Science.gov

Sample records for individual-based spatially-explicit model

  1. 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...

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae

    PubMed Central

    Wang, Ming; Cribb, Bronwen; Clarke, Anthony R.; Hanan, Jim

    2016-01-01

    Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of

  7. A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae.

    PubMed

    Wang, Ming; Cribb, Bronwen; Clarke, Anthony R; Hanan, Jim

    2016-01-01

    Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies' behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies' movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of

  8. Effect of plant dynamic processes on African vegetation responses to climate change: Analysis using the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM)

    NASA Astrophysics Data System (ADS)

    Sato, Hisashi; Ise, Takeshi

    2012-09-01

    We applied a dynamic global vegetation model (DGVM) to the African continent. After calibration, the model reproduced geographical distributions of the continent's biomes, annual gross primary productivity (GPP), and biomass under current climatic conditions. The model is driven by the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A1B scenario of rising CO2, and by climate changes during the twenty-first century resulting from the change in CO2concentrations, simulated by a coupled Model for Interdisciplinary Research on Climate (MIROC) ocean atmosphere model. Simulations under this condition revealed time lags between environmental change and biome change, with the extent of these lags depending largely on the type of biome change. A switch in forest type was accompanied by the longest delay in biome change among all changes classified, indicating that resident trees largely prevent the establishment of nonresident tree types adapted to the new environment, and that tree growth requires additional years after successful establishment. In addition, assumptions for tree dispersal, which determine whether nonresident tree types can be established, modified the patterns of biome change under the twenty-first-century environment: under the assumption that nonresident tree types cannot be established even if environmental conditions change, the extent of the forest type switch and the development of forest and savanna were suppressed, while forest dieback was enhanced. These changes accompanied a slowing of the increasing trend in net primary productivity (NPP), biomass, and soil carbon during the twenty-first century and in subsequent years. These results quantitatively demonstrate that both patch dynamics and invasive tree recruitment significantly modify the transient change in vegetation distribution and function under a changing environment on the African continent.

  9. Effect of plant dynamic processes on African vegetation responses to climate change: Analysis using the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM)

    NASA Astrophysics Data System (ADS)

    SATO, H.; Ise, T.

    2012-12-01

    We applied a dynamic global vegetation model (DGVM) to the African continent. After calibration, the model reproduced geographical distributions of the continent's biomes, annual gross primary productivity (GPP), and biomass under current climatic conditions. The model is driven by the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A1B scenario of rising CO2, and by climate changes during the 21st century resulting from the change in CO2 concentrations, simulated by a coupled Model for Interdisciplinary Research on Climate (MIROC) ocean atmosphere model. Simulations under this condition revealed time lags between environmental change and biome change, with the extent of these lags depending largely on the type of biome change. A switch in forest type was accompanied by the longest delay in biome change among all changes classified, indicating that resident trees largely prevent the establishment of non-resident tree types adapted to the new environment, and that tree growth requires additional years after successful establishment. In addition, assumptions for tree dispersal, which determine whether non-resident tree types can be established, modified the patterns of biome change under the 21st century environment: under the assumption that non-resident tree types cannot be established even if environmental conditions change, the extent of the forest type switch and the development of forest and savanna were suppressed, while forest dieback was enhanced. These changes accompanied a slowing of the increasing trend in net primary productivity (NPP), biomass, and soil carbon during the 21st century and in subsequent years. These results quantitatively demonstrate that both patch dynamics and invasive tree recruitment significantly modify the transient change in vegetation distribution and function under a changing environment on the African continent. Sato H & Ise T (2012) Journal of Geophysical Research - Biogeosciences

  10. 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.

  11. The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

    SciTech Connect

    Kostova, T; Carlsen, T

    2003-11-21

    We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in the literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.

  12. 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.

  13. Stay off the motorway: Resolving the pre-recruitment life history dynamics of the European anchovy in the SW Mediterranean through a spatially-explicit individual-based model (SEIBM)

    NASA Astrophysics Data System (ADS)

    Catalán, Ignacio A.; Macías, Diego; Solé, Jordi; Ospina-Álvarez, Andrés; Ruiz, Javier

    2013-04-01

    We explore the underlying mechanisms of the early life history dynamics of the European anchovy, Engraulis encrasicolus, in the SW Mediterranean. By using a 3D ROMS hydrodynamic model coupled to an individual-based model (IBM) of the larval stages of the European anchovy, we tested the following hypotheses: (1) the plausible effective spawning zones (those generating late larvae to the known nursery grounds) are mainly found in the vicinity of Malaga Bay, as suggested by published empirical data; (2) the observed, back-calculated growth of larvae sampled in the nursery grounds can be reasonably simulated by a simple temperature-dependent growth model; and (3) the inclusion of biological behavior in the IBM significantly improves the match between the observed and modeled late-larval recruitment and/or growth patterns. We performed simulations for the peak spawning season in 2008, for which survey data were available, and an average climatological run. Hypothesis 1 was accepted, whereas hypothesis 2 resulted in a good imitation of anchovy growth only after 10 days post-hatch. The inclusion of an empirically derived equation for egg buoyancy in the model (hypothesis 3) resulted in a slight improvement of the model of late-larval recruitment patterns. Finally, our model was used to explore possible retention-based nursery areas in the whole Alboran Sea. Our simulations showed to agree well with the existing data both in the European and in the African coast and confer the physics a dominant role in shaping the spatial dynamics of early life stages of anchovy in the area.

  14. 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.

  15. 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.

  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. 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...

  19. 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.

  20. 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...

  1. 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.

  2. 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 ...

  3. 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...

  4. 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.

  5. 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

  6. 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

  7. AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

    EPA Science Inventory

    We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

  8. 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

  9. 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.

  10. 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...

  11. 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.

  12. [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

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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...

  4. 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

  5. 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

  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.

    2012-12-01

    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

  7. 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

  8. 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.

  9. 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.

  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. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. AN INDIVIDUAL-BASED SIMULATION MODEL FOR MOTTLED SCULPIN (COTTUS BAIRDI) IN A SOUTHERN APPALACHIAN STREAM

    EPA Science Inventory

    We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was bas...

  1. A spatially explicit neutral model of beta-diversity in tropical forests.

    PubMed

    Chave, Jérôme; Leigh, Egbert G

    2002-09-01

    To represent species turnover in tropical rain forest, we use a neutral model where a tree's fate is not affected by what species it belongs to, seeds disperse a limited distance from their parents, and speciation is in equilibrium with random extinction. We calculate the similarity function, the probability F(r) that two trees separated by a distance r belong to the same species, assuming that the dispersal kernel P(r), the distribution of seeds about their parents and the prospects of mortality and reproduction, are the same for all trees regardless of their species. If P(r) is radially symmetric Gaussian with mean-square dispersal distance sigma, F(r) can be expressed in closed form. If P(r) is a radially symmetric Cauchy distribution, then, in two-dimensional space, F(r) is proportional to 1/r for large r. Analytical results are compared with individual-based simulations, and the relevance to field observations is discussed. PMID:12167354

  2. 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...

  3. Analysis of Sensitivity and Uncertainty in an Individual-Based Model of a Threatened Wildlife Species

    EPA Science Inventory

    We present a multi-faceted sensitivity analysis of a spatially explicit, individual-based model (IBM) (HexSim) of a threatened species, the Northern Spotted Owl (Strix occidentalis caurina) on a national forest in Washington, USA. Few sensitivity analyses have been conducted on ...

  4. 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.

  5. 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...

  6. 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

  7. 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

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

    Increased availability and quality of near real-time data should target at better understanding of predictive skills of distributed hydrological models. Nevertheless, predictions of regional scale water fluxes and states remains of great challenge to the scientific community. Large scale hydrological models are used for prediction of soil moisture, evapotranspiration and other related water states and fluxes. They are usually properly constrained against river discharge, which is an integral variable. Rakovec et al (2016) recently demonstrated that constraining model parameters against river discharge is necessary, but not a sufficient condition. Therefore, we further aim at scrutinizing appropriate incorporation of readily available information into a hydrological model that may help to improve the realism of hydrological processes. It is important to analyze how complementary datasets besides observed streamflow and related signature measures can improve model skill of internal model variables during parameter estimation. Among those products suitable for further scrutiny are for example the GRACE satellite observations. Recent developments of using this dataset in a multivariate fashion to complement traditionally used streamflow data within the distributed model mHM (www.ufz.de/mhm) are presented. Study domain consists of 80 European basins, which cover a wide range of distinct physiographic and hydrologic regimes. First-order data quality check ensures that heavily human influenced basins are eliminated. For river discharge simulations we show that model performance of discharge remains unchanged when complemented by information from the GRACE product (both, daily and monthly time steps). Moreover, the GRACE complementary data lead to consistent and statistically significant improvements in evapotranspiration estimates, which are evaluated using an independent gridded FLUXNET product. We also show that the choice of the objective function used to estimate

  16. 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.

  17. 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...

  18. 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

  19. 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

  20. 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.

  1. Spatially explicit modeling of lesser prairie-chicken lek density in Texas

    USGS Publications Warehouse

    Timmer, Jennifer M.; Butler, M.J.; Ballard, Warren; Boal, Clint W.; Whitlaw, H.A.

    2014-01-01

    As with many other grassland birds, lesser prairie-chickens (Tympanuchus pallidicinctus) have experienced population declines in the Southern Great Plains. Currently they are proposed for federal protection under the Endangered Species Act. In addition to a history of land-uses that have resulted in habitat loss, lesser prairie-chickens now face a new potential disturbance from energy development. We estimated lek density in the occupied lesser prairie-chicken range of Texas, USA, and modeled anthropogenic and vegetative landscape features associated with lek density. We used an aerial line-transect survey method to count lesser prairie-chicken leks in spring 2010 and 2011 and surveyed 208 randomly selected 51.84-km(2) blocks. We divided each survey block into 12.96-km(2) quadrats and summarized landscape variables within each quadrat. We then used hierarchical distance-sampling models to examine the relationship between lek density and anthropogenic and vegetative landscape features and predict how lek density may change in response to changes on the landscape, such as an increase in energy development. Our best models indicated lek density was related to percent grassland, region (i.e., the northeast or southwest region of the Texas Panhandle), total percentage of grassland and shrubland, paved road density, and active oil and gas well density. Predicted lek density peaked at 0.39leks/12.96km(2) (SE=0.09) and 2.05leks/12.96km(2) (SE=0.56) in the northeast and southwest region of the Texas Panhandle, respectively, which corresponds to approximately 88% and 44% grassland in the northeast and southwest region. Lek density increased with an increase in total percentage of grassland and shrubland and was greatest in areas with lower densities of paved roads and lower densities of active oil and gas wells. We used the 2 most competitive models to predict lek abundance and estimated 236 leks (CV=0.138, 95% CI=177-306leks) for our sampling area. Our results suggest that

  2. 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.

  3. A spatially explicit suspended-sediment load model for western Oregon

    USGS Publications Warehouse

    Wise, Daniel R.; O'Connor, Jim

    2016-01-01

    Knowledge of the regionally important patterns and factors in suspended-sediment sources and transport could support broad-scale, water-quality management objectives and priorities. Because of biases and limitations of this model, however, these results are most applicable for general comparisons and for broad areas such as large watersheds. For example, despite having similar area, precipitation, and land-use, the Umpqua River Basin generates 68 percent more suspended sediment than the Rogue River Basin, chiefly because of the large area of Coast Range sedimentary province in the Umpqua River Basin. By contrast, the Rogue River Basin contains a much larger area of Klamath terrane rocks, which produce significantly less suspended load, although recent fire disturbance (in 2002) has apparently elevated suspended sediment yields in the tributary Illinois River watershed. Fine-scaled analysis, however, will require more intensive, locally focused measurements.

  4. 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.

  5. 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.

  6. 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.

  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 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

  9. 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.

  10. 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 ...

  11. 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.

  12. 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.

  13. "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.

  14. The development of a spatially-explicit, individual-based, disease model for frogs and the chytrid fungus

    EPA Science Inventory

    Background / Question / Methods The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and even extinctions worldwide. Transmission of the fungus between amphibian hosts occurs via motile zoospores, which are produced on...

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. Individual-based modelling: an essential tool for microbiology.

    PubMed

    Ferrer, Jordi; Prats, Clara; López, Daniel

    2008-04-01

    Micro-organisms play a central role in every ecosystem and in the global biomass cycle. They are strongly involved in many fields of human interest, from medicine to the food industry and waste control. Nevertheless, most micro-organisms remain almost unknown, and nearly 99% of them have not yet been successfully cultured in vitro. Therefore, new approaches and new tools must be developed in order to understand the collective behaviour of microbial communities in any natural or artificial setting. In particular, theoretical and practical methodologies to deal with such systems at a mesoscopic level of description (covering the range from 100 to 10(8) cells) are required. Individual-based modelling (IBM) has become a widely used tool for describing complex systems made up of autonomous entities, such as ecosystems and social networks. Individual-based models (IBMs) provide some advantages over the traditional whole-population models: (a) they are bottom-up approaches, so they describe the behaviour of a system as a whole by establishing procedural rules for the individuals and for their interactions, and thus allow more realistic assumptions for the model of the individuals than population models do; (b) they permit the introduction of randomness and individual variability, so they can reproduce the diversity found in real systems; and (c) they can account for individual adaptive behaviour to their environmental conditions, so the evolution of the whole system arises from the dynamics that govern individuals in their pursuit of optimal fitness. However, they also present some drawbacks: they lack the clarity of continuous models and may easily become rambling, which makes them difficult to analyse and communicate. All in all, IBMs supply a holistic description of microbial systems and their emerging properties. They are specifically appropriate to deal with microbial communities in non-steady states, and spatially explicit IBMs are particularly appropriate to study

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. Uncertainty analysis of a spatially-explicit annual water-balance model: case study of the Cape Fear catchment, NC

    NASA Astrophysics Data System (ADS)

    Hamel, P.; Guswa, A. J.

    2014-10-01

    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 framework. Our study involved the comparison of ten subcatchments in the Cape Fear watershed, NC, ranging in size and land use configuration. We analyzed the model sensitivity to the eco-hydrological parameters and the effect of extrapolating a lumped theory to a fully distributed model. Comparison of the model predictions with observations and with a lumped water balance model confirmed that the model is able to represent differences in land uses. Our results also emphasize the effect of climate input errors, especially annual precipitation, and errors in the eco-hydrological parameter Z, which are both comparable to the model structure uncertainties. In practice, 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 the results are inherently local, analysis of the model structure suggests that many insights from this study will hold globally. Further work toward characterization of uncertainties in such simple models will help identify the regions and decision contexts where the model predictions may be used with confidence.

  9. 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.

  10. A Spatially Explicit Degree-day Model of Rift Valley Fever Transmission Risk in the Continental United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A degree-day model was used to assess the risk of Rift Valley Fever (RVF) transmission within five target states in the continental United States: California, Minnesota, Nebraska, New York, and Texas. Each state was evaluated on a 10-km grid using the average of historical daily temperature extreme...

  11. 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 ...

  12. Risk of endocrine disruption to fish in the Yellow River catchment in China assessed using a spatially explicit model.

    PubMed

    Liu, Xiaowei; Keller, Virginie; Dumont, Egon L; Shi, Jianghong; Johnson, Andrew C

    2015-12-01

    The global water availability assessment (GWAVA) model, incorporating regional water abstractions and reservoir information, was used to model the human-sourced steroid estrogens estrone (E1) and estradiol (E2) in the Yellow River catchment (China). The river flows in the main stem were calibrated using gauged flows. Following a review of Chinese data on estrogen discharge from a range of sewage treatment plants, low, median, and high discharge rates were identified and used as best, expected, and worst-case scenarios, respectively. For any given location, the temporal variation of modeled estrogen levels was summarized using the mean and upper 90th percentile, which is where the model predicts 90% of values would be below this concentration. The predicted means and 90th percentiles for E1 were comparable to previous E1 measurements reported in the river. For the whole catchment, only 19% (mean value) of the river system by length was predicted to exceed 1 ng/L E2 equivalents (EEQs) using expected estrogen sewage discharge. Only 3% of the network by length was predicted to exceed the dangerously high 10 ng/L EEQ when considering 90th percentile concentrations. The highest exposures were in the Fen and Wei tributaries. Endocrine disruption risk from estrogens was predicted to be minimal in the main stem. Only in the worst-case discharge scenario and 90th percentile predicted concentrations were the most downstream river reaches of the main stem predicted to be at risk. Reservoirs appeared to be helpful in reducing estrogen concentrations thanks to longer water residence facilitating biodegradation. PMID:26118536

  13. Quantifying flow-dependent changes in subyearling fall chinook salmon rearing habitat using two-dimensional spatially explicit modeling

    USGS Publications Warehouse

    Tiffan, K.F.; Garland, R.D.; Rondorf, D.W.

    2002-01-01

    We used an analysis based on a geographic information system (GIS) to determine the amount of rearing habitat and stranding area for subyearling fall chinook salmon Oncorhynchus tshawytscha in the Hanford Reach of the Columbia River at steady-state flows ranging from 1,416 to 11,328 m3/s. High-resolution river channel bathymetry was used in conjunction with a two-dimensional hydrodynamic model to estimate water velocities, depths, and lateral slopes throughout our 33-km study area. To relate the probability of fish presence in nearshore habitats to measures of physical habitat, we developed a logistic regression model from point electrofishing data. We only considered variables that were compatible with a GIS and therefore excluded other variables known to be important to juvenile salmonids. Water velocity and lateral slope were the only two variables included in our final model. The amount of available rearing habitat generally decreased as flow increased, with the greatest decreases occurring between 1,416 and 4,814 m3/s. When river discharges were between 3,682 and 7,080 m3/s, flow fluctuations of 566 m3/s produced the smallest change in available rearing area (from -6.3% to +6.8% of the total). Stranding pool area was greatly reduced at steady-state flows exceeding 4,531 m3/s, but the highest net gain in stranding area was produced by 850 m3/s decreases in flow when river discharges were between 5,381 and 5,664 m3/s. Current measures to protect rearing fall chinook salmon include limiting flow fluctuations at Priest Rapids Dam to 850 m3/s when the dam is spilling water and when the weekly flows average less than 4,814 m3/s. We believe that limiting flow fluctuations at all discharges would further protect subyearling fall chinook salmon.

  14. 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.

  15. Biodiversity patterns from an individual-based competition model on niche and physical spaces

    NASA Astrophysics Data System (ADS)

    Fort, H.; Inchausti, P.

    2012-02-01

    We formulate a microscopic (individual-based and spatially explicit) ecological model to assess whether key patterns of community structure, species-packing and the spatial distribution of species are robust to relaxing the mean-field approximation made in classical ecological models. In this model of community dynamics species compete both locally in physical space and along a niche axis and it includes just two free parameters, σ, controlling the extent of competition in niche space, and t, the simulation time. This minimalistic model (1) reproduces with considerable accuracy the dynamic sequence of relative species abundances, biodiversity indices and species-area relationships that are empirically found in censuses of trees in a well-studied tropical forest; (2) shows that the clumpy pattern of niches leading to long-lasting species coexistence obtained by classical competition models is robust to relaxing the mean-field assumption. Nevertheless species that are clumped in niche space are simultaneously spatially segregated.

  16. A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential

    PubMed Central

    Dunnett, Alex J; Adjiman, Claire S; Shah, Nilay

    2008-01-01

    Background Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities. Results Ethanol production costs for current technologies decrease significantly from $0.71 to $0.58 per litre with increasing economies of scale, up to a maximum single-plant capacity of 550 × 106 l year-1. The development of high-yielding energy crops and consolidated bio-processing realises significant cost reductions, with production costs ranging from $0.33 to $0.36 per litre. Increased feedstock yields result in systems of eight fully integrated plants operating within a 500 × 500 km2 region, each producing between 1.24 and 2.38 × 109 l year-1 of pure ethanol. A limited potential for distributed processing and centralised purification systems is identified, requiring developments in modular, ambient pretreatment and fermentation technologies and the pipeline transport of pure ethanol. Conclusion The conceptual and mathematical modelling framework developed provides a valuable tool for the assessment and optimisation of the lignocellulosic bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple plant systems. This information is invaluable in ensuring (near-)cost-optimal strategic development within the sector at the regional and national scale. The framework is flexible and can thus

  17. 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.

  18. 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

  19. 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.

  20. Spatially Explicit Modeling of Schistosomiasis Risk in Eastern China Based on a Synthesis of Epidemiological, Environmental and Intermediate Host Genetic Data

    PubMed Central

    Schrader, Matthias; Hauffe, Torsten; Zhang, Zhijie; Davis, George M.; Jopp, Fred; Remais, Justin V.; Wilke, Thomas

    2013-01-01

    Schistosomiasis japonica is a major parasitic disease threatening millions of people in China. Though overall prevalence was greatly reduced during the second half of the past century, continued persistence in some areas and cases of re-emergence in others remain major concerns. As many regions in China are approaching disease elimination, obtaining quantitative data on Schistosoma japonicum parasites is increasingly difficult. This study examines the distribution of schistosomiasis in eastern China, taking advantage of the fact that the single intermediate host serves as a major transmission bottleneck. Epidemiological, population-genetic and high-resolution ecological data are combined to construct a predictive model capable of estimating the probability that schistosomiasis occurs in a target area (“spatially explicit schistosomiasis risk”). Results show that intermediate host genetic parameters are correlated with the distribution of endemic disease areas, and that five explanatory variables—altitude, minimum temperature, annual precipitation, genetic distance, and haplotype diversity—discriminate between endemic and non-endemic zones. Model predictions are correlated with human infection rates observed at the county level. Visualization of the model indicates that the highest risks of disease occur in the Dongting and Poyang lake regions, as expected, as well as in some floodplain areas of the Yangtze River. High risk areas are interconnected, suggesting the complex hydrological interplay of Dongting and Poyang lakes with the Yangtze River may be important for maintaining schistosomiasis in eastern China. Results demonstrate the value of genetic parameters for risk modeling, and particularly for reducing model prediction error. The findings have important consequences both for understanding the determinants of the current distribution of S. japonicum infections, and for designing future schistosomiasis surveillance and control strategies. The results

  1. 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.

  2. 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

  3. 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

  4. 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

  5. An individual-based growth and competition model for coastal redwood forest restoration

    USGS Publications Warehouse

    van Mantgem, Phillip J.; Das, Adrian J.

    2014-01-01

    Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

  6. Individual-based models in ecology after four decades

    PubMed Central

    Grimm, Volker

    2014-01-01

    Individual-based models simulate populations and communities by following individuals and their properties. They have been used in ecology for more than four decades, with their use and ubiquity in ecology growing rapidly in the last two decades. Individual-based models have been used for many applied or “pragmatic” issues, such as informing the protection and management of particular populations in specific locations, but their use in addressing theoretical questions has also grown rapidly, recently helping us to understand how the sets of traits of individual organisms influence the assembly of communities and food webs. Individual-based models will play an increasingly important role in questions posed by complex ecological systems. PMID:24991416

  7. Can remote high-resolution mapping help individual-based fish population models go up-scale? (Invited)

    NASA Astrophysics Data System (ADS)

    Harvey, B.; Railsback, S.

    2009-12-01

    Spatially explicit, individual-based models of fish populations show great promise for linking physical conditions and processes to population dynamics. The ability to link physical processes and population outcomes is critical for optimizing habitat restoration efforts, forecasting the consequences of climate change, evaluating flow regimes, and other activities necessary to sustain at-risk fish populations. Because individual-based models simulate habitat from the perspective of individual fish, they commonly capture variation in physical habitat on a scale of 1- 50 square meters and rely on simulations (including hydraulic modeling) at the reach scale (0.2 to 1 km). Simulated reaches can be linked in some models such that virtual fish can move among them. The significance of the size, location and arrangement of reaches included in IBM simulations of fish populations has not been investigated in detail. However, the process of reach selection clearly benefits from information on channel physical conditions at the network scale, so that reaches can be selected to well-represent the diversity of habitat at larger spatial scales. High-resolution mapping of channel topography would be a richer source of network-scale information than others used to date, such as habitat typing and simple video. Remote, high-resolution mapping data might also provide a major step forward in the capability of individual-based models to address fish population dynamics at the network scale if the mapping data could be directly used for hydraulic simulations. Challenges for this step include the need to estimate physical habitat variables included in individual-based models that may not be readily discernable from topographic data, such as the availability of cover for fish. Exploring the use of high-resolution mapping data in individual-based modeling of fish populations seems worth doing, in that the individual-based models should be a particularly effective way to derive biological

  8. 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

  9. Advancing microbial sciences by individual-based modelling.

    PubMed

    Hellweger, Ferdi L; Clegg, Robert J; Clark, James R; Plugge, Caroline M; Kreft, Jan-Ulrich

    2016-07-01

    Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE). PMID:27265769

  10. Simulation of a rubber plantation productivity in central Cambodia using the individual-based dynamic vegetation model SEIB-DGVM

    NASA Astrophysics Data System (ADS)

    Kumagai, T.; SATO, H.; Shinjiro, Ph. D., F.

    2013-12-01

    To provide a useful tool for building strategy of forest plantation management, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulate productivity of tree plantations (SEIB-PP). Rubber (Hevea brasiliensis Müll. Arg.) plantations, which are rapidly expanding into both climatically optimal and sub-optimal environments throughout mainland Southeast Asia, potentially change the partitioning of water, energy, and carbon at multiple scales, compared with traditional land covers that are being replaced. Describing both primary and latex productivities in rubber plantations via SEIB-PP is, therefore, important to understanding the climatic impacts on productive processes. Model results are compared with measurements collected at a field site in central Cambodia, and here, we show some examples of projections: the rubber plantation production under future climate change conditions.

  11. Individual-based modeling of ecological and evolutionary processes

    USGS Publications Warehouse

    DeAngelis, Donald L.; Mooij, Wolf M.

    2005-01-01

    Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

  12. Evaluation of the Event Driven Phenology Model Coupled to the VegET Evapotranspiration Model Using Spatially Explicit Comparisons with Independent Reference Data

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    Vegetation growing cycles have a profound influence on regional evapotranspiration regimes. The recently developed Event Driven Phenology Model (EDPM) is an empirical crop-specific phenology model with data assimilation capabilities. Deployed in prognostic mode, the EDPM uses weather forcing data to produce daily estimates of phenology coefficients; and in diagnostic mode a one-dimensional Kalman filter is used to adjust EDPM estimates with satellite normalized difference vegetation index (NDVI) retrievals. In this study the EDPM is coupled to the VegET model that uses the Penman-Monteith equation to calculate reference ET and a water balance model for water stress coefficients to derive daily actual evapotranspiration. The coupled models were run for the croplands of the U.S. Northern Great Plains for three annual growing seasons to derive 8-day total actual evapotranspiration (ETa) estimates at 0.05° spatial resolution. The models were driven by North American Land Data Assimilation System (NLDAS) weather forcing and parameterized using annual MODIS cropland cover maps. Regional validation of the modeled NDVI and ETa were undertaken by comparison with MODIS NDVI and MODIS ETa products respectively. The modeled NDVI had a median coefficient of determination (r2) of 0.83 and a root mean square error (RMSE) of 0.15 within study area. With the EDPM deployed in both prognostic and diagnostic modes, the modeled ETa had r2 of 0.75 and RMSE of about 25% of season average ETa per observation period. With small computational effort these results yield comparable accuracy to those from computationally complex models of ETa which require more parameterization. The performance of the coupling scheme demonstrates that the modeling approach is a promising avenue for regional application studies.

  13. Building spatially-explicit model predictions for ecological condition of streams in the Pacific Northwest: An assessment of landscape variables, models, endpoints and prediction scale

    EPA Science Inventory

    While large-scale, randomized surveys estimate the percentage of a region’s streams in poor ecological condition, identifying particular stream reaches or watersheds in poor condition is an equally important goal for monitoring and management. We built predictive models of strea...

  14. Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

    PubMed

    Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

    2014-01-01

    Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

  15. Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

    PubMed Central

    Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.

    2014-01-01

    Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

  16. INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

    PubMed

    Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

    2015-01-01

    Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty. PMID:26630762

  17. Individual based and mean-field modeling of direct aggregation

    PubMed Central

    Burger, Martin; Haškovec, Jan; Wolfram, Marie-Therese

    2013-01-01

    We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the first-order model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. PMID:24926113

  18. Linking land use change to recreational fishery valuation with a spatially explicit behavior model: A case study from Tampa Bay, FL USA

    EPA Science Inventory

    Drawing a link between habitat change and production and delivery of ecosystem services is a priority in coastal estuarine ecosystems. This link is needed to fully understand how human communities can influence ecosystem sustainability. Mechanistic modeling tools are highly fun...

  19. Spatially explicit risk assessment of an estuarine fish in Barataria Bay, Louisiana, following the Deepwater Horizon Oil spill: evaluating tradeoffs in model complexity and parsimony

    EPA Science Inventory

    As ecological risk assessments (ERA) move beyond organism-based determinations towards probabilistic population-level assessments, model complexity must be evaluated against the goals of the assessment, the information available to parameterize components with minimal dependence ...

  20. Modelling Deep Water Habitats to Develop a Spatially Explicit, Fine Scale Understanding of the Distribution of the Western Rock Lobster, Panulirus cygnus

    PubMed Central

    Hovey, Renae K.; Van Niel, Kimberly P.; Bellchambers, Lynda M.; Pember, Matthew B.

    2012-01-01

    Background The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site. Methods and Findings Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables) were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand) and dominant biota (kelp, sessile invertebrates and macroalgae) within a 40 km2 area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D2 of 64 and an 80% correct classification. Conclusions Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical lobster habitats. PMID

  1. Eco-SpaCE: an object-oriented, spatially explicit model to assess the risk of multiple environmental stressors on terrestrial vertebrate populations.

    PubMed

    Loos, Mark; Ragas, Ad M J; Plasmeijer, Rinus; Schipper, Aafke M; Hendriks, A Jan

    2010-08-15

    Wildlife organisms are exposed to a combination of chemical, biological and physical stressors. Information about the relative impact of each stressor can support management decisions, e.g., by the allocation of resources to counteract those stressors that cause most harm. The present paper introduces Eco-SpaCE; a novel receptor-oriented cumulative exposure model for wildlife species that includes relevant ecological processes such as spatial habitat variation, food web relations, predation, and life history. A case study is presented in which the predicted mortality due to cadmium contamination is compared with the predicted mortality due to flooding, starvation, and predation for three small mammal species (Wood mouse, Common vole, and European mole) and a predator (Little owl) living in a lowland floodplain along the river Rhine in The Netherlands. Results indicated that cadmium is the principal stressor for European mole and Little owl populations. Wood mouse and Common vole population densities were mainly influenced by flooding and food availability. Their estimated population sizes were consistent with numbers reported in literature. Predictions for cadmium accumulation and flooding stress were in agreement with field data. The large uncertainty around cadmium toxicity for wildlife leads to the conclusion that more species-specific ecotoxicological data is required for more realistic risk assessments. The predictions for starvation were subject to the limited quantitative information on biomass obtainable as food for vertebrates. It is concluded that the modelling approach employed in Eco-SpaCE, combining ecology with ecotoxicology, provides a viable option to explore the relative contribution of contamination to the overall stress in an ecosystem. This can help environmental managers to prioritize management options, and to reduce local risks. PMID:20005557

  2. Spatially Explicit Full Carbon and Greenhouse Gas Accounting for the Midwestern and Continental US: Modeling and Decision Support for Carbon Management

    NASA Astrophysics Data System (ADS)

    West, T. O.; Brandt, C. C.; Wilson, B. S.; Hellwinckel, C. M.; Mueller, M.; Tyler, D. D.; de La Torre Ugarte, D. G.; Larson, J. A.; Nelson, R. G.; Marland, G.

    2006-12-01

    Full carbon accounting for terrestrial ecosystems is intended to quantify changes in net carbon emissions caused by changes in land management. On agricultural lands, changes in land management can cause changes in CO2 emissions from fossil fuel use, agricultural lime, and decomposition of soil carbon. Changes in off-site emissions can occur from the manufacturing of fertilizers, pesticides, and agricultural lime. We are developing a full carbon accounting framework that can be used for estimates of on-site net carbon flux or for full greenhouse gas accounting at a high spatial resolution. Estimates are based on the assimilation of national inventory data, soil carbon dynamics based on empirical analyses of field data, and Landsat-derived remote sensing products with 30x30m resolution. We applied this framework to a mid-western region of the US that consists of 679 counties approximately centered around Iowa. We estimate the 1990 baseline soil carbon for this region to be 4,099 Tg C to a 3m maximum depth. Soil carbon accumulation of 57.3 Tg C is estimated to have occurred in this region between 1991-2000. Without accounting for soil carbon loss associated with changes to more intense tillage practices, our estimate increases to 66.3 Tg C. This indicates that on-site permanence of soil carbon is approximately 86% with no additional economic incentives provided for soil carbon sequestration practices. Total net carbon flux from the agricultural activities in the Midwestern US in 2000 is estimated at about -5 Tg C. This estimate includes carbon uptake, decomposition, harvested products, and on-site fossil fuel emissions. Therefore, soil carbon accumulation offset on-site emissions in 2000. Our carbon accounting framework offers a method to integrate new inventory and remote sensing data on an annual basis, account for alternating annual trends in land management without the need for model equilibration, and provide a transparent means to monitor changes soil carbon

  3. IBSEM: An Individual-Based Atlantic Salmon Population Model

    PubMed Central

    Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A.

    2015-01-01

    Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

  4. IBSEM: An Individual-Based Atlantic Salmon Population Model.

    PubMed

    Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A

    2015-01-01

    Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a 'wild' genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

  5. Simulating the spread of an invasive termite in an urban environment using a stochastic individual-based model.

    PubMed

    Tonini, Francesco; Hochmair, Hartwig H; Scheffrahn, Rudolf H; Deangelis, Donald L

    2013-06-01

    Invasive termites are destructive insect pests that cause billions of dollars in property damage every year. Termite species can be transported overseas by maritime vessels. However, only if the climatic conditions are suitable will the introduced species flourish. Models predicting the areas of infestation following initial introduction of an invasive species could help regulatory agencies develop successful early detection, quarantine, or eradication efforts. At present, no model has been developed to estimate the geographic spread of a termite infestation from a set of surveyed locations. In the current study, we used actual field data as a starting point, and relevant information on termite species to develop a spatially-explicit stochastic individual-based simulation to predict areas potentially infested by an invasive termite, Nasutitermes corniger (Motschulsky), in Dania Beach, FL. The Monte Carlo technique is used to assess outcome uncertainty. A set of model realizations describing potential areas of infestation were considered in a sensitivity analysis, which showed that the model results had greatest sensitivity to number of alates released from nest, alate survival, maximum pheromone attraction distance between heterosexual pairs, and mean flight distance. Results showed that the areas predicted as infested in all simulation runs of a baseline model cover the spatial extent of all locations recently discovered. The model presented in this study could be applied to any invasive termite species after proper calibration of parameters. The simulation herein can be used by regulatory authorities to define most probable quarantine and survey zones. PMID:23726049

  6. 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.

  7. A spatially-explicit model of acarological risk of exposure to Borrelia burgdorferi-infected Ixodes pacificus nymphs in northwestern California based on woodland type, temperature, and water vapor.

    PubMed

    Eisen, Rebecca J; Eisen, Lars; Girard, Yvette A; Fedorova, Natalia; Mun, Jeomhee; Slikas, Beth; Leonhard, Sarah; Kitron, Uriel; Lane, Robert S

    2010-03-01

    In the far-western United States, the nymphal stage of the western black-legged tick, Ixodes pacificus, has been implicated as the primary vector to humans of Borrelia burgdorferi sensu stricto (hereinafter referred to as B. burgdorferi), the causative agent of Lyme borreliosis in North America. In the present study, we sought to determine if infection prevalence with B. burgdorferi in I. pacificus nymphs and the density of infected nymphs differ between dense-woodland types within Mendocino County, California, and to develop and evaluate a spatially-explicit model for density of infected nymphs in dense woodlands within this high-incidence area for Lyme borreliosis. In total, 4.9% (264) of 5431 I. pacificus nymphs tested for the presence of B. burgdorferi were infected. Among the 78 sampling sites, infection prevalence ranged from 0 to 22% and density of infected nymphs from 0 to 2.04 per 100 m(2). Infection prevalence was highest in woodlands dominated by hardwoods (6.2%) and lowest for redwood (1.9%) and coastal pine (0%). Density of infected nymphs also was higher in hardwood-dominated woodlands than in conifer-dominated ones that included redwood or pine. Our spatial risk model, which yielded an overall accuracy of 85%, indicated that warmer areas with less variation between maximum and minimum monthly water vapor in the air were more likely to include woodlands with elevated acarological risk of exposure to infected nymphs. We found that 37% of dense woodlands in the county were predicted to pose an elevated risk of exposure to infected nymphs, and that 94% of the dense-woodland areas that were predicted to harbor elevated densities of infected nymphs were located on privately-owned land. PMID:20532183

  8. A spatially-explicit model of acarological risk of exposure to Borrelia burgdorferi-infected Ixodes pacificus nymphs in northwestern California based on woodland type, temperature, and water vapor

    PubMed Central

    Eisen, Rebecca J.; Eisen, Lars; Girard, Yvette A.; Fedorova, Natalia; Mun, Jeomhee; Slikas, Beth; Leonhard, Sarah; Kitron, Uriel; Lane, Robert S.

    2010-01-01

    In the far-western United States, the nymphal stage of the western black-legged tick, Ixodes pacificus, has been implicated as the primary vector to humans of Borrelia burgdorferi sensu stricto (hereinafter referred to as B. burgdorferi), the causative agent of Lyme borreliosis in North America. In the present study, we sought to determine if infection prevalence with B. burgdorferi in I. pacificus nymphs and the density of infected nymphs differ between dense-woodland types within Mendocino County, California, and to develop and evaluate a spatially-explicit model for density of infected nymphs in dense woodlands within this high-incidence area for Lyme borreliosis. In total, 4.9% (264) of 5431 I. pacificus nymphs tested for the presence of B. burgdorferi were infected. Among the 78 sampling sites, infection prevalence ranged from 0 to 22% and density of infected nymphs from 0 to 2.04 per 100 m2. Infection prevalence was highest in woodlands dominated by hardwoods (6.2%) and lowest for redwood (1.9%) and coastal pine (0%). Density of infected nymphs also was higher in hardwood-dominated woodlands than in conifer-dominated ones that included redwood or pine. Our spatial risk model, which yielded an overall accuracy of 85%, indicated that warmer areas with less variation between maximum and minimum monthly water vapor in the air were more likely to include woodlands with elevated acarological risk of exposure to infected nymphs. We found that 37% of dense woodlands in the county were predicted to pose an elevated risk of exposure to infected nymphs, and that 94% of the dense-woodland areas that were predicted to harbor elevated densities of infected nymphs were located on privately-owned land. PMID:20532183

  9. An individual-based forest model links canopy dynamics and shade tolerances along a soil moisture gradient.

    PubMed

    Liénard, Jean; Strigul, Nikolay

    2016-02-01

    Understanding how forested ecosystems respond to climatic changes is a challenging problem as forest self-organization occurs simultaneously across multiple scales. Here, we explore the hypothesis that soil water availability shapes above-ground competition and gap dynamics, and ultimately alters the dominance of shade tolerant and intolerant species along the moisture gradient. We adapt a spatially explicit individual-based model with simultaneous crown and root competitions. Simulations show that the transition from xeric to mesic soils is accompanied by an increase in shade-tolerant species similar to the patterns documented in the North American forests. This transition is accompanied by a change from water to sunlight competitions, and happens at three successive stages: (i) mostly water-limited parkland, (ii) simultaneously water- and sunlight-limited closed canopy forests featuring a very sparse understory, and (iii) mostly sunlight-limited forests with a populated understory. This pattern is caused by contrasting successional dynamics that favour either shade-tolerant or shade-intolerant species, depending on soil moisture and understory density. This work demonstrates that forest patterns along environmental gradients can emerge from spatial competition without physiological trade-offs between shade and growth tolerance. Mechanistic understanding of population processes involved in the forest-parkland-desert transition will improve our ability to explain species distributions and predict forest responses to climatic changes. PMID:26998329

  10. An individual-based forest model links canopy dynamics and shade tolerances along a soil moisture gradient

    PubMed Central

    Liénard, Jean; Strigul, Nikolay

    2016-01-01

    Understanding how forested ecosystems respond to climatic changes is a challenging problem as forest self-organization occurs simultaneously across multiple scales. Here, we explore the hypothesis that soil water availability shapes above-ground competition and gap dynamics, and ultimately alters the dominance of shade tolerant and intolerant species along the moisture gradient. We adapt a spatially explicit individual-based model with simultaneous crown and root competitions. Simulations show that the transition from xeric to mesic soils is accompanied by an increase in shade-tolerant species similar to the patterns documented in the North American forests. This transition is accompanied by a change from water to sunlight competitions, and happens at three successive stages: (i) mostly water-limited parkland, (ii) simultaneously water- and sunlight-limited closed canopy forests featuring a very sparse understory, and (iii) mostly sunlight-limited forests with a populated understory. This pattern is caused by contrasting successional dynamics that favour either shade-tolerant or shade-intolerant species, depending on soil moisture and understory density. This work demonstrates that forest patterns along environmental gradients can emerge from spatial competition without physiological trade-offs between shade and growth tolerance. Mechanistic understanding of population processes involved in the forest–parkland–desert transition will improve our ability to explain species distributions and predict forest responses to climatic changes. PMID:26998329

  11. 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.

  12. 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

  13. 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

  14. Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management

    USGS Publications Warehouse

    Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Sanchez-chopitea, Erika; Mauch, Kimberly; Niell, Lara; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

    2016-01-01

    Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage

  15. An example of population-level risk assessments for small mammals using individual-based population models.

    PubMed

    Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn; Ebeling, Markus; Liu, Chun; Luttik, Robert; Mastitsky, Sergey; Nacci, Diane; Topping, Chris; Wang, Magnus

    2016-01-01

    This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. PMID:25891765

  16. Individual-based modeling of fish: Linking to physical models and water quality.

    SciTech Connect

    Rose, K.A.

    1997-08-01

    The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

  17. Breaking Functional Connectivity into Components: A Novel Approach Using an Individual-Based Model, and First Outcomes

    PubMed Central

    Pe'er, Guy; Henle, Klaus; Dislich, Claudia; Frank, Karin

    2011-01-01

    Landscape connectivity is a key factor determining the viability of populations in fragmented landscapes. Predicting ‘functional connectivity’, namely whether a patch or a landscape functions as connected from the perspective of a focal species, poses various challenges. First, empirical data on the movement behaviour of species is often scarce. Second, animal-landscape interactions are bound to yield complex patterns. Lastly, functional connectivity involves various components that are rarely assessed separately. We introduce the spatially explicit, individual-based model FunCon as means to distinguish between components of functional connectivity and to assess how each of them affects the sensitivity of species and communities to landscape structures. We then present the results of exploratory simulations over six landscapes of different fragmentation levels and across a range of hypothetical bird species that differ in their response to habitat edges. i) Our results demonstrate that estimations of functional connectivity depend not only on the response of species to edges (avoidance versus penetration into the matrix), the movement mode investigated (home range movements versus dispersal), and the way in which the matrix is being crossed (random walk versus gap crossing), but also on the choice of connectivity measure (in this case, the model output examined). ii) We further show a strong effect of the mortality scenario applied, indicating that movement decisions that do not fully match the mortality risks are likely to reduce connectivity and enhance sensitivity to fragmentation. iii) Despite these complexities, some consistent patterns emerged. For instance, the ranking order of landscapes in terms of functional connectivity was mostly consistent across the entire range of hypothetical species, indicating that simple landscape indices can potentially serve as valuable surrogates for functional connectivity. Yet such simplifications must be carefully

  18. Rates and potentials of soil organic carbon sequestration in agricultural lands in Japan: an assessment using a process-based model and spatially-explicit land-use change inventories

    NASA Astrophysics Data System (ADS)

    Yagasaki, Y.; Shirato, Y.

    2013-11-01

    In order to develop a system to estimate a country-scale soil organic carbon stock change (SCSC) in agricultural lands in Japan that enables to take account effect of land-use changes, climate, different agricultural activity and nature of soils, a spatially-explicit model simulation system using Rothamsted Carbon Model (RothC) integrated with spatial and temporal inventories was developed. Future scenarios on agricultural activity and land-use change were prepared, in addition to future climate projections by global climate models, with purposely selecting rather exaggerated and contrasting set of scenarios to assess system's sensitivity as well as to better factor out direct human influence in the SCSC accounting. Simulation was run from year 1970 to 2008, and to year 2020, with historical inventories and future scenarios involving target set in agricultural policy, respectively, and subsequently until year 2100 with no temporal changes in land-use and agricultural activity but with varying climate to investigate course of SCSC. Results of the country-scale SCSC simulation have indicated that conversion of paddy fields to croplands occurred during past decades, as well as a large conversion of agricultural fields to settlements or other lands that have occurred in historical period and would continue in future, could act as main factors causing greater loss of soil organic carbon (SOC) at country-scale, with reduction organic carbon input to soils and enhancement of SOC decomposition by transition of soil environment to aerobic conditions, respectively. Scenario analysis indicated that an option to increase organic carbon input to soils with intensified rotation with suppressing conversion of agricultural lands to other land-use types could achieve reduction of CO2 emission due to SCSC in the same level as that of another option to let agricultural fields be abandoned. These results emphasize that land-use changes, especially conversion of the agricultural lands

  19. A paradox in individual-based models of populations

    PubMed Central

    van der Meer, Jaap

    2016-01-01

    The standard dynamic energy budget model is widely used to describe the physiology of individual animals. It assumes that assimilation rate scales with body surface area, whereas maintenance rate scales with body volume. When the model is used as the building block of a population model, only limited dynamical behaviour, the so-called juvenile-driven cycles, emerges. The reason is that in the model juveniles are competitively superior over adults, because juveniles have a higher surface area-to-volume ratio. Maintenance requirements for adults are therefore relatively large, and a reduced assimilation rate as a result of lowered food levels will easily become insufficient. Here, an alternative dynamic energy budget model is introduced that gives rise to adult-driven cycles, which may be closer to what is often observed in reality. However, this comes at the price of a rather odd description of the individual, in that maintenance scales with body area and assimilation rate with body volume, resulting in unbounded exponential body growth. I make a plea to solve the paradox and come up with reliable descriptions at both the individual and the population level. PMID:27413533

  20. A paradox in individual-based models of populations.

    PubMed

    van der Meer, Jaap

    2016-01-01

    The standard dynamic energy budget model is widely used to describe the physiology of individual animals. It assumes that assimilation rate scales with body surface area, whereas maintenance rate scales with body volume. When the model is used as the building block of a population model, only limited dynamical behaviour, the so-called juvenile-driven cycles, emerges. The reason is that in the model juveniles are competitively superior over adults, because juveniles have a higher surface area-to-volume ratio. Maintenance requirements for adults are therefore relatively large, and a reduced assimilation rate as a result of lowered food levels will easily become insufficient. Here, an alternative dynamic energy budget model is introduced that gives rise to adult-driven cycles, which may be closer to what is often observed in reality. However, this comes at the price of a rather odd description of the individual, in that maintenance scales with body area and assimilation rate with body volume, resulting in unbounded exponential body growth. I make a plea to solve the paradox and come up with reliable descriptions at both the individual and the population level. PMID:27413533

  1. 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.

  2. Individual-based model for quorum sensing with background flow.

    PubMed

    Uecker, Hannes; Uecke, Hannes; Müller, Johannes; Hense, Burkhard A

    2014-07-01

    Quorum sensing is a wide-spread mode of cell-cell communication among bacteria in which cells release a signalling substance at a low rate. The concentration of this substance allows the bacteria to gain information about population size or spatial confinement. We consider a model for N cells which communicate with each other via a signalling substance in a diffusive medium with a background flow. The model consists of an initial boundary value problem for a parabolic PDE describing the exterior concentration u of the signalling substance, coupled with N ODEs for the masses ai of the substance within each cell. The cells are balls of radius R in R3, and under some scaling assumptions we formally derive an effective system of N ODEs describing the behaviour of the cells. The reduced system is then used to study the effect of flow on communication in general, and in particular for a number of geometric configurations. PMID:24849771

  3. 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

  4. Individual-Based Simulation Models of HIV Transmission: Reporting Quality and Recommendations

    PubMed Central

    Abuelezam, Nadia N.; Rough, Kathryn; Seage III, George R.

    2013-01-01

    Background Individual-based modeling is a growing technique in the HIV transmission and prevention literature, but insufficient attention has been paid to formally evaluate the quality of reporting in this field. We present reporting recommendations for individual-based models for HIV treatment and prevention, assess the quality of reporting in the existing literature, and comment on the contribution of this model type to HIV policy and prediction. Methods We developed reporting recommendations for individual-based HIV transmission mathematical models, and through a systematic search, used them to evaluate the reporting in the existing literature. We identified papers that employed individual-based simulation models and were published in English prior to December 31, 2012. Articles were included if the models they employed simulated and tracked individuals, simulated HIV transmission between individuals in a particular population, and considered a particular treatment or prevention intervention. The papers were assessed with the reporting recommendations. Findings Of 214 full text articles examined, 32 were included in the evaluation, representing 20 independent individual-based HIV treatment and prevention mathematical models. Manuscripts universally reported the objectives, context, and modeling conclusions in the context of the modeling assumptions and the model’s predictive capabilities, but the reporting of individual-based modeling methods, parameterization and calibration was variable. Six papers discussed the time step used and one discussed efforts to maintain internal validity in coding. Conclusion Individual-based models represent detailed HIV transmission processes with the potential to contribute to inference and policy making for many different regions and populations. The rigor in reporting of assumptions, methods, and calibration of individual-based models focused on HIV transmission and prevention varies greatly. Higher standards for reporting of

  5. Resolving discrepancies between deterministic population models and individual-based simulations.

    PubMed

    Wilson, W G

    1998-02-01

    This work ties together two distinct modeling frameworks for population dynamics: an individual-based simulation and a set of coupled integrodifferential equations involving population densities. The simulation model represents an idealized predator-prey system formulated at the scale of discrete individuals, explicitly incorporating their mutual interactions, whereas the population-level framework is a generalized version of reaction-diffusion models that incorporate population densities coupled to one another by interaction rates. Here I use various combinations of long-range dispersal for both the offspring and adult stages of both prey and predator species, providing a broad range of spatial and temporal dynamics, to compare and contrast the two model frameworks. Taking the individual-based modeling results as given, two examinations of the reaction-dispersal model are made: linear stability analysis of the deterministic equations and direct numerical solution of the model equations. I also modify the numerical solution in two ways to account for the stochastic nature of individual-based processes, which include independent, local perturbations in population density and a minimum population density within integration cells, below which the population is set to zero. These modifications introduce new parameters into the population-level model, which I adjust to reproduce the individual-based model results. The individual-based model is then modified to minimize the effects of stochasticity, producing a match of the predictions from the numerical integration of the population-level model without stochasticity. PMID:18811412

  6. 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

  7. Calculation of Individual Tree Water Use in a Bornean Tropical Rain Forest Using Individual-Based Dynamic Vegetation Model SEIB-DGVM

    NASA Astrophysics Data System (ADS)

    Nakai, T.; Kumagai, T.; Saito, T.; Matsumoto, K.; Kume, T.; Nakagawa, M.; Sato, H.

    2015-12-01

    Bornean tropical rain forests are among the moistest biomes of the world with abundant rainfall throughout the year, and considered to be vulnerable to a change in the rainfall regime; e.g., high tree mortality was reported in such forests induced by a severe drought associated with the ENSO event in 1997-1998. In order to assess the effect (risk) of future climate change on eco-hydrology in such tropical rain forests, it is important to understand the water use of trees individually, because the vulnerability or mortality of trees against climate change can depend on the size of trees. Therefore, we refined the Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIB-DGVM) so that the transpiration and its control by stomata are calculated for each individual tree. By using this model, we simulated the transpiration of each tree and its DBH-size dependency, and successfully reproduced the measured data of sap flow of trees and eddy covariance flux data obtained in a Bornean lowland tropical rain forest in Lambir Hills National Park, Sarawak, Malaysia.

  8. Assessment on the rates and potentials of soil organic carbon sequestration in agricultural lands in Japan using a process-based model and spatially explicit land-use change inventories - Part 2: Future potentials

    NASA Astrophysics Data System (ADS)

    Yagasaki, Y.; Shirato, Y.

    2014-08-01

    Future potentials of the sequestration of soil organic carbon (SOC) in agricultural lands in Japan were estimated using a simulation system we recently developed to simulate SOC stock change at country-scale under varying land-use change, climate, soil, and agricultural practices, in a spatially explicit manner. Simulation was run from 1970 to 2006 with historical inventories, and subsequently to 2020 with future scenarios of agricultural activity comprised of various agricultural policy targets advocated by the Japanese government. Furthermore, the simulation was run subsequently until 2100 while forcing no temporal changes in land-use and agricultural activity to investigate duration and course of SOC stock change at country scale. A scenario with an increased rate of organic carbon input to agricultural fields by intensified crop rotation in combination with the suppression of conversion of agricultural lands to other land-use types was found to have a greater reduction of CO2 emission by enhanced soil carbon sequestration, but only under a circumstance in which the converted agricultural lands will become settlements that were considered to have a relatively lower rate of organic carbon input. The size of relative reduction of CO2 emission in this scenario was comparable to that in another contrasting scenario (business-as-usual scenario of agricultural activity) in which a relatively lower rate of organic matter input to agricultural fields was assumed in combination with an increased rate of conversion of the agricultural fields to unmanaged grasslands through abandonment. Our simulation experiment clearly demonstrated that net-net-based accounting on SOC stock change, defined as the differences between the emissions and removals during the commitment period and the emissions and removals during a previous period (base year or base period of Kyoto Protocol), can be largely influenced by variations in future climate. Whereas baseline-based accounting, defined

  9. INDISIM-Paracoccus, an individual-based and thermodynamic model for a denitrifying bacterium.

    PubMed

    Araujo Granda, Pablo; Gras, Anna; Ginovart, Marta; Moulton, Vincent

    2016-08-21

    We have developed an individual-based model for denitrifying bacteria. The model, called INDISIM-Paracoccus, embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM, and is designed to simulate the bacterial cell population behavior and the product dynamics within the culture. The INDISIM-Paracoccus model assumes a culture medium containing succinate as a carbon source, ammonium as a nitrogen source and various electron acceptors such as oxygen, nitrate, nitrite, nitric oxide and nitrous oxide to simulate in continuous or batch culture the different nutrient-dependent cell growth kinetics of the bacterium Paracoccus denitrificans. The individuals in the model represent microbes and the individual-based model INDISIM gives the behavior-rules that they use for their nutrient uptake and reproduction cycle. Three previously described metabolic pathways for P. denitrificans were selected and translated into balanced chemical equations using a thermodynamic model. These stoichiometric reactions are an intracellular model for the individual behavior-rules for metabolic maintenance and biomass synthesis and result in the release of different nitrogen oxides to the medium. The model was implemented using the NetLogo platform and it provides an interactive tool to investigate the different steps of denitrification carried out by a denitrifying bacterium. The simulator can be obtained from the authors on request. PMID:27179457

  10. An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

    PubMed

    Allen, Corrie H; Parrott, Lael; Kyle, Catherine

    2016-01-01

    Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were

  11. An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis)

    PubMed Central

    Allen, Corrie H.; Kyle, Catherine

    2016-01-01

    Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were

  12. Coupling of an individual-based model of anchovy with lower trophic level and hydrodynamic models

    NASA Astrophysics Data System (ADS)

    Wang, Yuheng; Wei, Hao; Kishi, Michio J.

    2013-03-01

    Anchovy ( Engraulis japonicus), a small pelagic fish and food of other economic fishes, is a key species in the Yellow Sea ecosystem. Understanding the mechanisms of its recruitment and biomass variation is important for the prediction and management of fishery resources. Coupled with a hydrodynamic model (POM) and a lower trophic level ecosystem model (NEMURO), an individual-based model of anchovy is developed to study the influence of physical environment on anchovy's biomass variation. Seasonal variations of circulation, water temperature and mix-layer depth from POM are used as external forcing for NEMURO and the anchovy model. Biomasses of large zooplankton and predatory zooplankton which anchovy feeds on are output from NEMURO and are controlled by the consumption of anchovy on them. Survival fitness theory related to temperature and food is used to determine the swimming action of anchovy in the model. The simulation results agree well with observations and elucidate the influence of temperature in over-wintering migration and food in feeding migration.

  13. 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

  14. An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

    PubMed Central

    Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.

    2015-01-01

    Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409

  15. Weak Convergence of a Mass-Structured Individual-Based Model

    SciTech Connect

    Campillo, Fabien; Fritsch, Coralie

    2015-08-15

    We propose a model of chemostat where the bacterial population is individually-based, each bacterium is explicitly represented and has a mass evolving continuously over time. The substrate concentration is represented as a conventional ordinary differential equation. These two components are coupled with the bacterial consumption. Mechanisms acting on the bacteria are explicitly described (growth, division and washout). Bacteria interact via consumption. We set the exact Monte Carlo simulation algorithm of this model and its mathematical representation as a stochastic process. We prove the convergence of this process to the solution of an integro-differential equation when the population size tends to infinity. Finally, we propose several numerical simulations.

  16. 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

  17. 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

  18. Value of eddy-covariance data for individual-based, forest gap models

    NASA Astrophysics Data System (ADS)

    Roedig, Edna; Cuntz, Matthias; Huth, Andreas

    2014-05-01

    Individual-based forest gap models simulate tree growth and carbon fluxes on large time scales. They are a well established tool to predict forest dynamics and successions. However, the effect of climatic variables on processes of such individual-based models is uncertain (e.g. the effect of temperature or soil moisture on the gross primary production (GPP)). Commonly, functional relationships and parameter values that describe the effect of climate variables on the model processes are gathered from various vegetation models of different spatial scales. Though, their accuracies and parameter values have not been validated for the specific model scales of individual-based forest gap models. In this study, we address this uncertainty by linking Eddy-covariance (EC) data and a forest gap model. The forest gap model FORMIND is applied on the Norwegian spruce monoculture forest at Wetzstein in Thuringia, Germany for the years 2003-2008. The original parameterizations of climatic functions are adapted according to the EC-data. The time step of the model is reduced to one day in order to adapt to the high resolution EC-data. The FORMIND model uses functional relationships on an individual level, whereas the EC-method measures eco-physiological responses at the ecosystem level. However, we assume that in homogeneous stands as in our study, functional relationships for both methods are comparable. The model is then validated at the spruce forest Waldstein, Germany. Results show that the functional relationships used in the model, are similar to those observed with the EC-method. The temperature reduction curve is well reflected in the EC-data, though parameter values differ from the originally expected values. For example at the freezing point, the observed GPP is 30% higher than predicted by the forest gap model. The response of observed GPP to soil moisture shows that the permanent wilting point is 7 vol-% lower than the value derived from the literature. The light

  19. 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.

  20. Individual-based vs deterministic models for macroparasites: host cycles and extinction.

    PubMed

    Rosà, Roberto; Pugliese, Andrea; Villani, Alessandro; Rizzoli, Annapaola

    2003-06-01

    Our understanding of the qualitative dynamics of host-macroparasite systems is mainly based on deterministic models. We study here an individual-based stochastic model that incorporates the same assumptions as the classical deterministic model. Stochastic simulations, using parameter values based on some case studies, preserve many features of the deterministic model, like the average value of the variables and the approximate length of the cycles. An important difference is that, even when deterministic models yield damped oscillations, stochastic simulations yield apparently sustained oscillations. The amplitude of such oscillations may be so large to threaten parasites' persistence.With density-dependence in parasite demographic traits, persistence increases somewhat. Allowing instead for infections from an external parasite reservoir, we found that host extinction may easily occur. However, the extinction probability is almost independent of the level of external infection over a wide intermediate parameter region. PMID:12742175

  1. Individual-based model of bluegill sunfish production in aquatic mesocosms/microcosms

    SciTech Connect

    Florian, J.D. Jr.; Dixon, K.R.; DeAngelis, D.L.; Shaw, J.L.

    1994-12-31

    The development of an individual-based model for ag-ill sunfish, Lepomis macrochirus (Rafinesque) is described. Fish are modeled as an assemblage of individuals. Foraging, bioenergetics, interactions with conspecifics, and reproduction are modeled separately for each fish using control data from aquatic mesocosm/microcosm studies. The individual behavior of each fish is described by decision rules which specify what particular actions the fish performs on a daily basis. A summary of the most important behavioral rules for the model and how physical and resource environments can be taken into account is presented. Development of this type of modeling is pursued for ultimate use in field situations to better understand the influences of natural environmental conditions versus toxicant exposures on populations of fish through time.

  2. The role of spatial information in the preservation of the shrimp nursery function of mangroves: a spatially explicit bio-economic model for the assessment of land use trade-offs.

    PubMed

    Zavalloni, Matteo; Groeneveld, Rolf A; van Zwieten, Paul A M

    2014-10-01

    Conversion to aquaculture affects the provision of important ecosystem services provided by mangrove ecosystems, and this effect depends strongly on the location of the conversion. We introduce in a bio-economic mathematical programming model relevant spatial elements that affect the provision of the nursery habitat service of mangroves: (1) direct or indirect connection of mangroves to watercourses; (2) the spatial allocation of aquaculture ponds; and (3) the presence of non-linear relations between mangrove extent and juvenile recruitment to wild shrimp populations. By tracing out the production possibilities frontier of wild and cultivated shrimp, the model assesses the role of spatial information in the trade-off between aquaculture and the nursery habitat function using spatial elements relevant to our model of a mangrove area in Ca Mau Province, Viet Nam. Results show that where mangrove forests have to coexist with shrimp aquaculture ponds, the inclusion of specific spatial information on ecosystem functions in considerations of land allocation can achieve aquaculture benefits while largely preserving the economic benefits generated by the nursery habitat function. However, if spatial criteria are ignored, ill-advised land allocation decisions can easily lead to a collapse of the mangrove's nursery function. PMID:24833524

  3. Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

    PubMed

    Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

    2016-02-01

    Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. PMID:26598329

  4. Predicting shifts in dynamics of cannibalistic field populations using individual-based models.

    PubMed

    Persson, Lennart; de Roos, André M; Bertolo, Andrea

    2004-12-01

    The occurrence of qualitative shifts in population dynamical regimes has long been the focus of population biologists. Nonlinear ecological models predict that these shifts in dynamical regimes may occur as a result of parameter shifts, but unambiguous empirical evidence is largely restricted to laboratory populations. We used an individual-based modelling approach to predict dynamical shifts in field fish populations where the capacity to cannibalize differed between species. Model-generated individual growth trajectories that reflect different population dynamics were confronted with empirically observed growth trajectories, showing that our ordering and quantitative estimates of the different cannibalistic species in terms of life-history characteristics led to correct qualitative predictions of their dynamics. PMID:15590600

  5. Accumulation of PCBs by lake trout (Salvelinus namaycush): an individual-based model approach

    USGS Publications Warehouse

    Madenjian, Charles P.; Carpenter, Stephen R.; Eck, Gary W.; Miller, Michael A.

    1993-01-01

    To explain the variation in growth and in concentration of polychlorinated biphenyls (PCBs) among individual fish, an individual-based model (IBM) was applied to the lake trout (Salvelinus namaycush) population in Lake Michigan. The IBM accurately represented the variation in growth exhibited by the different age classes of lake trout. Uncertainty analysis of the IBM revealed that mean PCB concentration for the lake trout population was most sensitive to PCB concentration in their prey. The variability in PCB concentration among lake trout individuals was not adequately explained by the IBM, unless variation in prey fish PCBs was included in the model. To accomplish this, the simulated lake trout population was divided into subsets subjected to different levels of PCB concentration in the prey fish. Thus, model results indicated that variability in prey fish PCB concentration was an important component of the variation in PCB concnetration observed among individual lake trout comprising the Lake Michigan population.

  6. 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

  7. 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

  8. USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

    EPA Science Inventory

    Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

  9. Turing patterns and a stochastic individual-based model for predator-prey systems

    NASA Astrophysics Data System (ADS)

    Nagano, Seido

    2012-02-01

    Reaction-diffusion theory has played a very important role in the study of pattern formations in biology. However, a group of individuals is described by a single state variable representing population density in reaction-diffusion models and interaction between individuals can be included only phenomenologically. Recently, we have seamlessly combined individual-based models with elements of reaction-diffusion theory. To include animal migration in the scheme, we have adopted a relationship between the diffusion and the random numbers generated according to a two-dimensional bivariate normal distribution. Thus, we have observed the transition of population patterns from an extinction mode, a stable mode, or an oscillatory mode to the chaotic mode as the population growth rate increases. We show our phase diagram of predator-prey systems and discuss the microscopic mechanism for the stable lattice formation in detail.

  10. Spatially-explicit and spectral soil carbon modeling in Florida

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside i...

  11. An individual-based model of the krill Euphausia pacifica in the California Current

    NASA Astrophysics Data System (ADS)

    Dorman, Jeffrey G.; Sydeman, William J.; Bograd, Steven J.; Powell, Thomas M.

    2015-11-01

    Euphausia pacifica is an abundant and important prey resource for numerous predators of the California Current and elsewhere in the North Pacific. We developed an individual-based model (IBM) for E. pacifica to study its bioenergetics (growth, stage development, reproduction, and mortality) under constant/ideal conditions as well as under varying ocean conditions and food resources. To model E. pacifica under varying conditions, we coupled the IBM to an oceanographic-ecosystem model over the period 2000-2008 (9 years). Model results under constant/ideal food conditions compare favorably with experimental studies conducted under food unlimited conditions. Under more realistic variable oceanographic conditions, mean growth rates over the continental shelf were positive only when individuals migrated diurnally to the depth of maximum phytoplankton layer during nighttime feeding. Our model only used phytoplankton as prey and coastal growth rates were lower than expected (0.01 mm d-1), suggesting that a diverse prey base (zooplankton, protists, marine snow) may be required to facilitate growth and survival of modeled E. pacifica in the coastal environment. This coupled IBM-ROMS modeling framework and its parameters provides a tool for understanding the biology and ecology of E. pacifica and could be developed to further the understanding of climatic effects on this key prey species and enhance an ecosystem approach to fisheries and wildlife management in this region.

  12. A standard protocol for describing individual-based and agent-based models

    USGS Publications Warehouse

    Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

    2006-01-01

    Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

  13. An individual-based model of rabbit viral haemorrhagic disease on European wild rabbits (Oryctolagus cuniculus)

    USGS Publications Warehouse

    Fa, John E.; Sharples, Colin M.; Bell, Diana J.; DeAngelis, Donald L.

    2001-01-01

    We developed an individual-based model of Rabbit Viral Hemorrhagic Disease (RVHD) for European wild rabbits (Oryctolagus cuniculus L.), representing up to 1000 rabbits in four hectares. Model output for productivity and recruitment matched published values. The disease was density-dependent and virulence affected outcome. Strains that caused death after several days produced greater overall mortality than strains in which rabbits either died or recovered very quickly. Disease effect also depended on time of year. We also elaborated a larger scale model representing 25 km2 and 100,000+ rabbits, split into a number of grid-squares. This was a more traditional model that did not represent individual rabbits, but employed a system of dynamic equations for each grid-square. Disease spread depended on probability of transmission between neighboring grid-squares. Potential recovery from a major population crash caused by the disease relied on disease virulence and frequency of recurrence. The model's dependence on probability of disease transmission between grid-squares suggests the way that the model represents the spatial distribution of the population affects simulation. Although data on RVHD in Europe are lacking, our models provide a basis for describing the disease in realistic detail and for assessing influence of various social and spatial factors on spread.

  14. Individual-based model of yellow perch and walleye populations in Oneida Lake

    SciTech Connect

    Rose, K.A.; Rutherford, E.S.; McDermot, D.S.; Forney, J.L.; Mills, E.L.

    1999-05-01

    Predator-prey dynamics and density dependence are fundamental issues in ecology. The authors use a detailed, individual-based model of walleye and yellow perch to investigate the effects of alternative prey and compensatory responses on predator and prey population dynamics. The analyses focus on the numerical and developmental responses of the predator, rather than the traditional emphasis on functional responses. The extensive database for Oneida Lake, New York, USA was used to configure the model and ensure its realism. The model follows the daily growth, mortality, and spawning of individuals of each species through their lifetime. Three ecologically distinct periods in the history of Oneida Lake were simulated: baseline, high mayfly densities, and high forage fish densities. Mayflies and forage fish act as alternative prey for walleye. For model corroboration, the three periods were simulated sequentially as they occurred in Oneida Lake. Model predictions of abundances, size at age, and growth and survival rates compared favorably with Oneida Lake data. Three hypotheses suggested by the data were evaluated: alternative prey stabilizes yellow perch and walleye populations; alternative prey increases yellow perch and walleye recruitment; and density-dependent growth and survival compensate for changes in young-of-the-year mortality. Model simulations were performed under increased mayfly densities, increased forage fish densities, and increased egg mortality rates.

  15. iDynoMiCS: next-generation individual-based modelling of biofilms.

    PubMed

    Lardon, Laurent A; Merkey, Brian V; Martins, Sónia; Dötsch, Andreas; Picioreanu, Cristian; Kreft, Jan-Ulrich; Smets, Barth F

    2011-09-01

    Individual-based modelling of biofilms accounts for the fact that individual organisms of the same species may well be in a different physiological state as a result of environmental gradients, lag times in responding to change, or noise in gene expression, which we have become increasingly aware of with the advent of single-cell microbiology. But progress in developing and using individual-based modelling has been hampered by different groups writing their own code and the lack of an available standard model. We therefore set out to merge most features of previous models and incorporate various improvements in order to provide a common basis for further developments. Four improvements stand out: the biofilm pressure field allows for shrinking or consolidating biofilms; the continuous-in-time extracellular polymeric substances excretion leads to more realistic fluid behaviour of the extracellular matrix, avoiding artefacts; the stochastic chemostat mode allows comparison of spatially uniform and heterogeneous systems; and the separation of growth kinetics from the individual cell allows condition-dependent switching of metabolism. As an illustration of the model's use, we used the latter feature to study how environmentally fluctuating oxygen availability affects the diversity and composition of a community of denitrifying bacteria that induce the denitrification pathway under anoxic or low oxygen conditions. We tested the hypothesis that the existence of these diverse strategies of denitrification can be explained solely by assuming that faster response incurs higher costs. We found that if the ability to switch metabolic pathways quickly incurs no costs the fastest responder is always the best. However, if there is a trade-off where faster switching incurs higher costs, then there is a strategy with optimal response time for any frequency of environmental fluctuations, suggesting that different types of denitrifying strategies win in different environments. In a

  16. Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces.

    PubMed

    Kim, Minsu; Or, Dani

    2016-01-01

    Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803

  17. Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces

    PubMed Central

    Kim, Minsu; Or, Dani

    2016-01-01

    Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803

  18. 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).

  19. A parallel implementation of an off-lattice individual-based model of multicellular populations

    NASA Astrophysics Data System (ADS)

    Harvey, Daniel G.; Fletcher, Alexander G.; Osborne, James M.; Pitt-Francis, Joe

    2015-07-01

    As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population.

  20. Variable Cell Morphology Approach for Individual-Based Modeling of Microbial Communities

    PubMed Central

    Storck, Tomas; Picioreanu, Cristian; Virdis, Bernardino; Batstone, Damien J.

    2014-01-01

    An individual-based, mass-spring modeling framework has been developed to investigate the effect of cell properties on the structure of biofilms and microbial aggregates through Lagrangian modeling. Key features that distinguish this model are variable cell morphology described by a collection of particles connected by springs and a mechanical representation of deformable intracellular, intercellular, and cell-substratum links. A first case study describes the colony formation of a rod-shaped species on a planar substratum. This case shows the importance of mechanical interactions in a community of growing and dividing rod-shaped cells (i.e., bacilli). Cell-substratum links promote formation of mounds as opposed to single-layer biofilms, whereas filial links affect the roundness of the biofilm. A second case study describes the formation of flocs and development of external filaments in a mixed-culture activated sludge community. It is shown by modeling that distinct cell-cell links, microbial morphology, and growth kinetics can lead to excessive filamentous proliferation and interfloc bridging, possible causes for detrimental sludge bulking. This methodology has been extended to more advanced microbial morphologies such as filament branching and proves to be a very powerful tool in determining how fundamental controlling mechanisms determine diverse microbial colony architectures. PMID:24806936

  1. 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.

  2. An individual-based model for population viability analysis of humpback chub in Grand Canyon

    USGS Publications Warehouse

    Pine, William Pine, III; Healy, Brian; Smith, Emily Omana; Trammell, Melissa; Speas, Dave; Valdez, Rich; Yard, Mike; Walters, Carl; Ahrens, Rob; Vanhaverbeke, Randy; Stone, Dennis; Wilson, Wade

    2013-01-01

    We developed an individual-based population viability analysis model (females only) for evaluating risk to populations from catastrophic events or conservation and research actions. This model tracks attributes (size, weight, viability, etc.) for individual fish through time and then compiles this information to assess the extinction risk of the population across large numbers of simulation trials. Using a case history for the Little Colorado River population of Humpback Chub Gila cypha in Grand Canyon, Arizona, we assessed extinction risk and resiliency to a catastrophic event for this population and then assessed a series of conservation actions related to removing specific numbers of Humpback Chub at different sizes for conservation purposes, such as translocating individuals to establish other spawning populations or hatchery refuge development. Our results suggested that the Little Colorado River population is generally resilient to a single catastrophic event and also to removals of larvae and juveniles for conservation purposes, including translocations to establish new populations. Our results also suggested that translocation success is dependent on similar survival rates in receiving and donor streams and low emigration rates from recipient streams. In addition, translocating either large numbers of larvae or small numbers of large juveniles has generally an equal likelihood of successful population establishment at similar extinction risk levels to the Little Colorado River donor population. Our model created a transparent platform to consider extinction risk to populations from catastrophe or conservation actions and should prove useful to managers assessing these risks for endangered species such as Humpback Chub.

  3. An individual-based, spatial foraging model for cadmium accumulation in diving ducks

    SciTech Connect

    Lovvorn, J.R.; Gillingham, M.P.

    1994-12-31

    Contaminant studies of migratory birds include two main approaches: (1) collecting wild birds and analyzing their tissues, and (2) toxicity assays with captive birds. The first approach has shortcomings for these highly mobile animals--one seldom knows their length of stay in the area, and sites are often in urban environments where shooting is problematic. The second approach with captive birds ignores changes in food intake with varying activity and weather experienced by wild birds, and greater toxic consequences under multiple environmental stresses. Neither of these approaches alone can predict maximum allowable contaminant levels in foods that preclude toxic effects under different field conditions, or what body burdens accumulate during varying lengths of stay and affect the birds` biology at other places and times. To allow such predictions, the authors developed an individual-based model for intake of benthic foods by diving ducks for varying weather, water depth, food dispersion, and nutrient content of food. Food-intake estimates are combined with laboratory data on contaminant uptake as a function of food consumption and contaminant content. As an example, the authors estimate cadmium uptake by canvas back ducks foraging on below ground tubers of the submerged plant Vallisneria americans. They then show how their model can be used to include avian benthiovores in aquatic food web models for ecological risk assessment.

  4. Macroscopic limits of individual-based models for motile cell populations with volume exclusion.

    PubMed

    Dyson, Louise; Maini, Philip K; Baker, Ruth E

    2012-09-01

    Partial differential equation models are ubiquitous in studies of motile cell populations, giving a phenomenological description of events which can be analyzed and simulated using a wide range of existing tools. However, these models are seldom derived from individual cell behaviors and so it is difficult to accurately include biological hypotheses on this spatial scale. Moreover, studies which do attempt to link individual- and population-level behavior generally employ lattice-based frameworks in which the artifacts of lattice choice at the population level are unclear. In this work we derive limiting population-level descriptions of a motile cell population from an off-lattice, individual-based model (IBM) and investigate the effects of volume exclusion on the population-level dynamics. While motility with excluded volume in on-lattice IBMs can be accurately described by Fickian diffusion, we demonstrate that this is not the case off lattice. We show that the balance between two key parameters in the IBM (the distance moved in one step and the radius of an individual) determines whether volume exclusion results in enhanced or slowed diffusion. The magnitude of this effect is shown to increase with the number of cells and the rate of their movement. The method we describe is extendable to higher-dimensional and more complex systems and thereby provides a framework for deriving biologically realistic, continuum descriptions of motile populations. PMID:23030940

  5. Formation of Plant Canopy Hierarchies and Consequences for Water Use: Insights From Field Experiments and Individual Based Modeling of Weed-Crop Interactions

    NASA Astrophysics Data System (ADS)

    Berger, A. G.; McDonald, A. J.; Riha, S. J.

    2008-12-01

    In an agricultural landscape, water use is tightly linked to the dynamics of canopy development. When weeds are present, the plant community may develop leaf area faster than crop monocultures and several hierarchies of plants may be formed. The position of each individual plant within these hierarchies depends on the spatial arrangement of the plants, the initial sizes, and the availability of resources as determined by management, soil properties, weather, and competition. Together, these factors establish a highly dynamic system with nonlinear responses to the availability of resources (e.g. soil water) that is reflected in high levels of site and regional variability in crop yield losses due to weed interference. We developed a spatially-explicit, individual based model of plant competition to evaluate dynamic outcomes of crop-weed interactions and implications for water use. The model simulates the growth of individual plants using the light interception algorithms of the forest model MAESTRA, and estimates photosynthesis through the Farquhar-vonCaemmerer method. Transpiration and photosynthesis are coupled through stomatal conductance. Maximum stomatal conductance is determined by the photosynthetic demand for CO2, but under water stress, actual transpiration per plant is used to estimate stomatal conductance and then the actual rate of photosynthesis. We also used a novel approach to estimate profile water uptake, scaling the root zone of influence (volume of soil exploited by each individual plant) to plant biomass. Additive field experiments with maize in monoculture and in combination with high-density stands of a common annual weed species (A. theophrasti M.) were established to test model performance. Despite exceptionally dry conditions in the field in some years, we found no evidence that the maize-weed mixtures had less total soil water or different rates of water extraction through the profile than the maize monocrop. Furthermore, time series

  6. Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

    PubMed Central

    Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

    2014-01-01

    The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

  7. 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

  8. 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

  9. Examination of a Smallest CELSS (Microcosm) Through an Individual- Based-Model Simulation

    NASA Astrophysics Data System (ADS)

    Ishikawa, Y.; Sugiura, K.

    Research of the effect of space environment on an ecosystem consisting of plants and animals is essential when they are to be positively used in space. Although there have been experiments on various organisms under space environment in the past, they mainly studied the effect of space environment on an individual organism or a single species. Microcosm is drawing attention as an experimental material of an ecosystem consisting of multiple species. The object in this research is to understand the nature of this network system called ecosystem. Thus, a mixed microorganism culturing system consisting of three types of microorganisms (chlorella, bacteria, and rotifer) which form a minimum food chain system as a closed ecosystem was taken for the subject, on which the universal characteristics of ecosystems is searched. From the results of experiments under earth environment, formation of colonies, which is an ecological structure, has been observed at its mature stage. Therefore, formation of colonies in simulation models is important. For example, the Lotka- Volterra model forms a system of the differential equations expressing predator and prey relationship and many numerical calculations have been conducted to various ecosystems based on expanded L-V models. Conventionally, these top-down methods have been used. However, since this method only describes the average concentration of organisms that are distributed uniformly throughout the system and cannot express the spatial structure of the system, it was difficult to express the ecosystem structures like colonies and substance density distribution. In actual ecosystems, there is heterogeneity in the number of individuals and in substance density, and this is thought to have great significance in ecosystems. Consequently, an Individual-Based-Model was used to give rules to predator-prey relationship, suppression, production, self suppression, etc. of each species. It enabled the emergence of the overall system only

  10. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    ERIC Educational Resources Information Center

    Ginovart, Marta

    2014-01-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

  11. 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.

  12. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

    PubMed Central

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  13. Individual-based modelling of bacterial cultures to study the microscopic causes of the lag phase.

    PubMed

    Prats, Clara; López, Daniel; Giró, Antoni; Ferrer, Jordi; Valls, Joaquim

    2006-08-21

    The lag phase has been widely studied for years in an effort to contribute to the improvement of food safety. Many analytical models have been built and tested by several authors. The use of Individual-based Modelling (IbM) allows us to probe deeper into the behaviour of individual cells; it is a bridge between theories and experiments when needed. INDividual DIScrete SIMulation (INDISIM) has been developed and coded by our group as an IbM simulator and used to study bacterial growth, including the microscopic causes of the lag phase. First of all, the evolution of cellular masses, specifically the mean mass and biomass distribution, is shown to be a determining factor in the beginning of the exponential phase. Secondly, whenever there is a need for an enzyme synthesis, its rate has a direct effect on the lag duration. The variability of the lag phase with different factors is also studied. The known decrease of the lag phase with an increase in the temperature is also observed in the simulations. An initial study of the relationship between individual and collective lag phases is presented, as a complement to the studies already published. One important result is the variability of the individual lag times and generation times. It has also been found that the mean of the individual lags is greater than the population lag. This is the first in a series of studies of the lag phase that we are carrying out. Therefore, the present work addresses a generic system by making a simple set of assumptions. PMID:16524598

  14. Individual based modeling and parameter estimation for a Lotka-Volterra system.

    PubMed

    Waniewski, J; Jedruch, W

    1999-03-15

    Stochastic component, inevitable in biological systems, makes problematic the estimation of the model parameters from a single sequence of measurements, despite the complete knowledge of the system. We studied the problem of parameter estimation using individual-based computer simulations of a 'Lotka-Volterra world'. Two kinds (species) of particles--X (preys) and Y (predators)--moved on a sphere according to deterministic rules and at the collision (interaction) of X and Y the particle X was changed to a new particle Y. Birth of preys and death of predators were simulated by addition of X and removal of Y, respectively, according to exponential probability distributions. With this arrangement of the system, the numbers of particles of each kind might be described by the Lotka-Volterra equations. The simulations of the system with low (200-400 particles on average) number of individuals showed unstable oscillations of the population size. In some simulation runs one of the species became extinct. Nevertheless, the oscillations had some generic properties (e.g. mean, in one simulation run, oscillation period, mean ratio of the amplitudes of the consecutive maxima of X and Y numbers, etc.) characteristic for the solutions of the Lotka-Volterra equations. This observation made it possible to estimate the four parameters of the Lotka-Volterra model with high accuracy and good precision. The estimation was performed using the integral form of the Lotka-Volterra equations and two parameter linear regression for each oscillation cycle separately. We conclude that in spite of the irregular time course of the number of individuals in each population due to stochastic intraspecies component, the generic features of the simulated system evolution can provide enough information for quantitative estimation of the system parameters. PMID:10194922

  15. Examination of a smallest CELSS (microcosm) through an individual-based model simulation

    NASA Astrophysics Data System (ADS)

    Ishikawa, Y.; Yoshida, H.; Kinoshita, M.; Murakami, A.; Sugiura, K.

    2004-01-01

    Research of the effect of space environment on an ecosystem consisting of plants and animals is essential when they are to be positively used in space. Although there have been experiments on various organisms under space environment in the past, they mainly studied the effect of space environment on an individual organism or a single species. Microcosm is drawing attention as an experimental material of an ecosystem consisting of multiple species. The object in this research is to understand the nature of this network system called ecosystem. Thus, a mixed microorganism culturing system consisting of three types of microorganisms which form a minimum food chain system as a closed ecosystem (chlorella as the producer, bacteria as the decomposer, and rotifer as the consumer) was taken for the subject, on which to research the universal characteristics of ecosystems. From the results of experiments under the terrestrial environment, formation of colonies, which is an ecological structure, has been observed at its mature stage. The organisms form an optimal substance circulation system. Therefore, formation of colonies in simulation models is important. Many attempts have been made to create ecosystem models. For example, the Lotka-Volterra model forms a simultaneous equation with the differential equation expressing predator and prey relationship and many numerical calculations have been conducted on various ecosystems based on expanded L-V models. Conventionally, these top-down methods have been used. However, since this method only describes the average concentration of organisms that are distributed uniformly throughout the system and cannot express the spatial structure of the system, it was difficult to express ecosystem structures like colonies and density distributions. In actual ecosystems, there is heterogeneity in the number of individuals and in substance density, and this is thought to have great significance in ecosystems. Consequently, an individual-based

  16. A theoretical individual-based model of Brown Ring Disease in Manila clams, Venerupis philippinarum

    NASA Astrophysics Data System (ADS)

    Paillard, Christine; Jean, Fred; Ford, Susan E.; Powell, Eric N.; Klinck, John M.; Hofmann, Eileen E.; Flye-Sainte-Marie, Jonathan

    2014-08-01

    An individual-based mathematical model was developed to investigate the biological and environmental interactions that influence the prevalence and intensity of Brown Ring Disease (BRD), a disease, caused by the bacterial pathogen, Vibrio tapetis, in the Manila clam (Venerupis (= Tapes, = Ruditapes) philippinarum). V. tapetis acts as an external microparasite, adhering at the surface of the mantle edge and its secretion, the periostracal lamina, causing the symptomatic brown deposit. Brown Ring Disease is atypical in that it leaves a shell scar that provides a unique tool for diagnosis of either live or dead clams. The model was formulated using laboratory and field measurements of BRD development in Manila clams, physiological responses of the clam to the pathogen, and the physiology of V. tapetis, as well as theoretical understanding of bacterial disease progression in marine shellfish. The simulation results obtained for an individual Manila clam were expanded to cohorts and populations using a probability distribution that prescribed a range of variability for parameters in a three dimensional framework; assimilation rate, clam hemocyte activity rate (the number of bacteria ingested per hemocyte per day), and clam calcification rate (a measure of the ability to recover by covering over the symptomatic brown ring deposit), which sensitivity studies indicated to be processes important in determining BRD prevalence and intensity. This approach allows concurrent simulation of individuals with a variety of different physiological capabilities (phenotypes) and hence by implication differing genotypic composition. Different combinations of the three variables provide robust estimates for the fate of individuals with particular characteristics in a population that consists of mixtures of all possible combinations. The BRD model was implemented using environmental observations from sites in Brittany, France, where Manila clams routinely exhibit BRD signs. The simulated

  17. Population Evolution Model with the Wealth of the Individual Based on Penna Model

    NASA Astrophysics Data System (ADS)

    He, Mingfeng; Yu, Binglin; Chen, Liyu; Fang, Jian

    We present a simulation model based on the Penna model to study the population evolution. The wealth of the individual is considered in the model. We define increasing ratio α and decreasing ratio β of the wealth presenting the individual wealth variation, also define minimum wealth PROMO which works when one reproduces. We study the influence of α and β on a species' survival or downfall, and the influence of PROMO on the age distribution of a species. According to the different values of α and β, we find diverse regimes where a species will survive or die out, and even the regime where species' survival or downfall are very sensitive. We study the relation between life expectancy and the wealth of the individual, finding that life expectancy doesn't increase but decrease a little when the wealth of the individual increases.

  18. 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.

  19. INTRASPECIFIC COMPETITION AND SPATIAL HETEROGENEITY ALTER LIFE HISTORY TRAITS IN AN INDIVIDUAL-BASED MODEL OF GRASSHOPPERS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To aid in our understanding of the evolution of grasshopper life histories and their influence on population dynamics, an individual-based simulation model was developed that incorporates methods of evolutionary computation. Life history attributes, such as size of eggs, and timing of diapause, wer...

  20. 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

  1. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    NASA Astrophysics Data System (ADS)

    Ginovart, Marta

    2014-08-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

    NASA Astrophysics Data System (ADS)

    Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

    2016-04-01

    At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these

  8. 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

  9. 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; 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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. A Stochastic Individual-Based Model of the Progression of Atrial Fibrillation in Individuals and Populations

    PubMed Central

    Galla, Tobias; Clayton, Richard H.

    2016-01-01

    Models that represent the mechanisms that initiate and sustain atrial fibrillation (AF) in the heart are computationally expensive to simulate and therefore only capture short time scales of a few heart beats. It is therefore difficult to embed biophysical mechanisms into both policy-level disease models, which consider populations of patients over multiple decades, and guidelines that recommend treatment strategies for patients. The aim of this study is to link these modelling paradigms using a stylised population-level model that both represents AF progression over a long time-scale and retains a description of biophysical mechanisms. We develop a non-Markovian binary switching model incorporating three different aspects of AF progression: genetic disposition, disease/age related remodelling, and AF-related remodelling. This approach allows us to simulate individual AF episodes as well as the natural progression of AF in patients over a period of decades. Model parameters are derived, where possible, from the literature, and the model development has highlighted a need for quantitative data that describe the progression of AF in population of patients. The model produces time series data of AF episodes over the lifetimes of simulated patients. These are analysed to quantitatively describe progression of AF in terms of several underlying parameters. Overall, the model has potential to link mechanisms of AF to progression, and to be used as a tool to study clinical markers of AF or as training data for AF classification algorithms. PMID:27070920

  15. [Construction of individual-based ecological model for Scomber japonicas at its early growth stages in East China Sea].

    PubMed

    Li, Yue-Song; Chen, Xin-Jun; Yang, Hong

    2012-06-01

    By adopting FVCOM-simulated 3-D physical field and based on the biological processes of chub mackerel (Scomber japonicas) in its early life history from the individual-based biological model, the individual-based ecological model for S. japonicas at its early growth stages in the East China Sea was constructed through coupling the physical field in March-July with the biological model by the method of Lagrange particle tracking. The model constructed could well simulate the transport process and abundance distribution of S. japonicas eggs and larvae. The Taiwan Warm Current, Kuroshio, and Tsushima Strait Warm Current directly affected the transport process and distribution of the eggs and larvae, and indirectly affected the growth and survive of the eggs and larvae through the transport to the nursery grounds with different water temperature and foods. The spawning grounds in southern East China Sea made more contributions to the recruitment to the fishing grounds in northeast East China Sea, but less to the Yangtze estuary and Zhoushan Island. The northwestern and southwestern parts of spawning grounds had strong connectivity with the nursery grounds of Cheju and Tsushima Straits, whereas the northeastern and southeastern parts of the spawning ground had strong connectivity with the nursery grounds of Kyushu and Pacific Ocean. PMID:22937663

  16. An individual-based model for biofilm formation at liquid surfaces

    NASA Astrophysics Data System (ADS)

    Ardré, Maxime; Henry, Hervé; Douarche, Carine; Plapp, Mathis

    2015-12-01

    The bacterium Bacillus subtilis frequently forms biofilms at the interface between the culture medium and the air. We present a mathematical model that couples a description of bacteria as individual discrete objects to the standard advection-diffusion equations for the environment. The model takes into account two different bacterial phenotypes. In the motile state, bacteria swim and perform a run-and-tumble motion that is biased toward regions of high oxygen concentration (aerotaxis). In the matrix-producer state they excrete extracellular polymers, which allows them to connect to other bacteria and to form a biofilm. Bacteria are also advected by the fluid, and can trigger bioconvection. Numerical simulations of the model reproduce all the stages of biofilm formation observed in laboratory experiments. Finally, we study the influence of various model parameters on the dynamics and morphology of biofilms.

  17. Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

    NASA Astrophysics Data System (ADS)

    Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

    2014-11-01

    Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

  18. Influenza epidemic spread simulation for Poland — a large scale, individual based model study

    NASA Astrophysics Data System (ADS)

    Rakowski, Franciszek; Gruziel, Magdalena; Bieniasz-Krzywiec, Łukasz; Radomski, Jan P.

    2010-08-01

    In this work a construction of an agent based model for studying the effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland are reported. Simple transportation rules were employed to mimic individuals’ travels in dynamic route-changing schemes, allowing for the infection spread during a journey. Parameter space was checked for stable behaviour, especially towards the effective infection transmission rate variability. Although the model reported here is based on quite simple assumptions, it allowed to observe two different types of epidemic scenarios: characteristic for urban and rural areas. This differentiates it from the results obtained in the analogous studies for the UK or US, where settlement and daily commuting patterns are both substantially different and more diverse. The resulting epidemic scenarios from these ABM simulations were compared with simple, differential equations based, SIR models - both types of the results displaying strong similarities. The pDYN software platform developed here is currently used in the next stage of the project employed to study various epidemic mitigation strategies.

  19. Forest dynamics in Oregon landscapes: Evaluation and application of an individual-based model

    USGS Publications Warehouse

    Busing, R.T.; Solomon, A.M.; McKane, R.B.; Burdick, C.A.

    2007-01-01

    The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies. ?? 2007 by the Ecological Society of America.

  1. Large-scale Individual-based Models of Pandemic Influenza Mitigation Strategies

    NASA Astrophysics Data System (ADS)

    Kadau, Kai; Germann, Timothy; Longini, Ira; Macken, Catherine

    2007-03-01

    We have developed a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million people, to assess the likely effectiveness of various potential intervention strategies including antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) [1]. The heterogeneous population structure and mobility is based on available Census and Department of Transportation data where available. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For large basic reproductive numbers R0, we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve a substantial reduction in illness rates. [1] T. C. Germann, K. Kadau, I. M. Longini, and C. A. Macken, Proc. Natl. Acad. Sci. (USA) 103, 5935-5940 (2006).

  2. 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

  3. 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.

  4. 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

  5. Consequences of cannibalism and competition for food in a smallmouth bass population: An individual-based modeling study

    USGS Publications Warehouse

    Dong, Q.; DeAngelis, D.L.

    1998-01-01

    We used an individual-based modeling approach to study the consequences of cannibalism and competition for food in a freshwater fish population. We simulated the daily foraging, growth, and survival of the age-0 fish and older juvenile individuals of a sample population to reconstruct patterns of density dependence in the age-0 fish during the growth season. Cannibalism occurs as a part of the foraging process. For age-0 fish, older juvenile fish are both potential cannibals and competitors of food. We found that competition and cannibalism produced intraclass and interclass density dependence. Our modeling results suggested the following. (1) With low density of juvenile fish and weak interclass interactions, the age-0 fish recruitment shows a Beverton-Holt type of density dependence. (2) With high density of juvenile fish and strong interclass interactions, the age-0 fish recruitment shows a Ricker type of density dependence, and overcompensation occurs. (3) Interclass competition of food is responsible for much of the overcompensation. (4) Cannibalism intensifies the changes in the recruitment that are brought about by competition. Cannibalism can (a) generally reduce the recruitment, (b) particularly reduce the maximum level of recruitment, (c) cause overcompensation to occur at lower densities, and (d) produce a stronger overcompensation. (5) Growth is also a function of density. Cannibalism generally improves average growth of cannibals. (6) Variation in the lengths of age-0 fish increases with density and with a decreased average growth. These results imply that cannibalism and competition for food could strongly affect recruitment dynamics. Our model also showed that the rate of cannibalism either could be fairly even through the whole season or could vary dramatically. The individual-based modeling approach can help ecologists understand the mechanistic connection between daily behavioral and physiological processes operating at the level of individual

  6. Modeling wildlife populations with HexSim

    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 including population viability analysis for on...

  7. 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

  8. 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

  9. 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

  10. Simulating carbon stocks and fluxes of an African tropical montane forest with an individual-based forest model.

    PubMed

    Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

    2015-01-01

    Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha(-1) yr(-1). Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances. PMID:25915854