture. The Spatial and Temporal Structures Underlying Earth Science Data. Earth Science Data File (or Relation) Schemas. Data Producer Configuration Management Complexities. The Topology of Earth Science Data Inventories. Some Thoughts on the User Perspective. Science Data User Communities. Spatial and Temporal Structure Needs of Different Users. User Spatial Objects. Data Search Services. Inventory Search. Parameter (Keyword) Search. Metadata Searches. Documentation Search. Secondary Index Search. Print Technology and Hypertext. Inter-Data Collection Configuration Management Issues. An Archive View. Producer Data Ingest and Production. User Data Searching and Distribution. Subsetting and Supersetting. Semantic Requirements for Data Interchange. Tentative Conclusions. An Object Oriented View of Archive Information Evolution. Scientific Data Archival Issues. A Perspective on the Future of Digital Archives for Scientific Data. References Index for this paper.

Three-dimensional modelling of slope stability using the Local Factor of Safety concept

NASA Astrophysics Data System (ADS)

Moradi, Shirin; Huisman, Sander; Beck, Martin; Vereecken, Harry; Class, Holger

2017-04-01

Slope stability is governed by coupled hydrological and mechanical processes. The slope stability depends on the effective stress, which in turn depends on the weight of the soil and the matrix potential. Therefore, changes in water content and matrix potential associated with infiltration will affect slope stability. Most available models describing these coupled hydro-mechanical processes either rely on a one- or two-dimensional representation of hydrological and mechanical properties and processes, which obviously is a strong simplification in many applications. Therefore, the aim of this work is to develop a three-dimensional hydro-mechanical model that is able to capture the effect of spatial and temporal variability of both mechanical and hydrological parameters on slope stability. For this, we rely on DuMux, which is a free and open-source simulator for flow and transport processes in porous media that facilitates coupling of different model approaches and offers flexibility for model development. We use the Richards equation to model unsaturated water flow. The simulated water content and matrix potential distribution is used to calculate the effective stress. We only consider linear elasticity and solve for statically admissible fields of stress and displacement without invoking failure or the redistribution of post-failure stress or displacement. The Local Factor of Safety concept is used to evaluate slope stability in order to overcome some of the main limitations of commonly used methods based on limit equilibrium considerations. In a first step, we compared our model implementation with a 2D benchmark model that was implemented in COMSOL Multiphysics. In a second step, we present in-silico experiments with the newly developed 3D model to show the effect of slope morphology, spatial variability in hydraulic and mechanical material properties, and spatially variable soil depth on simulated slope stability. It is expected that this improved physically-based three-dimensional hydro-mechanical model is able to provide more reliable slope instability predictions in more complex situations.

Alteration of soil hydraulic properties and soil water repellency by fire and vegetation succession in a sagebrush steppe ecosystem

NASA Astrophysics Data System (ADS)

Chandler, D. G.; Seyfried, M. S.

2016-12-01

This study explores the impacts of fire and plant community succession on soil water repellency (SWR) and infiltration properties to improve understanding the long term impacts of prescribed fire on SWR and infiltration properties in sagebrush-steppe ecosystem. The objectives of this study were: 1) To explore the temporal effects of prescribed burning in sagebrush dominated landscape; 2) To investigate spatial variability of soil hydrologic properties; 3) To determine the relationship among soil organic fraction, soil hydrophobicity and infiltration properties. Fieldwork was conducted in paired catchments with three dominant vegetation cover communities: Low sage, big mountain sage and aspen. Detailed, heavily replicated analyses were conducted for unsaturated hydraulic conductivity, sorptivity water drop penetration time and static soil-water-air contact angle. The results show that the severity and presence of surface soil water repellency were considerably reduced six years after fire and that hydraulic conductivity increased significantly in each vegetation cover compared to pre-burn condition. Comparisons among soil hydrological properties shows that hydraulic conductivity is not strongly related to SWR, and that sorptivity is negatively correlated with SWR. The spatial variance of hydraulic properties within the burned high sage and low sage, in particularly, spatial variability of hydraulic conductivity is basically controlled by soil texture and sorptivity is affected by soil wettability. The average water repellency in Low Sage area was significantly different with Big Sage and Aspen as the gap of organic content between Low Sage and other vegetation area. The result of contact angle measurement and organic content analysis shows a strong positive correlation between SWR and organic matter.

Patterns of distribution, abundance, and change over time in a subarctic marine bird community

NASA Astrophysics Data System (ADS)

Cushing, Daniel A.; Roby, Daniel D.; Irons, David B.

2018-01-01

Over recent decades, marine ecosystems of Prince William Sound (PWS), Alaska, have experienced concurrent effects of natural and anthropogenic perturbations, including variability in the climate system of the northeastern Pacific Ocean. We documented spatial and temporal patterns of variability in the summer marine bird community in relation to habitat and climate variability using boat-based surveys of marine birds conducted during the period 1989-2012. We hypothesized that a major factor structuring marine bird communities in PWS would be proximity to the shoreline, which is theorized to relate to aspects of food web structure. We also hypothesized that shifts in physical ecosystem drivers differentially affected nearshore-benthic and pelagic components of PWS food webs. We evaluated support for our hypotheses using an approach centered on community-level patterns of spatial and temporal variability. We found that an environmental gradient related to water depth and distance from shore was the dominant factor spatially structuring the marine bird community. Responses of marine birds to this onshore-offshore environmental gradient were related to dietary specialization, and separated marine bird taxa by prey type. The primary form of temporal variability over the study period was monotonic increases or decreases in abundance for 11 of 18 evaluated genera of marine birds; 8 genera had declined, whereas 3 had increased. The greatest declines occurred in genera associated with habitats that were deeper and farther from shore. Furthermore, most of the genera that declined primarily fed on pelagic prey resources, such as forage fish and mesozooplankton, and few were directly affected by the 1989 Exxon Valdez oil spill. Our observations of synchronous declines are indicative of a shift in pelagic components of PWS food webs. This pattern was correlated with climate variability at time-scales of several years to a decade.

Patterns of distribution, abundance, and change over time in a subarctic marine bird community

USGS Publications Warehouse

Cushing, Daniel; Roby, Daniel D.; Irons, David B.

2017-01-01

Over recent decades, marine ecosystems of Prince William Sound (PWS), Alaska, have experienced concurrent effects of natural and anthropogenic perturbations, including variability in the climate system of the northeastern Pacific Ocean. We documented spatial and temporal patterns of variability in the summer marine bird community in relation to habitat and climate variability using boat-based surveys of marine birds conducted during the period 1989–2012. We hypothesized that a major factor structuring marine bird communities in PWS would be proximity to the shoreline, which is theorized to relate to aspects of food web structure. We also hypothesized that shifts in physical ecosystem drivers differentially affected nearshore-benthic and pelagic components of PWS food webs. We evaluated support for our hypotheses using an approach centered on community-level patterns of spatial and temporal variability. We found that an environmental gradient related to water depth and distance from shore was the dominant factor spatially structuring the marine bird community. Responses of marine birds to this onshore-offshore environmental gradient were related to dietary specialization, and separated marine bird taxa by prey type. The primary form of temporal variability over the study period was monotonic increases or decreases in abundance for 11 of 18 evaluated genera of marine birds; 8 genera had declined, whereas 3 had increased. The greatest declines occurred in genera associated with habitats that were deeper and farther from shore. Furthermore, most of the genera that declined primarily fed on pelagic prey resources, such as forage fish and mesozooplankton, and few were directly affected by the 1989 Exxon Valdez oil spill. Our observations of synchronous declines are indicative of a shift in pelagic components of PWS food webs. This pattern was correlated with climate variability at time-scales of several years to a decade.

Temporal and spatial variation in pharmaceutical concentrations in an urban river system.

PubMed

Burns, Emily E; Carter, Laura J; Kolpin, Dana W; Thomas-Oates, Jane; Boxall, Alistair B A

2018-06-15

Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse. Copyright © 2018 Elsevier Ltd. All rights reserved.

Worldwide estimation of river concentrations of any chemical originating from sewage-treatment plants using dilution factors.

PubMed

Keller, Virginie D J; Williams, Richard J; Lofthouse, Caryn; Johnson, Andrew C

2014-02-01

Dilution factors are a critical component in estimating concentrations of so-called "down-the-drain" chemicals (e.g., pharmaceuticals) in rivers. The present study estimated the temporal and spatial variability of dilution factors around the world using geographically referenced data sets at 0.5° × 0.5° resolution. Domestic wastewater effluents were derived from national per capita domestic water use estimates and gridded population. Monthly and annual river flows were estimated by accumulating runoff estimates using topographically derived flow directions. National statistics, including the median and interquartile range, were generated to quantify dilution factors. Spatial variability of the dilution factor was found to be considerable; for example, there are 4 orders of magnitude in annual median dilution factor between Canada and Morocco. Temporal variability within a country can also be substantial; in India, there are up to 9 orders of magnitude between median monthly dilution factors. These national statistics provide a global picture of the temporal and spatial variability of dilution factors and, hence, of the potential exposure to down-the-drain chemicals. The present methodology has potential for a wide international community (including decision makers and pharmaceutical companies) to assess relative exposure to down-the-drain chemicals released by human pollution in rivers and, thus, target areas of potentially high risk. © 2013 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

USGS Publications Warehouse

Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad

2013-01-01

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Effects of Topography-driven Micro-climatology on Evaporation

NASA Astrophysics Data System (ADS)

Adams, D. D.; Boll, J.; Wagenbrenner, N. S.

2017-12-01

The effects of spatial-temporal variation of climatic conditions on evaporation in micro-climates are not well defined. Current spatially-based remote sensing and modeling for evaporation is limited for high resolutions and complex topographies. We investigated the effect of topography-driven micro-climatology on evaporation supported by field measurements and modeling. Fourteen anemometers and thermometers were installed in intersecting transects over the complex topography of the Cook Agronomy Farm, Pullman, WA. WindNinja was used to create 2-D vector maps based on recorded observations for wind. Spatial analysis of vector maps using ArcGIS was performed for analysis of wind patterns and variation. Based on field measurements, wind speed and direction show consequential variability based on hill-slope location in this complex topography. Wind speed and wind direction varied up to threefold and more than 45 degrees, respectively for a given time interval. The use of existing wind models enables prediction of wind variability over the landscape and subsequently topography-driven evaporation patterns relative to wind. The magnitude of the spatial-temporal variability of wind therefore resulted in variable evaporation rates over the landscape. These variations may contribute to uneven crop development patterns observed during the late growth stages of the agricultural crops at the study location. Use of hill-slope location indexes and appropriate methods for estimating actual evaporation support development of methodologies to better define topography-driven heterogeneity in evaporation. The cumulative effects of spatially-variable climatic factors on evaporation are important to quantify the localized water balance and inform precision farming practices.

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

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

Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area.

PubMed

Meziti, Alexandra; Kormas, Konstantinos A; Moustaka-Gouni, Maria; Karayanni, Hera

2015-07-01

Studies focusing on the temporal and spatial dynamics of bacterioplankton communities within littoral areas undergoing direct influences from the coast are quite limited. In addition, they are more complicated to resolve compared to communities in the open ocean. In order to elucidate the effects of spatial vs. temporal variability on bacterial communities in a highly land-influenced semi-enclosed gulf, surface bacterioplankton communities from five coastal sites in Igoumenitsa Gulf (Ionian Sea, Greece) were analyzed over a nine-month period using 16S rDNA 454-pyrosequencing. Temporal differences were more pronounced than spatial ones, with lower diversity indices observed during the summer months. During winter and early spring, bacterial communities were dominated by SAR11 representatives, while this pattern changed in May when they were abruptly replaced by members of Flavobacteriales, Pseudomonadales, and Alteromonadales. Additionally, correlation analysis showed high negative correlations between the presence of SAR11 OTUs in relation to temperature and sunlight that might have driven, directly or indirectly, the disappearance of these OTUs in the summer months. The dominance of SAR11 during the winter months further supported the global distribution of the clade, not only in the open-sea, but also in coastal systems. This study revealed that specific bacteria exhibited distinct succession patterns in an anthropogenic-impacted coastal system. The major bacterioplankton component was represented by commonly found marine bacteria exhibiting seasonal dynamics, while freshwater and terrestrial-related phylotypes were absent. Copyright © 2015 Elsevier GmbH. All rights reserved.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Recent results on modelling the spatial and temporal structure of the Earth's gravity field.

PubMed

Moore, P; Zhang, Q; Alothman, A

2006-04-15

The Earth's gravity field plays a central role in sea-level change. In the simplest application a precise gravity field will enable oceanographers to capitalize fully on the altimetric datasets collected over the past decade or more by providing a geoid from which absolute sea-level topography can be recovered. However, the concept of a static gravity field is now redundant as we can observe temporal variability in the geoid due to mass redistribution in or on the total Earth system. Temporal variability, associated with interactions between the land, oceans and atmosphere, can be investigated through mass redistributions with, for example, flow of water from the land being balanced by an increase in ocean mass. Furthermore, as ocean transport is an important contributor to the mass redistribution the time varying gravity field can also be used to validate Global Ocean Circulation models. This paper will review the recent history of static and temporal gravity field recovery, from the 1980s to the present day. In particular, mention will be made of the role of satellite laser ranging and other space tracking techniques, satellite altimetry and in situ gravity which formed the basis of gravity field determination until the last few years. With the launch of Challenging Microsatellite Payload and Gravity and Circulation Experiment (GRACE) our knowledge of the spatial distribution of the Earth's gravity field is taking a leap forward. Furthermore, GRACE is now providing insight into temporal variability through 'monthly' gravity field solutions. Prior to this data we relied on satellite tracking, Global Positioning System and geophysical models to give us insight into the temporal variability. We will consider results from these methodologies and compare them to preliminary results from the GRACE mission.

Spatial and Temporal Coherence of SeaWiFS Chlorophyll Concentration Anomalies in the North Atlantic Bloom (1998-2005) Examined with Giovanni

NASA Technical Reports Server (NTRS)

Acker, James G.

2006-01-01

The availability of climatological chlorophyll-a concentration data products from the SeaWiFS mission spanning the eight-year mission period allowed the creation of a climatological anomaly analysis function in Giovanni, the GES DISC Interactive Online Visualization and ANalysis Infrastructure. This study utilizes the Giovanni anomaly analysis function to examine mesoscale anomalies in the North Atlantic Ocean during the springtime North Atlantic Bloom. This examination indicates that areas exhibiting positive anomalies and areas exhibiting negative anomalies are coherent over significant spatial scales, with relatively abrupt boundaries between areas with positive and negative anomalies. Year-to-year variability in anomaly "intensity" can be caused by either variability in the temporal occurrence of the bloom peak or by variability in the peak chlorophyll concentration in a particular area. The study will also discuss the feasibility of combining chlorophyll anomaly analysis with other data types.

Optimizing spatial and temporal constraints for cropland canopy water content retrieval through coupled radiative transfer model inversion

NASA Astrophysics Data System (ADS)

Boren, E. J.; Boschetti, L.; Johnson, D.

2017-12-01

Water plays a critical role in all plant physiological processes, including transpiration, photosynthesis, nutrient transportation, and maintenance of proper plant cell functions. Deficits in water content cause drought-induced stress conditions, such as constrained plant growth and cellular metabolism, while overabundance of water cause anoxic conditions which limit plant physiological processes and promote disease. Vegetation water content maps can provide agricultural producers key knowledge for improving production capacity and resiliency in agricultural systems while facilitating the ability to pinpoint, monitor, and resolve water scarcity issues. Radiative transfer model (RTM) inversion has been successfully applied to remotely sensed data to retrieve biophysical and canopy parameter estimates, including water content. The successful launch of the Landsat 8 Operational Land Imager (OLI) in 2012, Sentinel 2A Multispectral Instrument (MSI) in 2015, followed by Sentinel 2B in 2017, the systematic acquisition schedule and free data distribution policy provide the opportunity for water content estimation at a spatial and temporal scale that can meet the demands of potential operational users: combined, these polar-orbiting systems provide 10 m to 30 m multi-spectral global coverage up to every 3 days. The goal of the present research is to prototype the generation of a cropland canopy water content product, obtained from the newly developed Landsat 8 and Sentinel 2 atmospherically corrected HLS product, through the inversion of the leaf and canopy model PROSAIL5B. We assess the impact of a novel spatial and temporal stratification, where some parameters of the model are constrained by crop type and phenological phase, based on ancillary biophysical data, collected from various crop species grown in a controlled setting and under different water stress conditions. Canopy-level data, collected coincidently with satellite overpasses during four summer field campaigns in northern Idaho (2014 to 2017), are used to validate the results of the model inversion.

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing a Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessment of near-source air pollution at a fine spatial scale utilizing a mobile measurement platform approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle, an all-electric vehicle measuring real-time concentrations of particulate and gaseous poll...

Calculations Supporting Management Zones

USDA-ARS?s Scientific Manuscript database

Since the early 1990’s the tools of precision farming (GPS, yield monitors, soil sensors, etc.) have documented how spatial and temporal variability are important factors impacting crop yield response. For precision farming, variability can be measured then used to divide up a field so that manageme...

A soil sampling reference site: the challenge in defining reference material for sampling.

PubMed

de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Jacimovic, Radojko; Jeran, Zvonka; Sansone, Umberto; van der Perk, Marcel

2008-11-01

In the frame of the international SOILSAMP project, funded and coordinated by the Italian Environmental Protection Agency, an agricultural area was established as a reference site suitable for performing soil sampling inter-comparison exercises. The reference site was characterized for trace element content in soil, in terms of the spatial and temporal variability of their mass fraction. Considering that the behaviour of long-lived radionuclides in soil can be expected to be similar to that of some stable trace elements and that the distribution of these trace elements in soil can simulate the distribution of radionuclides, the reference site characterised in term of trace elements, can be also used to compare the soil sampling strategies developed for radionuclide investigations.

Spatio-temporal variation in stream water chemistry in a tropical urban watershed

Treesearch

A. Ramirez; K.G. Rosas; A.E. Lugo; O.M. Ramos-Gonzalez

2014-01-01

Urban activities and related infrastructure alter the natural patterns of stream physical and chemical conditions. According to the Urban Stream Syndrome, streams draining urban landscapes are characterized by high concentrations of nutrients and ions, and might have elevated water temperatures and variable oxygen concentrations. Here, we report temporal and spatial...

Temporal variation in photosynthetically active radiation (par) in mesic southern Appalachian hardwood forests with and without Rhododendron understories

Treesearch

Barton D. Clinton

1995-01-01

Understanding spatial and temporal variation in the understory light regime of southern Appalachian forests is central to understanding regeneration patterns of overstory species. One of the important contributors to this variability is the distribution of evergreen shrub species, primarily Rhododendron maximum L. We measured photosynthetically...

Temporal Variation in Photosynthetically Active Radiation (PAR) in Mesic Southern Appalachian Hardwood Forest with and without Rhododendron Understories

Treesearch

Barton D. Clinton

1995-01-01

Understanding spatial and temporal variation in, the understory light regime of southern Appalachian forests is central to understanding regeneration patterns of overstory species. One of the important contributors to this variability is the distribution of evergreen shrub species, primarily Rhododendrun maximun L, We measured...

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

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

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more importantmore » than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.« less

Spatial and Temporal Evolution of Earthquake Dynamics: Case Study of the Mw 8.3 Illapel Earthquake, Chile

NASA Astrophysics Data System (ADS)

Yin, Jiuxun; Denolle, Marine A.; Yao, Huajian

2018-01-01

We develop a methodology that combines compressive sensing backprojection (CS-BP) and source spectral analysis of teleseismic P waves to provide metrics relevant to earthquake dynamics of large events. We improve the CS-BP method by an autoadaptive source grid refinement as well as a reference source adjustment technique to gain better spatial and temporal resolution of the locations of the radiated bursts. We also use a two-step source spectral analysis based on (i) simple theoretical Green's functions that include depth phases and water reverberations and on (ii) empirical P wave Green's functions. Furthermore, we propose a source spectrogram methodology that provides the temporal evolution of dynamic parameters such as radiated energy and falloff rates. Bridging backprojection and spectrogram analysis provides a spatial and temporal evolution of these dynamic source parameters. We apply our technique to the recent 2015 Mw 8.3 megathrust Illapel earthquake (Chile). The results from both techniques are consistent and reveal a depth-varying seismic radiation that is also found in other megathrust earthquakes. The low-frequency content of the seismic radiation is located in the shallow part of the megathrust, propagating unilaterally from the hypocenter toward the trench while most of the high-frequency content comes from the downdip part of the fault. Interpretation of multiple rupture stages in the radiation is also supported by the temporal variations of radiated energy and falloff rates. Finally, we discuss the possible mechanisms, either from prestress, fault geometry, and/or frictional properties to explain our observables. Our methodology is an attempt to bridge kinematic observations with earthquake dynamics.

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

DOE PAGES

Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; ...

2017-11-22

Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less

Spatial and temporal variability of groundwater recharge in Geba basin, Northern Ethiopia

NASA Astrophysics Data System (ADS)

Yenehun, Alemu; Walraevens, Kristine; Batelaan, Okke

2017-10-01

WetSpa, a physically based, spatially distributed watershed model, has been used to study the spatial and temporal variation of recharge in the Geba basin, Northern Ethiopia. The model covers an area of about 4, 249 km2 and integrates elevation, soil and land-use data, hydrometeorological and river discharge data. The Geba basin has a highly variable topography ranging from 1000 to 3280 m with an average slope of 12.9%. The area is characterized by a distinct wet and long dry season with a mean annual precipitation of 681 mm and temperatures ranging between 6.5 °C and 32 °C. The model was simulated on daily basis for nearly four years (January 1, 2000 to December 18, 2003). It resulted in a good agreement between measured and simulated streamflow hydrographs with Nash-Sutcliffe efficiency of almost 70% and 85% for, respectively, the calibration and validation. The water balance terms show very strong spatial and temporal variability, about 3.8% of the total precipitation is intercepted by the plant canopy; 87.5% infiltrates into the soil (of which 13% percolates, 2.7% flows laterally off and 84.2% evapotranspired from the root zone), and 7.2% is surface runoff. The mean annual recharge varies from about 45 mm (2003) to 208 mm (2001), with average of 98.6 mm/yr. On monthly basis, August has the maximum (73 mm) and December the lowest (0.1 mm) recharge. The mean annual groundwater recharge spatially varies from 0 to 371 mm; mainly controlled by the distribution of rainfall amount, followed by soil and land-use, and to a certain extent, slope. About 21% of Geba has a recharge larger than 120 mm and 1% less than 5 mm.

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

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

Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.

Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less

Analysis of the global ISCCP TOVS water vapor climatology

NASA Technical Reports Server (NTRS)

Wittmeyer, Ian L.; Vonder Haar, Thomas H.

1994-01-01

A climatological examination of the global water vapor field based on a multiyear period of successfull satellite-based observations is presented. Results from the multiyear global ISCCP TIROS Operational Vertical Sounder (TOVS) water vapor dataset as operationally produced by NESDIS and ISCCP are shown. The methods employed for the retrieval of precipitable water content (PWC) utilize infrared measurements collected by the TOVS instrument package flown aboard the NOAA series of operational polar-orbiting satellites. Strengths of this dataset include the nearly global daily coverage, availability for a multiyear period, operational internal quality checks, and its description of important features in the mean state of the atmosphere. Weaknesses of this PWC dataset include that the infrared sensors are unable to collect data in cloudy regions, the retrievals are strongly biased toward a land-based radiosonde first-guess dataset, and the description of high spatial and temporal variability is inadequate. Primary consequences of these factors are seen in the underestimation of ITCZ water vapor maxima, and underestimation of midlatitude water vapor mean and standard deviation values where transient atmospheric phenomena contribute significantly toward time means. A comparison of TOVS analyses to SSM/I data over ocean for the month of July 1988 shows fair agreement in the magnitude and distribution of the monthly mean values, but the TOVS fields exhibit much less temporal and spatial variability on a daily basis in comparison to the SSM/I analyses. The emphasis of this paper is on the presentation and documentation of an early satellite-based water vapor climatology, and description of factors that prevent a more accurate representation of the global water vapor field.

The vertical structure of upper ocean variability at the Porcupine Abyssal Plain during 2012–2013

PubMed Central

Heywood, Karen J.; Thompson, Andrew F.; Binetti, Umberto; Kaiser, Jan

2016-01-01

Abstract This study presents the characterization of variability in temperature, salinity and oxygen concentration, including the vertical structure of the variability, in the upper 1000 m of the ocean over a full year in the northeast Atlantic. Continuously profiling ocean gliders with vertical resolution between 0.5 and 1 m provide more information on temporal variability throughout the water column than time series from moorings with sensors at a limited number of fixed depths. The heat, salt and dissolved oxygen content are quantified at each depth. While the near surface heat content is consistent with the net surface heat flux, heat content of the deeper layers is driven by gyre‐scale water mass changes. Below ∼150m, heat and salt content display intraseasonal variability which has not been resolved by previous studies. A mode‐1 baroclinic internal tide is detected as a peak in the power spectra of water mass properties. The depth of minimum variability is at ∼415m for both temperature and salinity, but this is a depth of high variability for oxygen concentration. The deep variability is dominated by the intermittent appearance of Mediterranean Water, which shows evidence of filamentation. Susceptibility to salt fingering occurs throughout much of the water column for much of the year. Between about 700–900 m, the water column is susceptible to diffusive layering, particularly when Mediterranean Water is present. This unique ability to resolve both high vertical and temporal variability highlights the importance of intraseasonal variability in upper ocean heat and salt content, variations that may be aliased by traditional observing techniques. PMID:27840785

Geo(spatial) Health Investigation of Rotavirus in an Endemic Region: Hydroclimatic Influences and Epidemiology of Rotavirus in Bangladesh

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Akanda, A. S.; Jutla, A.; Colwell, R. R.

2016-12-01

Rotavirus is the leading cause of severe dehydrating diarrhea among children under 5. Over 80% of the approximate half a million child deaths every year occur in South Asia and sub-Saharan Africa alone. Although less explored than cholera as a climate driven and influenced global health problem, recent studies have showed that the disease shown strong seasonality and spatio-temporal variability depending on regional hydroclimatic and local environmental conditions. Understanding the epidemiology of this disease, especially the spatio-temporal incidence patterns with respect to environmental factors is vitally important to allow for identification of "hotspots", preventative preparations, and vaccination strategies to improve wellbeing of the vulnerable populations. With climate change, spatio-temporal signatures and footprints of the disease are changing along with increasing burden. However, a robust understanding of the relationships between rotavirus epidemiology and hydroclimatic drivers is yet to be developed. In this study, we evaluate the seasonality and epidemiologic characteristics of rotavirous infection and its spatio-temporal incidence patterns with respect to regional hydroclimatic variables and their extremes in an endemic region in South Asia. Hospital-based surveillance data from different geographic locations allowed us to explore the detailed spatial and temporal characteristics of rotavirus propagation under the influence of climate variables in both coastal and inland areas. The rotavirus transmission patterns show two peaks in a year in the capital city of Dhaka, where winter season (highest in January) shows a high peak and the July-August monsoon season shows a smaller peak. Correlation with climate variables revealed that minimum temperature has strong influence on the winter season outbreak, while rainfall extremes show a strong positive association with the secondary monsoon peak. Spatial analysis also revealed that humidity and soil wetness may influence the timing as drier areas experience earlier outbreaks than wetter areas. Accurate understanding of rotavirus propagation with respect to hydroclimatic and environmental variability can be utilized to establish global surveillance and forecast imminent risk of diarrheal outbreaks in vulnerable regions.

Historical Arctic Logbooks Provide Insights into Past Diets and Climatic Responses of Cod

PubMed Central

Townhill, Bryony L.; Maxwell, David; Engelhard, Georg H.; Simpson, Stephen D.; Pinnegar, John K.

2015-01-01

Gadus morhua (Atlantic cod) stocks in the Barents Sea are currently at levels not seen since the 1950s. Causes for the population increase last century, and understanding of whether such large numbers will be maintained in the future, are unclear. To explore this, we digitised and interrogated historical cod catch and diet datasets from the Barents Sea. Seventeen years of catch data and 12 years of prey data spanning 1930–1959 cover unexplored spatial and temporal ranges, and importantly capture the end of a previous warm period, when temperatures were similar to those currently being experienced. This study aimed to evaluate cod catch per unit effort and prey frequency in relation to spatial, temporal and environmental variables. There was substantial spatio-temporal heterogeneity in catches through the time series. The highest catches were generally in the 1930s and 1940s, although at some localities more cod were recorded late in the 1950s. Generalized Additive Models showed that environmental, spatial and temporal variables are all valuable descriptors of cod catches, with the highest occurring from 15–45°E longitude and 73–77°N latitude, at bottom temperatures between 2 and 4°C and at depths between 150 and 250 m. Cod diets were highly variable during the study period, with frequent changes in the relative frequencies of different prey species, particularly Mallotus villosus (capelin). Environmental variables were particularly good at describing the importance of capelin and Clupea harengus (herring) in the diet. These new analyses support existing knowledge about how the ecology of the region is controlled by climatic variability. When viewed in combination with more recent data, these historical relationships will be valuable in forecasting the future of Barents Sea fisheries, and in understanding how environments and ecosystems may respond. PMID:26331271

Foraging characteristics of larval bluegill sunfish and larval longear sunfish in the Kanawha River, West Virginia

USGS Publications Warehouse

Rider, S.J.; Margraf, F.J.

1998-01-01

We determined spatial and temporal foraging characteristics of larval bluegill sunfish (Lepomis macrochirus) and longear sunfish (Lepomis megalotis) in the upper Kanawha River, West Virginia during the summer of 1989. Stomach contents were examined among habitat types (i.e., main channel, main-channel border, and shoreline habitats) and depth (surface, middle, and bottom). Diet of larval bluegill sunfish was dominated by Chironomidae, temporally and spatially. Chironomidae dominated larval longear sunfish diet in main channel and main-channel border collections from all three depths. However, along the shoreline, larval longear sunfish diet was dominated by Cladocera.

Understanding thermal circulations and near-surface turbulence processes in a small mountain valley

NASA Astrophysics Data System (ADS)

Pardyjak, E.; Dupuy, F.; Durand, P.; Gunawardena, N.; Thierry, H.; Roubin, P.

2017-12-01

The interaction of turbulence and thermal circulations in complex terrain can be significantly different from idealized flat terrain. In particular, near-surface horizontal spatial and temporal variability of winds and thermodynamic variables can be significant event over very small spatial scales. The KASCADE (KAtabatic winds and Stability over CAdarache for Dispersion of Effluents) 2017 conducted from January through March 2017 was designed to address these issues and to ultimately improve prediction of dispersion in complex terrain, particularly during stable atmospheric conditions. We have used a relatively large number of sensors to improve our understanding of the spatial and temporal development, evolution and breakdown of topographically driven flows. KASCADE 2017 consisted of continuous observations and fourteen Intensive Observation Periods (IOPs) conducted in the Cadarache Valley located in southeastern France. The Cadarache Valley is a relatively small valley (5 km x 1 km) with modest slopes and relatively small elevation differences between the valley floor and nearby hilltops ( 100 m). During winter, winds in the valley are light and stably stratified at night leading to thermal circulations as well as complex near-surface atmospheric layering. In this presentation we present results quantifying spatial variability of thermodynamic and turbulence variables as a function of different large -scale forcing conditions (e.g., quiescent conditions, strong westerly flow, and Mistral flow). In addition, we attempt to characterize highly-regular nocturnal horizontal wind meandering and associated turbulence statistics.

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

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

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

Changes in precipitation isotope-climate relationships from temporal grouping and aggregation of weekly-resolved USNIP data: impacts on paleoclimate and environmental applications

NASA Astrophysics Data System (ADS)

Akers, P. D.; Welker, J. M.

2015-12-01

Spatial variations in precipitation isotopes have been the focus of much recent research, but relatively less work has explored changes at various temporal scales. This is partly because most spatially-diverse and long-term isotope databases are offered at a monthly resolution, while daily or event-level records are spatially and temporally limited by cost and logistics. A subset of 25 United States Network for Isotopes in Precipitation (USNIP) sites with weekly-resolution in the east-central United States was analyzed for site-specific relationships between δ18O and δD (the local meteoric water line/LMWL), δ18O and surface temperature, and δ18O and precipitation amount. Weekly data were then aggregated into monthly and seasonal data to examine the effect of aggregation on correlation and slope values for each of the relationships. Generally, increasing aggregation improved correlations (>25% for some sites) due to a reduced effect of extreme values, but estimates on regression variable error increased (>100%) because of reduced sample sizes. Aggregation resulted in small, but significant drops (5-25%) in relationship slope values for some sites. Weekly data were also grouped by month and season to explore changes in relationships throughout the year. Significant subannual variability exists in slope values and correlations even for sites with very strong overall correlations. LMWL slopes are highest in winter and lowest in summer, while the δ18O-surface temperature relationship is strongest in spring. Despite these overall trends, a high level of month-to-month and season-to-season variability is the norm for these sites. Researchers blindly applying overall relationships drawn from monthly-resolved databases to paleoclimate or environmental research risk assuming these relationships apply at all temporal resolutions. When possible, researchers should match the temporal resolution used to calculate an isotopic relationship with the temporal resolution of their applied proxy.

Crust recycling induced compositional-temporal-spatial variations of Cenozoic basalts in the Trans-North China Orogen

NASA Astrophysics Data System (ADS)

Xu, Rong; Liu, Yongsheng; Wang, Xiaohong; Zong, Keqing; Hu, Zhaochu; Chen, Haihong; Zhou, Lian

2017-03-01

It has been advocated that the stagnant Pacific slab within the mantle transition zone played a critical role in the genesis of the Cenozoic basalts in the eastern part of the North China Craton (NCC); however, it is not clear whether this recycled oceanic crust contributed to the chemical makeup of the Cenozoic basalts in the Trans-North China Orogen (TNCO, the central zone of the NCC). Here, we show that Cenozoic basalts from the TNCO are featured by low CaO contents, high TiO2 and FeOT contents and high Fe/Mn and Zn/Fe ratios, indicating a mantle source of pyroxenite. Temporally, these basalts evolved from alkali basalts of Late Eocene-Oligocene age to coexisting alkali and tholeiitic basalts of Late Miocene-Quaternary age. Spatially, their isotopic and chemical compositions vary symmetrically from the center to both the north and the south sides along the TNCO, i.e., SiO2 contents and 87Sr/86Sr ratios increase, FeOT contents and 143Nd/144Nd, Sm/Yb and Ce/Pb ratios decrease. The estimated average melting pressure of the TNCO tholeiitic basalts ( 3 GPa) agrees well with the present lithosphere thickness beneath the north region of the TNCO ( 90-120 km). The temporal and spatial chemical variations of Cenozoic basalts in the TNCO suggest that the recycled oceanic crust in the mantle of the TNCO is mainly related to the southward subduction of the Paleo-Asian oceanic plate and the northward subduction of the Tethyan ocean plate. The westward subduction of Pacific slab may not have contributed much than previously thought.

Identifying change in spatial accumulation of soil salinity in an inland river watershed, China.

PubMed

Wang, Yugang; Deng, Caiyun; Liu, Yan; Niu, Ziru; Li, Yan

2018-04-15

Soil salinity accumulation is strong in arid areas and it has become a serious environmental problem. Knowledge of the process and spatial changes of accumulated salinity in soil can provide an insight into the spatial patterns of soil salinity accumulation. This is especially useful for estimating the spatial transport of soil salinity at the watershed scale. This study aimed to identify spatial patterns of salt accumulation in the top 20cm soils in a typical inland watershed, the Sangong River watershed in arid northwest China, using geostatistics, spatial analysis technology and the Lorenz curve. The results showed that: (1) soil salt content had great spatial variability (coefficient variation >1.0) in both in 1982 and 2015, and about 56% of the studied area experienced transition the degree of soil salt content from one class to another during 1982-2015. (2) Lorenz curves describing the proportions of soil salinity accumulation (SSA) identified that the boundary between soil salinity migration and accumulation regions was 24.3m lower in 2015 than in 1982, suggesting a spatio-temporal inequality in loading of the soil salinity transport region, indicating significant migration of soil salinity from the upstream to the downstream watershed. (3) Regardless of migration or accumulation region, the mean value of SSA per unit area was 0.17kg/m 2 higher in 2015 than 1982 (p<0.01) and the increasing SSA per unit area in irrigated land significantly increased by 0.19kg/m 2 compared with the migration region. Dramatic accumulation of soil salinity in all land use types was clearly increased by 0.29kg/m 2 in this agricultural watershed during the studied period in the arid northwest of China. This study demonstrates the spatial patterns of soil salinity accumulation, which is particularly useful for estimating the spatial transport of soil salinity at the watershed scale. Copyright © 2017 Elsevier B.V. All rights reserved.

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...

Monitoring Dissolved Oxygen in New Jersey Coastal Waters Using Autonomous Gliders

EPA Science Inventory

The coastal ocean is a highly variable system with processes that have significant implications on the hydrographic and oxygen characteristics of the water column. The spatial and temporal variability of these fields can cause dramatic changes to water quality and in turn the h...

The influence of lithology on surface water sources

EPA Science Inventory

Understanding the temporal and spatial variability of surface water sources within a basin is vital to our ability to manage the impacts of climate variability and land cover change. Water stable isotopes can be used as a tool to determine geographic and seasonal sources of water...

Dose reduction in fluoroscopic interventions using a combination of a region of interest (ROI) x-ray attenuator and spatially different, temporally variable temporal filtering

NASA Astrophysics Data System (ADS)

Swetadri Vasan, S. N.; Pope, Liza; Ionita, Ciprian N.; Titus, A. H.; Bednarek, D. R.; Rudin, S.

2013-03-01

A novel dose reduction technique for fluoroscopic interventions involving a combination of a material x-ray region of interest (ROI) attenuator and spatially different, temporally variable ROI temporal recursive filter, was used to guide the catheter to the ROI in three live animal studies, two involving rabbits and one involving a sheep. In the two rabbit studies presented , a catheter was guided to the entrance of the carotid artery. With the added ROI attenuator the image under the high attenuation region is very noisy. By using temporal filtering with a filter weight of 0.6 on previous frames, the noise is reduced. In the sheep study the catheter was guided to the descending aorta of the animal. The sheep offered a relatively higher attenuation to the incident x-rays and thus a higher temporal filter weight of 0.8 on previous frames was used during the procedure to reduce the noise to levels acceptable by the interventionalist. The image sequences from both studies show that significant dose reduction of 5-6 times can be achieved with acceptable image quality outside the ROI by using the above mentioned technique. Even though the temporal filter weighting outside the ROI is higher, the consequent lag does not prevent perception of catheter movement.

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.

Satellite Analysis of Ocean Biogeochemistry and Mesoscale Variability in the Sargasso Sea

NASA Technical Reports Server (NTRS)

Siegel, D. A.; Micheals, A. F.; Nelson, N. B.

1997-01-01

The objective of this study was to analyze the impact of spatial variability on the time-series of biogeochemical measurements made at the U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) site. Originally the study was planned to use SeaWiFS as well as AVHRR high-resolution data. Despite the SeaWiFS delays we were able to make progress on the following fronts: (1) Operational acquisition, processing, and archive of HRPT data from a ground station located in Bermuda; (2) Validation of AVHRR SST data using BATS time-series and spatial validation cruise CTD data; (3) Use of AVHRR sea surface temperature imagery and ancillary data to assess the impact of mesoscale spatial variability on P(CO2) and carbon flux in the Sargasso Sea; (4) Spatial and temporal extent of tropical cyclone induced surface modifications; and (5) Assessment of eddy variability using TOPEX/Poseidon data.

Documentation of programs that compute 1) static tilts for a spatially variable slip distribution, and 2) quasi-static tilts produced by an expanding dislocation loop with a spatially variable slip distribution

USGS Publications Warehouse

McHugh, Stuart

1976-01-01

The material in this report is concerned with the effects of a vertically oriented rectangular dislocation loop on the tilts observed at the free surface of an elastic half-space. Part I examines the effect of a spatially variable static strike-slip distribution across the slip surface. The tilt components as a function of distance parallel, or perpendicular, to the strike of the slip surface are displayed for different slip-versus-distance profiles. Part II examines the effect of spatially and temporally variable slip distributions across the dislocation loop on the quasi-static tilts at the free surface of an elastic half space. The model discussed in part II may be used to generate theoretical tilt versus time curves produced by creep events.

Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, T.; Ahmed, M.

2015-12-01

Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.

Small-scale temporal and spatial variability in the abundance of plastic pellets on sandy beaches: Methodological considerations for estimating the input of microplastics.

PubMed

Moreira, Fabiana Tavares; Prantoni, Alessandro Lívio; Martini, Bruno; de Abreu, Michelle Alves; Stoiev, Sérgio Biato; Turra, Alexander

2016-01-15

Microplastics such as pellets have been reported for many years on sandy beaches around the globe. Nevertheless, high variability is observed in their estimates and distribution patterns across the beach environment are still to be unravelled. Here, we investigate the small-scale temporal and spatial variability in the abundance of pellets in the intertidal zone of a sandy beach and evaluate factors that can increase the variability in data sets. The abundance of pellets was estimated during twelve consecutive tidal cycles, identifying the position of the high tide between cycles and sampling drift-lines across the intertidal zone. We demonstrate that beach dynamic processes such as the overlap of strandlines and artefacts of the methods can increase the small-scale variability. The results obtained are discussed in terms of the methodological considerations needed to understand the distribution of pellets in the beach environment, with special implications for studies focused on patterns of input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sulfur dioxide in the Venus Atmosphere: II. Spatial and temporal variability

NASA Astrophysics Data System (ADS)

Vandaele, A. C.; Korablev, O.; Belyaev, D.; Chamberlain, S.; Evdokimova, D.; Encrenaz, Th.; Esposito, L.; Jessup, K. L.; Lefèvre, F.; Limaye, S.; Mahieux, A.; Marcq, E.; Mills, F. P.; Montmessin, F.; Parkinson, C. D.; Robert, S.; Roman, T.; Sandor, B.; Stolzenbach, A.; Wilson, C.; Wilquet, V.

2017-10-01

The vertical distribution of sulfur species in the Venus atmosphere has been investigated and discussed in Part I of this series of papers dealing with the variability of SO2 on Venus. In this second part, we focus our attention on the spatial (horizontal) and temporal variability exhibited by SO2. Appropriate data sets - SPICAV/UV nadir observations from Venus Express, ground-based ALMA and TEXES, as well as UV observation on the Hubble Space Telescope - have been considered for this analysis. High variability both on short-term and short-scale are observed. The long-term trend observed by these instruments shows a succession of rapid increases followed by slow decreases in the SO2 abundance at the cloud top level, implying that the transport of air from lower altitudes plays an important role. The origins of the larger amplitude short-scale, short-term variability observed at the cloud tops are not yet known but are likely also connected to variations in vertical transport of SO2 and possibly to variations in the abundance and production and loss of H2O, H2SO4, and Sx.

Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2

NASA Technical Reports Server (NTRS)

Li, Zhen; Adamec, David; Takahashi, Taro; Sutherland, Stewart C.

2004-01-01

A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.

Spatial and temporal patterns of endocrine active chemicals in small streams indicate differential exposure to aquatic organisms

USGS Publications Warehouse

Lee, K.E.; Barber, L.B.; Schoenfuss, H.L.

2014-01-01

Alkylphenolic chemicals (APCs) and hormones were measured six times from February through October 2007 in three Minnesota streams receiving wastewater to identify spatial and temporal patterns in concentrations and in estrogen equivalency. Fish were collected once during the study to evaluate endpoints indicative of endocrine disruption. The most commonly detected APCs were 4-tert-octylphenol and 4-nonylphenol and the most commonly detected hormones were estrone and androstenedione. Chemical concentrations were greatest for nonylphenol ethoxycarboxylates (NPECs) (5,000-140,000 ng/l), followed by 4-nonlylphenol and 4-nonylphenolethoxylates (50-880 ng/l), 4-tert-octylphenol and 4-tert-octylphenolethoxylates with concentrations as great as 130 ng/l, and hormones (0.1-54 ng/l). Patterns in chemicals and estrogen equivalency indicated that wastewater effluent is a pathway of APCs and hormones to downstream locations in this study. However, upstream contributions can be equally or more important indicating alternative sources. This study indicates that aquatic organisms experience both spatially and temporally variable exposures in the number of compounds, total concentrations, and estrogenicity. This variability was evident in fish collected from the three rivers as no clear upstream to downstream pattern of endocrine disruption endpoints emerged.

Use of a handheld low-cost sensor to explore the effect of urban design features on local-scale spatial and temporal air quality variability.

PubMed

Miskell, Georgia; Salmond, Jennifer A; Williams, David E

2018-04-01

Portable low-cost instruments have been validated and used to measure ambient nitrogen dioxide (NO 2 ) at multiple sites over a small urban area with 20min time resolution. We use these results combined with land use regression (LUR) and rank correlation methods to explore the effects of traffic, urban design features, and local meteorology and atmosphere chemistry on small-scale spatio-temporal variations. We measured NO 2 at 45 sites around the downtown area of Vancouver, BC, in spring 2016, and constructed four different models: i) a model based on averaging concentrations observed at each site over the whole measurement period, and separate temporal models for ii) morning, iii) midday, and iv) afternoon. Redesign of the temporal models using the average model predictors as constants gave three 'hybrid' models that used both spatial and temporal variables. These accounted for approximately 50% of the total variation with mean absolute error±5ppb. Ranking sites by concentration and by change in concentration across the day showed a shift of high NO 2 concentrations across the central city from morning to afternoon. Locations could be identified in which NO 2 concentration was determined by the geography of the site, and others as ones in which the concentration changed markedly from morning to afternoon indicating the importance of temporal controls. Rank correlation results complemented LUR in identifying significant urban design variables that impacted NO 2 concentration. High variability across a relatively small space was partially described by predictor variables related to traffic (bus stop density, speed limits, traffic counts, distance to traffic lights), atmospheric chemistry (ozone, dew point), and environment (land use, trees). A high-density network recording continuously would be needed fully to capture local variations. Copyright © 2017 Elsevier B.V. All rights reserved.

[Spatial heterogeneity of soil salinization and its influencing factors in the typical region of the Mu Us Desert-Loess Plateau transitional zone, Northwest China].

PubMed

Zhao, Xuan; Hao, Qi Li; Sun, Ying Ying

2017-06-18

Studies on the spatial heterogeneity of saline soil in the Mu Us Desert-Loess Plateau transition zone are meaningful for understanding the mechanisms of land desertification. Taking the Mu Us Desert-Loess Plateau transition zone as the study subject, its spatial heterogeneity of pH, electrical conductivity (EC) and total salt content were analyzed by using on-site sampling followed with indoor analysis, classical statistical and geostatistical analysis. The results indicated that: 1) The average values of pH, EC and total salt content were 8.44, 5.13 mS·cm -1 and 21.66 g·kg -1 , respectively, and the coefficient of variation ranged from 6.9% to 73.3%. The pH was weakly variable, while EC and total salt content were moderately variable. 2) Results of semivariogram analysis showed that the most fitting model for spatial variability of all three indexes was spherical model. The C 0 /(C 0 +C) ratios of three indexes ranged from 8.6% to 14.3%, which suggested the spatial variability of all indexes had a strong spatial autocorrelation, and the structural factors played a more important role. The variation range decreased in order of pH

On the temporal and spatial characteristics of tornado days in the United States

NASA Astrophysics Data System (ADS)

Moore, Todd W.

2017-02-01

More tornadoes are produced per year in the United States than in any other country, and these tornadoes have produced tremendous losses of life and property. Understanding how tornado activity will respond to climate change is important if we wish to prepare for future changes. Trends in various tornado and tornado day characteristics, including their annual frequencies, their temporal variability, and their spatial distributions, have been reported in the past few years. This study contributes to this body of literature by further analyzing the temporal and spatial characteristics of tornado days in the United States. The analyses performed in this study support previously reported findings in addition to providing new perspectives, including that the temporal trends are observed only in low-frequency and high-frequency tornado days and that the eastward shift in tornado activity is produced, in part, by the increasing number of high-frequency tornado days, which tend to occur to the east of the traditionally depicted tornado alley in the Great Plains.

Spatio-temporal statistical models for river monitoring networks.

PubMed

Clement, L; Thas, O; Vanrolleghem, P A; Ottoy, J P

2006-01-01

When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.

Temporal and spatial patterns of ambient endotoxin concentrations in Fresno, California.

PubMed

Tager, Ira B; Lurmann, Frederick W; Haight, Thaddeus; Alcorn, Siana; Penfold, Bryan; Hammond, S Katharine

2010-10-01

Endotoxins are found in indoor dust generated by human activity and pets, in soil, and adsorbed onto the surfaces of ambient combustion particles. Endotoxin concentrations have been associated with respiratory symptoms and the risk of atopy and asthma in children. We characterized the temporal and spatial variability of ambient endotoxin in Fresno/Clovis, California, located in California's Central Valley, to identify correlates and potential predictors of ambient endotoxin concentrations in a cohort of children with asthma [Fresno Asthmatic Children's Environment Study (FACES)]. Between May 2001 and October 2004, daily ambient endotoxin and air pollutants were collected at the central ambient monitoring site of the California Air Resources Board in Fresno and, for shorter time periods, at 10 schools and indoors and outdoors at 84 residences in the community. Analyses were restricted to May-October, the dry months during which endotoxin concentrations are highest. Daily endotoxin concentration patterns were determined mainly by meteorologic factors, particularly the degree of air stagnation. Overall concentrations were lowest in areas distant from agricultural activities. Highest concentrations were found in areas immediately downwind from agricultural/pasture land. Among three other measured air pollutants [fine particulate matter, elemental carbon (a marker of traffic in Fresno), and coarse particulate matter (PMc)], PMc was the only pollutant correlated with endotoxin. Endotoxin, however, was the most spatially variable. Our data support the need to evaluate the spatial/temporal variability of endotoxin concentrations, rather than relying on a few measurements made at one location, in studies of exposure and and respiratory health effects, particularly in children with asthma and other chronic respiratory diseases.

Assessing spatial and temporal variability of acid-extractable organics in oil sands process-affected waters.

PubMed

Frank, Richard A; Milestone, Craig B; Rowland, Steve J; Headley, John V; Kavanagh, Richard J; Lengger, Sabine K; Scarlett, Alan G; West, Charles E; Peru, Kerry M; Hewitt, L Mark

2016-10-01

The acid-extractable organic compounds (AEOs), including naphthenic acids (NAs), present within oil sands process-affected water (OSPW) receive great attention due to their known toxicity. While recent progress in advanced separation and analytical methodologies for AEOs has improved our understanding of the composition of these mixtures, little is known regarding any variability (i.e., spatial, temporal) inherent within, or between, tailings ponds. In this study, 5 samples were collected from the same location of one tailings pond over a 2-week period. In addition, 5 samples were collected simultaneously from different locations within a tailings pond from a different mine site, as well as its associated recycling pond. In both cases, the AEOs were analyzed using SFS, ESI-MS, HRMS, GC×GC-ToF/MS, and GC- & LC-QToF/MS (GC analyses following conversion to methyl esters). Principal component analysis of HRMS data was able to distinguish the ponds from each other, while data from GC×GC-ToF/MS, and LC- and GC-QToF/MS were used to differentiate samples from within the temporal and spatial sample sets, with the greater variability associated with the latter. Spatial differences could be attributed to pond dynamics, including differences in inputs of tailings and surface run-off. Application of novel chemometric data analyses of unknown compounds detected by LC- and GC-QToF/MS allowed further differentiation of samples both within and between data sets, providing an innovative approach for future fingerprinting studies. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Spatial Distribution of Dorylaimid and Mononchid Nematodes from the Southeast Iberian Peninsula: Environmental Characterization of Chorotypes

PubMed Central

Liébanas, G.; Guerrero, P.; Martín-García, J.-M.; Peña-Santiago, R.

2004-01-01

The aim of this study was to determine the incidence of 18 environmental variables in the spatial distribution of 30 chorotypes (species groups with significantly similar distribution patterns) of dorylaimid and mononchid nematodes by means of logistic regression in a natural area in the southeastern Iberian Peninsula. Six variables (elevation, color chroma, clay content, nitrogen content, CaCO₃, and plant community associated) were the most important environmental factors that helped explain the distribution of chorotypes. The distribution of most chorotypes was characterized by some (one to three) environmental variables; only two chorotypes were characterized by five or more variables, and four have not been characterized. PMID:19262795

Using Mobile Monitoring to Assess Spatial Variability in Urban Air Pollution Levels: Opportunities and Challenges (Invited)

NASA Astrophysics Data System (ADS)

Larson, T.

2010-12-01

Measuring air pollution concentrations from a moving platform is not a new idea. Historically, however, most information on the spatial variability of air pollutants have been derived from fixed site networks operating simultaneously over space. While this approach has obvious advantages from a regulatory perspective, with the increasing need to understand ever finer scales of spatial variability in urban pollution levels, the use of mobile monitoring to supplement fixed site networks has received increasing attention. Here we present examples of the use of this approach: 1) to assess existing fixed-site fine particle networks in Seattle, WA, including the establishment of new fixed-site monitoring locations; 2) to assess the effectiveness of a regulatory intervention, a wood stove burning ban, on the reduction of fine particle levels in the greater Puget Sound region; and 3) to assess spatial variability of both wood smoke and mobile source impacts in both Vancouver, B.C. and Tacoma, WA. Deducing spatial information from the inherently spatio-temporal measurements taken from a mobile platform is an area that deserves further attention. We discuss the use of “fuzzy” points to address the fine-scale spatio-temporal variability in the concentration of mobile source pollutants, specifically to deduce the broader distribution and sources of fine particle soot in the summer in Vancouver, B.C. We also discuss the use of principal component analysis to assess the spatial variability in multivariate, source-related features deduced from simultaneous measurements of light scattering, light absorption and particle-bound PAHs in Tacoma, WA. With increasing miniaturization and decreasing power requirements of air monitoring instruments, the number of simultaneous measurements that can easily be made from a mobile platform is rapidly increasing. Hopefully the methods used to design mobile monitoring experiments for differing purposes, and the methods used to interpret those measurements will keep pace.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

Biogeochemical typology and temporal variability of lagoon waters in a coral reef ecosystem subject to terrigeneous and anthropogenic inputs (New Caledonia).

PubMed

Fichez, R; Chifflet, S; Douillet, P; Gérard, P; Gutierrez, F; Jouon, A; Ouillon, S; Grenz, C

2010-01-01

Considering the growing concern about the impact of anthropogenic inputs on coral reefs and coral reef lagoons, surprisingly little attention has been given to the relationship between those inputs and the trophic status of lagoon waters. The present paper describes the distribution of biogeochemical parameters in the coral reef lagoon of New Caledonia where environmental conditions allegedly range from pristine oligotrophic to anthropogenically influenced. The study objectives were to: (i) identify terrigeneous and anthropogenic inputs and propose a typology of lagoon waters, (ii) determine temporal variability of water biogeochemical parameters at time-scales ranging from hours to seasons. Combined ACP-cluster analyses revealed that over the 2000 km(2) lagoon area around the city of Nouméa, "natural" terrigeneous versus oceanic influences affecting all stations only accounted for less than 20% of the spatial variability whereas 60% of that spatial variability could be attributed to significant eutrophication of a limited number of inshore stations. ACP analysis allowed to unambiguously discriminating between the natural trophic enrichment along the offshore-inshore gradient and anthropogenically induced eutrophication. High temporal variability in dissolved inorganic nutrients concentrations strongly hindered their use as indicators of environmental status. Due to longer turn over time, particulate organic material and more specifically chlorophyll a appeared as more reliable nonconservative tracer of trophic status. Results further provided evidence that ENSO occurrences might temporarily lower the trophic status of the New Caledonia lagoon. It is concluded that, due to such high frequency temporal variability, the use of biogeochemical parameters in environmental surveys require adapted sampling strategies, data management and environmental alert methods. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

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.

Throughfall and its spatial variability beneath xerophytic shrub canopies within water-limited arid desert ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Ya-feng; Wang, Xin-ping; Hu, Rui; Pan, Yan-xia

2016-08-01

Throughfall is known to be a critical component of the hydrological and biogeochemical cycles of forested ecosystems with inherently temporal and spatial variability. Yet little is understood concerning the throughfall variability of shrubs and the associated controlling factors in arid desert ecosystems. Here we systematically investigated the variability of throughfall of two morphological distinct xerophytic shrubs (Caragana korshinskii and Artemisia ordosica) within a re-vegetated arid desert ecosystem, and evaluated the effects of shrub structure and rainfall characteristics on throughfall based on heavily gauged throughfall measurements at the event scale. We found that morphological differences were not sufficient to generate significant difference (P < 0.05) in throughfall between two studied shrub species under the same rainfall and meteorological conditions in our study area, with a throughfall percentage of 69.7% for C. korshinskii and 64.3% for A. ordosica. We also observed a highly variable patchy pattern of throughfall beneath individual shrub canopies, but the spatial patterns appeared to be stable among rainfall events based on time stability analysis. Throughfall linearly increased with the increasing distance from the shrub base for both shrubs, and radial direction beneath shrub canopies had a pronounced impact on throughfall. Throughfall variability, expressed as the coefficient of variation (CV) of throughfall, tended to decline with the increase in rainfall amount, intensity and duration, and stabilized passing a certain threshold. Our findings highlight the great variability of throughfall beneath the canopies of xerophytic shrubs and the time stability of throughfall pattern among rainfall events. The spatially heterogeneous and temporally stable throughfall is expected to generate a dynamic patchy distribution of soil moisture beneath shrub canopies within arid desert ecosystems.

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

NASA Technical Reports Server (NTRS)

Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

1998-01-01

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Aerosol direct effect on solar radiation over the eastern Mediterranean Sea based on AVHRR satellite measurements

NASA Astrophysics Data System (ADS)

Georgakaki, Paraskevi; Papadimas, Christos D.; Hatzianastassiou, Nikos; Fotiadi, Aggeliki; Matsoukas, Christos; Stackhouse, Paul; Kanakidou, Maria; Vardavas, Ilias M.

2017-04-01

Despite the improved scientific understanding of the direct effect of aerosols on solar radiation (direct radiative effect, DRE) improvements are necessary, for example regarding the accuracy of the magnitude of estimated DREs and their spatial and temporal variability. This variability cannot be ensured by in-situ surface and airborne measurements, while it is also relatively difficult to capture through satellite observations. This becomes even more difficult when complete spatial coverage of extended areas is required, especially concerning areas that host various aerosol types with variable physico-chemical and optical aerosol properties. Better assessments of aerosol DREs are necessary, relying on aerosol optical properties with high spatial and temporal variation. The present study aims to provide a refined, along these lines, assessment of aerosol DREs over the eastern Mediterranean (EM) Sea, which is a key area for aerosol studies. Daily DREs are computed for 1˚ x1˚ latitude-longitude grids with the FORTH detailed spectral radiation transfer model (RTM) using input data for various atmospheric and surface parameters, such as clouds, water vapor, ozone and surface albedo, taken from the NASA-Langley Global Earth Observing System (GEOS) database. The model spectral aerosol optical depth (AOD), single scattering albedo and asymmetry parameter are taken from the Global Aerosol Data Set and the NOAA Climate Data Record (CDR) version 2 of Advanced Very High resolution Radiometer (AVHRR) AOD dataset which is available over oceans at 0.63 microns and at 0.1˚ x0.1˚ . The aerosol DREs are computed at the surface, the top-of-atmosphere and within the atmosphere, over the period 1985-1995. Preliminary model results for the period 1990-1993 reveal a significant spatial and temporal variability of DREs over the EM Sea, for example larger values over the Aegean and Black Seas, surrounded by land areas with significant anthropogenic aerosol sources, and over the southernmost parts of EM Sea, affected by frequent Saharan dust export. The mean regional annual AODs range from 0.17±0.05 to 0.23±0.06. The corresponding regional annual DREs at surface range from -14±3 to -18±4 W/m2 (surface radiative cooling), while in the atmosphere they vary between 7±2 and 10±2 W/m2 (atmospheric heating), yielding a planetary cooling above the EM Sea between -6±1 and -8±2 W/m2. However, these AOD and DRE values vary depending on the criteria of data spatial and temporal availability applied in the AOD and DRE calculation, because of the limited availability of retrieved AVHRR AOD over specific areas and in specific days. The DREs reach larger magnitudes at pixel-level; for example the surface DREs slightly exceed -30 W/m2, whereas they take larger values (magnitudes larger than -50 W/m2 in summer) when computed on a monthly basis, and even larger values on daily basis. The model results underline the high spatial and temporal variability of aerosol DREs, and the care that must be taken when averaging over space and time. It also points to the need for availability of aerosol data with concurrent high spatial and temporal coverage and resolution, which should be sought in ongoing and future satellite missions.

High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

PubMed

Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

2015-01-06

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

2015-01-01

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

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.

Integrating Eddy Covariance, Penman-Monteith and METRIC based Evapotranspiration estimates to generate high resolution space-time ET over the Brazos River Basin

NASA Astrophysics Data System (ADS)

Mbabazi, D.; Mohanty, B.; Gaur, N.

2017-12-01

Evapotranspiration (ET) is an important component of the water and energy balance and accounts for 60 -70% of precipitation losses. However, accurate estimates of ET are difficult to quantify at varying spatial and temporal scales. Eddy covariance methods estimate ET at high temporal resolutions but without capturing the spatial variation in ET within its footprint. On the other hand, remote sensing methods using Landsat imagery provide ET with high spatial resolution but low temporal resolution (16 days). In this study, we used both eddy covariance and remote sensing methods to generate high space-time resolution ET. Daily, monthly and seasonal ET estimates were obtained using the eddy covariance (EC) method, Penman-Monteith (PM) and Mapping Evapotranspiration with Internalized Calibration (METRIC) models to determine cotton and native prairie ET dynamics in the Brazos river basin characterized by varying hydro-climatic and geological gradients. Daily estimates of spatially distributed ET (30 m resolution) were generated using spatial autocorrelation and temporal interpolations between the EC flux variable footprints and METRIC ET for the 2016 and 2017 growing seasons. A comparison of the 2016 and 2017 preliminary daily ET estimates showed similar ET dynamics/trends among the EC, PM and METRIC methods, and 5-20% differences in seasonal ET estimates. This study will improve the spatial estimates of EC ET and temporal resolution of satellite derived ET thus providing better ET data for water use management.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Spatial and temporal variability of the overall error of National Atmospheric Deposition Program measurements determined by the USGS collocated-sampler program, water years 1989-2001

USGS Publications Warehouse

Wetherbee, G.A.; Latysh, N.E.; Gordon, J.D.

2005-01-01

Data from the U.S. Geological Survey (USGS) collocated-sampler program for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) are used to estimate the overall error of NADP/NTN measurements. Absolute errors are estimated by comparison of paired measurements from collocated instruments. Spatial and temporal differences in absolute error were identified and are consistent with longitudinal distributions of NADP/NTN measurements and spatial differences in precipitation characteristics. The magnitude of error for calcium, magnesium, ammonium, nitrate, and sulfate concentrations, specific conductance, and sample volume is of minor environmental significance to data users. Data collected after a 1994 sample-handling protocol change are prone to less absolute error than data collected prior to 1994. Absolute errors are smaller during non-winter months than during winter months for selected constituents at sites where frozen precipitation is common. Minimum resolvable differences are estimated for different regions of the USA to aid spatial and temporal watershed analyses.

Speech production variability in fricatives of children and adults: Results of functional data analysis

PubMed Central

Koenig, Laura L.; Lucero, Jorge C.; Perlman, Elizabeth

2008-01-01

This study investigates token-to-token variability in fricative production of 5 year olds, 10 year olds, and adults. Previous studies have reported higher intrasubject variability in children than adults, in speech as well as nonspeech tasks, but authors have disagreed on the causes and implications of this finding. The current work assessed the characteristics of age-related variability across articulators (larynx and tongue) as well as in temporal versus spatial domains. Oral airflow signals, which reflect changes in both laryngeal and supralaryngeal apertures, were obtained for multiple productions of ∕h s z∕. The data were processed using functional data analysis, which provides a means of obtaining relatively independent indices of amplitude and temporal (phasing) variability. Consistent with past work, both temporal and amplitude variabilities were higher in children than adults, but the temporal indices were generally less adultlike than the amplitude indices for both groups of children. Quantitative and qualitative analyses showed considerable speaker- and consonant-specific patterns of variability. The data indicate that variability in ∕s∕ may represent laryngeal as well as supralaryngeal control and further that a simple random noise factor, higher in children than in adults, is insufficient to explain developmental differences in speech production variability. PMID:19045800

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

PubMed Central

Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

2010-01-01

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

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.

Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis

PubMed Central

Gopal, Shruti; Miller, Robyn L.; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R.; Cahill, Nathan; Baum, Stefi A.; Calhoun, Vince D.

2016-01-01

Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. PMID:26106217

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Impacts of climate on shrubland fuels and fire behavior in the Owyhee Basin, Idaho

NASA Astrophysics Data System (ADS)

Vogelmann, J. E.; Shi, H.; Hawbaker, T.; Li, Z.

2013-12-01

There is evidence that wildland fire is increasing as a function of global change. However, fire activity is spatially, temporally and ecologically variable across the globe, and our understanding of fire risk and behavior in many ecosystems is limited. After a series of severe fire seasons that occurred during the late 1990's in the western United States, the LANDFIRE program was developed with the goals of providing the fire community with objective spatial fuel data for assessing wildland fire risk. Even with access to the data provided by LANDFIRE, assessing fire behavior in shrublands in sagebrush-dominated ecosystems of the western United States has proven especially problematic, in part due to the complex nature of the vegetation, the variable influence of understory vegetation including invasive species (e.g. cheatgrass), and prior fire history events. Climate is undoubtedly playing a major role, affecting the intra- and inter-annual variability in vegetation conditions, which in turn impacts fire behavior. In order to further our understanding of climate-vegetation-fire interactions in shrublands, we initiated a study in the Owyhee Basin, which is located in southwestern Idaho and adjacent Nevada. Our goals include: (1) assessing the relationship between climate and vegetation condition, (2) quantifying the range of temporal variability in grassland and shrubland fuel loads, (3) identifying methods to operationally map the variability in fuel loads, and (4) assessing how the variability in fuel loads affect fire spread simulations. To address these goals, we are using a wide variety of geospatial data, including remotely sensed time-series data sets derived from MODIS and Landsat, and climate data from DAYMET and PRISM. Remotely-sensed information is used to characterize climate-induced temporal variability in primary productivity in the Basin, where fire spread can be extensive after senescence when dry vegetation is added to dead fuel loads. Gridded climate data indicate that this area has become warmer and dryer over the previous three decades. We have also observed that fires are especially prevalent in areas that have high Normalized Difference Vegetation Index (NDVI) values in the spring, followed by low NDVI in the summer. At present we are concentrating on the temporally rich MODIS data to map spatial and temporal variability in live fuel loads. To translate NDVI to biomass, we are scaling the range of biomass values using data from the literature. We assume that departure from maximum NDVI, typically occurring during spring, to NDVI values later in the season are related to the proportion of live biomass transferred to dead biomass, which burns more readily than green biomass. Using the FARSITE fire spread model, our initial simulations show that the conversion from live herbaceous fuel to dead fuel increases the burn area by 30% compared with using default static fuel parameters. This indicates that current fuel models underestimate fire spread and areas that could potentially burn. Our study also indicates that a combined remote sensing product with good temporal resolution (MODIS) and spatial resolution (Landsat) is necessary to provide accurate information on the fuel dynamics in shrublands.

Small-scale variability in peatland pore-water biogeochemistry, Hudson Bay Lowland, Canada.

PubMed

Ulanowski, T A; Branfireun, B A

2013-06-01

The Hudson Bay Lowland (HBL) of northern Ontario, Manitoba and Quebec, Canada is the second largest contiguous peatland complex in the world, currently containing more than half of Canada's soil carbon. Recent concerns about the ecohydrological impacts to these large northern peatlands resulting from climate change and resource extraction have catalyzed a resurgence in scientific research into this ecologically important region. However, the sheer size, heterogeneity and elaborate landscape arrangements of this ecosystem raise important questions concerning representative sampling of environmental media for chemical or physical characterization. To begin to quantify such variability, this study assessed the small-scale spatial (1m) and short temporal (21 day) variability of surface pore-water biogeochemistry (pH, dissolved organic carbon, and major ions) in a Sphagnum spp.-dominated, ombrotrophic raised bog, and a Carex spp.-dominated intermediate fen in the HBL. In general, pore-water pH and concentrations of dissolved solutes were similar to previously reported literature values from this region. However, systematic sampling revealed consistent statistically significant differences in pore-water chemistries between the bog and fen peatland types, and large within-site spatiotemporal variability. We found that microtopography in the bog was associated with consistent differences in most biogeochemical variables. Temporal changes in dissolved solute chemistry, particularly base cations (Na(+), Ca(2+) and Mg(2+)), were statistically significant in the intermediate fen, likely a result of a dynamic connection between surficial waters and mineral-rich deep groundwater. In both the bog and fen, concentrations of SO4(2-) showed considerable spatial variability, and a significant decrease in concentrations over the study period. The observed variability in peatland pore-water biogeochemistry over such small spatial and temporal scales suggests that under-sampling in northern peatland environments could lead to erroneous conclusions concerning the abundance and distribution of natural elements and pollutants alike. Copyright © 2013 Elsevier B.V. All rights reserved.

Composition and Chemistry of the Neutral Atmosphere of Venus

NASA Astrophysics Data System (ADS)

Marcq, Emmanuel; Mills, Franklin P.; Parkinson, Christopher D.; Vandaele, Ann Carine

2018-02-01

This paper deals with the composition and chemical processes occurring in the neutral atmosphere of Venus. Since the last synthesis, observers as well as modellers have emphasised the spatial and temporal variability of minor species, going beyond a static and uniform picture that may have prevailed in the past. The outline of this paper acknowledges this situation and follows closely the different dimensions along which variability in composition can be observed: vertical, latitudinal, longitudinal, temporal. The strong differences between the atmosphere below and above the cloud layers also dictate the structure of this paper. Observational constraints, obtained from both Earth and Venus Express, as well as 1D, 2D and 3D models results obtained since 1997 are also extensively referred and commented by the authors. An non-exhaustive list of topics included follows: modelled and observed latitudinal and vertical profiles of CO and OCS below the clouds of Venus; vertical profiles of CO and SO2 above the clouds as observed by solar occultation and modelled; temporal and spatial variability of sulphur oxides above the clouds. As a conclusion, open questions and topics of interest for further studies are discussed.

Using a Data-Driven Approach to Understand the Interaction between Catchment Characteristics and Water Quality Responses

NASA Astrophysics Data System (ADS)

Western, A. W.; Lintern, A.; Liu, S.; Ryu, D.; Webb, J. A.; Leahy, P.; Wilson, P.; Waters, D.; Bende-Michl, U.; Watson, M.

2016-12-01

Many streams, lakes and estuaries are experiencing increasing concentrations and loads of nutrient and sediments. Models that can predict the spatial and temporal variability in water quality of aquatic systems are required to help guide the management and restoration of polluted aquatic systems. We propose that a Bayesian hierarchical modelling framework could be used to predict water quality responses over varying spatial and temporal scales. Stream water quality data and spatial data of catchment characteristics collected throughout Victoria and Queensland (in Australia) over two decades will be used to develop this Bayesian hierarchical model. In this paper, we present the preliminary exploratory data analysis required for the development of the Bayesian hierarchical model. Specifically, we present the results of exploratory data analysis of Total Nitrogen (TN) concentrations in rivers in Victoria (in South-East Australia) to illustrate the catchment characteristics that appear to be influencing spatial variability in (1) mean concentrations of TN; and (2) the relationship between discharge and TN throughout the state. These important catchment characteristics were identified using: (1) monthly TN concentrations measured at 28 water quality gauging stations and (2) climate, land use, topographic and geologic characteristics of the catchments of these 28 sites. Spatial variability in TN concentrations had a positive correlation to fertiliser use in the catchment and average temperature. There were negative correlations between TN concentrations and catchment forest cover, annual runoff, runoff perenniality, soil erosivity and catchment slope. The relationship between discharge and TN concentrations showed spatial variability, possibly resulting from climatic and topographic differences between the sites. The results of this study will feed into the hierarchical Bayesian model of river water quality.

Classification of Regional Ionospheric Disturbances Based on Support Vector Machines

NASA Astrophysics Data System (ADS)

Begüm Terzi, Merve; Arikan, Feza; Arikan, Orhan; Karatay, Secil

2016-07-01

Ionosphere is an anisotropic, inhomogeneous, time varying and spatio-temporally dispersive medium whose parameters can be estimated almost always by using indirect measurements. Geomagnetic, gravitational, solar or seismic activities cause variations of ionosphere at various spatial and temporal scales. This complex spatio-temporal variability is challenging to be identified due to extensive scales in period, duration, amplitude and frequency of disturbances. Since geomagnetic and solar indices such as Disturbance storm time (Dst), F10.7 solar flux, Sun Spot Number (SSN), Auroral Electrojet (AE), Kp and W-index provide information about variability on a global scale, identification and classification of regional disturbances poses a challenge. The main aim of this study is to classify the regional effects of global geomagnetic storms and classify them according to their risk levels. For this purpose, Total Electron Content (TEC) estimated from GPS receivers, which is one of the major parameters of ionosphere, will be used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. In this work, for the automated classification of the regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. SVM is a supervised learning model used for classification with associated learning algorithm that analyze the data and recognize patterns. In addition to performing linear classification, SVM can efficiently perform nonlinear classification by embedding data into higher dimensional feature spaces. Performance of the developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from the GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing the developed classification technique to the Global Ionospheric Map (GIM) TEC data which is provided by the NASA Jet Propulsion Laboratory (JPL), it will be shown that SVM can be a suitable learning method to detect the anomalies in Total Electron Content (TEC) variations. This study is supported by TUBITAK 114E541 project as a part of the Scientific and Technological Research Projects Funding Program (1001).

Spatial and temporal adaptations that accompany increasing catching performance during learning.

PubMed

Mazyn, Liesbeth I N; Lenoir, Matthieu; Montagne, Gilles; Savelsbergh, Geert J P

2007-11-01

The authors studied changes in performance and kinematics during the acquisition of a 1-handed catch. Participants were 8 women who took an intensive 2-week training program during which they evolved from poor catchers to subexpert catchers. An increased temporal consistency, shift in spatial location of ball-hand contact away from the body, and higher peak velocity of the transport of the hand toward the ball accompanied their improvement in catching performance. Moreover, novice catchers first adjusted spatial characteristics of the catch to the task constraints and fine-tuned temporal features only later during learning. A principal components analysis on a large set of kinematic variables indicated that a successful catch depends on (a) forward displacement of the hand and (b) the dynamics of the hand closure, thereby providing a kinematic underpinning for the traditional transport-manipulation dissociation in the grasping and catching literature.

Spatial and temporal variability of microgeographic genetic structure in white-tailed deer

USGS Publications Warehouse

Scribner, Kim T.; Smith, Michael H.; Chesser, Ronald K.

1997-01-01

Techniques are described that define contiguous genetic subpopulations of white-tailed deer (Odocoileus virginianus) based on the spatial dispersion of 4,749 individuals that possessed discrete character values (alleles or genotypes) during each of 6 years (1974-1979). White-tailed deer were not uniformly distributed in space, but exhibited considerable spatial genetic structuring. Significant non-random clusters of individuals were documented during each year based on specific alleles and genotypes at the Sdh locus. Considerable temporal variation was observed in the position and genetic composition of specific clusters, which reflected changes in allele frequency in small geographic areas. The position of clusters did not consistently correspond with traditional management boundaries based on major discontinuities in habitat (swamp versus upland) and hunt compartments that were defined by roads and streams. Spatio-temporal stability of observed genetic contiguous clusters was interpreted relative to method and intensity of harvest, movements, and breeding ecology.

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport

USGS Publications Warehouse

Marineau, Mathieu D.; Minear, J. Toby; Wright, Scott A.

2015-01-01

Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.

A novel mobile monitoring approach to characterize spatial and temporal variation in traffic-related air pollutants in an urban community

NASA Astrophysics Data System (ADS)

Yu, Chang Ho; Fan, Zhihua; Lioy, Paul J.; Baptista, Ana; Greenberg, Molly; Laumbach, Robert J.

2016-09-01

Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30-10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09-16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512-159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27-46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22-6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.

Quantitative approaches in climate change ecology

PubMed Central

Brown, Christopher J; Schoeman, David S; Sydeman, William J; Brander, Keith; Buckley, Lauren B; Burrows, Michael; Duarte, Carlos M; Moore, Pippa J; Pandolfi, John M; Poloczanska, Elvira; Venables, William; Richardson, Anthony J

2011-01-01

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

Extremely Low Frequency (ELF) Communications System Ecological Monitoring Program: Summary of 1986 Progress.

DTIC Science & Technology

1987-12-01

assessment of data collection techniques *quantification of temporal and spatial patterns of variables *assessment of end point variability...nutrient variables are also being examined as covarlates. Development of a model to test for differences in growth patterns is continuing. At each of...condition. These variables are recorded at the end of each growing season. For evaluation of height growth patterns , a subsample of 100 seedlings per

Sensitivity of snowpack storage to precipitation and temperature using spatial and temporal analog models

NASA Astrophysics Data System (ADS)

Luce, Charles H.; Lopez-Burgos, Viviana; Holden, Zachary

2014-12-01

Empirical sensitivity analyses are important for evaluation of the effects of a changing climate on water resources and ecosystems. Although mechanistic models are commonly applied for evaluation of climate effects for snowmelt, empirical relationships provide a first-order validation of the various postulates required for their implementation. Previous studies of empirical sensitivity for April 1 snow water equivalent (SWE) in the western United States were developed by regressing interannual variations in SWE to winter precipitation and temperature. This offers a temporal analog for climate change, positing that a warmer future looks like warmer years. Spatial analogs are used to hypothesize that a warmer future may look like warmer places, and are frequently applied alternatives for complex processes, or states/metrics that show little interannual variability (e.g., forest cover). We contrast spatial and temporal analogs for sensitivity of April 1 SWE and the mean residence time of snow (SRT) using data from 524 Snowpack Telemetry (SNOTEL) stations across the western U.S. We built relatively strong models using spatial analogs to relate temperature and precipitation climatology to snowpack climatology (April 1 SWE, R2=0.87, and SRT, R2=0.81). Although the poorest temporal analog relationships were in areas showing the highest sensitivity to warming, spatial analog models showed consistent performance throughout the range of temperature and precipitation. Generally, slopes from the spatial relationships showed greater thermal sensitivity than the temporal analogs, and high elevation stations showed greater vulnerability using a spatial analog than shown in previous modeling and sensitivity studies. The spatial analog models provide a simple perspective to evaluate potential futures and may be useful in further evaluation of snowpack with warming.

A Conceptual Characterization of Online Videos Explaining Natural Selection

NASA Astrophysics Data System (ADS)

Bohlin, Gustav; Göransson, Andreas; Höst, Gunnar E.; Tibell, Lena A. E.

2017-11-01

Educational videos on the Internet comprise a vast and highly diverse source of information. Online search engines facilitate access to numerous videos claiming to explain natural selection, but little is known about the degree to which the video content match key evolutionary content identified as important in evolution education research. In this study, we therefore analyzed the content of 60 videos accessed through the Internet, using a criteria catalog with 38 operationalized variables derived from research literature. The variables were sorted into four categories: (a) key concepts (e.g. limited resources and inherited variation), (b) threshold concepts (abstract concepts with a transforming and integrative function), (c) misconceptions (e.g. that evolution is driven by need), and (d) organismal context (e.g. animal or plant). The results indicate that some concepts are frequently communicated, and certain taxa are commonly used to illustrate concepts, while others are seldom included. In addition, evolutionary phenomena at small temporal and spatial scales, such as subcellular processes, are rarely covered. Rather, the focus is on population-level events over time scales spanning years or longer. This is consistent with an observed lack of explanations regarding how randomly occurring mutations provide the basis for variation (and thus natural selection). The findings imply, among other things, that some components of natural selection warrant far more attention in biology teaching and science education research.

Spatial and temporal variability in sediment deposition and seabed character on the Waipaoa River margin, New Zealand

NASA Astrophysics Data System (ADS)

Walsh, J. P.; Corbett, D. R.; Kiker, J. M.; Orpin, A. R.; Hale, R. P.; Ogston, A. S.

2014-09-01

The stratigraphic record is the manifestation of a wide range of processes, interactions and responses to environmental drivers. Understanding the functioning of river sediment dispersal systems is necessary to determine the fate of sediment and associated material in the marine environment and differentiate key influences in the development of the stratigraphic record. To that end, this study uses sediment cores collected on four successive cruises (January, May and September 2010 and February 2011) on the Waipaoa River margin, New Zealand, to provide insight into spatial and temporal variability in sediment deposition and seabed character. The Waipaoa River discharges a large sediment load into an energetic coast that has a complex margin morphology. Several flood and wave events occurred during the study, and sedimentation varied spatially and temporally. X-radiographs and short-lived radioisotopes indicate emplacement of new event layers prior to all cruises. Notable variation in surficial seabed character (grain-size composition, loss-on-ignition percentage) was apparent on the inner shelf (water depths <40 m), but mid-shelf areas and seaward had more homogeneous sediment properties. 7Be inventories indicate variable patterns of deposition related to fluvial and oceanographic conditions prior to cruises. Ephemeral sediment storage occurs on the inner-shelf of Poverty Bay, into which the Waipaoa River discharges directly, and subsequent export and dispersal patterns are linked to the relative timing and size of flood and wave events. Surficial deposits with characteristics of fluid muds and wave-enhanced sediment gravity flows were noted at some (<25 sites total) mid-shelf and shallower sites from all cruises. During the last cruise considerable inter- and intra-site seabed variability occurred in the interbedded river-proximal inner-shelf deposits over spatial scales of less than a few kilometers. Evidence from earlier sidescan data infer that this could be related to variation in bedform development or influence. Contrasts in the observed event layering recorded over the experiment with the longer pattern of accumulation suggests stochastic dispersal behavior and reworking over time must shape the seabed to produce the time-averaged pattern of shelf sediment accumulation. This research highlights our improved ability to comprehend strata development and sheds light on the challenge of interpreting historical and ancient strata across spatial and temporal scales.

The advantages, and challenges, in using multiple techniques in the estimation of surface water-groundwater fluxes.

NASA Astrophysics Data System (ADS)

Shanafield, M.; Cook, P. G.

2014-12-01

When estimating surface water-groundwater fluxes, the use of complimentary techniques helps to fill in uncertainties in any individual method, and to potentially gain a better understanding of spatial and temporal variability in a system. It can also be a way of preventing the loss of data during infrequent and unpredictable flow events. For example, much of arid Australia relies on groundwater, which is recharged by streamflow through ephemeral streams during flood events. Three recent surface water/groundwater investigations from arid Australian systems provide good examples of how using multiple field and analysis techniques can help to more fully characterize surface water-groundwater fluxes, but can also result in conflicting values over varying spatial and temporal scales. In the Pilbara region of Western Australia, combining streambed radon measurements, vertical heat transport modeling, and a tracer test helped constrain very low streambed residence times, which are on the order of minutes. Spatial and temporal variability between the methods yielded hyporheic exchange estimates between 10-4 m2 s-1 and 4.2 x 10-2 m2 s-1. In South Australia, three-dimensional heat transport modeling captured heterogeneity within 20 square meters of streambed, identifying areas of sandy soil (flux rates of up to 3 m d-1) and clay (flux rates too slow to be accurately characterized). Streamflow front modeling showed similar flux rates, but averaged over 100 m long stream segments for a 1.6 km reach. Finally, in central Australia, several methods are used to decipher whether any of the flow down a highly ephemeral river contributes to regional groundwater recharge, showing that evaporation and evapotranspiration likely accounts for all of the infiltration into the perched aquifer. Lessons learned from these examples demonstrate the influences of the spatial and temporal variability between techniques on estimated fluxes.

Patterns of spatio-temporal distribution of winter chronic photoinhibition in leaves of three evergreen Mediterranean species with contrasting acclimation responses.

PubMed

Silva-Cancino, María Carolina; Esteban, Raquel; Artetxe, Unai; Plazaola, José Ignacio García

2012-03-01

High irradiance and relatively low temperature, which characterize Mediterranean winters, cause chilling stress in plants. Downregulation of photosynthetic efficiency is a mechanism that allows plants to survive these conditions. This study aims to address whether this process shows a regular spatial pattern across leaf surface or not. Three species (Buxus sempervirens, Cistus albidus and Arctostaphylos uva-ursi) with contrasting responses to winter stress were studied. During 7 days, macro and micro Fv/Fm spatial patterns were monitored by the use of chlorophyll fluorescence imaging techniques. In the field, the strongest photoinhibition was found in B. sempervirens, while there was almost no chronic photoinhibition in C. albidus. In leaves of the first species, Fv/Fm decreased from base to tip while in C. albidus it was uniform over the leaf lamina. An intermediate behavior is shown by A. uva-ursi leaves. Spatial heterogeneity distribution of Fv/Fm was found inside the leaves, resulting in greater Fv/Fm values in the inner layers than in the outer ones. Neither xanthophyll-linked downregulation of Fv/Fm nor protein remobilization were the reasons for such spatial patterns since pigment composition and nitrogen content did not reveal tip-base differences. During recovery from winter, photoinhibition changes occurred in Fv/Fm, pigments and chloroplast ultrastructure. This work shows for the first time that irrespective of physiological mechanisms responsible for development of winter photoinhibition, there is an acclimation response with strong spatio-temporal variability at leaf level in some species. This observation should be taken into account when modeling or scaling up photosynthetic responses. Copyright © Physiologia Plantarum 2011.

In-situ Chemical Exploration and Mapping using an Autonomous Underwater Vehicle

NASA Astrophysics Data System (ADS)

Camilli, R.; Bingham, B. S.; Jakuba, M.; Whelan, J.; Singh, H.; Whiticar, M.

2004-12-01

Recent advances in in-situ chemical sensing have emphasized several issues associated with making reliable chemical measurements in the ocean. Such measurements are often aliased temporally and or spatially, and may suffer from instrumentation artifacts, such as slow response time, limited dynamic range, hysteresis, and environmental sensitivities (eg., temperature and pressure). We focus on the in-situ measurement of light hydrocarbons. Specifically we examine data collected using a number of methods including: a vertical profiler, autonomous underwater vehicles (AUV) surveys, and adaptive spatio-temporal survey techniques. We present data collected using a commercial METS sensor on a vertical profiler to identify and map structures associated with ocean bottom methane sources in the Saanich inlet off Vancouver, Canada. This sensor was deployed in parallel with a submersible mass spectrometer and a shipboard equilibrator-gas chromatograph. Our results illustrate that spatial offsets as small as centimeters can produce significant differences in measured concentration. In addition, differences in response times between instruments can also alias the measurements. The results of this preliminary experiment underscore the challenges of quantifying ocean chemical processes with small-scale spatial variability and temporal variability that is often faster than the response times of many available instruments. We explore the capabilities and current limitations of autonomous underwater vehicles for extending the spatial coverage of new in-situ sensor technologies. We present data collected from deployments of Seabed, a passively stable, hover capable AUV, at large-scale gas blowout features located along the U.S. Atlantic margin. Although these deployments successfully revealed previously unobservable oceanographic processes, temporal aliasing caused by sensor response as well as tidal variability manifests itself, illustrating the possibilities for misinterpretation of localized periodic anomalies. Finally we present results of recent experimental chemical plume mapping surveys that were conducted off the coast of Massachusetts using adaptive behaviors that allow the AUV to optimize its mission plan to autonomously search for chemical anomalies. This adaptive operation is based on coupling the chemical sensor payload within a closed-loop architecture with the vehicle's navigation control system for real-time autonomous data assimilation and decision making processes. This allows the vehicle to autonomously refine the search strategy, thereby improving feature localization capabilities and enabling surveys at an appropriate temporal and spatial resolution.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Impact of spatial and temporal aggregation of input parameters on the assessment of irrigation scheme performance

NASA Astrophysics Data System (ADS)

Lorite, I. J.; Mateos, L.; Fereres, E.

2005-01-01

SummaryThe simulations of dynamic, spatially distributed non-linear models are impacted by the degree of spatial and temporal aggregation of their input parameters and variables. This paper deals with the impact of these aggregations on the assessment of irrigation scheme performance by simulating water use and crop yield. The analysis was carried out on a 7000 ha irrigation scheme located in Southern Spain. Four irrigation seasons differing in rainfall patterns were simulated (from 1996/1997 to 1999/2000) with the actual soil parameters and with hypothetical soil parameters representing wider ranges of soil variability. Three spatial aggregation levels were considered: (I) individual parcels (about 800), (II) command areas (83) and (III) the whole irrigation scheme. Equally, five temporal aggregation levels were defined: daily, weekly, monthly, quarterly and annually. The results showed little impact of spatial aggregation in the predictions of irrigation requirements and of crop yield for the scheme. The impact of aggregation was greater in rainy years, for deep-rooted crops (sunflower) and in scenarios with heterogeneous soils. The highest impact on irrigation requirement estimations was in the scenario of most heterogeneous soil and in 1999/2000, a year with frequent rainfall during the irrigation season: difference of 7% between aggregation levels I and III was found. Equally, it was found that temporal aggregation had only significant impact on irrigation requirements predictions for time steps longer than 4 months. In general, simulated annual irrigation requirements decreased as the time step increased. The impact was greater in rainy years (specially with abundant and concentrated rain events) and in crops which cycles coincide in part with the rainy season (garlic, winter cereals and olive). It is concluded that in this case, average, representative values for the main inputs of the model (crop, soil properties and sowing dates) can generate results within 1% of those obtained by providing spatially specific values for about 800 parcels.

Temporal and Spatial Variation of Chemical Water Quality in a Contour Canal.

NASA Astrophysics Data System (ADS)

Swanson, L. A.; Lunn, R. J.

2004-12-01

Chemical water quality is a highly variable aspect of any water body. Historically numerous researchers have investigated the chemical variability of rivers, streams and wetlands, artificial water bodies such as canals have been largely neglected. Canals are typically hydraulically characterised by low flows and a lack of mixing processes. This can potentially lead to significant spatial variability in water chemistry, and as a result many canals in the UK regularly fail water quality targets at specific locations. Recent changes to UK legislation, following the European Water Framework Directive (2000/60/EC), have resulted in canals being subject to achieving `good ecological status'. In the case of canals, what constitutes `good ecological status' is largely unknown and little expertise is available since historically canal management has not been driven by chemical and ecological quality targets. Consequently, there is an urgent need for new research to determine the main factors influencing canal water quality and their ecological status. This research presents results from a study based on a UK contour canal, the Union Canal in central Scotland. The Union Canal typically demonstrates spatially and temporally variable levels of dissolved oxygen (DO) and orthophosphate (PO4-P): simultaneously, seasonal and diel fluctuations of DO and PO4-P are pronounced at a small number of locations. During 1995, minimum levels of DO along the canal length ranged from 9mgl-1 in Edinburgh to as low as 2mgl-1 approximately 20kms away, this then rose again to 8mgl-1 after a further distance of 2km. These acutely low levels of DO are coupled with events of excessive PO4-P up to 0.235mgl-1:10 times greater than those normally found in rivers, causing localised eutrophication and extensive fish kills. To determine the cause of the `hot spots' of poor water quality found on the Union Canal, simultaneous investigations of the hydraulic regime, spatial and temporal water quality variation and the canal's biological status were carried out. Velocity metering in the canal identified extremely low flow rates ~0.15m3s-1. A tracer testing procedure for the canal's low flow conditions was designed and implemented which identified a lack of rapid dispersion processes with D~0.133m3s-1. Water quality sampling consisted of a year-long programme of high frequency temporal and spatial sampling along the canal length. Observations demonstrate significant variability, with widely differing measurements of DO as little as 5m apart. In addition, spot samples of water quality taken from individual incoming field drains showed PO4-P concentrations up to 2mgl-1, with a predominance of nutrient bound clay and silt sediments that ultimately settle on the canal bed. Due to low dispersion rates, residence times for pollutants are long and field drains, in combination with navigational activity, may well be one of the primary causes of raised nutrient levels at some locations. This research has shown that canal water quality is highly spatially and temporally variable; far in excess of the variability normally found in river systems. This is mainly determined by a lack of hydraulic mixing and the presence of small quantities of incoming runoff water of very low quality. Whilst low in volume, incoming sediment from the drains appears to strongly influence the nearby canal water quality. These results have important consequences both for future monitoring strategies of canals and management of their gradual ecological improvement.

Effects of soil spatial variability at the hillslope and catchment scales on characteristics of rainfall-induced landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2016-03-01

Spatial variations in soil properties affect key hydrological processes, yet their role in soil mechanical response to hydro-mechanical loading is rarely considered. This study aims to fill this gap by systematically quantifying effects of spatial variations in soil type and initial water content on rapid rainfall-induced shallow landslide predictions at the hillslope- and catchment-scales. We employed a physically-based landslide triggering model that considers mechanical interactions among soil columns governed by strength thresholds. At the hillslope scale, we found that the emergence of weak regions induced by spatial variations of soil type and initial water content resulted in early triggering of landslides with smaller volumes of released mass relative to a homogeneous slope. At the catchment scale, initial water content was linked to a topographic wetness index, whereas soil type varied deterministically with soil depth considering spatially correlated stochastic components. Results indicate that a strong spatial organization of initial water content delays landslide triggering, whereas spatially linked soil type with soil depth promoted landslide initiation. Increasing the standard deviation and correlation length of the stochastic component of soil type increases landslide volume and hastens onset of landslides. The study illustrates that for similar external boundary conditions and mean soil properties, landslide characteristics vary significantly with soil variability, hence it must be considered for improved landslide model predictions.

Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

NASA Astrophysics Data System (ADS)

Medyńska-Gulij, Beata; Cybulski, Paweł

2016-06-01

This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

Decadal changes of reference crop evapotranspiration attribution: Spatial and temporal variability over China 1960-2011

NASA Astrophysics Data System (ADS)

Fan, Ze-Xin; Thomas, Axel

2018-05-01

Atmospheric evaporative demand can be used as a measure of the hydrological cycle and the global energy balance. Its long-term variation and the role of driving climatic factors have received increasingly attention in climate change studies. FAO-Penman-Monteith reference crop evapotranspiration rates were estimated for 644 meteorological stations over China for the period 1960-2011 to analyze spatial and temporal attribution variability. Attribution of climatic variables to reference crop evapotranspiration rates was not stable over the study period. While for all of China the contribution of sunshine duration remained relatively stable, the importance of relative humidity increased considerably during the last two decades, particularly in winter. Spatially distributed attribution analysis shows that the position of the center of maximum contribution of sunshine duration has shifted from Southeast to Northeast China while in West China the contribution of wind speed has decreased dramatically. In contrast relative humidity has become an important factor in most parts of China. Changes in the Asian Monsoon circulation may be responsible for altered patterns of cloudiness and a general decrease of wind speeds over China. The continuously low importance of temperature confirms that global warming does not necessarily lead to rising atmospheric evaporative demand.

Spatial and temporal patterns in fish assemblages of upper coastal plain streams, Mississippi, USA

Treesearch

Susan B. Adams; Melvin L. Warren; Wendell R. Haag

2004-01-01

We assessed spatial, seasonal, and annual variation in fish assemblages over 17 months in three small- to medium-sized, incised streams characteristic of northwestern Mississippi streams. We sampled 17 962 fish representing 52 species and compared assemblages within and among streams. Although annual and seasonal variability inassemblage structure was high, fish...

Improving our process understanding of methane emissions from a mid-latitude reservoir by combining eddy covariance monitoring with spatial surveys

EPA Science Inventory

Reservoirs are a globally important source of methane (CH4) to the atmosphere, but measuring CH4 emission rates from reservoirs is difficult due to the spatial and temporal variability of the various emission pathways, including ebullition and diffusion. We used the eddy covarian...

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Assessing heterogeneity in soil nitrogen cycling: a plot-scale approach

Treesearch

Peter Baas; Jacqueline E. Mohan; David Markewitz; Jennifer D. Knoepp

2014-01-01

The high level of spatial and temporal heterogeneity in soil N cycling processes hinders our ability to develop an ecosystem-wide understanding of this cycle. This study examined how incorporating an intensive assessment of spatial variability for soil moisture, C, nutrients, and soil texture can better explain ecosystem N cycling at the plot scale. Five sites...

Hedonic valuation with translating amenities: Mountain Pine Beetles and host trees in the Colorado Front Range

Treesearch

Jed Cohen; Christine E. Blinn; Kevin J. Boyle; Tom Holmes; Klaus Moeltner

2016-01-01

In hedonic valuation studies the policy-relevant environmental quality attribute of interest is often costly to measure, especially under pronounced spatial and temporal variability. However, in many cases this attribute affects home prices and consumer preferences solely through its impact on a readily observable, spatially delineated, and time-invariant feature of...

Temporal-Spatial Variation and Controls of Soil Respiration in Different Primary Succession Stages on Glacier Forehead in Gongga Mountain, China

PubMed Central

Luo, Ji; Chen, Youchao; Wu, Yanhong; Shi, Peili; She, Jia; Zhou, Peng

2012-01-01

Soil respiration (SR) is an important process in the global carbon cycle. It is difficult to estimate SR emission accurately because of its temporal and spatial variability. Primary forest succession on Glacier forehead provides the ideal environment for examining the temporal-spatial variation and controlling factors of SR. However, relevant studies on SR are relatively scarce, and variations, as well as controlling factors, remain uncertain in this kind of region. In this study, we used a static chamber system to measure SR in six sites which represent different stages of forest succession on forehead of a temperate glacier in Gongga Mountain, China. Our results showed that there was substantial temporal (coefficient of variation (CV) ranged from 39.3% to 73.9%) and spatial (CV ranged from 12.3% to 88.6%) variation in SR. Soil temperature (ST) at 5 cm depth was the major controlling factor of temporal variation in all six sites. Spatial variation in SR was mainly caused by differences in plant biomass and Total N among the six sites. Moreover, soil moisture (SM), microbial biomass carbon (MBC), soil organic carbon (SOC), pH and bulk density could influence SR by directly or indirectly affecting plant biomass and Total N. Q10 values (ranged from 2.1 to 4.7) increased along the forest succession, and the mean value (3.3) was larger than that of temperate ecosystems, which indicated a general tendency towards higher-Q10 in colder ecosystems than in warmer ecosystems. Our findings provided valuable information for understanding temporal-spatial variation and controlling factors of SR. PMID:22879950

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

PubMed Central

Diago, Maria P.; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψs) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction (RP2) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture. PMID:29441086

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy.

PubMed

Diago, Maria P; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψ s ) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction ([Formula: see text]) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

Teacher spatial skills are linked to differences in geometry instruction.

PubMed

Otumfuor, Beryl Ann; Carr, Martha

2017-12-01

Spatial skills have been linked to better performance in mathematics. The purpose of this study was to examine the relationship between teacher spatial skills and their instruction, including teacher content and pedagogical knowledge, use of pictorial representations, and use of gestures during geometry instruction. Fifty-six middle school teachers participated in the study. The teachers were administered spatial measures of mental rotations and spatial visualization. Next, a single geometry class was videotaped. Correlational analyses revealed that spatial skills significantly correlate with teacher's use of representational gestures and content and pedagogical knowledge during instruction of geometry. Spatial skills did not independently correlate with the use of pointing gestures or the use of pictorial representations. However, an interaction term between spatial skills and content and pedagogical knowledge did correlate significantly with the use of pictorial representations. Teacher experience as measured by the number of years of teaching and highest degree did not appear to affect the relationships among the variables with the exception of the relationship between spatial skills and teacher content and pedagogical knowledge. Teachers with better spatial skills are also likely to use representational gestures and to show better content and pedagogical knowledge during instruction. Spatial skills predict pictorial representation use only as a function of content and pedagogical knowledge. © 2017 The British Psychological Society.

The Tölz Temporal Topography Study: mapping the visual field across the life span. Part II: cognitive factors shaping visual field maps.

PubMed

Poggel, Dorothe A; Treutwein, Bernhard; Calmanti, Claudia; Strasburger, Hans

2012-08-01

Part I described the topography of visual performance over the life span. Performance decline was explained only partly by deterioration of the optical apparatus. Part II therefore examines the influence of higher visual and cognitive functions. Visual field maps for 95 healthy observers of static perimetry, double-pulse resolution (DPR), reaction times, and contrast thresholds, were correlated with measures of visual attention (alertness, divided attention, spatial cueing), visual search, and the size of the attention focus. Correlations with the attentional variables were substantial, particularly for variables of temporal processing. DPR thresholds depended on the size of the attention focus. The extraction of cognitive variables from the correlations between topographical variables and participant age substantially reduced those correlations. There is a systematic top-down influence on the aging of visual functions, particularly of temporal variables, that largely explains performance decline and the change of the topography over the life span.

Turbulent dispersal promotes species coexistence

PubMed Central

Berkley, Heather A; Kendall, Bruce E; Mitarai, Satoshi; Siegel, David A

2010-01-01

Several recent advances in coexistence theory emphasize the importance of space and dispersal, but focus on average dispersal rates and require spatial heterogeneity, spatio-temporal variability or dispersal-competition tradeoffs to allow coexistence. We analyse a model with stochastic juvenile dispersal (driven by turbulent flow in the coastal ocean) and show that a low-productivity species can coexist with a high-productivity species by having dispersal patterns sufficiently uncorrelated from those of its competitor, even though, on average, dispersal statistics are identical and subsequent demography and competition is spatially homogeneous. This produces a spatial storage effect, with an ephemeral partitioning of a ‘spatial niche’, and is the first demonstration of a physical mechanism for a pure spatiotemporal environmental response. ‘Turbulent coexistence’ is widely applicable to marine species with pelagic larval dispersal and relatively sessile adult life stages (and perhaps some wind-dispersed species) and complements other spatial and temporal storage effects previously documented for such species. PMID:20455921

Modeling Spatial and Temporal Variability of Residential Air Exchange Rates for the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

EPA Science Inventory

Air pollution health studies often use outdoor concentrations as exposure surrogates. Failure to account for variability of residential infiltration of outdoor pollutants can induce exposure errors and lead to bias and incorrect confidence intervals in health effect estimates. Th...

Mars ozone: Mariner 9 revisited

NASA Technical Reports Server (NTRS)

Lindner, Bernhard Lee

1994-01-01

The efficacy of the UV spectroscopy technique used by Mariner 9 to remotely measure ozone abundance at Mars is discussed. Previously-inferred ozone abundances could be underestimated by as much as a factor of 3, and much of the observed variability in the ozone abundance could be due to temporal and spatial variability in cloud and dust amount.

Fluvial processes in Puget Sound rivers and the Pacific Northwest [Chapter 3

Treesearch

John M. Buffington; Richard D. Woodsmith; Derek B. Booth; David R. Montgomery

2003-01-01

The variability of topography, geology, climate; vegetation, and land use in the Pacific Northwest creates considerable spatial and temporal variability of fluvial processes and reach-scale channel type. Here we identify process domains of typical Pacific Northwest watersheds and examine local physiographic and geologic controls on channel processes and response...

Variability of wildland fire emissions across the contiguous United States

Treesearch

YongQiang Liu

2004-01-01

This study analyzes spatial and temporal variability of emissions from wildland fires across the contiguous US. The emissions are estimates based on a recently constructed dataset of historical fire records collected by multiple US governlnental agencies. Both wildfire and prescribed fires have the highest emissions over the Pacific coastal states. Prescribed fire...

Physical and geochemical drivers of CDOM variability near a natural seep site in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Edwards, C. R.; Powers, L.; Medeiros, P. M.

2016-02-01

Colored dissolved organic matter (CDOM) on the continental shelf and slope can serve as a marker for fresh water influence, indicate the presence of hydrocarbons, and provide important clues about nutrient content and organic matter cycling. Autonomous underwater vehicles such as gliders allow for subsurface measurement of CDOM fluorescence for weeks to months; these time series may be especially valuable in the northern Gulf of Mexico, where CDOM inputs of both terrestrial and oil and gas sources can be significant. Data from a recent glider deployment near a natural seep site (GC600) on the continental slope over 180km from shore suggest simultaneous influence of Mississippi plume water and hydrocarbon inputs in the upper 200m, with variability in fluorescence at a range of vertical and temporal scales. We will explore patterns in spatial and temporal variability of glider-measured hydrography, dissolved oxygen, and bio-optical data (CDOM, chlorophyll-a, backscatter fluorescence), and use their combination to infer a terrigenous and/or fossil fuel source(s). Taking advantage of a combination of satellite sea surface temperature, ocean color, wind, and data from moored and mobile platforms, we will examine physical controls on transport and vertical mixing of CDOM and the potential role of nonlinear mesoscale eddies, which can trap water in their interior and may transport river- or hydrocarbon-derived CDOM over long distances. The combined data set will be used to consider and potentially constrain the effect of photodegradation and other biogeochemical causes for CDOM fluorescence variability in the upper 200m.

Temporal variability of chlorophyll distribution in the Gulf of Mexico: bio-optical data from profiling floats

NASA Astrophysics Data System (ADS)

Pasqueron de Fommervault, Orens; Perez-Brunius, Paula; Damien, Pierre; Camacho-Ibar, Victor F.; Sheinbaum, Julio

2017-12-01

Chlorophyll concentration is a key oceanic biogeochemical variable. In the Gulf of Mexico (GOM), its distribution, which is mainly obtained from satellite surface observations and scarce in situ experiments, is still poorly understood. In 2011-2012, eight profiling floats equipped with biogeochemical sensors were deployed for the first time in the GOM and generated an unprecedented dataset that significantly increased the number of chlorophyll vertical distribution measurements in the region. The analysis of these data, once calibrated, permits us to reconsider the spatial and temporal variability of the chlorophyll concentration in the water column. At a seasonal scale, results confirm the surface signal seen by satellites, presenting maximum concentrations in winter and low values in summer. It is shown that the deepening of the mixed layer is the primary factor triggering the chlorophyll surface increase in winter. In the GOM, a possible interpretation is that this surface increase corresponds to a biomass increase. However, the present dataset suggests that the basin-scale climatological surface increase in chlorophyll content results from a vertical redistribution of subsurface chlorophyll and/or photoacclimation processes, rather than a net increase of biomass. One plausible explanation for this is the decoupling between the mixed-layer depth and the deep nutrient reservoir since mixed-layer depth only reaches the nitracline in sporadic events in the observations. Float measurements also provide evidence that the depth and the magnitude of the deep chlorophyll maximum is strongly controlled by the mesoscale variability, with higher chlorophyll biomass generally observed in cyclones rather than anticyclones.

Productivity in the barents sea--response to recent climate variability.

PubMed

Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.

Generalised synthesis of space-time variability in flood response: Dynamics of flood event types

NASA Astrophysics Data System (ADS)

Viglione, Alberto; Battista Chirico, Giovanni; Komma, Jürgen; Woods, Ross; Borga, Marco; Blöschl, Günter

2010-05-01

A analytical framework is used to characterise five flood events of different type in the Kamp area in Austria: one long-rain event, two short-rain events, one rain-on-snow event and one snowmelt event. Specifically, the framework quantifies the contributions of the space-time variability of rainfall/snowmelt, runoff coefficient, hillslope and channel routing to the flood runoff volume and the delay and spread of the resulting hydrograph. The results indicate that the components obtained by the framework clearly reflect the individual processes which characterise the event types. For the short-rain events, temporal, spatial and movement components can all be important in runoff generation and routing, which would be expected because of their local nature in time and, particularly, in space. For the long-rain event, the temporal components tend to be more important for runoff generation, because of the more uniform spatial coverage of rainfall, while for routing the spatial distribution of the produced runoff, which is not uniform, is also important. For the rain-on-snow and snowmelt events, the spatio-temporal variability terms typically do not play much role in runoff generation and the spread of the hydrograph is mainly due to the duration of the event. As an outcome of the framework, a dimensionless response number is proposed that represents the joint effect of runoff coefficient and hydrograph peakedness and captures the absolute magnitudes of the observed flood peaks.

Quantifying space-time dynamics of flood event types

NASA Astrophysics Data System (ADS)

Viglione, Alberto; Chirico, Giovanni Battista; Komma, Jürgen; Woods, Ross; Borga, Marco; Blöschl, Günter

2010-11-01

SummaryA generalised framework of space-time variability in flood response is used to characterise five flood events of different type in the Kamp area in Austria: one long-rain event, two short-rain events, one rain-on-snow event and one snowmelt event. Specifically, the framework quantifies the contributions of the space-time variability of rainfall/snowmelt, runoff coefficient, hillslope and channel routing to the flood runoff volume and the delay and spread of the resulting hydrograph. The results indicate that the components obtained by the framework clearly reflect the individual processes which characterise the event types. For the short-rain events, temporal, spatial and movement components can all be important in runoff generation and routing, which would be expected because of their local nature in time and, particularly, in space. For the long-rain event, the temporal components tend to be more important for runoff generation, because of the more uniform spatial coverage of rainfall, while for routing the spatial distribution of the produced runoff, which is not uniform, is also important. For the rain-on-snow and snowmelt events, the spatio-temporal variability terms typically do not play much role in runoff generation and the spread of the hydrograph is mainly due to the duration of the event. As an outcome of the framework, a dimensionless response number is proposed that represents the joint effect of runoff coefficient and hydrograph peakedness and captures the absolute magnitudes of the observed flood peaks.

Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China.

PubMed

Xiao, Yong; Gu, Xiaomin; Yin, Shiyang; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Niu, Yong

2016-01-01

Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R(2)) was applied to evaluate the accuracy of different methods. The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial-proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001-2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.

Measuring Spatial Variability of Vapor Flux to Characterize Vadose-zone VOC Sources: Flow-cell Experiments

DOE PAGES

Mainhagu, Jon; Morrison, C.; Truex, Michael J.; ...

2014-08-05

A method termed vapor-phase tomography has recently been proposed to characterize the distribution of volatile organic contaminant mass in vadose-zone source areas, and to measure associated three-dimensional distributions of local contaminant mass discharge. The method is based on measuring the spatial variability of vapor flux, and thus inherent to its effectiveness is the premise that the magnitudes and temporal variability of vapor concentrations measured at different monitoring points within the interrogated area will be a function of the geospatial positions of the points relative to the source location. A series of flow-cell experiments was conducted to evaluate this premise. Amore » well-defined source zone was created by injection and extraction of a non-reactive gas (SF6). Spatial and temporal concentration distributions obtained from the tests were compared to simulations produced with a mathematical model describing advective and diffusive transport. Tests were conducted to characterize both areal and vertical components of the application. Decreases in concentration over time were observed for monitoring points located on the opposite side of the source zone from the local–extraction point, whereas increases were observed for monitoring points located between the local–extraction point and the source zone. We found that the results illustrate that comparison of temporal concentration profiles obtained at various monitoring points gives a general indication of the source location with respect to the extraction and monitoring points.« less

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

Impact of Soil Moisture Dynamics on ASAR Observed Backscatters and its Spatial Variability over the Upstream of the Heihe River Basin, China

NASA Astrophysics Data System (ADS)

Wang, Shuguo

2013-01-01

The so called change detection method is a promising way to acquire soil moisture (SM) dynamics dependent on time series of radar backscatter (σ0) observations. The current study is a preceded step for using this method to carry out SM inversion at basin scale, in order to investigate the applicability of the change detection method in the Heihe River Basin, and to inspect the sensitivity of SAR signals to soil moisture variations. At the meantime, a prior knowledge of SM dynamics and land heterogeneities that may contribute to backscatter observations can be obtained. The impact of land surface states on spatial and temporal σ0 variability measured by ASAR has been evaluated in the upstream of the Heihe River Basin, which was one of the foci experimental areas (FEAs) in Watershed Allied Telemetry Experimental Research (WATER). Based on the in situ measurements provided by an automatic meteorological station (AMS) established at the A’rou site and time series of ASAR observations focused on a 1 km2 area, the relationships between the temporal dynamics of σ0 with in situ SM variations, and land heterogeneities of the study area according to the characteristics of spatial variability of σ0, were identified. The in situ measurements of soil moisture and temperature show a very clear seasonal freeze/thaw cycle in the study site. The temporal σ0 evolvement is basically coherent with ground measurements.

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

NASA Technical Reports Server (NTRS)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Productivity in the Barents Sea - Response to Recent Climate Variability

PubMed Central

Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513