Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

Litigation Technical Support and Services Rocky Mountain Arsenal. Biota Remedial Investigation, Version 3.2. Volume 4

DTIC Science & Technology

1989-05-01

microbial activity, nutrient content and pH as well as suspended sediment load, sedimentation rate- and other variables (in Eisler 1987 , p. 7). The...2.3-1 Study Area Boundaries 2-17 2.3-2 Vegetation Map of Rocky Mountain Arsenal 2-18 2.3-3 Raptor Nests Located on RMA in 1986 and 1987 2-24 3.2-1 RMA...Observations, Winter 1986- 1987 5-330 1 5.3-5 Rocky Mountain Arsenal Bald Eagle Feeding Observations, Winter, 1987 -1988 5-331 i I I i i i I i I I I I C-R,•A

GEOLAND2 global LAI, FAPAR Essential Climate Variables for terrestrial carbon modeling: principles and validation

NASA Astrophysics Data System (ADS)

Baret, F.; Weiss, M.; Lacaze, R.; Camacho, F.; Smets, B.; Pacholczyk, P.; Makhmara, H.

2010-12-01

LAI and fAPAR are recognized as Essential Climate Variables providing key information for the understanding and modeling of canopy functioning. Global remote sensing observations at medium resolution are routinely acquired since the 80’s mainly with AVHRR, SEAWIFS, VEGETATION, MODIS and MERIS sensors. Several operational products have been derived and provide global maps of LAI and fAPAR at daily to monthly time steps. Inter-comparison between MODIS, CYCLOPES, GLOBCARBON and JRC-FAPAR products showed generally consistent seasonality, while large differences in magnitude and smoothness may be observed. One of the objectives of the GEOLAND2 European project is to develop such core products to be used in a range of application services including the carbon monitoring. Rather than generating an additional product from scratch, the version 1 of GEOLAND2 products was capitalizing on the existing products by combining them to retain their pros and limit their cons. For these reasons, MODIS and CYCLOPES products were selected since they both include LAI and fAPAR while having relatively close temporal sampling intervals (8 to 10 days). GLOBCARBON products were not used here because of the too long monthly time step inducing large uncertainties in the seasonality description. JRC-FAPAR was not selected as well to preserve better consistency between LAI and fAPAR products. MODIS and CYCLOPES products were then linearly combined to take advantage of the good performances of CYCLOPES products for low to medium values of LAI and fAPAR while benefiting from the better MODIS performances for the highest LAI values. A training database representative of the global variability of vegetation type and conditions was thus built. A back-propagation neural network was then calibrated to estimate the new LAI and fAPAR products from VEGETATION preprocessed observations. Similarly, the vegetation cover fraction (fCover) was also derived by scaling the original CYCLOPES fCover products. Validation results achieved following the principles proposed by CEOS-LPV show that the new product called GEOV1 behaves as expected with good performances over the whole range of LAI and fAPAR in a temporally smooth and spatially consistent manner. These products will be processed and delivered by VITO in near real time at 1 km spatial resolution and 10 days frequency using a pre-operational production quality tracking system. The entire VEGETATION archive, from 1999 will be processed to provide a consistent time series over both VEGETATION sensors at the same spatial and temporal sampling. A climatology of products computed over the VEGETATION period will be also delivered at the same spatial and temporal sampling, showing average values, between year variability and possible trends over the decade. Finally, the VEGETATION derived time series starting back to 1999 will be completed with consistent products at 4 km spatial resolution derived from the NOAA/AVHRR series to cover the 1981-2010 period.

Selected Vegetables/Sun's Soup (PDQ®)—Patient Version

Cancer.gov

Expert-reviewed information summary about the use of selected vegetables/Sun's soup as a treatment for people with cancer. Note: The information in this summary is no longer being updated and is provided for reference purposes only.

GLEAM version 3: Global Land Evaporation Datasets and Model

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

2015-12-01

Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ observations. It is also shown that the performance of the revised model is higher compared to the original one.

Physical exercise, vegetable and fruit intake and health-related quality of life in Chinese breast cancer survivors: a cross-sectional study.

PubMed

Gong, Xiao-Huan; Wang, Ji-Wei; Li, Jiang; Chen, Xue-Fen; Sun, Li; Yuan, Zheng-Ping; Yu, Jin-Ming

2017-06-01

Breast cancer has long-term effects on health-related quality of life (HRQOL) of cancer survivors after treatment. Few research studies have focused on the association between health behaviors and HRQOL of Chinese breast cancer survivors (BCS). The aim of this study was to examine the separate and combined influence of physical exercise, vegetable and fruit intake on health-related quality of life of BCS. A cross-sectional study was conducted among BCS from April to July 2013, in Shanghai, China. Data were collected using a self-reported questionnaire, which included questions about basic socio-demographic characteristics, health conditions and treatments, health behaviors and HRQOL. HRQOL was measured using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core30 (EORTC QLQ-C30) simplified Chinese V3.0 version and the Functional Assessment of Cancer Therapy-General (FACT-G) simplified Chinese 4th version. Multiple linear regression models were performed to estimate the effects of physical exercise, vegetable and fruit intake as well as the effects of health behavior patterns on HRQOL adjusting for potential confounding variables. Exercisers reported significantly higher scores in most HRQOL dimensions than non-exercisers. Participants who ate more than 250 g of vegetables reported significantly higher scores in most HRQOL dimensions than participants who ate equal or less than 250 g of vegetables. Participants who ate fruit every day reported significantly higher scores in all HRQOL dimensions than those who did not eat fruit every day (P Adjusted  ≤ 0.032), except symptom subscales. All subscale scores and total scores of HRQOL, except symptom subscales, were positively associated with the number of adopted healthy lifestyle behaviors (P Trend  ≤ 0.003). Compared to participants who adopted only one healthy behavior, participants who adopted two or three healthy behaviors both reported significantly higher HRQOL scores. Physical exercise, enough vegetable and fruit intake are positively associated with HRQOL of BCS. BCS who adopted several healthy behaviors simultaneously had better HRQOL than one healthy behavior alone. Healthy behaviors, including engagement in exercise, proper diet, especially comprehensive lifestyle behavior interventions, should be valued in improving HRQOL of BCS.

Selected Vegetables/Sun's Soup (PDQ®)—Health Professional Version

Cancer.gov

Expert-reviewed information summary about the use of selected vegetables/Sun's soup as a treatment for people with cancer. Note: The information in this summary is no longer being updated and is provided for reference purposes only.

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Landcover change and light pollution in Kota Bandarlampung

NASA Astrophysics Data System (ADS)

Rohman, Akmal F.; Hafidz, Muhammad; Hazairin, Azra Q.; Riadini, Fitri

2016-10-01

Excessive emission of light or light pollution at night is one of the elements of environmental pollution. Indirectly light pollution causes increase of fossil fuel use, greenhouse gasses and pollution in the atmosphere. Direct effects of light pollution including: disturbance of animals life, human's psychology and environmental degradation. Light pollution in an area is related with the existence of built-up area and the lack of vegetation as a manifestation of economic and population growth. This research aims to know the relation of land cover changes with light pollution in Bandar Lampung and surrounding with 40 km radius over the last ten years. This research used satellite imagery to obtained data and later does the verification and accuracy tests on the field. The variables used in this research include light pollution radiance value, percentages in the built-up area and vegetation density. Light pollution radiance value is obtained from DMSP-OLS Version 4 satellite images, while the changes of built up and vegetation density data obtained from NDBI dan NDVI from Landsat 8 satellite images. The research area is divided into a grid with a size of 30"×30" which is the same as spatial resolution of DMSP. From sample grids, regression analysis between the percentage of light pollution radiance value with the percentage of NDVI and NDBI index on each grids. The percentages of built up areas and vegetation has 58 % of fair correlation with light emission.

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

Evaluation of improved land use and canopy representation in ...

EPA Pesticide Factsheets

Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp

Evaluating the interior thermal performance of mosques in the tropical environment

NASA Astrophysics Data System (ADS)

Nordin, N. I.; Misni, A.

2018-02-01

This study introduces the methodology applied in conducting data collection and data analysis. Data collection is the process of gathering and measuring information on targeted variables in an established systematic method. Qualitative and quantitative methods are combined in collecting data from government departments, site experiments and observation. Furthermore, analysing the indoor thermal performance data in the heritage and new mosques were used thermal monitoring tests, while validation will be made by meteorology data. Origin 8 version of the software is used to analyse all the data. Comparison techniques were applied to analyse several factors that influence the indoor thermal performance of mosques, namely building envelope include floor area, opening, and material used. Building orientation, location, surrounding vegetation and water elements are also recorded as supported building primary data. The comparison of primary data using these variables for four mosques include heritage and new buildings were revealed.

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten

2016-05-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

A further assessment of vegetation feedback on decadal Sahel rainfall variability

NASA Astrophysics Data System (ADS)

Kucharski, Fred; Zeng, Ning; Kalnay, Eugenia

2013-03-01

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM ("SPEEDY") is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.

2011 spring drought in France : Evaluation of the SURFEX land surface model.

NASA Astrophysics Data System (ADS)

Lafont, S.; Barbu, A.; Szczypta, C.; Carrer, D.; Delire, C.; Calvet, J.-C.

2012-04-01

The spring of the year 2011 has been exceptionally dry in Western Europe. Over France, May 2011 has been one of the driest over the last 50 years. This event had a marked impact on vegetation development leading to very low value of the Leaf Area Index (LAI) during the growing season . In contrast, July 2011 has been in general wet and cold allowing a new vegetation development. This extreme event, followed by higher than normal rainfall is an excellent case-study to evaluate the capacity of a land surface model to simulate the drought impact on vegetation, and vegetation recovery after a drought. In this study, we used the SURFEX land surface model, in its ISBA-CC (CC stands for Carbon Cycle) configuration. The ISBA-CC version simulates the vegetation carbon cycle, interactive LAI and the carbon accumulation in wood and in the soil organic matter. This model is used by the GEOLAND2 Land Carbon Core Information Service. We performed 20-years simulations of SURFEX at high resolution (8 km) with atmospheric forcing from the SAFRAN dataset, an operational product over France. The vegetation map is provided by the ECOCLIMAP2 database. Following previous work that have confirmed a good simulation of the LAI inter-annual variability, this study investigates the ability of the model of reproducing the observed anomalies of LAI in 2011, in terms of timing and spatial patterns. We compare the simulated LAI with long time series (10 yr) of LAI derived from Earth Observation product within GEOLAND2 BIOPAR project. We quantify the anomalies of energy, water and carbon fluxes. We investigate the robustness of these results and the impact of modifying several important sub-modules of the model: soil texture, photosynthesis, and rainfall interception.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Human impact on wildfires varies between regions and with vegetation productivity

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Kloster, Silvia

2017-11-01

We assess the influence of humans on burned area simulated with a dynamic global vegetation model. The human impact in the model is based on population density and cropland fraction, which were identified as important drivers of burned area in analyses of global datasets, and are commonly used in global models. After an evaluation of the sensitivity to these two variables we extend the model by including an additional effect of the cropland fraction on the fire duration. The general pattern of human influence is similar in both model versions: the strongest human impact is found in regions with intermediate productivity, where fire occurrence is not limited by fuel load or climatic conditions. Human effects in the model increases burned area in the tropics, while in temperate regions burned area is reduced. While the population density is similar on average for the tropical and temperate regions, the cropland fraction is higher in temperate regions, and leads to a strong suppression of fire. The model shows a low human impact in the boreal region, where both population density and cropland fraction is very low and the climatic conditions, as well as the vegetation productivity limit fire. Previous studies attributed a decrease in fire activity found in global charcoal datasets to human activity. This is confirmed by our simulations, which only show a decrease in burned area when the human influence on fire is accounted for, and not with only natural effects on fires. We assess how the vegetation-fire feedback influences the results, by comparing simulations with dynamic vegetation biogeography to simulations with prescribed vegetation. The vegetation-fire feedback increases the human impact on burned area by 10% for present day conditions. These results emphasize that projections of burned area need to account for the interactions between fire, climate, vegetation and humans.

Comparison modeling for alpine vegetation distribution in an arid area.

PubMed

Zhou, Jihua; Lai, Liming; Guan, Tianyu; Cai, Wetao; Gao, Nannan; Zhang, Xiaolong; Yang, Dawen; Cong, Zhentao; Zheng, Yuanrun

2016-07-01

Mapping and modeling vegetation distribution are fundamental topics in vegetation ecology. With the rise of powerful new statistical techniques and GIS tools, the development of predictive vegetation distribution models has increased rapidly. However, modeling alpine vegetation with high accuracy in arid areas is still a challenge because of the complexity and heterogeneity of the environment. Here, we used a set of 70 variables from ASTER GDEM, WorldClim, and Landsat-8 OLI (land surface albedo and spectral vegetation indices) data with decision tree (DT), maximum likelihood classification (MLC), and random forest (RF) models to discriminate the eight vegetation groups and 19 vegetation formations in the upper reaches of the Heihe River Basin in the Qilian Mountains, northwest China. The combination of variables clearly discriminated vegetation groups but failed to discriminate vegetation formations. Different variable combinations performed differently in each type of model, but the most consistently important parameter in alpine vegetation modeling was elevation. The best RF model was more accurate for vegetation modeling compared with the DT and MLC models for this alpine region, with an overall accuracy of 75 % and a kappa coefficient of 0.64 verified against field point data and an overall accuracy of 65 % and a kappa of 0.52 verified against vegetation map data. The accuracy of regional vegetation modeling differed depending on the variable combinations and models, resulting in different classifications for specific vegetation groups.

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Kimes, Daniel S.; Nelson, Ross F.

1998-01-01

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity

NASA Astrophysics Data System (ADS)

Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego

2015-04-01

Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity over the last two decades. The co-variability of a range of climate oscillation indices and newly-derived records of fluorescence and vegetation optical depth is analyzed using a statistical framework based on correlations, bootstrapping and Empirical Orthogonal Functions (EOFs). Results will enable us to characterize regional hotspots where particular climatic oscillations control vegetation productivity, as well as allowing us to underpin the climatic variables behind this control.

LDAS-Monde: Global scale satellite driven Land Data Assimilation System based on SURFEX modelling platform

NASA Astrophysics Data System (ADS)

Munier, Simon; Albergel, Clément; Leroux, Delphine; Calvet, Jean-Christophe

2017-04-01

In the past decades, large efforts have been made to improve our understanding of the dynamics of the terrestrial water cycle, including vertical and horizontal water fluxes as well as water stored in the biosphere. The soil water content is closely related to the development of the vegetation, which is in turn closely related to the water and energy exchanges with the atmosphere (through evapotranspiration) as well as to carbon fluxes. Land Surface Models (LSMs) are usually designed to represent biogeophysical variables, such as Surface and Root Zone Soil Moisture (SSM, RZSM) or Leaf Area Index (LAI), in order to simulate water, energy and carbon fluxes at the interface between land and atmosphere. With the recent increase of satellite missions and derived products, LSMs can benefit from Earth Observations via Data Assimilation systems to improve their representation of different biogeophysical variables. This study, which is part of the eartH2Observe European project (http://www.earth2observe.eu), presents LDAS-Monde, a global Land Data Assimilation System using an implementation of the Simplified Extended Kalman Filter (SEKF) in the Météo-France's modelling platform (SURFEX). SURFEX is based on the coupling of the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (CTRIP). Two global operational datasets derived from satellite observations are assimilated simultaneously: (i) SSM from the ESA Climate Change Initiative and (ii) LAI from the Copernicus Global Land Service project. Atmospheric forcing used in SURFEX are derived from the ERA-Interim reanalysis and corrected from GPCC precipitations. The simulations are conducted at the global scale at a 1 degree spatial resolution over the period 2000-2014. An analysis of the model sensitivity to the assimilated observations is performed over different regions of the globe under various hydro-climatic conditions. The impact of the SEKF on different biogeophysical and hydrological variables is assessed. It is shown that the assimilation scheme greatly improves the representation of the observed variables (SSM and LAI) and that it effectively affects most of the other variables related to the terrestrial water and vegetation cycles. Future developments include the optimization of LDAS-Monde in order to improve the spatial resolution and then take full advantage of the potential of Earth Observations.

Selected Vegetables/Sun's Soup (PDQ®)—Health Professional Version

Cancer.gov

“Selected Vegetables” and “Sun’s Soup” refer to several different mixtures of vegetables and herbs that have been studied as treatments for cancer. Neither has been approved by the FDA for the treatment of cancer or any other medical condition. Get detailed information in this clinician summary.

Selected Vegetables/Sun's Soup (PDQ®)—Patient Version

Cancer.gov

“Selected Vegetables” and “Sun’s Soup” refer to several different mixtures of vegetables and herbs that have been studied as treatments for cancer. Neither has been approved by the FDA for the treatment of cancer or any other medical condition. Learn more in this expert-reviewed summary.

Semi-arid vegetation response to antecedent climate and water balance windows

USGS Publications Warehouse

Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

2016-01-01

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

CRMS vegetation analytical team framework: Methods for collection, development, and use of vegetation response variables

USGS Publications Warehouse

Cretini, Kari F.; Visser, Jenneke M.; Krauss, Ken W.; Steyer, Gregory D.

2011-01-01

This document identifies the main objectives of the Coastwide Reference Monitoring System (CRMS) vegetation analytical team, which are to provide (1) collection and development methods for vegetation response variables and (2) the ways in which these response variables will be used to evaluate restoration project effectiveness. The vegetation parameters (that is, response variables) collected in CRMS and other coastal restoration projects funded under the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) are identified, and the field collection methods for these parameters are summarized. Existing knowledge on community and plant responses to changes in environmental drivers (for example, flooding and salinity) from published literature and from the CRMS and CWPPRA monitoring dataset are used to develop a suite of indices to assess wetland condition in coastal Louisiana. Two indices, the floristic quality index (FQI) and a productivity index, are described for herbaceous and forested vegetation. The FQI for herbaceous vegetation is tested with a long-term dataset from a CWPPRA marsh creation project. Example graphics for this index are provided and discussed. The other indices, an FQI for forest vegetation (that is, trees and shrubs) and productivity indices for herbaceous and forest vegetation, are proposed but not tested. New response variables may be added or current response variables removed as data become available and as our understanding of restoration success indicators develops. Once indices are fully developed, each will be used by the vegetation analytical team to assess and evaluate CRMS/CWPPRA project and program effectiveness. The vegetation analytical teams plan to summarize their results in the form of written reports and/or graphics and present these items to CRMS Federal and State sponsors, restoration project managers, landowners, and other data users for their input.

Are we really "eating well with Canada's food guide"?

PubMed

Slater, Joyce J; Mudryj, Adriana N

2018-05-22

Canada's Food Guide (CFG) has been an important health promotion tool for over seventy years. The most recent version was released in 2007. This study examined Canadians' exposure to, knowledge, and use of CFG. Data came from the Canadian Community Health Survey's Rapid Response on the Awareness and Usage of Canada's Food Guide, which included 10,098 Canadians ≥12 y in all ten provinces. Questions were asked on familiarity, awareness and usage of CFG and Canada's Food Guide for First Nations, Inuit and Métis, as well as healthy eating principles and behaviours. Descriptive statistics and logistic regression were used to observe counts and differences among key demographic variables. More than 80% of Canadians have heard of CFG however significantly more women than men were aware of the Guide. Most knew that 'Vegetables and Fruit' had the most recommended servings and that dark green vegetables should be consumed daily; however fewer than half knew this of orange vegetables. Just under one third had a copy in their homes, and the most common sources for obtaining CFG were child's school and health professional/trainer. Those who consulted CFG recently were more likely to consume the recommended servings of vegetables and fruits, and to state that their eating habits were 'much better' than one year previously. CFG has "brand recognition" among Canadians however there are gaps between awareness and eating behaviours. The new Food Guide could consider additional dissemination tools including social media, videos and workbooks tailored to various age groups, demographic groups and settings.

Relationships between vegetation and terrain variables in southeastern Arizona. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Mouat, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Relationships were established between eight terrain variables and plant species and 31 vegetation types. Certain plant species are better than others for differentiating or discriminating groups of specified terrain variables. Certain terrain variables are better than others for differentiating or discriminating groups of vegetation types. Stepwise discriminant analysis was shown to be a useful tool in plant ecological studies.

A toolkit for determining historical eco-hydrological interactions

NASA Astrophysics Data System (ADS)

Singer, M. B.; Sargeant, C. I.; Evans, C. M.; Vallet-Coulomb, C.

2016-12-01

Contemporary climate change is predicted to result in perturbations to hydroclimatic regimes across the globe, with some regions forecast to become warmer and drier. Given that water is a primary determinant of vegetative health and productivity, we can expect shifts in the availability of this critical resource to have significant impacts on forested ecosystems. The subject is particularly complex in environments where multiple sources of water are potentially available to vegetation and which may also exhibit spatial and temporal variability. To anticipate how subsurface hydrological partitioning may evolve in the future and impact overlying vegetation, we require well constrained, historical data and a modelling framework for assessing the dynamics of subsurface hydrology. We outline a toolkit to retrospectively investigate dynamic water use by trees. We describe a synergistic approach, which combines isotope dendrochronology of tree ring cellulose with a biomechanical model, detailed climatic and isotopic data in endmember waters to assess the mean isotopic composition of source water used in annual tree rings. We identify the data requirements and suggest three versions of the toolkit based on data availability. We present sensitivity analyses in order to identify the key variables required to constrain model predictions and then develop empirical relationships for constraining these parameters based on climate records. We demonstrate our methodology within a Mediterranean riparian forest site and show how it can be used along with subsurface hydrological modelling to validate source water determinations, which are fundamental to understanding climatic fluctuations and trends in subsurface hydrology. We suggest that the utility of our toolkit is applicable in riparian zones and in a range of forest environments where distinct isotopic endmembers are present.

Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

2017-04-01

Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM and LAI increments throughout the model impacting soil moisture, terrestrial vegetation and water cycle, surface carbon and energy fluxes.

Terrestrial vegetation monitoring protocol for the Mediterranean Coast Network—Cabrillo National Monument, Channel Islands National Park, and Santa Monica Mountains National Recreation Area: Standard Operating Procedures, Version 1.0

USGS Publications Warehouse

Tiszler, John; Rodriguez, Dirk; Lombardo, Keith; Sagar, Tarja; Aguilar, Luis; Lee, Lena; Handley, Timothy; McEachern, A. Kathryn; Harrod Starcevich, Leigh Ann; Witter, Marti; Philippi, Tom; Ostermann-Kelm, Stacey

2016-01-01

These Standard Operating Procedures are one part of a two-part protocol for monitoring terrestrial vegetation in the Mediterranean Coast Network. The second part of the protocol is the narrative:Tiszler, J., D. Rodriguez, K. Lombardo, T. Sagar, L. Aguilar, L. Lee, T. Handley, K. McEachern, L. Starcevich, M. Witter, T. Philippi, and S. Ostermann-Kelm. 2016. Terrestrial vegetation monitoring protocol for the Mediterranean Coast Network—Cabrillo National Monument, Channel Islands National Park, and Santa Monica Mountains National Recreation Area: Narrative, version 1.0. Natural Resource Report NPS/MEDN/NRR—2016/1296. National Park Service, Fort Collins, Colorado.National parks in the Mediterranean Inventory and Monitoring Network:Cabrillo National Monument (CABR)Channel Islands National Park (CHIS)Santa Monica Mountains National Recreation Area (SAMO)

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

The GLAS Standard Data Products Specification-Data Dictionary, Version 1.0. Volume 15

NASA Technical Reports Server (NTRS)

Lee, Jeffrey E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document contains the data dictionary for the GLAS standard data products. It details the parameters present on GLAS standard data products. Each parameter is defined with a short name, a long name, units on product, type of variable, a long description and products that contain it. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. These products are distributed by the National Snow and Ice Data Center (NSDIC).

The LANDFIRE Total Fuel Change Tool (ToFuΔ) user’s guide

USGS Publications Warehouse

Smail, Tobin; Martin, Charley; Napoli, Jim

2011-01-01

LANDFIRE fuel data were originally developed from coarse-scale existing vegetation type, existing vegetation cover, existing vegetation height, and biophysical setting layers. Fire and fuel specialists from across the country provided input to the original LANDFIRE National (LF_1.0.0) fuel layers to help calibrate fuel characteristics on a more localized scale. The LANDFIRE Total Fuel Change Tool (ToFu∆) was developed from this calibration process. Vegetation is subject to constant change – and fuels are therefore also dynamic, necessitating a systematic method for reflecting changes spatially so that fire behavior can be accurately accessed. ToFuΔ allows local experts to quickly produce maps that spatially display any proposed fuel characteristics changes. ToFu∆ works through a Microsoft Access database to produce spatial results in ArcMap based on rule sets devised by the user that take into account the existing vegetation type (EVT), existing vegetation cover (EVC), existing vegetation height (EVH), and biophysical setting (BpS) from the LANDFIRE grid data. There are also options within ToFu∆ to add discrete variables in grid format through use of the wildcard option and for subdividing specific areas for different fuel characteristic assignments through the BpS grid. The ToFu∆ user determines the size of the area for assessment by defining a Management Unit, or “MU.” User-defined rule sets made up of EVT, EVC, EVH, and BpS layers, as well as any wildcard selections, are used to change or refine fuel characteristics within the MU. Once these changes have been made to the fuel characteristics, new grids are created for fire behavior analysis or planning. These grids represent the most common ToFu∆ output. ToFuΔ is currently under development and will continue to be updated in the future. The current beta version (0.12), released in March 2011, is compatible with Windows 7 and will be the last release until the fall of 2011.

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

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

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less

Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

NASA Astrophysics Data System (ADS)

Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

2017-04-01

The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already operational SNPP VIIRS Green Vegetation Fraction (GVF) global gridded 4km resolution. The ultimate goal is a global consistent set of global gridded land products at 1-km resolution to enable consistent use of the products in the full suite of global and regional NCEP land models. The new JPSS vegetation products system is scheduled to transition to operations in the fall of 2017.

Hidden vegetables: an effective strategy to reduce energy intake and increase vegetable intake in adults123

PubMed Central

Blatt, Alexandria D; Roe, Liane S

2011-01-01

Background: The overconsumption of energy-dense foods leads to excessive energy intakes. The substitution of low-energy-dense vegetables for foods higher in energy density can help decrease energy intakes but may be difficult to implement if individuals dislike the taste of vegetables. Objective: We investigated whether incorporating puréed vegetables to decrease the energy density of entrées at multiple meals reduced daily energy intakes and increased daily vegetable intakes. Design: In this crossover study, 20 men and 21 women ate ad libitum breakfast, lunch, and dinner in the laboratory once a week for 3 wk. Across conditions, entrées at meals varied in energy density from standard versions (100% condition) to reduced versions (85% and 75% conditions) by the covert incorporation of 3 or 4.5 times the amount of puréed vegetables. Entrées were accompanied by unmanipulated side dishes. Participants rated their hunger and fullness before and after meals. Results: Subjects consumed a consistent weight of foods across conditions of energy density; thus, the daily energy intake significantly decreased by 202 ± 60 kcal in the 85% condition (P < 0.001) and by 357 ± 47 kcal in the 75% condition (P < 0.0001). Daily vegetable consumption significantly increased from 270 ± 17 g of vegetables in the 100% condition to 487 ± 25 g of vegetables in the 75% condition (P < 0.0001). Despite the decreased energy intake, ratings of hunger and fullness did not significantly differ across conditions. Entrées were rated as similar in palatability across conditions. Conclusions: Large amounts of puréed vegetables can be incorporated into various foods to decrease the energy density. This strategy can lead to substantial reductions in energy intakes and increases in vegetable intakes. This trial was registered at clinicaltrials.gov as NCT01165086. PMID:21289225

Hidden vegetables: an effective strategy to reduce energy intake and increase vegetable intake in adults.

PubMed

Blatt, Alexandria D; Roe, Liane S; Rolls, Barbara J

2011-04-01

The overconsumption of energy-dense foods leads to excessive energy intakes. The substitution of low-energy-dense vegetables for foods higher in energy density can help decrease energy intakes but may be difficult to implement if individuals dislike the taste of vegetables. We investigated whether incorporating puréed vegetables to decrease the energy density of entrées at multiple meals reduced daily energy intakes and increased daily vegetable intakes. In this crossover study, 20 men and 21 women ate ad libitum breakfast, lunch, and dinner in the laboratory once a week for 3 wk. Across conditions, entrées at meals varied in energy density from standard versions (100% condition) to reduced versions (85% and 75% conditions) by the covert incorporation of 3 or 4.5 times the amount of puréed vegetables. Entrées were accompanied by unmanipulated side dishes. Participants rated their hunger and fullness before and after meals. Subjects consumed a consistent weight of foods across conditions of energy density; thus, the daily energy intake significantly decreased by 202 ± 60 kcal in the 85% condition (P < 0.001) and by 357 ± 47 kcal in the 75% condition (P < 0.0001). Daily vegetable consumption significantly increased from 270 ± 17 g of vegetables in the 100% condition to 487 ± 25 g of vegetables in the 75% condition (P < 0.0001). Despite the decreased energy intake, ratings of hunger and fullness did not significantly differ across conditions. Entrées were rated as similar in palatability across conditions. Large amounts of puréed vegetables can be incorporated into various foods to decrease the energy density. This strategy can lead to substantial reductions in energy intakes and increases in vegetable intakes. This trial was registered at clinicaltrials.gov as NCT01165086.

The importance of environment vs. disturbance in the vegetation mosaic of central Arizona

Treesearch

Cynthia D. Huebner; John L. Vankat

2003-01-01

The vegetation of central Arizona is a mosaic of four vegetation types: chaparral, chaparral grassland, woodland, and woodland grassland. We analysed ten environmental variables, three disturbance variables, and five disturbance indicators to answer the question: What is the relative importance of environment and disturbance in explaining the vegetation pattern of our...

Vegetation-terrain feature relationships in southeast Arizona

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Mouat, D. A.

1972-01-01

There are no author-identified significant results in this report. Studies of relationships of vegetation distribution to geomorphic characteristics of the landscape and of plant phenological patterns to vegetation identification of satellite imagery indicate that there exists positive relationships between certain plant species and certain terrain features. Not all species were found to exhibit positive relationships with all terrain feature variables, but enough positive relationships seem to exist to indicate that terrain feature variable-vegetation relationship studies have a definite place in plant ecological investigations. Even more importantly, the vegetation groups examined appeared to be successfully discriminated by the terrain feature variables. This would seem to indicate that spatial interpretations of vegetation groups may be possible. While vegetational distributions aren't determined by terrain feature differences, terrain features do mirror factors which directly influence vegetational response and hence distribution. As a result, those environmental features which can be readily and rapidly ascertained on relatively small-scale imagery may prove to be valuable indicators of vegetation distribution.

Variability of Phenology and Fluxes of Water and Carbon with Observed and Simulated Soil Moisture in the Ent Terrestrial Biosphere Model (Ent TBM Version 1.0.1.0.0)

NASA Technical Reports Server (NTRS)

Kim, Y.; Moorcroft, P. R.; Aleinov, Igor; Puma, M. J.; Kiang, N. Y.

2015-01-01

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan- Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Variability of phenology and fluxes of water and carbon with observed and simulated soil moisture in the Ent Terrestrial Biosphere Model (Ent TBM version 1.0.1.0.0)

NASA Astrophysics Data System (ADS)

Kim, Y.; Moorcroft, P. R.; Aleinov, I.; Puma, M. J.; Kiang, N. Y.

2015-12-01

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan-Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

Users guide to the Most Similar Neighbor Imputation Program Version 2

Treesearch

Nicholas L. Crookston; Melinda Moeur; David Renner

2002-01-01

The Most Similar Neighbor (MSN, Moeur and Stage 1995) program is used to impute attributes measured on some sample units to sample units where they are not measured. In forestry applications, forest stands or vegetation polygons are examples of sample units. Attributes from detailed vegetation inventories are imputed to sample units where that information is not...

Sea Level Affecting Marshes Model (SLAMM)‐New Functionality for Predicting Changes in Distribution of Submerged Aquatic Vegetation in Response to Sea Level Rise.Version 1.0

EPA Science Inventory

Submerged aquatic vegetation (SAV) is an ecologically important habitat world-wide. In Pacific Northwest (PNW) estuaries, SAV in the lower intertidal and shallow subtidal habitats are dominated by the native seagrass, Zostera marina also referred to as submerged aquatic vegetati...

Australian Defence Force Nutritional Requirements in the 21st Century (Version 1)

DTIC Science & Technology

2009-05-01

vegetables 240 1200 15 High starch 2 Tortilla bread, Instant beef noodles 100 1500 60 Bf Cereal 1 Fruit muesli mix (with milk powder) 70 1000 40...the thiamin in a wet dish (canned chicken and vegetables) and a dry food (beef noodle soup powder) had been degraded following two years storage at

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

Treesearch

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

2016-01-01

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

User's Guide to the Western Root Disease Model, Version 3.0

Treesearch

Susan J. Frankel

1998-01-01

Effects of Armillaria spp., Phellinus weirii, Heterobasidion annosum, or bark beetles on stand dynamics are represented by the Western Root Disease Model,Version 3.0. This model, which operates in conjunction with the Forest Vegetation Simulator, can be used to evaluate the effects of many silvicultural practices. This guide contains instructions for use, detailed...

[Reliability and validity of a Mexican version of the Pro Children Project questionnaire].

PubMed

Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A

2014-08-01

To determine the test-retest reliability, the internal consistency, and the predictive validity of the constructs of the Mexican version of the Pro Children Project questionnaire (PCHP) for assessing personal and environmental factors related to fruit and vegetable intake in 10-12 year-old schoolchildren. Test-retest design with a 14 days interval. A sample of 957 children completed the questionnaire with 82 items. The study was conducted at eight primary schools in 2012 in Ciudad Juarez, Chihuahua, Mexico. For all fruit constructs and vegetable constructs, the test-retest reliability was moderate (intraclass correlation coefficient (ICC) > 0.60). Cronbach s alpha values were from moderate to high (range of 0.54 to 0.92) similar to those in the original study. Values for predictive validity ranged from moderate to good with Spearman correlations between 0.23 and 0.60 for personal factors and between 0.14 and 0.40 for environmental factors. The results of the Mexican version of the PCHP questionnaire provide a sufficient reliability and validity for assessing personal and environmental factors of fruit and vegetable intake in 10-12 year old schoolchildren. Finally, implications to administer this instrument in scholar settings and guidelines for futures studies are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USA

USGS Publications Warehouse

Chastain, R.A.; Struckhoff, M.A.; He, H.S.; Larsen, D.R.

2008-01-01

A vegetation community map was produced for the Ozark National Scenic Riverways consistent with the association level of the National Vegetation Classification System. Vegetation communities were differentiated using a large array of variables derived from remote sensing and topographic data, which were fused into independent mathematical functions using a discriminant analysis classification approach. Remote sensing data provided variables that discriminated vegetation communities based on differences in color, spectral reflectance, greenness, brightness, and texture. Topographic data facilitated differentiation of vegetation communities based on indirect gradients (e.g., landform position, slope, aspect), which relate to variations in resource and disturbance gradients. Variables derived from these data sources represent both actual and potential vegetation community patterns on the landscape. A hybrid combination of statistical and photointerpretation methods was used to obtain an overall accuracy of 63 percent for a map with 49 vegetation community and land-cover classes, and 78 percent for a 33-class map of the study area.

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.

The Benefits of Latent Variable Modeling to Develop Norms for a Translated Version of a Standardized Scale

ERIC Educational Resources Information Center

Seo, Hyojeong; Shaw, Leslie A.; Shogren, Karrie A.; Lang, Kyle M.; Little, Todd D.

2017-01-01

This article demonstrates the use of structural equation modeling to develop norms for a translated version of a standardized scale, the Supports Intensity Scale-Children's Version (SIS-C). The latent variable norming method proposed is useful when the standardization sample for a translated version is relatively small to derive norms…

Planned development and evaluation protocol of two versions of a web-based computer-tailored nutrition education intervention aimed at adults, including cognitive and environmental feedback

PubMed Central

2014-01-01

Background Despite decades of nutrition education, the prevalence of unhealthy dietary patterns is still high and inequalities in intake between high and low socioeconomic groups still exist. Therefore, it is important to innovate and improve existing nutrition education interventions. This paper describes the development, design and evaluation protocol of a web-based computer-tailored nutrition education intervention for adults targeting fruit, vegetable, high-energy snack and fat intake. This intervention innovates existing computer-tailored interventions by not only targeting motivational factors, but also volitional and self-regulation processes and environmental-level factors. Methods/design The intervention development was guided by the Intervention Mapping protocol, ensuring a theory-informed and evidence-based intervention. Two versions of the intervention were developed: a basic version targeting knowledge, awareness, attitude, self-efficacy and volitional and self-regulation processes, and a plus version additionally addressing the home environment arrangement and the availability and price of healthy food products in supermarkets. Both versions consist of four modules: one for each dietary behavior, i.e. fruit, vegetables, high-energy snacks and fat. Based on the self-regulation phases, each module is divided into three sessions. In the first session, feedback on dietary behavior is provided to increase awareness, feedback on attitude and self-efficacy is provided and goals and action plans are stated. In the second session goal achievement is evaluated, reasons for failure are explored, coping plans are stated and goals can be adapted. In the third session, participants can again evaluate their behavioral change and tips for maintenance are provided. Both versions will be evaluated in a three-group randomized controlled trial with measurements at baseline, 1-month, 4-months and 9-months post-intervention, using online questionnaires. Both versions will be compared with a generic nutrition information control condition. The primary outcomes are fruit, vegetable, high-energy snack and fat intake. Discussion The evaluation study will provide insight into the short- and long-term efficacy of both intervention versions in adults. Additionally, differences in the efficacy among high- and low-educated people will be examined. If these interventions are effective, two well-developed interventions will become available for the implementation and promotion of healthy dietary patterns among both high- and low-educated adults in the Netherlands. Trial registration Dutch Trial Registry NTR3396. PMID:24438381

Planned development and evaluation protocol of two versions of a web-based computer-tailored nutrition education intervention aimed at adults, including cognitive and environmental feedback.

PubMed

Springvloet, Linda; Lechner, Lilian; Oenema, Anke

2014-01-17

Despite decades of nutrition education, the prevalence of unhealthy dietary patterns is still high and inequalities in intake between high and low socioeconomic groups still exist. Therefore, it is important to innovate and improve existing nutrition education interventions. This paper describes the development, design and evaluation protocol of a web-based computer-tailored nutrition education intervention for adults targeting fruit, vegetable, high-energy snack and fat intake. This intervention innovates existing computer-tailored interventions by not only targeting motivational factors, but also volitional and self-regulation processes and environmental-level factors. The intervention development was guided by the Intervention Mapping protocol, ensuring a theory-informed and evidence-based intervention. Two versions of the intervention were developed: a basic version targeting knowledge, awareness, attitude, self-efficacy and volitional and self-regulation processes, and a plus version additionally addressing the home environment arrangement and the availability and price of healthy food products in supermarkets. Both versions consist of four modules: one for each dietary behavior, i.e. fruit, vegetables, high-energy snacks and fat. Based on the self-regulation phases, each module is divided into three sessions. In the first session, feedback on dietary behavior is provided to increase awareness, feedback on attitude and self-efficacy is provided and goals and action plans are stated. In the second session goal achievement is evaluated, reasons for failure are explored, coping plans are stated and goals can be adapted. In the third session, participants can again evaluate their behavioral change and tips for maintenance are provided. Both versions will be evaluated in a three-group randomized controlled trial with measurements at baseline, 1-month, 4-months and 9-months post-intervention, using online questionnaires. Both versions will be compared with a generic nutrition information control condition. The primary outcomes are fruit, vegetable, high-energy snack and fat intake. The evaluation study will provide insight into the short- and long-term efficacy of both intervention versions in adults. Additionally, differences in the efficacy among high- and low-educated people will be examined. If these interventions are effective, two well-developed interventions will become available for the implementation and promotion of healthy dietary patterns among both high- and low-educated adults in the Netherlands. Dutch Trial Registry NTR3396.

Household food insecurity and food expenditure in Bolivia, Burkina Faso, And the Philippines.

PubMed

Melgar-Quinonez, Hugo R; Zubieta, Ana C; MkNelly, Barbara; Nteziyaremye, Anastase; Gerardo, Maria Filipinas D; Dunford, Christopher

2006-05-01

This study examined the association between food insecurity, determined by a modified version of the U.S. Household Food Security Survey Module (US HFSSM), and total daily per capita (DPC) consumption (measured as household expenditures) in Bolivia, Burkina Faso, and the Philippines. Household food insecurity was determined by an adapted 9-item US HFSSM version. A short version of the World Bank's Living Standards Measurement Study (LSMS) consumption module measured household expenditures. Focus groups were used to adapt the survey instrument to each local context. The sample (n approximately 330 per country) includes residents of urban and rural areas. A 12-month food expenditure aggregate was generated as part of the total household expenditures calculation. DPC food expenditure, which represented over 60% of the total household consumption, as well as expenditures on specific food groups correlated with food insecurity both as a continuous Food Insecurity Score (FinSS) and a tricategorical food insecurity status variable. ANOVA and regression analysis were executed adjusting for social and demographic covariates. Food-secure households have significantly higher (P < 0.05) total DPC food expenditures as well as expenditures on animal source foods, vegetables, and fats and oils than moderately and severely food-insecure households. The results offer evidence that the US HFSSM is able to discriminate between households at different levels of food insecurity status in diverse developing world settings.

Predicting use of ineffective vegetable parenting practices with the Model of Goal Directed Behavior.

PubMed

Baranowski, Tom; Beltran, Alicia; Chen, Tzu-An; Thompson, Debbe; O'Connor, Teresia; Hughes, Sheryl; Diep, Cassandra; Baranowski, Janice C

2015-04-01

Increasing a parent's ability to influence a child's vegetable intake may require reducing the parent's use of ineffective vegetable parenting practices. The present study was designed to understand the psychosocial influences on ineffective vegetable parenting practices. A cross-sectional web-based survey was conducted to model use of ineffective vegetable parenting practices using validated scales from a Model of Goal Directed Vegetable Parenting Practices. The dependent variable was a composite ineffective vegetable parenting practices index. The independent variables included validated subscales of intention, habit, perceived barriers, desire, competence, autonomy, relatedness, attitudes, norms, perceived behavioural control and anticipated emotions. Models were analysed using block regression with backward deletion. Parents of 307 pre-school children (3-5 years old). Variables significantly positively related to ineffective vegetable parenting practices in order of relationship strength included habit of controlling vegetable practices (standardized β=0·349, P<0·0001) and desire (standardized β=0·117, P=0·025). Variables significantly negatively related to ineffective vegetable parenting practices in order of relationship strength included perceived behavioural control of negative parenting practices (standardized β=-0·215, P<0000), the habit of active child involvement in vegetable selection (standardized β=-0·142, P=0·008), anticipated negative parent emotional response to child vegetable refusal (standardized β=-0·133, P=0·009), autonomy (standardized β=-0·118, P=0.014), attitude about negative effects of vegetables (standardized β=-0·118, P=0·015) and descriptive norms (standardized β=-0·103, P=0·032). The model accounted for 40·5 % of the variance in use of ineffective vegetable parenting practices. The present study is the first report of psychometrically tested scales to predict use of ineffective vegetable parenting practices. Innovative intervention procedures will need to be designed and tested to reduce ineffective vegetable parenting practices.

Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

USGS Publications Warehouse

Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

2018-01-01

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

A novel assessment of the role of land-use and land-cover change in the global carbon cycle, using a new Dynamic Global Vegetation Model version of the CABLE land surface model

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Smith, Benjamin; Nieradzik, Lars; Briggs, Peter; Canadell, Josep

2017-04-01

In recent decades, terrestrial ecosystems have sequestered around 1.2 PgC y-1, an amount equivalent to 20% of fossil-fuel emissions. This land carbon flux is the net result of the impact of changing climate and CO2 on ecosystem productivity (CO2-climate driven land sink ) and deforestation, harvest and secondary forest regrowth (the land-use change (LUC) flux). The future trajectory of the land carbon flux is highly dependent upon the contributions of these processes to the net flux. However their contributions are highly uncertain, in part because the CO2-climate driven land sink and LUC components are often estimated independently, when in fact they are coupled. We provide a novel assessment of global land carbon fluxes (1800-2015) that integrates land-use effects with the effects of changing climate and CO2 on ecosystem productivity. For this, we use a new land-use enabled Dynamic Global Vegetation Model (DGVM) version of the CABLE land surface model, suitable for use in attributing changes in terrestrial carbon balance, and in predicting changes in vegetation cover and associated effects on land-atmosphere exchange. In this model, land-use-change is driven by prescribed gross land-use transitions and harvest areas, which are converted to changes in land-use area and transfer of carbon between pools (soil, litter, biomass, harvested wood products and cleared wood pools). A novel aspect is the treatment of secondary woody vegetation via the coupling between the land-use module and the POP (Populations Order Physiology) module for woody demography and disturbance-mediated landscape heterogeneity. Land-use transitions to and from secondary forest tiles modify the patch age distribution within secondary-vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. The resulting secondary forest patch age distribution also influences the magnitude of the secondary forest harvest and clearance fluxes, with oldest patches (high biomass) being preferentially harvested, and youngest patches (low biomass) being preferentially cleared. Our results, which agree well with the net land flux derived from the global carbon budget, are used for a process-attribution of the land carbon sink. Use of multiple constraints provides confidence in our process-attribution: we use observation-based data sets to evaluate predictions of global spatial distributions of vegetation cover, evaporation, gross primary production, biomass and soil carbon; interannual variability of the global terrestrial carbon sink; forest allometric relations and age-effects on net primary production.

Access to Fresh Fruits and Vegetables in School Lunches: A Policy Analysis.

PubMed

Schultz, Celeste; Thorlton, Janet

2018-01-01

Consumption of fresh fruits and vegetables helps to reduce childhood obesity and improves academic achievement and attendance. However, providing fresh fruits and vegetables is challenging for some schools due to cost, administrative burden, and concern for food waste. To address these challenges, the Fruit and Vegetable Access for Children Act proposes to allow federally funded programs to substitute fresh fruits and vegetables with canned, frozen, or pureed versions. In this policy analysis, we propose options for providing fresh fruits and vegetables to children enrolled in the National School Lunch Program. We recommend that school nurses actively facilitate the process of obtaining fresh fruits and vegetables by being appointed members of Team Nutrition giving them authority to collaborate with local famers, entrepreneurs, and land-grant universities in Farm to School Programs. This strategy empowers school nurses in promoting healthy eating habits, reducing obesity, and improving academic performance and school attendance.

Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment.

PubMed

Guay, Kevin C; Beck, Pieter S A; Berner, Logan T; Goetz, Scott J; Baccini, Alessandro; Buermann, Wolfgang

2014-10-01

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg ) series, and its recent successor version 3g (GIMMS3g ), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg ), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg , particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment

PubMed Central

Guay, Kevin C; Beck, Pieter S A; Berner, Logan T; Goetz, Scott J; Baccini, Alessandro; Buermann, Wolfgang

2014-01-01

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg) series, and its recent successor version 3g (GIMMS3g), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg, particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas. PMID:24890614

Reductions in entrée energy density increase children's vegetable intake and reduce energy intake.

PubMed

Leahy, Kathleen E; Birch, Leann L; Fisher, Jennifer O; Rolls, Barbara J

2008-07-01

The energy density (ED; kcal/g) of an entrée influences children's energy intake (EI), but the effect of simultaneously changing both ED and portion size of an entrée on preschool children's EI is unknown. In this within-subject crossover study, 3- to 5-year-old children (30 boys, 31 girls) in a daycare facility were served a test lunch once/week for 4 weeks. The amount and type of vegetables and cheeses incorporated into the sauce of a pasta entrée were manipulated to create two versions that varied in ED by 25% (1.6 or 1.2 kcal/g). Across the weeks, each version of the entrée was served to the children in each of two portion sizes (400 or 300 g). Lunch, consumed ad libitum, also included carrots, applesauce, and milk. Decreasing ED of the entrée by 25% significantly (P<0.0001) reduced children's EI of the entrée by 25% (63.1+/-8.3 kcal) and EI at lunch by 17% (60.7+/-8.9 kcal). Increasing the proportion of vegetables in the pasta entrée increased children's vegetable intake at lunch by half of a serving of vegetables (P<0.01). Decreasing portion size of the entrée by 25% did not significantly affect children's total food intake or EI at lunch. Therefore, reducing the ED of a lunch entrée resulted in a reduction in children's EI from the entrée and from the meal in both portion size conditions. Decreasing ED by incorporating more vegetables into recipes is an effective way of reducing children's EI while increasing their vegetable intake.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

Reliability and validity of the Turkish version of the situational self-efficacy scale for fruit and vegetable consumption in adolescents.

PubMed

Kadioglu, Hasibe; Erol, Saime; Ergun, Ayse

2015-01-01

The purpose of this research was to examine the psychometric properties of the Turkish version of the situational self-efficacy scale for vegetable and fruit consumption in adolescents. This was a methodological study. The study was conducted in four public secondary schools in Istanbul, Turkey. Subjects were 1586 adolescents. Content and construct validity were assessed to test the validity of the scale. The reliability was assessed in terms of internal consistency and test-retest reliability. For confirmatory factor analysis, χ(2) statistics plus other fit indices were used, including the goodness-of-fit index, the adjusted goodness-of-fit index, the nonnormed fit index, the comparative fit index, the standardized root mean residual, and the root mean square error of approximation. Pearson's correlation was used for test-retest reliability and item total correlation. The internal consistency was assessed by using Cronbach α. Confirmatory factor analysis strongly supported the three-component structure representing positive social situations (α = .81), negative effect situations (α = .93), and difficult situations (α = .78). Psychometric analyses of the Turkish version of the situational self-efficacy scale indicate high reliability and good content and construct validity. Researchers and health professionals will find it useful to employ the Turkish situational self-efficacy scale in evaluating situational self-efficacy for fruit and vegetable consumption in Turkish adolescents.

Climatic effects of biogenic volatile organic compounds (BVOCs) emissions and associated feedbacks due to vegetation change in the boreal zone

NASA Astrophysics Data System (ADS)

Blichner, Sara Marie; Koren Berntsen, Terje; Stordal, Frode

2017-04-01

As our understanding of the earth system improves, it is becoming increasingly clear that vegetation and ecosystems are not only influenced by the atmosphere, but that changes in these also feed back to the atmosphere and induce changes here. One such feedback involves the emission of biogenic volatile organic compounds (BVOCs) emitted from vegetation. As BVOCs are oxidized, they become less volatile and contribute to aerosol growth and formation in the atmosphere, and can thus change the radiative balance of the atmosphere through both the direct and indirect aerosol effects. The amount and type of BVOCs emitted by vegetation depends on a myriad of variables; temperature, leaf area index (LAI), species, water availability and various types of stress (e.g. insects attacks). They generally increase with higher temperatures and under stress. These factors beg the question of how emissions will change in the future in response to both temperature increase and changes to vegetation patterns and densities. The boreal region is of particular interest because forest cover in general has been thought to have a warming effect due to trees reducing the albedo, especially when snow covers the ground. We investigate feedbacks through BVOC emissions related to the expected northward expansion of boreal forests in response to global warming with a development version of the Norwegian Earth System Model (NorESM). BVOC emissions are computed by the Model of Emissions of Gases and Aerosols from Nature 2.1 (MEGAN2.1) which is incorporated into the Community Land Model v4.5 (CLM4.5). The atmospheric component is CAM5.3-Oslo. We will present preliminary results of effects on clouds and aerosol concentrations resulting from a fixed poleward shift in boreal forests and compare the radiative effects of this to changes in surface energy fluxes. CO2-concentrations and sea surface temperatures are kept fixed in order to isolate the effects of the change in vegetation patterns. Finally, these results are compared to simulations of a future climate (corresponding to 2xCO2-concentrations) both with present-day and shifted vegetation patterns.

A COMPARISON OF THE SALINITY REGIME ALONG THE TEXAS COAST WITH TERRESTRIAL VEGETATION GREENNESS AND WATER USE IN THE GALVESTON BAY WATERSHED USING REMOTING SENSING

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (A VHRR) flown on NOAA satellites. NDVI variability was compared with reg...

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Trachsel, M.; Rehfeld, K.; Telford, R.; Laepple, T.

2017-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution.

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

PubMed Central

Triviño, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas; Araújo, Miguel B.

2011-01-01

Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. PMID:22216263

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Historic range of variability for upland vegetation in the Medicine Bow National Forest, Wyoming

Treesearch

Gregory K. Dillon; Dennis H. Knight; Carolyn B. Meyer

2005-01-01

An approach for synthesizing the results of ecological research pertinent to land management is the analysis of the historic range of variability (HRV) for key ecosystem variables that are affected by management activities. This report provides an HRV analysis for the upland vegetation of the Medicine Bow National Forest in southeastern Wyoming. The variables include...

Historic range of variability for upland vegetation in the Bighorn National Forest, Wyoming

Treesearch

Carolyn B. Meyer; Dennis H. Knight; Gregory K. Dillon

2005-01-01

An approach for synthesizing the results of ecological research pertinent to land management is the analysis of the historic range of variability (HRV) for key ecosystem variables that are affected by management activities. This report provides an HRV analysis for the upland vegetation of the Bighorn National Forest in northcentral Wyoming. The variables include live...

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Topography and climate are more important drivers of long-term, post-fire vegetation assembly than time-since-fire in the Sonoran Desert, US

USGS Publications Warehouse

Shryock, Daniel F.; Esque, Todd C.; Chen, Felicia

2015-01-01

We find substantial evidence that environmental filters, rather than TSF, drive the majority of variability in long-term, post-fire vegetation assembly within the Sonoran Desert. Careful consideration of spatial variability in abiotic conditions may benefit post-fire vegetation modelling, as well as fire management and restoration strategies.

Streamflow simulation for continental-scale river basins

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Lettenmaier, Dennis P.; Liang, Xu; Wetzel, Suzanne W.; Wood, Eric F.

1997-04-01

A grid network version of the two-layer variable infiltration capacity (VIC-2L) macroscale hydrologic model is described. VIC-2L is a hydrologically based soil- vegetation-atmosphere transfer scheme designed to represent the land surface in numerical weather prediction and climate models. The grid network scheme allows streamflow to be predicted for large continental rivers. Off-line (observed and estimated surface meteorological and radiative forcings) applications of the model to the Columbia River (1° latitude-longitude spatial resolution) and Delaware River (0.5° resolution) are described. The model performed quite well in both applications, reproducing the seasonal hydrograph and annual flow volumes to within a few percent. Difficulties in reproducing observed streamflow in the arid portion of the Snake River basin are attributed to groundwater-surface water interactions, which are not modeled by VIC-2L.

Perceptions of individual and community environmental influences on fruit and vegetable intake, North Carolina, 2004.

PubMed

Boyington, Josephine E A; Schoster, Britta; Remmes Martin, Kathryn; Shreffler, Jack; Callahan, Leigh F

2009-01-01

Increases in obesity and other chronic conditions continue to fuel efforts for lifestyle behavior changes. However, many strategies do not address the impact of environment on lifestyle behaviors, particularly healthy dietary intake. This study explored the perceptions of environment on intake of fruits and vegetables in a cohort of 2,479 people recruited from 22 family practices in North Carolina. Participants were administered a health and social demographic survey. Formative assessment was conducted on a subsample of 32 people by using focus groups, semistructured individual interviews, community mapping, and photographs. Interviews and discussions were transcribed and content was analyzed using ATLAS.ti version 5. Survey data were evaluated for means, frequencies, and group differences. The 2,479 participants had a mean age of 52.8 years, mean body mass index (BMI) of 29.4, and were predominantly female, white, married, and high school graduates. The 32 subsample participants were older, heavier, and less educated. Some prevalent perceptions about contextual factors related to dietary intake included taste-bud fatigue (boredom with commonly eaten foods), life stresses, lack of forethought in meal planning, current health status, economic status, the ability to garden, lifetime dietary exposure, concerns about food safety, contradictory nutrition messages from the media, and variable work schedules. Perceptions about intake of fruits and vegetables intake are influenced by individual (intrinsic) and community (extrinsic) environmental factors. We suggest approaches for influencing behavior and changing perceptions using available resources.

The FORWARD Project: Incorporating Long-Term Hydrologic Datasets Into Detailed Forest Management Plans for the Canadian Boreal Forest

NASA Astrophysics Data System (ADS)

Dinsmore, P.; Prepas, E.; Putz, G.; Smith, D.

2008-12-01

The Forest Watershed and Riparian Disturbance (FORWARD) Project has collected data on weather, soils, vegetation, streamflow and stream water quality under relatively undisturbed conditions, as well as after experimental forest harvest, in partnership with industrial forest operations within the Boreal Plain and Boreal Shield ecozones of Canada. Research-based contributions from FORWARD were integrated into our Boreal Plain industry partner's 2007-2016 Detailed Forest Management Plan. These contributions consisted of three components: 1) A GIS watershed and stream layer that included a hydrological network, a Digital Elevation Model, and Strahler classified streams and watersheds for 1st- and 3rd-order watersheds; 2) a combined soil and wetland GIS layer that included maps and associated datasets for relatively coarse mineral soils (which drain quickly) and wetlands (which retain water), which were the key features that needed to be identified for the FORWARD modelling effort; and 3) a lookup table was developed that permits planners to determine runoff coefficients (the variable selected for hydrological modelling) for 1st-order watersheds, based upon slope, vegetation and soil attributes in forest polygons. The lookup table was populated with output from the deterministic Soil and Water Assessment Tool (SWAT), adapted for boreal forest vegetation with a version of the plant growth model, ALMANAC. The runoff coefficient lookup table facilitated integration of predictions of hydrologic impacts of forest harvest into planning. This pilot-scale effort will ultimately be extended to the Boreal Shield study area.

Effects of a large wildfire on vegetation structure in a variable fire mosaic.

PubMed

Foster, C N; Barton, P S; Robinson, N M; MacGregor, C I; Lindenmayer, D B

2017-12-01

Management guidelines for many fire-prone ecosystems highlight the importance of maintaining a variable mosaic of fire histories for biodiversity conservation. Managers are encouraged to aim for fire mosaics that are temporally and spatially dynamic, include all successional states of vegetation, and also include variation in the underlying "invisible mosaic" of past fire frequencies, severities, and fire return intervals. However, establishing and maintaining variable mosaics in contemporary landscapes is subject to many challenges, one of which is deciding how the fire mosaic should be managed following the occurrence of large, unplanned wildfires. A key consideration for this decision is the extent to which the effects of previous fire history on vegetation and habitats persist after major wildfires, but this topic has rarely been investigated empirically. In this study, we tested to what extent a large wildfire interacted with previous fire history to affect the structure of forest, woodland, and heath vegetation in Booderee National Park in southeastern Australia. In 2003, a summer wildfire burned 49.5% of the park, increasing the extent of recently burned vegetation (<10 yr post-fire) to more than 72% of the park area. We tracked the recovery of vegetation structure for nine years following the wildfire and found that the strength and persistence of fire effects differed substantially between vegetation types. Vegetation structure was modified by wildfire in forest, woodland, and heath vegetation, but among-site variability in vegetation structure was reduced only by severe fire in woodland vegetation. There also were persistent legacy effects of the previous fire regime on some attributes of vegetation structure including forest ground and understorey cover, and woodland midstorey and overstorey cover. For example, woodland midstorey cover was greater on sites with higher fire frequency, irrespective of the severity of the 2003 wildfire. Our results show that even after a large, severe wildfire, underlying fire histories can contribute substantially to variation in vegetation structure. This highlights the importance of ensuring that efforts to reinstate variation in vegetation fire age after large wildfires do not inadvertently reduce variation in vegetation structure generated by the underlying invisible mosaic. © 2017 by the Ecological Society of America.

Identifying high production, low production and degraded rangelands in Senegal with normalized difference vegetation index data

USGS Publications Warehouse

Tappan, G. Gray; Wood, Lynette; Moore, Donald G.

1993-01-01

Seasonal herbaceous vegetation production on Senegal's native rangelands exhibits high spatial and temporal variability. This variability can be monitored using normalized difference vegetation index (NDVI) data computed from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) image data. Although annual fluctuations in rainfall account for some of the variability, numerous long-term production patterns are evident in the AVHRR time-series data. Different n productivity reflect variations in the region's climate, topography, soils, and land use. Areas of overgrazing and intensive cultivation have caused long-term soil and vegetation degradation. Rangelands of high and low productivity, and degraded rangelands were identified using NDVI. Time-series image data from 1987 though 1992 were used to map relative rangeland productivity. The results were compared to detailed resource maps on soils, vegetation and land use. Much of the variation in rangeland productivity correlated well to the known distribution of resources. The study developed an approach that identified a number of areas of degraded soils and low vegetation production.

Prediction of Success in External Cephalic Version under Tocolysis: Still a Challenge.

PubMed

Vaz de Macedo, Carolina; Clode, Nuno; Mendes da Graça, Luís

2015-01-01

External cephalic version is a procedure of fetal rotation to a cephalic presentation through manoeuvres applied to the maternal abdomen. There are several prognostic factors described in literature for external cephalic version success and prediction scores have been proposed, but their true implication in clinical practice is controversial. We aim to identify possible factors that could contribute to the success of an external cephalic version attempt in our population. We retrospectively examined 207 consecutive external cephalic version attempts under tocolysis conducted between January 1997 and July 2012. We consulted the department's database for the following variables: race, age, parity, maternal body mass index, gestational age, estimated fetal weight, breech category, placental location and amniotic fluid index. We performed descriptive and analytical statistics for each variable and binary logistic regression. External cephalic version was successful in 46.9% of cases (97/207). None of the included variables was associated with the outcome of external cephalic version attempts after adjustment for confounding factors. We present a success rate similar to what has been previously described in literature. However, in contrast to previous authors, we could not associate any of the analysed variables with success of the external cephalic version attempt. We believe this discrepancy is partly related to the type of statistical analysis performed. Even though there are numerous prognostic factors identified for the success in external cephalic version, care must be taken when counselling and selecting patients for this procedure. The data obtained suggests that external cephalic version should continue being offered to all eligible patients regardless of prognostic factors for success.

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

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

Meng, L.; Paudel, R.; Hess, P. G. M.

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

DOE PAGES

Meng, L.; Paudel, R.; Hess, P. G. M.; ...

2015-07-03

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

BehavePlus fire modeling system, version 5.0: Variables

Treesearch

Patricia L. Andrews

2009-01-01

This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables.

Treesearch

Jan A. Henderson; Robin D. Lesher; David H. Peter; Chris D. Ringo

2011-01-01

A gradient-analysis-based model and grid-based map are presented that use the potential vegetation zone as the object of the model. Several new variables are presented that describe the environmental gradients of the landscape at different scales. Boundary algorithms are conceptualized, and then defined, that describe the environmental boundaries between vegetation...

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

NASA Astrophysics Data System (ADS)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-10-01

While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database (NDP-017) (2001 version of original 1985 data)

DOE Data Explorer

Olsen, Jerry S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Watts, Julia A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Allison, Linda J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2001-01-01

In 1980, this data base and the corresponding map were completed after more than 20 years of field investigations, consultations, and analyses of published literature. They characterize the use and vegetative cover of the Earth's land surface with a 0.5° × 0.5° grid. This world-ecosystem-complex data set and the accompanying map provide a current reference base for interpreting the role of vegetation in the global cycling of CO2 and other gases and a basis for improved estimates of vegetation and soil carbon, of natural exchanges of CO2, and of net historic shifts of carbon between the biosphere and the atmosphere.

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas

2016-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.

Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

NASA Technical Reports Server (NTRS)

Ganguly, S.; Park, Taejin; Choi, Sungho; Bi, Jian; Knyazikhin, Yuri; Myneni, Ranga

2016-01-01

Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

Validation of Vegetation Index Time Series from Suomi NPP Visible Infrared Imaging Radiometer Suite Using Tower Radiation Flux Measurements

NASA Astrophysics Data System (ADS)

Miura, T.; Kato, A.; Wang, J.; Vargas, M.; Lindquist, M.

2015-12-01

Satellite vegetation index (VI) time series data serve as an important means to monitor and characterize seasonal changes of terrestrial vegetation and their interannual variability. It is, therefore, critical to ensure quality of such VI products and one method of validating VI product quality is cross-comparison with in situ flux tower measurements. In this study, we evaluated the quality of VI time series derived from Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft by cross-comparison with in situ radiation flux measurements at select flux tower sites over North America and Europe. VIIRS is a new polar-orbiting satellite sensor series, slated to replace National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer in the afternoon overpass and to continue the highly-calibrated data streams initiated with Moderate Resolution Imaging Spectrometer of National Aeronautics and Space Administration's Earth Observing System. The selected sites covered a wide range of biomes, including croplands, grasslands, evergreen needle forest, woody savanna, and open shrublands. The two VIIRS indices of the Top-of-Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI) and the atmospherically-corrected, Top-of-Canopy (TOC) Enhanced Vegetation Index (EVI) (daily, 375 m spatial resolution) were compared against the TOC NDVI and a two-band version of EVI (EVI2) calculated from tower radiation flux measurements, respectively. VIIRS and Tower VI time series showed comparable seasonal profiles across biomes with statistically significant correlations (> 0.60; p-value < 0.01). "Start-of-season (SOS)" phenological metric values extracted from VIIRS and Tower VI time series were also highly compatible (R2 > 0.95), with mean differences of 2.3 days and 5.0 days for the NDVI and the EVI, respectively. These results indicate that VIIRS VI time series can capture seasonal evolution of vegetated land surface as good as in situ radiometric measurements. Future studies that address biophysical or physiological interpretations of Tower VI time series derived from radiation flux measurements are desirable.

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).

Micro-topographic hydrologic variability due to vegetation acclimation under climate change

NASA Astrophysics Data System (ADS)

Le, P. V.; Kumar, P.

2012-12-01

Land surface micro-topography and vegetation cover have fundamental effects on the land-atmosphere interactions. The altered temperature and precipitation variability associated with climate change will affect the water and energy processes both directly and that mediated through vegetation. Since climate change induces vegetation acclimation that leads to shifts in evapotranspiration and heat fluxes, it further modifies microclimate and near-surface hydrological processes. In this study, we investigate the impacts of vegetation acclimation to climate change on micro-topographic hydrologic variability. The ability to accurately predict these impacts requires the simultaneous considerations of biochemical, ecophysiological and hydrological processes. A multilayer canopy-root-soil system model coupled with a conjunctive surface-subsurface flow model is used to capture the acclimatory responses and analyze the changes in dynamics of structure and connectivity of micro-topographic storage and in magnitudes of runoff. The study is performed using Light Detection and Ranging (LiDAR) topographic data in the Birds Point-New Madrid floodway in Missouri, U.S.A. The result indicates that both climate change and its associated vegetation acclimation play critical roles in altering the micro-topographic hydrological responses.

Functionally relevant climate variables for arid lands: Aclimatic water deficit approach for modelling desert shrub distributions

Treesearch

Thomas E. Dilts; Peter J. Weisberg; Camie M. Dencker; Jeanne C. Chambers

2015-01-01

We have three goals. (1) To develop a suite of functionally relevant climate variables for modelling vegetation distribution on arid and semi-arid landscapes of the Great Basin, USA. (2) To compare the predictive power of vegetation distribution models based on mechanistically proximate factors (water deficit variables) and factors that are more mechanistically removed...

USE OF REMOTELY SENSED DATA FOR PARAMETERIZING AND VALIDATING LAND-USE HYDROLOGIC MODELS

EPA Science Inventory

Variability in vegetation greenness was determined for the Galveston Bay watershed using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA satellites. NDVI variability was compared with regi...

Standardized principal components for vegetation variability monitoring across space and time

NASA Astrophysics Data System (ADS)

Mathew, T. R.; Vohora, V. K.

2016-08-01

Vegetation at any given location changes through time and in space. In what quantity it changes, where and when can help us in identifying sources of ecosystem stress, which is very useful for understanding changes in biodiversity and its effect on climate change. Such changes known for a region are important in prioritizing management. The present study considers the dynamics of savanna vegetation in Kruger National Park (KNP) through the use of temporal satellite remote sensing images. Spatial variability of vegetation is a key characteristic of savanna landscapes and its importance to biodiversity has been demonstrated by field-based studies. The data used for the study were sourced from the U.S. Agency for International Development where AVHRR derived Normalized Difference Vegetation Index (NDVI) images available at spatial resolutions of 8 km and at dekadal scales. The study area was extracted from these images for the time-period 1984-2002. Maximum value composites were derived for individual months resulting in an image dataset of 216 NDVI images. Vegetation dynamics across spatio-temporal domains were analyzed using standardized principal components analysis (SPCA) on the NDVI time-series. Each individual image variability in the time-series is considered. The outcome of this study demonstrated promising results - the variability of vegetation change in the area across space and time, and also indicated changes in landscape on 6 individual principal components (PCs) showing differences not only in magnitude, but also in pattern, of different selected eco-zones with constantly changing and evolving ecosystem.

Mapping the spectral variability in photosynthetic and non-photosynthetic vegetation, soils, and shade using AVIRIS

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Smith, Milton O.; Sabol, Donald E.; Adams, John B.; Ustin, Susan L.

1992-01-01

The primary objective of this research was to map as many spectrally distinct types of green vegetation (GV), non-photosynthetic vegetation (NPV), shade, and soil (endmembers) in an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene as is warranted by the spectral variability of the data. Once determined, a secondary objective was to interpret these endmembers and their abundances spatially and spectrally in an ecological context.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Variability in vegetation effects on density and nesting success of grassland birds

USGS Publications Warehouse

Winter, Maiken; Johnson, Douglas H.; Shaffer, Jill A.

2005-01-01

The structure of vegetation in grassland systems, unlike that in forest systems, varies dramatically among years on the same sites, and among regions with similar vegetation. The role of this variation in vegetation structure on bird density and nesting success of grassland birds is poorly understood, primarily because few studies have included sufficiently large temporal and spatial scales to capture the variation in vegetation structure, bird density, or nesting success. To date, no large-scale study on grassland birds has been conducted to investigate whether grassland bird density and nesting success respond similarly to changes in vegetation structure. However, reliable management recommendations require investigations into the distribution and nesting success of grassland birds over larger temporal and spatial scales. In addition, studies need to examine whether bird density and nesting success respond similarly to changing environmental conditions. We investigated the effect of vegetation structure on the density and nesting success of 3 grassland-nesting birds: clay-colored sparrow (Spizella pallida), Savannah sparrow (Passerculus sandwichensis), and bobolink (Dolichonyx oryzivorus) in 3 regions of the northern tallgrass prairie in 1998-2001. Few vegetation features influenced the densities of our study species, and each species responded differently to those vegetation variables. We could identify only 1 variable that clearly influenced nesting success of 1 species: clay-colored sparrow nesting success increased with increasing percentage of nest cover from the surrounding vegetation. Because responses of avian density and nesting success to vegetation measures varied among regions, years, and species, land managers at all times need to provide grasslands with different types of vegetation structure. Management guidelines developed from small-scale, short-term studies may lead to misrepresentations of the needs of grassland-nesting birds.

Iterative development of Vegethon: a theory-based mobile app intervention to increase vegetable consumption.

PubMed

Mummah, Sarah A; King, Abby C; Gardner, Christopher D; Sutton, Stephen

2016-08-08

Mobile technology may serve as a cost-effective and scalable tool for delivering behavioral nutrition interventions. This research sought to iteratively develop a theory-driven mobile app, Vegethon, to increase vegetable consumption. Development of Vegethon followed phases outlined by the IDEAS framework: 1) empathize with users (qualitative interviews, n = 18); 2) specify target behavior; 3) ground in behavioral theory; 4) ideate implementation strategies; 5) prototype potential products; 6) gather user feedback (qualitative interviews, n = 14; questionnaire, n = 41); 7) build minimum viable product; and 8) pilot potential efficacy and usability (pilot RCT, n = 17). Findings from each phase informed subsequent phases. The target population that informed intervention development was 18-50 years of age, had BMIs of 28-40 kg/m(2), and lived in the geographical area surrounding Stanford University. A full description of the final version of Vegethon is included in the paper. Qualitative findings that shaped initial intervention conception were: participants' interests in accountability without judgment; their desire for simple and efficient dietary self-monitoring; and the importance of planning meals in advance. Qualitative findings identified during intervention refinement were the need for a focus on vegetable self-monitoring; inclusion of vegetable challenges; simplification of features; advice and inspiration for eating vegetables; reminder notifications; and peer comparison. Pilot RCT findings suggested the initial efficacy, acceptance, and feasibility of the intervention. The final version of Vegethon enabled easy self-monitoring of vegetable consumption and included a range of features designed to engage the user (e.g., surprise challenges; leaderboard; weekly reports). Vegethon was coded for its inclusion of 18 behavior change techniques (BCTs) (e.g., goal setting; feedback; social comparison; prompts/cues; framing/reframing; identity). Vegethon is a theory-based, user-informed mobile intervention that was systematically developed using the IDEAS framework. Vegethon targets increased vegetable consumption among overweight adults and is currently being evaluated in a randomized controlled efficacy trial. Clinical Trials.gov: NCT01826591.

Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data

NASA Astrophysics Data System (ADS)

Chemura, Abel; Mutanga, Onisimo; Odindi, John; Kutywayo, Dumisani

2018-04-01

Nitrogen (N) is the most limiting factor to coffee development and productivity. Therefore, development of rapid, spatially explicit and temporal remote sensing-based approaches to determine spatial variability of coffee foliar N are imperative for increasing yields, reducing production costs and mitigating environmental impacts associated with excessive N applications. This study sought to assess the value of Sentinel-2 MSI spectral bands and vegetation indices in empirical estimation of coffee foliar N content at landscape level. Results showed that coffee foliar N is related to Sentinel-2 MSI B4 (R2 = 0.32), B6 (R2 = 0.49), B7 (R2 = 0.42), B8 (R2 = 0.57) and B12 (R2 = 0.24) bands. Vegetation indices were more related to coffee foliar N as shown by the Inverted Red-Edge Chlorophyll Index - IRECI (R2 = 0.66), Relative Normalized Difference Index - RNDVI (R2 = 0.48), CIRE1 (R2 = 0.28), and Normalized Difference Infrared Index - NDII (R2 = 0.37). These variables were also identified by the random forest variable optimisation as the most valuable in coffee foliar N prediction. Modelling coffee foliar N using vegetation indices produced better accuracy (R2 = 0.71 with RMSE = 0.27 for all and R2 = 0.73 with RMSE = 0.25 for optimized variables), compared to using spectral bands (R2 = 0.57 with RMSE = 0.32 for all and R2 = 0.58 with RMSE = 0.32 for optimized variables). Combining optimized bands and vegetation indices produced the best results in coffee foliar N modelling (R2 = 0.78, RMSE = 0.23). All the three best performing models (all vegetation indices, optimized vegetation indices and combining optimal bands and optimal vegetation indices) established that 15.2 ha (4.7%) of the total area under investigation had low foliar N levels (<2.5%). This study demonstrates the value of Sentinel-2 MSI data, particularly vegetation indices in modelling coffee foliar N at landscape scale.

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) Dynamic Vegetation-Land Surface Model

NASA Astrophysics Data System (ADS)

Landry, J.-S.; Price, D. T.; Ramankutty, N.; Parrott, L.; Matthews, H. D.

2015-12-01

Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from broadleaf defoliators, needleleaf defoliators, and bark beetles, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water following a simulated outbreak of the mountain pine beetle. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.

Characterizing Exterior and Interior Tropical Forest Structure Variability with Full-Waveform Airborne LIDAR Data in Lopé, Gabon

NASA Astrophysics Data System (ADS)

Marselis, S.; Tang, H.; Blair, J. B.; Hofton, M. A.; Armston, J.; Dubayah, R.

2017-12-01

Terrestrial ecotones, transition zones between ecological systems, have been identified as important regions to monitor the effects of environmental and human pressures on ecosystems. To observe such changes, the variability in vegetation horizontal and vertical structure must be characterized. The objective of this study is to quantify changes in vegetation structure in a tropical forest-savanna mosaic using airborne waveform lidar data. The study area is located in the northern part of the Lopé National Park in Gabon and is comprised of the vegetation types: savanna, colonizing forest, monodominant Okoumé forest, young Marantaceae forest and mixed Marantaceae forest. The lidar data were collected by the Land Vegetation and Ice Sensor (LVIS) in early March 2016, during the AfriSAR campaign. Metrics derived from the LVIS waveforms were then used to classify the five main vegetation types and characterize observed structural variability within types and across ecotones. Several supervised and unsupervised classification alogrithms, in combination with statistical analysis, were applied. The investigated methods are promising in their use to directly describe the structural variability within and between different vegetation types, map these vegetation types and the extent and location of their transition zones, and to characterize, among other attributes, the sharpness and width of such ecotones. These results provide important information in ecosystem studies as these methods can be used to study changes in vegetation structure, species-specific habitat, or the effects of deforestation and other human and natural pressures on the exterior and interior forest structure. These methods thus provide ample opportunity to assess the vegetation structure in degraded and second growth tropical forests to explore effects of e.g. grazing, logging or fragmentation. From this study we can conclude that lidar waveform remote sensing is highly useful in distinguishing vegetation types and their transition zones which will be increasingly important when assessing the impact of natural and human pressures on the world's tropical forests.

Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions

NASA Astrophysics Data System (ADS)

Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.

2016-12-01

To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation patterns: Three-dimensional modeling for a tidal marsh. Journal of Geophysical Research: Earth Surface 110, F4 (2005).

The Demise of the Circumboreal Mammoth Steppe as an Ecological Regime Shift: Drivers and Consequences

NASA Astrophysics Data System (ADS)

Mann, D. H.; Groves, P.; Grosse, G.; Gaglioti, B.; Kunz, M.

2011-12-01

During the last ice age, the now-vanished Mammoth Steppe stretched from the Yukon westward to Europe and supported a unique guild of megafauna grazers including mammoth, bison, saiga, wooly rhinoceros, caribou, muskox, and horse. The detailed vegetational composition of this extinct biome remains uncertain because of its large size and temporal complexity during multiple climatic shifts. Grasses and sedges were prominent, and Mammoth Steppe vegetation was probably more spatially variable than the tundra and taiga vegetation that replaced it. The environmental factors that maintained the Mammoth Steppe and dictated its variability over time and space are poorly understood. Here we present evidence for an expanded version of the "Schweger Hypothesis", the idea that large regions of the Mammoth Steppe were created and maintained by processes associated with aeolian sediment activity that was driven by enhanced pressure gradients in the full-glacial atmosphere and by increased continentality caused by lowered sea level. Increased seasonal swings in climate plus stronger winds interacted to promote the widespread occurrence of steppe-like vegetation that grew on relatively inactive and marginal dune and loess deposits. Subsequent periods of resumed aeolian deposition or reworking would have inhibited thick organic horizon development which are largely absent from full glacial mammoth steppe. New mapping of sand dune systems in Siberia and improved chronological control over dune fields in Alaska demonstrate the presence of large dune fields and loess belts in the regions occupied by the Mammoth Steppe during the Last Glacial Maximum. In regions of north Siberia, intense periglacial weathering and local transport of sediments also contributed to development and maintenance of the Mammoth Steppe. Local areas where aeolian sediment activity persists today such as active dune fields and loessal soils share several characteristics with the mammoth steppe such as the abundance grass and sedges, firm substrates, and unusual mixtures of steppe and tundra vegetation. What caused the demise of the Mammoth Steppe is unclear, however understanding what maintained it over space and time would greatly aid this discussion. The habitat shift began ca. 12,500 14C yr BP and continued for approximately 2000 years. It coincided with a shift from well-drained, mineral soils to poorly drained, organic-rich ones. This regime shift may have been more significant than changes during previous interglacial climatic shifts as most megafaunal species adapted to life in the Mammoth Steppe experienced radical range reductions and, in some cases, global extinction during this period.

Short- and medium-term efficacy of a Web-based computer-tailored nutrition education intervention for adults including cognitive and environmental feedback: randomized controlled trial.

PubMed

Springvloet, Linda; Lechner, Lilian; de Vries, Hein; Candel, Math J J M; Oenema, Anke

2015-01-19

Web-based, computer-tailored nutrition education interventions can be effective in modifying self-reported dietary behaviors. Traditional computer-tailored programs primarily targeted individual cognitions (knowledge, awareness, attitude, self-efficacy). Tailoring on additional variables such as self-regulation processes and environmental-level factors (the home food environment arrangement and perception of availability and prices of healthy food products in supermarkets) may improve efficacy and effect sizes (ES) of Web-based computer-tailored nutrition education interventions. This study evaluated the short- and medium-term efficacy and educational differences in efficacy of a cognitive and environmental feedback version of a Web-based computer-tailored nutrition education intervention on self-reported fruit, vegetable, high-energy snack, and saturated fat intake compared to generic nutrition information in the total sample and among participants who did not comply with dietary guidelines (the risk groups). A randomized controlled trial was conducted with a basic (tailored intervention targeting individual cognition and self-regulation processes; n=456), plus (basic intervention additionally targeting environmental-level factors; n=459), and control (generic nutrition information; n=434) group. Participants were recruited from the general population and randomly assigned to a study group. Self-reported fruit, vegetable, high-energy snack, and saturated fat intake were assessed at baseline and at 1- (T1) and 4-months (T2) postintervention using online questionnaires. Linear mixed model analyses examined group differences in change over time. Educational differences were examined with group×time×education interaction terms. In the total sample, the basic (T1: ES=-0.30; T2: ES=-0.18) and plus intervention groups (T1: ES=-0.29; T2: ES=-0.27) had larger decreases in high-energy snack intake than the control group. The basic version resulted in a larger decrease in saturated fat intake than the control intervention (T1: ES=-0.19; T2: ES=-0.17). In the risk groups, the basic version caused larger decreases in fat (T1: ES=-0.28; T2: ES=-0.28) and high-energy snack intake (T1: ES=-0.34; T2: ES=-0.20) than the control intervention. The plus version resulted in a larger increase in fruit (T1: ES=0.25; T2: ES=0.37) and a larger decrease in high-energy snack intake (T1: ES=-0.38; T2: ES=-0.32) than the control intervention. For high-energy snack intake, educational differences were found. Stratified analyses showed that the plus version was most effective for high-educated participants. Both intervention versions were more effective in improving some of the self-reported dietary behaviors than generic nutrition information, especially in the risk groups, among both higher- and lower-educated participants. For fruit intake, only the plus version was more effective than providing generic nutrition information. Although feasible, incorporating environmental-level information is time-consuming. Therefore, the basic version may be more feasible for further implementation, although inclusion of feedback on the arrangement of the home food environment and on availability and prices may be considered for fruit and, for high-educated people, for high-energy snack intake. Netherlands Trial Registry NTR3396; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3396 (Archived by WebCite at http://www.webcitation.org/6VNZbdL6w).

Short- and Medium-Term Efficacy of a Web-Based Computer-Tailored Nutrition Education Intervention for Adults Including Cognitive and Environmental Feedback: Randomized Controlled Trial

PubMed Central

Lechner, Lilian; de Vries, Hein; Candel, Math JJM; Oenema, Anke

2015-01-01

Background Web-based, computer-tailored nutrition education interventions can be effective in modifying self-reported dietary behaviors. Traditional computer-tailored programs primarily targeted individual cognitions (knowledge, awareness, attitude, self-efficacy). Tailoring on additional variables such as self-regulation processes and environmental-level factors (the home food environment arrangement and perception of availability and prices of healthy food products in supermarkets) may improve efficacy and effect sizes (ES) of Web-based computer-tailored nutrition education interventions. Objective This study evaluated the short- and medium-term efficacy and educational differences in efficacy of a cognitive and environmental feedback version of a Web-based computer-tailored nutrition education intervention on self-reported fruit, vegetable, high-energy snack, and saturated fat intake compared to generic nutrition information in the total sample and among participants who did not comply with dietary guidelines (the risk groups). Methods A randomized controlled trial was conducted with a basic (tailored intervention targeting individual cognition and self-regulation processes; n=456), plus (basic intervention additionally targeting environmental-level factors; n=459), and control (generic nutrition information; n=434) group. Participants were recruited from the general population and randomly assigned to a study group. Self-reported fruit, vegetable, high-energy snack, and saturated fat intake were assessed at baseline and at 1- (T1) and 4-months (T2) postintervention using online questionnaires. Linear mixed model analyses examined group differences in change over time. Educational differences were examined with group×time×education interaction terms. Results In the total sample, the basic (T1: ES=–0.30; T2: ES=–0.18) and plus intervention groups (T1: ES=–0.29; T2: ES=–0.27) had larger decreases in high-energy snack intake than the control group. The basic version resulted in a larger decrease in saturated fat intake than the control intervention (T1: ES=–0.19; T2: ES=–0.17). In the risk groups, the basic version caused larger decreases in fat (T1: ES=–0.28; T2: ES=–0.28) and high-energy snack intake (T1: ES=–0.34; T2: ES=–0.20) than the control intervention. The plus version resulted in a larger increase in fruit (T1: ES=0.25; T2: ES=0.37) and a larger decrease in high-energy snack intake (T1: ES=–0.38; T2: ES=–0.32) than the control intervention. For high-energy snack intake, educational differences were found. Stratified analyses showed that the plus version was most effective for high-educated participants. Conclusions Both intervention versions were more effective in improving some of the self-reported dietary behaviors than generic nutrition information, especially in the risk groups, among both higher- and lower-educated participants. For fruit intake, only the plus version was more effective than providing generic nutrition information. Although feasible, incorporating environmental-level information is time-consuming. Therefore, the basic version may be more feasible for further implementation, although inclusion of feedback on the arrangement of the home food environment and on availability and prices may be considered for fruit and, for high-educated people, for high-energy snack intake. Trial Registration Netherlands Trial Registry NTR3396; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3396 (Archived by WebCite at http://www.webcitation.org/6VNZbdL6w). PMID:25599828

Impact of Holocene climate variability on Arctic vegetation

NASA Astrophysics Data System (ADS)

Gajewski, K.

2015-10-01

This paper summarizes current knowledge about the postglacial history of the vegetation of the Canadian Arctic Archipelago (CAA) and Greenland. Available pollen data were used to understand the initial migration of taxa across the Arctic, how the plant biodiversity responded to Holocene climate variability, and how past climate variability affected primary production of the vegetation. Current evidence suggests that most of the flora arrived in the area during the Holocene from Europe or refugia south or west of the region immediately after local deglaciation, indicating rapid dispersal of propagules to the region from distant sources. There is some evidence of shrub species arriving later in Greenland, but it is not clear if this is dispersal limited or a response to past climates. Subsequent climate variability had little effect on biodiversity across the CAA, with some evidence of local extinctions in areas of Greenland in the late Holocene. The most significant impact of climate changes is on vegetation density and/or plant production.

Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

NASA Astrophysics Data System (ADS)

El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

2012-12-01

The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary Production (NPP)), minimum annual NDVI, maximum annual NDVI, and annual amplitude, were extracted using that new framework. A multi-linear regression has been applied to these vegetation phenology metrics as well as to the relationship between pheno-metrics and environmental variables, to detect potential vegetation changes and to examine the existing relationship between vegetation dynamics and rainfall and elevation gradients. The results suggest that vegetation behavior is foremost governed by rainfall gradients (R-square =0.74). Trend analyses confirmed that around 80 percent of pixels showed a general decline of greenness with confidence level of 95% (p< 0.05), while 4 percent showed a general greening up. Vegetation in the area showed a significant and strong relationship with elevation and precipitation gradients. This correlation was more prominent at mid-elevations, which could be explained by the snowmelt dynamics and hydrological redistribution of water at that elevation. These tools, methods and results can be used to aid in monitoring and understanding climate change and variability impacts on vegetation productivity, ecosystem services, and water resources of the region, and to inform decision-makers and range managers at Hopi Tribe and Navajo nation. Keywords: drought, remote sensing, time series, vegetation dynamics, Hopi Tribe and Navajo Nations

Is Ground Cover Vegetation an Effective Biological Control Enhancement Strategy against Olive Pests?

PubMed Central

Paredes, Daniel; Cayuela, Luis; Gurr, Geoff M.; Campos, Mercedes

2015-01-01

Ground cover vegetation is often added or allowed to generate to promote conservation biological control, especially in perennial crops. Nevertheless, there is inconsistent evidence of its effectiveness, with studies reporting positive, nil or negative effects on pest control. This might arise from differences between studies at the local scale (e.g. orchard management and land use history), the landscape context (e.g. presence of patches of natural or semi-natural vegetation near the focal orchard), or regional factors, particularly climate in the year of the study. Here we present the findings from a long-term regional monitoring program conducted on four pest species (Bactrocera oleae, Prays oleae, Euphyllura olivina, Saissetia oleae) in 2,528 olive groves in Andalusia (Spain) from 2006 to 2012. Generalized linear mixed effect models were used to analyze the effect of ground cover on different response variables related to pest abundance, while accounting for variability at the local, landscape and regional scales. There were small and inconsistent effects of ground cover on the abundance of pests whilst local, landscape and regional variability explained a large proportion of the variability in pest response variables. This highlights the importance of local and landscape-related variables in biological control and the potential effects that might emerge from their interaction with practices, such as groundcover vegetation, implemented to promote natural enemy activity. The study points to perennial vegetation close to the focal crop as a promising alternative strategy for conservation biological control that should receive more attention. PMID:25646778

Impact of small-scale vegetation structure on tephra layer preservation

PubMed Central

Cutler, Nick A.; Shears, Olivia M.; Streeter, Richard T.; Dugmore, Andrew J.

2016-01-01

The factors that influence tephra layer taphonomy are poorly understood, but vegetation cover is likely to play a role in the preservation of terrestrial tephra deposits. The impact of vegetation on tephra layer preservation is important because: 1) the morphology of tephra layers could record key characteristics of past land surfaces and 2) vegetation-driven variability in tephra thickness could affect attempts to infer eruption and dispersion parameters. We investigated small- (metre-) scale interactions between vegetation and a thin (<10 cm), recent tephra layer. We conducted surveys of vegetation structure and tephra thickness at two locations which received a similar tephra deposit, but had contrasting vegetation cover (moss vs shrub). The tephra layer was thicker and less variable under shrub cover. Vegetation structure and layer thickness were correlated on the moss site but not under shrub cover, where the canopy reduced the influence of understory vegetation on layer morphology. Our results show that vegetation structure can influence tephra layer thickness on both small and medium (site) scales. These findings suggest that some tephra layers may carry a signal of past vegetation cover. They also have implications for the sampling effort required to reliably estimate the parameters of initial deposits. PMID:27845415

Evaluation of the AMSR-E Data Calibration Over Land

NASA Technical Reports Server (NTRS)

Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.

2004-01-01

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 1

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

Iversen, C. M.; Powell, A. S.; McCormack, M. L.

To address the need for a centralized root trait database, we are compiling the Fine-Root Ecology Database (FRED) from published literature and unpublished data. FRED Version 1 (FRED 1.0) currently houses more than 70,000 observations of root traits and their associated site, vegetation, edaphic, and climatic conditions from across the globe (see image below, which shows the more than 1000 distinct locations associated with observations in FRED 1.0). Data collection is ongoing and will continue for the foreseeable future. The more than 300 root traits currently housed in FRED 1.0 are described in detail here. FRED is focused on finemore » roots (less than 2 mm), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations.« less

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

Predicting habits of vegetable parenting practices to facilitate the design of change programmes.

PubMed

Baranowski, Tom; Chen, Tzu-An; O'Connor, Teresia M; Hughes, Sheryl O; Diep, Cassandra S; Beltran, Alicia; Brand, Leah; Nicklas, Theresa; Baranowski, Janice

2016-08-01

Habit has been defined as the automatic performance of a usual behaviour. The present paper reports the relationships of variables from a Model of Goal Directed Behavior to four scales in regard to parents' habits when feeding their children: habit of (i) actively involving child in selection of vegetables; (ii) maintaining a positive vegetable environment; (iii) positive communications about vegetables; and (iv) controlling vegetable practices. We tested the hypothesis that the primary predictor of each habit variable would be the measure of the corresponding parenting practice. Internet survey data from a mostly female sample. Primary analyses employed regression modelling with backward deletion, controlling for demographics and parenting practices behaviour. Houston, Texas, USA. Parents of 307 pre-school (3-5-year-old) children. Three of the four models accounted for about 50 % of the variance in the parenting practices habit scales. Each habit scale was primarily predicted by the corresponding parenting practices scale (suggesting validity). The habit of active child involvement in vegetable selection was also most strongly predicted by two barriers and rudimentary self-efficacy; the habit of maintaining a positive vegetable environment by one barrier; the habit of maintaining positive communications about vegetables by an emotional scale; and the habit of controlling vegetable practices by a perceived behavioural control scale. The predictiveness of the psychosocial variables beyond parenting practices behaviour was modest. Discontinuing the habit of ineffective controlling parenting practices may require increasing the parent's perceived control of parenting practices, perhaps through simulated parent-child interactions.

HYPERDIRE-HYPERgeometric functions DIfferential REduction: Mathematica-based packages for the differential reduction of generalized hypergeometric functions: Lauricella function FC of three variables

NASA Astrophysics Data System (ADS)

Bytev, Vladimir V.; Kniehl, Bernd A.

2016-09-01

We present a further extension of the HYPERDIRE project, which is devoted to the creation of a set of Mathematica-based program packages for manipulations with Horn-type hypergeometric functions on the basis of differential equations. Specifically, we present the implementation of the differential reduction for the Lauricella function FC of three variables. Catalogue identifier: AEPP_v4_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEPP_v4_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 243461 No. of bytes in distributed program, including test data, etc.: 61610782 Distribution format: tar.gz Programming language: Mathematica. Computer: All computers running Mathematica. Operating system: Operating systems running Mathematica. Classification: 4.4. Does the new version supersede the previous version?: No, it significantly extends the previous version. Nature of problem: Reduction of hypergeometric function FC of three variables to a set of basis functions. Solution method: Differential reduction. Reasons for new version: The extension package allows the user to handle the Lauricella function FC of three variables. Summary of revisions: The previous version goes unchanged. Running time: Depends on the complexity of the problem.

Notable shifting in the responses of vegetation activity to climate change in China

NASA Astrophysics Data System (ADS)

Chen, Aifang; He, Bin; Wang, Honglin; Huang, Ling; Zhu, Yunhua; Lv, Aifeng

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (PNDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive PNDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

Improving the prediction of African savanna vegetation variables using time series of MODIS products

NASA Astrophysics Data System (ADS)

Tsalyuk, Miriam; Kelly, Maggi; Getz, Wayne M.

2017-09-01

African savanna vegetation is subject to extensive degradation as a result of rapid climate and land use change. To better understand these changes detailed assessment of vegetation structure is needed across an extensive spatial scale and at a fine temporal resolution. Applying remote sensing techniques to savanna vegetation is challenging due to sparse cover, high background soil signal, and difficulty to differentiate between spectral signals of bare soil and dry vegetation. In this paper, we attempt to resolve these challenges by analyzing time series of four MODIS Vegetation Products (VPs): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR) for Etosha National Park, a semiarid savanna in north-central Namibia. We create models to predict the density, cover, and biomass of the main savanna vegetation forms: grass, shrubs, and trees. To calibrate remote sensing data we developed an extensive and relatively rapid field methodology and measured herbaceous and woody vegetation during both the dry and wet seasons. We compared the efficacy of the four MODIS-derived VPs in predicting vegetation field measured variables. We then compared the optimal time span of VP time series to predict ground-measured vegetation. We found that Multiyear Partial Least Square Regression (PLSR) models were superior to single year or single date models. Our results show that NDVI-based PLSR models yield robust prediction of tree density (R2 = 0.79, relative Root Mean Square Error, rRMSE = 1.9%) and tree cover (R2 = 0.78, rRMSE = 0.3%). EVI provided the best model for shrub density (R2 = 0.82) and shrub cover (R2 = 0.83), but was only marginally superior over models based on other VPs. FPAR was the best predictor of vegetation biomass of trees (R2 = 0.76), shrubs (R2 = 0.83), and grass (R2 = 0.91). Finally, we addressed an enduring challenge in the remote sensing of semiarid vegetation by examining the transferability of predictive models through space and time. Our results show that models created in the wetter part of Etosha could accurately predict trees' and shrubs' variables in the drier part of the reserve and vice versa. Moreover, our results demonstrate that models created for vegetation variables in the dry season of 2011 could be successfully applied to predict vegetation in the wet season of 2012. We conclude that extensive field data combined with multiyear time series of MODIS vegetation products can produce robust predictive models for multiple vegetation forms in the African savanna. These methods advance the monitoring of savanna vegetation dynamics and contribute to improved management and conservation of these valuable ecosystems.

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

NASA Technical Reports Server (NTRS)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Reimplementation of the Biome-BGC model to simulate successional change.

PubMed

Bond-Lamberty, Ben; Gower, Stith T; Ahl, Douglas E; Thornton, Peter E

2005-04-01

Biogeochemical process models are increasingly employed to simulate current and future forest dynamics, but most simulate only a single canopy type. This limitation means that mixed stands, canopy succession and understory dynamics cannot be modeled, severe handicaps in many forests. The goals of this study were to develop a version of Biome-BGC that supported multiple, interacting vegetation types, and to assess its performance and limitations by comparing modeled results to published data from a 150-year boreal black spruce (Picea mariana (Mill.) BSP) chronosequence in northern Manitoba, Canada. Model data structures and logic were modified to support an arbitrary number of interacting vegetation types; an explicit height calculation was necessary to prioritize radiation and precipitation interception. Two vegetation types, evergreen needle-leaf and deciduous broadleaf, were modeled based on site-specific meteorological and physiological data. The new version of Biome-BGC reliably simulated observed changes in leaf area, net primary production and carbon stocks, and should be useful for modeling the dynamics of mixed-species stands and ecological succession. We discuss the strengths and limitations of Biome-BGC for this application, and note areas in which further work is necessary for reliable simulation of boreal biogeochemical cycling at a landscape scale.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Variability in understory evapotranspiration with overstory density in Siberian larch forests

NASA Astrophysics Data System (ADS)

Tobio, A.; Loranty, M. M.; Kropp, H.; Pena, H., III; Alexander, H. D.; Natali, S.; Kholodov, A. L.

2016-12-01

Arctic ecosystems are changing rapidly in response to amplified rates of climate change. Increased vegetation productivity, altered ecosystem carbon and hydrologic cycling, and increased wildfire severity are among the key responses to changing permafrost and climate conditions. Boreal larch forests in northeastern Siberia are a critical but understudied ecosystem affected by these modifications. Understory vegetation in these ecosystems, which typically have low canopy cover, may account for half of all water fluxes. Despite the potential importance of the understory for ecosystem water exchange, there has been relatively little research examining variability in understory evapotranspiration in boreal larch forests. In particular, the water balance of understory shrubs and mosses is largely undefined and could provide insight on how understory vegetation and our changing climate interact. This is especially important because both observed increases in vegetation productivity and wildfire severity could lead to increases in forests density, altering the proportional contributions of over- and understory vegetation to whole ecosystem evapotranspiration. In order to better understand variability in understory evapotranspiration we measured in larch forests with differing overstory density and permafrost conditions that likely vary as a consequence of fire severity. We used the static chamber technique to measure fluxes across a range of understory vegetation types and environmental conditions. In general, we found that the understory vegetation in low density stands transpires more than that in high density stands. This tends to be correlated with a larger amount of aboveground biomass in the low density stands, and an increase in solar radiation, due to less shading by overstory trees. These results will help us to better understand water balances, evapotranspiration variability, and productivity changes associated with climate on understory vegetation. Additionally, our results will help understand how fire regime shifts may alter understory contributions to ecosystem evapotranspiration in Siberian larch forests.

Arabic versions of the sleep timing questionnaire and the composite scale of morningness.

PubMed

Mansour, Hader; Tobar, Salwa; Fathi, Warda; Ibrahim, Ibtihal; Wood, Joel; Elassy, Mai; Elsayed, Hanan; Yassin, Amal; Salah, Hala; Eissa, Ahmed; El-Boraie, Hala; El-Boraie, Osama; Dobea, Ahmed; Osama, Haitham; Gomaa, Zeinab; El-Bahaei, Wafaa; Monk, Timothy H; Nimgaonkar, Vishwajit L

2015-02-01

To develop Arabic versions of English language questionnaires to estimate morningness/eveningness and sleep variables. We translated the Composite scale of morningness (CSM) and the sleep timing questionnaire (STQ) [with added siesta questions] into Arabic; the Arabic versions were then back translated. The revised Arabic and the original English versions were next administered to bi-lingual Egyptians using a crossover design (n=25). The Arabic versions of both scales were subsequently administered to an independent Egyptian sample (n=79) and the siesta variables examined in relation to the CSM. Satisfactory correlations were present between the English and Arabic versions for total CSM scores (Spearman's ρ=0.90, p<0.001). All but one of the STQ variables were significantly correlated (Spearman's ρ=0.45-0.88, p≤0.05). In the Arabic version, the frequency of siesta naps per week was significantly correlated with the total CSM score, with evening types taking more naps (Spearman's ρ=-0.23, p≤0.05). Arabic versions of the STQ and CSM have been developed in Egypt, and are freely available. They can be used for behavioral research related to sleep and circadian function and can be adapted for use in other Arab speaking populations. Copyright © 2014 Elsevier B.V. All rights reserved.

Impacts of Climate Change/Variability and Human Activities on Contemporary Vegetation Productivity across Africa

NASA Astrophysics Data System (ADS)

Ugbaje, S. U.; Odeh, I. A.; Bishop, T.

2015-12-01

Vegetation productivity is increasingly being impacted upon by climate change/variability and anthropogenic activities, especially in developing countries, where many livelihoods depend on the natural resource base. Despite these impacts, the individual and combined roles of climate and anthropogenic factors on vegetation dynamics have rarely been quantified in many ecosystems and regions of the world. This paper analyzes recent trend in vegetation productivity across Africa and quantified the relative roles of climate change/variability and human activities in driving this trend over 2000-2014 using net primary productivity (NPP) as an indicator. The relative roles of these factors to vegetation productivity change were quantified by comparing the trend slope (p<0.1) and total change in interannual actual NPP (NPPA), potential NPP (NPPP), and human appropriated NPP (NPPH). NPP significantly increased across Africa relative to NPP decline, though the extent of NPP decline is also quite appreciable. Whereas estimated NPP declined by 207 Tg C over 140 X 104 km of land area, vegetation productivity was estimated to improve by 1415 Tg C over 786 X 104 km of land area. NPP improvement is largely concentrated in equatorial and northern hemispheric Africa, while subequatorial Africa exhibited the most NPP decline. Generally, anthropogenic activities dominated climate change/variability in improving or degrading vegetation productivity. Of the estimated total NPP gained over the study period, 32.6, 8.8, and 58.6 % were due to individual human, climate and combined impacts respectively. The contributions of the factors to NPP decline in the same order are: 50.7, 16.0 and 33.3 %. The Central Africa region is where human activities had the greatest impact on NPP improvement; whereas the Sahel and the coastlines of west northern Africa are areas associated with the greatest influence of climate-driven NPP gain. Areas with humans dominating NPP degradation include eastern Angola, western Zambia, and Liberia; whereas climate-driven NPP loss is pronounced in Zambia and Mozambique. Results from this study indicate that, compared to climate change/variability, contemporary anthropogenic activities are contributing more to the decline of Africa's vegetation productivity than to vegetation improvement.

Classification of vegetation in an open landscape using full-waveform airborne laser scanner data

NASA Astrophysics Data System (ADS)

Alexander, Cici; Deák, Balázs; Kania, Adam; Mücke, Werner; Heilmeier, Hermann

2015-09-01

Airborne laser scanning (ALS) is increasingly being used for the mapping of vegetation, although the focus so far has been on woody vegetation, and ALS data have only rarely been used for the classification of grassland vegetation. In this study, we classified the vegetation of an open alkali landscape, characterized by two Natura 2000 habitat types: Pannonic salt steppes and salt marshes and Pannonic loess steppic grasslands. We generated 18 variables from an ALS dataset collected in the growing (leaf-on) season. Elevation is a key factor determining the patterns of vegetation types in the landscape, and hence 3 additional variables were based on a digital terrain model (DTM) generated from an ALS dataset collected in the dormant (leaf-off) season. We classified the vegetation into 24 classes based on these 21 variables, at a pixel size of 1 m. Two groups of variables with and without the DTM-based variables were used in a Random Forest classifier, to estimate the influence of elevation, on the accuracy of the classification. The resulting classes at Level 4, based on associations, were aggregated at three levels - Level 3 (11 classes), Level 2 (8 classes) and Level 1 (5 classes) - based on species pool, site conditions and structure, and the accuracies were assessed. The classes were also aggregated based on Natura 2000 habitat types to assess the accuracy of the classification, and its usefulness for the monitoring of habitat quality. The vegetation could be classified into dry grasslands, wetlands, weeds, woody species and man-made features, at Level 1, with an accuracy of 0.79 (Cohen's kappa coefficient, κ). The accuracies at Levels 2-4 and the classification based on the Natura 2000 habitat types were κ: 0.76, 0.61, 0.51 and 0.69, respectively. Levels 1 and 2 provide suitable information for nature conservationists and land managers, while Levels 3 and 4 are especially useful for ecologists, geologists and soil scientists as they provide high resolution data on species distribution, vegetation patterns, soil properties and on their correlations. Including the DTM-based variables increased the accuracy (κ) from 0.73 to 0.79 for Level 1. These findings show that the structural and spectral attributes of ALS echoes can be used for the classification of open landscapes, especially those where vegetation is influenced by elevation, such as coastal salt marshes, sand dunes, karst or alluvial areas; in these cases, ALS has a distinct advantage over other remotely sensed data.

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China.

PubMed

Liu, Zhihua

2016-11-18

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states.

Testing the effectiveness of in-home behavioral economics strategies to increase vegetable intake, liking, and variety among children residing in households that receive food assistance.

PubMed

Leak, Tashara M; Swenson, Alison; Vickers, Zata; Mann, Traci; Mykerezi, Elton; Redden, Joseph P; Rendahl, Aaron; Reicks, Marla

2015-01-01

To test the effectiveness of behavioral economics strategies for increasing vegetable intake, variety, and liking among children residing in homes receiving food assistance. A randomized controlled trial with data collected at baseline, once weekly for 6 weeks, and at study conclusion. Family homes. Families with a child (9-12 years) will be recruited through community organizations and randomly assigned to an intervention (n = 36) or control (n = 10) group. The intervention group will incorporate a new behavioral economics strategy during home dinner meal occasions each week for 6 weeks. Strategies are simple and low-cost. The primary dependent variable will be child's dinner meal vegetable consumption based on weekly reports by caregivers. Fixed independent variables will include the strategy and week of strategy implementation. Secondary dependent variables will include vegetable liking and variety of vegetables consumed based on data collected at baseline and study conclusion. Mean vegetable intake for each strategy across families will be compared using a mixed-model analysis of variance with a random effect for child. In additionally, overall mean changes in vegetable consumption, variety, and liking will be compared between intervention and control groups. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China

PubMed Central

Liu, Zhihua

2016-01-01

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states. PMID:27857204

The influence of competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, Joe; Arora, Vivek

2015-04-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the earth system modelling framework of the Canadian Centre for Climate Modelling and Analysis (CCCma). In its current framework, CTEM uses prescribed fractional coverage of plant functional types (PFTs) in each grid cell. In reality, vegetation cover is continually adjusting to changes in climate, atmospheric composition, and anthropogenic forcing, for example, through human-caused fires and CO2 fertilization. These changes in vegetation spatial patterns occur over timescales of years to centuries as tree migration is a slow process and vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM that includes a representation of competition between PFTs through a modified version of the Lotka-Volterra (L-V) predator-prey equations. The simulated areal extents of CTEM's seven non-crop PFTs are compared with available observation-based estimates, and simulations using unmodified L-V equations (similar to other models like TRIFFID), to demonstrate that the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. Differences remain, however, since representing the multitude of plant species with just seven non-crop PFTs only allows the large scale climatic controls on the distributions of PFTs to be captured. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model and the corresponding driving climate or the limited number of PFTs used to model the terrestrial ecosystem processes. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably with each other and observation-based estimates. These results illustrate that the parametrization of competition between PFTs in CTEM behaves in a reasonably realistic manner while the use of unmodified L-V equations results in unrealistic plant distributions.

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model.

PubMed

Sakschewski, Boris; von Bloh, Werner; Boit, Alice; Rammig, Anja; Kattge, Jens; Poorter, Lourens; Peñuelas, Josep; Thonicke, Kirsten

2015-01-22

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects. © 2015 John Wiley & Sons Ltd.

A canopy radiative transfer scheme with explicit FAPAR for the ISBA-A-gs land surface model: impact on carbon fluxes

NASA Astrophysics Data System (ADS)

Calvet, Jean-Christophe; Carrer, Dominique; Roujean, Jean-Louis; Lafont, Sébastien

2013-04-01

The ISBA-A-gs land surface model is a component of the SURFEX modeling platform developed by Meteo-France, used for research and operational applications in meteorology, hydrology, and climate modeling. ISBA-A-gs simulates hourly water and CO2 fluxes together with soil moisture. An option of the model permits the simulation of the vegetation biomass and of the leaf area index (LAI). The simulated photosynthesis depends on atmospheric CO2 concentration, air temperature and humidity, soil moisture, radiant solar energy, the photosynthetic capacity of the leaves and on factors that condition the distribution of solar radiation over the leaves. In the original version of the model (Jacobs et al. (Agr. Forest Meteorol., 1996), Calvet et al. (Agr. Forest Meteorol., 1998)), the radiative transfer scheme within the canopy was implemented according to a self shading approach. The incident fluxes at the top of the canopy go through a multi-layer vegetation cover. Then, the attenuated flux in the PAR wavelength domain of each layer is used by the photosynthesis model to calculate the leaf net assimilation of CO2 (An). The leaf-level An values are then integrated at the canopy level. In this study, an upgraded version of the radiative transfer model is implemented. An assessment of the vegetation transmittance functions and of various canopy light-response curves is made. The fluxes produced by the new version of ISBA-A-gs are evaluated using data from a number of FLUXNET forest sites. The new model presents systematically better scores than the previous version. Moreover, ISBA-A-gs is now able to simulate prognostic values of the fraction of absorbed PAR (FAPAR). As FAPAR can be observed from space, this new capability permits the validation of the model simulations at a global scale, and the integration of measured FAPAR values in the model through data assimilation techniques.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

PubMed

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-10-07

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

PubMed Central

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-01-01

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. PMID:27713530

Sensitivity of volatile organic compounds (VOCs) and ozone to land surface processes and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, C.; Huang, M.; Fast, J. D.; Berg, L. K.; Qian, Y.; Guenther, A. B.; Gu, D.; Shrivastava, M. B.; Liu, Y.; Walters, S.; Jin, J.

2014-12-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect secondary organic aerosol (SOA) formation and ultimately aerosol radiative forcing. These uncertainties result from many factors, including coupling strategy between biogenic emissions and land-surface schemes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (VOCs). In this study, sensitivity experiments are conducted using the Weather Research and Forecasting model with chemistry (WRF-Chem) to examine the sensitivity of simulated VOCs and ozone to land surface processes and vegetation distributions in California. The measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010 provide a good opportunity to evaluate the simulations. First, the biogenic VOC emissions in the WRF-Chem simulations with the two land surface schemes, Noah and CLM4, are estimated by the Model of Emissions of Gases and Aerosols from Nature version one (MEGANv1), which has been publicly released and widely used with WRF-Chem. The impacts of land surface processes on estimating biogenic VOC emissions and simulating VOCs and ozone are investigated. Second, in this study, a newer version of MEGAN (MEGANv2.1) is coupled with CLM4 as part of WRF-Chem to examine the sensitivity of biogenic VOC emissions to the MEGAN schemes used and determine the importance of using a consistent vegetation map between a land surface scheme and the biogenic VOC emission scheme. Specifically, MEGANv2.1 is embedded into the CLM4 scheme and shares a consistent vegetation map for estimating biogenic VOC emissions. This is unlike MEGANv1 in WRF-Chem that uses a standalone vegetation map that differs from what is used in land surface schemes. Furthermore, we examine the impact of vegetation distribution on simulating VOCs and ozone by comparing coupled WRF-Chem-CLM-MEGANv2.1 simulations using multiple vegetation maps.

Urban green land cover changes and their relation to climatic variables in an anthropogenically impacted area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Dida, Adrian I.

2017-10-01

Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.

Fine-Root Ecology Database (FRED): A Global Collection of Root Trait Data with Coincident Site, Vegetation, Edaphic, and Climatic Data, Version 2.

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

Iversen, C.M.; Powell, A.S.; McCormack, M.L.

The second version of the Fine-Root Ecology Database is available for download! Download the full FRED 2.0 data set, user guidance document, map, and list of data sources here. Prior to downloading the data, please read and follow the Data Use Guidelines, and it's worth checking out some tips for using FRED before you begin your analyses. Also, see here for an updating list of corrections to FRED 2.0.

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China.

PubMed

Yue, Yuemin; Wang, Kelin; Zhang, Bing; Chen, Zhengchao; Jiao, Quanjun; Liu, Bo; Chen, Hongsong

2010-01-01

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2015-04-01

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

Predicting use of effective vegetable parenting practices with the Model of Goal Directed Behavior.

PubMed

Diep, Cassandra S; Beltran, Alicia; Chen, Tzu-An; Thompson, Debbe; O'Connor, Teresia; Hughes, Sheryl; Baranowski, Janice; Baranowski, Tom

2015-06-01

To model effective vegetable parenting practices using the Model of Goal Directed Vegetable Parenting Practices construct scales. An Internet survey was conducted with parents of pre-school children to assess their agreement with effective vegetable parenting practices and Model of Goal Directed Vegetable Parenting Practices items. Block regression modelling was conducted using the composite score of effective vegetable parenting practices scales as the outcome variable and the Model of Goal Directed Vegetable Parenting Practices constructs as predictors in separate and sequential blocks: demographics, intention, desire (intrinsic motivation), perceived barriers, autonomy, relatedness, self-efficacy, habit, anticipated emotions, perceived behavioural control, attitudes and lastly norms. Backward deletion was employed at the end for any variable not significant at P<0·05. Houston, TX, USA. Three hundred and seven parents (mostly mothers) of pre-school children. Significant predictors in the final model in order of relationship strength included habit of active child involvement in vegetable selection, habit of positive vegetable communications, respondent not liking vegetables, habit of keeping a positive vegetable environment and perceived behavioural control of having a positive influence on child's vegetable consumption. The final model's adjusted R 2 was 0·486. This was the first study to test scales from a behavioural model to predict effective vegetable parenting practices. Further research needs to assess these Model of Goal Directed Vegetable Parenting Practices scales for their (i) predictiveness of child consumption of vegetables in longitudinal samples and (ii) utility in guiding design of vegetable parenting practices interventions.

Classification and ordination of understory vegetation using multivariate techniques in the Pinus wallichiana forests of Swat Valley, northern Pakistan

NASA Astrophysics Data System (ADS)

Rahman, Inayat Ur; Khan, Nasrullah; Ali, Kishwar

2017-04-01

An understory vegetation survey of the Pinus wallichiana-dominated temperate forests of Swat District was carried out to inspect the structure, composition and ecological associations of the forest vegetation. A quadrat method of sampling was used to record the floristic and phytosociological data necessary for the analysis using 300 quadrats of 10 × 10 m each. Some vegetation parameters viz. frequency and density for trees (overstory vegetation) as well as for the understory vegetation were recorded. The results revealed that in total, 92 species belonging to 77 different genera and 45 families existed in the area. The largest families were Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively. Ward's agglomerative cluster analysis for tree species resulted in three floristically and ecologically distinct community types along different topographic and soil variables. Importance value indices (IVI) were also calculated for understory vegetation and were subjected to ordination techniques, i.e. canonical correspondence analysis (CCA) and detrended correspondence analysis (DCA). DCA bi-plots for stands show that most of the stands were scattered around the centre of the DCA bi-plot, identified by two slightly scattered clusters. DCA for species bi-plot clearly identified three clusters of species revealing three types of understory communities in the study area. Results of the CCA were somewhat different from the DCA showing the impact of environmental variables on the understory species. CCA results reveal that three environmental variables, i.e. altitude, slope and P (mg/kg), have a strong influence on distribution of stands and species. Impact of tree species on the understory vegetation was also tested by CCA which showed that four tree species, i.e. P. wallichiana A.B. Jackson, Juglans regia Linn., Quercus dilatata Lindl. ex Royle and Cedrus deodara (Roxb. ex Lamb.) G. Don, have strong influences on associated understory vegetation. It is therefore concluded that Swat District has various microclimatic zones with suitable environmental variables to support distinct flora.

Legume Diversity Patterns in West Central Africa: Influence of Species Biology on Distribution Models

PubMed Central

de la Estrella, Manuel; Mateo, Rubén G.; Wieringa, Jan J.; Mackinder, Barbara; Muñoz, Jesús

2012-01-01

Objectives Species Distribution Models (SDMs) are used to produce predictions of potential Leguminosae diversity in West Central Africa. Those predictions are evaluated subsequently using expert opinion. The established methodology of combining all SDMs is refined to assess species diversity within five defined vegetation types. Potential species diversity is thus predicted for each vegetation type respectively. The primary aim of the new methodology is to define, in more detail, areas of species richness for conservation planning. Methodology Using Maxent, SDMs based on a suite of 14 environmental predictors were generated for 185 West Central African Leguminosae species, each categorised according to one of five vegetation types: Afromontane, coastal, non-flooded forest, open formations, or riverine forest. The relative contribution of each environmental variable was compared between different vegetation types using a nonparametric Kruskal-Wallis analysis followed by a post-hoc Kruskal-Wallis Paired Comparison contrast. Legume species diversity patterns were explored initially using the typical method of stacking all SDMs. Subsequently, five different ensemble models were generated by partitioning SDMs according to vegetation category. Ecological modelers worked with legume specialists to improve data integrity and integrate expert opinion in the interpretation of individual species models and potential species richness predictions for different vegetation types. Results/Conclusions Of the 14 environmental predictors used, five showed no difference in their relative contribution to the different vegetation models. Of the nine discriminating variables, the majority were related to temperature variation. The set of variables that played a major role in the Afromontane species diversity model differed significantly from the sets of variables of greatest relative important in other vegetation categories. The traditional approach of stacking all SDMs indicated overall centers of diversity in the region but the maps indicating potential species richness by vegetation type offered more detailed information on which conservation efforts can be focused. PMID:22911808

Food environment and fruit and vegetable intake in a urban population: a multilevel analysis.

PubMed

Pessoa, Milene Cristine; Mendes, Larissa Loures; Gomes, Crizian Saar; Martins, Paula Andréa; Velasquez-Melendez, Gustavo

2015-10-05

Environmental, social and individual factors influence eating patterns, which in turn affect the risk of many chronic diseases. This study aimed to estimate associations between environmental factors and the consumption of fruit and vegetables among adults in a Brazilian urban context. Data from the surveillance system for risk factors for chronic diseases (VIGITEL) of Brazilian Ministry of Health were used. A cross-sectional telephone survey (VIGITEL - 2008-2010) was carried out with 5826 adults in the urban area of Belo Horizonte. Individual variables were collected. The frequency of fruit and vegetables consumption was assessed from number of servings, weekly frequency and an intake score was calculated. Georeferenced variables were used to characterize the food environment. The density of healthy food outlets (stores specialized in selling fruit and vegetables), unhealthy food outlets (bars, snack bars and food trucks/trailers) and the neighborhood family income were investigated and associated with fruit and vegetables intake score. Weighted multilevel linear regression was used to evaluate the associations between the environment variables and the fruit and vegetables intake score. Higher fruit and vegetables intake scores were observed in neighborhoods with higher density of healthy food outlets and higher income. Lower scores were observed in neighborhood with higher density of unhealthy food outlets. These associations were adjusted by individual variables such as gender, age, physical activity, sugar sweetened beverages consumption, education level and smoking. The food environment might explain some of the socioeconomic disparities with respect to healthy food intake and health outcomes. Healthy food stores are less common in socially disadvantaged neighborhoods, and therefore, healthy foods such as fruits and vegetables are less available or are of a lower quality in lower income areas. Food environment characteristics and neighborhood socioeconomic level had significant associations with fruit and vegetable intake score. These are initial findings that require further investigation within the middle income world populations and the role of the environment with respect to both healthy and unhealthy food acquisition and intake.

[Evaluation on environmental quality of heavy metals in soils and vegetables based on geostatistics and GIS].

PubMed

Xie, Zheng-miao; Li, Jing; Wang, Bi-ling; Chen, Jian-jun

2006-10-01

Contents of heavy metals (Pb, Zn, Cd, Cu) in soils and vegetables from Dongguan town in Shangyu city, China were studied using geostatistical analysis and GIS technique to evaluate environmental quality. Based on the evaluation criteria, the distribution of the spatial variability of heavy metals in soil-vegetable system was mapped and analyzed. The results showed that the distribution of soil heavy metals in a large number of soil samples in Dongguan town was asymmetric. The contents of Zn and Cu were lower than those of Cd and Pb. The concentrations distribution of Pb, Zn, Cd and Cu in soils and vegetables were different in spatial variability. There was a close relationship between total and available contents of heavy metals in soil. The contents of Pb and Cd in green vegetables were higher than those of Zn and Cu and exceeded the national sanitation standards for vegetables.

[The variability of vegetation beginning date of greenness period in spring in the north-south transect of eastern China based on NOAA NDVI].

PubMed

Wang, Zhi; Liu, Shi-rong; Sun, Peng-sen; Guo, Zhi-hua; Zhou, Lian-di

2010-10-01

NDVI based on NOAA/AVHRR from 1982 to 2003 are used to monitor variable rules for the growing season in spring of vegetation in the north-south transect of eastern China (NSTEC). The following, mainly, are included: (1) The changing speed of greenness period in spring of most regions in NSTEC is slow and correlation with the year is not distinct; (2) The regions in which greenness period in spring distinctly change mainly presented an advance; (3) The regions in which inter-annual fluctuation of greenness period in spring is over 10 days were found in 3 kinds of areas: the area covered with agricultural vegetation types; the areas covered with evergreen vegetation types; the areas covered with steppe vegetation types; (4) changes of vegetation greenness period in spring have spatio-temporal patterns.

Implementing seasonal carbon allocation into a dynamic vegetation model

NASA Astrophysics Data System (ADS)

Vermeulen, Marleen; Kruijt, Bart; Hickler, Thomas; Forrest, Matthew; Kabat, Pavel

2014-05-01

Long-term measurements of terrestrial fluxes through the FLUXNET Eddy Covariance network have revealed that carbon and water fluxes can be highly variable from year-to-year. This so-called interannual variability (IAV) of ecosystems is not fully understood because a direct relation with environmental drivers cannot always be found. Many dynamic vegetation models allocate NPP to leaves, stems, and root compartments on an annual basis, and thus do not account for seasonal changes in productivity in response to changes in environmental stressors. We introduce this vegetation seasonality into dynamic vegetation model LPJ-GUESS by implementing a new carbon allocation scheme on a daily basis. We focus in particular on modelling the observed flux seasonality of the Amazon basin, and validate our new model against fluxdata and MODIS GPP products. We expect that introducing seasonal variability into the model improves estimates of annual productivity and IAV, and therefore the model's representation of ecosystem carbon budgets as a whole.

Modeling of vegetation canopy reflectance: Status, issues and recommended future strategy

NASA Technical Reports Server (NTRS)

Goel, N. S. (Editor)

1982-01-01

Various technical issues related to mapping of vegetative type, condition and stage of maturity, utilizing remotely sensed spectral data are reviewed. The existing knowledge base of models, especially of radiative properties of the vegetation canopy and atmosphere, is reviewed to establish the state of the art for addressing the problem of vegetation mapping. Activities to advance the state of the art are recommended. They include working on canopy reflectance and atmospheric scattering models, and field measurements of canopy reflectance as well as of canopy components. Leaf area index (LAI) and solar radiation interception (SRI) are identified as the two most important vegetation variables requiring further investigation. It is recommended that activities related to sensing them or understanding their relationships with measurable variables, should be encouraged and supported.

The Changing California Coast: The Effect of a Variable Water Budget on Coastal Vegetation Succession

NASA Technical Reports Server (NTRS)

Hsu, Wei-Chen; Remar, Alex; McClure, Adam; Williams, Emily; Kannan, Soumya; Steers, Robert; Schmidt, Cindy; Skiles, Joseph W.; Hsu, Wei-Chen

2011-01-01

The land-ocean interface along the central coast of California is one of the most diverse biogeographic regions of the state. This area is composed of a species-rich mosaic of coastal grassland, shrubland, and forest vegetation types. An acceleration of conifer encroachment into shrublands and shrub encroachment into grasslands along the coast has been recently documented. These vegetation changes are believed to be driven primarily by fire suppression and changing grazing patterns. Climatic variables such as precipitation, fog, cloud cover, temperature, slope, and elevation also play an important role in vegetation succession. Our study area is located along the central California coast, which is characterized by a precipitation gradient from the relatively wetter and cooler north to the drier and warmer south. Some studies indicate changing fog patterns along this coast, which may greatly impact vegetation. A decrease in water availability could slow succession processes. The primary objective of this project is to determine if vegetation succession rates are changing for the study area and to identify climate and ecosystem variables which contribute to succession, specifically the transition among grassland, shrubland, and forest. To identify vegetation types and rates of succession, we classified two Landsat TM 5 scenes from 1985 to 2010 with a resulting overall accuracy of 82.4%. Vegetation succession was correlated to changes in maximum and minimum temperatures, precipitation, and elevation for each sub-region of the study area. Fog frequency was then compared between the northern and southern regions of the study area for determining the spatial relation between fog frequency and the percent of vegetation change.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-02-26

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

Modeling Global Atmospheric CO2 Fluxes and Transport Using NASA MERRA Reanalysis Data

NASA Astrophysics Data System (ADS)

Liu, Y.; Kawa, S. R.; Collatz, G. J.

2010-12-01

We present our first results of CO2 surface biosphere fluxes and global atmospheric CO2 transport using NASA’s new MERRA reanalysis data. MERRA is the Modern Era Retrospective-Analysis For Research And Applications based on the Goddard Global Modeling and Assimilation Office GEOS-5 data assimilation system. After some application testing and analysis, we have generated biospheric CO2 fluxes at 3-hourly temporal resolution from an updated version of the CASA carbon cycle model using the 1x1.25-degree reanalysis data. The experiment covers a period of 9 years from 2000 -2008. The affects of US midwest crop (largely corn and soy) carbon uptake and removal by harvest are explicitly included in this version of CASA. Across the agricultural regions of the Midwest US, USDA crop yield data are used to scale vegetation fluxes producing a strong sink in the growing season and a comparatively weaker source from respiration after harvest. Comparisons of the new fluxes to previous ones generated using GEOS-4 data are provided. The Parameterized Chemistry/Transport Model (PCTM) is then used with the analyzed meteorology in offline CO2 transport. In the simulation of CO2 transport, we have a higher vertical resolution from MERRA (the lowest 56 of 72 levels are used in our simulation). A preliminary analysis of the CO2 simulation results is carried out, including diurnal, seasonal and latitudinal variability. We make comparisons of our simulation to continuous CO2 analyzer sites, especially those in agricultural regions. The results show that the model captures reasonably well the observed synoptic variability due to transport changes and biospheric fluxes.

The impact of flood variables on riparian vegetation

NASA Astrophysics Data System (ADS)

Dzubakova, Katarina; Molnar, Peter

2016-04-01

The riparian vegetation of Alpine rivers often grows in temporally dynamic riverine environments which are characterized by pronounced meteorological and hydrological fluctuations and high resource competition. Within these relatively rough conditions, riparian vegetation fulfils essential ecosystem functions such as water retention, biomass production and habitat to endangered species. The identification of relevant flood attributes impacting riparian vegetation is crucial for a better understanding of the vegetation dynamics in the riverine ecosystem. Hence, in this contribution we aim to quantify the ecological effects of flood attributes on riparian vegetation and to analyze the spatial coherence of flood-vegetation interaction patterns. We analyzed a 500 m long and 300-400 m wide study reach located on the Maggia River in southern Switzerland. Altogether five floods between 2008 and 2011 with return periods ranging from 1.4 to 20.1 years were studied. To assess the significance of the flood attributes, we compared post-flood to pre-flood vegetation vigour to flood intensity. Pre- and post-flood vegetation vigour was represented by the Normalized Difference Vegetation Index (NDVI) which was computed from images recorded by high resolution ground-based cameras. Flood intensity was expressed in space in the study reach by six flood attributes (inundation duration, maximum depth, maximum and total velocity, maximum and total shear stress) which were simulated by the 2D hydrodynamic model BASEMENT (VAW, ETH Zurich). We considered three floodplain units separately (main bar, secondary bar, transitional zone). Based on our results, pre-flood vegetation vigour largely determined vegetation reaction to the less intense floods (R = 0.59-0.96). However for larger floods with a strong erosive effect, its contribution was significantly lower (R = 0.59-0.68). Using multivariate regression analysis we show that pre-flood vegetation vigour and maximum velocity proved to be the most significant variables impacting vegetation response. Generally, maximal flood attributes had more significant impacts than integrated attributes over the flood duration. Additional explanatory variables in the model should account for vegetation heterogeneity, groundwater conditions and different effects of lateral and surface erosion.

AmeriFlux US-SRC Santa Rita Creosote

DOE Data Explorer

Kurc, Shirley [University of Arizona

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site US-SRC Santa Rita Creosote. Site Description - Part of the Santa Rita Experimental Range since 1901; Site vegetation has been dominated by Creosote bush since at least 1934

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

Jiang, Nan; Zhu, Wenquan; Zheng, Zhoutao

The long-term Normalized Difference Vegetation Index (NDVI) time-series data set generated from the Advanced Very High Resolution Radiometers (AVHRR) has been widely used to monitor vegetation activity change. The third version of NDVI (NDVI3g) produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group was released recently. The comparisons between the new and old versions should be conducted for linking existing studies with future applications of NDVI3g in monitoring vegetation activity change. Based on simple and piecewise linear regression methods, this research made a comparative analysis between NDVIg and NDVI3g for monitoring vegetation activity change and its responses tomore » climate change in the middle and high latitudes of the Northern Hemisphere during 1982–2008. Our results indicated that there were large differences between NDVIg and NDVI3g in the spatial patterns for both the overall changing trends and the timing of Turning Points (TP) in NDVI time series, which spread over almost the entire study region. The average NDVI trend from NDVI3g was almost twice as great as that from NDVIg and the detected average timing of TP from NDVI3g was about one year later. Although the general spatial patterns were consistent between two data sets for detecting the responses of growing-season NDVI to temperature and precipitation changes, there were large differences in the response magnitude, with a higher response magnitude to temperature in NDVI3g and an opposite response to precipitation change for the two data sets. Finally, these results demonstrated that the NDVIg data set may underestimate the vegetation activity change trend and its response to climate change in the middle and high latitudes of the Northern Hemisphere during the past three decades.« less

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation-land surface model

NASA Astrophysics Data System (ADS)

Landry, Jean-Sébastien; Price, David T.; Ramankutty, Navin; Parrott, Lael; Damon Matthews, H.

2016-04-01

Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from three different insect functional types: (1) defoliators on broadleaf deciduous trees, (2) defoliators on needleleaf evergreen trees, and (3) bark beetles on needleleaf evergreen trees, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water in a simplified setting and for bark beetles only. More precisely, we simulated 100 % mortality events from the mountain pine beetle for three locations in western Canada. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.

Predicted Water and Carbon Fluxes as well as Vegetation Distribution on the Korean Peninsula in the Future with the Ecosystem Demography Model version 2

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kim, Y.

2017-12-01

This study investigates how the water and carbon fluxes as well as vegetation distribution on the Korean peninsula would vary with climate change. Ecosystem Demography (ED) Model version 2 (ED2) is used in this study, which is an integrated terrestrial biosphere model that can utilize a set of size- and age- structured partial differential equations that track the changing structure and composition of the plant canopy. With using the vegetation distribution data of Jeju Island, located at the southern part of the Korean Peninsula, ED2 is setup and driven for the past 10 years. Then the results of ED2 are evaluated and adjusted with observed forestry data, i.e., growth and mortality, and the flux tower and MODIS satellite data, i.e., evapotranspiration (ET) and gross primary production (GPP). This adjusted ED2 are used to simulate the water and carbon fluxes as well as vegetation dynamics in the Korean Peninsula for the historical period with evaluating the model against the MODIS satellite data. Finally, the climate scenarios of RCP 2.6 and 6.0 are used to predict the fluxes and vegetation distribution of the Korean Peninsula in the future. With using the state-of-art terrestrial ecosystem model, this study would provide us better understanding of the future ecosystem vulnerability of the Korean Peninsula. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. This work was also supported by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

Biosphere-Atmosphere Transfer Scheme (BATS) version le as coupled to the NCAR community climate model. Technical note. [NCAR (National Center for Atmospheric Research)

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

Dickinson, R.E.; Henderson-Sellers, A.; Kennedy, P.J.

A comprehensive model of land-surface processes has been under development suitable for use with various National Center for Atmospheric Research (NCAR) General Circulation Models (GCMs). Special emphasis has been given to describing properly the role of vegetation in modifying the surface moisture and energy budgets. The result of these efforts has been incorporated into a boundary package, referred to as the Biosphere-Atmosphere Transfer Scheme (BATS). The current frozen version, BATS1e is a piece of software about four thousand lines of code that runs as an offline version or coupled to the Community Climate Model (CCM).

Regional sensitivities of seasonal snowpack to elevation, aspect, and vegetation cover in western North America

NASA Astrophysics Data System (ADS)

Tennant, Christopher J.; Harpold, Adrian A.; Lohse, Kathleen Ann; Godsey, Sarah E.; Crosby, Benjamin T.; Larsen, Laurel G.; Brooks, Paul D.; Van Kirk, Robert W.; Glenn, Nancy F.

2017-08-01

In mountains with seasonal snow cover, the effects of climate change on snowpack will be constrained by landscape-vegetation interactions with the atmosphere. Airborne lidar surveys used to estimate snow depth, topography, and vegetation were coupled with reanalysis climate products to quantify these interactions and to highlight potential snowpack sensitivities to climate and vegetation change across the western U.S. at Rocky Mountain (RM), Northern Basin and Range (NBR), and Sierra Nevada (SNV) sites. In forest and shrub areas, elevation captured the greatest amount of variability in snow depth (16-79%) but aspect explained more variability (11-40%) in alpine areas. Aspect was most important at RM sites where incoming shortwave to incoming net radiation (SW:NetR↓) was highest (˜0.5), capturing 17-37% of snow depth variability in forests and 32-37% in shrub areas. Forest vegetation height exhibited negative relationships with snow depth and explained 3-6% of its variability at sites with greater longwave inputs (NBR and SNV). Variability in the importance of physiography suggests differential sensitivities of snowpack to climate and vegetation change. The high SW:NetR↓ and importance of aspect suggests RM sites may be more responsive to decreases in SW:NetR↓ driven by warming or increases in humidity or cloud cover. Reduced canopy-cover could increase snow depths at SNV sites, and NBR and SNV sites are currently more sensitive to shifts from snow to rain. The consistent importance of aspect and elevation indicates that changes in SW:NetR↓ and the elevation of the rain/snow transition zone could have widespread and varied effects on western U.S. snowpacks.

Ecological controls on water-cycle response to climate variability in deserts.

PubMed

Scanlon, B R; Levitt, D G; Reedy, R C; Keese, K E; Sully, M J

2005-04-26

The impact of climate variability on the water cycle in desert ecosystems is controlled by biospheric feedback at interannual to millennial timescales. This paper describes a unique field dataset from weighing lysimeters beneath nonvegetated and vegetated systems that unequivocally demonstrates the role of vegetation dynamics in controlling water cycle response to interannual climate variability related to El Nino southern oscillation in the Mojave Desert. Extreme El Nino winter precipitation (2.3-2.5 times normal) typical of the U.S. Southwest would be expected to increase groundwater recharge, which is critical for water resources in semiarid and arid regions. However, lysimeter data indicate that rapid increases in vegetation productivity in response to elevated winter precipitation reduced soil water storage to half of that in a nonvegetated lysimeter, thereby precluding deep drainage below the root zone that would otherwise result in groundwater recharge. Vegetation dynamics have been controlling the water cycle in interdrainage desert areas throughout the U.S. Southwest, maintaining dry soil conditions and upward soil water flow since the last glacial period (10,000-15,000 yr ago), as shown by soil water chloride accumulations. Although measurements are specific to the U.S. Southwest, correlations between satellite-based vegetation productivity and elevated precipitation related to El Nino southern oscillation indicate this model may be applicable to desert basins globally. Understanding the two-way coupling between vegetation dynamics and the water cycle is critical for predicting how climate variability influences hydrology and water resources in water-limited landscapes.

Plant community variability on a small area in southeastern Montana

Treesearch

James G. MacCracken; Daniel W. Uresk; Richard M. Hansen

1984-01-01

Plant communities are inherently variable due to a number of environmental and biological forces. Canopy cover and aboveground biomass were determined for understory vegetation in plant communities of a prairie grassland-forest ecotone in southeastern Montana. Vegetation units were described using polar ordination and stepwise discriminant analysis. Nine of a total of...

International Spinal Cord Injury Core Data Set (version 2.0)-including standardization of reporting.

PubMed

Biering-Sørensen, F; DeVivo, M J; Charlifue, S; Chen, Y; New, P W; Noonan, V; Post, M W M; Vogel, L

2017-08-01

The study design includes expert opinion, feedback, revisions and final consensus. The objective of the study was to present the new knowledge obtained since the International Spinal Cord Injury (SCI) Core Data Set (Version 1.0) published in 2006, and describe the adjustments made in Version 2.0, including standardization of data reporting. International. Comments received from the SCI community were discussed in a working group (WG); suggestions from the WG were reviewed and revisions were made. All suggested revisions were considered, and a final version was circulated for final approval. The International SCI Core Data Set (Version 2.0) consists of 25 variables. Changes made to this version include the deletion of one variable 'Total Days Hospitalized' and addition of two variables 'Date of Rehabilitation Admission' and 'Date of Death.' The variable 'Injury Etiology' was extended with six non-traumatic categories, and corresponding 'Date of Injury' for non-traumatic cases, was defined as the date of first physician visit for symptoms related to spinal cord dysfunction. A category reflecting transgender was added. A response category was added to the variable on utilization of ventilatory assistance to document the use of continuous positive airway pressure for sleep apnea. Other clarifications were made to the text. The reporting of the pediatric SCI population was updated as age groups 0-5, 6-12, 13-14, 15-17 and 18-21. Collection of the core data set should be a basic requirement of all studies of SCI to facilitate accurate descriptions of patient populations and comparison of results across published studies from around the world.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

In the hot seat : Insolation and ENSO controls on vegetation productivity in tropical Africa inferred from NDVI

NASA Astrophysics Data System (ADS)

Ivory, S.; Russell, J. L.; Cohen, A. S.

2010-12-01

Threats to tropical biodiversity with serious and costly implications for both ecosystems and human well-being in Africa have led the IPCC to classify this region as vulnerable to negative impacts from climate change. Yet little is known about how vegetation communities respond to altered patterns of rainfall and evaporation. Paleoclimate records within the tropics can help answer questions about how vegetation response to climate forcing changes over time. However, sparse spatial extent of records and uncertainty surrounding the climate-vegetation relationship complicate these insights. Understanding the climatic mechanisms involved in landscape change at all temporal scales creates the need for quantitative constraints of the modern relationship between climatic controls, hydrology, and vegetation. Though modern observational data can help elucidate this relationship, low resolution and complicated rainfall/vegetation associations make them less than ideal. Satellite data of vegetation productivity (NDVI) with continuous high-resolution spatial coverage provides a robust and elegant tool for identifying the link between global and regional controls and vegetation. We use regression analyses of variables either previously proposed or potentially important in regulating Afro-tropical vegetation (insolation, out-going long-wave radiation, geopotential height, Southern Oscillation Index, Indian Ocean Dipole, Indian Monsoon precipitation, sea-level pressure, surface wind, sea-surface temperature) on continuous, time-varying spatial fields of 8km NDVI for sub-Saharan Africa. These analyses show the importance of global atmospheric controls in producing regional intra-annual and inter-annual vegetation variability. Dipole patterns emerge primarily correlated with both the seasonal and inter-annual extent of the Intertropical Convergence Zone (ITCZ). Inter-annual ITCZ variability drives patterns in African vegetation resulting from the effect of insolation anomalies and ENSO events on atmospheric circulation rather than sea surface temperatures or teleconnections to mid/high latitudes. Global controls on tropical atmospheric circulation regulate vegetation throughout sub-Saharan Africa on many time scales through alteration of dry season length and moisture convergence, rather than precipitation amount.

Environmental variation, vegetation distribution, carbon dynamics and water/energy exchange at high latitudes

USGS Publications Warehouse

McGuire, A.D.; Wirth, C.; Apps, M.; Beringer, J.; Clein, J.; Epstein, H.; Kicklighter, D.W.; Bhatti, J.; Chapin, F. S.; De Groot, B.; Efremov, D.; Eugster, W.; Fukuda, M.; Gower, T.; Hinzman, L.; Huntley, B.; Jia, G.J.; Kasischke, E.; Melillo, J.; Romanovsky, V.; Shvidenko, A.; Vaganov, E.; Walker, D.

2002-01-01

The responses of high latitude ecosystems to global change involve complex interactions among environmental variables, vegetation distribution, carbon dynamics, and water and energy exchange. These responses may have important consequences for the earth system. In this study, we evaluated how vegetation distribution, carbon stocks and turnover, and water and energy exchange are related to environmental variation spanned by the network of the IGBP high latitude transects. While the most notable feature of the high latitude transects is that they generally span temperature gradients from southern to northern latitudes, there are substantial differences in temperature among the transects. Also, along each transect temperature co-varies with precipitation and photosynthetically active radiation, which are also variable among the transects. Both climate and disturbance interact to influence latitudinal patterns of vegetation and soil carbon storage among the transects, and vegetation distribution appears to interact with climate to determine exchanges of heat and moisture in high latitudes. Despite limitations imposed by the data we assembled, the analyses in this study have taken an important step toward clarifying the complexity of interactions among environmental variables, vegetation distribution, carbon stocks and turnover, and water and energy exchange in high latitude regions. This study reveals the need to conduct coordinated global change studies in high latitudes to further elucidate how interactions among climate, disturbance, and vegetation distribution influence carbon dynamics and water and energy exchange in high latitudes.

Insufficient acetabular version increases blood metal ion levels after metal-on-metal hip resurfacing.

PubMed

Hart, Alister J; Skinner, John A; Henckel, Johann; Sampson, Barry; Gordon, Fabiana

2011-09-01

Many factors affect the blood metal ion levels after metal-on-metal (MOM) hip arthroplasty. The main surgically adjustable variable is the amount of coverage of the head provided by the cup which is a function of the inclination and version angles. However, most studies have used plain radiographs which have questionable precision and accuracy, particularly for version and large diameter metal heads; further, these studies do not simultaneously assess version and inclination. Thus the relationship between version and blood metal ions levels has not been resolved. We determined whether cup inclination and version influence blood metal ion levels while adjusting for age at assessment, gender, body mass index, horizontal femoral offset, head size, manufacturer hip type, and Oxford hip score. We prospectively followed 100 individuals (51 females, 49 males) with unilateral MOM hip resurfacing who underwent clinical assessment, CT scanning, and blood metal ion measurement. Multiple regression analysis was used to determine which variables were predictors of blood metal ion levels and to model the effect of these variables. Only cup inclination, version angles, and gender influenced blood cobalt or chromium levels. Cobalt and chromium levels positively correlated with inclination angle and negatively correlated with version angle. The effect of changes in version angle was less than for inclination angle. Based on our observations, we developed a formula to predict the effect of these parameters on metal ion levels. Our data suggest insufficient cup version can cause high blood metal ions after MOM hip arthroplasty. We were unable to show that excessive version caused high levels. Level II, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.

IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Das, Kamalika; Kodali, Anuradha; Szubert, Marcin; Ganguly, Sangram; Bongard, Joshua

2016-01-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.

2016-12-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

LANDFIRE 2010 - updated data to support wildfire and ecological management

USGS Publications Warehouse

Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Picotte, Joshua J.

2013-01-01

Wildfire is a global phenomenon that affects human populations and ecosystems. Wildfire effects occur at local to global scales impacting many people in different ways (Figure 1). Ecological concerns due to land use, fragmentation, and climate change impact natural resource use, allocation, and conservation. Access to consistent and current environmental data is a constant challenge, yet necessary for understanding the complexities of wildfire and ecological management. Data products and tools from the LANDFIRE Program help decision-makers to clarify problems and identify possible solutions when managing fires and natural resources. LANDFIRE supports the reduction of risk from wildfire to human lives and property, monitoring of fire danger, prediction of fire behavior on active incidents, and assessment of fire severity and impacts on natural systems [1] [2] [3]. LANDFIRE products are unique in that they are nationally consistent and provide the only complete geospatial dataset describing vegetation and wildland fuel information for the entire U.S. As such, LANDFIRE data are useful for many ecological applications [3]. For example, LANDFIRE data were recently integrated into a decision-support system for resource management and conservation decision-making along the Appalachian Trail. LANDFIRE is a joint effort between the U.S. Department of the Interior Office of Wildland Fire, U.S. Department of Agriculture Forest Service Fire & Aviation Management, and The Nature Conservancy. To date, seven versions of LANDFIRE data have been released, with each successive version improving the quality of the data, adding additional features, and/or updating the time period represented by the data. The latest version, LANDFIRE 2010 (LF 2010), released mid-2013, represents circa 2010 landscape conditions and succeeds LANDFIRE 2008 (LF 2008), which represented circa 2008 landscape conditions. LF 2010 used many of the same processes developed for the LF 2008 effort [3]. Ongoing refinement of the LANDFIRE vegetation and fuel data is necessary to improve the quality and usability of the data and to capture landscape disturbance. LANDFIRE relies on Landsat multi-spectral imagery to produce and update vegetation and fuel data. The deep Landsat archive provides data needed for vegetation classification, change analysis, and historical disturbance characterization, for which LANDFIRE has used more than 24,000 image scenes since the program’s inception. In addition, LF 2010 used airborne and spaceborne lidar, and spaceborne synthetic aperture radar (SAR) to map vegetation structure in areas where ground-based field information was lacking, including Alaska and U.S.-affiliated islands in the Caribbean and the Pacific. The mapping of insular areas is new for the 2010 data release; previous versions of LANDFIRE were limited to the conterminous U.S., Alaska, and Hawaii.

Can individual cognitions, self-regulation and environmental variables explain educational differences in vegetable consumption?: a cross-sectional study among Dutch adults.

PubMed

Springvloet, Linda; Lechner, Lilian; Oenema, Anke

2014-12-06

Educational differences in health-related behaviors, where low- and moderate-educated individuals have poorer outcomes than high-educated individuals, are persistent. The reasons for these differences remain poorly understood. This study explored whether individual cognitions, self-regulation and environmental-level factors may explain educational differences in vegetable consumption. A cross-sectional study was conducted among 1,342 Dutch adults, of whom 54.5% were low/moderate-educated. Individuals completed an online questionnaire, assessing education, vegetable consumption, demographics, individual cognitions (attitude towards consuming 200 grams of vegetables a day, self-efficacy, subjective norm, intention, perception of vegetables as being expensive), self-regulation (general self-regulation, vegetable-specific action- and coping planning) and environmental-level factors (perception of availability of vegetables in the supermarket and availability of vegetables at home). The joint-significance test was used to determine significant mediation effects. Low/moderate-educated individuals consumed less vegetables (M = 151.2) than high-educated individuals (M = 168.1, β = -0.15, P < .001). Attitude and availability of vegetables at home were found to partially mediate the association between education and vegetable consumption (percentage mediated effect: 24.46%). Since attitude and availability of vegetables at home partially explain the difference in vegetable consumption between low/moderate- and high-educated individuals, these variables may be good target points for interventions to promote vegetable consumption among low/moderate-educated individuals.

A Comparative Analysis between GIMSS NDVIg and NDVI3g for Monitoring Vegetation Activity Change in the Northern Hemisphere during 1982-2008

DOE PAGES

Jiang, Nan; Zhu, Wenquan; Zheng, Zhoutao; ...

2013-08-12

The long-term Normalized Difference Vegetation Index (NDVI) time-series data set generated from the Advanced Very High Resolution Radiometers (AVHRR) has been widely used to monitor vegetation activity change. The third version of NDVI (NDVI3g) produced by the Global Inventory Modeling and Mapping Studies (GIMMS) group was released recently. The comparisons between the new and old versions should be conducted for linking existing studies with future applications of NDVI3g in monitoring vegetation activity change. Based on simple and piecewise linear regression methods, this research made a comparative analysis between NDVIg and NDVI3g for monitoring vegetation activity change and its responses tomore » climate change in the middle and high latitudes of the Northern Hemisphere during 1982–2008. Our results indicated that there were large differences between NDVIg and NDVI3g in the spatial patterns for both the overall changing trends and the timing of Turning Points (TP) in NDVI time series, which spread over almost the entire study region. The average NDVI trend from NDVI3g was almost twice as great as that from NDVIg and the detected average timing of TP from NDVI3g was about one year later. Although the general spatial patterns were consistent between two data sets for detecting the responses of growing-season NDVI to temperature and precipitation changes, there were large differences in the response magnitude, with a higher response magnitude to temperature in NDVI3g and an opposite response to precipitation change for the two data sets. Finally, these results demonstrated that the NDVIg data set may underestimate the vegetation activity change trend and its response to climate change in the middle and high latitudes of the Northern Hemisphere during the past three decades.« less

Doing It Right: 366 answers to computing questions you didn't know you had

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

Herring, Stuart Davis

Slides include information on history: version control, version control: branches, version control: Git, releases, requirements, readability, readability control flow, global variables, architecture, architecture redundancy, processes, input/output, unix, etcetera.

Learning to eat vegetables in early life: the role of timing, age and individual eating traits.

PubMed

Caton, Samantha J; Blundell, Pam; Ahern, Sara M; Nekitsing, Chandani; Olsen, Annemarie; Møller, Per; Hausner, Helene; Remy, Eloïse; Nicklaus, Sophie; Chabanet, Claire; Issanchou, Sylvie; Hetherington, Marion M

2014-01-01

Vegetable intake is generally low among children, who appear to be especially fussy during the pre-school years. Repeated exposure is known to enhance intake of a novel vegetable in early life but individual differences in response to familiarisation have emerged from recent studies. In order to understand the factors which predict different responses to repeated exposure, data from the same experiment conducted in three groups of children from three countries (n = 332) aged 4-38 m (18.9±9.9 m) were combined and modelled. During the intervention period each child was given between 5 and 10 exposures to a novel vegetable (artichoke puree) in one of three versions (basic, sweet or added energy). Intake of basic artichoke puree was measured both before and after the exposure period. Overall, younger children consumed more artichoke than older children. Four distinct patterns of eating behaviour during the exposure period were defined. Most children were "learners" (40%) who increased intake over time. 21% consumed more than 75% of what was offered each time and were labelled "plate-clearers". 16% were considered "non-eaters" eating less than 10 g by the 5th exposure and the remainder were classified as "others" (23%) since their pattern was highly variable. Age was a significant predictor of eating pattern, with older pre-school children more likely to be non-eaters. Plate-clearers had higher enjoyment of food and lower satiety responsiveness than non-eaters who scored highest on food fussiness. Children in the added energy condition showed the smallest change in intake over time, compared to those in the basic or sweetened artichoke condition. Clearly whilst repeated exposure familiarises children with a novel food, alternative strategies that focus on encouraging initial tastes of the target food might be needed for the fussier and older pre-school children.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

On the sources of vegetation activity variation, and their relation with water balance in Mexico

Treesearch

F. Mora; L.R. Iverson

1998-01-01

Natural landscape surface processes are largely controlled by the relationship between climate and vegetation. Water balance integrates the effects of climate on patterns of vegetation distribution and productivity, and for that season, functional relationships can be established using water balance variables as predictors of vegetation response. In this study, we...

Awareness of Environmental Change, Climate Variability, and Their Role in Prevalence of Mosquitoes among Urban Dwellers in Southern Ghana.

PubMed

Mattah, Precious Agbeko Dzorgbe; Futagbi, Godfred; Mattah, Memuna Mawusi

2018-01-01

This study evaluates the extent to which urban residents of Accra and Sekondi-Takoradi (all of southern Ghana) were aware of environment and climate-related variability. A total of 150 questionnaires were given to adults of 40 years and above who lived in the cities for at least 35 years. SPSS version 16 was used to process the data. Results show that all respondents in Accra Metropolitan Area (AMA) and 96% of them in Sekondi-Takoradi Metropolitan Area (STMA) noted the deteriorating vegetation cover over the cities. Similarly, 93% and 83% of them in AMA and STMA, respectively, observed that land use pattern of the two cities has changed considerably. There was positive and statistically significant correlation between respondents' educational attainment and their awareness of changes in land use/land cover ( r = 0.18, n = 140, p = 0.03). Also, 71% in AMA and 89% in STMA stated that temperature of the cities had been increasing over the years. In all, 82.9% of the respondents mentioned that they had problem with the increasing population of mosquitoes. Respondents demonstrated ample knowledge of environment and climate variability and should be engaged in preventing further environmental degradation. The top-down approach to environmental issues has failed; the bottom-up approach to environmental maintenance is needed.

Vegetation and climate variability in tropical and subtropical South America during the late Quaternary

NASA Astrophysics Data System (ADS)

Behling, H.

2013-05-01

Detailed palynological studies from different ecosystems in tropical and subtropical South America reflect interesting vegetation and climate dynamics, in particular during glacial and late glacial times. Records from ecosystems such as the Amazon rainforest, savanna, Caatinga, Atlantic rainforest, Araucaria forest and grasslands provide interesting insight of past climate variability. The influence of events such as Dansgaard-Oeschger, Heinnrich stadials, changes in the thermohaline circulation (THC) will be discussed. In particular the Younger Dryas (YD) period shows at different places distinct vegetational changes, revealing unexpected past climatic conditions.

[Advance in researches on vegetation cover and management factor in the soil erosion prediction model].

PubMed

Zhang, Yan; Yuan, Jianping; Liu, Baoyuan

2002-08-01

Vegetation cover and land management are the main limiting factors of soil erosion, and quantitative evaluation on the effect of different vegetation on soil erosion is essential to land use and soil conservation planning. The vegetation cover and management factor (C) in the universal soil loss equation (USLE) is an index to evaluate this effect, which has been studied deeply and used widely. However, the C factor study is insufficient in China. In order to strengthen the research of C factor, this paper reviewed the developing progress of C factor, and compared the methods of estimating C value in different USLE versions. The relative studies in China were also summarized from the aspects of vegetation canopy coverage, soil surface cover, and root density. Three problems in C factor study were pointed out. The authors suggested that cropland C factor research should be furthered, and its methodology should be unified in China to represent reliable C values for soil loss prediction and conservation planning.

Nutrition Knowledge, Attitudes, and Fruit and Vegetable Intake as Predictors of Head Start Teachers' Classroom Mealtime Behaviors.

PubMed

Halloran, Katherine Marie; Gorman, Kathleen; Fallon, Megan; Tovar, Alison

2018-04-01

To examine the association between nutrition knowledge, attitudes, and fruit/vegetable intake among Head Start teachers and their classroom mealtime behaviors (self-reported and observed). Cross-sectional design using observation and survey. Sixteen Head Start centers across Rhode Island between September, 2014 and May, 2015. Teachers were e-mailed about the study by directors and were recruited during on-site visits. A total of 85 participants enrolled through phone/e-mail (19%) or in person (81%). Independent variables were nutrition knowledge, attitudes, and fruit/vegetable intake. The dependent variable was classroom mealtime behaviors (self-reported and observed). Regression analyses conducted on teacher mealtime behavior were examined separately for observation and self-report, with knowledge, attitudes, and fruit and vegetable intake as independent variables entered into the models, controlling for covariates. Nutrition attitudes were positively associated with teacher self-reported classroom mealtime behavior total score. Neither teacher nutrition knowledge nor fruit/vegetable intake was associated with observed or self-reported classroom mealtime behavior total scores. There was limited support for associations among teacher knowledge, attitudes, and fruit/vegetable intake, and teacher classroom mealtime behavior. Findings showed that teacher mealtime behavior was significantly associated with teacher experience. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Exploring individual cognitions, self-regulation skills, and environmental-level factors as mediating variables of two versions of a Web-based computer-tailored nutrition education intervention aimed at adults: A randomized controlled trial.

PubMed

Springvloet, Linda; Lechner, Lilian; Candel, Math J J M; de Vries, Hein; Oenema, Anke

2016-03-01

This study explored whether the determinants that were targeted in two versions of a Web-based computer-tailored nutrition education intervention mediated the effects on fruit, high-energy snack, and saturated fat intake among adults who did not comply with dietary guidelines. A RCT was conducted with a basic (tailored intervention targeting individual cognitions and self-regulation), plus (additionally targeting environmental-level factors), and control group (generic nutrition information). Participants were recruited from the general Dutch adult population and randomly assigned to one of the study groups. Online self-reported questionnaires assessed dietary intake and potential mediating variables (behavior-specific cognitions, action- and coping planning, environmental-level factors) at baseline and one (T1) and four (T2) months post-intervention (i.e. four and seven months after baseline). The joint-significance test was used to establish mediating variables at different time points (T1-mediating variables - T2-intake; T1-mediating variables - T1-intake; T2-mediating variables - T2-intake). Educational differences were examined by testing interaction terms. The effect of the plus version on fruit intake was mediated (T2-T2) by intention and fruit availability at home and for high-educated participants also by attitude. Among low/moderate-educated participants, high-energy snack availability at home mediated (T1-T1) the effect of the basic version on high-energy snack intake. Subjective norm mediated (T1-T1) the effect of the basic version on fat intake among high-educated participants. Only some of the targeted determinants mediated the effects of both intervention versions on fruit, high-energy snack, and saturated fat intake. A possible reason for not finding a more pronounced pattern of mediating variables is that the educational content was tailored to individual characteristics and that participants only received feedback for relevant and not for all assessed mediating variables. Netherlands Trial Registry NTR3396. Copyright © 2015. Published by Elsevier Ltd.

Assessing parents' receptiveness to a vegetable-focussed in-school nutrition intervention.

PubMed

Jongenelis, Michelle I; Pettigrew, Simone; Pratt, Iain S; Wright, Shannon; Myers, Gael

2017-10-01

Crunch&Sip is an Australian school-based initiative designed to increase the consumption of fruit, vegetables, and water among primary school children. To address the significant deficiencies in children's vegetable intake, the present study aimed to examine the responsiveness of parents (the main providers of food for Crunch&Sip) to a modified version of the program that focuses primarily on vegetable consumption. A total of 329 Western Australian parents completed an online questionnaire examining their support for a vegetable focus for Crunch&Sip and any perceived barriers, motivators, and facilitators. Most (80%) parents were supportive of a shift to a vegetable focus for Crunch&Sip. Belief in the effectiveness of Crunch&Sip at improving children's attitudes towards vegetables and increasing children's vegetable consumption was found to be significantly associated with levels of support. The most commonly nominated motivator was to improve their children's eating habits and the main facilitator was the perceived ability of teachers and peers to influence children's food consumption behaviours. Identified potential barriers included the difficulties associated with providing a variety of vegetables, maintaining freshness, and the preparation time required. The primary suggested strategy to overcome these barriers was for schools to conduct education sessions to provide information about vegetable provision options. The results suggest that parents can be supportive of school-based nutrition programs that specifically encourage the consumption of vegetables but they may require guidance to reduce the identified barriers related to vegetable provision. Copyright © 2017 Elsevier Ltd. All rights reserved.

Which Food Security Determinants Predict Adequate Vegetable Consumption among Rural Western Australian Children?

PubMed Central

Godrich, Stephanie L.; Lo, Johnny; Davies, Christina R.; Darby, Jill; Devine, Amanda

2017-01-01

Improving the suboptimal vegetable consumption among the majority of Australian children is imperative in reducing chronic disease risk. The objective of this research was to determine whether there was a relationship between food security determinants (FSD) (i.e., food availability, access, and utilisation dimensions) and adequate vegetable consumption among children living in regional and remote Western Australia (WA). Caregiver-child dyads (n = 256) living in non-metropolitan/rural WA completed cross-sectional surveys that included questions on FSD, demographics and usual vegetable intake. A total of 187 dyads were included in analyses, which included descriptive and logistic regression analyses via IBM SPSS (version 23). A total of 13.4% of children in this sample had adequate vegetable intake. FSD that met inclusion criteria (p ≤ 0.20) for multivariable regression analyses included price; promotion; quality; location of food outlets; variety of vegetable types; financial resources; and transport to outlets. After adjustment for potential demographic confounders, the FSD that predicted adequate vegetable consumption were, variety of vegetable types consumed (p = 0.007), promotion (p = 0.017), location of food outlets (p = 0.027), and price (p = 0.043). Food retail outlets should ensure that adequate varieties of vegetable types (i.e., fresh, frozen, tinned) are available, vegetable messages should be promoted through food retail outlets and in community settings, towns should include a range of vegetable purchasing options, increase their reliance on a local food supply and increase transport options to enable affordable vegetable purchasing. PMID:28054955

Which Food Security Determinants Predict Adequate Vegetable Consumption among Rural Western Australian Children?

PubMed

Godrich, Stephanie L; Lo, Johnny; Davies, Christina R; Darby, Jill; Devine, Amanda

2017-01-03

Improving the suboptimal vegetable consumption among the majority of Australian children is imperative in reducing chronic disease risk. The objective of this research was to determine whether there was a relationship between food security determinants (FSD) (i.e., food availability, access, and utilisation dimensions) and adequate vegetable consumption among children living in regional and remote Western Australia (WA). Caregiver-child dyads ( n = 256) living in non-metropolitan/rural WA completed cross-sectional surveys that included questions on FSD, demographics and usual vegetable intake. A total of 187 dyads were included in analyses, which included descriptive and logistic regression analyses via IBM SPSS (version 23). A total of 13.4% of children in this sample had adequate vegetable intake. FSD that met inclusion criteria ( p ≤ 0.20) for multivariable regression analyses included price; promotion; quality; location of food outlets; variety of vegetable types; financial resources; and transport to outlets. After adjustment for potential demographic confounders, the FSD that predicted adequate vegetable consumption were, variety of vegetable types consumed ( p = 0.007), promotion ( p = 0.017), location of food outlets ( p = 0.027), and price ( p = 0.043). Food retail outlets should ensure that adequate varieties of vegetable types (i.e., fresh, frozen, tinned) are available, vegetable messages should be promoted through food retail outlets and in community settings, towns should include a range of vegetable purchasing options, increase their reliance on a local food supply and increase transport options to enable affordable vegetable purchasing.

Herbaceous versus forested riparian vegetation: narrow and simple versus wide, woody and diverse stream habitat

Treesearch

C.R. Jackson; D.S. Leigh; S.L. Scarbrough; J.F. Chamblee

2014-01-01

We investigated interactions of riparian vegetative conditions upon a suite of channel morphological variables: active channel width, variability of width within a reach, large wood frequency, mesoscale habitat distributions, mesoscale habitat diversity, median particle size and per cent fines. We surveyed 49 wadeable streams, 45 with low levels of development,...

Examining the relationship between vegetable intake of mothers and that of their children: a cross-sectional study of 10- to 12-year-old schoolchildren in Japan.

PubMed

Tada, Yuki; Tomata, Yasutake; Sunami, Ayaka; Yokoyama, Yuri; Hida, Azumi; Furusho, Tadasu; Kawano, Yukari

2015-12-01

The present study aimed to investigate the correlation between mothers' and children's vegetable intake and whether children are conscious about their vegetable intake. Cross-sectional study. Self-administered questionnaires for mothers and children, consisting of items regarding diet history, were distributed to children via homeroom teachers. We created dummy exposure variables for each quartile of mothers' vegetable intake. Multiple regression analysis was performed with children's vegetable intake as the outcome variable. Two public elementary schools in a residential district of Tokyo, Japan. Study participants were upper-grade children (aged 10-12 years) and their mothers (332 pairs of mothers and children). The mean vegetable intake in mothers and children was 310 (sd 145) g/d and 276 (sd 105) g/d, respectively. A positive linear relationship was found between mothers' and children's vegetable intake even after adjustment for considerable covariates (P<0·001). When stratified by children's consciousness, the positive linear relationship was more pronounced in children who were conscious of eating all their vegetables (P<0·001 for interaction with children's consciousness). Mothers' vegetable intake was significantly correlated with children's vegetable intake. However, this correlation was stronger in children who were conscious of eating all their vegetables. Our findings suggest that enhancing mother's vegetable intake and health consciousness of children are indispensable prerequisites for increasing vegetable intake among children.

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

Chorological classification approach for species and ecosystem conservation practice

NASA Astrophysics Data System (ADS)

Rogova, T. V.; Kozevnikova, M. V.; Prokhorov, V. E.; Timofeeva, N. O.

2018-01-01

The habitat type allocation approach based on the EUNIS Habitat Classification and the JUICE version 7 software is used for the conservation of species and ecosystem biodiversity. Using the vegetation plots of the Vegetation Database of Tatarstan, included in the EVA (European Vegetation Archive) and GIVD (Global Index of Vegetation-plots Databases) types of habitats of dry meadows and steppes are distinguished by differing compositions of the leading families composing their flora - Asteraceae, Fabaceae, Poaceae and Rosaceae. E12a - Semi-dry perennial calcareous grassland, and E12b - Perennial calcareous grassland and basic steppes were identified. The selected group of relevés that do not correspond to any of the EUNIS types can be considered specific for ecotone forest-steppe landscapes of the southeast of the Republic of Tatarstan. In all types of studied habitats, rare and protected plant species are noted, most of which are South-East-European-Asian species.

Potential climatic impacts of vegetation change: A regional modeling study

NASA Astrophysics Data System (ADS)

Copeland, Jeffrey H.; Pielke, Roger A.; Kittel, Timothy G. F.

1996-03-01

The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage.

Potential climatic impacts of vegetation change: A regional modeling study

USGS Publications Warehouse

Copeland, J.H.; Pielke, R.A.; Kittel, T.G.F.

1996-01-01

The human species has been modifying the landscape long before the development of modern agrarian techniques. Much of the land area of the conterminous United States is currently used for agricultural production. In certain regions this change in vegetative cover from its natural state may have led to local climatic change. A regional climate version of the Colorado State University Regional Atmospheric Modeling System was used to assess the impact of a natural versus current vegetation distribution on the weather and climate of July 1989. The results indicate that coherent regions of substantial changes, of both positive and negative sign, in screen height temperature, humidity, wind speed, and precipitation are a possible consequence of land use change throughout the United States. The simulated changes in the screen height quantities were closely related to changes in the vegetation parameters of albedo, roughness length, leaf area index, and fractional coverage. Copyright 1996 by the American Geophysical Union.

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Shen, Sunhung; Leptoukh, Gregory G.; Gerasimov, Irina

2012-01-01

Vegetation growth depends on local climate. Significant anthropogenic land cover and land use change activities over Asia have changed vegetation distribution as well. On the other hand, vegetation is one of the important land surface variables that influence the Asian Monsoon variability through controlling atmospheric energy and water vapor conditions. In this presentation, the mean and variations of vegetation index of last decade at regional scale resolution (5km and higher) from MODIS have been analyzed. Results indicate that the vegetation index has been reduced significantly during last decade over fast urbanization areas in east China, such as Yangtze River Delta, where local surface temperatures were increased significantly in term of urban heat Island. The relationship between vegetation Index and climate (surface temperature, precipitation) over a grassland in northern Asia and over a woody savannas in southeast Asia are studied. In supporting Monsoon Asian Integrated Regional Study (MAIRS) program, the data in this study have been integrated into Giovanni, the online visualization and analysis system at NASA GES DISC. Most images in this presentation are generated from Giovanni system.

Seasonally asymmetric enhancement of northern vegetation productivity

NASA Astrophysics Data System (ADS)

Park, T.; Myneni, R.

2017-12-01

Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

Noise-induced transitions and shifts in a climate-vegetation feedback model.

PubMed

Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B

2018-04-01

Motivated by the extremely important role of the Earth's vegetation dynamics in climate changes, we study the stochastic variability of a simple climate-vegetation system. In the case of deterministic dynamics, the system has one stable equilibrium and limit cycle or two stable equilibria corresponding to two opposite (cold and warm) climate-vegetation states. These states are divided by a separatrix going across a point of unstable equilibrium. Some possible stochastic scenarios caused by different externally induced natural and anthropogenic processes inherit properties of deterministic behaviour and drastically change the system dynamics. We demonstrate that the system transitions across its separatrix occur with increasing noise intensity. The climate-vegetation system therewith fluctuates, transits and localizes in the vicinity of its attractor. We show that this phenomenon occurs within some critical range of noise intensities. A noise-induced shift into the range of smaller global average temperatures corresponding to substantial oscillations of the Earth's vegetation cover is revealed. Our analysis demonstrates that the climate-vegetation interactions essentially contribute to climate dynamics and should be taken into account in more precise and complex models of climate variability.

Vegetation and Carbon Cycle Dynamics in the High-Resolution Transient Holocene Simulations Using the MPI Earth System Model

NASA Astrophysics Data System (ADS)

Brovkin, V.; Lorenz, S.; Raddatz, T.; Claussen, M.; Dallmeyer, A.

2017-12-01

One of the interesting periods to investigate a climatic role of terrestrial biosphere is the Holocene, when, despite of the relatively steady global climate, the atmospheric CO2 grew by about 20 ppm from 7 kyr BP to pre-industrial. We use a new setup of the Max Planck Institute Earth System Model MPI-ESM1 consisting of the latest version of the atmospheric model ECHAM6, including the land surface model JSBACH3 with carbon cycle and vegetation dynamics, coupled to the ocean circulation model MPI-OM, which includes the HAMOCC model of ocean biogeochemistry. The model has been run for several simulations over the Holocene period of the last 8000 years under the forcing data sets of orbital insolation, atmospheric greenhouse gases, volcanic aerosols, solar irradiance and stratospheric ozone, as well as land-use changes. In response to this forcing, the land carbon storage increased by about 60 PgC between 8 and 4 kyr BP, stayed relatively constant until 2 kyr BP, and decreased by about 90 PgC by 1850 AD due to land use changes. At 8 kyr BP, vegetation cover was much denser in Africa, mainly due to increased rainfall in response to the orbital forcing. Boreal forests moved northward in both, North America and Eurasia. The boreal forest expansion in North America is much less pronounced than in Eurasia. Simulated physical ocean fields, including surface temperatures and meridional overturning, do not change substantially in the Holocene. Carbonate ion concentration in deep ocean decreases in both, prescribed and interactive CO2simulations. Comparison with available proxies for terrestrial vegetation and for the ocean carbonate chemistry will be presented. Vegetation and soil carbon changes significantly affected atmospheric CO2 during the periods of strong volcanic eruptions. In response to the eruption-caused cooling, the land initially stores more carbon as respiration decreases, but then it releases even more carbon die to productivity decrease. This decadal-scale variability helps to quantify the vegetation and land carbon feedbacks during the past periods when the temporal resolution of the ice-core CO2 record is not sufficient to capture fast CO2 variations. From a set of Holocene simulations with prescribed or interactive atmospheric CO2, we get estimates of climate-carbon feedback useful for future climate studies.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Responses of the terrestrial carbon cycle to drought: modeling sensitivities of the interactive nitrogen and dynamic vegetation

NASA Astrophysics Data System (ADS)

Jia, B.; Wang, Y.; Xie, Z.

2016-12-01

Drought can trigger both immediate and time-lagged responses of terrestrial ecosystems and even cause sizeable positive feedbacks to climate warming. In this study, the influences of interactive nitrogen (N) and dynamic vegetation (DV) on the response of the carbon cycle in terrestrial ecosystems of China to drought were investigated using the Community Land Model version 4.5 (CLM4.5). Model simulations from three configurations of CLM4.5 (C, carbon cycle only; CN, dynamic carbon and nitrogen cycle; CNDV, dynamic carbon and nitrogen cycle as well as dynamic vegetation) between 1961 and 2010 showed that the incorporation of a prognostic N cycle and DV into CLM4.5 reduce the predicted annual means and inter-annual variability of predicted gross primary production (GPP) and net ecosystem production (NEP), except for a slight increase in NEP for CNDV compared to CN. These model improvements resulted in better agreement with observations (7.0 PgC yr-1) of annual GPP over the terrestrial ecosystems in China for CLM45-CN (7.5 PgC yr-1) and CLM45-CNDV (7.3 PgC yr-1) than for CLM45-C (10.9 PgC yr-1). Compared to the CLM45-C, the carbon-nitrogen coupling strengthened the predicted response of GPP to drought, resulting in a higher correlation with the standardized precipitation index (SPI; rC = 0.62, rCN = 0.67), but led to a weaker sensitivity of NEP to SPI (rC = 0.51, rCN = 0.45). The CLM45-CNDV had the longest lagged responses of GPP to drought among the three configurations. These results enhance our understanding of the response of the terrestrial carbon cycle to drought.

Ecological controls on water-cycle response to climate variability in deserts

PubMed Central

Scanlon, B. R.; Levitt, D. G.; Reedy, R. C.; Keese, K. E.; Sully, M. J.

2005-01-01

The impact of climate variability on the water cycle in desert ecosystems is controlled by biospheric feedback at interannual to millennial timescales. This paper describes a unique field dataset from weighing lysimeters beneath nonvegetated and vegetated systems that unequivocally demonstrates the role of vegetation dynamics in controlling water cycle response to interannual climate variability related to El Niño southern oscillation in the Mojave Desert. Extreme El Niño winter precipitation (2.3-2.5 times normal) typical of the U.S. Southwest would be expected to increase groundwater recharge, which is critical for water resources in semiarid and arid regions. However, lysimeter data indicate that rapid increases in vegetation productivity in response to elevated winter precipitation reduced soil water storage to half of that in a nonvegetated lysimeter, thereby precluding deep drainage below the root zone that would otherwise result in groundwater recharge. Vegetation dynamics have been controlling the water cycle in interdrainage desert areas throughout the U.S. Southwest, maintaining dry soil conditions and upward soil water flow since the last glacial period (10,000-15,000 yr ago), as shown by soil water chloride accumulations. Although measurements are specific to the U.S. Southwest, correlations between satellite-based vegetation productivity and elevated precipitation related to El Niño southern oscillation indicate this model may be applicable to desert basins globally. Understanding the two-way coupling between vegetation dynamics and the water cycle is critical for predicting how climate variability influences hydrology and water resources in water-limited landscapes. PMID:15837922

Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-05-01

This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Recovery of endemic dragonflies after removal of invasive alien trees.

PubMed

Samways, Michael J; Sharratt, Norma J

2010-02-01

Because dragonflies are very sensitive to alien trees, we assessed their response to large-scale restoration of riparian corridors. We compared three types of disturbance regime--alien invaded, cleared of alien vegetation, and natural vegetation (control)--and recorded data on 22 environmental variables. The most significant variables in determining dragonfly assemblages were percentage of bank cover and tree canopy cover, which indicates the importance of vegetation architecture for these dragonflies. This finding suggests that it is important to restore appropriate marginal vegetation and sunlight conditions. Recovery of dragonfly assemblages after the clearing of alien trees was substantial. Species richness and abundance at restored sites matched those at control sites. Dragonfly assemblage patterns reflected vegetation succession. Thus, initially eurytopic, widespread species were the main beneficiaries of the removal of alien trees, and stenotopic, endemic species appeared after indigenous vegetation recovered over time. Important indicator species were the two national endemics (Allocnemis leucosticta and Pseudagrion furcigerum), which, along with vegetation type, can be used to monitor return of overall integrity of riparian ecology and to make management decisions. Endemic species as a whole responded positively to restoration, which suggests that indigenous vegetation recovery has major benefits for irreplaceable and widespread generalist species.

Social support is a primary influence on home fruit, 100% juice, and vegetable availability.

PubMed

Baranowski, Tom; Watson, Kathy; Missaghian, Mariam; Broadfoot, Alison; Cullen, Karen; Nicklas, Theresa; Fisher, Jennifer; Baranowski, Janice; O'Donnell, Sharon

2008-07-01

Children tend to eat more fruit and vegetables when more are available in the home. We proposed and tested a model that predicts the availability at home (hereinafter termed "home availability") of fruit, 100% juice, and vegetables, using new measures of frequency of food shopping, purchase, and comparative purchase outcome expectancies (ie, the perceived benefits and costs of purchasing fruit and vegetables), home food pantry management practices, family social support for purchasing fruit and vegetables, food shopping practices, and body mass index (BMI). Participants (N=98) were recruited in 2004 in front of grocery stores and completed two telephone interviews. Cross-sectional hierarchical regression was employed with backward deletion of nonsignificant variables. Despite many statistically significant bivariate correlations between the new variables and home fruit, 100% juice, and vegetable availability, social support was the primary predictor of home fruit availability in multivariate regression. BMI and home 100% juice pantry management were the primary predictors of home 100% juice availability. Social support, BMI, and shopping practices were the primary predictors of home vegetable availability. Social support for purchasing fruit, 100% juice, and vegetables was an important, consistent predictor of home availability. These findings need to be replicated in larger samples.

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

PubMed

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

2012-06-01

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

Psychosocial correlates of fruit and vegetable consumption among African American men.

PubMed

Moser, Richard P; Green, Valerie; Weber, Deanne; Doyle, Colleen

2005-01-01

To determine the best predictors of fruit and vegetable consumption among African American men age 35 years and older. Data (n = 291) from a 2001 nationally representative mail survey commissioned by the American Cancer Society. 291 African American men age 35 years and older. (1) total fruits and vegetables without fried potatoes, (2) total fruit with juice, and (3) total vegetables without fried potatoes. Independent variables included 3 blocks of predictors: (1) demographics, (2) a set of psychosocial scales, and (3) intent to change variables based on a theoretical algorithm. Linear regression models; analysis of variance for the intent to change group. Alpha = .05. Regression model for total fruits and vegetables, significant psychosocial predictors: social norms, benefits, tangible rewards, and barriers-other. Total fruit with juice: social norms, benefits, tangible rewards. Total vegetables, no fried potatoes: tangible rewards, barriers-other interests. For African American men, fruit consumption appears to be motivated by perceived benefits and standards set by important people in their lives; vegetable consumption is a function of extrinsic rewards and preferences for high-calorie, fatty foods. The results suggest that communications to increase fruit and vegetable consumption should be crafted to reflect differences in sources of motivation for eating fruits versus eating vegetables.

Microhabitat influence on larval fish assemblages within vegetated beds: Implications for restoration

EPA Science Inventory

We examined larval and juvenile fish assemblage structure in relation to microhabitat variables within the St. Louis River estuary, a drowned river mouth of Lake Superior. Fish were sampled in vegetated beds throughout the estuary, across a gradient of vegetation types and densit...

Status of Vegetation Classification in Redwood Ecosystems

Treesearch

Thomas M. Mahony; John D. Stuart

2007-01-01

Vegetation classifications, based primarily on physiognomic variability and canopy dominants and derived principally from remotely sensed imagery, have been completed for the entire redwood range (Eyre 1980, Fox 1989). However, systematic, quantitative, floristic-based vegetation classifications in old-growth redwood forests have not been completed for large portions...

GLEAM v3: satellite-based land evaporation and root-zone soil moisture

NASA Astrophysics Data System (ADS)

Martens, Brecht; Miralles, Diego G.; Lievens, Hans; van der Schalie, Robin; de Jeu, Richard A. M.; Fernández-Prieto, Diego; Beck, Hylke E.; Dorigo, Wouter A.; Verhoest, Niko E. C.

2017-05-01

The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land-atmosphere feedbacks.

SIMPPLLE, version 2.5 user's guide

Treesearch

Jimmie D. Chew; Kirk Moeller; Christine Stalling

2012-01-01

SIMPPLLE is a spatially-interactive, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire, and other natural and management-caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem...

Braided river flow and invasive vegetation dynamics in the Southern Alps, New Zealand.

PubMed

Caruso, Brian S; Edmondson, Laura; Pithie, Callum

2013-07-01

In mountain braided rivers, extreme flow variability, floods and high flow pulses are fundamental elements of natural flow regimes and drivers of floodplain processes, understanding of which is essential for management and restoration. This study evaluated flow dynamics and invasive vegetation characteristics and changes in the Ahuriri River, a free-flowing braided, gravel-bed river in the Southern Alps of New Zealand's South Island. Sixty-seven flow metrics based on indicators of hydrologic alteration and environmental flow components (extreme low flows, low flows, high flow pulses, small floods and large floods) were analyzed using a 48-year flow record. Changes in the areal cover of floodplain and invasive vegetation classes and patch characteristics over 20 years (1991-2011) were quantified using five sets of aerial photographs, and the correlation between flow metrics and cover changes were evaluated. The river exhibits considerable hydrologic variability characteristic of mountain braided rivers, with large variation in floods and other flow regime metrics. The flow regime, including flood and high flow pulses, has variable effects on floodplain invasive vegetation, and creates dynamic patch mosaics that demonstrate the concepts of a shifting mosaic steady state and biogeomorphic succession. As much as 25 % of the vegetation cover was removed by the largest flood on record (570 m(3)/s, ~50-year return period), with preferential removal of lupin and less removal of willow. However, most of the vegetation regenerated and spread relatively quickly after floods. Some flow metrics analyzed were highly correlated with vegetation cover, and key metrics included the peak magnitude of the largest flood, flood frequency, and time since the last flood in the interval between photos. These metrics provided a simple multiple regression model of invasive vegetation cover in the aerial photos evaluated. Our analysis of relationships among flow regimes and invasive vegetation cover has implications for braided rivers impacted by hydroelectric power production, where increases in invasive vegetation cover are typically greater than in unimpacted rivers.

Dependence of Wetland Vegetation on Hydrological Regime in a Large Floodplain Lake (Poyang Lake) in the Middle Yangtze River

NASA Astrophysics Data System (ADS)

Zhang, Q.; Tan, Z.; Xu, X.

2017-12-01

Exemplified in the Yangtze River floodplain lake, Poyang Lake, investigations were carried out to examine the dependence of vegetation on hydrological variables. The Lake is one of the few lakes that remain naturally connected to the Yangtze River. The Lake surface expanses to 4000 km2 in wet seasons, and reduces to less than 1000 km2 in dry seasons, creating some 3000 km2 vital wetland habitats for many animals. Remote sensing was used to obtain the spatial distribution of wetland vegetations. A lake hydrodynamic model using MIKE 21 was employed to determine the variability of wetland inundation. In-situ high time frequency observations of climate, soil moisture, and groundwater depth were also conducted in a typical wetland transect of 1 km long. Vegetations were sampled periodically to obtain species composition, diversity and biomass. Results showed that the spatial distribution of vegetation highly depended on the inundation duration and depth. Optimal hydrological variables existed for the typical vegetations in Poyang Lake wetland. Numerical simulations using HYDRUS-1D further demonstrated that both groundwater depth and soil moisture had significant effects on the growth of vegetation and the water demand in terms of transpiration, even in a wet climate zone such as middle Yangtze River. It was found that the optimal groundwater depths existed for both above- and belowground biomass. Simulation scenarios indicated that climate changes and human modification of hydrology would affect the water usage of vegetation and may cause a strategic adaptation of the vegetation to the stressed hydrological conditions. The study revealed new knowledge on the high dependence of wetland vegetation on both surface water regime and groundwater depths, in wet climate zone. Outcomes of this study may provide support for an integrated management of balancing water resources development and wetland sustainability maintenance in Poyang Lake, and other floodplain wetlands, with strong natural and human interferences.

Use of a cable-based system for observing the heterogeneity of vegetation communities in arctic tundra

NASA Astrophysics Data System (ADS)

Ahrends, H. E.; Oberbauer, S. F.; Tweedie, C.; Hollister, R. D.

2010-12-01

Knowledge of changing tundra vegetation and its response to climate variability is critical for understanding the land-atmosphere-interactions for the Arctic and the global system. However, vegetation characteristics, such as phenology, structure and species composition, are characterized by an extreme heterogeneity at a small scale. Manual observations of these variables are highly time-consuming, labor intensive, subjective, and disturbing to the vegetation. In contrast, recently developed robotic systems (networked infomechanical systems, NIMS) allow for performing non-intrusive spatially integrated measurements of vegetation communities. Within the ITEX (International Tundra Experiment) AON (Arctic Observation Network) project we installed a cable-based sensor system, running over a transect of approximately 50 m length and 2 m width, at two long-term arctic research sites in Alaska. The trolley was initially equipped with instruments recording the distance to vegetation canopy, up- and downwelling short- and longwave radiation, air and surface temperature and spectral reflection. We aim to study the thermal and spectral response of the vegetation communities over a wide range of ecosystem types. We expect that automated observations, covering the spatial heterogeneity of vegetation and surface characteristics, can give a deeper insight in ecosystem functioning and vegetation response to climate. The data can be used for scaling up vegetation characteristics derived from manual measurements and for linking them to aircraft and satellite data and to carbon, water and surface energy budgets measured at the ecosystem scale. Sampling errors due to cable sag are correctable and effects of wind-driven movements can be offset by repeat measurements. First hand-pulled test measurements during summer 2010 show strong heterogeneity of the observation parameters and a variable spectral and thermal response of the plants within the transects. Differences support the importance of our approach for upscaling purposes and for a comprehensive understanding of the arctic biome.

Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA

USGS Publications Warehouse

Miller, J.D.; Knapp, E.E.; Key, C.H.; Skinner, C.N.; Isbell, C.J.; Creasy, R.M.; Sherlock, J.W.

2009-01-01

Multispectral satellite data have become a common tool used in the mapping of wildland fire effects. Fire severity, defined as the degree to which a site has been altered, is often the variable mapped. The Normalized Burn Ratio (NBR) used in an absolute difference change detection protocol (dNBR), has become the remote sensing method of choice for US Federal land management agencies to map fire severity due to wildland fire. However, absolute differenced vegetation indices are correlated to the pre-fire chlorophyll content of the vegetation occurring within the fire perimeter. Normalizing dNBR to produce a relativized dNBR (RdNBR) removes the biasing effect of the pre-fire condition. Employing RdNBR hypothetically allows creating categorical classifications using the same thresholds for fires occurring in similar vegetation types without acquiring additional calibration field data on each fire. In this paper we tested this hypothesis by developing thresholds on random training datasets, and then comparing accuracies for (1) fires that occurred within the same geographic region as the training dataset and in similar vegetation, and (2) fires from a different geographic region that is climatically and floristically similar to the training dataset region but supports more complex vegetation structure. We additionally compared map accuracies for three measures of fire severity: the composite burn index (CBI), percent change in tree canopy cover, and percent change in tree basal area. User's and producer's accuracies were highest for the most severe categories, ranging from 70.7% to 89.1%. Accuracies of the moderate fire severity category for measures describing effects only to trees (percent change in canopy cover and basal area) indicated that the classifications were generally not much better than random. Accuracies of the moderate category for the CBI classifications were somewhat better, averaging in the 50%-60% range. These results underscore the difficulty in isolating fire effects to individual vegetation strata when fire effects are mixed. We conclude that the models presented here and in Miller and Thode ([Miller, J.D. & Thode, A.E., (2007). Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 109, 66-80.]) can produce fire severity classifications (using either CBI, or percent change in canopy cover or basal area) that are of similar accuracy in fires not used in the original calibration process, at least in conifer dominated vegetation types in Mediterranean-climate California.

Midlife women, bone health, vegetables, herbs and fruit study. The Scarborough Fair study protocol.

PubMed

Gunn, Caroline A; Weber, Janet L; Kruger, Marlena C

2013-01-10

Bone loss is accelerated in middle aged women but increased fruit/vegetable intake positively affects bone health by provision of micronutrients essential for bone formation, buffer precursors which reduce acid load and phytochemicals affecting inflammation and oxidative stress. Animal studies demonstrated bone resorption inhibiting properties of specific vegetables, fruit and herbs a decade ago. To increase fruit/vegetable intake in post menopausal women to 9 servings/day using a food specific approach to significantly reduce dietary acid load and include specific vegetables, fruit and herbs with bone resorbing inhibiting properties to assess effect on bone turnover, metabolic and inflammatory markers. The Scarborough Fair Study is a randomised active comparator controlled multi centre trial. It aimed to increase fruit and vegetable intake in 100 post menopausal women from ≤ 5 servings/day to ≥ 9 servings/day for 3 months. The women in the dietary intervention were randomly assigned to one of the two arms of the study. Both groups consumed ≥ 9 servings/day of fruit/vegetables and selected herbs but the diet of each group emphasised different fruit/vegetables/herbs with one group (B) selecting from a range of vegetables, fruit and culinary herbs with bone resorbing inhibiting properties. 50 women formed a negative control group (Group C usual diet). Primary outcome variables were plasma bone markers assessed at baseline, 6 weeks and 12 weeks. Secondary outcome variables were plasma inflammation and metabolic markers and urinary electrolytes (calcium, magnesium, potassium and sodium) assessed at baseline and 12 weeks. Dietary intake and urine pH change also were outcome variables. The dietary change was calculated with 3 day diet diaries and a 24 hour recall. Intervention participants kept a twice weekly record of fruit, vegetable and herb intake and urine pH. This study will provide information on midlife women's bone health and how a dietary intervention increasing fruit and vegetable/herb intake affects bone, inflammatory and metabolic markers and urinary electrolyte excretion. It assesses changes in nutrient intake, estimated dietary acid load and sodium: potassium ratios. The study also explores whether specific fruit/vegetables and herbs with bone resorbing properties has an effect on bone markers. ACTRN 12611000763943.

Using MODIS and GRACE to assess water storage in regional Wetlands: Iraqi and Sudd Marsh systems

NASA Astrophysics Data System (ADS)

Becker, R.

2015-12-01

Both The Iraqi (Mesopotamian) Marshes, an extensive wetlands system in Iraq, and the Sudd Marshlands, located in Sudan have been heavily impacted by both human and climate forces over the past decades. The Sudd wetlands are highly variable in size, averaging roughly 30,000 km2, but extending to as large as ~130,000 km2 during the wet seasons, while the Iraqi marshes are smaller, at ~15,000 km2, without the same extent of intra-annual variability. A combination of MODIS and GRACE images from 2003-2015 for the study areas were used to determine the time dependent change in surface water area (SWA) in the marshes, marshland extent and variability in total water storage. Combined open water area and vegetation abundance and cover, as determined by MODIS (NDVI and MNDWI), is highly correlated with total mass variability observed by GRACE (RL05 Tellus land grid). Annual variability in the Iraqi marshes correlates well with combined SWA and vegetation extent. Variability of vegetation in the Sudd marshes is seen to correlate well on an annual basis with water storage variation, and with a 2 month lag (water mass increases and decreases lead vegetation increases and decreases) when examined on a monthly basis. As a result, in both systems, the overall wetlands extent and health is observed to be water limited. Predictions for precipitation variability and human diversions of water through either dam storage or navigation modifications are predicted to lower water availability and lower variability in these systems. These two regional wetlands systems will shrink, with resulting loss in habitat and other ecosystem services.

Microhabitat Influence on Larval Fish Assemblages Within Vegetated Beds: Implications for Tubenose Goby Detection and Invasion

EPA Science Inventory

We examined larval and juvenile fish assemblage structure in relation to microhabitat variables within the St. Louis River estuary, a drowned river mouth of Lake Superior. Fish were sampled in vegetated beds throughout the estuary, across a gradient of vegetation types and densit...

Distance to food stores & adolescent male fruit and vegetable consumption: mediation effects

USDA-ARS?s Scientific Manuscript database

The physical environments in which adolescents reside and their access to food stores may influence their consumption of fruit and vegetables. This association could either be direct or mediated via psychosocial variables or home availability of fruit and vegetables. A greater understanding of these...

Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

USGS Publications Warehouse

Sankey, Joel B.; Munson, Seth M.; Webb, Robert H.; Wallace, Cynthia S.A.; Duran, Cesar M.

2015-01-01

Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

Slow recovery in desert perennial vegetation following prolonged human disturbance

USGS Publications Warehouse

Guo, Q.

2004-01-01

Questions: How long may it take for desert perennial vegetation to recover from prolonged human disturbance and how do different plant community variables (i.e. diversity, density and cover) change during the recovery process? Location: Sonoran Desert, Arizona, USA. Methods: Since protection from grazing from 1907 onwards, plant diversity, density and cover of perennial species were monitored intermittently on ten 10 m x 10 m permanent plots on Tumamoc Hill, Tucson, Arizona, USA. Results: The study shows an exceptionally slow recovery of perennial vegetation from prolonged heavy grazing and other human impacts. Since protection, overall species richness and habitat heterogeneity at the study site continued to increase until the 1960s when diversity, density and cover had been stabilized. During the same period, overall plant density and cover also increased. Species turnover increased gradually with time but no significant relation between any of the three community variables and precipitation or Palmer Drought Severity Index (PDSI) was detected. Conclusions: It took more than 50 yr for the perennial vegetation to recover from prolonged human disturbance. The increases in plant species richness, density, and cover of the perennial vegetation were mostly due to the increase of herbaceous species, especially palatable species. The lack of a clear relationship between environment (e.g. precipitation) and community variables suggests that site history and plant life history must be taken into account in examining the nature of vegetation recovery processes after disturbance.

Validation of the Italian version of the Coma Recovery Scale-Revised (CRS-R).

PubMed

Sacco, Simona; Altobelli, Emma; Pistarini, Caterina; Cerone, Davide; Cazzulani, Benedetta; Carolei, Antonio

2011-01-01

To validate the Italian version of the Coma Recovery Scale-Revised (CRS-R). Two observers applied the Italian version of the CRS-R to selected patients. On day 1, observer A and B independently scored each patient; the comparison of their observations was used to evaluate inter-observer agreement. On day 2, observer A completed a second evaluation and the comparison of this observation with that obtained on day 1 by the same observer was used to evaluate test-re-test agreement. For each evaluation, also diagnostic impression (vegetative state/minimally conscious state) was reported. Thirty-eight patients were evaluated (mean age ± SD, 58.9 ± 13.8 years). Inter-observer (ρ = 0.81; p < 0.001) as well as test-re-test agreement (ρ = 0.97; p < 0.001) for the total score was high. Inter-observer agreement was excellent for the communication sub-scale, good for the auditory, visual and motor sub-scales and moderate for the oromotor/verbal and arousal sub-scales. Test-re-test agreement was excellent for the visual, motor, oromotor/verbal and communication sub-scales, good for the auditory sub-scale and moderate for the arousal sub-scale. When considering the diagnostic impression, inter-observer agreement was good (κ = 0.75; p < 0.001) and test-re-test agreement was excellent (κ = 0.92; p < 0.001). The Italian version of the CRS-R can be administered reliably and can be also employed to discriminate patients in vegetative and in minimally conscious state.

Estimating Catchment-Scale Snowpack Variability in Complex Forested Terrain, Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Harpold, A. A.; Brooks, P. D.; Biederman, J. A.; Swetnam, T.

2011-12-01

Difficulty estimating snowpack variability across complex forested terrain currently hinders the prediction of water resources in the semi-arid Southwestern U.S. Catchment-scale estimates of snowpack variability are necessary for addressing ecological, hydrological, and water resources issues, but are often interpolated from a small number of point-scale observations. In this study, we used LiDAR-derived distributed datasets to investigate how elevation, aspect, topography, and vegetation interact to control catchment-scale snowpack variability. The study area is the Redondo massif in the Valles Caldera National Preserve, NM, a resurgent dome that varies from 2500 to 3430 m and drains from all aspects. Mean LiDAR-derived snow depths from four catchments (2.2 to 3.4 km^2) draining different aspects of the Redondo massif varied by 30%, despite similar mean elevations and mixed conifer forest cover. To better quantify this variability in snow depths we performed a multiple linear regression (MLR) at a 7.3 by 7.3 km study area (5 x 106 snow depth measurements) comprising the four catchments. The MLR showed that elevation explained 45% of the variability in snow depths across the study area, aspect explained 18% (dominated by N-S aspect), and vegetation 2% (canopy density and height). This linear relationship was not transferable to the catchment-scale however, where additional MLR analyses showed the influence of aspect and elevation differed between the catchments. The strong influence of North-South aspect in most catchments indicated that the solar radiation is an important control on snow depth variability. To explore the role of solar radiation, a model was used to generate winter solar forcing index (SFI) values based on the local and remote topography. The SFI was able to explain a large amount of snow depth variability in areas with similar elevation and aspect. Finally, the SFI was modified to include the effects of shading from vegetation (in and out of canopy), which further explained snow depth variability. The importance of SFI for explaining catchment-scale snow depth variability demonstrates that aspect is not a sufficient metric for direct radiation in complex terrain where slope and remote topographic shading are significant. Surprisingly, the net effects of interception and shading by vegetation on snow depths were minimal compared to elevation and aspect in these catchments. These results suggest that snowpack losses from interception may be balanced by increased shading to reduce the overall impacts from vegetation compared to topographic factors in this high radiation environment. Our analysis indicated that elevation and solar radiation are likely to control snow variability in larger catchments, with interception and shading from vegetation becoming more important at smaller scales.

Spatial variability of mountain stream dynamics along the Ethiopian Rift Valley escarpment

NASA Astrophysics Data System (ADS)

Asfaha, Tesfaalem-Ghebreyohannes; Frankl, Amaury; Zenebe, Amanuel; Haile, Mitiku; Nyssen, Jan

2014-05-01

Changes in hydrogeomorphic characteristics of mountain streams are generally deemed to be controlled mainly by land use/cover changes and rainfall variability. This study investigates the spatial variability of peak discharge in relation to land cover, rainfall and topographic variables in eleven catchments of the Ethiopian Rift Valley escarpment (average slope gradient = 48% (± 13%). Rapid deforestation of the escarpment in the second half of the 20th century resulted in the occurrence of strong flash floods, transporting large amounts of discharge and sediment to the lower graben bottom. Due to integrated reforestation interventions as of the 1980s, many of these catchments do show improvement in vegetation cover at various degrees. Daily rainfall was measured using seven non-recording rain gauges, while peak stage discharges were measured after floods using crest stage gauges installed at eleven stream reaches. Peak discharges were calculated using the Manning's equation. Daily area-weighted rainfall was computed for each catchment using the Thiessen Polygon method. To estimate the vegetation cover of each catchment, the Normalized Difference Vegetation Index was calculated from Landsat TM imagery (mean = 0.14 ± 0.05). In the rainy season of 2012, there was a positive correlation between daily rainfall and peak discharge in each of the monitored catchments. In a multiple linear regression analysis (R² = 0.83; P<0.01), average daily peak discharge in all rivers was positively related with rainfall depth and catchment size and negatively with vegetation cover (as represented by average NDVI values). Average slope gradient of the catchments and Gravelius's compactness index did not show a statistically significant relation with peak discharge. This study shows that though the average vegetation cover of the catchments is still relatively low, differences in vegetation cover, together with rainfall variability plays a determining role in the amount of peak discharges in flashy mountain streams.

Vegetation Variability And Its Effect On Monsoon Rainfall Over South East Asia: Observational and Modeling Results

NASA Astrophysics Data System (ADS)

Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.

2005-12-01

Increasing population and urbanization have created stress on developing nations. The quickly shifting patterns of vegetation change in different parts of the world have given rise to the pertinent question of feedback on the climate prevailing on local to regional scales. It is now known with some certainty, that vegetation changes can affect the climate by influencing the heat and water balance. The hydrological cycle particularly is susceptible to changes in vegetation. The Monsoon rainfall forms a vital link in the hydrological cycle prevailing over South East Asia This work examines the variability of vegetation over South East Asia and assesses its impact on the monsoon rainfall. We explain the role of changing vegetation and show how this change has affected the heat and energy balance. We demonstrate the role of vegetation one season earlier in influencing rainfall intensity over specific areas in South East Asia and show the ramification of vegetation change on the summer rainfall behavior. The vegetation variability study specifically focuses on India and China, two of the largest and most populous nations. We have done an assessment to find out the key meteorological and human induced parameters affecting vegetation over the study area through a spatial analysis of monthly NDVI values. This study highlights the role of monsoon rainfall, regional climate dynamics and large scale human induced pollution to be the crucial factors governing the vegetation and vegetation distribution. The vegetation is seen to follow distinct spatial patterns that have been found to be crucial in its eventual impact on monsoon rainfall. We have carried out a series of sensitivity experiments using a land surface hydrologic modeling scheme. The vital energy and water balance parameters are identified and the daily climatological cycles are examined for possible change in behavior for different boundary conditions. It is found that the change from native deciduous forest vegetation to crop land affects monsoon rainfall in two ways: 1) The presence of cropland increases the sensible heat release from ground, increasing the chances for development of forced convection; 2) Large scale irrigation associated with spring crop development creates a moister lower boundary layer thus inducing more moist instability and free convection in the succeeding season.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Soybean varieties discrimination using non-imaging hyperspectral sensor

NASA Astrophysics Data System (ADS)

da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo

2018-03-01

Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Predicting physical activity and fruit and vegetable intake in adolescents: a test of the information, motivation, behavioral skills model.

PubMed

Kelly, Stephanie; Melnyk, Bernadette Mazurek; Belyea, Michael

2012-04-01

Most adolescents do not meet national recommendations regarding physical activity and/or the intake of fruits and vegetables. The purpose of this study was to explore whether variables in the information, motivation, behavioral skills (IMB) model of health promotion predicted physical activity and fruit and vegetable intake in 404 adolescents from 2 high schools in the Southwest United States using structural equation modeling (SEM). The SEM models included theoretical constructs, contextual variables, and moderators. The theoretical relationships in the IMB model were confirmed and were moderated by gender and race. Interventions that incorporate cognitive-behavioral skills building may be a key factor for promoting physical activity as well as fruit and vegetable intake in adolescents. Copyright © 2012 Wiley Periodicals, Inc.

Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products

NASA Astrophysics Data System (ADS)

Wegmann, Martin; Dutra, Emanuel; Jacobi, Hans-Werner; Zolina, Olga

2018-06-01

This study uses daily observations and modern reanalyses in order to evaluate reanalysis products over northern Eurasia regarding the spring snow albedo feedback (SAF) during the period from 2000 to 2013. We used the state-of-the-art reanalyses from ERA-Interim/Land and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) as well as an experimental set-up of ERA-Interim/Land with prescribed short grass as land cover to enhance the comparability with the station data while underlining the caveats of comparing in situ observations with gridded data. Snow depth statistics derived from daily station data are well reproduced in all three reanalyses. However day-to-day albedo variability is notably higher at the stations than for any reanalysis product. The ERA-Interim grass set-up shows improved performance when representing albedo variability and generates comparable estimates for the snow albedo in spring. We find that modern reanalyses show a physically consistent representation of SAF, with realistic spatial patterns and area-averaged sensitivity estimates. However, station-based SAF values are significantly higher than in the reanalyses, which is mostly driven by the stronger contrast between snow and snow-free albedo. Switching to grass-only vegetation in ERA-Interim/Land increases the SAF values up to the level of station-based estimates. We found no significant trend in the examined 14-year time series of SAF, but interannual changes of about 0.5 % K-1 in both station-based and reanalysis estimates were derived. This interannual variability is primarily dominated by the variability in the snowmelt sensitivity, which is correctly captured in reanalysis products. Although modern reanalyses perform well for snow variables, efforts should be made to improve the representation of dynamic albedo changes.

Global change data sets: Excerpts from the Master Directory, version 2.0

NASA Technical Reports Server (NTRS)

Beier, Joy

1992-01-01

The recent awakening to the reality of human-induced changes to the environment has resulted in an organized effort to promote global change research. The goal of this research as outlined by NASA's Earth System Science Committee (Earth System Science: A closer View, 1988) is to understand the entire Earth system on a global scale by describing how its component parts and their interactions have evolved, how they function, and how they may be expected to evolve on all timescales. The practical result is the capacity to predict that evolution over the next decade to century. Key variables important for the study of global change include external forcing factors (solar radiance, UV flux), radiatively and chemically important trace species (CO2, CH4, N2O, etc.), atmospheric response variables (temperature, pressure, winds), landsurface properties (river run-off, snow cover, albedo, soil moisture, vegetation cover), and oceanic variables (sea surface temperature, sea ice extent, sea level ocean wind stress, currents, chlorophyll, biogeochemical fluxes). The purpose of this document is to identify existing data sets available (both remotely sensed and in situ data) covering some of these variables. This is not intended to be a complete list of global change data, but merely a highlight of what is available. The information was extracted from the Master Directory (MD), an on-line scientific data information service which may be used by any researcher. This report contains the coverage dates for the data sets, sources (satellites, instruments) of the data and where they are archived.

An expert system shell for inferring vegetation characteristics

NASA Technical Reports Server (NTRS)

Harrison, P. Ann; Harrison, Patrick R.

1992-01-01

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The report describes the extensions that have been made to the first generation version of VEG. An interface to a file of unkown cover type data has been constructed. An interface that allows the results of VEG to be written to a file has been implemented. A learning system that learns class descriptions from a data base of historical cover type data and then uses the learned class descriptions to classify an unknown sample has been built. This system has an interface that integrates it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented.

78 FR 42736 - Spirotetramat; Proposed Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-17

... CD-ROM the specific information that is claimed as CBI. In addition to one complete version of the...; banana; bulb vegetable group 3-07; low growing berry, except strawberry, subgroup 13-07H; bushberry... exposure to spirotetramat is safe for the general population, including infants and children. In addition...

Medhost: An encyclopedic bibliography of the host plants of the Mediterranean fruit fly, Ceratitis capitata (Wiedemann), version 3.0

USDA-ARS?s Scientific Manuscript database

The Mediterranean fruit fly (Medfly), Ceratitis capitata (Wiedemann), causes direct damage to fruits and vegetables through oviposition and larval feeding. Rigorous quarantine procedures are currently enforced to prevent domestic and transnational spread of Medfly. Accessible and reliable informatio...

SAVEWS Jr. User’s Manual, Version 1.0

DTIC Science & Technology

2014-04-01

Botany 53: 227-233. Mueller-Dombois, D., and H. Ellenberg. 1974. Aims and methods of vegetation ecology. New York: John Wiley & Sons, Inc. Norris...videography. Aquatic Botany 58: 269-287. Sabol, B., R. E. Melton, R. Chamberlain, P. Doering, and K. Haunert. 2002. Evaluation of a digital echo

A streamlined artificial variable free version of simplex method.

PubMed

Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

2015-01-01

This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.

A Streamlined Artificial Variable Free Version of Simplex Method

PubMed Central

Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

2015-01-01

This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement. PMID:25767883

HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

PubMed

Salimon, Cleber; Anderson, Liana

2017-05-22

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

Understanding patterns of vegetation structure and distribution across Great Smoky Mountains National Park using LiDAR and meteorology data

NASA Astrophysics Data System (ADS)

Kumar, J.; Hargrove, W. W.; Norman, S. P.; Hoffman, F. M.

2017-12-01

Great Smoky Mountains National Park (GSMNP) in Tennessee is a biodiversity hotspot and home to a large number of plant, animal and bird species. Driven by gradients of climate (ex. temperature, precipitation regimes), topography (ex. elevation, slope, aspect), geology (ex. soil types, textures, depth), hydrology (ex. drainage, moisture availability) etc. GSMNP offers a diverse composition and distribution of vegetation which in turn supports an array of wildlife. Understanding the vegetation canopy structure is critical to understand, monitor and manage the complex forest ecosystems like the Great Smoky Mountain National Park (GSMNP). Vegetation canopies not only help understand the vegetation, but are also a critically important habitat characteristics of many threatened and endangered animal and bird species that GSMNP is home to. Using airborne Light Detection and Ranging (LiDAR) we characterize the three-dimensional structure of the vegetation. LiDAR based analysis gives detailed insight in the canopy structure (overstory and understory) and its spatial variability within and across forest types. Vegetation structure and spatial distribution show strong correlation with climate, topographic, and edaphic variables and our multivariate analysis not just mines rich and large LiDAR data but presents ecological insights and data for vegetation within the park that can be useful to forest managers in their management and conservation efforts.

The carry-over effects of school gardens on fruit and vegetable availability at home: A randomized controlled trial with low-income elementary schools.

PubMed

Wells, Nancy M; Meyers, Beth M; Todd, Lauren E; Henderson, Charles R; Barale, Karen; Gaolach, Brad; Ferenz, Gretchen; Aitken, Martha; Tse, Caroline C; Pattison, Karen Ostlie; Hendrix, Laura; Carson, Janet B; Taylor, Cayla; Franz, Nancy K

2018-07-01

This group-randomized controlled trial examines the effects of a school garden intervention on availability of fruits and vegetables (FV) in elementary school children's homes. Within each region, low income U.S. schools in Arkansas, Iowa, New York, and Washington State were randomly assigned to intervention group (n = 24) or waitlist control group (n = 22). Children were in grades 2, 4, and 5 at baseline (n = 2768). The garden intervention consisted of both raised-bed garden kits and a series of grade-appropriate lessons. FV availability at home was measured with a modified version of the GEMS FJV Availability Questionnaire. The instrument was administered at baseline (Fall 2011) and throughout the intervention (Spring 2012, Fall 2012, Spring 2013). Analyses were completed using general linear mixed models. The garden intervention led to an overall increase in availability of low-fat vegetables at home. Among younger children (2nd grade at baseline), the garden intervention led to greater home availability of vegetables, especially, low-fat vegetables. Moreover, for the younger group, garden intervention fidelity (GIF) or robustness predicted home availability of fruit, vegetables, and low-fat vegetables. School gardens have potential to affect FV availability in the home environment. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Effect of water table fluctuations on phreatophytic root distribution.

PubMed

Tron, Stefania; Laio, Francesco; Ridolfi, Luca

2014-11-07

The vertical root distribution of riparian vegetation plays a relevant role in soil water balance, in the partition of water fluxes into evaporation and transpiration, in the biogeochemistry of hyporheic corridors, in river morphodynamics evolution, and in bioengineering applications. The aim of this work is to assess the effect of the stochastic variability of the river level on the root distribution of phreatophytic plants. A function describing the vertical root profile has been analytically obtained by coupling a white shot noise representation of the river level variability to a description of the dynamics of root growth and decay. The root profile depends on easily determined parameters, linked to stream dynamics, vegetation and soil characteristics. The riparian vegetation of a river characterized by a high variability turns out to have a rooting system spread over larger depths, but with shallower mean root depths. In contrast, a lower river variability determines root profiles with higher mean root depths. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel characterization of landscape-level variability in historical vegetation structure

Treesearch

Brandon M. Collins; Jamie M. Lydersen; Richard G. Everett; Danny L. Fry; Scott L. Stephens

2015-01-01

We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for...

Global latitudinal-asymmetric vegetation growth trends and their driving mechanisms: 1982-2009

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

Mao, Jiafu; Shi, Xiaoying; Thornton, Peter E

2013-01-01

Using a recent Leaf Area Index (LAI) dataset and the Community Land Model version 4 (CLM4), we investigate percent changes and controlling factors of global vegetation growth for the period 1982 to 2009. Over that 28-year period, both the remote-sensing estimate and model simulation show a significant increasing trend in annual vegetation growth. Latitudinal asymmetry appeared in both products, with small increases in the Southern Hemisphere (SH) and larger increases at high latitudes in the Northern Hemisphere (NH). The south-to-north asymmetric land surface warming was assessed to be the principal driver of this latitudinal asymmetry of LAI trend. Heterogeneous precipitationmore » functioned to decrease this latitudinal LAI gradient, and considerably regulated the local LAI change. CO2 fertilization during the last three decades, was simulated to be the dominant cause for the enhanced vegetation growth. Our study, though limited by observational and modeling uncertainties, adds further insight into vegetation growth trends and environmental correlations. These validation exercises also provide new quantitative and objective metrics for evaluation of land ecosystem process models at multiple spatio-temporal scales.« less

Millennial-scale variability during the last glacial in vegetation records from North America

USGS Publications Warehouse

Jiménez-Moreno, Gonzalo; Anderson, R. Scott; Desprat, S.; Grigg, L.D.; Grimm, E.C.; Heusser, L.E.; Jacobs, Brian F.; Lopez-Martinez, C.; Whitlock, C.L.; Willard, D.A.

2010-01-01

High-resolution pollen records from North America show that terrestrial environments were affected by Dansgaard-Oeschger (D-O) and Heinrich climate variability during the last glacial. In the western, more mountainous regions, these climate changes are generally observed in the pollen records as altitudinal movements of climate-sensitive plant species, whereas in the southeast, they are recorded as latitudinal shifts in vegetation. Heinrich (HS) and Greenland (GS) stadials are generally correlated with cold and dry climate and Greenland interstadials (GI) with warm-wet phases. The pollen records from North America confirm that vegetation responds rapidly to millennial-scale climate variability, although the difficulties in establishing independent age models for the pollen records make determination of the absolute phasing of the records to surface temperatures in Greenland somewhat uncertain. ?? 2009 Elsevier Ltd.

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

Hydrological drivers of wetland vegetational biodiversity patterns within Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Todd, J.; Pumo, D.; Azaele, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of wetland structure. We attempt to link hydrological dynamics with vegetational distribution and species richness across Everglades National Park (ENP) using two publicly available datasets. The first, the Everglades Depth Estimation Network (EDEN),is a water-surface model which determines the median daily measure of water level across a 400mX400m grid over seven years of measurement. The second is a vegetation map and classification system at the 1:15,000 scale which categorizes vegetation within the Everglades into 79 community types. From these data, we have studied the probabilistic structure of the frequency, duration, and depth of hydroperiods. Preliminary results indicate that the percentage of time a location is inundated is a principal structuring variable with individual communities responding differently. For example, sawgrass appears to be more of a generalist community as it is found across a wide range of time inundated percentages while spike rush has a more restricted distribution and favors wetter environments disproportionately more than predicted at random. Further, the diversity of vegetation communities (e.g. a measure of biodiversity) found across a hydrologic variable does not necessarily match the distribution function for that variable on the landscape. For instance, the number of communities does not differ across the percentage of time inundated. Different measures of vegetation biodiversity such as the local number of community types are also studied at different spatial scales with some characteristics, like the slope of the semi-logarithmic relation between rank and occupancy, found to be robust to scale changes. The ENP offers an expansive natural environment in which to study how vegetational dynamics and community composition are affected by hydrologic variables from the small scale (at the individual community level) to the large (biodiversity measures at differing spatial scales).

The influence of labeling the vegetable content of snack food on children's taste preferences: a pilot study.

PubMed

Pope, Lizzy; Wolf, Randi L

2012-01-01

This pilot study examined whether informing children of the presence of vegetables in select snack food items alters taste preference. A random sample of 68 elementary and middle school children tasted identical pairs of 3 snack food items containing vegetables. In each pair, 1 sample's label included the food's vegetable (eg, broccoli gingerbread spice cake), and 1 sample's label did not (eg, gingerbread spice cake). Participants reported whether the samples tasted the same, or whether they preferred one sample. Frequency of vegetable consumption was also assessed. Taste preferences did not differ for the labeled versus the unlabeled sample of zucchini chocolate chip bread, χ(2) (2, n = 68) = 3.21, P = .20 or broccoli gingerbread spice cake χ(2) (2, n = 68) = 2.15, P = .34. However, students preferred the unlabeled cookies (ie, chocolate chip cookies) over the vegetable-labeled version (ie, chickpea chocolate chip cookies), χ(2) = (2, n = 68) 9.21, P = .01. Chickpeas were consumed less frequently (81% had not tried in past year) as compared to zucchini and broccoli. Informing children of the presence of vegetables hidden within snack food may or may not alter taste preference and may depend on the frequency of prior exposure to the vegetable. Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Asynchronous vegetation phenology enhances winter body condition of a large mobile herbivore.

PubMed

Searle, Kate R; Rice, Mindy B; Anderson, Charles R; Bishop, Chad; Hobbs, N T

2015-10-01

Understanding how spatial and temporal heterogeneity influence ecological processes forms a central challenge in ecology. Individual responses to heterogeneity shape population dynamics, therefore understanding these responses is central to sustainable population management. Emerging evidence has shown that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants. We quantified the benefits mule deer (Odocoileus hemionus) accrue from accessing habitats with asynchronous plant phenology in northwest Colorado over 3 years. Our analysis examined both the direct physiological and indirect environmental effects of weather and vegetation phenology on mule deer winter body condition. We identified several important effects of annual weather patterns and topographical variables on vegetation phenology in the home ranges of mule deer. Crucially, temporal patterns of vegetation phenology were linked with differences in body condition, with deer tending to show poorer body condition in areas with less asynchronous vegetation green-up and later vegetation onset. The direct physiological effect of previous winter precipitation on mule deer body condition was much less important than the indirect effect mediated by vegetation phenology. Additionally, the influence of vegetation phenology on body fat was much stronger than that of overall vegetation productivity. In summary, changing annual weather patterns, particularly in relation to seasonal precipitation, have the potential to alter body condition of this important ungulate species during the critical winter period. This finding highlights the importance of maintaining large contiguous areas of spatially and temporally variable resources to allow animals to compensate behaviourally for changing climate-driven resource patterns.

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States

PubMed Central

Trout Fryxell, R. T.; Moore, J. E.; Collins, M. D.; Kwon, Y.; Jean-Philippe, S. R.; Schaeffer, S. M.; Odoi, A.; Kennedy, M.; Houston, A. E.

2015-01-01

Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas. PMID:26656122

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Climate controls photosynthetic capacity more than leaf nitrogen contents

NASA Astrophysics Data System (ADS)

Ali, A. A.; Xu, C.; McDowell, N. G.

2013-12-01

Global vegetation models continue to lack the ability to make reliable predictions because the photosynthetic capacity varies a lot with growth conditions, season and among species. It is likely that vegetation models link photosynthetic capacity to concurrent changes in leaf nitrogen content only. To improve the predictions of the vegetation models, there is an urgent need to review species growth conditions and their seasonal response to changing climate. We sampled the global distribution of the Vcmax (maximum carboxylation rates) data of various species across different environmental gradients from the literature and standardized its value to 25 degree Celcius. We found that species explained the largest variation in (1) the photosynthetic capacity and (2) the proportion of nitrogen allocated for rubisco (PNcb). Surprisingly, climate variables explained more variations in photosynthetic capacity as well as PNcb than leaf nitrogen content and/or specific leaf area. The chief climate variables that explain variation in photosynthesis and PNcb were radiation, temperature and daylength. Our analysis suggests that species have the greatest control over photosynthesis and PNcb. Further, compared to leaf nitrogen content and/or specific leaf area, climate variables have more control over photosynthesis and PNcb. Therefore, climate variables should be incorporated in the global vegetation models when making predictions about the photosynthetic capacity.

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

Decadal climate simulations using the Climate Forecast System (CFS) coupled to the SSiB2 land surface model

NASA Astrophysics Data System (ADS)

De Sales, F.; Xue, Y.; Marx, L.; Ek, M. B.

2016-12-01

The Simplified Simple Biophysical version 2 (SSiB2) model was implemented in the NCEP Climate Forecast System (CFS) for two 30-yr simulations. One simulation was initialized from CFS reanalysis data (EXP1), and the other from a 10-yr spin-up run (EXP2), in which the ocean model was allowed to run freely while the atmosphere and land surface were maintained constant to adjust inconsistencies in the initial conditions. EXP2 also includes an update in the SSiB2's average soil water potential calculation. The material presented highlights the model's performance in predicting spatial and temporal variability of monthly precipitation and surface temperature and aims at determining the optimum configuration for longer simulations. In general, the model is able to reproduce the main features of large-scale precipitation, with spatial correlation (scorr) and RMSE of 0.8 and 1.4 mm day-1, respectively. A split ITCZ pattern is observed in the Pacific and Indian oceans, which results in dry biases along the equator and wet-bias bands to its north and south. Positive biases are also observed in the Atlantic ITCZ. The model generates consistent surface temperature climatology (scorr > 0.9, RMSE= 2.3°C). Warm biases are observed especially over southern Asia during summer. Both experiments produce similar precipitation climatology patterns with similar biases. EXP2, however, improves the temperature simulation by reducing the global bias by 48% and 26% during boreal winter and summer, respectively; and improves the temperature decadal variability for many areas. Moreover, EXP2 generates a better continental surface air warming trend. In the attempt to improve the precipitation decadal variability in the simulations, remotely-sensed LAI and vegetation cover fraction have been implemented in the CFS/SSiB2 to substitute the look-up table originally used in EXP1 and 2. The satellite vegetation data has been processed into global monthly maps which are continuous updated throughout the simulation. Results from this experiment will also be presented.

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of global terrestrial ecosystems to climate variability

NASA Astrophysics Data System (ADS)

Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

2016-03-01

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Novel characterization of landscape-level variability in historical vegetation structure.

PubMed

Collins, Brandon M; Lydersen, Jamie M; Everett, Richard G; Fry, Danny L; Stephens, Scott L

2015-07-01

We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for nine distinct vegetation groups. Our findings highlight some key aspects of forest structure under an intact disturbance regime: (1) forests were low density, with mean live basal area and tree density ranging from 8-30 m2 /ha and 25-79 trees/ha, respectively; (2) understory and overstory structure and composition varied considerably across the landscape; and (3) elevational gradients largely explained variability in forest structure over the landscape. Furthermore, the presence of large trees across most of the surveyed area suggests that extensive stand-replacing disturbances were rare in these forests. The vegetation structure and composition characteristics we quantified, along with evidence of largely elevational control on these characteristics, can provide guidance for restoration efforts in similar forests.

Implications of introducing realistic fire response traits in a Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Kelley, D.; Harrison, S. P.; Prentice, I. C.

2013-12-01

Bark thickness is a key trait protecting woody plants against fire damage, while the ability to resprout is a trait that confers competitive advantage over non-resprouting individuals in fire-prone landscapes. Neither trait is well represented in fire-enabled dynamic global vegetation models (DGVMs). Here we describe a version of the Land Processes and eXchanges (LPX-Mv1) DGVM that incorporates both of these traits in a realistic way. From a synthesis of a large number of field studies, we show there is considerable innate variability in bark thickness between species within a plant-functional type (PFT). Furthermore, bark thickness is an adaptive trait at ecosystem level, increasing with fire frequency. We use the data to specify the range of bark thicknesses characteristic of each model PFT. We allow this distribution to change dynamically: thinner-barked trees are killed preferentially by fire, shifting the distribution of bark thicknesses represented in a model grid cell. We use the PFT-specific bark-thickness probability range for saplings during re-establishment. Since it is rare to destroy all trees in a grid cell, this treatment results in average bark thickness increasing with fire frequency and intensity. Resprouting is a prominent adaptation of temperate and tropical trees in fire-prone areas. The ability to resprout from above-ground tissue (apical or epicormic resprouting) results in the fastest recovery of total biomass after disturbance; resprouting from basal or below-ground meristems results in slower recovery, while non-resprouting species must regenerate from seed and therefore take the longest time to recover. Our analyses show that resprouting species have thicker bark than non-resprouting species. Investment in resprouting is accompanied by reduced efficacy of regeneration from seed. We introduce resprouting PFTs in LPX-Mv1 by specifying an appropriate range of bark thickness, allowing resprouters to survive fire and regenerate vegetatively in the next growing season, while regenerating from seed at 10% the rate of non-resprouters. Tests of LPX-Mv1 for Australia - a continent with a wide range of fire-adapted ecosystems - show that it produces a 33% improvement in the simulation of vegetation composition compared to the previous version of the model, with more realistic vegetation transitions from forests to woodland/savanna. It also produces a 19% improvement in the simulation of burnt area compared to the original model. Resprouting PFTs dominate tropical and temperate areas where the climate is semi-humid but are not common in very dry or very wet areas. Comparison with site-based observations of the abundance of resprouters indicate this is realistic. Ecosystems dominated by resprouters in the simulations recover to pre-fire levels of biomass within 5-7 years, much faster than ecosystems dominated by non-resprouters; again this is confirmed by our analyses of the observations. Simulations of the response to projected future climate change show that the incorporation of adaptive bark thickness and of resprouting has a significant effect on terrestrial carbon stocks in fire-affected areas.

The SMAP Level-4 ECO Project: Linking the Terrestrial Water and Carbon Cycles

NASA Technical Reports Server (NTRS)

Kolassa, J.; Reichle, R. H.; Liu, Qing; Koster, Randal D.

2017-01-01

The SMAP (Soil Moisture Active Passive) Level-4 projects aims to develop a fully coupled hydrology-vegetation data assimilation algorithm to generate improved estimates of modeled hydrological fields and carbon fluxes. This includes using the new NASA Catchment-CN (Catchment-Carbon-Nitrogen) model, which combines the Catchment land surface hydrology model with dynamic vegetation components from the Community Land Model version 4 (CLM4). As such, Catchment-CN allows a more realistic, fully coupled feedback between the land hydrology and the biosphere. The L4 ECO project further aims to inform the model through the assimilation of Soil Moisture Active Passive (SMAP) brightness temperature observations as well as observations of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of absorbed photosynthetically active radiation (FPAR). Preliminary results show that the assimilation of SMAP observations leads to consistent improvements in the model soil moisture skill. An evaluation of the Catchment-CN modeled vegetation characteristics showed that a calibration of the model's vegetation parameters is required before an assimilation of MODIS FPAR observations is feasible.

Regional effects of vegetation restoration on water yield across the Loess Plateau, China

Treesearch

X. M. Feng; G. Sun; B. J. Fu; C. H. Su; Y. Liu; H. Lamparski

2012-01-01

The general relationships between vegetation and water yield under different climatic regimes are well established at a small watershed scale in the past century. However, applications of these basic theories to evaluate the regional effects of land cover change on water resources remain challenging due to the complex interactions of vegetation and climatic variability...

Modeling wilderness campsites: Factors that influence amount of impact

Treesearch

David N. Cole

1991-01-01

A standard campsite model is proposed and then manipulated to examine the influence of individual variables on amount of vegetation loss. Amount of impact is influenced by amount of use, vegetation fragility, vegetation density, and the degree to which activities are concentrated spatially on the site. Degree of concentration also influences the importance of the other...

Item Response Modeling: An Evaluation of the Children's Fruit and Vegetable Self-Efficacy Questionnaire

ERIC Educational Resources Information Center

Watson, Kathy; Baranowski, Tom; Thompson, Debbe

2006-01-01

Perceived self-efficacy (SE) for eating fruit and vegetables (FV) is a key variable mediating FV change in interventions. This study applies item response modeling (IRM) to a fruit, juice and vegetable self-efficacy questionnaire (FVSEQ) previously validated with classical test theory (CTT) procedures. The 24-item (five-point Likert scale) FVSEQ…

Avian community composition and habitat importance in the Rio Grande corridor of New Mexico

Treesearch

David A. Leal; Raymond A. Meyer; Bruce C. Thompson

1996-01-01

We investigated avian species richness and abundance within vegetation communities of the Rio Grande Corridor of New Mexico during spring, summer, and fall 1992 and 1993. A subset of 64 transects, for which all bird and vegetation variables were available, representing 16 composite vegetation community types were subjected to canonical correlation analysis to...

TERRESTRIAL VEGETATION GREENNESS OF THE LOWER GALVESTON BAY WATERSHED FROM SATELLITE REMOTE SENSING AND ITS RELATION TO WATER AND THE SALINITY REGIME OF THE GALVESTON BAY ESTUARY

EPA Science Inventory

Spatial and temporal variability of vegetation greenness have been determined for coastal Texas using biweekly Normalized Difference Vegetation Index (NDVI) data derived from the Advanced Very High Resolution Radiometer (AVHRR). Results are presented on relationships between grou...

FRUIT AND VEGETABLE CONSUMPTION BY ECOLOGICAL ZONE AND SOCIOECONOMIC STATUS IN GHANA.

PubMed

Amo-Adjei, Joshua; Kumi-Kyereme, Akwasi

2015-09-01

The disease burden in both developed and developing countries is moving towards higher proportions of chronic diseases, and diseases such as cancers are now considered to be of public health concern. In sub-Saharan Africa, healthy behaviours such as fruit and vegetable consumption are recommended to reduce the chances of onset of chronic diseases. This paper examines the determinants of fruit and vegetable consumption in Ghana with particular emphasis on consumption by ecological zone. Data were from the 2008 Ghana Demographic and Health Survey (n=4916 females; n=4568 males). Univariate and multivariate analyses were performed using basic descriptive and Poisson regression. The main independent variable was ecological zone and the dependent variables were levels of fruit and vegetable consumption. The mean number of fruits and vegetables consumed in a week was higher among females (fruits: 7.5, 95% CI=7.3-7.7; vegetables: 8.1, 95% CI=7.8-8.3) than males (fruits: 6.2, 95% CI=6.0-6.4; vegetables: 7.9, 95% CI=7.7-8.2). There were significant differences in consumption by ecological zone. Respondents in the Savannah zone consumed less fruit than those in the Coastal and Forest zones, but the differences in fruit and vegetable consumption between the Coastal and Savannah zones were not consistent, especially for vegetable consumption. The findings suggest that one of the key interventions to improve fruit and vegetable consumption could lie in improving distribution systems since their consumption is significantly higher in the Forest zone, where the production of fruit and vegetables is more developed than in the Savannah and Coastal zones. The findings relating to household wealth challenge conventional knowledge on fruit and vegetable consumption, and rather argue for equal consideration of spatial differences in critical health outcomes.

Vegetation anomalies caused by antecedent precipitation in most of the world

NASA Astrophysics Data System (ADS)

Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

2017-07-01

Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth system models in their representations of past vegetation sensitivity to changes in climate.

Impact of schoolchildren's involvement in the design process on the effectiveness of healthy food promotion materials.

PubMed

Gustafson, Christopher R; Abbey, Bryce M; Heelan, Kate A

2017-06-01

Marketing techniques may improve children's vegetable consumption. However, student participation in the design of marketing materials may increase the material's salience, while also improving children's commitment and attitudes towards healthy eating. The impact of student-led design of vegetable promotional materials on choice and consumption was investigated using 1614 observations of students' vegetable choice and plate waste in four public elementary schools in Kearney, Nebraska. Data were collected on children's vegetable choice and consumption in four comparison groups: 1) control; 2) students designed materials only; 3) students were exposed to promotional materials only; and 4) students designed materials that were then posted in the lunchroom. Vegetable choice and consumption data were collected through a validated digital photography-based plate-waste method. Multivariate linear regression was used to estimate average treatment effects of the conditions at various time periods. Dependent variables were vegetable choice and consumption, and independent variables included the condition, time period, and interaction terms, as well as controls for gender and grade. Relative to baseline, students in group 4 doubled their vegetable consumption ( p  < 0.001) when materials were posted. Vegetable consumption remained elevated at a follow-up 2-3 months later ( p  < 0.05). Students in group 3 initially increased the quantity of vegetables selected ( p  < 0.05), but did not increase consumption. In the follow-up period, however, students in group 3 increased their vegetable consumption ( p  < 0.01). Involving elementary-aged students in the design of vegetable promotional materials that were posted in the lunchroom increased the amount of vegetables students consumed.

Interaction Between Ecohydrologic Dynamics and Microtopographic Variability Under Climate Change

NASA Astrophysics Data System (ADS)

Le, Phong V. V.; Kumar, Praveen

2017-10-01

Vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behavior in ecologic and hydrologic functions. We hypothesize that microtopographic variability, which are landscape features typically of the length scale of the order of meters, such as topographic depressions, will play an important role in determining this dynamics by altering the persistence and variability of moisture. To investigate these emergent ecohydrologic dynamics, we develop a modeling framework, Dhara, which explicitly incorporates the control of microtopographic variability on vegetation, moisture, and energy dynamics. The intensive computational demand from such a modeling framework that allows coupling of multilayer modeling of the soil-vegetation continuum with 3-D surface-subsurface flow processes is addressed using hybrid CPU-GPU parallel computing framework. The study is performed for different climate change scenarios for an intensively managed agricultural landscape in central Illinois, USA, which is dominated by row-crop agriculture, primarily soybean (Glycine max) and maize (Zea mays). We show that rising CO2 concentration will decrease evapotranspiration, thus increasing soil moisture and surface water ponding in topographic depressions. However, increased atmospheric demand from higher air temperature overcomes this conservative behavior resulting in a net increase of evapotranspiration, leading to reduction in both soil moisture storage and persistence of ponding. These results shed light on the linkage between vegetation acclimation under climate change and microtopography variability controls on ecohydrologic processes.

Analysis of spatio-temporal variability of C-factor derived from remote sensing data

NASA Astrophysics Data System (ADS)

Pechanec, Vilem; Benc, Antonin; Purkyt, Jan; Cudlin, Pavel

2016-04-01

In some risk areas water erosion as the present task has got the strong influence on agriculture and can threaten inhabitants. In our country combination of USLE and RUSLE models has been used for water erosion assessment (Krása et al., 2013). Role of vegetation cover is characterized by the help of vegetation protection factor, so-called C- factor. Value of C-factor is given by the ratio of washing-off on a plot with arable crops to standard plot which is kept as fallow regularly spud after any rain (Janeček et al., 2012). Under conditions we cannot identify crop structure and its turn, determination of C-factor can be problem in large areas. In such case we only determine C-factor according to the average crop representation. New technologies open possibilities for acceleration and specification of the approach. Present-day approach for the C-factor determination is based on the analysis of multispectral image data. Red and infrared spectrum is extracted and these parts of image are used for computation of vegetation index series (NDVI, TSAVI). Acquired values for fractional time sections (during vegetation period) are averaged out. At the same time values of vegetation indices for a forest and cleared area are determined. Also regressive coefficients are computed. Final calculation is done by the help of regressive equations expressing relation between values of NDVI and C-factor (De Jong, 1994; Van der Knijff, 1999; Karaburun, 2010). Up-to-date land use layer is used for the determination of erosion threatened areas on the base of selection of individual landscape segments of erosion susceptible categories of land use. By means of Landsat 7 data C-factor has been determined for the whole area of the Czech Republic in every month of the year of 2014. At the model area in a small watershed C-factor has been determined by the conventional (tabular) procedure. Analysis was focused on: i) variability assessment of C-factor values while using the conventional procedure and remote sensing, ii) variability assessment of values in different months for selected crops - time variability, growth dynamics and vegetation cover have been taken into account; iii) evaluation of space variability of C-factor values for selected crops - variability of natural conditions, markedly influencing vegetation fitness, has been taken into account. Described methods can be used for the planning of agricultural activities and for the proposing of full-scale land replotting. Presently these activities have been financially supported by the European Structural and Investment Funds.

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

NASA Astrophysics Data System (ADS)

Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong

2015-05-01

A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Demonstration of Airborne Wide Area Assessment Technologies at Pueblo Precision Bombing Ranges, Colorado. Hyperspectral Imaging, Version 2.0

DTIC Science & Technology

2007-09-27

the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets

AmeriFlux US-Brw Barrow

DOE Data Explorer

Oechel, Walt [San Diego State University; Zona, Donatella [San Diego State University

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site US-Brw Barrow. Site Description - The local landscape surrounding the Barrow site has a history absent of any disturbances. The terrain was not heavily glaciated during the last period of glaciation. The vegetation is mature in an unmanaged and undisturbed Arctic tundra.

Variability of pesticide exposure in a stream mesocosm system: macrophyte-dominated vs. non-vegetated sections.

PubMed

Beketov, Mikhail A; Liess, Matthias

2008-12-01

For flowing water bodies no information is available about patterns of contaminant distribution in flowing water compared to macrophyte-dominated structures. The aim of the study was to examine temporal dynamic and spatial cross-channel variability of pulse exposure of the insecticide thiacloprid in outdoor stream mesocosms. Two distinct cross-channel sections have been considered: macrophyte-dominated littoral and non-vegetated midstream. Median disappearance time ranged from 17 to 43 h (water phase, midstream). We showed that during the exposure pulse (10h) thiacloprid concentrations in the macrophyte-dominated section were 20-60% lower than those in the non-vegetated section. This suggests that spatial variability in contaminant concentrations, particularly in streams containing macrophytes, should be taken into account to enable a more realistic assessment of (i) exposure and associated effects and (ii) mass transport of pesticides and other chemicals into river systems (e.g. losses with surface runoff).

A Changing Number of Alternative States in the Boreal Biome: Reproducibility Risks of Replacing Remote Sensing Products.

PubMed

Xu, Chi; Holmgren, Milena; Van Nes, Egbert H; Hirota, Marina; Chapin, F Stuart; Scheffer, Marten

2015-01-01

Publicly available remote sensing products have boosted science in many ways. The openness of these data sources suggests high reproducibility. However, as we show here, results may be specific to versions of the data products that can become unavailable as new versions are posted. We focus on remotely-sensed tree cover. Recent studies have used this public resource to detect multi-modality in tree cover in the tropical and boreal biomes. Such patterns suggest alternative stable states separated by critical tipping points. This has important implications for the potential response of these ecosystems to global climate change. For the boreal region, four distinct ecosystem states (i.e., treeless, sparse and dense woodland, and boreal forest) were previously identified by using the Collection 3 data of MODIS Vegetation Continuous Fields (VCF). Since then, the MODIS VCF product has been updated to Collection 5; and a Landsat VCF product of global tree cover at a fine spatial resolution of 30 meters has been developed. Here we compare these different remote-sensing products of tree cover to show that identification of alternative stable states in the boreal biome partly depends on the data source used. The updated MODIS data and the newer Landsat data consistently demonstrate three distinct modes around similar tree-cover values. Our analysis suggests that the boreal region has three modes: one sparsely vegetated state (treeless), one distinct 'savanna-like' state and one forest state, which could be alternative stable states. Our analysis illustrates that qualitative outcomes of studies may change fundamentally as new versions of remote sensing products are used. Scientific reproducibility thus requires that old versions remain publicly available.

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

NASA Astrophysics Data System (ADS)

Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

2016-12-01

Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (<1 m) and land cover features such as substrate exposure that may affect estimates of vegetation structure in satellite data. Yet it is unclear how differences in spatial and spectral resolution between UAS and satellite data affect their relationships to each other, and to common field measurements of leaf area (e.g. LiCOR photosensors) and land cover. Constraining these relationships is important for leveraging UAS data to improve scaling of field data on leaf area and biomass to satellite data from Landsat, Sentinel-2, and increasing numbers of commercial sensors. Here, we quantify relationships among field, UAS and satellite estimates of vegetation leaf area and biomass in three case study landscapes spanning semi-arid Mediterranean (Matera, Southern Italy and Mallorca, Spain) and North American temperate ecosystems (New Jersey, USA). We assess how land cover and sensor spectral characteristics affect UAS and satellite-derived NDVI, leaf-area and biomass estimates. Then, we assess the fidelity of UAS, WorldView-2, and Landsat leaf-area and biomass estimates to field-measured landscape changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

Comparison of the New LEAF Area INDEX (LAI 3G) with the Kazahstan-Wide LEAF Area INDEX DATA SET (GGRS-LAI) over Central ASIA

NASA Astrophysics Data System (ADS)

Kappas, M.; Propastin, P.; Degener, J.; Renchin, T.

2014-12-01

Long-term global data sets of Leaf Area Index (LAI) are important for monitoring global vegetation dynamics. LAI indicating phenological development of vegetation is an important state variable for modeling land surface processes. The comparison of long-term data sets is based on two recently available data sets both derived from AVHRR time series. The LAI 3g data set introduced by Zaichun Zhu et al. (2013) is developed from the new improved third generation Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) and best-quality MODIS LAI data. The second long-term data set is based on the 8 km spatial resolution GIMMS-AVHRR data (GGRS-data set by Propastin et al. 2012). The GGRS-LAI product uses a three-dimensional physical radiative transfer model which establishes relationship between LAI, vegetation fractional cover and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. The model incorporates a number of site/region specific parameters, including the vegetation architecture variables such as leaf angle distribution, clumping index, and light extinction coefficient. For the application of the model to Kazakhstan, the vegetation architecture variables were computed at the local (pixel) level based on extensive field surveys of the biophysical properties of vegetation in representative grassland areas of Kazakhstan. The comparison of both long-term data sets will be used to interpret their quality for scientific research in other disciplines. References:Propastin, P., Kappas, M. (2012). Retrieval of coarse-resolution leaf area index over the Republic of Kazakhstan using NOAA AVHRR satellite data and ground measurements," Remote Sensing, vol. 4, no. 1, pp. 220-246. Zaichun Zhu, Jian Bi, Yaozhong Pan, Sangram Ganguly, Alessandro Anav, Liang Xu, Arindam Samanta, Shilong Piao, Ramakrishna R. Nemani and Ranga B. Myneni (2013). Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011. Remote Sens. 2013, 5, 927-948; doi:10.3390/rs5020927

Role of vegetation in interplay of climate, soil and groundwater recharge in a global dataset

NASA Astrophysics Data System (ADS)

Kim, J. H.; Jackson, R. B.

2010-12-01

Groundwater is an essential resource for people and ecosystems worldwide. Our capacity to ameliorate predicted global water shortages and to maintain sustainable water supplies depend on a better understanding of the controls of recharge and how vegetation change may affect recharge mechanisms. The goals of this study are to quantify the importance of vegetation as a dominant control on recharge globally and to compare the importance of vegetation with other hydrologically important variables, including climate and soil. We based our global analysis on > 500 recharge estimates from the literature that contained information on vegetation, soil and climate or location. Plant functional types significantly affected groundwater recharge rates substantially. After climatic factors (water inputs, PET, and seasonality), vegetation types explained about 15% of the residuals in the dataset. Across all climatic factors, croplands had the highest recharge rates, followed by grasslands, scrublands and woodlands (average recharge: 75, 63, 30, 22 mm/yr respectively). Recharge under woodlands showed the most nonlinear response to water inputs. Differences in recharge between the vegetation types were more exaggerated at arid climates and in clay soils, indicating greater biological control on soil water fluxes in these conditions. Our results shows that vegetation greatly affects recharge rates globally and alters relationship between recharge and physical variables allowing us to better predict recharge rates globally.

Effects of sand fences on coastal dune vegetation distribution

NASA Astrophysics Data System (ADS)

Grafals-Soto, Rosana

2012-04-01

Sand fences are important human adjustments modifying the morphology of developed shores. The effects of sand fences on sediment transport and deposition in their initial stages have been well studied, but little is known about the effect of deteriorated sand fences that have become partially buried low scale barriers within the dune, potentially benefiting vegetation growth by protecting it from onshore stress. Data on vegetation, topography and fence characteristics were gathered at three dune sites in Ocean City, New Jersey on September 2007 and March 2008 to evaluate the effect of fences within the dune on vegetation distribution. Variables include: distance landward of dune toe, degree of sheltering from onshore stressors, net change in surface elevation (deposition or erosion), vegetation diversity and density, presence of remnant fence, and distance landward of fence. Results for the studied environment reveal that 1) vegetation diversity or density does not increase near remnant fences because most remnants are lower than average vegetation height and can not provide shelter; but 2) vegetation distribution is related to topographic variables, such as degree of sheltering, that are most likely the result of sand accretion caused by fence deployment. Fence deployment that prioritizes the creation of topographically diverse dunes within a restricted space may increase the diversity and density of the vegetation, and the resilience and value of developed dunes. Managers should consider the benefits of using sand fences on appropriately wide beaches to create a protective dune that is also diverse, functional and better able to adapt to change.

Spatial and temporal variation in plant hydraulic traits and their relevance for climate change impacts on vegetation.

PubMed

Anderegg, William R L

2015-02-01

Plant hydraulics mediate terrestrial woody plant productivity, influencing global water, carbon, and biogeochemical cycles, as well as ecosystem vulnerability to drought and climate change. While inter-specific differences in hydraulic traits are widely documented, intra-specific hydraulic variability is less well known and is important for predicting climate change impacts. Here, I present a conceptual framework for this intra-specific hydraulic trait variability, reviewing the mechanisms that drive variability and the consequences for vegetation response to climate change. I performed a meta-analysis on published studies (n = 33) of intra-specific variation in a prominent hydraulic trait - water potential at which 50% stem conductivity is lost (P50) - and compared this variation to inter-specific variability within genera and plant functional types used by a dynamic global vegetation model. I found that intra-specific variability is of ecologically relevant magnitudes, equivalent to c. 33% of the inter-specific variability within a genus, and is larger in angiosperms than gymnosperms, although the limited number of studies highlights that more research is greatly needed. Furthermore, plant functional types were poorly situated to capture key differences in hydraulic traits across species, indicating a need to approach prediction of drought impacts from a trait-based, rather than functional type-based perspective.

Analysis of Post-Fire Vegetation Recovery in the Mediterranean Basin using MODIS Derived Vegetation Indices

NASA Astrophysics Data System (ADS)

Hawtree, Daniel; San Miguel, Jesus; Sedano, Fernando; Kempeneers, Pieter

2010-05-01

The Mediterranean basin region is highly susceptible to wildfire, with approximately 60,000 individual fires and half a million ha of natural vegetation burnt per year. Of particular concern in this region is the impact of repeated wildfires on the ability of natural lands to return to a pre-fire state, and of the possibility of desertification of semi-arid areas. Given these concerns, understanding the temporal patterns of vegetation recovery is important for the management of environmental resources in the region. A valuable tool for evaluating these recovery patterns are vegetation indices derived from remote sensing data. Previous research on post-fire vegetation recovery conducted in this region has found significant variability in recovery times across different study sites. It is unclear what the primary variables are affecting the differences in the rates of recovery, and if any geographic patterns of behavior exist across the Mediterranean basin. This research has primarily been conducted using indices derived from Landsat imagery. However, no extensive analysis of vegetation regeneration for large regions has been published, and assessment of vegetation recovery on the basis of medium-spatial resolution imagery such as that of MODIS has not yet been analyzed. This study examines the temporal pattern of vegetation recovery in a number of fire sites in the Mediterranean basin, using data derived from MODIS 16 -day composite vegetation indices. The intent is to develop a more complete picture of the temporal sequence of vegetation recovery, and to evaluate what additional factors impact variations in the recovery sequence. In addition, this study evaluates the utility of using MODIS derived vegetation indices for regeneration studies, and compares the findings to earlier studies which rely on Landsat data. Wildfires occurring between the years 2000 and 2004 were considered as potential study sites for this research. Using the EFFIS dataset, all wildfires covering an area of at least 1,000 ha were identified. The land-cover / land-use of these large fires sites were then evaluated using the CORINE land-cover data set, and the sites dominated primarily by natural vegetation were identified. Once these candidate sites were identified, a subset was selected across a range of locations and site characteristics for post-fire recovery analysis. To evaluate the post-fire recovery sequence in these locations, time-series of NDVI, EVI, and LAI were derived using 250 meter resolution MODIS data (MOD13Q). The vegetation index values were then compared to pre-fire values to determine recovery relative to the pre-fire vegetative state. The variability in rates of recovery are then considered with respect to moisture availability, vegetation type, and local site conditions to evaluate if any patterns of recovery can be determined.

The Farm Process Version 2 (FMP2) for MODFLOW-2005 - Modifications and Upgrades to FMP1

USGS Publications Warehouse

Schmid, Wolfgang; Hanson, R.T.

2009-01-01

The ability to dynamically simulate the integrated supply-and-demand components of irrigated agricultural is needed to thoroughly understand the interrelation between surface water and groundwater flow in areas where the water-use by vegetation is an important component of the water budget. To meet this need, the computer program Farm Process (FMP1) was updated and refined for use with the U.S. Geological Survey's MODFLOW-2005 groundwater-flow model, and is referred to as MF2005-FMP2. The updated program allows the simulation, analysis, and management of nearly all components of human and natural water use. MF2005-FMP2 represents a complete hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for water consumption of irrigated agriculture, but also of urban use, and of natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, the MF2005-FMP2 has the unique set of capabilities to simulate and analyze historical, present, and future conditions. MF2005-FMP2 facilitates the analysis of agricultural water use where little data is available for pumpage, land use, or agricultural information. The features presented in this new version of FMP2 along with the linkages to the Streamflow Routing (SFR), Multi-Node Well (MNW), and Unsaturated Zone Flow (UZF) Packages prevents mass loss to an open system and helps to account for 'all of the water everywhere and all of the time'. The first version, FMP1 for MODFLOW-2000, is limited to (a) transpiration uptake from unsaturated root zones, (b) on-farm efficiency defined solely by farm and not by crop type, (c) a simulation of water use and returnflows related only to irrigated agriculture and not also to non-irrigated vegetation, (d) a definition of consumptive use as potential crop evapotranspiration, (e) percolation being instantly recharged to the uppermost active aquifer, (f) automatic routing of returnflow from runoff either to reaches of tributary stream segments adjacent to a farm or to one reach nearest to the farm's lowest elevation, (g) farm-well pumping from cell locations regardless of whether an irrigation requirement from these cells exists or not, and (h) specified non-routed water transfers from an undefined source outside the model domain. All of these limitations are overcome in MF2005-FMP2. The new features include (a) simulation of transpiration uptake from variably saturated, fully saturated, or ponded root zones (for example, for crops like rice or riparian vegetation), (b) definition of on-farm efficiency not only by farm but also by crop, (c) simulation of water use and returnflow from non-irrigated vegetation (for example, rain-fed agriculture or native vegetation), (d) use of crop coefficients and reference evapotranspiration, (e) simulation of the delay between percolation from farms through the unsaturated zone and recharge into the uppermost active aquifer by linking FMP2 to the UZF Package, (f) an option to manually control the routing of returnflow from farm runoff to streams, (g) an option to limit pumping to wells located only in cells where an irrigation requirement exists, and (h) simulation of water transfers to farms from a series of well fields (for example, recovery well field of an aquifer-storage-and-recovery system, ASR). In addition to the output of an economic budget for each farm between irrigation demand and supply ('Farm Demand and Supply Budget' in FMP1), a new output option called 'Farm Budget' was created for FMP2, which allows the user to track all physical flows into and out of a water accounting unit at all times. Such a unit can represent individual farms, farming districts, natural areas, or urban areas. The example model demonstrates the application of MF2005-FMP2 with delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in de

Sexual differences in microhabitat selection of breeding little bustards Tetrax tetrax: Ecological segregation based on vegetation structure

NASA Astrophysics Data System (ADS)

Morales, M. B.; Traba, J.; Carriles, E.; Delgado, M. P.; de la Morena, E. L. García

2008-11-01

We examined sexual differences in patterns of vegetation structure selection in the sexually dimorphic little bustard. Differences in vegetation structure between male, female and non-used locations during reproduction were examined and used to build a presence/absence model for each sex. Ten variables were measured in each location, extracting two PCA factors (PC1: a visibility-shelter gradient; PC2: a gradient in food availability) used as response variables in GLM explanatory models. Both factors significantly differed between female, male and control locations. Neither study site nor phenology was significant. Logistic regression was used to model male and female presence/absence. Female presence was positively associated to cover of ground by vegetation litter, as well as overall vegetation cover, and negatively to vegetation density over 30 cm above ground. Male presence was positively related to litter cover and short vegetation and negatively to vegetation density over 30 cm above ground. Models showed good global performance and robustness. Female microhabitat selection and distribution seems to be related to the balance between shelter and visibility for surveillance. Male microhabitat selection would be related mainly to the need of conspicuousness for courtship. Accessibility to food resources seems to be equally important for both sexes. Differences suggest ecological sexual segregation resulting from different ecological constraints. These are the first detailed results on vegetation structure selection in both male and female little bustards, and are useful in designing management measures addressing vegetation structure irrespective of landscape composition. Similar microhabitat approaches can be applied to manage the habitat of many declining farmland birds.

The interactions between soil-biosphere-atmosphere land surface model with a multi-energy balance (ISBA-MEB) option in SURFEXv8 - Part 1: Model description

NASA Astrophysics Data System (ADS)

Boone, Aaron; Samuelsson, Patrick; Gollvik, Stefan; Napoly, Adrien; Jarlan, Lionel; Brun, Eric; Decharme, Bertrand

2017-02-01

Land surface models (LSMs) are pushing towards improved realism owing to an increasing number of observations at the local scale, constantly improving satellite data sets and the associated methodologies to best exploit such data, improved computing resources, and in response to the user community. As a part of the trend in LSM development, there have been ongoing efforts to improve the representation of the land surface processes in the interactions between the soil-biosphere-atmosphere (ISBA) LSM within the EXternalized SURFace (SURFEX) model platform. The force-restore approach in ISBA has been replaced in recent years by multi-layer explicit physically based options for sub-surface heat transfer, soil hydrological processes, and the composite snowpack. The representation of vegetation processes in SURFEX has also become much more sophisticated in recent years, including photosynthesis and respiration and biochemical processes. It became clear that the conceptual limits of the composite soil-vegetation scheme within ISBA had been reached and there was a need to explicitly separate the canopy vegetation from the soil surface. In response to this issue, a collaboration began in 2008 between the high-resolution limited area model (HIRLAM) consortium and Météo-France with the intention to develop an explicit representation of the vegetation in ISBA under the SURFEX platform. A new parameterization has been developed called the ISBA multi-energy balance (MEB) in order to address these issues. ISBA-MEB consists in a fully implicit numerical coupling between a multi-layer physically based snowpack model, a variable-layer soil scheme, an explicit litter layer, a bulk vegetation scheme, and the atmosphere. It also includes a feature that permits a coupling transition of the snowpack from the canopy air to the free atmosphere. It shares many of the routines and physics parameterizations with the standard version of ISBA. This paper is the first of two parts; in part one, the ISBA-MEB model equations, numerical schemes, and theoretical background are presented. In part two (Napoly et al., 2016), which is a separate companion paper, a local scale evaluation of the new scheme is presented along with a detailed description of the new forest litter scheme.

Determinants of anemia among pregnant mothers attending antenatal care in Dessie town health facilities, northern central Ethiopia, unmatched case -control study.

PubMed

Tadesse, Sisay Eshete; Seid, Omer; G/Mariam, Yemane; Fekadu, Abel; Wasihun, Yitbarek; Endris, Kedir; Bitew, Abebayehu

2017-01-01

Anemia affects around 38.2% and 22% of pregnant women at a global and national level respectively. In developing countries, women start pregnancy with already depleted body stores of iron and other vitamins with significant variation of anemia within and between regions. To identify the determinants of anemia among pregnant mothers attending antenatal care in Dessie town health facilities, northern central Ethiopia. A health facility based unmatched case control study was conducted among 112 cases and 336 controls from January to March 2016 G.C. The sample size was determined by using Epi Info version 7.1.5.2. Study subjects were selected using consecutive sampling technique. Data were collected using a structured questionnaire, entered using Epi Data version 3.1 and analyzed using SPSS version 20. Bivariable and multivariable logistic regression model was used to see the determinants of anemia. Adjusted odds ratio (AOR) with 95% confidence interval (CI) and p-value<0.05 were used to see the significant association. Failure to take dark green leafy vegetables per two weeks (AOR = 5.02, 95% CI: 2.16, 11.71), didn't take chicken per two weeks (AOR = 2.68, 95% CI: 1.22, 5.86), 1st trimester (AOR = 2.07, 95% CI: 1.12, 3.84), 3rd trimester (AOR = 2.96, 95% CI: 1.53, 5.72), HIV infection (AOR = 6.78, 95% CI: 2.28, 20.18) and medication (AOR = 3.57 95% CI: 1.60, 7.98) were positively associated with anemia. Inadequate intake of dark green leafy vegetables, inadequate consumption of chicken, trimester of the current pregnancy, HIV infection and medication were the determinants of anemia among pregnant women. Therefore, anemia prevention strategy should include promotion of adequate intake of dark green leafy vegetables and chicken, increase meal pattern during the entire pregnancy and strengthen the prevention of mother to child HIV transmission/antenatal care programs.

An expert system shell for inferring vegetation characteristics: Changes to the historical cover type database (Task F)

NASA Technical Reports Server (NTRS)

1993-01-01

All the options in the NASA VEGetation Workbench (VEG) make use of a database of historical cover types. This database contains results from experiments by scientists on a wide variety of different cover types. The learning system uses the database to provide positive and negative training examples of classes that enable it to learn distinguishing features between classes of vegetation. All the other VEG options use the database to estimate the error bounds involved in the results obtained when various analysis techniques are applied to the sample of cover type data that is being studied. In the previous version of VEG, the historical cover type database was stored as part of the VEG knowledge base. This database was removed from the knowledge base. It is now stored as a series of flat files that are external to VEG. An interface between VEG and these files was provided. The interface allows the user to select which files of historical data to use. The files are then read, and the data are stored in Knowledge Engineering Environment (KEE) units using the same organization of units as in the previous version of VEG. The interface also allows the user to delete some or all of the historical database units from VEG and load new historical data from a file. This report summarizes the use of the historical cover type database in VEG. It then describes the new interface to the files containing the historical data. It describes minor changes that were made to VEG to enable the externally stored database to be used. Test runs to test the operation of the new interface and also to test the operation of VEG using historical data loaded from external files are described. Task F was completed. A Sun cartridge tape containing the KEE and Common Lisp code for the new interface and the modified version of the VEG knowledge base was delivered to the NASA GSFC technical representative.

Determinants of anemia among pregnant mothers attending antenatal care in Dessie town health facilities, northern central Ethiopia, unmatched case -control study

PubMed Central

Seid, Omer; G/Mariam, Yemane; Fekadu, Abel; Wasihun, Yitbarek; Endris, Kedir; Bitew, Abebayehu

2017-01-01

Introduction Anemia affects around 38.2% and 22% of pregnant women at a global and national level respectively. In developing countries, women start pregnancy with already depleted body stores of iron and other vitamins with significant variation of anemia within and between regions. Objective To identify the determinants of anemia among pregnant mothers attending antenatal care in Dessie town health facilities, northern central Ethiopia. Methods A health facility based unmatched case control study was conducted among 112 cases and 336 controls from January to March 2016 G.C. The sample size was determined by using Epi Info version 7.1.5.2. Study subjects were selected using consecutive sampling technique. Data were collected using a structured questionnaire, entered using Epi Data version 3.1 and analyzed using SPSS version 20. Bivariable and multivariable logistic regression model was used to see the determinants of anemia. Adjusted odds ratio (AOR) with 95% confidence interval (CI) and p-value<0.05 were used to see the significant association. Results Failure to take dark green leafy vegetables per two weeks (AOR = 5.02, 95% CI: 2.16, 11.71), didn’t take chicken per two weeks (AOR = 2.68, 95% CI: 1.22, 5.86), 1st trimester (AOR = 2.07, 95% CI: 1.12, 3.84), 3rd trimester (AOR = 2.96, 95% CI: 1.53, 5.72), HIV infection (AOR = 6.78, 95% CI: 2.28, 20.18) and medication (AOR = 3.57 95% CI: 1.60, 7.98) were positively associated with anemia. Conclusions Inadequate intake of dark green leafy vegetables, inadequate consumption of chicken, trimester of the current pregnancy, HIV infection and medication were the determinants of anemia among pregnant women. Therefore, anemia prevention strategy should include promotion of adequate intake of dark green leafy vegetables and chicken, increase meal pattern during the entire pregnancy and strengthen the prevention of mother to child HIV transmission/antenatal care programs. PMID:28288159

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas.

PubMed

Wang, Zhiwei; Wang, Qian; Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the environmental factors (including permafrost) related to the underlying surface conditions.

Vegetation Changes in the Permafrost Regions of the Qinghai-Tibetan Plateau from 1982-2012: Different Responses Related to Geographical Locations and Vegetation Types in High-Altitude Areas

PubMed Central

Wu, Xiaodong; Zhao, Lin; Yue, Guangyang; Nan, Zhuotong; Wang, Puchang; Yi, Shuhua; Zou, Defu; Qin, Yu; Wu, Tonghua; Shi, Jianzong

2017-01-01

The Qinghai-Tibetan Plateau (QTP) contains the largest permafrost area in a high-altitude region in the world, and the unique hydrothermal environments of the active layers in this region have an important impact on vegetation growth. Geographical locations present different climatic conditions, and in combination with the permafrost environments, these conditions comprehensively affect the local vegetation activity. Therefore, the responses of vegetation to climate change in the permafrost region of the QTP may be varied differently by geographical location and vegetation condition. In this study, using the latest Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) product based on turning points (TPs), which were calculated using a piecewise linear model, 9 areas within the permafrost region of the QTP were selected to investigate the effect of geographical location and vegetation type on vegetation growth from 1982 to 2012. The following 4 vegetation types were observed in the 9 selected study areas: alpine swamp meadow, alpine meadow, alpine steppe and alpine desert. The research results show that, in these study areas, TPs mainly appeared in 2000 and 2001, and almost 55.1% and 35.0% of the TPs were located in 2000 and 2001. The global standardized precipitation evapotranspiration index (SPEI) and 7 meteorological variables were selected to analyze their correlations with NDVI. We found that the main correlative variables to vegetation productivity in study areas from 1982 to 2012 were precipitation, surface downward long-wave radiation and temperature. Furthermore, NDVI changes exhibited by different vegetation types within the same study area followed similar trends. The results show that regional effects rather than vegetation type had a larger impact on changes in vegetation growth in the permafrost regions of the QTP, indicating that climatic factors had a larger impact in the permafrost regions than the environmental factors (including permafrost) related to the underlying surface conditions. PMID:28068392

Remote sensing of the Canadian Arctic: Modelling biophysical variables

NASA Astrophysics Data System (ADS)

Liu, Nanfeng

It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic overestimation of 0.08, which was attributed to PAR absorption by soil that could not be excluded from the fAPAR calculation. This research clearly demonstrates that high spectral and spatial resolution remote sensing VIs can be used to successfully model Arctic biophysical variables. The methods and results presented in this research provided a guide for future studies aiming to model other Arctic biophysical variables through remote sensing data.

Slow recovery in desert perennial vegetation following prolonged human disturbance

USGS Publications Warehouse

Guo, Q.

2004-01-01

The study shows an exceptionally long-term recovery of perennial vegetation from prolonged heavy grazing and other human impacts. Since protection in 1906, overall species richness and habitat heterogeneity at the study site continued to increase until the 1960s when diversity, density and cover stabilized. During the same period, overall plant density and cover also increased. Species turnover increased gradually with time but no significant relation between any of the three community variables and precipitation or Palmer Drought Severity Index (PDSI) was detected. The increases in plant species richness, density, and cover of the perennial vegetation were mostly due to the increase of herbaceous species, especially palatable species. The lack of clear relationship between environment (e.g., precipitation) and community variables suggests that site history and plant life history must be taken into account in examining the nature of vegetation recovery process after disturbances.

Remotely sensed vegetation moisture as explanatory variable of Lyme borreliosis incidence

NASA Astrophysics Data System (ADS)

Barrios, J. M.; Verstraeten, W. W.; Maes, P.; Clement, J.; Aerts, J. M.; Farifteh, J.; Lagrou, K.; Van Ranst, M.; Coppin, P.

2012-08-01

The strong correlation between environmental conditions and abundance and spatial spread of the tick Ixodes ricinus is widely documented. I. ricinus is in Europe the main vector of the bacterium Borrelia burgdorferi, the pathogen causing Lyme borreliosis (LB). Humidity in vegetated systems is a major factor in tick ecology and its effects might translate into disease incidence in humans. Time series of two remotely sensed indices with sensitivity to vegetation greenness and moisture were tested as explanatory variables of LB incidence. Wavelet-based multiresolution analysis allowed the examination of these signals at different temporal scales in study sites in Belgium, where increases in LB incidence were reported in recent years. The analysis showed the potential of the tested indices for disease monitoring, the usefulness of analyzing the signal in different time frames and the importance of local characteristics of the study area for the selection of the vegetation index.

Season plays a role in variability in vitamin C content of fresh fruits and vegetables in a local retail market

USDA-ARS?s Scientific Manuscript database

Seasonal variation of vitamin C in fresh fruits and vegetables is not reflected in food composition database average values, yet many factors influence content and retention. Fresh fruits and vegetables were sampled on three occasions in each season, from the same local retail outlets, for one or tw...

Spatial relationships among lightning, precipitation and vegetative cover in watersheds of the Rio Puerco Basin: An introduction

Treesearch

Deborah Ulinski Potter; Susan M. Gorman

1996-01-01

This paper explores the question "is there a relationship between seasonal precipitation amounts and vegetative cover at a specific site near Grants, New Mexico?" Several hypotheses will be investigated. One is that the organizing factor for vegetation response to precipitation is the amount of summer precipitation from convective thunderstorms. The variable...

Detection of the Coupling between Vegetation Leaf Area and Climate in a Multifunctional Watershed, Northwestern China

Treesearch

Lu Hao; Cen Pan; Peilong Liu; Decheng Zhou; Liangxia Zhang; Zhe Xiong; Yongqiang Liu; Ge Sun

2016-01-01

Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past...

Within-stand variation in understorey vegetation affects fire behaviour in longleaf pine xeric sandhills

Treesearch

Evelyn S. Wenk; G. Geoff Wang; Joan L. Walker

2011-01-01

The frequent fires typical of the longleaf pine ecosystem in the south-eastern USA are carried by live understorey vegetation and pine litter. Mature longleaf pine stands in the xeric sandhills region have a variable understory vegetation layer, creating several fuel complexes at the within-stand scale (20 m2). We identified three fuel complexes...

Associations of wintering birds with habitat in semidesert and plains grasslands in Arizona

USGS Publications Warehouse

Ruth, Janet M.; Stanley, Thomas R.; Gordon, Caleb E.

2014-01-01

We studied associations with winter habitat for seven species of birds, one species-group (eastern and western meadowlarks combined), and total sparrows at seven sites in the semidesert and plains grasslands of southeastern Arizona from 1999–2001, sampling with mist-nets and survey-transects. We measured structure and composition of vegetation, assessing vegetative differences among sites, and modeled associations between indices of avian abundance and six vegetative variables using generalized linear models. For all vegetative variables, there were significant differences among sites. Numbers of northern harriers (Circus cyaneus) were positively associated with total number of sparrows. Indices of abundance for individual species of birds were statistically correlated with various measures of structure and composition of vegetation. In particular, grasshopper (Ammodramus savannarum) and vesper (Pooecetes gramineus) sparrows were negatively associated with amount of bare ground; horned larks (Eremophila alpestris) were negatively associated with vertical grass density; Baird's sparrows (A. bairdii) were negatively associated with shrub density; meadowlarks (Sturnella magna and S. neglecta combined) were positively associated with native grass. Our results suggest that these species would benefit from management of habitat that affects the vegetative characteristics associated with their abundance.

Soil-vegetation relationships and community structure in a "terra-firme"-white-sand vegetation gradient in Viruá National Park, northern Amazon, Brazil.

PubMed

Mendonça, Bruno A F DE; Fernandes, Elpídio I; Schaefer, Carlos E G R; Mendonça, Júlia G F DE; Vasconcelos, Bruno N F

2017-01-01

Viruá National Park encompasses a vast and complex system of hydromorphic sandy soils covered largely by the white sand vegetation ("Campinarana") ecosystem. The purpose of this study was to investigate a vegetation gradient of "terra-firme"-white sand vegetation at the Viruá National Park. Nine plots representing three physiognomic units were installed for floristic and phytosociological surveys as well as to collect composite soil samples. The data were subjected to assessments of floristic diversity and similarity, phytosociological parameters and to statistical analyses, focused on principal components (PC) and canonical correspondence analysis (CCA). The vegetation of the Campinaranas types and Forest differed in biomass and species density. Ten species, endemic to Brazil, were particularly well-represented. PC and CCA indicated a clear distinction between the studied plots, based on measured soil variables, especially base sum and clay, which were the most differentiating properties between Campinarana and Forest; For the separation of the Campinarana types, the main distinguishing variable was organic matter content and cation exchange capacity. Higher similarity of Campinaranas was associated to a monodominant species and the lower similarity of Forest was related to the high occurrence of locally rare species.

Understanding Vegetation Response To Climate Variability From Space: The Scientific Objectives< The Approach and The Concept of The Spectra Mission

NASA Astrophysics Data System (ADS)

Menenti, M.; Rast, M.; Baret, F.; Mauser, W.; Miller, J.; Schaepman, M.; Schimel, D.; Verstraete, M.

The response of vegetation to climate variability is a major scientific question. The monitoring of the carbon stock in terrestrial environments, as well as the improved understanding of the surface-atmosphere interactions controlling the exchange of mat- ter, energy and momentum, is of immediate interest for an improved assessment of the various components of the global carbon cycle. Studies of the Earth System processes at the global scale rely on models that require an advanced understanding and proper characterization of processes at smaller scales. The goal of the SPECTRA mission is to improve the description of those processes by means of better constraints on and parameterizations of the associated models. Many vegetation properties are related to features of reflectance spectra in the region 400 nm U 2500 nm. Detailed observa- tions of spectral reflectance reveal subtle features related to biochemical components of leaves such as chlorophyll and water. The architecture of vegetation canopies de- termines complex changes of observed reflectance spectra with view and illumination angle. Quantitative analysis of reflectance spectra requires, therefore, an accurate char- acterization of the anisotropy of reflected radiance. This can be achieved with nearly U simultaneous observations at different view angles. Exchange of energy between the biosphere and the atmosphere is an important mechanism determining the response of vegetation to climate variability. This requires measurements of the component tem- perature of foliage and soil. The prime objective of SPECTRA is to determine the amount, assess the conditions and understand the response of terrestrial vegetation to climate variability and its role in the coupled cycles of energy, water and carbon. The amount and state of vegetation will be determined by the combination of observed vegetation properties and data assimilation. Specifically, the mission will character- ize the amount and state of vegetation with observations of the following variables: 1) Fractional vegetation cover; 2) Fraction Absorbed Photosynthetically Active Radi- ation (FAPAR); 3) Albedo; 4) Leaf Area Index (LAI); 5) Leaf chlorophyll content; 6)Leaf water content; 7) Foliage temperature; 8) Soil temperature; 9) Fractional cover of living and dead biomass. SPECTRA will provide spatially distributed observations (maps) of the key vegetation properties at the spatial resolution of one image pixel and 1 a temporal frequency of one week or lower. Each map will cover an area of 50 km x 50 km. The SPECTRA mission is being studied by the European Space Agency to ad- dress these scientific issues. The mission comprises the following elements: A. Space segment consisting of an imaging spectrometer covering the region 400 nm U 2400 nm with a nominal spectral resolution of 10 nm and of an agile platform to perform subsequent, along track observations at seven view angles between -70 and + 70. B. Ground segment consisting of a core data processing facility and specialized Centers of Excellence to guarantee to a wide and diverse community access to higher level data products and to specialized data assimilation systems. C. Field segment consist- ing of 50 to 100 dedicated sites where teams of investigators evaluate the observations and assimilate them in models describing the functioning of terrestrial ecosystems. 2

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

NASA Technical Reports Server (NTRS)

Ni, Wenjian; Sun, Guoqing; Ranson, Kenneth J.

2013-01-01

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

NASA Astrophysics Data System (ADS)

Nwaogu, Chukwudi; Okeke, Onyedikachi J.; Fadipe, Olusola O.; Bashiru, Kehinde A.; Pechanec, Vilém

2017-12-01

Onitsha is one of the largest commercial cities in Africa with its population growth rate increasing arithmetically for the past two decades. This situation has direct and indirect effects on the natural resources including vegetation and water. The study aimed at assessing land use-land cover (LULC) change and its effects on the vegetation and landscape from 1987 to 2015 using geoinformatics. Supervised and unsupervised classifications including maximum likelihood algorithm were performed using ENVI 4.7 and ArcGIS 10.1 versions. The LULC was classified into 7 classes: built-up areas (settlement), waterbody, thick vegetation, light vegetation, riparian vegetation, sand deposit (bare soil) and floodplain. The result revealed that all the three vegetation types decreased in areas throughout the study period while, settlement, sand deposit and floodplain areas have remarkable increase of about 100% in 2015 when compared with the total in 1987. Number of dominant plant species decreased continuously during the study. The overall classification accuracies in 1987, 2002 and 2015 was 90.7%, 92.9% and 95.5% respectively. The overall kappa coefficient of the image classification for 1987, 2002 and 2015 was 0.98, 0.93 and 0.96 respectively. In general, the average classification was above 90%, a proof that the classification was reliable and acceptable.

A multiscaled model of southwestern willow flycatcher breeding habitat

USGS Publications Warehouse

Hatten, J.R.; Paradzick, C.E.

2003-01-01

The southwestern willow flycatcher (SWFL; Empidonax traillii extimus) is an endangered songbird whose habitat has declined dramatically over the last century. Understanding habitat selection patterns and the ability to identify potential breeding areas for the SWFL is crucial to the management and conservation of this species. We developed a multiscaled model of SWTL breeding habitat with a Geographic Information System (GIS), survey data, GIS variables, and multiple logistic regressions. We obtained presence and absence survey data from a riverine ecosystem and a reservoir delta in south-central Arizona, USA, in 1999. We extracted the GIS variables from satellite imagery and digital elevation models to characterize vegetation and floodplain within the project area. We used multiple logistic regressions within a cell-based (30 X 30 m) modeling environment to (1) determine associations between GIS variables and breeding-site occurrence at different spatial scales (0.09-72 ha), and (2) construct a predictive model. Our best model explained 54% of the variability in breeding-site occurrence with the following variables: vegetation density at the site (0.09 ha), proportion of dense vegetation and variability in vegetation density within a 4.5-ha neighborhood, and amount of floodplain or flat terrain within a 41-ha neighborhood. The density of breeding sites was highest in areas that the model predicted to be most suitable within the project area and at an external test site 200 km away. Conservation efforts must focus on protecting not only occupied patches, but also surrounding riparian forests and floodplain to ensure long-term viability of SWTL. We will use the multiscaled model to map SWTL breeding habitat in Arizona, prioritize future survey effort, and examine changes in habitat abundance and quality over time.

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

PubMed Central

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change. PMID:24823495

Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity.

PubMed

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species' occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species' occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

Effects of vegetation, a clay cap and environmental variables on 222Rn fluence rate from reclaimed U mill tailings.

PubMed

Morris, R C; Fraley, L

1989-04-01

We measured 222Rn fluence rate and several environmental variables on two plots with U mill tailings buried beneath 30 cm of overburden and 20 cm of topsoil. An additional 30 cm of clay covered the tailings on one plot and each plot was subdivided into bare soil and vegetated subplots. We used linear correlation, two-way ANOVA and stepwise multiple regression to analyze the effects of the plot characteristics and the environmental variables on 222Rn fluence rate. The most important effect on 222Rn fluence rates from these plots was the combination of a clay cap and a vegetated surface. The mean annual fluence rate from the plot having both of these characteristics (520 +/- 370 mBq m-2 s-1) was over three times that of the vegetated plot without a clay cap (170 +/- 130 mBq m-2 s-1) and 18 times that of the bare plot with a clay cap (29 +/- 13 mBq m-2 s-1). The interaction effect may have been due to the growth of roots in the moist clay and active transport of dissolved 222Rn to the surface in water. This speculation is supported by the observation that on vegetated plots with a clay cap, moisture in the clay enhanced the fluence rate.

Paleoecology and high-resolution paleohydrology of a kettle peatland in upper Michigan

NASA Astrophysics Data System (ADS)

Booth, Robert K.; Jackson, Stephen T.; Gray, Catherine E. D.

2004-01-01

We investigated the developmental and hydrological history of a Sphagnum-dominated, kettle peatland in Upper Michigan using testate amoebae, plant macrofossils, and pollen. Our primary objective was to determine if the paleohydrological record of the peatland represents a record of past climate variability at subcentennial to millennial time scales. To assess the role of millennial-scale climate variability on peatland paleohydrology, we compared the timing of peatland and upland vegetation changes. To investigate the role of higher-frequency climate variability on peatland paleohydrology, we used testate amoebae to reconstruct a high-resolution, hydrologic history of the peatland for the past 5100 years, and compared this record to other regional records of paleoclimate and vegetation. Comparisons revealed coherent patterns of hydrological, vegetational, and climatic changes, suggesting that peatland paleohydrology responded to climate variability at millennial to sub-centennial time scales. Although ombrotrophic peatlands have been the focus of most high-resolution peatland paleoclimate research, paleohydrological records from Sphagnum-dominated, closed-basin peatlands record high-frequency and low-magnitude climatic changes and thus represent a significant source of unexplored paleoclimate data.

Neighbour effects on Erica multiflora (Ericaceae) reproductive performance after clipping

NASA Astrophysics Data System (ADS)

Vilà, Montserrat; Terradas, Jaume

1998-04-01

The effect of interspecific competition on resprouting and reproductive success and the relationship between above-ground vegetative biomass variability and reproductive biomass variability were analysed during resprouting after clipping. For this purpose, a field experiment was performed by removing neighbours around individuals of Erica multiflora in a Mediterranean shrub community. Removal of neighbours increased the number of sprouts and the above-ground vegetative biomass of target plants. However, it did not decrease plant size variability. Neighbours decreased the likelihood of fruiting and the biomass of fruits. In target plants that had set fruits a simple allometric relationship between above-ground vegetative biomass and the biomass of fruits explained 42% of the variation in fruit biomass. The probability to set fruits at a given plant size was smaller in plants with neighbours than without neighbours. Presence of neighbours also increased the variability of fruit biomass within the population, because 50% of target plants with neighbours did not set fruits. This failure to set fruits may be related to shading, the small size of plants with neighbours, as well as a delay in development.

Accuracy and equivalence testing of crown ratio models and assessment of their impact on diameter growth and basal area increment predictions of two variants of the Forest Vegetation Simulator

Treesearch

Laura P. Leites; Andrew P. Robinson; Nicholas L. Crookston

2009-01-01

Diameter growth (DG) equations in many existing forest growth and yield models use tree crown ratio (CR) as a predictor variable. Where CR is not measured, it is estimated from other measured variables. We evaluated CR estimation accuracy for the models in two Forest Vegetation Simulator variants: the exponential and the logistic CR models used in the North...

The Consolidated Human Activity Database — Master Version (CHAD-Master) Technical Memorandum

EPA Pesticide Factsheets

This technical memorandum contains information about the Consolidated Human Activity Database -- Master version, including CHAD contents, inventory of variables: Questionnaire files and Event files, CHAD codes, and references.

LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response

USGS Publications Warehouse

Picotte, Joshua J.; Long, Jordan; Peterson, Birgit; Nelson, Kurtis

2017-01-01

The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as well as many other applications. The initial LANDFIRE National Existing Vegetation Type (EVT) and vegetation structure layers, including vegetation percent cover and height, were mapped circa 2001 and released in 2009 [5]. Each EVT is representative of the dominant plant community within a given area. The EVT layer has since been updated by identifying areas of landscape change and modifying the vegetation types utilizing a series of rules that consider the disturbance type, severity of disturbance, and time since disturbance [6, 7]. Non-disturbed areas were adjusted for vegetation growth and succession. LANDFIRE vegetation structure layers also have been updated by using data modeling techniques [see 6 for a full description]. The subsequent updated versions of LANDFIRE include LANDFIRE 2008, 2010, 2012, and LANDFIRE 2014 is being incrementally released, with all data being released in early 2017. Additionally, a comprehensive remap of the baseline data, LANDFIRE 2015 Remap, is being prototyped, and production is tentatively planned to begin in early 2017 to provide a more current baseline for future updates.

Effects of late Holocene climate variability and anthropogenic stressors on the vegetation of the Maya highlands

NASA Astrophysics Data System (ADS)

Franco-Gaviria, F.; Correa-Metrio, A.; Cordero-Oviedo, C.; López-Pérez, M.; Cárdenes-Sandí, G. M.; Romero, F. M.

2018-06-01

Climate variability and human activities have shaped the vegetation communities of the Maya region of southern Mexico and Central America on centennial to millennial timescales. Most research efforts in the region have focused on the lowlands, with relatively little known about the environmental history of the regional highlands. Here we present data from two sediment sequences collected from lakes in the highlands of Chiapas, Mexico. Our aim was to disentangle the relative contributions of climate and human activities in the development of regional vegetation during the late Holocene. The records reveal a long-term trend towards drier conditions with superimposed centennial-scale droughts. A declining moisture trend from 3400 to 1500 cal yr BP is consistent with previously reported southward displacement of the Intertropical Convergence Zone, whereas periodic droughts were probably a consequence of drivers such as El Niño. These conditions, together with dense human occupation, converted the vegetation from forest to more open systems. According to the paleoecological records, cultural abandonment of the area occurred ca. 1500 cal yr BP, favoring forest recovery that was somewhat limited by low moisture availability. About 600 cal yr BP, wetter conditions promoted the establishment of modern montane cloud forests, which consist of a diverse mixture of temperate and tropical elements. The vegetation types that occupied the study area during the last few millennia have remained within the envelope defined by the modern vegetation mosaic. This finding highlights the importance of microhabitats in the maintenance biodiversity through time, even under scenarios of high climate variability and anthropogenic pressure.

Forest structure affects trophic linkages: How silvicultural disturbance impacts bats and their insect prey

USGS Publications Warehouse

Dodd, L.E.; Lacki, M.J.; Britzke, E.R.; Buehler, D.A.; Keyser, P.D.; Larkin, J.L.; Rodewald, A.D.; Wigley, T.B.; Wood, P.B.; Rieske, L.K.

2012-01-01

Vertebrate insectivores such as bats are a pervasive top-down force on prey populations in forest ecosystems. Conservation focusing on forest-dwelling bats requires understanding of community-level interactions between these predators and their insect prey. Our study assessed bat activity and insect occurrence (abundance and diversity) across a gradient of forest disturbance and structure (silvicultural treatments) in the Central Appalachian region of North America. We conducted acoustic surveys of bat echolocation concurrent with insect surveys using blacklight and malaise traps over 2 years. Predator activity, prey occurrence and prey biomass varied seasonally and across the region. The number of bat echolocation pulses was positively related with forest disturbance, whereas prey demonstrated varied trends. Lepidopteran abundance was negatively related with disturbance, while dipteran abundance and diversity was positively related with disturbance. Coleoptera were unaffected. Neither bat nor insect response variables differed between plot interiors and edges. Correlations between bat activity and vegetative structure reflected differences in foraging behavior among ensembles. Activity of myotine bats was correlated with variables describing sub-canopy vegetation, whereas activity of lasiurine bats was more closely correlated with canopy-level vegetation. Lepidopteran abundance was correlated with variables describing canopy and sub-canopy vegetation, whereas coleopteran and dipteran occurrence were more closely correlated with canopy-level vegetative structure. Our study demonstrates regional variation in bat activity and prey occurrence across a forested disturbance gradient. Land management and conservation efforts should consider the importance of vegetation structure and plant species richness to sustain forest-dwelling bats and their insect prey.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

Screening of melon genotypes for resistance to vegetable leafminer and your phenotypic correlations with colorimetry.

PubMed

Oliveira, Frederico I C DE; Fiege, Leonardo B C; Celin, Elaine F; Innecco, Renato; Nunes, Glauber H S; Aragão, Fernando A S DE

2017-01-01

Melon is one of the most important vegetable crops in the world. With short cycle in a system of phased planting, phytosanitary control is compromised, and a great volume of agricultural chemicals is used to control vegetable leafminer. Genetic control is an ideal alternative to avoid the damage caused by this insect. Thus, the aim of this study was to evaluate Cucumis accessions in regard to resistance to leafminer and correlate the variables analyzed. Fifty-four accessions and four commercial hybrids of melon were tested. The study was divided into two experiments: with and with no choice. The following characteristics were evaluated: with choice, in field - subjective score based on the infestation and the number of mines per leaf; and with no choice, in cage - number of mines per leaf, chlorophyll content, and leaf colorimetry. The results showed variability among the accessions and some genotypes showed favorable results for resistance in both experiments. There was correlation between the two variables in the experiment in the field. The accessions CNPH 11-282, CNPH 06-1047, and CNPH 11-1077 are the most recommended for future breeding programs with aim on introgression of resistance to vegetable leafminer in melon.

Linking imaging spectroscopy and trait data to better understand spatial and temporal variability in functional traits

NASA Astrophysics Data System (ADS)

Townsend, Philip; Kruger, Eric; Wang, Zhihui; Singh, Aditya

2017-04-01

Imaging spectroscopy exhibits great potential for mapping foliar functional traits that are impractical or expensive to regularly measure on the ground, and are essentially impossible to characterize comprehensively across space. Specifically, the high information content in spectroscopic data enables us to identify narrow spectral feature that are associated with vegetation primary and secondary biochemistry (nutrients, pigments, defensive compounds), leaf structure (e.g., leaf mass per area), canopy structure, and physiological capacity. Ultimately, knowledge of the variability in such traits is critical to understanding vegetation productivity, as well as responses to climatic variability, disturbances, pests and pathogens. The great challenge to the use of imaging spectroscopy to supplement trait databases is the development of trait retrieval approaches that are broadly applicable within and between ecosystem types. Here, we outline how we are using the US National Ecological Observatory Network (NEON) to prototype the scaling and comparison of trait distributions derived from field measurements and imagery. We find that algorithms to map traits from imagery are robust across ecosystem types, when controlling for physiognomy and vegetation percent cover, and that among all vegetation types, the chemometric algorithms utilize similar features for mapping of traits.

Biochemical processes in sagebrush ecosystems: Interactions with terrain

NASA Technical Reports Server (NTRS)

Matson, P. (Principal Investigator); Reiners, W.; Strong, L.

1985-01-01

The objectives of a biogeochemical study of sagebrush ecosystems in Wyoming and their interactions with terrain are as follows: to describe the vegetational pattern on the landscape and elucidate controlling variables, to measure the soil properties and chemical cycling properties associated with the vegetation units, to associate soil properties with vegetation properties as measured on the ground, to develop remote sensing capabilities for vegetation and surface characteristics of the sagebrush landscape, to develop a system of sensing snow cover and indexing seasonal soil to moisture; and to develop relationships between temporal Thematic Mapper (TM) data and vegetation phenological state.

Habitat use by larval fishes in backwater lake of the upper Mississippi River

USGS Publications Warehouse

Dewey, M.R.; Jennings, C.A.

1992-01-01

Light traps were used to sample larval fishes in Lawrence Lake (Pool 8, upper Mississippi River) from late May through mid-August 1990. Catches differed considerably between vegetated sites and an adjacent open- water area and were highly variable among vegetated stations. Sunfishes (Lepomis spp.) dominated the vegetated sites. Brook silversides (Labidesthes sicculus), Cyprinidae ad gizzard shad (Dorosoma cepedianum) dominated catches at the open-water site. There was no difference in fish use of vegetated habitats near and far from the main channel of the Mississippi River. Taxonomic diversity was greatest at stations with emergent vegetation.

Use of generalized regression tree models to characterize vegetation favoring Anopheles albimanus breeding.

PubMed

Hernandez, J E; Epstein, L D; Rodriguez, M H; Rodriguez, A D; Rejmankova, E; Roberts, D R

1997-03-01

We propose the use of generalized tree models (GTMs) to analyze data from entomological field studies. Generalized tree models can be used to characterize environments with different mosquito breeding capacity. A GTM simultaneously analyzes a set of predictor variables (e.g., vegetation coverage) in relation to a response variable (e.g., counts of Anopheles albimanus larvae), and how it varies with respect to a set of criterion variables (e.g., presence of predators). The algorithm produces a treelike graphical display with its root at the top and 2 branches stemming down from each node. At each node, conditions on the value of predictors partition the observations into subgroups (environments) in which the relation between response and criterion variables is most homogeneous.

Early Clinical Manifestations Associated with Death from Visceral Leishmaniasis

PubMed Central

de Araújo, Valdelaine Etelvina Miranda; Morais, Maria Helena Franco; Reis, Ilka Afonso; Rabello, Ana; Carneiro, Mariângela

2012-01-01

Background In Brazil, lethality from visceral leishmaniasis (VL) is high and few studies have addressed prognostic factors. This historical cohort study was designed to investigate the prognostic factors for death from VL in Belo Horizonte (Brazil). Methodology The analysis was based on data of the Reportable Disease Information System-SINAN (Brazilian Ministry of Health) relating to the clinical manifestations of the disease. During the study period (2002–2009), the SINAN changed platform from a Windows to a Net-version that differed with respect to some of the parameters collected. Multivariate logistic regression models were performed to identify variables associated with death from VL, and these were included in prognostic score. Principal Findings Model 1 (period 2002–2009; 111 deaths from VL and 777 cured patients) included the variables present in both SINAN versions, whereas Model 2 (period 2007–2009; 49 deaths from VL and 327 cured patients) included variables common to both SINAN versions plus the additional variables included in the Net version. In Model 1, the variables significantly associated with a greater risk of death from VL were weakness (OR 2.9; 95%CI 1.3–6.4), Leishmania-HIV co-infection (OR 2.4; 95%CI 1.2–4.8) and age ≥60 years (OR 2.5; 95%CI 1.5–4.3). In Model 2, the variables were bleeding (OR 3.5; 95%CI 1.2–10.3), other associated infections (OR 3.2; 95%CI 1.3–7.8), jaundice (OR 10.1; 95%CI 3.7–27.2) and age ≥60 years (OR 3.1; 95%CI 1.4–7.1). The prognosis score was developed using the variables associated with death from VL of the latest version of the SINAN (Model 2). The predictive performance of which was evaluated by sensitivity (71.4%), specificity (73.7%), positive and negative predictive values (28.9% and 94.5%) and area under the receiver operating characteristic curve (75.6%). Conclusions Knowledge regarding the factors associated with death from VL may improve clinical management of patients and contribute to lower mortality. PMID:22347514

Most Likely to Succeed: Exploring Predictor Variables for the Counselor Preparation Comprehensive Examination

ERIC Educational Resources Information Center

Hartwig, Elizabeth Kjellstrand; Van Overschelde, James P.

2016-01-01

The authors investigated predictor variables for the Counselor Preparation Comprehensive Examination (CPCE) to examine whether academic variables, demographic variables, and test version were associated with graduate counseling students' CPCE scores. Multiple regression analyses revealed all 3 variables were statistically significant predictors of…

Exposure of tropical ecosystems to artificial light at night: Brazil as a case study.

PubMed

Freitas, Juliana Ribeirão de; Bennie, Jon; Mantovani, Waldir; Gaston, Kevin J

2017-01-01

Artificial nighttime lighting from streetlights and other sources has a broad range of biological effects. Understanding the spatial and temporal levels and patterns of this lighting is a key step in determining the severity of adverse effects on different ecosystems, vegetation, and habitat types. Few such analyses have been conducted, particularly for regions with high biodiversity, including the tropics. We used an intercalibrated version of the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) images of stable nighttime lights to determine what proportion of original and current Brazilian vegetation types are experiencing measurable levels of artificial light and how this has changed in recent years. The percentage area affected by both detectable light and increases in brightness ranged between 0 and 35% for native vegetation types, and between 0 and 25% for current vegetation (i.e. including agriculture). The most heavily affected areas encompassed terrestrial coastal vegetation types (restingas and mangroves), Semideciduous Seasonal Forest, and Mixed Ombrophilous Forest. The existing small remnants of Lowland Deciduous and Semideciduous Seasonal Forests and of Campinarana had the lowest exposure levels to artificial light. Light pollution has not often been investigated in developing countries but our data show that it is an environmental concern.

General classification handbook for floodplain vegetation in large river systems

USGS Publications Warehouse

Dieck, Jennifer J.; Ruhser, Janis; Hoy, Erin E.; Robinson, Larry R.

2015-01-01

This handbook describes the General Wetland Vegetation Classification System developed as part of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program, Long Term Resource Monitoring (LTRM) element. The UMRR is a cooperative effort between the U.S. Army Corps of Engineers, U.S. Geological Survey, U.S. Fish and Wildlife Service, and the states of Illinois, Iowa, Minnesota, Missouri, and Wisconsin. The classification system consists of 31 general map classes and has been used to create systemic vegetation data layers throughout the diverse Upper Mississippi River System (UMRS), which includes the commercially navigable reaches of the Mississippi River from Minneapolis, Minnesota, in the north to Cairo, Illinois, in the south, the Illinois River, and navigable portions of the Kaskaskia, Black, St. Croix, and Minnesota Rivers. In addition, this handbook describes the evolution of the General Wetland Vegetation Classification System, discusses the process of creating a vegetation data layer, and describes each of the 31 map classes in detail. The handbook also acts as a pictorial guide to each of the map classes as they may appear in the field, as well as on color-infrared imagery. This version is an update to the original handbook published in 2004.

Spectral Behavior of a Linearized Land-Atmosphere Model: Applications to Hydrometeorology

NASA Astrophysics Data System (ADS)

Gentine, P.; Entekhabi, D.; Polcher, J.

2008-12-01

The present study develops an improved version of the linearized land-atmosphere model first introduced by Lettau (1951). This model is used to investigate the spectral response of land-surface variables to a daily forcing of incoming radiation at the land-surface. An analytical solution of the problem is found in the form of temporal Fourier series and gives the atmospheric boundary-layer and soil profiles of state variables (potential temperature, specific humidity, sensible and latent heat fluxes). Moreover the spectral dependency of surface variables is expressed as function of land-surface parameters (friction velocity, vegetation height, aerodynamic resistance, stomatal conductance). This original approach has several advantages: First, the model only requires little data to work and perform well: only time series of incoming radiation at the land-surface, mean specific humidity and temperature at any given height are required. These inputs being widely available over the globe, the model can easily be run and tested under various conditions. The model will also help analysing the diurnal shape and frequency dependency of surface variables and soil-ABL profiles. In particular, a strong emphasis is being placed on the explanation and prediction of Evaporative Fraction (EF) and Bowen Ratio diurnal shapes. EF is shown to remain a diurnal constant under restricting conditions: fair and dry weather, with strong solar radiation and no clouds. Moreover, the EF pseudo-constancy value is found and given as function of surface parameters, such as aerodynamic resistance and stomatal conductance. Then, application of the model for the conception of remote-sensing tools, according to the temporal resolution of the sensor, will also be discussed. Finally, possible extensions and improvement of the model will be discussed.

Absorption models for low-frequency variability in compact radio sources

NASA Technical Reports Server (NTRS)

Marscher, A. P.

1979-01-01

The consequences of the most plausible version of the absorption model for low-frequency variability in compact extragalactic radio sources are considered. The general restrictions placed on such a model are determined, and observational tests are suggested that can be used either to support the model or to discriminate among its various versions. It is shown that low-frequency variability in compact radio sources can be successfully explained by a class of models in which the flux is modulated by changes in free-free optical depth within an intervening ionized medium. Two versions of such a model are distinguished, one involving large changes in optical depth and the other, small changes. It is noted that while absorption effects are capable of causing rapid flux and structural variations at centimetric wavelengths, the models predict detailed behavior that is in direct conflict with observational data.

Consistency across missions of long time series of global biophysical variables: challenges and lessons learnt

NASA Astrophysics Data System (ADS)

Lacaze, Roselyne; Smets, Bruno; Calvet, Jean-Christophe; Camacho, Fernando; Swinnen, Else; Verger, Aleixandre

2017-04-01

The Global component of the Copernicus Land Monitoring Service (CGLS) provides continuously a set of bio-geophysical variables describing the dynamics of vegetation, the energy budget at the continental surface, the water cycle and the cryosphere. Products are generated on a reliable and automatic basis from Earth Observation satellite data, at a frequency ranging from one hour to 10 days. They are accessible free of charge through the GCLS website (http://land.copernicus.eu/global/), associated with documentation describing the physical methodologies, the technical properties of products, and the quality of variables based on the results of validation exercises. The portfolio of the CGLS contains some Essential Climate Variables (ECV) like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, and additional vegetation indices. These products were derived from SPOT/VEGETATION sensor data till December 2013, are currently derived from PROBA-V sensor data, and will be derived in the future from Sentinel-3 data. This talk will show how challenging is the transition between sensors to ensure the sustainability of the production while keeping the consistency of the time series. We will discuss the various sources of differences from input data, the impact of these differences on the biophysical variables and, in turn, on some final users' applications as such those based upon anomalies or assimilation of time series. We will present the mitigation measures taken to reduce as much as possible this impact. We will conclude with the lessons learnt and how this experience will be exploited to manage the transition towards Sentinel-3.

Measuring phenological variability from satellite imagery

USGS Publications Warehouse

Reed, Bradley C.; Brown, Jesslyn F.; Vanderzee, D.; Loveland, Thomas R.; Merchant, James W.; Ohlen, Donald O.

1994-01-01

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

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.

Climate-FVS Version 2: Content, users guide, applications, and behavior

Treesearch

Nicholas L. Crookston

2014-01-01

Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...

Simulating post-wildfire forest trajectories under alternative climate and management scenarios

Treesearch

Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom

2014-01-01

Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...

On measuring bird habitat: influence of observer variability and sample size

Treesearch

William M. Block; Kimberly A. With; Michael L. Morrison

1987-01-01

We studied the effects of observer variability when estimating vegetation characteristics at 75 0.04-ha bird plots. Observer estimates were significantly different for 31 of 49 variables. Multivariate analyses showed significant interobserver differences for five of the seven classes of variables studied. Variable classes included the height, number, and diameter of...

Historical and modern disturbance regimes, stand structures, and landscape dynamics in pinon-juniper vegetation of the western U.S.

Treesearch

William H. Romme; Craig D. Allen; John D. Bailey; William L. Baker; Brandon T. Bestelmeyer; Peter M. Brown; Karen S. Eisenhart; Lisa Floyd-Hanna; Dustin W. Huffman; Brian F. Jacobs; Richard F. Miller; Esteban H. Muldavin; Thomas W. Swetnam; Robin J. Tausch; Peter J. Weisberg

2008-01-01

Pinon-juniper is one of the major vegetation types in western North America. It covers a huge area, provides many resources and ecosystem services, and is of great management concern. Management of pinon-juniper vegetation has been hindered, especially where ecological restoration is a goal, by inadequate understanding of the variability in historical and modern...

Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures

NASA Astrophysics Data System (ADS)

Lehnert, Lukas; Wesche, Karsten; Trachte, Katja; Reudenbach, Christoph; Miehe, Georg; Bendix, Jörg

2016-04-01

The Tibetan Plateau has been entitled "Third-Pole-Environment" because of its outstanding importance for the climate and the hydrology in East and South-east Asia. Its climatological and hydrological influences are strongly affected by the local grassland vegetation which is supposed to be subject to ongoing degradation. On a local scale, numerous studies focused on grassland degradation of the Tibetan pastures. However, because methods and scales substantially differed among previous studies, the overall pattern of the degradation in the Tibetan Plateau is unknown. Consequently, a satellite based approach was selected to cope with the spatial limitations. Therefore, a MODIS-based vegetation cover product was developed which is fully validated against 600 in situ measurements covering a wide extent of the Tibetan Plateau. The vegetation cover as a proxy for grassland degradation is modelled with low error rates using support vector machine regressions. To identify the changes in the vegetation cover, the trends seen in the new vegetation cover product since the beginning of the new millennium were analysed. The drivers of the vegetation changes were identified by the analysis of trends of climatic variables (precipitation and 2 m air temperature) and land-use (livestock numbers) over the same time. The results reveal that - in contrast to the prevailing opinion - pasture degradation on the Tibetan Plateau is not a generally proceeding process because areas of positive and negative changes are almost equal in extent. The positive and negative vegetation changes have regionally different triggers: While, from 2000 on, the vegetation cover has increased in the north-eastern part of the Tibetan Plateau due to increasing precipitation, it has declined in the central and western parts due to rising air temperature and declining precipitation. Increasing livestock numbers as a result of land use changes exacerbated the negative trends but, contrarily to the assumptions of former studies, were not their exclusive driver. Thus, it can be concluded that climate variability instead of overgrazing has been the primary cause for large scale vegetation cover changes on the Tibetan Plateau since the new millennium.

Earth Observation for monitoring phenology for european land use and ecosystems over 1998-2011

NASA Astrophysics Data System (ADS)

Ceccherini, Guido; Gobron, Nadine

2013-04-01

Long-term measurements of plant phenology have been used to track vegetation responses to climate change but are often limited to particular species and locations and may not represent synoptic patterns. Given the limitations of working directly with in-situ data, many researchers have instead used available satellite remote sensing. Remote sensing extends the possible spatial coverage and temporal range of phenological assessments of environmental change due to the greater availability of observations. Variations and trends of vegetation dynamics are important because they alter the surface carbon, water and energy balance. For example, the net ecosystem CO2 exchange of vegetation is strongly linked to length of the growing season: extentions and decreases in length of growing season modify carbon uptake and the amount of CO2 in the atmosphere. Advances and delays in starting of growing season also affect the surface energy balance and consequently transpiration. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a key climate variable identified by Global Terrestrial Observing System (GTOS) that can be monitored from space. This dimensionless variable - varying between 0 and 1- is directly linked to the photosynthetic activity of vegetation, and therefore, can monitor changes in phenology. In this study, we identify the spatio/temporal patterns of vegetation dynamics using a long-term remotely sensed FAPAR dataset over Europe. Our aim is to provide a quantitative analysis of vegetation dynamics relevant to climate studies in Europe. As part of this analysis, six vegetation phenological metrics have been defined and made routinely in Europe. Over time, such metrics can track simple, yet critical, impacts of climate change on ecosystems. Validation has been performed through a direct comparison against ground-based data over ecological sites. Subsequently, using the spatio/temporal variability of this suite of metrics, we classify areas with similar vegetation dynamics. This permits assessment of variations and trends of vegetation dynamics over Europe. Statistical tests to assess the significance of temporal changes are used to evaluate trends in the metrics derived from the recorded time series of the FAPAR.

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

NASA Astrophysics Data System (ADS)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA. Concluding, so far SA has managed to get a decent productivity over croplands due to the advanced cultivation techniques which likely to be at risk under future warming climate. Also NV areas of SA are in constant threat from the anthropogenic activities and climate changes.

Co-evolution of Climate, Soil, and Vegetation and their interplay with Hydrological Partitioning at the Catchment Scale

NASA Astrophysics Data System (ADS)

Zapata-Rios, X.; Brooks, P. D.; Troch, P. A. A.; McIntosh, J. C.

2014-12-01

Landscape, climate, and vegetation interactions play a fundamental role in controlling the distribution of available water in hillslopes and catchments. In mid-latitudes, terrain aspect can regulate surface and subsurface hydrological processes, which not only affect the partitioning of energy and precipitation on short time scales, but also soil development, vegetation characteristics on long time scales. In Redondo Peak in northern New Mexico, a volcanic resurgent dome, first order streams drain different slopes around the mountain. In this setting, we study three adjacent first order catchments that share similar physical characteristics, but drain different aspects, allowing for an empirical study of how topographically controlled microclimate and soil influence the integrated hydrological and vegetation response. From 2008 to 2012, catchments were compared for the way they partition precipitation and how vegetation responds to variable water fluxes. Meteorological variables were monitored in 5 stations around Redondo Peak and surface runoff was monitored at the catchments' outlets. Hydrological partitioning at the catchment scale was estimated with the Horton Index, defined as the ratio between vaporization and wetting and it represents a measure of catchment-scale vegetation water use. Vegetation response was estimated using remotely sensed vegetation greenness (NDVI) derived from MODIS every 16 days with a spatial resolution of 250 m. Results show that the predominantly north facing catchment has the largest and least variable baseflow and discharge, consistent with greater mineral weathering fluxes and longer water transit times. In addition, vaporization, wetting and Horton Index, as well as NDVI, are smaller in the north facing catchment compared to the south east facing catchments. The predominant terrain aspect controls soil development, which affects the partitioning of precipitation and vegetation response at the catchment scale. These results also demonstrate how landscape evolution (e.g. depth of weathering profile) can affect various hydrologic processes, including streamflow response to precipitation and water residence time. In turn these processes are first-order controls on the sensitivity of the landscape to land use and climate change.

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

NASA Technical Reports Server (NTRS)

Huemmrich, Karl F.; Gamon, John; Tweedie, Craig; Campbell, Petya P. K.; Landis, David; Middleton, Elizabeth

2012-01-01

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Associations among food insecurity, acculturation, demographic factors, and fruit and vegetable intake at home in Hispanic children.

PubMed

Dave, Jayna M; Evans, Alexandra E; Saunders, Ruth P; Watkins, Ken W; Pfeiffer, Karin A

2009-04-01

The purpose of this cross-sectional pilot study was to examine associations between food insecurity, acculturation, demographic factors, and children's fruit and vegetable intake among a sample of Hispanic children ages 5 to 12 years. A convenience sample of 184 parents of low socioeconomic status completed one-time, self-administered questionnaires assessing demographic information, acculturation, and food insecurity in the spring of 2006. In addition, children's fruit and vegetable intake at home was measured using a validated seven-item index. Parents were recruited through local elementary schools in San Antonio, TX. Pearson and Spearman correlations were used to examine the associations between the variables. t tests were used to explore the differences in means of children's fruit and vegetable intake at home for acculturation and food insecurity levels. Statistical significance was set at P<0.05. Significant correlations were found between demographic variables, acculturation, food insecurity, and children's fruit and vegetable intake at home. The overall mean fruit and vegetable intake at home was 1.04+/-0.63 (mean+/-standard deviation) servings per day. Higher rates of acculturation and higher rates of food insecurity were associated with lower fruit and vegetable intake at home. The findings reported in this study suggest a need for culturally tailored interventions targeting Hispanic children because fruit and vegetable intake at home among Hispanic children was low, regardless of the level of acculturation or food insecurity.

Interpreting vegetation reflectance measurements as a function of solar zenith angle

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Smith, J. A.; Ranson, K. J.

1979-01-01

Spectral hemispherical-conical reflectances of a nadir looking sensor were taken throughout the day for a lodgepole pine and two grass canopies. Mathematical simulations of both spectral hemispherical-conical and bi-hemispherical reflectances were performed for two theoretical canopies of contrasting geometric structure. These results and comparisons with literature studies showed a great amount of variability of vegetation canopy reflectances as a function of solar zenith angle. Explanations for this variability are discussed and recommendations for further measurements are proposed.

Vegetation projections for Wind Cave National Park with three future climate scenarios: Final report in completion of Task Agreement J8W07100052

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2013-01-01

Since the initial application of MC1 to a small portion of WICA (Bachelet et al. 2000), the model has been altered to improve model performance with the inclusion of dynamic fire. Applying this improved version to WICA required substantial recalibration, during which we have made a number of improvements to MC1 that will be incorporated as permanent changes. In this report we document these changes and our calibration procedure following a brief overview of the model. We compare the projections of current vegetation to the current state of the park and present projections of vegetation dynamics under future climates downscaled from three GCMs selected to represent the existing range in available GCM projections. In doing so, we examine the consequences of different management options regarding fire and grazing, major aspects of biotic management at Wind Cave.

Documentation for the machine-readable version of the Bright Star Catalogue

NASA Technical Reports Server (NTRS)

Warren, W. H., Jr.

1982-01-01

The machine-readable version of The Bright Star Catalogue, 4th edition, is described. In addition to the large number of newly determined fundamental data, such as photoelectric magnitudes, MK spectral types, parallaxes, and radial velocities, the new version contains data and information not included in the third edition such as the identification of IR sources, U-B and R-I colors, radial velocity comments (indication and identification of spectroscopic and occultation binaries), and projected rotational velocities. The equatorial coordinates for equinoxes 1900 and 2000 are recorded to greater precision details concerning variability, spectral characteristics, duplicity, and group membership are included. Data compiled through 1979, some information and variable-star designations found through 1981 are considered.

[Development of a technique for recovering Giardia cysts and Cryptosporidium oocysts from fresh vegetables].

PubMed

Di Benedetto, M A; Di Piazza, F; Oliveri, R; Cerame, G; Valenti, R; Firenze, A

2006-01-01

Techniques described for recovering Giardia and Cryptosporidium (oo)cysts from fruit and vegetables are generally inadequate and present variable recovery efficience and elevated costs. The aim of our study was to evaluate the recovery efficiency of a simple and economic technique to apply either to berry vegetables, like tomatoes and peppers, or to large leave vegetables, like lettuce and chicory. The method include contamination and further elution of the vegetables. Then sedimentation of (oo)cysts by centrifugation of the eluate of vegetables and their visualization by means of direct immunofluorescence. The higher recovery values for both protozoa were obtained in large leave vegetables with mean data above 70% for Giardia and 76% for Cryptosporidium, whereas the values observed in the berry vegetables were above 43% for Giardia and above 37% for Cryptosporidium on average.

The predictive information obtained by testing multiple software versions

NASA Technical Reports Server (NTRS)

Lee, Larry D.

1987-01-01

Multiversion programming is a redundancy approach to developing highly reliable software. In applications of this method, two or more versions of a program are developed independently by different programmers and the versions are combined to form a redundant system. One variation of this approach consists of developing a set of n program versions and testing the versions to predict the failure probability of a particular program or a system formed from a subset of the programs. The precision that might be obtained, and also the effect of programmer variability if predictions are made over repetitions of the process of generating different program versions, are examined.

Quantifying the effects of land use and climate on Holocene vegetation in Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph M.; Jönsson, Anna Maria; Smith, Benjamin; Kaplan, Jed O.; Alenius, Teija; Birks, H. John B.; Bjune, Anne E.; Christiansen, Jörg; Dodson, John; Edwards, Kevin J.; Giesecke, Thomas; Herzschuh, Ulrike; Kangur, Mihkel; Koff, Tiiu; Latałowa, Małgorzata; Lechterbeck, Jutta; Olofsson, Jörgen; Seppä, Heikki

2017-09-01

Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen-based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming practices and forestry in response to population growth and industrialization. This is a unique signature of anthropogenic impact within the Holocene but European vegetation remains climatically sensitive and thus may continue to respond to ongoing climate change.

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.

General catalogue of variable stars: Version GCVS 5.1

NASA Astrophysics Data System (ADS)

Samus', N. N.; Kazarovets, E. V.; Durlevich, O. V.; Kireeva, N. N.; Pastukhova, E. N.

2017-01-01

Work aimed at compiling detailed catalogs of variable stars in the Galaxy, which has been carried out continuously by Moscow variable-star researchers since 1946 on behalf of the International Astronomical Union, has entered the stage of the publication of the 5th, completely electronic edition of the General Catalogue of Variable Stars (GCVS). This paper describes the requirements for the contents of the 5th edition and the current state of the catalog in its new version, GCVS 5.1. The complete revision of information for variable stars in the constellation Carina and the compilation of the 81st Name-list of Variable Stars are considered as examples of work on the 5th edition. The GCVS 5.1 is freely accessible on the Internet. We recommend the present paper as a unified reference to the 5th edition of the GCVS.

Vegetable parenting practices scale: Item response modeling analyses

USDA-ARS?s Scientific Manuscript database

Our objective was to evaluate the psychometric properties of a vegetable parenting practices scale using multidimensional polytomous item response modeling which enables assessing item fit to latent variables and the distributional characteristics of the items in comparison to the respondents. We al...

Improving Shade Modelling in a Regional River Temperature Model Using Fine-Scale LIDAR Data

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Loicq, P.; Moatar, F.; Beaufort, A.; Melin, E.; Jullian, Y.

2015-12-01

Air temperature is often considered as a proxy of the stream temperature to model the distribution areas of aquatic species water temperature is not available at a regional scale. To simulate the water temperature at a regional scale (105 km²), a physically-based model using the equilibrium temperature concept and including upstream-downstream propagation of the thermal signal was developed and applied to the entire Loire basin (Beaufort et al., submitted). This model, called T-NET (Temperature-NETwork) is based on a hydrographical network topology. Computations are made hourly on 52,000 reaches which average 1.7 km long in the Loire drainage basin. The model gives a median Root Mean Square Error of 1.8°C at hourly time step on the basis of 128 water temperature stations (2008-2012). In that version of the model, tree shadings is modelled by a constant factor proportional to the vegetation cover on 10 meters sides the river reaches. According to sensitivity analysis, improving the shade representation would enhance T-NET accuracy, especially for the maximum daily temperatures, which are currently not very well modelized. This study evaluates the most efficient way (accuracy/computing time) to improve the shade model thanks to 1-m resolution LIDAR data available on tributary of the LoireRiver (317 km long and an area of 8280 km²). Two methods are tested and compared: the first one is a spatially explicit computation of the cast shadow for every LIDAR pixel. The second is based on averaged vegetation cover characteristics of buffers and reaches of variable size. Validation of the water temperature model is made against 4 temperature sensors well spread along the stream, as well as two airborne thermal infrared imageries acquired in summer 2014 and winter 2015 over a 80 km reach. The poster will present the optimal length- and crosswise scale to characterize the vegetation from LIDAR data.

Implementation of the MEGAN (v2.1) biogenic emission model in the ECHAM6-HAMMOZ chemistry climate model

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; Stanelle, Tanja; Schröder, Sabine; Siegenthaler, Colombe; Taraborrelli, Domenico; Schultz, Martin G.

2017-02-01

A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the reference simulation is 634 Tg C yr-1 (simulation period 2000-2012). Isoprene is the main contributor to the average emission total, accounting for 66 % (417 Tg C yr-1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %), and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated with tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional biogenic volatile organic compound (BVOC) emissions of the reference simulation were compared to previous published experiment results with MEGAN. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained here are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of MEGAN. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about -9 %, but reaches +75 % for α-pinene when switching from global emission factor maps to PFT-specific emission factor distributions. The highest sensitivity of isoprene emissions is calculated when considering soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has an impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.

Spatial and temporal dynamic of surface water and vegetation dynamic using remotely sensed data in the Murray -Darling Basin, Australia

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Kingsford, R.; Broich, M.

2012-12-01

Australia is the driest inhabited continent and river systems have highly variable flows in space and time. The Murray-Darling Basin (MDB), a catchment covering 14% of the continent contains the nation's largest rivers and important groundwater systems. The basin has highly variable rainfall patterns in space and time and the vast majority of rainfall is lost to evapotranspiration with only 4% becoming runoff. The basin is home to several wetlands of high hydrological and ecological value with a number of them being recognised as wetlands of international importance. The basin produces more than a third of Australia's food supply, making it the most important agricultural area in the country. However, variation in surface and ground water availability exacerbated by a long period of drought, combined with high water demands for irrigation and in several major cities, and the need for water to maintain ecosystem health in the floodplains have led to the need of managing water resources in an integrated fashion. Several dams have been constructed in the basin, which store water during wet periods which is released during dry periods as environmental flows. Assessment of water resources and understanding of the effectiveness of environmental flows requires knowledge of 1) long term trends in occurrence and extent of surface water, 2) what is the vegetation response to flooding and 3) whether water reached target vegetation communities. However, such information does not exist at the basin level. Satellite remote sensing is the only viable way for synoptically mapping and monitoring the extent and dynamic of flooding and vegetation response to flooding. Moreover, recent La Nina -induced, extreme flooding broke a decade long of drought and made 2010 the wettest calendar year on record in the MDB and across vast areas of Australia. This represents a unique opportunity to develop predictive models relating flow regime to vegetation response and identify trends over long term and across a large space in a drying yet variable climate. Using an internally consistent method, Landsat TM and ETM+ data were used to synoptically map the extent and dynamic of surface water bodies and track the response of vegetation communities to flooding in space and time at selected sites. Per pixel trajectory of surface water and vegetation index time series were used. Results show high interannual variability in number and size of flooded areas and a positive relationship with rainfall. Response of vegetation communities to flooding varied in space and time and with vegetation types and densities. Knowledge of the spatial and temporal dynamic of flooding and the response of vegetation communities to flooding is important for management of floodplain wetlands and vegetation communities and for investigating effectiveness of environmental flows and flow regimes in the MDB. The approach presented here can be transferred to other river systems around the world where high demand for water requires informed management decisions.

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

NASA Astrophysics Data System (ADS)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

δ18O water isotope in the iLOVECLIM model (version 1.0) - Part 2: Evaluation of model results against observed δ18O in water samples

NASA Astrophysics Data System (ADS)

Roche, D. M.; Caley, T.

2013-09-01

The H218O stable isotope was previously introduced in the three coupled components of the earth system model iLOVECLIM: atmosphere, ocean and vegetation. The results of a long (5000 yr) pre-industrial equilibrium simulation are presented and evaluated against measurement of H218O abundance in present-day water for the atmospheric and oceanic components. For the atmosphere, it is found that the model reproduces the observed spatial distribution and relationships to climate variables with some merit, though limitations following our approach are highlighted. Indeed, we obtain the main gradients with a robust representation of the Rayleigh distillation but caveats appear in Antarctica and around the Mediterranean region due to model limitation. For the oceanic component, the agreement between the modelled and observed distribution of water δ18O is found to be very good. Mean ocean surface latitudinal gradients are faithfully reproduced as well as the mark of the main intermediate and deep water masses. This opens large prospects for the applications in palaeoclimatic context.

δ18O water isotope in the iLOVECLIM model (version 1.0) - Part 2: Evaluation of model results against observed δ18O in water samples

NASA Astrophysics Data System (ADS)

Roche, D. M.; Caley, T.

2013-03-01

The H218O stable isotope was previously introduced in the three coupled components of the Earth System Model iLOVECLIM: atmosphere, ocean and vegetation. The results of a long (5000 yr) pre-industrial equilibrium simulation are presented and evaluated against measurement of H218O abundance in present-day water for the atmospheric and oceanic components. For the atmosphere, it is found that the model reproduces the observed spatial distribution and relationships to climate variables with some merit, though limitations following our approach are highlighted. Indeed, we obtain the main gradients with a robust representation of the Rayleigh distillation but caveats appear in Antarctica and around the Mediterranean region due to model limitation. For the oceanic component, the agreement between the modelled and observed distribution of water δ18O is found to be very good. Mean ocean surface latitudinal gradients are faithfully reproduced as well as the mark of the main intermediate and deep water masses. This opens large prospects for the applications in paleoclimatic context.

Health behaviors and occupational stress of Brazilian civil servants living in an urban center.

PubMed

Goston, Janaina Lavalli; Caiaffa, Waleska Teixeira; de Souza Andrade, Amanda Cristina; Vlahov, David

2013-01-01

Occupational stress and unhealthy lifestyles are common characteristics of urban workers. The association between health behaviors and job stress of urban Brazilian civil servants was studied. A cross-sectional study included 893 workers. Health markers, the dependent variables, were: Fruit/vegetable (FV) and alcohol (A) intake, physical activity (PA), including at work (PAW), smoking (S), BMI ≥ 25 Kg/m(2). Occupational stress, assessed by Job Stress Scale-Brazilian version, classified employees into: High-strain, Low-strain, Active, and Passive. Prevalence rates and multivariate Poisson models were adopted. On average, employees (mean age = 40.2 years; 69.1% female) reported healthy lifestyle factors: FV (56%); PA (59.7%); S (13.3%); however, 49.4% were overweight. Compared to low-strain, high-strain workers reported higher PAW; passive workers lesser PA and higher PAW. After adjusting for socio-demographics and work characteristics, the occupational stress dimensions were no longer associated to health behaviors. Our results do not support the hypothesis of an effect for occupational stress on urban employees' health behaviors. Copyright © 2012 Wiley Periodicals, Inc.

Cubic map algebra functions for spatio-temporal analysis

USGS Publications Warehouse

Mennis, J.; Viger, R.; Tomlin, C.D.

2005-01-01

We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

Floral and Vegetative Morphometrics of Five Pleurothallis (Orchidaceae) Species: Correlation with Taxonomy, Phylogeny, Genetic Variability and Pollination Systems

PubMed Central

BORBA, EDUARDO L.; SHEPHERD, GEORGE J.; BERG, CÁSSIO VAN DEN; SEMIR, JOÃO

2002-01-01

Morphometric analyses of vegetative and floral characters were conducted in 21 populations of five Pleurothallis (Orchidaceae) species occurring in Brazilian ‘campo rupestre’ vegetation. A phylogenetic analysis of this species group was also carried out using nuclear ribosomal DNA internal transcribed spacers (ITS1 and ITS2). Results of the ordination and cluster analyses agree with species’ delimitation revealed by taxonomic and allozyme studies. The groups formed in ordination analysis correspond to the pollinator groups determined in a previous pollination study. Relationships among the species in the cluster analysis using only vegetative characters are similar to those found in a previous allozyme study, but those indicated by cluster analysis using only floral characters differ. These results support the hypothesis that floral similarities are due to convergence driven by similar pollination mechanisms, and therefore floral traits may not be good indicators of phylogenetic relationships in this group. The results of the phylogenetic analysis support this conclusion to some extent. There is no correlation between genetic (allozyme) and morphological variability in the populations nor in the way this variability is distributed among conspecific populations. We describe a new subspecies of Pleurothallis ochreata based on differences in vegetative and chemical characters as well as geographic distribution. Absence of differentiation in floral characters, attraction of the same pollinator species, interfertility and genetic similarity support the argument for subspecific rather than specific status. PMID:12197519

The Plant Foliage Projective Coverage Change over the Northern Tibetan Plateau during 1957-2009

NASA Astrophysics Data System (ADS)

Cuo, L.

2015-12-01

Northern Tibetan Plateau is the headwater of the Yellow River, the Yangtze River and the Mekong River that support billions of the population. Vegetation change will affect the regional ecosystem and water balances through the changes in biomass and evapotranspiration. Dynamic vegetation growth is determined by physiological, morphological, bioclimatic and phenological properties. These properties are affected by climate variables such as air temperature, precipitation, soil temperature and concentration of CO2, etc. Due to climate change, some parts of the northern Tibetan Plateau are under the threat of desertification. Identifying the places of vegetation degradation and the dominant driven climatic factors will help mitigate the climate change impacts on ecosystem and water resources in this region. In this study, the changes of foliage projective coverages (FPCs) of various plant functional types (PFTs) existed in the northern Tibetan Plateau and the responses of FPCs to the four climate variables over 1957-2009 are examined. The dominant factors among the four climate variables are also identified. The Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) is modified and used for the investigation. The modified LPJ-DGVM can better account for soil temperature in the top 0.4-m depth where vegetation root concentrates over the northern Tibetan Plateau. The modified model is evaluated by using monthly and annual soil temperature observed at stations across the region, and the eco-geographic maps that describe plant types and spatial distributions developed from field surveys and satellite images for this region.

How much rainfall sustained a Green Sahara during the mid-Holocene?

NASA Astrophysics Data System (ADS)

Hopcroft, Peter; Valdes, Paul; Harper, Anna

2016-04-01

The present-day Sahara desert has periodically transformed to an area of lakes and vegetation during the Quaternary in response to orbitally-induced changes in the monsoon circulation. Coupled atmosphere-ocean general circulation model simulations of the mid-Holocene generally underestimate the required monsoon shift, casting doubt on the fidelity of these models. However, the climatic regime that characterised this period remains unclear. To address this, we applied an ensemble of dynamic vegetation model simulations using two different models: JULES (Joint UK Land Environment Simulator) a comprehensive land surface model, and LPJ (Lund-Potsdam-Jena model) a widely used dynamic vegetation model. The simulations are forced with a number of idealized climate scenarios, in which an observational climatology is progressively altered with imposed anomalies of precipitation and other related variables, including cloud cover and humidity. The applied anomalies are based on an ensemble of general circulation model simulations, and include seasonal variations but are spatially uniform across the region. When perturbing precipitation alone, a significant increase of at least 700mm/year is required to produce model simulations with non-negligible vegetation coverage in the Sahara region. Changes in related variables including cloud cover, surface radiation fluxes and humidity are found to be important in the models, as they modify the water balance and so affect plant growth. Including anomalies in all of these variables together reduces the precipitation change required for a Green Sahara compared to the case of increasing precipitation alone. We assess whether the precipitation changes implied by these vegetation model simulations are consistent with reconstructions for the mid-Holocene from pollen samples. Further, Earth System models predict precipitation increases that are significantly smaller than that inferred from these vegetation model simulations. Understanding this difference presents an ongoing challenge.

Ecological site-based assessments of wind and water erosion: informing accelerated soil erosion management in rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Herrick, Jeffrey E.; Duniway, Michael C.

2014-01-01

Accelerated soil erosion occurs when anthropogenic processes modify soil, vegetation or climatic conditions causing erosion rates at a location to exceed their natural variability. Identifying where and when accelerated erosion occurs is a critical first step toward its effective management. Here we explore how erosion assessments structured in the context of ecological sites (a land classification based on soils, landscape setting and ecological potential) and their vegetation states (plant assemblages that may change due to management) can inform systems for reducing accelerated soil erosion in rangelands. We evaluated aeolian horizontal sediment flux and fluvial sediment erosion rates for five ecological sites in southern New Mexico, USA, using monitoring data and rangeland-specific wind and water erosion models. Across the ecological sites, plots in shrub-encroached and shrub-dominated vegetation states were consistently susceptible to aeolian sediment flux and fluvial sediment erosion. Both processes were found to be highly variable for grassland and grass-succulent states across the ecological sites at the plot scale (0.25 Ha). We identify vegetation thresholds that define cover levels below which rapid (exponential) increases in aeolian sediment flux and fluvial sediment erosion occur across the ecological sites and vegetation states. Aeolian sediment flux and fluvial erosion in the study area can be effectively controlled when bare ground cover is 100 cm in length is less than ~35%. Land use and management activities that alter cover levels such that they cross thresholds, and/or drive vegetation state changes, may increase the susceptibility of areas to erosion. Land use impacts that are constrained within the range of natural variability should not result in accelerated soil erosion. Evaluating land condition against the erosion thresholds identified here will enable identification of areas susceptible to accelerated soil erosion and the development of practical management solutions.

Climate change threatens endangered plant species by stronger and interacting water-related stresses

NASA Astrophysics Data System (ADS)

Bartholomeus, Ruud P.; Witte, Jan-Philip M.; van Bodegom, Peter M.; van Dam, Jos C.; Aerts, Rien

2011-12-01

Atmospheric CO2-concentration, temperature and rainfall variability are all expected to increase in the near future. The resulting increased dynamics of soil moisture contents, together with increased plant physiological demands for both oxygen and water, will lead to an increased occurrence of wet and dry extremes of plant stresses, i.e., of oxygen and drought stress, respectively, alone and in interaction. The use of indirect environmental variables in previous studies and a focus on individual stresses rather than their combined effects has hampered understanding of the causal impact of climate change on plant species composition through changes in abiotic site conditions. Here, we use process-based simulations of oxygen and drought stresses in conjunction with a downscaled national version of IPCC scenarios in order to show that these stresses will increase (on average by ˜20% at sites where both stresses occur) in a warmer and more variable future (2050) climate. These two types of stresses will increasingly coincide, i.e. both stresses will occur more often (but not at the same time) within a single vegetation plot. We further show that this increased coincidence of water-related stresses will negatively affect the future occurrence of currently endangered plant species (causing a reduction of ˜16%), while apparently no such decrease will occur among common species. Individual stresses did not appear to affect the occurrence of endangered plant species. Consequently, our study demonstrates that species that are already threatened under the current climate will suffer most from the effects of climate change.

Food choices at lunch during the third year of life: high selection of animal and starchy foods but avoidance of vegetables.

PubMed

Nicklaus, Sophie; Boggio, Vincent; Issanchou, Sylvie

2005-07-01

The objective was to show patterns of food selection by 2- to 3-y-old children for a wide variety of foods in a self-service cafeteria and to assess the effect of individual variables (gender, BMI, mode of feeding after birth and rank in sibship). In a nursery self-service canteen, food choices at lunch made by children (n=418, 24-36 mo; 109 observations per child on average) were recorded by trained assistants who monitored portion size. An offer of eight dishes (animal products, starchy foods, combination dishes, vegetables and dairy products), excluding dessert-type foods, was proposed. Choice level was calculated for each food. Analysis of variance was used to compare choices for the various foods and to assess the effect of the individual variables. The choice of a food largely depended upon its nature: animal products, starchy foods and their combinations were widely chosen, whereas vegetables were not often selected; the choice for dairy products depended upon the type. The mode of preparation of the food influenced its choice. Segmenting products were identified; however, except for cheeses, a given child did not refuse an entire food category. Children's characteristics did not explain the choice variability. At the age of 2 to 3 y, children preferentially choose animal products and starchy foods and avoid vegetables; the high individual variability of their food choices could be related to previous food experiences.

Concentrations of lead, cadmium and barium in urban garden-grown vegetables: the impact of soil variables

PubMed Central

McBride, Murray B.; Shayler, Hannah A.; Spliethoff, Henry M.; Mitchell, Rebecca G.; Marquez-Bravo, Lydia G.; Ferenz, Gretchen S.; Russell-Anelli, Jonathan M.; Casey, Linda; Bachman, Sharon

2014-01-01

Paired vegetable/soil samples from New York City and Buffalo, NY, gardens were analyzed for lead (Pb), cadmium (Cd) and barium (Ba). Vegetable aluminum (Al) was measured to assess soil adherence. Soil and vegetable metal concentrations did not correlate; vegetable concentrations varied by crop type. Pb was below health-based guidance values (EU standards) in virtually all fruits. 47% of root crops and 9% of leafy greens exceeded guidance values; over half the vegetables exceeded the 95th percentile of market-basket concentrations for Pb. Vegetable Pb correlated with Al; soil particle adherence/incorporation was more important than Pb uptake via roots. Cd was similar to market-basket concentrations and below guidance values in nearly all samples. Vegetable Ba was much higher than Pb or Cd, although soil Ba was lower than soil Pb. The poor relationship between vegetable and soil metal concentrations is attributable to particulate contamination of vegetables and soil characteristics that influence phytoavailability. PMID:25163429

Concentrations of lead, cadmium and barium in urban garden-grown vegetables: the impact of soil variables.

PubMed

McBride, Murray B; Shayler, Hannah A; Spliethoff, Henry M; Mitchell, Rebecca G; Marquez-Bravo, Lydia G; Ferenz, Gretchen S; Russell-Anelli, Jonathan M; Casey, Linda; Bachman, Sharon

2014-11-01

Paired vegetable/soil samples from New York City and Buffalo, NY, gardens were analyzed for lead (Pb), cadmium (Cd) and barium (Ba). Vegetable aluminum (Al) was measured to assess soil adherence. Soil and vegetable metal concentrations did not correlate; vegetable concentrations varied by crop type. Pb was below health-based guidance values (EU standards) in virtually all fruits. 47% of root crops and 9% of leafy greens exceeded guidance values; over half the vegetables exceeded the 95th percentile of market-basket concentrations for Pb. Vegetable Pb correlated with Al; soil particle adherence/incorporation was more important than Pb uptake via roots. Cd was similar to market-basket concentrations and below guidance values in nearly all samples. Vegetable Ba was much higher than Pb or Cd, although soil Ba was lower than soil Pb. The poor relationship between vegetable and soil metal concentrations is attributable to particulate contamination of vegetables and soil characteristics that influence phytoavailability. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1

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

Xu, Chonggang; Christoffersen, Bradley

The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems andmore » the Earth system under changing climate and other forcings.« less

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

Normalized difference vegetation index (NDVI) variation among cultivars and environments

USDA-ARS?s Scientific Manuscript database

Although Nitrogen (N) is an essential nutrient for crop production, large preplant applications of fertilizer N can result in off-field loss that causes environmental concerns. Canopy reflectance is being investigated for use in variable rate (VR) N management. Normalized difference vegetation index...

AmeriFlux US-Wjs Willard Juniper Savannah

DOE Data Explorer

Litvak, Marcy [University of New Mexico

2016-01-01

This is the AmeriFlux version of the carbon flux data for the site US-Wjs Willard Juniper Savannah. Site Description - The Juniper Savanna site is located in the Southwestern Tablelands in central New Mexico on a private ranch. Its vegetation is composed of Juniperus monosperma and intermittently grazed C4 perennial grasses of which the dominant species is Bouteloua gracilis.

AmeriFlux US-OWC Old Woman Creek

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

Bohrer, Gil

This is the AmeriFlux version of the carbon flux data for the site US-OWC Old Woman Creek. Site Description - Old Woman Creek is a natural freshwater estuary connected to Lake Erie in northern Ohio. It is one of few natuaral estuary systems left in Ohio. The site is permanently flooded and contains a mixture of wetland vegetation, open water, and mud flats.

Host plants of Melon Fly, Bactrocera cucurbitae(Coquillett)(Diptera:Tephritidae); and provisional list of suitable host plants of the Melon Fly, Bactrocera(Zeugodacus)cucurbitae(Coquillett)(Diptera:Tephritidae),Version 2.0

USDA-ARS?s Scientific Manuscript database

The melon fly, Bactrocera cucurbitae (Coquillett), is a widespread, economically important tephritid fruit fly (Diptera: Tephritidae) species. Bactrocera cucurbitae infests fruits and vegetables of a number of different plant species, with many host plants in the plant family Cucurbitaceae, but with...

VEMAP vs VINCERA: a DGVM sensitivity to differences in climate scenarios

Treesearch

Dominique Bachelet; James Lenihan; Ray Drapek; Ronald Neilson

2008-01-01

The MCI DGVM has been used in two international model comparison projects, VEMAP (Vegetation Ecosystem Modeling and Analysis Project) and VINCERA (Vulnerability and Impacts of North American forests to Climate Change: Ecosystem Responses and Adaptation). The latest version of MC1 was run on both VINCERA and VEMAP climate and soil input data to document how a change in...

NGEE Arctic Tram: Photographs over Low- and High-Centered Polygon Vegetation Communities, Barrow, Alaska, 2014-2017

DOE Data Explorer

J. Bryan Curtis; Margaret Torn

2017-10-05

This dataset provides a digital image of each measurement position stop for every run of the Tram. There are 137 stops per run and there were sometimes multiple runs per day. This first version provides 12,714 images (*.jpg) collected over 28 days in 2015. Images for the other years will be added.

Department of Defense: Electronic Biometric Transmission Specification. Version 2.0

DTIC Science & Technology

2009-03-27

Abstractions = ABSTRACT Insignias & Symbols = SYMBOL Other Images = OTHER Information Item Number: 3 Tattoo Subclass Description: This information item...Tattoo Subclasses: American Flag = USA State Flag = STATE Nazi Flag = NAZI Confederate Flag = CONFED British Flag = BRIT Miscellaneous Flags = MFLAG...Vegetables = MPLANT Flag Tattoo Subclasses: American Flag = USA State Flag = STATE Nazi Flag = NAZI Confederate Flag = CONFED British Flag = BRIT

Comparative analysis of 2 glenoid version measurement methods in variable axial slices on 3-dimensionally reconstructed computed tomography scans.

PubMed

Cunningham, Gregory; Freebody, John; Smith, Margaret M; Taha, Mohy E; Young, Allan A; Cass, Benjamin; Giuffre, Bruno

2018-05-16

Most glenoid version measurement methods have been validated on 3-dimensionally corrected axial computed tomography (CT) slices at the mid glenoid. Variability of the vault according to slice height and angulation has not yet been studied and is crucial for proper surgical implant positioning. The aim of this study was to analyze the variation of the glenoid vault compared with the Friedman angle according to different CT slice heights and angulations. The hypothesis was that the Friedman angle would show less variability. Sixty shoulder CT scans were retrieved from a hospital imaging database and were reconstructed in the plane of the scapula. Seven axial slices of different heights and coronal angulations were selected, and measurements were carried out by 3 observers. Mid-glenoid mean version was -8.0° (±4.9°; range, -19.6° to +7.0°) and -2.1° (±4.7°; range, -13.0° to +10.3°) using the vault method and Friedman angle, respectively. For both methods, decreasing slice height or angulation did not significantly alter version. Increasing slice height or angulation significantly increased anteversion for the vault method (P < .001). Both interobserver reliability and intraobserver reliability were significantly higher using the Friedman angle. Version at the mid and lower glenoid is similar using either method. The vault method shows less reliability and more variability according to slice height or angulation. Yet, as it significantly differs from the Friedman angle, it should still be used in situations where maximum bone purchase is sought with glenoid implants. For any other situation, the Friedman angle remains the method of choice. Copyright © 2018 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Estimation of photosynthetic capacity using MODIS polarization: 1988 proposal to NASA Headquarters

NASA Technical Reports Server (NTRS)

Vanderbilt, Vern C.

1992-01-01

The remote sensing community has clearly identified the utility of NDVI (normalized difference vegetation index) and SR (simple ratio) and other vegetation indices for estimating such metrics of landscape ecology as green foliar biomass, photosynthetic capacity, and net primary production. Both theoretical and empirical investigations have established cause and effect relationships between the photosynthetic process in plant canopies and these combinations of remotely sensed data. Yet it has also been established that the relationships exhibit considerable variability that appears to be ecosystem-dependent and may represent a source of ecologically important information. The overall hypothesis of this proposal is that the ecosystem-dependent variability in the various vegetation indices is in part attributable to the effects of specular reflection. The polarization channels on MODIS provide the potential to estimate this specularly reflected light and allow the modification of the vegetation indices to better measure the photosynthetic process in plant canopies. In addition, these polarization channels potentially provide additional ecologically important information about the plant canopy.

Habitat selection by owls in a seasonal semi-deciduous forest in southern Brazil.

PubMed

Menq, W; Anjos, L

2015-11-01

This paper tested the hypothesis that the structural components of vegetation have impact over the distribution of owl species in a fragment of a semi-deciduous seasonal forest. This paper also determined which vegetation variables contributed to the spatial distribution of owl species. It was developed in the Perobas Biological Reserve (PBR) between September and December 2011. To conduct the owl census, a playback technique was applied at hearing points distributed to cover different vegetation types in the study area. A total of 56 individual owls of six species were recorded: Tropical Screech-Owl (Megascops choliba), Black-capped Screech-Owl (Megascops atricapilla), Tawny-browed Owl (Pulsatrix koeniswaldiana), Ferruginous Pygmy-Owl (Glaucidium brasilianum), Mottled Owl (Strix virgata) and Stygian Owl (Asio stygius). The results suggest that the variables of vegetation structure have impact on the occurrence of owls. The canopy height, the presence of hollow trees, fallen trees and glades are the most important structural components influencing owl distribution in the sampled area.

Towards a Stochastic Predictive Understanding of Ecosystem Functioning and Resilience to Environmental Changes

NASA Astrophysics Data System (ADS)

Pappas, C.

2017-12-01

Terrestrial ecosystem processes respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Process-based modeling of ecosystem functioning is therefore challenging, especially when long-term predictions are envisioned. Here we analyze the statistical properties of hydrometeorological and ecosystem variability, i.e., the variability of ecosystem process related to vegetation carbon dynamics, from hourly to decadal timescales. 23 extra-tropical forest sites, covering different climatic zones and vegetation characteristics, are examined. Micrometeorological and reanalysis data of precipitation, air temperature, shortwave radiation and vapor pressure deficit are used to describe hydrometeorological variability. Ecosystem variability is quantified using long-term eddy covariance flux data of hourly net ecosystem exchange of CO2 between land surface and atmosphere, monthly remote sensing vegetation indices, annual tree-ring widths and above-ground biomass increment estimates. We find that across sites and timescales ecosystem variability is confined within a hydrometeorological envelope that describes the range of variability of the available resources, i.e., water and energy. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. We derive an analytical model, combining deterministic harmonics and stochastic processes, that represents major mechanisms and uncertainties and mimics the observed pattern of hydrometeorological and ecosystem variability. This stochastic framework offers a parsimonious and mathematically tractable approach for modelling ecosystem functioning and for understanding its response and resilience to environmental changes. Furthermore, this framework reflects well the observed ecological memory, an inherent property of ecosystem functioning that is currently not captured by simulation results with process-based models. Our analysis offers a perspective for terrestrial ecosystem modelling, combining current process understanding with stochastic methods, and paves the way for new model-data integration opportunities in Earth system sciences.

Assessing global climate-terrestrial vegetation feedbacks on carbon and nitrogen cycling in the earth system model EC-Earth

NASA Astrophysics Data System (ADS)

Wårlind, David; Miller, Paul; Nieradzik, Lars; Söderberg, Fredrik; Anthoni, Peter; Arneth, Almut; Smith, Ben

2017-04-01

There has been great progress in developing an improved European Consortium Earth System Model (EC-Earth) in preparation for the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the next Assessment Report of the IPCC. The new model version has been complemented with ocean biogeochemistry, atmospheric composition (aerosols and chemistry) and dynamic land vegetation components, and has been configured to use the recommended CMIP6 forcing data sets. These new components will give us fresh insights into climate change. This study focuses on the terrestrial biosphere component Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) that simulates vegetation dynamics and compound exchange between the terrestrial biosphere and the atmosphere in EC-Earth. LPJ-GUESS allows for vegetation to dynamically evolve, depending on climate input, and in return provides the climate system and land surface scheme with vegetation-dependent fields such as vegetation types and leaf area index. We present the results of a study to examine the feedbacks between the dynamic terrestrial vegetation and the climate and their impact on the terrestrial ecosystem carbon and nitrogen cycles. Our results are based on a set of global, atmosphere-only historical simulations (1870 to 2014) with and without feedback between climate and vegetation and including or ignoring the effect of nitrogen limitation on plant productivity. These simulations show to what extent the addition degree of freedom in EC-Earth, introduced with the coupling of interactive dynamic vegetation to the atmosphere, has on terrestrial carbon and nitrogen cycling, and represent contributions to CMIP6 (C4MIP and LUMIP) and the EU Horizon 2020 project CRESCENDO.

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

DOE PAGES

Sakaguchi, K.; Zeng, X.; Leung, L. R.; ...

2016-12-21

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

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

Sakaguchi, K.; Zeng, X.; Leung, L. R.

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Investigating phenology of larval fishes in St. Louis River ...

EPA Pesticide Factsheets

As part of the development of an early detection monitoring strategy for non-native fishes, larval fish surveys have been conducted since 2012 in the St. Louis River estuary. Survey data demonstrates there is considerable variability in fish abundance and species assemblages across different habitats and at multiple temporal scales. To optimize early detection monitoring we need to understand temporal and spatial patterns of larval fishes related to their development and dispersion, as well as the environmental factors that influence them. In 2016 we designed an experiment to assess the phenological variability in larval fish abundance and assemblages amongst shallow water habitats. Specifically, we sought to contrast different thermal environments and turbidity levels, as well as assess the importance of vegetation in these habitats. To evaluate phenological differences we sampled larval fish bi-weekly at nine locations from mid-May to mid-July. Sampling locations were split between upper estuary and lower estuary to contrast river versus seiche influenced habitats. To assess differences in thermal environments, temperature was monitored every 15 minutes at each sampling location throughout the study, beginning in early April. Our design also included sampling at both vegetated (or pre-vegetated) and non-vegetated stations within each sampling location throughout the study to assess the importance of this habitat variable. Hydroacoustic surveys (Biosonics) were

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Bateson, C. Ann; Curtiss, Brian; Benning, Tracy L.

1993-01-01

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables.

How landscape dynamics link individual- to population-level movement patterns: A multispecies comparison of ungulate relocation data

USGS Publications Warehouse

Mueller, Thomas; Olson, K.A.; Dressler, G.; Leimgruber, Peter; Fuller, Todd K.; Nicholson, Craig; Novaro, A.J.; Bolgeri, M.J.; Wattles, David W.; DeStefano, Stephen; Calabrese, J.M.; Fagan, William F.

2011-01-01

Aim  To demonstrate how the interrelations of individual movements form large-scale population-level movement patterns and how these patterns are associated with the underlying landscape dynamics by comparing ungulate movements across species.Locations  Arctic tundra in Alaska and Canada, temperate forests in Massachusetts, Patagonian Steppes in Argentina, Eastern Steppes in Mongolia.Methods  We used relocation data from four ungulate species (barren-ground caribou, Mongolian gazelle, guanaco and moose) to examine individual movements and the interrelation of movements among individuals. We applied and developed a suite of spatial metrics that measure variation in movement among individuals as population dispersion, movement coordination and realized mobility. Taken together, these metrics allowed us to quantify and distinguish among different large-scale population-level movement patterns such as migration, range residency and nomadism. We then related the population-level movement patterns to the underlying landscape vegetation dynamics via long-term remote sensing measurements of the temporal variability, spatial variability and unpredictability of vegetation productivity.Results  Moose, which remained in sedentary home ranges, and guanacos, which were partially migratory, exhibited relatively short annual movements associated with landscapes having very little broad-scale variability in vegetation. Caribou and gazelle performed extreme long-distance movements that were associated with broad-scale variability in vegetation productivity during the peak of the growing season. Caribou exhibited regular seasonal migration in which individuals were clustered for most of the year and exhibited coordinated movements. In contrast, gazelle were nomadic, as individuals were independently distributed and moved in an uncoordinated manner that relates to the comparatively unpredictable (yet broad-scale) vegetation dynamics of their landscape.Main conclusions  We show how broad-scale landscape unpredictability may lead to nomadism, an understudied type of long-distance movement. In contrast to classical migration where landscapes may vary at broad scales but in a predictable manner, long-distance movements of nomadic individuals are uncoordinated and independent from other such individuals. Landscapes with little broad-scale variability in vegetation productivity feature smaller-scale movements and allow for range residency. Nomadism requires distinct integrative conservation strategies that facilitate long-distance movements across the entire landscape and are not limited to certain migration corridors.

How landscape dynamics link individual- to population-level movement patterns: A multispecies comparison of ungulate relocation data

USGS Publications Warehouse

Mueller, T.; Olson, K.A.; Dressler, G.; Leimgruber, P.; Fuller, T.K.; Nicolson, C.; Novaro, A.J.; Bolgeri, M.J.; Wattles, David W.; DeStefano, S.; Calabrese, J.M.; Fagan, W.F.

2011-01-01

Aim To demonstrate how the interrelations of individual movements form large-scale population-level movement patterns and how these patterns are associated with the underlying landscape dynamics by comparing ungulate movements across species. Locations Arctic tundra in Alaska and Canada, temperate forests in Massachusetts, Patagonian Steppes in Argentina, Eastern Steppes in Mongolia. Methods We used relocation data from four ungulate species (barren-ground caribou, Mongolian gazelle, guanaco and moose) to examine individual movements and the interrelation of movements among individuals. We applied and developed a suite of spatial metrics that measure variation in movement among individuals as population dispersion, movement coordination and realized mobility. Taken together, these metrics allowed us to quantify and distinguish among different large-scale population-level movement patterns such as migration, range residency and nomadism. We then related the population-level movement patterns to the underlying landscape vegetation dynamics via long-term remote sensing measurements of the temporal variability, spatial variability and unpredictability of vegetation productivity. Results Moose, which remained in sedentary home ranges, and guanacos, which were partially migratory, exhibited relatively short annual movements associated with landscapes having very little broad-scale variability in vegetation. Caribou and gazelle performed extreme long-distance movements that were associated with broad-scale variability in vegetation productivity during the peak of the growing season. Caribou exhibited regular seasonal migration in which individuals were clustered for most of the year and exhibited coordinated movements. In contrast, gazelle were nomadic, as individuals were independently distributed and moved in an uncoordinated manner that relates to the comparatively unpredictable (yet broad-scale) vegetation dynamics of their landscape. Main conclusions We show how broad-scale landscape unpredictability may lead to nomadism, an understudied type of long-distance movement. In contrast to classical migration where landscapes may vary at broad scales but in a predictable manner, long-distance movements of nomadic individuals are uncoordinated and independent from other such individuals. Landscapes with little broad-scale variability in vegetation productivity feature smaller-scale movements and allow for range residency. Nomadism requires distinct integrative conservation strategies that facilitate long-distance movements across the entire landscape and are not limited to certain migration corridors. ?? 2011 Blackwell Publishing Ltd.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

Characterization of Seasonally Dependent Emergent Vegetation Variables for Coastal Impact Models

NASA Astrophysics Data System (ADS)

Stellern, C.; Grossman, E.; Linneman, S. R.; Fuller, R.

2015-12-01

Emergent wetland vegetation has been shown to mitigate coastal inundation and erosion hazards by reducing wave energy through friction (Shepard et al., 2011), although its use in coastal protection planning is limited because predictive models require improved vegetation data. We isolated biophysical characteristics (biomass, stem density, rigidity, etc.) of plants using horizontal digital photographs (Side-On Photos) in conjunction with remote sensing and physical surveys. We studied the dominant salt-marsh species/assemblages in Port Susan Bay of Washington State, a vulnerable estuary that has experienced up to 1 kilometer of marsh retreat since the mid-1960s. We measured plant height, stem diameter, stem density (area available for flow) from fall to early spring (August 2014 through April 2015) using Side-On Photography and digital image processing techniques. Metrics from Side-On Photography were highly correlated to physical lab measurements. Vegetation rigidity was measured in-situ with a handheld digital scale with respect to measurement height and bending angle. Plant elasticity showed a strong correlation to stem diameter in two dominant bulrush species. We employed remote sensing supervised classifications techniques (Maximum-Likelihood and Decision Tree Classifiers) to hyperspectral imagery to map the spatial extent of vegetation assemblages with an overall accuracy of 86.7%. Combining these methods enabled us to extrapolate and validate vegetation characteristics across the study area and to estimate species-specific friction coefficients for input to cross-shore wave models. On-going studies include sensitivity analyses of wave models to seasonally-dependent vegetation parameters in the nearshore and ultimately wave impacts along the coast. By accounting for site-specific and spatiotemporal variability in vegetation data, we inform scientific understanding of the interactions of vegetation, waves, and sediment processes.

Controls on sinuosity in the sparsely vegetated Fossálar River, southern Iceland

NASA Astrophysics Data System (ADS)

Ielpi, Alessandro

2017-06-01

Vegetation exerts strong controls on fluvial sinuosity, providing bank stability and buffering surface runoff. These controls are manifest in densely vegetated landscapes, whereas sparsely vegetated fluvial systems have been so far overlooked. This study integrates remote sensing and gauging records of the meandering to wandering Fossálar River, a relatively steep-sloped (< 2.5%) Icelandic river featuring well-developed point bars (79%-85% of total active bar surface) despite the lack of thick, arborescent vegetation. Over four decades, fluctuations in the sinuosity index (1.15-1.43) and vegetation cover (63%-83%) are not significantly correlated (r = 0.28, p > 0.05), suggesting that relationships between the two are mediated by intervening variables and uncertain lag times. By comparison, discharge regime and fluvial planform show direct correlation over monthly to yearly time scales, with stable discharge stages accompanying the accretion of meander bends and peak floods related to destructive point-bar reworking. Rapid planform change is aided by the unconsolidated nature of unrooted alluvial banks, with recorded rates of lateral channel-belt migration averaging 18 m/yr. Valley confinement and channel mobility also control the geometry and evolution of individual point bars, with the highest degree of spatial geomorphic variability recorded in low-gradient stretches where lateral migration is unimpeded. Point bars in the Fossálar River display morphometric values comparable to those of other sparsely vegetated rivers, suggesting shared scalar properties. This conjecture prompts the need for more sophisticated integrations between remote sensing and gauging records on modern rivers lacking widespread plant life. While a large volume of experimental and field-based work maintains that thick vegetation has a critical role in limiting braiding, thus favouring sinuosity, this study demonstrates the stronger controls of discharge regime and alluvial morphology on sparsely vegetated sinuous rivers.

Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s

USGS Publications Warehouse

Stow, D.; Daeschner, Scott; Hope, A.; Douglas, David C.; Petersen, A.; Myneni, Ranga B.; Zhou, L.; Oechel, W.

2003-01-01

The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

Vegetation-rainfall feedbacks across the Sahel: a combined observational and modeling study

NASA Astrophysics Data System (ADS)

Yu, Y.; Notaro, M.; Wang, F.; Mao, J.; Shi, X.; Wei, Y.

2016-12-01

The Sahel rainfall is characterized by large interannual variability. Past modeling studies have concluded that the Sahel rainfall variability is primarily driven by oceanic forcings and amplified by land-atmosphere interactions. However, the relative importance of oceanic versus terrestrial drivers has never been assessed from observations. The current understanding of vegetation's impacts on climate, i.e. positive vegetation-rainfall feedback through the albedo, moisture, and momentum mechanisms, comes from untested models. Neither the positive vegetation-rainfall feedback, nor the underlying mechanisms, has been fully resolved in observations. The current study fills the knowledge gap about the observed vegetation-rainfall feedbacks, through the application of the multivariate statistical method Generalized Equilibrium Feedback Assessment (GEFA) to observational data. According to GEFA, the observed oceanic impacts dominate over terrestrial impacts on Sahel rainfall, except in the post-monsoon period. Positive leaf area index (LAI) anomalies favor an extended, wetter monsoon across the Sahel, largely due to moisture recycling. The albedo mechanism is not responsible for this positive vegetation feedback on the seasonal-interannual time scale, which is too short for a grass-desert transition. A low-level stabilization and subsidence is observed in response to increased LAI - potentially responsible for a negative vegetation-rainfall feedback. However, the positive moisture feedback overwhelms the negative momentum feedback, resulting in an observed positive vegetation-rainfall feedback. We further applied GEFA to a fully-coupled Community Earth System Model (CESM) control run, as an example of evaluating climate models against the GEFA-based observational benchmark. In contrast to the observed positive vegetation-rainfall feedbacks, CESM simulates a negative vegetation-rainfall feedback across Sahel, peaking in the pre-monsoon season. The simulated negative feedback is largely due to the low-level stabilization caused by increased LAI. Positive moisture feedback is present in the CESM simulation, but an order weaker than the observed and weaker than the negative momentum feedback, thereby leading to the simulated negative vegetation-rainfall feedbacks.

Sensitivity of Climate to Changes in NDVI

NASA Technical Reports Server (NTRS)

Bounoua, L.; Collatz, G. J.; Los, S. O.; Sellers, P. J.; Dazlich, D. A.; Tucker, C. J.; Randall, D. A.

1999-01-01

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere-atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (ndvi). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982-1990. Albedo decreased in the northern latitudes and increased in the tropics with increased ndvi. The increase in vegetation density revealed that the vegetation's physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic C02 uptake on a global annual basis. This caused the canopy transpiration and interception fluxes to increase, and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting. Important effects of increased vegetation on climate are : (1) A cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy. and (2) A year round cooling of 0.8 K in the tropics. These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming . Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however increased more than precipitation resulting in a global soil-water deficit of about 15 %. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low-frequency modes of the precipitation distribution and might reduce its low frequency variability in the tropics while increasing it in northern latitudes.

Complexity confers stability: Climate variability, vegetation response and sand transport on longitudinal sand dunes in Australia's deserts

NASA Astrophysics Data System (ADS)

Hesse, Paul P.; Telfer, Matt W.; Farebrother, Will

2017-04-01

The relationship between antecedent precipitation, vegetation cover and sand movement on sand dunes in the Simpson and Strzelecki Deserts was investigated by repeated (up to four) surveys of dune crest plots (≈25 × 25 m) over a drought cycle (2002-2012) in both winter (low wind) and spring (high wind). Vegetation varied dramatically between surveys on vegetated and active dune crests. Indices of sand movement had significant correlations with vegetation cover: the depth of loose sand has a strong inverse relationship with crust (cyanobacterial and/or physical) while the area covered by ripples has a strong inverse relationship with the areal cover of vascular plants. However, the relationship between antecedent rainfall and vegetation cover was found to be complex. We tentatively identify two thresholds; (1) >10 mm of rainfall in the preceding 90 days leads to rapid and near total cover of crust and/or small plants <50 cm tall, and (2) >400 mm of rainfall in the preceding three years leads to higher cover of persistent and longer-lived plants >50 cm tall. These thresholds were used to predict days of low vegetation cover on dune crests. The combination of seasonality of predicted bare-crest days, potential sand drift and resultant sand drift direction explains observed patterns of sand drift on these dunes. The complex vegetation and highly variable rainfall regime confer meta-stability on the dunes through the range of responses to different intervals of antecedent rainfall and non-linear growth responses. This suggests that the geomorphic response of dunes to climate variation is complex and non-linear.

Approaches to vegetation mapping and ecophysiological hypothesis testing using combined information from TIMS, AVIRIS, and AIRSAR

NASA Technical Reports Server (NTRS)

Oren, R.; Vane, G.; Zimmermann, R.; Carrere, V.; Realmuto, V.; Zebker, Howard A.; Schoeneberger, P.; Schoeneberger, M.

1991-01-01

The Tropical Rainforest Ecology Experiment (TREE) had two primary objectives: (1) to design a method for mapping vegetation in tropical regions using remote sensing and determine whether the result improves on available vegetation maps; and (2) to test a specific hypothesis on plant/water relations. Both objectives were thought achievable with the combined information from the Thermal Infrared Multispectral Scanner (TIMS), Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and Airborne Synthetic Aperture Radar (AIRSAR). Implicitly, two additional objectives were: (1) to ascertain that the range within each variable potentially measurable with the three instruments is large enough in the site, relative to the sensitivity of the instruments, so that differences between ecological groups may be detectable; and (2) to determine the ability of the three systems to quantify different variables and sensitivities. We found that the ranges in values of foliar nitrogen concentration, water availability, stand structure and species composition, and plant/water relations were large, even within the upland broadleaf vegetation type. The range was larger when other vegetation types were considered. Unfortunately, cloud cover and navigation errors compromised the utility of the TIMS and AVIRIS data. Nevertheless, the AIRSAR data alone appear to have improved on the available vegetation map for the study area. An example from an area converted to a farm is given to demonstrate how the combined information from AIRSAR, TIMS, and AVIRIS can uniquely identify distinct classes of land use. The example alludes to the potential utility of the three instruments for identifying vegetation at an ecological scale finer than vegetation types.

Contribution of Phenological and Physiological Variations on Northern Vegetation Productivity Changes over Last Three Decades

NASA Technical Reports Server (NTRS)

Ganguly, Sangram

2015-01-01

Plant phenology and maximum photosynthetic state determine spatiotemporal variability of gross primary productivity (GPP) of vegetation. Recent warming induced impacts accelerate shifts of phenology and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we investigate 1) how vegetation phenology and physiological status (maximum photosynthesis) are evolved over last three decades and 2) how such components (phenology and physiological status) contribute on inter-annual variation of the GPP during the last three decades. We utilized both long-term remotely sensed (GIMMS (Global Inventory Modeling and Mapping Studies), NDVI3g (Normalized Difference Vegetation Index 3rd generation) and MODIS (Moderate Resolution Imaging Spectroradiometer)) to extract larger scale phenology metrics (growing season start, end and duration); and productivity (i.e., growing season integrated vegetation index, GSIVI) to answer these questions. For evaluation purpose, we also introduced field-measured phenology and productivity datasets (e.g., FLUXNET) and possible remotely-sensed and modeled metrics at continental and regional scales. From this investigation, we found that onset of the growing season has advanced by 1.61 days per decade and the growing season end has delayed by 0.67 days per decade over the circumpolar region. This asymmetric extension of growing season results in a longer growing-season trend (2.96 days per decade) and widespread increasing vegetation-productivity trend (2.96 GSIVI per decade) over Northern land. However, the regionally-diverged phenology shift and maximum photosynthetic state contribute differently characterized productivity, inter-annual variability and trend. We quantified that about 50 percent, 13 percent and 6.5 percent of Northern land's inter-annual variability are dominantly controlled by the onset of the growing season, the end of the growing season and the maximum photosynthetic state, respectively. Productivity characterization over the other approximately 30 percent region has been driven by these co-dominant drivers. Our study clearly shows that regionally different contribution of phenological and physiological components on characterizing vegetation production over the last three decades.

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

NASA Technical Reports Server (NTRS)

Eagleson, Peter S.; Jasinski, Michael F.

1988-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

RELATIONSHIPS OF MEADOW VEGETATION TO GROUNDWATER DEPTH: EFFECTS OF PRECIPITATION VARIABILITY AND STREAM INCISION

EPA Science Inventory

The composition of riparian meadow vegetation is controlled by access to groundwater. Depth to groundwater is controlled by meadow architecture and water source, and changes in either meadow architecture or water source through stream incision or changes in annual precipitation c...

The AMMA-CATCH Gourma observatory site in Mali: Relating climatic variations to changes in vegetation, surface hydrology, fluxes and natural resources

NASA Astrophysics Data System (ADS)

Mougin, E.; Hiernaux, P.; Kergoat, L.; Grippa, M.; de Rosnay, P.; Timouk, F.; Le Dantec, V.; Demarez, V.; Lavenu, F.; Arjounin, M.; Lebel, T.; Soumaguel, N.; Ceschia, E.; Mougenot, B.; Baup, F.; Frappart, F.; Frison, P. L.; Gardelle, J.; Gruhier, C.; Jarlan, L.; Mangiarotti, S.; Sanou, B.; Tracol, Y.; Guichard, F.; Trichon, V.; Diarra, L.; Soumaré, A.; Koité, M.; Dembélé, F.; Lloyd, C.; Hanan, N. P.; Damesin, C.; Delon, C.; Serça, D.; Galy-Lacaux, C.; Seghieri, J.; Becerra, S.; Dia, H.; Gangneron, F.; Mazzega, P.

2009-08-01

SummaryThe Gourma site in Mali is one of the three instrumented meso-scale sites deployed in West-Africa as part of the African Monsoon Multi-disciplinary Analysis (AMMA) project. Located both in the Sahelian zone sensu stricto, and in the Saharo-Sahelian transition zone, the Gourma meso-scale window is the northernmost site of the AMMA-CATCH observatory reached by the West African Monsoon. The experimental strategy includes deployment of a variety of instruments, from local to meso-scale, dedicated to monitoring and documentation of the major variables characterizing the climate forcing, and the spatio-temporal variability of surface processes and state variables such as vegetation mass, leaf area index (LAI), soil moisture and surface fluxes. This paper describes the Gourma site, its associated instrumental network and the research activities that have been carried out since 1984. In the AMMA project, emphasis is put on the relations between climate, vegetation and surface fluxes. However, the Gourma site is also important for development and validation of satellite products, mainly due to the existence of large and relatively homogeneous surfaces. The social dimension of the water resource uses and governance is also briefly analyzed, relying on field enquiry and interviews. The climate of the Gourma region is semi-arid, daytime air temperatures are always high and annual rainfall amounts exhibit strong inter-annual and seasonal variations. Measurements sites organized along a north-south transect reveal sharp gradients in surface albedo, net radiation, vegetation production, and distribution of plant functional types. However, at any point along the gradient, surface energy budget, soil moisture and vegetation growth contrast between two main types of soil surfaces and hydrologic systems. On the one hand, sandy soils with high water infiltration rates and limited run-off support almost continuous herbaceous vegetation with scattered woody plants. On the other hand, water infiltration is poor on shallow soils, and vegetation is sparse and discontinuous, with more concentrated run-off that ends in pools or low lands within structured endorheic watersheds. Land surface in the Gourma is characterized by rapid response to climate variability, strong intra-seasonal, seasonal and inter-annual variations in vegetation growth, soil moisture and energy balance. Despite the multi-decadal drought, which still persists, ponds and lakes have increased, the grass cover has largely recovered, and there are signs of increased tree cover at least in the low lands.

A late Holocene pollen record from proglacial Oblong Tarn, Mount Kenya.

PubMed

Courtney Mustaphi, Colin J; Gajewski, Konrad; Marchant, Rob; Rosqvist, Gunhild

2017-01-01

High-elevation ecosystems, such as those on Mount Kenya are undergoing significant changes, with accelerated glacial ice losses over the twentieth century creating new space for alpine plants to establish. These ecosystems respond rapidly to climatic variability and within decades of glacial retreat, Afroalpine pioneering taxa stabilize barren land and facilitate soil development, promoting complex patches of alpine vegetation. Periglacial lake sediment records can be used to examine centennial and millennial scale variations in alpine and montane vegetation compositions. Here we present a 5300-year composite pollen record from an alpine tarn (4370 m asl) in the Hausberg Valley of Mount Kenya. Overall, the record shows little apparent variation in the pollen assemblage through time with abundant montane forest taxa derived and transported from mid elevations, notably high abundances of aerophilous Podocarpus pollen. Afroalpine taxa included Alchemilla, Helichrysum and Dendrosenecio-type, reflecting local vegetation cover. Pollen from the ericaceous zone was present throughout the record and Poaceae percentages were high, similar to other high elevation pollen records from eastern Africa. The Oblong Tarn record pollen assemblage composition and abundances of Podocarpus and Poaceae since the late Holocene (~4000 cal yr BP-present) are similar to pollen records from mid-to-high elevation sites of nearby high mountains such as Mount Elgon and Kilimanjaro. These results suggest a significant amount of uphill pollen transport with only minor apparent variation in local taxa. Slight decreasing trends in alpine and ericaceous taxonomic groups show a long-term response to global late Holocene cooling and a step decrease in rate of change estimated from the pollen assemblages at 3100 cal yr BP in response to regional hydroclimatic variability. Changes in the principal component axis scores of the pollen assemblage were coherent with an independent mid-elevation temperature reconstruction, which supported the strong influence of uphill pollen transport from montane forest vegetation and association between temperatures and montane vegetation dynamics. Pollen accumulation rates showed some variability related to minerogenic sediment input to the lake. The Oblong Tarn pollen record provides an indication of long term vegetation change atop Mount Kenya showing some decreases in local alpine and ericaceous taxa from 5300-3100 cal yr BP and minor centennial-scale variability of montane taxa from mid elevation forests. The record highlights potentials, challenges and opportunities for the use of proglacial lacustrine sediment to examine vegetation change on prominent mountain massifs.

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Relationships between substrate, surface characteristics, and vegetation in an initial ecosystem

NASA Astrophysics Data System (ADS)

Biber, P.; Seifert, S.; Zaplata, M. K.; Schaaf, W.; Pretzsch, H.; Fischer, A.

2013-12-01

We investigated surface and vegetation dynamics in the artificial initial ecosystem "Chicken Creek" (Lusatia, Germany) in the years 2006-2011 across a wide spectrum of empirical data. We scrutinized three overarching hypotheses concerning (1) the relations between initial geomorphological and substrate characteristics with surface structure and terrain properties, (2) the effects of the latter on the occurrence of grouped plant species, and (3) vegetation density effects on terrain surface change. Our data comprise and conflate annual vegetation monitoring results, biennial terrestrial laser scans (starting in 2008), annual groundwater levels, and initially measured soil characteristics. The empirical evidence mostly confirms the hypotheses, revealing statistically significant relations for several goal variables: (1) the surface structure properties, local rill density, local relief energy and terrain surface height change; (2) the cover of different plant groups (annual, herbaceous, grass-like, woody, Fabaceae), and local vegetation height; and (3) terrain surface height change showed significant time-dependent relations with a variable that proxies local plant biomass. Additionally, period specific effects (like a calendar-year optimum effect for the occurrence of Fabaceae) were proven. Further and beyond the hypotheses, our findings on the spatiotemporal dynamics during the system's early development grasp processes which generally mark the transition from a geo-hydro-system towards a bio-geo-hydro system (weakening geomorphology effects on substrate surface dynamics, while vegetation effects intensify with time), where pure geomorphology or substrate feedbacks are changing into vegetation-substrate feedback processes.

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA.

PubMed

Stephens, Jaime L; Dinger, Eric C; Alexander, John D; Mohren, Sean R; Ralph, C John; Sarr, Daniel A

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region.

Bird Communities and Environmental Correlates in Southern Oregon and Northern California, USA

PubMed Central

Dinger, Eric C.; Alexander, John D.; Mohren, Sean R.; Ralph, C. John; Sarr, Daniel A.

2016-01-01

We examined avian community ecology in the Klamath Ecoregion and determined that individual bird species co-exist spatially to form 29 statistically distinguishable bird groups. We identified climate, geography, and vegetation metrics that are correlated with these 29 bird groups at three scales: Klamath Ecoregion, vegetation formation (agriculture, conifer, mixed conifer/hardwood, shrubland), and National Park Service unit. Two climate variables (breeding season mean temperature and temperature range) and one geography variable (elevation) were correlated at all scales, suggesting that for some vegetation formations and park units there is sufficient variation in climate and geography to be an important driver of bird communities, a level of variation we expected only at the broader scale. We found vegetation to be important at all scales, with coarse metrics (environmental site potential and existing vegetation formation) meaningful across all scales and structural vegetation patterns (e.g. succession, disturbance) important only at the scale of vegetation formation or park unit. Additionally, we examined how well six National Park Service units represent bird communities in the broader Klamath Ecoregion. Park units are inclusive of most bird communities with the exception of the oak woodland community; mature conifer forests are well represented, primarily associated with conifer canopy and lacking multi-layered structure. Identifying environmental factors that shape bird communities at three scales within this region is important; such insights can inform local and regional land management decisions necessary to ensure bird conservation in this globally significant region. PMID:27732625

Exposure of tropical ecosystems to artificial light at night: Brazil as a case study

PubMed Central

Bennie, Jon; Mantovani, Waldir; Gaston, Kevin J.

2017-01-01

Artificial nighttime lighting from streetlights and other sources has a broad range of biological effects. Understanding the spatial and temporal levels and patterns of this lighting is a key step in determining the severity of adverse effects on different ecosystems, vegetation, and habitat types. Few such analyses have been conducted, particularly for regions with high biodiversity, including the tropics. We used an intercalibrated version of the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) images of stable nighttime lights to determine what proportion of original and current Brazilian vegetation types are experiencing measurable levels of artificial light and how this has changed in recent years. The percentage area affected by both detectable light and increases in brightness ranged between 0 and 35% for native vegetation types, and between 0 and 25% for current vegetation (i.e. including agriculture). The most heavily affected areas encompassed terrestrial coastal vegetation types (restingas and mangroves), Semideciduous Seasonal Forest, and Mixed Ombrophilous Forest. The existing small remnants of Lowland Deciduous and Semideciduous Seasonal Forests and of Campinarana had the lowest exposure levels to artificial light. Light pollution has not often been investigated in developing countries but our data show that it is an environmental concern. PMID:28178352

Training Vegetable Parenting Practices Through a Mobile Game: Iterative Qualitative Alpha Test

PubMed Central

Beltran, Alicia; Buday, Richard; Hughes, Sheryl; O'Connor, Teresia; Baranowski, Janice; Dadabhoy, Hafza R; Diep, Cassandra S; Baranowski, Tom

2015-01-01

Background Vegetable consumption protects against chronic diseases, but many young children do not eat vegetables. One quest within the mobile application Mommio was developed to train mothers of preschoolers in effective vegetable parenting practices, or ways to approach getting their child to eat and enjoy vegetables. A much earlier version of the game, then called Kiddio, was alpha tested previously, but the game has since evolved in key ways. Objective The purpose of this research was to alpha test the first quest, substantiate earlier findings and obtain feedback on new game features to develop an effective, compelling parenting game. Methods Mothers of preschool children (n=20) played a single quest of Mommio 2 to 4 times, immediately after which a semi-structured interview about their experience was completed. Interviews were transcribed and double coded using thematic analysis methods. Results Mothers generally liked the game, finding it realistic and engaging. Some participants had difficulties with mechanics for moving around the 3-D environment. Tips and hints were well received, and further expansion and customization were desired. Conclusions Earlier findings were supported, though Mommio players reported more enjoyment than Kiddio players. Continued development will include more user-friendly mechanics, customization, opportunities for environment interaction, and food parenting scenarios. PMID:26208899

Non-valvular main pulmonary artery vegetation associated with aortopulmonary window.

PubMed

Unal, M; Tuncer, C; Serçe, K; Bostan, M; Gökçe, M; Erem, C

1995-01-01

We present a 32-year-old female with aortopulmonary window and vegetation of non-valvular main pulmonary artery. The aortopulmonary window is a rare congenital disease in which the aorta and pulmonary arteries are communicated by a defect of variable diameter. The pulmonic valve is the least commonly involved valve in bacterial endocarditis, but there is no vegetation of non-valvular main pulmonary artery in the literature. Colour duplex sonography showed an aortopulmonary window with aortic regurgitation. Magnetic resonance (MR) imaging demonstrating the vegetation on the wall of main pulmonary artery, is an useful and complementary method, and can be used for demonstration of congenital and acquired cardiovascular pathologies including aortopulmonary window and subpulmonic or suprapulmonic vegetations.

Influence of vegetation dynamic modeling on the allocation of green and blue waters

NASA Astrophysics Data System (ADS)

Ruiz-Pérez, Guiomar; Francés, Félix

2015-04-01

The long history of the Mediterranean region is dominated by the interactions and co-evolution between man and its natural environment. It is important to consider that the Mediterranean region is recurrently or permanently confronted with the scarcity of the water. The issue of climate change is (and will be) aggravating this situation. This raises the question of a loss of services that ecosystems provide to human and also the amount of available water to be used by vegetation. The question of the water cycle, therefore, should be considered in an integrated manner by taking into account both blue water (water in liquid form used for the human needs or which flows into the oceans) and green water (water having the vapor for resulting from evaporation and transpiration processes). In spite of this, traditionally, very few hydrological models have incorporated the vegetation dynamic as a state variable. In fact, most of them are able to represent fairly well the observed discharge, but usually including the vegetation as a static parameter. However, in the last decade, the number of hydrological models which explicitly take into account the vegetation development as a state variable has increased substantially. In this work, we want to analyze if it is really necessary to use a dynamic vegetation model to quantify adequately the distribution of water into blue and green water. The study site is located in the Public Forest Monte de la Hunde y Palomeras (Spain). The vegetation in the study area is dominated by Aleppo pine of high tree density with scant presence of other species. Two different daily models were applied (with static and dynamic vegetation representation respectively) in three different scenarios: dry year (2005), normal year (2008) and wet year (2010). The static vegetation model simulates the evapotranspiration considering the vegetation as a stationary parameter. Contrarily, the dynamic vegetation model connects the hydrological model with a parsimonious dynamic vegetation sub-model which assumes the vegetation biomass as a state variable. Using both models, we estimated the amount of 'blue' water and the amount of 'green' water (according to the previous definitions) in each scenario. Comparing the results, we observed that the static model underestimated the amount of green water in any case (dry, normal or wet year). In fact, the value of the ratio between blue and green water is higher in all scenarios for the static option (0.23 in the dry year, 0.42 in the normal year and 0.96 in the wet year) than the obtained ones for the dynamic model (0.098, 0.29 and 0.76, respectively). It means that we are overestimating the amount of water available for human needs if we assume vegetation as static. This type of error can be very dangerous for water resources predictions with future climates, especially in Mediterranean areas due to their water scarcity.

HYDROLOGIC EVALUATION OF LANDFILL PERFORMANCE (HELP) MODEL - USER'S GUIDE FOR VERSION 3

EPA Science Inventory

This report documents the solution methods and process descriptions used in the Version 3 of the HELP model. Program documentation including program options, system and operating requirements, file structures, program structure and variable descriptions are provided in a separat...

Great Basin vegetation response to groundwater fluctuation, climate variability, and previous land cultivation: The application of multitemporal measurements from remote sensing data to regional vegetation dynamics

NASA Astrophysics Data System (ADS)

Elmore, Andrew James

The conversion of large natural basins to managed watersheds for the purpose of providing water to urban centers has had a negative impact on semiarid ecosystems, worldwide. We view semiarid plant communities as being adapted to short, regular periods of drought. However, human induced changes in the water balance often remove these systems from the range of natural variability that has been historically established. This thesis explores vegetation changes over a 13-yr period for Owens Valley, in eastern California. Using remotely sensed measurements of vegetation cover, an extensive vegetation survey, field data and observations, precipitation records, and data on water table depth, I identify the key modes of response of xeric, phreatophytic, and exotic Great Basin plant communities. Three specific advancements were reached as a result of this work. (1) A change classification technique was developed that was used to separate regions of land-cover that were dependent on precipitation from regions dependent on groundwater. This technique utilized Spectral Mixture Analysis of annually acquired Landsat Thematic Mapper remote sensing data, to retrieve regional estimates of percent vegetation cover. (2) A threshold response related to depth-to-water dependence was identified for phreatophytic Alkali Meadow communities. Plant communities that were subject to groundwater depths below this threshold exhibited greater invasion by precipitation sensitive plants. (3) The floristic differences between previously cultivated and uncultivated land were found to account for an increased sensitivity of plant communities to precipitation variability. Through (2) and (3), two human influences (groundwater decline and previous land cultivation) were shown to alter land cover such that the land became more sensitive to precipitation change. Climate change predictions include a component of increased climate variability for the western United States; therefore, these results place serious doubt on the sustainability of human activities in this region. The results from this work broadly cover topics from remote sensing techniques to the ecology of Great Basin plant communities and are applicable wherever large regions of land are being managed in an era of changing environmental conditions.

a Empirical Modelation of Runoff in Small Watersheds Using LIDAR Data

NASA Astrophysics Data System (ADS)

Lopatin, J.; Hernández, J.; Galleguillos, M.; Mancilla, G.

2013-12-01

Hydrological models allow the simulation of water natural processes and also the quantification and prediction of the effects of human impacts in runoff behavior. However, obtaining the information that is need for applying these models can be costly in both time and resources, especially in large and difficult to access areas. The objective of this research was to integrate LiDAR data in the hydrological modeling of runoff in small watersheds, using derivated hydrologic, vegetation and topography variables. The study area includes 10 small head watersheds cover bay forest, between 2 and 16 ha, which are located in the south-central coastal range of Chile. In each of the former instantaneous rainfall and runoff flow of a total of 15 rainfall events were measured, between August 2012 and July 2013, yielding a total of 79 observations. In March 2011 a Harrier 54/G4 Dual System was used to obtain a LiDAR point cloud of discrete pulse with an average of 4.64 points per square meter. A Digital Terrain Model (DTM) of 1 meter resolution was obtained from the point cloud, and subsequently 55 topographic variables were derived, such as physical watershed parameters and morphometric features. At the same time, 30 vegetation descriptive variables were obtained directly from the point cloud and from a Digital Canopy Model (DCM). The classification and regression "Random Forest" (RF) algorithm was used to select the most important variables in predicting water height (liters), and the "Partial Least Squares Path Modeling" (PLS-PM) algorithm was used to fit a model using the selected set of variables. Four Latent variables were selected (outer model) related to: climate, topography, vegetation and runoff, where in each one was designated a group of the predictor variables selected by RF (inner model). The coefficient of determination (R2) and Goodnes-of-Fit (GoF) of the final model were obtained. The best results were found when modeling using only the upper 50th percentile of rainfall events. The best variables selected by the RF algorithm were three topographic variables and three vegetation related ones. We obtained an R2 of 0.82 and a GoF of 0.87 with a 95% of confidence interval. This study shows that it is possible to predict the water harvesting collected during a rainstorm event in forest environment using only LiDAR data. However, this type of methodology does not have good result in flow produced by low magnitude rainfall events, as these are more influenced by initial conditions of soil, vegetation and climate, which make their behavior slower and erratic.

The Mars Climate Database (MCD version 5.2)

NASA Astrophysics Data System (ADS)

Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team

2015-10-01

The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2

Geomorphology and reflectance patterns of vegetation-covered dunes at the Tsodilo Hills, north-west Botswana

NASA Technical Reports Server (NTRS)

Jacobberger, P. A.; Hooper, D. M.

1991-01-01

Seasonal reflectance variations in semigrid environments provide a means of assessing vegetation health and density as well as monitoring landform processes. Multitemporal Landsat Thematic Mapper scenes with field measurements are used to map geomorphology and vegetation density in a stabilized dune environment and to measure seasonal reflectance changes for a series of ten geomorphological and vegetation units on the Kalahari-age linear dunes. Units were chosen based on differences in landform and proportion of trees, forbs and bare soil. Reflectance curves and normalized-difference vegetation indices (NDVI) show that dune crests have the strongest seasonal variability in color and brightness. The geomorphological link with reflectance and NDVI values are linked to biomass production and zoning of vegetation with slope, drainage and subtle soil differences.

Trend analysis of vegetation in Louisiana's Atchafalaya river basin

USGS Publications Warehouse

O'Neil, Calvin P.; deSteiguer, J. Edward; North, Gary W.

1978-01-01

The purpose of the study was to determine vegetation succession trends; produce a current vegetation map of the basin; and to develop a mathematical model capable of predicting vegetation changes based on hydrologic factors. A statistical relationship of forests and hydrological variables with forest succession constraints predicted forest acreage totals for 16 forest categories within 70% or better of actual values in two-thirds of the cases. Using time-lapsed photography covering 42 years, 23 categories were described. The succession trend of vegetation since 1930, by sedimentation, had been toward mixed hardwoods, except for isolated areas. Satellite MSS Band 7 imagery was used to map the current vegetation into three main categories and for assessment of acreage. Additionally, a geological anomaly was recognized on satellite imagery indication an effect on drainage and sedimentation.

Tailoring auditory training to patient needs with single and multiple talkers: transfer-appropriate gains on a four-choice discrimination test.

PubMed

Barcroft, Joe; Sommers, Mitchell S; Tye-Murray, Nancy; Mauzé, Elizabeth; Schroy, Catherine; Spehar, Brent

2011-11-01

Our long-term objective is to develop an auditory training program that will enhance speech recognition in those situations where patients most want improvement. As a first step, the current investigation trained participants using either a single talker or multiple talkers to determine if auditory training leads to transfer-appropriate gains. The experiment implemented a 2 × 2 × 2 mixed design, with training condition as a between-participants variable and testing interval and test version as repeated-measures variables. Participants completed a computerized six-week auditory training program wherein they heard either the speech of a single talker or the speech of six talkers. Training gains were assessed with single-talker and multi-talker versions of the Four-choice discrimination test. Participants in both groups were tested on both versions. Sixty-nine adult hearing-aid users were randomly assigned to either single-talker or multi-talker auditory training. Both groups showed significant gains on both test versions. Participants who trained with multiple talkers showed greater improvement on the multi-talker version whereas participants who trained with a single talker showed greater improvement on the single-talker version. Transfer-appropriate gains occurred following auditory training, suggesting that auditory training can be designed to target specific patient needs.

Remote sensing technologies applied to the irrigation water management on a golf course

NASA Astrophysics Data System (ADS)

Pedras, Celestina; Lança, Rui; Martins, Fernando; Soares, Cristina; Guerrero, Carlos; Paixão, Helena

2015-04-01

An adequate irrigation water management in a golf course is a complex task that depends upon climate (multiple microclimates) and land cover (where crops differ in morphology, physiology, plant density, sensitivity to water stress, etc.). These factors change both in time and space on a landscape. A direct measurement provides localized values of the evapotranspiration and climate conditions. Therefore this is not a practical or economical methodology for large-scale use due to spatial and temporal variability of vegetation, soils, and irrigation management strategies. Remote sensing technology combines large scale with ground measurement of vegetation indexes. These indexes are mathematical combinations of different spectral bands mostly in the visible and near infrared regions of the electromagnetic spectrum. They represent the measures of vegetation activity that vary not only with the seasonal variability of green foliage, but also across space, thus they are suitable for detecting spatial landscape variability. The spectral vegetation indexes may enhance irrigation management through the information contained in spectral reflectance data. This study was carried out on the 18th fairway of the Royal Golf Course, Vale do Lobo, Portugal, and it aims to establish the relationship between direct measurements and vegetation indexes. For that it is required (1) to characterize the soil and climatic conditions, (2) to assessment of the irrigation system, (3) to estimate the evapotranspiration (4) and to calculate the vegetation indices. The vegetation indices were determined with basis on spectral bands red, green and blue, RGB, and near Infrared, NIR, obtained from the analysis of images acquired from a unpiloted aerial vehicle, UAV, platform. The measurements of reference evapotranspiration (ETo) were obtained from two meteorological stations located in the study area. The landscape evapotranspiration, ETL, was determined in the fairway with multiple microclimates and managed stress. The ETL was obtained thru the use of mobile reference ET stations and also by the development of the surface renewal (SR) measurement technique. The sprinkler irrigation system installed was evaluated according to the methodology described by ASAE. The Normalized Difference Vegetation Index, NDVI, and Visible atmospherically Resistant Index, VARI, are confronted with the direct localized measurements. The NDVI is the most used indicator to assess the vigor status of the vegetation. However, this index depends of the use of NIR bands which demands quite expensive sensors. The use vegetation indexes obtained by sensors that collect data in the visible wavelength, such as VARI is less expensive and allow the vegetative vigor evaluation with a similar rigor. The information of vegetation indices is crossed with edafoclimatic data obtained in situ, in order to improve the irrigation water management based on aerial imagery.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Psychosocial and demographic predictors of fruit, juice and vegetable consumption among 11-14-year-old Boy Scouts

USDA-ARS?s Scientific Manuscript database

Psychosocial and demographic correlates of fruit, juice, and vegetable (FJV) consumption were investigated to guide how to increase FJV intake. Experimental design consisted of hierarchical multiple regression analysis of FJV consumption on demographics and psychosocial variables. Subjects were boys...

Interpreting Physiological Data from Riparian Vegetation: Cautions and Complications

Treesearch

John G. Williams

1989-01-01

Water potential and stomatal conductance are important indicators of the response of vegetation to manipulations of riparian systems. However, interpretation of measurements of these variables is not always straightforward. An extensive monitoring program along the Carmel River in central California, carried out by the Monterey Peninsula Water Management District,...

Organ transplant AN-DRGs: modifying the exceptions hierarchy in casemix classification.

PubMed

Antioch, K; Zhang, X

2000-01-01

The study described in this article sought to develop AN-DRG Version 3 classification revisions for organ transplantation through statistical analyses of recommendations formulated by the Australian Casemix Clinical Committee. Two separate analyses of variance were undertaken for AN-DRG Version 2 and for the proposed Version 3 AN-DRGs, using average length of stay as the dependent variable. The committee made four key recommendations which were accepted and incorporated into AN-DRG Versions 3 and 3.1. This article focuses on the classification revisions for organ transplantation.

The effects of vegetation and climate change on catchment erosion over millennial time scales: Insights from coupled dynamic vegetation and landscape evolution models

NASA Astrophysics Data System (ADS)

Schmid, Manuel; Ehlers, Todd; Werner, Christian; Hickler, Thomas

2017-04-01

Recent studies hypothesize that vegetation and the morphology of landscapes are strongly coupled. On a small scale, plants influence the erosivity of soil and sediments and therefore systematically impact catchment erosion and topography. Previous landscape evolution modeling studies primarily focus on changes in fluvial and hillslope erosion due to variations in climate and tectonics, without explicit consideration of vegetation effects. In this study, we complement previous work by investigating the effects of vegetation and vegetation change on hillslope and fluvial processes by combining LPJ-GUESS, a dynamic global vegetation model, with a modified version of the Landlab surface process model. The LandLab model was extended to account for vegetation-dependent sediment fluxes for both hillslope and detachment-limited fluvial erosion. The models are coupled by using predicted changes in surface vegetation from LPJ-GUESS for different climate scenarios as input for vegetation dependent erosional coefficients in Landlab. Simulations were conducted with the general climate and vegetation conditions representative between 25° and 40°S along the Coastal Cordillera of Chile. This region is the focus of the EarthShape research program (www.earthshape.net). These areas present a natural climatic and associated vegetation gradient that ranges from hyper-arid (Atacama desert) to humid-temperate conditions without a dry season and pristine temperate Araucaria forest. All study areas considered have a similar and uniform granite substrate, which minimizes lithologic variations and their effect on catchment erosion. Simulations are in progress that were designed to independently determine the climatic or vegetation controls on topography and erosion histories over the last 21 kyr. Our preliminary findings suggest that an increase in the surface vegetation results in a modulation of the mean hillslope angle and the average drainage density. In addition, we find that a decrease in surface vegetation density within a landscape can act as a trigger for sudden pulses of erosion, leading towards a new equilibrium topography. Our study suggests that vegetation changes (e.g. from the Last Glacial Maximum to present) act as a main agent of perturbing topographic equilibria. Reducing surface vegetation increases erosional efficiency and therefore sediment transport until a new stable state is reached.

Spatial and temporal variability of runoff and streamflow generation within and among headwater catchments: a combined hydrometric and stable isotope approach

NASA Astrophysics Data System (ADS)

Singh, N. K.; Emanuel, R. E.; McGlynn, B. L.

2012-12-01

The combined influence of topography and vegetation on runoff generation and streamflow in headwater catchments remains unclear. We aim to understand how spatial, hydrological and climate variables affect runoff generation and streamflow at hillslope and watershed scales at the Coweeta Hydrologic Laboratory (CHL) in the southern Appalachian Mountains by analyzing stable isotopes of hydrogen (2H) and oxygen (18O) coupled with measurements of hydrological variables (stream discharge, soil moisture, shallow groundwater) and landscape variables (upslope accumulated area, vegetation density slope, and aspect). We investigated four small catchments, two of which contained broadleaf deciduous vegetation and two of which contained evergreen coniferous vegetation. Beginning in June 2011, we collected monthly water samples at 25 m intervals along each stream, monthly samples from 24 shallow groundwater wells, and weekly to monthly samples from 10 rain gauges distributed across CHL. Water samples were analyzed for 2H and 18O using cavity ring-down spectroscopy. During the same time period we recorded shallow groundwater stage at 30 min intervals from each well, and beginning in fall 2011 we collected volumetric soil moisture data at 30 min intervals from multiple depths at 16 landscape positions. Results show high spatial and temporal variability in δ2H and δ18O within and among streams, but in general we found isotopic enrichment with increasing contributing area along each stream. We used a combination of hydrometric observations and geospatial analyses to understand why stream isotope patterns varied during the year and among watersheds, and we used complementary measurements of δ2H and δ18O from other pools within the watersheds to understand the movement and mixing of precipitation that precedes runoff formation. This combination of high resolution stable isotope data and hydrometric observations facilitates a clearer understanding of spatial controls on streamflow generation. In addition, understanding the relative influences of topography and vegetation on runoff generation could help scientists and managers better assess potential impacts of disturbance on water supplies downstream of forested headwater catchments.

Monitoring the state of vegetation in Hungary using 15 years long MODIS Data

NASA Astrophysics Data System (ADS)

Kern, Anikó; Bognár, Péter; Pásztor, Szilárd; Barcza, Zoltán; Timár, Gábor; Lichtenberger, János; Ferencz, Csaba

2015-04-01

Monitoring the state and health of the vegetation is essential to understand causes and severity of environmental change and to prepare for the negative effects of climate change on plant growth and productivity. Satellite remote sensing is the fundamental tool to monitor and study the changes of vegetation activity in general and to understand its relationship with the climate fluctuations. Vegetation indices and other vegetation related measures calculated from remotely sensed data are widely used to monitor and characterize the state of the terrestrial vegetation. Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are among the most popular indices that can be calculated from measurements of the MODerate resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS-AM1/Terra and EOS-PM1/Aqua satellites (since 1999 and 2002 respectively). Based on the available, 15 years long MODIS data (2000-2014) the vegetation characteristics of Hungary was investigated in our research, primarily using vegetation indices. The MODIS NDVI and EVI (both part of the so-called MOD13 product of NASA) are freely available with a finest spatial resolution of 250 meters and a temporal resolution of 16 days since 2000/2002 (for Terra and Aqua respectively). The accuracy, the spatial resolution and temporal continuity of the MODIS products makes these datasets highly valuable despite of its relatively short temporal coverage. NDVI is also calculated routinely from the raw MODIS data collected by the receiving station of Eötvös Loránd University. In order to characterize vegetation activity and its variability within the Carpathian Basin the area-averaged annual cycles and their interannual variability were determined. The main aim was to find those years that can be considered as extreme according to specific indices. Using archive meteorological data the effects of extreme weather on vegetation activity and growth were investigated with emphasis on drought and heat waves. Te relationship between anomalies of vegetation characteristics and crop yield decrease in agricultural regions were characterised as well. The mean NDVI values of Hungary during the 15 years reveal the behaviour of the vegetation in the country, where the main land cover types (forest, agriculture and grassland) were distinguished as well. NDVI anomalies are analyzed separately for the main land cover types. Deviations from the potential maximum vegetation greenness are also calculated for the entire time period.

Correlation between the habitats productivity and species richness (amphibians and reptiles) in Portugal through remote sensed data

NASA Astrophysics Data System (ADS)

Teodoro, A. C.; Sillero, N.; Alves, S.; Duarte, L.

2013-10-01

Several biogeographic theories propose that the species richness depends on the structure and ecosystems diversity. The habitat productivity, a surrogate for these variables, can be evaluated through satellite imagery, namely using vegetation indexes (e.g. NDVI). We analyzed the correlation between species richness (from the Portuguese Atlas of Amphibians and Reptiles) and NDVI (from Landsat, MODIS, and Vegetation images). The species richness database contains more than 80000 records, collected from bibliographic sources (at 1 or 10 km of spatial resolution) and fieldwork sampling stations (recorded with GPS devices). Several study areas were chosen for Landsat images (three subsets), and all Portugal for MODIS and Vegetation images. The Landsat subareas had different climatic and habitat characteristics, located in the north, center and south of Portugal. Different species richness datasets were used depending on the image spatial resolution: data with metric resolution were used for Landsat, and with 1 km resolution, for MODIS and Vegetation images. The NDVI indexes and all the images were calculated/processed in an open source software (Quantum GIS). Several plug-ins were applied in order to automatize several procedures. We did not find any correlation between the species richness of amphibians and reptiles (not even after separating both groups by species of Atlantic and Mediterranean affinity) and the NDVI calculated with Landsat, MODIS and Vegetation images. Our results may fail to find a relationship because as the species richness is not correlated with only one variable (NDVI), and thus other environmental variables must be considered.

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

USGS Publications Warehouse

Kumar, S.; Simonson, S.E.; Stohlgren, T.J.

2009-01-01

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 ?? 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike's Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions. ?? 2008 Springer Science+Business Media B.V.

SRS 2010 Vegetation Inventory GeoStatistical Mapping Results for Custom Reaction Intensity and Total Dead Fuels.

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

Edwards, Lloyd A.; Paresol, Bernard

This report of the geostatistical analysis results of the fire fuels response variables, custom reaction intensity and total dead fuels is but a part of an SRS 2010 vegetation inventory project. For detailed description of project, theory and background including sample design, methods, and results please refer to USDA Forest Service Savannah River Site internal report “SRS 2010 Vegetation Inventory GeoStatistical Mapping Report”, (Edwards & Parresol 2013).

Socioecological and soil-plant studies of the natural vegetation in the northern Mojave Desert-Great Basin Desert interface

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

El-Ghonemy, A.A.; Wallace, A.; Romney, E.M.

1980-01-01

The purpose of this study is to further describe the distribution, habitats, and ecological characteristics of the natural vegetation in the northern sector of the northern Mojave Desert. Sixty-six stands were classified on the basis of shared leading dominant species. Each of these groupings is well defined and represents a sociologically distinct entity quite recognizable in the field. The relationships between each vegetational grouping and several environmental variables were statistically analyzed. Significant differences were found among plant groupings with respect to soil moisture tension, absolute and relative amounts of exchangeable Na, exchangeable K, cation exchange capacity, and elevation. The analysismore » of the relationship between the phytosociological behavior of the major leading dominant species and the environmental variables shows that some of the simple, or multiple, linear correlations obtained with regard to Larrea tridentata were highly significant. Atriplex confertifolia and Atriplex canescens showed the highest number of significant correlations obtained. Diversity varies from one vegetational grouping to the other as well as between stands of the same grouping. The grouping of L. tridentata has proved to be the most widespread, diversified, and consequently the most stable vegetation cover in the study area; it, therefore, represents a climate community. The vegetational grouping dominated by A. confertifolia, on the other hand, appears not to be a climax community.« less

Retrieval of seasonal dynamics of forest understory reflectance from semi-arid to boreal forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael; Karnieli, Arnon; Sprintsin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi

2016-04-01

Ground vegetation (understory) provides an essential contribution to the whole-stand reflectance signal in many boreal, sub-boreal, and temperate forests. Accurate knowledge about forest understory reflectance is urgently needed in various forest reflectance modelling efforts. However, systematic collections of understory reflectance data covering different sites and ecosystems are almost missing. Measurement of understory reflectance is a real challenge because of an extremely high variability of irradiance at the forest floor, weak signal in some parts of the spectrum, spectral separability issues of over- and understory and its variable nature. Understory can consist of several sub-layers (regenerated tree, shrub, grasses or dwarf shrub, mosses, lichens, litter, bare soil), it has spatially-temporally variable species composition and ground coverage. Additional challenges are introduced by patchiness of ground vegetation, ground surface roughness, and understory-overstory relations. Due to this variability, remote sensing might be the only means to provide consistent data at spatially relevant scales. In this presentation, we report on retrieving seasonal courses of understory Normalized Difference Vegetation Index (NDVI) from multi-angular MODIS BRDF/Albedo data. We compared satellite-based seasonal courses of understory NDVI against an extended collection of different types of forest sites with available in-situ understory reflectance measurements. These sites are distributed along a wide latitudinal gradient on the Northern hemisphere: a sparse and dense black spruce forests in Alaska and Canada, a northern European boreal forest in Finland, hemiboreal needleleaf and deciduous stands in Estonia, a mixed temperate forest in Switzerland, a cool temperate deciduous broadleaf forest in Korea, and a semi-arid pine plantation in Israel. Our results indicated the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated. The retrieval of understory signal can be used e.g. to improve the estimates of leaf area index (LAI), fAPAR in sparsely vegetated areas, and also to study the phenology of understory layer. Our results are particularly useful to producing Northern hemisphere maps of seasonal dynamics of forests, allowing to separately retrieve understory variability, being a main contributor to spring emergence and fall senescence uncertainty. The inclusion of understory variability in ecological models will ultimately improve prediction and forecast horizons of vegetation dynamics.

Accounting for the influence of vegetation and landscape improves model transferability in a tropical savannah region

NASA Astrophysics Data System (ADS)

Gao, Hongkai; Hrachowitz, Markus; Sriwongsitanon, Nutchanart; Fenicia, Fabrizio; Gharari, Shervan; Savenije, Hubert H. G.

2016-10-01

Understanding which catchment characteristics dominate hydrologic response and how to take them into account remains a challenge in hydrological modeling, particularly in ungauged basins. This is even more so in nontemperate and nonhumid catchments, where—due to the combination of seasonality and the occurrence of dry spells—threshold processes are more prominent in rainfall runoff behavior. An example is the tropical savannah, the second largest climatic zone, characterized by pronounced dry and wet seasons and high evaporative demand. In this study, we investigated the importance of landscape variability on the spatial variability of stream flow in tropical savannah basins. We applied a stepwise modeling approach to 23 subcatchments of the Upper Ping River in Thailand, where gradually more information on landscape was incorporated. The benchmark is represented by a classical lumped model (FLEXL), which does not account for spatial variability. We then tested the effect of accounting for vegetation information within the lumped model (FLEXLM), and subsequently two semidistributed models: one accounting for the spatial variability of topography-based landscape features alone (FLEXT), and another accounting for both topographic features and vegetation (FLEXTM). In cross validation, each model was calibrated on one catchment, and then transferred with its fitted parameters to the remaining catchments. We found that when transferring model parameters in space, the semidistributed models accounting for vegetation and topographic heterogeneity clearly outperformed the lumped model. This suggests that landscape controls a considerable part of the hydrological function and explicit consideration of its heterogeneity can be highly beneficial for prediction in ungauged basins in tropical savannah.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

An assessment of climate change and the vulnerability of wildlife in the Sky Islands of the Southwest

Treesearch

Sharon J. Coe; Deborah M. Finch; Megan M. Friggens

2012-01-01

We evaluated the historical and projected trends in climate and vegetation relevant to the Coronado National Forest in southeast Arizona, USA. We then applied this information in an assessment of the vulnerability of 30 species of terrestrial vertebrates on the Coronado National Forest to the potential effects of future climate change. We used a pilot version of a...

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

2017-10-01

In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

Variability of surface temperature in agricultural fields of central California

NASA Technical Reports Server (NTRS)

Hatfield, J. L.; Millard, J. P.; Goettelman, R. C.

1982-01-01

In an attempt to evaluate the relationship between hand-held infrared thermometers and aircraft thermal scanners in near-level terrain and to quantify the variability of surface temperatures within individual fields, ground-based and aircraft thermal sensor measurements were made along a 50-km transect on 3 May 1979 and a 20-km transect on 7 August 1980. These comparisons were made on fields near Davis, California. Agreement was within 1 C for fields covered with vegetation and 3.6 C for bare, dry fields. The variability within fields was larger for bare, dry fields than for vegetatively covered fields. In 1980, with improvements in the collection of ground truth data, the agreement was within 1 C for a variety of fields.

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

NASA Technical Reports Server (NTRS)

Greegor, D.; Norwine, J. (Principal Investigator)

1981-01-01

A climatological model/variable termed the sponge (a measure of moisture availability based on daily temperature maxima and minima, and precipitation) was tested for potential biogeograhic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic form, suggest that, as generalized climatic index, sponge is particularly appropriate for large-area and global vegetation monitoring. The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge and AVHRR data was initiated. Along an east-west Texas gradient, vegetation, sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values along the Texas gradient suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

A remote sensing based vegetation classification logic for global land cover analysis

USGS Publications Warehouse

Running, Steven W.; Loveland, Thomas R.; Pierce, Lars L.; Nemani, R.R.; Hunt, E. Raymond

1995-01-01

This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.

Older People's Perceptions of Pedestrian Friendliness and Traffic Safety: An Experiment Using Computer-Simulated Walking Environments.

PubMed

Kahlert, Daniela; Schlicht, Wolfgang

2015-08-21

Traffic safety and pedestrian friendliness are considered to be important conditions for older people's motivation to walk through their environment. This study uses an experimental study design with computer-simulated living environments to investigate the effect of micro-scale environmental factors (parking spaces and green verges with trees) on older people's perceptions of both motivational antecedents (dependent variables). Seventy-four consecutively recruited older people were randomly assigned watching one of two scenarios (independent variable) on a computer screen. The scenarios simulated a stroll on a sidewalk, as it is 'typical' for a German city. In version 'A,' the subjects take a fictive walk on a sidewalk where a number of cars are parked partially on it. In version 'B', cars are in parking spaces separated from the sidewalk by grass verges and trees. Subjects assessed their impressions of both dependent variables. A multivariate analysis of covariance showed that subjects' ratings on perceived traffic safety and pedestrian friendliness were higher for Version 'B' compared to version 'A'. Cohen's d indicates medium (d = 0.73) and large (d = 1.23) effect sizes for traffic safety and pedestrian friendliness, respectively. The study suggests that elements of the built environment might affect motivational antecedents of older people's walking behavior.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

PubMed

Tagesson, Torbern; Fensholt, Rasmus; Guiro, Idrissa; Rasmussen, Mads Olander; Huber, Silvia; Mbow, Cheikh; Garcia, Monica; Horion, Stéphanie; Sandholt, Inge; Holm-Rasmussen, Bo; Göttsche, Frank M; Ridler, Marc-Etienne; Olén, Niklas; Lundegard Olsen, Jørgen; Ehammer, Andrea; Madsen, Mathias; Olesen, Folke S; Ardö, Jonas

2015-01-01

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models. © 2014 John Wiley & Sons Ltd.

One-Year Efficacy Testing of Enabling Mothers to Prevent Pediatric Obesity Through Web-Based Education and Reciprocal Determinism (EMPOWER) Randomized Control Trial.

PubMed

Knowlden, Adam; Sharma, Manoj

2016-02-01

The purpose of this study was to evaluate the efficacy of the Enabling Mothers to Prevent Pediatric Obesity through Web-Based Education and Reciprocal Determinism (EMPOWER) intervention at 1-year, postintervention follow-up. A mixed between-within subjects design was used to evaluate the trial. Independent variables included a two-level, group assignment: EMPOWER (experimental intervention) based on social cognitive theory (SCT) as well as a knowledge-based intervention Healthy Lifestyles (active control intervention). Dependent variables were evaluated across four levels of time: baseline (Week 0), posttest (Week 4), 1-month follow-up (Week 8), and 1-year follow-up (Week 60). Dependent variables included five maternal-facilitated SCT constructs (environment, emotional coping, expectations, self-control, and self-efficacy) as well as four child behaviors (minutes of child physical activity, cups of fruits and vegetables consumed, 8-ounce glasses of sugar-sweetened beverages consumed, and minutes of screen time). Null hypotheses implied no significant group-by-time interactions for the dependent variables under investigation. A significant group-by-time interaction for child fruit and vegetable consumption was found in the experimental group (p = .012) relative to the control group. At 1 year, results suggested an overall increase of 1.847 cups of fruits and vegetables (95% confidence interval = 1.207-2.498) in the experimental group (p < .001). Analysis suggested changes in the maternal-facilitated home environment accounted for 13.3% of the variance in the change in child fruit and vegetable consumption. Improvements in child physical activity, sugar-free beverage intake, and screen time first detected at 1-month follow-up in both groups were no longer significant at 1-year follow-up. An online family-and-home-based intervention was efficacious for improving child fruit and vegetable consumption. Follow-up booster sessions may assist in maintaining treatment effects. © 2015 Society for Public Health Education.

Functional Extended Redundancy Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop

2012-01-01

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

Developing a global mixed-canopy, height-variable vegetation structure dataset for estimating global vegetation albedo and biomass in the NASA Ent Terrestrial Biosphere Model and GISS GCM

NASA Astrophysics Data System (ADS)

Montes, C.; Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Schaaf, C.; Aleinov, I. D.; Jonas, J.; Zhao, F. A.; Yao, T.; Wang, Z.; Sun, Q.

2015-12-01

Processes determining biosphere-atmosphere coupling are strongly influenced by vegetation structure. Thus, ecosystem carbon sequestration and evapotranspiration affecting global carbon and water balances will depend upon the spatial extent of vegetation, its vertical structure, and its physiological variability. To represent this globally, Dynamic Global Vegetation Models (DGVMs) coupled to General Circulation Models (GCMs) make use of satellite and/or model-based vegetation classifications often composed by homogeneous communities. This work aims at developing a new Global Vegetation Structure Dataset (GVSD) by incorporating varying vegetation heights for mixed plant communities to be used as input to the Ent Terrestrial Biosphere Model (TBM), the DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. Information sources include the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and plant functional types (PFTs) (Friedl et al., 2010), vegetation height from the Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice, Cloud, and land Elevation Satellite) (Simard et al., 2011; Tang et al., 2014) along with the Global Data Sets of Vegetation Leaf Area Index (LAI)3g (Zhu et al. 2013). Further PFT partitioning is performed according to a climate classification utilizing the Climate Research Unit (CRU) and the NOAA Global Precipitation Climatology Centre (GPCC) data. Final products are a GVSD consisting of mixed plant communities (e.g. mixed forests, savannas, mixed PFTs) following the Ecosystem Demography model (Moorcroft et al., 2001) approach represented by multi-cohort community patches at the sub-grid level of the GCM, which are ensembles of identical individuals whose differences are represented by PFTs, canopy height, density and vegetation structure sensitivity to allometric parameters. To assess the sensitivity of the GISS GCM to vegetation structure, we produce a range of estimates of Ent TBM biomass and plant densities by varying allometric specifications. Ultimately, this GVSD will serve as a template for community data sets, and be used as boundary conditions to the Ent TBM for prediction of canopy albedo in the Analytical Clumped Two-Stream canopy radiative transfer scheme, biomass, primary productivity, respiration, and GISS GCM climate.

Spatial contexts for temporal variability in alpine vegetation under ongoing climate change

USGS Publications Warehouse

Fagre, Daniel B.; ,; George P. Malanson,

2013-01-01

A framework to monitor mountain summit vegetation (The Global Observation Research Initiative in Alpine Environments, GLORIA) was initiated in 1997. GLORIA results should be taken within a regional context of the spatial variability of alpine tundra. Changes observed at GLORIA sites in Glacier National Park, Montana, USA are quantified within the context of the range of variability observed in alpine tundra across much of western North America. Dissimilarity is calculated and used in nonmetric multidimensional scaling for repeated measures of vascular species cover at 14 GLORIA sites with 525 nearby sites and with 436 sites in western North America. The lengths of the trajectories of the GLORIA sites in ordination space are compared to the dimensions of the space created by the larger datasets. The absolute amount of change on the GLORIA summits over 5 years is high, but the degree of change is small relative to the geographical context. The GLORIA sites are on the margin of the ordination volumes with the large datasets. The GLORIA summit vegetation appears to be specialized, arguing for the intrinsic value of early observed change in limited niche space.

Distance and environmental difference in alpine plant communities

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Fagre, Daniel B.

2017-01-01

Differences in plant communities are a response to the abiotic environment, species interactions, and dispersal. The role of geographic distance relative to the abiotic environment is explored for alpine tundra vegetation from 319 plots of four regions along the Rocky Mountain cordillera in the USA. The site by species data were ordinated using nonmetric multidimensional scaling to produce dependent variables for use in best-subsets regression. For independent variables, observations of local topography and microtopography were used as environmental indicators. Two methods of including distance in studies of vegetation and environment are used and contrasted. The relative importance of geographic distance in accounting for the pattern of alpine tundra similarity indicates that location is a factor in plant community composition. Mantel tests provide direct correlations between difference and distance but have known weaknesses. Moran spatial eigenvectors used in regression based approaches have greater geographic specificity, but require another step, ordination, in creating a vegetation variable. While the spatial eigenvectors are generally preferable, where species–environment relations are weak, as seems to be the case for the alpine sites studied here, the fewer abstractions of the Mantel test may be useful.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

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

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

NASA Astrophysics Data System (ADS)

Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat) and 500m Moderate Resolution Imaging Spectrometer (MODIS). A robust logistic-growth model of canopy cover was employed to determine phenological characteristics at each forest stand. The duel analyses revealed important findings: (a) local phenological gradients from microclimatic structures are highly influential in broad-scale phenological observations; (b) satellite observed phenology reflects observations of canopy growth from field studies; (c) phenological anomalies in urban areas which were previously attributed to urban heat may be a function of urban-specific land cover (i.e. green lawns); and (d) patterns of interannual variability in phenology at the regional scale have high spatial coherency and appear to be driven by broad-scale climatic change. Satellite-observed phenology may reflect temperatures during spring and provides a proxy of climate variability.

Downstream Effects of Diversion Dams on Riparian Vegetation Communities in the Routt National Forest, Colorado

NASA Astrophysics Data System (ADS)

Caskey, S. T.; Wohl, E. E.; Dwire, K. A.; Merritt, D. M.; Schnackenberg, L.

2012-12-01

The relationship between riparian vegetation and changes in fluvial processes as a response to flow diversion is not well understood. Water extraction affects the hydrologic flow regime (i.e., magnitude, duration, and frequency of flows) reducing peak and base-flows, which could negatively impact riparian vegetation. Vegetation communities are temporally and spatially variable and are strongly interrelated with alluvial landforms and hydrograph variability. This research compares riparian community characteristics on diverted and undiverted pool-riffle channels and low gradient valleys to examine changes associated with flow diversion in the Routt National Forest (RNF). The RNF is the only under-appropriated area in Colorado, making future water extraction proposals likely. Many small extraction canals siphon water from small, headwater streams in the RNF, but the site-specific or cumulative effects of these diversions on riverine ecosystems have not been investigated. Systematic investigation is necessary, however, to determine whether existing flow diversions have influenced riparian communities and, if so, which communities are most sensitive to diversions. A total of 36 sites were sampled with five channel cross sections established per site, extending into the riparian zone at distance of two times the active channel width, and vegetation was sampled using the line-point intercept method. Preliminary results suggest a shift in vegetation communities from typical riparian species composition to more upland vegetation. The relative sensitivity of these responses are different depending on valley type; low- gradient, unconfined areas are less tolerant of diversion than steeper, confined reaches. Additionally, when stratified by plant assemblage, Salix abundance is significantly reduced downstream of diversion. The results of this study contribute to the collective understanding of mountain headwater riparian vegetation community response to changes in flow regimes and fluvial processes related directly to water extraction by diversion dams.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile.

PubMed

Glade, Francisco E; Miranda, Marcelo D; Meza, Francisco J; van Leeuwen, Willem J D

2016-12-01

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.

Satellite view of seasonal greenness trends and controls in South Asia

NASA Astrophysics Data System (ADS)

Sarmah, Sangeeta; Jia, Gensuo; Zhang, Anzhi

2018-03-01

South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982–2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

A true challenge for any superhero: an evaluation of a comic book obesity prevention program.

PubMed

Branscum, Paul; Sharma, Manoj; Wang, Lihshing Leigh; Wilson, Bradley R A; Rojas-Guyler, Liliana

2013-01-01

The purpose of this study was to pilot test the Comics for Health program, a theory-based nutrition and physical activity intervention for children. Twelve after-school programs were randomized to either a theory-based (n = 37) or a knowledge-based (n = 34 children) version of the intervention. Pretests, posttests, and 3-month follow-up tests were administered to evaluate the programmatic effects on body mass index percentile, obesity-related behaviors, and constructs of social cognitive theory. Both interventions found significant, yet modest effects for fruit and vegetable consumption (P < .005), physical activities (P < .004), and water and sugar-free beverage consumption (P < .001) and self-efficacy for fruit and vegetable consumption (P < .015) and physical activities (P < .009).

Accounting for observation uncertainties in an evaluation metric of low latitude turbulent air-sea fluxes: application to the comparison of a suite of IPSL model versions

NASA Astrophysics Data System (ADS)

Servonnat, Jérôme; Găinuşă-Bogdan, Alina; Braconnot, Pascale

2017-09-01

Turbulent momentum and heat (sensible heat and latent heat) fluxes at the air-sea interface are key components of the whole energetic of the Earth's climate. The evaluation of these fluxes in the climate models is still difficult because of the large uncertainties associated with the reference products. In this paper we present an objective metric accounting for reference uncertainties to evaluate the annual cycle of the low latitude turbulent fluxes of a suite of IPSL climate models. This metric consists in a Hotelling T 2 test between the simulated and observed field in a reduce space characterized by the dominant modes of variability that are common to both the model and the reference, taking into account the observational uncertainty. The test is thus more severe when uncertainties are small as it is the case for sea surface temperature (SST). The results of the test show that for almost all variables and all model versions the model-reference differences are not zero. It is not possible to distinguish between model versions for sensible heat and meridional wind stress, certainly due to the large observational uncertainties. All model versions share similar biases for the different variables. There is no improvement between the reference versions of the IPSL model used for CMIP3 and CMIP5. The test also reveals that the higher horizontal resolution fails to improve the representation of the turbulent surface fluxes compared to the other versions. The representation of the fluxes is further degraded in a version with improved atmospheric physics with an amplification of some of the biases in the Indian Ocean and in the intertropical convergence zone. The ranking of the model versions for the turbulent fluxes is not correlated with the ranking found for SST. This highlights that despite the fact that SST gradients are important for the large-scale atmospheric circulation patterns, other factors such as wind speed, and air-sea temperature contrast play an important role in the representation of turbulent fluxes.

Mapping Variation in Vegetation Functioning with Imaging Spectroscopy

NASA Astrophysics Data System (ADS)

Townsend, P. A.; Couture, J. J.; Kruger, E. L.; Serbin, S.; Singh, A.

2015-12-01

Imaging spectroscopy (otherwise known as hyperspectral remote sensing) offers the potential to characterize the spatial and temporal variation in biophysical and biochemical properties of vegetation that can be costly or logistically difficult to measure comprehensively using traditional methods. A number of recent studies have illustrated the capacity for imaging spectroscopy data, such as from NASA's AVIRIS sensor, to empirically estimate functional traits related to foliar chemistry and physiology (Singh et al. 2015, Serbin et al. 2015). Here, we present analyses that illustrate the implications of those studies to characterize within-field or -stand variability in ecosystem functioning. In agricultural ecosystems, within-field photosynthetic capacity can vary by 30-50%, likely due to within-field variations in water availability and soil fertility. In general, the variability of foliar traits is lower in forests than agriculture, but can still be significant. Finally, we demonstrate that functional trait variability at the stand scale is strongly related to vegetation diversity. These results have two significant implications: 1) reliance on a small number of field samples to broadly estimate functional traits likely underestimates variability in those traits, and 2) if trait estimations from imaging spectroscopy are reliable, such data offer the opportunity to greatly increase the density of measurements we can use to predict ecosystem function.

Visualizing the ill-posedness of the inversion of a canopy radiative transfer model: A case study for Sentinel-2

NASA Astrophysics Data System (ADS)

Zurita-Milla, R.; Laurent, V. C. E.; van Gijsel, J. A. E.

2015-12-01

Monitoring biophysical and biochemical vegetation variables in space and time is key to understand the earth system. Operational approaches using remote sensing imagery rely on the inversion of radiative transfer models, which describe the interactions between light and vegetation canopies. The inversion required to estimate vegetation variables is, however, an ill-posed problem because of variable compensation effects that can cause different combinations of soil and canopy variables to yield extremely similar spectral responses. In this contribution, we present a novel approach to visualise the ill-posed problem using self-organizing maps (SOM), which are a type of unsupervised neural network. The approach is demonstrated with simulations for Sentinel-2 data (13 bands) made with the Soil-Leaf-Canopy (SLC) radiative transfer model. A look-up table of 100,000 entries was built by randomly sampling 14 SLC model input variables between their minimum and maximum allowed values while using both a dark and a bright soil. The Sentinel-2 spectral simulations were used to train a SOM of 200 × 125 neurons. The training projected similar spectral signatures onto either the same, or contiguous, neuron(s). Tracing back the inputs that generated each spectral signature, we created a 200 × 125 map for each of the SLC variables. The lack of spatial patterns and the variability in these maps indicate ill-posed situations, where similar spectral signatures correspond to different canopy variables. For Sentinel-2, our results showed that leaf area index, crown cover and leaf chlorophyll, water and brown pigment content are less confused in the inversion than variables with noisier maps like fraction of brown canopy area, leaf dry matter content and the PROSPECT mesophyll parameter. This study supports both educational and on-going research activities on inversion algorithms and might be useful to evaluate the uncertainties of retrieved canopy biophysical and biochemical state variables.

Greening the Grid - Advancing Solar, Wind, and Smart Grid Technologies (Spanish Version)

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

This is the Spanish version of 'Greening the Grid - Advancing Solar, Wind, and Smart Grid Technologies'. Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

Spectral Unmixing of Vegetation, Soil and Dry Carbon in Arid Regions: Comparing Multispectral and Hyperspectral Observations

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Heidebrecht, Kathleen B.

2001-01-01

Remote sensing of vegetation cover and condition is critically needed to understand the impacts of land use and climate variability in and and semi-arid regions. However, remote sensing of vegetation change in these environments is difficult for several reasons. First, individual plant canopies are typically small and do not reach the spatial scale of typical Landsat-like satellite image pixels. Second, the phenological status and subsequent dry carbon (or non-photosynthetic) fraction of plant canopies varies dramatically in both space and time throughout and and semi-arid regions. Detection of only the 'green' part of the vegetation using a metric such as the normalized difference vegetation index (NDVI) thus yields limited information on the presence and condition of plants in these ecosystems. Monitoring of both photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) is needed to understand a range of ecosystem characteristics including vegetation presence, cover and abundance, physiological and biogeochemical functioning, drought severity, fire fuel load, disturbance events and recovery from disturbance.

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer. [North America

NASA Technical Reports Server (NTRS)

Goward, S. N.; Tucker, C. J.; Dye, D. G.

1985-01-01

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the advanced very high resolution radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. Significant information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

Plant Succession on the Mount St. Helen's Debris-Avalanche Deposit and the Role of Non-native Species

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

Denton, Elsie M.; Dale, Virginia H.

The abstract is published online only. If you did not include a short abstract for the online version when you submitted the manuscript, the first paragraph or the first 10 lines of the chapter will be displayed here. If possible, please provide us with an informative abstract. The debris-avalanche deposit is one of the most disturbed areas created by the 1980 eruption of Mount St. Helens, with little survival of a few plant fragments and primary succession mostly being initiated by the seeds dispersed onto the newly emplaced material. Vegetation changes on the debris-avalanche deposit during the first 30 yearsmore » post eruption are analyzed considering the role of non-native species and potential future vegetation patterns on the deposit. We found that the aerial distribution of largely non-native seeds on a subset of plots at Mount St. Helens in 1980 has had a pronounced and enduring effect on subsequent vegetation communities.« less

Vegetation regulation on streamflow intra-annual variability through adaption to climate variations

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

Ye, Sheng; Li, Hongyi; Li, Shuai

2015-12-16

This study aims to provide a mechanistic explanation of the empirical patterns of streamflow intra-annual variability revealed by watershed-scale hydrological data across the contiguous United States. A mathematical extension of the Budyko formula with explicit account for the soil moisture storage change is used to show that, in catchments with a strong seasonal coupling between precipitation and potential evaporation, climate aridity has a dominant control on intra-annual streamflow variability, but in other catchments, additional factors related to soil water storage change also have important controls on how precipitation seasonality propagates to streamflow. More importantly, use of leaf area index asmore » a direct and indirect indicator of the above ground biomass and plant root system, respectively, reveals the vital role of vegetation in regulating soil moisture storage and hence streamflow intra-annual variability under different climate conditions.« less

Effects of light quality on the accumulation of phytochemicals in vegetables produced in controlled environments: a review.

PubMed

Bian, Zhong Hua; Yang, Qi Chang; Liu, Wen Ke

2015-03-30

Phytochemicals in vegetables are important for human health, and their biosynthesis, metabolism and accumulation are affected by environmental factors. Light condition (light quality, light intensity and photoperiod) is one of the most important environmental variables in regulating vegetable growth, development and phytochemical accumulation, particularly for vegetables produced in controlled environments. With the development of light-emitting diode (LED) technology, the regulation of light environments has become increasingly feasible for the provision of ideal light quality, intensity and photoperiod for protected facilities. In this review, the effects of light quality regulation on phytochemical accumulation in vegetables produced in controlled environments are identified, highlighting the research progress and advantages of LED technology as a light environment regulation tool for modifying phytochemical accumulation in vegetables. © 2014 Society of Chemical Industry.

Nutrient digestibility of vegetables waste flour on male quail (Coturnix coturnix japonica)

NASA Astrophysics Data System (ADS)

Pramono, A.; Primadhani, M. S.; Swastike, W.; Sutrisno, J.

2018-03-01

The aim of this research is to determine the nutrient digestibility of vegetables waste flour on of male quail. Four hundred male quails were divided into four groups with five replications. The experiment is Completely Randomized Design and the data were analyzed by analyses of variants. The experimental diets were P0 = basal diet, P1 = 97% basal diet + 3% vegetables waste flour, P2 = 94% basal diet + 6% vegetables waste flour, and P3 = 91% basal diet + 9% vegetables waste flour. The observed variables were the digestibility of dry matter, crude protein and extract ether. Result showed that of the addition of vegetable waste flour in the diet had no effect on crude protein digestibility (P>0.05), however shown significant effect on dry matter (P <0.01) and extract ether (P <0.01) digestibility.

Effects of Solar Geoengineering on Vegetation: Implications for Biodiversity and Conservation

NASA Astrophysics Data System (ADS)

Dagon, K.; Schrag, D. P.

2017-12-01

Climate change will have significant impacts on vegetation and biodiversity. Solar geoengineering has potential to reduce the climate effects of greenhouse gas emissions through albedo modification, yet more research is needed to better understand how these techniques might impact terrestrial ecosystems. Here we utilize the fully coupled version of the Community Earth System Model to run transient solar geoengineering simulations designed to stabilize radiative forcing starting mid-century, relative to the Representative Concentration Pathway 6 (RCP6) scenario. Using results from 100-year simulations, we analyze model output through the lens of ecosystem-relevant metrics. We find that solar geoengineering improves the conservation outlook under climate change, but there are still potential impacts on biodiversity. Two commonly used climate classification systems show shifts in vegetation under solar geoengineering relative to RCP6, though we acknowledge the associated uncertainties with these systems. We also show that rates of warming and the climate velocity are minimized globally under solar geoengineering by the end of the century, while trends persist over land in the Northern Hemisphere. Shifts in the amplitude of temperature and precipitation seasonal cycles are observed in the results, and have implications for vegetation phenology. Different metrics for vegetation productivity also show decreases under solar geoengineering relative to RCP6, but could be related to the model parameterization of nutrient cycling. Vegetation water cycling is found to be an important mechanism for understanding changes in ecosystems under solar geoengineering.

Understory vegetation response to mechanical mastication and other fuels treatments in a ponderosa pine forest

Treesearch

Jeffrey M. Kane; J. Morgan Varner; Eric E. Knapp

2010-01-01

Questions: What influence does mechanical mastication and other fuel treatments have on: (1) canopy and forest floor response variables that influence understory plant development; (2) initial understory vegetation cover, diversity, and composition; and (3) shrub and non-native species density in a secondgrowth ponderosa pine forest....

Variable responses to CO2 of the duration of vegetative growth within maturity group IV soybeans

USDA-ARS?s Scientific Manuscript database

Prior experiments in indoor chambers and in the field using free-air carbon dioxide enrichment (FACE) systems indicated variation among soybean cultivars in whether and how much elevated CO2 prolonged vegetative development. However, the cultivars tested differed in maturity group, and it is not kn...

Depressional wetland vegetation types: a question of plant commmunity development

Treesearch

Katherine L. Kirkman; Charles P. Goebel; Larry West; Mark B. Drew; Brian Palik

2000-01-01

When wetland restoration includes re-establishing native plant taxa as an objective, an understanding of the variables driving the development of plant communities is necessary. With this in mind, we examined soil and physiographic characteristics of depressional wetlands of three vegetation types (cypressgum swamps, cypress savannas, and grass-sedge marshes) located...

Understanding the behavioral linkages needed for designing effective interventions to increase fruit and vegetable intake in diverse populations

USDA-ARS?s Scientific Manuscript database

The design of interventions to increase fruit and vegetable consumption in a population (e.g. all men, all elementary school students) requires an underlying model that organizes the relevant literatures and provides an audience. The mediating-moderating variable model is a statistical analysis tech...

Management considerations to enhance use of stock ponds by waterfowl broods

Treesearch

Mark A. Rumble; Lester D. Flake

1983-01-01

Use of 36 livestock watering ponds by mallard (Anas playtrhynchos), blue-winged teal (A. discors), and total broods was tested against 32 habitat variables from 1977 and 1978. Pond size, shallow water areas with submersed vegetation, number of natural wetlands in a 1.6-km radius, and emersed vegetation composed of smartweed (

VARIABILITY IN SOILS AND VEGETATION ASSOCIATED WITH HARVESTER ANT (POGONOMYRMEX RUGOSUS) NESTS ON A CHIHUAHUAN DESERT WATERSHED

EPA Science Inventory

The effects of harvester ant (Pogonomyrmex rugosus) nests on the density and cover of spring annual plants and on soil characteristics were measured at three locations characterized by different soils and dominant vegetation on a desert watershed. There were few differences in ve...

[The contribution of L.G. Ramensky theoretical legacy to modern vegetation science (to the 130 anniversary of the scientist's birth)].

PubMed

Mirkin, B M; Naumova, L G

2015-01-01

L.G. Ramensky (1884-1953) was an outstanding Soviet geobotanist of the first part of XX century. Considered is his theoretical legacy and its contribution to modern vegetation science. L.G. Ramensky formulated the principle of vegetation continuum based on which the modern paradigm of vegetation science has been put into shape. The scientist made a contribution to the development of such important theoretical conceptions as types of plant strategy, coenosis and coenobiosis (coexistence of species), patterns of interannual variability in plant communities, ecological successions. The unique ecological scales were established by L.G. Ramensky that characterize the distribution of 1400 species over the gradients of soil moistening, richness, and salinization as well as moistening variability, pastoral digression, and alluvial intensity. He came out against mechanistic notions by V.N. Sukachev on a biogeocoenosis structure. The scientist did not offer his own method of plant communities classification but his well-reasoned criticism of dominant classification played a great role in adoption of floristical classification principles (Braun-Blanquet approach) by phytocenology in our country.

Cover of coastal vegetation as an indicator of eutrophication along environmental gradients.

PubMed

Wikström, Sofia A; Carstensen, Jacob; Blomqvist, Mats; Krause-Jensen, Dorte

2016-01-01

Coastal vegetation communities are important for primary production, biodiversity, coastal protection, carbon and nutrient cycling which, in combination with their sensitivity to eutrophication, render them potential indicators of environmental status for environmental policies like the EU Water and Marine Strategy Framework Directives. We evaluated one potential indicator for coastal vegetation, the cumulative cover at depths where the vegetation is light limited, by investigating its response to eutrophication along gradients in natural conditions. We used a large data set covering the Swedish coastline, spanning broad gradients in nutrient level, water clarity, seabed substrate, physical exposure and climate in addition to a salinity gradient from 0.5 to 30.5. Macroalgal cover increased significantly along gradients of declining nutrient concentration and increasing water clarity when we had accounted for diver effects, spatio-temporal sampling variability, salinity gradients, wave exposure and latitude. The developed empirical model explained 79% of the variation in algal cover across 130 areas. Based on this, we identified macroalgal cover as a promising indicator across the Baltic Sea, Kattegat and Skagerrak. A parallel analysis of soft-substrate macrophytes similarly identified significant increases in cover with decreasing concentrations of total nitrogen and increasing salinity, but the resulting empirical model explained only 52% of the variation in cover, probably due to the spatially more variable nature of soft-substrate vegetation. The identified general responses of vegetation cover to gradients of eutrophication across wide ranges in environmental settings may be useful for monitoring and management of marine vegetation in areas with strong environmental gradients.

Women and vulnerability to depression: some personality and clinical factors.

PubMed

Carrillo, Jesús M; Rojo, Nieves; Staats, Arthur W

2004-05-01

The purpose of this study is to explore the role of sex differences and personality in vulnerability to depression. Sex differences in personality and some clinical variables are described. We also assess the value of the variables that revealed significant sex differences as predictors of vulnerability to depression. In a group of adult participants (N = 112), 50% males and 50% females (mean age = 41.30; SD = 15.09; range 17-67), we studied sex differences in the three-factor personality model, using the Eysenck Personality Questionnaire, Form A (EPQ-A; Eysenck & Eysenck, 1975), and in the Five-Factor Personality Model, with the NEO Personality Inventory (NEO-PI; Costa & McCrae, 1985). The following clinical scales were used: the Beck Depression Inventory (BDI; Beck, Rush, Shaw, & Emery, 1979), the Schizotypy Questionnaire (STQ; Claridge & Broks, 1984; Spanish version, Carrillo & Rojo, 1999), the THARL Scales (Dua, 1989, 1990; Spanish version, Dua & Carrillo, 1994) and the Adjustment Inventory (Bell, 1937; Spanish version, Cerdá, 1980). Subsequently, simple linear regression analysis, with BDI scores as criterion, were performed to estimate the value of the variables as predictors of vulnerability to depression. The results indicate that a series of personality variables cause women to be more vulnerable to depression than men and that these variables could be explained by a negative emotion main factor. Results are discussed within the framework of the psychological behaviorism theory of depression.

Vegetation Productivity in Natural vs. Cultivated Systems along Water Availability Gradients in the Dry Subtropics.

PubMed

Baldi, Germán; Texeira, Marcos; Murray, Francisco; Jobbágy, Esteban G

2016-01-01

The dry subtropics are subject to a rapid expansion of crops and pastures over vast areas of natural woodlands and savannas. In this paper, we explored the effect of this transformation on vegetation productivity (magnitude, and seasonal and long-term variability) along aridity gradients which span from semiarid to subhumid conditions, considering exclusively those areas with summer rains (>66%). Vegetation productivity was characterized with the proxy metric "Enhanced Vegetation Index" (EVI) (2000 to 2012 period), on 6186 natural and cultivated sampling points on five continents, and combined with a global climatology database by means of additive models for quantile regressions. Globally and regionally, cultivation amplified the seasonal and inter-annual variability of EVI without affecting its magnitude. Natural and cultivated systems maintained a similar and continuous increase of EVI with increasing water availability, yet achieved through contrasting ways. In natural systems, the productivity peak and the growing season length displayed concurrent steady increases with water availability, while in cultivated systems the productivity peak increased from semiarid to dry-subhumid conditions, and stabilized thereafter giving place to an increase in the growing season length towards wetter conditions. Our results help to understand and predict the ecological impacts of deforestation on vegetation productivity, a key ecosystem process linked to a broad range of services.

Vegetation dynamics at the upper elevational limit of vascular plants in Himalaya.

PubMed

Dolezal, Jiri; Dvorsky, Miroslav; Kopecky, Martin; Liancourt, Pierre; Hiiesalu, Inga; Macek, Martin; Altman, Jan; Chlumska, Zuzana; Rehakova, Klara; Capkova, Katerina; Borovec, Jakub; Mudrak, Ondrej; Wild, Jan; Schweingruber, Fritz

2016-05-04

A rapid warming in Himalayas is predicted to increase plant upper distributional limits, vegetation cover and abundance of species adapted to warmer climate. We explored these predictions in NW Himalayas, by revisiting uppermost plant populations after ten years (2003-2013), detailed monitoring of vegetation changes in permanent plots (2009-2012), and age analysis of plants growing from 5500 to 6150 m. Plant traits and microclimate variables were recorded to explain observed vegetation changes. The elevation limits of several species shifted up to 6150 m, about 150 vertical meters above the limit of continuous plant distribution. The plant age analysis corroborated the hypothesis of warming-driven uphill migration. However, the impact of warming interacts with increasing precipitation and physical disturbance. The extreme summer snowfall event in 2010 is likely responsible for substantial decrease in plant cover in both alpine and subnival vegetation and compositional shift towards species preferring wetter habitats. Simultaneous increase in summer temperature and precipitation caused rapid snow melt and, coupled with frequent night frosts, generated multiple freeze-thaw cycles detrimental to subnival plants. Our results suggest that plant species responses to ongoing climate change will not be unidirectional upward range shifts but rather multi-dimensional, species-specific and spatially variable.

Effects of grazing on spatiotemporal variations in community structure and ecosystem function on the grasslands of Inner Mongolia, China.

PubMed

Su, Rina; Cheng, Junhui; Chen, Dima; Bai, Yongfei; Jin, Hua; Chao, Lumengqiqige; Wang, Zhijun; Li, Junqing

2017-02-28

Grasslands worldwide are suffering from overgrazing, which greatly alters plant community structure and ecosystem functioning. However, the general effects of grazing on community structure and ecosystem function at spatial and temporal scales has rarely been examined synchronously in the same grassland. Here, during 2011-2013, we investigated community structure (cover, height, and species richness) and aboveground biomass (AGB) using 250 paired field sites (grazed vs. fenced) across three vegetation types (meadow, typical, and desert steppes) on the Inner Mongolian Plateau. Grazing, vegetation type, and year all had significant effects on cover, height, species richness, and AGB, although the primary factor influencing variations in these variables was vegetation type. Spatially, grazing significantly reduced the measured variables in meadow and typical steppes, whereas no changes were observed in desert steppe. Temporally, both linear and quadratic relationships were detected between growing season precipitation and cover, height, richness, or AGB, although specific relationships varied among observation years and grazing treatments. In each vegetation type, the observed community properties were significantly correlated with each other, and the shape of the relationship was unaffected by grazing treatment. These findings indicate that vegetation type is the most important factor to be considered in grazing management for this semi-arid grassland.