Science.gov

Sample records for assembling spatially explicit

  1. Spatially explicit modelling of cholera epidemics

    NASA Astrophysics Data System (ADS)

    Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.

    2013-12-01

    Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.

  2. Spatially explicit methane inventory for Switzerland

    NASA Astrophysics Data System (ADS)

    Hiller, Rebecca; Bretscher, Daniel; DelSontro, Tonya; Eugster, Werner; Henne, Stephan; Henneberger, Ruth; Künzle, Thomas; Merbold, Lutz; Neininger, Bruno; Schellenberger, Andreas; Schroth, Martin; Buchmann, Nina; Brunner1, Dominik

    2013-04-01

    Spatially explicit greenhouse gas inventories are gaining in importance as a tool for policy makers to plan and control mitigation measures, and are a required input for atmospheric models used to relate atmospheric concentration measurements with upstream sources. In order to represent the high spatial heterogeneity in Switzerland, we compiled the national methane inventory into a 500 m x 500 m cadaster. In addition to the anthropogenic emissions reported to the United Nation Framework Convention on Climate Change (UNFCCC), we also included natural and semi-natural methane fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as forest uptake. Methane emissions were disaggregated according to geostatistical information about source location and extent. In Switzerland, highest methane emissions originate from the agricultural sector (152 Gg CH4 yr-1), followed by emissions from waste management (16 Gg CH4 yr-1) with highest contributions from landfills, and the energy sector (13 Gg CH4 yr-1) with highest contributions from the distribution of natural gas. Natural and semi-natural emissions only add a small amount (< 5%) to the total Swiss emissions. For validation, the bottom-up inventory was evaluated against methane concentrations measured from a small research aircraft (METAIR-DIMO) above the Swiss Plateau on 18 different days from May 2009 to August 2010 over. Source sensitivities of the air measured were determined by backward runs of the Lagrangian particle dispersion model FLEXPART-COSMO. Source sensitivities were multiplied with the methane inventory to derive simulated methane concentration time series. While the pattern of the variations can be reproduced well for some flight days (correlation coefficient up to 0.75), the amplitude of the variations for the simulated time series is underestimated by at least 20% suggesting an underestimation of CH4 emissions by the inventory, which is also concluded from inverse estimation

  3. Explicit cosmological coarse graining via spatial averaging

    NASA Astrophysics Data System (ADS)

    Paranjape, Aseem; Singh, T. P.

    2008-01-01

    The present matter density of the Universe, while highly inhomogeneous on small scales, displays approximate homogeneity on large scales. We propose that whereas it is justified to use the Friedmann Lemaître Robertson Walker (FLRW) line element (which describes an exactly homogeneous and isotropic universe) as a template to construct luminosity distances in order to compare observations with theory, the evolution of the scale factor in such a construction must be governed not by the standard Einstein equations for the FLRW metric, but by the modified Friedmann equations derived by Buchert (Gen Relat Gravit 32:105, 2000; 33:1381, 2001) in the context of spatial averaging in Cosmology. Furthermore, we argue that this scale factor, defined in the spatially averaged cosmology, will correspond to the effective FLRW metric provided the size of the averaging domain coincides with the scale at which cosmological homogeneity arises. This allows us, in principle, to compare predictions of a spatially averaged cosmology with observations, in the standard manner, for instance by computing the luminosity distance versus red-shift relation. The predictions of the spatially averaged cosmology would in general differ from standard FLRW cosmology, because the scale-factor now obeys the modified FLRW equations. This could help determine, by comparing with observations, whether or not cosmological inhomogeneities are an alternative explanation for the observed cosmic acceleration.

  4. Modeling aqueous solvation with semi-explicit assembly

    PubMed Central

    Fennell, Christopher J.; Kehoe, Charles W.; Dill, Ken A.

    2011-01-01

    We describe a computational solvation model called semi-explicit assembly (SEA). SEA water captures much of the physics of explicit-solvent models but with computational speeds approaching those of implicit-solvent models. We use an explicit-water model to precompute properties of water solvation shells around simple spheres, then assemble a solute’s solvation shell by combining the shells of these spheres. SEA improves upon implicit-solvent models of solvation free energies by accounting for local solute curvature, accounting for near-neighbor nonadditivities, and treating water’s dipole as being asymmetrical with respect to positive or negative solute charges. SEA does not involve parameter fitting, because parameters come from the given underlying explicit-solvation model. SEA is about as accurate as explicit simulations as shown by comparisons against four different homologous alkyl series, a set of 504 varied solutes, solutes taken retrospectively from two solvation-prediction events, and a hypothetical polar-solute series, and SEA is about 100-fold faster than Poisson–Boltzmann calculations. PMID:21300905

  5. Spatially explicit spectral analysis of point clouds and geospatial data

    NASA Astrophysics Data System (ADS)

    Buscombe, Daniel

    2016-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described

  6. Spatially explicit spectral analysis of point clouds and geospatial data

    USGS Publications Warehouse

    Buscombe, Daniel D.

    2015-01-01

    The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is

  7. Integrating remote sensing and spatially explicit epidemiological modeling

    NASA Astrophysics Data System (ADS)

    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

    2015-04-01

    Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

  8. Spatial and temporal heterogeneity explain disease dynamics in a spatially explicit network model.

    PubMed

    Brooks, Christopher P; Antonovics, Janis; Keitt, Timothy H

    2008-08-01

    There is an increasing recognition that individual-level spatial and temporal heterogeneity may play an important role in metapopulation dynamics and persistence. In particular, the patterns of contact within and between aggregates (e.g., demes) at different spatial and temporal scales may reveal important mechanisms governing metapopulation dynamics. Using 7 years of data on the interaction between the anther smut fungus (Microbotryum violaceum) and fire pink (Silene virginica), we show how the application of spatially explicit and implicit network models can be used to make accurate predictions of infection dynamics in spatially structured populations. Explicit consideration of both spatial and temporal organization reveals the role of each in spreading risk for both the host and the pathogen. This work suggests that the application of spatially explicit network models can yield important insights into how heterogeneous structure can promote the persistence of species in natural landscapes. PMID:18662121

  9. Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

    NASA Astrophysics Data System (ADS)

    Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

    2014-05-01

    Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.

  10. Compensatory heterogeneity in spatially explicit capture-recapture data.

    PubMed

    Efford, M G; Mowat, G

    2014-05-01

    Spatially explicit capture-recapture methods, used widely to estimate the abundance of large carnivores, allow for movement within home ranges during sampling. Probability of detection is a decreasing function of distance from the home range center, with one parameter for magnitude and another for spatial scale. Sex-based and other differences in home range size potentially cause heterogeneity in individual detection and bias in estimates of density. The two parameters of detection have hitherto been treated as independent, but we suggest that an inverse relation is expected when detection probability depends on time spent near the detector. Variation in the spatial scale of detection is then compensated by reciprocal variation in the magnitude parameter. We define a net measure of detection ("single-detector sampling area," a(0)), and show by simulation that its coefficient of variation (CV) is a better predictor of bias than the CV of either component or the sum of their squared CVs. In an example using the grizzly bear Ursus arctos, the estimated sex variation in a(0) was small despite large variation in each component. From the simulations, the relative bias of density estimates was generally negligible (< 5%) when CV(a(0)) < 30%. Parameterization of the detection model in terms of a(0) and spatial scale can be more parsimonious and significantly aids the biological interpretation of detection parameters. PMID:25000765

  11. SEARCH: Spatially Explicit Animal Response to Composition of Habitat

    PubMed Central

    Pauli, Benjamin P.; McCann, Nicholas P.; Zollner, Patrick A.; Cummings, Robert; Gilbert, Jonathan H.; Gustafson, Eric J.

    2013-01-01

    Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of

  12. SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

    PubMed

    Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

    2013-01-01

    Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of

  13. Spatially explicit shallow landslide susceptibility mapping over large areas

    USGS Publications Warehouse

    Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

  14. Global spatially explicit CO2 emission metrics for forest bioenergy

    NASA Astrophysics Data System (ADS)

    Cherubini, Francesco; Huijbregts, Mark; Kindermann, Georg; van Zelm, Rosalie; van der Velde, Marijn; Stadler, Konstantin; Strømman, Anders Hammer

    2016-02-01

    Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.). Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2-1 (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2-1 for GTP, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1 for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales.

  15. Spatially-explicit hydrologic controls on benthic invertebrate habitat suitability

    NASA Astrophysics Data System (ADS)

    Ceola, Serena; Bertuzzo, Enrico; Singer, Gabriel; Battin, Tom; Montanari, Alberto; Rinaldo, Andrea

    2014-05-01

    Streamflow variability is a major determinant of basin-scale distribution of benthic invertebrates. Here we present a probabilistic approach for a spatially explicit quantitative assessment of benthic invertebrate abundance as derived from near-bed flow variability throughout an entire stream network. We consider aquatic invertebrates as these are widely employed as sensitive indicators of fluvial ecosystem health and human-induced perturbations. Moving from the analytical characterization of site-specific probability distribution functions of streamflow and bottom shear stress, we achieve a spatial extension to a stream network ranging up to 5th order. Bottom shear stress distributions, coupled with habitat suitability curves derived from field studies, are then used to produce maps of invertebrate habitat suitability based on shear stress conditions. The proposed framework allows to inspect the possible impacts of human-induced perturbations of streamflow variability on river ecology. We apply our approach to an Austrian river network, for which rainfall and streamflow time series, river network hydraulic properties and local information on invertebrate abundance for a limited number of sites are available. This allows a comparison between observed species density versus modeled habitat suitability based on shear stress. Although the proposed strategy neglects ecological determinants other than hydraulic ones and thus represents an ecological minimal model, it allows derivation of important implications of water resource management and fluvial ecosystem protection for basin-scale distribution patterns of organisms.

  16. Spatially-explicit models of global tree density

    PubMed Central

    Glick, Henry B.; Bettigole, Charlie; Maynard, Daniel S.; Covey, Kristofer R.; Smith, Jeffrey R.; Crowther, Thomas W.

    2016-01-01

    Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services. PMID:27529613

  17. Spatially-explicit models of global tree density.

    PubMed

    Glick, Henry B; Bettigole, Charlie; Maynard, Daniel S; Covey, Kristofer R; Smith, Jeffrey R; Crowther, Thomas W

    2016-01-01

    Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services. PMID:27529613

  18. Spatial working memory interferes with explicit, but not probabilistic cuing of spatial attention.

    PubMed

    Won, Bo-Yeong; Jiang, Yuhong V

    2015-05-01

    Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal that working memory is attention directed toward internal representations. Here, we show that the close relationship between these 2 constructs is limited to some but not all forms of spatial attention. In 5 experiments, participants held color arrays, dot locations, or a sequence of dots in working memory. During the memory retention interval, they performed a T-among-L visual search task. Crucially, the probable target location was cued either implicitly through location probability learning or explicitly with a central arrow or verbal instruction. Our results showed that whereas imposing a visual working memory load diminished the effectiveness of explicit cuing, it did not interfere with probability cuing. We conclude that spatial working memory shares similar mechanisms with explicit, goal-driven attention but is dissociated from implicitly learned attention. PMID:25401460

  19. Global spatially explicit CO2 emission metrics for forest bioenergy.

    PubMed

    Cherubini, Francesco; Huijbregts, Mark; Kindermann, Georg; Van Zelm, Rosalie; Van Der Velde, Marijn; Stadler, Konstantin; Strømman, Anders Hammer

    2016-01-01

    Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.). Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2(-1) (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2(-1) for GTP, and 2.14·10(-14) ± 0.11·10(-14) °C (kg yr(-1))(-1) for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales. PMID:26830755

  20. Global spatially explicit CO2 emission metrics for forest bioenergy

    PubMed Central

    Cherubini, Francesco; Huijbregts, Mark; Kindermann, Georg; Van Zelm, Rosalie; Van Der Velde, Marijn; Stadler, Konstantin; Strømman, Anders Hammer

    2016-01-01

    Emission metrics aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.). Examples include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Despite the importance of biomass as a primary energy supplier in existing and future scenarios, emission metrics for CO2 from forest bioenergy are only available on a case-specific basis. Here, we produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy and illustrate their applications to global emissions in 2015 and until 2100 under the RCP8.5 scenario. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2−1 (mean ± standard deviation) for GWP, 0.05 ± 0.05 kgCO2-eq. kgCO2−1 for GTP, and 2.14·10−14 ± 0.11·10−14 °C (kg yr−1)−1 for aSET. We explore metric dependencies on temperature, precipitation, biomass turnover times and extraction rates of forest residues. We find relatively high emission metrics with low precipitation, long rotation times and low residue extraction rates. Our results provide a basis for assessing CO2 emissions from forest bioenergy under different indicators and across various spatial and temporal scales. PMID:26830755

  1. Spatially-Explicit Holocene Drought Reconstructions in Amazonian Forests

    NASA Astrophysics Data System (ADS)

    McMichael, C.; Bush, M. B.

    2014-12-01

    Climate models predict increasing drought in Amazonian forests over the next century, and the synergy of drought and fire may lead to forest dieback. El Niño Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO) are two primary drivers of Amazonian drought, and each process has a spatially distinct manifestation in the Basin. Paleoecological reconstructions can contextualize the forest response to past drought periods. Stalagmite and lake sediment records have documented that the early- to mid-Holocene, i.e. 10,000 - 5000 calibrated years before present (cal yr BP), was among the driest periods of the last 100,000 years in western Amazonia. Climatic conditions became wetter and more similar to the modern climate over the last 4000 cal yr BP, and fires rarely occurred in the absence of human activity. Yet there are currently no drought and fire reconstructions that examine the spatially explicit patterns of drought during the Holocene. Here, we present regional drought histories from southwestern and northeastern sections Amazonia for the last 10,000 years that document the drought-fire dynamics resulting from both climatic processes. Our reconstructions were based on a compilation of dated soil charcoal fragments (N= 291) collected from within Amazonia sensu stricto, which were analyzed by region using summed probability analysis. The compiled soil charcoal dates contained limited evidence of fire over the last 10,000 years in some regions. Fire frequency rose markedly across the Basin, however, during the last 2000 years, indicating an increased human presence. Fire probabilities, and thus droughts, had similar increasing trajectories between southwestern and northeastern Amazonia from 1500-1100 cal yr BP, which decoupled from 1100-740 cal yr BP, and then regained synchronicity from 740-500 cal yr BP. Fire probability declined markedly after 500 yr cal BP, coincident with European arrival to the Americas. Native populations were decimated

  2. Spatially-explicit representation of state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The broad-scale assessment of natural resource conditions (e.g., rangeland health, restoration needs) requires knowledge of their spatial distribution. We argue that creating a database that links state-and-transition models (STMs) to spatial units is a valuable management tool for structuring groun...

  3. Spatially explicit analyses of gastropod biodiversity in ancient Lake Ohrid

    NASA Astrophysics Data System (ADS)

    Hauffe, T.; Albrecht, C.; Schreiber, K.; Birkhofer, K.; Trajanovski, S.; Wilke, T.

    2010-07-01

    Spatial heterogeneity of biodiversity arises from evolutionary processes, constraints of environmental factors and the interaction of communities. The quality of such spatial analyses of biodiversity is improved by (i) utilizing study areas with well defined physiogeographical boundaries, (ii) limiting the impact of widespread species, and (iii) using taxa with heterogeneous distributions. These conditions are typically met by ecosystems such as oceanic islands or ancient lakes and their biota. While research on ancient lakes has contributed significantly to our understanding of evolutionary processes, statistically sound studies of spatial variation of extant biodiversity have been hampered by the frequently vast size of ancient lakes, their limited accessibility, and the lack of infrastructure around them. The small European ancient Lake Ohrid provides a rare opportunity for such a reliable spatial study. The comprehensive horizontal and vertical sampling of a species-rich taxon, the Gastropoda, presented here, revealed interesting patterns of biodiversity, which, in part, have not been shown before for other ancient lakes. In a total of 224 locations throughout the Ohrid Basin, representatives of 68 gastropod species with 50 of them being endemic (=73.5%) could be reported. The spatial distribution of these species shows the following characteristics: (i) within Lake Ohrid, the most frequent species are endemic taxa with a wide depth range, (ii) widespread species (i.e. those occurring throughout the Balkans or beyond) are rare and mainly occur in the upper layer of the lake, (iii) while the total number of species decreases with water depth, the share of endemics increases, (iv) the deeper layers of Lake Ohrid appear to have a higher spatial homogeneity of biodiversity and related environmental factors, (v) biotic interaction due to possible spillover effects may contribute to the establishment of hotspots, and (vi) eco-insularity within the Ohrid Basin occurs

  4. Spatially explicit analysis of gastropod biodiversity in ancient Lake Ohrid

    NASA Astrophysics Data System (ADS)

    Hauffe, T.; Albrecht, C.; Schreiber, K.; Birkhofer, K.; Trajanovski, S.; Wilke, T.

    2011-01-01

    The quality of spatial analyses of biodiversity is improved by (i) utilizing study areas with well defined physiogeographical boundaries, (ii) limiting the impact of widespread species, and (iii) using taxa with heterogeneous distributions. These conditions are typically met by ecosystems such as oceanic islands or ancient lakes and their biota. While research on ancient lakes has contributed significantly to our understanding of evolutionary processes, statistically sound studies of spatial variation of extant biodiversity have been hampered by the frequently vast size of ancient lakes, their limited accessibility, and the lack of scientific infrastructure. The European ancient Lake Ohrid provides a rare opportunity for such a reliable spatial study. The comprehensive horizontal and vertical sampling of a species-rich taxon, the Gastropoda, presented here, revealed interesting patterns of biodiversity, which, in part, have not been shown before for other ancient lakes. In a total of 284 samples from 224 different locations throughout the Ohrid Basin, 68 gastropod species, with 50 of them (= 73.5%) being endemic, could be reported. The spatial distribution of these species shows the following characteristics: (i) within Lake Ohrid, the most frequent species are endemic taxa with a wide depth range, (ii) widespread species (i.e. those occurring throughout the Balkans or beyond) are rare and mainly occur in the upper layer of the lake, (iii) while the total number of species decreases with water depth, the proportion of endemics increases, and (iv) the deeper layers of Lake Ohrid appear to have a higher spatial homogeneity of biodiversity. Moreover, gastropod communities of Lake Ohrid and its feeder springs are both distinct from each other and from the surrounding waters. The analysis also shows that community similarity of Lake Ohrid is mainly driven by niche processes (e.g. environmental factors), but also by neutral processes (e.g. dispersal limitation and

  5. Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher

    USGS Publications Warehouse

    Bakian, Amanda V.; Sullivan, Kimberly A.; Paxton, Eben H.

    2012-01-01

    Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus, using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers (n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.

  6. A spatially explicit estimate of avoided forest loss.

    PubMed

    Honey-Rosés, Jordi; Baylis, Kathy; Ramírez, M Isabel

    2011-10-01

    With the potential expansion of forest conservation programs spurred by climate-change agreements, there is a need to measure the extent to which such programs achieve their intended results. Conventional methods for evaluating conservation impact tend to be biased because they do not compare like areas or account for spatial relations. We assessed the effect of a conservation initiative that combined designation of protected areas with payments for environmental services to conserve over wintering habitat for the monarch butterfly (Danaus plexippus) in Mexico. To do so, we used a spatial-matching estimator that matches covariates among polygons and their neighbors. We measured avoided forest loss (avoided disturbance and deforestation) by comparing forest cover on protected and unprotected lands that were similar in terms of accessibility, governance, and forest type. Whereas conventional estimates of avoided forest loss suggest that conservation initiatives did not protect forest cover, we found evidence that the conservation measures are preserving forest cover. We found that the conservation measures protected between 200 ha and 710 ha (3-16%) of forest that is high-quality habitat for monarch butterflies, but had a smaller effect on total forest cover, preserving between 0 ha and 200 ha (0-2.5%) of forest with canopy cover >70%. We suggest that future estimates of avoided forest loss be analyzed spatially to account for how forest loss occurs across the landscape. Given the forthcoming demand from donors and carbon financiers for estimates of avoided forest loss, we anticipate our methods and results will contribute to future studies that estimate the outcome of conservation efforts. PMID:21902720

  7. Landscape equivalency analysis: methodology for estimating spatially explicit biodiversity credits.

    PubMed

    Bruggeman, Douglas J; Jones, Michael L; Lupi, Frank; Scribner, Kim T

    2005-10-01

    We propose a biodiversity credit system for trading endangered species habitat designed to minimize and reverse the negative effects of habitat loss and fragmentation, the leading cause of species endangerment in the United States. Given the increasing demand for land, approaches that explicitly balance economic goals against conservation goals are required. The Endangered Species Act balances these conflicts based on the cost to replace habitat. Conservation banking is a means to manage this balance, and we argue for its use to mitigate the effects of habitat fragmentation. Mitigating the effects of land development on biodiversity requires decisions that recognize regional ecological effects resulting from local economic decisions. We propose Landscape Equivalency Analysis (LEA), a landscape-scale approach similar to HEA, as an accounting system to calculate conservation banking credits so that habitat trades do not exacerbate regional ecological effects of local decisions. Credits purchased by public agencies or NGOs for purposes other than mitigating a take create a net investment in natural capital leading to habitat defragmentation. Credits calculated by LEA use metapopulation genetic theory to estimate sustainability criteria against which all trades are judged. The approach is rooted in well-accepted ecological, evolutionary, and economic theory, which helps compensate for the degree of uncertainty regarding the effects of habitat loss and fragmentation on endangered species. LEA requires application of greater scientific rigor than typically applied to endangered species management on private lands but provides an objective, conceptually sound basis for achieving the often conflicting goals of economic efficiency and long-term ecological sustainability. PMID:16132443

  8. Spatially Explicit Data: Stewardship and Ethical Challenges in Science

    PubMed Central

    Hartter, Joel; Ryan, Sadie J.; MacKenzie, Catrina A.; Parker, John N.; Strasser, Carly A.

    2013-01-01

    Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of data stewardship and data sharing. Formal data management plans represent a new emphasis in research, enabling access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration. PMID:24058292

  9. Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

    USGS Publications Warehouse

    Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

    2012-01-01

    1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

  10. Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

    USGS Publications Warehouse

    Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

    2013-01-01

    Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

  11. Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls

    PubMed Central

    Vander Heyden, Karin M.; van Atteveldt, Nienke M.; Huizinga, Mariette; Jolles, Jelle

    2016-01-01

    Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., “spatial ability is for boys”) in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest—instruction—posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain. PMID:27507956

  12. Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls.

    PubMed

    Vander Heyden, Karin M; van Atteveldt, Nienke M; Huizinga, Mariette; Jolles, Jelle

    2016-01-01

    Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., "spatial ability is for boys") in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest-instruction-posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain. PMID:27507956

  13. Computing solvent-induced forces in the solvation approach called Semi Explicit Assembly

    NASA Astrophysics Data System (ADS)

    Brini, Emiliano; Hummel, Michelle H.; Coutsias, Evangelos A.; Fennell, Christopher J.; Dill, Ken A.

    2014-03-01

    Many biologically relevant processes (e.g. protein folding) are often too big and slow to be simulated by computer methods that model atomically detailed water. Faster physical models of water are needed. We have developed an approach called Semi Explicit Assembly (SEA) [C.J. Fennell, C.W. Kehoe, K.A. Dill, PNAS, 108, 3234 (2011)]. It is physical because it uses pre-simulations of explicit-solvent models, and it is fast because at runtime, we just combine the pre-simulated results in rapid computations. SEA has also now been proven physically accurate in two blind tests called SAMPL. Here, we describe the computation of solvation forces in SEA, so that this solvation procedure can be incorporated into standard molecular dynamics codes. We describe experimental tests.

  14. HexSim - A general purpose framework for spatially-explicit, individual-based modeling

    EPA Science Inventory

    HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

  15. DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

    EPA Science Inventory

    We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

  16. Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

    EPA Science Inventory

    Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

  17. On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

    NASA Astrophysics Data System (ADS)

    Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

    2010-12-01

    A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

  18. Spatial Working Memory Interferes with Explicit, but Not Probabilistic Cuing of Spatial Attention

    ERIC Educational Resources Information Center

    Won, Bo-Yeong; Jiang, Yuhong V.

    2015-01-01

    Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal…

  19. Reenvisioning cross-sectional at-a-station hydraulic geometry as spatially explicit hydraulic topography

    NASA Astrophysics Data System (ADS)

    Gonzalez, R. L.; Pasternack, G. B.

    2015-10-01

    Transect-based hydraulic geometry is well established but depends on a complex set of subjective fieldwork and computational decisions that sometimes go unexplained. As a result, it is ripe for reenvisioning in the light of the emergence of meter-scale, spatially explicit data and algorithmic geospatial analysis. This study developed and evaluated a new spatially explicit method for analyzing discharge-dependent hydraulics coined 'hydraulic topography' that not only increases accuracy but also eliminates several sample- and assumption-based inconsistencies. Using data and hydrodynamic simulations from the regulated, gravel-cobble-bed lower Yuba River in California, power functions were fitted to discharge-dependent average width, depth, and depth-weighted velocity for three spatial scales and then their corresponding exponents and coefficients were compared across scales and against ones computed using traditional approaches. Average hydraulic values from cross sections at the segment scale spanned up to 1.5 orders of magnitude for a given discharge. Transect-determined exponents for reach-scale depth and velocity relations were consistently over- and underestimated, respectively, relative to the hydraulic topography benchmark. Overall, 73% of cross-sectional power regression parameters assessed fell between 10 and 50 absolute percent error with respect to the spatially explicit hydraulic topography baseline. Although traditional transect-based sampling may be viable for certain uses, percent errors of this magnitude could compromise engineering applications in river management and training works.

  20. Heteroskedasticity as a leading indicator of desertification in spatially explicit data.

    PubMed

    Seekell, David A; Dakos, Vasilis

    2015-06-01

    Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale-free patterning. These models simulate shifts from extensive vegetative cover to bare, desert-like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data. PMID:26078855

  1. Heteroskedasticity as a leading indicator of desertification in spatially explicit data

    PubMed Central

    Seekell, David A; Dakos, Vasilis

    2015-01-01

    Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale-free patterning. These models simulate shifts from extensive vegetative cover to bare, desert-like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data. PMID:26078855

  2. ANOSPEX: a stochastic, spatially explicit model for studying Anopheles metapopulation dynamics.

    PubMed

    Oluwagbemi, Olugbenga O; Fornadel, Christen M; Adebiyi, Ezekiel F; Norris, Douglas E; Rasgon, Jason L

    2013-01-01

    Anopheles mosquitoes transmit malaria, a major public health problem among many African countries. One of the most effective methods to control malaria is by controlling the Anopheles mosquito vectors that transmit the parasites. Mathematical models have both predictive and explorative utility to investigate the pros and cons of different malaria control strategies. We have developed a C++ based, stochastic spatially explicit model (ANOSPEX; Ano pheles Spatially-Explicit) to simulate Anopheles metapopulation dynamics. The model is biologically rich, parameterized by field data, and driven by field-collected weather data from Macha, Zambia. To preliminarily validate ANOSPEX, simulation results were compared to field mosquito collection data from Macha; simulated and observed dynamics were similar. The ANOSPEX model will be useful in a predictive and exploratory manner to develop, evaluate and implement traditional and novel strategies to control malaria, and for understanding the environmental forces driving Anopheles population dynamics. PMID:23861847

  3. Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

    NASA Astrophysics Data System (ADS)

    Jones, B.; O’Neill, B. C.

    2016-08-01

    The projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatially explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.

  4. Using a spatially explicit analysis model to evaluate spatial variation of corn yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...

  5. Locally adaptive, spatially explicit projection of US population for 2030 and 2050

    PubMed Central

    McKee, Jacob J.; Rose, Amy N.; Bright, Edward A.; Huynh, Timmy; Bhaduri, Budhendra L.

    2015-01-01

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census’s projection methodology, with the US Census’s official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations. PMID:25605882

  6. Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge.

    PubMed

    Li, Libo; Dill, Ken A; Fennell, Christopher J

    2014-03-01

    Here, we test a method, called semi-explicit assembly (SEA), that computes the solvation free energies of molecules in water in the SAMPL4 blind test challenge. SEA was developed with the intention of being as accurate as explicit-solvent models, but much faster to compute. It is accurate because it uses pre-simulations of simple spheres in explicit solvent to obtain structural and thermodynamic quantities, and it is fast because it parses solute free energies into regionally additive quantities. SAMPL4 provided us the opportunity to make new tests of SEA. Our tests here lead us to the following conclusions: (1) The newest version, called Field-SEA, which gives improved predictions for highly charged ions, is shown here to perform as well as the earlier versions (dipolar and quadrupolar SEA) on this broad blind SAMPL4 test set. (2) We find that both the past and present SEA models give solvation free energies that are as accurate as TIP3P. (3) Using a new approach for force field parameter optimization, we developed improved hydroxyl parameters that ensure consistency with neat-solvent dielectric constants, and found that they led to improved solvation free energies for hydroxyl-containing compounds in SAMPL4. We also learned that these hydroxyl parameters are not just fixing solvent exposed oxygens in a general sense, and therefore do not improve predictions for carbonyl or carboxylic-acid groups. Other such functional groups will need their own independent optimizations for potential improvements. Overall, these tests in SAMPL4 indicate that SEA is an accurate, general and fast new approach to computing solvation free energies. PMID:24474161

  7. Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

    PubMed Central

    2011-01-01

    The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

  8. Spatially Explicit Forest Characteristics of Europe Integrating NFI and Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Moreno, A. L. S.; Neumann, M.; Hasenauer, H.

    2015-12-01

    Seeing the forest through the trees in Europe is easier said than done. European forest data is nationally collected using different methodologies and sampling techniques. This data can be difficult to obtain, and if made available often lacks spatial information and might only be provided in the local language. This makes analyzing forests in Europe difficult. The reporting systems of Food and Agriculture Organization (FAO) and the European Forestry Institute (EFI) permit several acquisition and calculation methodologies which lead to difficulties in comparing country level data. We have collected spatially explicit national forest inventory (NFI) data from 13 countries in Europe and harmonized these datasets. Using this data along with remote sensing data products we have derived spatially explicit forest characteristics maps of Europe on a 0.017o resolution representing the time period 2000-2010. We have created maps for every NFI variable in our dataset including carbon stock, forest age, forest height, volume, basal area, etc. Cross-validating this data shows that this method produces accurate results for most variables while variables pertaining to forest cover type have lower accuracy. This data is in line with data from FAO and EFI in most cases. However, our dataset allows us to identify large incongruities quickly in FAO and EFI data. Our spatially explicit data is also accurate at predicting forest characteristics in areas where we have no NFI data. This data set provides a consistent harmonized view of the state of European forests in a way hitherto not possible, giving researchers the ability to analyze forests spatially across the entire continent. This method can also be useful for those researching areas that have little or no NFI data or areas where data acquisition is difficult or impossible. This data can also quickly give policy makers a greater view of how forest management practices have shaped our current European forests.

  9. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

    PubMed Central

    Broekhuis, Femke; Gopalaswamy, Arjun M.

    2016-01-01

    Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

  10. Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

    PubMed

    Broekhuis, Femke; Gopalaswamy, Arjun M

    2016-01-01

    Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

  11. On Spatially Explicit Models of Epidemic and Endemic Cholera: The Haiti and Lake Kivu Case Studies.

    NASA Astrophysics Data System (ADS)

    Rinaldo, A.; Bertuzzo, E.; Mari, L.; Finger, F.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.

    2014-12-01

    The first part of the Lecture deals with the predictive ability of mechanistic models for the Haitian cholera epidemic. Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. A formal model comparison framework provides a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels. Intensive computations and objective model comparisons show that parsimonious spatially explicit models accounting for spatial connections have superior explanatory power than spatially disconnected ones for short-to intermediate calibration windows. In general, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. The second part deals with approaches suitable to describe patterns of endemic cholera. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of lake Kivu. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multi-year dataset of reported cholera cases. Fourteen models, accounting for different environmental drivers, are selected in calibration. Among these, the one accounting for seasonality, El Nino Southern Oscillation, precipitation and human mobility outperforms the others in cross-validation.

  12. A Hybrid Wetland Map for China: A Synergistic Approach Using Census and Spatially Explicit Datasets

    PubMed Central

    Ma, Kun; You, Liangzhi; Liu, Junguo; Zhang, Mingxiang

    2012-01-01

    Wetlands play important ecological, economic, and cultural roles in societies around the world. However, wetland degradation has become a serious ecological issue, raising the global sustainability concern. An accurate wetland map is essential for wetland management. Here we used a fuzzy method to create a hybrid wetland map for China through the combination of five existing wetlands datasets, including four spatially explicit wetland distribution data and one wetland census. Our results show the total wetland area is 384,864 km2, 4.08% of China’s national surface area. The hybrid wetland map also shows spatial distribution of wetlands with a spatial resolution of 1 km. The reliability of the map is demonstrated by comparing it with spatially explicit datasets on lakes and reservoirs. The hybrid wetland map is by far the first wetland mapping that is consistent with the statistical data at the national and provincial levels in China. It provides a benchmark map for research on wetland protection and management. The method presented here is applicable for not only wetland mapping but also for other thematic mapping in China and beyond. PMID:23110105

  13. Explicit spatial scattering for load balancing in conservatively synchronized parallel discrete-event simulations

    SciTech Connect

    Thulasidasan, Sunil; Kasiviswanathan, Shiva; Eidenbenz, Stephan; Romero, Philip

    2010-01-01

    We re-examine the problem of load balancing in conservatively synchronized parallel, discrete-event simulations executed on high-performance computing clusters, focusing on simulations where computational and messaging load tend to be spatially clustered. Such domains are frequently characterized by the presence of geographic 'hot-spots' - regions that generate significantly more simulation events than others. Examples of such domains include simulation of urban regions, transportation networks and networks where interaction between entities is often constrained by physical proximity. Noting that in conservatively synchronized parallel simulations, the speed of execution of the simulation is determined by the slowest (i.e most heavily loaded) simulation process, we study different partitioning strategies in achieving equitable processor-load distribution in domains with spatially clustered load. In particular, we study the effectiveness of partitioning via spatial scattering to achieve optimal load balance. In this partitioning technique, nearby entities are explicitly assigned to different processors, thereby scattering the load across the cluster. This is motivated by two observations, namely, (i) since load is spatially clustered, spatial scattering should, intuitively, spread the load across the compute cluster, and (ii) in parallel simulations, equitable distribution of CPU load is a greater determinant of execution speed than message passing overhead. Through large-scale simulation experiments - both of abstracted and real simulation models - we observe that scatter partitioning, even with its greatly increased messaging overhead, significantly outperforms more conventional spatial partitioning techniques that seek to reduce messaging overhead. Further, even if hot-spots change over the course of the simulation, if the underlying feature of spatial clustering is retained, load continues to be balanced with spatial scattering leading us to the observation that

  14. Fire in the Brazilian Amazon: A Spatially Explicit Model for Policy Impact Analysis

    NASA Technical Reports Server (NTRS)

    Arima, Eugenio Y.; Simmons, Cynthia S.; Walker, Robert T.; Cochrane, Mark A.

    2007-01-01

    This article implements a spatially explicit model to estimate the probability of forest and agricultural fires in the Brazilian Amazon. We innovate by using variables that reflect farmgate prices of beef and soy, and also provide a conceptual model of managed and unmanaged fires in order to simulate the impact of road paving, cattle exports, and conservation area designation on the occurrence of fire. Our analysis shows that fire is positively correlated with the price of beef and soy, and that the creation of new conservation units may offset the negative environmental impacts caused by the increasing number of fire events associated with early stages of frontier development.

  15. Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

    DOE PAGESBeta

    McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; Huynh, Timmy N.; Bhaduri, Budhendra L.

    2015-02-03

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

  16. Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

    SciTech Connect

    McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; Huynh, Timmy N.; Bhaduri, Budhendra L.

    2015-02-03

    Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

  17. Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

    PubMed Central

    Currat, Mathias; Gerbault, Pascale; Di, Da; Nunes, José M.; Sanchez-Mazas, Alicia

    2015-01-01

    SELECTOR is a software package for studying the evolution of multiallelic genes under balancing or positive selection while simulating complex evolutionary scenarios that integrate demographic growth and migration in a spatially explicit population framework. Parameters can be varied both in space and time to account for geographical, environmental, and cultural heterogeneity. SELECTOR can be used within an approximate Bayesian computation estimation framework. We first describe the principles of SELECTOR and validate the algorithms by comparing its outputs for simple models with theoretical expectations. Then, we show how it can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow. We identify situations in which balancing selection reduces genetic differentiation between population groups compared with neutrality and explain conflicting outcomes observed for human leukocyte antigen loci. These results and three previously published applications demonstrate that SELECTOR is efficient and robust for building insight into human settlement history and evolution. PMID:26949332

  18. Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

    EPA Science Inventory

    Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

  19. Spatial-explicit modeling of social vulnerability to malaria in East Africa

    PubMed Central

    2014-01-01

    Background Despite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures. Methods Based on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases (VBDs) in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out. Results Results indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the

  20. Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore Tuna (Thunnus alalunga)

    NASA Astrophysics Data System (ADS)

    Lehodey, P.; Senina, I.; Dragon, A.-C.; Arrizabalaga, H.

    2014-04-01

    The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. Unlike standard stock assessment models, new state-of-the-art ecosystem models require geo-referenced fishing data with highest possible spatial resolution. This study presents an application to the north Atlantic albacore tuna stock with a careful definition and validation of a spatially explicit fishing dataset prepared from publically available sources (ICCAT) for its use in a spatial ecosystem and population dynamics model (SEAPODYM) to provide the first spatially explicit estimate of albacore density in the North Atlantic by life stage. Density distributions are provided (http://doi.pangaea.de/10.1594/PANGAEA.831499) together with the fishing data used for these estimates http://doi.pangaea.de/10.1594/PANGAEA.830797, http://doi.pangaea.de/10.15 1594/PANGAEA.828168, http://doi.pangaea.de/10.1594/PANGAEA.828170, and http://doi.pangaea.de/10.1594/PANGAEA.828171 (see section Source Data References).

  1. Using spatially explicit indicators to investigate watershed characteristics and stream temperature relationships.

    PubMed

    Grabowski, Zbigniew J; Watson, Eric; Chang, Heejun

    2016-05-01

    We generate a series of novel indicators of spatially explicit watershed permeability and runoff characteristics to examine the relationship between land cover and water temperature parameters in a rapidly urbanizing watershed. Our framework provides a readily adaptable method to examine the thermal sensitivity of streams based upon the underlying geomorphological and surface characteristics of drainage basins. Using four model groups each using a different landscape characteristic weighting scheme (Model Group 1: areal averages; Model Group 2: inverse distance by total flow length; Model Group 3: overland distance to stream network and distance squared; Model Group 4: proportional flow accumulation), we examined the predictive capacity of 19 variables, including combinations of simplified land cover, elevation, slope, and flow accumulation, on five stream thermal properties: seven day moving average of daily minimum and maximum, seasonal mean temperature, a novel metric of thermal 'flashiness', and total days with maximum temperature exceeding 17.8°C. We find that the use of spatially explicit landscape indicators combining watershed processes improves the performance of regressions for predicting a number of ecologically relevant stream temperature variables. Improved indicators of watershed condition lend themselves for rapid investigation of the relationship between stream thermal conditions and landscape characteristics in watersheds modified by human land uses, ultimately providing a more hydrologically meaningful indicator for the impacts of landscape change. PMID:26881729

  2. SEHR-ECHO v1.0: a Spatially Explicit Hydrologic Response model for ecohydrologic applications

    NASA Astrophysics Data System (ADS)

    Schaefli, B.; Nicótina, L.; Imfeld, C.; Da Ronco, P.; Bertuzzo, E.; Rinaldo, A.

    2014-11-01

    This paper presents the Spatially Explicit Hydrologic Response (SEHR) model developed at the Laboratory of Ecohydrology of the Ecole Polytechnique Fédérale de Lausanne for the simulation of hydrological processes at the catchment scale. The key concept of the model is the formulation of water transport by geomorphologic travel time distributions through gravity-driven transitions among geomorphic states: the mobilization of water (and possibly dissolved solutes) is simulated at the subcatchment scale and the resulting responses are convolved with the travel paths distribution within the river network to obtain the hydrologic response at the catchment outlet. The model thus breaks down the complexity of the hydrologic response into an explicit geomorphological combination of dominant spatial patterns of precipitation input and of hydrologic process controls. Nonstationarity and nonlinearity effects are tackled through soil moisture dynamics in the active soil layer. We present here the basic model set-up for precipitation-runoff simulation and a detailed discussion of its parameter estimation and of its performance for the Dischma River (Switzerland), a snow-dominated catchment with a small glacier cover.

  3. [Applicability analysis of spatially explicit model of leaf litter in evergreen broad-leaved forests].

    PubMed

    Zhao, Qing-Qing; Liu, He-Ming; Jonard, Mathieu; Wang, Zhang-Hua; Wang, Xi-Hua

    2014-11-01

    The spatially explicit model of leaf litter can help to understand its dispersal process, which is very important to predict the distribution pattern of leaves on the surface of the earth. In this paper, the spatially explicit model of leaf litter was developed for 20 tree species using litter trap data from the mapped forest plot in an evergreen broad-leaved forest in Tiantong, Zhejiang Pro- vince, eastern China. Applicability of the model was analyzed. The model assumed an allometric equation between diameter at breast height (DBH) and leaf litter amount, and the leaf litter declined exponentially with the distance. Model parameters were estimated by the maximum likelihood method. Results showed that the predicted and measured leaf litter amounts were significantly correlated, but the prediction accuracies varied widely for the different tree species, averaging at 49.3% and ranging from 16.0% and 74.0%. Model qualities of tree species significantly correlated with the standard deviations of the leaf litter amount per trap, DBH of the tree species and the average leaf dry mass of tree species. There were several ways to improve the forecast precision of the model, such as installing the litterfall traps according to the distribution of the tree to cover the different classes of the DBH and distance apart from the parent trees, determining the optimal dispersal function of each tree species, and optimizing the existing dispersal function. PMID:25898606

  4. Re-Envisioning Cross Sectional Hydraulic Geometry as Spatially Explicit Hydraulic Topography

    NASA Astrophysics Data System (ADS)

    Gonzalez, R. L.; Pasternack, G. B.

    2014-12-01

    Traditional transect-based methodology for determining hydraulic geometry relationships depends on a complex set of opaque fieldwork and computational decisions that sometimes go unexplained. The fields of river hydraulics and fluvial geomorphology are in the midst of a transformation from considering limited cross-sectional data to using an abundance of spatially explicit data. Hydraulic geometry is one of the classic tools of fluvial geomorphology that is ripe for re-envisioning so it can continue to be useful in the spatially explicit era. This study developed a new method for analyzing discharge-dependent hydraulics coined "hydraulic topography" that not only increases the accuracy of the tool, but also should eliminate several sample- and assumption-based inconsistencies from traditional hydraulic geometry analysis. Hydraulic topography relied on detailed, near-census river surveying and served as the standard by which to assess cross sectional methods. Both hydraulic topography and uniformly spaced cross sectional hydraulic geometry sample approaches were applied to a series of high resolution 2D hydrodynamic simulations of the gravel-cobble bed lower Yuba River- their associated results were analyzed. More specifically, the power functions fit to discharge-dependent average width, depth, and velocity for three spatial scales were visually inspected and their corresponding exponents and coefficients were compared. Average cross sectional hydraulics at the segment scale spanned up to 1.5 orders of magnitude for a given discharge. Transect-determined rates of reach scale depth and velocity increase with changing discharge were consistently over- and underestimated, respectively, relative to the near-census benchmark. Both methods showed that relative to riffles, pools had lower velocities at low discharges but a higher rate of velocity increase with increased flows. Overall, 73 percent of cross sectional power regression parameters assessed fell between 10 and

  5. Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

    USGS Publications Warehouse

    Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

    2010-01-01

    We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

  6. Hydroclimatology of dual-peak annual cholera incidence: Insights from a spatially explicit model

    NASA Astrophysics Data System (ADS)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2012-03-01

    Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g., sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of a model river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of river flows. The model is forced by seasonal environmental drivers, namely river flow, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. Our modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

  7. Ecological and evolutionary consequences of explicit spatial structure in exploiter-victim systems

    NASA Astrophysics Data System (ADS)

    Klopfer, Eric David

    One class of spatial model which has been widely used in ecology has been termed "pseudo-spatial models" and classically employs various types of aggregation in studying the coexistence of competing parasitoids. Yet, little is known about the relative effects of each of these aggregation behaviors. Thus, in Chapter 1 I chose to examine three types of aggregation and explore their relative strengths in promoting coexistence of two competing parasitoids. A striking shortcoming of spatial models in ecology to date is that there is a relative lack of use of spatial models to investigate problems on the evolutionary as opposed to ecological time scale. Consequently, in Chapter 2 I chose to start with a classic problem of evolutionary time scale--the evolution of virulence and predation rates. Debate about this problem has continued through several decades, yet many instances are not adequately explained by current models. In this study I explored the effect of explicit spatial structure on exploitation rates by comparing a cellular automata (CA) exploiter-victim model which incorporates local dynamics to a metapopulation model which does not include such dynamics. One advantage of CA models is that they are defined by simple rules rather than the often complex equations of other types of spatial models. This is an extremely useful attribute when one wants to convey results of models to an audience with an applied bent that is often uncomfortable with hard-to-understand equations. Thus, in Chapter 3, through the use of CA models I show that there are spatial phenomena which alter the impact of introduced predators and that these phenomena are potentially important in the implementation of biocontrol programs. The relatively recent incorporation of spatial models into the ecological literature has left most ecologists and evolutionary biologists without the ability to understand, let alone employ, spatial models in evolutionary problems. In order to give the next

  8. A spatially explicit reconstruction of forest cover in China over 1700-2000

    NASA Astrophysics Data System (ADS)

    He, Fanneng; Li, Shicheng; Zhang, Xuezhen

    2015-08-01

    The spatially explicit reconstruction of historical forest plays an important role in understanding human modifications of land surfaces and its environmental effects. Based on an analysis of the forest change history of China, we devised a reconstruction method for the historical forest cover in China. The core idea of the method is that the lands with high suitability for cultivation will be cultivated and deforested first, spreading to marginal lands with lower suitability for cultivation. By determining the possible maximum distribution extent of the forest, as well as devising the land suitability for cultivation assessment model and provincial forest area allocation model, we created 10 km forest cover maps of China for the years 1700 to 2000 with 10 year intervals. By comparison with satellite-based data in 2000, we found that the grids within 25% differences account for as much as 66.07% of all grids. The comparison with the historical documents-based data in northeast China indicated that the number of counties within 30% relative differences is 99, accounting for 74.44% of all counties. Therefore, the forest area allocation model we devised can accurately reproduce the spatial patterns of historical forest cover in China. Our reconstruction indicates that from 1700 to the 1960s, the deforestation mainly occurred in southwest China, the hilly regions of south China, the southeast of Gansu province, and northeast China; from the 1960s to 2000, the reforestation occurred in most traditional forested regions of China, particularly in the Tibet Plateau, hilly regions of south China and the Greater Khingan Mountains. The spatially explicit forest cover data sets we reconstructed can be used in global or regional climatic models to study the impact of land cover change on climate change.

  9. Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

    NASA Astrophysics Data System (ADS)

    Madani, N.; Kimball, J. S.; Running, S. W.

    2014-12-01

    Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE < 257 g C m-2 yr-1) relative to GPP modeled using biome-specific LUEopt constants (R2 = 34; RMSE = 439 g C m-2 yr-1). We show that general landscape and plant trait information

  10. Explicit off-line criteria for stable accurate time filtering of strongly unstable spatially extended systems.

    PubMed

    Majda, Andrew J; Grote, Marcus J

    2007-01-23

    Many contemporary problems in science involve making predictions based on partial observation of extremely complicated spatially extended systems with many degrees of freedom and physical instabilities on both large and small scales. Various new ensemble filtering strategies have been developed recently for these applications, and new mathematical issues arise. Here, explicit off-line test criteria for stable accurate discrete filtering are developed for use in the above context and mimic the classical stability analysis for finite difference schemes. First, constant coefficient partial differential equations, which are randomly forced and damped to mimic mesh scale energy spectra in the above problems are developed as off-line filtering test problems. Then mathematical analysis is used to show that under natural suitable hypothesis the time filtering algorithms for general finite difference discrete approximations to an sxs partial differential equation system with suitable observations decompose into much simpler independent s-dimensional filtering problems for each spatial wave number separately; in other test problems, such block diagonal models rigorously provide upper and lower bounds on the filtering algorithm. In this fashion, elementary off-line filtering criteria can be developed for complex spatially extended systems. The theory is illustrated for time filters by using both unstable and implicit difference scheme approximations to the stochastically forced heat equation where the combined effects of filter stability and model error are analyzed through the simpler off-line criteria. PMID:17227864

  11. Spatially explicit models for inference about density in unmarked or partially marked populations

    USGS Publications Warehouse

    Chandler, Richard B.; Royle, J. Andrew

    2013-01-01

    Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating

  12. MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

    USGS Publications Warehouse

    Carter, J.; Finn, John T.

    1999-01-01

    We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.

  13. A spatially explicit model of synchronization in fiddler crab waving displays.

    PubMed

    Araujo, Sabrina Borges Lino; Rorato, Ana C; Perez, Daniela M; Pie, Marcio R

    2013-01-01

    Fiddler crabs (Uca spp., Decapoda: Ocypodidae) are commonly found forming large aggregations in intertidal zones, where they perform rhythmic waving displays with their greatly enlarged claws. While performing these displays, fiddler crabs often synchronize their behavior with neighboring males, forming the only known synchronized visual courtship displays involving reflected light and moving body parts. Despite being one of the most conspicuous aspects of fiddler crab behavior, little is known about the mechanisms underlying synchronization of male displays. In this study we develop a spatially explicit model of fiddler crab waving displays using coupled logistic map equations. We explored two alternative models in which males either direct their attention at random angles or preferentially toward neighbors. Our results indicate that synchronization is possible over a fairly large region of parameter space. Moreover, our model was capable of generating local synchronization neighborhoods, as commonly observed in fiddler crabs under natural conditions. PMID:23483905

  14. A Spatially Explicit Model of Synchronization in Fiddler Crab Waving Displays

    PubMed Central

    Araujo, Sabrina Borges Lino; Rorato, Ana C.; Perez, Daniela M.; Pie, Marcio R.

    2013-01-01

    Fiddler crabs (Uca spp., Decapoda: Ocypodidae) are commonly found forming large aggregations in intertidal zones, where they perform rhythmic waving displays with their greatly enlarged claws. While performing these displays, fiddler crabs often synchronize their behavior with neighboring males, forming the only known synchronized visual courtship displays involving reflected light and moving body parts. Despite being one of the most conspicuous aspects of fiddler crab behavior, little is known about the mechanisms underlying synchronization of male displays. In this study we develop a spatially explicit model of fiddler crab waving displays using coupled logistic map equations. We explored two alternative models in which males either direct their attention at random angles or preferentially toward neighbors. Our results indicate that synchronization is possible over a fairly large region of parameter space. Moreover, our model was capable of generating local synchronization neighborhoods, as commonly observed in fiddler crabs under natural conditions. PMID:23483905

  15. Interactions Between Spatially Explicit Conservation and Management Measures: Implications for the Governance of Marine Protected Areas

    NASA Astrophysics Data System (ADS)

    Cárcamo, P. Francisco; Gaymer, Carlos F.

    2013-12-01

    Marine protected areas are not established in an institutional and governance vacuum and managers should pay attention to the wider social-ecological system in which they are immersed. This article examines Islas Choros-Damas Marine Reserve, a small marine protected area located in a highly productive and biologically diverse coastal marine ecosystem in northern Chile, and the interactions between human, institutional, and ecological dimensions beyond those existing within its boundaries. Through documents analysis, surveys, and interviews, we described marine reserve implementation (governing system) and the social and natural ecosystem-to-be-governed. We analyzed the interactions and the connections between the marine reserve and other spatially explicit conservation and/or management measures existing in the area and influencing management outcomes and governance. A top-down approach with poor stakeholder involvement characterized the implementation process. The marine reserve is highly connected with other spatially explicit measures and with a wider social-ecological system through various ecological processes and socio-economic interactions. Current institutional interactions with positive effects on the management and governance are scarce, although several potential interactions may be developed. For the study area, any management action must recognize interferences from outside conditions and consider some of them (e.g., ecotourism management) as cross-cutting actions for the entire social-ecological system. We consider that institutional interactions and the development of social networks are opportunities to any collective effort aiming to improve governance of Islas Choros-Damas marine reserve. Communication of connections and interactions between marine protected areas and the wider social-ecological system (as described in this study) is proposed as a strategy to improve stakeholder participation in Chilean marine protected areas.

  16. A method for spatially explicit representation of sub-watershed sediment yield, Southern California, USA.

    PubMed

    Booth, Derek B; Leverich, Glen; Downs, Peter W; Dusterhoff, Scott; Araya, Sebastian

    2014-05-01

    We present here a method to integrate geologic, topographic, and land-cover data in a geographic information system to provide a fine-scale, spatially explicit prediction of sediment yield to support management applications. The method is fundamentally qualitative but can be quantified using preexisting sediment-yield data, where available, to verify predictions using other independent data sets. In the 674-km(2) Sespe Creek watershed of southern California, 30 unique "geomorphic landscape units" (GLUs, defined by relatively homogenous areas of geology, hillslope gradient, and land cover) provide a framework for discriminating relative rates of sediment yield across this landscape. Field observations define three broad groupings of GLUs that are well-associated with types, relative magnitudes, and rates of erosion processes. These relative rates were then quantified using sediment-removal data from nearby debris basins, which allow relatively low-precision but robust calculations of both local and whole-watershed sediment yields, based on the key assumption that minimal sediment storage throughout most of the watershed supports near-equivalency of long-term rates of hillslope sediment production and watershed sediment yield. The accuracy of these calculations can be independently assessed using geologically inferred uplift rates and integrated suspended sediment measurements from mainstem Sespe Creek, which indicate watershed-averaged erosion rates between about 0.6-1.0 mm year(-1) and corresponding sediment yields of about 2 × 10(3) t km(-2) year(-1). A spatially explicit representation of sediment production is particularly useful in a region where wildfires, rapid urban development, and the downstream delivery of upstream sediment loads are critical drivers of both geomorphic processes and land-use management. PMID:24567071

  17. Interactions between spatially explicit conservation and management measures: implications for the governance of marine protected areas.

    PubMed

    Cárcamo, P Francisco; Gaymer, Carlos F

    2013-12-01

    Marine protected areas are not established in an institutional and governance vacuum and managers should pay attention to the wider social-ecological system in which they are immersed. This article examines Islas Choros-Damas Marine Reserve, a small marine protected area located in a highly productive and biologically diverse coastal marine ecosystem in northern Chile, and the interactions between human, institutional, and ecological dimensions beyond those existing within its boundaries. Through documents analysis, surveys, and interviews, we described marine reserve implementation (governing system) and the social and natural ecosystem-to-be-governed. We analyzed the interactions and the connections between the marine reserve and other spatially explicit conservation and/or management measures existing in the area and influencing management outcomes and governance. A top-down approach with poor stakeholder involvement characterized the implementation process. The marine reserve is highly connected with other spatially explicit measures and with a wider social-ecological system through various ecological processes and socio-economic interactions. Current institutional interactions with positive effects on the management and governance are scarce, although several potential interactions may be developed. For the study area, any management action must recognize interferences from outside conditions and consider some of them (e.g., ecotourism management) as cross-cutting actions for the entire social-ecological system. We consider that institutional interactions and the development of social networks are opportunities to any collective effort aiming to improve governance of Islas Choros-Damas marine reserve. Communication of connections and interactions between marine protected areas and the wider social-ecological system (as described in this study) is proposed as a strategy to improve stakeholder participation in Chilean marine protected areas. PMID:24091586

  18. Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea.

    PubMed

    Puerta, Patricia; Hunsicker, Mary E; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel

    2015-01-01

    Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable

  19. Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

    NASA Astrophysics Data System (ADS)

    Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

    2011-10-01

    Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

  20. Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea

    PubMed Central

    Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel

    2015-01-01

    Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable

  1. Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

    NASA Astrophysics Data System (ADS)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2012-12-01

    Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g. sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of precipitation and river flows. To single out the single out the hydroclimatologic controls on the prevalence patterns in a non-specific geographical context, we first apply the model to Optimal Channel Networks as a general model of hydrological networks. Moreover, we impose a uniform distribution of population. The model is forced by seasonal environmental drivers, namely precipitation, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. We then proceed applying the model to the specific settings of Bay of Bengal accounting for the actual river networks (derived from digital terrain map manipulations), the proper distribution of population (estimated from downscaling of census data based on remotely sensed features) and precipitation patterns. Overall our

  2. Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

    NASA Astrophysics Data System (ADS)

    Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

    2012-12-01

    Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is

  3. Production of stream habitat gradients by montane watersheds: Hypothesis tests based on spatially explicit path analyses

    USGS Publications Warehouse

    Isaak, D.J.; Hubert, W.A.

    2001-01-01

    We studied how the features of mountain watersheds interact to cause gradients in three stream attributes: baseflow stream widths, total alkalinity, and stream slope. A priori hypotheses were developed before being tested in a series of path analyses using data from 90 stream reaches on 24 second- to fourth-order streams across a fifth-order Rocky Mountain watershed. Because most of the conventional least squares regressions initially calculated for the path analyses had spatially correlated residuals (13 of 15 regressions), spatially explicit regressions were often used to derive more accurate parameter estimates and significance tests. Our final working hypotheses accounted for most of the variation in baseflow stream width (73%), total alkalinity (74%), and stream slope (78%) and provide systemic views of watershed function by depicting interactions that occur between geomorphology, land surface features, and stream attributes. Stream gradients originated mainly from the unidirectional changes in geomorphic features that occur over the lengths of streams. Land surface features were of secondary importance and, because they change less predictably relative to the stream, appear to modify the rate at which stream gradients change.

  4. Exploring behavior of an unusual megaherbivore: A spatially explicit foraging model of the hippopotamus

    USGS Publications Warehouse

    Lewison, R.L.; Carter, J.

    2004-01-01

    Herbivore foraging theories have been developed for and tested on herbivores across a range of sizes. Due to logistical constraints, however, little research has focused on foraging behavior of megaherbivores. Here we present a research approach that explores megaherbivore foraging behavior, and assesses the applicability of foraging theories developed on smaller herbivores to megafauna. With simulation models as reference points for the analysis of empirical data, we investigate foraging strategies of the common hippopotamus (Hippopotamus amphibius). Using a spatially explicit individual based foraging model, we apply traditional herbivore foraging strategies to a model hippopotamus, compare model output, and then relate these results to field data from wild hippopotami. Hippopotami appear to employ foraging strategies that respond to vegetation characteristics, such as vegetation quality, as well as spatial reference information, namely distance to a water source. Model predictions, field observations, and comparisons of the two support that hippopotami generally conform to the central place foraging construct. These analyses point to the applicability of general herbivore foraging concepts to megaherbivores, but also point to important differences between hippopotami and other herbivores. Our synergistic approach of models as reference points for empirical data highlights a useful method of behavioral analysis for hard-to-study megafauna. ?? 2003 Elsevier B.V. All rights reserved.

  5. Graph theory as a proxy for spatially explicit population models in conservation planning.

    PubMed

    Minor, Emily S; Urban, Dean L

    2007-09-01

    Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes. PMID:17913139

  6. Maintaining the Conservation Value of Shifting Cultivation Landscapes Requires Spatially Explicit Interventions

    NASA Astrophysics Data System (ADS)

    Robiglio, Valentina; Sinclair, Fergus

    2011-08-01

    Fallow vegetation within landscapes dominated by shifting cultivation represents a woody species pool of critical importance with considerable potential for biodiversity conservation. Here, through the analysis of factors that influence the early stages of fallow vegetation regrowth in two contrasting forest margin landscapes in Southern Cameroon, we assessed the impact of current trends of land use intensification and expansion of the cultivated areas, upon the conservation potential of shifting cultivation landscapes. We combined the analysis of plot and landscape scale factors and identified a complex set of variables that influence fallow regrowth processes in particular the characteristics of the agricultural matrix and the distance from forest. Overall we observed a decline in the fallow species pool, with composition becoming increasingly dominated by species adapted to recurrent disturbance. It is clear that without intervention and if present intensification trends continue, the potential of fallow vegetation to contribute to biodiversity conservation declines because of a reduced capacity, (1) to recover forest vegetation with anything like its original species composition, (2) to connect less disturbed forest patches for forest dependent organisms. Strategies to combat biodiversity loss, including promotion of agroforestry practices and the increase of old secondary forest cover, will need not only to operate at a landscape scale but also to be spatially explicit, reflecting the spatial pattern of species reservoirs and dispersal strategies and human usage across landscapes.

  7. Anthropogenic and natural methane fluxes in Switzerland synthesized within a spatially-explicit inventory

    NASA Astrophysics Data System (ADS)

    Hiller, R. V.; Bretscher, D.; DelSontro, T.; Diem, T.; Eugster, W.; Henneberger, R.; Hobi, S.; Hodson, E.; Imer, D.; Kreuzer, M.; Künzle, T.; Merbold, L.; Niklaus, P. A.; Rihm, B.; Schellenberger, A.; Schroth, M. H.; Schubert, C. J.; Siegrist, H.; Stieger, J.; Buchmann, N.; Brunner, D.

    2013-09-01

    We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process- or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4 yr-1), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4 yr-1) mainly from landfills and the energy sector (12 Gg CH4 yr-1), which was dominated by emissions from natural gas distribution. Compared to the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH4 yr-1), making up only 3 % of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between -1.5 and 0 Gg CH4 yr-1), while forest soils are a CH4 sink (approx. -2.8 Gg CH4 yr-1), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and a European CH4 inventory (TNO/MACC). This new spatially-explicit emission inventory for Switzerland will provide valuable input for regional scale atmospheric modeling and inverse source estimation.

  8. Anthropogenic and natural methane fluxes in Switzerland synthesized within a spatially explicit inventory

    NASA Astrophysics Data System (ADS)

    Hiller, R. V.; Bretscher, D.; DelSontro, T.; Diem, T.; Eugster, W.; Henneberger, R.; Hobi, S.; Hodson, E.; Imer, D.; Kreuzer, M.; Künzle, T.; Merbold, L.; Niklaus, P. A.; Rihm, B.; Schellenberger, A.; Schroth, M. H.; Schubert, C. J.; Siegrist, H.; Stieger, J.; Buchmann, N.; Brunner, D.

    2014-04-01

    We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates 90 % of the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process- or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4 yr-1), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4 yr-1) mainly from landfills and the energy sector (12 Gg CH4 yr-1), which was dominated by emissions from natural gas distribution. Compared with the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH4 yr-1), making up only 3% of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between -1.5 and 0 Gg CH4 yr-1), while forest soils are a CH4 sink (approx. -2.8 Gg CH4 yr-1), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and an European (TNO/MACC) CH4 inventory. This new spatially explicit emission inventory for Switzerland will provide valuable input for regional-scale atmospheric modeling and inverse source estimation.

  9. Density-dependent home-range size revealed by spatially explicit capture–recapture

    USGS Publications Warehouse

    Efford, M.G.; Dawson, Deanna K.; Jhala, Y.V.; Qureshi, Q.

    2016-01-01

    The size of animal home ranges often varies inversely with population density among populations of a species. This fact has implications for population monitoring using spatially explicit capture–recapture (SECR) models, in which both the scale of home-range movements σ and population density D usually appear as parameters, and both may vary among populations. It will often be appropriate to model a structural relationship between population-specific values of these parameters, rather than to assume independence. We suggest re-parameterizing the SECR model using kp = σp √Dp, where kp relates to the degree of overlap between home ranges and the subscript p distinguishes populations. We observe that kp is often nearly constant for populations spanning a range of densities. This justifies fitting a model in which the separate kp are replaced by the single parameter k and σp is a density-dependent derived parameter. Continuous density-dependent spatial variation in σ may also be modelled, using a scaled non-Euclidean distance between detectors and the locations of animals. We illustrate these methods with data from automatic photography of tigers (Panthera tigris) across India, in which the variation is among populations, from mist-netting of ovenbirds (Seiurus aurocapilla) in Maryland, USA, in which the variation is within a single population over time, and from live-trapping of brushtail possums (Trichosurus vulpecula) in New Zealand, modelling spatial variation within one population. Possible applications and limitations of the methods are discussed. A model in which kp is constant, while density varies, provides a parsimonious null model for SECR. The parameter k of the null model is a concise summary of the empirical relationship between home-range size and density that is useful in comparative studies. We expect deviations from this model, particularly the dependence of kp on covariates, to be biologically interesting.

  10. Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling.

    PubMed

    Schur, Nadine; Hürlimann, Eveline; Stensgaard, Anna-Sofie; Chimfwembe, Kingford; Mushinge, Gabriel; Simoonga, Christopher; Kabatereine, Narcis B; Kristensen, Thomas K; Utzinger, Jürg; Vounatsou, Penelope

    2013-11-01

    Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, but current statistics are outdated due to demographic and ecological transformations and ongoing control efforts. Reliable risk estimates are important to plan and evaluate interventions in a spatially explicit and cost-effective manner. We analysed a large ensemble of georeferenced survey data derived from an open-access neglected tropical diseases database to create smooth empirical prevalence maps for Schistosoma mansoni and Schistosoma haematobium for a total of 13 countries of eastern Africa. Bayesian geostatistical models based on climatic and other environmental data were used to account for potential spatial clustering in spatially structured exposures. Geostatistical variable selection was employed to reduce the set of covariates. Alignment factors were implemented to combine surveys on different age-groups and to acquire separate estimates for individuals aged ≤20 years and entire communities. Prevalence estimates were combined with population statistics to obtain country-specific numbers of Schistosoma infections. We estimate that 122 million individuals in eastern Africa are currently infected with either S. mansoni, or S. haematobium, or both species concurrently. Country-specific population-adjusted prevalence estimates range between 12.9% (Uganda) and 34.5% (Mozambique) for S. mansoni and between 11.9% (Djibouti) and 40.9% (Mozambique) for S. haematobium. Our models revealed that infection risk in Burundi, Eritrea, Ethiopia, Kenya, Rwanda, Somalia and Sudan might be considerably higher than previously reported, while in Mozambique and Tanzania, the risk might be lower than current estimates suggest. Our empirical, large-scale, high-resolution infection risk estimates for S. mansoni and S. haematobium in eastern Africa can guide future control interventions and provide a benchmark for subsequent monitoring and evaluation activities. PMID:22019933

  11. A hydrologically explicit, spatially exact, classification of landforms for Canada at 1:500,000 scale.

    NASA Astrophysics Data System (ADS)

    MacMillan, Robert A.; Geng, Xiaoyuan; Smith, Scott; Zawadzka, Joanna; Hengl, Tom

    2016-04-01

    A new approach for classifying landform types has been developed and applied to all of Canada using a 250 m DEM. The resulting LandMapR classification has been designed to provide a stable and consistent spatial fabric to act as initial proto-polygons to be used in updating the current 1:1 M scale Soil Landscapes of Canada map to 1:500,000 scale. There is a desire to make the current SLC polygon fabric more consistent across the country, more correctly aligned to observable hydrological and landscape features, more spatially exact, more detailed and more interpretable. The approach is essentially a modification of the Hammond (1954) criteria for classifying macro landform types as implemented for computerized analysis by Dikau (1989, 1991) and Brabyn (1998). The major modification is that the key input variables of local relief and relative position in the landscape are computed for specific hillslopes that occur between individual, explicitly defined, channels and divides. While most approaches, including Dikau et al., (1991) and SOTER (Dobos et al., 2005) compute relative relief and landscape position within a neighborhood analysis window (NAW) of some fixed size (9,600 m and 1 km respectively) the LandMapR method assesses these variables based on explicit analysis of flow paths between locally defined divides and channels (or lakes). We have modified the Hammond criteria by splitting the lowest relief class of 0-30 m into 4 classes of 0-0 m, 0-1 m, 1-10 m and 10-30 m) in order to be able to better differentiate subtle landform features in areas of low relief. Essentially this enables recognition of lakes and open water (0 relief and 0 slope), shorelines and littoral zones (0-1 m), nearly flat, low-relief landforms (1-10 m) and low relief undulating plains (10-30 m). We also modified the Hammond approach for separating upper versus lower landform positions used to differentiate flat areas in uplands from flat lowlands. We instead differentiate 3 relative slope

  12. Remote Sensing of Vegetation Nitrogen Content for Spatially Explicit Carbon and Water Cycle Estimation

    NASA Astrophysics Data System (ADS)

    Zhang, Y. L.; Miller, J. R.; Chen, J. M.

    2009-05-01

    Foliage nitrogen concentration is a determinant of photosynthetic capacity of leaves, thereby an important input to ecological models for estimating terrestrial carbon and water budgets. Recently, spectrally continuous airborne hyperspectral remote sensing imagery has proven to be useful for retrieving an important related parameter, total chlorophyll content at both leaf and canopy scales. Thus remote sensing of vegetation biochemical parameters has promising potential for improving the prediction of global carbon and water balance patterns. In this research, we explored the feasibility of estimating leaf nitrogen content using hyperspectral remote sensing data for spatially explicit estimation of carbon and water budgets. Multi-year measurements of leaf biochemical contents of seven major boreal forest species were carried out in northeastern Ontario, Canada. The variation of leaf chlorophyll and nitrogen content in response to various growth conditions, and the relationship between them,were investigated. Despite differences in plant type (deciduous and evergreen), leaf age, stand growth conditions and developmental stages, leaf nitrogen content was strongly correlated with leaf chlorophyll content on a mass basis during the active growing season (r2=0.78). With this general correlation, leaf nitrogen content was estimated from leaf chlorophyll content at an accuracy of RMSE=2.2 mg/g, equivalent to 20.5% of the average measured leaf nitrogen content. Based on this correlation and a hyperspectral remote sensing algorithm for leaf chlorophyll content retrieval, the spatial variation of leaf nitrogen content was inferred from the airborne hyperspectral remote sensing imagery acquired by Compact Airborne Spectrographic Imager (CASI). A process-based ecological model Boreal Ecosystem Productivity Simulator (BEPS) was used for estimating terrestrial carbon and water budgets. In contrast to the scenario with leaf nitrogen content assigned as a constant value without

  13. Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore tuna (Thunnus alalunga)

    NASA Astrophysics Data System (ADS)

    Lehodey, P.; Senina, I.; Dragon, A.-C.; Arrizabalaga, H.

    2014-09-01

    The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated data sets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models outputs, while the use of a standard data set facilitates models inter-comparison. Unlike standard stock assessment models, new state-of-the-art ecosystem models require geo-referenced fishing data with the highest possible spatial resolution. This study presents an application to the North Atlantic albacore tuna stock with a careful definition and validation of a spatially explicit fishing data set prepared from publicly available sources (ICCAT) for its use in a spatial ecosystem and population dynamics model (SEAPODYM) to provide the first spatially explicit estimate of albacore density in the North Atlantic by life stage. Density distributions together with the fishing data used for the estimates are provided at http://doi.pangaea.de/ (see section Source Data References) (doi:10.1594/PANGAEA.828115; doi:10.1594/PANGAEA.828226; doi:10.1594/PANGAEA.828227; doi:10.1594/PANGAEA.828228; doi:10.1594/PANGAEA.828229; doi:10.1594/PANGAEA.828230; doi:10.1594/PANGAEA.828231; doi:10.1594/PANGAEA.828232; doi:10.1594/PANGAEA.828232; doi:10.1594/PANGAEA.828233; Spatially-Explicit Estimation of Geographical Representation in Large-Scale Species Distribution Datasets

    PubMed Central

    Kalwij, Jesse M.; Robertson, Mark P.; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

    2014-01-01

    Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution

  14. Spatially-explicit model of mercury accumulation in the forest floor of the United States

    NASA Astrophysics Data System (ADS)

    Perry, C. H.; Zimmerman, P.

    2009-12-01

    Atmospherically-deposited Hg has a strong affinity for soil organic matter. The Forest Service, US Department of Agriculture, Forest Inventory and Analysis (FIA) program collects soil samples from forested areas across the United States as part of its sampling program, and annual soils inventories are underway or completed in 46 of the 50 states (Alaska, Hawaii, New Mexico, and Oklahoma have yet to be sampled). Our objective is to describe the spatial distribution of forest floor Hg for a transect running across the United States, from Arizona in the southwest to Maine in the northeast. The collection of forest floor samples was accomplished as part of the standard FIA Phase 3 Soil Quality Indicator program. Field protocols include the measurement of the thickness of the forest floor and the collection of the entire forest floor found within a 30-cm diameter sampling frame. We removed approximately 0.1 g of the sample for plots in our region of interest, and these were sent to two different laboratories for Hg analysis by cold-vapor atomic absorption. The two laboratories calibrated their instruments against common Hg standards. We found good agreement between samples analyzed at both laboratories. Observations of mercury concentrations were joined with the Forest Inventory and Analysis Database and other geospatial databases to assign basic location information and associated inventory data. Ecoprovince and forest-type group are significant predictors of Hg storage; conifer species tend to store more mercury than hardwood species. Additionally, models created using spatially-explicit techniques yield distinct patterns of Hg storage that vary across forest-type groups.

  15. Behavioral response to contamination risk information in a spatially explicit groundwater environment: Experimental evidence

    NASA Astrophysics Data System (ADS)

    Li, Jingyuan; Michael, Holly A.; Duke, Joshua M.; Messer, Kent D.; Suter, Jordan F.

    2014-08-01

    This paper assesses the effectiveness of aquifer monitoring information in achieving more sustainable use of a groundwater resource in the absence of management policy. Groundwater user behavior in the face of an irreversible contamination threat is studied by applying methods of experimental economics to scenarios that combine a physics-based, spatially explicit, numerical groundwater model with different representations of information about an aquifer and its risk of contamination. The results suggest that the threat of catastrophic contamination affects pumping decisions: pumping is significantly reduced in experiments where contamination is possible compared to those where pumping cost is the only factor discouraging groundwater use. The level of information about the state of the aquifer also affects extraction behavior. Pumping rates differ when information that synthesizes data on aquifer conditions (a "risk gauge") is provided, despite invariant underlying economic incentives, and this result does not depend on whether the risk information is location-specific or from a whole aquifer perspective. Interestingly, users increase pumping when the risk gauge signals good aquifer status compared to a no-gauge treatment. When the gauge suggests impending contamination, however, pumping declines significantly, resulting in a lower probability of contamination. The study suggests that providing relatively simple aquifer condition guidance derived from monitoring data can lead to more sustainable use of groundwater resources.

  16. Spatially explicit forest characteristics of Europe through integrating Forest Inventory and Remotely sensed data

    NASA Astrophysics Data System (ADS)

    Moreno, Adam; Neumann, Mathias; Hasenauer, Hubert

    2015-04-01

    Carbon stock estimates are critical for any carbon trading scheme or climate change mitigation strategy. Understanding the carbon allocation and the structure of its ecosystem further help scientists and policy makers develop realistic plans for utilizing these systems. Forests play an important role in global carbon storage. Therefore it is imperative to include forests in any climate change mitigation and/or carbon trading scheme. Currently there is no estimate of forest carbon stocks and allocation nor forest structure maps throughout Europe. We compiled National Forest Inventory (NFI) data from 12 European countries. We integrated the NFI data with Net Primary Production data (NPP) from Moderate Resolution Imaging Spectroradiometer (MODIS), tree height data from Light Detection and Ranging (LIDAR) data from the Geosciences Laser Altimeter System (GLAS) instrument, and various other spatially explicit data sets. Through this process of integration of terrestrial and space based data we produced wall-to-wall forest characteristics maps of Europe. These maps include forest age, basal area, average diameter at breast height, total carbon, carbon allocation (stem, branches, leaves, roots), and other characteristics derived from forest inventory data. These maps cover Europe - including countries without terrestrial data - and give one coherent harmonized data set of current forest structure and carbon storage on a 16x16km resolution. The methodology presented here has the potential to be used world-wide in regions with data limitations or with limited access to data.

  17. Cholera in the Lake Kivu region (DRC): Integrating remote sensing and spatially explicit epidemiological modeling

    NASA Astrophysics Data System (ADS)

    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

    2014-07-01

    Mathematical models of cholera dynamics can not only help in identifying environmental drivers and processes that influence disease transmission, but may also represent valuable tools for the prediction of the epidemiological patterns in time and space as well as for the allocation of health care resources. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. They have been ravaging the shore of Lake Kivu in the east of the country repeatedly during the last decades. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of the lake. Remotely sensed data sets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multiyear data set of reported cholera cases. The best fourteen models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via proper cross validation. Among these, the one accounting for seasonality, El Niño Southern Oscillation, precipitation and human mobility outperforms the others in cross validation. Some drivers (such as human mobility and rainfall) are retained only by a few models, possibly indicating that the mechanisms through which they influence cholera dynamics in the area will have to be investigated further.

  18. Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

    USGS Publications Warehouse

    Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

    2015-01-01

    Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

  19. Integral assessment of floodplains as a basis for spatially-explicit flood loss forecasts

    NASA Astrophysics Data System (ADS)

    Zischg, Andreas Paul; Mosimann, Markus; Weingartner, Rolf

    2016-04-01

    A key aspect of disaster prevention is flood discharge forecasting which is used for early warning and therefore as a decision support for intervention forces. Hereby, the phase between the issued forecast and the time when the expected flood occurs is crucial for an optimal planning of the intervention. Typically, river discharge forecasts cover the regional level only, i.e. larger catchments. However, it is important to note that these forecasts are not useable directly for specific target groups on local level because these forecasts say nothing about the consequences of the predicted flood in terms of affected areas, number of exposed residents and houses. For this, on one hand simulations of the flooding processes and on the other hand data of vulnerable objects are needed. Furthermore, flood modelling in a high spatial and temporal resolution is required for robust flood loss estimation. This is a resource-intensive task from a computing time point of view. Therefore, in real-time applications flood modelling in 2D is not suited. Thus, forecasting flood losses in the short-term (6h-24h in advance) requires a different approach. Here, we propose a method to downscale the river discharge forecast to a spatially-explicit flood loss forecast. The principal procedure is to generate as many flood scenarios as needed in advance to represent the flooded areas for all possible flood hydrographs, e.g. very high peak discharges of short duration vs. high peak discharges with high volumes. For this, synthetic flood hydrographs were derived from the hydrologic time series. Then, the flooded areas of each scenario were modelled with a 2D flood simulation model. All scenarios were intersected with the dataset of vulnerable objects, in our case residential, agricultural and industrial buildings with information about the number of residents, the object-specific vulnerability, and the monetary value of the objects. This dataset was prepared by a data-mining approach. For each

  1. A risk assessment example for soil invertebrates using spatially explicit agent-based models.

    PubMed

    Reed, Melissa; Alvarez, Tania; Chelinho, Sónia; Forbes, Valery; Johnston, Alice; Meli, Mattia; Voss, Frank; Pastorok, Rob

    2016-01-01

    Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier, population-level effects are assessed using semifield and field trials at a higher tier because modeling methods for extrapolating available lower-tier information to population effects have not yet been implemented. Field trials are expensive, time consuming, and cannot be applied to variable landscape scenarios. Mechanistic modeling of the toxicological effects of PPPs on individuals and their responses combined with simulation of population-level response shows great potential in fulfilling such a need, aiding ecologically informed extrapolation. Here, we introduce and demonstrate the potential of 2 population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed "overall"], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover within 1 year after pesticide application, regardless of application method. The population modeling for both soil organisms also illustrated that a lower predicted average environmental concentration in soil (PECsoil) could potentially lead to greater effects at the population level, depending on the spatial heterogeneity of the pesticide and the behavior of the soil organisms. Population-level effects of spatial-temporal variations in exposure were elucidated in the

  2. Spatially explicit modeling of conflict zones between wildlife and snow sports: prioritizing areas for winter refuges.

    PubMed

    Braunisch, Veronika; Patthey, Patrick; Arlettaz, Raphaël

    2011-04-01

    Outdoor winter recreation exerts an increasing pressure upon mountain ecosystems, with unpredictable, free-ranging activities (e.g., ski mountaineering, snowboarding, and snowshoeing) representing a major source of stress for wildlife. Mitigating anthropogenic disturbance requires the spatially explicit prediction of the interference between the activities of humans and wildlife. We applied spatial modeling to localize conflict zones between wintering Black Grouse (Tetrao tetrix), a declining species of Alpine timberline ecosystems, and two free-ranging winter sports (off-piste skiing [including snow-boarding] and snowshoeing). Track data (snow-sports and birds' traces) obtained from aerial photographs taken over a 585-km transect running along the timberline, implemented within a maximum entropy model, were used to predict the occurrence of snow sports and Black Grouse as a function of landscape characteristics. By modeling Black Grouse presence in the theoretical absence of free-ranging activities and ski infrastructure, we first estimated the amount of habitat reduction caused by these two factors. The models were then extrapolated to the altitudinal range occupied by Black Grouse, while the spatial extent and intensity of potential conflict were assessed by calculating the probability of human-wildlife co-occurrence. The two snow-sports showed different distribution patterns. Skiers' occurrence was mainly determined by ski-lift presence and a smooth terrain, while snowshoers' occurrence was linked to hiking or skiing routes and moderate slopes. Wintering Black Grouse avoided ski lifts and areas frequented by free-ranging snow sports. According to the models, Black Grouse have faced a substantial reduction of suitable wintering habitat along the timberline transect: 12% due to ski infrastructure and another 16% when adding free-ranging activities. Extrapolating the models over the whole study area results in an overall habitat loss due to ski infrastructure of

  3. POTENTIAL EFFECTS OF A FOREST MANAGEMENT PLAN ON BACHMAN'S SPARROWS (AIMOPHILA AESTIVALIS): LINKING A SPATIALLY EXPLICIT MODEL WITH GIS

    EPA Science Inventory

    By combining a spatially explicit, individual-based population simulation model with a geographic information system, this study simulated the potential effects of a U.S. Forest management plan on the population dynamics of Bachman's Sparrow at the Savannah River Site, South Caro...

  4. SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

    EPA Science Inventory

    This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

  5. Spatially explicit exposure assessment for small streams in catchments of the orchard growing region `Lake Constance

    NASA Astrophysics Data System (ADS)

    Golla, B.; Bach, M.; Krumpe, J.

    2009-04-01

    1. Introduction Small streams differ greatly from the standardised water body used in the context of aquatic risk assessment for the regulation of plant protection products in Germany. The standard water body is static, with a depth of 0.3 m and a width of 1.0 m. No dilution or water replacement takes place. Spray drift happens always in direction to the water body. There is no variability in drift deposition rate (90th percentile spray drift deposition values [2]). There is no spray drift filtering by vegetation. The application takes place directly adjacent to the water body. In order to establish a more realistic risk assessment procedure the Federal Office for Consumer Protection and Food Safety (BVL) and the Federal Environment Agency (UBA) aggreed to replace deterministic assumptions with data distributions and spatially explicit data and introduce probabilistic methods [3, 4, 5]. To consider the spatial and temporal variability in the exposure situations of small streams the hydraulic and morphological characteristics of catchments need to be described as well as the spatial distribution of fields treated with pesticides. As small streams are the dominant type of water body in most German orchard regions, we use the growing region Lake Constance as pilot region. 2. Materials and methods During field surveys we derive basic morphological parameters for small streams in the Lake Constance region. The mean water width/depth ratio is 13 with a mean depth of 0.12 m. The average residence time is 5.6 s/m (n=87) [1]. Orchards are mostly located in the upper parts of the catchments. Based on an authoritative dataset on rivers and streams of Germany (ATKIS DLM25) we constructed a directed network topology for the Lake Constance region. The gradient of the riverbed is calculated for river stretches of > 500 m length. The network for the pilot region consists of 2000 km rivers and streams. 500 km stream length are located within a distance of 150 m to orchards. Within

  6. A spatially explicit decision support model for restoration of forest bird habitat

    USGS Publications Warehouse

    Twedt, D.J.; Uihlein, W.B., III; Elliott, A.B.

    2006-01-01

    The historical area of bottomland hardwood forest in the Mississippi Alluvial Valley has been reduced by >75%. Agricultural production was the primary motivator for deforestation; hence, clearing deliberately targeted higher and drier sites. Remaining forests are highly fragmented and hydrologically altered, with larger forest fragments subject to greater inundation, which has negatively affected many forest bird populations. We developed a spatially explicit decision support model, based on a Partners in Flight plan for forest bird conservation, that prioritizes forest restoration to reduce forest fragmentation and increase the area of forest core (interior forest >1 km from 'hostile' edge). Our primary objective was to increase the number of forest patches that harbor >2000 ha of forest core, but we also sought to increase the number and area of forest cores >5000 ha. Concurrently, we targeted restoration within local (320 km2) landscapes to achieve >60% forest cover. Finally, we emphasized restoration of higher-elevation bottomland hardwood forests in areas where restoration would not increase forest fragmentation. Reforestation of 10% of restorable land in the Mississippi Alluvial Valley (approximately 880,000 ha) targeted at priorities established by this decision support model resulted in approximately 824,000 ha of new forest core. This is more than 32 times the amount of core forest added through reforestation of randomly located fields (approximately 25,000 ha). The total area of forest core (1.6 million ha) that resulted from targeted restoration exceeded habitat objectives identified in the Partners in Flight Bird Conservation Plan and approached the area of forest core present in the 1950s.

  7. A spatially explicit capture-recapture estimator for single-catch traps.

    PubMed

    Distiller, Greg; Borchers, David L

    2015-11-01

    Single-catch traps are frequently used in live-trapping studies of small mammals. Thus far, a likelihood for single-catch traps has proven elusive and usually the likelihood for multicatch traps is used for spatially explicit capture-recapture (SECR) analyses of such data. Previous work found the multicatch likelihood to provide a robust estimator of average density. We build on a recently developed continuous-time model for SECR to derive a likelihood for single-catch traps. We use this to develop an estimator based on observed capture times and compare its performance by simulation to that of the multicatch estimator for various scenarios with nonconstant density surfaces. While the multicatch estimator is found to be a surprisingly robust estimator of average density, its performance deteriorates with high trap saturation and increasing density gradients. Moreover, it is found to be a poor estimator of the height of the detection function. By contrast, the single-catch estimators of density, distribution, and detection function parameters are found to be unbiased or nearly unbiased in all scenarios considered. This gain comes at the cost of higher variance. If there is no interest in interpreting the detection function parameters themselves, and if density is expected to be fairly constant over the survey region, then the multicatch estimator performs well with single-catch traps. However if accurate estimation of the detection function is of interest, or if density is expected to vary substantially in space, then there is merit in using the single-catch estimator when trap saturation is above about 60%. The estimator's performance is improved if care is taken to place traps so as to span the range of variables that affect animal distribution. As a single-catch likelihood with unknown capture times remains intractable for now, researchers using single-catch traps should aim to incorporate timing devices with their traps. PMID:26640683

  8. EnviroAtlas: A Spatially Explicit Tool Combining Climate Change Scenarios with Ecosystem Services Indicators

    NASA Astrophysics Data System (ADS)

    Neale, A. C.; Pickard, B. R.; Megan, M.; Baynes, J.

    2014-12-01

    While discussions of global climate change tend to center on greenhouse gases and sea levelrise, other factors, such as technological developments, land and energy use, economics, and populationgrowth all play a critical role in understanding climate change. There is increasing urgency for methodsto forecast how different sectors, in particular ecosystems and the goods and services they provide, maybe altered as a result of climate change. However, due to their complexity, it is difficult to assess theseecosystem services at a single point in space or time, as they may be influenced by surrounding anddistant patterns of land use and biophysical attributes in addition to climate change. In order to makemeaningful conservation and adaptation choices, specific ecosystem components must be viewed inrelation to future climate information. The US Environmental Protection Agency and its partners, havedeveloped EnviroAtlas, a web-based geospatial tool that allows users to interact with climate changemodeling information while simultaneously providing a range of information and data on differentecosystem goods and services. This can be a useful platform for inquiry about the supply, demand, orbenefits provided by a specific ecosystem service, and to understand the potential impacts to thatecosystem service due to our changing climate. Housing a variety of data in one publicly available toolencourages users to think in new, trans-disciplinary ways that focus on the relationships betweenecosystem services and climate change impacts. By combining many fields of research through this easyto-use interface, the result is a novel tool that is spatially and temporally explicit and enables betterdecision making across multiple sectors. This talk will illustrate how the information presented inEnviroAtlas can be used in research.

  9. A spatially explicit model simulating western corn rootworm (Coleoptera: Chrysomelidae) adaptation to insect-resistant maize.

    PubMed

    Storer, Nicholas P

    2003-10-01

    A stochastic spatially explicit computer model is described that simulates the adaptation by western corn rootworm, Diabrotica virgifera virgifera LeConte, to rootworm-resistance traits in maize. The model reflects the ecology of the rootworm in much of the corn belt of the United States. It includes functions for crop development, egg and larval mortality, adult emergence, mating, egg laying, mortality and dispersal, and alternative methods of rootworm control, to simulate the population dynamics of the rootworm. Adaptation to the resistance trait is assumed to be controlled by a monogenic diallelic locus, whereby the allele for adaptation varies from incompletely recessive to incompletely dominant, depending on the efficacy of the resistance trait. The model was used to compare the rate at which the adaptation allele spread through the population under different nonresistant maize refuge deployment scenarios, and under different levels of crop resistance. For a given refuge size, the model indicated that placing the nonresistant refuge in a block within a rootworm-resistant field would be likely to delay rootworm adaptation rather longer than planting the refuge in separate fields in varying locations. If a portion of the refuge were to be planted in the same fields or in-field blocks each year, rootworm adaptation would be delayed substantially. Rootworm adaptation rates are also predicted to be greatly affected by the level of crop resistance, because of the expectation of dependence of functional dominance on dose. If the dose of the insecticidal protein in the maize is sufficiently high to kill >90% of heterozygotes and approximately 100% of susceptible homozygotes, the trait is predicted to be much more durable than if the dose is lower. A partial sensitivity analysis showed that parameters relating to adult dispersal affected the rate of pest adaptation. Partial validation of the model was achieved by comparing output of the model with field data on

  10. A spatially explicit estimate of the prewhaling abundance of the endangered North Atlantic right whale.

    PubMed

    Monsarrat, Sophie; Pennino, M Grazia; Smith, Tim D; Reeves, Randall R; Meynard, Christine N; Kaplan, David M; Rodrigues, Ana S L

    2016-08-01

    The North Atlantic right whale (NARW) (Eubalaena glacialis) is one of the world's most threatened whales. It came close to extinction after nearly a millennium of exploitation and currently persists as a population of only approximately 500 individuals. Setting appropriate conservation targets for this species requires an understanding of its historical population size, as a baseline for measuring levels of depletion and progress toward recovery. This is made difficult by the scarcity of records over this species' long whaling history. We sought to estimate the preexploitation population size of the North Atlantic right whale and understand how this species was distributed across its range. We used a spatially explicit data set on historical catches of North Pacific right whales (NPRWs) (Eubalaena japonica) to model the relationship between right whale relative density and the environment during the summer feeding season. Assuming the 2 right whale species select similar environments, we projected this model to the North Atlantic to predict how the relative abundance of NARWs varied across their range. We calibrated these relative abundances with estimates of the NPRW total prewhaling population size to obtain high and low estimates for the overall NARW population size prior to exploitation. The model predicted 9,075-21,328 right whales in the North Atlantic. The current NARW population is thus <6% of the historical North Atlantic carrying capacity and has enormous potential for recovery. According to the model, in June-September NARWs concentrated in 2 main feeding areas: east of the Grand Banks of Newfoundland and in the Norwegian Sea. These 2 areas may become important in the future as feeding grounds and may already be used more regularly by this endangered species than is thought. PMID:26632250

  11. A spatially explicit model for the future progression of the current Haiti cholera epidemic

    NASA Astrophysics Data System (ADS)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2011-12-01

    As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to July 2011, climb to 385,000 cases and 5,800 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of textit{Vibrio cholera}, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan texttrademark project). The model directly account for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations, clean water supply and educational campaigns, thus emerging as an essential component of the control of future cholera

  12. Human Mobility Patterns and Cholera Epidemics: a Spatially Explicit Modeling Approach

    NASA Astrophysics Data System (ADS)

    Mari, L.; Bertuzzo, E.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2010-12-01

    Cholera is an acute enteric disease caused by the ingestion of water or food contaminated by the bacterium Vibrio cholerae. Although most infected individuals do not develop severe symptoms, their stool may contain huge quantities of V.~cholerae cells. Therefore, while traveling or commuting, asymptomatic carriers can be responsible for the long-range dissemination of the disease. As a consequence, human mobility is an alternative and efficient driver for the spread of cholera, whose primary propagation pathway is hydrological transport through river networks. We present a multi-layer network model that accounts for the interplay between epidemiological dynamics, hydrological transport and long-distance dissemination of V.~cholerae due to human movement. In particular, building on top of state-of-the-art spatially explicit models for cholera spread through surface waters, we describe human movement and its effects on the propagation of the disease by means of a gravity-model approach borrowed from transportation theory. Gravity-like contact processes have been widely used in epidemiology, because they can satisfactorily depict human movement when data on actual mobility patterns are not available. We test our model against epidemiological data recorded during the cholera outbreak occurred in the KwaZulu-Natal province of South Africa during years 2000--2001. We show that human mobility does actually play an important role in the formation of the spatiotemporal patterns of cholera epidemics. In particular, long-range human movement may determine inter-catchment dissemination of V.~cholerae cells, thus in turn explaining the emergence of epidemic patterns that cannot be produced by hydrological transport alone. We also show that particular attention has to be devoted to study how heterogeneously distributed drinking water supplies and sanitation conditions may affect cholera transmission.

  13. SPATIALLY-EXPLICIT BAT IMPACT SCREENING TOOL FOR WIND TURBINE SITING

    SciTech Connect

    Versar, Inc.; Exponent, Inc.

    2013-10-28

    As the U.S. seeks to increase energy production from renewable energy sources, development of wind power resources continues to grow. One of the most important ecological issues restricting wind energy development, especially the siting of wind turbines, is the potential adverse effect on bats. High levels of bat fatality have been recorded at a number of wind energy facilities, especially in the eastern United States. The U.S. Department of Energy contracted with Versar, Inc., and Exponent to develop a spatially-explicit site screening tool to evaluate the mortality of bats resulting from interactions (collisions or barotrauma) with wind turbines. The resulting Bat Vulnerability Assessment Tool (BVAT) presented in this report integrates spatial information about turbine locations, bat habitat features, and bat behavior as it relates to possible interactions with turbines. A model demonstration was conducted that focuses on two bat species, the eastern red bat (Lasiurus borealis) and the Indiana bat (Myotis sodalis). The eastern red bat is a relatively common tree-roosting species that ranges broadly during migration in the Eastern U.S., whereas the Indiana bat is regional species that migrates between a summer range and cave hibernacula. Moreover, Indiana bats are listed as endangered, and so the impacts to this species are of particular interest. The model demonstration used conditions at the Mountaineer Wind Energy Center (MWEC), which consists of 44 wind turbines arranged in a linear array near Thomas, West Virginia (Tucker County), to illustrate model functions and not to represent actual or potential impacts of the facility. The turbines at MWEC are erected on the ridge of Backbone Mountain with a nacelle height of 70 meters and a collision area of 72 meters (blade height) or 4,071 meters square. The habitat surrounding the turbines is an Appalachian mixed mesophytic forest. Model sensitivity runs showed that bat mortality in the model was most sensitive to

  14. SEHR-ECHO v1.0: a Spatially-Explicit Hydrologic Response model for ecohydrologic applications

    NASA Astrophysics Data System (ADS)

    Schaefli, Bettina; Nicótina, Ludovico; Da Ronco, Pierfrancesco; Bertuzzo, Enrico; Rinaldo, Andrea

    2015-04-01

    We present here the SEHR-ECHO model, which stands for Spatially Explicit Hydrologic Response (SEHR) model developed at the Laboratory of Ecohydrology (ECHO) of the Ecole Polytechnique Fédérale de Lausanne. The model is being developed for the spatially-explicit simulation of streamflow and transport processes at the catchment scale. The key concept of the model is the formulation of water transport by geomorphologic travel time distributions: the mobilization of water (and possibly dissolved solutes) is simulated at the subcatchment scale and the resulting responses are convolved with the travel paths distribution within the river network to obtain the hydrologic response at the catchment outlet. The Matlab source code of the current version for alpine streamflow simulation is already freely available. A truly free open source version using Python will become available in the future.

  15. A Spatially Explicit Dual-Isotope Approach to Map Regions of Plant-Plant Interaction after Exotic Plant Invasion.

    PubMed

    Hellmann, Christine; Werner, Christiane; Oldeland, Jens

    2016-01-01

    Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent of influence of

  16. A Spatially Explicit Dual-Isotope Approach to Map Regions of Plant-Plant Interaction after Exotic Plant Invasion

    PubMed Central

    Hellmann, Christine; Werner, Christiane; Oldeland, Jens

    2016-01-01

    Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent of influence of

  17. CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

    USGS Publications Warehouse

    Erin L. Landguth; Muhlfeld, Clint C.; Luikart, Gordon

    2012-01-01

    We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

  18. Programmable DNA scaffolds for spatially-ordered protein assembly

    NASA Astrophysics Data System (ADS)

    Chandrasekaran, Arun Richard

    2016-02-01

    Ever since the notion of using DNA as a material was realized, it has been employed in the construction of complex structures that facilitate the assembly of nanoparticles or macromolecules with nanometer-scale precision. Specifically, tiles fashioned from DNA strands and DNA origami sheets have been shown to be suitable as scaffolds for immobilizing proteins with excellent control over their spatial positioning. Supramolecular assembly of proteins into periodic arrays in one or more dimensions is one of the most challenging aspects in the design of scaffolds for biomolecular investigations and macromolecular crystallization. This review provides a brief overview of how various biomolecular interactions with high degree of specificity such as streptavidin-biotin, antigen-antibody, and aptamer-protein interactions have been used to fabricate linear and multidimensional assemblies of structurally intact and functional proteins. The use of DNA-binding proteins as adaptors, polyamide recognition on DNA scaffolds and oligonucleotide linkers for protein assembly are also discussed.Ever since the notion of using DNA as a material was realized, it has been employed in the construction of complex structures that facilitate the assembly of nanoparticles or macromolecules with nanometer-scale precision. Specifically, tiles fashioned from DNA strands and DNA origami sheets have been shown to be suitable as scaffolds for immobilizing proteins with excellent control over their spatial positioning. Supramolecular assembly of proteins into periodic arrays in one or more dimensions is one of the most challenging aspects in the design of scaffolds for biomolecular investigations and macromolecular crystallization. This review provides a brief overview of how various biomolecular interactions with high degree of specificity such as streptavidin-biotin, antigen-antibody, and aptamer-protein interactions have been used to fabricate linear and multidimensional assemblies of structurally

  19. Functional Assembly of Protein Fragments Induced by Spatial Confinement

    PubMed Central

    Yu, Yongsheng; Wang, Jianpeng; Liu, Jiahui; Ling, Daishun; Xia, Jiang

    2015-01-01

    Natural proteins are often confined within their local microenvironments, such as three-dimensional confinement in organelles or two-dimensional confinement in lipid rafts on cytoplasmic membrane. Spatial confinement restricts proteins' entropic freedom, forces their lateral interaction, and induces new properties that the same proteins lack at the soluble state. So far, the phenomenon of environment-induced protein functional alteration still lacks a full illustration. We demonstrate here that engineered protein fragments, although being non-functional in solution, can be re-assembled within the nanometer space to give the full activity of the whole protein. Specific interaction between hexahistidine-tag (His-tag) and NiO surface immobilizes protein fragments on NiO nanoparticles to form a self-assembled protein "corona" on the particles inside the nanopores of mesoporous silica. Site-specific assembly forces a shoulder-by-shoulder orientation and promotes fragment−fragment interaction; this interaction together with spatial confinement of the mesopores results in functional re-assembly of the protein half fragments. To our surprise, a single half fragment of luciferase (non-catalytic in solution) exhibited luciferase activity when immobilized on NiO in the mesopores, in the absence of the complimentary half. This shows for the first time that spatial confinement can induce the folding of a half fragment, reconstitute the enzyme active site, and re-gain the catalytic capability of the whole protein. Our work thereby highlights the under-documented notion that aside from the chemical composition such as primary sequence, physical environment of a protein also determines its function. PMID:25875003

  20. Functional assembly of protein fragments induced by spatial confinement.

    PubMed

    Yu, Yongsheng; Wang, Jianpeng; Liu, Jiahui; Ling, Daishun; Xia, Jiang

    2015-01-01

    Natural proteins are often confined within their local microenvironments, such as three-dimensional confinement in organelles or two-dimensional confinement in lipid rafts on cytoplasmic membrane. Spatial confinement restricts proteins' entropic freedom, forces their lateral interaction, and induces new properties that the same proteins lack at the soluble state. So far, the phenomenon of environment-induced protein functional alteration still lacks a full illustration. We demonstrate here that engineered protein fragments, although being non-functional in solution, can be re-assembled within the nanometer space to give the full activity of the whole protein. Specific interaction between hexahistidine-tag (His-tag) and NiO surface immobilizes protein fragments on NiO nanoparticles to form a self-assembled protein "corona" on the particles inside the nanopores of mesoporous silica. Site-specific assembly forces a shoulder-by-shoulder orientation and promotes fragment-fragment interaction; this interaction together with spatial confinement of the mesopores results in functional re-assembly of the protein half fragments. To our surprise, a single half fragment of luciferase (non-catalytic in solution) exhibited luciferase activity when immobilized on NiO in the mesopores, in the absence of the complimentary half. This shows for the first time that spatial confinement can induce the folding of a half fragment, reconstitute the enzyme active site, and re-gain the catalytic capability of the whole protein. Our work thereby highlights the under-documented notion that aside from the chemical composition such as primary sequence, physical environment of a protein also determines its function. PMID:25875003

  1. Plant community assembly at small scales: Spatial vs. environmental factors in a European grassland

    NASA Astrophysics Data System (ADS)

    Horn, Sebastian; Hempel, Stefan; Ristow, Michael; Rillig, Matthias C.; Kowarik, Ingo; Caruso, Tancredi

    2015-02-01

    Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15 × 15, 12 × 12 and 12 × 12 m in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

  2. Spatially Explicit Analyses of Anopheline Mosquitoes Indoor Resting Density: Implications for Malaria Control

    PubMed Central

    Kamdem, Colince; Fouet, Caroline; Etouna, Joachim; Etoa, François-Xavier; Simard, Frédéric; Besansky, Nora J.; Costantini, Carlo

    2012-01-01

    Background The question of sampling and spatial aggregation of malaria vectors is central to vector control efforts and estimates of transmission. Spatial patterns of anopheline populations are complex because mosquitoes' habitats and behaviors are strongly heterogeneous. Analyses of spatially referenced counts provide a powerful approach to delineate complex distribution patterns, and contributions of these methods in the study and control of malaria vectors must be carefully evaluated. Methodology/Principal Findings We used correlograms, directional variograms, Local Indicators of Spatial Association (LISA) and the Spatial Analysis by Distance IndicEs (SADIE) to examine spatial patterns of Indoor Resting Densities (IRD) in two dominant malaria vectors sampled with a 5×5 km grid over a 2500 km2 area in the forest domain of Cameroon. SADIE analyses revealed that the distribution of Anopheles gambiae was different from regular or random, whereas there was no evidence of spatial pattern in Anopheles funestus (Ia = 1.644, Pa<0.05 and Ia = 1.464, Pa>0.05, respectively). Correlograms and variograms showed significant spatial autocorrelations at small distance lags, and indicated the presence of large clusters of similar values of abundance in An. gambiae while An. funestus was characterized by smaller clusters. The examination of spatial patterns at a finer spatial scale with SADIE and LISA identified several patches of higher than average IRD (hot spots) and clusters of lower than average IRD (cold spots) for the two species. Significant changes occurred in the overall spatial pattern, spatial trends and clusters when IRDs were aggregated at the house level rather than the locality level. All spatial analyses unveiled scale-dependent patterns that could not be identified by traditional aggregation indices. Conclusions/Significance Our study illustrates the importance of spatial analyses in unraveling the complex spatial patterns of malaria vectors, and

  3. Mapping of the CO2 and anthropogenic heat emission under spatially explicit urban land use scenarios

    NASA Astrophysics Data System (ADS)

    Nakamichi, K.; Yamagata, Y.; Seya, H.

    2010-12-01

    possible range of future land use change. The first one is a compact city scenario and the second one is a dispersion scenario. In the compact city scenario, we assumed that commuting to work by cars would be prohibited. In the dispersion scenario, we assumed that all workers would work in their own houses and the time of commuting to work would be zero. The spatially explicit emissions are mapped by using Geographical Information System (GIS). As for the CO2 emission, this study focuses on the analysis of the tendency from the viewpoint of both direct and indirect emission. As a result, people would live in suburbs in the second scenario, and the emissions would increase. It is concluded that the results shows the importance of low-carbon city as compact city. Moreover, the anthropogenic heat emission estimated in this study can used as the input parameters for the climate models. The developed system can be used for analyzing the implications of urban planning and carbon management scenarios.

  4. Spatially Explicit Large Area Biomass Estimation: Three Approaches Using Forest Inventory and Remotely Sensed Imagery in a GIS

    PubMed Central

    Wulder, Michael A.; White, Joanne C.; Fournier, Richard A.; Luther, Joan E.; Magnussen, Steen

    2008-01-01

    Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the area of interest (i.e., inventories not spatially exhaustive), or by the omission of inventory attributes required for biomass estimation. These spatial and attributional gaps in the forest inventory may result in an underestimation of large area AGB. The continuous nature and synoptic coverage of remotely sensed data have led to their increased application for AGB estimation over large areas, although the use of these data remains challenging in complex forest environments. In this paper, we present an approach to generating spatially explicit estimates of large area AGB by integrating AGB estimates from multiple data sources; 1. using a lookup table of conversion factors applied to a non-spatially exhaustive forest inventory dataset (R2 = 0.64; RMSE = 16.95 t/ha), 2. applying a lookup table to unique combinations of land cover and vegetation density outputs derived from remotely sensed data (R2 = 0.52; RMSE = 19.97 t/ha), and 3. hybrid mapping by augmenting forest inventory AGB estimates with remotely sensed AGB estimates where there are spatial or attributional gaps in the forest inventory data. Over our 714,852 ha study area in central Saskatchewan, Canada, the AGB estimate generated from the forest inventory was approximately 40 Mega tonnes (Mt); however, the inventory estimate represents only 51% of the total study area. The AGB estimate generated from the remotely sensed outputs that overlap those made from the forest inventory based approach differ by only 2 %; however in total, the remotely sensed estimate is 30 % greater (58 Mt) than the estimate generated from the forest inventory when the entire study area is accounted for. Finally, using the hybrid approach, whereby

  5. Exploring spatial change and gravity center movement for ecosystem services value using a spatially explicit ecosystem services value index and gravity model.

    PubMed

    He, Yingbin; Chen, Youqi; Tang, Huajun; Yao, Yanmin; Yang, Peng; Chen, Zhongxin

    2011-04-01

    Spatially explicit ecosystem services valuation and change is a newly developing area of research in the field of ecology. Using the Beijing region as a study area, the authors have developed a spatially explicit ecosystem services value index and implemented this to quantify and spatially differentiate ecosystem services value at 1-km grid resolution. A gravity model was developed to trace spatial change in the total ecosystem services value of the Beijing study area from a holistic point of view. Study results show that the total value of ecosystem services for the study area decreased by 19.75% during the period 1996-2006 (3,226.2739 US$×10(6) in 1996, 2,589.0321 US$×10(6) in 2006). However, 27.63% of the total area of the Beijing study area increased in ecosystem services value. Spatial differences in ecosystem services values for both 1996 and 2006 are very clear. The center of gravity of total ecosystem services value for the study area moved 32.28 km northwestward over the 10 years due to intensive human intervention taking place in southeast Beijing. The authors suggest that policy-makers should pay greater attention to ecological protection under conditions of rapid socio-economic development and increase the area of green belt in the southeastern part of Beijing. PMID:20556644

  6. Robustness of Well-Verified, Spatially-Explicit High Resolution Climate Reconstructions: Characterization of Issues and Potential for Their Resolution

    NASA Astrophysics Data System (ADS)

    Wahl, E. R.; Anchukaitis, K. J.; Frank, D.

    2009-04-01

    High-resolution, spatially-explicit reconstructions of climate over the past 1-2 millennia offer the potential to achieve two key goals of paleoclimatology: 1) joining the instrumental and paleo records in a systematic way, to facilitate an extended synoptic-scale perspective on climate variability at regional scales; and 2) elucidating spatial patterns of the response to forcing changes over much longer time spans than possible with instrumental data, allowing for a greater range of responses to be included in composite analyses of forcings impacts on climate. A suite of spatially-explicit reconstruction methods coupled with experimental examination of long-term reconstruction performance in climate model simulation environments now provide a rich set of resources with which to move towards these goals, and also to examine likely situations of good and poor performance. A key concern of all paleo-reconstruction methods is that even well-calibrated and well-verified models of the same phenomenon over the same spatial and temporal domains can diverge outside of the calibration and verification periods. Divergence can occur simply by altering proxy data richness within the same reconstruction model. This suite of problems is relatively well characterized for regional, hemispheric, and global average temperature time series, and even has a well-known visual representation - the so-called "spaghetti diagrams". These issues also exist in spatially-explicit reconstructions, but are not as well characterized as they are for spatially-averaged time series; their potential impacts on achieving the goals described above are also not as well understood. We present examples of these issues from our current work in western North America and the South Asia/Indian Ocean region, along with ways to better characterize and deal with them. An intensive empirical approach is taken that examines a large variety of reconstruction situations for a given spatial-temporal domain - using

  7. A Spatially Explicit and Seasonally Varying Cholera Prevalence Model With Distributed Macro-Scale Environmental and Hydroclimatic Forcings

    NASA Astrophysics Data System (ADS)

    Akanda, A. S.; Jutla, A. S.; Eltahir, E. A.; Islam, S.

    2011-12-01

    Despite major advances in the ecological and microbiological understanding of the bacterium Vibrio cholerae, the role of underlying large-scale processes in the progression of the cholera disease in space and time is not well understood. Here, we present a spatially explicit and seasonally varying coupled hydroclimatology-epidemiology model for understanding regional scale cholera prevalence in response to large scale hydroclimatic and environmental forcings. Our results show that environmental cholera transmission can be modulated by two spatially and seasonally distinct mechanisms - influenced by dry and wet season hydrologic determinants. The model is applied to the Ganges-Brahmaputra-Meghna Basin areas in Bangladesh to simulate spatially explicit cholera prevalence rates, and validated with long-term cholera data from Dhaka and shorter-term records from regional surveillance locations. The model reproduces the variability of cholera prevalence at monthly, seasonal, and interannual timescales and highlights the role of asymmetric large scale hydroclimatic processes as the dominant controls. Our findings have important implications for formulating effective cholera intervention strategies, and for understanding the impacts of changing climate patterns on seasonal cholera transmission.

  8. USE OF HABITAT-CONTAMINATION SPATIAL CORRELATION TO DETERMINE WHEN TO PERFORM A SPATIALLY EXPLICIT ECOLOGICAL RISK ASSESSMENT

    EPA Science Inventory

    Anthropogenic contamination is typically distributed heterogeneously through space. This spatial structure can have different effects on the cumulative doses of individuals exposed to contamination within the environment. These effects are accentuated when individuals pursue di...

  9. Dynamic multiprotein assemblies shape the spatial structure of cell signaling.

    PubMed

    Nussinov, Ruth; Jang, Hyunbum

    2014-01-01

    Cell signaling underlies critical cellular decisions. Coordination, efficiency as well as fail-safe mechanisms are key elements. How the cell ensures that these hallmarks are at play are important questions. Cell signaling is often viewed as taking place through discrete and cross-talking pathways; oftentimes these are modularized to emphasize distinct functions. While simple, convenient and clear, such models largely neglect the spatial structure of cell signaling; they also convey inter-modular (or inter-protein) spatial separation that may not exist. Here our thesis is that cell signaling is shaped by a network of multiprotein assemblies. While pre-organized, the assemblies and network are loose and dynamic. They contain transiently-associated multiprotein complexes which are often mediated by scaffolding proteins. They are also typically anchored in the membrane, and their continuum may span the cell. IQGAP1 scaffolding protein which binds proteins including Raf, calmodulin, Mek, Erk, actin, and tens more, with actin shaping B-cell (and likely other) membrane-anchored nanoclusters and allosterically polymerizing in dynamic cytoskeleton formation, and Raf anchoring in the membrane along with Ras, provides a striking example. The multivalent network of dynamic proteins and lipids, with specific interactions forming and breaking, can be viewed as endowing gel-like properties. Collectively, this reasons that efficient, productive and reliable cell signaling takes place primarily through transient, preorganized and cooperative protein-protein interactions spanning the cell rather than stochastic, diffusion-controlled processes. PMID:25046855

  10. Observation of spatial propagation of amyloid assembly from single nuclei

    PubMed Central

    Knowles, Tuomas P. J.; White, Duncan A.; Abate, Adam R.; Agresti, Jeremy J.; Cohen, Samuel I. A.; Sperling, Ralph A.; De Genst, Erwin J.; Dobson, Christopher M.; Weitz, David A.

    2011-01-01

    The crucial early stages of amyloid growth, in which normally soluble proteins are converted into fibrillar nanostructures, are challenging to study using conventional techniques yet are critical to the protein aggregation phenomena implicated in many common pathologies. As with all nucleation and growth phenomena, it is difficult to track individual nuclei in traditional macroscopic experiments, which probe the overall temporal evolution of the sample, but do not yield detailed information on the primary nucleation step as they mix independent stochastic events into an ensemble measurement. To overcome this limitation, we have developed microdroplet assays enabling us to detect single primary nucleation events and to monitor their subsequent spatial as well as temporal evolution, both of which we find to be determined by secondary nucleation phenomena. By deforming the droplets to high aspect ratio, we visualize in real-time propagating waves of protein assembly emanating from discrete primary nucleation sites. We show that, in contrast to classical gelation phenomena, the primary nucleation step is characterized by a striking dependence on system size, and the filamentous protein self-assembly process involves a highly nonuniform spatial distribution of aggregates. These findings deviate markedly from the current picture of amyloid growth and uncover a general driving force, originating from confinement, which, together with biological quality control mechanisms, helps proteins remain soluble and therefore functional in nature. PMID:21876182

  11. EVALUATING MULTIPLE STRESSORS IN LOGGERHEAD SEA TURTLES: DEVELOPING A TWO-SEX SPATIALLY EXPLICIT MODEL

    EPA Science Inventory

    North Atlantic loggerhead sea turtle (Caretta caretta L.) populations respond to the integrated effects of multiple environmental stressors. Environmental stressors often occur in spatially distinct frameworks and affect distinct age classes, sexes, and subpopulations differentia...

  12. A SPATIALLY EXPLICIT HIERARCHICAL APPROACH TO MODELING COMPLEX ECOLOGICAL SYSTEMS: THEORY AND APPLICATIONS. (R827676)

    EPA Science Inventory

    Ecological systems are generally considered among the most complex because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. Hierarchy theory, as well as empirical evidence, suggests that comp...

  13. REVIEW OF SIMULATION METHODS FOR SPATIALLY-EXPLICIT POPULATION-LEVEL RISK ASSESSMENT

    EPA Science Inventory

    Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

  14. Use of spatially explicit physicochemical data to measure downstream impacts of headwater stream disturbance

    EPA Science Inventory

    Regulatory agencies need methods to quantify the influence of headwater streams on downstream water quality as a result of litigation surrounding jurisdictional criteria and the influence of mountaintop removal coal mining activities. We collected comprehensive, spatially-referen...

  15. Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States

    USGS Publications Warehouse

    Sohl, Terry L.; Sayler, Kristi L.; Bouchard, Michelle; Reker, Ryan R.; Friesz, Aaron M.; Bennett, Stacie L.; Sleeter, Benjamin M.; Sleeter, Rachel R.; Wilson, Tamara; Knuppe, Michelle; Van Hofwegen, Travis

    2014-01-01

    Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on 5 Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the Forecasting Scenarios of Land-use Change (FORE-SCE) model. Four spatially explicit datasets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of 10 anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting have relatively lower mean stand ages compared to those with less 15 forest cutting. Stand ages differ substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, 20 biodiversity, climate and weather variability, hydrologic change, and other ecological processes.

  16. Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States.

    PubMed

    Sohl, Terry L; Sayler, Kristi L; Bouchard, Michelle A; Reker, Ryan R; Friesz, Aaron M; Bennett, Stacie L; Sleeter, Benjamin M; Sleeter, Rachel R; Wilson, Tamara; Soulard, Chris; Knuppe, Michelle; Van Hofwegen, Travis

    2014-07-01

    Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the forecasting scenarios of land-use change (FORE-SCE) model. Four spatially explicit data sets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both the proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting had relatively lower mean stand ages compared to those with less forest cutting. Stand ages differed substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand-age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, biodiversity, climate and weather variability, hydrologic change, and other ecological processes. PMID:25154094

  17. The Value of Simple Models: Performance of a Spatially-explicit Seasonal Model for Valuing Water Provisioning (InVEST)

    NASA Astrophysics Data System (ADS)

    Hamel, P.; Guswa, A. J.; Wemple, B. C.; Mohammed, I. N.; Sharp, R.

    2015-12-01

    Valuing hydrologic ecosystem services (ES) requires a truly integrated approach, linking knowledge of hydrologic processes to that of the socio-economic context of a region. Although both the hydrological and socio-economic dimensions are complex, practitioners need simple and credible models to address pressing questions brought by global change. We developed such a model for the supply, service, and value of water provisioning; available to the ES community through the open-source InVEST (Integrated Valuation of Ecosytem Services and Trade-offs) software. The model is characterized by i) low data requirements, with the aim of being applied in data-scarce environments; ii) spatially-explicit outputs, to easily address spatial planning questions; iii) a seasonal time-step, representing a compromise between data knowledge and ability to address season-dependent questions (water supply for irrigation, hydropower production); iv) explicit representation of beneficiaries, to facilitate valuation of the provisioning service for different groups; v) flexible valuation framework, to address a variety of ES questions. The model theory is based on the recent advances in hydrology, using the "limits" concept for water balance modeling and spatial indices for subsurface and surface runoff. We tested the model performance in the Mad River catchment, Vermont, USA, comparing its results with the data-intensive RHESSys model for two typical ES questions: the identification of hotspots of service and valuation of the provisioning service for hydropower production. Uncertainty analyses, including sensitivity analyses and Monte Carlo analyses, were performed to quantify uncertainty in both hydrological outputs and service provisioning, and improve guidance for users. We present these results through a range of spatial and non-spatial outputs, emphasizing the importance of results interpretation and visualization for ES assessments.

  18. Spatially-explicit risk profiling of Plasmodium falciparum infections at a small scale: a geostatistical modelling approach

    PubMed Central

    Silué, Kigbafori D; Raso, Giovanna; Yapi, Ahoua; Vounatsou, Penelope; Tanner, Marcel; N'Goran, Eliézer K; Utzinger, Jürg

    2008-01-01

    Background There is a renewed political will and financial support to eradicate malaria. Spatially-explicit risk profiling will play an important role in this endeavour. Patterns of Plasmodium falciparum infection prevalence were examined among schoolchildren in a highly malaria-endemic area. Methods A questionnaire was administered and finger prick blood samples collected from 3,962 children, aged six to 16 years, attending 55 schools in a rural part of western Côte d'Ivoire. Information was gathered from the questionnaire on children's socioeconomic status and the use of bed nets for the prevention of malaria. Blood samples were processed with standardized, quality-controlled methods for diagnosis of Plasmodium spp. infections. Environmental data were obtained from satellite images and digitized maps. Bayesian variogram models for spatially-explicit risk modelling of P. falciparum infection prevalence were employed, assuming for stationary and non-stationary spatial processes. Findings The overall prevalence of P. falciparum infection was 64.9%, ranging between 34.0% and 91.9% at the unit of the school. Risk factors for a P. falciparum infection included age, socioeconomic status, not sleeping under a bed net, distance to health care facilities and a number of environmental features (i.e. normalized difference vegetation index, rainfall and distance to rivers). After taking into account spatial correlation only age remained significant. Non-stationary models performed better than stationary models. Conclusion Spatial risk profiling of P. falciparum prevalence data provides a useful tool for targeting malaria control intervention, and hence will play a role in the quest of local elimination and ultimate eradication of the disease. PMID:18570685

  19. USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

    EPA Science Inventory

    We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

  20. A Watershed-based spatially-explicit demonstration of an Integrated Environmental Modeling Framework for Ecosystem Services in the Coal River Basin (WV, USA)

    EPA Science Inventory

    We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quant...

  1. Deconstructing Building Blocks: Preschoolers' Spatial Assembly Performance Relates to Early Mathematical Skills

    ERIC Educational Resources Information Center

    Verdine, Brian N.; Golinkoff, Roberta M.; Hirsh-Pasek, Kathryn; Newcombe, Nora S.; Filipowicz, Andrew T.; Chang, Alicia

    2014-01-01

    This study focuses on three main goals: First, 3-year-olds' spatial assembly skills are probed using interlocking block constructions (N = 102). A detailed scoring scheme provides insight into early spatial processing and offers information beyond a basic accuracy score. Second, the relation of spatial assembly to early mathematical skills…

  2. Spatially explicit West Nile virus risk modeling in Santa Clara County, California

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A previously created Geographic Information Systems model designed to identify regions of West Nile virus (WNV) transmission risk is tested and calibrated in Santa Clara County, California. American Crows that died from WNV infection in 2005 provide the spatial and temporal ground truth. Model param...

  3. Spatially Explicit West Nile Virus Risk Modeling in Santa Clara County, CA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A geographic information systems model designed to identify regions of West Nile virus (WNV) transmission risk was tested and calibrated with data collected in Santa Clara County, California. American Crows that died from WNV infection in 2005, provided spatial and temporal ground truth. When the mo...

  4. Dynamic spatially-explicit mass-balance modeling for targeted watershed phosphorus management II: Model Application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cost-effective nonpoint source phosphorus (P) control should target the land areas at greatest risk for P loss. We combined mass-balance modeling and geographic analysis to identify and map high-risk areas for P export by integrating long-term P input/output accounting with spatially variable physi...

  5. Asymptotically exact analysis of stochastic metapopulation dynamics with explicit spatial structure.

    PubMed

    Ovaskainen, Otso; Cornell, Stephen J

    2006-02-01

    We describe a mathematically exact method for the analysis of spatially structured Markov processes. The method is based on a systematic perturbation expansion around the deterministic, non-spatial mean-field theory, using the theory of distributions to account for space and the underlying stochastic differential equations to account for stochasticity. As an example, we consider a spatial version of the Levins metapopulation model, in which the habitat patches are distributed in the d-dimensional landscape Rd in a random (but possibly correlated) manner. Assuming that the dispersal kernel is characterized by a length scale L, we examine how the behavior of the metapopulation deviates from the mean-field model for a finite but large L. For example, we show that the equilibrium fraction of occupied patches is given by p(0)+c/L(d)+O(L(-3d/2)), where p(0) is the equilibrium state of the Levins model and the constant c depends on p(0), the dispersal kernel, and the structure of the landscape. We show that patch occupancy can be increased or decreased by spatial structure, but is always decreased by stochasticity. Comparison with simulations show that the analytical results are not only asymptotically exact (as L-->infinity), but a good approximation also when L is relatively small. PMID:16246386

  6. Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long...

  7. Colonization history of the Swiss Rhine basin by the bullhead (Cottus gobio): inference under a Bayesian spatially explicit framework.

    PubMed

    Neuenschwander, Samuel; Largiadèr, Carlo R; Ray, Nicolas; Currat, Mathias; Vonlanthen, Pascal; Excoffier, Laurent

    2008-02-01

    The present distribution of freshwater fish in the Alpine region has been strongly affected by colonization events occurring after the last glacial maximum (LGM), some 20,000 years ago. We use here a spatially explicit simulation framework to model and better understand their colonization dynamics in the Swiss Rhine basin. This approach is applied to the European bullhead (Cottus gobio), which is an ideal model organism to study fish past demographic processes since it has not been managed by humans. The molecular diversity of eight sampled populations is simulated and compared to observed data at six microsatellite loci under an approximate Bayesian computation framework to estimate the parameters of the colonization process. Our demographic estimates fit well with current knowledge about the biology of this species, but they suggest that the Swiss Rhine basin was colonized very recently, after the Younger Dryas some 6600 years ago. We discuss the implication of this result, as well as the strengths and limits of the spatially explicit approach coupled to the approximate Bayesian computation framework. PMID:18194169

  8. SEHR-ECHO v1.0: a Spatially-Explicit Hydrologic Response model for ecohydrologic applications

    NASA Astrophysics Data System (ADS)

    Schaefli, B.; Nicótina, L.; Imfeld, C.; Da Ronco, P.; Bertuzzo, E.; Rinaldo, A.

    2014-03-01

    This paper presents the Spatially-Explicit Hydrologic Response (SEHR) model developed at the Laboratory of Ecohydrology of the Ecole Polytechnique Fédérale de Lausanne for the simulation of hydrological processes at the catchment scale. The key concept of the model is the formulation of water transport by geomorphologic travel time distributions through gravity-driven transitions among geomorphic states: the mobilization of water (and possibly dissolved solutes) is simulated at the sub-catchment scale and the resulting responses are convolved with the travel paths distribution within the river network to obtain the hydrologic response at the catchment outlet. The model thus breaks down the complexity of the hydrologic response into an explicit geomorphological combination of dominant spatial patterns of precipitation input and of hydrologic process controls. Nonstationarity and nonlinearity effects are tackled through soil moisture dynamics in the active soil layer. We present here the basic model set-up for precipitation-runoff simulation. The performance of the model is illustrated for a snow-dominated catchment in Switzerland with a small glacier cover.

  9. Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

    PubMed Central

    Kitchen, James L.; Allaby, Robin G.

    2013-01-01

    Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

  10. Relative role of deterministic and stochastic determinants of soil animal community: a spatially explicit analysis of oribatid mites.

    PubMed

    Caruso, Tancredi; Taormina, Mauro; Migliorini, Massimo

    2012-01-01

    1. Ecologists are debating the relative role of deterministic and stochastic determinants of community structure. Although the high diversity and strong spatial structure of soil animal assemblages could provide ecologists with an ideal ecological scenario, surprisingly little information is available on these assemblages. 2. We studied species-rich soil oribatid mite assemblages from a Mediterranean beech forest and a grassland. We applied multivariate regression approaches and analysed spatial autocorrelation at multiple spatial scales using Moran's eigenvectors. Results were used to partition community variance in terms of the amount of variation uniquely accounted for by environmental correlates (e.g. organic matter) and geographical position. Estimated neutral diversity and immigration parameters were also applied to a soil animal group for the first time to simulate patterns of community dissimilarity expected under neutrality, thereby testing neutral predictions. 3. After accounting for spatial autocorrelation, the correlation between community structure and key environmental parameters disappeared: about 40% of community variation consisted of spatial patterns independent of measured environmental variables such as organic matter. Environmentally independent spatial patterns encompassed the entire range of scales accounted for by the sampling design (from tens of cm to 100 m). This spatial variation could be due to either unmeasured but spatially structured variables or stochastic drift mediated by dispersal. Observed levels of community dissimilarity were significantly different from those predicted by neutral models. 4. Oribatid mite assemblages are dominated by processes involving both deterministic and stochastic components and operating at multiple scales. Spatial patterns independent of the measured environmental variables are a prominent feature of the targeted assemblages, but patterns of community dissimilarity do not match neutral predictions

  11. Incorporating spatially explicit crown light competition into a model of canopy transpiration

    NASA Astrophysics Data System (ADS)

    Loranty, M. M.; Mackay, D. S.; Roberts, D. E.; Ewers, B. E.; Kruger, E. L.; Traver, E.

    2006-12-01

    Stomatal conductance parameterized in a transpiration model has been shown to vary spatially for aspen ( Populus tremuloides) and alder (Alnus incana) growing along a moisture gradient. We hypothesized that competition for light within the canopy would explain some of this variation. Sap flux data was collected over 10 days in 2004, and 30 days in 2005 at a 1.5 ha site near the WLEF AmeriFlux tower in the Chequmegon National Forest near Park Falls, Wisconsin. We used inverse modeling with the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to estimate values of GSref for individual trees. Competition data for individual aspen sampled for sap flux was collected in August 2006. The number, height, DBH, and location of all competitors within 5 meters of each flux tree were recorded. Preliminary geostatistical analysis indicates that the number of competitor trees varies spatially for aspen. We hypothesize that height and species specific crown characteristics of competitor trees will have a spatially variable affect on transpiration via light attenuation. Furthermore, a simple light competition term will be able to incorporate this variability into the TREES transpiration model.

  12. Spatially explicit control of invasive species using a reaction-diffusion model

    USGS Publications Warehouse

    Bonneau, Mathieu; Johnson, Fred A.; Romagosa, Christina M.

    2016-01-01

    Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction–diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction–diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction–diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.

  13. Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

    USGS Publications Warehouse

    Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

    2015-01-01

    Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

  14. Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

    2014-07-01

    The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

  15. A Spatial Explicit Watershed Model of Water and Tritium Fluxes in the Vadose Zone

    NASA Astrophysics Data System (ADS)

    Rebel, K. T.; Riha, S. J.; Karssenberg, D.; Hitchcock, D. R.

    2002-05-01

    A simple, spatial, dynamic model of water uptake by trees in a watershed was developed using the PCRaster Environmental Modelling Software. This software provides a computer language especially developed for modeling temporal and spatial processes in a GIS, and is well suited for the development of dynamic ecological and hydrological models. The model we developed is grid based and has vertical layering. The water budget is calculated for each grid cell in every layer for every time step. Change in soil water storage is obtained by adding the incoming water and subtracting the outgoing water in each grid cell soil layer. When a soil layer in a grid cell exceeds field capacity, water can potentially flow to the grid cell in the layer underneath. However, when soil water reaches saturation, water can flow to the grid in the direction of the local drainage. Potential evapotranspiration sets the upper limit of water uptake in this model. Actual transpiration falls below potential evapotranspiration as soil water content approaches the permanent wilting point. The spatial distribution of the water budget components is available for every time step. We are using this model to simulate water uptake and subsurface lateral movement in a coniferous and a mixed hardwood - coniferous forest on Coastal Plain soils of the southern United States. These soils are characteristically sand overlying slowly permeable clays found at depths of 30 to 200 cm. Temporary perched water tables can develop. Twenty-five hectares of the watershed we are modeling is periodically irrigated with tritium enriched water, which we use to validate the model. We use this model to optimize irrigation and evaluate the amount of tritium entering the atmosphere due to evapotranspiration.

  16. A theory of forest dynamics: Spatially explicit models and issues of scale

    NASA Technical Reports Server (NTRS)

    Pacala, S.

    1990-01-01

    Good progress has been made in the first year of DOE grant (number sign) FG02-90ER60933. The purpose of the project is to develop and investigate models of forest dynamics that apply across a range of spatial scales. The grant is one third of a three-part project. The second third was funded by the NSF this year and is intended to provide the empirical data necessary to calibrate and test small-scale (less than or equal to 1000 ha) models. The final third was also funded this year (NASA), and will provide data to calibrate and test the large-scale features of the models.

  17. Spatially explicit scenario analysis for hydrologic services in an urbanizing agricultural watershed

    NASA Astrophysics Data System (ADS)

    Qiu, J.; Booth, E.; Carpenter, S. R.; Turner, M.

    2013-12-01

    The sustainability of hydrologic services (benefits to people generated by terrestrial ecosystem effects on freshwater) is challenged by changes in climate and land use. Despite the importance of hydrologic services, few studies have investigated how the provision of ecosystem services related to freshwater quantity and quality may vary in magnitude and spatial pattern for alternative future trajectories. Such analyses may provide useful information for sustaining freshwater resources in the face of a complex and uncertain future. We analyzed the supply of multiple hydrologic services from 2010 to 2070 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) What are the potential trajectories for the supply of hydrologic services under contrasting but plausible future scenarios? (ii) Where on the landscape is the delivery of hydrologic services most vulnerable to future changes? The Nested Watershed scenario represents extreme climate change (warmer temperatures and more frequent extreme events) and a concerted response from institutions, whereas in the Investment in Innovation scenario, climate change is less severe and technological innovations play a major role. Despite more extreme climate in the Nested Watershed scenario, all hydrologic services (i.e., freshwater supply, surface water quality, flood regulation) were maintained or enhanced (~30%) compared to the 2010 baseline, by strict government interventions that prioritized freshwater resources. Despite less extreme climate in the Investment in Innovation scenario and advances in green technology, only surface water quality and flood regulation were maintained or increased (~80%); freshwater supply declined by 25%, indicating a potential future tradeoff between water quality and quantity. Spatially, the locations of greatest vulnerability (i.e., decline) differed by service and among scenarios. In the Nested Watershed scenario, although

  18. Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.

    2007-01-01

    Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

  19. Spatial explicit assessment of rural land abandonment in the Mediterranean area

    NASA Astrophysics Data System (ADS)

    Weissteiner, Christof J.; Boschetti, Mirco; Böttcher, Kristin; Carrara, Paola; Bordogna, Gloria; Brivio, Pietro Alessandro

    2011-10-01

    This study adopts the "syndrome approach", originally defined by the Potsdam Institute for Climate Impact Research (PIK), ( Downing et al., 2002) to assess and map rural land abandonment (RLA), that occurred during the period 1990-2005 within the wider Mediterranean area. The basic idea behind the syndrome approach is to describe change processes by archetypical, dynamic, and co-evolutionary patterns of civilization-nature interactions. In the frame of the Rural Exodus Syndrome the RLA can be interpreted as the occurrence of environmental degradation through the abandonment of traditional agricultural practices. Multi-source spatial data, including biophysical-related variables mainly derived from Earth Observation as well as socio-economical GIS-based data, were used to define proxies for expected underlying processes and drivers of the mentioned syndrome. The analysis of data is rooted in the fuzzy set theory and approximate reasoning techniques which allows for the handling of uncertain and imprecise knowledge of environmental systems. Generalized Conjunction/Disjunction operators (GCD) were applied to compute intermediate indicator score maps representing the conditions that may affect the RLA, and a bipolar operator was used to combine mandatory and favouring conditions with the aim of generating a RLA indicator. The indicator expresses the detailed location and severity, or degree, of the syndrome. The Northern Mediterranean was generally found to suffer from RLA to a distinctly higher degree than the Southern Mediterranean. Reported abandonment studies from the existing literature, the European CORINE land cover map, and the Less Favoured Areas (LFA) map all supported the findings by confirming plausibility through convergence of evidence from comparisons with different types of independent information. This spatially highly-detailed results obtained may be of particular interest to policy and decision makers involved in rural development planning in the

  20. Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management

    USGS Publications Warehouse

    Coates, Peter S.; Casazza, Michael L.; Ricca, Mark A.; Brussee, Brianne E.; Blomberg, Erik J.; Gustafson, K. Benjamin; Overton, Cory T.; Davis, Dawn M.; Niell, Lara E.; Espinosa, Shawn P.; Gardner, Scott C.; Delehanty, David J.

    2016-01-01

    Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management. Greater sage-grouse Centrocercus urophasianus, hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information. Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes. We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across

  1. Reducing fertilizer-nitrogen losses from rowcrop landscapes: Insights and implications from a spatially explicit watershed model

    USGS Publications Warehouse

    McLellan, Eileen; Schilling, Keith; Robertson, Dale

    2015-01-01

    We present conceptual and quantitative models that predict changes in fertilizer-derived nitrogen delivery from rowcrop landscapes caused by agricultural conservation efforts implemented to reduce nutrient inputs and transport and increase nutrient retention in the landscape. To evaluate the relative importance of changes in the sources, transport, and sinks of fertilizer-derived nitrogen across a region, we use the spatially explicit SPAtially Referenced Regression On Watershed attributes watershed model to map the distribution, at the small watershed scale within the Upper Mississippi-Ohio River Basin (UMORB), of: (1) fertilizer inputs; (2) nutrient attenuation during delivery of those inputs to the UMORB outlet; and (3) nitrogen export from the UMORB outlet. Comparing these spatial distributions suggests that the amount of fertilizer input and degree of nutrient attenuation are both important in determining the extent of nitrogen export. From a management perspective, this means that agricultural conservation efforts to reduce nitrogen export would benefit by: (1) expanding their focus to include activities that restore and enhance nutrient processing in these highly altered landscapes; and (2) targeting specific types of best management practices to watersheds where they will be most valuable. Doing so successfully may result in a shift in current approaches to conservation planning, outreach, and funding.

  2. Multi-variate spatial explicit constraining of a large scale hydrological model

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

    2016-04-01

    model parameters leads to considerable changes in the partitioning of precipitation into runoff components, while maintaining total runoff estimates unaltered. Objective functions that take into account the spatial patters of GRACE estimates perform better than those constrained only against discharge. Improvements in parameter estimation based on multiple data sources will enhance the community efforts towards spatially consistent large scale seamless predictions. Reference: Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger, S., Schäfer, D., Schrön, M., Samaniego, L. (2016): Multiscale and multivariate evaluation of water fluxes and states over European river basins, J. Hydrometeorol., 17, 287-307, doi: 10.1175/JHM-D-15-0054.1.

  3. Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region

    USGS Publications Warehouse

    Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.; Crimmins, Shawn M.

    2015-01-01

    Knowledge of factors influencing animal abundance is important to wildlife biologists developing management plans. This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird,Agelaius phoeniceus; yellow-headed blackbird, Xanthocephalus xanthocephalus; common grackle, Quiscalus quiscula) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader

  4. Impacts of impervious surface expansion on soil organic carbon - a spatially explicit study

    NASA Astrophysics Data System (ADS)

    Yan, Yan; Kuang, Wenhui; Zhang, Chi; Chen, Chunbo

    2015-12-01

    The rapid expansion of impervious surface areas (ISA) threatens soil organic carbon (SOC) pools in urbanized areas globally. The paucity of field observations on SOC under ISA (SOCISA), especially in dryland areas has limited our ability to assess the ecological impacts of ISA expansion. Based on systematically measured SOCISA (0-80 cm depth) of a dryland city, and land-use and land-cover change data derived from remotely sensed data, we investigated the magnitude and vertical/horizontal patterns of SOCISA and mapped the impact of ISA expansion on SOC storage. The mean SOCISA in the city was 5.36 ± 0.51 kg C m-2, lower than that observed in humid cities but much higher than that assumed in many regional carbon assessments. SOCISA decreased linearly as the soil depth or the horizontal distance from the open area increased. SOCISA accounted for over half of the city’s SOC stock, which decreased by 16% (primarily in the converted croplands) because of ISA expansion from 1990 to 2010. The impacts of the ISA expansion varied spatially, depending on the land- use and converted land-cover type.

  5. Impacts of impervious surface expansion on soil organic carbon--a spatially explicit study.

    PubMed

    Yan, Yan; Kuang, Wenhui; Zhang, Chi; Chen, Chunbo

    2015-01-01

    The rapid expansion of impervious surface areas (ISA) threatens soil organic carbon (SOC) pools in urbanized areas globally. The paucity of field observations on SOC under ISA (SOCISA), especially in dryland areas has limited our ability to assess the ecological impacts of ISA expansion. Based on systematically measured SOCISA (0-80 cm depth) of a dryland city, and land-use and land-cover change data derived from remotely sensed data, we investigated the magnitude and vertical/horizontal patterns of SOCISA and mapped the impact of ISA expansion on SOC storage. The mean SOCISA in the city was 5.36 ± 0.51 kg C m(-2), lower than that observed in humid cities but much higher than that assumed in many regional carbon assessments. SOCISA decreased linearly as the soil depth or the horizontal distance from the open area increased. SOCISA accounted for over half of the city's SOC stock, which decreased by 16% (primarily in the converted croplands) because of ISA expansion from 1990 to 2010. The impacts of the ISA expansion varied spatially, depending on the land- use and converted land-cover type. PMID:26642831

  6. A Spatially Explicit Approach for Evaluating Relationships among Coastal Cutthroat, Habitat, and Disturbance in Headwater Streams

    NASA Astrophysics Data System (ADS)

    Gresswell, R. E.; Bateman, D. S.; Torgersen, C. E.; Guy, T. J.; Hendricks, S. R.; Wofford, J. E.

    2005-05-01

    Headwater stream systems are complex networks that form a physicochemical template governing the persistence of aquatic species such as coastal cutthroat trout. Individual portions of the network can function as conduits or receptacles for sediments, wood, and nutrients from terrestrial areas. Temporal and spatial changes in the delivery of these constituents can substantially alter the habitat template and its ability to support this native fish. Our study of 40 mid-sized watersheds (500 - 1,500 ha) in western Oregon is providing new insights into the factors affecting the distribution of coastal cutthroat trout within, and among, headwater stream networks. For example, data suggest that coastal cutthroat trout move throughout the accessible portions of headwater streams for reproductive, feeding, and refuge purposes. Fish congregate in these areas and form local populations that may exhibit unique phenotypic and genetic attributes. At times, coastal cutthroat trout move into larger downstream portions of the network where they may contribute to the persistence and genetic character of anadromous or local potamodromous assemblages. Variation in distribution patterns among watersheds reflects diverse environments and selective factors, such as geology, geomorphology, climate, and land-management history. Our research findings suggest that human activities that impede movement among suitable habitat patches can have lasting consequences for local assemblages of coastal cutthroat trout and may ultimately affect persistence.

  7. An open and extensible framework for spatially explicit land use change modelling: the lulcc R package

    NASA Astrophysics Data System (ADS)

    Moulds, S.; Buytaert, W.; Mijic, A.

    2015-10-01

    We present the lulcc software package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment.

  8. Impacts of impervious surface expansion on soil organic carbon – a spatially explicit study

    PubMed Central

    Yan, Yan; Kuang, Wenhui; Zhang, Chi; Chen, Chunbo

    2015-01-01

    The rapid expansion of impervious surface areas (ISA) threatens soil organic carbon (SOC) pools in urbanized areas globally. The paucity of field observations on SOC under ISA (SOCISA), especially in dryland areas has limited our ability to assess the ecological impacts of ISA expansion. Based on systematically measured SOCISA (0–80 cm depth) of a dryland city, and land-use and land-cover change data derived from remotely sensed data, we investigated the magnitude and vertical/horizontal patterns of SOCISA and mapped the impact of ISA expansion on SOC storage. The mean SOCISA in the city was 5.36 ± 0.51 kg C m−2, lower than that observed in humid cities but much higher than that assumed in many regional carbon assessments. SOCISA decreased linearly as the soil depth or the horizontal distance from the open area increased. SOCISA accounted for over half of the city’s SOC stock, which decreased by 16% (primarily in the converted croplands) because of ISA expansion from 1990 to 2010. The impacts of the ISA expansion varied spatially, depending on the land- use and converted land-cover type. PMID:26642831

  9. A Spatially Explicit Model of Functional Connectivity for the Endangered Przewalski’s Gazelle (Procapra przewalskii) in a Patchy Landscape

    PubMed Central

    Li, Chunlin; Jiang, Zhigang; Fang, Hongxia; Li, Chunwang

    2013-01-01

    Background Habitat fragmentation, associated with human population expansion, impedes dispersal, reduces gene flow and aggravates inbreeding in species on the brink of extinction. Both scientific and conservation communities increasingly realize that maintaining and restoring landscape connectivity is of vital importance in biodiversity conservation. Prior to any conservation initiatives, it is helpful to present conservation practitioners with a spatially explicit model of functional connectivity for the target species or landscape. Methodology/Principal Findings Using Przewalski’s gazelle (Procapra przewalskii) as a model of endangered ungulate species in highly fragmented landscape, we present a model providing spatially explicit information to inform the long-term preservation of well-connected metapopulations. We employed a Geographic Information System (GIS) and expert-literature method to create a habitat suitability map, to identify potential habitats and to delineate a functional connectivity network (least-cost movement corridors and paths) for the gazelle. Results indicated that there were limited suitable habitats for the gazelle, mainly found to the north and northwest of the Qinghai Lake where four of five potential habitat patches were identified. Fifteen pairs of least-cost corridors and paths were mapped connecting eleven extant populations and two neighboring potential patches. The least-cost paths ranged from 0.2 km to 26.8 km in length (averaging 12.4 km) and were all longer than corresponding Euclidean distances. Conclusions/Significance The model outputs were validated and supported by the latest findings in landscape genetics of the species, and may provide impetus for connectivity conservation programs. Dispersal barriers were examined and appropriate mitigation strategies were suggested. This study provides conservation practitioners with thorough and visualized information to reserve the landscape connectivity for Przewalski’s gazelle

  10. Modeling spatially- and temporally-explicit water stress indices for use in life cycle assessment

    NASA Astrophysics Data System (ADS)

    Scherer, L.; Venkatesh, A.; Karuppiah, R.; Usadi, A.; Pfister, S.; Hellweg, S.

    2013-12-01

    Water scarcity is a regional issue in many areas across the world, and can affect human health and ecosystems locally. Water stress indices (WSIs) have been developed as quantitative indicators of such scarcities - examples include the Falkenmark indicator, Social Water Stress Index, and the Water Supply Stress Index1. Application of these indices helps us understand water supply and demand risks for multiple users, including those in the agricultural, industrial, residential and commercial sectors. Pfister et al.2 developed a method to calculate WSIs that were used to estimate characterization factors (CFs) in order to quantify environmental impacts of freshwater consumption within a life cycle assessment (LCA) framework. Global WSIs were based on data from the WaterGAP model3, and presented as annual averages for watersheds. Since water supply and demand varies regionally and temporally, the resolution used in Pfister et al. does not effectively differentiate between seasonal and permanent water scarcity. This study aims to improve the temporal and spatial resolution of the water scarcity calculations used to estimate WSIs and CFs. We used the Soil and Water Assessment Tool (SWAT)4 hydrological model to properly simulate water supply in different world regions with high spatial and temporal resolution, and coupled it with water use data from WaterGAP3 and Pfister et al.5. Input data to SWAT included weather, land use, soil characteristics and a digital elevation model (DEM), all from publicly available global data sets. Potential evapotranspiration, which affects water supply, was determined using an improved Priestley-Taylor approach. In contrast to most other hydrological studies, large reservoirs, water consumption and major water transfers were simulated. The model was calibrated against observed monthly discharge, actual evapotranspiration, and snow water equivalents wherever appropriate. Based on these simulations, monthly WSIs were calculated for a few

  11. Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

    USGS Publications Warehouse

    Carr, Joel; D'Odorico, Paul; McGlathery, Karen; Wiberg, Patricia L.

    2016-01-01

    In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

  12. Crucial nesting habitat for gunnison sage-grouse: A spatially explicit hierarchical approach

    USGS Publications Warehouse

    Aldridge, C.L.; Saher, D.J.; Childers, T.M.; Stahlnecker, K.E.; Bowen, Z.H.

    2012-01-01

    Gunnison sage-grouse (Centrocercus minimus) is a species of special concern and is currently considered a candidate species under Endangered Species Act. Careful management is therefore required to ensure that suitable habitat is maintained, particularly because much of the species' current distribution is faced with exurban development pressures. We assessed hierarchical nest site selection patterns of Gunnison sage-grouse inhabiting the western portion of the Gunnison Basin, Colorado, USA, at multiple spatial scales, using logistic regression-based resource selection functions. Models were selected using Akaike Information Criterion corrected for small sample sizes (AIC c) and predictive surfaces were generated using model averaged relative probabilities. Landscape-scale factors that had the most influence on nest site selection included the proportion of sagebrush cover >5%, mean productivity, and density of 2 wheel-drive roads. The landscape-scale predictive surface captured 97% of known Gunnison sage-grouse nests within the top 5 of 10 prediction bins, implicating 57% of the basin as crucial nesting habitat. Crucial habitat identified by the landscape model was used to define the extent for patch-scale modeling efforts. Patch-scale variables that had the greatest influence on nest site selection were the proportion of big sagebrush cover >10%, distance to residential development, distance to high volume paved roads, and mean productivity. This model accurately predicted independent nest locations. The unique hierarchical structure of our models more accurately captures the nested nature of habitat selection, and allowed for increased discrimination within larger landscapes of suitable habitat. We extrapolated the landscape-scale model to the entire Gunnison Basin because of conservation concerns for this species. We believe this predictive surface is a valuable tool which can be incorporated into land use and conservation planning as well the assessment of

  13. Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

    NASA Astrophysics Data System (ADS)

    Carr, Joel A.; D'Odorico, Paolo; McGlathery, Karen J.; Wiberg, Patricia L.

    2016-07-01

    In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

  14. Deconstructing building blocks: preschoolers' spatial assembly performance relates to early mathematical skills.

    PubMed

    Verdine, Brian N; Golinkoff, Roberta M; Hirsh-Pasek, Kathryn; Newcombe, Nora S; Filipowicz, Andrew T; Chang, Alicia

    2014-01-01

    This study focuses on three main goals: First, 3-year-olds' spatial assembly skills are probed using interlocking block constructions (N = 102). A detailed scoring scheme provides insight into early spatial processing and offers information beyond a basic accuracy score. Second, the relation of spatial assembly to early mathematical skills was evaluated. Spatial skill independently predicted a significant amount of the variability in concurrent mathematical performance. Finally, the relation between spatial assembly skill and socioeconomic status (SES), gender, and parent-reported spatial language was examined. While children's performance did not differ by gender, lower SES children were already lagging behind higher SES children in block assembly. Furthermore, lower SES parents reported using significantly fewer spatial words with their children. PMID:24112041

  15. Deconstructing Building Blocks: Preschoolers' Spatial Assembly Performance Relates to Early Mathematics Skills

    PubMed Central

    Verdine, Brian N.; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn; Newcombe, Nora S.; Filipowicz, Andrew T.; Chang, Alicia

    2013-01-01

    This study focuses on three main goals: First, 3-year-olds' spatial assembly skills are probed using interlocking block constructions (N = 102). A detailed scoring scheme provides insight into early spatial processing and offers information beyond a basic accuracy score. Second, the relation of spatial assembly to early mathematics skills was evaluated. Spatial skill independently predicted a significant amount of the variability in concurrent mathematics performance. Finally, the relationship between spatial assembly skill and socioeconomic status, gender, and parent-reported spatial language was examined. While children's performance did not differ by gender, lower-SES children were already lagging behind higher-SES children in block assembly. Furthermore, lower-SES parents reported using significantly fewer spatial words with their children. PMID:24112041

  16. Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

    USGS Publications Warehouse

    Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang

    2012-01-01

    The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.

  17. A Spatially-Explicit Modeling Approach to Examine the Interaction of Reproductive Traits and Landscape Characteristics on Arctic Shrub Expansion

    NASA Astrophysics Data System (ADS)

    Naito, A. T.; Cairns, D. M.; Feldman, R. M.; Grant, W. E.

    2014-12-01

    Shrub expansion is one of the most recognized components of terrestrial Arctic change. While experimental work has provided valuable insights into its fine-scale drivers and implications, the contribution of shrub reproductive characteristics to their spatial patterns is poorly understood at broader scales. Building upon our previous work in river valleys in northern Alaska, we developed a C#-based spatially-explicit model that simulates historic landscape-scale shrub establishment between the 1970s and the late 2000s on a yearly time-step while accounting for parameters relating to different reproduction modes (clonal development with and without the "mass effect" and short-distance dispersal), as well as the presence and absence of the interaction of hydrologic constraints using the topographic wetness index. We examined these treatments on floodplains, valley slopes, and interfluves in the Ayiyak, Colville, and Kurupa River valleys. After simulating 30 landscape realizations using each parameter combination, we quantified the spatial characteristics (patch density, edge density, patch size variability, area-weighted shape index, area-weighted fractal dimension index, and mean distance between patches) of the resulting shrub patches on the simulation end date using FRAGSTATS. We used Principal Components Analysis to determine which treatments produced spatial characteristics most similar to those observed in the late 2000s. Based upon our results, we hypothesize that historic shrub expansion in northern Alaska has been driven in part by clonal reproduction with the "mass effect" or short-distance dispersal (< 5 m). The interactive effect of hydrologic characteristics, however, is less clear. These hypotheses may then be tested in future work involving field observations. Given the potential that climate change may facilitate a shift from a clonal to a sexual reproductive strategy, this model may facilitate predictions regarding future Arctic vegetation patterns.

  18. Spatially explicit measures of production of young alewives in Lake Michigan: Linkage between essential fish habitat and recruitment

    USGS Publications Warehouse

    Hook, Tomas O.; Rutherford, Edward S.; Brines, Shannon J.; Mason, Doran M.; Schwab, David J.; McCormick, Michael; Desorcie, Timothy J.

    2003-01-01

    The identification and protection of essential habitats for early life stages of fishes are necessary to sustain fish stocks. Essential fish habitat for early life stages may be defined as areas where fish densities, growth, survival, or production rates are relatively high. To identify critical habitats for young-of-year (YOY) alewives (Alosa pseud oharengus) in Lake Michigan, we integrated bioenergetics models with GIS (Geographic Information Systems) to generate spatially explicit estimates of potential population production (an index of habitat quality). These estimates were based upon YOY alewife bioenergetic growth rate potential and their salmonine predators’ consumptive demand. We compared estimates of potential population production to YOY alewife yield (an index of habitat importance). Our analysis suggested that during 1994–1995, YOY alewife habitat quality and yield varied widely throughout Lake Michigan. Spatial patterns of alewife yield were not significantly correlated to habitat quality. Various mechanisms (e.g., predator migrations, lake circulation patterns, alternative strategies) may preclude YOY alewives from concentrating in areas of high habitat quality in Lake Michigan.

  19. Uncertainty analysis of a spatially explicit annual water-balance model: case study of the Cape Fear basin, North Carolina

    NASA Astrophysics Data System (ADS)

    Hamel, P.; Guswa, A. J.

    2015-02-01

    There is an increasing demand for assessment of water provisioning ecosystem services. While simple models with low data and expertise requirements are attractive, their use as decision-aid tools should be supported by uncertainty characterization. We assessed the performance of the InVEST annual water yield model, a popular tool for ecosystem service assessment based on the Budyko hydrological framework. Our study involved the comparison of 10 subcatchments ranging in size and land-use configuration, in the Cape Fear basin, North Carolina. We analyzed the model sensitivity to climate variables and input parameters, and the structural error associated with the use of the Budyko framework, a lumped (catchment-scale) model theory, in a spatially explicit way. Comparison of model predictions with observations and with the lumped model predictions confirmed that the InVEST model is able to represent differences in land uses and therefore in the spatial distribution of water provisioning services. Our results emphasize the effect of climate input errors, especially annual precipitation, and errors in the ecohydrological parameter Z, which are both comparable to the model structure uncertainties. Our case study supports the use of the model for predicting land-use change effect on water provisioning, although its use for identifying areas of high water yield will be influenced by precipitation errors. While some results are context-specific, our study provides general insights and methods to help identify the regions and decision contexts where the model predictions may be used with confidence.

  20. Global spatially explicit CO2 emission metrics at 0.25° horizontal resolution for forest bioenergy

    NASA Astrophysics Data System (ADS)

    Cherubini, F.

    2015-12-01

    Bioenergy is the most important renewable energy option in studies designed to align with future RCP projections, reaching approximately 250 EJ/yr in RCP2.6, 145 EJ/yr in RCP4.5 and 180 EJ/yr in RCP8.5 by the end of the 21st century. However, many questions enveloping the direct carbon cycle and climate response to bioenergy remain partially unexplored. Bioenergy systems are largely assessed under the default climate neutrality assumption and the time lag between CO2 emissions from biomass combustion and CO2 uptake by vegetation is usually ignored. Emission metrics of CO2 from forest bioenergy are only available on a case-specific basis and their quantification requires processing of a wide spectrum of modelled or observed local climate and forest conditions. On the other hand, emission metrics are widely used to aggregate climate impacts of greenhouse gases to common units such as CO2-equivalents (CO2-eq.), but a spatially explicit analysis of emission metrics with global forest coverage is today lacking. Examples of emission metrics include the global warming potential (GWP), the global temperature change potential (GTP) and the absolute sustained emission temperature (aSET). Here, we couple a global forest model, a heterotrophic respiration model, and a global climate model to produce global spatially explicit emission metrics for CO2 emissions from forest bioenergy. We show their applications to global emissions in 2015 and until 2100 under the different RCP scenarios. We obtain global average values of 0.49 ± 0.03 kgCO2-eq. kgCO2-1 (mean ± standard deviation), 0.05 ± 0.05 kgCO2-eq. kgCO2-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1, and 2.14·10-14 ± 0.11·10-14 °C (kg yr-1)-1 for GWP, GTP and aSET, respectively. We also present results aggregated at a grid, national and continental level. The metrics are found to correlate with the site-specific turnover times and local climate variables like annual mean temperature and precipitation. Simplified

  1. A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

    SciTech Connect

    Morton, April M; McManamay, Ryan A; Nagle, Nicholas N; Piburn, Jesse O; Stewart, Robert N; Surendran Nair, Sujithkumar

    2016-01-01

    Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may therefore not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  2. Spatially and temporally reconfigurable assembly of colloidal crystals

    NASA Astrophysics Data System (ADS)

    Kim, Youngri; Shah, Aayush A.; Solomon, Michael J.

    2014-04-01

    The self-assembly of colloidal crystals is important to the production of materials with functional optical, mechanical and conductive properties. Yet, self-assembly methods are limited by their slow kinetics and lack of structural control in space and time. Refinements such as templating and directed assembly partially address the problem, albeit by introducing fixed surface features such as templates or electrodes. A template-free method to reconfigure colloidal crystals simultaneously in three-dimensional space and time would better align work in colloidal assembly with materials applications. Here, we report a photo-induced assembly method that yields regions either filled with colloidal crystals or completely devoid of colloids. The origin of the effect is found to be electrophoresis of colloids generated by photochemistry at an indium tin oxide-coated substrate. Simple optical manipulations are applied to reconfigure these assembly and depletion regions. Thus, the method represents a new kind of template-free, reconfigurable three-dimensional photolithography.

  3. "The right answer for the wrong reason" revisited: validation of a spatially-explicit soil erosion model (RillGrow)

    NASA Astrophysics Data System (ADS)

    Favis-Mortlock, David

    2010-05-01

    difficulty of objectively comparing two rilled soil surfaces. Real and modelled surfaces might appear very similar, but if planwise rill locations differ by even a few mm, then correlation-based measures indicate a poor result. The converse can also be true. * Flow velocity within rills can vary widely over short distances. However velocity values obtained using e.g. dye tracers have had this small-scale variation smoothed away. How should such values be compared with point-based simulated flow velocity values? Such ambiguities once again open the possibility of obtaining "the right answer for the wrong reason". Thus this paper highlights these and other issues which can arise when validating a spatially-explicit soil erosion model such as RillGrow.

  4. Recursive cross-entropy downscaling model for spatially explicit future land uses: A case study of the Heihe River Basin

    NASA Astrophysics Data System (ADS)

    Zhang, Xinxin; Ermolieva, Tatiana; Balkovic, Juraj; Mosnier, Aline; Kraxner, Florian; Liu, Junguo

    Downscaling methods assist decision makers in coping with the uncertainty regarding sustainable local area developments. In particular, they allow investigating local heterogeneities regarding water, food, energy, and environment consistently with global, national, and sub-national drivers and trends. In this paper, we develop a conceptual framework that integrates a partial equilibrium Global Biosphere Management Model (GLOBIOM) with a dynamic cross-entropy downscaling model to derive spatially explicit projections of land uses at 1-km spatial resolution from 2010 to 2050 relying on aggregate land demand projections. The fusion of the two models is applied in a case study in Heihe River Basin to analyze the extent of potential cropland, grassland, and unused land transformations, which may exacerbate already extensive water consumption caused by rapid expansion of irrigated agriculture in the case study region. The outcomes are illustrated for two Shared Socioeconomic Pathway scenarios. The kappa coefficients show that the downscaling results are in agreement with the land use and land cover map of the Heihe River Basin, which indicates that the proposed approach produces realistic local land use projections. The downscaling results show that under both SSP scenarios the cropland area is expected to increase from 2010 to 2050, while the grassland area is projected to increase sharply from 2010 to 2030 and then gradually come to a standstill after 2030. The results can be used as an input for planning sustainable land and water management in the study area, and the conceptual framework provides a general approach to creating high-resolution land-use datasets.

  5. Spatially explicit estimates of N2 O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management.

    PubMed

    Gerber, James S; Carlson, Kimberly M; Makowski, David; Mueller, Nathaniel D; Garcia de Cortazar-Atauri, Iñaki; Havlík, Petr; Herrero, Mario; Launay, Marie; O'Connell, Christine S; Smith, Pete; West, Paul C

    2016-10-01

    With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2 O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2 O emissions at the country scale by aggregating all crops, under the assumption that N2 O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2 O emissions are relatively greater at higher N application rates. Here, we apply a super-linear emissions response model to crop-specific, spatially explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2 O emissions from croplands. We estimate 0.66 Tg of N2 O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2 O emissions range from 20% to 40% lower throughout sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak nonlinear response of N2 O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2 O emissions. As aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2 O emissions estimates. PMID:27185532

  6. Spatially-explicit life cycle assessment of sun-to-wheels transportation pathways in the U.S.

    PubMed

    Geyer, Roland; Stoms, David; Kallaos, James

    2013-01-15

    Growth in biofuel production, which is meant to reduce greenhouse gas (GHG) emissions and fossil energy demand, is increasingly seen as a threat to food supply and natural habitats. Using photovoltaics (PV) to directly convert solar radiation into electricity for battery electric vehicles (BEVs) is an alternative to photosynthesis, which suffers from a very low energy conversion efficiency. Assessments need to be spatially explicit, since solar insolation and crop yields vary widely between locations. This paper therefore compares direct land use, life cycle GHG emissions and fossil fuel requirements of five different sun-to-wheels conversion pathways for every county in the contiguous U.S.: Ethanol from corn or switchgrass for internal combustion vehicles (ICVs), electricity from corn or switchgrass for BEVs, and PV electricity for BEVs. Even the most land-use efficient biomass-based pathway (i.e., switchgrass bioelectricity in U.S. counties with hypothetical crop yields of over 24 tonnes/ha) requires 29 times more land than the PV-based alternative in the same locations. PV BEV systems also have the lowest life cycle GHG emissions throughout the U.S. and the lowest fossil fuel inputs, except for locations with hypothetical switchgrass yields of 16 or more tonnes/ha. Including indirect land use effects further strengthens the case for PV. PMID:23268715

  7. Decoding leaf hydraulics with a spatially explicit model: principles of venation architecture and implications for its evolution.

    PubMed

    McKown, Athena D; Cochard, Hervé; Sack, Lawren

    2010-04-01

    Leaf venation architecture is tremendously diverse across plant species. Understanding the hydraulic functions of given venation traits can clarify the organization of the vascular system and its adaptation to environment. Using a spatially explicit model (the program K_leaf), we subjected realistic simulated leaves to modifications and calculated the impacts on xylem and leaf hydraulic conductance (K(x) and K(leaf), respectively), important traits in determining photosynthesis and growth. We tested the sensitivity of leaves to altered vein order conductivities (1) in the absence or (2) presence of hierarchical vein architecture, (3) to major vein tapering, and (4) to modification of vein densities (length/leaf area). The K(x) and K(leaf) increased with individual vein order conductivities and densities; for hierarchical venation systems, the greatest impact was from increases in vein conductivity for lower vein orders and increases in density for higher vein orders. Individual vein order conductivities were colimiting of K(x) and K(leaf), as were their densities, but the effects of vein conductivities and densities were orthogonal. Both vein hierarchy and vein tapering increased K(x) relative to xylem construction cost. These results highlight the important consequences of venation traits for the economics, ecology, and evolution of plant transport capacity. PMID:20178410

  8. Spatially-explicit bioenergetics of Pacific sardine in the Southern California Bight: are mesoscale eddies areas of exceptional prerecruit production?

    NASA Astrophysics Data System (ADS)

    Logerwell, Elizabeth A.; Lavaniegos, Bertha; Smith, Paul E.

    Previous research shows that offshore mesoscale eddies in the Southern California Bight region are areas where sardine larval abundance is significantly increased relative to inshore, slope and surrounding offshore waters. In order for mesoscale eddies to be a mechanism linking climate and sardine population variability they must be areas of exceptional prerecruit production. Temperature and prey data from various Southern California Bight (SCB) habitats, including offshore eddies, were applied to a spatially-explicit bioenergetic model which predicts sardine prerecruit growth potential. Growth potential was similar in inshore, slope, and eddy regions (11% and 12% day -1), and was lower in the offshore region, 9% day -1. To estimate production in eddy and non-eddy habitats, growth potential was multiplied by habitat-specific estimates of sardine larval biomass from at-sea surveys. A production index, a measure of potential production resulting from individual growth rate potential and local abundance, was greater in the model cyclonic eddy than in all other regions by more than an order of magnitude. In fact, the production index in the eddy was four times greater than in all other regions combined.

  9. Spatially explicit model of transposon-based genetic drive mechanisms for displacing fluctuating populations of anopheline vector mosquitoes.

    PubMed

    Kiszewski, A E; Spielman, A

    1998-07-01

    To evaluate the prospect of transposon-based genetic drive mechanisms for replacing African vectors of malaria with nonvector anopheline mosquitoes, we developed a spatially explicit simulation model that determined the likelihood that released transgenic mosquitoes may proceed to fixation or extinction under diverse conditions. We compared the effect on fixation of long breeding seasons with relatively subtle population fluctuations to short breeding seasons with severe bottlenecks. Assuming 100% transposition efficiency among heterozygotes with fitness varying between 50 and 100% of that of wild-type mosquitoes, we simulated releases of 1, 10, 50, 90, and 99% of transposon-bearers in relation to wild mosquitoes as well as 1 and 10% releases that were repeated annually. We also evaluated diverse patterns of release including linear, marginal, focused, and scattered distribution. Random dispersal provided the most rapid fixation of transposons within populations. More massive releases allowed longer persistence of transposon-bearers but did not promote fixation, especially when breeding seasons were long. Relative fitness of transposon-bearers, however, proved more powerful than pattern or number of releases in determining whether a construct will become fixed or extinct. Even when fitness approaches that of the wild-type, fixation of a construct may require 150 generations or more. PMID:9701949

  10. Comparing approaches to spatially explicit ecosystem service modeling: a case study from the San Pedro River, Arizona

    USGS Publications Warehouse

    Bagstad, Kenneth J.; Semmens, Darius J.; Winthrop, Robert

    2013-01-01

    Although the number of ecosystem service modeling tools has grown in recent years, quantitative comparative studies of these tools have been lacking. In this study, we applied two leading open-source, spatially explicit ecosystem services modeling tools – Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) – to the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. We modeled locally important services that both modeling systems could address – carbon, water, and scenic viewsheds. We then applied managerially relevant scenarios for urban growth and mesquite management to quantify ecosystem service changes. InVEST and ARIES use different modeling approaches and ecosystem services metrics; for carbon, metrics were more similar and results were more easily comparable than for viewsheds or water. However, findings demonstrate similar gains and losses of ecosystem services and conclusions when comparing effects across our scenarios. Results were more closely aligned for landscape-scale urban-growth scenarios and more divergent for a site-scale mesquite-management scenario. Follow-up studies, including testing in different geographic contexts, can improve our understanding of the strengths and weaknesses of these and other ecosystem services modeling tools as they move closer to readiness for supporting day-to-day resource management.

  11. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  12. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    PubMed Central

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  13. Modeling the fate of nitrogen on the catchment scale using a spatially explicit hydro-biogeochemical simulation system

    NASA Astrophysics Data System (ADS)

    Klatt, S.; Butterbach-Bahl, K.; Kiese, R.; Haas, E.; Kraus, D.; Molina-Herrera, S. W.; Kraft, P.

    2015-12-01

    The continuous growth of the human population demands an equally growing supply for fresh water and food. As a result, available land for efficient agriculture is constantly diminishing which forces farmers to cultivate inferior croplands and intensify agricultural practices, e.g., increase the use of synthetic fertilizers. This intensification of marginal areas in particular will cause a dangerous rise in nitrate discharge into open waters or even drinking water resources. In order to reduce the amount of nitrate lost by surface runoff or lateral subsurface transport, bufferstrips have proved to be a valuable means. Current laws, however, promote rather static designs (i.e., width and usage) even though a multitude of factors, e.g., soil type, slope, vegetation and the nearby agricultural management, determines its effectiveness. We propose a spatially explicit modeling approach enabling to assess the effects of those factors on nitrate discharge from arable lands using the fully distributed hydrology model CMF coupled to the complex biogeochemical model LandscapeDNDC. Such a modeling scheme allows to observe the displacement of dissolved nutrients in both vertical and horizontal directions and serves to estimate both their uptake by the vegetated bufferstrip and loss to the environment. First results indicate a significant reduction of nitrate loss in the presence of a bufferstrip (2.5 m). We show effects induced by various buffer strip widths and plant cover on the nitrate retention.

  14. Individual-Based Spatially-Explicit Model of an Herbivore and Its Resource: The Effect of Habitat Reduction and Fragmentation

    SciTech Connect

    Kostova, T; Carlsen, T; Kercher, J

    2002-06-17

    We present an individual-based, spatially-explicit model of the dynamics of a small mammal and its resource. The life histories of each individual animal are modeled separately. The individuals can have the status of residents or wanderers and belong to behaviorally differing groups of juveniles or adults and males or females. Their territory defending and monogamous behavior is taken into consideration. The resource, green vegetation, grows depending on seasonal climatic characteristics and is diminished due to the herbivore's grazing. Other specifics such as a varying personal energetic level due to feeding and starvation of the individuals, mating preferences, avoidance of competitors, dispersal of juveniles, as a result of site overgrazing, etc. are included in the model. We determined model parameters from real data for the species Microtus ochrogaster (prairie vole). The simulations are done for a case of an enclosed habitat without predators or other species competitors. The goal of the study is to find the relation between size of habitat and population persistence. The experiments with the model show the populations go extinct due to severe overgrazing, but that the length of population persistence depends on the area of the habitat as well as on the presence of fragmentation. Additionally, the total population size of the vole population obtained during the simulations exhibits yearly fluctuations as well as multi-yearly peaks of fluctuations. This dynamics is similar to the one observed in prairie vole field studies.

  15. A spatially explicit multi-isotope approach to map influence regions of plant-plant interactions after exotic plant invasion

    NASA Astrophysics Data System (ADS)

    Hellmann, Christine; Oldeland, Jens; Werner, Christiane

    2015-04-01

    Exotic plant invasions impose profound alterations to native ecosystems, including changes of water, carbon and nutrient cycles. However, explicitly quantifying these impacts remains a challenge. Stable isotopes, by providing natural tracers of biogeochemical processes, can help to identify and measure such alterations in space and time. Recently, δ15N isoscapes, i.e. spatially continuous representations of isotopic values, derived from native plant foliage, enabled to accurately trace nitrogen introduced by the N2-fixing invasive Acacia longifolia into a native Portuguese dune system. It could be shown that the area of the system which was altered by the invasive species exceeded the area which was covered by the invader by far. But still, definition of clear regions of influence is to some extent ambiguous. Here, we present an approach using multiple isoscapes derived from measured foliar δ13C and δ15N values of a native, non-fixing species, Corema album. By clustering isotopic information, we obtained an objective classification of the study area. Properties and spatial position of clusters could be interpreted to distinguish areas that were or were not influenced by A. longifolia. Spatial clusters at locations where A. longifolia was present had δ15N values that were enriched, i.e. close to the atmospheric signal of 0 o compared to the depleted values of the uninvaded system (ca. -11 o). Furthermore, C. album individuals in these clusters were characterized by higher foliar N content and enriched δ13C. These results indicate that the N2-fixing A. longifolia added nitrogen to the system which originated from the atmosphere and was used by the native C. album, inducing functional changes, i.e. an increase in WUE. Additionally, clusters were identified that were presumably determined by inherent properties of the native system. Thus, combining isotope ecology with geostatistical methods is a promising approach for mapping regions of influence in multi

  16. Anthropogenic habitat disturbance and the dynamics of hantavirus using remote sensing, GIS, and a spatially explicit agent-based model

    NASA Astrophysics Data System (ADS)

    Cao, Lina

    Sin Nombre virus (SNV), a strain of hantavirus, causes hantavirus pulmonary syndrome (HPS) in humans, a deadly disease with high mortality rate (>50%). The primary virus host is deer mice, and greater deer mice abundance has been shown to increase the human risk of HPS. There is a great need in understanding the nature of the virus host, its temporal and spatial dynamics, and its relation to the human population with the purpose of predicting human risk of the disease. This research studies SNV dynamics in deer mice in the Great Basin Desert of central Utah, USA using multiyear field data and integrated geospatial approaches including remote sensing, Geographic Information System (GIS), and a spatially explicit agent-based model. The goal is to advance our understanding of the important ecological and demographic factors that affect the dynamics of deer mouse population and SNV prevalence. The primary research question is how climate, habitat disturbance, and deer mouse demographics affect deer mouse population density, its movement, and SNV prevalence in the sagebrush habitat. The results show that the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) can be good predictors of deer mouse density and the number of infected deer mice with a time lag of 1.0 to 1.3 years. This information can be very useful in predicting mouse abundance and SNV risk. The results also showed that climate, mouse density, sex, mass, and SNV infection had significant effects on deer mouse movement. The effect of habitat disturbance on mouse movement varies according to climate conditions with positive relationship in predrought condition and negative association in postdrought condition. The heavier infected deer mice moved the most. Season and disturbance alone had no significant effects. The spatial agent-based model (SABM) simulation results show that prevalence was negatively related to the disturbance levels and the sensitivity analysis showed that

  17. High-resolution fingerprints of past landsliding and spatially explicit, probabilistic assessment of future reactivations: Aiguettes landslide, Southeastern French Alps

    NASA Astrophysics Data System (ADS)

    Lopez Saez, Jérôme; Corona, Christophe; Stoffel, Markus; Berger, Frédéric

    2013-08-01

    The purpose of this study was to reconstruct spatio-temporal patterns of past landslide reactivation and the possible occurrence of future events in a forested area of the Barcelonnette basin (Southeastern French Alps). Analysis of past events on the Aiguettes landslide was based on growth-ring series from 223 heavily affected Mountain pine (Pinus uncinata Mill. ex Mirb.) trees growing on the landslide body. A total of 355 growth disturbances were identified in the samples indicating 14 reactivation phases of the landslide body since AD 1898. Accuracy of the spatio-temporal reconstruction is confirmed by historical records and aerial photographs. Logistic regressions using monthly rainfall data from the HISTALP database indicated that landslide reactivations occurred due to above-average precipitation anomalies in winter. They point to the important role of snow in the triggering of reactivations at the Aiguettes landslide body. In a subsequent step, spatially explicit probabilities of landslide reactivation were computed based on the extensive dendrogeomorphic dataset using a Poisson distribution model for an event to occur in 5, 20, 50, and 100 yr. High-resolution maps indicate highest probabilities of reactivation in the lower part of the landslide body and increase from 0.28 for a 5-yr period to 0.99 for a 100-yr period. In the upper part of the landslide body, probabilities do not exceed 0.57 for a 100-yr period and somehow confirm the more stable character of this segment of the Aiguettes landslide. The approach presented in this paper is considered a valuable tool for land-use planners and emergency cells in charge of forecasting future events and in protecting people and their assets from the negative effects of landslides.

  18. Spatially explicit groundwater vulnerability assessment to support the implementation of the Water Framework Directive - a practical approach with stakeholders

    NASA Astrophysics Data System (ADS)

    Berkhoff, K.

    2008-01-01

    The main objective of the study presented in this paper was to develop an evaluation scheme which is suitable for spatially explicit groundwater vulnerability assessment according to the Water Framework Directive (WFD). Study area was the Hase river catchment, an area of about 3 000 km2 in north-west Germany which is dominated by livestock farming, in particular pig and poultry production. For the Hase river catchment, the first inventory of the WFD led to the conclusion that 98% of the catchment area is "unclear/unlikely" to reach a good groundwater status due to diffuse nitrogen emissions from agriculture. The groundwater vulnerability assessment was embedded in the PartizipA project ("Participative modelling, Actor and Ecosystem Analysis in Regions with Intensive Agriculture", www.partizipa.net), within which a so-called actors' platform was established in the study area. The objective of the participatory process was to investigate the effects of the WFD on agriculture as well as to discuss groundwater protection measures which are suitable for an integration in the programme of measures. The study was conducted according to the vulnerability assessment concept of the Intergovernmental Panel on Climate Change, considering sensitivity, exposure and adaptive capacity. Sensitivity was computed using the DRASTIC index of natural groundwater pollution potential. Exposure (for a reference scenario) was computed using the STOFFBILANZ nutrient model. Several regional studies were analysed to evaluate the adaptive capacity. From these studies it was concluded that the adaptive capacity in the Hase river catchment is very low due to the economic importance of the agricultural sector which will be significantly affected by groundwater protection measures. As a consequence, the adaptive capacity was not considered any more in the vulnerability assessment. A groundwater vulnerability evaluation scheme is presented which enjoys the advantage

  19. Cognitive Process Modeling of Spatial Ability: The Assembling Objects Task

    ERIC Educational Resources Information Center

    Ivie, Jennifer L.; Embretson, Susan E.

    2010-01-01

    Spatial ability tasks appear on many intelligence and aptitude tests. Although the construct validity of spatial ability tests has often been studied through traditional correlational methods, such as factor analysis, less is known about the cognitive processes involved in solving test items. This study examines the cognitive processes involved in…

  20. Renewable Energy Production from Waste to Mitigate Climate Change and Counteract Soil Degradation - A Spatial Explicit Assessment for Japan

    NASA Astrophysics Data System (ADS)

    Kraxner, Florian; Yoshikawa, Kunio; Leduc, Sylvain; Fuss, Sabine; Aoki, Kentaro; Yamagata, Yoshiki

    2014-05-01

    Waste production from urban areas is growing faster than urbanization itself, while at the same time urban areas are increasingly contributing substantial emissions causing climate change. Estimates indicate for urban residents a per capita solid waste (MSW) production of 1.2 kg per day, subject to further increase to 1.5 kg beyond 2025. Waste water and sewage production is estimated at about 260 liters per capita and day, also at increasing rates. Based on these figures, waste - including e.g. MSW, sewage and animal manure - can generally be assumed as a renewable resource with varying organic components and quantity. This paper demonstrates how new and innovative technologies in the field of Waste-to-Green Products can help in various ways not only to reduce costs for waste treatment, reduce the pressure on largely overloaded dump sites, and reduce also the effect of toxic materials at the landfill site and by that i.e. protect the groundwater. Moreover, Waste-to-Green Products can contribute actively to mitigating climate change through fossil fuel substitution and carbon sequestration while at the same time counteracting negative land use effects from other types of renewable energy and feedstock production through substitution. At the same time, the co-production and recycling of fertilizing elements and biochar can substantially counteract soil degradation and improve the soil organic carbon content of different land use types. The overall objective of this paper is to assess the total climate change mitigation potential of MSW, sewage and animal manure for Japan. A techno-economic approach is used to inform the policy discussion on the suitability of this substantial and sustainable mitigation option. We examine the spatial explicit technical mitigation potential from e.g. energy substitution and carbon sequestration through biochar in rural and urban Japan. For this exercise, processed information on respective Japanese waste production, energy demand

  1. Spatially explicit modeling of animal tuberculosis at the wildlife-livestock interface in Ciudad Real province, Spain.

    PubMed

    LaHue, Nathaniel P; Baños, Joaquín Vicente; Acevedo, Pelayo; Gortázar, Christian; Martínez-López, Beatriz

    2016-06-01

    Eurasian wild boar (Sus scrofa) and red deer (Cervus elaphus) are the most important wildlife reservoirs for animal tuberculosis (TB) caused by the Mycobacterium tuberculosis complex (MTC), in Mediterranean Spain. These species are considered to play an important role in the transmission and persistence of MTC in cattle in some regions; however the factors contributing to the risk of transmission at the wildlife-livestock interface and the areas at highest risk for such transmission are largely unknown. This study sought to identify geographic areas where wildlife-livestock interactions are most likely to occur and to characterize the environmental and management factors at this interface contributing to persistence, incidence, and occurrence of TB on cattle farms, in one of the provinces with higher TB prevalence in Spain, Ciudad Real. We used spatially explicit, ecological niche models to evaluate the importance of factors such as wildlife demographics and hunting management, land use, climatic, and environmental variables as well as TB status in wildlife for TB breakdown (model 1), persistence (model 2) and new infection (model 3) on cattle farms and to generate high resolution maps of predicted TB occurrence to guide risk-based interventions. Models revealed that land use, particularly open area and woodland, high wild boar TB prevalence, and close proximity to fenced hunting estates were the most important factors associated with TB infection on cattle farms. This is the first time that local TB prevalence in wild boar for individual hunting estates has been significantly associated with TB occurrence on cattle farms at a local scale. Prediction maps identified two areas with high likelihood of TB occurrence in the southwest and northwest of the province where wildlife-livestock interactions and TB occurrence are highly likely and where TB preventative and mitigation strategies (e.g. targeted vaccination, increased biosecurity, etc.) should be prioritized

  2. Assessment of mineral concentration impacts from pumped stormwater on an Everglades Wetland, Florida, USA - Using a spatially-explicit model

    NASA Astrophysics Data System (ADS)

    Chen, Chunfang; Meselhe, Ehab; Waldon, Michael

    2012-07-01

    SummaryThe Arthur R. Marshall Loxahatchee National Wildlife Refuge (Refuge) overlays a 58,725 ha remnant of the Northern Everglades which is termed Water Conservation Area 1 (WCA-1). The Refuge is impacted by stormwater inflow from flood control pump stations which discharge to a perimeter canal system inside an impounding levee. These discharges contain elevated mineral and nutrient concentrations, with chloride concentration averaging well over 100 mg/L. It has long been established that the Refuge naturally has low mineral content softwater, and that this low-mineral condition affects the species composition of wetland periphyton that are at the base of much of the Refuge food chain. The interior marsh of the Refuge has today been termed rainfall-driven or ombrotrophic, with median chloride concentration averaging 20.5 mg/L. However, chloride concentration in rain water averages roughly 2 mg/L. The level of impact of exogenous pumped inflow on the concentration of chloride and other mineral constituents in the interior marsh has been unclear, and at times it has been debated whether atmospheric loading and evaporation can alone explain observed concentration of chloride in the interior. We applied a spatially explicit hydrodynamic and constituent transport model, MIKE FLOOD, to estimate the unimpacted condition of the interior. We compare this with simulated and monitored chloride concentrations under current conditions. The model was calibrated for a 5-year period (2000-2004), and validated for a 2-year period (2005-2006). We found that when pumped inflow concentration is reduced to an estimated rainfall chloride concentration, interior chloride concentration ranges typically below 5 mg/L. We therefore conclude that the interior chloride concentration is currently dominated by pumped inflows and should not be termed ombrotrophic. We also present initial modeling of one proposed remedial solution for reducing this impact. Our study demonstrates the feasibility

  3. Simulating Human and Environmental Exposure from Hand-Held Knapsack Pesticide Application: Be-WetSpa-Pest, an Integrative, Spatially Explicit Modeling Approach.

    PubMed

    Binder, Claudia R; García-Santos, Glenda; Andreoli, Romano; Diaz, Jaime; Feola, Giuseppe; Wittensoeldner, Moritz; Yang, Jing

    2016-05-25

    This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato-producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops, or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easily to other regions in developing countries with similar conditions. PMID:26828854

  4. A comparison of three empirically based, spatially explicit predictive models of residential soil Pb concentrations in Baltimore, Maryland, USA: understanding the variability within cities.

    PubMed

    Schwarz, Kirsten; Weathers, Kathleen C; Pickett, Steward T A; Lathrop, Richard G; Pouyat, Richard V; Cadenasso, Mary L

    2013-08-01

    In many older US cities, lead (Pb) contamination of residential soil is widespread; however, contamination is not uniform. Empirically based, spatially explicit models can assist city agencies in addressing this important public health concern by identifying areas predicted to exceed public health targets for soil Pb contamination. Sampling of 61 residential properties in Baltimore City using field portable X-ray fluorescence revealed that 53 % had soil Pb that exceeded the USEPA reportable limit of 400 ppm. These data were used as the input to three different spatially explicit models: a traditional general linear model (GLM), and two machine learning techniques: classification and regression trees (CART) and Random Forests (RF). The GLM revealed that housing age, distance to road, distance to building, and the interactions between variables explained 38 % of the variation in the data. The CART model confirmed the importance of these variables, with housing age, distance to building, and distance to major road networks determining the terminal nodes of the CART model. Using the same three predictor variables, the RF model explained 42 % of the variation in the data. The overall accuracy, which is a measure of agreement between the model and an independent dataset, was 90 % for the GLM, 83 % for the CART model, and 72 % for the RF model. A range of spatially explicit models that can be adapted to changing soil Pb guidelines allows managers to select the most appropriate model based on public health targets. PMID:23775390

  5. Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data

    PubMed Central

    Zhang, Chao; Zheng, Yu; Ma, Xiuli; Han, Jiawei

    2015-01-01

    Recent years have witnessed the wide proliferation of geo-sensory applications wherein a bundle of sensors are deployed at different locations to cooperatively monitor the target condition. Given massive geo-sensory data, we study the problem of mining spatial co-evolving patterns (SCPs), i.e., groups of sensors that are spatially correlated and co-evolve frequently in their readings. SCP mining is of great importance to various real-world applications, yet it is challenging because (1) the truly interesting evolutions are often flooded by numerous trivial fluctuations in the geo-sensory time series; and (2) the pattern search space is extremely large due to the spatiotemporal combinatorial nature of SCP. In this paper, we propose a two-stage method called Assembler. In the first stage, Assembler filters trivial fluctuations using wavelet transform and detects frequent evolutions for individual sensors via a segment-and-group approach. In the second stage, Assembler generates SCPs by assembling the frequent evolutions of individual sensors. Leveraging the spatial constraint, it conceptually organizes all the SCPs into a novel structure called the SCP search tree, which facilitates the effective pruning of the search space to generate SCPs efficiently. Our experiments on both real and synthetic data sets show that Assembler is effective, efficient, and scalable. PMID:26705506

  6. Integrative Structure Determination of Protein Assemblies by Satisfaction of Spatial Restraints

    NASA Astrophysics Data System (ADS)

    Alber, Frank; Chait, Brian T.; Rout, Michael P.; Sali, Andrej

    To understand the cell, we need to determine the structures of macromolecular assemblies, many of which consist of tens to hundreds of components. A great variety of experimental data can be used to characterize the assemblies at several levels of resolution, from atomic structures to component configurations. To maximize completeness, resolution, accuracy, precision and efficiency of the structure determination, a computational approach is needed that can use spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. We illustrate the approach by determining the configuration of the 456 proteins in the nuclear pore complex from Baker's yeast.

  7. Modeling Behavior by Coastal River Otter (Lontra Canadensis) in Response to Prey Availability in Prince William Sound, Alaska: A Spatially-Explicit Individual-Based Approach.

    PubMed

    Albeke, Shannon E; Nibbelink, Nathan P; Ben-David, Merav

    2015-01-01

    Effects of climate change on animal behavior and cascading ecosystem responses are rarely evaluated. In coastal Alaska, social river otters (Lontra Canadensis), largely males, cooperatively forage on schooling fish and use latrine sites to communicate group associations and dominance. Conversely, solitary otters, mainly females, feed on intertidal-demersal fish and display mutual avoidance via scent marking. This behavioral variability creates "hotspots" of nutrient deposition and affects plant productivity and diversity on the terrestrial landscape. Because the abundance of schooling pelagic fish is predicted to decline with climate change, we developed a spatially-explicit individual-based model (IBM) of otter behavior and tested six scenarios based on potential shifts to distribution patterns of schooling fish. Emergent patterns from the IBM closely mimicked observed otter behavior and landscape use in the absence of explicit rules of intraspecific attraction or repulsion. Model results were most sensitive to rules regarding spatial memory and activity state following an encounter with a fish school. With declining availability of schooling fish, the number of social groups and the time simulated otters spent in the company of conspecifics declined. Concurrently, model results suggested an elevation of defecation rate, a 25% increase in nitrogen transport to the terrestrial landscape, and significant changes to the spatial distribution of "hotspots" with declines in schooling fish availability. However, reductions in availability of schooling fish could lead to declines in otter density over time. PMID:26061497

  8. Modeling Behavior by Coastal River Otter (Lontra Canadensis) in Response to Prey Availability in Prince William Sound, Alaska: A Spatially-Explicit Individual-Based Approach

    PubMed Central

    Albeke, Shannon E.; Nibbelink, Nathan P.; Ben-David, Merav

    2015-01-01

    Effects of climate change on animal behavior and cascading ecosystem responses are rarely evaluated. In coastal Alaska, social river otters (Lontra Canadensis), largely males, cooperatively forage on schooling fish and use latrine sites to communicate group associations and dominance. Conversely, solitary otters, mainly females, feed on intertidal-demersal fish and display mutual avoidance via scent marking. This behavioral variability creates “hotspots” of nutrient deposition and affects plant productivity and diversity on the terrestrial landscape. Because the abundance of schooling pelagic fish is predicted to decline with climate change, we developed a spatially-explicit individual-based model (IBM) of otter behavior and tested six scenarios based on potential shifts to distribution patterns of schooling fish. Emergent patterns from the IBM closely mimicked observed otter behavior and landscape use in the absence of explicit rules of intraspecific attraction or repulsion. Model results were most sensitive to rules regarding spatial memory and activity state following an encounter with a fish school. With declining availability of schooling fish, the number of social groups and the time simulated otters spent in the company of conspecifics declined. Concurrently, model results suggested an elevation of defecation rate, a 25% increase in nitrogen transport to the terrestrial landscape, and significant changes to the spatial distribution of “hotspots” with declines in schooling fish availability. However, reductions in availability of schooling fish could lead to declines in otter density over time. PMID:26061497

  9. Spatial regulation of cytoplasmic snRNP assembly at the cellular level

    PubMed Central

    Hyjek, Malwina; Wojciechowska, Natalia; Rudzka, Magda; Kołowerzo-Lubnau, Agnieszka; Smoliński, Dariusz Jan

    2015-01-01

    Small nuclear ribonucleoproteins (snRNPs) play a crucial role in pre-mRNA splicing in all eukaryotic cells. In contrast to the relatively broad knowledge on snRNP assembly within the nucleus, the spatial organization of the cytoplasmic stages of their maturation remains poorly understood. Nevertheless, sparse research indicates that, similar to the nuclear steps, the crucial processes of cytoplasmic snRNP assembly may also be strictly spatially regulated. In European larch microsporocytes, it was determined that the cytoplasmic assembly of snRNPs within a cell might occur in two distinct spatial manners, which depend on the rate of de novo snRNP formation in relation to the steady state of these particles within the nucleus. During periods of moderate expression of splicing elements, the cytoplasmic assembly of snRNPs occurred diffusely throughout the cytoplasm. Increased expression of both Sm proteins and U snRNA triggered the accumulation of these particles within distinct, non-membranous RNP-rich granules, which are referred to as snRNP-rich cytoplasmic bodies. PMID:26320237

  10. Spatial variability in plant predation determines the strength of stochastic community assembly.

    PubMed

    Germain, Rachel M; Johnson, Laura; Schneider, Stefan; Cottenie, Karl; Gillis, Elizabeth A; MacDougall, Andrew S

    2013-08-01

    High diversity is often poorly explained by trait-based deterministic models, in part because stochastic processes also influence community assembly. Testing how deterministic and stochastic processes combine to regulate diversity, however, has been limited by the spatial complexity of these interactions. Here, we demonstrate how spatial variability in small-mammal predation on plants, mostly by granivory, results in fine-scale switching between deterministically and stochastically regulated plant community assembly in an otherwise environmentally homogeneous tallgrass prairie. We initiated assembly with the uniform application of a 24-species mixture of prairie grasses and forbs, thereby setting the maximum level of diversity (γ-diversity). In field edges with higher densities of small mammals, traits reducing seed palatability deterministically produced homogeneous subsets of less palatable plant species within the first few months after planting (low α and β diversity). As small-mammal densities decreased in more open areas, assembly unfolded stochastically on the basis of which planted species happened to land at a given location (high α and β diversity). We used randomization models to validate that this higher β diversity was explained by true differences in community structure among plots rather than by the hidden effects of increasing α diversity. The net effect at the site level was a spatially structured array of prairie species, including a positive relationship between diversity and environmental suitability relating to reduced predator intensity. PMID:23852352

  11. Factors influencing export of dissolved inorganic nitrogen by major rivers: A new seasonal, spatially explicit, global model - 2012

    EPA Science Inventory

    Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and zone and ...

  12. A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

    PubMed Central

    Liu, Junguo; Folberth, Christian; Yang, Hong; Röckström, Johan; Abbaspour, Karim; Zehnder, Alexander J. B.

    2013-01-01

    Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security. PMID:23460901

  13. Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model

    EPA Science Inventory

    Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in depth. Much less is known, however, about seasonal patterns and controls of coastal DIN delivery across larg...

  14. A global and spatially explicit assessment of climate change impacts on crop production and consumptive water use.

    PubMed

    Liu, Junguo; Folberth, Christian; Yang, Hong; Röckström, Johan; Abbaspour, Karim; Zehnder, Alexander J B

    2013-01-01

    Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security. PMID:23460901

  15. Factors influencing export of dissolved inorganic nitrogen by major rivers: a new seasonal, spatially explicit, global model

    EPA Science Inventory

    Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and controls ...

  16. REMOTE SENSING AND SPATIALLY EXPLICIT LANDSCAPE-BASED NITROGEN MODELING METHODS DEVELOPMENT IN THE NEUSE RIVER BASIN, NC

    EPA Science Inventory

    The objective of this research was to model and map the spatial patterns of excess nitrogen (N) sources across the landscape within the Neuse River Basin (NRB) of North
    Carolina. The process included an initial land cover characterization effort to map landscape "patches" at ...

  17. Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China.

    PubMed

    Gong, Jian; Yang, Jianxin; Tang, Wenwu

    2015-11-01

    Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270

  18. Reconciling nature conservation and traditional farming practices: a spatially explicit framework to assess the extent of High Nature Value farmlands in the European countryside.

    PubMed

    Lomba, Angela; Alves, Paulo; Jongman, Rob H G; McCracken, David I

    2015-03-01

    Agriculture constitutes a dominant land cover worldwide, and rural landscapes under extensive farming practices acknowledged due to high biodiversity levels. The High Nature Value farmland (HNVf) concept has been highlighted in the EU environmental and rural policies due to their inherent potential to help characterize and direct financial support to European landscapes where high nature and/or conservation value is dependent on the continuation of specific low-intensity farming systems. Assessing the extent of HNV farmland by necessity relies on the availability of both ecological and farming systems' data, and difficulties associated with making such assessments have been widely described across Europe. A spatially explicit framework of data collection, building out from local administrative units, has recently been suggested as a means of addressing such difficulties. This manuscript tests the relevance of the proposed approach, describes the spatially explicit framework in a case study area in northern Portugal, and discusses the potential of the approach to help better inform the implementation of conservation and rural development policies. Synthesis and applications: The potential of a novel approach (combining land use/cover, farming and environmental data) to provide more accurate and efficient mapping and monitoring of HNV farmlands is tested at the local level in northern Portugal. The approach is considered to constitute a step forward toward a more precise targeting of landscapes for agri-environment schemes, as it allowed a more accurate discrimination of areas within the case study landscape that have a higher value for nature conservation. PMID:25798221

  19. Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China

    PubMed Central

    Gong, Jian; Yang, Jianxin; Tang, Wenwu

    2015-01-01

    Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270

  20. Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

    PubMed

    Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

    2013-09-01

    Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate. PMID:24772388

  1. Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

    USGS Publications Warehouse

    Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

    2014-01-01

    Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use

  2. Spatially explicit, nano-mechanical models of the muscle half-sarcomere: Implications for biomechanical tuning in atrophy and fatigue

    NASA Astrophysics Data System (ADS)

    Kataoka, Aya; Tanner, Bertrand C. W.; Macpherson, J. Michael; Xu, Xiangrong; Wang, Qi; Regnier, Michael; Daniel, Thomas L.; Chase, P. Bryant

    2007-01-01

    Astronaut biomechanical performance depends on a wide variety of factors. Results from computational modelling suggest that muscle function—a key component of performance—could be modulated by compliance of the contractile filaments in muscle, especially when force is low such as transient Ca activation in a twitch, reduced activation in muscle fatigue encountered during EVA, or perhaps atrophy during prolonged space flight. We used Monte-Carlo models to investigate the hypotheses that myofilament compliance influences muscle function during a twitch, and also modulates the effects of cooperative interactions between contractile proteins on force generation. Peak twitch force and the kinetics of force decay were both decreased, while tension cost was increased, when myofilament compliance was increased relative to physiological values. Both the apparent Ca sensitivity and cooperativity of activation of steady-state isometric force were altered by myofilament compliance even when there were no explicit interactions included between binding sites. The effects of cooperative interactions between adjacent regulatory units were found to be greater than either the effect of myofilament compliance on apparent cooperativity of activation or that due to myosin cross-bridge-induced cooperativity. These results indicate that muscle function may be "tuned" at the molecular level, particularly under conditions of reduced Ca activation.

  3. Drought tolerance as a driver of tropical forest assembly: resolving spatial signatures for multiple processes.

    PubMed

    Bartlett, M K; Zhang, Y; Yang, J; Kreidler, N; Sun, S w; Lin, L; Hu, Y H; Cao, K F; Sack, L

    2016-02-01

    Spatial patterns in trait variation reflect underlying community assembly processes, allowing us to test hypotheses about their trait and environmental drivers by identifying the strongest correlates of characteristic spatial patterns. For 43 evergreen tree species (> 1 cm dbh) in a 20-ha seasonal tropical rainforest plot in Xishuangbanna, China, we compared the ability of drought-tolerance traits, other physiological traits, and commonly measured functional traits to predict the spatial patterns expected from the assembly processes of habitat associations, niche-overlap-based competition, and hierarchical competition. We distinguished the neighborhood-scale (0-20 m) patterns expected from competition from larger-scale habitat associations with a wavelet method. Species' drought tolerance and habitat variables related to soil water supply were strong drivers of habitat associations, and drought tolerance showed a significant spatial signal for influencing competition. Overall, the traits most strongly associated with habitat, as quantified using multivariate models, were leaf density, leaf turgor loss point (π(tlp); also known as the leaf wilting point), and stem hydraulic conductivity (r2 range for the best fit models = 0.27-0.36). At neighborhood scales, species spatial associations were positively correlated with similarity in π(tlp), consistent with predictions for hierarchical competition. Although the correlation between π(tlp) and interspecific spatial associations was weak (r2 < 0.01), this showed a persistent influence of drought tolerance on neighborhood interactions and community assembly. Quantifying the full impact of traits on competitive interactions in forests may require incorporating plasticity among individuals within species, especially among specific life stages, and moving beyond individual traits to integrate the impact of multiple traits on whole-plant performance and resource demand. PMID:27145624

  4. Imaging Self-assembly Dependent Spatial Distribution of Small Molecules in Cellular Environment

    PubMed Central

    Gao, Yuan; Kuang, Yi; Du, Xuewen; Zhou, Jie; Chandran, Preethi; Horkay, Ferenc; Xu, Bing

    2014-01-01

    Self-assembly of small molecules, as a more common phenomenon than one previously thought, can be either beneficial or detrimental to cells. Despite its profound biological implications, how the self-assembly of small molecules behave in cellular environment is largely unknown and barely explored. This work studies four fluorescent molecules that consist of the same peptidic backbone (e.g., Phe-Phe-Lys) and enzyme trigger (e.g., a phosphotyrosine residue), but bear different fluorophores on the side chain of the lysine residue of the peptidic motif. These molecules, however, exhibit different ability of self-assembly before and after enzymatic transformation (e.g., dephosphorylation). Fluorescent imaging reveals that self-assembly directly affects the distribution of these small molecules in cellular environment. Moreover, cell viability tests suggest that the states and the location of the molecular assemblies in the cellular environment control the phenotypes of the cells. For example, the molecular nanofibers of one of the small molecules apparently stabilize actin filaments and alleviate the insult of an F-actin toxin (e.g., latrunculin A). Combining fluorescent imaging and enzyme-instructed self-assembly of small peptidic molecules, this work not only demonstrates that self-assembly as a key factor for dictating the spatial distribution of small molecules in cellular environment. In addition, it illustrates a useful approach, based on enzyme-instructed self-assembly of small molecules, to modulate spatiotemporal profiles of small molecules in cellular environment, which allows the use of the emergent properties of small molecules to control the fate of cells. PMID:24266765

  5. Imaging self-assembly dependent spatial distribution of small molecules in a cellular environment.

    PubMed

    Gao, Yuan; Kuang, Yi; Du, Xuewen; Zhou, Jie; Chandran, Preethi; Horkay, Ferenc; Xu, Bing

    2013-12-10

    Self-assembly of small molecules, as a more common phenomenon than one previously thought, can be either beneficial or detrimental to cells. Despite its profound biological implications, how the self-assembly of small molecules behave in a cellular environment is largely unknown and barely explored. This work studies four fluorescent molecules that consist of the same peptidic backbone (e.g., Phe-Phe-Lys) and enzyme trigger (e.g., a phosphotyrosine residue), but bear different fluorophores on the side chain of the lysine residue of the peptidic motif. These molecules, however, exhibit a different ability of self-assembly before and after enzymatic transformation (e.g., dephosphorylation). Fluorescent imaging reveals that self-assembly directly affects the distribution of these small molecules in a cellular environment. Moreover, cell viability tests suggest that the states and the locations of the molecular assemblies in the cellular environment control the phenotypes of the cells. For example, the molecular nanofibers of one of the small molecules apparently stabilize actin filaments and alleviate the insult of an F-actin toxin (e.g., latrunculin A). Combining fluorescent imaging and enzyme-instructed self-assembly of small peptidic molecules, this work demonstrates self-assembly as a key factor for dictating the spatial distribution of small molecules in a cellular environment. In addition, it illustrates a useful approach, based on enzyme-instructed self-assembly of small molecules, to modulate spatiotemporal profiles of small molecules in a cellular environment, which allows the use of the emergent properties of small molecules to control the fate of cells. PMID:24266765

  6. SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily

    PubMed Central

    Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio

    2014-01-01

    Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of

  7. Temporal and spatial constraints on community assembly during microbial colonization of wood in seawater.

    PubMed

    Kalenitchenko, Dimitri; Fagervold, Sonja K; Pruski, Audrey M; Vétion, Gilles; Yücel, Mustafa; Le Bris, Nadine; Galand, Pierre E

    2015-12-01

    Wood falls on the ocean floor form chemosynthetic ecosystems that remain poorly studied compared with features such as hydrothermal vents or whale falls. In particular, the microbes forming the base of this unique ecosystem are not well characterized and the ecology of communities is not known. Here we use wood as a model to study microorganisms that establish and maintain a chemosynthetic ecosystem. We conducted both aquaria and in situ deep-sea experiments to test how different environmental constraints structure the assembly of bacterial, archaeal and fungal communities. We also measured changes in wood lipid concentrations and monitored sulfide production as a way to detect potential microbial activity. We show that wood falls are dynamic ecosystems with high spatial and temporal community turnover, and that the patterns of microbial colonization change depending on the scale of observation. The most illustrative example was the difference observed between pine and oak wood community dynamics. In pine, communities changed spatially, with strong differences in community composition between wood microhabitats, whereas in oak, communities changed more significantly with time of incubation. Changes in community assembly were reflected by changes in phylogenetic diversity that could be interpreted as shifts between assemblies ruled by species sorting to assemblies structured by competitive exclusion. These ecological interactions followed the dynamics of the potential microbial metabolisms accompanying wood degradation in the sea. Our work showed that wood is a good model for creating and manipulating chemosynthetic ecosystems in the laboratory, and attracting not only typical chemosynthetic microbes but also emblematic macrofaunal species. PMID:25885564

  8. Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

    NASA Astrophysics Data System (ADS)

    Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

    2014-12-01

    The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution

  9. Evaluating effects of Everglades restoration on American crocodile populations in south Florida using a spatially-explicit, stage-based population model

    USGS Publications Warehouse

    Green, Timothy W.; Slone, Daniel H.; Swain, Eric D.; Cherkiss, Michael S.; Lohmann, Melinda; Mazzotti, Frank J.; Rice, Kenneth G.

    2014-01-01

    The distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.

  10. A spatially-explicit data driven approach to assess the effect of agricultural land occupation on species groups

    NASA Astrophysics Data System (ADS)

    Elshout, P.; van Zelm, R.; Karuppiah, R.; Laurenzi, I.; Huijbregts, M.

    2013-12-01

    Change of vegetation cover and increased land use intensity can directly affect the natural habitat and the wildlife it houses. The actual impact of agricultural land use is region specific as crops are grown under various climatic conditions and ways of cultivation and refining. Furthermore, growing a specific crop in a tropical region may require clearance of rainforest while the same crop may replace natural grasslands in temperate regions. Within life cycle impact assessment (LCIA), methods to address impacts of land use on a global scale are still in need of development. We aim to extend existing methods to improve the robustness of LCIA by allowing spatial differentiation of agricultural land use impacts. The goal of this study is to develop characterization factors for the direct impact of land use on biodiversity, which results from the replacement of natural habitat with farmland. The characterization factor expresses the change in species richness under crop cultivation compared to the species richness in the natural situation over a certain area. A second goal was to identify the differences in impacts caused by cultivation of different crop types, sensitivity of different taxonomic groups, and differences in natural land cover. Empirical data on species richness were collected from literature for both natural reference situations and agricultural land use situations. Reference situations were selected on an ecoregion or biome basis. We calculated characterization factors for four crop groups (oil palm, low crops, cereals, and perennial grasses), four species groups (arthropods, birds, mammals, vascular plants), and six biomes.

  11. Estimating Brownian motion dispersal rate, longevity and population density from spatially explicit mark-recapture data on tropical butterflies.

    PubMed

    Tufto, Jarle; Lande, Russell; Ringsby, Thor-Harald; Engen, Steinar; Saether, Bernt-Erik; Walla, Thomas R; DeVries, Philip J

    2012-07-01

    1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity. PMID:22320218

  12. Anticipating Knowledge to Inform Species Management: Predicting Spatially Explicit Habitat Suitability of a Colonial Vulture Spreading Its Range

    PubMed Central

    Mateo-Tomás, Patricia; Olea, Pedro P.

    2010-01-01

    Background The knowledge of both potential distribution and habitat suitability is fundamental in spreading species to inform in advance management and conservation planning. After a severe decline in the past decades, the griffon vulture (Gyps fulvus) is now spreading its breeding range towards the northwest in Spain and Europe. Because of its key ecological function, anticipated spatial knowledge is required to inform appropriately both vulture and ecosystem management. Methodology/Findings Here we used maximum entropy (Maxent) models to determine the habitat suitability of potential and current breeding distribution of the griffon vulture using presence-only data (N = 124 colonies) in north-western Spain. The most relevant ecological factors shaping this habitat suitability were also identified. The resulting model had a high predictive performance and was able to predict species' historical distribution. 7.5% (∼1,850 km2) of the study area resulted to be suitable breeding habitat, most of which (∼70%) is already occupied by the species. Cliff availability and livestock density, especially of sheep and goats, around 10 km of the colonies were the fundamental factors determining breeding habitat suitability for this species. Conclusions/Significance Griffon vultures could still spread 50–60 km towards the west, increasing their breeding range in 1,782 km2. According to our results, 7.22% of the area suitable for griffon vulture will be affected by wind farms, so our results could help to better plan wind farm locations. The approach here developed could be useful to inform management of reintroductions and recovery programmes currently being implemented for both the griffon vulture and other threatened vulture species. PMID:20811501

  13. YALINA-booster subcritical assembly pulsed-neutron experiments : data processing and spatial corrections.

    SciTech Connect

    Cao, Y.; Gohar, Y.; Nuclear Engineering Division

    2010-10-11

    The YALINA-Booster experiments and analyses are part of the collaboration between Argonne National Laboratory of USA and the Joint Institute for Power & Nuclear Research - SOSNY of Belarus for studying the physics of accelerator driven systems for nuclear energy applications using low enriched uranium. The YALINA-Booster subcritical assembly is utilized for studying the kinetics of accelerator driven systems with its highly intensive D-T or D-D pulsed neutron source. In particular, the pulsed neutron methods are used to determine the reactivity of the subcritical system. This report examines the pulsed-neutron experiments performed in the YALINA-Booster facility with different configurations for the subcritical assembly. The 1141 configuration with 90% U-235 fuel and the 1185 configuration with 36% or 21% U-235 fuel are examined. The Sjoestrand area-ratio method is utilized to determine the reactivities of the different configurations. The linear regression method is applied to obtain the prompt neutron decay constants from the pulsed-neutron experimental data. The reactivity values obtained from the experimental data are shown to be dependent on the detector locations inside the subcritical assembly and the types of detector used for the measurements. In this report, Bell's spatial correction factors are calculated based on a Monte Carlo model to remove the detector dependences. The large differences between the reactivity values given by the detectors in the fast neutron zone of the YALINA-Booster are reduced after applying the spatial corrections. In addition, the estimated reactivity values after the spatial corrections are much less spatially dependent.

  14. Towards more spatially explicit assessments of virtual water flows: linking local water use and scarcity to global demand of Brazilian farming commodities

    NASA Astrophysics Data System (ADS)

    Flach, Rafaela; Ran, Ylva; Godar, Javier; Karlberg, Louise; Suavet, Clement

    2016-07-01

    Global consumption of farming commodities is an important driver of water demand in regions of production. This is the case in Brazil, which has emerged as one of the main producers of globally traded farming commodities. Traditional methods to assess environmental implications of this demand rely on international trade material flows at country resolution; we argue for the need of finer scales that capture spatial heterogeneity in environmental variables in the regions of production, and that account for differential sourcing within the borders of a country of production. To illustrate this, we obtain virtual water flows from Brazilian municipalities to countries of consumption, by allocating high-resolution water footprints of sugarcane and soy production to spatially-explicit material trade flows. We found that this approach results in differences of virtual water use estimations of over 20% when compared to approaches that disregard spatial heterogeneity in sourcing patterns, for three of the main consumers of the analysed crops. This discrepancy against methods using national resolution in trade flows is determined by national heterogeneity in water resources, and differential sourcing. To illustrate the practical implications of this approach, we relate virtual water flows to water stress, identifying where global demand for water coincides with high levels of water stress. For instance, the virtual water flows for Brazilian sugarcane sourced by China were disproportionally less associated to areas with higher water stress when compared to those of the EU, due to EU’s much higher reliance on sugarcane from water scarce areas in Northeast Brazil. Our findings indicate that the policy relevance of current assessments of virtual water flows that rely on trade data aggregated at the national level may be hampered, as they do not capture the spatial heterogeneity in water resources, water use and water management options.

  15. Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs

    NASA Astrophysics Data System (ADS)

    Teshager, Awoke Dagnew; Gassman, Philip W.; Secchi, Silvia; Schoof, Justin T.; Misgna, Girmaye

    2016-04-01

    Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

  16. Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs.

    PubMed

    Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T; Misgna, Girmaye

    2016-04-01

    Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner. PMID:26616430

  17. A spatially and temporally explicit risk assessment for salmon from a prey base exposed to agricultural insecticides.

    PubMed

    Poletika, Nicholas N; Teply, Mark; Dominguez, Lawrence G; Cramer, Steven P; Schocken, Mark J; Habig, Clifford; Kern, Matthew; Ochoa-Acuña, Hugo; Mitchell, Gary C

    2012-04-01

    This risk assessment applied a framework for determining probable co-occurrence of juvenile spring Chinook salmon (Oncorhynchus tshawytscha) with agricultural pesticides in the Willamette Basin, Oregon (Teply et al. this issue) to characterize risk to the threatened population. The assessment accounted for spatial and temporal distribution of 6 acetylcholinesterase-inhibiting insecticides in salmonid habitat within the basin and their relative contributions to mixture toxicity estimated from chemical monitoring data. The 6 insecticides were chlorpyrifos, diazinon, malathion, carbaryl, carbofuran, and methomyl. Seasonal distributions of the juvenile salmon prey base across the basin were determined and compared to co-occurrence with the insecticide mixture to determine the probability of prey reduction and reduced production of juvenile fish. Probability of effect on freshwater aquatic invertebrates was based on acute toxicity species sensitivity distributions (normalized to the most potent compound, chlorpyrifos) using a novel approach to apply the toxicological concept of concentration addition to species sensitivity distributions with differing slopes. The chlorpyrifos distribution was then used to determine relative sensitivity among various species tested within the important taxa making up the prey base. A prey base index was devised, incorporating diet composition and prey availability, to evaluate the indirect effects of the insecticide mixture on juvenile salmon production occurring as a result of a reduction in the prey base. Our analysis targeted fish use of backwater and off-channel habitat units, because they generally coincide with agricultural lands in lowlands and represent shallow habitat with limited water exchange. The percentage of agricultural land use within 300 m of critical habitat stream reaches was used to scale chemical measurement data from a site with high agricultural land use across the full extent of the basin to provide estimates of

  18. Effects of habitat heterogeneity at multiple spatial scales on fish community assembly.

    PubMed

    Yeager, Lauren A; Layman, Craig A; Allgeier, Jacob E

    2011-09-01

    Habitat variability at multiple spatial scales may affect community structure within a given habitat patch, even within seemingly homogenous landscapes. In this context, we tested the importance of habitat variables at two spatial scales (patch and landscape) in driving fish community assembly using experimental artificial reefs constructed across a gradient of seagrass cover in a coastal bay of The Bahamas. We found that species richness and benthic fish abundance increased over time, but eventually reached an asymptote. The correlation between habitat variables and community structure strengthened over time, suggesting deterministic processes were detectable in community assembly. Abundance of benthic fishes, as well as overall community structure, were predicted by both patch- and landscape-scale variables, with the cover of seagrass at the landscape-scale emerging as the most important explanatory variable. Results of this study indicate that landscape features can drive differences in community assembly even within a general habitat type (i.e., within seagrass beds). A primary implication of this finding is that human activities driving changes in seagrass cover may cause significant shifts in faunal community structure well before complete losses of seagrass habitat. PMID:21409448

  19. An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

    NASA Astrophysics Data System (ADS)

    Moulds, S.; Buytaert, W.; Mijic, A.

    2015-04-01

    Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

  20. Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

    PubMed Central

    Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

    2015-01-01

    Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

  1. Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

    NASA Technical Reports Server (NTRS)

    Kovalskyy, V.; Henebry, G. M.; Adusei, B.; Hansen, M.; Roy, D. P.; Senay, G.; Mocko, D. M.

    2011-01-01

    A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and

  2. DNA as a Powerful Tool for Morphology Control, Spatial Positioning, and Dynamic Assembly of Nanoparticles

    PubMed Central

    2015-01-01

    Conspectus Several properties of nanomaterials, such as morphologies (e.g., shapes and surface structures) and distance dependent properties (e.g., plasmonic and quantum confinement effects), make nanomaterials uniquely qualified as potential choices for future applications from catalysis to biomedicine. To realize the full potential of these nanomaterials, it is important to demonstrate fine control of the morphology of individual nanoparticles, as well as precise spatial control of the position, orientation, and distances between multiple nanoparticles. In addition, dynamic control of nanomaterial assembly in response to multiple stimuli, with minimal or no error, and the reversibility of the assemblies are also required. In this Account, we summarize recent progress of using DNA as a powerful programmable tool to realize the above goals. First, inspired by the discovery of genetic codes in biology, we have discovered DNA sequence combinations to control different morphologies of nanoparticles during their growth process and have shown that these effects are synergistic or competitive, depending on the sequence combination. The DNA, which guides the growth of the nanomaterial, is stable and retains its biorecognition ability. Second, by taking advantage of different reactivities of phosphorothioate and phosphodiester backbone, we have placed phosphorothioate at selective positions on different DNA nanostructures including DNA tetrahedrons. Bifunctional linkers have been used to conjugate phosphorothioate on one end and bind nanoparticles or proteins on the other end. In doing so, precise control of distances between two or more nanoparticles or proteins with nanometer resolution can be achieved. Furthermore, by developing facile methods to functionalize two hemispheres of Janus nanoparticles with two different DNA sequences regioselectively, we have demonstrated directional control of nanomaterial assembly, where DNA strands with specific hybridization serve as

  3. Unraveling the interplay of community assembly processes acting on multiple niche axes across spatial scales.

    PubMed

    Trisos, Christopher H; Petchey, Owen L; Tobias, Joseph A

    2014-11-01

    How the relative importance of community assembly processes varies with spatial scale is the focus of intensive debate, in part because inferring the scales at which specific niche-based processes act is difficult. One obstacle is that standard phylogenetic and functional diversity metrics may integrate the signals of multiple processes when combining separate niche axes into one variable (multiple-niche-axis metrics), potentially obscuring overlapping niche-based processes. We use simulations to evaluate the power of these metrics to detect competition and habitat filtering when these processes operate across multiple niche axes and vary in their relative importance. We then test for both processes at a range of spatial scales in a Neotropical bird assemblage. Simulations revealed that multiple-niche-axis metrics had low power to detect competition and habitat filtering when a mix of both processes acts across niche axes, whereas metrics focused on single-niche axes were better able to deal with this complexity. We found the same contrast in bird communities, where both competition and habitat filtering were detected at the scale of individual territories, but only by single-niche-axis metrics focused on specific niche axes (e.g., foraging traits). Our results suggest that multiple-niche-axis metrics may produce misleading evidence that niche-based processes are partitioned, particularly across scales, and highlight the importance of analyzing functional diversity patterns on individual niche axes when testing assembly models. PMID:25325744

  4. Spatial Control of Epsin-induced Clathrin Assembly by Membrane Curvature.

    PubMed

    Holkar, Sachin S; Kamerkar, Sukrut C; Pucadyil, Thomas J

    2015-06-01

    Epsins belong to the family of highly conserved clathrin-associated sorting proteins that are indispensable for clathrin-mediated endocytosis, but their precise functions remain unclear. We have developed an assay system of budded supported membrane tubes displaying planar and highly curved membrane surfaces to analyze intrinsic membrane curvature preference shown by clathrin-associated sorting proteins. Using real-time fluorescence microscopy, we find that epsin preferentially partitions to and assembles clathrin on highly curved membrane surfaces. Sorting of epsin to regions of high curvature strictly depends on binding to phosphatidylinositol 4,5-bisphosphate. Fluorescently labeled clathrins rapidly assemble as foci, which in turn cluster epsin, while maintaining tube integrity. Clathrin foci grow in intensity with a typical time constant of ∼75 s, similar to the time scales for coated pit formation seen in cells. Epsin therefore effectively senses membrane curvature to spatially control clathrin assembly. Our results highlight the potential role of membrane curvature in orchestrating the myriad molecular interactions necessary for the success of clathrin-mediated membrane budding. PMID:25837255

  5. Spatial Control of Epsin-induced Clathrin Assembly by Membrane Curvature*♦

    PubMed Central

    Holkar, Sachin S.; Kamerkar, Sukrut C.; Pucadyil, Thomas J.

    2015-01-01

    Epsins belong to the family of highly conserved clathrin-associated sorting proteins that are indispensable for clathrin-mediated endocytosis, but their precise functions remain unclear. We have developed an assay system of budded supported membrane tubes displaying planar and highly curved membrane surfaces to analyze intrinsic membrane curvature preference shown by clathrin-associated sorting proteins. Using real-time fluorescence microscopy, we find that epsin preferentially partitions to and assembles clathrin on highly curved membrane surfaces. Sorting of epsin to regions of high curvature strictly depends on binding to phosphatidylinositol 4,5-bisphosphate. Fluorescently labeled clathrins rapidly assemble as foci, which in turn cluster epsin, while maintaining tube integrity. Clathrin foci grow in intensity with a typical time constant of ∼75 s, similar to the time scales for coated pit formation seen in cells. Epsin therefore effectively senses membrane curvature to spatially control clathrin assembly. Our results highlight the potential role of membrane curvature in orchestrating the myriad molecular interactions necessary for the success of clathrin-mediated membrane budding. PMID:25837255

  6. A spatially explicit model of runoff, evaporation, and lake extent: Application to modern and late Pleistocene lakes in the Great Basin region, western United States

    NASA Astrophysics Data System (ADS)

    Matsubara, Yo; Howard, Alan D.

    2009-06-01

    A spatially explicit hydrological model was applied to the Great Basin in the western United States to predict runoff magnitude and lake distributions under modern and late Pleistocene conditions. The model iteratively routes runoff through depression to find a steady state solution and was calibrated with mean annual precipitation, pan evaporation, temperature, and stream runoff data. The predicted lake distribution provides a close match to present-day lakes. For the late Pleistocene, the sizes of lakes Bonneville and Lahontan are well predicted by linear combinations of 0.2°-5.8°C decreases in temperature and corresponding increases in precipitation from 2.0 to 1.0 times modern values. This corresponds to runoff depths ranging from 1.7 to 4.1 times the present values and yearly evaporation from 0.4 to 1 times modern values. To reproduce Lake Manly, however, combinations of temperature decreases up to 9°C or precipitation up to 2.8 times the present values were required.

  7. Environmental Distributions of Benzo[a]pyrene in China: Current and Future Emission Reduction Scenarios Explored Using a Spatially Explicit Multimedia Fate Model.

    PubMed

    Zhu, Ying; Tao, Shu; Price, Oliver R; Shen, Huizhong; Jones, Kevin C; Sweetman, Andrew J

    2015-12-01

    SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction. PMID:25942589

  8. Functional strategies drive community assembly of stream fishes along environmental gradients and across spatial scales.

    PubMed

    Troia, Matthew J; Gido, Keith B

    2015-02-01

    Trade-offs among functional traits produce multi-trait strategies that shape species' interactions with the environment and drive the assembly of local communities from regional species pools. Stream fish communities vary along stream size gradients and among hierarchically structured habitat patches, but little is known about how the dispersion of strategies varies along environmental gradients and across spatial scales. We used null models to quantify the dispersion of reproductive life history, feeding, and locomotion strategies in communities sampled at three spatial scales in a prairie stream network in Kansas, USA. Strategies were generally underdispersed at all spatial scales, corroborating the longstanding notion of abiotic filtering in stream fish communities. We tested for variation in strategy dispersion along a gradient of stream size and between headwater streams draining different ecoregions. Reproductive life history strategies became increasingly underdispersed moving from downstream to upstream, suggesting that abiotic filtering is stronger in headwaters. This pattern was stronger among reaches compared to mesohabitats, supporting the premise that differences in hydrologic regime among reaches filter reproductive life history strategies. Feeding strategies became increasingly underdispersed moving from upstream to downstream, indicating that environmental filters associated with stream size affect the dispersion of feeding and reproductive life history in opposing ways. Weak differences in strategy dispersion were detected between ecoregions, suggesting that different abiotic filters or strategies drive community differences between ecoregions. Given the pervasiveness of multi-trait strategies in plant and animal communities, we conclude that the assessment of strategy dispersion offers a comprehensive approach for elucidating mechanisms of community assembly. PMID:25502608

  9. Designing Optimal LNG Station Network for U.S. Heavy-Duty Freight Trucks using Temporally and Spatially Explicit Supply Chain Optimization

    NASA Astrophysics Data System (ADS)

    Lee, Allen

    The recent natural gas boom has opened much discussion about the potential of natural gas and specifically Liquefied Natural Gas (LNG) in the United States transportation sector. The switch from diesel to natural gas vehicles would reduce foreign dependence on oil, spur domestic economic growth, and potentially reduce greenhouse gas emissions. LNG provides the most potential for the medium to heavy-duty vehicle market partially due to unstable oil prices and stagnant natural gas prices. As long as the abundance of unconventional gas in the United States remains cheap, fuel switching to natural gas could provide significant cost savings for long haul freight industry. Amid a growing LNG station network and ever increasing demand for freight movement, LNG heavy-duty truck sales are less than anticipated and the industry as a whole is less economic than expected. In spite of much existing and mature natural gas infrastructure, the supply chain for LNG is different and requires explicit and careful planning. This thesis proposes research to explore the claim that the largest obstacle to widespread LNG market penetration is sub-optimal infrastructure planning. No other study we are aware of has explicitly explored the LNG transportation fuel supply chain for heavy-duty freight trucks. This thesis presents a novel methodology that links a network infrastructure optimization model (represents supply side) with a vehicle stock and economic payback model (represents demand side). The model characterizes both a temporal and spatial optimization model of future LNG transportation fuel supply chains in the United States. The principal research goal is to assess the economic feasibility of the current LNG transportation fuel industry and to determine an optimal pathway to achieve ubiquitous commercialization of LNG vehicles in the heavy-duty transport sector. The results indicate that LNG is not economic as a heavy-duty truck fuel until 2030 under current market conditions

  10. Predicting Biomass and Species Composition in the Siberian Boreal Forest Using a New Spatially-Explicit Vegetation Dynamics Model: Model Development, Calibration, and Climate Sensitivity Analysis.

    NASA Astrophysics Data System (ADS)

    Brazhnik, K.; Shugart, H. H., Jr.

    2014-12-01

    Circumpolar boreal forests contain one third of the terrestrial carbon stores, and it has been shown that they are already affected by climate change. As temperature and precipitation regimes shift, the total biomass and species composition may change in ways that promote further warming on the regional level through atmosphere-vegetation feedbacks. Changes in vegetation cover and the resulting atmosphere-vegetation feedbacks may be the determining factors in how regional terrestrial carbon stores change with climate change. This project reports on the development of a new spatially-explicit individual-based gap model SibBorK that can be utilized to investigate the potential changes in biomass and species composition in the Siberian boreal forest over the coming decades and centuries. SibBorK tracks the establishment, growth, and mortality of individual trees on 0.01-ha plots within a 9-ha simulation area. The new model is based on the principles of the ZELIG vegetation model, implemented in Python to facilitate interface with geographic information systems for explicit modeling of vegetation across artificial and real terrain. SibBorK was trained on modal (actual) regional forestry yield tables for southern taiga region of central Siberia. The model was calibrated and tested against the regional forestry yield tables, and further tested against an independent dataset from a forest inventory. Model comparisons were made on monospecies and mixed species stands, and included the evaluation of total stand biomass, species-specific biomass, species composition, and stem density based on site index and terrain elevation. Additionally, species distribution along altitudinal gradients and total biomass for specific locations was independently tested against other published forest inventory values. SibBorK is particularly good at predicting biomass and species composition on poor soils, with Orlov site indices III-V, which dominate the Siberian landscape. Herein, Sib