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Sample records for spatially explicit metapopulations

  1. 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

  2. Generalizing Levins metapopulation model in explicit space: models of intermediate complexity.

    PubMed

    Roy, Manojit; Harding, Karin; Holt, Robert D

    2008-11-07

    A recent study [Harding and McNamara, 2002. A unifying framework for metapopulation dynamics. Am. Nat. 160, 173-185] presented a unifying framework for the classic Levins metapopulation model by incorporating several realistic biological processes, such as the Allee effect, the Rescue effect and the Anti-rescue effect, via appropriate modifications of the two basic functions of colonization and extinction rates. Here we embed these model extensions on a spatially explicit framework. We consider population dynamics on a regular grid, each site of which represents a patch that is either occupied or empty, and with spatial coupling by neighborhood dispersal. While broad qualitative similarities exist between the spatially explicit models and their spatially implicit (mean-field) counterparts, there are also important differences that result from the details of local processes. Because of localized dispersal, spatial correlation develops among the dynamics of neighboring populations that decays with distance between patches. The extent of this correlation at equilibrium differs among the metapopulation types, depending on which processes prevail in the colonization and extinction dynamics. These differences among dynamical processes become manifest in the spatial pattern and distribution of "clusters" of occupied patches. Moreover, metapopulation dynamics along a smooth gradient of habitat availability show significant differences in the spatial pattern at the range limit. The relevance of these results to the dynamics of disease spread in metapopulations is discussed.

  3. Metapopulations in multifractal landscapes: on the role of spatial aggregation

    PubMed Central

    Gamarra, Javier G.P

    2005-01-01

    The use of fractals in ecology is currently pervasive over many areas. However, very few studies have linked fractal properties of landscapes to generating ecological mechanisms and dynamics. In this study I show that lacunarity (a measure of the landscape texture) is a well suited ecologically scaled landscape index that can be explicitly incorporated in metapopulation models such as the classical Levins equation. I show that the average lacunarity of an aggregated landscape is linearly correlated to the habitat that a species with local spatial processed information may perceive. Lacunarity is a computationally feasible index to measure, and is related to the metapopulation capacity of landscapes. A general approach to multifractal landscapes has been conceived, and some analytical results for self-similar landscapes are outlined, including the specific effect of landscape heterogeneity, decoupled from that of contagion by dispersal. Spatially explicit simulations show agreement with the semi-implicit method presented. PMID:16096094

  4. Metapopulations in multifractal landscapes: on the role of spatial aggregation.

    PubMed

    Gamarra, Javier G P

    2005-09-07

    The use of fractals in ecology is currently pervasive over many areas. However, very few studies have linked fractal properties of landscapes to generating ecological mechanisms and dynamics. In this study I show that lacunarity (a measure of the landscape texture) is a well suited ecologically scaled landscape index that can be explicitly incorporated in metapopulation models such as the classical Levins equation. I show that the average lacunarity of an aggregated landscape is linearly correlated to the habitat that a species with local spatial processed information may perceive. Lacunarity is a computationally feasible index to measure, and is related to the metapopulation capacity of landscapes. A general approach to multifractal landscapes has been conceived, and some analytical results for self-similar landscapes are outlined, including the specific effect of landscape heterogeneity, decoupled from that of contagion by dispersal. Spatially explicit simulations show agreement with the semi-implicit method presented.

  5. Dynamics of Adaptation in Spatially Heterogeneous Metapopulations

    PubMed Central

    Papaïx, Julien; David, Olivier; Lannou, Christian; Monod, Hervé

    2013-01-01

    The selection pressure experienced by organisms often varies across the species range. It is hence crucial to characterise the link between environmental spatial heterogeneity and the adaptive dynamics of species or populations. We address this issue by studying the phenotypic evolution of a spatial metapopulation using an adaptive dynamics approach. The singular strategy is found to be the mean of the optimal phenotypes in each habitat with larger weights for habitats present in large and well connected patches. The presence of spatial clusters of habitats in the metapopulation is found to facilitate specialisation and to increase both the level of adaptation and the evolutionary speed of the population when dispersal is limited. By showing that spatial structures are crucial in determining the specialisation level and the evolutionary speed of a population, our results give insight into the influence of spatial heterogeneity on the niche breadth of species. PMID:23424618

  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. Spatial patterns of prisoner's dilemma game in metapopulations.

    PubMed

    Hui, C; Huia, C; McGeoch, M A

    2007-02-01

    Because to defect is the evolutionary stable strategy in the prisoner's dilemma game (PDG), understanding the mechanism generating and maintaining cooperation in PDG, i.e. the paradox of cooperation, has intrinsic significance for understanding social altruism behaviors. Spatial structure serves as the key to this dilemma. Here, we build the model of spatial PDG under a metapopulation framework: the sub-populations of cooperators and defectors obey the rules in spatial PDG as well as the colonization-extinction process of metapopulations. Using the mean-field approximation and the pair approximation, we obtain the differential equations for the dynamics of occupancy and spatial correlation. Cellular automaton is also built to simulate the spatiotemporal dynamics of the spatial PDG in metapopulations. Join-count statistics are used to measure the spatial correlation as well as the spatial association of the metapopulation. Simulation results show that the distribution is self-organized and that it converges to a static boundary due to the boycotting of cooperators to defectors. Metapopulations can survive even when the colonization rate is lower than the extinction rate due to the compensation of cooperation rewards for extinction debt. With a change of parameters in the model, a metapopulation can consist of pure cooperators, pure defectors, or cooperator-defector coexistence. The necessary condition of cooperation evolution is the local colonization of a metapopulation. The spatial correlation between the cooperators tends to be weaker with the increase in the temptation to defect and the habitat connectivity; yet the spatial correlation between defectors becomes stronger. The relationship between spatial structure and the colonization rate is complicated, especially for cooperators. The metapopulation may undergo a temporary period of prosperity just before the extinction, even while the colonization rate is declining.

  9. Metapopulation dynamics and spatial heterogeneity in cancer.

    PubMed

    González-García, Isabel; Solé, Ricard V; Costa, José

    2002-10-01

    With the advent of drugs targeting specific molecular defects in cancerous cells [Gorre, M. E., et al. (2001) Science 293, 876-880], it is important to understand the degree of genetic heterogeneity present in tumor cell populations and the rules that govern microdiversity in human cancer. Here, we first show that populations with different genotypes in genes influencing cell growth and programmed cell death coexist in advanced malignant tumors of the colon, exhibiting microsatellite instability. Detailed, physical mapping of the diverse populations shows them to be arranged in small, intermingling areas, resulting in a variegated pattern of diversity. Using computational modeling of the experimental data, we find that the coexistence between similar competitors is enhanced, instead of deterred, by spatial dynamics [Hanski, I. (1999) Metapopulation Dynamics (Oxford Univ. Press, New York)]. The model suggests a simple and plausible scenario for the generation of spatial heterogeneity during tumor progression. The emergence and persistence of the patterns of diversity encountered in the tumors can be generated without a need to invoke differences in mutation rates, neutrality of interactions, or separated time scales. We posit that the rules that apply to spatial ecology and explain the maintenance of diversity are also at work in tumors and may underlie tumor microheterogeneity.

  10. The emergence of the rescue effect from explicit within- and between-patch dynamics in a metapopulation

    PubMed Central

    Eriksson, Anders; Elías-Wolff, Federico; Mehlig, Bernhard; Manica, Andrea

    2014-01-01

    Immigration can rescue local populations from extinction, helping to stabilize a metapopulation. Local population dynamics is important for determining the strength of this rescue effect, but the mechanistic link between local demographic parameters and the rescue effect at the metapopulation level has received very little attention by modellers. We develop an analytical framework that allows us to describe the emergence of the rescue effect from interacting local stochastic dynamics. We show this framework to be applicable to a wide range of spatial scales, providing a powerful and convenient alternative to individual-based models for making predictions concerning the fate of metapopulations. We show that the rescue effect plays an important role in minimizing the increase in local extinction probability associated with high demographic stochasticity, but its role is more limited in the case of high local environmental stochasticity of recruitment or survival. While most models postulate the rescue effect, our framework provides an explicit mechanistic link between local dynamics and the emergence of the rescue effect, and more generally the stability of the whole metapopulation. PMID:24523274

  11. A spatially structured metapopulation model within a stochastic environment.

    PubMed

    Smith, Andrew G

    2017-09-01

    Populations often exist, either by choice or by external pressure, in a fragmented way, referred to as a metapopulation. Typically, the dynamics accounted for within metapopulation models are assumed to be static. For example, patch occupancy models often assume that the colonisation and extinction rates do not change, while spatially structured models often assume that the rates of births, deaths and migrations do not depend on time. While some progress has been made when these dynamics are changing deterministically, less is known when the changes are stochastic. It can be quite common that the environment a population inhabits determines how these dynamics change over time. Changes to this environment can have a large impact on the survival probability of a population and such changes will often be stochastic. The typical metapopulation model allows for catastrophes that could eradicate most, if not all, individuals on an entire patch. It is this type of phenomenon that this article addresses. A Markov process is developed that models the number of individuals on each patch within a metapopulation. An approximation for the original model is presented in the form of a piecewise-deterministic Markov process and the approximation is analysed to present conditions for extinction. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Spatial variation in disease resistance: from molecules to metapopulations

    PubMed Central

    Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.

    2010-01-01

    Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do

  13. Impact of travel patterns on epidemic dynamics in heterogeneous spatial metapopulation networks

    NASA Astrophysics Data System (ADS)

    Ni, Shunjiang; Weng, Wenguo

    2009-01-01

    We report the results of a series of simulations of a susceptible-infected-recovered epidemic model in heterogeneous spatial metapopulation networks with quantitative knowledge of human traveling statistics that human travel behavior obeys scaling laws in the sense of geographical distance and period of waiting time. By tuning the edge length distribution of the spatial metapopulation network, we can conveniently control the distribution of human travel distance. The simulation results show that the occurrence probability of global outbreaks is significantly dependent on the characteristic travel distance, the characteristic waiting time, and the memory effects of human travel. We also present some preliminary results on the effects of travel restrictions in epidemic control.

  14. Human influence on the spatial structure of threatened Pacific salmon metapopulations.

    PubMed

    Fullerton, Aimee H; Lindley, Steven T; Pess, George R; Feist, Blake E; Steel, E Ashley; McElhany, Paul

    2011-10-01

    To remain viable, populations must be resilient to both natural and human-caused environmental changes. We evaluated anthropogenic effects on spatial connections among populations of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) (designated as threatened under the U.S. Endangered Species Act) in the lower Columbia and Willamette rivers. For several anthropogenic-effects scenarios, we used graph theory to characterize the spatial relation among populations. We plotted variance in population size against connectivity among populations. In our scenarios, reduced habitat quality decreased the size of populations and hydropower dams on rivers led to the extirpation of several populations, both of which decreased connectivity. Operation of fish hatcheries increased connectivity among populations and led to patchy or panmictic populations. On the basis of our results, we believe recolonization of the upper Cowlitz River by fall and spring Chinook and winter steelhead would best restore metapopulation structure to near-historical conditions. Extant populations that would best conserve connectivity would be those inhabiting the Molalla (spring Chinook), lower Cowlitz, or Clackamas (fall Chinook) rivers and the south Santiam (winter steelhead) and north fork Lewis rivers (summer steelhead). Populations in these rivers were putative sources; however, they were not always the most abundant or centrally located populations. This result would not have been obvious if we had not considered relations among populations in a metapopulation context. Our results suggest that dispersal rate strongly controls interactions among the populations that comprise salmon metapopulations. Thus, monitoring efforts could lead to understanding of the true rates at which wild and hatchery fish disperse. Our application of graph theory allowed us to visualize how metapopulation structure might respond to human activity. The method could be easily extended to evaluations of

  15. The influence of spatially and temporally varying oceanographic conditions on meroplanktonic metapopulations

    NASA Astrophysics Data System (ADS)

    Botsford, L. W.; Moloney, C. L.; Hastings, A.; Largier, J. L.; Powell, T. M.; Higgins, K.; Quinn, J. F.

    We synthesize the results of several modelling studies that address the influence of variability in larval transport and survival on the dynamics of marine metapopulations distributed along a coast. Two important benthic invertebrates in the California Current System (CCS), the Dungeness crab and the red sea urchin, are used as examples of the way in which physical oceanographic conditions can influence stability, synchrony and persistence of meroplanktonic metapopulations. We first explore population dynamics of subpopulations and metapopulations. Even without environmental forcing, isolated local subpopulations with density-dependence can vary on time scales roughly twice the generation time at high adult survival, shifting to annual time scales at low survivals. The high frequency behavior is not seen in models of the Dungeness crab, because of their high adult survival rates. Metapopulations with density-dependent recruitment and deterministic larval dispersal fluctuate in an asynchronous fashion. Along the coast, abundance varies on spatial scales which increase with dispersal distance. Coastwide, synchronous, random environmental variability tends to synchronize these metapopulations. Climate change could cause a long-term increase or decrease in mean larval survival, which in this model leads to greater synchrony or extinction respectively. Spatially managed metapopulations of red sea urchins go extinct when distances between harvest refugia become greater than the scale of larval dispersal. All assessments of population dynamics indicate that metapopulation behavior in general dependes critically on the temporal and spatial nature of larval dispersal, which is largely determined by physical oceanographic conditions. We therfore explore physical influences on larval dispersal patterns. Observed trends in temperature and salinity applied to laboratory-determined responses indicate that natural variability in temperature and salinity can lead to variability in

  16. Introducing stage-specific spatial distribution into the Levins metapopulation model

    PubMed Central

    Nakazawa, Takefumi

    2015-01-01

    The Levins model is a classical but still widely used metapopulation model that describes temporal changes in the regional abundance of a species by extinction and colonization of subpopulations. A fundamental assumption of the model is that the landscape is homogeneous and the species moves between identical patches at random. However, this assumption clearly contrasts with the common observation that different stages prefer or require different habitat types. Here I studied a minimum extension of the Levins model in which the species has stage-specific (juvenile and adult) spatial distributions and dispersal occurs at the timing of reproduction and maturation (i.e., ontogenetic habitat shifts). I examined how the persistence of the stage-structured metapopulations would be affected by rescue effect and interspecific competition. The models predict that rates of ontogenetic habitat shifts are particularly crucial for the persistence or coexistence of stage-structured metapopulations because the species need to complete biphasic life cycles. The present study opens a new avenue for exploring stage- and space-structured population dynamics and will contribute to better landscape management for the conservation of stage-structured animals. PMID:25598411

  17. Spatial variation in senescence rates in a bird metapopulation.

    PubMed

    Holand, H; Kvalnes, T; Gamelon, M; Tufto, J; Jensen, H; Pärn, H; Ringsby, T H; Sæther, B-E

    2016-07-01

    Investigating factors which affect the decline in survival with age, i.e. actuarial senescence, is important in order to understand how demographic rates vary in wild populations. Although the evidence for the occurrence of actuarial senescence in wild populations is growing, very few studies have compared actuarial senescence rates between wild populations of the same species. We used data from a long-time study of demography of house sparrows (Passer domesticus) to investigate differences in rates of actuarial senescence between habitats and sub-populations. We also investigated whether rates of actuarial senescence differed between males and females. We found that rates of actuarial senescence showed large spatial variation. We also found that the onset of actuarial senescence varied between sub-populations. However, these differences were not significantly explained by a general difference in habitat type. We also found no significant difference in actuarial senescence rates between males and females. This study shows that senescence rates in natural populations may vary significantly between sub-populations and that failing to account for such differences may give a biased estimate of senescence rates of a species.

  18. Dynamics of range margins for metapopulations under climate change

    PubMed Central

    Anderson, B.J.; Akçakaya, H.R.; Araújo, M.B.; Fordham, D.A.; Martinez-Meyer, E.; Thuiller, W.; Brook, B.W.

    2009-01-01

    We link spatially explicit climate change predictions to a dynamic metapopulation model. Predictions of species' responses to climate change, incorporating metapopulation dynamics and elements of dispersal, allow us to explore the range margin dynamics for two lagomorphs of conservation concern. Although the lagomorphs have very different distribution patterns, shifts at the edge of the range were more pronounced than shifts in the overall metapopulation. For Romerolagus diazi (volcano rabbit), the lower elevation range limit shifted upslope by approximately 700 m. This reduced the area occupied by the metapopulation, as the mountain peak currently lacks suitable vegetation. For Lepus timidus (European mountain hare), we modelled the British metapopulation. Increasing the dispersive estimate caused the metapopulation to shift faster on the northern range margin (leading edge). By contrast, it caused the metapopulation to respond to climate change slower, rather than faster, on the southern range margin (trailing edge). The differential responses of the leading and trailing range margins and the relative sensitivity of range limits to climate change compared with that of the metapopulation centroid have important implications for where conservation monitoring should be targeted. Our study demonstrates the importance and possibility of moving from simple bioclimatic envelope models to second-generation models that incorporate both dynamic climate change and metapopulation dynamics. PMID:19324811

  19. Dynamics of range margins for metapopulations under climate change.

    PubMed

    Anderson, B J; Akçakaya, H R; Araújo, M B; Fordham, D A; Martinez-Meyer, E; Thuiller, W; Brook, B W

    2009-04-22

    We link spatially explicit climate change predictions to a dynamic metapopulation model. Predictions of species' responses to climate change, incorporating metapopulation dynamics and elements of dispersal, allow us to explore the range margin dynamics for two lagomorphs of conservation concern. Although the lagomorphs have very different distribution patterns, shifts at the edge of the range were more pronounced than shifts in the overall metapopulation. For Romerolagus diazi (volcano rabbit), the lower elevation range limit shifted upslope by approximately 700 m. This reduced the area occupied by the metapopulation, as the mountain peak currently lacks suitable vegetation. For Lepus timidus (European mountain hare), we modelled the British metapopulation. Increasing the dispersive estimate caused the metapopulation to shift faster on the northern range margin (leading edge). By contrast, it caused the metapopulation to respond to climate change slower, rather than faster, on the southern range margin (trailing edge). The differential responses of the leading and trailing range margins and the relative sensitivity of range limits to climate change compared with that of the metapopulation centroid have important implications for where conservation monitoring should be targeted. Our study demonstrates the importance and possibility of moving from simple bioclimatic envelope models to second-generation models that incorporate both dynamic climate change and metapopulation dynamics.

  20. 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.

  1. 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

  2. Identifying Spatial Invasion of Pandemics on Metapopulation Networks Via Anatomizing Arrival History.

    PubMed

    Wang, Jian-Bo; Wang, Lin; Li, Xiang

    2016-12-01

    Spatial spread of infectious diseases among populations via the mobility of humans is highly stochastic and heterogeneous. Accurate forecast/mining of the spread process is often hard to be achieved by using statistical or mechanical models. Here we propose a new reverse problem, which aims to identify the stochastically spatial spread process itself from observable information regarding the arrival history of infectious cases in each subpopulation. We solved the problem by developing an efficient optimization algorithm based on dynamical programming, which comprises three procedures: 1) anatomizing the whole spread process among all subpopulations into disjoint componential patches; 2) inferring the most probable invasion pathways underlying each patch via maximum likelihood estimation; and 3) recovering the whole process by assembling the invasion pathways in each patch iteratively, without burdens in parameter calibrations and computer simulations. Based on the entropy theory, we introduced an identifiability measure to assess the difficulty level that an invasion pathway can be identified. Results on both artificial and empirical metapopulation networks show the robust performance in identifying actual invasion pathways driving pandemic spread.

  3. Evolutionary ecology of E. coli metapopulations in patchy landscapes

    NASA Astrophysics Data System (ADS)

    Keymer, Juan

    2006-03-01

    Spatial ecology and metapopulation biology are essential features of natural populations. Extinction of local populations, the colonization of new suitable habitat patches (metapopulation dynamics) as well as the creation and destruction of local habitats (patch dynamics) are basic components of the evolutionary process shaping life-history strategies. As Darwin liked to put it ``the zoology of archipelagoes''. The role of spatial structure have been shown to be important for both, persistence and coexistence. However, the spatial ecology of microbial metapopulations have rarely been observed nor exploited technologically. We use nano and micro fabrication technology to build a spatially explicit (dynamic) landscape of habitat patches (the metapopulation chip) and a (UV) laser-based disturbance regime (patch dynamics). By building upon the theory of metapopulations in dynamic landscapes, we build fitness landscapes by linking patch dynamics to fluorescent patterns coming from molecular markers in the cell culture. We use landscape ecology and metapopulation biology to generate selective forces that can be used for evolutionary design of microorganisms.

  4. Cluster formation in a heterogeneous metapopulation model.

    PubMed

    Silva, Jacques A L

    2016-05-01

    A spatially explicit heterogeneous metapopulation model with two different patch types is analyzed. Some network topologies support a partially synchronized dynamics, a state where two different clusters of patches are formed. Within each cluster the dynamics of all patches are synchronized. The linearized asymptotic stability of the partially synchronized attractor is studied. The transversal stability is analyzed and a simple expression for the transversal Lyapunov number of partially synchronized attractors is obtained.

  5. Applying metapopulation theory to conservation of migratory birds

    USGS Publications Warehouse

    Esler, Daniel N.

    2000-01-01

    Metapopulation theory has proven useful for understanding the population structure and dynamics of many species of conservation concern. The metapopulation concept has been applied almost exclusively to nonmigratory species, however, for which subpopulation demographic independence—a requirement for a classically defined metapopulation - is explicitly related to geographic distribution and dispersal probabilities. Defining the degree of demographic independence among subpopulations of migratory animals, and thus the applicability of metapopulation theory as a conceptual framework for understanding population dynamics, is much more difficult. Unlike nonmigratory species, subpopulations of migratory animals cannot be defined as synonymous with geographic areas. Groups of migratory birds that are geographically separate at one part of the annual cycle may occur together at others, but co-occurrence in time and space does not preclude the demographic independence of subpopulations. I suggest that metapopulation theory can be applied to migratory species but that understanding the degree of subpopulation independence may require information about both spatial distribution throughout the annual cycle and behavioral mechanisms that may lead to subpopulation demographic independence. The key for applying metapopulation theory to migratory animals lies in identifying demographically independent subpopulations, even as they move during the annual cycle and potentially co-occur with other subpopulations. Using examples of migratory bird species, I demonstrate that spatial and temporal modes of subpopulation independence can interact with behavioral mechanisms to create demographically independent subpopulations, including cases in which subpopulations are not spatially distinct in some parts of the annual cycle.

  6. 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.

  7. Identifying critical regions in small-world marine metapopulations.

    PubMed

    Watson, James R; Siegel, David A; Kendall, Bruce E; Mitarai, Satoshi; Rassweiller, Andrew; Gaines, Steven D

    2011-10-25

    The precarious state of many nearshore marine ecosystems has prompted the use of marine protected areas as a tool for management and conservation. However, there remains substantial debate over their design and, in particular, how to best account for the spatial dynamics of nearshore marine species. Many commercially important nearshore marine species are sedentary as adults, with limited home ranges. It is as larvae that they disperse greater distances, traveling with ocean currents sometimes hundreds of kilometers. As a result, these species exist in spatially complex systems of connected subpopulations. Here, we explicitly account for the mutual dependence of subpopulations and approach protected area design in terms of network robustness. Our goal is to characterize the topology of nearshore metapopulation networks and their response to perturbation, and to identify critical subpopulations whose protection would reduce the risk for stock collapse. We define metapopulation networks using realistic estimates of larval dispersal generated from ocean circulation simulations and spatially explicit metapopulation models, and we then explore their robustness using node-removal simulation experiments. Nearshore metapopulations show small-world network properties, and we identify a set of highly connected hub subpopulations whose removal maximally disrupts the metapopulation network. Protecting these subpopulations reduces the risk for systemic failure and stock collapse. Our focus on catastrophe avoidance provides a unique perspective for spatial marine planning and the design of marine protected areas.

  8. 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.

  9. Bottlenecks drive temporal and spatial genetic changes in alpine caddisfly metapopulations.

    PubMed

    Shama, Lisa N S; Kubow, Karen B; Jokela, Jukka; Robinson, Christopher T

    2011-09-27

    Extinction and re-colonisation of local populations is common in ephemeral habitats such as temporary streams. In most cases, such population turnover leads to reduced genetic diversity within populations and increased genetic differentiation among populations due to stochastic founder events, genetic drift, and bottlenecks associated with re-colonisation. Here, we examined the spatio-temporal genetic structure of 8 alpine caddisfly populations inhabiting permanent and temporary streams from four valleys in two regions of the Swiss Alps in years before and after a major stream drying event, the European heat wave in summer 2003. We found that population turnover after 2003 led to a loss of allelic richness and gene diversity but not to significant changes in observed heterozygosity. Within all valleys, permanent and temporary streams in any given year were not differentiated, suggesting considerable gene flow and admixture between streams with differing hydroperiods. Large changes in allele frequencies after 2003 resulted in a substantial increase in genetic differentiation among valleys within one to two years (1-2 generations) driven primarily by drift and immigration. Signatures of genetic bottlenecks were detected in all 8 populations after 2003 using the M-ratio method, but in no populations when using a heterozygosity excess method, indicating differential sensitivity of bottleneck detection methods. We conclude that genetic differentiation among A. uncatus populations changed markedly both temporally and spatially in response to the extreme climate event in 2003. Our results highlight the magnitude of temporal population genetic changes in response to extreme events. More specifically, our results show that extreme events can cause rapid genetic divergence in metapopulations. Further studies are needed to determine if recovery from this perturbation through gradual mixing of diverged populations by migration and gene flow leads to the pre-climate event state

  10. Bottlenecks drive temporal and spatial genetic changes in alpine caddisfly metapopulations

    PubMed Central

    2011-01-01

    Background Extinction and re-colonisation of local populations is common in ephemeral habitats such as temporary streams. In most cases, such population turnover leads to reduced genetic diversity within populations and increased genetic differentiation among populations due to stochastic founder events, genetic drift, and bottlenecks associated with re-colonisation. Here, we examined the spatio-temporal genetic structure of 8 alpine caddisfly populations inhabiting permanent and temporary streams from four valleys in two regions of the Swiss Alps in years before and after a major stream drying event, the European heat wave in summer 2003. Results We found that population turnover after 2003 led to a loss of allelic richness and gene diversity but not to significant changes in observed heterozygosity. Within all valleys, permanent and temporary streams in any given year were not differentiated, suggesting considerable gene flow and admixture between streams with differing hydroperiods. Large changes in allele frequencies after 2003 resulted in a substantial increase in genetic differentiation among valleys within one to two years (1-2 generations) driven primarily by drift and immigration. Signatures of genetic bottlenecks were detected in all 8 populations after 2003 using the M-ratio method, but in no populations when using a heterozygosity excess method, indicating differential sensitivity of bottleneck detection methods. Conclusions We conclude that genetic differentiation among A. uncatus populations changed markedly both temporally and spatially in response to the extreme climate event in 2003. Our results highlight the magnitude of temporal population genetic changes in response to extreme events. More specifically, our results show that extreme events can cause rapid genetic divergence in metapopulations. Further studies are needed to determine if recovery from this perturbation through gradual mixing of diverged populations by migration and gene flow leads

  11. 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

  12. 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...

  13. Spatial heterogeneity in the effects of climate and density-dependence on dispersal in a house sparrow metapopulation

    PubMed Central

    Pärn, Henrik; Ringsby, Thor Harald; Jensen, Henrik; Sæther, Bernt-Erik

    2012-01-01

    Dispersal plays a key role in the response of populations to climate change and habitat fragmentation. Here, we use data from a long-term metapopulation study of a non-migratory bird, the house sparrow (Passer domesticus), to examine the influence of increasing spring temperature and density-dependence on natal dispersal rates and how these relationships depend on spatial variation in habitat quality. The effects of spring temperature and population size on dispersal rate depended on the habitat quality. Dispersal rate increased with temperature and population size on poor-quality islands without farms, where house sparrows were more exposed to temporal fluctuations in weather conditions and food availability. By contrast, dispersal rate was independent of spring temperature and population size on high-quality islands with farms, where house sparrows had access to food and shelter all the year around. This illustrates large spatial heterogeneity within the metapopulation in how population density and environmental fluctuations affect the dispersal process. PMID:21613299

  14. Individual genetic diversity correlates with the size and spatial isolation of natal colonies in a bird metapopulation

    PubMed Central

    Ortego, Joaquín; Aparicio, José Miguel; Cordero, Pedro J; Calabuig, Gustau

    2008-01-01

    The genetic consequences of small population size and isolation are of central concern in both population and conservation biology. Organisms with a metapopulation structure generally show effective population sizes that are much smaller than the number of mature individuals and this can reduce genetic diversity especially in small sized and isolated subpopulations. Here, we examine the association between heterozygosity and the size and spatial isolation of natal colonies in a metapopulation of lesser kestrels (Falco naumanni). For this purpose, we used capture–mark–recapture data to determine the patterns of immigration into the studied colonies, and 11 highly polymorphic microsatellite markers that allowed us to estimate genetic diversity of locally born individuals. We found that individuals born in smaller and more isolated colonies were genetically less diverse. These colonies received a lower number of immigrants, supporting the idea that both reduced gene flow and small population size are responsible for the genetic pattern observed. Our results are particularly intriguing because the lesser kestrel is a vagile and migratory species with great movement capacity and dispersal potential. Overall, this study provides evidence of the association between individual heterozygosity and the size and spatial isolation of natal colonies in a highly mobile vertebrate showing relatively frequent dispersal and low genetic differentiation among local subpopulations. PMID:18505717

  15. Networks in metapopulation dynamics

    NASA Astrophysics Data System (ADS)

    Vuorinen, V.; Peltomäki, M.; Rost, M.; Alava, M. J.

    2004-03-01

    The behavior of spatially inhomogeneous populations in networks of habitats provides examples of dynamical systems on random graphs with structure. A particular example is a butterfly species inhabiting the Åland archipelago. A metapopulation description of the patch occupancies is here mapped to a quenched graph, using the empirical ecology-based incidence function description as a starting point. Such graphs are shown to have interesting features that both reflect the probably “self-organized” nature of a metapopulation that can survive and the geographical details of the landscape. Simulations of the Susceptible-Infected-Susceptible model, to mimick the time-dependent population dynamics relate to the graph features: lack of a typical scale, large connectivity per vertex, and the existence of independent subgraphs. Finally, ideas related to the application and extension of scale-free graphs to metapopulations are discussed.

  16. Influence of local demography on asymptotic and transient dynamics of a yellow-bellied marmot metapopulation.

    PubMed

    Ozgul, Arpat; Oli, Madan K; Armitage, Kenneth B; Blumstein, Daniel T; Van Vuren, Dirk H

    2009-04-01

    Despite recent advances in biodemography and metapopulation ecology, we still have limited understanding of how local demographic parameters influence short- and long-term metapopulation dynamics. We used long-term data from 17 local populations, along with the recently developed methods of matrix metapopulation modeling and transient sensitivity analysis, to investigate the influence of local demography on long-term (asymptotic) versus short-term (transient) dynamics of a yellow-bellied marmot metapopulation in Colorado. Both long- and short-term dynamics depended primarily on a few colony sites and were highly sensitive to changes in demography at these sites, particularly in survival of reproductive adult females. Interestingly, the relative importance of sites differed between long- and short-term dynamics; the spatial structure and local population sizes, while insignificant for asymptotic dynamics, were influential on transient dynamics. However, considering the spatial structure was uninformative about the relative influence of local demography on metapopulation dynamics. The vital rates that were the most influential on local dynamics were also the most influential on both long- and short-term metapopulation dynamics. Our results show that an explicit consideration of local demography is essential for a complete understanding of the dynamics and persistence of spatially structured populations.

  17. 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/.

  18. Enhancing the area-isolation paradigm: habitat heterogeneity and metapopulation dynamics of a rare wetland mammal.

    PubMed

    Schooley, Robert L; Branch, Lyn C

    2009-10-01

    Conservation of species in fragmented landscapes often is guided by spatially realistic metapopulation theory. However, convincing cases of metapopulation dynamics are uncommon, especially for vertebrates. Moreover, there is concern that the patch area and isolation paradigm for metapopulations is an oversimplification for heterogeneous landscapes. We tested predictions from metapopulation theory for a rare wetland mammal (round-tailed muskrat, Neofiber alleni) and asked whether it was necessary to use a habitat-informed version of the area-isolation paradigm that included patch quality and matrix heterogeneity. In each of two years, we surveyed 457 isolated wetlands in central Florida, USA, for presence-absence of Neofiber and evaluated logistic regression models of patch occupancy, extinction, and colonization. We documented metapopulation dynamics in which patch occupancy was constant between years (26% of patches occupied) due to balanced local extinctions (n = 45) and recolonizations (n = 46). Neofiber was both habitat and dispersal limited. Local extinctions were related negatively to patch area, patch quality (cover of maidencane grass, Panicum hemitomon), and distance to nearest roadside ditch. Patch colonization depended on patch area, patch quality, and spatial connectivity to potential source wetlands. Despite the importance of patch quality, Neofiber did not exhibit a habitat-tracking metapopulation on an annual time scale. Cost-distance modeling suggested effective distances that included high costs for moving through forested matrix habitats generally were better than Euclidean distances for predicting patch colonization and occupancy. Two dominant land uses were tied to turnover dynamics: cattle grazing decreased habitat quality of wetlands, and presence of pine (Pinus spp.) plantations decreased functional connectivity. The simple area-isolation paradigm was not adequate for characterizing spatial dynamics of the Neofiber metapopulation

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

    PubMed

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

    2005-10-01

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

  20. 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...

  1. 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...

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

    NASA Astrophysics Data System (ADS)

    Klopfer, Eric David

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

  3. Population dynamics of epiphytic orchids in a metapopulation context

    PubMed Central

    Winkler, Manuela; Hülber, Karl; Hietz, Peter

    2009-01-01

    Background and Aims Populations of many epiphytes show a patchy distribution where clusters of plants growing on individual trees are spatially separated and may thus function as metapopulations. Seed dispersal is necessary to (re)colonize unoccupied habitats, and to transfer seeds from high- to low-competition patches. Increasing dispersal distances, however, reduces local fecundity and the probability that seeds will find a safe site outside the original patch. Thus, there is a conflict between seed survival and colonization. Methods Populations of three epiphytic orchids were monitored over three years in a Mexican humid montane forest and analysed with spatially averaged and with spatially explicit matrix metapopulation models. In the latter, population dynamics at the scale of the subpopulations (epiphytes on individual host trees) are based on detailed stage-structured observations of transition probabilities and trees are connected by a dispersal function. Key Results Population growth rates differed among trees and years. While ignoring these differences, and averaging the population matrices over trees, yields negative population growth, metapopulation models predict stable or growing populations because the trees that support growing subpopulations determine the growth of the metapopulation. Stochastic models which account for the differences among years differed only marginally from deterministic models. Population growth rates were significantly lower, and extinctions of local patches more frequent in models where higher dispersal results in reduced local fecundity compared with hypothetical models where this is not the case. The difference between the two models increased with increasing mean dispersal distance. Though recolonization events increased with dispersal distance, this could not compensate the losses due to reduced local fecundity. Conclusions For epiphytes, metapopulation models are useful to capture processes beyond the level of the single

  4. 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.

  5. 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

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

    USGS Publications Warehouse

    Buscombe, Daniel D.

    2015-01-01

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

  7. 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

  8. 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.

  9. Spatially and financially explicit population viability analysis of Maculinea alcon in The Netherlands.

    PubMed

    Radchuk, Viktoriia; Wallisdevries, Michiel F; Schtickzelle, Nicolas

    2012-01-01

    The conservation of species structured in metapopulations involves an important dilemma of resource allocation: should investments be directed at restoring/enlarging habitat patches or increasing connectivity. This is still an open question for Maculinea species despite they are among the best studied and emblematic butterfly species, because none of the population dynamics models developed so far included dispersal. We developed the first spatially and financially explicit Population Viability Analysis model for Maculinea alcon, using field data from The Netherlands. Implemented using the RAMAS/GIS platform, the model incorporated both local (contest density dependence, environmental and demographic stochasticities), and regional population dynamics (dispersal rates between habitat patches). We selected four habitat patch networks, contrasting in several basic features (number of habitat patches, their quality, connectivity, and occupancy rate) to test how these features are affecting the ability to enhance population viability of four basic management options, designed to incur the same costs: habitat enlargement, habitat quality improvement, creation of new stepping stone habitat patches, and reintroduction of captive-reared butterflies. The PVA model was validated by the close match between its predictions and independent field observations on the patch occupancy pattern. The four patch networks differed in their sensitivity to model parameters, as well as in the ranking of management options. Overall, the best cost-effective option was enlargement of existing habitat patches, followed by either habitat quality improvement or creation of stepping stones depending on the network features. Reintroduction was predicted to generally be inefficient, except in one specific patch network. Our results underline the importance of spatial and regional aspects (dispersal and connectivity) in determining the impact of conservation actions, even for a species previously

  10. Human influence on the spatial structure of threatened Pacific salmon metapopulations

    Treesearch

    Aimee H. Fullerton; Steven T. Lindley; George R. Pess; Blake E. Feist; E. Ashley Steel; Paul. McElhany

    2011-01-01

    To remain viable, populations must be resilient to both natural and human-caused environmental changes. We evaluated anthropogenic effects on spatial connections among populations of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) (designated as threatened under the U.S. Endangered Species Act) in the lower...

  11. Spatial occupancy models for predicting metapopulation dynamics and viability following reintroduction

    USGS Publications Warehouse

    Chandler, Richard B.; Muths, Erin L.; Sigafus, Brent H.; Schwalbe, Cecil R.; Jarchow, Christopher J.; Hossack, Blake R.

    2015-01-01

    Synthesis and applications. This work demonstrates how spatio-temporal statistical models based on ecological theory can be applied to forecast the outcomes of conservation actions such as reintroduction. Our spatial occupancy model should be particularly useful when management agencies lack the funds to collect intensive individual-level data.

  12. 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.

  13. 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.

  14. Spatial and temporal variation of diet within a presumed metapopulation of Adelie penguins

    USGS Publications Warehouse

    Ainley, D.G.; Ballard, G.; Barton, K.J.; Karl, B.J.; Rau, G.H.; Ribic, C.A.; Wilson, P.R.

    2003-01-01

    We investigated temporal and spatial variability in the diet of chick-provisioning Ade??lie Penguins (Pygoscelis adeliae) breeding at all colonies within one isolated cluster in the southwestern Ross Sea, Antarctica, 1994-2000. We wished to determine if prey quality explained different population growth and emigration rates among colonies. Diet composition was described both by conventional means (stomach samples) and by analysis of stable isotopes in chick tissues (toenails of individuals killed by skuas [Stercorarius maccormicki]). Diets were similar among the four study colonies compared to the disparity apparent among 14 widely spaced sites around the continent. Calorimetry indicated that fish are more energetically valuable than krill, implying that if diet varied by colony, diet quality could attract recruits and help to explain differential rates of colony growth. However, a multiple-regression analysis indicated that diet varied as a function of year, time within the year, and percent of foraging area covered by sea ice, but not by colony location. Stable isotopes revealed similarity of diet at one colony where conventional sampling was not possible. We confirmed that sea ice importantly affects diet composition of this species in neritic waters, and found that (1) quality of summer diet cannot explain different population growth rates among colonies, and (2) stable isotope analysis of chick tissues (toenails) is a useful tool to synoptically describe diet in this species over a large area.

  15. 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.

  16. 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

    still lacking. Here, we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0 explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

  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 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.

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

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

    PubMed

    Won, Bo-Yeong; Jiang, Yuhong V

    2015-05-01

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

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

    PubMed Central

    Won, Bo-Yeong; Jiang, Yuhong V.

    2014-01-01

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

  7. Global spatially explicit CO2 emission metrics for forest bioenergy

    PubMed Central

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

    2016-01-01

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

  8. 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

  9. Modelling metapopulations with stochastic membrane systems.

    PubMed

    Besozzi, Daniela; Cazzaniga, Paolo; Pescini, Dario; Mauri, Giancarlo

    2008-03-01

    Metapopulations, or multi-patch systems, are models describing the interactions and the behavior of populations living in fragmented habitats. Dispersal, persistence and extinction are some of the characteristics of interest in ecological studies of metapopulations. In this paper, we propose a novel method to analyze metapopulations, which is based on a discrete and stochastic modelling framework in the area of Membrane Computing. New structural features of membrane systems, necessary to appropriately describe a multi-patch system, are introduced, such as the reduction of the maximal parallel consumption of objects, the spatial arrangement of membranes and the stochastic creation of objects. The role of the additional features, their meaning for a metapopulation model and the emergence of relevant behaviors are then investigated by means of stochastic simulations. Conclusive remarks and ideas for future research are finally presented.

  10. 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.

  11. 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

  12. Metapopulation persistence in random fragmented landscapes.

    PubMed

    Grilli, Jacopo; Barabás, György; Allesina, Stefano

    2015-05-01

    Habitat destruction and land use change are making the world in which natural populations live increasingly fragmented, often leading to local extinctions. Although local populations might undergo extinction, a metapopulation may still be viable as long as patches of suitable habitat are connected by dispersal, so that empty patches can be recolonized. Thus far, metapopulations models have either taken a mean-field approach, or have modeled empirically-based, realistic landscapes. Here we show that an intermediate level of complexity between these two extremes is to consider random landscapes, in which the patches of suitable habitat are randomly arranged in an area (or volume). Using methods borrowed from the mathematics of Random Geometric Graphs and Euclidean Random Matrices, we derive a simple, analytic criterion for the persistence of the metapopulation in random fragmented landscapes. Our results show how the density of patches, the variability in their value, the shape of the dispersal kernel, and the dimensionality of the landscape all contribute to determining the fate of the metapopulation. Using this framework, we derive sufficient conditions for the population to be spatially localized, such that spatially confined clusters of patches act as a source of dispersal for the whole landscape. Finally, we show that a regular arrangement of the patches is always detrimental for persistence, compared to the random arrangement of the patches. Given the strong parallel between metapopulation models and contact processes, our results are also applicable to models of disease spread on spatial networks.

  13. Portfolio conservation of metapopulations under climate change.

    PubMed

    Anderson, Sean C; Moore, Jonathan W; McClure, Michelle M; Dulvy, Nicholas K; Cooper, Andrew B

    2015-03-01

    Climate change is likely to lead to increasing population variability and extinction risk. Theoretically, greater population diversity should buffer against rising climate variability, and this theory is often invoked as a reason for greater conservation. However, this has rarely been quantified. Here we show how a portfolio approach to managing population diversity can inform metapopulation conservation priorities in a changing world. We develop a salmon metapopulation model in which productivity is driven by spatially distributed thermal tolerance and patterns of short- and long-term climate change. We then implement spatial conservation scenarios that control population carrying capacities and evaluate the metapopulation portfolios as a financial manager might: along axes of conservation risk and return. We show that preserving a diversity of thermal tolerances minimizes risk, given environmental stochasticity, and ensures persistence, given long-term environmental change. When the thermal tolerances of populations are unknown, doubling the number of populations conserved may nearly halve expected metapopulation variability. However, this reduction in variability can come at the expense of long-term persistence if climate change increasingly restricts available habitat, forcing ecological managers to balance society's desire for short-term stability and long-term viability. Our findings suggest the importance of conserving the processes that promote thermal-tolerance diversity, such as genetic diversity, habitat heterogeneity, and natural disturbance regimes, and demonstrate that diverse natural portfolios may be critical for metapopulation conservation in the face of increasing climate variability and change.

  14. 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...

  15. 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...

  16. 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,...

  17. Viability of piping plover Charadrius melodus metapopulations

    USGS Publications Warehouse

    Plissner, Jonathan H.; Haig, Susan M.

    2000-01-01

    The metapopulation viability analysis package, VORTEX, was used to examine viability and recovery objectives for piping plovers Charadrius melodus, an endangered shorebird that breeds in three distinct regions of North America. Baseline models indicate that while Atlantic Coast populations, under current management practices, are at little risk of near-term extinction, Great Plains and Great Lakes populations require 36% higher mean fecundity for a significant probability of persisting for the next 100 years. Metapopulation structure (i.e. the delineation of populations within the metapopulation) and interpopulation dispersal rates had varying effects on model results; however, spatially-structured metapopulations exhibited lower viability than that reported for single-population models. The models were most sensitive to variation in survivorship; hence, additional mortality data will improve their accuracy. With this information, such models become useful tools in identifying successful management objectives; and sensitivity analyses, even in the absence of some data, may indicate which options are likely to be most effective. Metapopulation viability models are best suited for developing conservation strategies for achieving recovery objectives based on maintaining an externally derived, target population size and structure.

  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. 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.

  20. A spatially explicit estimate of avoided forest loss.

    PubMed

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

    2011-10-01

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

  1. 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.

  2. A Spatially Explicit Method for Prioritizing AIS Surveillance ...

    EPA Pesticide Factsheets

    Choosing where to sample for aquatic invasive species (AIS) is a daunting challenge in the Laurentian Great Lakes. Management resources are finite hence it is important that monitoring efforts concentrate on those sites with the highest risk of introduction based on transparent criteria and assumptions and the best available data. Here we describe the development of a site prioritization method designed to address such challenges. The U.S. waters of the Great Lakes and tributaries were divided into standardized management units (9 km x 9 km). An index of invasion pressure was defined using a standardized set of spatial surrogates to estimate cumulative propagule pressure for each management unit. Weighting multipliers were applied to the attributed spatial surrogate data so that both historic patterns and future predicted patterns of introduction were incorporated into the final calculation of the index of invasion pressure for each management unit. Of the total of 5,953 management units in the U.S. Great Lakes basin (land and water), about 1,800 units have attributes resulting in index scores greater than zero. The site prioritization method can be used to select surveillance priorities for fish, invertebrates, and/or plants across the U.S. waters of the Great Lakes basin. not applicable

  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. 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...

  5. Spatially explicit data: stewardship and ethical challenges in science.

    PubMed

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

    2013-09-01

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

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

    PubMed Central

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

    2013-01-01

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

  7. 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.

  8. A Spatially-Explicit Technique for Evaluation of Alternative ...

    EPA Pesticide Factsheets

    Ecosystems contribute to maintaining human well-being directly through provision of goods and indirectly through provision of services that support clean water, clean air, flood protection and atmospheric stability. Transparently accounting for biophysical attributes from which humans derive benefit is essential to support dialog among the public, resource managers, decision makers, and scientists. We analyzed the potential ecosystem goods and services production from alternative future land use scenarios in the US Tampa Bay region. Ecosystem goods and service metrics included carbon sequestration, nitrogen removal, air pollutant removal, and stormwater retention. Each scenario was compared to a 2006 baseline land use. Estimated production of denitrification services changed by 28% and carbon sequestration by 20% between 2006 and the “business as usual” scenario. An alternative scenario focused on “natural resource protection” resulted in an estimated 9% loss in air pollution removal. Stormwater retention was estimated to change 18% from 2006 to 2060 projections. Cost effective areas for conservation, almost 1588 ha, beyond current conservation lands, were identified by comparing ecosystem goods and services production to assessed land values. Our ecosystem goods and services approach provides a simple and quantitative way to examine a more complete set of potential outcomes from land use decisions. This study demonstrates an approach for spatially expli

  9. 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

  10. Spatial and temporal patterns of larval dispersal in a coral-reef fish metapopulation: evidence of variable reproductive success.

    PubMed

    Pusack, Timothy J; Christie, Mark R; Johnson, Darren W; Stallings, Christopher D; Hixon, Mark A

    2014-07-01

    Many marine organisms can be transported hundreds of kilometres during their pelagic larval stage, yet little is known about spatial and temporal patterns of larval dispersal. Although traditional population-genetic tools can be applied to infer movement of larvae on an evolutionary timescale, large effective population sizes and high rates of gene flow present serious challenges to documenting dispersal patterns over shorter, ecologically relevant, timescales. Here, we address these challenges by combining direct parentage analysis and indirect genetic analyses over a 4-year period to document spatial and temporal patterns of larval dispersal in a common coral-reef fish: the bicolour damselfish (Stegastes partitus). At four island locations surrounding Exuma Sound, Bahamas, including a long-established marine reserve, we collected 3278 individuals and genotyped them at 10 microsatellite loci. Using Bayesian parentage analysis, we identified eight parent-offspring pairs, thereby directly documenting dispersal distances ranging from 0 km (i.e., self-recruitment) to 129 km (i.e., larval connectivity). Despite documenting substantial dispersal and gene flow between islands, we observed more self-recruitment events than expected if the larvae were drawn from a common, well-mixed pool (i.e., a completely open population). Additionally, we detected both spatial and temporal variation in signatures of sweepstakes and Wahlund effects. The high variance in reproductive success (i.e., 'sweepstakes') we observed may be influenced by seasonal mesoscale gyres present in the Exuma Sound, which play a prominent role in shaping local oceanographic patterns. This study documents the complex nature of larval dispersal in a coral-reef fish, and highlights the importance of sampling multiple cohorts and coupling both direct and indirect genetic methods in order disentangle patterns of dispersal, gene flow and variable reproductive success. © 2014 John Wiley & Sons Ltd.

  11. 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

  12. Abiotic and biotic interactions determine whether increased colonization is beneficial or detrimental to metapopulation management.

    PubMed

    Southwell, Darren M; Rhodes, Jonathan R; McDonald-Madden, Eve; Nicol, Sam; Helmstedt, Kate J; McCarthy, Michael A

    2016-06-01

    Increasing the colonization rate of metapopulations can improve persistence, but can also increase exposure to threats. To make good decisions, managers must understand whether increased colonization is beneficial or detrimental to metapopulation persistence. While a number of studies have examined interactions between metapopulations, colonization, and threats, they have assumed that threat dynamics respond linearly to changes in colonization. Here, we determined when to increase colonization while explicitly accounting for non-linear dependencies between a metapopulation and its threats. We developed patch occupancy metapopulation models for species susceptible to abiotic, generalist, and specialist threats and modeled the total derivative of the equilibrium proportion of patches occupied by each metapopulation with respect to the colonization rate. By using the total derivative, we developed a rule for determining when to increase metapopulation colonization. This rule was applied to a simulated metapopulation where the dynamics of each threat responded to increased colonization following a power function. Before modifying colonization, we show that managers must understand: (1) whether a metapopulation is susceptible to a threat; (2) the type of threat acting on a metapopulation; (3) which component of threat dynamics might depend on colonization, and; (4) the likely response of a threat-dependent variable to changes in colonization. The sensitivity of management decisions to these interactions increases uncertainty in conservation planning decisions. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

  13. A spatial explicit strategy reduces error but interferes with sensorimotor adaptation

    PubMed Central

    Benson, Bryan L.; Anguera, Joaquin A.

    2011-01-01

    Although sensorimotor adaptation is typically thought of as an implicit form of learning, it has been shown that participants who gain explicit awareness of the nature of the perturbation during adaptation exhibit more learning than those who do not. With rare exceptions, however, explicit awareness is typically polled at the end of the study. Here, we provided participants with either an explicit spatial strategy or no instructions before learning. Early in learning, explicit instructions greatly reduced movement errors but also resulted in increased trial-to-trial variability and longer reaction times. Late in adaptation, performance was indistinguishable between the explicit and implicit groups, but the mechanisms underlying performance improvements remained fundamentally different, as revealed by catch trials. The progression of implicit recalibration in the explicit group was modulated by the use of an explicit strategy: these participants showed a lower level of recalibration as well as decreased aftereffects. This phenomenon may be due to the reduced magnitude of errors made to the target during adaptation or inhibition of implicit learning mechanisms by explicit processing. PMID:21451054

  14. 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.

  15. 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.

  16. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  19. 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...

  20. 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...

  1. 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 ...

  2. 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...

  3. 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 ...

  4. 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...

  5. 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.

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

    ERIC Educational Resources Information Center

    Won, Bo-Yeong; Jiang, Yuhong V.

    2015-01-01

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

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

    ERIC Educational Resources Information Center

    Won, Bo-Yeong; Jiang, Yuhong V.

    2015-01-01

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

  8. 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.

  9. Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

    PubMed

    Pos, Edwin; Guevara Andino, Juan Ernesto; Sabatier, Daniel; Molino, Jean-François; Pitman, Nigel; Mogollón, Hugo; Neill, David; Cerón, Carlos; Rivas-Torres, Gonzalo; Di Fiore, Anthony; Thomas, Raquel; Tirado, Milton; Young, Kenneth R; Wang, Ophelia; Sierra, Rodrigo; García-Villacorta, Roosevelt; Zagt, Roderick; Palacios Cuenca, Walter; Aulestia, Milton; Ter Steege, Hans

    2017-06-01

    With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of

  10. 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

  11. 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...

  12. 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.

  13. 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 ...

  14. 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

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Interference-free acquisition of overlapping sequences in explicit spatial memory.

    PubMed

    Eggert, Thomas; Drever, Johannes; Straube, Andreas

    2014-04-01

    Some types of human sequential memory, e.g. the acquisition of a new composition by a trained musician, seem to be very efficient in extending the length of a memorized sequence and in flexible reuse of known subsequences in a newly acquired sequential context. This implies that interference between known and newly acquired subsequences can be avoided even when learning a sequence which is a partial mutation of a known sequence. It is known that established motor sequences do not have such flexibility. Using learning of deferred imitation, the current study investigates the flexibility of explicit spatial memory by quantifying the interferences between successively acquired, partially overlapping sequences. After learning a spatial sequence on day 1, this sequence was progressively modified on day 2. On day 3, a retention test was performed with both the initial and the modified sequence. The results show that subjects performed very well on day 1 and day 2. No spatial interference between changed and unchanged targets was observed during the stepwise progressive modification of the reproduced sequence. Surprisingly, subjects performed well on both sequences on day 3. Comparison with a control experiment without intermediate mutation training showed that the initial training on day 1 did not proactively interfere with the retention of the modified sequence on day 3. Vice versa, the mutation training on day 2 did not interfere retroactively with the retention of the original sequence as tested on day 3. The results underline the flexibility in acquiring explicit spatial memory.

  7. 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

  8. 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

  9. The need for spatially explicit quantification of benefits in invasive-species management.

    PubMed

    Januchowski-Hartley, Stephanie R; Adams, Vanessa M; Hermoso, Virgilio

    2017-09-22

    Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive-species control, and planning processes are needed to identify cost-effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive-species management. There is a need to improve understanding of how such assets are considered in invasive-species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty-four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty-five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision-making processes that guide invasive-species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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

    SciTech Connect

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

    2010-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  12. 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.

  13. Metapopulation dynamics of bubonic plague.

    PubMed

    Keeling, M J; Gilligan, C A

    2000-10-19

    Bubonic plague is widely regarded as a disease of mainly historical importance; however, with increasing reports of incidence and the discovery of antibiotic-resistant strains of the plague bacterium Yersinia pestis, it is re-emerging as a significant health concerns. Here we bypass the conventional human-disease models, and propose that bubonic plague is driven by the dynamics of the disease in the rat population. Using a stochastic, spatial metapopulation model, we show that bubonic plague can persist in relatively small rodent populations from which occasional human epidemics arise, without the need for external imports. This explains why historically the plague persisted despite long disease-free periods, and how the disease re-occurred in cities with tight quarantine control. In a contemporary setting, we show that human vaccination cannot eradicate the plague, and that culling of rats may prevent or exacerbate human epidemics, depending on the timing of the cull. The existence of plague reservoirs in wild rodent populations has important public-health implications for the transmission to urban rats and the subsequent risk of human outbreaks.

  14. Optimizing metapopulation sustainability through a checkerboard strategy.

    PubMed

    Zion, Yossi Ben; Yaari, Gur; Shnerb, Nadav M

    2010-01-22

    The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent) of stable solutions and the structure of their basin of attraction (dependence on initial population size). Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors) in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.

  15. Optimizing Metapopulation Sustainability through a Checkerboard Strategy

    PubMed Central

    Ben Zion, Yossi; Yaari, Gur; Shnerb, Nadav M.

    2010-01-01

    The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent) of stable solutions and the structure of their basin of attraction (dependence on initial population size). Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors) in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign. PMID:20098493

  16. 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...

  17. 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...

  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. 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.

  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. 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

  2. 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

  3. 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.

  4. Minimum viable metapopulation size, extinction debt, and the conservation of a declining species.

    PubMed

    Bulman, Caroline R; Wilson, Robert J; Holt, Alison R; Gálvez Bravo, Lucia; Early, Regan I; Warren, Martin S; Thomas, Chris D

    2007-07-01

    A key question facing conservation biologists is whether declines in species' distributions are keeping pace with landscape change, or whether current distributions overestimate probabilities of future persistence. We use metapopulations of the marsh fritillary butterfly Euphydryas aurinia in the United Kingdom as a model system to test for extinction debt in a declining species. We derive parameters for a metapopulation model (incidence function model, IFM) using information from a 625-km2 landscape where habitat patch occupancy, colonization, and extinction rates for E. aurinia depend on patch connectivity, area, and quality. We then show that habitat networks in six extant metapopulations in 16-km2 squares were larger, had longer modeled persistence times (using IFM), and higher metapopulation capacity (lambdaM) than six extinct metapopulations. However, there was a > 99% chance that one or more of the six extant metapopulations would go extinct in 100 years in the absence of further habitat loss. For 11 out of 12 networks, minimum areas of habitat needed for 95% persistence of metapopulation simulations after 100 years ranged from 80 to 142 ha (approximately 5-9% of land area), depending on the spatial location of habitat. The area of habitat exceeded the estimated minimum viable metapopulation size (MVM) in only two of the six extant metapopulations, and even then by only 20%. The remaining four extant networks were expected to suffer extinction in 15-126 years. MVM was consistently estimated as approximately 5% of land area based on a sensitivity analysis of IFM parameters and was reduced only marginally (to approximately 4%) by modeling the potential impact of long-distance colonization over wider landscapes. The results suggest a widespread extinction debt among extant metapopulations of a declining species, necessitating conservation management or reserve designation even in apparent strongholds. For threatened species, metapopulation modeling is a

  5. A Metapopulation Approach to African Lion (Panthera leo) Conservation

    PubMed Central

    Dolrenry, Stephanie; Stenglein, Jennifer; Hazzah, Leela; Lutz, R. Scott; Frank, Laurence

    2014-01-01

    Due to anthropogenic pressures, African lion (Panthera leo) populations in Kenya and Tanzania are increasingly limited to fragmented populations. Lions living on isolated habitat patches exist in a matrix of less-preferred habitat. A framework of habitat patches within a less-suitable matrix describes a metapopulation. Metapopulation analysis can provide insight into the dynamics of each population patch in reference to the system as a whole, and these analyses often guide conservation planning. We present the first metapopulation analysis of African lions. We use a spatially-realistic model to investigate how sex-biased dispersal abilities of lions affect patch occupancy and also examine whether human densities surrounding the remaining lion populations affect the metapopulation as a whole. Our results indicate that male lion dispersal ability strongly contributes to population connectivity while the lesser dispersal ability of females could be a limiting factor. When populations go extinct, recolonization will not occur if distances between patches exceed female dispersal ability or if females are not able to survive moving across the matrix. This has profound implications for the overall metapopulation; the female models showed an intrinsic extinction rate from five-fold to a hundred-fold higher than the male models. Patch isolation is a consideration for even the largest lion populations. As lion populations continue to decline and with local extinctions occurring, female dispersal ability and the proximity to the nearest lion population are serious considerations for the recolonization of individual populations and for broader conservation efforts. PMID:24505385

  6. A metapopulation approach to African lion (Panthera leo) conservation.

    PubMed

    Dolrenry, Stephanie; Stenglein, Jennifer; Hazzah, Leela; Lutz, R Scott; Frank, Laurence

    2014-01-01

    Due to anthropogenic pressures, African lion (Panthera leo) populations in Kenya and Tanzania are increasingly limited to fragmented populations. Lions living on isolated habitat patches exist in a matrix of less-preferred habitat. A framework of habitat patches within a less-suitable matrix describes a metapopulation. Metapopulation analysis can provide insight into the dynamics of each population patch in reference to the system as a whole, and these analyses often guide conservation planning. We present the first metapopulation analysis of African lions. We use a spatially-realistic model to investigate how sex-biased dispersal abilities of lions affect patch occupancy and also examine whether human densities surrounding the remaining lion populations affect the metapopulation as a whole. Our results indicate that male lion dispersal ability strongly contributes to population connectivity while the lesser dispersal ability of females could be a limiting factor. When populations go extinct, recolonization will not occur if distances between patches exceed female dispersal ability or if females are not able to survive moving across the matrix. This has profound implications for the overall metapopulation; the female models showed an intrinsic extinction rate from five-fold to a hundred-fold higher than the male models. Patch isolation is a consideration for even the largest lion populations. As lion populations continue to decline and with local extinctions occurring, female dispersal ability and the proximity to the nearest lion population are serious considerations for the recolonization of individual populations and for broader conservation efforts.

  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. 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.

  9. 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.

  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. [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.

  12. 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.

  13. Rhythmogenesis, birhythmicity and chaos in a metapopulation model

    NASA Astrophysics Data System (ADS)

    Arumugam, Ramesh; Banerjee, Tanmoy; Dutta, Partha Sharathi

    2017-06-01

    We study a mean-field coupled ecological model of metapopulation in which species from spatially fragmented habitats are connected through dispersal. The interplay between dispersal and heterogeneous characteristics of connected habitats determines the mechanisms in promoting dispersal-induced synchrony and stability of metapopulation. Depending on dispersal rate and environmental heterogeneity, the mean-field coupling acts as a feedback to the system which enables various rhythmic processes such as rhythmogenesis and birhythmicity. In addition to that, heterogeneity determines period-doubling of limit cycle which further leads to chaotic oscillation.

  14. Epidemic fronts in complex networks with metapopulation structure

    USDA-ARS?s Scientific Manuscript database

    Infection dynamics have been studied extensively on complex networks, yielding insight into the effects of heterogeneity in contact patterns on disease spread. Somewhat separately, metapopulations have provided a paradigm for modeling systems with spatially extended and “patchy” organization. In thi...

  15. Metapopulation dynamics in a complex ecological landscape.

    PubMed

    Colombo, E H; Anteneodo, C

    2015-08-01

    We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction.

  16. 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

  17. 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.

  18. 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.

  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 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.

  1. Quantifying spatially and temporally explicit CO2 fertilization effects on global terrestrial ecosystem carbon dynamics

    DOE PAGES

    Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

    2016-07-25

    Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO2) concentration data at the global scale. However, high-precision CO2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO2 data sets to analyze the atmospheric CO2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 to 2010. Our results demonstrated that CO2more » seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr–1 and 0.08 Pg C•yr–1 higher than the simulation using uniformly distributed CO2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO2 observation network should be expanded so that the realistic CO2 variation can be incorporated into the land surface models to adequately account for CO2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

  2. Evaluating the importance of demographic connectivity in a marine metapopulation.

    PubMed

    Carson, Henry S; Cook, Geoffrey S; López-Duarte, Paola C; Levin, Lisa A

    2011-10-01

    of recruits was retained within the predominant source subpopulation. Despite differences in habitat and planktonic duration, both species exhibited similar overall metapopulation dynamics with respect to key life stages and processes. However, different peak reproductive periods in an environment of seasonal current reversals led to different regional (subpopulation) contributions to metapopulation maintenance; this result emphasizes the importance of connectivity analysis for spatial management of coastal resources.

  3. 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.

  4. Relative contributions of spatial weighting, explicit knowledge and proprioception to hand localisation during positional ambiguity.

    PubMed

    Bellan, Valeria; Gilpin, Helen R; Stanton, Tasha R; Dagsdóttir, Lilja K; Gallace, Alberto; Lorimer Moseley, G

    2017-02-01

    When vision and proprioception are rendered incongruent during a hand localisation task, vision is initially weighted more than proprioception in determining location, and proprioception gains more weighting over time. However, it is not known whether, under these incongruency conditions, particular areas of space are also weighted more heavily than others, nor whether explicit knowledge of the sensory incongruence (i.e. disconfirming the perceived location of the hand) modulates the effect. Here, we hypothesised that both non-informative inputs coming from one side of space and explicit knowledge of sensory incongruence would modulate perceived location of the limb. Specifically, we expected spatial weighting to shift hand localisation towards the weighted area of space, and we expected greater weighting of proprioceptive input once perceived location was demonstrated to be inaccurate. We manipulated spatial weighting using an established auditory cueing paradigm (Experiment 1, n = 18) and sensory incongruence using the 'disappearing hand trick' (Experiment 2, n = 9). Our first hypothesis was not supported-spatial weighting did not modulate hand localisation. Our second hypothesis was only partially supported-disconfirmation of hand position did lead to more accurate localisations, even if participants were still unaware of their hand position. This raised the possibility that rather than disconfirmation, a simple movement of the hand in view could update the sensory-motor system, by immediately increasing the weighting of proprioceptive input relative to visual input. This third hypothesis was then confirmed (Experiment 3, n = 9). These results suggest that hand localisation is robust in the face of differential weighting of space, but open to modulation in a modality-specific manner, when one sense (vision) is rendered inaccurate.

  5. 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.

  6. 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

  7. 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.

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

    PubMed

    Majda, Andrew J; Grote, Marcus J

    2007-01-23

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

  9. 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...

  10. 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

  11. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  12. On the role of attention in generating explicit awareness of contingent relations: evidence from spatial priming.

    PubMed

    Fiacconi, Chris M; Milliken, Bruce

    2011-12-01

    In a series of four experiments, we examine the hypothesis that selective attention is crucial for the generation of conscious knowledge of contingency information. We investigated this question using a spatial priming task in which participants were required to localize a target letter in a probe display. In Experiment 1, participants kept track of the frequency with which the predictive letter in the prime appeared in various locations. This manipulation had a negligible impact on contingency awareness. Subsequent experiments requiring participants to attend to features (color, location) of the predictive letter increased contingency awareness somewhat, but there remained a large proportion of individuals who remained unaware of the strong contingency. Together the results of our experiments suggest that the construct of attention does not fully capture the processes that lead to contingency awareness, and suggest a critical role for bottom-up feature integration in explicit contingency learning. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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

  1. 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

  2. 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

  3. 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.

  4. Linking extinction-colonization dynamics to genetic structure in a salamander metapopulation.

    PubMed

    Cosentino, Bradley J; Phillips, Christopher A; Schooley, Robert L; Lowe, Winsor H; Douglas, Marlis R

    2012-04-22

    Theory predicts that founder effects have a primary role in determining metapopulation genetic structure. However, ecological factors that affect extinction-colonization dynamics may also create spatial variation in the strength of genetic drift and migration. We tested the hypothesis that ecological factors underlying extinction-colonization dynamics influenced the genetic structure of a tiger salamander (Ambystoma tigrinum) metapopulation. We used empirical data on metapopulation dynamics to make a priori predictions about the effects of population age and ecological factors on genetic diversity and divergence among 41 populations. Metapopulation dynamics of A. tigrinum depended on wetland area, connectivity and presence of predatory fish. We found that newly colonized populations were more genetically differentiated than established populations, suggesting that founder effects influenced genetic structure. However, ecological drivers of metapopulation dynamics were more important than age in predicting genetic structure. Consistent with demographic predictions from metapopulation theory, genetic diversity and divergence depended on wetland area and connectivity. Divergence was greatest in small, isolated wetlands where genetic diversity was low. Our results show that ecological factors underlying metapopulation dynamics can be key determinants of spatial genetic structure, and that habitat area and isolation may mediate the contributions of drift and migration to divergence and evolution in local populations.

  5. Linking extinction–colonization dynamics to genetic structure in a salamander metapopulation

    PubMed Central

    Cosentino, Bradley J.; Phillips, Christopher A.; Schooley, Robert L.; Lowe, Winsor H.; Douglas, Marlis R.

    2012-01-01

    Theory predicts that founder effects have a primary role in determining metapopulation genetic structure. However, ecological factors that affect extinction–colonization dynamics may also create spatial variation in the strength of genetic drift and migration. We tested the hypothesis that ecological factors underlying extinction–colonization dynamics influenced the genetic structure of a tiger salamander (Ambystoma tigrinum) metapopulation. We used empirical data on metapopulation dynamics to make a priori predictions about the effects of population age and ecological factors on genetic diversity and divergence among 41 populations. Metapopulation dynamics of A. tigrinum depended on wetland area, connectivity and presence of predatory fish. We found that newly colonized populations were more genetically differentiated than established populations, suggesting that founder effects influenced genetic structure. However, ecological drivers of metapopulation dynamics were more important than age in predicting genetic structure. Consistent with demographic predictions from metapopulation theory, genetic diversity and divergence depended on wetland area and connectivity. Divergence was greatest in small, isolated wetlands where genetic diversity was low. Our results show that ecological factors underlying metapopulation dynamics can be key determinants of spatial genetic structure, and that habitat area and isolation may mediate the contributions of drift and migration to divergence and evolution in local populations. PMID:22113029

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  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. 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.

  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. 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

  17. 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.

  18. Variability in primary productivity determines metapopulation dynamics

    PubMed Central

    2016-01-01

    Temporal variability in primary productivity can change habitat quality for consumer species by affecting the energy levels available as food resources. However, it remains unclear how habitat-quality fluctuations may determine the dynamics of spatially structured populations, where the effects of habitat size, quality and isolation have been customarily assessed assuming static habitats. We present the first empirical evaluation on the effects of stochastic fluctuations in primary productivity—a major outcome of ecosystem functions—on the metapopulation dynamics of a primary consumer. A unique 13-year dataset from an herbivore rodent was used to test the hypothesis that inter-annual variations in primary productivity determine spatiotemporal habitat occupancy patterns and colonization and extinction processes. Inter-annual variability in productivity and in the growing season phenology significantly influenced habitat colonization patterns and occupancy dynamics. These effects lead to changes in connectivity to other potentially occupied habitat patches, which then feed back into occupancy dynamics. According to the results, the dynamics of primary productivity accounted for more than 50% of the variation in occupancy probability, depending on patch size and landscape configuration. Evidence connecting primary productivity dynamics and spatiotemporal population processes has broad implications for metapopulation persistence in fluctuating and changing environments. PMID:27053739

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  1. 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

  2. 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

  3. 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.

  4. Intermediate disturbance in experimental landscapes improves persistence of beetle metapopulations.

    PubMed

    Govindan, Byju N; Feng, Zhilan; DeWoody, Yssa D; Swihart, Robert K

    2015-03-01

    Human-dominated landscapes often feature patches that fluctuate in suitability through space and time, but there is little experimental evidence relating the consequences of dynamic patches for species persistence. We used a spatially and temporally dynamic metapopulation model to assess and compare metapopulation capacity and persistence for red flour beetles (Tribolium castaneum) in experimental landscapes differentiated by resource structure, patch dynamics (destruction and restoration), and connectivity. High connectivity increased the colonization rate of beetles, but this effect was less pronounced in heterogeneous relative to homogeneous landscapes. Higher connectivity and faster patch dynamics increased extinction rates in landscapes. Lower connectivity promoted density-dependent emigration. Heterogeneous landscapes containing patches of different carrying capacity enhanced landscape-level occupancy probability. The highest metapopulation capacity and persistence was observed in landscapes with heterogeneous patches, low connectivity, and slow patch dynamics. Control landscapes with no patch dynamics exhibited rapid declines in abundance and approached extinction due to increased adult mortality in the matrix, higher pupal cannibalism by adults, and extremely low rates of exchange between remaining habitable patches. Our results highlight the role of intermediate patch dynamics, intermediate connectivity, and the nature of density dependence of emigration for persistence of species in heterogeneous landscapes. Our results also demonstrate the importance of incorporating local dynamics into the estimation of metapopulation capacity for conservation planning.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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...

  18. 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

  19. 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

  20. 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

  1. 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

  2. Spatially Explicit Simulation of Mesotopographic Controls on Peatland Hydrology and Carbon Fluxes

    NASA Astrophysics Data System (ADS)

    Sonnentag, O.; Chen, J. M.; Roulet, N. T.

    2006-12-01

    A number of field carbon flux measurements, paleoecological records, and model simulations have acknowledged the importance of northern peatlands in terrestrial carbon cycling and methane emissions. An important parameter in peatlands that influences both net primary productivity, the net gain of carbon through photosynthesis, and decomposition under aerobic and anaerobic conditions, is the position of the water table. Biological and physical processes involved in peatland carbon dynamics and their hydrological controls operate at different spatial scales. The highly variable hydraulic characteristics of the peat profile and the overall shape of the peat body as defined by its surface topography at the mesoscale (104 m2) are of major importance for peatland water table dynamics. Common types of peatlands include bogs with a slightly domed centre. As a result of the convex profile, their water supply is restricted to atmospheric inputs, and water is mainly shed by shallow subsurface flow. From a modelling perspective the influence of mesotopographic controls on peatland hydrology and thus carbon balance requires that process-oriented models that examine the links between peatland hydrology, ecosystem functioning, and climate must incorporate some form of lateral subsurface flow consideration. Most hydrological and ecological modelling studies in complex terrain explicitly account for the topographic controls on lateral subsurface flow through digital elevation models. However, modelling studies in peatlands often employ simple empirical parameterizations of lateral subsurface flow, neglecting the influence of peatlands low relief mesoscale topography. Our objective is to explicitly simulate the mesotopographic controls on peatland hydrology and carbon fluxes using the Boreal Ecosystem Productivity Simulator (BEPS) adapted to northern peatlands. BEPS is a process-oriented ecosystem model in a remote sensing framework that takes into account peatlands multi

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography

    NASA Astrophysics Data System (ADS)

    Sonnentag, O.; Chen, J. M.; Roulet, N. T.; Ju, W.; Govind, A.

    2008-06-01

    Carbon dynamics in peatlands are controlled, in large part, by their wetness as defined by water table depth and volumetric liquid soil moisture content. A common type of peatland is raised bogs that typically have a multiple-layer canopy of vascular plants over a Sphagnum moss ground cover. Their convex form restricts water supply to precipitation and water is shed toward the margins, usually by lateral subsurface flow. The hydraulic gradient for lateral subsurface flow is governed by the peat surface topography at the mesoscale (˜200 m to 5 km). To investigate the influence of mesoscale topography on wetness, evapotranspiration (ET), and gross primary productivity (GPP) in a bog during the snow-free period, we compare the outputs of a further developed version of the daily Boreal Ecosystem Productivity Simulator (BEPS) with observations made at the Mer Bleue peatland, located near Ottawa, Canada. Explicitly considering mesoscale topography, simulated total ET and GPP correlate well with measured ET (r = 0.91) and derived gross ecosystem productivity (GEP; r = 0.92). Both measured ET and derived GEP are simulated similarly well when mesoscale topography is neglected, but daily simulated values are systematically underestimated by about 10% and 12% on average, respectively, due to greater wetness resulting from the lack of lateral subsurface flow. Owing to the differences in moss surface conductances of water vapor and carbon dioxide with increasing moss water content, the differences in the spatial patterns of simulated total ET and GPP are controlled by the mesotopographic position of the moss ground cover.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  11. 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.

  12. Probabilistic measures of persistence and extinction in measles (meta)populations

    PubMed Central

    Gunning, Christian E.; Wearing, Helen J.

    2013-01-01

    Persistence and extinction are fundamental processes in ecological systems that are difficult to accurately measure due to stochasticity and incomplete observation. Moreover, these processes operate on multiple scales, from individual populations to metapopulations. Here we examine an extensive new dataset of measles case reports and associated demographics in pre-vaccine era U.S. cities, alongside a classic England & Wales dataset. We first infer the per-population quasi-continuous distribution of log incidence. We then use stochastic, spatially implicit metapopulation models to explore the frequency of rescue events and apparent extinctions. We show that, unlike critical community size, the inferred distributions account for observational processes, allowing direct comparisons between metapopulations. The inferred distributions scale with population size. We use these scalings to estimate extinction boundary probabilities. We compare these predictions with measurements in individual populations and random aggregates of populations, highlighting the importance of medium-sized populations in metapopulation persistence. PMID:23782847

  13. Ecological and genetic basis of metapopulation persistence of the Glanville fritillary butterfly in fragmented landscapes

    PubMed Central

    Hanski, Ilkka; Schulz, Torsti; Wong, Swee Chong; Ahola, Virpi; Ruokolainen, Annukka; Ojanen, Sami P.

    2017-01-01

    Ecologists are challenged to construct models of the biological consequences of habitat loss and fragmentation. Here, we use a metapopulation model to predict the distribution of the Glanville fritillary butterfly during 22 years across a large heterogeneous landscape with 4,415 small dry meadows. The majority (74%) of the 125 networks into which the meadows were clustered are below the extinction threshold for long-term persistence. Among the 33 networks above the threshold, spatial configuration and habitat quality rather than the pooled habitat area predict metapopulation size and persistence, but additionally allelic variation in a SNP in the gene Phosphoglucose isomerase (Pgi) explains 30% of variation in metapopulation size. The Pgi genotypes are associated with dispersal rate and hence with colonizations and extinctions. Associations between Pgi genotypes, population turnover and metapopulation size reflect eco-evolutionary dynamics, which may be a common feature in species inhabiting patch networks with unstable local dynamics. PMID:28211463

  14. Ecological and genetic basis of metapopulation persistence of the Glanville fritillary butterfly in fragmented landscapes.

    PubMed

    Hanski, Ilkka; Schulz, Torsti; Wong, Swee Chong; Ahola, Virpi; Ruokolainen, Annukka; Ojanen, Sami P

    2017-02-17

    Ecologists are challenged to construct models of the biological consequences of habitat loss and fragmentation. Here, we use a metapopulation model to predict the distribution of the Glanville fritillary butterfly during 22 years across a large heterogeneous landscape with 4,415 small dry meadows. The majority (74%) of the 125 networks into which the meadows were clustered are below the extinction threshold for long-term persistence. Among the 33 networks above the threshold, spatial configuration and habitat quality rather than the pooled habitat area predict metapopulation size and persistence, but additionally allelic variation in a SNP in the gene Phosphoglucose isomerase (Pgi) explains 30% of variation in metapopulation size. The Pgi genotypes are associated with dispersal rate and hence with colonizations and extinctions. Associations between Pgi genotypes, population turnover and metapopulation size reflect eco-evolutionary dynamics, which may be a common feature in species inhabiting patch networks with unstable local dynamics.

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. 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

  18. 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

  19. 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.

  20. Empirical determinants of measles metapopulation dynamics in England and Wales.

    PubMed

    Finkenstädt, B; Grenfell, B

    1998-02-07

    A key issue in metapopulation dynamics is the relative impact of internal patch dynamics and coupling between patches. This problem can be addressed by analysing large spatiotemporal data sets, recording the local and global dynamics of metapopulations. In this paper, we analyse the dynamics of measles meta-populations in a large spatiotemporal case notification data set, collected during the pre-vaccination era in England and Wales. Specifically, we use generalized linear statistical models to quantify the relative importance of local influences (birth rate and population size) and regional coupling on local epidemic dynamics. Apart from the proportional effect of local population size on case totals, the models indicate patterns of local and regional dynamic influences which depend on the current state of epidemics. Birth rate and geographic coupling are not associated with the size of major epidemics. By contrast, minor epidemics--and especially the incidence of local extinction of infection--are influenced both by birth rate and geographical coupling. Birth rate at a lag of four years provides the best fit, reflecting the delayed recruitment of susceptibles to school cohorts. A hierarchical index of spatial coupling to large centres provides the best spatial model. The model also indicates that minor epidemics and extinction patterns are more strongly influenced by this regional effect than the local impact of birth rate.

  1. 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.

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

    PubMed Central

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

    2008-01-01

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

  3. Gene genealogies in a metapopulation.

    PubMed Central

    Wakeley, J; Aliacar, N

    2001-01-01

    A simple genealogical process is found for samples from a metapopulation, which is a population that is subdivided into a large number of demes, each of which is subject to extinction and recolonization and receives migrants from other demes. As in the migration-only models studied previously, the genealogy of any sample includes two phases: a brief sample-size adjustment followed by a coalescent process that dominates the history. This result will hold for metapopulations that are composed of a large number of demes. It is robust to the details of population structure, as long as the number of possible source demes of migrants and colonists for each deme is large. Analytic predictions about levels of genetic variation are possible, and results for average numbers of pairwise differences within and between demes are given. Further analysis of the expected number of segregating sites in a sample from a single deme illustrates some previously known differences between migration and extinction/recolonization. The ancestral process is also amenable to computer simulation. Simulation results show that migration and extinction/recolonization have very different effects on the site-frequency distribution in a sample from a single deme. Migration can cause a U-shaped site-frequency distribution, which is qualitatively similar to the pattern reported recently for positive selection. Extinction and recolonization, in contrast, can produce a mode in the site-frequency distribution at intermediate frequencies, even in a sample from a single deme. PMID:11606561

  4. New Genes in Traditional Seed Systems: Diffusion, Detectability and Persistence of Transgenes in a Maize Metapopulation

    PubMed Central

    van Heerwaarden, Joost; Ortega Del Vecchyo, Diego; Alvarez-Buylla, Elena R.; Bellon, Mauricio R.

    2012-01-01

    Gene flow of transgenes into non-target populations is an important biosafety concern. The case of genetically modified (GM) maize in Mexico has been of particular interest because of the country’s status as center of origin and landrace diversity. In contrast to maize in the U.S. and Europe, Mexican landraces form part of an evolving metapopulation in which new genes are subject to evolutionary processes of drift, gene flow and selection. Although these processes are affected by seed management and particularly seed flow, there has been little study into the population genetics of transgenes under traditional seed management. Here, we combine recently compiled data on seed management practices with a spatially explicit population genetic model to evaluate the importance of seed flow as a determinant of the long-term fate of transgenes in traditional seed systems. Seed flow between farmers leads to a much wider diffusion of transgenes than expected by pollen movement alone, but a predominance of seed replacement over seed mixing lowers the probability of detection due to a relative lack of homogenization in spatial frequencies. We find that in spite of the spatial complexities of the modeled system, persistence probabilities under positive selection are estimated quite well by existing theory. Our results have important implications concerning the feasibility of long term transgene monitoring and control in traditional seed systems. PMID:23056246

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

    PubMed

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

    2011-04-01

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

  6. Metapopulation extinction caused by mutation accumulation

    PubMed Central

    Higgins, Kevin; Lynch, Michael

    2001-01-01

    Theory suggests that the risk of extinction by mutation accumulation can be comparable to that by environmental stochasticity for an isolated population smaller than a few thousand individuals. Here we show that metapopulation structure, habitat loss or fragmentation, and environmental stochasticity can be expected to greatly accelerate the accumulation of mildly deleterious mutations, lowering the genetic effective size to such a degree that even large metapopulations may be at risk of extinction. Because of mutation accumulation, viable metapopulations may need to be far larger and better connected than would be required under just stochastic demography. PMID:11226343

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  8. 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.

  9. 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.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  12. 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 ...

  13. 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 ...

  14. 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.

  15. 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 ...

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

    EPA Science Inventory

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

  17. 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...

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  1. 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...

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

    EPA Science Inventory

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

  3. Metapopulation dynamics and the evolution of dispersal

    NASA Astrophysics Data System (ADS)

    Parvinen, Kalle

    A metapopulation consists of local populations living in habitat patches. In this chapter metapopulation dynamics and the evolution of dispersal is studied in two metapopulation models defined in discrete time. In the first model there are finitely many patches, and in the other one there are infinitely many patches, which allows to incorporate catastrophes into the model. In the first model, cyclic local population dynamics can be either synchronized or not, and increasing dispersal both synchronizes and stabilizes metapopulation dynamics. On the other hand, the type of dynamics has a strong effect on the evolution of dispersal. In case of non-synchronized metapopulation dynamics, dispersal is much more beneficial than in the case of synchronized metapopulation dynamics. Local dynamics has a substantial effect also on the possibility of evolutionary branching in both models. Furthermore, with an Allee effect in the local dynamics of the second model, even evolutionary suicide can occur. It is an evolutionary process in which a viable population adapts in such a way that it can no longer persist.

  4. Spatially Explicit Observations to Elucidate Simple Scalars of Forest Canopy Transpiration Across Environmental Gradients

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

    The ability to scale from point measurements to watersheds has been a key goal of 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. To test this, we chose a site in the Chequamegon National Forest near Park Falls, WI because of its proximity to the WLEF Ameriflux tower providing kilometer scale estimates of water fluxes from a heterogeneous forest. We used a cyclic sampling design for all 144 plots of spatial measurements within a 1.5 ha area, in order to efficiently quantify spatial trends using geostatistics. Spatial data was collected for sap flux using Granier type sensors daily for ten days in 170 trees representing 7 species, including aspen, alder, and white cedar. Aspen is a dominant species in the managed forests around the WLEF tower and we have previously shown it to have the highest transpiration rates per unit leaf area of all dominant species in the area. Consequently, for this study we focused on aspen. Spatial soil moisture, vapor pressure deficit, and leaf area index were also measured periodically at the same 144 plots. We found that the semivariagram of soil moisture showed a range of 110 meters on a low soil moisture day and 80 meters on a high soil moisture day. When we quantified sap flux per unit xylem area across a 105-meter long gradient from a wetland to an upland we found no differences. However, once we scaled the sap flux measurements to the whole tree using basal area, there was more than a 100 percent increase in whole tree water use in the upland area in comparison to the wetland area. Thus, we will test the hypothesis that in the absence of moisture stress, canopy transpiration in aspen varies spatially with allometrically scaled sapwood area and leaf area and not as a function of sap flux per unit sapwood area.

  5. 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.

  6. 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

  7. Synchrony in Metapopulations with Sporadic Dispersal

    NASA Astrophysics Data System (ADS)

    Jeter, Russell; Belykh, Igor

    2015-06-01

    We study synchronization in ecological networks under the realistic assumption that the coupling among the patches is sporadic/stochastic and due to rare and short-term meteorological conditions. Each patch is described by a tritrophic food chain model, representing the producer, consumer, and predator. If all three species can migrate, we rigorously prove that the network can synchronize as long as the migration occurs frequently, i.e. fast compared to the period of the ecological cycle, even though the network is disconnected most of the time. In the case where only the top trophic level (i.e. the predator) can migrate, we reveal an unexpected range of intermediate switching frequencies where synchronization becomes stable in a network which switches between two nonsynchronous dynamics. As spatial synchrony increases the danger of extinction, this counterintuitive effect of synchrony emerging from slower switching dispersal can be destructive for overall metapopulation persistence, presumably expected from switching between two dynamics which are unfavorable to extinction.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    PubMed Central

    Kitchen, James L.; Allaby, Robin G.

    2013-01-01

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

  10. 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.

  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. 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...

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

    USDA-ARS?s Scientific Manuscript database

    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...

  14. Linking climate change and fish conservation efforts using spatially explicit decision support tools

    Treesearch

    Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

    2013-01-01

    Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

  15. 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...

  16. Spatially explicit forecasts of large wildland fire probability and suppression costs for California

    Treesearch

    Haiganoush Preisler; Anthony L. Westerling; Krista M. Gebert; Francisco Munoz-Arriola; Thomas P. Holmes

    2011-01-01

    In the last decade, increases in fire activity and suppression expenditures have caused budgetary problems for federal land management agencies. Spatial forecasts of upcoming fire activity and costs have the potential to help reduce expenditures, and increase the efficiency of suppression efforts, by enabling them to focus resources where they have the greatest effect...

  17. Spatially explicit measurements of forest structure and fire behavior following restoration treatments in dry forests

    Treesearch

    Justin Paul Ziegler; Chad Hoffman; Michael Battaglia; William Mell

    2017-01-01

    Restoration treatments in dry forests of the western US often attempt silvicultural practices to restore the historical characteristics of forest structure and fire behavior. However, it is suggested that a reliance on non-spatial metrics of forest stand structure, along with the use of wildland fire behavior models that lack the ability to handle complex structures,...

  18. Comparing spatially explicit ecological and social values for natural areas to identify effective conservation strategies.

    PubMed

    Bryan, Brett Anthony; Raymond, Christopher Mark; Crossman, Neville David; King, Darran

    2011-02-01

    Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science-based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science-based conservation planning.

  19. Patch definition in metapopulation analysis: a graph theory approach to solve the mega-patch problem.

    PubMed

    Cavanaugh, Kyle C; Siegel, David A; Raimondi, Peter T; Alberto, Filipe

    2014-02-01

    The manner in which patches are delineated in spatially realistic metapopulation models will influence the size, connectivity, and extinction and recolonization dynamics of those patches. Most commonly used patch-definition methods focus on identifying discrete, contiguous patches of habitat from a single temporal observation of species occurrence or from a model of habitat suitability. However, these approaches are not suitable for many metapopulation systems where entire patches may not be fully colonized at a given time. For these metapopulation systems, a single large patch of habitat may actually support multiple, interacting subpopulations. The interactions among these subpopulations will be ignored if the patch is treated as a single unit, a situation we term the "mega-patch problem." Mega-patches are characterized by variable intra-patch synchrony, artificially low inter-patch connectivity, and low extinction rates. One way to detect this problem is by using time series data to calculate demographic synchrony within mega-patches. We present a framework for identifying subpopulations in mega-patches using a combination of spatial autocorrelation and graph theory analyses. We apply our approach to southern California giant kelp (Macrocystis pyrifera) forests using a new, long-term (27 years), satellite-based data set of giant kelp canopy biomass. We define metapopulation patches using our method as well as several other commonly used patch delineation methodologies and examine the colonization and extinction dynamics of the metapopulation under each approach. We find that the relationships between patch characteristics such as area and connectivity and the demographic processes of colonizations and extinctions vary among the different patch-definition methods. Our spatial-analysis/graph-theoretic framework produces results that match theoretical expectations better than the other methods. This approach can be used to identify subpopulations in metapopulations

  20. 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.

  1. Demographic stochasticity reduces the synchronizing effect of dispersal in predator-prey metapopulations.

    PubMed

    Simonis, Joseph L

    2012-07-01

    Dispersal may affect predator-prey metapopulations by rescuing local sink populations from extinction or by synchronizing population dynamics across the metapopulation, increasing the risk of regional extinction. Dispersal is likely influenced by demographic stochasticity, however, particularly because dispersal rates are often very low in metapopulations. Yet the effects of demographic stochasticity on predator-prey metapopulations are not well known. To that end, I constructed three models of a two-patch predator-prey system. The models constitute a hierarchy of complexity, allowing direct comparisons. Two models included demographic stochasticity (pure jump process [PJP] and stochastic differential equations [SDE]), and the third was deterministic (ordinary differential equations [ODE]). One stochastic model (PJP) treated population sizes as discrete, while the other (SDE) allowed population sizes to change continuously. Both stochastic models only produced synchronized predator-prey dynamics when dispersal was high for both trophic levels. Frequent dispersal by only predators or prey in the PJP and SDE spatially decoupled the trophic interaction, reducing synchrony of the non-dispersive species. Conversely, the ODE generated synchronized predator-prey dynamics across all dispersal rates, except when initial conditions produced anti-phase transients. These results indicate that demographic stochasticity strongly reduces the synchronizing effect of dispersal, which is ironic because demographic stochasticity is often invoked post hoc as a driver of extinctions in synchronized metapopulations.

  2. The effects of connectivity on metapopulation persistence: network symmetry and degree correlations.

    PubMed

    Shtilerman, Elad; Stone, Lewi

    2015-05-07

    A spatial metapopulation is a mosaic of interconnected patch populations. The complex routes of colonization between the patches are governed by the metapopulation's dispersal network. Over the past two decades, there has been considerable interest in uncovering the effects of dispersal network topology and its symmetry on metapopulation persistence. While most studies find that the level of symmetry in dispersal pattern enhances persistence, some have reached the conclusion that symmetry has at most a minor effect. In this work, we present a new perspective on the debate. We study properties of the in- and out-degree distribution of patches in the metapopulation which define the number of dispersal routes into and out of a particular patch, respectively. By analysing the spectral radius of the dispersal matrices, we confirm that a higher level of symmetry has only a marginal impact on persistence. We continue to analyse different properties of the in-out degree distribution, namely the 'in-out degree correlation' (IODC) and degree heterogeneity, and find their relationship to metapopulation persistence. Our analysis shows that, in contrast to symmetry, the in-out degree distribution and particularly, the IODC are dominant factors controlling persistence.

  3. Identification of metapopulation dynamics among Northern Goshawks of the Alexander Archipelago, Alaska, and Coastal British Columbia

    USGS Publications Warehouse

    Sonsthagen, Sarah A.; McClaren, Erica L.; Doyle, Frank I.; Titus, K.; Sage, George K.; Wilson, Robert E.; Gust, Judy R.; Talbot, Sandra L.

    2012-01-01

    Northern Goshawks occupying the Alexander Archipelago, Alaska, and coastal British Columbia nest primarily in old-growth and mature forest, which results in spatial heterogeneity in the distribution of individuals across the landscape. We used microsatellite and mitochondrial data to infer genetic structure, gene flow, and fluctuations in population demography through evolutionary time. Patterns in the genetic signatures were used to assess predictions associated with the three population models: panmixia, metapopulation, and isolated populations. Population genetic structure was observed along with asymmetry in gene flow estimates that changed directionality at different temporal scales, consistent with metapopulation model predictions. Therefore, Northern Goshawk assemblages located in the Alexander Archipelago and coastal British Columbia interact through a metapopulation framework, though they may not fit the classic model of a metapopulation. Long-term population sources (coastal mainland British Columbia) and sinks (Revillagigedo and Vancouver islands) were identified. However, there was no trend through evolutionary time in the directionality of dispersal among the remaining assemblages, suggestive of a rescue-effect dynamic. Admiralty, Douglas, and Chichagof island complex appears to be an evolutionarily recent source population in the Alexander Archipelago. In addition, Kupreanof island complex and Kispiox Forest District populations have high dispersal rates to populations in close geographic proximity and potentially serve as local source populations. Metapopulation dynamics occurring in the Alexander Archipelago and coastal British Columbia by Northern Goshawks highlight the importance of both occupied and unoccupied habitats to long-term population persistence of goshawks in this region.

  4. 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.

  5. imVisIR - spatially explicit characterisation of soil organic matter quality on the pedon scale

    NASA Astrophysics Data System (ADS)

    Steffens, Markus; Kohlpaintner, Michael; Buddenbaum, Henning

    2014-05-01

    Organic matter (OM) is an important soil component controlling many chemical and physical properties ranging from nutrient and pollutant sorption to aggregate stability and water holding capacity. Advanced techniques and sophisticated methods have been developed to characterise and separate qualitatively different fractions of SOM. Despite its importance and the technical progress, two main deficiencies still constrain the comprehensive analysis of OM quantity and quality in soils: 1) Most of the techniques (e.g. solid state 13C NMR spectroscopy or fourier-transformed infrared spectroscopy) are destructive so that the sample is lost after the measurement; and 2) SOM quantity and quality generally show a heterogeneous spatial distribution across many scales which is not considered in an adequate way in most studies since the analytical techniques require substantial amounts of soil material impeding the sampling of small structures. The natural arrangement of particles is disturbed and information about the spatial variability and association with other particles is lost. Therefore, an imaging technique that non-destructively measures SOM quantity and quality with a high spatial resolution on the pedon scale is needed. We show the potential of laboratory imaging Vis-NIR spectroscopy for the qualitative mapping of SOM on the pedon scale.

  6. 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.

  7. Integrating landscape genomics and spatially explicit approaches to detect loci under selection in clinal populations.

    PubMed

    Jones, Matthew R; Forester, Brenna R; Teufel, Ashley I; Adams, Rachael V; Anstett, Daniel N; Goodrich, Betsy A; Landguth, Erin L; Joost, Stéphane; Manel, Stéphanie

    2013-12-01

    Uncovering the genetic basis of adaptation hinges on the ability to detect loci under selection. However, population genomics outlier approaches to detect selected loci may be inappropriate for clinal populations or those with unclear population structure because they require that individuals be clustered into populations. An alternate approach, landscape genomics, uses individual-based approaches to detect loci under selection and reveal potential environmental drivers of selection. We tested four landscape genomics methods on a simulated clinal population to determine their effectiveness at identifying a locus under varying selection strengths along an environmental gradient. We found all methods produced very low type I error rates across all selection strengths, but elevated type II error rates under "weak" selection. We then applied these methods to an AFLP genome scan of an alpine plant, Campanula barbata, and identified five highly supported candidate loci associated with precipitation variables. These loci also showed spatial autocorrelation and cline patterns indicative of selection along a precipitation gradient. Our results suggest that landscape genomics in combination with other spatial analyses provides a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

  8. A common framework for conservation planning: Linking individual and metapopulation models [Chapter 7

    Treesearch

    Barry R. Noon; Kevin S. McKelvey

    1996-01-01

    Many populations exhibit pronounced spatial structure: dispersed areas of high population density embedded in areas of low density, with population centers connected through dispersal. This recognition has led many conservation biologists to embrace the metapopulation concept (Levins 1970) as the appropriate paradigm for reserve design structures (reviewed in Hanski...

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  10. A novel spatially-explicit condition for the onset of waterborne diseases in complex environments

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    In spatial models of waterborne infections the condition that all the local reproduction numbers be larger than one is neither necessary nor sufficient for outbreaks to occur. Here, to properly determine epidemic onset conditions, we examine the transition from stable to unstable of the disease-free equilibrium of a system of nonlinear differential equations characterizing the evolution of susceptible and infected individuals within their respective settlements, and pathogen concentration in their accessible environment. Two different network connectivity layers are assumed to link human settlements: hydrologic pathways serve as ecological corridors for pathogens, while human mobility acts as disease vehicle through susceptibles contracting the disease and asymptomatic infectives shedding bacteria at their temporary destinations. We show that an epidemic outbreak can be triggered if the dominant eigenvalue of a generalized reproduction matrix G0, suitably accounting for spatial distribution of human settlements, hydrological pathways for pathogen dispersal and pathogen redistribution mechanisms due to human mobility, is larger than unity. Matrix G0 and its dominant eigenvalue thus replace the usual reproduction number whenever spatial effects on disease propagation cannot be ignored. Conversely, our novel criterion decays into the standard onset condition based on local reproduction numbers in nonspatial settings. By analyzing realistic test cases we show that within a connected network system the disease can start even if all the local reproduction numbers are smaller than unity, or might not start even if all the local reproduction numbers are larger than unity. We also show that onset geography in complex environments is linked to the dominant eigenvector of matrix G0. Applications to cholera outbreaks in developing countries demonstrate that our approach can be successfully used for disease prediction and emergency management.

  11. 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.

  12. Spatially explicit methane emissions from petroleum production and the natural gas system in California.

    PubMed

    Jeong, Seongeun; Millstein, Dev; Fischer, Marc L

    2014-05-20

    We present a new, spatially resolved inventory of methane (CH4) emissions based on US-EPA emission factors and publically available activity data for 2010 California petroleum production and natural gas production, processing, transmission, and distribution. Compared to official California bottom-up inventories, our initial estimates are 3 to 7 times higher for the petroleum and natural gas production sectors but similar for the natural gas transmission and distribution sectors. Evidence from published "top-down" atmospheric measurement campaigns within Southern California supports our initial emission estimates from production and processing but indicates emission estimates from transmission and distribution are low by a factor of approximately 2. To provide emission maps with more accurate total emissions we scale the spatially resolved inventory by sector-specific results from a Southern California aircraft measurement campaign to all of California. Assuming uncertainties are determined by the uncertainties estimated in the top-down study, our estimated state total CH4 emissions are 541 ± 144 Gg yr(-1) (as compared with 210.7 Gg yr(-1) in California's current official inventory), where the majority of our reported uncertainty is derived from transmission and distribution. We note uncertainties relative to the mean for a given region are likely larger than that for the State total, emphasizing the need for additional measurements in undersampled regions.

  13. Spatially explicit predictions of blood parasites in a widely distributed African rainforest bird.

    PubMed

    Sehgal, R N M; Buermann, W; Harrigan, R J; Bonneaud, C; Loiseau, C; Chasar, A; Sepil, I; Valkiūnas, G; Iezhova, T; Saatchi, S; Smith, T B

    2011-04-07

    Critical to the mitigation of parasitic vector-borne diseases is the development of accurate spatial predictions that integrate environmental conditions conducive to pathogen proliferation. Species of Plasmodium and Trypanosoma readily infect humans, and are also common in birds. Here, we develop predictive spatial models for the prevalence of these blood parasites in the olive sunbird (Cyanomitra olivacea). Since this species exhibits high natural parasite prevalence and occupies diverse habitats in tropical Africa, it represents a distinctive ecological model system for studying vector-borne pathogens. We used PCR and microscopy to screen for haematozoa from 28 sites in Central and West Africa. Species distribution models were constructed to associate ground-based and remotely sensed environmental variables with parasite presence. We then used machine-learning algorithm models to identify relationships between parasite prevalence and environmental predictors. Finally, predictive maps were generated by projecting model outputs to geographically unsampled areas. Results indicate that for Plasmodium spp., the maximum temperature of the warmest month was most important in predicting prevalence. For Trypanosoma spp., seasonal canopy moisture variability was the most important predictor. The models presented here visualize gradients of disease prevalence, identify pathogen hotspots and will be instrumental in studying the effects of ecological change on these and other pathogens.

  14. The shift from plant-plant facilitation to competition under severe water deficit is spatially explicit.

    PubMed

    O'Brien, Michael J; Pugnaire, Francisco I; Armas, Cristina; Rodríguez-Echeverría, Susana; Schöb, Christian

    2017-04-01

    The stress-gradient hypothesis predicts a higher frequency of facilitative interactions as resource limitation increases. Under severe resource limitation, it has been suggested that facilitation may revert to competition, and identifying the presence as well as determining the magnitude of this shift is important for predicting the effect of climate change on biodiversity and plant community dynamics. In this study, we perform a meta-analysis to compare temporal differences of species diversity and productivity under a nurse plant (Retama sphaerocarpa) with varying annual rainfall quantity to test the effect of water limitation on facilitation. Furthermore, we assess spatial differences in the herbaceous community under nurse plants in situ during a year with below-average rainfall. We found evidence that severe rainfall deficit reduced species diversity and plant productivity under nurse plants relative to open areas. Our results indicate that the switch from facilitation to competition in response to rainfall quantity is nonlinear. The magnitude of this switch depended on the aspect around the nurse plant. Hotter south aspects under nurse plants resulted in negative effects on beneficiary species, while the north aspect still showed facilitation. Combined, these results emphasize the importance of spatial heterogeneity under nurse plants for mediating species loss under reduced precipitation, as predicted by future climate change scenarios. However, the decreased water availability expected under climate change will likely reduce overall facilitation and limit the role of nurse plants as refugia, amplifying biodiversity loss.

  15. Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.

    USGS Publications Warehouse

    Flint, Paul L.; Grand, James B.; Petersen, Margaret; Rockwell, Robert F.

    2016-01-01

    subpopulation is independent and that future management actions may be improved through a metapopulation framework. For example, management actions could include displacement of breeding females from"sink" areas that reduce the growth potential of the population as a whole. However, this action is contingent upon dispersal among local populations, for which there is limited information. Thus, we recommend that researchers examine dispersal behavior among areas on the Yukon-Kuskokwim Delta in western Alaska. The metapopulation framework could also be applied at the rangewide scale to address the density-dependent limitation of available polynya habitat during winter that may limit the recovery of small subpopulations, such as that on the Yukon-Kuskokwim Delta. Reductions in other subpopulations may be necessary to ensure an increase in the Yukon-Kuskokwim Delta population. Thus, we recommend that managers consider the interpopulation dynamics of spectacled eiders at different spatial scales in future management actions.

  16. 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

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  19. 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.

  20. 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.

  1. Spatially-Explicit Assessments of Genetic Biodiversity and Dispersal in Gopher Tortoises for Evaluation of Habitat Fragmentation at DoD Sites

    DTIC Science & Technology

    2008-10-01

    FINAL REPORT Spatially -Explicit Assessments of Genetic Biodiversity and Dispersal in Gopher Tortoises for Evaluation of Habitat Fragmentation...5.2.1 Specific Aim # 1: Testing If the Populations Are Spatially Structured...Program (SERDP) for the financial assistance that enabled undertaking this project. Appreciation for technical assistance is extended to Mr. Bradley

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

  3. 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.

  4. 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).

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

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

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

    2016-04-01

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

  11. 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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

  15. 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.

  16. Ethiopian wheat yield and yield gap estimation: A spatially explicit small area integrated data approach.

    PubMed

    Mann, Michael L; Warner, James M

    2017-02-01

    Despite the routine collection of annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has integrated these data sources in estimating developing nations' agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 principal Meher crop seasons at the kebele administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. Reflecting on the high interannual variability in output per hectare, we explore whether these changes can be explained by weather, shocks to, and management of rain-fed agricultural systems. The model identifies specific contributors to wheat yields that include farm management techniques (e.g. area planted, improved seed, fertilizer, and irrigation), weather (e.g. rainfall), water availability (e.g. vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their locally attainable wheat yields given their altitude, weather conditions, terrain, and plant health. In conclusion, we believe the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

  17. Explicit consideration of spatial hydrogen bonding direction for activity coefficient prediction based on implicit solvation calculations.

    PubMed

    Chen, Wei-Lin; Lin, Shiang-Tai

    2017-08-09

    The activity coefficient of a chemical in a mixture is important in understanding the thermodynamic properties and non-ideality of the mixture. The COSMO-SAC model based on the result of quantum mechanical implicit solvation calculations has been shown to provide reliable predictions of activity coefficients for mixed fluids. However, it is found that the prediction accuracy is in general inferior for associating fluids. Existing methods for describing the hydrogen-bonding interaction consider the strength of the interaction based only on the polarity of the screening charges, neglecting the fact that the formation of hydrogen bonds requires a specific orientation between the donor and acceptor pairs. In this work, we propose a new approach that takes into account the spatial orientational constraints in hydrogen bonds. Based on the Valence Shell Electron Pair Repulsion (VSEPR) theory, the molecular surfaces associated with the formation of hydrogen bonds are limited to those in the projection of the lone pair electrons of hydrogen bond acceptors, in addition to the polarity of the surface screening charges. Our results show that this new directional hydrogen bond approach, denoted as the COSMO-SAC(DHB) model, requires fewer universal parameters and is significantly more accurate and reliable compared to previous models for a variety of properties, including vapor-liquid equilibria (VLE), infinite dilution activity coefficient (IDAC) and water-octanol partition coefficient (Kow).

  18. Effects of habitat destruction in a prey-predator metapopulation model

    PubMed

    Bascompte; Sole

    1998-12-07

    A mean field, metapopulation model of a predator-prey interaction is developed in order to understand the consequences of habitate destruction at different trophic levels. Such a model allows is to explore different ecological scenarios (donor control vs. top-down control) by changing a single parameter. The response to habitat destruction is qualitatively the same for both predator and prey, although there are interesting differences linked to the trophic position. A similar decrease in the colonization rates affects the two species quite differently. Predators diminish faster than prey, and furthermore, the fraction of occupied sites decreases more sharply as colonization rates are lowered, i.e. there is a nonlinear relationship between regional abundance and colonization rate. There is a well-defined threshold in the colonization rate below which the predator becomes extinct. Thus, dispersal rate is critical for predicting the consequences of habitat destruction. Finally, these results are compared with the behavior of a spatially explicit simulation. The only difference between the analytical model and the simulation is that colonization is no longer a global phenomenon in the latter, but it is a local process, constrained to the nearest patches. The bulk of the results are similar to the mean field behavior, and we comment on some differences related with non-homogeneity and real space. Some general implications for conservation biology and biological control are outlined. Copyright 1998 Academic Press

  19. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  1. 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.

  2. 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.

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

    USGS Publications Warehouse

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

    2016-01-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  6. Inferring contemporary dispersal processes in plant metapopulations: comparison of direct and indirect estimates of dispersal for the annual species Crepis sancta

    PubMed Central

    Dornier, A; Cheptou, P-O

    2013-01-01

    Analyzing population dynamics in changing habitats is a prerequisite for population dynamics forecasting. The recent development of metapopulation modeling allows the estimation of dispersal kernels based on the colonization pattern but the accuracy of these estimates compared with direct estimates of the seed dispersal kernel has rarely been assessed. In this study, we used recent genetic methods based on parentage analysis (spatially explicit mating models) to estimate seed and pollen dispersal kernels as well as seed and pollen immigration in fragmented urban populations of the plant species Crepis sancta with contrasting patch dynamics. Using two independent networks, we documented substantial seed immigration and a highly restricted dispersal kernel. Moreover, immigration heterogeneity among networks was consistent with previously reported metapopulation dynamics, showing that colonization was mainly due to external colonization in the first network (propagule rain) and local colonization in the second network. We concluded that the differences in urban patch dynamics are mainly due to seed immigration heterogeneity, highlighting the importance of external population source in the spatio-temporal dynamics of plants in a fragmented landscape. The results show that indirect and direct methods were qualitatively consistent, providing a proper interpretation of indirect estimates. This study provides attempts to link genetic and demographic methods and show that patch occupancy models may provide simple methods for analyzing population dynamics in heterogeneous landscapes in the context of global change. PMID:23443058

  7. 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.

  8. A spatially and temporally explicit life cycle inventory of air pollutants from gasoline and ethanol in the United States.

    PubMed

    Tessum, Christopher W; Marshall, Julian D; Hill, Jason D

    2012-10-16

    The environmental health impacts of transportation depend in part on where and when emissions occur during fuel production and combustion. Here we describe spatially and temporally explicit life cycle inventories (LCI) of air pollutants from gasoline, ethanol derived from corn grain, and ethanol from corn stover. Previous modeling for the U.S. by Argonne National Laboratory (GREET: Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) suggested that life cycle emissions are generally higher for ethanol from corn grain or corn stover than for gasoline. Our results show that for ethanol, emissions are concentrated in the Midwestern "Corn Belt". We find that life cycle emissions from ethanol exhibit different temporal patterns than from gasoline, reflecting seasonal aspects of farming activities. Enhanced chemical speciation beyond current GREET model capabilities is also described. Life cycle fine particulate matter emissions are higher for ethanol from corn grain than for ethanol from corn stover; for black carbon, the reverse holds. Overall, our results add to existing state-of-the-science transportation fuel LCI by providing spatial and temporal disaggregation and enhanced chemical speciation, thereby offering greater understanding of the impacts of transportation fuels on human health and opening the door to advanced air dispersion modeling of fuel life cycles.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. Impact of mosquito gene drive on malaria elimination in a computational model with explicit spatial and temporal dynamics.

    PubMed

    Eckhoff, Philip A; Wenger, Edward A; Godfray, H Charles J; Burt, Austin

    2017-01-10

    The renewed effort to eliminate malaria and permanently remove its tremendous burden highlights questions of what combination of tools would be sufficient in various settings and what new tools need to be developed. Gene drive mosquitoes constitute a promising set of tools, with multiple different possible approaches including population replacement with introduced genes limiting malaria transmission, driving-Y chromosomes to collapse a mosquito population, and gene drive disrupting a fertility gene and thereby achieving population suppression or collapse. Each of these approaches has had recent success and advances under laboratory conditions, raising the urgency for understanding how each could be deployed in the real world and the potential impacts of each. New analyses are needed as existing models of gene drive primarily focus on nonseasonal or nonspatial dynamics. We use a mechanistic, spatially explicit, stochastic, individual-based mathematical model to simulate each gene drive approach in a variety of sub-Saharan African settings. Each approach exhibits a broad region of gene construct parameter space with successful elimination of malaria transmission due to the targeted vector species. The introduction of realistic seasonality in vector population dynamics facilitates gene drive success compared with nonseasonal analyses. Spatial simulations illustrate constraints on release timing, frequency, and spatial density in the most challenging settings for construct success. Within its parameter space for success, each gene drive approach provides a tool for malaria elimination unlike anything presently available. Provided potential barriers to success are surmounted, each achieves high efficacy at reducing transmission potential and lower delivery requirements in logistically challenged settings.

  15. 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.

  16. Impact of mosquito gene drive on malaria elimination in a computational model with explicit spatial and temporal dynamics

    PubMed Central

    Eckhoff, Philip A.; Wenger, Edward A.; Godfray, H. Charles J.; Burt, Austin

    2017-01-01

    The renewed effort to eliminate malaria and permanently remove its tremendous burden highlights questions of what combination of tools would be sufficient in various settings and what new tools need to be developed. Gene drive mosquitoes constitute a promising set of tools, with multiple different possible approaches including population replacement with introduced genes limiting malaria transmission, driving-Y chromosomes to collapse a mosquito population, and gene drive disrupting a fertility gene and thereby achieving population suppression or collapse. Each of these approaches has had recent success and advances under laboratory conditions, raising the urgency for understanding how each could be deployed in the real world and the potential impacts of each. New analyses are needed as existing models of gene drive primarily focus on nonseasonal or nonspatial dynamics. We use a mechanistic, spatially explicit, stochastic, individual-based mathematical model to simulate each gene drive approach in a variety of sub-Saharan African settings. Each approach exhibits a broad region of gene construct parameter space with successful elimination of malaria transmission due to the targeted vector species. The introduction of realistic seasonality in vector population dynamics facilitates gene drive success compared with nonseasonal analyses. Spatial simulations illustrate constraints on release timing, frequency, and spatial density in the most challenging settings for construct success. Within its parameter space for success, each gene drive approach provides a tool for malaria elimination unlike anything presently available. Provided potential barriers to success are surmounted, each achieves high efficacy at reducing transmission potential and lower delivery requirements in logistically challenged settings. PMID:28028208

  17. Metapopulation capacity of evolving fluvial landscapes

    NASA Astrophysics Data System (ADS)

    Bertuzzo, Enrico; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

    2015-04-01

    The form of fluvial landscapes is known to attain stationary network configurations that settle in dynamically accessible minima of total energy dissipation by landscape-forming discharges. Recent studies have highlighted the role of the dendritic structure of river networks in controlling population dynamics of the species they host and large-scale biodiversity patterns. Here, we systematically investigate the relation between energy dissipation, the physical driver for the evolution of river networks, and the ecological dynamics of their embedded biota. To that end, we use the concept of metapopulation capacity, a measure to link landscape structures with the population dynamics they host. Technically, metapopulation capacity is the leading eigenvalue λM of an appropriate "landscape" matrix subsuming whether a given species is predicted to persist in the long run. λM can conveniently be used to rank different landscapes in terms of their capacity to support viable metapopulations. We study how λM changes in response to the evolving network configurations of spanning trees. Such sequence of configurations is theoretically known to relate network selection to general landscape evolution equations through imperfect searches for dynamically accessible states frustrated by the vagaries of Nature. Results show that the process shaping the metric and the topological properties of river networks, prescribed by physical constraints, leads to a progressive increase in the corresponding metapopulation capacity and therefore on the landscape capacity to support metapopulations—with implications on biodiversity in fluvial ecosystems.

  18. Network Analysis Shows Asymmetrical Flows within a Bird Metapopulation

    PubMed Central

    Rojas, Emilio R.; Sueur, Cédric; Henry, Pierre-Yves; Doligez, Blandine; Wey, Gérard; Dehorter, Olivier; Massemin, Sylvie

    2016-01-01

    How the spatial expansion of a species changes at a human time scale is a process difficult to determine. We studied the dispersal pattern of the French white stork population, using a 21-year ringing/resighting dataset. We used the graph-theory to investigate the strength of links between 5 populations (North-East, North-West, Centre, West, and South) and to determine factors important for the birds’ movements. Two clusters of populations were identified within the metapopulation, with most frequent movements of individuals between North-Eastern and Centre populations, and between North-Western and Western populations. Exchanges of individuals between populations were asymmetrical, where North-Eastern and North-Western populations provided more emigrants than they received immigrants. Neither the geographical distance between populations, nor the difference in densities influenced the number of individuals exchanging between populations. The graph-theory approach provides a dynamic view of individual movements within a metapopulation and might be useful for future population studies in the context of conservation. PMID:27893770

  19. Spatio-temporal variation in the strength and mode of selection acting on major histocompatibility complex diversity in water vole (Arvicola terrestris) metapopulations.

    PubMed

    Oliver, Matthew K; Lambin, Xavier; Cornulier, Thomas; Piertney, Stuart B

    2009-01-01

    Patterns of spatio-temporal genetic variation at a class II major histocompatibility complex (MHC) locus and multiple microsatellite loci were analysed within and between three water vole metapopulations in Scotland, UK. Comparisons of MHC and microsatellite spatial genetic differentiation, based on standardised tests between two demographically asynchronous zones within a metapopulation, suggested that spatial MHC variation was affected by balancing selection, directional selection and random genetic drift, but that the relative effects of these microevolutionary forces vary temporally. At the metapopulation level, between-year differentiation for MHC loci was significantly correlated with that of microsatellites, signifying that neutral factors such as migration and drift were primarily responsible for overall temporal genetic change at the metapopulation scale. Between metapopulations, patterns of genetic differentiation implied that, at large spatial scales, MHC variation was primarily affected by directional selection and drift. Levels of MHC heterozygosity in excess of Hardy-Weinberg expectations were consistent with overdominant balancing selection operating on MHC variation within metapopulations. However, this effect was not constant among all samples, indicating temporal variation in the strength of selection relative to other factors. The results highlight the benefit of contrasting variation at MHC with neutral markers to separate the effects of stochastic and deterministic microevolutionary forces, and add to a growing body of evidence showing that the mode and relative strength of selection acting on MHC diversity varies both spatially and temporally.

  20. 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.

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

    PubMed

    Geyer, Roland; Stoms, David; Kallaos, James

    2013-01-15

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

  3. A 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

  4. 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.

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

    PubMed

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

    2016-10-01

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

  6. Spatially explicit fire-climate history of the boreal forest-tundra (Eastern Canada) over the last 2000 years.

    PubMed

    Payette, Serge; Filion, Louise; Delwaide, Ann

    2008-07-12

    Across the boreal forest, fire is the main disturbance factor and driver of ecosystem changes. In this study, we reconstructed a long-term, spatially explicit fire history of a forest-tundra region in northeastern Canada. We hypothesized that current occupation of similar topographic and edaphic sites by tundra and forest was the consequence of cumulative regression with time of forest cover due to compounding fire and climate disturbances. All fires were mapped and dated per 100 year intervals over the last 2,000 years using several fire dating techniques. Past fire occurrences and post-fire regeneration at the northern forest limit indicate 70% reduction of forest cover since 1800 yr BP and nearly complete cessation of forest regeneration since 900 yr BP. Regression of forest cover was particularly important between 1500s-1700s and possibly since 900 yr BP. Although fire frequency was very low over the last 100 years, each fire event was followed by drastic removal of spruce cover. Contrary to widespread belief of northward boreal forest expansion due to recent warming, lack of post-fire recovery during the last centuries, in comparison with active tree regeneration more than 1,000 years ago, indicates that the current climate does not favour such expansion.

  7. 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.

  8. 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.

  9. Intermediate fragmentation per se provides stable predator-prey metapopulation dynamics.

    PubMed

    Cooper, Jennifer K; Li, Jiqiu; Montagnes, David J S

    2012-08-01

    The extent to which a landscape is fragmented affects persistence of predator-prey dynamics. Increasing fragmentation concomitantly imposes conditions that stabilise and destabilise metapopulations. For the first time, we explicitly assessed the hypothesis that intermediate levels provide optimal conditions for stability. We examine four structural changes arising from increased fragmentation: increased fragment number; decreased fragment size; increased connectedness (corridors scaled to fragment); increased fragment heterogeneity (based on connectedness). Using the model predator-prey system (Didinium-Paramecium) we support our hypothesis, by examining replicated metapopulations dynamics at five fragmentation levels. Although both species became extinct without fragmentation, prey survived at low and high levels, and both survived at intermediate levels. By examining time to extinction, maximum abundances, and population asynchrony we conclude that fragmentation produces structural heterogeneity (independent of environmental heterogeneity), which influences stability. Our analysis suggests why some theoretical, field and microcosm studies present conflicting views of fragmentation effects on population persistence.

  10. Comparing large-scale computational approaches to epidemic modeling: agent based versus structured metapopulation models

    NASA Astrophysics Data System (ADS)

    Gonçalves, Bruno; Ajelli, Marco; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José; Merler, Stefano; Vespignani, Alessandro

    2010-03-01

    We provide for the first time a side by side comparison of the results obtained with a stochastic agent based model and a structured metapopulation stochastic model for the evolution of a baseline pandemic event in Italy. The Agent Based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high resolution census data worldwide, and integrating airline travel flow data with short range human mobility patterns at the global scale. Both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing of the order of few days. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes.

  11. 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...

  12. 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, ...

  13. 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

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

    NASA Astrophysics Data System (ADS)

    Hellmann, Christine; Oldeland, Jens; Werner, Christiane

    2015-04-01

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

  15. Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis).

    PubMed

    Kazyak, David C; Hilderbrand, Robert H; King, Tim L; Keller, Stephen R; Chhatre, Vikram E

    2016-01-01

    A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors.

  16. Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis)

    PubMed Central

    Kazyak, David C.; Hilderbrand, Robert H.; King, Tim L.; Keller, Stephen R.; Chhatre, Vikram E.

    2016-01-01

    A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors. PMID:26730588

  17. 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.

  18. 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

  19. 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

  20. 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, 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

  1. Metapopulation Models of Unionid Fish Hosts: Landscape Ecology Theory Applied in the Upper Mississippi River

    NASA Astrophysics Data System (ADS)

    Woolnough, D. A.; Downing, J. A.; Newton, T. J.

    2005-05-01

    Explanations for patterns observed in local assemblages of unionids are frequently sought with reference to interactions between fish host species. We compared the ability of a neutral model to reproduce the fish-mediated movement of larval unionids and examine fish host data from the Upper Mississippi River in comparison with this neutral model. The models focus on the condition of mussel beds (species richness, species abundance, mussel bed size, and size classes) and four measures of fish host connectivity. We considered the non-host fish community (n=57 species) within our neutral model and examined the variation in spatial patterns of fish hosts (n=31 species) and differences in connectivity of the models among mussel beds. We found greater connectivity in main channel and side channel border areas among mussel beds. Using Ripley's K-function we determined that the distribution of host fish species indicate spatial clustering at multiple scales which reflects the spatial clustering of mussel beds in the Upper Mississippi River. This spatial clustering lends itself to metapopulation analysis with host fish providing the connection between populations of unionids; we present a metapopulation equation for unionids and suggest reasons why unionid populations are predisposed to metapopulation analysis.

  2. Unprecedented restoration of a native oyster metapopulation.

    PubMed

    Schulte, David M; Burke, Russell P; Lipcius, Romuald N

    2009-08-28

    Native oyster species were once vital ecosystem engineers, but their populations have collapsed worldwide because of overfishing and habitat destruction. In 2004, we initiated a vast (35-hectare) field experiment by constructing native oyster reefs of three types (high-relief, low-relief, and unrestored) in nine protected sanctuaries throughout the Great Wicomico River in Virginia, United States. Upon sampling in 2007 and 2009, we found a thriving metapopulation comprising 185 million oysters of various age classes. Oyster density was fourfold greater on high-relief than on low-relief reefs, explaining the failure of past attempts. Juvenile recruitment and reef accretion correlated with oyster density, facilitating reef development and population persistence. This reestablished metapopulation is the largest of any native oyster worldwide and validates ecological restoration of native oyster species.

  3. Evolution of specialization in resource utilization in structured metapopulations.

    PubMed

    Nurmi, Tuomas; Geritz, Stefan; Parvinen, Kalle; Gyllenberg, Mats

    2008-07-01

    We study the evolution of resource utilization in a structured discrete-time metapopulation model with an infinite number of patches, prone to local catastrophes. The consumer faces a trade-off in the abilities to consume two resources available in different amounts in each patch. We analyse how the evolution of specialization in the utilization of the resources is affected by different ecological factors: migration, local growth, local catastrophes, forms of the trade-off and distribution of the resources in the patches. Our modelling approach offers a natural way to include more than two patch types into the models. This has not been usually possible in the previous spatially heterogeneous models focusing on the evolution of specialization.

  4. Local enrichment and its nonlocal consequences for victim exploiter metapopulations

    NASA Astrophysics Data System (ADS)

    Yaari, Gur; Solomon, Sorin; Schiffer, Marcelo; Shnerb, Nadav M.

    2008-10-01

    The stabilizing effects of local enrichment are revisited. Diffusively coupled host-parasitoid and predator-prey metapopulations are shown to admit a stable fixed point, limit cycle or stable torus with a rich bifurcation structure. A linear toy model that yields many of the basic qualitative features of this system is presented. The further nonlinear complications are analyzed in the framework of the marginally stable Lotka-Volterra model, and the continuous time analog of the unstable, host-parasitoid Nicholson-Bailey model. The dependence of the results on the migration rate and level of spatial variations is examined, and the possibility of “nonlocal” effect of enrichment, where local enrichment induces stable oscillations at a distance, is studied. A simple method for basic estimation of the relative importance of this effect in experimental systems is presented and exemplified.

  5. The pitcher plant flesh fly exhibits a mixture of patchy and metapopulation attributes.

    PubMed

    Rasic, Gordana; Keyghobadi, Nusha

    2012-01-01

    We investigated the pattern of spatial genetic structure and the extent of gene flow in the pitcher plant flesh fly Fletcherimyia fletcheri, the largest member of the inquiline community of the purple pitcher plant Sarracenia purpurea. Using microsatellite loci, we tested the theoretical predictions of different hypothesized population models (patchy population, metapopulation, or isolated populations) among 11 bogs in Algonquin Provincial Park (Canada). Our results revealed that the pitcher plant flesh fly exhibits a mixture of patchy and metapopulation characteristics. There is significant differentiation among bogs and limited gene flow at larger spatial scales, but local populations do not experience frequent local extinctions/recolonizations. Our findings suggest a strong dispersal ability and stable population sizes in F. fletcheri, providing novel insights into the ecology of this member of a unique ecological microcosm.

  6. Connecting deterministic and stochastic metapopulation models.

    PubMed

    Barbour, A D; McVinish, R; Pollett, P K

    2015-12-01

    In this paper, we study the relationship between certain stochastic and deterministic versions of Hanski's incidence function model and the spatially realistic Levins model. We show that the stochastic version can be well approximated in a certain sense by the deterministic version when the number of habitat patches is large, provided that the presence or absence of individuals in a given patch is influenced by a large number of other patches. Explicit bounds on the deviation between the stochastic and deterministic models are given.

  7. Increasing frequency of low summer precipitation synchronizes dynamics and compromises metapopulation stability in the Glanville fritillary butterfly

    PubMed Central

    Tack, Ayco J. M.; Mononen, Tommi; Hanski, Ilkka

    2015-01-01

    Climate change is known to shift species' geographical ranges, phenologies and abundances, but less is known about other population dynamic consequences. Here, we analyse spatio-temporal dynamics of the Glanville fritillary butterfly (Melitaea cinxia) in a network of 4000 dry meadows during 21 years. The results demonstrate two strong, related patterns: the amplitude of year-to-year fluctuations in the size of the metapopulation as a whole has increased, though there is no long-term trend in average abundance; and there is a highly significant increase in the level of spatial synchrony in population dynamics. The increased synchrony cannot be explained by increasing within-year spatial correlation in precipitation, the key environmental driver of population change, or in per capita growth rate. On the other hand, the frequency of drought during a critical life-history stage (early larval instars) has increased over the years, which is sufficient to explain the increasing amplitude and the expanding spatial synchrony in metapopulation dynamics. Increased spatial synchrony has the general effect of reducing long-term metapopulation viability even if there is no change in average metapopulation size. This study demonstrates how temporal changes in weather conditions can lead to striking changes in spatio-temporal population dynamics. PMID:25854888

  8. Determinants of Genetic Structure in a Nonequilibrium Metapopulation of the Plant Silene latifolia

    PubMed Central

    Fields, Peter D.; Taylor, Douglas R.

    2014-01-01

    Population genetic differentiation will be influenced by the demographic history of populations, opportunities for migration among neighboring demes and founder effects associated with repeated extinction and recolonization. In natural populations, these factors are expected to interact with each other and their magnitudes will vary depending on the spatial distribution and age structure of local demes. Although each of these effects has been individually identified as important in structuring genetic variance, their relative magnitude is seldom estimated in nature. We conducted a population genetic analysis in a metapopulation of the angiosperm, Silene latifolia, from which we had more than 20 years of data on the spatial distribution, demographic history, and extinction and colonization of demes. We used hierarchical Bayesian methods to disentangle which features of the populations contributed to among population variation in allele frequencies, including the magnitude and direction of their effects. We show that population age, long-term size and degree of connectivity all combine to affect the distribution of genetic variance; small, recently-founded, isolated populations contributed most to increase FST in the metapopulation. However, the effects of population size and population age are best understood as being modulated through the effects of connectivity to other extant populations, i.e. FST diminishes as populations age, but at a rate that depends how isolated the population is. These spatial and temporal correlates of population structure give insight into how migration, founder effect and within-deme genetic drift have combined to enhance and restrict genetic divergence in a natural metapopulation. PMID:25198341

  9. Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks

    USGS Publications Warehouse

    Campbell Grant, Evan H.

    2011-01-01

    Spatial complexity in metacommunities can be separated into 3 main components: size (i.e., number of habitat patches), spatial arrangement of habitat patches (network topology), and diversity of habitat patch types. Much attention has been paid to lattice-type networks, such as patch-based metapopulations, but interest in understanding ecological networks of alternative geometries is building. Dendritic ecological networks (DENs) include some increasingly threatened ecological systems, such as caves and streams. The restrictive architecture of dendritic ecological networks might have overriding implications for species persistence. I used a modeling approach to investigate how number and spatial arrangement of habitat patches influence metapopulation extinction risk in 2 DENs of different size and topology. Metapopulation persistence was higher in larger networks, but this relationship was mediated by network topology and the dispersal pathways used to navigate the network. Larger networks, especially those with greater topological complexity, generally had lower extinction risk than smaller and less-complex networks, but dispersal bias and magnitude affected the shape of this relationship. Applying these general results to real systems will require empirical data on the movement behavior of organisms and will improve our understanding of the implications of network complexity on population and community patterns and processes.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  12. 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

  13. 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.

  14. 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...

  15. Fragments, extinction, and recolonization: The genetics of metapopulations

    Treesearch

    Michael F. Antolin; Anna W. Schoettle

    2001-01-01

    The idea of a metapopulation - a group of local populations in a patchy habitat - recurs in both ecology and evolutionary biology. Although the metapopulation concept is at least 50-75 years old, it has recently resurged, as natural habitats become fragmented and are lost because of humans' use of resources. However, fragmentation is not the same as...

  16. Plague metapopulation dynamics in a natural reservoir: the burrow system as the unit of study.

    PubMed

    Davis, S; Klassovskiy, N; Ageyev, V; Suleimenov, B; Atshabar, B; Klassovskaya, A; Bennett, M; Leirs, H; Begon, M

    2007-07-01

    The ecology of plague (Yersinia pestis infection) in its ancient foci in Central Asia remains poorly understood. We present field data from two sites in Kazakhstan where the great gerbil (Rhombomys opimus) is the major natural host. Family groups inhabit and defend burrow systems spaced throughout the landscape, such that the host population may be considered a metapopulation, with each occupied burrow system a subpopulation. We examine plague transmission within and between family groups and its effect on survival. Transmission of plague occurred disproportionately within family groups although not all gerbils became infected once plague entered a burrow system. There were no spatial patterns to suggest that family groups in close proximity to infected burrow systems were more at risk of infection than those far away. At one site, infection increased the chances of burrow-system extinction. Overall, it is useful to consider the burrow system as the unit of study within a much larger metapopulation.

  17. Combining incidence and demographic modelling approaches to evaluate metapopulation parameters for an endangered riparian plant

    PubMed Central

    Charney, Noah D.; Record, Sydne

    2016-01-01

    Metapopulations are a central concept in ecology and conservation biology; however, estimating key parameters such as colonization rates presents a substantial obstacle to modelling metapopulations in many species. We develop spatial and non-spatial simulation models that combine incidence- and demographic-based approaches to build a relationship between observed patch occupancy, habitat turnover rates, colonization rates and dispersal scales. Applying these models to long-term observations of Pedicularis furbishiae (Furbish’s lousewort), a rare plant endemic to the Saint John River, we predict that observed habitat patches averaging 550 m in length receive colonizing seedlings with a yearly probability of 0.45 or 0.54, based on two different models. Predictions are consistent with a standard analytic metapopulation formulation modified to partition extinction drivers during the early and the late phases of a population’s life cycle. While the specific results rest on several simplifying assumptions, the models allow us to understand the impact that increasing rates of habitat turnover would have on the future survival of this species. PMID:27339047

  18. Refugia and connectivity sustain amphibian metapopulations afflicted by disease.

    PubMed

    Heard, Geoffrey W; Thomas, Chris D; Hodgson, Jenny A; Scroggie, Michael P; Ramsey, David S L; Clemann, Nick

    2015-08-01

    Metapopulation persistence in fragmented landscapes depends on habitat patches that can support resilient local populations and sufficient connectivity between patches. Yet epidemiological theory for metapopulations has largely overlooked the capacity of particular patches to act as refuges from disease, and has suggested that connectivity can undermine persistence. Here, we show that relatively warm and saline wetlands are environmental refuges from chytridiomycosis for an endangered Australian frog, and act jointly with connectivity to sustain frog metapopulations. We coupled models of microclimate and infection probability to map chytrid prevalence, and demonstrate a strong negative relationship between chytrid prevalence and the persistence of frog populations. Simulations confirm that frog metapopulations are likely to go extinct when they lack environmental refuges from disease and lose connectivity between patches. This study demonstrates that environmental heterogeneity can mediate host-pathogen interactions in fragmented landscapes, and provides evidence that connectivity principally supports host metapopulations afflicted by facultative pathogens.

  19. 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.

  20. Metapopulation epidemic models with heterogeneous mixing and travel behaviour.

    PubMed

    Apolloni, Andrea; Poletto, Chiara; Ramasco, José J; Jensen, Pablo; Colizza, Vittoria

    2014-01-13

    Determining the pandemic potential of an emerging infectious disease and how it depends on the various epidemic and population aspects is critical for the preparation of an adequate response aimed at its control. The complex interplay between population movements in space and non-homogeneous mixing patterns have so far hindered the fundamental understanding of the conditions for spatial invasion through a general theoretical framework. To address this issue, we present an analytical modelling approach taking into account such interplay under general conditions of mobility and interactions, in the simplifying assumption of two population classes. We describe a spatially structured population with non-homogeneous mixing and travel behaviour through a multi-host stochastic epidemic metapopulation model. Different population partitions, mixing patterns and mobility structures are considered, along with a specific application for the study of the role of age partition in the early spread of the 2009 H1N1 pandemic influenza. We provide a complete mathematical formulation of the model and derive a semi-analytical expression of the threshold condition for global invasion of an emerging infectious disease in the metapopulation system. A rich solution space is found that depends on the social partition of the population, the pattern of contacts across groups and their relative social activity, the travel attitude of each class, and the topological and traffic features of the mobility network. Reducing the activity of the less social group and reducing the cross-group mixing are predicted to be the most efficient strategies for controlling the pandemic potential in the case the less active group constitutes the majority of travellers. If instead traveling is dominated by the more social class, our model predicts the existence of an optimal across-groups mixing that maximises the pandemic potential of the disease, whereas the impact of variations in the activity of each group

  1. Metapopulation epidemic models with heterogeneous mixing and travel behaviour

    PubMed Central

    2014-01-01

    Background Determining the pandemic potential of an emerging infectious disease and how it depends on the various epidemic and population aspects is critical for the preparation of an adequate response aimed at its control. The complex interplay between population movements in space and non-homogeneous mixing patterns have so far hindered the fundamental understanding of the conditions for spatial invasion through a general theoretical framework. To address this issue, we present an analytical modelling approach taking into account such interplay under general conditions of mobility and interactions, in the simplifying assumption of two population classes. Methods We describe a spatially structured population with non-homogeneous mixing and travel behaviour through a multi-host stochastic epidemic metapopulation model. Different population partitions, mixing patterns and mobility structures are considered, along with a specific application for the study of the role of age partition in the early spread of the 2009 H1N1 pandemic influenza. Results We provide a complete mathematical formulation of the model and derive a semi-analytical expression of the threshold condition for global invasion of an emerging infectious disease in the metapopulation system. A rich solution space is found that depends on the social partition of the population, the pattern of contacts across groups and their relative social activity, the travel attitude of each class, and the topological and traffic features of the mobility network. Reducing the activity of the less social group and reducing the cross-group mixing are predicted to be the most efficient strategies for controlling the pandemic potential in the case the less active group constitutes the majority of travellers. If instead traveling is dominated by the more social class, our model predicts the existence of an optimal across-groups mixing that maximises the pandemic potential of the disease, whereas the impact of variations in

  2. 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

  3. 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.

  4. Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India

    PubMed Central

    Sharma, Sandeep; Dutta, Trishna; Maldonado, Jesús E.; Wood, Thomas C.; Panwar, Hemendra Singh; Seidensticker, John

    2013-01-01

    Understanding the patterns of gene flow of an endangered species metapopulation occupying a fragmented habitat is crucial for landscape-level conservation planning and devising effective conservation strategies. Tigers (Panthera tigris) are globally endangered and their populations are highly fragmented and exist in a few isolated metapopulations across their range. We used multi-locus genotypic data from 273 individual tigers (Panthera tigris tigris) from four tiger populations of the Satpura–Maikal landscape of central India to determine whether the corridors in this landscape are functional. This 45 000 km2 landscape contains 17% of India's tiger population and 12% of its tiger habitat. We applied Bayesian and coalescent-based analyses to estimate contemporary and historical gene flow among these populations and to infer their evolutionary history. We found that the tiger metapopulation in central India has high rates of historical and contemporary gene flow. The tests for population history reveal that tigers populated central India about 10 000 years ago. Their population subdivision began about 1000 years ago and accelerated about 200 years ago owing to habitat fragmentation, leading to four spatially separated populations. These four populations have been in migration–drift equilibrium maintained by high gene flow. We found the highest rates of contemporary gene flow in populations that are connected by forest corridors. This information is highly relevant to conservation practitioners and policy makers, because deforestation, road widening and mining are imminent threats to these corridors. PMID:23902910

  5. Forest corridors maintain historical gene flow in a tiger metapopulation in the highlands of central India.

    PubMed

    Sharma, Sandeep; Dutta, Trishna; Maldonado, Jesús E; Wood, Thomas C; Panwar, Hemendra Singh; Seidensticker, John

    2013-09-22

    Understanding the patterns of gene flow of an endangered species metapopulation occupying a fragmented habitat is crucial for landscape-level conservation planning and devising effective conservation strategies. Tigers (Panthera tigris) are globally endangered and their populations are highly fragmented and exist in a few isolated metapopulations across their range. We used multi-locus genotypic data from 273 individual tigers (Panthera tigris tigris) from four tiger populations of the Satpura-Maikal landscape of central India to determine whether the corridors in this landscape are functional. This 45 000 km(2) landscape contains 17% of India's tiger population and 12% of its tiger habitat. We applied Bayesian and coalescent-based analyses to estimate contemporary and historical gene flow among these populations and to infer their evolutionary history. We found that the tiger metapopulation in central India has high rates of historical and contemporary gene flow. The tests for population history reveal that tigers populated central India about 10 000 years ago. Their population subdivision began about 1000 years ago and accelerated about 200 years ago owing to habitat fragmentation, leading to four spatially separated populations. These four populations have been in migration-drift equilibrium maintained by high gene flow. We found the highest rates of contemporary gene flow in populations that are connected by forest corridors. This information is highly relevant to conservation practitioners and policy makers, because deforestation, road widening and mining are imminent threats to these corridors.

  6. Applications of Rapid Evaluation of Metapopulation Persistence (REMP) in Conservation Planning for Vulnerable Fauna Species

    NASA Astrophysics Data System (ADS)

    Taylor, Subhashni; Drielsma, Michael; Taylor, Robert; Kumar, Lalit

    2016-06-01

    In many regions species are declining due to fragmentation and loss of habitat. If species persistence is to be achieved, ecologically informed, effective conservation action is required. Yet it remains a challenge to identify optimal places in a landscape to direct habitat reconstruction and management. Rather than relying on individual landscape metrics, process-based regional scale assessment methodology is needed that focuses primarily on species persistence. This means integrating, according to species' ecology, habitat extent, suitability, quality and spatial configuration. The rapid evaluation of metapopulation persistence (REMP) methodology has been developed for this purpose. However, till now no practical conservation planning application of REMP has been described. By integration of expert ecological knowledge, we extended REMP's capabilities to prioritize conservation action for a highly modified agricultural region of central NSW, Australia based on the metapopulation ecology of 34 fauna species. The region's current capacity to support the species was evaluated in relation to the pre-European state for which there was known viability. Six of the species were found to currently have insufficient habitat to support viable populations. Seeking locations to maximize overall improvement in viability for these species, we prioritized conservation action to locations near the threshold of metapopulation persistence.

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

    PubMed

    Caruso, Tancredi; Taormina, Mauro; Migliorini, Massimo

    2012-01-01

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

  8. Effects of matrix heterogeneity on animal dispersal: from individual behavior to metapopulation-level parameters.

    PubMed

    Revilla, Eloy; Wiegand, Thorsten; Palomares, Francisco; Ferreras, Pablo; Delibes, Miguel

    2004-11-01

    Mounting theoretical and empirical evidence shows that matrix heterogeneity may have contrasting effects on metapopulation dynamics by contributing to patch isolation in nontrivial ways. We analyze the movement properties during interpatch dispersal in a metapopulation of Iberian lynx (Lynx pardinus). On a daily temporal scale, lynx habitat selection defines two types of matrix habitats where individuals may move: open and dispersal habitats (avoided and used as available, respectively). There was a strong and complex impact of matrix heterogeneity on movement properties at several temporal scales (hourly and daily radiolocations and the entire dispersal event). We use the movement properties on the hourly temporal scale to build a simulation model to reconstruct individual dispersal events. The two most important parameters affecting model predictions at both the individual (daily) and metapopulation scales were related to the movement capacity (number of movement steps per day and autocorrelation in dispersal habitat) followed by the parameters representing the habitat selection in the matrix. The model adequately reproduced field estimates of population-level parameters (e.g., interpatch connectivity, maximum and final dispersal distances), and its performance was clearly improved when including the effect of matrix heterogeneity on movement properties. To assume there is a homogeneous matrix results in large errors in the estimate of interpatch connectivity, especially for close patches separated by open habitat or corridors of dispersal habitat, showing how important it is to consider matrix heterogeneity when it is present. Movement properties affect the interaction of dispersing individuals with the landscape and can be used as a mechanistic representation of dispersal at the metapopulation level. This is so when the effect of matrix heterogeneity on movement properties is evaluated under biologically meaningful spatial and temporal scales.

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

    EPA Science Inventory

    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 re...

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

    EPA Science Inventory

    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 re...

  11. Probability of identity by descent in metapopulations.

    PubMed Central

    Kaj, I; Lascoux, M

    1999-01-01

    Equilibrium probabilities of identity by descent (IBD), for pairs of genes within individuals, for genes between individuals within subpopulations, and for genes between subpopulations are calculated in metapopulation models with fixed or varying colony sizes. A continuous-time analog to the Moran model was used in either case. For fixed-colony size both propagule and migrant pool models were considered. The varying population size model is based on a birth-death-immigration (BDI) process, to which migration between colonies is added. Wright's F statistics are calculated and compared to previous results. Adding between-island migration to the BDI model can have an important effect on the equilibrium probabilities of IBD and on Wright's index. PMID:10388835

  12. Inclusive fitness for traits affecting metapopulation demography.

    PubMed

    Rousset, François; Ronce, Ophélie

    2004-03-01

    Defining computable analytical measures of the effects of selection in populations with demographic and environmental stochasticity is a long-standing problem. We derive an analytical measure which takes in account all consequences of the discrete nature of deme size. Expressions of this measure are detailed for infinite island models of population structure. As an illustration we consider the evolution of dispersal in populations made of small demes with environmental and demographic stochasticity. We confirm some results obtained from the analysis of models based on deterministic approximations. In particular, when there is an Allee effect, we show that evolution of the dispersal rate may lead the metapopulation to extinction. Thus, selection on the dispersal rate could restrict the distribution of species subject to Allee effects. This selection-driven extinction is prevented by kin selection when the environmental extinction rate is small.

  13. Modeling vaccination in a heterogeneous metapopulation system

    NASA Astrophysics Data System (ADS)

    Lachiany, Menachem

    2016-09-01

    We present here a multicity SIS epidemic model with vaccination. The model describes the dynamics of heterogeneous metapopulations that contain imperfectly vaccinated individuals. The effect of vaccination on heterogeneous multicity models has not been previously studied. We show that under very generic conditions, the epidemic threshold does not depend on the diffusion coefficient of the vaccinated individuals, but it does depend on the diffusion coefficient of the infected population. We then show, using a novel methodology, that the reproduction number is determined by the homogeneous model parameters and by the maximal number of neighbors a city can have, when the diffusion coefficient of the infected population is low. Finally, we present numerical simulations to support the analytical results.

  14. Landscape genetics of high mountain frog metapopulations

    USGS Publications Warehouse

    Murphy, M.A.; Dezzani, R.; Pilliod, D.S.; Storfer, A.

    2010-01-01

    Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a

  15. Landscape genetics of high mountain frog metapopulations.

    PubMed

    Murphy, Melanie A; Dezzani, R; Pilliod, D S; Storfer, A

    2010-09-01

    Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a

  16. 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.

  17. A stochastic metapopulation model accounting for habitat dynamics.

    PubMed

    Ross, J V

    2006-06-01

    A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.

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

    PubMed

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

    2015-03-01

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

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

    PubMed Central

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

    2015-01-01

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

  20. Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

    USGS Publications Warehouse

    Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

    2013-01-01

    Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987–2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

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

    PubMed

    Gong, Jian; Yang, Jianxin; Tang, Wenwu

    2015-11-09

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

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

    PubMed Central

    Gong, Jian; Yang, Jianxin; Tang, Wenwu

    2015-01-01

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

  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. 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.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  10. 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 ...

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

    PubMed Central

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

    2013-01-01

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    PubMed

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

    2013-01-01

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

  16. 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

  17. 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.

  18. 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

  19. 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

  20. Population-specific life histories contribute to metapopulation viability

    USGS Publications Warehouse

    Halsey, Samniqueka J.; Bell, Timothy J.; McEachern, Kathryn; Pavlovic, Noel B.

    2016-01-01

    Restoration efforts can be improved by understanding how variations in life-history traits occur within populations of the same species living in different environments. This can be done by first understanding the demographic responses of natural occurring populations. Population viability analysis continues to be useful to species management and conservation with sensitivity analysis aiding in the understanding of population dynamics. In this study, using life-table response experiments and elasticity analyses, we investigated how population-specific life-history demographic responses contributed to the metapopulation viability of the Federally threatened Pitcher's thistle (Cirsium pitcheri). Specifically, we tested the following hypotheses: (1) Subpopulations occupying different environments within a metapopulation have independent demographic responses and (2) advancing succession results in a shift from a demographic response focused on growth and fecundity to one dominated by stasis. Our results showed that reintroductions had a positive contribution to the metapopulation growth rate as compared to native populations which had a negative contribution. We found no difference in succession on the contribution to metapopulation viability. In addition, we identified distinct population-specific contributions to metapopulation viability and were able to associate specific life-history demographic responses. For example, the positive impact of Miller High Dunes population on the metapopulation growth rate resulted from high growth contributions, whereas increased time of plant in stasis for the State Park Big Blowout population resulted in negative contributions. A greater understanding of how separate populations respond in their corresponding environment may ultimately lead to more effective management strategies aimed at reducing extinction risk. We propose the continued use of sensitivity analyses to evaluate population-specific demographic influences on

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  2. 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.

  3. 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.

  4. Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

    NASA Astrophysics Data System (ADS)

    Zhan, Yu; Luo, Yuzhou; Deng, Xunfei; Chen, Huajin; Grieneisen, Michael L.; Shen, Xueyou; Zhu, Lizhong; Zhang, Minghua

    2017-04-01

    A high degree of uncertainty associated with the emission inventory for China tends to degrade the performance of chemical transport models in predicting PM2.5 concentrations especially on a daily basis. In this study a novel machine learning algorithm, Geographically-Weighted Gradient Boosting Machine (GW-GBM), was developed by improving GBM through building spatial smoothing kernels to weigh the loss function. This modification addressed the spatial nonstationarity of the relationships between PM2.5 concentrations and predictor variables such as aerosol optical depth (AOD) and meteorological conditions. GW-GBM also overcame the estimation bias of PM2.5 concentrations due to missing AOD retrievals, and thus potentially improved subsequent exposure analyses. GW-GBM showed good performance in predicting daily PM2.5 concentrations (R2 = 0.76, RMSE = 23.0 μg/m3) even with partially missing AOD data, which was better than the original GBM model (R2 = 0.71, RMSE = 25.3 μg/m3). On the basis of the continuous spatiotemporal prediction of PM2.5 concentrations, it was predicted that 95% of the population lived in areas where the estimated annual mean PM2.5 concentration was higher than 35 μg/m3, and 45% of the population was exposed to PM2.5 >75 μg/m3 for over 100 days in 2014. GW-GBM accurately predicted continuous daily PM2.5 concentrations in China for assessing acute human health effects.

  5. Comparison of reintroduction and enhancement effects on metapopulation viability

    USGS Publications Warehouse

    Halsey, Samniqueka J; Bell, Timothy J.; McEachern, Kathryn; Pavlovic, Noel B.

    2015-01-01

    Metapopulation viability depends upon a balance of extinction and colonization of local habitats by a species. Mechanisms that can affect this balance include physical characteristics related to natural processes (e.g. succession) as well as anthropogenic actions. Plant restorations can help to produce favorable metapopulation dynamics and consequently increase viability; however, to date no studies confirm this is true. Population viability analysis (PVA) allows for the use of empirical data to generate theoretical future projections in the form of median time to extinction and probability of extinction. In turn, PVAs can inform and aid the development of conservation, recovery, and management plans. Pitcher's thistle (Cirsium pitcheri) is a dune endemic that exhibited metapopulation dynamics. We projected viability of three natural and two restored populations with demographic data spanning 15–23 years to determine the degree the addition of reintroduced population affects metapopulation viability. The models were validated by comparing observed and projected abundances and adjusting parameters associated with demographic and environmental stochasticity to improve model performance. Our chosen model correctly predicted yearly population abundance for 60% of the population-years. Using that model, 50-year projections showed that the addition of reintroductions increases metapopulation viability. The reintroduction that simulated population performance in early-successional habitats had the maximum benefit. In situ enhancements of existing populations proved to be equally effective. This study shows that restorations can facilitate and improve metapopulation viability of species dependent on metapopulation dynamics for survival with long-term persistence of C. pitcheri in Indiana likely to depend on continued active management.

  6. Stochastic environmental fluctuations drive epidemiology in experimental host–parasite metapopulations

    PubMed Central

    Duncan, Alison B.; Gonzalez, Andrew; Kaltz, Oliver

    2013-01-01

    Environmental fluctuations are important for parasite spread and persistence. However, the effects of the spatial and temporal structure of environmental fluctuations on host–parasite dynamics are not well understood. Temporal fluctuations can be random but positively autocorrelated, such that the environment is similar to the recent past (red noise), or random and uncorrelated with the past (white noise). We imposed red or white temporal temperature fluctuations on experimental metapopulations of Paramecium caudatum, experiencing an epidemic of the bacterial parasite Holospora undulata. Metapopulations (two subpopulations linked by migration) experienced fluctuations between stressful (5°C) and permissive (23°C) conditions following red or white temporal sequences. Spatial variation in temperature fluctuations was implemented by exposing subpopulations to the same (synchronous temperatures) or different (asynchronous temperatures) temporal sequences. Red noise, compared with white noise, enhanced parasite persistence. Despite this, red noise coupled with asynchronous temperatures allowed infected host populations to maintain sizes equivalent to uninfected populations. It is likely that this occurs because subpopulations in permissive conditions rescue declining subpopulations in stressful conditions. We show how patterns of temporal and spatial environmental fluctuations can impact parasite spread and host population abundance. We conclude that accurate prediction of parasite epidemics may require realistic models of environmental noise. PMID:23966645

  7. Observations of migrant exchange and mixing in a coral reef fish metapopulation link scales of marine population connectivity.

    PubMed

    Horne, John B; van Herwerden, Lynne; Abellana, Sheena; McIlwain, Jennifer L

    2013-01-01

    Much progress has been made toward understanding marine metapopulation dynamics, largely because of multilocus microsatellite surveys able to connect related individuals within the metapopulation. However, most studies are focused on small spatial scales, tens of kilometers, while demographic exchange at larger spatial scales remains poorly documented. Additionally, many small-scale demographic studies conflict with broad-scale phylogeographic patterns concerning levels of marine population connectivity, highlighting a need for data on more intermediate scales. Here, we investigated demographic recruitment processes of a commercially important coral reef fish, the bluespine unicornfish (Naso unicornis) using a suite of mitochondrial DNA (mtDNA) and microsatellite markers. Sampling for this study ranged across the southern Marianas Islands, a linear distance of 250 km and included 386 newly settled postlarval recruits. In contrast with other studies, we report that cohorts of recruits were genetically homogeneous in space and time, with no evidence of temporally stochastic sweepstakes reproduction. The genetic diversity of recruits was high and commensurate with that of the adult population. In addition, there is substantial evidence that 2 recruits, separated by 250 km, were full siblings. This is the largest direct observation of dispersal to date for a coral reef fish. All indications suggest that subpopulations of N. unicornis experience high levels of demographic migrant exchange and metapopulation mixing on a spatial scale of hundreds of kilometers, consistent with high levels of broad-scale genetic connectivity previously reported in this species.

  8. Metapopulation modelling of riparian tree species persistence in river networks under climate change.

    PubMed

    Van Looy, Kris; Piffady, Jérémy

    2017-11-01

    Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and ¼ for poplar after 25 years already. But proposed adaptation measures prove effective to even

  9. The Scaling of Human Contacts and Epidemic Processes in Metapopulation Networks

    NASA Astrophysics Data System (ADS)

    Tizzoni, Michele; Sun, Kaiyuan; Benusiglio, Diego; Karsai, Márton; Perra, Nicola

    2015-10-01

    We study the dynamics of reaction-diffusion processes on heterogeneous metapopulation networks where interaction rates scale with subpopulation sizes. We first present new empirical evidence, based on the analysis of the interactions of 13 million users on Twitter, that supports the scaling of human interactions with population size with an exponent γ ranging between 1.11 and 1.21, as observed in recent studies based on mobile phone data. We then integrate such observations into a reaction- diffusion metapopulation framework. We provide an explicit analytical expression for the global invasion threshold which sets a critical value of the diffusion rate below which a contagion process is not able to spread to a macroscopic fraction of the system. In particular, we consider the Susceptible-Infectious-Recovered epidemic model. Interestingly, the scaling of human contacts is found to facilitate the spreading dynamics. This behavior is enhanced by increasing heterogeneities in the mobility flows coupling the subpopulations. Our results show that the scaling properties of human interactions can significantly affect dynamical processes mediated by human contacts such as the spread of diseases, ideas and behaviors.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    PubMed

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

    2012-07-01

    1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

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

    NASA Astrophysics Data System (ADS)

    Govind, A.; Chen, J. M.; Margolis, H.

    2007-12-01

    Current estimates of terrestrial carbon overlook the effects of topographically-driven lateral flow of soil water. We hypothesize that this component, which occur at a landscape or watershed scale have significant influences on the spatial distribution of carbon, due to its large contribution to the local water balance. To this end, we further developed a spatially explicit ecohydrological model, BEPS-TerrainLab V2.0. We simulated the coupled hydrological and carbon cycle processes in a black spruce-moss ecosystem in central Quebec, Canada. The carbon stocks were initialized using a long term carbon cycling model, InTEC, under a climate change and disturbance scenario, the accuracy of which was determined with inventory plot measurements. Further, we simulated and validated several ecosystem indicators such as ET, GPP, NEP, water table, snow depth and soil temperature, using the measurements for two years, 2004 and 2005. After gaining confidence in the model's ability to simulate ecohydrological processes, we tested the influence of lateral water flow on the carbon cycle. We made three hydrological modeling scenarios 1) Explicit, were realistic lateral water routing was considered 2) Implicit where calculations were based on a bucket modeling approach 3) NoFlow, where the lateral water flow was turned off in the model. The results showed that pronounced anomalies exist among the scenarios for the simulated GPP, ET and NEP. In general, Implicit calculation overestimated GPP and underestimated NEP, as opposed to Explicit simulation. NoFlow underestimated GPP and overestimated NEP. The key processes controlling GPP were manifested through stomatal conductance which reduces under conditions of rapid soil saturation ( NoFlow ) or increases in the Implicit case, and, nitrogen availability which affects Vcmax, the maximum carboxylation rate. However, for NEP, the anomalies were attributed to differences in soil carbon pool decomposition, which determine the heterotrophic

  13. 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.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  16. Anticipating knowledge to inform species management: predicting spatially explicit habitat suitability of a colonial vulture spreading its range.

    PubMed

    Mateo-Tomás, Patricia; Olea, Pedro P

    2010-08-25

    The knowledge of both potential distribution and habitat suitability is fundamental in spreading species to inform in advance management and conservation planning. After a severe decline in the past decades, the griffon vulture (Gyps fulvus) is now spreading its breeding range towards the northwest in Spain and Europe. Because of its key ecological function, anticipated spatial knowledge is required to inform appropriately both vulture and ecosystem management. Here we used maximum entropy (Maxent) models to determine the habitat suitability of potential and current breeding distribution of the griffon vulture using presence-only data (N = 124 colonies) in north-western Spain. The most relevant ecological factors shaping this habitat suitability were also identified. The resulting model had a high predictive performance and was able to predict species' historical distribution. 7.5% (approximately 1,850 km(2)) of the study area resulted to be suitable breeding habitat, most of which (approximately 70%) is already occupied by the species. Cliff availability and livestock density, especially of sheep and goats, around 10 km of the colonies were the fundamental factors determining breeding habitat suitability for this species. Griffon vultures could still spread 50-60 km towards the west, increasing their breeding range in 1,782 km(2). According to our results, 7.22% of the area suitable for griffon vulture will be affected by wind farms, so our results could help to better plan wind farm locations. The approach here developed could be useful to inform management of reintroductions and recovery programmes currently being implemented for both the griffon vulture and other threatened vulture species.

  17. Spatially Explicit Analysis of Genome-Wide SNPs Detects Subtle Population Structure in a Mobile Marine Mammal, the Harbor Porpoise.

    PubMed

    Lah, Ljerka; Trense, Daronja; Benke, Harald; Berggren, Per; Gunnlaugsson, Þorvaldur; Lockyer, Christina; Öztürk, Ayaka; Öztürk, Bayram; Pawliczka, Iwona; Roos, Anna; Siebert, Ursula; Skóra, Krzysztof; Víkingsson, Gísli; Tiedemann, Ralph

    2016-01-01

    The population structure of the highly mobile marine mammal, the harbor porpoise (Phocoena phocoena), in the Atlantic shelf waters follows a pattern of significant isolation-by-distance. The population structure of harbor porpoises from the Baltic Sea, which is connected with the North Sea through a series of basins separated by shallow underwater ridges, however, is more complex. Here, we investigated the population differentiation of harbor porpoises in European Seas with a special focus on the Baltic Sea and adjacent waters, using a population genomics approach. We used 2872 single nucleotide polymorphisms (SNPs), derived from double digest restriction-site associated DNA sequencing (ddRAD-seq), as well as 13 microsatellite loci and mitochondrial haplotypes for the same set of individuals. Spatial principal components analysis (sPCA), and Bayesian clustering on a subset of SNPs suggest three main groupings at the level of all studied regions: the Black Sea, the North Atlantic, and the Baltic Sea. Furthermore, we observed a distinct separation of the North Sea harbor porpoises from the Baltic Sea populations, and identified splits between porpoise populations within the Baltic Sea. We observed a notable distinction between the Belt Sea and the Inner Baltic Sea sub-regions. Improved delineation of harbor porpoise population assignments for the Baltic based on genomic evidence is important for conservation management of this endangered cetacean in threatened habitats, particularly in the Baltic Sea proper. In addition, we show that SNPs outperform microsatellite markers and demonstrate the utility of RAD-tags from a relatively small, opportunistically sampled cetacean sample set for population diversity and divergence analysis.

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

    PubMed Central

    Mateo-Tomás, Patricia; Olea, Pedro P.

    2010-01-01

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

  19. Spatially Explicit Analysis of Genome-Wide SNPs Detects Subtle Population Structure in a Mobile Marine Mammal, the Harbor Porpoise

    PubMed Central

    Lah, Ljerka; Trense, Daronja; Benke, Harald; Berggren, Per; Gunnlaugsson, Þorvaldur; Lockyer, Christina; Öztürk, Ayaka; Öztürk, Bayram; Pawliczka, Iwona; Roos, Anna; Siebert, Ursula; Víkingsson, Gísli; Tiedemann, Ralph

    2016-01-01

    The population structure of the highly mobile marine mammal, the harbor porpoise (Phocoena phocoena), in the Atlantic shelf waters follows a pattern of significant isolation-by-distance. The population structure of harbor porpoises from the Baltic Sea, which is connected with the North Sea through a series of basins separated by shallow underwater ridges, however, is more complex. Here, we investigated the population differentiation of harbor porpoises in European Seas with a special focus on the Baltic Sea and adjacent waters, using a population genomics approach. We used 2872 single nucleotide polymorphisms (SNPs), derived from double digest restriction-site associated DNA sequencing (ddRAD-seq), as well as 13 microsatellite loci and mitochondrial haplotypes for the same set of individuals. Spatial principal components analysis (sPCA), and Bayesian clustering on a subset of SNPs suggest three main groupings at the level of all studied regions: the Black Sea, the North Atlantic, and the Baltic Sea. Furthermore, we observed a distinct separation of the North Sea harbor porpoises from the Baltic Sea populations, and identified splits between porpoise populations within the Baltic Sea. We observed a notable distinction between the Belt Sea and the Inner Baltic Sea sub-regions. Improved delineation of harbor porpoise population assignments for the Baltic based on genomic evidence is important for conservation management of this endangered cetacean in threatened habitats, particularly in the Baltic Sea proper. In addition, we show that SNPs outperform microsatellite markers and demonstrate the utility of RAD-tags from a relatively small, opportunistically sampled cetacean sample set for population diversity and divergence analysis. PMID:27783621

  20. Spatially explicit power analyses for occupancy-based monitoring of wolverine in the U.S. Rocky Mountains.

    PubMed

    Ellis, Martha M; Ivan, Jacob S; Schwartz, Michael K

    2014-02-01

    Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy-based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy-based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per-visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. © 2013 Society for Conservation Biology.

  1. 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

    perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances

  2. 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 plan