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. CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

    USGS Publications Warehouse

    Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason

    2016-01-01

    1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

  5. Modeling the population-level effects of hypoxia on a coastal fish: implications of a spatially-explicit individual-based model

    NASA Astrophysics Data System (ADS)

    Rose, K.; Creekmore, S.; Thomas, P.; Craig, K.; Neilan, R.; Rahman, S.; Wang, L.; Justic, D.

    2016-02-01

    The northwestern Gulf of Mexico (USA) currently experiences a large hypoxic area ("dead zone") during the summer. The population-level effects of hypoxia on coastal fish are largely unknown. We developed a spatially-explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of individual Atlantic croaker could lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 x 800 spatial grid of 1 km2 cells for 140 years. Chlorophyll-a concentration and water temperature were specified daily for each grid cell. Dissolved oxygen (DO) was obtained from a 3-D water quality model for four years that differed in their severity of hypoxia. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and movement behavior was based on temperature preferences and avoidance of low DO. Hypoxia effects were imposed using exposure-effects sub-models that converted time-varying exposure to DO to reductions in growth and fecundity, and increases in mortality. Using sequences of mild, intermediate, and severe hypoxia years, the model predicted a 20% decrease in population abundance. Additional simulations were performed under the assumption that river-based nutrients loadings that lead to more hypoxia also lead to higher primary production and more food for croaker. Twenty-five percent and 50% nutrient reduction scenarios were simulated by adjusting the cholorphyll-a concentrations used as food proxy for the croaker. We then incrementally increased the DO concentrations to determine how much hypoxia would need to be reduced to offset the lower food production resulting from reduced nutrients. We discuss the generality of our results, the hidden effects of hypoxia on fish, and our overall strategy of combining laboratory and field studies with modeling to produce robust predictions of population responses to stressors under

  6. 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

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

    PubMed

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

    2015-01-01

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

  8. Uncertainty in spatially explicit animal dispersal models

    USGS Publications Warehouse

    Mooij, Wolf M.; DeAngelis, Donald L.

    2003-01-01

    Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

  9. 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

  10. On spatially explicit models of cholera epidemics

    PubMed Central

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

    2010-01-01

    We generalize a recently proposed model for cholera epidemics that 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 that 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 waterborne pathogens. Using the diffusion approximation, we analytically derive the speed of propagation for travelling fronts of epidemics on regular lattices (either one-dimensional or two-dimensional) endowed with uniform population density. Power laws are found that relate the propagation speed to the diffusion coefficient and the basic reproduction number. We numerically obtain the related, slower speed of epidemic spreading for more complex, yet realistic river structures such as Peano networks and optimal channel networks. The analysis of the limit case of uniformly distributed population sizes proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, the ratio between spreading and disease outbreak time scales 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 susceptible–infected–recovered (SIR)-like type. Our results suggest that in many cases of real-life epidemiological interest, time scales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. PMID:19605400

  11. 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.

  12. 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.

  13. 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.

  14. Spatially explicit modeling in ecology: A review

    USGS Publications Warehouse

    DeAngelis, Donald L.; Yurek, Simeon

    2017-01-01

    The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

  15. 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.

  16. 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.

  17. Maximum sustainable yields from a spatially-explicit harvest model.

    PubMed

    Takashina, Nao; Mougi, Akihiko

    2015-10-21

    Spatial heterogeneity plays an important role in complex ecosystem dynamics, and therefore is also an important consideration in sustainable resource management. However, little is known about how spatial effects can influence management targets derived from a non-spatial harvest model. Here, we extended the Schaefer model, a conventional non-spatial harvest model that is widely used in resource management, to a spatially-explicit harvest model by integrating environmental heterogeneities, as well as species exchange between patches. By comparing the maximum sustainable yields (MSY), one of the central management targets in resource management, obtained from the spatially extended model with that of the conventional model, we examined the effect of spatial heterogeneity. When spatial heterogeneity exists, we found that the Schaefer model tends to overestimate the MSY, implying potential for causing overharvesting. In addition, by assuming a well-mixed population in the heterogeneous environment, we showed analytically that the Schaefer model always overestimate the MSY, regardless of the number of patches existing. The degree of overestimation becomes significant when spatial heterogeneity is marked. Collectively, these results highlight the importance of integrating the spatial structure to conduct sustainable resource management.

  18. 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

  19. Spatially-explicit models of global tree density

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

    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.

  20. Predicting Cumulative Watershed Effects using Spatially Explicit Models

    NASA Astrophysics Data System (ADS)

    MacDonald, L. H.; Litschert, S.

    2004-12-01

    Cumulative watershed effects /(CWEs/) result from the combined effects of land disturbances distributed over both space and time. They are of concern because changes in flow and sediment yields can adversely affect aquatic habitat, channel morphology, water yields, and water quality. The assessment procedures currently used by agencies such as the U.S. Forest Service generally rely on a lumped approach to quantify disturbance, despite the widespread recognition that site conditions and location do matter! The overall goal of our work is to develop spatially-explicit models to quantify changes in flow and sediment yields. Key objectives include: use of readily available GIS data; ease of use for resource managers with minimal GIS experience; modularity so that models can be added or updated; and allowing users to select the models and values for key parameters. The DeltaQ model calculates changes in peak, median, and low flows due to forest management activities and fires. Inputs include GIS data with disturbance polygons, an initial change in flow rate, and the time to recovery. Data from paired watershed studies are provided to help guide the user. The initial version of FORest Erosion Simulation Tools /(FOREST/) calculates sediment production from forest harvest, fires, and unpaved roads. Additional modules are being developed to deliver this sediment to the stream channel and route it to downstream locations. In accordance with our objectives, the user can predict sediment production rates using different empirical equations, assign an initial sediment production rate and a specified linear recovery period, or develop a look-up table based on local knowledge, published values, or data from other models such as WEPP. The required GIS layers vary according to the model/(s/) selected, but generally include past disturbances /(e.g., fires and timber harvest/), roads, and elevation. Outputs include GIS layers and text files that can be subjected to additional

  1. Spatially explicit neutral models for population genetics and community ecology: Extensions of the Neyman-Scott clustering process.

    PubMed

    Shimatani, Ichiro K

    2010-02-01

    Spatially explicit models relating to plant populations have developed little since Felsenstein (1975) pointed out that if limited seed dispersal causes clustering of individuals, such models cannot reach an equilibrium. This paper aims to resolve this issue by modifying the Neyman-Scott cluster point process. The new point processes are dynamic models with random immigration, and the continuous increase in the clustering of individuals stops at some level. Hence, an equilibrium state is achieved, and new individual-based spatially explicit neutral coalescent models are established. By fitting the spatial structure at equilibrium to individual spatial distribution data, we can indirectly estimate seed dispersal and effective population density. These estimates are improved when genetic data are available, and become even more sophisticated if spatial distribution and genetic data pertaining to the offspring are also available.

  2. CDPOP: A spatially explicit cost distance population genetics program

    Treesearch

    Erin L. Landguth; S. A. Cushman

    2010-01-01

    Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

  3. 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.

  4. 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.

  5. A spatially explicit model for tropical tree diversity patterns.

    PubMed

    Horvát, Sz; Derzsi, A; Néda, Z; Balog, A

    2010-08-21

    A simple two-parameter model resembling the classical voter model is introduced to describe macroecological properties of tropical tree communities. The parameters of the model characterize the speciation- and global-dispersion rates. Monte Carlo type computer simulations are performed on the model, investigating species abundances and the spatial distribution of individuals and species. Simulation results are critically compared with the experimental data obtained from a tree census on a 50 hectare area of the Barro Colorado Island (BCI), Panama. Fitting to only two observable quantities from the BCI data (total species number and the slope of the log-log species-area curve at the maximal area), it is possible to reproduce the full species-area curve, the relative species abundance distribution, and a more realistic spatial distribution of species. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  6. Software System Design for Large Scale, Spatially-explicit Agroecosystem Modeling

    SciTech Connect

    Wang, Dali; Nichols, Dr Jeff A; Kang, Shujiang; Post, Wilfred M; Liu, Sumang

    2012-01-01

    Recently, site-based agroecosystem model has been applied at regional and state level to enable comprehensive analyses of environmental sustainability of food and biofuel production. Those large-scale, spatially-explicit simulations present computational challenges in software systems design. Herein, we describe our software system design for large-scale, spatially-explicit agroecosystem modeling and data analysis. First, we describe the software design principles in three major phases: data preparation, high performance simulation, and data management and analysis. Then, we use a case study at a regional intensive modeling area (RIMA) to demonstrate our system implementation and capability.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  8. FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

    Treesearch

    Russell A. Parsons

    2006-01-01

    Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...

  9. 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...

  10. 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 ...

  11. 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 ...

  12. 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...

  13. 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.

  14. Spatially explicit multimedia fate models for pollutants in Europe: state of the art and perspectives.

    PubMed

    Pistocchi, A; Sarigiannis, D A; Vizcaino, P

    2010-08-15

    A review by Hollander et al. (in preparation), discusses the relative potentials, advantages and shortcomings of spatial and non spatial models of chemical fate, highlighting that spatially explicit models may be needed for specific purposes. The present paper reviews the state of the art in spatially explicit chemical fate and transport modeling in Europe. We summarize the three main approaches currently adopted in spatially explicit modeling, namely (1) multiple box models, (2) numerical solutions of simultaneous advection-dispersion equations (ADE) in air, soil and water, and (3) the development of meta-models. As all three approaches experience limitations, we describe in further detail geographic information system (GIS)-based modeling as an alternative approach allowing a simple, yet spatially explicit description of chemical fate. We review the input data needed, and the options available for their retrieval at the European scale. We also discuss the importance of, and limitations in model evaluation. We observe that the high uncertainty in chemical emissions and physico-chemical behavior in the environment make realistic simulations difficult to obtain. Therefore we envisage a shift in model use from process simulation to hypothesis testing, in which explaining the discrepancies between observed and computed chemical concentrations in the environment takes importance over prediction per se. This shift may take advantage of using simple models in GIS with residual uses of complex models for detailed studies. It also calls for tighter joint interpretation of models and spatially distributed monitoring datasets, and more refined spatial representation of environmental drivers such as landscape and climate variables, and better emission estimates. In summary, we conclude that the problem is not "how to compute" (i.e. emphasis on numerical methods, spatial/temporal discretization, quantitative uncertainty and sensitivity analysis...) but "what to compute" (i

  15. Spatially explicit modeling of habitat dynamics and fish population persistence in an intermittent lowland stream.

    PubMed

    Perry, George L W; Bond, Nicholas R

    2009-04-01

    In temperate and arid climate zones many streams and rivers flow intermittently, seasonally contracting to a sequence of isolated pools or waterholes over the dry period, before reconnecting in the wetter parts of the year. This seasonal drying process is central to our understanding of the population dynamics of aquatic organisms such as fish and invertebrates in these systems. However, there is a dearth of empirical data on the temporal dynamics of such populations. We describe a spatially explicit individual-based model (SEIBM) of fish population dynamics in such systems, which we use to explore the long-term population viability of the carp gudgeon Hypseleotris spp. in a lowland stream in southeastern Australia. We explicitly consider the impacts of interannual variability in stream flow, for example, due to drought, on habitat availability and hence population persistence. Our results support observations that these populations are naturally highly variable, with simulated fish population sizes typically varying over four orders of magnitude within a 50-year simulation run. The most sensitive parameters in the model relate to the amount of water (habitat) in the system: annual rainfall, seepage loss from the pools, and the carrying capacity (number of individuals per cubic meter) of the pools as they dry down. It seems likely that temporal source sink dynamics allow the fish populations to persist in these systems, with good years (high rainfall and brief cease-to-flow [CTF] periods) buffering against periods of drought. In dry years during which the stream may contract to very low numbers of pools, each of these persistent pools becomes crucial for the persistence of the population in the system. Climate change projections for this area suggest decreases in rainfall and increased incidence of drought; under these environmental conditions the long-term persistence of these fish populations is uncertain.

  16. ANOSPEX: A Stochastic, Spatially Explicit Model for Studying Anopheles Metapopulation Dynamics

    PubMed Central

    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; AnophelesSpatially-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

  17. Developing Spatially Explicit Habitat Models for Grassland Bird Conservation Planning in the Prairie Pothole Region of North Dakota

    Treesearch

    Neal D. Niemuth; Michael E. Estey; Charles R. Loesch

    2005-01-01

    Conservation planning for birds is increasingly focused on landscapes. However, little spatially explicit information is available to guide landscape-level conservation planning for many species of birds. We used georeferenced 1995 Breeding Bird Survey (BBS) data in conjunction with land-cover information to develop a spatially explicit habitat model predicting the...

  18. 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

  19. 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...

  20. 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...

  1. Modeling trends from North American breeding bird survey data: a spatially explicit approach.

    PubMed

    Bled, Florent; Sauer, John; Pardieck, Keith; Doherty, Paul; Royle, J Andrew

    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.

  2. 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.

  3. 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.

  4. 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.

  5. [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.

  6. Spatially-explicit bioaccumulation modeling in aquatic environments: Results from two demonstration sites.

    PubMed

    von Stackelberg, Katherine; Williams, Marc A; Clough, Jonathan; Johnson, Mark S

    2017-03-11

    Bioaccumulation models quantify the relationship between sediment and water exposure concentrations and resulting tissue levels of chemicals in aquatic organisms, and represent a key link in the suite of tools used to support decision making at contaminated sediment sites. Predicted concentrations in the aquatic food web provide exposure estimates for human health and ecological risk assessments, which, in turn, provide risk-based frameworks for evaluating potential remedial activities and other management alternatives based on the fish consumption pathway. Despite the widespread use of bioaccumulation models to support remedial decision-making, concerns remain about the predictive power of these models. A review of the available literature finds the increased mathematical complexity of typical bioaccumulation model applications is not matched by the deterministic exposure concentrations used to drive the models. We tested a spatially explicit exposure model (FishRand) at two nominally contaminated sites and compared results to estimates of bioaccumulation based on conventional, non-spatial techniques and monitoring data. Differences in predicted fish tissue concentrations across applications were evident, although these demonstration sites were only mildly contaminated and would not warrant management actions on the basis of fish consumption. Nonetheless, predicted tissue concentrations based on the spatially-explicit exposure characterization consistently outperformed conventional, non-spatial techniques across a variety of model performance metrics. These results demonstrate the improved predictive power as well as greater flexibility in evaluating the impacts of food web exposure and fish foraging behavior in a heterogeneous exposure environment. This article is protected by copyright. All rights reserved.

  7. Mapping malaria risk and vulnerability in the United Republic of Tanzania: a spatial explicit model.

    PubMed

    Hagenlocher, Michael; Castro, Marcia C

    2015-01-01

    Outbreaks of vector-borne diseases (VBDs) impose a heavy burden on vulnerable populations. Despite recent progress in eradication and control, malaria remains the most prevalent VBD. Integrative approaches that take into account environmental, socioeconomic, demographic, biological, cultural, and political factors contributing to malaria risk and vulnerability are needed to effectively reduce malaria burden. Although the focus on malaria risk has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria risk including malaria vulnerability in a spatial explicit manner. Building on a conceptual risk and vulnerability framework, we propose a spatial explicit approach for modeling relative levels of malaria risk - as a function of hazard, exposure, and vulnerability - in the United Republic of Tanzania. A logistic regression model was employed to identify a final set of risk factors and their contribution to malaria endemicity based on multidisciplinary geospatial information. We utilized a Geographic Information System for the construction and visualization of a malaria vulnerability index and its integration into a spatially explicit malaria risk map. The spatial pattern of malaria risk was very heterogeneous across the country. Malaria risk was higher in Mainland areas than in Zanzibar, which is a result of differences in both malaria entomological inoculation rate and prevailing vulnerabilities. Areas of high malaria risk were identified in the southeastern part of the country, as well as in two distinct "hotspots" in the northwestern part of the country bordering Lake Victoria, while concentrations of high malaria vulnerability seem to occur in the northwestern, western, and southeastern parts of the mainland. Results were visualized using both 10×10 km(2) grids and subnational administrative units. The presented approach makes an important contribution toward a decision support tool. By decomposing malaria

  8. 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...

  9. 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...

  10. Using spatially explicit surveillance models to provide confidence in the eradication of an invasive ant

    PubMed Central

    Ward, Darren F.; Anderson, Dean P.; Barron, Mandy C.

    2016-01-01

    Effective detection plays an important role in the surveillance and management of invasive species. Invasive ants are very difficult to eradicate and are prone to imperfect detection because of their small size and cryptic nature. Here we demonstrate the use of spatially explicit surveillance models to estimate the probability that Argentine ants (Linepithema humile) have been eradicated from an offshore island site, given their absence across four surveys and three surveillance methods, conducted since ant control was applied. The probability of eradication increased sharply as each survey was conducted. Using all surveys and surveillance methods combined, the overall median probability of eradication of Argentine ants was 0.96. There was a high level of confidence in this result, with a high Credible Interval Value of 0.87. Our results demonstrate the value of spatially explicit surveillance models for the likelihood of eradication of Argentine ants. We argue that such models are vital to give confidence in eradication programs, especially from highly valued conservation areas such as offshore islands. PMID:27721491

  11. Using spatially explicit surveillance models to provide confidence in the eradication of an invasive ant.

    PubMed

    Ward, Darren F; Anderson, Dean P; Barron, Mandy C

    2016-10-10

    Effective detection plays an important role in the surveillance and management of invasive species. Invasive ants are very difficult to eradicate and are prone to imperfect detection because of their small size and cryptic nature. Here we demonstrate the use of spatially explicit surveillance models to estimate the probability that Argentine ants (Linepithema humile) have been eradicated from an offshore island site, given their absence across four surveys and three surveillance methods, conducted since ant control was applied. The probability of eradication increased sharply as each survey was conducted. Using all surveys and surveillance methods combined, the overall median probability of eradication of Argentine ants was 0.96. There was a high level of confidence in this result, with a high Credible Interval Value of 0.87. Our results demonstrate the value of spatially explicit surveillance models for the likelihood of eradication of Argentine ants. We argue that such models are vital to give confidence in eradication programs, especially from highly valued conservation areas such as offshore islands.

  12. 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

  13. A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone.

    PubMed

    Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A

    2006-11-01

    A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.

  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. Movement rules for individual-based models of stream fish

    Treesearch

    Steven F. Railsback; Roland H. Lamberson; Bret C. Harvey; Walter E. Duffy

    1999-01-01

    Abstract - Spatially explicit individual-based models (IBMs) use movement rules to determine when an animal departs its current location and to determine its movement destination; these rules are therefore critical to accurate simulations. Movement rules typically define some measure of how an individual's expected fitness varies among locations, under the...

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

    PubMed

    Kienberger, Stefan; Hagenlocher, Michael

    2014-08-15

    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. 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 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 immunity indicator which has a

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

    Treesearch

    Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

    2005-01-01

    Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

  2. Landscape-based spatially explicit species index models for everglades restoration

    USGS Publications Warehouse

    Curnutt, J.L.; Comiskey, J.; Nott, M.P.; Gross, L.J.

    2000-01-01

    As part of the effort to restore the ???10 000-km2 Everglades drainage in southern Florida, USA, we developed spatially explicit species index (SESI) models of a number of species and species groups. In this paper we describe the methodology and results of three such models: those for the Cape Sable Seaside Sparrow and the Snail Kite, and the species group model of long-legged wading birds. SESI models are designed to produce relative comparisons of one management alternative to a base scenario or to another alternative. The model outputs do not provide an exact quantitative prediction of future biotic group responses, but rather, when applying the same input data and different hydrologic plans, the models provide the best available means to compare the relative response of the biotic groups. We compared four alternative hydrologic management scenarios to a base scenario (i.e., predicted conditions assuming that current water management practices continue). We ranked the results of the comparisons for each set of models. No one scenario was beneficial to all species; however, they provide a uniform assessment, based on the best available observational information, of relative species responses to alternative water-management plans. As such, these models were used extensively in the restoration planning.

  3. 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.

  4. Spatially explicit cholera model: effects of population, water resources and health conditions distributions.

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    Cholera epidemics are still a major public health concern to date in many areas of the world. In order to understand and forecast cholera outbreaks, one of the most important factors is the role played by the environmental matrix in which the disease spreads. The environmental matrix is constituted by different human communities and their interconnections. Each community is characterized by its spatial position, population size, water resources availability and hygiene conditions. By implementing a spatially explicit cholera model we seek the effects on epidemic dynamics of: i) the topology and metrics of the pathogens pathways that connect different communities; ii) the spatial distribution of the population size; and iii) the spatial distributions of water resources and public health conditions, and how they vary with population size. We further extend the model by deriving the speed of propagation of traveling fronts in the case of uniformly distributed systems for different topologies: one and two dimensional lattices and river networks. The derivation of the spreading celerity proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. The conditions are sought by comparison between spreading and disease timescales. Consider a cholera epidemic that starts from a point and spreads throughout a finite size system, it is possible to identify two different timescales: i) the spreading timescale, that is the time needed for the disease to spread and involve all the communities in the system; and ii) the epidemic timescale, defined by the duration of the epidemic in a single community. While the latter mainly depends on biological factors, the former is controlled also by the geometry of the environmental matrix. If the epidemics timescales are comparable or larger than pathogens' spreading timescales, one expects that the spatial variability does not play a role and the system may be approximated by a well

  5. 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.

  6. Spatially-explicit modelling of nutrient loading to the landscape in the Great Lakes Basin

    NASA Astrophysics Data System (ADS)

    Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Hyndman, D. W.

    2016-12-01

    Loading of nitrogen and phosphorus to the landscape has resulted in dangerous algal blooms, contaminated drinking water, and decreased biodiversity. Here, we developed a GIS model to estimate spatially explicit nutrient loading across the Great Lakes Basin. The model expands on previous work in the lower peninsula of Michigan by Luscz et al. (2015). Inputs to the model include point source loads to streams along with five non-point source landscape loads: atmospheric deposition, chemical agricultural fertilizer, chemical non-agricultural fertilizer, manure application, and septic tanks. Scaling up from Michigan to the eight U.S. states and two Canadian provinces in the Great Lakes Basin provided unique challenges. In the case of the septic tank inputs, we compiled a multistate database of drinking water wells for use in an automated Python script to delineate wastewater treatment plant service areas and to estimate placement of septic tanks appropriately within the landscape. Using a model with individual nutrient inputs showed that even within a single land use class, there is high variability in loading rates. This variability suggests that simply prescribing loading estimates based on land use class is insufficient. Modelling high resolution and source specific landscape nutrient loading will be valuable to target strategies to decrease excessive anthropogenic nutrient loading in the Great Lakes Basin.

  7. 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.

  8. 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.

  9. Life cycle impact assessment of terrestrial acidification: modeling spatially explicit soil sensitivity at the global scale.

    PubMed

    Roy, Pierre-Olivier; Deschênes, Louise; Margni, Manuele

    2012-08-07

    This paper presents a novel life cycle impact assessment (LCIA) approach to derive spatially explicit soil sensitivity indicators for terrestrial acidification. This global approach is compatible with a subsequent damage assessment, making it possible to consistently link the developed midpoint indicators with a later endpoint assessment along the cause-effect chain-a prerequisite in LCIA. Four different soil chemical indicators were preselected to evaluate sensitivity factors (SFs) for regional receiving environments at the global scale, namely the base cations to aluminum ratio, aluminum to calcium ratio, pH, and aluminum concentration. These chemical indicators were assessed using the PROFILE geochemical steady-state soil model and a global data set of regional soil parameters developed specifically for this study. Results showed that the most sensitive regions (i.e., where SF is maximized) are in Canada, northern Europe, the Amazon, central Africa, and East and Southeast Asia. However, the approach is not bereft of uncertainty. Indeed, a Monte Carlo analysis showed that input parameter variability may induce SF variations of up to over 6 orders of magnitude for certain chemical indicators. These findings improve current practices and enable the development of regional characterization models to assess regional life cycle inventories in a global economy.

  10. 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...

  11. 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...

  12. Field theory for biogeography: a spatially explicit model for predicting patterns of biodiversity

    PubMed Central

    O'Dwyer, James P; Green, Jessica L

    2010-01-01

    Predicting the variation of biodiversity across the surface of the Earth is a fundamental issue in ecology, and in this article we focus on one of the most widely studied spatial biodiversity patterns: the species–area relationship (SAR). The SAR is a central tool in conservation, being used to predict species loss following global climate change, and is striking in its universality throughout different geographical regions and across the tree of life. In this article we draw upon the methods of quantum field theory and the foundation of neutral community ecology to derive the first spatially explicit neutral prediction for the SAR. We find that the SAR has three phases, with a power law increase at intermediate scales, consistent with decades of documented empirical patterns. Our model also provides a building block for incorporating non-neutral biological variation, with the potential to bridge the gap between neutral and niche-based approaches to community assembly. Ecology Letters (2010) 13: 87–95 PMID:19909313

  13. 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

  14. 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

  15. Development and Validation of Spatially Explicit Habitat Models for Cavity-nesting Birds in Fishlake National Forest, Utah

    Treesearch

    Randall A., Jr. Schultz; Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino

    2005-01-01

    The ability of USDA Forest Service Forest Inventory and Analysis (FIA) generated spatial products to increase the predictive accuracy of spatially explicit, macroscale habitat models was examined for nest-site selection by cavity-nesting birds in Fishlake National Forest, Utah. One FIA-derived variable (percent basal area of aspen trees) was significant in the habitat...

  16. 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.

  17. Spatially Explicit Modelling of the Belgian Major Endurance Event ‘The 100 km Dodentocht’

    PubMed Central

    Van Nieuland, Steffie; Baetens, Jan M.; De Baets, Bernard

    2016-01-01

    ‘The 100 km Dodentocht’, which takes place annually and has its start in Bornem, Belgium, is a long distance march where participants have to cover a 100 km trail in at most 24 hours. The approximately 11 000 marchers per edition are tracked by making use of passive radio-frequency-identification (RFID). These tracking data were analyzed to build a spatially explicit marching model that gives insights into the dynamics of the event and allows to evaluate the effect of changes in the starting procedure of the event. For building the model, the empirical distribution functions (edf) of the marching speeds at every section of the trail in between two consecutive checkpoints and of the checkpoints where marchers retire, are determined, taking into account age, gender, and marching speeds at previous sections. These distribution functions are then used to sample the consecutive speeds and retirement, and as such to simulate the times when individual marchers pass by the consecutive checkpoints. We concluded that the data-driven model simulates the event reliably. Furthermore, we tested three scenarios to reduce the crowdiness along the first part of the trail and in this way were able to conclude that either the start should be moved to a location outside the town center where the streets are at least 25% wider, or that the marchers should start in two groups at two different locations, and that these groups should ideally merge at about 20 km after the start. The crowdiness at the start might also be reduced by installing a bottleneck at the start in order to limit the number of marchers that can pass per unit of time. Consequently, the operating hours of the consecutive checkpoints would be longer. The developed framework can likewise be used to analyze and improve the operation of other endurance events if sufficient tracking data are available. PMID:27764202

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

    USGS Publications Warehouse

    Twedt, D.J.; Uihlein, W.B.; 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.

  19. Consequences of environmental and biological variances for range margins: a spatially explicit theoretical model

    NASA Astrophysics Data System (ADS)

    Malanson, G. P.; DeRose, R. J.; Bekker, M. F.

    2016-12-01

    The consequences of increasing climatic variance while including variability among individuals and populations are explored for range margins of species with a spatially explicit simulation. The model has a single environmental gradient and a single species then extended to two species. Species response to the environment is a Gaussian function with a peak of 1.0 at their peak fitness on the gradient. The variance in the environment is taken from the total variance in the tree ring series of 399 individuals of Pinus edulis in FIA plots in the western USA. The variability is increased by a multiplier of the standard deviation for various doubling times. The variance of individuals in the simulation is drawn from these same series. Inheritance of individual variability is based on the geographic locations of the individuals. The variance for P. edulis is recomputed as time-dependent conditional standard deviations using the GARCH procedure. Establishment and mortality are simulated in a Monte Carlo process with individual variance. Variance for P. edulis does not show a consistent pattern of heteroscedasticity. An obvious result is that increasing variance has deleterious effects on species persistence because extreme events that result in extinctions cannot be balanced by positive anomalies, but even less extreme negative events cannot be balanced by positive anomalies because of biological and spatial constraints. In the two species model the superior competitor is more affected by increasing climatic variance because its response function is steeper at the point of intersection with the other species and so the uncompensated effects of negative anomalies are greater for it. These theoretical results can guide the anticipated need to mitigate the effects of increasing climatic variability on P. edulis range margins. The trailing edge, here subject to increasing drought stress with increasing temperatures, will be more affected by negative anomalies.

  20. 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. Copyright © 2011

  1. 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

  2. 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

  3. 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

  4. 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

  5. Hydroclimatology of Dual Peak Cholera Incidence in Bengal Region: Inferences from a Spatial Explicit Model

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    The seasonality of cholera and its relation with environmental drivers are receiving increasing interest and research efforts, yet they remain unsatisfactorily understood. A striking example is the observed annual cycle of cholera incidence in the Bengal region which exhibits two peaks despite the main environmental drivers that have been linked to the disease (air and sea surface temperature, zooplankton density, river discharge) follow a synchronous single-peak annual pattern. A first outbreak, mainly affecting the coastal regions, occurs in spring and it is followed, after a period of low incidence during summer, by a second, usually larger, peak in autumn also involving regions situated farther inland. A hydroclimatological explanation for this unique seasonal cycle has been recently proposed: the low river spring flows favor the intrusion of brackish water (the natural environment of the causative agent of the disease) which, in turn, triggers the first outbreak. The summer rising river discharges have a temporary dilution effect and prompt the repulsion of contaminated water which lowers the disease incidence. However, the monsoon flooding, together with the induced crowding of the population and the failure of the sanitation systems, can possibly facilitate the spatial transmission of the disease and promote the autumn outbreak. We test this hypothesis using a mechanistic, spatially explicit model of cholera epidemic. The framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for the annual fluctuation of the river flow. The model is forced with the actual environmental drivers of the region, namely river flow and temperature. Our results show that these two drivers, both having a single peak in the summer, can generate a double peak cholera incidence pattern. Besides temporal patterns, the model is also able to qualitatively reproduce spatial patterns characterized

  6. 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.

  7. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

    EPA Pesticide Factsheets

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

  8. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

    EPA Pesticide Factsheets

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

  9. 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.

  10. Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

    DTIC Science & Technology

    2015-08-01

    assessments. Bioaccumulation of sediment-associated contaminants through aquatic food webs often represents the predominant pathway of concern in these risk...associated organic contaminants likely to bioaccumulate in aquatic food webs leading to the potential for human health and ecological impacts through...identified the “evaluation of food web models in setting remedial goals and long-term monitoring requirements” as a critical research area. This was

  11. 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.

  12. 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.

  13. 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...

  14. 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...

  15. 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.

  16. 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.

  17. Analysis of sensitivity and uncertainty in an individual-based model of a threatened wildlife species

    Treesearch

    Bruce G. Marcot; Peter H. Singleton; Nathan H. Schumaker

    2015-01-01

    Sensitivity analysis—determination of how prediction variables affect response variables—of individual-based models (IBMs) are few but important to the interpretation of model output. We present sensitivity analysis of a spatially explicit IBM (HexSim) of a threatened species, the Northern Spotted Owl (NSO; Strix occidentalis caurina) in Washington...

  18. 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...

  19. An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

    Treesearch

    Brenda Rashleigh; Gary D. Grossman

    2005-01-01

    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 based on consumption bioenergetics of benthic macroinvertebrate prey;...

  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. Phosphorus in global agricultural soils: spatially explicit modelling of soil phosphorus and crop uptake for 1900 to 2010

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Beusen, A.; Bouwman, L.; Apeldoorn, D. V.; Yu, C.

    2016-12-01

    Phosphorus (P) plays a vital role in global crop production and food security. To explore the global P status of soils, in this study we developed a spatially explicit version of a two-pool dynamic soil P model at 0.5°resolution. With this model, we analyzed the historical changes of soil P inputs (including manure and inorganic P fertilizer) from 1900 to 2010, reproduced the historical crop P uptake, calculated the phosphorus use efficiency (PUE) and conducted a comprehensive inventory of soil P pools and P budgets (deficit and surplus) in global soils under croplands. Our results suggest that the spatially explicit model is capable of simulating the long-term soil P budget changes and crop uptake, with model simulations closely matching historical P uptake for cropland in all countries. The global P inputs from fertilizers and manure increased from 2 Tg P in 1900 to 23 Tg P in 2010 with great variation across different regions and countries of the world. The magnitude of crop uptake has also changed rapidly over the 20th century: according to our model, crop P uptake per hectare in Western Europe increased by more than three times while the total soil P stock per hectare increased by close to 37% due to long-term P surplus application, with a slight decrease in recent years. Croplands in China (total P per hectare slight decline during 1900-1970, +34% since 1970) and India (total P per hectare gradual increase by 14% since 1900, 6% since 1970) are currently in the phase of accumulation.The total soil P content per hectare in Sub-Saharan Africa has slightly decreased since 1900.Our model is a promising tool to analyze the changes in the soil P status and the capacity of soils to supply P to crops, including future projections of required nutrient inputs.

  2. 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

  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. 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 ...

  5. Analyzing key constraints to biogas production from crop residues and manure in the EU-A spatially explicit model.

    PubMed

    Einarsson, Rasmus; Persson, U Martin

    2017-01-01

    This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates' biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures' carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent).

  6. Analyzing key constraints to biogas production from crop residues and manure in the EU—A spatially explicit model

    PubMed Central

    Persson, U. Martin

    2017-01-01

    This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates’ biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures’ carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent). PMID:28141827

  7. An empirical evaluation of camera trapping and spatially explicit capture-recapture models for estimating chimpanzee density.

    PubMed

    Després-Einspenner, Marie-Lyne; Howe, Eric J; Drapeau, Pierre; Kühl, Hjalmar S

    2017-03-07

    Empirical validations of survey methods for estimating animal densities are rare, despite the fact that only an application to a population of known density can demonstrate their reliability under field conditions and constraints. Here, we present a field validation of camera trapping in combination with spatially explicit capture-recapture (SECR) methods for enumerating chimpanzee populations. We used 83 camera traps to sample a habituated community of western chimpanzees (Pan troglodytes verus) of known community and territory size in Taï National Park, Ivory Coast, and estimated community size and density using spatially explicit capture-recapture models. We aimed to: (1) validate camera trapping as a means to collect capture-recapture data for chimpanzees; (2) validate SECR methods to estimate chimpanzee density from camera trap data; (3) compare the efficacy of targeting locations frequently visited by chimpanzees versus deploying cameras according to a systematic design; (4) evaluate the performance of SECR estimators with reduced sampling effort; and (5) identify sources of heterogeneity in detection probabilities. Ten months of camera trapping provided abundant capture-recapture data. All weaned individuals were detected, most of them multiple times, at both an array of targeted locations, and a systematic grid of cameras positioned randomly within the study area, though detection probabilities were higher at targeted locations. SECR abundance estimates were accurate and precise, and analyses of subsets of the data indicated that the majority of individuals in a community could be detected with as few as five traps deployed within their territory. Our results highlight the potential of camera trapping for cost-effective monitoring of chimpanzee populations.

  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 modelling of forest structure and function using airborne lidar and hyperspectral remote sensing data combined with micrometeorological measurements

    NASA Astrophysics Data System (ADS)

    Thomas, Valerie Anne

    This research models canopy-scale photosynthesis at the Groundhog River Flux Site through the integration of high-resolution airborne remote sensing data and micrometeorological measurements collected from a flux tower. Light detection and ranging (lidar) data are analysed to derive models of tree structure, including: canopy height, basal area, crown closure, and average aboveground biomass. Lidar and hyperspectral remote sensing data are used to model canopy chlorophyll (Chl) and carotenoid concentrations (known to be good indicators of photosynthesis). The integration of lidar and hyperspectral data is applied to derive spatially explicit models of the fraction of photosynthetically active radiation (fPAR) absorbed by the canopy as well as a species classification for the site. These products are integrated with flux tower meteorological measurements (i.e., air temperature and global solar radiation) collected on a continuous basis over 2004 to apply the C-Fix model of carbon exchange to the site. Results demonstrate that high resolution lidar and lidar-hyperspectral integration techniques perform well in the boreal mixedwood environment. Lidar models are well correlated with forest structure, despite the complexities introduced in the mixedwood case (e.g., r2=0.84, 0.89, 0.60, and 0.91, for mean dominant height, basal area, crown closure, and average aboveground biomass). Strong relationships are also shown for canopy scale chlorophyll/carotenoid concentration analysis using integrated lidar-hyperspectral techniques (e.g., r2=0.84, 0.84, and 0.82 for Chl(a), Chl(a+b), and Chl(b)). Examination of the spatially explicit models of fPAR reveal distinct spatial patterns which become increasingly apparent throughout the season due to the variation in species groupings (and canopy chlorophyll concentration) within the 1 km radius surrounding the flux tower. Comparison of results from the modified local-scale version of the C-Fix model to tower gross ecosystem

  10. 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.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  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 matrix models. A mathematical analysis of stage-structured integrodifference equations.

    PubMed

    Lutscher, Frithjof; Lewis, Mark A

    2004-03-01

    This paper is concerned with mathematical analysis of the 'critical domain-size' problem for structured populations. Space is introduced explicitly into matrix models for stage-structured populations. Movement of individuals is described by means of a dispersal kernel. The mathematical analysis investigates conditions for existence, stability and uniqueness of equilibrium solutions as well as some bifurcation behaviors. These mathematical results are linked to species persistence or extinction in connected habitats of different sizes or fragmented habitats; hence the framework is given for application of such models to ecology. Several approximations which reduce the complexity of integrodifference equations are given. A simple example is worked out to illustrate the analytical results and to compare the behavior of the integrodifference model to that of the approximations.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  19. Spatially explicit modeling of mixed-severity fire regimes and landscape dynamics

    Treesearch

    Michael C. Wimberly; Rebecca S.H. Kennedy

    2008-01-01

    Simulation models of disturbance and succession are being increasingly applied to characterize landscape composition and dynamics under natural fire regimes, and to evaluate alternative management strategies for ecological restoration and fire hazard reduction. However, we have a limited understanding of how landscapes respond to changes in fire frequency, and about...

  20. Integrating ecosystem sampling, gradient modeling, remote sensing, and ecosystem simulation to create spatially explicit landscape inventories

    Treesearch

    Robert E. Keane; Matthew G. Rollins; Cecilia H. McNicoll; Russell A. Parsons

    2002-01-01

    Presented is a prototype of the Landscape Ecosystem Inventory System (LEIS), a system for creating maps of important landscape characteristics for natural resource planning. This system uses gradient-based field inventories coupled with gradient modeling remote sensing, ecosystem simulation, and statistical analyses to derive spatial data layers required for ecosystem...

  1. 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

  2. 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

  3. Cohen's Kappa and classification table metrics 2.0: An ArcView 3.x extension for accuracy assessment of spatially explicit models

    Treesearch

    Jeff Jenness; J. Judson Wynne

    2005-01-01

    In the field of spatially explicit modeling, well-developed accuracy assessment methodologies are often poorly applied. Deriving model accuracy metrics have been possible for decades, but these calculations were made by hand or with the use of a spreadsheet application. Accuracy assessments may be useful for: (1) ascertaining the quality of a model; (2) improving model...

  4. 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.

  5. Improvement, Verification, and Refinement of Spatially Explicit Exposure Models in Risk Assessment - SEEM Demonstration

    DTIC Science & Technology

    2015-06-01

    Food   Items/Prey And  Bioaccumulation  Factor Wildlife Receptor  and Receptor  Foraging  Characteristics Draw Polygons  Defining Site  Chemistry  and...Society of Environmental Toxicology and Chemistry TSCA Toxic Substances Control Act TRV toxicity reference value TWEM Terrestrial Wildlife...It relies on inputs including deterministic bioaccumulation factors, terrestrial food chain ingestion modeling factors, toxicity reference values

  6. Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - SEEM

    DTIC Science & Technology

    2015-06-01

    also partly composed of tulip trees , maple , sweet gum, and mowed or developed fields. 5.2.2 Sampling Methods This study was conducted in...the short-tailed shrew (Blarina brevicauda), and the southern red -backed vole (Clethrionomys gapperi) were the three mammalian receptors utilized...in these models. The white-footed mouse and short-tailed shrew were both noted during site visits. The southern red -backed vole was assumed to be

  7. 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.

  8. Improving ecosystem productivity modeling through spatially explicit estimation of optimal light use efficiency

    NASA Astrophysics Data System (ADS)

    Madani, Nima; Kimball, John S.; Affleck, David L. R.; Kattge, Jens; Graham, Jon; van Bodegom, Peter M.; Reich, Peter B.; Running, Steven W.

    2014-09-01

    A common assumption of remote sensing-based light use efficiency (LUE) models for estimating vegetation gross primary productivity (GPP) is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed constant biome maximum light use efficiency parameter (LUEmax) defines the maximum photosynthetic carbon conversion rate under these conditions and is a large source of model uncertainty. Here we used tower eddy covariance measurement-based carbon (CO2) fluxes for spatial estimation of optimal LUE (LUEopt) across North America. LUEopt was estimated at 62 Flux Network sites using tower daily carbon fluxes and meteorology, and satellite observed fractional photosynthetically active radiation from the Moderate Resolution Imaging Spectroradiometer. A geostatistical model was fitted to 45 flux tower-derived LUEopt data points using independent geospatial environmental variables, including global plant traits, soil moisture, terrain aspect, land cover type, and percent tree cover, and validated at 17 independent tower sites. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from the sparse tower network. Leaf nitrogen content and soil moisture regime are major factors explaining LUEopt patterns. GPP derived from estimated LUEopt shows significant correlation improvement against tower GPP records (R2 = 76.9%; mean root-mean-square error (RMSE) = 257 g C m-2 yr-1), relative to alternative GPP estimates derived using biome-specific LUEmax constants (R2 = 34.0%; RMSE = 439 g C m-2 yr-1). GPP determined from the LUEopt map also explains a 49.4% greater proportion of tower GPP variability at the independent validation sites and shows promise for improving understanding of LUE patterns and environmental controls and enhancing regional GPP monitoring from satellite remote sensing.

  9. 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

  10. 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.

  11. Using spatially explicit models to characterize foraging performance in heterogeneous landscapes.

    PubMed

    Grünbaum, D

    1998-02-01

    The success of most foragers is constrained by limits to their sensory perception, memory, and locomotion. However, a general and quantitative understanding of how these constraints affect foraging benefits, and the trade-offs they imply for foraging strategies, is difficult to achieve. This article develops foraging performance statistics to assess constraints and define trade-offs for foragers using biased random walk behaviors, a widespread class of foraging strategies that includes area-restricted searches, kineses, and taxes. The statistics are expected payoff and expected travel time and assess two components of foraging performance: how effectively foragers distinguish between resource-poor and resource-rich parts of their environments and how quickly foragers in poor parts of the environment locate resource concentrations. These statistics provide a link between mechanistic models of individuals' movement and functional responses, population-level models of forager distributions in space and time, and foraging theory predictions of optimal forager distributions and criteria for abandoning resource patches. Application of the analysis to area-restricted search in coccinellid beetles suggests that the most essential aspect of these predators's foraging strategy is the "turning threshold," the prey density at which ladybirds switch from slow to rapid turning. This threshold effectively determines whether a forager exploits or abandons a resource concentration. Foraging is most effective when the threshold is tuned to match physiological or energetic requirements. These performance statistics also help anticipate and interpret the dynamics of complex spatially and temporally varying forager-resource systems.

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

    USGS Publications Warehouse

    Wise, Daniel R.; O'Connor, Jim

    2016-06-27

    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.

  13. Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance

    USGS Publications Warehouse

    Huang, Shengli; Liu, Heping; Dahal, Devendra; Jin, Suming; Welp, Lisa R.; Liu, Jinxun; Liu, Shuguang

    2013-01-01

    In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098 gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging

  14. 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.

  15. 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.

  16. 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.

  17. A watershed-based spatially-explicit demonstration of an integrated environmental modeling framework for ecosystem services in the Coal River Basin (WV, USA)

    Treesearch

    John M. Johnston; Mahion C. Barber; Kurt Wolfe; Mike Galvin; Mike Cyterski; Rajbir Parmar; Luis Suarez

    2016-01-01

    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 quantity, habitat suitability for aquatic biota, fish biomasses, population densities, ...

  18. 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 ...

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

    EPA Science Inventory

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

  20. Understanding African Swine Fever infection dynamics in Sardinia using a spatially explicit transmission model in domestic pig farms.

    PubMed

    Mur, L; Sánchez-Vizcaíno, J M; Fernández-Carrión, E; Jurado, C; Rolesu, S; Feliziani, F; Laddomada, A; Martínez-López, B

    2017-03-13

    African swine fever virus (ASFV) has been endemic in Sardinia since 1978, resulting in severe losses for local pig producers and creating important problems for the island's veterinary authorities. This study used a spatially explicit stochastic transmission model followed by two regression models to investigate the dynamics of ASFV spread amongst domestic pig farms, to identify geographic areas at highest risk and determine the role of different susceptible pig populations (registered domestic pigs, non-registered domestic pigs [brado] and wild boar) in ASF occurrence. We simulated transmission within and between farms using an adapted version of the previously described model known as Be-FAST. Results from the model revealed a generally low diffusion of ASF in Sardinia, with only 24% of the simulations resulting in disease spread, and for each simulated outbreak on average only four farms and 66 pigs were affected. Overall, local spread (indirect transmission between farms within a 2 km radius through fomites) was the most common route of transmission, being responsible for 98.6% of secondary cases. The risk of ASF occurrence for each domestic pig farm was estimated from the spread model results and integrated in two regression models together with available data for brado and wild boar populations. There was a significant association between the density of all three populations (domestic pigs, brado, and wild boar) and ASF occurrence in Sardinia. The most significant risk factors were the high densities of brado (OR = 2.2) and wild boar (OR = 2.1). The results of both analyses demonstrated that ASF epidemiology and infection dynamics in Sardinia create a complex and multifactorial disease situation, where all susceptible populations play an important role. To stop ASF transmission in Sardinia, three main factors (improving biosecurity on domestic pig farms, eliminating brado practices and better management of wild boars) need to be addressed.

  1. Management of on-farm risk to livestock from bovine tuberculosis in Michigan, USA, white-tailed deer: Predictions from a spatially-explicit stochastic model.

    PubMed

    Ramsey, David S L; O'Brien, Daniel J; Smith, Rick W; Cosgrove, Melinda K; Schmitt, Stephen M; Rudolph, Brent A

    2016-11-01

    The eradication of bovine tuberculosis (bTB), caused by Mycobacterium bovis, from cattle in many locations worldwide is complicated by endemic foci of the disease in free-ranging wildlife. Recent simulation modeling of the bTB outbreak in white-tailed deer (WTD) in Michigan, USA, suggests current management is unlikely to eradicate bTB from the core outbreak area (DMU 452) within the next three decades. However, some level of control short of eradication might sufficiently reduce transmission from deer to cattle to a point at which the negative effects of bTB on the cattle industry could be reduced or eliminated, while minimizing the negative consequences of reducing deer numbers. We extended our existing spatially-explicit, individual-based stochastic simulation model of bTB transmission in WTD to incorporate transmission to cattle, to characterize the effects of vaccination and increased harvest of WTD on cattle herd breakdown rates, to examine the effects of localized culling or vaccination of WTD in the vicinity of cattle farms, to assess the effects of concurrent deer baiting, and to determine the effect of progressive restriction of deer/cattle contact on herd breakdowns. A spatially-explicit "cattle layer" was constructed describing the spatial locations, farm size and cattle density of all farms within and directly adjacent to DMU452. Increased hunter harvest or vaccination of deer, or a combination, would likely decrease the number of cattle herd breakdowns to <1 per year in less than 15 years. Concurrent deer baiting variably increased the time necessary to achieve zero breakdowns. The prevalence of bTB in deer needed to fall below ∼0.5% before ≤1 herd breakdown per year could be expected, and below 0.1% before zero breakdowns were likely. Locally applied post-harvest deer culling or vaccination also rapidly reduced herd breakdowns. On farm biosecurity measures needed to reduce deer to cattle contact by >95% in order to reliably reduce herd breakdowns

  2. 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.

  3. Integration of an Individual-Based Fish Bioenergetics Model into a Spatially Explicit Water Quality Model (CE-QUAL-ICM)

    DTIC Science & Technology

    2010-04-01

    Effects of menhaden predation on plankton populations in Narragansett Bay, Rhode Island. Estuaries 21(3):449-465. Durbin, E. G., and A. G. Durbin...with the number lost to other natural causes (ΔNprd, typically predation ) and those caught by the fishery (ΔNfsh). The number lost due to any specific...cell cell DFSU DO if DO mg l if DO mg l       (4) [DOcell] is the concentration of dissolved oxygen (mg/l). Predation and fishing mortality are

  4. 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

  5. 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

  6. 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.

  7. 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

  8. A different time and place test of ArcHSI: A spatially explicit habitat model for elk in the Black Hills

    Treesearch

    Mark A. Rumble; Lakhdar Benkobi; R. Scott Gamo

    2007-01-01

    We tested predictions of the spatially explicit ArcHSI habitat model for elk. The distribution of elk relative to proximity of forage and cover differed from that predicted. Elk used areas near primary roads similar to that predicted by the model, but elk were farther from secondary roads. Elk used areas categorized as good (> 0.7), fair (> 0.42 to 0.7), and poor...

  9. Habitat restoration from an ecosystem goods and services perspective: Application of a spatially explicit individual-based model

    EPA Science Inventory

    Estuarine ecosystems provide many services to humans, but these ecosystems are also under pressure from human development, which has led to large investments in habitat protection and restoration. Restoration in estuaries is typically focused on emergent and submerged vegetation ...

  10. Habitat restoration from an ecosystem goods and services perspective: Application of a spatially explicit individual-based model

    EPA Science Inventory

    Estuarine ecosystems provide many services to humans, but these ecosystems are also under pressure from human development, which has led to large investments in habitat protection and restoration. Restoration in estuaries is typically focused on emergent and submerged vegetation ...

  11. 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...

  12. 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...

  13. Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean

    PubMed Central

    Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I.; Brdicka, Radim; Jodice, Carla

    2016-01-01

    Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools. PMID:27898725

  14. Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean.

    PubMed

    Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I; Brdicka, Radim; Jodice, Carla; Novelletto, Andrea

    2016-01-01

    Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

  15. 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.

  16. Individual-based Modeling of a Pseudomonas aeruginosa Biofilm with Glucose Substrate

    NASA Astrophysics Data System (ADS)

    Steffens, Matthew J.; Clement, Barbara J.; Wentworth, Christopher D.

    2011-11-01

    Individual-based modeling is a technique for simulating the spatially explicit dynamics of a community of individuals that can each be in a different state. In this investigation we use IBM to simulate growth of a simple biofilm system: Pseudomonas aeruginosa with a glucose substrate. The recently published IBM framework for microbial communities, iDynoMiCS, is used together with growth parameters from a recent kinetics study of this system to explore patterns of films over a 24 hour growth period for a two-dimensional and a 12 hour growth period for a three-dimensional model.

  17. 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

  18. 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

  19. 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

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

    PubMed Central

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

    2015-01-01

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

  1. Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

    PubMed

    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.

  2. A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

    NASA Astrophysics Data System (ADS)

    Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

    2009-04-01

    SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

  3. Exploring the persistence of stream-dwelling trout populations under alternative real-world turbidity regimes with an individual-based model

    Treesearch

    Bret C. Harvey; Steven F. Railsback

    2009-01-01

    We explored the effects of elevated turbidity on stream-resident populations of coastal cutthroat trout Oncorhynchus clarkii clarkii using a spatially explicit individual-based model. Turbidity regimes were contrasted by means of 15-year simulations in a third-order stream in northwestern California. The alternative regimes were based on multiple-year, continuous...

  4. 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.

  5. 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.

  6. LANDIS 4.0 users guide. LANDIS: a spatially explicit model of forest landscape disturbance, management, and succession

    Treesearch

    Hong S. He; Wei Li; Brian R. Sturtevant; Jian Yang; Bo Z. Shang; Eric J. Gustafson; David J. Mladenoff

    2005-01-01

    LANDIS 4.0 is new-generation software that simulates forest landscape change over large spatial and temporal scales. It is used to explore how disturbances, succession, and management interact to determine forest composition and pattern. Also describes software architecture, model assumptions and provides detailed instructions on the use of the model.

  7. Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change

    Treesearch

    Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew. Peters

    2013-01-01

    Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...

  8. Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

    USGS Publications Warehouse

    Ickes, Brian S.; Sauer, J.S.; Richards, N.; Bowler, M.; Schlifer, B.

    2014-01-01

    Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different

  9. A Spatially Explicit Modeling Approach to Capture the Hydrological Effects on Biogeochemical Processes in a Boreal Watershed

    NASA Astrophysics Data System (ADS)

    Govind, A.; Chen, J.

    2009-05-01

    Current estimates of terrestrial carbon (C) fluxes overlook hydrological controls. A modeling study was conducted to explore the hydrological, ecophysiological and biogeochemical interactions in a humid boreal ecosystem. Several hydro-ecological processes were simulated and validated using field measurements for two years. After gaining confidence in the model's ability and having understood that topographically driven sub-surface baseflow is the main process determining the soil moisture regime in humid boreal ecosystem, its influence on ecophysiological and biogeochemical processes were investigated. Three modeling scenarios were designed that represent strategies that are commonly used in ecological models to represent hydrological controls. These scenarios were: 1) Explicit, where realistic lateral water routing was considered; 2) Implicit, where calculations were based on a bucket-modeling approach; and 3) NoFlow, where the lateral sub-surface flow was turned off in the model. In general, the Implicit scenario overestimated GPP, ET and NEP, as opposed to the Explicit scenario. The NoFlow scenario underestimated GPP and ET but overestimated NEP. The key processes controlling the differences were due to the combined effects of variations in plant physiology, photosynthesis, heterotrophic respiration, autotrophic respiration and nitrogen mineralization; all of which occurred simultaneously in different directions, at different rates, affecting the spatio-temporal distribution of terrestrial C-sources or sinks (NEP). The scientific implication of this work is that regional or global scale terrestrial C estimates could have significant errors if proper hydrological constraints are not considered for modeling ecological and biogeochemical processes due to large topographic variations of the Earth's surface and also because of the non-linear interactions between these processes.

  10. Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

    PubMed

    Bateman, Ian; Agarwala, Matthew; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Lovett, Andrew; Posen, Paulette

    2016-10-01

    We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale.

  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. 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 ...

  13. 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.

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

    PubMed

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

    2008-07-28

    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. 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 x 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 x 500 km2 region, each producing between 1.24 and 2.38 x 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. 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 accommodate a range of processing

  15. 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

  16. 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.

  17. 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.

  18. Achieving Durable Resistance Against Plant Diseases: Scenario Analyses with a National-Scale Spatially Explicit Model for a Wind-Dispersed Plant Pathogen.

    PubMed

    Elisabeth Lof, Marjolein; de Vallavieille-Pope, Claude; van der Werf, Wopke

    2017-05-01

    Genetic resistance in crops is a cornerstone of disease management in agriculture. Such genetic resistance is often rapidly broken due to selection for virulence in the pathogen population. Here, we ask whether there are strategies that can prolong the useful life of plant resistance genes. In a modeling study, we compared four deployment strategies: gene pyramiding, sequential use, simultaneous use, and a mixed strategy. We developed a spatially explicit model for France and parameterized it for the fungal pathogen Puccinia striiformis f. sp. tritici (causing wheat yellow rust) to test management strategies in a realistic spatial setting. We found that pyramiding two new resistance genes in one variety was the most durable solution only when the virulent genotype had to emerge by mutation. Deploying single-gene-resistant varieties concurrently with the pyramided variety eroded the durability of the gene pyramid. We found that continuation of deployment of varieties with broken-down resistance prolonged the useful life of simultaneous deployment of four single-gene-resistant varieties versus sequential use. However, when virulence was already present in the pathogen population, durability was low and none of the deployment strategies had effect. These results provide guidance on effective strategies for using resistance genes in crop protection practice.

  19. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    PubMed

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  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.

    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.

  2. 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.

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

    PubMed Central

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

    2014-01-01

    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. 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.

  5. 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

    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

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

    PubMed Central

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

    2014-01-01

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

  7. Investigation of inflammation and tissue patterning in the gut using a Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT).

    PubMed

    Cockrell, Chase; Christley, Scott; An, Gary

    2014-03-01

    The mucosa of the intestinal tract represents a finely tuned system where tissue structure strongly influences, and is turn influenced by, its function as both an absorptive surface and a defensive barrier. Mucosal architecture and histology plays a key role in the diagnosis, characterization and pathophysiology of a host of gastrointestinal diseases. Inflammation is a significant factor in the pathogenesis in many gastrointestinal diseases, and is perhaps the most clinically significant control factor governing the maintenance of the mucosal architecture by morphogenic pathways. We propose that appropriate characterization of the role of inflammation as a controller of enteric mucosal tissue patterning requires understanding the underlying cellular and molecular dynamics that determine the epithelial crypt-villus architecture across a range of conditions from health to disease. Towards this end we have developed the Spatially Explicit General-purpose Model of Enteric Tissue (SEGMEnT) to dynamically represent existing knowledge of the behavior of enteric epithelial tissue as influenced by inflammation with the ability to generate a variety of pathophysiological processes within a common platform and from a common knowledge base. In addition to reproducing healthy ileal mucosal dynamics as well as a series of morphogen knock-out/inhibition experiments, SEGMEnT provides insight into a range of clinically relevant cellular-molecular mechanisms, such as a putative role for Phosphotase and tensin homolog/phosphoinositide 3-kinase (PTEN/PI3K) as a key point of crosstalk between inflammation and morphogenesis, the protective role of enterocyte sloughing in enteric ischemia-reperfusion and chronic low level inflammation as a driver for colonic metaplasia. These results suggest that SEGMEnT can serve as an integrating platform for the study of inflammation in gastrointestinal disease.

  8. Spatially explicit shallow landslide susceptibility mapping over large areas

    Treesearch

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

    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...

  9. Evaluating spatially explicit burn probabilities for strategic fire management planning

    Treesearch

    C. Miller; M.-A. Parisien; A. A. Ager; M. A. Finney

    2008-01-01

    Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have...

  10. 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

  11. 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.

  12. 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.

  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. Effects of landscape composition and configuration on migrating songbirds: inference from an individual-based model.

    PubMed

    Cohen, Emily B; Pearson, Scott M; Moore, Frank R

    2014-01-01

    The behavior of long-distance migrants during stopover is constrained by the need to quickly and safely replenish energetic reserves. Replenishing fuel stores at stopover sites requires adjusting to unfamiliar landscapes with little to no information about the distribution of resources. Despite their critical importance to the success of songbird migration, the effects of landscape composition and configuration on fuel deposition rates (FDR [g/d]), the currency of migration, has not been tested empirically. Our objectives were to understand the effects of heterogeneous landscapes on FDR of forest-dwelling songbirds during spring migration. The results of field experiments were used to parameterize a spatially explicit, individual-based model of forest songbird movement and resulting FDR. Further field experiments were used to validate the results from the individual-based model. In simulation experiments, we altered a Gulf South landscape in a factorial design to predict the effects of future patterns under different scenarios of land use change in which the abundance of high-quality hardwood habitat and the spatial aggregation of habitat varied. Simulated FDR decreased as the amount of hardwood in the landscape decreased from 41% to 22% to 12%. Further, migrants that arrived in higher-quality habitat types gained more mass. Counter to our expectations, FDR was higher with lower spatial aggregation of habitat. Differences in refueling rates may be most influenced by whether or not an individual experiences an initial searching cost after landing in poor-quality habitat. Therefore, quickly locating habitat with sufficient food resources at each stopover may be the most important factor determining a successful migration. Our findings provide empirical evidence for the argument that hardwood forest cover is a primary determinant of the quality of a stopover site in this region. This study represents the first effort to empirically quantify FDRs based on the

  15. Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model

    NASA Astrophysics Data System (ADS)

    Arakida, Hazuki; Miyoshi, Takemasa; Ise, Takeshi; Shima, Shin-ichiro; Kotsuki, Shunji

    2017-09-01

    We developed a data assimilation system based on a particle filter approach with the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM). We first performed an idealized observing system simulation experiment to evaluate the impact of assimilating the leaf area index (LAI) data every 4 days, simulating the satellite-based LAI. Although we assimilated only LAI as a whole, the tree and grass LAIs were estimated separately with high accuracy. Uncertain model parameters and other state variables were also estimated accurately. Therefore, we extended the experiment to the real world using the real Moderate Resolution Imaging Spectroradiometer (MODIS) LAI data and obtained promising results.

  16. 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.

  17. 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 ...

  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. 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...

  1. 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

  2. Modelling deep water habitats to develop a spatially explicit, fine scale understanding of the distribution of the western rock lobster, Panulirus cygnus.

    PubMed

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

    2012-01-01

    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. 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 km(2) 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 D(2) of 64 and an 80% correct classification. 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.

  3. Spatially explicit models of dynamic histories: examination of the genetic consequences of Pleistocene glaciation and recent climate change on the American Pika.

    PubMed

    Brown, Jason L; Knowles, L Lacey

    2012-08-01

    A central goal of phylogeography is to identify and characterize the processes underlying divergence. One of the biggest impediments currently faced is how to capture the spatiotemporal dynamic under which a species evolved. Here, we described an approach that couples species distribution models (SDMs), demographic and genetic models in a spatiotemporally explicit manner. Analyses of American Pika (Ochotona princeps) from the sky islands of the central Rocky Mountains of North America are used to provide insights into key questions about integrative approaches in landscape genetics, population genetics and phylogeography. This includes (i) general issues surrounding the conversion of time-specific SDMs into simple continuous, dynamic landscapes from past to current, (ii) the utility of SDMs to inform demographic models with deme-specific carrying capacities and migration potentials as well as (iii) the contribution of the temporal dynamic of colonization history in shaping genetic patterns of contemporary populations. Our results support that the inclusion of a spatiotemporal dynamic is an important factor when studying the impact of distributional shifts on patterns of genetic data. Our results also demonstrate the utility of SDMs to generate species-specific predictions about patterns of genetic variation that account for varying degrees of habitat specialization and life history characteristics of taxa. Nevertheless, the results highlight some key issues when converting SDMs for use in demographic models. Because the transformations have direct effects on the genetic consequence of population expansion by prescribing how habitat heterogeneity and spatiotemporal variation is related to the species-specific demographic model, it is important to consider alternative transformations when studying the genetic consequences of distributional shifts. © 2012 Blackwell Publishing Ltd.

  4. 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

  5. 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.

  6. A Spatially Explicit Metapopulation Model and Cattle Trade Analysis Suggests Key Determinants for the Recurrent Circulation of Rift Valley Fever Virus in a Pilot Area of Madagascar Highlands

    PubMed Central

    Nicolas, Gaëlle; Chevalier, Véronique; Tantely, Luciano Michaël; Fontenille, Didier; Durand, Benoît

    2014-01-01

    Rift Valley fever (RVF) is a vector-borne zoonotic disease that causes high morbidity and mortality in ruminants. In 2008–2009, a RVF outbreak affected the whole Madagascar island, including the Anjozorobe district located in Madagascar highlands. An entomological survey showed the absence of Aedes among the potential RVF virus (RVFV) vector species identified in this area, and an overall low abundance of mosquitoes due to unfavorable climatic conditions during winter. No serological nor virological sign of infection was observed in wild terrestrial mammals of the area, suggesting an absence of wild RVF virus (RVFV) reservoir. However, a three years serological and virological follow-up in cattle showed a recurrent RVFV circulation. The objective of this study was to understand the key determinants of this unexpected recurrent transmission. To achieve this goal, a spatial deterministic discrete-time metapopulation model combined with cattle trade network was designed and parameterized to reproduce the local conditions using observational data collected in the area. Three scenarios that could explain the RVFV recurrent circulation in the area were analyzed: (i) RVFV overwintering thanks to a direct transmission between cattle when viraemic cows calve, vectors being absent during the winter, (ii) a low level vector-based circulation during winter thanks to a residual vector population, without direct transmission between cattle, (iii) combination of both above mentioned mechanisms. Multi-model inference methods resulted in a model incorporating both a low level RVFV winter vector-borne transmission and a direct transmission between animals when viraemic cows calve. Predictions satisfactorily reproduced field observations, 84% of cattle infections being attributed to vector-borne transmission, and 16% to direct transmission. These results appeared robust according to the sensitivity analysis. Interweaving between agricultural works in rice fields, seasonality of

  7. A spatially explicit metapopulation model and cattle trade analysis suggests key determinants for the recurrent circulation of rift valley Fever virus in a pilot area of madagascar highlands.

    PubMed

    Nicolas, Gaëlle; Chevalier, Véronique; Tantely, Luciano Michaël; Fontenille, Didier; Durand, Benoît

    2014-12-01

    Rift Valley fever (RVF) is a vector-borne zoonotic disease that causes high morbidity and mortality in ruminants. In 2008-2009, a RVF outbreak affected the whole Madagascar island, including the Anjozorobe district located in Madagascar highlands. An entomological survey showed the absence of Aedes among the potential RVF virus (RVFV) vector species identified in this area, and an overall low abundance of mosquitoes due to unfavorable climatic conditions during winter. No serological nor virological sign of infection was observed in wild terrestrial mammals of the area, suggesting an absence of wild RVF virus (RVFV) reservoir. However, a three years serological and virological follow-up in cattle showed a recurrent RVFV circulation. The objective of this study was to understand the key determinants of this unexpected recurrent transmission. To achieve this goal, a spatial deterministic discrete-time metapopulation model combined with cattle trade network was designed and parameterized to reproduce the local conditions using observational data collected in the area. Three scenarios that could explain the RVFV recurrent circulation in the area were analyzed: (i) RVFV overwintering thanks to a direct transmission between cattle when viraemic cows calve, vectors being absent during the winter, (ii) a low level vector-based circulation during winter thanks to a residual vector population, without direct transmission between cattle, (iii) combination of both above mentioned mechanisms. Multi-model inference methods resulted in a model incorporating both a low level RVFV winter vector-borne transmission and a direct transmission between animals when viraemic cows calve. Predictions satisfactorily reproduced field observations, 84% of cattle infections being attributed to vector-borne transmission, and 16% to direct transmission. These results appeared robust according to the sensitivity analysis. Interweaving between agricultural works in rice fields, seasonality of

  8. 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.

  9. A spatially explicit framework for quantifying downstream hydrologic conditions.

    PubMed

    Strager, Michael P; Petty, J Todd; Strager, Jacquelyn M; Barker-Fulton, Jennifer

    2009-04-01

    Continued improvements in spatial datasets and hydrological modeling algorithms within Geographic Information Systems (GISs) have enhanced opportunities for watershed analysis. With more detailed hydrology layers and watershed delineation techniques, we can now better represent and model landscape to water quality relationships. Two challenges in modeling these relationships are selecting the appropriate spatial scale of watersheds for the receiving stream segment, and handling the network or pass-through issues of connected watersheds. This paper addresses these two important issues for enhancing cumulative watershed capabilities in GIS. Our modeling framework focuses on the delineation of stream-segment-level watershed boundaries for 1:24,000 scale hydrology, in combination with a topological network model. The result is a spatially explicit, vector-based, spatially cumulative watershed modeling framework for quantifying watershed conditions to aid in restoration. We demonstrate the new insights available from this modeling framework in a cumulative mining index for the management of aquatic resources in a West Virginia watershed.

  10. Individual-based model for dieldrin contamination in lake trout

    USGS Publications Warehouse

    Madenjian, Charles P.; Carpenter, Stephen R.; Noguchi, George E.

    1993-01-01

    An individual-based model (IBM) was applied to dieldrin contamination in the lake trout (Salvelinus namaycush) population of Lake Michigan in order to determine if a model structure originally developed for contamination by polychlorinated biphenyls (PCBs) in Lake Michigan lake trout would also apply to dieldrin contamination. Many different congeners constitute PCBs, whereas dieldrin is a single chemical compound. The model accurately accounted for the variation in dieldrin concentrations exhibited within the Lake Michigan lake trout population. The degree of variability included in dieldrin concentrations of the prey fish was similar to that used for modeling total PCBs. These results supported the argument that any heterogeneity in PCB congener distribution in Lake Michigan contributed relatively little to the observed variability in lake trout total PCB concentrations. Furthermore, these results indicate that the IBM has potential to be applicable to a variety of organochlorine contaminants. The IBM should prove useful for risk assessment of contaminants in fish.

  11. Fisher waves: An individual-based stochastic model

    NASA Astrophysics Data System (ADS)

    Houchmandzadeh, B.; Vallade, M.

    2017-07-01

    The propagation of a beneficial mutation in a spatially extended population is usually studied using the phenomenological stochastic Fisher-Kolmogorov-Petrovsky-Piscounov (SFKPP) equation. We derive here an individual-based, stochastic model founded on the spatial Moran process where fluctuations are treated exactly. The mean-field approximation of this model leads to an equation that is different from the phenomenological FKPP equation. At small selection pressure, the front behavior can be mapped into a Brownian motion with drift, the properties of which can be derived from the microscopic parameters of the Moran model. Finally, we generalize the model to take into account dispersal kernels beyond migration to nearest neighbors. We show how the effective population size (which controls the noise amplitude) and the diffusion coefficient can both be computed from the dispersal kernel.

  12. 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.

  13. 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

  14. 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.

  15. Continuum approximations of individual-based models for epithelial monolayers.

    PubMed

    Fozard, J A; Byrne, H M; Jensen, O E; King, J R

    2010-03-01

    This work examines a 1D individual-based model (IBM) for a system of tightly adherent cells, such as an epithelial monolayer. Each cell occupies a bounded region, defined by the location of its endpoints, has both elastic and viscous mechanical properties and is subject to drag generated by adhesion to the substrate. Differential-algebraic equations governing the evolution of the system are obtained from energy considerations. This IBM is then approximated by continuum models (systems of partial differential equations) in the limit of a large number of cells, N, when the cell parameters vary slowly in space or are spatially periodic (and so may be heterogeneous, with substantial variation between adjacent cells). For spatially periodic cell properties with significant cell viscosity, the relationship between the mean cell pressure and length for the continuum model is found to be history dependent. Terms involving convective derivatives, not normally included in continuum tissue models, are identified. The specific problem of the expansion of an aggregate of cells through cell growth (but without division) is considered in detail, including the long-time and slow-growth-rate limits. When the parameters of neighbouring cells vary slowly in space, the O(1/N(2)) error in the continuum approximation enables this approach to be used even for modest values of N. In the spatially periodic case, the neglected terms are found to be O(1/N). The model is also used to examine the acceleration of a wound edge observed in wound-healing assays.

  16. A mechanistic Individual-based Model of microbial communities

    PubMed Central

    Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A. Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

    2017-01-01

    Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup. PMID:28771505

  17. A mechanistic Individual-based Model of microbial communities.

    PubMed

    Jayathilake, Pahala Gedara; Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

    2017-01-01

    Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

  18. 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.

  19. 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

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

    PubMed

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

    2010-11-01

    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.

  1. 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.

  2. 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

  3. 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

  4. Benefits of dispersed central-place foraging: an individual-based model of a polydomous ant colony.

    PubMed

    Schmolke, Amelie

    2009-06-01

    Colonies of many ant species are not confined to a single nest but inhabit several dispersed nests, a colony organization referred to as polydomy. The benefits of polydomy are not well understood. It has been proposed that increased foraging efficiency promotes polydomy. In a spatially explicit individual-based model, I compare the foraging success of monodomous and polydomous colonies in environments with varying food distributions. Multiple nests increased the colony's foraging success if food sources were randomly scattered in the environment. Monodomous and polydomous colonies did not differ in foraging success if food sources were clustered in one or three locations. These results support the hypothesis that foraging success serves as a driver for polydomous colony organization. Because transport may occur between the dispersed nests of a polydomous colony, I tested the efficiency of a simple mechanism of food exchange between nests. This mechanism, as introduced previously in the literature, proves insufficient to equalize the level of food between nests. While the importance of transport between nests remains unclear, the model results indicate that polydomy may increase the foraging success of ant colonies and that this effect may be robust across a range of food distributions.

  5. Spatially explicit assessment of estuarine fish after Deepwater ...

    EPA Pesticide Factsheets

    Evaluating long- term contaminant effects on wildlife populations depends on spatial information about habitat quality, heterogeneity in contaminant exposure, and sensitivities and distributions of species integrated into a systems modeling approach. Rarely is this information readily available, making it difficult to determine the applicability of realistic models to quantify population- level risks. To evaluate the trade- offs between data demands and increased specificity of spatially explicit models for population- level risk assessments, we developed a model for a standard toxicity test species, the sheepshead minnow (Cyprinodon variegatus), exposed to oil contamination following the Deepwater Horizon oil spill and compared the output with various levels of model complexity to a standard risk quotient approach. The model uses habitat and fish occupancy data collected over five sampling periods throughout 2008–2010 in Pensacola and Choctawhatchee Bays, Florida, USA, to predict species distribution, field- collected and publically available data on oil distribution and concentration, and chronic toxicity data from laboratory assays applied to a matrix population model. The habitat suitability model established distribution of fish within Barataria Bay, Louisiana, USA, and the population model projected the dynamics of the species in the study area over a 5- yr period (October 2009–September 2014). Vital rates were modified according to estimated co

  6. 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

  7. 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.

    2016-05-20

    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

  8. 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

  9. Spatially explicit and stochastic simulation of forest landscape fire disturbance and succession

    Treesearch

    Hong S. He; David J. Mladenoff

    1999-01-01

    Understanding disturbance and recovery of forest landscapes is a challenge because of complex interactions over a range of temporal and spatial scales. Landscape simulation models offer an approach to studying such systems at broad scales. Fire can be simulated spatially using mechanistic or stochastic approaches. We describe the fire module in a spatially explicit,...

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

    PubMed

    Efford, M G; Mowat, G

    2014-05-01

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

  11. Evaluating impacts of fire management strategies on native and invasive plants using an individual-based model

    NASA Astrophysics Data System (ADS)

    Gangur, Alexander N.; Fill, Jennifer M.; Northfield, Tobin D.; van de Wiel, Marco

    2017-04-01

    The capacity for species to coexist and potentially exclude one another can broadly be attributed to drivers that influence fitness differences (such as competitive ability) and niche differences (such as environmental change). These drivers, and thus the determinants of coexistence they influence, can interact and fluctuate both spatially and temporally. Understanding the spatiotemporal variation in niche and fitness differences in systems prone to fluctuating drivers, such as fire, can help to inform the management of invasive species. In the Cape floristic region of South Africa, invasive Pinus pinaster seedlings are strong competitors in the post-burn environment of the fire-driven Fynbos vegetation. In this, system native Protea spp. are especially vulnerable to unseasonal burns, but seasonal prescribed (Summer) burns are thought to present a high safety risk. Together, these issues have limited the appeal of prescribed burn management as an alternative to costly manual eradication of P. pinaster. Using a spatially-explicit field-of-neighbourhood individual-based model, we represent the drivers of spatiotemporal variation in niche differences (driven by fire regimes) and fitness differences (driven by competitive ability). In doing so, we evaluate optimal fire management strategies to a) control invasive P. pinaster in the Cape floristic region of South Africa, while b) minimizing deleterious effects of management on native Protea spp. The scarcity of appropriate data for model calibration has been problematic for models in invasion biology, but we use recent advances in Approximate Bayesian Computing techniques to overcome this limitation. We present early conclusions on the viability of prescribed burn management to control P. pinaster in South Africa.

  12. 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

  13. Examining the role of individual movement in promoting coexistence in a spatially explicit prisoner's dilemma.

    PubMed

    Burgess, Andrew E F; Lorenzi, Tommaso; Schofield, Pietà G; Hubbard, Stephen F; Chaplain, Mark A J

    2017-02-27

    The emergence of cooperation is a major conundrum of evolutionary biology. To unravel this evolutionary riddle, several models have been developed within the theoretical framework of spatial game theory, focussing on the interactions between two general classes of player, "cooperators" and "defectors". Generally, explicit movement in the spatial domain is not considered in these models, with strategies moving via imitation or through colonisation of neighbouring sites. We present here a spatially explicit stochastic individual-based model in which pure cooperators and defectors undergo random motion via diffusion and also chemotaxis guided by the gradient of a semiochemical. Individual movement rules are derived from an underlying system of reaction-diffusion-taxis partial differential equations which describes the dynamics of the local number of individuals and the concentration of the semiochemical. Local interactions are governed by the payoff matrix of the classical prisoner's dilemma, and accumulated payoffs are translated into offspring. We investigate the cases of both synchronous and non-synchronous generations. Focussing on an ecological scenario where defectors are parasitic on cooperators, we find that random motion and semiochemical sensing bring about self-generated patterns in which resident cooperators and parasitic defectors can coexist in proportions that fluctuate about non-zero values. Remarkably, coexistence emerges as a genuine consequence of the natural tendency of cooperators to aggregate into clusters, without the need for them to find physical shelter or outrun the parasitic defectors. This provides further evidence that spatial clustering enhances the benefits of mutual cooperation and plays a crucial role in preserving cooperative behaviours.

  14. Spatially Explicit Assessment of Agricultural Water Equilibrium in Korea Peninsula

    NASA Astrophysics Data System (ADS)

    Lee, S. J.; Lim, C. H.; Lee, W. K.

    2016-12-01

    In agriculture, balance between water retention and water use is an issue handled in most region and crops. This study suggested agricultural water equilibrium (AWE) it a new assessing concept for management of agricultural water in spatially explicit. This concept based on the principle of supply and demand, to the usage of agricultural water, it is possible to define virtual water content of crops (VWC) as the demand, and cropland water budget (CWB) as the supply. For the assessing AWE of the Korean Peninsula, quantified by estimating the CWB based on the natural hydrological cycle and the VWC of rice, a key crop in the Korean Peninsula. Among five factors used to assess AWE, four factors except annual precipitation were estimated by using the GEPIC model, and calculated CWB and VWC at past three decade. AWE results over the past 30 years were computed by deducting VWC showing demands in croplands from CWB meaning water supply that result showed highly vertical difference of South and North Korea. When sorting AWE data by major river basin in the Korean Peninsula, most river basins in North Korea also showed very low level. The cause of making latitudinal change in AWE is the differences of VWC and CWB in terms of latitudinal change. Which can be explained by decoupling of agricultural water demand and supply. Identifying relation with AWE, VWC and CWB in concept of elasticity, elasticity of AWE following VWC was appeared as very low relatively and absolutely. And the elasticity of AWE following CWB is very good relatively and good absolutely. When VWC is inelastic, the relative elasticity of CWB tended to become very high. AWE values presented in the study were not absolute, though these values appeared enough in explaining the latitudinal change, demand and supply of agricultural water, and have been meaningful in establishing the concept of AWE.

  15. 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.

  16. Individual-Based Models, and Scaling from Individuals to Landscapes

    NASA Technical Reports Server (NTRS)

    Levin, Simon A.; Pacala, Stephen W.

    1998-01-01

    The project had the principal goals of simplifying forest growth and grassland models, and of developing scaling rules for models of forest growth and animal grouping. It was a great success, and the three years of funding under the two grants produced 20 publications. In the areas of forest and grassland models, a variety of techniques were developed that led to simplification and scaling laws. In particular, Deutschman's (1996) thesis led to dramatic simplification of light regimes and spatial resolution; complementary work with Bolker and Pacala (1998), developed moment methods for simplifying forest and other models; and Molofsky et al. (1998) considered simplified models of competition as ways of exploring complex local rules of interaction. Overton (Overton and Levin 1998) provided background analyses for grasslands, as a template for developing similar model simplifications. Kinzig et al. (1998) put competition into a coherent framework, deriving remarkable scaling laws; these are now being generalized. A manuscript with George Hurtt (Hurtt et aL 1998) relating climate and vegetation models was completed, accepted and published. Finally, Levin (1998) summarized many of these findings, characterizing ecosystems and the biosphere as complex adaptive systems. In the area of animal grouping, a major paper (Flierl et aL 1998) established the linkages between Lagrangian and Eulerian formulations, providing a powerful methodology for model simplification. This has been completed, submitted and accepted.

  17. Individual-Based Models, and Scaling from Individuals to Landscapes

    NASA Technical Reports Server (NTRS)

    Levin, Simon A.; Pacala, Stephen W.

    1998-01-01

    The project had the principal goals of simplifying forest growth and grassland models, and of developing scaling rules for models of forest growth and animal grouping. It was a great success, and the three years of funding under the two grants produced 20 publications. In the areas of forest and grassland models, a variety of techniques were developed that led to simplification and scaling laws. In particular, Deutschman's (1996) thesis led to dramatic simplification of light regimes and spatial resolution; complementary work with Bolker and Pacala (1998), developed moment methods for simplifying forest and other models; and Molofsky et al. (1998) considered simplified models of competition as ways of exploring complex local rules of interaction. Overton (Overton and Levin 1998) provided background analyses for grasslands, as a template for developing similar model simplifications. Kinzig et al. (1998) put competition into a coherent framework, deriving remarkable scaling laws; these are now being generalized. A manuscript with George Hurtt (Hurtt et aL 1998) relating climate and vegetation models was completed, accepted and published. Finally, Levin (1998) summarized many of these findings, characterizing ecosystems and the biosphere as complex adaptive systems. In the area of animal grouping, a major paper (Flierl et aL 1998) established the linkages between Lagrangian and Eulerian formulations, providing a powerful methodology for model simplification. This has been completed, submitted and accepted.

  18. Spatially explicit animal response to composition of habitat

    Treesearch

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

    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-...

  19. Individual-based model for radiation risk assessment

    NASA Astrophysics Data System (ADS)

    Smirnova, O.

    A mathematical model is developed which enables one to predict the life span probability for mammals exposed to radiation. It relates statistical biometric functions with statistical and dynamic characteristics of an organism's critical system. To calculate the dynamics of the latter, the respective mathematical model is used too. This approach is applied to describe the effects of low level chronic irradiation on mice when the hematopoietic system (namely, thrombocytopoiesis) is the critical one. For identification of the joint model, experimental data on hematopoiesis in nonirradiated and irradiated mice, as well as on mortality dynamics of those in the absence of radiation are utilized. The life span probability and life span shortening predicted by the model agree with corresponding experimental data. Modeling results show the significance of ac- counting the variability of the individual radiosensitivity of critical system cells when estimating the radiation risk. These findings are corroborated by clinical data on persons involved in the elimination of the Chernobyl catastrophe after- effects. All this makes it feasible to use the model for radiation risk assessments for cosmonauts and astronauts on long-term missions such as a voyage to Mars or a lunar colony. In this case the model coefficients have to be determined by making use of the available data for humans. Scenarios for the dynamics of dose accumulation during space flights should also be taken into account.

  20. 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

  1. 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

  2. Simulation of oak early life history and interactions with disturbance via an individual-based model, SOEL.

    PubMed

    Kellner, Kenneth F; Swihart, Robert K

    2017-01-01

    Early tree life history and demography are driven by interactions with the environment such as seed predation, herbivory, light availability, and drought. For oak (Quercus) in the eastern United States, these interactions may contribute to oak regeneration failure. Numerous studies have examined the impact of individual factors (like seed predation) on the oak regeneration process, but less information is available on the relative and combined impacts of multiple intrinsic and extrinsic factors on early oak life history. We developed an individual-based, spatially explicit model to Simulate Oak Early Life history (SOEL). The model connects acorn survival, acorn dispersal, germination, seedling growth, and seedling survival submodels based on empirical data with an existing gap model (JABOWA). Using SOEL, we assessed the sensitivity of several metrics of oak regeneration to different parameters associated with early oak life history. We also applied the model in three individual case studies to assess: (1) how variable acorn production interacts with timing of timber harvest; (2) the effect of shelterwood harvest-induced differences on seed predation; and (3) the consequences of interactions between drought, seedling growth and survival, and timber harvest. We found that oak regeneration metrics including percent emergence, seedling density, and sapling density were most sensitive to the amount of acorn production, acorn caching probability by scatterhoarders, and seedling growth rates. In the case studies, we found that timing harvest to follow large acorn crops can increase the density of oak regeneration in the short term following harvest, at least under some conditions. Following midstory removal, lower weevil infestation probability and lower post-dispersal acorn survival resulted in a modest decline in seedling density, but the decline did not persist to the sapling life stage class. Drought frequency had a powerful negative impact on both growth and survival

  3. Simulation of oak early life history and interactions with disturbance via an individual-based model, SOEL

    PubMed Central

    Swihart, Robert K.

    2017-01-01

    Early tree life history and demography are driven by interactions with the environment such as seed predation, herbivory, light availability, and drought. For oak (Quercus) in the eastern United States, these interactions may contribute to oak regeneration failure. Numerous studies have examined the impact of individual factors (like seed predation) on the oak regeneration process, but less information is available on the relative and combined impacts of multiple intrinsic and extrinsic factors on early oak life history. We developed an individual-based, spatially explicit model to Simulate Oak Early Life history (SOEL). The model connects acorn survival, acorn dispersal, germination, seedling growth, and seedling survival submodels based on empirical data with an existing gap model (JABOWA). Using SOEL, we assessed the sensitivity of several metrics of oak regeneration to different parameters associated with early oak life history. We also applied the model in three individual case studies to assess: (1) how variable acorn production interacts with timing of timber harvest; (2) the effect of shelterwood harvest-induced differences on seed predation; and (3) the consequences of interactions between drought, seedling growth and survival, and timber harvest. We found that oak regeneration metrics including percent emergence, seedling density, and sapling density were most sensitive to the amount of acorn production, acorn caching probability by scatterhoarders, and seedling growth rates. In the case studies, we found that timing harvest to follow large acorn crops can increase the density of oak regeneration in the short term following harvest, at least under some conditions. Following midstory removal, lower weevil infestation probability and lower post-dispersal acorn survival resulted in a modest decline in seedling density, but the decline did not persist to the sapling life stage class. Drought frequency had a powerful negative impact on both growth and survival

  4. A Random Walk in the Park: An Individual-Based Null Model for Behavioral Thermoregulation.

    PubMed

    Vickers, Mathew; Schwarzkopf, Lin

    2016-04-01

    Behavioral thermoregulators leverage environmental temperature to control their body temperature. Habitat thermal quality therefore dictates the difficulty and necessity of precise thermoregulation, and the quality of behavioral thermoregulation in turn impacts organism fitness via the thermal dependence of performance. Comparing the body temperature of a thermoregulator with a null (non-thermoregulating) model allows us to estimate habitat thermal quality and the effect of behavioral thermoregulation on body temperature. We define a null model for behavioral thermoregulation that is a random walk in a temporally and spatially explicit thermal landscape. Predicted body temperature is also integrated through time, so recent body temperature history, environmental temperature, and movement influence current body temperature; there is no particular reliance on an organism's equilibrium temperature. We develop a metric called thermal benefit that equates body temperature to thermally dependent performance as a proxy for fitness. We measure thermal quality of two distinct tropical habitats as a temporally dynamic distribution that is an ergodic property of many random walks, and we compare it with the thermal benefit of real lizards in both habitats. Our simple model focuses on transient body temperature; as such, using it we observe such subtleties as shifts in the thermoregulatory effort and investment of lizards throughout the day, from thermoregulators to thermoconformers.

  5. 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.

  6. Individual-based model formulation for cutthroat trout, Little Jones Creek, California

    Treesearch

    Steven F. Railsback; Bret C. Harvey

    2001-01-01

    This report contains the detailed formulation of an individual-based model (IBM) of cutthroat trout developed for three study sites on Little Jones Creek, Del Norte County, in northwestern California. The model was designed to support research on relations between habitat and fish population dynamics, the importance of small tributaries to trout populations, and the...

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

    PubMed Central

    2011-01-01

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

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

    PubMed

    Hongoh, Valerie; Hoen, Anne Gatewood; Aenishaenslin, Cécile; Waaub, Jean-Philippe; Bélanger, Denise; Michel, Pascal

    2011-12-29

    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.

  9. Improving carbon monitoring and reporting in forests using spatially-explicit information.

    PubMed

    Boisvenue, Céline; Smiley, Byron P; White, Joanne C; Kurz, Werner A; Wulder, Michael A

    2016-12-01

    Understanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere-specifically the process of C removal from the atmosphere, and how this process is changing-is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada. Our results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year(-1)) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha(-1). Comparisons between our estimates and estimates from Canada's National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates. Both estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences

  10. 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

  11. Contrast of degraded and restored stream habitat using an individual-based salmon model

    Treesearch

    S. F. Railsback; M. Gard; Bret Harvey; Jason White; J.K.H. Zimmerman

    2013-01-01

    Stream habitat restoration projects are popular, but can be expensive and difficult to evaluate. We describe inSALMO, an individual-based model designed to predict habitat effects on freshwater life stages (spawning through juvenile out-migration) of salmon. We applied inSALMO to Clear Creek, California, simulating the production of total and large (>5 cm FL)...

  12. Population-level analysis and validation of an individual-based cutthroat trout model

    Treesearch

    Steven F. Railsback; Bret C. Harvey; Roland H. Lamberson; Derek E. Lee; Claasen Nathan J.; Shuzo Yoshihara

    2002-01-01

    Abstract - An individual-based model of stream trout is analyzed by testing its ability to reproduce patterns of population-level behavior observed in real trout: (1) "self-thinning," a negative power relation between weight and abundance; (2) a "critical period" of density-dependent mortality in young-of-the-year; (3) high and age-speci...

  13. Analysis of habitat-selection rules using an individual-based model

    Treesearch

    Steven F. Railsback; Bret C. Harvey

    2002-01-01

    Abstract - Despite their promise for simulating natural complexity,individual-based models (IBMs) are rarely used for ecological research or resource management. Few IBMs have been shown to reproduce realistic patterns of behavior by individual organisms.To test our IBM of stream salmonids and draw conclusions about foraging theory,we analyzed the IBM ’s ability to...

  14. Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises

    USGS Publications Warehouse

    Heaton, Jill S.; Nussear, Kenneth E.; Esque, Todd C.; Inman, Richard D.; Davenport, Frank; Leuteritz, Thomas E.; Medica, Philip A.; Strout, Nathan W.; Burgess, Paul A.; Benvenuti, Lisa

    2008-01-01

    Spatially explicit decision support systems are assuming an increasing role in natural resource and conservation management. In order for these systems to be successful, however, they must address real-world management problems with input from both the scientific and management communities. The National Training Center at Fort Irwin, California, has expanded its training area, encroaching U.S. Fish and Wildlife Service critical habitat set aside for the Mojave desert tortoise (Gopherus agassizii), a federally threatened species. Of all the mitigation measures proposed to offset expansion, the most challenging to implement was the selection of areas most feasible for tortoise translocation. We developed an objective, open, scientifically defensible spatially explicit decision support system to evaluate translocation potential within the Western Mojave Recovery Unit for tortoise populations under imminent threat from military expansion. Using up to a total of 10 biological, anthropogenic, and/or logistical criteria, seven alternative translocation scenarios were developed. The final translocation model was a consensus model between the seven scenarios. Within the final model, six potential translocation areas were identified.

  15. 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.

  16. 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

    2016-02-02

    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.

  17. 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.

  18. Estimation of population density by spatially explicit capture-recapture analysis of data from area searches.

    PubMed

    Efford, Murray G

    2011-12-01

    The recent development of capture-recapture methods for estimating animal population density has focused on passive detection using devices such as traps or automatic cameras. Some species lend themselves more to active searching: a polygonal plot may be searched repeatedly and the locations of detected individuals recorded, or a plot may be searched just once and multiple cues (feces or other sign) identified as belonging to particular individuals. This report presents new likelihood-based spatially explicit capture-recapture (SECR) methods for such data. The methods are shown to be at least as robust in simulations as an equivalent Bayesian analysis, and to have negligible bias and near-nominal confidence interval coverage with parameter values from a lizard data set. It is recommended on the basis of simulation that plots for SECR should be at least as large as the home range of the target species. The R package "secr" may be used to fit the models. The likelihood-based implementation extends the spatially explicit analyses available for search data to include binary data (animal detected or not detected on each occasion) or count data (multiple detections per occasion) from multiple irregular polygons, with or without dependence among polygons. It is also shown how the method may be adapted for detections along a linear transect.

  19. 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

  20. An analysis of wetland productivity and biomass in Coastal Louisiana: Current base line data and knowledge gaps for the development of spatially explicit models for restoration and rehabilitation programs

    NASA Astrophysics Data System (ADS)

    Rivera-Monroy, V. H.; Elliton, C.; Visser, J.; Narra, S.; Simard, M.; Snedden, G.; Stagg, C. L.; Wang, H.; Castañeda-Moya, E.

    2016-02-01

    Wetland above and below net primary productivity (NPP) and biomass (BM) are two critical ecosystem properties to evaluate vegetation successional trajectories in restoration and rehabilitation (R/R) programs. Enhancing sediment deposition and changes in salinity regimes are major environmental drivers that significantly determine vegetation establishment and species composition. In costal Louisiana, wetland restoration and rehabilitation (R/R)programs aim to slow down wetland loss and improve vegetation coverage by diverting freshwater and sediments from the Mississippi River into areas where wetlands loss rates are high. Although vegetation establishment and coverage are considered key performance measures (PMs) to evaluate R/R success, few studies have explicitly established NPP and BM targets due to the lack of long-term studies to analyze spatiotemporal patterns. To contribute to the development of vegetation PMs in restoration projects, we evaluated BM and NPP data and assessed statistical measures of central tendency and dispersion, field methodology, and number of studies per wetland class and species across coastal Louisiana from 1974-2014. Mean NPP ranged from 400 (±250) to 8500 (±500) gdw/m2/yr and showed significant differences among wetland types independently of salinity regime. Peak BM at the end of the growing season was distinct among wetlands communities dominated by grasses, particularly between freshwater (1200 g/m2 ± 300) and brackish/saline marshes (700 g/m2 ±250). Productivity studies have been focused on few species including Panicum virgatum, Scirpus americanus, Spartina patens, Juncus roemerianus, Distichlis spicata, Spartina alterniflora, Sagittaria falcate, Taxodium distichum, Nyssa aquatic, Acer rubrum. The BM/NPP analysis and database compilation will be used to inform the development and integration of functional performance measures in ecological models (statistical, dynamic and cellular automata) to forecast wetland R/R scenarios

  1. 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

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

    USDA-ARS?s Scientific Manuscript database

    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...

  3. 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

  4. 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.

  5. 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.

  6. 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.

  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. Controlling chaos in ecology: from deterministic to individual-based models.

    PubMed

    Solé, R V; Gamarra, J G; Ginovart, M; López, D

    1999-11-01

    The possibility of chaos control in biological systems has been stimulated by recent advances in the study of heart and brain tissue dynamics. More recently, some authors have conjectured that such a method might be applied to population dynamics and even play a nontrivial evolutionary role in ecology. In this paper we explore this idea by means of both mathematical and individual-based simulation models. Because of the intrinsic noise linked to individual behavior, controlling a noisy system becomes more difficult but, as shown here, it is a feasible task allowed to be experimentally tested.

  9. 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.

  10. Simulating winter flounder population dynamics using coupled individual-based YOY and Leslie matrix models

    SciTech Connect

    Tyler, J.A.; Rose, K.A. ); Chambers, R.C. )

    1994-06-01

    Winter flounder populations support an important commercial fishery in eastern North America that has recently experienced declines in catch. We developed a model for winter flounder that combines an individual-based (IBM) simulation of the young-of-the-year (yoy) period and a Leslie matrix model of the adult period. The model is designed to depicit the biotic and abiotic environment of bays off the northeastern United States coast. Using the model we replicated the spawn and recruit relationship of winter flounder determined from 12 years of study in the Niantic River. The simulations show the importance of inter-annual variation in temperature and the spawning population as well as density-dependent growth and mortality in determining yoy recruitment. With 100 year simulations we determined the effect of variation in the environment on the recruitment of yoy winder flounder and on long term population stability.

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

    PubMed

    Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

    2016-02-07

    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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. 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.

  14. Modeling of Mycobacterium avium subsp. paratuberculosis dynamics in a dairy herd: An individual based approach.

    PubMed

    Al-Mamun, Mohammad A; Smith, Rebecca L; Schukken, Ynte H; Gröhn, Yrjö T

    2016-11-07

    In the dairy industry, Johne's disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP) is one of the major investigated diseases. To date, researchers have suggested some control strategies for JD, such as test-and-cull based herd management, isolated calf rearing management, and vaccinations. Due to the slow progressing nature of MAP, tests with low diagnostic test sensitivity and specificity, and economic limitations, implementing these strategies has not resulted in elimination of MAP from farms. To date, no study has integrated detailed dairy herd dynamics with different MAP transmission routes. We have developed an individual-based dairy herd model by incorporating basic herd dynamics in a closed herd environment where no new animals have been bought from outside. The model considered three age groups of animals: calves, heifers and adults. It includes sequential life events of a dairy animal and such key dynamic processes of the dairy herd as lactation cycle, calving, voluntary waiting period, insemination, pregnancy, dry-off period and calf and heifer rearing. After initially validating that the model reproduced typical herd dynamics, it was extended by incorporating MAP infection dynamics, where each individual adult animal belonged to one of four infection compartments: susceptible, latent, low shedding and high shedding. The model includes two disease transmission routes: horizontal transmission (i.e., fecal-oral) and vertical transmission (i.e., in utero infection). The results confirm that this model can simulate a realistic dairy herd and that inclusion of the above-mentioned dynamic processes provides useful information about individual infected animals to farmers. Access to the individual animal information offers more validity to assessment of appropriate control strategies for an endemically MAP infected herd. This model can serve as an accurate and novel tool not only to better understand MAP dynamics, but is also valuable as an

  15. 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 ...

  16. 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 ...

  17. Sensitivity analysis of an individual-based model for simulation of influenza epidemics.

    PubMed

    Nsoesie, Elaine O; Beckman, Richard J; Marathe, Madhav V

    2012-01-01

    Individual-based epidemiology models are increasingly used in the study of influenza epidemics. Several studies on influenza dynamics and evaluation of intervention measures have used the same incubation and infectious period distribution parameters based on the natural history of influenza. A sensitivity analysis evaluating the influence of slight changes to these parameters (in addition to the transmissibility) would be useful for future studies and real-time modeling during an influenza pandemic.In this study, we examined individual and joint effects of parameters and ranked parameters based on their influence on the dynamics of simulated epidemics. We also compared the sensitivity of the model across synthetic social networks for Montgomery County in Virginia and New York City (and surrounding metropolitan regions) with demographic and rural-urban differences. In addition, we studied the effects of changing the mean infectious period on age-specific epidemics. The research was performed from a public health standpoint using three relevant measures: time to peak, peak infected proportion and total attack rate. We also used statistical methods in the design and analysis of the experiments. The results showed that: (i) minute changes in the transmissibility and mean infectious period significantly influenced the attack rate; (ii) the mean of the incubation period distribution appeared to be sufficient for determining its effects on the dynamics of epidemics; (iii) the infectious period distribution had the strongest influence on the structure of the epidemic curves; (iv) the sensitivity of the individual-based model was consistent across social networks investigated in this study and (v) age-specific epidemics were sensitive to changes in the mean infectious period irrespective of the susceptibility of the other age groups. These findings suggest that small changes in some of the disease model parameters can significantly influence the uncertainty observed in real

  18. Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution.

    PubMed

    Rikvold, Per Arne

    2007-11-01

    We compare and contrast the long-time dynamical properties of two individual-based models of biological coevolution. Selection occurs via multispecies, stochastic population dynamics with reproduction probabilities that depend nonlinearly on the population densities of all species resident in the community. New species are introduced through mutation. Both models are amenable to exact linear stability analysis, and we compare the analytic results with large-scale kinetic Monte Carlo simulations, obtaining the population size as a function of an average interspecies interaction strength. Over time, the models self-optimize through mutation and selection to approximately maximize a community potential function, subject only to constraints internal to the particular model. If the interspecies interactions are randomly distributed on an interval including positive values, the system evolves toward self-sustaining, mutualistic communities. In contrast, for the predator-prey case the matrix of interactions is antisymmetric, and a nonzero population size must be sustained by an external resource. Time series of the diversity and population size for both models show approximate 1/f noise and power-law distributions for the lifetimes of communities and species. For the mutualistic model, these two lifetime distributions have the same exponent, while their exponents are different for the predator-prey model. The difference is probably due to greater resilience toward mass extinctions in the food-web like communities produced by the predator-prey model.

  19. 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.

  20. Explaining Bacterial Dispersion on Leaf Surfaces with an Individual-Based Model (PHYLLOSIM)

    PubMed Central

    van der Wal, Annemieke; Tecon, Robin; Kreft, Jan-Ulrich; Mooij, Wolf M.; Leveau, Johan H. J.

    2013-01-01

    We developed the individual-based model PHYLLOSIM to explain observed variation in the size of bacterial clusters on plant leaf surfaces (the phyllosphere). Specifically, we tested how different ‘waterscapes’ impacted the diffusion of nutrients from the leaf interior to the surface and the growth of individual bacteria on these nutrients. In the ‘null’ model or more complex ‘patchy’ models, the surface was covered with a continuous water film or with water drops of equal or different volumes, respectively. While these models predicted the growth of individual bacterial immigrants into clusters of variable sizes, they were unable to reproduce experimentally derived, previously published patterns of dispersion which were characterized by a much larger variation in cluster sizes and a disproportionate occurrence of clusters consisting of only one or two bacteria. The fit of model predictions to experimental data was about equally poor (<5%) regardless of whether the water films were continuous or patchy. Only by allowing individual bacteria to detach from developing clusters and re-attach elsewhere to start a new cluster, did PHYLLOSIM come much closer to reproducing experimental observations. The goodness of fit including detachment increased to about 70–80% for all waterscapes. Predictions of this ‘detachment’ model were further supported by the visualization and quantification of bacterial detachment and attachment events at an agarose-water interface. Thus, both model and experiment suggest that detachment of bacterial cells from clusters is an important mechanism underlying bacterial exploration of the phyllosphere. PMID:24124501

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Speciation rates decline through time in individual-based models of speciation and extinction.

    PubMed

    Wang, Shaopeng; Chen, Anping; Fang, Jingyun; Pacala, Stephen W

    2013-09-01

    A well-documented pattern in the fossil record is a long-term decline in the origination rate of new taxa after diversity rebounds from a mass extinction. The mechanisms for this pattern remain elusive. In this article, we investigate the macroevolutionary predictions of an individual-based birth-death model (BDI model) where speciation and extinction rates emerge from population dynamics. We start with the simplest neutral model in which every individual has the same per capita rates of birth, death, and speciation. Although the prediction of the simplest neutral model agrees qualitatively with the fossil pattern, the predicted decline in per-species speciation rates is too fast to explain the long-term trend in fossil data. We thus consider models with variation among species in per capita rates of speciation and a suite of alternative assumptions about the heritability of speciation rate. The results show that interspecific variation in per capita speciation rate can induce differences among species in their ability to resist extinction because a low speciation rate confers a small but important demographic advantage. As a consequence, the model predicts an appropriately slow temporal decline in speciation rates, which provides a mechanistic explanation for the fossil pattern.

  6. BacArena: Individual-based metabolic modeling of heterogeneous microbes in complex communities

    PubMed Central

    Baldini, Federico; Thiele, Ines

    2017-01-01

    Recent advances focusing on the metabolic interactions within and between cellular populations have emphasized the importance of microbial communities for human health. Constraint-based modeling, with flux balance analysis in particular, has been established as a key approach for studying microbial metabolism, whereas individual-based modeling has been commonly used to study complex dynamics between interacting organisms. In this study, we combine both techniques into the R package BacArena (https://cran.r-project.org/package=BacArena) to generate novel biological insights into Pseudomonas aeruginosa biofilm formation as well as a seven species model community of the human gut. For our P. aeruginosa model, we found that cross-feeding of fermentation products cause a spatial differentiation of emerging metabolic phenotypes in the biofilm over time. In the human gut model community, we found that spatial gradients of mucus glycans are important for niche formations which shape the overall community structure. Additionally, we could provide novel hypothesis concerning the metabolic interactions between the microbes. These results demonstrate the importance of spatial and temporal multi-scale modeling approaches such as BacArena. PMID:28531184

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

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

    USGS Publications Warehouse

    Pine, William Pine; 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.

  14. Evolving the selfish herd: emergence of distinct aggregating strategies in an individual-based model.

    PubMed

    Wood, Andrew J; Ackland, Graeme J

    2007-07-07

    From zebra to starlings, herring and even tadpoles, many creatures move in an organized group. The emergent behaviour arises from simple underlying movement rules, but the evolutionary pressure which favours these rules has not been conclusively identified. Various explanations exist for the advantage to the individual of group formation: reduction of predation risk; increased foraging efficiency or reproductive success. Here, we adopt an individual-based model for group formation and subject it to simulated predation and foraging; the haploid individuals evolve via a genetic algorithm based on their relative success under such pressure. Our work suggests that flock or herd formation is likely to be driven by predator avoidance. Individual fitness in the model is strongly dependent on the presence of other phenotypes, such that two distinct types of evolved group can be produced by the same predation or foraging conditions, each stable against individual mutation. We draw analogies with multiple Nash equilibria theory of iterated games to explain and categorize these behaviours. Our model is sufficient to capture the complex behaviour of dynamic collective groups, yet is flexible enough to manifest evolutionary behaviour.

  15. 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.

  16. A population estimate of chimpanzees (Pan troglodytes schweinfurthii) in the Ugalla region using standard and spatially explicit genetic capture-recapture methods.

    PubMed

    Moore, Deborah L; Vigilant, Linda

    2014-04-01

    Population parameters such as size, density, and distribution of a species across a landscape are important metrics that inform conservation science and are key to management strategies. In this study, we used genetic capture-recapture methods to estimate the population size and density of the little-studied chimpanzees in the Ugalla region of western Tanzania. From 237 fecal samples collected non-invasively over a 10-month period, we identified a minimum of 113 individuals. Based on the two-innate rate method (TIRM) modeled in the software capwire, we obtained a maximum-likelihood estimate of 322 (CI 227-373) individuals over the 624 km(2) area surveyed. Using a spatially explicit capture-recapture (SECR) method, we estimated a population density of 0.25 (CI 0.16-0.38) individuals/km(2) . Observations of nests and search effort data revealed areas of more intense usage. The findings of this study are an important step in the characterization of the Ugalla chimpanzees, and substantially improve our understanding of the number of chimpanzees that occupy this savanna-woodland region at the easternmost extent of the geographic range of this endangered subspecies.

  17. 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

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

    DOE PAGES

    McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

    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

  19. Individual-Based Model Framework to Assess Population Consequences of Polychlorinated Biphenyl Exposure in Bottlenose Dolphins

    PubMed Central

    Hall, Ailsa J.; McConnell, Bernie J.; Rowles, Teri K.; Aguilar, Alex; Borrell, Asuncion; Schwacke, Lori; Reijnders, Peter J.H.; Wells, Randall S.

    2006-01-01

    Marine mammals are susceptible to the effects of anthropogenic contaminants. Here we examine the effect of different polychlorinated biphenyl (PCB) accumulation scenarios on potential population growth rates using, as an example, data obtained for the population of bottlenose dolphins from Sarasota Bay, Florida. To achieve this goal, we developed an individual-based model framework that simulates the accumulation of PCBs in the population and modifies first-year calf survival based on maternal blubber PCB levels. In our example the current estimated annual PCB accumulation rate for the Sarasota Bay dolphin population might be depressing the potential population growth rate. However, our predictions are limited both by model naivety and parameter uncertainty. We emphasize the need for more data collection on the relationship between maternal blubber PCB levels and calf survivorship, the annual accumulation of PCBs in the blubber of females, and the transfer of PCBs to the calf through the placenta and during lactation. Such data require continued efforts directed toward long-term studies of known individuals in wild and semi-wild populations. PMID:16818247

  20. Individual-based model framework to assess population consequences of polychlorinated biphenyl exposure in bottlenose dolphins.

    PubMed

    Hall, Ailsa J; McConnell, Bernie J; Rowles, Teri K; Aguilar, Alex; Borrell, Asuncion; Schwacke, Lori; Reijnders, Peter J H; Wells, Randall S

    2006-04-01

    Marine mammals are susceptible to the effects of anthropogenic contaminants. Here we examine the effect of different polychlorinated biphenyl (PCB) accumulation scenarios on potential population growth rates using, as an example, data obtained for the population of bottlenose dolphins from Sarasota Bay, Florida. To achieve this goal, we developed an individual-based model framework that simulates the accumulation of PCBs in the population and modifies first-year calf survival based on maternal blubber PCB levels. In our example the current estimated annual PCB accumulation rate for the Sarasota Bay dolphin population might be depressing the potential population growth rate. However, our predictions are limited both by model naivety and parameter uncertainty. We emphasize the need for more data collection on the relationship between maternal blubber PCB levels and calf survivorship, the annual accumulation of PCBs in the blubber of females, and the transfer of PCBs to the calf through the placenta and during lactation. Such data require continued efforts directed toward long-term studies of known individuals in wild and semiwild populations.

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

    PubMed Central

    Seekell, David A; Dakos, Vasilis

    2015-01-01

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

  2. A spatially explicit Bayesian framework for cognitive schooling behaviours

    PubMed Central

    Grünbaum, Daniel

    2012-01-01

    Social aggregations such as schools, swarms, flocks and herds occur across a broad diversity of animal species, strongly impacting ecological and evolutionary dynamics of these species and their predators, prey and competitors. The mechanisms through which individual-level responses to neighbours generate group-level characteristics have been extensively investigated both experimentally and using mathematical models. Models of social groups typically adopt a ‘zone’ approach, in which individuals’ movement responses to neighbours are functions of instantaneous relative position. Empirical studies have demonstrated that most social animals such as fish exhibit well-developed spatial memory and other advanced cognitive capabilities. However, most models of social grouping do not explicitly include spatial memory, largely because a tractable framework for modelling acquisition of and response to historical spatial information has been lacking. Using fish schooling as a focal example, this study presents a framework for including cognitive responses to spatial memory in models of social aggregation. The framework utilizes Bayesian estimation parameters that are continuously distributed in time and space as proxies for animals’ spatial memory. The result is a hybrid Lagrangian–Eulerian model in which the effects of cognitive state and behavioural responses to historical spatial data on individual-, group- and population-level distributions of social animals can be explicitly investigated. PMID:24312727

  3. Patterns in the spatial distribution of Peruvian anchovy ( Engraulis ringens) revealed by spatially explicit fishing data

    NASA Astrophysics Data System (ADS)

    Bertrand, Sophie; Díaz, Erich; Lengaigne, Matthieu

    2008-10-01

    Peruvian anchovy ( Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse-seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse-seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions

  4. Population-level effects in Amphiascus tenuiremis: contrasting matrix- and individual-based population models.

    PubMed

    Lundström Belleza, Elin; Brinkmann, Markus; Preuss, Thomas G; Breitholtz, Magnus

    2014-12-01

    Environmental risk assessment (ERA) is generally based on individual-level endpoints, even though protection goals in ERA intend higher biological levels. Population models have the potential to translate individual-level endpoints to population-level responses and range from simple demographic equations to highly complex individual based models (IBMs). The aims of the current study were to develop a matrix model (MM) with the structure and parameterization proposed in the draft OECD guideline "Harpacticoid copepod development and reproduction test with Amphiascus tenuiremis", and an IBM with the same data requirements. Experimental data from lindane exposure from validation studies of the OECD guideline was projected to the population level. Lindane does not only cause effects on survival and reproduction, but also on the time it takes to develop from larvae to adults. The two model approaches were contrasted in terms of their ability to properly project these effects on development. The MM projected smaller effects of the lindane treatments on population growth rate compared to the IBM since in its proposed structure, it did not include the delay in development explicitly. Population-level EC10 for population growth rate in the IBM was at the same level as the most sensitive individual-level endpoint, whereas the EC10 from the MM was not as sensitive. Based on these findings, our conclusion is that the IBM (or an improved MM) should be used for datasets including shifts in development, whereas the simpler MM is sufficient for datasets where only mortality and reproduction are affected, or as a screening tool in lower-tier population-level ERA. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. 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…

  6. 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…

  7. Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

    NASA Astrophysics Data System (ADS)

    Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

    2016-02-01

    Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

  8. Maintenance of polygenic sex determination in a fluctuating environment: An individual-based model.

    PubMed

    Bateman, Andrew W; Anholt, Bradley R

    2017-02-10

    R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent between-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. This article is protected by copyright. All rights reserved.

  9. Modular and Spatially Explicit: A Novel Approach to System Dynamics

    EPA Science Inventory

    The Open Modeling Environment (OME) is an open-source System Dynamics (SD) simulation engine which has been created as a joint project between Oregon State University and the US Environmental Protection Agency. It is designed around a modular implementation, and provides a standa...

  10. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software.

    PubMed

    Cheng, Lu; Connor, Thomas R; Sirén, Jukka; Aanensen, David M; Corander, Jukka

    2013-05-01

    Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.

  11. 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.

  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. 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.

  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.

  15. 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.

  16. A global, spatially-explicit assessment of irrigated croplands influenced by urban wastewater flows

    NASA Astrophysics Data System (ADS)

    Thebo, A. L.; Drechsel, P.; Lambin, E. F.; Nelson, K. L.

    2017-07-01

    When urban areas expand without concomitant increases in wastewater treatment capacity, vast quantities of wastewater are released to surface waters with little or no treatment. Downstream of many urban areas are large areas of irrigated croplands reliant on these same surface water sources. Case studies document the widespread use of untreated wastewater in irrigated agriculture, but due to the practical and political challenges of conducting a true census of this practice, its global extent is not well known except where reuse has been planned. This study used GIS-based modeling methods to develop the first spatially-explicit estimate of the global extent of irrigated croplands influenced by urban wastewater flows, including indirect wastewater use. These croplands were further classified by their likelihood of using poor quality water based on the spatial proximity of croplands to urban areas, urban wastewater return flow ratios, and proportion of wastewater treated. This study found that 65% (35.9 Mha) of downstream irrigated croplands were located in catchments with high levels of dependence on urban wastewater flows. These same catchments were home to 1.37 billion urban residents. Of these croplands, 29.3 Mha were located in countries with low levels of wastewater treatment and home to 885 million urban residents. These figures provide insight into the key role that water reuse plays in meeting the water and food needs of people around the world, and the need to invest in wastewater treatment to protect public health.

  17. Large-scale, spatially-explicit test of the refuge strategy for delaying insecticide resistance

    PubMed Central

    Carrière, Yves; Ellers-Kirk, Christa; Hartfield, Kyle; Larocque, Guillaume; Degain, Ben; Dutilleul, Pierre; Dennehy, Timothy J.; Marsh, Stuart E.; Crowder, David W.; Li, Xianchun; Ellsworth, Peter C.; Naranjo, Steven E.; Palumbo, John C.; Fournier, Al; Antilla, Larry; Tabashnik, Bruce E.

    2012-01-01

    The refuge strategy is used worldwide to delay the evolution of pest resistance to insecticides that are either sprayed or produced by transgenic Bacillus thuringiensis (Bt) crops. This strategy is based on the idea that refuges of host plants where pests are not exposed to an insecticide promote survival of susceptible pests. Despite widespread adoption of this approach, large-scale tests of the refuge strategy have been problematic. Here we tested the refuge strategy with 8 y of data on refuges and resistance to the insecticide pyriproxyfen in 84 populations of the sweetpotato whitefly (Bemisia tabaci) from cotton fields in central Arizona. We found that spatial variation in resistance to pyriproxyfen within each year was not affected by refuges of melons or alfalfa near cotton fields. However, resistance was negatively associated with the area of cotton refuges and positively associated with the area of cotton treated with pyriproxyfen. A statistical model based on the first 4 y of data, incorporating the spatial distribution of cotton treated and not treated with pyriproxyfen, adequately predicted the spatial variation in resistance observed in the last 4 y of the study, confirming that cotton refuges delayed resistance and treated cotton fields accelerated resistance. By providing a systematic assessment of the effectiveness of refuges and the scale of their effects, the spatially explicit approach applied here could be useful for testing and improving the refuge strategy in other crop–pest systems. PMID:22215605

  18. 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.

  19. Large-scale, spatially-explicit test of the refuge strategy for delaying insecticide resistance.

    PubMed

    Carrière, Yves; Ellers-Kirk, Christa; Hartfield, Kyle; Larocque, Guillaume; Degain, Ben; Dutilleul, Pierre; Dennehy, Timothy J; Marsh, Stuart E; Crowder, David W; Li, Xianchun; Ellsworth, Peter C; Naranjo, Steven E; Palumbo, John C; Fournier, Al; Antilla, Larry; Tabashnik, Bruce E

    2012-01-17

    The refuge strategy is used worldwide to delay the evolution of pest resistance to insecticides that are either sprayed or produced by transgenic Bacillus thuringiensis (Bt) crops. This strategy is based on the idea that refuges of host plants where pests are not exposed to an insecticide promote survival of susceptible pests. Despite widespread adoption of this approach, large-scale tests of the refuge strategy have been problematic. Here we tested the refuge strategy with 8 y of data on refuges and resistance to the insecticide pyriproxyfen in 84 populations of the sweetpotato whitefly (Bemisia tabaci) from cotton fields in central Arizona. We found that spatial variation in resistance to pyriproxyfen within each year was not affected by refuges of melons or alfalfa near cotton fields. However, resistance was negatively associated with the area of cotton refuges and positively associated with the area of cotton treated with pyriproxyfen. A statistical model based on the first 4 y of data, incorporating the spatial distribution of cotton treated and not treated with pyriproxyfen, adequately predicted the spatial variation in resistance observed in the last 4 y of the study, confirming that cotton refuges delayed resistance and treated cotton fields accelerated resistance. By providing a systematic assessment of the effectiveness of refuges and the scale of their effects, the spatially explicit approach applied here could be useful for testing and improving the refuge strategy in other crop-pest systems.

  20. Spatially explicit scenario analysis for reconciling agricultural expansion, forest protection, and carbon conservation in Indonesia.

    PubMed

    Koh, Lian Pin; Ghazoul, Jaboury

    2010-06-15

    Palm oil is the world's most important vegetable oil in terms of production quantity. Indonesia, the world's largest palm-oil producer, plans to double its production by 2020, with unclear implications for the other national priorities of food (rice) production, forest and biodiversity protection, and carbon conservation. We modeled the outcomes of alternative development scenarios and show that every single-priority scenario had substantial tradeoffs associated with other priorities. The exception was a hybrid approach wherein expansion targeted degraded and agricultural lands that are most productive for oil palm, least suitable for food cultivation, and contain the lowest carbon stocks. This approach avoided any loss in forest or biodiversity and substantially ameliorated the impacts of oil-palm expansion on carbon stocks (limiting net loss to 191.6 million tons) and annual food production capacity (loss of 1.9 million tons). Our results suggest that the environmental and land-use tradeoffs associated with oil-palm expansion can be largely avoided through the implementation of a properly planned and spatially explicit development strategy.

  1. Spatially Explicit Mapping of Heat Health Risk Utilizing Environmental and Socioeconomic Data.

    PubMed

    Hu, Kejia; Yang, Xuchao; Zhong, Jieming; Fei, Fangrong; Qi, Jiaguo

    2017-02-07

    Extreme heat events, a leading cause of weather-related fatality worldwide, are expected to intensify, last longer, and occur more frequently in the near future. In heat health risk assessments, a spatiotemporal mismatch usually exists between hazard (heat stress) data and exposure (population distribution) data. Such mismatch is present because demographic data are generally updated every couple of years and unavailable at the subcensus unit level, which hinders the ability to diagnose human risks. In the present work, a human settlement index based on multisensor remote sensing data, including nighttime light, vegetation index, and digital elevation model data, was used for heat exposure assessment on a per-pixel basis. Moreover, the nighttime urban heat island effect was considered in heat hazard assessment. The heat-related health risk was spatially explicitly assessed and mapped at the 250 m × 250 m pixel level across Zhejiang Province in eastern China. The results showed that the accumulated heat risk estimates and the heat-related deaths were significantly correlated at the county level (Spearman's correlation coefficient = 0.76, P ≤ 0.01). Our analysis introduced a spatially specific methodology for the risk mapping of heat-related health outcomes, which is useful for decision support in preparation and mitigation of heat-related risk and potential adaptation.

  2. Integrating spatially explicit representations of landscape perceptions into land change research

    USGS Publications Warehouse

    Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.

    2017-01-01

    Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

  3. Spatially explicit methodology for coordinated manure management in shared watersheds.

    PubMed

    Sharara, Mahmoud; Sampat, Apoorva; Good, Laura W; Smith, Amanda S; Porter, Pamela; Zavala, Victor M; Larson, Rebecca; Runge, Troy

    2017-05-01

    Increased clustering and consolidation of livestock production systems has been linked to adverse impacts on water quality. This study presents a methodology to optimize manure management within a hydrologic region to minimize agricultural phosphorus (P) loss associated with winter manure application. Spatial and non-spatial data representing livestock, crop, soil, terrain and hydrography were compiled to determine manure P production rates, crop P uptake, existing manure storage capabilities, and transportation distances. Field slope, hydrologic soil group (HSG), and proximity to waterbodies were used to classify crop fields according to their runoff risk for winter-applied manure. We use these data to construct a comprehensive optimization model that identifies optimal location, size, and transportation strategy to achieve environmental and economic goals. The environmental goal was the minimization of daily hauling of manure to environmentally sensitive crop fields, i.e., those classified as high P-loss fields, whereas the economic goal was the minimization of the transportation costs across the entire study area. A case study encompassing two contiguous 10-digit hydrologic unit subwatersheds (HUC-10) in South Central Wisconsin, USA was developed to demonstrate the proposed methodology. Additionally, scenarios representing different management decisions (storage facility maximum volume, and project capital) and production conditions (increased milk production and 20-year future projection) were analyzed to determine their impact on optimal decisions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. 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

  5. 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

  6. Evaluation of and insights from ALFISH: a spatially explicit landscape-level simulation of fish populations in the Everglades

    USGS Publications Warehouse

    Gaff, Holly; Chick, John; Trexler, Joel; DeAngelis, Donald L.; Gross, Louis; Salinas, Rene

    2004-01-01

    We present an evaluation of a spatially explicit, age-structured model created to assess fish density dynamics in the Florida Everglades area. This model, ALFISH, has been used to compare alternative management scenarios for the Florida Everglades region. This area is characterized by periodic dry downs and refloodings. ALFISH uses spatially explicit water depth data to predict patterns of fish density. Here we present a method for calibration of ALFISH, based on information concerning fish movement, pond locations and other field data. With the current information, the greatest coefficient of determination achieved from regressions of ALFISH output to field data is 0.35 for fish density and 0.88 for water depth. The poor predictability of fish density mirrors the empirical findings that hydrology, which is the main driver of the model, only accounts for 20–40% of the variance of fish densities across the Everglades landscape. Sensitivity analyses indicate that fish in this system are very sensitive to frequency, size and location of permanent ponds as well as availability of prey.

  7. 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.

  8. The assessment of mangrove biomass and carbon in West Africa: a spatially explicit analytical framework

    Treesearch

    Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Carl C. Trettin

    2015-01-01

    Mangrove forests are highly productive and have large carbon sinks while also providing numerous goods and ecosystem services. However, effective management and conservation of the mangrove forests are often dependent on spatially explicit assessments of the resource. Given the remote and highly dispersed nature of mangroves, estimation of biomass and carbon...

  9. Spatially explicit analysis of field inventories for national forest carbon monitoring.

    PubMed

    Marvin, David C; Asner, Gregory P

    2016-12-01

    Tropical forests provide a crucial carbon sink for a sizable portion of annual global CO2 emissions. Policies that incentivize tropical forest conservation by monetizing forest carbon ultimately depend on accurate estimates of national carbon stocks, which are often based on field inventory sampling. As an exercise to understand the limitations of field inventory sampling, we tested whether two common field-plot sampling approaches could accurately estimate carbon stocks across approximately 76 million ha of Perúvian forests. A 1-ha resolution LiDAR-based map of carbon stocks was used as a model of the country's carbon geography. Both field inventory sampling approaches worked well in estimating total national carbon stocks, almost always falling within 10 % of the model national total. However, the sampling approaches were unable to produce accurate spatially-explicit estimates of the carbon geography of Perú, with estimates falling within 10 % of the model carbon geography across no more than 44 % of the country. We did not find any associations between carbon stock errors from the field plot estimates and six different environmental variables. Field inventory plot sampling does not provide accurate carbon geography for a tropical country with wide ranging environmental gradients such as Perú. The lack of association between estimated carbon errors and environmental variables suggests field inventory sampling results from other nations would not differ from those reported here. Tropical forest nations should understand the risks associated with primarily field-based sampling approaches, and consider alternatives leading to more effective forest conservation and climate change mitigation.

  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. Modelling Holocene peatland dynamics with an individual-based dynamic vegetation model

    NASA Astrophysics Data System (ADS)

    Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

    2017-05-01

    Dynamic global vegetation models (DGVMs) are designed for the study of past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks. However, most DGVMs do not yet have detailed representations of permafrost and non-permafrost peatlands, which are an important store of carbon, particularly at high latitudes. We demonstrate a new implementation of peatland dynamics in a customized Arctic version of the LPJ-GUESS DGVM, simulating the long-term evolution of selected northern peatland ecosystems and assessing the effect of changing climate on peatland carbon balance. Our approach employs a dynamic multi-layer soil with representation of freeze-thaw processes and litter inputs from a dynamically varying mixture of the main peatland plant functional types: mosses, shrubs and graminoids. The model was calibrated and tested for a sub-Arctic mire in Stordalen, Sweden, and validated at a temperate bog site in Mer Bleue, Canada. A regional evaluation of simulated carbon fluxes, hydrology and vegetation dynamics encompassed additional locations spread across Scandinavia. Simulated peat accumulation was found to be generally consistent with published data and the model was able to capture reported long-term vegetation dynamics, water table position and carbon fluxes. A series of sensitivity experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We found that the Stordalen mire may be expected to sequester more carbon in the first half of the 21st century due to milder and wetter climate conditions, a longer growing season, and the CO2 fertilization effect, turning into a carbon source after mid-century because of higher decomposition rates in response to warming soils.

  12. 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.

  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.

    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.

  14. 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.

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

    USGS Publications Warehouse

    Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

    2016-01-01

    Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to

  16. Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

    NASA Astrophysics Data System (ADS)

    Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

    2017-04-01

    The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool

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

    DOE PAGES

    Jones, B.; O’Neill, B. C.

    2016-07-29

    Here we report that 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, spatiallymore » 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.« less

  18. Spatially explicit assessment of estuarine fish after Deepwater Horizon oil spill: trade-off in complexity and parsimony.

    PubMed

    Awkerman, Jill A; Hemmer, Becky; Almario, Alex; Lilavois, Crystal; Barron, Mace G; Raimondo, Sandy

    2016-09-01

    Evaluating long-term contaminant effects on wildlife populations depends on spatial information about habitat quality, heterogeneity in contaminant exposure, and sensitivities and distributions of species integrated into a systems modeling approach. Rarely is this information readily available, making it difficult to determine the applicability of realistic models to quantify population-level risks. To evaluate the trade-offs between data demands and increased specificity of spatially explicit models for population-level risk assessments, we developed a model for a standard toxicity test species, the sheepshead minnow (Cyprinodon variegatus), exposed to oil contamination following the Deepwater Horizon oil spill and compared the output with various levels of model complexity to a standard risk quotient approach. The model uses habitat and fish occupancy data collected over five sampling periods throughout 2008-2010 in Pensacola and Choctawhatchee Bays, Florida, USA, to predict species distribution, field-collected and publically available data on oil distribution and concentration, and chronic toxicity data from laboratory assays applied to a matrix population model. The habitat suitability model established distribution of fish within Barataria Bay, Louisiana, USA, and the population model projected the dynamics of the species in the study area over a 5-yr period (October 2009-September 2014). Vital rates were modified according to estimated contaminant concentrations to simulate oil exposure effects. To evaluate the differences in levels of model complexity, simulations varied from temporally and spatially explicit, including seasonal variation and location-specific oiling, to simple interpretations of a risk quotient derived for the study area. The results of this study indicate that species distribution, as well as spatially and temporally variable contaminant concentrations, can provide a more ecologically relevant evaluation of species recovery from

  19. 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

  20. Spatially Explicit Estimates of Suspended Sediment and Bedload Transport Rates for Western Oregon and Northwestern California

    NASA Astrophysics Data System (ADS)

    O'Connor, J. E.; Wise, D. R.; Mangano, J.; Jones, K.

    2015-12-01

    Empirical analyses of suspended sediment and bedload transport gives estimates of sediment flux for western Oregon and northwestern California. The estimates of both bedload and suspended load are from regression models relating measured annual sediment yield to geologic, physiographic, and climatic properties of contributing basins. The best models include generalized geology and either slope or precipitation. The best-fit suspended-sediment model is based on basin geology, precipitation, and area of recent wildfire. It explains 65% of the variance for 68 suspended sediment measurement sites within the model area. Predicted suspended sediment yields range from no yield from the High Cascades geologic province to 200 tonnes/ km2-yr in the northern Oregon Coast Range and 1000 tonnes/km2-yr in recently burned areas of the northern Klamath terrain. Bed-material yield is similarly estimated from a regression model based on 22 sites of measured bed-material transport, mostly from reservoir accumulation analyses but also from several bedload measurement programs. The resulting best-fit regression is based on basin slope and the presence/absence of the Klamath geologic terrane. For the Klamath terrane, bed-material yield is twice that of the other geologic provinces. This model explains more than 80% of the variance of the better-quality measurements. Predicted bed-material yields range up to 350 tonnes/ km2-yr in steep areas of the Klamath terrane. Applying these regressions to small individual watersheds (mean size; 66 km2 for bed-material; 3 km2 for suspended sediment) and cumulating totals down the hydrologic network (but also decreasing the bed-material flux by experimentally determined attrition rates) gives spatially explicit estimates of both bed-material and suspended sediment flux. This enables assessment of several management issues, including the effects of dams on bedload transport, instream gravel mining, habitat formation processes, and water-quality. The

  1. 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.

  2. Evaluating Effects of Pump-Storage Water Withdrawals Using an Individual-Based Metapopulation Model of a Benthic Fish Species

    DTIC Science & Technology

    2011-04-01

    maintaining ab- undance of a native fish species, the Turquoise darter (Etheostoma inscriptum). We developed and applied an individual-based...based metapopulation model for assessing the effects of water withdrawals on a flow-dependent species, the Turquoise darter (Etheostoma inscriptum...withdrawal strategy for a municipal pump-storage reservoir and the status of the Turquoise darter over a 20-year period in the Middle Oco- nee River near

  3. 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

  4. 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...

  5. 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...

  6. 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

  7. Spatially- explicit Fossil Fuel Carbon Dioxide Inventories for Transportation in the U.S.

    NASA Astrophysics Data System (ADS)

    Hutchins, M.; Gurney, K. R.

    2016-12-01

    related FFCO2 emissions at a CCS stations using fuel specific emissions factors combined with the raw traffic counts. The CCS network provides a unique opportunity to compare spatially explicit, "bottom-up" models of transportation related FFCO2 emissions to measured traffic volume at over 300 specific locations.

  8. 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

  9. Comparing individual-based approaches to modelling the self-organization of multicellular tissues

    PubMed Central

    2017-01-01

    The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage. PMID:28192427

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  11. InSTREAM: the individual-based stream trout research and environmental assessment model

    Treesearch

    Steven F. Railsback; Bret C. Harvey; Stephen K. Jackson; Roland H. Lamberson

    2009-01-01

    This report documents Version 4.2 of InSTREAM, including its formulation, software, and application to research and management problems. InSTREAM is a simulation model designed to understand how stream and river salmonid populations respond to habitat alteration, including altered flow, temperature, and turbidity regimes and changes in channel morphology. The model...

  12. 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.

  13. Individual-based and continuum models of growing cell populations: a comparison.

    PubMed

    Byrne, Helen; Drasdo, Dirk

    2009-04-01

    In this paper we compare two alternative theoretical approaches for simulating the growth of cell aggregates in vitro: individual cell (agent)-based models and continuum models. We show by a quantitative analysis of both a biophysical agent-based and a continuum mechanical model that for densely packed aggregates the expansion of the cell population is dominated by cell proliferation controlled by mechanical stress. The biophysical agent-based model introduced earlier (Drasdo and Hoehme in Phys Biol 2:133-147, 2005) approximates each cell as an isotropic, homogeneous, elastic, spherical object parameterised by measurable biophysical and cell-biological quantities and has been shown by comparison to experimental findings to explain the growth patterns of dense monolayers and multicellular spheroids. Both models exhibit the same growth kinetics, with initial exponential growth of the population size and aggregate diameter followed by linear growth of the diameter and power-law growth of the cell population size. Very sparse monolayers can be explained by a very small or absent cell-cell adhesion and large random cell migration. In this case the expansion speed is not controlled by mechanical stress but by random cell migration and can be modelled by the Fisher-Kolmogorov-Petrovskii-Piskounov (FKPP) reaction-diffusion equation. The growth kinetics differs from that of densely packed aggregates in that the initial spread, as quantified by the radius of gyration, is diffusive. Since simulations of the lattice-free agent-based model in the case of very large random migration are too long to be practical, lattice-based cellular automaton (CA) models have to be used for a quantitative analysis of sparse monolayers. Analysis of these dense monolayers leads to the identification of a critical parameter of the CA model so that eventually a hierarchy of three model types (a detailed biophysical lattice-free model, a rule-based cellular automaton and a continuum approach

  14. 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.

  15. 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.

    2014-01-01

    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 the dynamic vegetation model LPJ-GUESS 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 exemplary "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. Under a 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 until 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 contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  17. 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.

  18. Forest dynamics in Oregon landscapes: evaluation and application of an individual-based model.

    PubMed

    Busing, Richard T; Solomon, Allen M; McKane, Robert B; Burdick, Connie A

    2007-10-01

    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.

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

    PubMed Central

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

    2012-01-01

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

  20. A hybrid wetland map for China: a synergistic approach using census and spatially explicit datasets.

    PubMed

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

    2012-01-01

    Wetlands play important ecological, economic, and cultural roles in societies around the world. However, wetland degradation has become a serious ecological issue, raising the global sustainability concern. An accurate wetland map is essential for wetland management. Here we used a fuzzy method to create a hybrid wetland map for China through the combination of five existing wetlands datasets, including four spatially explicit wetland distribution data and one wetland census. Our results show the total wetland area is 384,864 km(2), 4.08% of China's national surface area. The hybrid wetland map also shows spatial distribution of wetlands with a spatial resolution of 1 km. The reliability of the map is demonstrated by comparing it with spatially explicit datasets on lakes and reservoirs. The hybrid wetland map is by far the first wetland mapping that is consistent with the statistical data at the national and provincial levels in China. It provides a benchmark map for research on wetland protection and management. The method presented here is applicable for not only wetland mapping but also for other thematic mapping in China and beyond.

  1. 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.

  2. Punctuated equilibria and 1/f noise in a biological coevolution model with individual-based dynamics

    NASA Astrophysics Data System (ADS)

    Rikvold, Per Arne; Zia, R. K.

    2003-09-01

    We present a study by linear stability analysis and large-scale Monte Carlo simulations of a simple model of biological coevolution. Selection is provided through a reproduction probability that contains quenched, random interspecies interactions, while genetic variation is provided through a low mutation rate. Both selection and mutation act on individual organisms. Consistent with some current theories of macroevolutionary dynamics, the model displays intermittent, statistically self-similar behavior with punctuated equilibria. The probability density for the lifetimes of ecological communities is well approximated by a power law with exponent near -2, and the corresponding power spectral densities show 1/f noise (flicker noise) over several decades. The long-lived communities (quasisteady states) consist of a relatively small number of mutualistically interacting species, and they are surrounded by a “protection zone” of closely related genotypes that have a very low probability of invading the resident community. The extent of the protection zone affects the stability of the community in a way analogous to the height of the free-energy barrier surrounding a metastable state in a physical system. Measures of biological diversity are on average stationary with no discernible trends, even over our very long simulation runs of approximately 3.4×107 generations.

  3. Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki).

    PubMed

    Beaudouin, Rémy; Ginot, Vincent; Monod, Gilles

    2012-01-01

    Experimental ecosystems such as mesocosms have been developed to improve the ecological relevance of ecotoxicity test. However, in mesocosm studies, the number of replicates is limited by practical and financial constraints. In addition, high levels of biological organization are characterized by a high variability of descriptive variables. This variability and the poor number of replicates have been recognized as a major drawback for detecting significant effects of chemicals in mesocosm studies. In this context, a tool able to predict precisely control mesocosms outputs, to which endpoints in mesocosms exposed to chemicals could be compared should constitute a substantial improvement. We evaluated here a solution which consists in stochastic modelling of the control fish populations to assess the probabilistic distributions of population endpoints. An individual-based approach was selected, because it generates realistic fish length distributions and accounts for both individual and environmental sources of variability. This strategy was applied to mosquitofish (Gambusia holbrooki) populations monitored in lentic mesocosms. We chose the number of founders as a so-called "stressor" because subsequent consequences at the population level could be expected. Using this strategy, we were able to detect more significant and biologically relevant perturbations than using classical methods. We conclude that designing an individual-based model is very promising for improving mesocosm data analysis. This methodology is currently being applied to ecotoxicological issues.

  4. 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).

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

    PubMed

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

    2016-02-01

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

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

    USGS Publications Warehouse

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

    2016-01-01

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

  7. Evaluation of alternative PCB clean-up strategies using an individual-based population model of mink.

    PubMed

    Salice, Christopher J; Sample, Bradley E; Miller Neilan, Rachael; Rose, Kenneth A; Sable, Shaye

    2011-12-01

    Population models can be used to place observed toxic effects into an assessment of the impacts on population-level endpoints, which are generally considered to provide greater ecological insight and relevance. We used an individual-based model of mink to evaluate the population-level effects of exposure to polychlorinated biphenyls (PCBs) and the impact that different remediation strategies had on mink population endpoints (population size and extinction risk). Our simulations indicated that the initial population size had a strong impact on mink population dynamics. In addition, mink populations were extremely responsive to clean-up scenarios that were initiated soon after the contamination event. In fact, the rate of PCB clean-up did not have as strong a positive effect on mink as did the initiation of clean-up (start time). We show that population-level approaches can be used to understand adverse effects of contamination and to also explore the potential benefits of various remediation strategies.

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

    NASA Astrophysics Data System (ADS)

    Cherubini, F.

    2015-12-01

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

  9. 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

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

    USGS Publications Warehouse

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

    2015-01-01

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

  11. Use of an Individual-based Model to Control Transmission Pathways of Mycobacterium avium Subsp. paratuberculosis Infection in Cattle Herds.

    PubMed

    Al-Mamun, M A; Smith, R L; Schukken, Y H; Gröhn, Y T

    2017-09-19

    Johne's disease (JD) is a chronic enteric disease in cattle caused by Mycobacterium avian subsp. paratuberculosis (MAP). Eradicating JD is a difficult task due to the long incubation period of MAP, inefficient diagnostic tests, and delayed clinical signs. Effective control strategies can help farmers to reduce prevalence, but those most acceptable to farmers combine specific information about lactation performance and testing results, which existing models do not provide. This paper presents an individual-based model of MAP infection dynamics and assesses the relative performance of the applied alternative control strategies. The base dairy herd model included the daily life events of a dairy cow and reflects several current dairy management processes. We then integrated MAP infection dynamics into the model. The model adopted four different test-based control strategies based on risk-based culling decisions and three hygiene scenarios. The model tracked the source of each infection and quantified the efficacy of each control strategy in reducing the risks of different transmission routes. The results suggest that risk-based culling can reduce prevalence compared with no control, but cannot eliminate the infection. Overall, this work provides not only a valuable tool to investigate MAP transmission dynamics but also offers adaptability to model similar infectious diseases.

  12. Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential

    NASA Astrophysics Data System (ADS)

    Vågen, Tor-Gunnar; Winowiecki, Leigh A.

    2013-03-01

    Current methods for assessing soil organic carbon (SOC) stocks are generally not well suited for understanding variations in SOC stocks in landscapes. This is due to the tedious and time-consuming nature of the sampling methods most commonly used to collect bulk density cores, which limits repeatability across large areas, particularly where information is needed on the spatial dynamics of SOC stocks at scales relevant to management and for spatially explicit targeting of climate change mitigation options. In the current study, approaches were explored for (i) field-based estimates of SOC stocks and (ii) mapping of SOC stocks at moderate to high resolution on the basis of data from four widely contrasting ecosystems in East Africa. Estimated SOC stocks for 0-30 cm depth varied both within and between sites, with site averages ranging from 2 to 8 kg m-2. The differences in SOC stocks were determined in part by rainfall, but more importantly by sand content. Results also indicate that managing soil erosion is a key strategy for reducing SOC loss and hence in mitigation of climate change in these landscapes. Further, maps were developed on the basis of satellite image reflectance data with multiple R-squared values of 0.65 for the independent validation data set, showing variations in SOC stocks across these landscapes. These maps allow for spatially explicit targeting of potential climate change mitigation efforts through soil carbon sequestration, which is one option for climate change mitigation and adaptation. Further, the maps can be used to monitor the impacts of such mitigation efforts over time.

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

    NASA Astrophysics Data System (ADS)

    Cárcamo, P. Francisco; Gaymer, Carlos F.

    2013-12-01

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

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

    PubMed

    Cárcamo, P Francisco; Gaymer, Carlos F

    2013-12-01

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

  15. Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

    PubMed Central

    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-1yr-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

  16. 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.

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

    PubMed Central

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

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

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

    PubMed

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

    2016-10-01

    With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2 O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2 O emissions at the country scale by aggregating all crops, under the assumption that N2 O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2 O emissions are relatively greater at higher N application rates. Here, we apply a super-linear emissions response model to crop-specific, spatially explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2 O emissions from croplands. We estimate 0.66 Tg of N2 O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2 O emissions range from 20% to 40% lower throughout sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak nonlinear response of N2 O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2 O emissions. As aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2 O emissions estimates. © 2016 John Wiley & Sons Ltd.

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

    PubMed

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

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

  1. Amplification due to spatial clustering in an individual-based model of mosquito-avian arbovirus transmission.

    PubMed

    Shaman, Jeffrey

    2007-05-01

    Theory and observations indicate that spatial clustering of birds and mosquitoes may be necessary for epizootic amplification of arboviruses with avian zoonoses. In this paper, I present an individual-based model of zoonotic arbovirus transmission among birds and mosquitoes. The results of initial ensemble model simulations indicate that the co-location of a vector mosquito oviposition site with an infected bird roost increases the local vector-to-host density and increases the likelihood of arbovirus amplification within the infected roost. Such amplification also increases the likelihood of secondary amplification at other roost sites, produces higher vector and host infection rates, increases the time to virus extinction within the model population, and increases the total number of birds infected. Additional oviposition locations within the model domain also increase the likelihood of secondary amplification. These findings support the idea that spatial clustering of mosquitoes and birds may facilitate arbovirus amplification. This model provides a basis for future exploration of specific zoonotic transmission cycles, including West Nile virus, and could be used to test the efficacy of various control strategies.

  2. Cost-Effectiveness of Adolescent Pertussis Vaccination for The Netherlands: Using an Individual-Based Dynamic Model

    PubMed Central

    de Vries, Robin; Kretzschmar, Mirjam; Schellekens, Joop F. P.; Versteegh, Florens G. A.; Westra, Tjalke A.; Roord, John J.; Postma, Maarten J.

    2010-01-01

    Background Despite widespread immunization programs, a clear increase in pertussis incidence is apparent in many developed countries during the last decades. Consequently, additional immunization strategies are considered to reduce the burden of disease. The aim of this study is to design an individual-based stochastic dynamic framework to model pertussis transmission in the population in order to predict the epidemiologic and economic consequences of the implementation of universal booster vaccination programs. Using this framework, we estimate the cost-effectiveness of universal adolescent pertussis booster vaccination at the age of 12 years in the Netherlands. Methods/Principal Findings We designed a discrete event simulation (DES) model to predict the epidemiological and economic consequences of implementing universal adolescent booster vaccination. We used national age-specific notification data over the period 1996–2000—corrected for underreporting—to calibrate the model assuming a steady state situation. Subsequently, booster vaccination was introduced. Input parameters of the model were derived from literature, national data sources (e.g. costing data, incidence and hospitalization data) and expert opinions. As there is no consensus on the duration of immunity acquired by natural infection, we considered two scenarios for this duration of protection (i.e. 8 and 15 years). In both scenarios, total pertussis incidence decreased as a result of adolescent vaccination. From a societal perspective, the cost-effectiveness was estimated at €4418/QALY (range: 3205–6364 € per QALY) and €6371/QALY (range: 4139–9549 € per QALY) for the 8- and 15-year protection scenarios, respectively. Sensitivity analyses revealed that the outcomes are most sensitive to the quality of life weights used for pertussis disease. Conclusions/Significance To our knowledge we designed the first individual-based dynamic framework to model pertussis transmission in the

  3. The Role of Ocean Currents in the Temperature Selection of Plankton: Insights from an Individual-Based Model.

    PubMed

    Hellweger, Ferdi L; van Sebille, Erik; Calfee, Benjamin C; Chandler, Jeremy W; Zinser, Erik R; Swan, Brandon K; Fredrick, Neil D

    2016-01-01

    Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental factors may not be representative of those that shaped the local population. Here we use an individual-based model of microbes in the global surface ocean to explore this effect for temperature. We simulate up to 25 million individual cells belonging to up to 50 species with different temperature optima. Microbes are moved around the globe based on a hydrodynamic model, and grow and die based on local temperature. We quantify the role of currents using the "advective temperature differential" metric, which is the optimum temperature of the most abundant species from the model with advection minus that from the model without advection. This differential depends on the location and can be up to 4°C. Poleward-flowing currents, like the Gulf Stream, generally experience cooling and the differential is positive. We apply our results to three global datasets. For observations of optimum growth temperature of phytoplankton, accounting for the effect of currents leads to a slightly better agreement with observations, but there is large variability and the improvement is not statistically significant. For observed Prochlorococcus ecotype ratios and metagenome nucleotide divergence, accounting for advection improves the correlation significantly, especially in areas with relatively strong poleward or equatorward currents.

  4. The Role of Ocean Currents in the Temperature Selection of Plankton: Insights from an Individual-Based Model

    PubMed Central

    Hellweger, Ferdi L.; van Sebille, Erik; Calfee, Benjamin C.; Chandler, Jeremy W.; Zinser, Erik R.; Swan, Brandon K.; Fredrick, Neil D.

    2016-01-01

    Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental factors may not be representative of those that shaped the local population. Here we use an individual-based model of microbes in the global surface ocean to explore this effect for temperature. We simulate up to 25 million individual cells belonging to up to 50 species with different temperature optima. Microbes are moved around the globe based on a hydrodynamic model, and grow and die based on local temperature. We quantify the role of currents using the “advective temperature differential” metric, which is the optimum temperature of the most abundant species from the model with advection minus that from the model without advection. This differential depends on the location and can be up to 4°C. Poleward-flowing currents, like the Gulf Stream, generally experience cooling and the differential is positive. We apply our results to three global datasets. For observations of optimum growth temperature of phytoplankton, accounting for the effect of currents leads to a slightly better agreement with observations, but there is large variability and the improvement is not statistically significant. For observed Prochlorococcus ecotype ratios and metagenome nucleotide divergence, accounting for advection improves the correlation significantly, especially in areas with relatively strong poleward or equatorward currents. PMID:27907181

  5. An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model.

    PubMed

    Gras, Robin; Devaurs, Didier; Wozniak, Adrianna; Aspinall, Adam

    2009-01-01

    We present an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a fuzzy cognitive map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator or prey, distance to potential breeding partner, distance to food, energy level) and its internal states (e.g., fear, hunger, curiosity), and to choose several possible actions such as evasion, eating, or breeding. The FCM of each individual is unique and is the result of the evolutionary process. The notion of species is also implemented in such a way that species emerge from the evolving population of agents. To our knowledge, our system is the only one that allows the modeling of links between behavior patterns and speciation. The simulation produces a lot of data, including number of individuals, level of energy by individual, choice of action, age of the individuals, and average FCM associated with each species. This study investigates patterns of macroevolutionary processes, such as the emergence of species in a simulated ecosystem, and proposes a general framework for the study of specific ecological problems such as invasive species and species diversity patterns. We present promising results showing coherent behaviors of the whole simulation with the emergence of strong correlation patterns also observed in existing ecosystems.

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

    USGS Publications Warehouse

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

    2003-01-01

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

  7. Use of an individual-based simulation model to explore and evaluate potential insecticide resistance management strategies.

    PubMed

    Slater, Russell; Stratonovitch, Pierre; Elias, Jan; Semenov, Mikhail A; Denholm, Ian

    2017-07-01

    Tools with the potential to predict risks of insecticide resistance and aid the evaluation and design of resistance management tactics are of value to all sectors of the pest management community. Here we describe use of a versatile individual-based model of resistance evolution to simulate how strategies employing single and multiple insecticides influence resistance development in the pollen beetle, Meligethes aeneus. Under repeated exposure to a single insecticide, resistance evolved faster to a pyrethroid (lambda-cyhalothrin) than to a pyridine azomethane (pymetrozine), due to difference in initial efficacy. A mixture of these compounds delayed resistance compared to use of single products. The effectiveness of rotations depended on the sequence in which compounds were applied in response to pest density thresholds. Effectiveness of a mixture strategy declined with reductions in grower compliance. At least 50% compliance was needed to cause some delay in resistance development. No single strategy meets all requirements for managing resistance. It is important to evaluate factors that prevail under particular pest management scenarios. The model used here provides operators with a valuable means for evaluating and extending sound resistance management advice, as well as understanding needs and opportunities offered by new control techniques. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  8. Individual-based modeling of potential poliovirus transmission in connected religious communities in North America with low uptake of vaccination.

    PubMed

    Kisjes, Kasper H; Duintjer Tebbens, Radboud J; Wallace, Gregory S; Pallansch, Mark A; Cochi, Stephen L; Wassilak, Steven G F; Thompson, Kimberly M

    2014-11-01

    Pockets of undervaccinated individuals continue to raise concerns about their potential to sustain epidemic transmission of vaccine-preventable diseases. Prior importations of live polioviruses (LPVs) into Amish communities in North America led to their recognition as a potential and identifiable linked network of undervaccinated individuals. We developed an individual-based model to explore the potential transmission of a LPV throughout the North American Amish population. Our model demonstrates the expected limited impact associated with the historical importations, which occurred in isolated communities during the low season for poliovirus transmission. We show that some conditions could potentially lead to wider circulation of LPVs and cases of paralytic polio in Amish communities if an importation occurred during or after 2013. The impact will depend on the uncertain historical immunity to poliovirus infection among members of the community. Heterogeneity in immunization coverage represents a risk factor for potential outbreaks of polio if introduction of a LPV occurs, although overall high population immunity in North America suggests that transmission would remain relatively limited. Efforts to prevent spread between Amish church districts with any feasible measures may offer the best opportunity to contain an outbreak and limit its size. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Trait contributions to fish community assembly emerge from trophicinteractions in an individual-based model

    USGS Publications Warehouse

    Giacomini, Henrique C.; DeAngelis, Donald; Trexler, Joel C.; Petrere, Miguel

    2013-01-01

    Community ecology seeks to understand and predict the characteristics of communities that can develop under different environmental conditions, but most theory has been built on analytical models that are limited in the diversity of species traits that can be considered simultaneously. We address that limitation with an individual-based model to simulate assembly of fish communities characterized by life history and trophic interactions with multiple physiological tradeoffs as constraints on species performance. Simulation experiments were carried out to evaluate the distribution of 6 life history and 4 feeding traits along gradients of resource productivity and prey accessibility. These experiments revealed that traits differ greatly in importance for species sorting along the gradients. Body growth rate emerged as a key factor distinguishing community types and defining patterns of community stability and coexistence, followed by egg size and maximum body size. Dominance by fast-growing, relatively large, and fecund species occurred more frequently in cases where functional responses were saturated (i.e. high productivity and/or prey accessibility). Such dominance was associated with large biomass fluctuations and priority effects, which prevented richness from increasing with productivity and may have limited selection on secondary traits, such as spawning strategies and relative size at maturation. Our results illustrate that the distribution of species traits and the consequences for community dynamics are intimately linked and strictly dependent on how the benefits and costs of these traits are balanced across different conditions.

  10. An equation-free computational approach for extracting population-level behavior from individual-based models of biological dispersal

    NASA Astrophysics Data System (ADS)

    Erban, Radek; Kevrekidis, Ioannis G.; Othmer, Hans G.

    2006-03-01

    The movement of many organisms can be described as a random walk at either or both the individual and population level. The rules for this random walk are based on complex biological processes and it may be difficult to develop a tractable, quantitatively-accurate, individual-level model. However, important problems in areas ranging from ecology to medicine involve large collections of individuals, and a further intellectual challenge is to model population-level behavior based on a detailed individual-level model. Because of the large number of interacting individuals and because the individual-level model is complex, classical direct Monte Carlo simulations can be very slow, and often of little practical use. In this case, an equation-free approach [I.G. Kevrekidis, C.W. Gear, J.M. Hyman, P. Kevrekidis, O. Runborg, K. Theodoropoulos, Equation-free, coarse-grained multiscale computation: enabling microscopic simulators to perform system-level analysis, Commun. Math. Sci. 1 (4) (2003) 715-762] may provide effective methods for the analysis and simulation of individual-based models. In this paper we analyze equation-free coarse projective integration. For analytical purposes, we start with known partial differential equations describing biological random walks and we study the projective integration of these equations. In particular, we illustrate how to accelerate explicit numerical methods for solving these equations. Then we present illustrative kinetic Monte Carlo simulations of these random walks and show that a decrease in computational time by as much as a factor of a thousand can be obtained by exploiting the ideas developed by analysis of the closed form PDEs. The illustrative biological example here is chemotaxis, but it could be any random walker that biases its movement in response to environmental cues.

  11. Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese

    PubMed Central

    Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

    2013-01-01

    An individual-based modeling (IBM) approach was developed to describe the behavior of a few Listeria monocytogenes cells contaminating smear soft cheese surface. The IBM approach consisted of assessing the stochastic individual behaviors of cells on cheese surfaces and knowing the characteristics of their surrounding microenvironments. We used a microelectrode for pH measurements and micro-osmolality to assess the water activity of cheese microsamples. These measurements revealed a high variability of microscale pH compared to that of macroscale pH. A model describing the increase in pH from approximately 5.0 to more than 7.0 during ripening was developed. The spatial variability of the cheese surface characterized by an increasing pH with radius and higher pH on crests compared to that of hollows on cheese rind was also modeled. The microscale water activity ranged from approximately 0.96 to 0.98 and was stable during ripening. The spatial variability on cheese surfaces was low compared to between-cheese variability. Models describing the microscale variability of cheese characteristics were combined with the IBM approach to simulate the stochastic growth of L. monocytogenes on cheese, and these simulations were compared to bacterial counts obtained from irradiated cheeses artificially contaminated at different ripening stages. The simulated variability of L. monocytogenes counts with the IBM/microenvironmental approach was consistent with the observed one. Contrasting situations corresponding to no growth or highly contaminated foods could be deduced from these models. Moreover, the IBM approach was more effective than the traditional population/macroenvironmental approach to describe the actual bacterial behavior variability. PMID:23872572

  12. Combining individual-based modeling and food microenvironment descriptions to predict the growth of Listeria monocytogenes on smear soft cheese.

    PubMed

    Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie; Augustin, Jean-Christophe

    2013-10-01

    An individual-based modeling (IBM) approach was developed to describe the behavior of a few Listeria monocytogenes cells contaminating smear soft cheese surface. The IBM approach consisted of assessing the stochastic individual behaviors of cells on cheese surfaces and knowing the characteristics of their surrounding microenvironments. We used a microelectrode for pH measurements and micro-osmolality to assess the water activity of cheese microsamples. These measurements revealed a high variability of microscale pH compared to that of macroscale pH. A model describing the increase in pH from approximately 5.0 to more than 7.0 during ripening was developed. The spatial variability of the cheese surface characterized by an increasing pH with radius and higher pH on crests compared to that of hollows on cheese rind was also modeled. The microscale water activity ranged from approximately 0.96 to 0.98 and was stable during ripening. The spatial variability on cheese surfaces was low compared to between-cheese variability. Models describing the microscale variability of cheese characteristics were combined with the IBM approach to simulate the stochastic growth of L. monocytogenes on cheese, and these simulations were compared to bacterial counts obtained from irradiated cheeses artificially contaminated at different ripening stages. The simulated variability of L. monocytogenes counts with the IBM/microenvironmental approach was consistent with the observed one. Contrasting situations corresponding to no growth or highly contaminated foods could be deduced from these models. Moreover, the IBM approach was more effective than the traditional population/macroenvironmental approach to describe the actual bacterial behavior variability.

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

    USGS Publications Warehouse

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

    2012-01-01

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

  14. Informed herbivore movement and interplant communication determine the effects of induced resistance in an individual-based model.

    PubMed

    Rubin, Ilan N; Ellner, Stephen P; Kessler, André; Morrell, Kimberly A

    2015-09-01

    1. Plant induced resistance to herbivory affects the spatial distribution of herbivores, as well as their performance. In recent years, theories regarding the benefit to plants of induced resistance have shifted from ideas of optimal resource allocation towards a more eclectic set of theories that consider spatial and temporal plant variability and the spatial distribution of herbivores among plants. However, consensus is lacking on whether induced resistance causes increased herbivore aggregation or increased evenness, as both trends have been experimentally documented. 2. We created a spatial individual-based model that can describe many plant-herbivore systems with induced resistance, in order to analyse how different aspects of induced resistance might affect herbivore distribution, and the total damage to a plant population, during a growing season. 3. We analyse the specific effects on herbivore aggregation of informed herbivore movement (preferential movement to less-damaged plants) and of information transfer between plants about herbivore attacks, in order to identify mechanisms driving both aggregation and evenness. We also investigate how the resulting herbivore distributions affect the total damage to plants and aggregation of damage. 4. Even, random and aggregated herbivore distributions can all occur in our model with induced resistance. Highest levels of aggregation occurred in the models with informed herbivore movement, and the most even distributions occurred when the average number of herbivores per plant was low. With constitutive resistance, only random distributions occur. Damage to plants was spatially correlated, unless plants recover very quickly from damage; herbivore spatial autocorrelation was always weak. 5. Our model and results provide a simple explanation for the apparent conflict between experimental results, indicating that both increased aggregation and increased evenness of herbivores can result from induced resistance. We

  15. An individual based computational model of intestinal crypt fission and its application to predicting unrestrictive growth of the intestinal epithelium.

    PubMed

    Pin, Carmen; Parker, Aimee; Gunning, A Patrick; Ohta, Yuki; Johnson, Ian T; Carding, Simon R; Sato, Toshiro

    2015-02-01

    Intestinal crypt fission is a homeostatic phenomenon, observable in healthy adult mucosa, but which also plays a pathological role as the main mode of growth of some intestinal polyps. Building on our previous individual based model for the small intestinal crypt and on in vitro cultured intestinal organoids, we here model crypt fission as a budding process based on fluid mechanics at the individual cell level and extrapolated predictions for growth of the intestinal epithelium. Budding was always observed in regions of organoids with abundant Paneth cells. Our data support a model in which buds are biomechanically initiated by single stem cells surrounded by Paneth cells which exhibit greater resistance to viscoelastic deformation, a hypothesis supported by atomic force measurements of single cells. Time intervals between consecutive budding events, as simulated by the model and observed in vitro, were 2.84 and 2.62 days, respectively. Predicted cell dynamics was unaffected within the original crypt which retained its full capability of providing cells to the epithelium throughout fission. Mitotic pressure in simulated primary crypts forced upward migration of buds, which simultaneously grew into new protruding crypts at a rate equal to 1.03 days(-1) in simulations and 0.99 days(-1) in cultured organoids. Simulated crypts reached their final size in 4.6 days, and required 6.2 days to migrate to the top of the primary crypt. The growth of the secondary crypt is independent of its migration along the original crypt. Assuming unrestricted crypt fission and multiple budding events, a maximal growth rate of the intestinal epithelium of 0.10 days(-1) is predicted and thus approximately 22 days are required for a 10-fold increase of polyp size. These predictions are in agreement with the time reported to develop macroscopic adenomas in mice after loss of Apc in intestinal stem cells.

  16. The Dynamics of Avian Influenza: Individual-Based Model with Intervention Strategies in Traditional Trade Networks in Phitsanulok Province, Thailand

    PubMed Central

    Wilasang, Chaiwat; Wiratsudakul, Anuwat; Chadsuthi, Sudarat

    2016-01-01

    Avian influenza virus subtype H5N1 is endemic to Southeast Asia. In Thailand, avian influenza viruses continue to cause large poultry stock losses. The spread of the disease has a serious impact on poultry production especially among rural households with backyard chickens. The movements and activities of chicken traders result in the spread of the disease through traditional trade networks. In this study, we investigate the dynamics of avian influenza in the traditional trade network in Phitsanulok Province, Thailand. We also propose an individual-based model with intervention strategies to control the spread of the disease. We found that the dynamics of the disease mainly depend on the transmission probability and the virus inactivation period. This study also illustrates the appropriate virus disinfection period and the target for intervention strategies on traditional trade network. The results suggest that good hygiene and cleanliness among household traders and trader of trader areas and ensuring that any equipment used is clean can lead to a decrease in transmission and final epidemic size. These results may be useful to epidemiologists, researchers, and relevant authorities in understanding the spread of avian influenza through traditional trade networks. PMID:27110273

  17. Exploring the lag phase and growth initiation of a yeast culture by means of an individual-based model.

    PubMed

    Ginovart, Marta; Prats, Clara; Portell, Xavier; Silbert, Moises

    2011-06-01

    The performance of fermentation processes is greatly influenced by the size and quality of inocula. The characterization of the replicative age is decided by the number of birth scars each yeast exhibits on its cellular membrane. Yeast ageing and inoculum size are factors that affect industrial fermentation, particularly those processes in which the yeast cells are reused such as the production of beer. This process reuses yeast cropped at the end of one fermentation in the following one, in a process called "serial repitching". The aim of this study was to explore the effects of inoculum size and ageing on the first stages of the dynamics of yeast population growth. However, only Individual-based Models (IbMs) allow the study of small, well-characterized, microbial inocula. We used INDISIM-YEAST, based on the generic IbM simulator INDISIM, to carry out these studies. Several simulations were performed to analyze the effect of the inoculum size and genealogical age of the cells that made it up on the lag phase, first division time and specific growth rate. The shortest lag phase and time to the first division were obtained with largest inocula and with the youngest inoculated parent cells. Copyright © 2010 Elsevier Ltd. All rights reserved.

  18. Effect of EPS on biofilm structure and function as revealed by an individual-based model of biofilm growth.

    PubMed

    Kreft, J U; Wimpenny, J W

    2001-01-01

    We have simulated a nitrifying biofilm with one ammonia and one nitrite oxidising species in order to elucidate the effect of various extracellular polymeric substance (EPS) production scenarios on biofilm structure and function. The individual-based model (IbM) BacSim simulates diffusion of all substrates on a two-dimensional lattice. Each bacterium is individually simulated as a sphere of given size in a continuous, three-dimensional space. EPS production kinetics was described by a growth rate dependent and an independent term (Leudeking-Piret equation). The structure of the biofilm was dramatically influenced by EPS production or capsule formation. EPS production decreased growth of producers and stimulated growth of non-producers because of the energy cost involved. For the same reason, EPS accumulation can fall as its rate of production increases. The patchiness and roughness of the biofilm decreased and the porosity increased due to EPS production. EPS density was maximal in the middle of the vertical profile. Introduction of binding forces between like cells increased clustering.

  19. The Dynamics of Avian Influenza: Individual-Based Model with Intervention Strategies in Traditional Trade Networks in Phitsanulok Province, Thailand.

    PubMed

    Wilasang, Chaiwat; Wiratsudakul, Anuwat; Chadsuthi, Sudarat

    2016-01-01

    Avian influenza virus subtype H5N1 is endemic to Southeast Asia. In Thailand, avian influenza viruses continue to cause large poultry stock losses. The spread of the disease has a serious impact on poultry production especially among rural households with backyard chickens. The movements and activities of chicken traders result in the spread of the disease through traditional trade networks. In this study, we investigate the dynamics of avian influenza in the traditional trade network in Phitsanulok Province, Thailand. We also propose an individual-based model with intervention strategies to control the spread of the disease. We found that the dynamics of the disease mainly depend on the transmission probability and the virus inactivation period. This study also illustrates the appropriate virus disinfection period and the target for intervention strategies on traditional trade network. The results suggest that good hygiene and cleanliness among household traders and trader of trader areas and ensuring that any equipment used is clean can lead to a decrease in transmission and final epidemic size. These results may be useful to epidemiologists, researchers, and relevant authorities in understanding the spread of avian influenza through traditional trade networks.

  20. How will predicted land-use change affect waterfowl spring stopover ecology? Inferences from an individual-based model

    USGS Publications Warehouse

    Beatty, William; Kesler, Dylan C.; Webb, Elisabeth B.; Naylor, Luke W.; Raedeke, Andrew H.; Humburg, Dale D.; Coluccy, John M.; Soulliere, Gregory J.

    2016-01-01

    Habitat loss, habitat fragmentation, overexploitation and climate change pose familiar and new challenges to conserving natural populations throughout the world. One approach conservation planners may use to evaluate the effects of these challenges on wildlife populations is scenario planning.We developed an individual-based model to evaluate the effects of future land use and land cover changes on spring-migrating dabbling ducks in North America. We assessed the effects of three Intergovernmental Panel on Climate Change emission scenarios (A1B, A2 and B1) on dabbling duck stopover duration, movement distances and mortality. We specifically focused on migration stopover duration because previous research has demonstrated that individuals arriving earlier on the nesting grounds exhibit increased reproductive fitness.Compared to present conditions, all three scenarios increased stopover duration and movement distances of agent ducks.Although all three scenarios presented migrating ducks with increased amounts of wetland habitat, scenarios also contained substantially less cropland, which decreased overall carrying capacity of the study area.Synthesis and applications. Land-use change may increase waterfowl spring migration stopover duration in the midcontinent region of North America due to reduced landscape energetic carrying capacity. Climate change will alter spatial patterns of crop distributions with corn and rice production areas shifting to different regions. Thus, conservation planners will have to address population-level energetic implications of shifting agricultural food resources and increased uncertainty in yearly precipitation patterns within the next 50 years.

  1. Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

    NASA Astrophysics Data System (ADS)

    Govind, Ajit; Chen, Jing Ming; Ju, Weimin

    2009-06-01

    Ecosystem models that simulate biogeochemical processes usually ignore hydrological controls that govern them. It is quite possible that topographically driven water fluxes significantly influence the spatial distribution of C sources and sinks because of their large contribution to the local water balance. To investigate this, we simulated biogeochemical processes along with the associated feedback mechanisms in a boreal ecosystem using a spatially explicit hydroecological model, boreal ecosystem productivity simulator (BEPS)-TerrainLab V2.0, that has a tight coupling of ecophysiological, hydrological, and biogeochemical processes. First, the simulated dynamics of snowpack, soil temperature, net ecosystem productivity (NEP), and total ecosystem respiration (TER) were validated with high-frequency measurements for 2 years. The model was able to explain 80% of the variability in NEP and 84% of the variability in TER. Further, we investigated the influence of topographically driven subsurface base flow on soil C and N cycling and on the spatiotemporal patterns of C sources and sinks using three hydrological modeling scenarios that differed in hydrological conceptualizations. In general, the scenarios that had nonexplicit hydrological representation overestimated NEP, as opposed to the scenario that had an explicit (realistic) representation. The key processes controlling the NEP differences were attributed to the combined effects of variations in photosynthesis (due to changes in stomatal conductance and nitrogen (N) availability), heterotrophic respiration, and autotrophic respiration, all of which occur simultaneously affecting NEP. Feedback relationships were also found to exacerbate the differences. We identified six types of NEP differences (biases), of which the most commonly found was due to an underestimation of the existing C sources, highlighting the vulnerability of regional-scale ecosystem models that ignore hydrological processes.

  2. Quantifying multiple telecouplings using an integrated suite of spatially-explicit tools

    NASA Astrophysics Data System (ADS)

    Tonini, F.; Liu, J.

    2016-12-01

    Telecoupling is an interdisciplinary research umbrella concept that enables natural and social scientists to understand and generate information for managing how humans and nature can sustainably coexist worldwide. To systematically study telecoupling, it is essential to build a comprehensive set of spatially-explicit tools for describing and quantifying multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we introduce the Telecoupling Toolbox, a new free and open-source set of tools developed to map and identify the five major interrelated components of the telecoupling framework: systems, flows, agents, causes, and effects. The modular design of the toolbox allows the integration of existing tools and software (e.g. InVEST) to assess synergies and tradeoffs associated with policies and other local to global interventions. We show applications of the toolbox using a number of representative studies that address a variety of scientific and management issues related to telecouplings throughout the world. The results suggest that the toolbox can thoroughly map and quantify multiple telecouplings under various contexts while providing users with an easy-to-use interface. It provides a powerful platform to address globally important issues, such as land use and land cover change, species invasion, migration, flows of ecosystem services, and international trade of goods and products.

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

    NASA Astrophysics Data System (ADS)

    Moreno, Adam; Neumann, Mathias; Hasenauer, Hubert

    2015-04-01

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

  4. Application of an individual-based model with real data for transportation mode and location to pandemic influenza.

    PubMed

    Ohkusa, Yasushi; Sugawara, Tamie

    2007-12-01

    Currently, an individual-based model is a basic tool for creating a plan to prepare for the outbreak of pandemic influenza. However, even if we can construct the model as finely as possible, it cannot mimic the real world precisely. Therefore, we should use real data for transportation modes and locations, and simulate the diffusion of an infectious disease into that real data. In the present study, we obtained data on the transportation modes and locations of 0.88 million persons a day in the Tokyo metropolitan area. First, we defined the location of all individuals in the data set every 6 min. Second, we determined how many people they came in contact with in their household, in each area, and on the train, and then we assumed that a certain percentage of those contacted would become infected and transmit the disease. Data for natural history and other parameters were taken from previous research. The average number of contacts in each area was 51 748 (95% confidence intervals [CI],46 846-56 650]), at home it was 246 (95% CI, 232-260), and on the train it was 91 (95% CI, 81-101). The number of newly infected people was estimated to be 3032 on day 7 and 126 951 on day 10. The geographic diffusion on day 7, the day when the earliest response would have started, expanded to the whole of the Tokyo metropolitan area. We were able to realize the speed and geographic spread of infection with the highest reality. Therefore, we can use this model for making preparedness plans.

  5. Amazon Forest Response to Changes in Rainfall Regime: Results from an Individual-Based Dynamic Vegetation Model

    NASA Astrophysics Data System (ADS)

    Longo, Marcos

    The Amazon is the largest tropical rainforest in the world, and thus plays a major role on global water, energy, and carbon cycles. However, it is still unknown how the Amazon forest will respond to the ongoing changes in climate, especially droughts, which are expected to become more frequent. To help answering this question, in this thesis I developed and improved the representation of biophysical processes and photosynthesis in the Ecosystem Demography model (ED-2.2), an individual-based land ecosystem model. I also evaluated the model biophysics against multiple data sets for multiple forest and savannah sites in tropical South America. Results of this comparison showed that ED-2.2 is able to represent the radiation and water cycles, but exaggerates heterotrophic respiration seasonality. Also, the model generally predicted correct distribution of biomass across different areas, although it overestimated biomass in subtropical savannahs. To evaluate the forest resilience to droughts, I used ED-2.2 to simulate the plant community dynamics at two sites in Eastern Amazonia, and developed scenarios by resampling observed annual rainfall but increasing the probability of selecting dry years. While the model predicted little response at French Guiana, results at the mid-Eastern Amazonia site indicated substantial biomass loss at modest rainfall reductions. Also, the response to drier climate varied within the plant community, with evergreen, early-successional, and larger trees being the most susceptible. The model also suggests that competition for water during prolonged periods of drought caused the largest impact on larger trees, when insufficient wet season rainfall did not recharge deeper soil layers. Finally, results suggested that a decrease in return period of long-lasting droughts could prevent ecosystem recovery. Using different rainfall datasets, I defined vulnerability based on the change in climate needed to reduce the return period of long droughts. The

  6. Integrating distributional, spatial prioritization, and individual-based models to evaluate potential critical habitat networks: A case study using the Northern Spotted Owl

    EPA Science Inventory

    As part of the northern spotted owl recovery planning effort, we evaluated a series of alternative critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individual-based population model (HexSim). With this suite ...

  7. Integrating distributional, spatial prioritization, and individual-based models to evaluate potential critical habitat networks: A case study using the Northern Spotted Owl

    EPA Science Inventory

    As part of the northern spotted owl recovery planning effort, we evaluated a series of alternative critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individual-based population model (HexSim). With this suite ...

  8. Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015).

    PubMed

    Willem, Lander; Verelst, Frederik; Bilcke, Joke; Hens, Niel; Beutels, Philippe

    2017-09-11

    Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines. We systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening. We identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but

  9. Cost-Utility of Quadrivalent Versus Trivalent Influenza Vaccine in Germany, Using an Individual-Based Dynamic Transmission Model.

    PubMed

    Dolk, Christiaan; Eichner, Martin; Welte, Robert; Anastassopoulou, Anastassia; Van Bellinghen, Laure-Anne; Poulsen Nautrup, Barbara; Van Vlaenderen, Ilse; Schmidt-Ott, Ruprecht; Schwehm, Markus; Postma, Maarten

    2016-12-01

    Seasonal influenza infection is primarily caused by circulation of two influenza A strain subtypes and strains from two B lineages that vary each year. Trivalent influenza vaccine (TIV) contains only one of the two B-lineage strains, resulting in mismatches between vaccine strains and the predominant circulating B lineage. Quadrivalent influenza vaccine (QIV) includes both B-lineage strains. The objective was to estimate the cost-utility of introducing QIV to replace TIV in Germany. An individual-based dynamic transmission model (4Flu) using German data was used to provide realistic estimates of the impact of TIV and QIV on age-specific influenza infections. Cases were linked to health and economic outcomes to calculate the cost-utility of QIV versus TIV, from both a societal and payer perspective. Costs and effects were discounted at 3.0 and 1.5 % respectively, with 2014 as the base year. Univariate and probabilistic sensitivity analyses were conducted. Using QIV instead of TIV resulted in additional quality-adjusted life-years (QALYs) and cost savings from the societal perspective (i.e. it represents the dominant strategy) and an incremental cost-utility ratio (ICUR) of €14,461 per QALY from a healthcare payer perspective. In all univariate analyses, QIV remained cost-effective (ICUR <€50,000). In probabilistic sensitivity analyses, QIV was cost-effective in >98 and >99 % of the simulations from the societal and payer perspective, respectively. This analysis suggests that QIV in Germany would provide additional health gains while being cost-saving to society or costing €14,461 per QALY gained from the healthcare payer perspective, compared with TIV.

  10. A community model of ciliate Tetrahymena and bacteria E. coli. Part 1: Individual-based models of Tetrahymena and E. coli populations

    SciTech Connect

    Jaworska, J.S.; Hallam, T.G.; Schultz, T.W.

    1996-03-01

    The dynamics of a microbial community consisting of a eucaryotic ciliate Tetrahymena pyriformis and procaryotic. Escherichia coli in a batch culture is explored by employing an individual-based approach. In this portion of the article, Part 1, population models are presented. Because both models are individual-based, models of individual organisms are developed prior to construction of the population models. The individual models use an energy budget method in which growth depends on energy gain from feeding and energy sinks such as maintenance and reproduction. These models are not limited by simplifying assumptions about constant yield, constant energy sinks and Monod growth kinetics as are traditional models of microbial organisms. Population models are generated from individual models by creating distinct individual types and assigning to each type the number of real individuals they represent. A population is a compilation of individual types that vary in a phase of cell cycle and physiological parameters such as filtering rate for ciliates and maximum anabolic rate for bacteria. An advantage of the developed models is that they realistically describe the growth of the individual cells feeding on resource which varies in density and composition. Part 2, the core of the project, integrates models into a dynamic microbial community and provides model analysis based upon available data.

  11. Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia

    NASA Astrophysics Data System (ADS)

    Graham, Victoria; Laurance, Susan G.; Grech, Alana; Venter, Oscar

    2017-04-01

    Carbon emissions from the conversion and degradation of tropical forests contribute to anthropogenic climate change. Implementing programs to reduce emissions from tropical forest loss in Southeast Asia are perceived to be expensive due to high opportunity costs of avoided deforestation. However, these costs are not representative of all REDD+ opportunities as they are typically based on average costs across large land areas and are primarily for reducing deforestation from oil palm or pulp concessions. As mitigation costs and carbon benefits can vary according to site characteristics, spatially-explicit information should be used to assess cost-effectiveness and to guide the allocation of scarce REDD+ resources. We analyzed the cost-effectiveness of the following REDD+ strategies in Indonesia, one of the world’s largest sources of carbon emissions from deforestation: halting additional deforestation in protected areas, timber and oil palm concessions, reforesting degraded land and employing reduced-impact logging techniques in logging concessions. We discover that when spatial variation in costs and benefits is considered, low-cost options emerged even for the two most expensive strategies: protecting forests from conversion to oil palm and timber plantations. To achieve a low emissions reduction target of 25%, we suggest funding should target deforestation in protected areas, and oil palm and timber concessions to maximize emissions reductions at the lowest cumulative cost. Low-cost opportunities for reducing emissions from oil palm are where concessions have been granted on deep peat deposits or unproductive land. To achieve a high emissions reduction target of 75%, funding is allocated across all strategies, emphasizing that no single strategy can reduce emissions cost-effectively across all of Indonesia. These findings demonstrate that by using a spatially-targeted approach to identify high priority locations for reducing emissions from deforestation and

  12. Spatially Explicit Analysis of Metal Transfer to Biota: Influence of Soil Contamination and Landscape

    PubMed Central

    Fritsch, Clémentine; Cœurdassier, Michaël; Giraudoux, Patrick; Raoul, Francis; Douay, Francis; Rieffel, Dominique; de Vaufleury, Annette; Scheifler, Renaud

    2011-01-01

    Concepts and developments for a new field in ecotoxicology, referred to as “landscape ecotoxicology,” were proposed in the 1990s; however, to date, few studies have been developed in this emergent field. In fact, there is a strong interest in developing this area, both for renewing the concepts and tools used in ecotoxicology as well as for responding to practical issues, such as risk assessment. The aim of this study was to investigate the spatial heterogeneity of metal bioaccumulation in animals in order to identify the role of spatially explicit factors, such as landscape as well as total and extractable metal concentrations in soils. Over a smelter-impacted area, we studied the accumulation of trace metals (TMs: Cd, Pb and Zn) in invertebrates (the grove snail Cepaea sp and the glass snail Oxychilus draparnaudi) and vertebrates (the bank vole Myodes glareolus and the greater white-toothed shrew Crocidura russula). Total and CaCl2-extractable concentrations of TMs were measured in soils from woody patches where the animals were captured. TM concentrations in animals exhibited a high spatial heterogeneity. They increased with soil pollution and were better explained by total rather than CaCl2-extractable TM concentrations, except in Cepaea sp. TM levels in animals and their variations along the pollution gradient were modulated by the landscape, and this influence was species and metal specific. Median soil metal concentrations (predicted by universal kriging) were calculated in buffers of increasing size and were related to bioaccumulation. The spatial scale at which TM concentrations in animals and soils showed the strongest correlations varied between metals, species and landscapes. The potential underlying mechanisms of landscape influence (community functioning, behaviour, etc.) are discussed. Present results highlight the need for the further development of landscape ecotoxicology and multi-scale approaches, which would enhance our understanding of

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

  14. Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

    PubMed

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

    2014-01-01

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

  15. Life history and biogeography of Calanus copepods in the Arctic Ocean: An individual-based modeling study

    NASA Astrophysics Data System (ADS)

    Ji, Rubao; Ashjian, Carin J.; Campbell, Robert G.; Chen, Changsheng; Gao, Guoping; Davis, Cabell S.; Cowles, Geoffrey W.; Beardsley, Robert C.

    2012-04-01

    Calanus spp. copepods play a key role in the Arctic pelagic ecosystem. Among four congeneric species of Calanus found in the Arctic Ocean and its marginal seas, two are expatriates in the Arctic (Calanus finmarchicus and Calanus marshallae) and two are endemic (Calanus glacialis and Calanus hyperboreus). The biogeography of these species likely is controlled by the interactions of their life history traits and physical environment. A mechanistic understanding of these interactions is critical to predicting their future responses to a warming environment. Using a 3-D individual-based model that incorporates temperature-dependent and, for some cases, food-dependent development rates, we show that (1) C. finmarchicus and C. marshallae are unable to penetrate, survive, and colonize the Arctic Ocean under present conditions of temperature, food availability, and length of the growth season, mainly due to insufficient time to reach their diapausing stage and slow transport of the copepods into the Arctic Ocean during the growing season or even during the following winter at the depths the copepods are believed to diapause. (2) For the two endemic species, the model suggests that their capability of diapausing at earlier copepodite stages and utilizing ice-algae as a food source (thus prolonging the growth season length) contribute to the population sustainability in the Arctic Ocean. (3) The inability of C. hyperboreus to attain their first diapause stage in the central Arctic, as demonstrated by the model, suggests that the central Arctic population may be advected from the surrounding shelf regions along with multi-year successive development and diapausing, and/or our current estimation of the growth parameters and the growth season length (based on empirical assessment or literature) needs to be further evaluated. Increasing the length of the growth season or increasing water temperature by 2 °C, and therefore increasing development rates, greatly increased the area

  16. A Small Community Model for the Transmission of Infectious Diseases: Comparison of School Closure as an Intervention in Individual-Based Models of an Influenza Pandemic

    PubMed Central

    Milne, George J.; Kelso, Joel K.; Kelly, Heath A.; Huband, Simon T.; McVernon, Jodie

    2008-01-01

    Background In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic. Method We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world. Results We showed that published individual based models estimate similar final attack rates over a range of values for R0 in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R0 values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure. Conclusion Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined. PMID:19104659

  17. A web-tool to find spatially explicit climate-smart solutions for the sector agriculture

    NASA Astrophysics Data System (ADS)

    Verzandvoort, Simone; Kuikman, Peter; Walvoort, Dennis

    2017-04-01

    Europe faces the challenge to produce more food and more biomass for the bio-economy, to adapt its agricultural sector to negative consequences of climate change, and to reduce greenhouse gas emissions from agriculture. Climate-smart agriculture (CSA) solutions and technologies improve agriculture's productivity and provide economic growth and stability, increase resilience, and help to reduce GHG emissions from agricultural activities. The Climate Smart Agriculture Booster (CSAb) (http://csabooster.climate-kic.org/) is a Flagship Program under Climate-KIC, aiming to facilitate the adoption of CSA solutions and technologies in the European agro-food sector. This adoption requires spatially explicit, contextual information on farming activities and risks and opportunities related to climate change in regions across Europe. Other spatial information supporting adoption includes Information on where successful implementations were already done, on where CSA would profit from enabling policy conditions, and where markets or business opportunities for selling or purchasing technology and knowledge are located or emerging. The Spatial Solution Finder is a web-based spatial tool aiming to help agri-food companies (supply and processing), authorities or agricultural organisations find CSA solutions and technologies that fit local farmers and regions, and to demonstrate examples of successful implementations as well as expected impact at the farm and regional level. The tool is based on state of the art (geo)datasets of environmental and socio-economic conditions (partly open access, partly derived from previous research) and open source web-technology. The philosophy of the tool is that combining existing datasets with contextual information on the region of interest with personalized information entered by the user provides a suitable basis for offering a basket of options for CSA solutions and technologies. Solutions and technologies are recommended to the user based on

  18. Effects of streamflow diversion on a fish population: combining empirical data and individual-based models in a site-specific evaluation

    Treesearch

    Bret C. Harvey; Jason L. White; Rodney J. Nakamoto; Steven F. Railsback

    2014-01-01

    Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The...

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  20. An individual-based modeling approach to spawning-potential per-recruit models: An application to blue crab (Callinectes sapidus) in Chesapeake Bay

    USGS Publications Warehouse

    Bunnell, D.B.; Miller, T.J.

    2005-01-01

    An individual-based modeling approach to estimate biological reference points for blue crabs (Callinectes sapidus) in Chesapeake Bay offered several advantages over conventional models: (i) known individual variation in size and growth rate could be incorporated, (ii) the underlying discontinuous growth pattern could be simulated, and (iii) the complexity of the fishery, where vulnerability is based on size, shell status (e.g., soft, hard), maturity, and sex could be accommodated. Across a range of natural mortality (M) scenarios (0.375-1.2??year-1), we determined the exploitation fraction (??) and fishing mortality (F) that protected 20% of the spawning potential of an unfished population, the current target. As M increased, ??20% and F-20% decreased. Assuming that M = 0.9??year-1, our models estimated ??20% = 0.45, which is greater than field-based estimates of ?? in 64% of the years since 1990. Hence, the commercial fishery has likely contributed to the recent population decline in Chesapeake Bay. Comparisons of our results with conventional per-recruit approaches indicated that incorporating the complexity of the fishery was the most important advantage in our individual-based modeling approach. ?? 2005 NRC.

  1. Spatially Explicit Observations Elucidate Simple Scalars of Forest Canopy Transpiration Along Moisture Gradients in Semi-Arid and Humid Climates

    NASA Astrophysics Data System (ADS)

    Mackay, D. S.; Loranty, M. M.; Adelman, J. D.; Ewers, B. E.; Kruger, E. L.

    2004-12-01

    The ability to scale from point measurements to watersheds is critical for making predictions in hydrology. Assumptions are often made that averaging point measurements and scaling them up using a cookie-cutter or paint-by-numbers approach will capture relevant spatial gradients. Two issues are whether such assumptions are valid and how these assumptions hold across environmental conditions. We made spatially explicit measurements and modeling at two field sites representing semi-arid and humid climates. For our semi-arid site we identified a topography-soil moisture gradient in an alpine watershed near Laramie, Wyoming. For our humid climate we chose a wetland-to-upland gradient in the Chequamegon National Forest near Park Falls, Wisconsin. At both sites we used cyclic sampling designs to efficiently quantify spatial trends using geostatistics. Spatial data was collected for sap flux using Granier type sensors. In addition, we collected spatial soil moisture, vapor pressure deficit, and leaf area index with the same level of spatial detail, at both study sites. At the Wyoming site our dominant species was Lodgepole pine, as it spans most of the topography-soil gradients from the edges of riparian areas to upslope positions. At the Wisconsin site we selected aspen as our focus species, as it is a dominant species in terms of transpiration in the region and it grows over a wide variation in topographic positions from wetland to upland. We found that the semivariagrams of soil moisture at both sites showed ranges of about 110 meters on low soil moisture days and 80 meters on high soil moisture days. Neither site showed differences in sap flux per unit xylem along soil moisture gradients. However, once we scaled the sap flux measurements to the whole tree using basal area, we found that the semi-arid site had much higher fluxes near the stream compared to upslope, but at the humid site the uplands had much higher scaled sap fluxes than the wetlands. It appears that

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

    NASA Astrophysics Data System (ADS)

    Berkhoff, K.

    2008-01-01

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

  3. SPATIAL EXPLICIT POPULATION MODELS FOR RISK ASSESSMENT: COMMON LOONS AND MERCURY AS A CASE STUDY

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  5. EVALUATING HABITAT AS A SURROGATE FOR POPULATION VIABILITY USING A SPATIALLY EXPLICIT POPULATION MODEL

    EPA Science Inventory

    Because data for conservation planning are always limited, surrogates are often substituted for intractable measurements such as species richness or population viability. We examined the ability of habitat quality to act as a surrogate for population performance for both Red-sho...

  6. COMPARING ECOLOGICALLY SCALED LANDSCAPE INDICES WITH A SPATIALLY EXPLICIT POPULATION MODEL

    EPA Science Inventory

    Vos et al. (2001) proposed a class of landscape indices they called ecologically scaled. By this they meant that the indices incorporate species-specific characteristics that are assumed to be important for population viability. I used their two ideas of species carrying capaci...

  7. COMPARING ECOLOGICALLY SCALED LANDSCAPE INDICES WITH A SPATIALLY EXPLICIT POPULATION MODEL

    EPA Science Inventory

    Vos et al. (2001) proposed a class of landscape indices they called ecologically scaled. By this they meant that the indices incorporate species-specific characteristics that are assumed to be important for population viability. I used their two ideas of species carrying capaci...

  8. EVALUATING HABITAT AS A SURROGATE FOR POPULATION VIABILITY USING A SPATIALLY EXPLICIT POPULATION MODEL

    EPA Science Inventory

    Because data for conservation planning are always limited, surrogates are often substituted for intractable measurements such as species richness or population viability. We examined the ability of habitat quality to act as a surrogate for population performance for both Red-sho...

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

    USDA-ARS?s Scientific Manuscript database

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

  10. EVALUATING SPATIALLY EXPLICIT METRICS OF STREAM ENERGY GRADIENTS USING HYDRODYNAMIC MODEL SIMULATIONS. (R825760)

    EPA Science Inventory

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

  11. Comparison of individual-based model output to data using a model of walleye pollock early life history in the Gulf of Alaska

    NASA Astrophysics Data System (ADS)

    Hinckley, Sarah; Parada, Carolina; Horne, John K.; Mazur, Michael; Woillez, Mathieu

    2016-10-01

    Biophysical individual-based models (IBMs) have been used to study aspects of early life history of marine fishes such as recruitment, connectivity of spawning and nursery areas, and marine reserve design. However, there is no consistent approach to validating the spatial outputs of these models. In this study, we hope to rectify this gap. We document additions to an existing individual-based biophysical model for Alaska walleye pollock (Gadus chalcogrammus), some simulations made with this model and methods that were used to describe and compare spatial output of the model versus field data derived from ichthyoplankton surveys in the Gulf of Alaska. We used visual methods (e.g. distributional centroids with directional ellipses), several indices (such as a Normalized Difference Index (NDI), and an Overlap Coefficient (OC), and several statistical methods: the Syrjala method, the Getis-Ord Gi* statistic, and a geostatistical method for comparing spatial indices. We assess the utility of these different methods in analyzing spatial output and comparing model output to data, and give recommendations for their appropriate use. Visual methods are useful for initial comparisons of model and data distributions. Metrics such as the NDI and OC give useful measures of co-location and overlap, but care must be taken in discretizing the fields into bins. The Getis-Ord Gi* statistic is useful to determine the patchiness of the fields. The Syrjala method is an easily implemented statistical measure of the difference between the fields, but does not give information on the details of the distributions. Finally, the geostatistical comparison of spatial indices gives good information of details of the distributions and whether they differ significantly between the model and the data. We conclude that each technique gives quite different information about the model-data distribution comparison, and that some are easy to apply and some more complex. We also give recommendations for

  12. Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach.

    PubMed

    Gaisberger, Hannes; Kindt, Roeland; Loo, Judy; Schmidt, Marco; Bognounou, Fidèle; Da, Sié Sylvestre; Diallo, Ousmane Boukary; Ganaba, Souleymane; Gnoumou, Assan; Lompo, Djingdia; Lykke, Anne Mette; Mbayngone, Elisée; Nacoulma, Blandine Marie Ivette; Ouedraogo, Moussa; Ouédraogo, Oumarou; Parkouda, Charles; Porembski, Stefan; Savadogo, Patrice; Thiombiano, Adjima; Zerbo, Guibien; Vinceti, Barbara

    2017-01-01

    Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana) and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change). We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs), climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as 'highly threatened' due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted regeneration in the

  13. Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach

    PubMed Central

    Kindt, Roeland; Loo, Judy; Schmidt, Marco; Bognounou, Fidèle; Da, Sié Sylvestre; Diallo, Ousmane Boukary; Ganaba, Souleymane; Gnoumou, Assan; Lompo, Djingdia; Lykke, Anne Mette; Mbayngone, Elisée; Nacoulma, Blandine Marie Ivette; Ouedraogo, Moussa; Ouédraogo, Oumarou; Parkouda, Charles; Porembski, Stefan; Savadogo, Patrice; Thiombiano, Adjima; Zerbo, Guibien; Vinceti, Barbara

    2017-01-01

    Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa,