Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.
Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C
2017-07-01
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
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.
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
Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi
2014-11-01
Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
Post, Eric; Forchhammer, Mads C
2004-06-22
According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.
Eco-evolutionary spatial dynamics in the Glanville fritillary butterfly.
Hanski, Ilkka A
2011-08-30
Demographic population dynamics, gene flow, and local adaptation may influence each other and lead to coupling of ecological and evolutionary dynamics, especially in species inhabiting fragmented heterogeneous environments. Here, I review long-term research on eco-evolutionary spatial dynamics in the Glanville fritillary butterfly inhabiting a large network of approximately 4,000 meadows in Finland. The metapopulation persists in a balance between frequent local extinctions and recolonizations. The genetic spatial structure as defined by neutral markers is much more coarse-grained than the demographic spatial structure determined by the fragmented habitat, yet small-scale spatial structure has important consequences for the dynamics. I discuss three examples of eco-evolutionary spatial dynamics. (i) Extinction-colonization metapopulation dynamics influence allele frequency changes in the phosphoglucose isomerase (Pgi) gene, which leads to strong associations between genetic variation in Pgi and dispersal, recolonization, and local population dynamics. (ii) Inbreeding in local populations increases their risk for extinction, whereas reciprocal effects between inbreeding, population size, and emigration represent likely eco-evolutionary feedbacks. (iii) Genetically determined female oviposition preference for two host plant species exhibits a cline paralleling a gradient in host plant relative abundances, and host plant preference of dispersing females in relation to the host plant composition of habitat patches influences immigration (gene flow) and recolonization (founder events). Eco-evolutionary spatial dynamics in heterogeneous environments may not lead to directional evolutionary changes unless the environment itself changes, but eco-evolutionary dynamics may contribute to the maintenance of genetic variation attributable to fluctuating selection in space and time.
SPATIAL SCALE OF AUTOCORRELATION IN WISCONSIN FROG AND TOAD SURVEY DATA
The degree to which local population dynamics are correlated with nearby sites has important implications for metapopulation dynamics and landscape management. Spatially extensive monitoring data can be used to evaluate large-scale population dynamic processes. Our goals in this ...
Patrick C. Tobin
2004-01-01
The estimation of spatial autocorrelation in spatially- and temporally-referenced data is fundamental to understanding an organism's population biology. I used four sets of census field data, and developed an idealized space-time dynamic system, to study the behavior of spatial autocorrelation estimates when a practical method of sampling is employed. Estimates...
Eco-evolutionary spatial dynamics in the Glanville fritillary butterfly
Hanski, Ilkka A.
2011-01-01
Demographic population dynamics, gene flow, and local adaptation may influence each other and lead to coupling of ecological and evolutionary dynamics, especially in species inhabiting fragmented heterogeneous environments. Here, I review long-term research on eco-evolutionary spatial dynamics in the Glanville fritillary butterfly inhabiting a large network of approximately 4,000 meadows in Finland. The metapopulation persists in a balance between frequent local extinctions and recolonizations. The genetic spatial structure as defined by neutral markers is much more coarse-grained than the demographic spatial structure determined by the fragmented habitat, yet small-scale spatial structure has important consequences for the dynamics. I discuss three examples of eco-evolutionary spatial dynamics. (i) Extinction-colonization metapopulation dynamics influence allele frequency changes in the phosphoglucose isomerase (Pgi) gene, which leads to strong associations between genetic variation in Pgi and dispersal, recolonization, and local population dynamics. (ii) Inbreeding in local populations increases their risk for extinction, whereas reciprocal effects between inbreeding, population size, and emigration represent likely eco-evolutionary feedbacks. (iii) Genetically determined female oviposition preference for two host plant species exhibits a cline paralleling a gradient in host plant relative abundances, and host plant preference of dispersing females in relation to the host plant composition of habitat patches influences immigration (gene flow) and recolonization (founder events). Eco-evolutionary spatial dynamics in heterogeneous environments may not lead to directional evolutionary changes unless the environment itself changes, but eco-evolutionary dynamics may contribute to the maintenance of genetic variation attributable to fluctuating selection in space and time. PMID:21788506
Spatial and temporal synchrony in reptile population dynamics in variable environments.
Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R
2016-10-01
Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.
Revilla, Eloy; Wiegand, Thorsten
2008-12-09
The dynamics of spatially structured populations is characterized by within- and between-patch processes. The available theory describes the latter with simple distance-dependent functions that depend on landscape properties such as interpatch distance or patch size. Despite its potential role, we lack a good mechanistic understanding of how the movement of individuals between patches affects the dynamics of these populations. We used the theoretical framework provided by movement ecology to make a direct representation of the processes determining how individuals connect local populations in a spatially structured population of Iberian lynx. Interpatch processes depended on the heterogeneity of the matrix where patches are embedded and the parameters defining individual movement behavior. They were also very sensitive to the dynamic demographic variables limiting the time moving, the within-patch dynamics of available settlement sites (both spatiotemporally heterogeneous) and the response of individuals to the perceived risk while moving. These context-dependent dynamic factors are an inherent part of the movement process, producing connectivities and dispersal kernels whose variability is affected by other demographic processes. Mechanistic representations of interpatch movements, such as the one provided by the movement-ecology framework, permit the dynamic interaction of birth-death processes and individual movement behavior, thus improving our understanding of stochastic spatially structured populations.
Spatial evolutionary epidemiology of spreading epidemics
2016-01-01
Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295
Spatial evolutionary epidemiology of spreading epidemics.
Lion, S; Gandon, S
2016-10-26
Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).
Spatial distribution of limited resources and local density regulation in juvenile Atlantic salmon.
Finstad, Anders G; Einum, Sigurd; Ugedal, Ola; Forseth, Torbjørn
2009-01-01
1. Spatial heterogeneity of resources may influence competition among individuals and thus have a fundamental role in shaping population dynamics and carrying capacity. In the present study, we identify shelter opportunities as a limiting resource for juvenile Atlantic salmon (Salmo salar L.). Experimental and field studies are combined in order to demonstrate how the spatial distribution of shelters may influence population dynamics on both within and among population scales. 2. In closed experimental streams, fish performance scaled negatively with decreasing shelter availability and increasing densities. In contrast, the fish in open stream channels dispersed according to shelter availability and performance of fish remaining in the streams did not depend on initial density or shelters. 3. The field study confirmed that spatial variation in densities of 1-year-old juveniles was governed both by initial recruit density and shelter availability. Strength of density-dependent population regulation, measured as carrying capacity, increased with decreasing number of shelters. 4. Nine rivers were surveyed for spatial variation in shelter availability and increased shelter heterogeneity tended to decrease maximum observed population size (measured using catch statistics of adult salmon as a proxy). 5. Our studies highlight the importance of small-scale within-population spatial structure in population dynamics and demonstrate that not only the absolute amount of limiting resources but also their spatial arrangement can be an important factor influencing population carrying capacity.
The impact of natural transformation on adaptation in spatially structured bacterial populations.
Moradigaravand, Danesh; Engelstädter, Jan
2014-06-20
Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations.
A general modeling framework for describing spatially structured population dynamics
Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan
2017-01-01
Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles
Bartolino, Valerio; Tian, Huidong; Bergström, Ulf; Jounela, Pekka; Aro, Eero; Dieterich, Christian; Meier, H. E. Markus; Cardinale, Massimiliano; Bland, Barbara
2017-01-01
Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes. PMID:28207804
Eric R. Waits; Mark J. Bagley; Michael J. Blum; Frank H. McCormick; James M. Lazorchak
2008-01-01
Relating local demographic processes to spatial structure (e.g. habitat heterogeneity) is essential for understanding population and species persistence (Hanski & Gilpin, 1997; Fagan, 2002). Yet few studies have tested general hypotheses about the importance of spatial patterns in determining population dynamics within riverÂstream networks (Lowe, Likens &...
Spatio-temporal dynamics of a tree-killing beetle and its predator
Aaron S. Weed; Matthew P. Ayres; Andrew M. Liebhold; Ronald F. Billings
2016-01-01
Resolving linkages between local-scale processes and regional-scale patterns in abundance of interacting species is important for understanding long-term population stability across spatial scales. Landscape patterning in consumer population dynamics may be largely the result of interactions between consumers and their predators, or driven by spatial variation in basal...
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
Spatial dynamics of invasion: the geometry of introduced species.
Korniss, Gyorgy; Caraco, Thomas
2005-03-07
Many exotic species combine low probability of establishment at each introduction with rapid population growth once introduction does succeed. To analyse this phenomenon, we note that invaders often cluster spatially when rare, and consequently an introduced exotic's population dynamics should depend on locally structured interactions. Ecological theory for spatially structured invasion relies on deterministic approximations, and determinism does not address the observed uncertainty of the exotic-introduction process. We take a new approach to the population dynamics of invasion and, by extension, to the general question of invasibility in any spatial ecology. We apply the physical theory for nucleation of spatial systems to a lattice-based model of competition between plant species, a resident and an invader, and the analysis reaches conclusions that differ qualitatively from the standard ecological theories. Nucleation theory distinguishes between dynamics of single- and multi-cluster invasion. Low introduction rates and small system size produce single-cluster dynamics, where success or failure of introduction is inherently stochastic. Single-cluster invasion occurs only if the cluster reaches a critical size, typically preceded by a number of failed attempts. For this case, we identify the functional form of the probability distribution of time elapsing until invasion succeeds. Although multi-cluster invasion for sufficiently large systems exhibits spatial averaging and almost-deterministic dynamics of the global densities, an analytical approximation from nucleation theory, known as Avrami's law, describes our simulation results far better than standard ecological approximations.
Astrand, Elaine; Ibos, Guilhem; Duhamel, Jean-René; Ben Hamed, Suliann
2015-02-18
Despite an ever growing knowledge on how parietal and prefrontal neurons encode low-level spatial and color information or higher-level information, such as spatial attention, an understanding of how these cortical regions process neuronal information at the population level is still missing. A simple assumption would be that the function and temporal response profiles of these neuronal populations match that of its constituting individual cells. However, several recent studies suggest that this is not necessarily the case and that the single-cell approach overlooks dynamic changes in how information is distributed over the neuronal population. Here, we use a time-resolved population pattern analysis to explore how spatial position, spatial attention and color information are differentially encoded and maintained in the macaque monkey prefrontal (frontal eye fields) and parietal cortex (lateral intraparietal area). Overall, our work brings about three novel observations. First, we show that parietal and prefrontal populations operate in two distinct population regimens for the encoding of sensory and cognitive information: a stationary mode and a dynamic mode. Second, we show that the temporal dynamics of a heterogeneous neuronal population brings about complementary information to that of its functional subpopulations. Thus, both need to be investigated in parallel. Last, we show that identifying the neuronal configuration in which a neuronal population encodes given information can serve to reveal this same information in a different context. All together, this work challenges common views on neural coding in the parietofrontal network. Copyright © 2015 the authors 0270-6474/15/353174-16$15.00/0.
Stochastic population dynamics in spatially extended predator-prey systems
NASA Astrophysics Data System (ADS)
Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.
2018-02-01
Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex Ginzburg-Landau equation. Multiple-species extensions to general ‘food networks’ can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time patterns emerge as a result of the formation of competing alliances; e.g. coarsening domains that each incorporate rock-paper-scissors competition games.
NASA Astrophysics Data System (ADS)
Yang, Hyun Mo
2015-12-01
Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.
Dynamic Patterns of Modern Epidemics
NASA Astrophysics Data System (ADS)
Brockmann, Dirk; Hufnagel, Lars; Geisel, Theo
2004-03-01
We investigate the effects of scale-free travelling of humans and their inhomogeneous geographic distribution on the dynamic patterns of spreading epidemics. Our approach combines the susceptible/infected/recovered paradigm for the infection dynamics with superdiffusive dispersion of individuals and their inhomogeneous spatial distribution. We show that scale-free motion of individuals and their variable spatial distribution leads to the absence of wavefronts in dynamic epidemic patterns which are typical for the limiting cases of ordinary diffusion and spatially homogeneous populations. Instead, patterns emerge with isolated hotspots on highly populated areas from which regional epidemic outbursts are triggered. Hotspot sizes are independent of the correlation length in the spatial distribution of individuals and occur on all scales. Our theory predicts that highly populated areas are reached by an epidemic in advance and must receive special attention in control measure strategies. Furthermore, our analysis predicts strong fluctuations in the time course of the total infection which cannot be accounted for by ordinary reaction-diffusion models for epidemics.
Andrew M. Liebhold; Derek M. Johnson; Ottar N. Bj& #248rnstad
2006-01-01
Explanations for the ubiquitous presence of spatially synchronous population dynamics have assumed that density-dependent processes governing the dynamics of local populations are identical among disjunct populations, and low levels of dispersal or small amounts of regionalized stochasticity ("Moran effect") can act to synchronize populations. In this study...
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.
Spatial-temporal population dynamics across species range: from centre to margin
Qinfeng Guo; Mark Taper; Michele Schoenberger; J. Brandle
2005-01-01
Understanding the boundaries of species'rangs and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-tamporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in...
Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J
2014-01-01
Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.
Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.
2014-01-01
Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860
Landscape Pattern Determines Neighborhood Size and Structure within a Lizard Population
Ryberg, Wade A.; Hill, Michael T.; Painter, Charles W.; Fitzgerald, Lee A.
2013-01-01
Although defining population structure according to discrete habitat patches is convenient for metapopulation theories, taking this approach may overlook structure within populations continuously distributed across landscapes. For example, landscape features within habitat patches direct the movement of organisms and define the density distribution of individuals, which can generate spatial structure and localized dynamics within populations as well as among them. Here, we use the neighborhood concept, which describes population structure relative to the scale of individual movements, to illustrate how localized dynamics within a population of lizards (Sceloporus arenicolus) arise in response to variation in landscape pattern within a continuous habitat patch. Our results emphasize links between individual movements at small scales and the emergence of spatial structure within populations which resembles metapopulation dynamics at larger scales. We conclude that population dynamics viewed in a landscape context must consider the explicit distribution and movement of individuals within continuous habitat as well as among habitat patches. PMID:23441217
H. H. Welsh; C. A. Wheeler; A. J. Lind
2010-01-01
Spatial patterns of animals have important implications for population dynamics and can reveal other key aspects of a species' ecology. Movements and the resulting spatial arrangements have fitness and genetic consequences for both individuals and populations. We studied the spatial and dispersal patterns of the Oregon Gartersnake, Thamnophis atratus...
Mauritzen, Mette; Derocher, Andrew E.; Wiig, Øystein; Belikov, Stanislav; Boltunov, Andrei N.; Garner, Gerald W.
2002-01-01
1. Animal populations, defined by geographical areas within a species’ distribution where population dynamics are largely regulated by births and deaths rather than by migration from surrounding areas, may be the correct unit for wildlife management. However, in heterogeneous landscapes varying habitat quality may yield subpopulations with distinct patterns in resource use and demography significant to the dynamics of populations.2. To define the spatial population structure of polar bears Ursus maritimus in the Norwegian and western Russian Arctic, and to assess the existence of a shared population between the two countries, we analysed satellite telemetry data obtained from 105 female polar bears over 12 years.3. Using both cluster analyses and home-range estimation methods, we identified five population units inhabiting areas with different sea-ice characteristics and prey availability.4. The continuous distribution of polar bear positions indicated that the different subpopulations formed one continuous polar bear population in the Norwegian and western Russian Arctic. Hence, Norway and Russia have a shared management responsibility.5. The spatial population structure identified will provide a guide for evaluating geographical patterns in polar bear ecology, the dynamics of polar bear–seal relationships and the effects of habitat alteration due to climate change. The work illustrates the importance of defining population borders and subpopulation structure in understanding the dynamics and management of larger animals.
AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS
We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...
Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith
2014-01-01
Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.
Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.
Lantschner, M Victoria; Corley, Juan C
2015-01-01
Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...
2016-10-24
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.
2016-01-01
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.
Clustering Effect on the Dynamics in a Spatial Rock-Paper-Scissors System
NASA Astrophysics Data System (ADS)
Hashimoto, Tsuyoshi; Sato, Kazunori; Ichinose, Genki; Miyazaki, Rinko; Tainaka, Kei-ichi
2018-01-01
The lattice dynamics for rock-paper-scissors games is related to population theories in ecology. In most cases, simulations are performed by local and global interactions. It is known in the former case that the dynamics is usually stable. We find two types of non-random distributions in the stationary state. One is a cluster formation of endangered species: when the density of a species approaches zero, its clumping degree diverges to infinity. The other is the strong aggregations of high-density species. Such spatial pattern formations play important roles in population dynamics.
Andrew Birt
2011-01-01
The population dynamics of the southern pine beetle (SPB) exhibit characteristic fluctuations between relatively long endemic and shorter outbreak periods. Populations exhibit complex and hierarchical spatial structure with beetles and larvae aggregating within individual trees, infestations with multiple infested trees, and regional outbreaks that comprise a large...
Spatial heterogeneity in the carrying capacity of sika deer in Japan.
Iijima, Hayato; Ueno, Mayumi
2016-06-09
Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area.
Jackson, Doug; Vandermeer, John; Perfecto, Ivette; Philpott, Stacy M
2014-01-01
Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants' dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution - a signal of spatial self organization - but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations.
Jackson, Doug; Vandermeer, John; Perfecto, Ivette; Philpott, Stacy M.
2014-01-01
Spatial structure can have a profound, but often underappreciated, effect on the temporal dynamics of ecosystems. Here we report on a counterintuitive increase in the population of a tree-nesting ant, Azteca sericeasur, in response to a drastic reduction in the number of potential nesting sites. This surprising result is comprehensible when viewed in the context of the self-organized spatial dynamics of the ants and their effect on the ants’ dispersal-limited natural enemies. Approximately 30% of the trees in the study site, a coffee agroecosystem in southern Mexico, were pruned or felled over a two-year period, and yet the abundance of the ant nests more than doubled over the seven-year study. Throughout the transition, the spatial distribution of the ants maintained a power-law distribution – a signal of spatial self organization – but the local clustering of the nests was reduced post-pruning. A cellular automata model incorporating the changed spatial structure of the ants and the resulting partial escape from antagonists reproduced the observed increase in abundance, highlighting how self-organized spatial dynamics can profoundly influence the responses of ecosystems to perturbations. PMID:24842117
A spatial age-structured model for describing sea lamprey (Petromyzon marinus) population dynamics
Robinson, Jason M.; Wilberg, Michael J.; Adams, Jean V.; Jones, Michael L.
2013-01-01
The control of invasive sea lampreys (Petromyzon marinus) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.
Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago
Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.
2018-01-01
Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753
Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.
Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc
2018-03-01
Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.
REVIEW OF SIMULATION METHODS FOR SPATIALLY-EXPLICIT POPULATION-LEVEL RISK ASSESSMENT
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 ...
S.M. Moore; C.A. Manore; V.A. Bokil; E.T. Borer; P.R. Hosseini
2011-01-01
Many generalist pathogens are influenced by the spatial distributions and relative abundances of susceptible host species. The spatial structure of host populations can influence patterns of infection incidence (or disease outbreaks), and the effects of a generalist pathogen on host community dynamics in a spatially heterogeneous community may differ from predictions...
Restoration ecology: two-sex dynamics and cost minimization.
Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy
2013-01-01
We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model's equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost.
Restoration Ecology: Two-Sex Dynamics and Cost Minimization
Molnár, Ferenc; Caragine, Christina; Caraco, Thomas; Korniss, Gyorgy
2013-01-01
We model a spatially detailed, two-sex population dynamics, to study the cost of ecological restoration. We assume that cost is proportional to the number of individuals introduced into a large habitat. We treat dispersal as homogeneous diffusion in a one-dimensional reaction-diffusion system. The local population dynamics depends on sex ratio at birth, and allows mortality rates to differ between sexes. Furthermore, local density dependence induces a strong Allee effect, implying that the initial population must be sufficiently large to avert rapid extinction. We address three different initial spatial distributions for the introduced individuals; for each we minimize the associated cost, constrained by the requirement that the species must be restored throughout the habitat. First, we consider spatially inhomogeneous, unstable stationary solutions of the model’s equations as plausible candidates for small restoration cost. Second, we use numerical simulations to find the smallest rectangular cluster, enclosing a spatially homogeneous population density, that minimizes the cost of assured restoration. Finally, by employing simulated annealing, we minimize restoration cost among all possible initial spatial distributions of females and males. For biased sex ratios, or for a significant between-sex difference in mortality, we find that sex-specific spatial distributions minimize the cost. But as long as the sex ratio maximizes the local equilibrium density for given mortality rates, a common homogeneous distribution for both sexes that spans a critical distance yields a similarly low cost. PMID:24204810
Linking extinction-colonization dynamics to genetic structure in a salamander metapopulation.
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.
Spatial aggregations arising from gregarious behavior are common in nature and have important implications for population dynamics, community stability, and conservation. However, the translation of aggregation behaviors into emergent properties of populations and communities de...
SPATIAL EXPLICIT POPULATION MODELS FOR RISK ASSESSMENT: COMMON LOONS AND MERCURY AS A CASE STUDY
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 ...
Disease Spread and Its Effect on Population Dynamics in Heterogeneous Environment
NASA Astrophysics Data System (ADS)
Upadhyay, Ranjit Kumar; Roy, Parimita
In this paper, an eco-epidemiological model in which both species diffuse along a spatial gradient has been shown to exhibit temporal chaos at a fixed point in space. The proposed model is a modification of the model recently presented by Upadhyay and Roy [2014]. The spatial interactions among the species have been represented in the form of reaction-diffusion equations. The model incorporates the intrinsic growth rate of fish population which varies linearly with the depth of water. Numerical results show that diffusion can drive otherwise stable system into aperiodic behavior with sensitivity to initial conditions. We show that spatially induced chaos plays an important role in spatial pattern formation in heterogeneous environment. Spatiotemporal distributions of species have been simulated using the diffusivity assumptions realistic for natural eco-epidemic systems. We found that in heterogeneous environment, the temporal dynamics of both the species are drastically different and show chaotic behavior. It was also found that the instability observed in the model is due to spatial heterogeneity and diffusion-driven. Cumulative death rate of predator has an appreciable effect on model dynamics as the spatial distribution of all constituent populations exhibit significant changes when this model parameter is changed and it acts as a regularizing factor.
Spatial structure and nutrients promote invasion of IncP-1 plasmids in bacterial populations
Fox, Randal E; Zhong, Xue; Krone, Stephen M; Top, Eva M
2008-01-01
In spite of the importance of plasmids in bacterial adaptation, we have a poor understanding of their dynamics. It is not known if or how plasmids persist in and spread through (invade) a bacterial population when there is no selection for plasmid-encoded traits. Moreover, the differences in dynamics between spatially structured and mixed populations are poorly understood. Through a joint experimental/theoretical approach, we tested the hypothesis that self-transmissible IncP-1 plasmids can invade a bacterial population in the absence of selection when initially very rare, but only in spatially structured habitats and when nutrients are regularly replenished. Using protocols that differed in the degree of spatial structure and nutrient levels, the invasiveness of plasmid pB10 in Escherichia coli was monitored during at least 15 days, with an initial fraction of plasmid-bearing (p+) cells as low as 10−7. To further explore the mechanisms underlying plasmid dynamics, we developed a spatially explicit mathematical model. When cells were grown on filters and transferred to fresh medium daily, the p+ fraction increased to 13%, whereas almost complete invasion occurred when the population structure was disturbed daily. The plasmid was unable to invade in liquid. When carbon source levels were lower or not replenished, plasmid invasion was hampered. Simulations of the mathematical model closely matched the experimental results and produced estimates of the effects of alternative experimental parameters. This allowed us to isolate the likely mechanisms most responsible for the observations. In conclusion, spatial structure and nutrient availability can be key determinants in the invasiveness of plasmids. PMID:18528415
Patrick C. Tobin; Ottar N. Bjornstad
2005-01-01
Natural enemy-victim systems may exhibit a range of dynamic space-time patterns. We used a theoretical framework to study spatiotemporal structuring in a transient natural enemy-victim system subject to differential rates of dispersal, stochastic forcing, and nonlinear dynamics. Highly mobile natural enemies that attacked less mobile victims were locally spatially...
The influence of spatial processes on population dynamics within river-stream networks is poorly understood. Utilizing spatially explicit analyses of temporal genetic variance, we examined whether persistence of Central Stonerollers (Campostoma anomalum) reflects differences in h...
The geography of spatial synchrony
Jonathan A. Walter; Lawrence W. Sheppard; Thomas L. Anderson; Jude H. Kastens; Ottar N. Bjørnstad; Andrew M. Liebhold; Daniel C. Reuman; Bernd Blasius
2017-01-01
Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the...
Benjamin A. Crabb; James A. Powell; Barbara J. Bentz
2012-01-01
Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...
Spatio-temporal transitions in the dynamics of bacterial populations
NASA Astrophysics Data System (ADS)
Lin, Anna; Lincoln, Bryan; Mann, Bernward; Torres, Gelsy; Kas, Josef; Swinney, Harry
2001-03-01
We experimentally investigate the population dynamics of a strain of E. coli bacteria living under spatially inhomogeneous growth conditions. A localized perturbation that moves with a well-defined drift velocity is imposed on the system. A reaction-diffusion model of this situation^1 predicts that an abrupt transition between spatial localization and extinction of the colony occurs for a fixed average growth rate when the drift velocity exceeds a critical value. Also, a transition between localized and delocalized populations is predicted to occur at a fixed drift velocity when the spatially averaged growth rate is varied. We create a spatially localized perturbation with UV light and vary the strength and drift velocity of the perturbation to investigate the existence of the different bacterial population distributions and the transitions between them. Numerical simulations of a 250 mm by 20 mm system guide our experiments. ^1K. A. Dahmen, D. R. Nelson, N. M. Shnerb, Jour. Math. Bio., 41 1 (2000).
Temporally increasing spatial synchrony of North American temperature and bird populations
NASA Astrophysics Data System (ADS)
Koenig, Walter D.; Liebhold, Andrew M.
2016-06-01
The ecological impacts of modern global climate change are detectable in a wide variety of phenomena, ranging from shifts in species ranges to changes in community composition and human disease dynamics. So far, however, little attention has been given to temporal changes in spatial synchrony--the coincident change in abundance or value across the landscape--despite the importance of environmental synchrony as a driver of population trends and the central role of environmental variability in population rescue and extinction. Here we demonstrate that across North America, spatial synchrony of a significant proportion of 49 widespread North American wintering bird species has increased over the past 50 years--the period encompassing particularly intense anthropogenic effects in climate--paralleling significant increases in spatial synchrony of mean maximum air temperature. These results suggest the potential for increased spatial synchrony in environmental factors to be affecting a wide range of ecological phenomena. These effects are likely to vary, but for North American wildlife species, increased spatial synchrony driven by environmental factors may be the basis for a previously unrecognized threat to their long-term persistence in the form of more synchronized population dynamics reducing the potential for demographic rescue among interacting subpopulations.
Spatial heterogeneity in the carrying capacity of sika deer in Japan
Iijima, Hayato; Ueno, Mayumi
2016-01-01
Abstract Carrying capacity is 1 driver of wildlife population dynamics. Although in previous studies carrying capacity was considered to be a fixed entity, it may differ among locations due to environmental variation. The factors underlying variability in carrying capacity, however, have rarely been examined. Here, we investigated spatial heterogeneity in the carrying capacity of Japanese sika deer ( Cervus nippon ) from 2005 to 2014 in Yamanashi Prefecture, central Japan (mesh with grid cells of 5.5×4.6 km) by state-space modeling. Both carrying capacity and density dependence differed greatly among cells. Estimated carrying capacities ranged from 1.34 to 98.4 deer/km 2 . According to estimated population dynamics, grid cells with larger proportions of artificial grassland and deciduous forest were subject to lower density dependence and higher carrying capacity. We conclude that population dynamics of ungulates may vary spatially through spatial variation in carrying capacity and that the density level for controlling ungulate abundance should be based on the current density level relative to the carrying capacity for each area. PMID:29692470
Homogenization techniques for population dynamics in strongly heterogeneous landscapes.
Yurk, Brian P; Cobbold, Christina A
2018-12-01
An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.
Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.
2005-01-01
A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.
Kahilainen, Aapo; van Nouhuys, Saskya; Schulz, Torsti; Saastamoinen, Marjo
2018-04-23
Habitat fragmentation and climate change are both prominent manifestations of global change, but there is little knowledge on the specific mechanisms of how climate change may modify the effects of habitat fragmentation, for example, by altering dynamics of spatially structured populations. The long-term viability of metapopulations is dependent on independent dynamics of local populations, because it mitigates fluctuations in the size of the metapopulation as a whole. Metapopulation viability will be compromised if climate change increases spatial synchrony in weather conditions associated with population growth rates. We studied a recently reported increase in metapopulation synchrony of the Glanville fritillary butterfly (Melitaea cinxia) in the Finnish archipelago, to see if it could be explained by an increase in synchrony of weather conditions. For this, we used 23 years of butterfly survey data together with monthly weather records for the same period. We first examined the associations between population growth rates within different regions of the metapopulation and weather conditions during different life-history stages of the butterfly. We then examined the association between the trends in the synchrony of the weather conditions and the synchrony of the butterfly metapopulation dynamics. We found that precipitation from spring to late summer are associated with the M. cinxia per capita growth rate, with early summer conditions being most important. We further found that the increase in metapopulation synchrony is paralleled by an increase in the synchrony of weather conditions. Alternative explanations for spatial synchrony, such as increased dispersal or trophic interactions with a specialist parasitoid, did not show paralleled trends and are not supported. The climate driven increase in M. cinxia metapopulation synchrony suggests that climate change can increase extinction risk of spatially structured populations living in fragmented landscapes by altering their dynamics. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Range expansion through fragmented landscapes under a variable climate
Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J
2013-01-01
Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124
Mary M. Conner; John J. Keane; Claire V. Gallagher; Thomas E. Munton; Paula A. Shaklee
2016-01-01
Monitoring studies often use marked animals to estimate population abundance at small spatial scales. However, at smaller scales, occupancy sampling, which uses detection/nondetection data, may be useful where sites are approximately territories, and occupancy dynamics should be strongly correlated with population dynamics. Occupancy monitoring has advantages...
Potts, Jonathan R; Petrovskii, Sergei V
2017-05-07
Animal movement is a key mechanism for shaping population dynamics. The effect of interactions between competing animals on a population's survival has been studied for many decades. However, interactions also affect an animal's subsequent movement decisions. Despite this, the indirect effect of these decisions on animal survival is much less well-understood. Here, we incorporate movement responses to foreign animals into a model of two competing populations, where inter-specific competition is greater than intra-specific competition. When movement is diffusive, the travelling wave moves from the stronger population to the weaker. However, by incorporating behaviourally induced directed movement towards the stronger population, the weaker one can slow the travelling wave down, even reversing its direction. Hence movement responses can switch the predictions of traditional mechanistic models. Furthermore, when environmental heterogeneity is combined with aggressive movement strategies, it is possible for spatially segregated co-existence to emerge. In this situation, the spatial patterns of the competing populations have the unusual feature that they are slightly out-of-phase with the environmental patterns. Finally, incorporating dynamic movement responses can also enable stable co-existence in a homogeneous environment, giving a new mechanism for spatially segregated co-existence. Copyright © 2017 Elsevier Ltd. All rights reserved.
Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa
Wesolowski, Amy; O’Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J.; Buckee, Caroline O.
2015-01-01
Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. PMID:26158274
Living in the branches: population dynamics and ecological processes in dendritic networks
Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.
2007-01-01
Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.
Spatial structures in a simple model of population dynamics for parasite-host interactions
NASA Astrophysics Data System (ADS)
Dong, J. J.; Skinner, B.; Breecher, N.; Schmittmann, B.; Zia, R. K. P.
2015-08-01
Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the population's long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocity generally increases the parasite population.
Bacterial predator–prey dynamics in microscale patchy landscapes
Rotem, Or; Jurkevitch, Edouard; Dekker, Cees
2016-01-01
Soil is a microenvironment with a fragmented (patchy) spatial structure in which many bacterial species interact. Here, we explore the interaction between the predatory bacterium Bdellovibrio bacteriovorus and its prey Escherichia coli in microfabricated landscapes. We ask how fragmentation influences the prey dynamics at the microscale and compare two landscape geometries: a patchy landscape and a continuous landscape. By following the dynamics of prey populations with high spatial and temporal resolution for many generations, we found that the variation in predation rates was twice as large in the patchy landscape and the dynamics was correlated over shorter length scales. We also found that while the prey population in the continuous landscape was almost entirely driven to extinction, a significant part of the prey population in the fragmented landscape persisted over time. We observed significant surface-associated growth, especially in the fragmented landscape and we surmise that this sub-population is more resistant to predation. Our results thus show that microscale fragmentation can significantly influence bacterial interactions. PMID:26865299
Machine Vision Within The Framework Of Collective Neural Assemblies
NASA Astrophysics Data System (ADS)
Gupta, Madan M.; Knopf, George K.
1990-03-01
The proposed mechanism for designing a robust machine vision system is based on the dynamic activity generated by the various neural populations embedded in nervous tissue. It is postulated that a hierarchy of anatomically distinct tissue regions are involved in visual sensory information processing. Each region may be represented as a planar sheet of densely interconnected neural circuits. Spatially localized aggregates of these circuits represent collective neural assemblies. Four dynamically coupled neural populations are assumed to exist within each assembly. In this paper we present a state-variable model for a tissue sheet derived from empirical studies of population dynamics. Each population is modelled as a nonlinear second-order system. It is possible to emulate certain observed physiological and psychophysiological phenomena of biological vision by properly programming the interconnective gains . Important early visual phenomena such as temporal and spatial noise insensitivity, contrast sensitivity and edge enhancement will be discussed for a one-dimensional tissue model.
Ozgul, Arpat; Armitage, Kenneth B; Blumstein, Daniel T; Oli, Madan K
2006-04-01
Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.
Spatial variation in population dynamics of Sitka mice in floodplain forests.
T.A. Hanley; J.C. Barnard
1999-01-01
Population dynamics and demography of the Sitka mouse, Peromyscus keeni sitkensis, were studied by mark-recapture live-trapping over a 4-year period in four floodplain and upland forest habitats: old-growth Sitka spruce (Picea sitchensis) floodplain; red alder (Alnus rubra) floodplain; beaver-pond...
MODELING THE DYNAMICS OF WILDLIFE HABITAT AND POPULATIONS AT THE LANDSCAPE SCALE
A forest dynamics model (FORCLIM) was linked to a spatial wildlife population model (PATCH) to assess the effects of habitat change in a landscape on selected wildlife species. The habitat changes included forest responses to harvesting, development, and climate change on a west...
The role of insect dispersal and migration in population processes
NASA Technical Reports Server (NTRS)
Rabb, R. L.; Stinner, R. E.
1979-01-01
Movement functions in the population dynamics of insects are discussed. Modes of movement, movement from a population view, and population patterns are described and predicted. A wide-area of spatial and temporal patterns are presented.
Otárola, Mauricio Fernández; Avalos, Gerardo
2014-06-01
• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.
Zhang, Rong; Leng, Yun-fa; Zhu, Meng-meng; Wang, Fang
2007-11-01
Based on geographic information system and geostatistics, the spatial structure of Therioaphis trifolii population of different periods in Yuanzhou district of Guyuan City, the southern Ningxia Province, was analyzed. The spatial distribution of Therioaphis trifolii population was also simulated by ordinary Kriging interpretation. The results showed that Therioaphis trifolii population of different periods was correlated spatially in the study area. The semivariograms of Therioaphis trifolii could be described by exponential model, indicating an aggregated spatial arrangement. The spatial variance varied from 34.13%-48.77%, and the range varied from 8.751-12.049 km. The degree and direction of aggregation showed that the trend was increased gradually from southwest to northeast. The dynamic change of Therioaphis trifolii population in different periods could be analyzed intuitively on the simulated maps of the spatial distribution from the two aspects of time and space, The occurrence position and degree of Therioaphis trifolii to a state of certain time could be determined easily.
Long-term spatial heterogeneity in mallard distribution in the Prairie pothole region
Janke, Adam K.; Anteau, Michael J.; Stafford, Joshua D.
2017-01-01
The Prairie Pothole Region (PPR) of north-central United States and south-central Canada supports greater than half of all breeding mallards (Anas platyrhynchos) annually counted in North America and is the focus of widespread conservation and research efforts. Allocation of conservation resources for this socioeconomically important population would benefit from an understanding of the nature of spatiotemporal variation in distribution of breeding mallards throughout the 850,000 km2 landscape. We used mallard counts from the Waterfowl Breeding Population and Habitat Survey to test for spatial heterogeneity and identify high- and low-abundance regions of breeding mallards over a 50-year time series. We found strong annual spatial heterogeneity in all years: 90% of mallards counted annually were on an average of only 15% of surveyed segments. Using a local indicator of spatial autocorrelation, we found a relatively static distribution of low-count clusters in northern Montana, USA, and southern Alberta, Canada, and a dynamic distribution of high-count clusters throughout the study period. Distribution of high-count clusters shifted southeast from northwestern portions of the PPR in Alberta and western Saskatchewan, Canada, to North and South Dakota, USA, during the latter half of the study period. This spatial redistribution of core mallard breeding populations was likely driven by interactions between environmental variation that created favorable hydrological conditions for wetlands in the eastern PPR and dynamic land-use patterns related to upland cropping practices and government land-retirement programs. Our results highlight an opportunity for prioritizing relatively small regions within the PPR for allocation of wetland and grassland conservation for mallard populations. However, the extensive spatial heterogeneity in core distributions over our study period suggests such spatial prioritization will have to overcome challenges presented by dynamic land-use and climate patterns in the region, and thus merits additional monitoring and empirical research to anticipate future population distribution. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
Population dynamics in an intermittent refuge
NASA Astrophysics Data System (ADS)
Colombo, E. H.; Anteneodo, C.
2016-10-01
Population dynamics is constrained by the environment, which needs to obey certain conditions to support population growth. We consider a standard model for the evolution of a single species population density, which includes reproduction, competition for resources, and spatial spreading, while subject to an external harmful effect. The habitat is spatially heterogeneous, there existing a refuge where the population can be protected. Temporal variability is introduced by the intermittent character of the refuge. This scenario can apply to a wide range of situations, from a laboratory setting where bacteria can be protected by a blinking mask from ultraviolet radiation, to large-scale ecosystems, like a marine reserve where there can be seasonal fishing prohibitions. Using analytical and numerical tools, we investigate the asymptotic behavior of the total population as a function of the size and characteristic time scales of the refuge. We obtain expressions for the minimal size required for population survival, in the slow and fast time scale limits.
Dispersal responses override density effects on genetic diversity during post-disturbance succession
Landguth, Erin L.; Bull, C. Michael; Banks, Sam C.; Gardner, Michael G.; Driscoll, Don A.
2016-01-01
Dispersal fundamentally influences spatial population dynamics but little is known about dispersal variation in landscapes where spatial heterogeneity is generated predominantly by disturbance and succession. We tested the hypothesis that habitat succession following fire inhibits dispersal, leading to declines over time in genetic diversity in the early successional gecko Nephrurus stellatus. We combined a landscape genetics field study with a spatially explicit simulation experiment to determine whether successional patterns in genetic diversity were driven by habitat-mediated dispersal or demographic effects (declines in population density leading to genetic drift). Initial increases in genetic structure following fire were likely driven by direct mortality and rapid population expansion. Subsequent habitat succession increased resistance to gene flow and decreased dispersal and genetic diversity in N. stellatus. Simulated changes in population density alone did not reproduce these results. Habitat-mediated reductions in dispersal, combined with changes in population density, were essential to drive the field-observed patterns. Our study provides a framework for combining demographic, movement and genetic data with simulations to discover the relative influence of demography and dispersal on patterns of landscape genetic structure. Our results suggest that succession can inhibit connectivity among individuals, opening new avenues for understanding how disturbance regimes influence spatial population dynamics. PMID:27009225
Dynamic feature analysis of vector-based images for neuropsychological testing
NASA Astrophysics Data System (ADS)
Smith, Stephen L.; Cervantes, Basilio R.
1998-07-01
The dynamic properties of human motor activities, such as those observed in the course of drawing simple geometric shapes, are considerably more complex and often more informative than the goal to be achieved; in this case a static line drawing. This paper demonstrates how these dynamic properties may be used to provide a means of assessing a patient's visuo-spatial ability -- an important component of neuropsychological testing. The work described here provides a quantitative assessment of visuo-spatial ability, whilst preserving the conventional test environment. Results will be presented for a clinical population of long-term haemodialysis patients and test population comprises three groups of children (1) 7-8 years, (2) 9-10 years and (3) 11-12 years, all of which have no known neurological dysfunction. Ten new dynamic measurements extracted from patient responses in conjunction with one static feature deduced from earlier work describe a patient's visuo-spatial ability in a quantitative manner with sensitivity not previously attainable. The dynamic feature measurements in isolation provide a unique means of tracking a patient's approach to motor activities and could prove useful in monitoring a child' visuo-motor development.
Transoceanic migration, spatial dynamics, and population linkages of white sharks.
Bonfil, Ramón; Meÿer, Michael; Scholl, Michael C; Johnson, Ryan; O'Brien, Shannon; Oosthuizen, Herman; Swanson, Stephan; Kotze, Deon; Paterson, Michael
2005-10-07
The large-scale spatial dynamics and population structure of marine top predators are poorly known. We present electronic tag and photographic identification data showing a complex suite of behavioral patterns in white sharks. These include coastal return migrations and the fastest known transoceanic return migration among swimming fauna, which provide direct evidence of a link between widely separated populations in South Africa and Australia. Transoceanic return migration involved a return to the original capture location, dives to depths of 980 meters, and the tolerance of water temperatures as low as 3.4 degrees C. These findings contradict previous ideas that female white sharks do not make transoceanic migrations, and they suggest natal homing behavior.
Social and spatial effects on genetic variation between foraging flocks in a wild bird population.
Radersma, Reinder; Garroway, Colin J; Santure, Anna W; de Cauwer, Isabelle; Farine, Damien R; Slate, Jon; Sheldon, Ben C
2017-10-01
Social interactions are rarely random. In some instances, animals exhibit homophily or heterophily, the tendency to interact with similar or dissimilar conspecifics, respectively. Genetic homophily and heterophily influence the evolutionary dynamics of populations, because they potentially affect sexual and social selection. Here, we investigate the link between social interactions and allele frequencies in foraging flocks of great tits (Parus major) over three consecutive years. We constructed co-occurrence networks which explicitly described the splitting and merging of 85,602 flocks through time (fission-fusion dynamics), at 60 feeding sites. Of the 1,711 birds in those flocks, we genotyped 962 individuals at 4,701 autosomal single nucleotide polymorphisms (SNPs). By combining genomewide genotyping with repeated field observations of the same individuals, we were able to investigate links between social structure and allele frequencies at a much finer scale than was previously possible. We explicitly accounted for potential spatial effects underlying genetic structure at the population level. We modelled social structure and spatial configuration of great tit fission-fusion dynamics with eigenvector maps. Variance partitioning revealed that allele frequencies were strongly affected by group fidelity (explaining 27%-45% of variance) as individuals tended to maintain associations with the same conspecifics. These conspecifics were genetically more dissimilar than expected, shown by genomewide heterophily for pure social (i.e., space-independent) grouping preferences. Genomewide homophily was linked to spatial configuration, indicating spatial segregation of genotypes. We did not find evidence for homophily or heterophily for putative socially relevant candidate genes or any other SNP markers. Together, these results demonstrate the importance of distinguishing social and spatial processes in determining population structure. © 2017 John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kostova, T; Carlsen, T
2003-11-21
We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less
Circumpolar variation in periodicity and synchrony among gypsy moth populations
Derek M. Johnson; Andrew M. Liebhold; Ottar N. Bjornstad; Michael L. Mcmanus; Michael L. Mcmanus
2005-01-01
Previous studies or insect dynamics have detected spatial synchrony in intraspecific population dynamics up to, but not exceeding, 1000 km. Oddly, interspecific synchrony has recently been reported at distances well over 1000 km (at continental and circumpolar scales). While the authors implicated climatic effects as the cause for the apparent largescale interspecific...
Effects of the distant population density on spatial patterns of demographic dynamics
NASA Astrophysics Data System (ADS)
Tamura, Kohei; Masuda, Naoki
2017-08-01
Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.
Effects of the distant population density on spatial patterns of demographic dynamics.
Tamura, Kohei; Masuda, Naoki
2017-08-01
Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m ) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.
Effects of the distant population density on spatial patterns of demographic dynamics
2017-01-01
Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km. PMID:28878987
Modeling wildlife populations with HexSim
HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications including population viability analysis for on...
Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J
2017-10-10
Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.
Modeling spatial competition for light in plant populations with the porous medium equation.
Beyer, Robert; Etard, Octave; Cournède, Paul-Henry; Laurent-Gengoux, Pascal
2015-02-01
We consider a plant's local leaf area index as a spatially continuous variable, subject to particular reaction-diffusion dynamics of allocation, senescence and spatial propagation. The latter notably incorporates the plant's tendency to form new leaves in bright rather than shaded locations. Applying a generalized Beer-Lambert law allows to link existing foliage to production dynamics. The approach allows for inter-individual variability and competition for light while maintaining robustness-a key weakness of comparable existing models. The analysis of the single plant case leads to a significant simplification of the system's key equation when transforming it into the well studied porous medium equation. Confronting the theoretical model to experimental data of sugar beet populations, differing in configuration density, demonstrates its accuracy.
A high-resolution genetic signature of demographic and spatial expansion in epizootic rabies virus
Biek, Roman; Henderson, J. Caroline; Waller, Lance A.; Rupprecht, Charles E.; Real, Leslie A.
2007-01-01
Emerging pathogens potentially undergo rapid evolution while expanding in population size and geographic range during the course of invasion, yet it is generally difficult to demonstrate how these processes interact. Our analysis of a 30-yr data set covering a large-scale rabies virus outbreak among North American raccoons reveals the long lasting effect of the initial infection wave in determining how viral populations are genetically structured in space. We further find that coalescent-based estimates derived from the genetic data yielded an amazingly accurate reconstruction of the known spatial and demographic dynamics of the virus over time. Our study demonstrates the combined evolutionary and population dynamic processes characterizing the spread of pathogen after its introduction into a fully susceptible host population. Furthermore, the results provide important insights regarding the spatial scale of rabies persistence and validate the use of coalescent approaches for uncovering even relatively complex population histories. Such approaches will be of increasing relevance for understanding the epidemiology of emerging zoonotic diseases in a landscape context. PMID:17470818
NASA Astrophysics Data System (ADS)
Ma, Zhanshan (Sam)
In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three categories of population dynamics models: deterministic modeling with Logistic chaos map as an example, stochastic modeling with spatial distribution patterns as an example, as well as survival analysis and extended evolutionary game theory (EEGT) modeling. Sample experiment results with Genetic algorithms (GA) are presented to demonstrate the applications of these models. The proposed EC population dynamics approach also makes survival selection largely unnecessary or much simplified since the individuals are naturally selected (controlled) by the mathematical models for EC population dynamics.
Sustainable and Smart City Planning Using Spatial Data in Wallonia
NASA Astrophysics Data System (ADS)
Stephenne, N.; Beaumont, B.; Hallot, E.; Wolff, E.; Poelmans, L.; Baltus, C.
2016-09-01
Simulating population distribution and land use changes in space and time offer opportunities for smart city planning. It provides a holistic and dynamic vision of fast changing urban environment to policy makers. Impacts, such as environmental and health risks or mobility issues, of policies can be assessed and adapted consequently. In this paper, we suppose that "Smart" city developments should be sustainable, dynamic and participative. This paper addresses these three smart objectives in the context of urban risk assessment in Wallonia, Belgium. The sustainable, dynamic and participative solution includes (i) land cover and land use mapping using remote sensing and GIS, (ii) population density mapping using dasymetric mapping, (iii) predictive modelling of land use changes and population dynamics and (iv) risk assessment. The comprehensive and long-term vision of the territory should help to draw sustainable spatial planning policies, to adapt remote sensing acquisition, to update GIS data and to refine risk assessment from regional to city scale.
Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.
Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre
2003-05-01
We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.
Wagner, Tyler; Jones, Michael L.; Ebener, Mark P.; Arts, Michael T.; Brenden, Travis O.; Honeyfield, Dale C.; Wright, Gregory M.; Faisal, Mohamed
2010-01-01
We examined the spatial and temporal dynamics of health indicators in four lake whitefish (Coregonus clupeaformis) stocks located in northern lakes Michigan and Huron from 2003 to 2006. The specific objectives were to (1) quantify spatial and temporal variability in health indicators; (2) examine relationships among nutritional indicators and stock-specific spatial and temporal dynamics of pathogen prevalence and intensity of infection; and (3) examine relationships between indicators measured on individual fish and stock-specific estimates of natural mortality. The percent of the total variation attributed to spatial and temporal sources varied greatly depending on the health indicator examined. The most notable pattern was a downward trend in the concentration of highly unsaturated fatty acids (HUFAs), observed in all stocks, in the polar lipid fraction of lake whitefish dorsal muscle tissue over the three study years. Variation among stocks and years for some indicators were correlated with the prevalence and intensity of the swimbladder nematode Cystidicola farionis, suggesting that our measures of fish health were related, at some level, with disease dynamics. We did not find relationships between spatial patterns in fish health indicators and estimates of natural mortality rates for the stocks. Our research highlights the complexity of the interactions between fish nutritional status, disease dynamics, and natural mortality in wild fish populations. Additional research that identifies thresholds of health indicators, below (or above) which survival may be reduced, will greatly help in understanding the relationship between indicators measured on individual fish and potential population-level effects.
Sibly, Richard M; Nabe-Nielsen, Jacob; Forchhammer, Mads C; Forbes, Valery E; Topping, Christopher J
2009-01-01
Background Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology. PMID:19549327
D. J. Isaak; R. F. Thurow; B. E. Rieman; J. B. Dunham
2003-01-01
Metapopulation dynamics have emerged as a key consideration in conservation planning for salmonid fishes. Implicit to many models of spatially structured populations is a degree of synchrony, or correlation, among populations. We used a spatially and temporally extensive database of chinook salmon (Oncorhynchus tshawytscha) redd counts from a wilderness area in central...
Spatial-temporal population dynamics across species range: from center to margin
Guo, Q.; Taper, M.L.; Schoenberger, M.; Brandl, J.
2005-01-01
Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either or local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.
Spatial-temporal population dynamics across species range: From centre to margin
Guo, Q.; Taper, M.; Schoenberger, M.; Brandle, J.
2005-01-01
Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.
Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di
2016-07-15
We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.
Predator-prey-subsidy population dynamics on stepping-stone domains with dispersal delays.
Eide, Ragna M; Krause, Andrew L; Fadai, Nabil T; Van Gorder, Robert A
2018-08-14
We examine the role of the travel time of a predator along a spatial network on predator-prey population interactions, where the predator is able to partially or fully sustain itself on a resource subsidy. The impact of access to food resources on the stability and behaviour of the predator-prey-subsidy system is investigated, with a primary focus on how incorporating travel time changes the dynamics. The population interactions are modelled by a system of delay differential equations, where travel time is incorporated as discrete delay in the network diffusion term in order to model time taken to migrate between spatial regions. The model is motivated by the Arctic ecosystem, where the Arctic fox consumes both hunted lemming and scavenged seal carcass. The fox travels out on sea ice, in addition to quadrennially migrating over substantial distances. We model the spatial predator-prey-subsidy dynamics through a "stepping-stone" approach. We find that a temporal delay alone does not push species into extinction, but rather may stabilize or destabilize coexistence equilibria. We are able to show that delay can stabilize quasi-periodic or chaotic dynamics, and conclude that the incorporation of dispersal delay has a regularizing effect on dynamics, suggesting that dispersal delay can be proposed as a solution to the paradox of enrichment. Copyright © 2018 Elsevier Ltd. All rights reserved.
Integrating population dynamics into mapping human exposure to seismic hazard
NASA Astrophysics Data System (ADS)
Freire, S.; Aubrecht, C.
2012-11-01
Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.
Evolution of the stellar mass function in multiple-population globular clusters
NASA Astrophysics Data System (ADS)
Vesperini, Enrico; Hong, Jongsuk; Webb, Jeremy J.; D'Antona, Franca; D'Ercole, Annibale
2018-05-01
We present the results of a survey of N-body simulations aimed at studying the effects of the long-term dynamical evolution on the stellar mass function (MF) of multiple stellar populations in globular clusters. Our simulations show that if first-(1G) and second-generation (2G) stars have the same initial MF (IMF), the global MFs of the two populations are affected similarly by dynamical evolution and no significant differences between the 1G and 2G MFs arise during the cluster's evolution. If the two populations have different IMFs, dynamical effects do not completely erase memory of the initial differences. Should observations find differences between the global 1G and 2G MFs, these would reveal the fingerprints of differences in their IMFs. Irrespective of whether the 1G and 2G populations have the same global IMF or not, dynamical effects can produce differences between the local (measured at various distances from the cluster centre) 1G and 2G MFs; these differences are a manifestation of the process of mass segregation in populations with different initial structural properties. In dynamically old and spatially mixed clusters, however, differences between the local 1G and 2G MFs can reveal differences between the 1G and 2G global MFs. In general, for clusters with any dynamical age, large differences between the local 1G and 2G MFs are more likely to be associated with differences in the global MF. Our study also reveals a dependence of the spatial mixing rate on the stellar mass, another dynamical consequence of the multiscale nature of multiple-population clusters.
Life history determines genetic structure and evolutionary potential of host–parasite interactions
Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.
2009-01-01
Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899
Life history determines genetic structure and evolutionary potential of host-parasite interactions.
Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C
2008-12-01
Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.
Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.
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.
Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.
Leaman, Eric J; Geuther, Brian Q; Behkam, Bahareh
2018-04-20
Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).
NASA Technical Reports Server (NTRS)
Finn, J. T.; Howard, R.
1981-01-01
A preliminary dynamic model of beaver spatial distribution and population growth was developed. The feasibility of locating beaver ponds on LANDSAT digital tapes, and of using this information to provide initial conditions of beaver spatial distribution for the model, and to validate model predictions is discussed. The techniques used to identify beaver ponds on LANDSAT are described.
Population changes in residential clusters in Japan.
Sekiguchi, Takuya; Tamura, Kohei; Masuda, Naoki
2018-01-01
Population dynamics in urban and rural areas are different. Understanding factors that contribute to local population changes has various socioeconomic and political implications. In the present study, we use population census data in Japan to examine contributors to the population growth of residential clusters between years 2005 and 2010. The data set covers the entirety of Japan and has a high spatial resolution of 500 × 500 m2, enabling us to examine population dynamics in various parts of the country (urban and rural) using statistical analysis. We found that, in addition to the area, population density, and age, the shape of the cluster and the spatial distribution of inhabitants within the cluster are significantly related to the population growth rate of a residential cluster. Specifically, the population tends to grow if the cluster is "round" shaped (given the area) and the population is concentrated near the center rather than periphery of the cluster. Combination of the present results and analysis framework with other factors that have been omitted in the present study, such as migration, terrain, and transportation infrastructure, will be fruitful.
Approaching the molecular origins of collective dynamics in oscillating cell populations
Mehta, Pankaj; Gregor, Thomas
2011-01-01
From flocking birds, to organ generation, to swarming bacterial colonies, biological systems often exhibit collective behaviors. Here, we review recent advances in our understanding of collective dynamics in cell populations. We argue that understanding population-level oscillations requires examining the system under consideration at three different levels of complexity: at the level of isolated cells, homogenous populations, and spatially structured populations. We discuss the experimental and theoretical challenges this poses and highlight how new experimental techniques, when combined with conceptual tools adapted from physics, may help us overcome these challenges. PMID:20934869
Holyoak, Marcel; Heath, Sacha K
2016-01-01
A growing number of studies have looked at how climate change alters the effects of habitat fragmentation and degradation on both single and multiple species; some raise concern that biodiversity loss and its effects will be exacerbated. The published literature on spatial dynamics (such as dispersal and metapopulation dynamics), habitat fragmentation and climate change requires synthesis and a conceptual framework to simplify thinking. We propose a framework that integrates how climate change affects spatial population dynamics and the effects of habitat fragmentation in terms of: (i) habitat quality, quantity and distribution; (ii) habitat connectivity; and (iii) the dynamics of habitat itself. We use the framework to categorize existing autecological studies and investigate how each is affected by anthropogenic climate change. It is clear that a changing climate produces changes in the geographic distribution of climatic conditions, and the amount and quality of habitat. The most thorough published studies show how such changes impact metapopulation persistence, source-sink dynamics, changes in species' geographic range and community composition. Climate-related changes in movement behavior and quantity, quality and distribution of habitat have also produced empirical changes in habitat connectivity for some species. An underexplored area is how habitat dynamics that are driven by climatic processes will affect species that live in dynamic habitats. We end our discussion by suggesting ways to improve current attempts to integrate climate change, spatial population dynamics and habitat fragmentation effects, and suggest distinct areas of study that might provide opportunities for more fully integrative work. © 2015 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.
Dynamics of place, boundary and object encoding in rat anterior claustrum
Jankowski, Maciej M.; O’Mara, Shane M.
2015-01-01
Discrete populations of brain cells signal differing types of spatial information. These “spatial cells” are largely confined to a closely-connected network of sites. We describe here, for the first time, cells in the anterior claustrum of the freely-moving rat encoding place, boundary and object information. This novel claustral spatial signal potentially directly modulates a wide variety of anterior cortical regions. We hypothesize that one of the functions of the claustrum is to provide information about body position, boundaries and landmark information, enabling dynamic control of behavior. PMID:26557060
Corn rootworms (Coleoptera: Chrysomelidae) in space and time
NASA Astrophysics Data System (ADS)
Park, Yong-Lak
Spatial dispersion is a main characteristic of insect populations. Dispersion pattern provides useful information for developing effective sampling and scouting programs because it affects sampling accuracy, efficiency, and precision. Insect dispersion, however, is dynamic in space and time and largely dependent upon interactions among insect, plant and environmental factors. This study investigated the spatial and temporal dynamics of corn rootworm dispersion at different spatial scales by using the global positioning system, the geographic information system, and geostatistics. Egg dispersion pattern was random or uniform in 8-ha cornfields, but could be aggregated at a smaller scale. Larval dispersion pattern was aggregated regardless of spatial scales used in this study. Soil moisture positively affected corn rootworm egg and larval dispersions. Adult dispersion tended to be aggregated during peak population period and random or uniform early and late in the season and corn plant phenology was a major factor to determine dispersion patterns. The dispersion pattern of root injury by corn rootworm larval feeding was aggregated and the degree of aggregation increased as the root injury increased within the range of root injury observed in microscale study. Between-year relationships in dispersion among eggs, larvae, adult, and environment provided a strategy that could predict potential root damage the subsequent year. The best prediction map for the subsequent year's potential root damage was the dispersion maps of adults during population peaked in the cornfield. The prediction map was used to develop site-specific pest management that can reduce chemical input and increase control efficiency by controlling pests only where management is needed. This study demonstrated the spatio-temporal dynamics of insect population and spatial interactions among insects, plants, and environment.
R. Justin DeRose; James N. Long
2012-01-01
Host conditions are known to influence spruce beetle population levels, but whether they influence the spatial and temporal patterns of beetle-caused mortality during an outbreak is unknown. Using dendrochronological techniques, we quantified the spatiotemporal dynamics of a modern (late 1980s through the early 2000s) spruce beetle outbreak in Engelmann spruce on the...
Besserve, Michel; Lowe, Scott C; Logothetis, Nikos K; Schölkopf, Bernhard; Panzeri, Stefano
2015-01-01
Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow are not yet fully understood. We investigated the role of gamma band (50-80 Hz) oscillations in transient modulations of communication among neural populations by using measures of direction-specific causal information transfer. We found that the local phase of gamma-band rhythmic activity exerted a stimulus-modulated and spatially-asymmetric directed effect on the firing rate of spatially separated populations within the primary visual cortex. The relationships between gamma phases at different sites (phase shifts) could be described as a stimulus-modulated gamma-band wave propagating along the spatial directions with the largest information transfer. We observed transient stimulus-related changes in the spatial configuration of phases (compatible with changes in direction of gamma wave propagation) accompanied by a relative increase of the amount of information flowing along the instantaneous direction of the gamma wave. These effects were specific to the gamma-band and suggest that the time-varying relationships between gamma phases at different locations mark, and possibly causally mediate, the dynamic reconfiguration of functional connections.
Besserve, Michel; Lowe, Scott C.; Logothetis, Nikos K.; Schölkopf, Bernhard; Panzeri, Stefano
2015-01-01
Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow are not yet fully understood. We investigated the role of gamma band (50–80 Hz) oscillations in transient modulations of communication among neural populations by using measures of direction-specific causal information transfer. We found that the local phase of gamma-band rhythmic activity exerted a stimulus-modulated and spatially-asymmetric directed effect on the firing rate of spatially separated populations within the primary visual cortex. The relationships between gamma phases at different sites (phase shifts) could be described as a stimulus-modulated gamma-band wave propagating along the spatial directions with the largest information transfer. We observed transient stimulus-related changes in the spatial configuration of phases (compatible with changes in direction of gamma wave propagation) accompanied by a relative increase of the amount of information flowing along the instantaneous direction of the gamma wave. These effects were specific to the gamma-band and suggest that the time-varying relationships between gamma phases at different locations mark, and possibly causally mediate, the dynamic reconfiguration of functional connections. PMID:26394205
Spatially explicit dynamic N-mixture models
Zhao, Qing; Royle, Andy; Boomer, G. Scott
2017-01-01
Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.
Heat exposure in cities: combining the dynamics of temperature and population
NASA Astrophysics Data System (ADS)
Hu, L.; Wilhelmi, O.; Uejio, C. K.
2017-12-01
Assessment of human exposure to extreme heat requires the distributions of temperature and population. However, both variables are dynamic, thus presenting many challenges in capturing temperature and population patterns spatially and over time in an urban context. This study aims to improve the understanding of spatiotemporal patterns of urban population exposure to heat, taking Chicago, USA as an example. We estimate the hourly, geographically variable, population distribution considering commute of workers and students in a regular weekday and analyze the diurnal air temperature patterns during different meteorological conditions from satellite observations. The results show a relatively larger temperature increase in less urbanized areas during extreme heat events (EHEs), resulting in a spatially homogeneous temperature distribution over Chicago Metropolitan area. A lake cooling effect is weaker during EHEs. Population dynamics due to daily commute determine higher population density in more urbanized areas during daytime. The city-wide analysis reveals that the exposure is more sensitive to the nighttime temperature increases, and EHEs enhance this sensitivity. The high exposure hotspots are identified at the northwest Chicago, Cicero and Oak Park areas, where the influence from Lake Michigan is weakened, while the spatial extent of high outdoor exposure areas varies diurnally. This study's findings have potential to better inform general heat mitigation strategies during hot summer months and facilitate emergency response during EHEs. Availability of remotely-sensed temperature observations as well as the workers and students commute-adjusted population data allows for the adoption of this study's methodology in other major metropolitan areas. A better understanding of space-time patterns of urban population's exposure to heat will further enable local decision makers to mitigate extreme heat health risks and develop more targeted heat preparedness and response strategies.
Sources, Sinks, and Model Accuracy
Spatial demographic models are a necessary tool for understanding how to manage landscapes sustainably for animal populations. These models, therefore, must offer precise and testable predications about animal population dynamics and how animal demographic parameters respond to ...
Effects of landscape and patch-level attributes on regional population persistence
Habitat patch size and isolation are often described as the key habitat variables influencing population dynamics. Yet habitat quality may also play an important role in influencing the regional persistence of spatially structured populations as the value or density of resources ...
Dispersal leads to spatial autocorrelation in species distributions: A simulation model
Bahn, V.; Krohn, W.B.; O'Connor, R.J.
2008-01-01
Compared to population growth regulated by local conditions, dispersal has been underappreciated as a central process shaping the spatial distribution of populations. This paper asks: (a) which conditions increase the importance of dispersers relative to local recruits in determining population sizes? and (b) how does dispersal influence the spatial distribution patterns of abundances among connected populations? We approached these questions with a simulation model of populations on a coupled lattice with cells of continuously varying habitat quality expressed as carrying capacities. Each cell contained a population with the basic dynamics of density-regulated growth, and was connected to other populations by immigration and emigration. The degree to which dispersal influenced the distribution of population sizes depended most strongly on the absolute amount of dispersal, and then on the potential population growth rate. Dispersal decaying in intensity with distance left close neighbours more alike in population size than distant populations, leading to an increase in spatial autocorrelation. The spatial distribution of species with low potential growth rates is more dependent on dispersal than that of species with high growth rates; therefore, distribution modelling for species with low growth rates requires particular attention to autocorrelation, and conservation management of these species requires attention to factors curtailing dispersal, such as fragmentation and dispersal barriers. ?? 2007 Elsevier B.V. All rights reserved.
Diffusion, Absorbing States, and Nonequilibrium Phase Transitions in Range Expansions and Evolution
NASA Astrophysics Data System (ADS)
Lavrentovich, Maxim Olegovich
The spatial organization of a population plays a key role in its evolutionary dynamics and growth. In this thesis, we study the dynamics of range expansions, in which populations expand into new territory. Focussing on microbes, we first consider how nutrients diffuse and are absorbed in a population, allowing it to grow. These nutrients may be absorbed before reaching the population interior, and this "nutrient shielding'' can confine the growth to a thin region on the population periphery. A thin population front implies a small local effective population size and enhanced number fluctuations (or genetic drift). We then study evolutionary dynamics under these growth conditions. In particular, we calculate the survival probability of mutations with a selective advantage occurring at the population front for two-dimensional expansions (e.g., along the surface of an agar plate), and three-dimensional expansions (e.g., an avascular tumor). We also consider the effects of irreversible, deleterious mutations which can lead to the loss of the advantageous mutation in the population via a "mutational meltdown,'' or non-equilibrium phase transition. We examine the effects of an inflating population frontier on the phase transition. Finally, we discuss how spatial dimension and frontier roughness influence range expansions of mutualistic, cross-feeding variants. We find here universal features of the phase diagram describing the onset of a mutualistic phase in which the variants remain mixed at long times.
The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3
Samuel A. Cushman; Jeremy Littell; Kevin McGarigal
2010-01-01
In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...
K.yle J. Haynes; Ottar N. Bjornstad; Andrew J. Allstadt; Andrew M. Liebhold
2012-01-01
Despite the pervasiveness of spatial synchrony of population fluctuations in virtually every taxon, it remains difficult to disentangle its underlying mechanisms, such as environmental perturbations and dispersal. We used multiple regression of distance matrices (MRMs) to statistically partition the importance of several factors potentially synchronizing the dynamics...
Haydon, D. T.; Stenseth, N. C.; Boyce, M. S.; Greenwood, P. E.
2001-01-01
Population ecologists have traditionally focused on the patterns and causes of population variation in the temporal domain for which a substantial body of practical analytic techniques have been developed. More recently, numerous studies have documented how populations may fluctuate synchronously over large spatial areas; analyses of such spatially extended time-series have started to provide additional clues regarding the causes of these population fluctuations and explanations for their synchronous occurrence. Here, we report on the development of a phase-based method for identifying coupling between temporally coincident but spatially distributed cyclic time-series, which we apply to the numbers of muskrat and mink recorded at 81 locations across Canada. The analysis reveals remarkable parallel clines in the strength of coupling between proximate populations of both species—declining from west to east—together with a corresponding increase in observed synchrony between these populations the further east they are located. PMID:11606729
Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan
2017-01-01
Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.
Consequences of parental care on population dynamics
NASA Astrophysics Data System (ADS)
de Oliveira, S. Moss
1999-12-01
We review the results obtained using the Penna model for biological ageing (T.J.P. Penna, J. Stat. Phys. 78 (1995) 1629) when different strategies of parental care are introduced into evolving populations. These results concern to: longevity of semelparous populations; self-organization of female menopause; the spatial distribution of the populations and finally, sexual fidelity.
Critical patch size generated by Allee effect in gypsy moth, Lymantria dispar (L.)
E. Vercken; A.M. Kramer; P.C. Tobin; J.M. Drake
2011-01-01
Allee effects are important dynamical mechanisms in small-density populations in which per capita population growth rate increases with density. When positive density dependence is sufficiently severe (a 'strong' Allee effect), a critical density arises below which populations do not persist. For spatially distributed populations subject to dispersal, theory...
Wallace, Cynthia S.A.; Advised by Marsh, Stuart E.
2002-01-01
The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.
Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan
2013-11-07
A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Runge, Jeffrey A.; Kovach, Adrienne I.; Churchill, James H.; Kerr, Lisa A.; Morrison, John R.; Beardsley, Robert C.; Berlinsky, David L.; Chen, Changsheng; Cadrin, Steven X.; Davis, Cabell S.; Ford, Kathryn H.; Grabowski, Jonathan H.; Howell, W. Huntting; Ji, Rubao; Jones, Rebecca J.; Pershing, Andrew J.; Record, Nicholas R.; Thomas, Andrew C.; Sherwood, Graham D.; Tallack, Shelly M. L.; Townsend, David W.
2010-10-01
We put forward a combined observing and modeling strategy for evaluating effects of environmental forcing on the dynamics of spatially structured cod populations spawning in the western Gulf of Maine. Recent work indicates at least two genetically differentiated complexes in this region: a late spring spawning, coastal population centered in Ipswich Bay, and a population that spawns in winter inshore and on nearshore banks in the Gulf of Maine and off southern New England. The two populations likely differ in trophic interactions and in physiological and behavioral responses to different winter and spring environments. Coupled physical-biological modeling has advanced to the point where within-decade forecasting of environmental conditions for recruitment to each of the two populations is feasible. However, the modeling needs to be supported by hydrographic, primary production and zooplankton data collected by buoys, and by data from remote sensing and fixed station sampling. Forecasts of environmentally driven dispersal and growth of planktonic early life stages, combined with an understanding of possible population-specific predator fields, usage of coastal habitat by juveniles and adult resident and migratory patterns, can be used to develop scenarios for spatially explicit population responses to multiple forcings, including climate change, anthropogenic impacts on nearshore juvenile habitat, connectivity among populations and management interventions such as regional fisheries closures.
1. The population dynamics of native herbivore species in central Appalachian deciduous forests were studied by analysing patterns of synchrony among intra- and interspecific populations and weather. 2. Spatial synchrony of 10 Lepidoptera species and three weather variables (min...
The interplay between human population dynamics and flooding in Bangladesh: a spatial analysis
NASA Astrophysics Data System (ADS)
di Baldassarre, G.; Yan, K.; Ferdous, MD. R.; Brandimarte, L.
2014-09-01
In Bangladesh, socio-economic and hydrological processes are both extremely dynamic and inter-related. Human population patterns are often explained as a response, or adaptation strategy, to physical events, e.g. flooding, salt-water intrusion, and erosion. Meanwhile, these physical processes are exacerbated, or mitigated, by diverse human interventions, e.g. river diversion, levees and polders. In this context, this paper describes an attempt to explore the complex interplay between floods and societies in Bangladeshi floodplains. In particular, we performed a spatially-distributed analysis of the interactions between the dynamics of human settlements and flood inundation patterns. To this end, we used flooding simulation results from inundation modelling, LISFLOOD-FP, as well as global datasets of population distribution data, such as the Gridded Population of the World (20 years, from 1990 to 2010) and HYDE datasets (310 years, from 1700 to 2010). The outcomes of this work highlight the behaviour of Bangladeshi floodplains as complex human-water systems and indicate the need to go beyond the traditional narratives based on one-way cause-effects, e.g. climate change leading to migrations.
Modeling spatial variation in avian survival and residency probabilities
Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth
2010-01-01
The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.
Modeling oscillations and spiral waves in Dictyostelium populations
NASA Astrophysics Data System (ADS)
Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj
2015-06-01
Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.
Newby, Jesse R.; Mills, L. Scott; Ruth, Toni K.; Pletscher, Daniel H.; Mitchell, Michael S.; Quigley, Howard B.; Murphy, Kerry M.; DeSimone, Rich
2013-01-01
An understanding of how stressors affect dispersal attributes and the contribution of local populations to multi-population dynamics are of immediate value to basic and applied ecology. Puma (Puma concolor) populations are expected to be influenced by inter-population movements and susceptible to human-induced source–sink dynamics. Using long-term datasets we quantified the contribution of two puma populations to operationally define them as sources or sinks. The puma population in the Northern Greater Yellowstone Ecosystem (NGYE) was largely insulated from human-induced mortality by Yellowstone National Park. Pumas in the western Montana Garnet Mountain system were exposed to greater human-induced mortality, which changed over the study due to the closure of a 915 km2 area to hunting. The NGYE’s population growth depended on inter-population movements, as did its ability to act as a source to the larger region. The heavily hunted Garnet area was a sink with a declining population until the hunting closure, after which it became a source with positive intrinsic growth and a 16× increase in emigration. We also examined the spatial and temporal characteristics of individual dispersal attributes (emigration, dispersal distance, establishment success) of subadult pumas (N = 126). Human-caused mortality was found to negatively impact all three dispersal components. Our results demonstrate the influence of human-induced mortality on not only within population vital rates, but also inter-population vital rates, affecting the magnitude and mechanisms of local population’s contribution to the larger metapopulation.
Phenotypically heterogeneous populations in spatially heterogeneous environments
NASA Astrophysics Data System (ADS)
Patra, Pintu; Klumpp, Stefan
2014-03-01
The spatial expansion of a population in a nonuniform environment may benefit from phenotypic heterogeneity with interconverting subpopulations using different survival strategies. We analyze the crossing of an antibiotic-containing environment by a bacterial population consisting of rapidly growing normal cells and slow-growing, but antibiotic-tolerant persister cells. The dynamics of crossing is characterized by mean first arrival times and is found to be surprisingly complex. It displays three distinct regimes with different scaling behavior that can be understood based on an analytical approximation. Our results suggest that a phenotypically heterogeneous population has a fitness advantage in nonuniform environments and can spread more rapidly than a homogeneous population.
Environmentally driven synchronies of Mediterranean cephalopod populations
NASA Astrophysics Data System (ADS)
Keller, Stefanie; Quetglas, Antoni; Puerta, Patricia; Bitetto, Isabella; Casciaro, Loredana; Cuccu, Danila; Esteban, Antonio; Garcia, Cristina; Garofalo, Germana; Guijarro, Beatriz; Josephides, Marios; Jadaud, Angelique; Lefkaditou, Evgenia; Maiorano, Porzia; Manfredi, Chiara; Marceta, Bojan; Micallef, Reno; Peristeraki, Panagiota; Relini, Giulio; Sartor, Paolo; Spedicato, Maria Teresa; Tserpes, George; Hidalgo, Manuel
2017-03-01
The Mediterranean Sea is characterized by large scale gradients of temperature, productivity and salinity, in addition to pronounced mesoscale differences. Such a heterogeneous system is expected to shape the population dynamics of marine species. On the other hand, prevailing environmental and climatic conditions at whole basin scale may force spatially distant populations to fluctuate in synchrony. Cephalopods are excellent case studies to test these hypotheses owing to their high sensitivity to environmental conditions. Data of two cephalopod species with contrasting life histories (benthic octopus vs nectobenthic squid), obtained from scientific surveys carried out throughout the Mediterranean during the last 20 years were analyzed. The objectives of this study and the methods used to achieve them (in parentheses) were: (i) to investigate synchronies in spatially separated populations (decorrelation analysis); (ii) detect underlying common abundance trends over distant regions (dynamic factor analysis, DFA); and (iii) analyse putative influences of key environmental drivers such as productivity and sea surface temperature on the population dynamics at regional scale (general linear models, GLM). In accordance with their contrasting spatial mobility, the distance from where synchrony could no longer be detected (decorrelation scale) was higher in squid than in octopus (349 vs 217 km); for comparison, the maximum distance between locations was 2620 km. The DFA revealed a general increasing trend in the abundance of both species in most areas, which agrees with the already reported worldwide proliferation of cephalopods. DFA results also showed that population dynamics are more similar in the eastern than in the western Mediterranean basin. According to the GLM models, cephalopod populations were negatively affected by productivity, which would be explained by an increase of competition and predation by fishes. While warmer years coincided with declining octopus numbers, areas of high sea surface temperature showed higher densities of squid. Our results are relevant for regional fisheries management and demonstrate that the regionalisation objectives envisaged under the new Common Fishery Policy may not be adequate for Mediterranean cephalopod stocks.
Théron, A; Pointier, J P; Morand, S; Imbert-Establet, D; Borel, G
1992-04-01
Dynamics of natural populations of Schistosoma mansoni were studied during 8 consecutive years among Rattus rattus populations from 8 transmission sites of the marshy forest focus of Guadeloupe (French West Indies). The schistosome population is over-dispersed (k = 0.119) within the murine hosts and ecological factors linked to the patchy environment may be responsible for such aggregated distribution. Analysis of the spatio-temporal variations in prevalences, intensities and abundances showed limited variations of the infection during the 8 years at the level of the whole parasite population but great spatial heterogeneity at the level of local schistosome populations. Inter-populational genetic variability linked to the degree of adaptation of this human parasite to the murine host may explain differences in transmission dynamics between the local populations of S. mansoni.
Spatial and seasonal dynamics of brook trout populations inhabiting a central Appalachian watershed
Petty, J.T.; Lamothe, P.J.; Mazik, P.M.
2005-01-01
We quantified the watershed-scale spatial population dynamics of brook trout Salvelinus fontinalis in the Second Fork, a third-order tributary of Shavers Fork in eastern West Virginia. We used visual surveys, electrofishing, and mark-recapture techniques to quantify brook trout spawning intensity, population density, size structure, and demographic rates (apparent survival and immigration) throughout the watershed. Our analyses produced the following results. Spawning by brook trout was concentrated in streams with small basin areas (i.e., segments draining less than 3 km2), relatively high alkalinity (>10 mg CaCO3/L), and high amounts of instream cover. The spatial distribution of juvenile and small-adult brook trout within the watershed was relatively stable and was significantly correlated with spawning intensity. However, no such relationship was observed for large adults, which exhibited highly variable distribution patterns related to seasonally important habitat features, including instream cover, stream depth and width, and riparian canopy cover. Brook trout survival and immigration rates varied seasonally, spatially, and among size-classes. Differential survival and immigration tended to concentrate juveniles and small adults in small, alkaline streams, whereas dispersal tended to redistribute large adults at the watershed scale. Our results suggest that spatial and temporal variations in spawning, survival, and movement interact to determine the distribution, abundance, and size structure of brook trout populations at a watershed scale. These results underscore the importance of small tributaries for the persistence of brook trout in this watershed and the need to consider watershed-scale processes when designing management plans for Appalachian brook trout populations. ?? Copyright by the American Fisheries Society 2005.
Blauvelt, David G.; Sato, Tomokazu F.; Wienisch, Martin; Murthy, Venkatesh N.
2013-01-01
The acquisition of olfactory information and its early processing in mammals are modulated by brain states through sniffing behavior and neural feedback. We imaged the spatiotemporal pattern of odor-evoked activity in a population of output neurons (mitral/tufted cells, MTCs) in the olfactory bulb (OB) of head-restrained mice expressing a genetically-encoded calcium indicator. The temporal dynamics of MTC population activity were relatively simple in anesthetized animals, but were highly variable in awake animals. However, the apparently irregular activity in awake animals could be predicted well using sniff timing measured externally, or inferred through fluctuations in the global responses of MTC population even without explicit knowledge of sniff times. The overall spatial pattern of activity was conserved across states, but odor responses had a diffuse spatial component in anesthetized mice that was less prominent during wakefulness. Multi-photon microscopy indicated that MTC lateral dendrites were the likely source of spatially disperse responses in the anesthetized animal. Our data demonstrate that the temporal and spatial dynamics of MTCs can be significantly modulated by behavioral state, and that the ensemble activity of MTCs can provide information about sniff timing to downstream circuits to help decode odor responses. PMID:23543674
Genetic diversity affects the strength of population regulation in a marine fish.
Johnson, D W; Freiwald, J; Bernardi, G
2016-03-01
Variation is an essential feature of biological populations, yet much of ecological theory treats individuals as though they are identical. This simplifying assumption is often justified by the perception that variation among individuals does not have significant effects on the dynamics of whole populations. However, this perception may be skewed by a historic focus on studying single populations. A true evaluation of the extent to which among-individual variation affects the dynamics of populations requires the study of multiple populations. In this study, we examined variation in the dynamics of populations of a live-bearing, marine fish (black surfperch; Embiotoca jacksoni). In collaboration with an organization of citizen scientists (Reef Check California), we were able to examine the dynamics of eight populations that were distributed throughout approximately 700 km of coastline, a distance that encompasses much of this species' range. We hypothesized that genetic variation within a local population would be related to the intensity of competition and to the strength of population regulation. To test this hypothesis, we examined whether genetic diversity (measured by the diversity of mitochondrial DNA haplotypes) was related to the strength of population regulation. Low-diversity populations experienced strong density dependence in population growth rates and population sizes were regulated much more tightly than they were in high-diversity populations. Mechanisms that contributed to this pattern include links between genetic diversity, habitat use, and spatial crowding. On average, low-diversity populations used less of the available habitat and exhibited greater spatial clustering (and more intense competition) for a given level of density (measured at the scale of the reef). Although the populations we studied also varied with respect to exogenous characteristics (habitat complexity, densities of predators, and interspecific competitors), none of these characteristics was significantly related to the strength of population regulation. In contrast, an endogenous characteristic of the population (genetic diversity) explained 77% of the variation in the strength of population regulation (95% CI: 27-94%). Our results suggest that the genetic and phenotypic composition of populations can play a major role in their dynamics.
Spatial patterns of modern period human-caused fire occurrence in the Missouri Ozark Highlands
Jian Yang; Hong S. Healy; Stephen R. Shifley; Eric J. Gustafson
2007-01-01
The spatial pattern of forest fire locations is important in the study of the dynamics of fire disturbance. In this article we used a spatial point process modeling approach to quantitatively study the effects of land cover, topography, roads, municipalities, ownership, and population density on fire occurrence reported between 1970 and 2002 in the Missouri Ozark...
Jeffrey R. Garnas; David R. Houston; Mark J. Twery; Matthew P. Ayres; Celia Evans
2013-01-01
Spatial pattern in the distribution and abundance of organisms is an emergent property of collective rates of reproduction, survival and movement of individuals in a heterogeneous environment. The form, intensity and scale of spatial patterning can be used to test hypotheses regarding the relative importance of candidate processes to population dynamics. Using 84 plots...
HexSim - A general purpose framework for spatially-explicit, individual-based modeling
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...
Factors that significantly impact wildlife population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby contribute to the heterogeneous spatial distributions of organisms. The spatial co-occurrence of organisms, environmenta...
Dynamics and life histories of northern ungulates in changing environments
NASA Astrophysics Data System (ADS)
Hendrichsen, D. K.
2011-12-01
Regional climate and local weather conditions can profoundly influence life history parameters (growth, survival, fecundity) and population dynamics in northern ungulates (Post and Stenseth 1999, Coulson et al. 2001). The influence is both direct, for example through reduced growth or survival (Aanes et al. 2000, Tyler et al. 2008), and indirect, for example through changes in resource distribution, phenology and quality, changes which subsequently influence consumer dynamics (Post et al. 2008). By comparing and contrasting data from three spatially independent populations of ungulates, I discuss how variation in local weather parameters and vegetation growth influence spatial and temporal dynamics through changes in life history parameters and/or behavioural dynamics. The data originate from long term (11-15 years) monitoring data from three populations of ungulates in one subarctic and two high Arctic sites; semi-domesticated reindeer (Rangifer tarandus tarandus) in northern Norway, Svalbard reindeer (R. t. platyrhynchus) on Spitsbergen and muskoxen (Ovibos moschatus) in Northeast Greenland. The results show that juvenile animals can be particularly vulnerable to changes in their environment, and that this is mirrored to different degrees in the spatio-temporal dynamics of the three populations. Adverse weather conditions, acting either directly or mediated through access to and quality of vegetation, experienced by young early in life, or even by their dams during pregnancy, can lead to reduced growth, lower survival and reduced reproductive performance later in life. The influence of current climatic variation, and the predictions of how local weather conditions may change over time, differs between the three sites, resulting in potentially different responses in the three populations. Aanes R, Saether BE and Øritsland NA. 2000. Fluctuations of an introduced population of Svalbard reindeer: the effects of density dependence and climatic variation. Ecography, 23: 437-443 Coulson T, Catchpole EA, Albon SD, Morgan BJT, Pemberton JM, Clutton-Brock TH, Crawley MJ and Grenfell BT. 2001. Age, sex, density, winter weather, and population crashes in Soay sheep. Science, 292: 1528-1531 Post, E and Stenseth NC. 1999. Climatic variability, plant phenology, and northern ungulates. Ecology, 80: 1322-1339 Post E, Pedersen C, Wilmers CC and Forchhammer MC. 2008. Warming, plant phenology and the spatial dimension of trophic mismatch for large herbivores. Proc. Roy Soc. B., 275: 2005-2013 Tyler NJC, Forchhammer MC and Øritsland NA. 2008. Nonlinear effects of climate and density in the dynamics of a fluctuating population of reindeer. Ecology, 89: 1675-1686
Bonsall, Michael B; Dooley, Claire A; Kasparson, Anna; Brereton, Tom; Roy, David B; Thomas, Jeremy A
2014-01-01
Conservation of endangered species necessitates a full appreciation of the ecological processes affecting the regulation, limitation, and persistence of populations. These processes are influenced by birth, death, and dispersal events, and characterizing them requires careful accounting of both the deterministic and stochastic processes operating at both local and regional population levels. We combined ecological theory and observations on Allee effects by linking mathematical analysis and the spatial and temporal population dynamics patterns of a highly endangered butterfly, the high brown fritillary, Argynnis adippe. Our theoretical analysis showed that the role of density-dependent feedbacks in the presence of local immigration can influence the strength of Allee effects. Linking this theory to the analysis of the population data revealed strong evidence for both negative density dependence and Allee effects at the landscape or regional scale. These regional dynamics are predicted to be highly influenced by immigration. Using a Bayesian state-space approach, we characterized the local-scale births, deaths, and dispersal effects together with measurement and process uncertainty in the metapopulation. Some form of an Allee effect influenced almost three-quarters of these local populations. Our joint analysis of the deterministic and stochastic dynamics suggests that a conservation priority for this species would be to increase resource availability in currently occupied and, more importantly, in unoccupied sites.
A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS
Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...
2017-01-01
Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589
Garcia, A G; Godoy, W A C
2017-06-01
Studies of the influence of biological parameters on the spatial distribution of lepidopteran insects can provide useful information for managing agricultural pests, since the larvae of many species cause serious impacts on crops. Computational models to simulate the spatial dynamics of insect populations are increasingly used, because of their efficiency in representing insect movement. In this study, we used a cellular automata model to explore different patterns of population distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), when the values of two biological parameters that are able to influence the spatial pattern (larval viability and adult longevity) are varied. We mapped the spatial patterns observed as the parameters varied. Additionally, by using population data for S. frugiperda obtained in different hosts under laboratory conditions, we were able to describe the expected spatial patterns occurring in corn, cotton, millet, and soybean crops based on the parameters varied. The results are discussed from the perspective of insect ecology and pest management. We concluded that computational approaches can be important tools to study the relationship between the biological parameters and spatial distributions of lepidopteran insect pests.
Ellis, Alicia M
2008-01-01
1. Researchers often use the spatial distribution of insect offspring as a measure of adult oviposition preferences, and then make conclusions about the consequences of these preferences for population growth and the relationship between life-history traits (e.g. oviposition preference and offspring performance). However, several processes other than oviposition preference can generate spatial patterns of offspring density (e.g. dispersal limitations, spatially heterogeneous mortality rates). Incorrectly assuming that offspring distributions reflect oviposition preferences may therefore compromise our ability to understand the mechanisms determining population distributions and the relationship between life-history traits. 2. The purpose of this study was to perform an empirical study at the whole-system scale to examine the movement and oviposition behaviours of the eastern tree hole mosquito Ochlerotatus triseriatus (Say) and test the importance of these behaviours in determining population distribution relative to other mechanisms. 3. A mark-release-recapture experiment was performed to distinguish among the following alternative hypotheses that may explain a previously observed aggregated distribution of tree hole mosquito offspring: (H(1)) mosquitoes prefer habitats with particular vegetation characteristics and these preferences determine the distribution of their offspring; (H(2)) mosquitoes distribute their eggs randomly or evenly throughout their environment, but spatial differences in developmental success generate an aggregated pattern of larval density; (H(3)) mosquitoes randomly colonize habitats, but have limited dispersal capability causing them to distribute offspring where founder populations were established; (H(4)) wind or other environmental factors may lead to passive aggregation, or spatial heterogeneity in adult mortality (H(5)), rather than dispersal, generates clumped offspring distributions. 4. Results indicate that the distribution of tree hole mosquito larvae is determined in part by adult habitat selection (H(1)), but do not exclude additional effects from passive aggregation (H(4)), or spatial patterns in adult mortality (H(5)). 5. This research illustrates the importance of studying oviposition behaviour at the population scale to better evaluate its relative importance in determining population distribution and dynamics. Moreover, this study demonstrates the importance of linking behavioural and population dynamics for understanding evolutionary relationships among life-history traits (e.g. preference and offspring performance) and predicting when behaviour will be important in determining population phenomena.
NASA Astrophysics Data System (ADS)
Koenig, W.
2016-12-01
The ecological impacts of modern global climate change are detectable in a wide variety of phenomena ranging from shifts in species ranges to changes in community composition and human disease dynamics. Thus far, however, little attention has been given to temporal changes in environmental spatial synchrony-the coincident change in abundance or value across the landscape-or environmental variability, despite the importance of these factors as drivers of population rescue and extinction and reproductive dynamics of both animal and plant populations. We quantified spatial synchrony of widespread North American wintering birds species using Audubon Christmas Bird Counts over the past 50 years and seed set variability (mast fruiting) among trees over the past century and found that both spatial synchrony of the birds and seed set variability have significantly increased over these time periods. The first of these results was mirrored by significant increases in spatial synchrony of mean maximum air temperature across North America, primarily during the summer, while the second is consistent with the hypothesis that climate change is resulting in greater seed set variability. These findings suggest the potential for temporal changes in envioronmental synchrony and variability to be affecting a wide range of ecological phenomena by influencing the probability of population rescue and extinction and by affecting ecosystem processes that rely on the resource pulses provided by mast fruiting plants.
Coupling population dynamics with earth system models: the POPEM model.
Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J
2017-09-16
Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.
USDA-ARS?s Scientific Manuscript database
Spatial and temporal dynamics of pest populations is an important aspect of effective pest management. However, absolute sampling of some pest populations such as the ham mite, Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae), a serious pest of dry-cured ham, can be difficult. Sampling ...
Optimizing habitat location for black-tailed prairie dogs in southwestern South Dakota
John Hof; Michael Bevers; Daniel W. Uresk; Gregory L. Schenbeck
2002-01-01
A spatial optimization model was formulated and used to maximize black-tailed prairie dog populations in the Badlands National Park and the Buffalo Gap National Grassland in South Dakota. The choice variables involved the strategic placement of limited additional protected habitat. Population dynamics were captured in formulations that reflected exponential population...
NASA Astrophysics Data System (ADS)
Bellesia, Giovanni; Bales, Benjamin B.
2016-10-01
We investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been "extended" and considered as a prototype reaction-diffusion system. Our results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatial stochastic simulation methods for the study of biochemical networks in vivo where the "well-mixed" approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.
Two-photon imaging of spatially extended neuronal network dynamics with high temporal resolution.
Lillis, Kyle P; Eng, Alfred; White, John A; Mertz, Jerome
2008-07-30
We describe a simple two-photon fluorescence imaging strategy, called targeted path scanning (TPS), to monitor the dynamics of spatially extended neuronal networks with high spatiotemporal resolution. Our strategy combines the advantages of mirror-based scanning, minimized dead time, ease of implementation, and compatibility with high-resolution low-magnification objectives. To demonstrate the performance of TPS, we monitor the calcium dynamics distributed across an entire juvenile rat hippocampus (>1.5mm), at scan rates of 100 Hz, with single cell resolution and single action potential sensitivity. Our strategy for fast, efficient two-photon microscopy over spatially extended regions provides a particularly attractive solution for monitoring neuronal population activity in thick tissue, without sacrificing the signal-to-noise ratio or high spatial resolution associated with standard two-photon microscopy. Finally, we provide the code to make our technique generally available.
Sammy L. King; Terry J. Antrobus; Sarah Billups
2000-01-01
A disturbance can be defined as "any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment" (Pickett and White 1985). Vegetation dynamics are a function of the temporal and spatial patterns of the disturbance regime. Natural disturbance regimes...
Variation in predator foraging behavior changes predator-prey spatio-temporal dynamics
USDA-ARS?s Scientific Manuscript database
1. Foraging underlies the ability of all animals to acquire essential resources and, thus, provides a critical link to understanding population dynamics. A key issue is how variation in foraging behavior affects foraging efficiency and predator-prey interactions in spatially-heterogeneous environmen...
WEAKLY SYNCHRYRONIZED SUBPOPULATION DYNAMICS IN WISCONSIN FROGS AND TOADS
Spatial synchrony in population dynamics is a topic of increasing interest in basic and applied ecology. We used data from 18 years of frog and toad calling surveys conducted throughout Wisconsin to determine the level of intraspecific synchrony among survey sites, and the relat...
Five challenges for spatial epidemic models
Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter
2015-01-01
Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. PMID:25843387
NASA Astrophysics Data System (ADS)
Carlotti, F.; Eisenhauer, L.; Campbell, R.; Diaz, F.
2014-07-01
The spatio-temporal dynamics of a simulated Centropages typicus (Kröyer) population during the year 2001 at the regional scale of the northwestern Mediterranean Sea are addressed using a 3D coupled physical-biogeochemical model. The setup of the coupled biological model comprises a pelagic plankton ecosystem model and a stage-structured population model forced by the 3D velocity and temperature fields provided by an eddy-resolving regional circulation model. The population model for C. typicus (C. t. below) represents demographic processes through five groups of developmental stages, which depend on underlying individual growth and development processes and are forced by both biotic (prey and predator fields) and abiotic (temperature, advection) factors from the coupled physical-biogeochemical model. The objective is to characterize C. t. ontogenic habitats driven by physical and trophic processes. The annual dynamics are presented for two of the main oceanographic stations in the Gulf of Lions, which are representative of shelf and open sea conditions, while the spatial distributions over the whole area are presented for three dates during the year, in early and late spring and in winter. The simulated spatial patterns of C. t. developmental stages are closely related to mesoscale hydrodynamic features and circulation patterns. The seasonal and spatial distributions on the Gulf of Lions shelf depend on the seasonal interplay between the Rhône river plume, the mesoscale eddies on the shelf and the Northern Current acting as either as a dynamic barrier between the shelf and the open sea or allowing cross-shelf exchanges. In the central gyre of the northwestern Mediterranean Sea, the patchiness of plankton is tightly linked to mesoscale frontal systems, surface eddies and filaments and deep gradients. Due to its flexibility in terms of its diet, C. t. succeeds in maintaining its population in both coastal and offshore areas year round. The simulations suggest that the winte-spring food conditions are more favorable on the shelf for C. t., whereas in late summer and fall, the offshore depth-integrated food biomasses represent a larger resource for C. t., particularly when mesoscale structures and vertical discontinuities increase food patchiness. The development and reproduction of C. t. depend on the prey field within the mesoscale structures that induce a contrasting spatial distribution of successive developmental stages on a given observation date. In late fall and winter, the results of the model suggest the existence of three refuge areas where the population maintains winter generations near the coast and within the Rhone River plume, or offshore within canyons within the shelf break, or in the frontal system related to the Northern Current. The simulated spatial and temporal distributions as well as the life cycle and physiological features of C. t. are discussed in light of recent reviews on the dynamics of C. t. in the northwestern Mediterranean Sea.
The effects of spatial population dataset choice on estimates of population at risk of disease
2011-01-01
Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885
Life-History and Spatial Determinants of Somatic Growth Dynamics in Komodo Dragon Populations
Laver, Rebecca J.; Purwandana, Deni; Ariefiandy, Achmad; Imansyah, Jeri; Forsyth, David; Ciofi, Claudio; Jessop, Tim S.
2012-01-01
Somatic growth patterns represent a major component of organismal fitness and may vary among sexes and populations due to genetic and environmental processes leading to profound differences in life-history and demography. This study considered the ontogenic, sex-specific and spatial dynamics of somatic growth patterns in ten populations of the world’s largest lizard the Komodo dragon (Varanus komodoensis). The growth of 400 individual Komodo dragons was measured in a capture-mark-recapture study at ten sites on four islands in eastern Indonesia, from 2002 to 2010. Generalized Additive Mixed Models (GAMMs) and information-theoretic methods were used to examine how growth rates varied with size, age and sex, and across and within islands in relation to site-specific prey availability, lizard population density and inbreeding coefficients. Growth trajectories differed significantly with size and between sexes, indicating different energy allocation tactics and overall costs associated with reproduction. This leads to disparities in maximum body sizes and longevity. Spatial variation in growth was strongly supported by a curvilinear density-dependent growth model with highest growth rates occurring at intermediate population densities. Sex-specific trade-offs in growth underpin key differences in Komodo dragon life-history including evidence for high costs of reproduction in females. Further, inverse density-dependent growth may have profound effects on individual and population level processes that influence the demography of this species. PMID:23028983
Travelling waves and spatial hierarchies in measles epidemics
NASA Astrophysics Data System (ADS)
Grenfell, B. T.; Bjørnstad, O. N.; Kappey, J.
2001-12-01
Spatio-temporal travelling waves are striking manifestations of predator-prey and host-parasite dynamics. However, few systems are well enough documented both to detect repeated waves and to explain their interaction with spatio-temporal variations in population structure and demography. Here, we demonstrate recurrent epidemic travelling waves in an exhaustive spatio-temporal data set for measles in England and Wales. We use wavelet phase analysis, which allows for dynamical non-stationarity-a complication in interpreting spatio-temporal patterns in these and many other ecological time series. In the pre-vaccination era, conspicuous hierarchical waves of infection moved regionally from large cities to small towns; the introduction of measles vaccination restricted but did not eliminate this hierarchical contagion. A mechanistic stochastic model suggests a dynamical explanation for the waves-spread via infective `sparks' from large `core' cities to smaller `satellite' towns. Thus, the spatial hierarchy of host population structure is a prerequisite for these infection waves.
Mooij, Wolf M.; Bennetts, Robert E.; Kitchens, Wiley M.; DeAngelis, Donald L.
2002-01-01
The paper aims at exploring the viability of the Florida snail kite population under various drought regimes in its wetland habitat. The population dynamics of snail kites are strongly linked with the hydrology of the system due to the dependence of this bird species on one exclusive prey species, the apple snail, which is negatively affected by a drying out of habitat. Based on empirical evidence, it has been hypothesised that the viability of the snail kite population critically depends not only on the time interval between droughts, but also on the spatial extent of these droughts. A system wide drought is likely to result in reduced reproduction and increased mortality, whereas the birds can respond to local droughts by moving to sites where conditions are still favourable. This paper explores the implications of this hypothesis by means of a spatially-explicit individual-based model. The specific aim of the model is to study in a factorial design the dynamics of the kite population in relation to two scale parameters, the temporal interval between droughts and the spatial correlation between droughts. In the model high drought frequencies led to reduced numbers of kites. Also, habitat degradation due to prolonged periods of inundation led to lower predicted numbers of kites. Another main result was that when the spatial correlation between droughts was low, the model showed little variability in the predicted numbers of kites. But when droughts occurred mostly on a system wide level, environmental stochasticity strongly increased the stochasticity in kite numbers and in the worst case the viability of the kite population was seriously threatened.
An agent-based approach for modeling dynamics of contagious disease spread
Perez, Liliana; Dragicevic, Suzana
2009-01-01
Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403
Human seizures couple across spatial scales through travelling wave dynamics
NASA Astrophysics Data System (ADS)
Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.
2017-04-01
Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.
NASA Astrophysics Data System (ADS)
Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita
2015-06-01
In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.
Lion, Sébastien
2009-09-07
Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.
Investigation of Kibble-Zurek Quench Dynamics in a Spin-1 Ferromagnetic BEC
NASA Astrophysics Data System (ADS)
Anquez, Martin; Robbins, Bryce; Hoang, Thai; Yang, Xiaoyun; Land, Benjamin; Hamley, Christopher; Chapman, Michael
2014-05-01
We study the temporal evolution of spin populations in small spin-1 87Rb condensates following a slow quench. A ferromagnetic spin-1 BEC exhibits a second-order gapless (quantum) phase transition due to a competition between the magnetic and collisional spin interaction energies. The dynamics of slow quenches through the critical point are predicted to exhibit universal power-law scaling as a function of quench speed. In spatially extended condensates, these excitations are revealed as spatial spin domains. In small condensates, the excitations are manifest in the temporal evolution of the spin populations, illustrating a Kibble-Zurek type scaling. We will present the results of our investigation and compare them to full quantum simulations of the system.
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 population density was one of the most important parameters affecting the SNV dynamics. The results also indicated that habitat disturbance could increase hantavirus transmission likely by increasing the movement and consequently contact rates. However, the model suggested that habitat disturbance had a much stronger effect on prevalence by decreasing population density than by increasing mice movement. Therefore, overall habitat disturbance reduces SNV prevalence.
NASA Astrophysics Data System (ADS)
Li, Bing-Wei; Cao, Xiao-Zhi; Fu, Chenbo
2017-12-01
Many biological and chemical systems could be modeled by a population of oscillators coupled indirectly via a dynamical environment. Essentially, the environment by which the individual element communicates with each other is heterogeneous. Nevertheless, most of previous works considered the homogeneous case only. Here we investigated the dynamical behaviors in a population of spatially distributed chaotic oscillators immersed in a heterogeneous environment. Various dynamical synchronization states (such as oscillation death, phase synchronization, and complete synchronized oscillation) as well as their transitions were explored. In particular, we uncovered a non-traditional quorum sensing transition: increasing the population density leaded to a transition from oscillation death to synchronized oscillation at first, but further increasing the density resulted in degeneration from complete synchronization to phase synchronization or even from phase synchronization to desynchronization. The underlying mechanism of this finding was attributed to the dual roles played by the population density. What's more, by treating the environment as another component of the oscillator, the full system was then effectively equivalent to a locally coupled system. This fact allowed us to utilize the master stability functions approach to predict the occurrence of complete synchronization oscillation, which agreed with that from the direct numerical integration of the system. The potential candidates for the experimental realization of our model were also discussed.
Historical demographic dynamics underlying local adaptation in the presence of gene flow
Ribeiro, Ângela M; Lopes, Ricardo J; Bowie, Rauri C K
2012-01-01
The range of a species is the result of the relative contribution of spatial tracking of environmental requirements and adaptation to ecological conditions outside the ancestral niche. The appearance of novel habitats caused by climatic oscillation can promote range expansion and accompanying demographic growth. The demographic dynamics of populations leave a signal in \\ patterns. We modeled three competing scenarios pertaining to the circumstance of a range expansion by the Karoo Scrub-Robin into newly available habitat resulting from the increasing aridification of southern Africa. Genetic variation was contrasted with the theoretical expectations of a spatial range expansion, and compared with data of a putative adaptive trait. We infer that this bird likely colonized the arid zone, as a consequence of adaptive evolution in a small peripheral population, followed by an expansion with recurrent exchange of migrants with the ancestral populations. PMID:23170207
Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm
2017-10-03
Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.
Row, Jeffery R.; Oyler-McCance, Sara J.; Fedy, Brad C.
2016-01-01
The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and (i) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and (ii) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e. population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions.
Effects of fir sawyer beetle on spatial structure of Siberian fir stands
Vladimir L. Gavrikov; Valentina P. Vetrova
1991-01-01
Insects not only use plants for food and habitat; they also change plant populations by influencing their structure and dynamics. This influence is evidenced in the alteration of the spatial structure of a stand. The fir sawyer, Monochamus urussovi Fisch. (Coleoptera: Cerambycidae), is the most abundant xylophagous insect injuring siberian fir,...
Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...
Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana.
Berens, D G; Braun, C; González-Martínez, S C; Griebeler, E M; Nathan, R; Böhning-Gaese, K
2014-11-01
Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.
Analysis of spatial density dependence in gypsy moth mortality
Andrew Liebhold; Joseph S. Elkinton
1991-01-01
The gypsy moth is perhaps the most widely studied forest insect in the world and much of this research has focused on various aspects of population dynamics. But despite this voluminous amount of research we still lack a good understanding of which, if any, natural enemy species regulate gypsy moth populations. The classical approach to analyzing insect population...
Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai
2017-11-01
In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.
Enhancing Disaster Management: Development of a Spatial Database of Day Care Centers in the USA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, Nagendra; Tuttle, Mark A.; Bhaduri, Budhendra L.
Children under the age of five constitute around 7% of the total U.S. population and represent a segment of the population, which is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day care arrangement while their parents are away from home. Accounting for those children during emergencies is of high priority, which requires a broad understanding of the locations of such day care centers. As concentrations of at risk population, the spatial location of day care centers is critical for any type of emergency preparedness and response (EPR). However,more » until recently, the U.S. emergency preparedness and response community did not have access to a comprehensive spatial database of day care centers at the national scale. This paper describes an approach for the development of the first comprehensive spatial database of day care center locations throughout the USA utilizing a variety of data harvesting techniques to integrate information from widely disparate data sources followed by geolocating for spatial precision. In the context of disaster management, such spatially refined demographic databases hold tremendous potential for improving high resolution population distribution and dynamics models and databases.« less
Enhancing Disaster Management: Development of a Spatial Database of Day Care Centers in the USA
Singh, Nagendra; Tuttle, Mark A.; Bhaduri, Budhendra L.
2015-07-30
Children under the age of five constitute around 7% of the total U.S. population and represent a segment of the population, which is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day care arrangement while their parents are away from home. Accounting for those children during emergencies is of high priority, which requires a broad understanding of the locations of such day care centers. As concentrations of at risk population, the spatial location of day care centers is critical for any type of emergency preparedness and response (EPR). However,more » until recently, the U.S. emergency preparedness and response community did not have access to a comprehensive spatial database of day care centers at the national scale. This paper describes an approach for the development of the first comprehensive spatial database of day care center locations throughout the USA utilizing a variety of data harvesting techniques to integrate information from widely disparate data sources followed by geolocating for spatial precision. In the context of disaster management, such spatially refined demographic databases hold tremendous potential for improving high resolution population distribution and dynamics models and databases.« less
Stochastic Spatial Models in Ecology: A Statistical Physics Approach
NASA Astrophysics Data System (ADS)
Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.
2018-07-01
Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.
Stochastic Spatial Models in Ecology: A Statistical Physics Approach
NASA Astrophysics Data System (ADS)
Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.
2017-11-01
Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.
Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns.
Norred, S Elizabeth; Caveney, Patrick M; Chauhan, Gaurav; Collier, Lauren K; Collier, C Patrick; Abel, Steven M; Simpson, Michael L
2018-05-18
Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting-the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increase in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA ("spatial noise") that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. These results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.
Spatial dynamics of a population with stage-dependent diffusion
NASA Astrophysics Data System (ADS)
Azevedo, F.; Coutinho, R. M.; Kraenkel, R. A.
2015-05-01
We explore the spatial dynamics of a population whose individuals go through life stages with very different dispersal capacities. We model it through a system of partial differential equations of the reaction-diffusion kind, with nonlinear diffusion terms that may depend on population density and on the stage. This model includes a few key biological ingredients: growth and saturation, life stage structure, small population effects, and diffusion dependent on the stage. In particular, we consider that adults exhibit two distinct classes: one highly mobile and the other less mobile but with higher fecundity rate, and the development of juveniles into one or the other depends on population density. We parametrize the model with estimated parameters of an insect species, the brown planthopper. We focus on a situation akin to an invasion of the species in a new habitat and find that the front of invasion is led by the most mobile adult class. We also show that the trade-off between dispersal and fecundity leads to invasion speed attaining its maximum at an intermediate value of the diffusion coefficient of the most mobile class.
Spatial dispersal of Douglas-fir beetle populations in Colorado and Wyoming
John R. Withrow; John E. Lundquist; Jose F. Negron
2013-01-01
Bark beetles (Coleoptera: Curculionidae: Scolytinae) are mortality agents to multiple tree species throughout North America. Understanding spatiotemporal dynamics of these insects can assist management, prediction of outbreaks, and development of "real time" assessments of forest susceptibility incorporating insect population data. Here, dispersal of Douglas-...
Novotny, Josef; Hasman, Jiri
2015-01-01
This paper examines the patterns of the US and Australian immigration geography and the process of regional population diversification and the emergence of new immigrant concentrations at the regional level. It presents a new approach in the context of human migration studies, focusing on spatial relatedness between individual foreign-born groups as revealed from the analysis of their joint spatial concentrations. The approach employs a simple assumption that the more frequently the members of two population groups concentrate in the same locations the higher is the probability that these two groups can be related. Based on detailed data on the spatial distribution of foreign-born groups in US counties (2000–2010) and Australian postal areas (2006–2011) we firstly quantify the spatial relatedness between all pairs of foreign-born groups and model the aggregate patterns of US and Australian immigration systems conceptualized as the undirected networks of foreign-born groups linked by their spatial relatedness. Secondly, adopting a more dynamic perspective, we assume that immigrant groups with higher spatial relatedness to those groups already concentrated in a region are also more likely to settle in this region in future. As the ultimate goal of the paper, we examine the power of spatial relatedness measures in projecting the emergence of new immigrant concentrations in the US and Australian regions. The results corroborate that the spatial relatedness measures can serve as useful instruments in the analysis of the patterns of population structure and prediction of regional population change. More generally, this paper demonstrates that information contained in spatial patterns (relatedness in space) of population composition has yet to be fully utilized in population forecasting. PMID:25966371
Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B
2013-01-29
Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.
Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.
2013-01-01
Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737
Turelli, Michael; Barton, Nicholas H
2017-06-01
A novel strategy for controlling the spread of arboviral diseases such as dengue, Zika and chikungunya is to transform mosquito populations with virus-suppressing Wolbachia. In general, Wolbachia transinfected into mosquitoes induce fitness costs through lower viability or fecundity. These maternally inherited bacteria also produce a frequency-dependent advantage for infected females by inducing cytoplasmic incompatibility (CI), which kills the embryos produced by uninfected females mated to infected males. These competing effects, a frequency-dependent advantage and frequency-independent costs, produce bistable Wolbachia frequency dynamics. Above a threshold frequency, denoted pˆ, CI drives fitness-decreasing Wolbachia transinfections through local populations; but below pˆ, infection frequencies tend to decline to zero. If pˆ is not too high, CI also drives spatial spread once infections become established over sufficiently large areas. We illustrate how simple models provide testable predictions concerning the spatial and temporal dynamics of Wolbachia introductions, focusing on rate of spatial spread, the shape of spreading waves, and the conditions for initiating spread from local introductions. First, we consider the robustness of diffusion-based predictions to incorporating two important features of wMel-Aedes aegypti biology that may be inconsistent with the diffusion approximations, namely fast local dynamics induced by complete CI (i.e., all embryos produced from incompatible crosses die) and long-tailed, non-Gaussian dispersal. With complete CI, our numerical analyses show that long-tailed dispersal changes wave-width predictions only slightly; but it can significantly reduce wave speed relative to the diffusion prediction; it also allows smaller local introductions to initiate spatial spread. Second, we use approximations for pˆ and dispersal distances to predict the outcome of 2013 releases of wMel-infected Aedes aegypti in Cairns, Australia, Third, we describe new data from Ae. aegypti populations near Cairns, Australia that demonstrate long-distance dispersal and provide an approximate lower bound on pˆ for wMel in northeastern Australia. Finally, we apply our analyses to produce operational guidelines for efficient transformation of vector populations over large areas. We demonstrate that even very slow spatial spread, on the order of 10-20 m/month (as predicted), can produce area-wide population transformation within a few years following initial releases covering about 20-30% of the target area. Copyright © 2017 Elsevier Inc. All rights reserved.
On the preservation of cooperation in two-strategy games with nonlocal interactions.
Aydogmus, Ozgur; Zhou, Wen; Kang, Yun
2017-03-01
Nonlocal interactions such as spatial interaction are ubiquitous in nature and may alter the equilibrium in evolutionary dynamics. Models including nonlocal spatial interactions can provide a further understanding on the preservation and emergence of cooperation in evolutionary dynamics. In this paper, we consider a variety of two-strategy evolutionary spatial games with nonlocal interactions based on an integro-differential replicator equation. By defining the invasion speed and minimal traveling wave speed for the derived model, we study the effects of the payoffs, the selection pressure and the spatial parameter on the preservation of cooperation. One of our most interesting findings is that, for the Prisoners Dilemma games in which the defection is the only evolutionary stable strategy for unstructured populations, analyses on its asymptotic speed of propagation suggest that, in contrast with spatially homogeneous games, the cooperators can invade the habitat under proper conditions. Other two-strategy evolutionary spatial games are also explored. Both our theoretical and numerical studies show that the nonlocal spatial interaction favors diversity in strategies in a population and is able to preserve cooperation in a competing environment. A real data application in a virus mutation study echoes our theoretical observations. In addition, we compare the results of our model to the partial differential equation approach to demonstrate the importance of including non-local interaction component in evolutionary game models. Copyright © 2016 Elsevier Inc. All rights reserved.
Spatial capture-recapture models allowing Markovian transience or dispersal
Royle, J. Andrew; Fuller, Angela K.; Sutherland, Chris
2016-01-01
Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.
Barbu, Corentin; Dumonteil, Eric; Gourbière, Sébastien
2011-01-01
Background Chagas disease is a major neglected tropical disease with deep socio-economical effects throughout Central and South America. Vector control programs have consistently reduced domestic populations of triatomine vectors, but non-domiciliated vectors still have to be controlled efficiently. Designing control strategies targeting these vectors is challenging, as it requires a quantitative description of the spatio-temporal dynamics of village infestation, which can only be gained from combinations of extensive field studies and spatial population dynamic modelling. Methodology/Principal Findings A spatially explicit population dynamic model was combined with a two-year field study of T. dimidiata infestation dynamics in the village of Teya, Mexico. The parameterized model fitted and predicted accurately both intra-annual variation and the spatial gradient in vector abundance. Five different control strategies were then applied in concentric rings to mimic spatial design targeting the periphery of the village, where vectors were most abundant. Indoor insecticide spraying and insect screens reduced vector abundance by up to 80% (when applied to the whole village), and half of this effect was obtained when control was applied only to the 33% of households closest to the village periphery. Peri-domicile cleaning was able to eliminate up to 60% of the vectors, but at the periphery of the village it has a low effect, as it is ineffective against sylvatic insects. The use of lethal traps and the management of house attractiveness provided similar levels of control. However this required either house attractiveness to be null, or ≥5 lethal traps, at least as attractive as houses, to be installed in each household. Conclusion/Significance Insecticide and insect screens used in houses at the periphery of the village can contribute to reduce house infestation in more central untreated zones. However, this beneficial effect remains insufficient to allow for a unique spatially targeted strategy to offer protection to all households. Most efficiently, control should combine the use of insect screens in outer zones to reduce infestation by both sylvatic and peri-domiciliated vectors, and cleaning of peri-domicile in the centre of the village where sylvatic vectors are absent. The design of such spatially mixed strategies of control offers a promising avenue to reduce the economic cost associated with the control of non-domiciliated vectors. PMID:21610862
Spontaneous emergence of cataclysmic networks in spatially extended systems
NASA Astrophysics Data System (ADS)
Manrubia, Susanna C.; Poyatos, Juan F.; Pérez-Mercader, Juan
2002-11-01
A system of interacting chemical species able to catalyse each others' production is studied. We consider a two-dimensional surface where single molecules attach, diffuse, catalytically interact, and decay. The population of species molecules and the network of interactions among them are dynamical entities. After a short transient time, robust catalytic cycles emerge and a "stationary" state of high diversity and large population numbers settles down. Population dynamics and physical space select among possible graphs of catalytic interactions. The organization of the system is robust: parasitic invaders are short-lived, their populations are kept at low levels, and are unable to sweep away the emerging catalytic cycles.
Adams, Helen; Adger, W Neil; Ahmad, Sate; Ahmed, Ali; Begum, Dilruba; Lázár, Attila N; Matthews, Zoe; Rahman, Mohammed Mofizur; Streatfield, Peter Kim
2016-11-08
Populations in resource dependent economies gain well-being from the natural environment, in highly spatially and temporally variable patterns. To collect information on this, we designed and implemented a 1586-household quantitative survey in the southwest coastal zone of Bangladesh. Data were collected on material, subjective and health dimensions of well-being in the context of natural resource use, particularly agriculture, aquaculture, mangroves and fisheries. The questionnaire included questions on factors that mediate poverty outcomes: mobility and remittances; loans and micro-credit; environmental perceptions; shocks; and women's empowerment. The data are stratified by social-ecological system to take into account spatial dynamics and the survey was repeated with the same respondents three times within a year to incorporate seasonal dynamics. The dataset includes blood pressure measurements and height and weight of men, women and children. In addition, the household listing includes basic data on livelihoods and income for approximately 10,000 households. The dataset facilitates interdisciplinary research on spatial and temporal dynamics of well-being in the context of natural resource dependence in low income countries.
Adams, Helen; Adger, W. Neil; Ahmad, Sate; Ahmed, Ali; Begum, Dilruba; Lázár, Attila N.; Matthews, Zoe; Rahman, Mohammed Mofizur; Streatfield, Peter Kim
2016-01-01
Populations in resource dependent economies gain well-being from the natural environment, in highly spatially and temporally variable patterns. To collect information on this, we designed and implemented a 1586-household quantitative survey in the southwest coastal zone of Bangladesh. Data were collected on material, subjective and health dimensions of well-being in the context of natural resource use, particularly agriculture, aquaculture, mangroves and fisheries. The questionnaire included questions on factors that mediate poverty outcomes: mobility and remittances; loans and micro-credit; environmental perceptions; shocks; and women’s empowerment. The data are stratified by social-ecological system to take into account spatial dynamics and the survey was repeated with the same respondents three times within a year to incorporate seasonal dynamics. The dataset includes blood pressure measurements and height and weight of men, women and children. In addition, the household listing includes basic data on livelihoods and income for approximately 10,000 households. The dataset facilitates interdisciplinary research on spatial and temporal dynamics of well-being in the context of natural resource dependence in low income countries. PMID:27824340
Synchronous population dynamics in California butterflies explained by climatic forcing
Shapiro, Arthur M.
2017-01-01
A long-standing challenge for population biology has been to understand why some species are characterized by populations that fluctuate in size independently, while populations of other species fluctuate synchronously across space. The effects of climatic variation and dispersal have been invoked to explain synchronous population dynamics, however an understanding of the relative influence of these drivers in natural populations is lacking. Here we compare support for dispersal- versus climate-driven models of interspecific variation in synchrony using 27 years of observations of 65 butterfly species at 10 sites spanning 2750 m of elevation in Northern California. The degree of spatial synchrony exhibited by each butterfly species was used as a response in a unique approach that allowed us to investigate whether interspecific variation in response to climate or dispersal propensity was most predictive of interspecific variation in synchrony. We report that variation in sensitivity to climate explained 50% of interspecific variation in synchrony, whereas variation in dispersal propensity explained 23%. Sensitivity to the El Niño Southern Oscillation, a primary driver of regional climate, was the best predictor of synchrony. Combining sensitivity to climate and dispersal propensity into a single model did not greatly increase model performance, confirming the primacy of climatic sensitivity for driving spatial synchrony in butterflies. Finally, we uncovered a relationship between spatial synchrony and population decline that is consistent with theory, but small in magnitude, which suggests that the degree to which populations fluctuate in synchrony is of limited use for understanding the ongoing decline of the Northern California butterfly fauna. PMID:28791146
Jones, B W; Maruyama, A; Ouverney, C C; Nishiguchi, M K
2007-08-01
Relatively little is known about large-scale spatial and temporal fluctuations in bacterioplankton, especially within the bacterial families. In general, however, a number of abiotic factors (namely, nutrients and temperature) appear to influence distribution. Community dynamics within the Vibrionaceae are of particular interest to biologists because this family contains a number of important pathogenic, commensal, and mutualist species. Of special interest to this study is the mutualism between sepiolid squids and Vibrio fischeri and Vibrio logei, where host squids seed surrounding waters daily with their bacterial partners. This study seeks to examine the spatial and temporal distribution of the Vibrionaceae with respect to V. fischeri and V. logei in Hawaii, southeastern Australia, and southern France sampling sites. In particular, we examine how the presence of sepiolid squid hosts influences community population structure within the Vibrionaceae. We found that abiotic (temperature) and biotic (host distribution) factors both influence population dynamics. In Hawaii, three sites within squid host habitat contained communities of Vibrionaceae with higher proportions of V. fischeri. In Australia, V. fischeri numbers at host collection sites were greater than other populations; however, there were no spatial or temporal patterns seen at other sample sites. In France, host presence did not appear to influence Vibrio communities, although sampled populations were significantly greater in the winter than summer sampling periods. Results of this study demonstrate the importance of understanding how both abiotic and biotic factors interact to influence bacterial community structure within the Vibrionaceae.
Schroeder, Natalia M; Matteucci, Silvia D; Moreno, Pablo G; Gregorio, Pablo; Ovejero, Ramiro; Taraborelli, Paula; Carmanchahi, Pablo D
2014-01-01
Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability, a difficult task to achieve for large herbivores at ecologically meaningful scales. Co-occurrence patterns can be used to infer mechanisms of community organization (such as biotic interactions), although it has been traditionally applied to binary presence/absence data. Here, we combine density surface and null models of abundance data as a novel approach to analyze the spatial and seasonal dynamics of abundance and distribution of guanacos (Lama guanicoe) and domestic herbivores in northern Patagonia, in order to visually and analytically compare the dispersion and co-occurrence pattern of ungulates. We found a marked seasonal pattern in abundance and spatial distribution of L. guanicoe. The guanaco population reached its maximum annual size and spatial dispersion in spring-summer, decreasing up to 6.5 times in size and occupying few sites of the study area in fall-winter. These results are evidence of the seasonal migration process of guanaco populations, an increasingly rare event for terrestrial mammals worldwide. The maximum number of guanacos estimated for spring (25,951) is higher than the total population size (10,000) 20 years ago, probably due to both counting methodology and population growth. Livestock were mostly distributed near human settlements, as expected by the sedentary management practiced by local people. Herbivore distribution was non-random; i.e., guanaco and livestock abundances co-varied negatively in all seasons, more than expected by chance. Segregation degree of guanaco and small-livestock (goats and sheep) was comparatively stronger than that of guanaco and large-livestock, suggesting a competition mechanism between ecologically similar herbivores, although various environmental factors could also contribute to habitat segregation. The new and compelling combination of methods used here is highly useful for researchers who conduct counts of animals to simultaneously estimate population sizes, distributions, assess temporal trends and characterize multi-species spatial interactions.
Changes in population and agricultural land in conterminous United States counties, 1790 to 1997
Waisanen, Pamela J.; Bliss, Norman B.
2002-01-01
We have developed a data set of changes in population and agricultural land for the conterminous United States at the county level, resulting in more spatial detail than in previously available compilations. The purpose was to provide data on the timing of land conversion as an input to dynamic models of the carbon cycle, although a wide variety of applications exist for the physical, biological, and social sciences. The spatial data represent the appropriate county boundaries for each census year between 1790 and 1997, and the census attributes are attached to the appropriate spatial region. The resulting time series and maps show the history of population (1790-1990) and the history of agricultural development (1850-1997). The patterns of agricultural development reflect the influences of climate, soil productivity, increases in population size, variations in the general economy, and technological changes in the energy, transportation, and agricultural sectors.
NASA Astrophysics Data System (ADS)
Xiao, X.; Dong, J.; Zhang, G.; Xin, F.; Li, X.
2017-12-01
Paddy rice croplands account for more than 12% of the global cropland areas, and provide food to feed more than 50% of the world population. Spatial patterns and temporal dynamics of paddy rice croplands have changed remarkably in the past decades, driven by growing human population and their changing diet structure, land use (e.g., urbanization, industrialization), climate, markets, and technologies. In this presentation, we will provide a comprehensive review of our current knowledge on (1) the spatial patterns and temporal dynamics of paddy rice croplands from agricultural statistics data and remote sensing approaches; (2) major driving factors for the observed changes in paddy rice areas, including social, economic, climate, land use, markets, crop breeding technology, and farming technology; and (3) major impacts on atmospheric methane concentration, land surface temperature, water resources and use, and so on. We will highlight the results from a few case studies in China and monsoon Asia. We will also call for a global synthesis analysis of paddy rice agriculture, and invite researchers to join the effort to write and edit a book that provides comprehensive and updated knowledge on paddy rice agriculture.
Five challenges for spatial epidemic models.
Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter
2015-03-01
Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
Chung, Mi Yoon; Nason, John D; Chung, Myong Gi
2007-07-01
Spatial genetic structure within plant populations is influenced by variation in demographic processes through space and time, including a population's successional status. To determine how demographic structure and fine-scale genetic structure (FSGS) change with stages in a population's successional history, we studied Hemerocallis thunbergii (Liliaceae), a nocturnal flowering and hawkmoth-pollinated herbaceous perennial with rapid population turnover dynamics. We examined nine populations assigned to three successive stages of population succession: expansion, maturation, and senescence. We developed stage-specific expectations for within-population demographic and genetic structure, and then for each population quantified the spatial aggregation of individuals and genotypes using spatial autocorrelation methods (nonaccumulative O-ring and kinship statistics, respectively), and at the landscape level measured inbreeding and genetic structure using Wright's F-statistics. Analyses using the O-ring statistic revealed significant aggregation of individuals at short spatial scales in expanding and senescing populations, in particular, which may reflect restricted seed dispersal around maternal individuals combined with relatively low local population densities at these stages. Significant FSGS was found for three of four expanding, no mature, and only one senescing population, a pattern generally consistent with expectations of successional processes. Although allozyme genetic diversity was high within populations (mean %P = 78.9 and H(E) = 0.281), landscape-level differentiation among sites was also high (F(ST) = 0.166) and all populations exhibited a significant deficit of heterozygotes relative to Hardy-Weinberg expectations (range F = 0.201-0.424, mean F(IS) = 0.321). Within populations, F was not correlated with the degree of FSGS, thus suggesting inbreeding due primarily to selfing as opposed to mating among close relatives in spatially structured populations. Our results demonstrate considerable variation in the spatial distribution of individuals and patterns and magnitude of FSGS in H. thunbergii populations across the landscape. This variation is generally consistent with succession-stage-specific differences in ecological processes operating within these populations.
Modeling the spatial and temporal dynamics of isolated emerald ash borer populations
Nathan W. Siegert; Andrew M. Liebhold; Deborah G. McCullough
2008-01-01
The ability to predict the distance and rate of emerald ash borer (EAB) spread in outlier populations is needed to continue development of effective management strategies for improved EAB control. We have developed a coupled map lattice model to estimate the spread and dispersal of isolated emerald ash borer populations. This model creates an artificial environment in...
Miranda H. Mockrin; Robert F. Rockwell; Kent H. Redford; Nicholas S. Keuler
2011-01-01
Understanding the spatial dimensions of hunting and prey population dynamics is important in order to estimate the sustainability of hunting in tropical forests. We investigated how hunting offtake of vertebrates differed in mixed forest and monodominant forest (composed of Gilbertiodendron dewevrei) and over different spatial extents within the hunting catchment...
Spatial model for transmission of mosquito-borne diseases
NASA Astrophysics Data System (ADS)
Kon, Cynthia Mui Lian; Labadin, Jane
2015-05-01
In this paper, a generic model which takes into account spatial heterogeneity for the dynamics of mosquito-borne diseases is proposed. The dissemination of the disease is described by a system of reaction-diffusion partial differential equations. Host human and vector mosquito populations are divided into susceptible and infectious classes. Diffusion is considered to occur in all classes of both populations. Susceptible humans are infected when bitten by infectious mosquitoes. Susceptible mosquitoes bite infectious humans and become infected. The biting rate of mosquitoes is considered to be density dependent on the total human population in different locations. The system is solved numerically and results are shown.
Macroparasite dynamics of migratory host populations.
Peacock, Stephanie J; Bouhours, Juliette; Lewis, Mark A; Molnár, Péter K
2018-03-01
Spatial variability in host density is a key factor affecting disease dynamics of wildlife, and yet there are few spatially explicit models of host-macroparasite dynamics. This limits our understanding of parasitism in migratory hosts, whose densities change considerably in both space and time. In this paper, we develop a model for host-macroparasite dynamics that considers the directional movement of host populations and their associated parasites. We include spatiotemporal changes in the mean and variance in parasite burden per host, as well as parasite-mediated host mortality and parasite-mediated migratory ability. Reduced migratory ability with increasing parasitism results in heavily infested hosts halting their migration, and higher parasite burdens in stationary hosts than in moving hosts. Simulations reveal the potential for positive feedbacks between parasite-reduced migratory ability and increasing parasite burdens at infection hotspots, such as stopover sites, that may lead to parasite-induced migratory stalling. This framework could help understand how global change might influence wildlife disease via changes to migratory patterns and parasite demographic rates. Copyright © 2018 Elsevier Inc. All rights reserved.
Disease-emergence dynamics and control in a socially-structured wildlife species
NASA Astrophysics Data System (ADS)
Pepin, Kim M.; Vercauteren, Kurt C.
2016-04-01
Once a pathogen is introduced in a population, key factors governing rate of spread include contact structure, supply of susceptible individuals and pathogen life-history. We examined the interplay of these factors on emergence dynamics and efficacy of disease prevention and response. We contrasted transmission dynamics of livestock viruses with different life-histories in hypothetical populations of feral swine with different contact structures (homogenous, metapopulation, spatial and network). Persistence probability was near 0 for the FMDV-like case under a wide range of parameter values and contact structures, while persistence was probable for the CSFV-like case. There were no sets of conditions where the FMDV-like pathogen persisted in every stochastic simulation. Even when population growth rates were up to 300% annually, the FMDV-like pathogen persisted in <25% of simulations regardless of transmission probabilities and contact structure. For networks and spatial contact structure, persistence probability of the FMDV-like pathogen was always <10%. Because of its low persistence probability, even very early response to the FMDV-like pathogen in feral swine was unwarranted while response to the CSFV-like pathogen was generally effective. When pre-emergence culling of feral swine caused population declines, it was effective at decreasing outbreak size of both diseases by ≥80%.
The phenology of space: Spatial aspects of bison density dependence in Yellowstone National Park
Taper, M.L.; Meagher, M.; Jerde, C.L.
2000-01-01
The Yellowstone bison represent the only bison population in the United States that survived in the wild the near-extermination of the late 1800's. This paper capitalizes on a unique opportunity provided by the record of the bison population of Yellowstone National Park (YNP). This population has been intensely monitored for almost four decades. The analysis of long-term spatio-temporal data from 1970-1997 supports the following conclusions. 1) Even though the Yellowstone bison herd exhibits an extended period of what appears to be linear growth, this pattern can be explained with classical density dependent dynamics if one realizes that perhaps the primary response of the herd to increased density is range expansion. 2) Several spatial aspects of social behavior in the YNP bison may be behavioral adaptations by the bison to environmental changes. These behavioral strategies may buffer, temporarily at least, bison population dynamics from the immediate repercussions of possible environmental stress and habitat deterioration. 3) Bison ecological carrying capacity for YNP is on the order of 2800 to 3200 animals. 4) There do appear to be indications of changes in the bison dynamics that are associated with increasing use of sections of the interior road system in winter. 5) The possibility of habitat degradation is indicated.
Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics.
Xia, Yingcun; Bjørnstad, Ottar N; Grenfell, Bryan T
2004-08-01
Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer-resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible-infected-recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.
Lagrue, Clément; Poulin, Robert; Cohen, Joel E.
2015-01-01
How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor’s law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution. PMID:25550506
Lagrue, Clément; Poulin, Robert; Cohen, Joel E
2015-02-10
How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor's law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution.
Is the Voter Model a Model for Voters?
NASA Astrophysics Data System (ADS)
Fernández-Gracia, Juan; Suchecki, Krzysztof; Ramasco, José J.; San Miguel, Maxi; Eguíluz, Víctor M.
2014-04-01
The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anisotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of U.S. presidential elections as the stationary vote-share fluctuations across counties and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when the geographical space is coarse grained at different scales—from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations.
A Malthusian curb on spatial structure in microorganism populations.
Martin, A P
2004-10-07
That all organisms are born in the company of a parent but die alone is a fundamental biological asymmetry. It has been suggested that this provides a deep-rooted source of spatial pattern formation for microorganisms even at the scale of the population. Such a theory, however, neglects the strong influence in nature of the limited and spatially variable availability of food. The tendency, first recognized by Thomas Malthus in the 18th century, of a population to out-strip its food resources will eventually lead, through local starvation, to the suppression of a heterogeneity growing within a population. Using a generic model it is demonstrated that including local food limitation of breeding strongly dampens spatial structure otherwise resulting from birth and death. The extent of this damping is shown to be a function of the strength of the coupling between organisms and their food and of the total abundance of organic material. Moreover, this work provides an example of a density-dependent process acting to diminish spatial structure rather than to create it and highlights the rich variety of behaviour that is missed by continuum models which fail to represent such local dynamics.
A dynamic landscape model for fish in the Everglades and its application to restoration
Gaff, H.D.; DeAngelis, D.L.; Gross, L.J.; Salinas, R.; Shorrosh, M.
2000-01-01
A model (ALFISH) for fish functional groups in freshwater marshes of the greater Everglades area of southern Florida has been developed. Its main objective is to assess the spatial pattern of fish densities through time across freshwater marshes. This model has the capability of providing a dynamic measure of the spatially-explicit food resources available to wading birds. ALFISH simulates two functional groups, large and small fish, where the larger ones can prey on the small fish type. Both functional groups are size-structured. The marsh landscape is modeled as 500×500 m spatial cells on a grid across southern Florida. A hydrology model predicts water levels in the spatial cells on 5-day time steps. Fish populations spread across the marsh during flooded conditions and either retreat into refugia (alligator ponds), move to other spatial cells, or die if their cell dries out. ALFISH has been applied to the evaluation of alternative water regulation scenarios under the Central and South Florida Comprehensive Project Review Study. The objective of this Review Study is to compare alternative methods for restoring historical ecological conditions in southern Florida. ALFISH has provided information on which plans are most are likely to increase fish biomass and its availability to wading bird populations.
Ojanen, Sami P; Nieminen, Marko; Meyke, Evgeniy; Pöyry, Juha; Hanski, Ilkka
2013-10-01
Long-term observational studies conducted at large (regional) spatial scales contribute to better understanding of landscape effects on population and evolutionary dynamics, including the conditions that affect long-term viability of species, but large-scale studies are expensive and logistically challenging to keep running for a long time. Here, we describe the long-term metapopulation study of the Glanville fritillary butterfly (Melitaea cinxia) that has been conducted since 1991 in a large network of 4000 habitat patches (dry meadows) within a study area of 50 by 70 km in the Åland Islands in Finland. We explain how the landscape structure has been described, including definition, delimitation, and mapping of the habitat patches; methods of field survey, including the logistics, cost, and reliability of the survey; and data management using the EarthCape biodiversity platform. We describe the long-term metapopulation dynamics of the Glanville fritillary based on the survey. There has been no long-term change in the overall size of the metapopulation, but the level of spatial synchrony and hence the amplitude of fluctuations in year-to-year metapopulation dynamics have increased over the years, possibly due to increasing frequency of exceptional weather conditions. We discuss the added value of large-scale and long-term population studies, but also emphasize the need to integrate more targeted experimental studies in the context of long-term observational studies. For instance, in the case of the Glanville fritillary project, the long-term study has produced an opportunity to sample individuals for experiments from local populations with a known demographic history. These studies have demonstrated striking differences in dispersal rate and other life-history traits of individuals from newly established local populations (the offspring of colonizers) versus individuals from old, established local populations. The long-term observational study has stimulated the development of metapopulation models and provided an opportunity to test model predictions. This combination of empirical studies and modeling has facilitated the study of key phenomena in spatial dynamics, such as extinction threshold and extinction debt.
Ojanen, Sami P; Nieminen, Marko; Meyke, Evgeniy; Pöyry, Juha; Hanski, Ilkka
2013-01-01
Long-term observational studies conducted at large (regional) spatial scales contribute to better understanding of landscape effects on population and evolutionary dynamics, including the conditions that affect long-term viability of species, but large-scale studies are expensive and logistically challenging to keep running for a long time. Here, we describe the long-term metapopulation study of the Glanville fritillary butterfly (Melitaea cinxia) that has been conducted since 1991 in a large network of 4000 habitat patches (dry meadows) within a study area of 50 by 70 km in the Åland Islands in Finland. We explain how the landscape structure has been described, including definition, delimitation, and mapping of the habitat patches; methods of field survey, including the logistics, cost, and reliability of the survey; and data management using the EarthCape biodiversity platform. We describe the long-term metapopulation dynamics of the Glanville fritillary based on the survey. There has been no long-term change in the overall size of the metapopulation, but the level of spatial synchrony and hence the amplitude of fluctuations in year-to-year metapopulation dynamics have increased over the years, possibly due to increasing frequency of exceptional weather conditions. We discuss the added value of large-scale and long-term population studies, but also emphasize the need to integrate more targeted experimental studies in the context of long-term observational studies. For instance, in the case of the Glanville fritillary project, the long-term study has produced an opportunity to sample individuals for experiments from local populations with a known demographic history. These studies have demonstrated striking differences in dispersal rate and other life-history traits of individuals from newly established local populations (the offspring of colonizers) versus individuals from old, established local populations. The long-term observational study has stimulated the development of metapopulation models and provided an opportunity to test model predictions. This combination of empirical studies and modeling has facilitated the study of key phenomena in spatial dynamics, such as extinction threshold and extinction debt. PMID:24198935
NASA Astrophysics Data System (ADS)
Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.
2012-12-01
The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.
Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline.
Bromaghin, Jeffrey F; Mcdonald, Trent L; Stirling, Ian; Derocher, Andrew E; Richardson, Evan S; Regehr, Eric V; Douglas, David C; Durner, George M; Atwood, Todd; Amstrup, Steven C
2015-04-01
In the southern Beaufort Sea of the United States and Canada, prior investigations have linked declines in summer sea ice to reduced physical condition, growth, and survival of polar bears (Ursus maritimus). Combined with projections of population decline due to continued climate warming and the ensuing loss of sea ice habitat, those findings contributed to the 2008 decision to list the species as threatened under the U.S. Endangered Species Act. Here, we used mark-recapture models to investigate the population dynamics of polar bears in the southern Beaufort Sea from 2001 to 2010, years during which the spatial and temporal extent of summer sea ice generally declined. Low survival from 2004 through 2006 led to a 25-50% decline in abundance. We hypothesize that low survival during this period resulted from (1) unfavorable ice conditions that limited access to prey during multiple seasons; and possibly, (2) low prey abundance. For reasons that are not clear, survival of adults and cubs began to improve in 2007 and abundance was comparatively stable from 2008 to 2010, with ~900 bears in 2010 (90% CI 606-1212). However, survival of subadult bears declined throughout the entire period. Reduced spatial and temporal availability of sea ice is expected to increasingly force population dynamics of polar bears as the climate continues to warm. However, in the short term, our findings suggest that factors other than sea ice can influence survival. A refined understanding of the ecological mechanisms underlying polar bear population dynamics is necessary to improve projections of their future status and facilitate development of management strategies.
Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns
Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav; ...
2018-04-24
Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less
Macromolecular Crowding Induces Spatial Correlations That Control Gene Expression Bursting Patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Norred, Sarah Elizabeth; Caveney, Patrick M.; Chauhan, Gaurav
Recent superresolution microscopy studies in E. coli demonstrate that the cytoplasm has highly variable local concentrations where macromolecular crowding plays a central role in establishing membrane-less compartmentalization. This spatial inhomogeneity significantly influences molecular transport and association processes central to gene expression. Yet, little is known about how macromolecular crowding influences gene expression bursting—the episodic process where mRNA and proteins are produced in bursts. Here, we simultaneously measured mRNA and protein reporters in cell-free systems, showing that macromolecular crowding decoupled the well-known relationship between fluctuations in the protein population (noise) and mRNA population statistics. Crowded environments led to a 10-fold increasemore » in protein noise even though there were only modest changes in the mRNA population and fluctuations. Instead, cell-like macromolecular crowding created an inhomogeneous spatial distribution of mRNA (“spatial noise”) that led to large variability in the protein production burst size. As a result, the mRNA spatial noise created large temporal fluctuations in the protein population. Furthermore, these results highlight the interplay between macromolecular crowding, spatial inhomogeneities, and the resulting dynamics of gene expression, and provide insights into using these organizational principles in both cell-based and cell-free synthetic biology.« less
Robinson, Stacie J.; Samuel, Michael D.; Lopez, Davin L.; Shelton, Paul
2012-01-01
One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.
Silva, Nuno Miguel; Rio, Jeremy; Currat, Mathias
2017-12-15
Recent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples. We first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes. Here, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.
Host-plant relationships and comparative ecology of conifer - feeding budworms (Choristoneura spp.)
V. G. Nealis
2003-01-01
North American budworms are eruptive insect species that form intimate ecological relationships with their host trees. Population data for the eastern spruce budworm and jack pine budworm implicate natural enemies as primary determinants of population collapses. Yet the dynamics of these two species display markedly different temporal and spatial characteristics. One...
Expanded home ranges in a peripheral population: Space use by endangered Mt. Graham red squirrels
John L. Koprowski; Sarah R. B. King; Melissa J. Merrick
2008-01-01
Peripheral populations are often of increased conservation value; however, knowledge of the ecological and evolutionary consequences of a peripheral location is poor. Spatial dynamics are often interpreted as strategies to maximize access to fitness-limiting resources. Red squirrels Tamiasciurus hudsonicus are territorial in western portions of their...
Evolutionary dynamics on graphs
NASA Astrophysics Data System (ADS)
Lieberman, Erez; Hauert, Christoph; Nowak, Martin A.
2005-01-01
Evolutionary dynamics have been traditionally studied in the context of homogeneous or spatially extended populations. Here we generalize population structure by arranging individuals on a graph. Each vertex represents an individual. The weighted edges denote reproductive rates which govern how often individuals place offspring into adjacent vertices. The homogeneous population, described by the Moran process, is the special case of a fully connected graph with evenly weighted edges. Spatial structures are described by graphs where vertices are connected with their nearest neighbours. We also explore evolution on random and scale-free networks. We determine the fixation probability of mutants, and characterize those graphs for which fixation behaviour is identical to that of a homogeneous population. Furthermore, some graphs act as suppressors and others as amplifiers of selection. It is even possible to find graphs that guarantee the fixation of any advantageous mutant. We also study frequency-dependent selection and show that the outcome of evolutionary games can depend entirely on the structure of the underlying graph. Evolutionary graph theory has many fascinating applications ranging from ecology to multi-cellular organization and economics.
Biogeography of the Sulfolobus islandicus pan-genome
Reno, Michael L.; Held, Nicole L.; Fields, Christopher J.; Burke, Patricia V.; Whitaker, Rachel J.
2009-01-01
Variation in gene content has been hypothesized to be the primary mode of adaptive evolution in microorganisms; however, very little is known about the spatial and temporal distribution of variable genes. Through population-scale comparative genomics of 7 Sulfolobus islandicus genomes from 3 locations, we demonstrate the biogeographical structure of the pan-genome of this species, with no evidence of gene flow between geographically isolated populations. The evolutionary independence of each population allowed us to assess genome dynamics over very recent evolutionary time, beginning ≈910,000 years ago. On this time scale, genome variation largely consists of recent strain-specific integration of mobile elements. Localized sectors of parallel gene loss are identified; however, the balance between the gain and loss of genetic material suggests that S. islandicus genomes acquire material slowly over time, primarily from closely related Sulfolobus species. Examination of the genome dynamics through population genomics in S. islandicus exposes the process of allopatric speciation in thermophilic Archaea and brings us closer to a generalized framework for understanding microbial genome evolution in a spatial context. PMID:19435847
Tompkins, Adrian M; Ermert, Volker
2013-02-18
The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.
2013-01-01
Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192
Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics
Chuang, Ting-Wu; Henebry, Geoffrey M.; Kimball, John S.; VanRoekel-Patton, Denise L.; Hildreth, Michael B.; Wimberly, Michael C.
2012-01-01
Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems. PMID:23049143
Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik
2018-04-17
Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.
Spatially structured superinfection and the evolution of disease virulence.
Caraco, Thomas; Glavanakov, Stephan; Li, Shengua; Maniatty, William; Szymanski, Boleslaw K
2006-06-01
When pathogen strains differing in virulence compete for hosts, spatial structuring of disease transmission can govern both evolved levels of virulence and patterns in strain coexistence. We develop a spatially detailed model of superinfection, a form of contest competition between pathogen strains; the probability of superinfection depends explicitly on the difference in levels of virulence. We apply methods of adaptive dynamics to address the interplay of spatial dynamics and evolution. The mean-field approximation predicts evolution to criticality; any small increase in virulence capable of dynamical persistence is favored. Both pair approximation and simulation of the detailed model indicate that spatial structure constrains disease virulence. Increased spatial clustering reduces the maximal virulence capable of single-strain persistence and, more importantly, reduces the convergent-stable virulence level under strain competition. The spatially detailed model predicts that increasing the probability of superinfection, for given difference in virulence, increases the likelihood of between-strain coexistence. When strains differing in virulence can coexist ecologically, our results may suggest policies for managing diseases with localized transmission. Comparing equilibrium densities from the pair approximation, we find that introducing a more virulent strain into a host population infected by a less virulent strain can sometimes reduce total host mortality and increase global host density.
Rastislav Jakus; Wojciech Grodzki; Marek Jezik; Marcin Jachym
2003-01-01
The spread of bark beetle outbreaks in the Tatra Mountains was explored by using both terrestrial and remote sensing techniques. Both approaches have proven to be useful for studying spatial patterns of bark beetle population dynamics. The terrestrial methods were applied on existing forestry databases. Vegetation change analysis (image differentiation), digital...
Kyle J. Haynes; Andrew M. Liebhold; Ottar N. Bjørnstad; Andrew J. Allstadt; Randall S. Morin
2018-01-01
Evaluating the causes of spatial synchrony in population dynamics in nature is notoriously difficult due to a lack of data and appropriate statistical methods. Here, we use a recently developed method, a multivariate extension of the local indicators of spatial autocorrelation statistic, to map geographic variation in the synchrony of gypsy moth outbreaks. Regression...
Patrick M.A. James; Barry Cooke; Bryan M.T. Brunet; Lisa M. Lumley; Felix A.H. Sperling; Marie-Josee Fortin; Vanessa S. Quinn; Brian R. Sturtevant
2015-01-01
Dispersal determines the flux of individuals, energy and information and is therefore a key determinant of ecological and evolutionary dynamics. Yet, it remains difficult to quantify its importance relative to other factors. This is particularly true in cyclic populations in which demography, drift and dispersal contribute to spatio-temporal variability in genetic...
What tree-ring reconstruction tells us about conifer defoliator outbreaks
Ann M. Lynch
2012-01-01
Our ability to understand the dynamics of forest insect outbreaks is limited by the lack of long-term data describing the temporal and spatial trends of outbreaks, the size and long life span of host plants, and the impracticability of manipulative experiments at relevant temporal and spatial scales. Population responses can be studied across varying site and stand...
Accounting for system dynamics in reserve design.
Leroux, Shawn J; Schmiegelow, Fiona K A; Cumming, Steve G; Lessard, Robert B; Nagy, John
2007-10-01
Systematic conservation plans have only recently considered the dynamic nature of ecosystems. Methods have been developed to incorporate climate change, population dynamics, and uncertainty in reserve design, but few studies have examined how to account for natural disturbance. Considering natural disturbance in reserve design may be especially important for the world's remaining intact areas, which still experience active natural disturbance regimes. We developed a spatially explicit, dynamic simulation model, CONSERV, which simulates patch dynamics and fire, and used it to evaluate the efficacy of hypothetical reserve networks in northern Canada. We designed six networks based on conventional reserve design methods, with different conservation targets for woodland caribou habitat, high-quality wetlands, vegetation, water bodies, and relative connectedness. We input the six reserve networks into CONSERV and tracked the ability of each to maintain initial conservation targets through time under an active natural disturbance regime. None of the reserve networks maintained all initial targets, and some over-represented certain features, suggesting that both effectiveness and efficiency of reserve design could be improved through use of spatially explicit dynamic simulation during the planning process. Spatial simulation models of landscape dynamics are commonly used in natural resource management, but we provide the first illustration of their potential use for reserve design. Spatial simulation models could be used iteratively to evaluate competing reserve designs and select targets that have a higher likelihood of being maintained through time. Such models could be combined with dynamic planning techniques to develop a general theory for reserve design in an uncertain world.
Piotti, A.; Satovic, Z.; de la Rosa, R.; Belaj, A.
2017-01-01
Abstract Background and Aims Wild olive (Olea europaea subsp. europaea var. sylvestris) is important from an economic and ecological point of view. The effects of anthropogenic activities may lead to the genetic erosion of its genetic patrimony, which has high value for breeding programmes. In particular, the consequences of the introgression from cultivated stands are strongly dependent on the extent of gene flow and therefore this work aims at quantitatively describing contemporary gene flow patterns in wild olive natural populations. Methods The studied wild population is located in an undisturbed forest, in southern Spain, considered one of the few extant hotspots of true oleaster diversity. A total of 225 potential father trees and seeds issued from five mother trees were genotyped by eight microsatellite markers. Levels of contemporary pollen flow, in terms of both pollen immigration rates and within-population dynamics, were measured through paternity analyses. Moreover, the extent of fine-scale spatial genetic structure (SGS) was studied to assess the relative importance of seed and pollen dispersal in shaping the spatial distribution of genetic variation. Key Results The results showed that the population under study is characterized by a high genetic diversity, a relatively high pollen immigration rate (0·57), an average within-population pollen dispersal of about 107 m and weak but significant SGS up to 40 m. The population is a mosaic of several intermingled genetic clusters that is likely to be generated by spatially restricted seed dispersal. Moreover, wild oleasters were found to be self-incompatible and preferential mating between some genotypes was revealed. Conclusions Knowledge of the within-population genetic structure and gene flow dynamics will lead to identifying possible strategies aimed at limiting the effect of anthropogenic activities and improving breeding programmes for the conservation of olive tree forest genetic resources. PMID:28028015
Beghè, D; Piotti, A; Satovic, Z; de la Rosa, R; Belaj, A
2017-03-01
Wild olive ( Olea europaea subsp. europaea var. sylvestris ) is important from an economic and ecological point of view. The effects of anthropogenic activities may lead to the genetic erosion of its genetic patrimony, which has high value for breeding programmes. In particular, the consequences of the introgression from cultivated stands are strongly dependent on the extent of gene flow and therefore this work aims at quantitatively describing contemporary gene flow patterns in wild olive natural populations. The studied wild population is located in an undisturbed forest, in southern Spain, considered one of the few extant hotspots of true oleaster diversity. A total of 225 potential father trees and seeds issued from five mother trees were genotyped by eight microsatellite markers. Levels of contemporary pollen flow, in terms of both pollen immigration rates and within-population dynamics, were measured through paternity analyses. Moreover, the extent of fine-scale spatial genetic structure (SGS) was studied to assess the relative importance of seed and pollen dispersal in shaping the spatial distribution of genetic variation. The results showed that the population under study is characterized by a high genetic diversity, a relatively high pollen immigration rate (0·57), an average within-population pollen dispersal of about 107 m and weak but significant SGS up to 40 m. The population is a mosaic of several intermingled genetic clusters that is likely to be generated by spatially restricted seed dispersal. Moreover, wild oleasters were found to be self-incompatible and preferential mating between some genotypes was revealed. Knowledge of the within-population genetic structure and gene flow dynamics will lead to identifying possible strategies aimed at limiting the effect of anthropogenic activities and improving breeding programmes for the conservation of olive tree forest genetic resources. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Evolutionary dynamics of cooperation in neutral populations
NASA Astrophysics Data System (ADS)
Szolnoki, Attila; Perc, Matjaž
2018-01-01
Cooperation is a difficult proposition in the face of Darwinian selection. Those that defect have an evolutionary advantage over cooperators who should therefore die out. However, spatial structure enables cooperators to survive through the formation of homogeneous clusters, which is the hallmark of network reciprocity. Here we go beyond this traditional setup and study the spatiotemporal dynamics of cooperation in a population of populations. We use the prisoner's dilemma game as the mathematical model and show that considering several populations simultaneously gives rise to fascinating spatiotemporal dynamics and pattern formation. Even the simplest assumption that strategies between different populations are payoff-neutral with one another results in the spontaneous emergence of cyclic dominance, where defectors of one population become prey of cooperators in the other population, and vice versa. Moreover, if social interactions within different populations are characterized by significantly different temptations to defect, we observe that defectors in the population with the largest temptation counterintuitively vanish the fastest, while cooperators that hang on eventually take over the whole available space. Our results reveal that considering the simultaneous presence of different populations significantly expands the complexity of evolutionary dynamics in structured populations, and it allows us to understand the stability of cooperation under adverse conditions that could never be bridged by network reciprocity alone.
Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.
Models of Eucalypt phenology predict bat population flux.
Giles, John R; Plowright, Raina K; Eby, Peggy; Peel, Alison J; McCallum, Hamish
2016-10-01
Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86-93% accuracy. Negative binomial models explained 43-53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape-scale population movement and spatiotemporal disease dynamics.
Implications of recurrent disturbance for genetic diversity.
Davies, Ian D; Cary, Geoffrey J; Landguth, Erin L; Lindenmayer, David B; Banks, Sam C
2016-02-01
Exploring interactions between ecological disturbance, species' abundances and community composition provides critical insights for ecological dynamics. While disturbance is also potentially an important driver of landscape genetic patterns, the mechanisms by which these patterns may arise by selective and neutral processes are not well-understood. We used simulation to evaluate the relative importance of disturbance regime components, and their interaction with demographic and dispersal processes, on the distribution of genetic diversity across landscapes. We investigated genetic impacts of variation in key components of disturbance regimes and spatial patterns that are likely to respond to climate change and land management, including disturbance size, frequency, and severity. The influence of disturbance was mediated by dispersal distance and, to a limited extent, by birth rate. Nevertheless, all three disturbance regime components strongly influenced spatial and temporal patterns of genetic diversity within subpopulations, and were associated with changes in genetic structure. Furthermore, disturbance-induced changes in temporal population dynamics and the spatial distribution of populations across the landscape resulted in disrupted isolation by distance patterns among populations. Our results show that forecast changes in disturbance regimes have the potential to cause major changes to the distribution of genetic diversity within and among populations. We highlight likely scenarios under which future changes to disturbance size, severity, or frequency will have the strongest impacts on population genetic patterns. In addition, our results have implications for the inference of biological processes from genetic data, because the effects of dispersal on genetic patterns were strongly mediated by disturbance regimes.
Treml, Eric A; Ford, John R; Black, Kerry P; Swearer, Stephen E
2015-01-01
Population connectivity, which is essential for the persistence of benthic marine metapopulations, depends on how life history traits and the environment interact to influence larval production, dispersal and survival. Although we have made significant advances in our understanding of the spatial and temporal dynamics of these individual processes, developing an approach that integrates the entire population connectivity process from reproduction, through dispersal, and to the recruitment of individuals has been difficult. We present a population connectivity modelling framework and diagnostic approach for quantifying the impact of i) life histories, ii) demographics, iii) larval dispersal, and iv) the physical seascape, on the structure of connectivity and metapopulation dynamics. We illustrate this approach using the subtidal rocky reef ecosystem of Port Phillip Bay, were we provide a broadly-applicable framework of population connectivity and quantitative methodology for evaluating the relative importance of individual factors in determining local and system outcomes. The spatial characteristics of marine population connectivity are primarily influenced by larval mortality, the duration of the pelagic larval stage, and the settlement competency characteristics, with significant variability imposed by the geographic setting and the timing of larval release. The relative influence and the direction and strength of the main effects were strongly consistent among 10 connectivity-based metrics. These important intrinsic factors (mortality, length of the pelagic larval stage, and the extent of the precompetency window) and the spatial and temporal variability represent key research priorities for advancing our understanding of the connectivity process and metapopulation outcomes.
Zu Erbach-Schoenberg, Elisabeth; Alegana, Victor A; Sorichetta, Alessandro; Linard, Catherine; Lourenço, Christoper; Ruktanonchai, Nick W; Graupe, Bonita; Bird, Tomas J; Pezzulo, Carla; Wesolowski, Amy; Tatem, Andrew J
2016-01-01
Reliable health metrics are crucial for accurately assessing disease burden and planning interventions. Many health indicators are measured through passive surveillance systems and are reliant on accurate estimates of denominators to transform case counts into incidence measures. These denominator estimates generally come from national censuses and use large area growth rates to estimate annual changes. Typically, they do not account for any seasonal fluctuations and thus assume a static denominator population. Many recent studies have highlighted the dynamic nature of human populations through quantitative analyses of mobile phone call data records and a range of other sources, emphasizing seasonal changes. In this study, we use mobile phone data to capture patterns of short-term human population movement and to map dynamism in population densities. We show how mobile phone data can be used to measure seasonal changes in health district population numbers, which are used as denominators for calculating district-level disease incidence. Using the example of malaria case reporting in Namibia we use 3.5 years of phone data to investigate the spatial and temporal effects of fluctuations in denominators caused by seasonal mobility on malaria incidence estimates. We show that even in a sparsely populated country with large distances between population centers, such as Namibia, populations are highly dynamic throughout the year. We highlight how seasonal mobility affects malaria incidence estimates, leading to differences of up to 30 % compared to estimates created using static population maps. These differences exhibit clear spatial patterns, with likely overestimation of incidence in the high-prevalence zones in the north of Namibia and underestimation in lower-risk areas when compared to using static populations. The results here highlight how health metrics that rely on static estimates of denominators from censuses may differ substantially once mobility and seasonal variations are taken into account. With respect to the setting of malaria in Namibia, the results indicate that Namibia may actually be closer to malaria elimination than previously thought. More broadly, the results highlight how dynamic populations are. In addition to affecting incidence estimates, these changes in population density will also have an impact on allocation of medical resources. Awareness of seasonal movements has the potential to improve the impact of interventions, such as vaccination campaigns or distributions of commodities like bed nets.
Demographic inference under the coalescent in a spatial continuum.
Guindon, Stéphane; Guo, Hongbin; Welch, David
2016-10-01
Understanding population dynamics from the analysis of molecular and spatial data requires sound statistical modeling. Current approaches assume that populations are naturally partitioned into discrete demes, thereby failing to be relevant in cases where individuals are scattered on a spatial continuum. Other models predict the formation of increasingly tight clusters of individuals in space, which, again, conflicts with biological evidence. Building on recent theoretical work, we introduce a new genealogy-based inference framework that alleviates these issues. This approach effectively implements a stochastic model in which the distribution of individuals is homogeneous and stationary, thereby providing a relevant null model for the fluctuation of genetic diversity in time and space. Importantly, the spatial density of individuals in a population and their range of dispersal during the course of evolution are two parameters that can be inferred separately with this method. The validity of the new inference framework is confirmed with extensive simulations and the analysis of influenza sequences collected over five seasons in the USA. Copyright © 2016 Elsevier Inc. All rights reserved.
Preemptive spatial competition under a reproduction-mortality constraint.
Allstadt, Andrew; Caraco, Thomas; Korniss, G
2009-06-21
Spatially structured ecological interactions can shape selection pressures experienced by a population's different phenotypes. We study spatial competition between phenotypes subject to antagonistic pleiotropy between reproductive effort and mortality rate. The constraint we invoke reflects a previous life-history analysis; the implied dependence indicates that although propagation and mortality rates both vary, their ratio is fixed. We develop a stochastic invasion approximation predicting that phenotypes with higher propagation rates will invade an empty environment (no biotic resistance) faster, despite their higher mortality rate. However, once population density approaches demographic equilibrium, phenotypes with lower mortality are favored, despite their lower propagation rate. We conducted a set of pairwise invasion analyses by simulating an individual-based model of preemptive competition. In each case, the phenotype with the lowest mortality rate and (via antagonistic pleiotropy) the lowest propagation rate qualified as evolutionarily stable among strategies simulated. This result, for a fixed propagation to mortality ratio, suggests that a selective response to spatial competition can extend the time scale of the population's dynamics, which in turn decelerates phenotypic evolution.
Spatial and temporal features of the growth of a bacterial species colonizing the zebrafish gut.
Jemielita, Matthew; Taormina, Michael J; Burns, Adam R; Hampton, Jennifer S; Rolig, Annah S; Guillemin, Karen; Parthasarathy, Raghuveer
2014-12-16
The vertebrate intestine is home to microbial ecosystems that play key roles in host development and health. Little is known about the spatial and temporal dynamics of these microbial communities, limiting our understanding of fundamental properties, such as their mechanisms of growth, propagation, and persistence. To address this, we inoculated initially germ-free zebrafish larvae with fluorescently labeled strains of an Aeromonas species, representing an abundant genus in the zebrafish gut. Using light sheet fluorescence microscopy to obtain three-dimensional images spanning the gut, we quantified the entire bacterial load, as founding populations grew from tens to tens of thousands of cells over several hours. The data yield the first ever measurements of the growth kinetics of a microbial species inside a live vertebrate intestine and show dynamics that robustly fit a logistic growth model. Intriguingly, bacteria were nonuniformly distributed throughout the gut, and bacterial aggregates showed considerably higher growth rates than did discrete individuals. The form of aggregate growth indicates intrinsically higher division rates for clustered bacteria, rather than surface-mediated agglomeration onto clusters. Thus, the spatial organization of gut bacteria both relative to the host and to each other impacts overall growth kinetics, suggesting that spatial characterizations will be an important input to predictive models of host-associated microbial community assembly. Our intestines are home to vast numbers of microbes that influence many aspects of health and disease. Though we now know a great deal about the constituents of the gut microbiota, we understand very little about their spatial structure and temporal dynamics in humans or in any animal: how microbial populations establish themselves, grow, fluctuate, and persist. To address this, we made use of a model organism, the zebrafish, and a new optical imaging technique, light sheet fluorescence microscopy, to visualize for the first time the colonization of a live, vertebrate gut by specific bacteria with sufficient resolution to quantify the population over a range from a few individuals to tens of thousands of bacterial cells. Our results provide unprecedented measures of bacterial growth kinetics and also show the influence of spatial structure on bacterial populations, which can be revealed only by direct imaging. Copyright © 2014 Jemielita et al.
The scaling of contact rates with population density for the infectious disease models.
Hu, Hao; Nigmatulina, Karima; Eckhoff, Philip
2013-08-01
Contact rates and patterns among individuals in a geographic area drive transmission of directly-transmitted pathogens, making it essential to understand and estimate contacts for simulation of disease dynamics. Under the uniform mixing assumption, one of two mechanisms is typically used to describe the relation between contact rate and population density: density-dependent or frequency-dependent. Based on existing evidence of population threshold and human mobility patterns, we formulated a spatial contact model to describe the appropriate form of transmission with initial growth at low density and saturation at higher density. We show that the two mechanisms are extreme cases that do not capture real population movement across all scales. Empirical data of human and wildlife diseases indicate that a nonlinear function may work better when looking at the full spectrum of densities. This estimation can be applied to large areas with population mixing in general activities. For crowds with unusually large densities (e.g., transportation terminals, stadiums, or mass gatherings), the lack of organized social contact structure deviates the physical contacts towards a special case of the spatial contact model - the dynamics of kinetic gas molecule collision. In this case, an ideal gas model with van der Waals correction fits well; existing movement observation data and the contact rate between individuals is estimated using kinetic theory. A complete picture of contact rate scaling with population density may help clarify the definition of transmission rates in heterogeneous, large-scale spatial systems. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Bjorndal, Karen A.; Schroeder, Barbara A.; Foley, Allen M.; Witherington, Blair E.; Bresette, Michael; Clark, David; Herren, Richard M.; Arendt, Michael D.; Schmid, Jeffrey R.; Meylan, Anne B.; Meylan, Peter A.; Provancha, Jane A.; Hart, Kristen M.; Lamont, Margaret M.; Carthy, Raymond R.; Bolten, Alan B.
2013-01-01
In response to a call from the US National Research Council for research programs to combine their data to improve sea turtle population assessments, we analyzed somatic growth data for Northwest Atlantic (NWA) loggerhead sea turtles (Caretta caretta) from 10 research programs. We assessed growth dynamics over wide ranges of geography (9–33°N latitude), time (1978–2012), and body size (35.4–103.3 cm carapace length). Generalized additive models revealed significant spatial and temporal variation in growth rates and a significant decline in growth rates with increasing body size. Growth was more rapid in waters south of the USA (<24°N) than in USA waters. Growth dynamics in southern waters in the NWA need more study because sample size was small. Within USA waters, the significant spatial effect in growth rates of immature loggerheads did not exhibit a consistent latitudinal trend. Growth rates declined significantly from 1997 through 2007 and then leveled off or increased. During this same interval, annual nest counts in Florida declined by 43 % (Witherington et al. in Ecol Appl 19:30–54, 2009) before rebounding. Whether these simultaneous declines reflect responses in productivity to a common environmental change should be explored to determine whether somatic growth rates can help interpret population trends based on annual counts of nests or nesting females. Because of the significant spatial and temporal variation in growth rates, population models of NWA loggerheads should avoid employing growth data from restricted spatial or temporal coverage to calculate demographic metrics such as age at sexual maturity.
Assortative mating and mutation diffusion in spatial evolutionary systems
NASA Astrophysics Data System (ADS)
Paley, C. J.; Taraskin, S. N.; Elliott, S. R.
2010-04-01
The influence of spatial structure on the equilibrium properties of a sexual population model defined on networks is studied numerically. Using a small-world-like topology of the networks as an investigative tool, the contributions to the fitness of assortative mating and of global mutant spread properties are considered. Simple measures of nearest-neighbor correlations and speed of spread of mutants through the system have been used to confirm that both of these dynamics are important contributory factors to the fitness. It is found that assortative mating increases the fitness of populations. Quick global spread of favorable mutations is shown to be a key factor increasing the equilibrium fitness of populations.
Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales
Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias
2016-01-01
Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625
Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics
Lythgoe, Katrina A.; Blanquart, François
2016-01-01
The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation. PMID:27706164
WKB theory of large deviations in stochastic populations
NASA Astrophysics Data System (ADS)
Assaf, Michael; Meerson, Baruch
2017-06-01
Stochasticity can play an important role in the dynamics of biologically relevant populations. These span a broad range of scales: from intra-cellular populations of molecules to population of cells and then to groups of plants, animals and people. Large deviations in stochastic population dynamics—such as those determining population extinction, fixation or switching between different states—are presently in a focus of attention of statistical physicists. We review recent progress in applying different variants of dissipative WKB approximation (after Wentzel, Kramers and Brillouin) to this class of problems. The WKB approximation allows one to evaluate the mean time and/or probability of population extinction, fixation and switches resulting from either intrinsic (demographic) noise, or a combination of the demographic noise and environmental variations, deterministic or random. We mostly cover well-mixed populations, single and multiple, but also briefly consider populations on heterogeneous networks and spatial populations. The spatial setting also allows one to study large fluctuations of the speed of biological invasions. Finally, we briefly discuss possible directions of future work.
Inostroza, Luis; Baur, Rolf; Csaplovics, Elmar
2013-01-30
South America is one of the most urbanized continents in the world, where almost 84% of the total population lives in cities, more urbanized than North America (82%) and Europe (73%). Spatial dynamics, their structure, main features, land consumption rates, spatial arrangement, fragmentation degrees and comparability, remain mostly unknown for most Latin American cities. Using satellite imagery the main parameters of sprawl are quantified for 10 Latin American cities over a period of 20 years by monitoring growth patterns and identifying spatial metrics to characterize urban development and sprawling features measured with GIS tools. This quantification contributes to a better understanding of urban form in Latin America. A pervasive spatial expansion has been observed, where most of the studied cities are expanding at fast rates with falling densities trend. Although important differences in the rates of land consumption and densities exist, there is an underlying fragmentation trend towards increasing sprawl. These trends of spatial discontinuity may eventually be intensified by further economic development. Urban Sprawl/Latin America/GIS metrics/spatial development. Copyright © 2012 Elsevier Ltd. All rights reserved.
The spatial dynamics of ecosystem engineers.
Franco, Caroline; Fontanari, José F
2017-10-01
The changes on abiotic features of ecosystems have rarely been taken into account by population dynamics models, which typically focus on trophic and competitive interactions between species. However, understanding the population dynamics of organisms that must modify their habitats in order to survive, the so-called ecosystem engineers, requires the explicit incorporation of abiotic interactions in the models. Here we study a model of ecosystem engineers that is discrete both in space and time, and where the engineers and their habitats are arranged in patches fixed to the sites of regular lattices. The growth of the engineer population is modeled by Ricker equation with a density-dependent carrying capacity that is given by the number of modified habitats. A diffusive dispersal stage ensures that a fraction of the engineers move from their birth patches to neighboring patches. We find that dispersal influences the metapopulation dynamics only in the case that the local or single-patch dynamics exhibit chaotic behavior. In that case, it can suppress the chaotic behavior and avoid extinctions in the regime of large intrinsic growth rate of the population. Copyright © 2017 Elsevier Inc. All rights reserved.
Lima, Mauricio; Estay, Sergio A; Fuentes, Rodrigo; Rubilar, Paola; Broutin, Hélène; Chowell-Puente, Gerardo
2015-12-30
The spatial-temporal dynamics of Bordetella pertussis remains as a highly interesting case in infectious disease epidemiology. Despite large-scale vaccination programs in place for over 50 years around the world, frequent outbreaks are still reported in many countries. Here, we use annual time series of pertussis incidence from the thirteen different regions of Chile (1952-2010) to study the spatial-temporal dynamics of Pertussis. The period 1975-1995 was characterized by a strong 4 year cycle, while the last two decades of the study period (1990-2010) were characterized by disease resurgence without significant periodic patterns. During the first decades, differences in periodic patterns across regions can be explained by the differences in susceptible recruitment. The observed shift in periodicity from the period 1952-1974 to the period 1975-1995 across regions was relatively well predicted by the susceptible recruitment and population size. However, data on vaccination rates was not taken into account in this study. Our findings highlight how demography and population size have interacted with the immunization program in shaping periodicity along a unique latitudinal gradient. Widespread B. pertussis vaccination appears to lead to longer periodic dynamics, which is line with a reduction in B. pertussis transmission, but our findings indicate that regions characterized by both low birth rate and population size decreased in periodicity following immunization efforts.
Roger B. Hammer; Susan I. Stewart; Richelle L. Winkler; Volker C. Radeloff; Paul R. Voss
2004-01-01
The spatial deconcentration of population during the 20th century and the resulting expansion of human settlements has been a significant cause of anthropogenic landscape change in the United States and many other countries. In the seven-state North Central Region, as in other regions of the US, changing human settlement patterns are most prominent at the outlying...
Temporally increasing spatial synchrony of North American temperature and bird populations
Walter D. Koenig; Andrew M. Liebhold
2016-01-01
The ecological impacts of modern global climate change are detectable in a wide variety of phenomena, ranging from shifts in species ranges to changes in community composition and human disease dynamics. So far, however, little attention has been given to temporal changes in spatial synchronyâthe coincident change in abundance or value across the landscapeâdespite the...
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
Vegetation changes associated with a population irruption by Roosevelt elk
Starns, H D; Weckerly, Floyd W.; Ricca, Mark; Duarte, Adam
2015-01-01
Interactions between large herbivores and their food supply are central to the study of population dynamics. We assessed temporal and spatial patterns in meadow plant biomass over a 23-year period for meadow complexes that were spatially linked to three distinct populations of Roosevelt elk (Cervus elaphus roosevelti) in northwestern California. Our objectives were to determine whether the plant community exhibited a tolerant or resistant response when elk population growth became irruptive. Plant biomass for the three meadow complexes inhabited by the elk populations was measured using Normalized Difference Vegetation Index (NDVI), which was derived from Landsat 5 Thematic Mapper imagery. Elk populations exhibited different patterns of growth through the time series, whereby one population underwent a complete four-stage irruptive growth pattern while the other two did not. Temporal changes in NDVI for the meadow complex used by the irruptive population suggested a decline in forage biomass during the end of the dry season and a temporal decline in spatial variation of NDVI at the peak of plant biomass in May. Conversely, no such patterns were detected in the meadow complexes inhabited by the nonirruptive populations. Our findings suggest that the meadow complex used by the irruptive elk population may have undergone changes in plant community composition favoring plants that were resistant to elk grazing.
An accessible method for implementing hierarchical models with spatio-temporal abundance data
Ross, Beth E.; Hooten, Melvin B.; Koons, David N.
2012-01-01
A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.
Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems
Lea, James S. E.; Wetherbee, Bradley M.; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L.; Mucientes, Gonzalo R.; Humphries, Nicolas E.; Harvey, Guy M.; Sims, David W.; Shivji, Mahmood S.
2015-01-01
Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks. PMID:26057337
Lea, James S E; Wetherbee, Bradley M; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L; Mucientes, Gonzalo R; Humphries, Nicolas E; Harvey, Guy M; Sims, David W; Shivji, Mahmood S
2015-06-09
Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.
Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems
NASA Astrophysics Data System (ADS)
Lea, James S. E.; Wetherbee, Bradley M.; Queiroz, Nuno; Burnie, Neil; Aming, Choy; Sousa, Lara L.; Mucientes, Gonzalo R.; Humphries, Nicolas E.; Harvey, Guy M.; Sims, David W.; Shivji, Mahmood S.
2015-06-01
Long-distance movements of animals are an important driver of population spatial dynamics and determine the extent of overlap with area-focused human activities, such as fishing. Despite global concerns of declining shark populations, a major limitation in assessments of population trends or spatial management options is the lack of information on their long-term migratory behaviour. For a large marine predator, the tiger shark Galeocerdo cuvier, we show from individuals satellite-tracked for multiple years (up to 1101 days) that adult males undertake annually repeated, round-trip migrations of over 7,500 km in the northwest Atlantic. Notably, these migrations occurred between the highly disparate ecosystems of Caribbean coral reef regions in winter and high latitude oceanic areas in summer, with strong, repeated philopatry to specific overwintering insular habitat. Partial migration also occurred, with smaller, immature individuals displaying reduced migration propensity. Foraging may be a putative motivation for these oceanic migrations, with summer behaviour showing higher path tortuosity at the oceanic range extremes. The predictable migratory patterns and use of highly divergent ecosystems shown by male tiger sharks appear broadly similar to migrations seen in birds, reptiles and mammals, and highlight opportunities for dynamic spatial management and conservation measures of highly mobile sharks.
Causes and consequences of complex population dynamics in an annual plant, Cardamine pensylvanica
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crone, E.E.
1995-11-08
The relative importance of density-dependent and density-independent factors in determining the population dynamics of plants has been widely debated with little resolution. In this thesis, the author explores the effects of density-dependent population regulation on population dynamics in Cardamine pensylvanica, an annual plant. In the first chapter, she shows that experimental populations of C. pensylvanica cycled from high to low density in controlled constant-environment conditions. These cycles could not be explained by external environmental changes or simple models of direct density dependence (N{sub t+1} = f[N{sub t}]), but they could be explained by delayed density dependence (N{sub t+1} = f[N{submore » t}, N{sub t+1}]). In the second chapter, she shows that the difference in the stability properties of population growth models with and without delayed density dependence is due to the presence of Hopf as well as slip bifurcations from stable to chaotic population dynamics. She also measures delayed density dependence due to effects of parental density on offspring quality in C. pensylvanica and shows that this is large enough to be the cause of the population dynamics observed in C. pensylvanica. In the third chapter, the author extends her analyses of density-dependent population growth models to include interactions between competing species. In the final chapter, she compares the effects of fixed spatial environmental variation and variation in population size on the evolutionary response of C. pensylvanica populations.« less
Indigenous migration dynamics in the Ecuadorian Amazon: a longitudinal and hierarchical analysis.
Davis, Jason; Sellers, Samuel; Gray, Clark; Bilsborrow, Richard
2017-01-01
Amazonian indigenous populations are approaching a critical stage in their history in which increasing education and market integration, rapid population growth and degradation of natural resources threaten the survival of their traditions and livelihoods. A topic that has hardly been touched upon in this context is migration and population mobility. We address this by analysing a unique longitudinal dataset from the Ecuadorian Amazon on the spatial mobility of five indigenous groups and mestizo co-residents. Analyses reveal traditional and new forms of population mobility and migrant selectivity, including gendered forms of marriage migration and rural-urban moves driven by education. These results illustrate a dynamic present and an uncertain future for indigenous populations in which rural, natural-resource-based lifeways may well be sustained but with increasing links to urban areas.
Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics
Lobelle, Delphine; Kenyon, Emma J.; Cook, Kevan J.; Bull, James C.
2013-01-01
It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value. PMID:23437313
Lobelle, Delphine; Kenyon, Emma J; Cook, Kevan J; Bull, James C
2013-01-01
It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value.
Russell F. Thurow
2000-01-01
Research was begun in 1995 to describe factors influencing the spatial dynamics and persistence of federally listed chinook salmon within the Frank Church River of No Return Wilderness. Results addressed two objectives: 1) description of chinook salmon redd distributions, and 2) comparison of index and total redd counts. Annual redd counts ranged from 20 to 661, and 99...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.
2015-09-28
Two dimensional electronic spectroscopy has proven to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.
2015-09-28
Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less
Lewis, Nicholas H C; Dong, Hui; Oliver, Thomas A A; Fleming, Graham R
2015-09-28
Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derive response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.
Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline
Bromaghin, Jeffrey F.; McDonald, Trent L.; Stirling, Ian; Derocher, Andrew E.; Richardson, Evan S.; Regehr, Eric V.; Douglas, David C.; Durner, George M.; Atwood, Todd C.; Amstrup, Steven C.
2015-01-01
In the southern Beaufort Sea of the United States and Canada, prior investigations have linked declines in summer sea ice to reduced physical condition, growth, and survival of polar bears (Ursus maritimus). Combined with projections of population decline due to continued climate warming and the ensuing loss of sea ice habitat, those findings contributed to the 2008 decision to list the species as threatened under the U.S. Endangered Species Act. Here, we used mark–recapture models to investigate the population dynamics of polar bears in the southern Beaufort Sea from 2001 to 2010, years during which the spatial and temporal extent of summer sea ice generally declined. Low survival from 2004 through 2006 led to a 25–50% decline in abundance. We hypothesize that low survival during this period resulted from (1) unfavorable ice conditions that limited access to prey during multiple seasons; and possibly, (2) low prey abundance. For reasons that are not clear, survival of adults and cubs began to improve in 2007 and abundance was comparatively stable from 2008 to 2010, with ~900 bears in 2010 (90% CI 606–1212). However, survival of subadult bears declined throughout the entire period. Reduced spatial and temporal availability of sea ice is expected to increasingly force population dynamics of polar bears as the climate continues to warm. However, in the short term, our findings suggest that factors other than sea ice can influence survival. A refined understanding of the ecological mechanisms underlying polar bear population dynamics is necessary to improve projections of their future status and facilitate development of management strategies.
Jue, Nathaniel K.; Brulé, Thierry; Coleman, Felicia C.; Koenig, Christopher C.
2015-01-01
Describing patterns of connectivity among populations of species with widespread distributions is particularly important in understanding the ecology and evolution of marine species. In this study, we examined patterns of population differentiation, migration, and historical population dynamics using microsatellite and mitochondrial loci to test whether populations of the epinephelid fish, Gag, Mycteroperca microlepis, an important fishery species, are genetically connected across the Gulf of Mexico and if so, whether that connectivity is attributable to either contemporary or historical processes. Populations of Gag on the Campeche Bank and the West Florida Shelf show significant, but low magnitude, differentiation. Time since divergence/expansion estimates associated with historical population dynamics indicate that any population or spatial expansions indicated by population genetics would have likely occurred in the late Pleistocene. Using coalescent-based approaches, we find that the best model for explaining observed spatial patterns of contemporary genetic variation is one of asymmetric gene flow, with movement from Campeche Bank to the West Florida Shelf. Both estimated migration rates and ecological data support the hypothesis that Gag populations throughout the Gulf of Mexico are connected via present day larval dispersal. Demonstrating this greatly expanded scale of connectivity for Gag highlights the influence of “ghost” populations (sensu Beerli) on genetic patterns and presents a critical consideration for both fisheries management and conservation of this and other species with similar genetic patterns. PMID:25856095
Measurements of spatial population synchrony: influence of time series transformations.
Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël
2015-09-01
Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.
Scale-up of ecological experiments: Density variation in the mobile bivalve Macomona liliana
Schneider, Davod C.; Walters, R.; Thrush, S.; Dayton, P.
1997-01-01
At present the problem of scaling up from controlled experiments (necessarily at a small spatial scale) to questions of regional or global importance is perhaps the most pressing issue in ecology. Most of the proposed techniques recommend iterative cycling between theory and experiment. We present a graphical technique that facilitates this cycling by allowing the scope of experiments, surveys, and natural history observations to be compared to the scope of models and theory. We apply the scope analysis to the problem of understanding the population dynamics of a bivalve exposed to environmental stress at the scale of a harbour. Previous lab and field experiments were found not to be 1:1 scale models of harbour-wide processes. Scope analysis allowed small scale experiments to be linked to larger scale surveys and to a spatially explicit model of population dynamics.
Synchronisation and stability in river metapopulation networks.
Yeakel, J D; Moore, J W; Guimarães, P R; de Aguiar, M A M
2014-03-01
Spatial structure in landscapes impacts population stability. Two linked components of stability have large consequences for persistence: first, statistical stability as the lack of temporal fluctuations; second, synchronisation as an aspect of dynamic stability, which erodes metapopulation rescue effects. Here, we determine the influence of river network structure on the stability of riverine metapopulations. We introduce an approach that converts river networks to metapopulation networks, and analytically show how fluctuation magnitude is influenced by interaction structure. We show that river metapopulation complexity (in terms of branching prevalence) has nonlinear dampening effects on population fluctuations, and can also buffer against synchronisation. We conclude by showing that river transects generally increase synchronisation, while the spatial scale of interaction has nonlinear effects on synchronised dynamics. Our results indicate that this dual stability - conferred by fluctuation and synchronisation dampening - emerges from interaction structure in rivers, and this may strongly influence the persistence of river metapopulations. © 2013 John Wiley & Sons Ltd/CNRS.
Spatial structure and distribution of small pelagic fish in the northwestern Mediterranean Sea.
Saraux, Claire; Fromentin, Jean-Marc; Bigot, Jean-Louis; Bourdeix, Jean-Hervé; Morfin, Marie; Roos, David; Van Beveren, Elisabeth; Bez, Nicolas
2014-01-01
Understanding the ecological and anthropogenic drivers of population dynamics requires detailed studies on habitat selection and spatial distribution. Although small pelagic fish aggregate in large shoals and usually exhibit important spatial structure, their dynamics in time and space remain unpredictable and challenging. In the Gulf of Lions (north-western Mediterranean), sardine and anchovy biomasses have declined over the past 5 years causing an important fishery crisis while sprat abundance rose. Applying geostatistical tools on scientific acoustic surveys conducted in the Gulf of Lions, we investigated anchovy, sardine and sprat spatial distributions and structures over 10 years. Our results show that sardines and sprats were more coastal than anchovies. The spatial structure of the three species was fairly stable over time according to variogram outputs, while year-to-year variations in kriged maps highlighted substantial changes in their location. Support for the McCall's basin hypothesis (covariation of both population density and presence area with biomass) was found only in sprats, the most variable of the three species. An innovative method to investigate species collocation at different scales revealed that globally the three species strongly overlap. Although species often co-occurred in terms of presence/absence, their biomass density differed at local scale, suggesting potential interspecific avoidance or different sensitivity to local environmental characteristics. Persistent favourable areas were finally detected, but their environmental characteristics remain to be determined.
NASA Astrophysics Data System (ADS)
Taylor, Bradford P.; Penington, Catherine J.; Weitz, Joshua S.
2016-12-01
Multiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virus-microbe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases in viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean field model. We also observe long-tails in the distribution of the multiplicity of infection in contrast to mean field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.
Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar
2018-05-15
The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.
2015-01-01
Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911
Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik
2017-10-01
Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G
2008-10-23
Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
Cabral, Juliano Sarmento; Bond, William J; Midgley, Guy F; Rebelo, Anthony G; Thuiller, Wilfried; Schurr, Frank M
2011-02-01
Wildflower harvesting is an economically important activity of which the ecological effects are poorly understood. We assessed how harvesting of flowers affects shrub persistence and abundance at multiple spatial extents. To this end, we built a process-based model to examine the mean persistence and abundance of wild shrubs whose flowers are subject to harvest (serotinous Proteaceae in the South African Cape Floristic Region). First, we conducted a general sensitivity analysis of how harvesting affects persistence and abundance at nested spatial extents. For most spatial extents and combinations of demographic parameters, persistence and abundance of flowering shrubs decreased abruptly once harvesting rate exceeded a certain threshold. At larger extents, metapopulations supported higher harvesting rates before their persistence and abundance decreased, but persistence and abundance also decreased more abruptly due to harvesting than at smaller extents. This threshold rate of harvest varied with species' dispersal ability, maximum reproductive rate, adult mortality, probability of extirpation or local extinction, strength of Allee effects, and carrying capacity. Moreover, spatial extent interacted with Allee effects and probability of extirpation because both these demographic properties affected the response of local populations to harvesting more strongly than they affected the response of metapopulations. Subsequently, we simulated the effects of harvesting on three Cape Floristic Region Proteaceae species and found that these species reacted differently to harvesting, but their persistence and abundance decreased at low rates of harvest. Our estimates of harvesting rates at maximum sustainable yield differed from those of previous investigations, perhaps because researchers used different estimates of demographic parameters, models of population dynamics, and spatial extent than we did. Good demographic knowledge and careful identification of the spatial extent of interest increases confidence in assessments and monitoring of the effects of harvesting. Our general sensitivity analysis improved understanding of harvesting effects on metapopulation dynamics and allowed qualitative assessment of the probability of extirpation of poorly studied species. ©2010 Society for Conservation Biology.
Human population dynamics in Europe over the Last Glacial Maximum.
Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki
2015-07-07
The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.
Human population dynamics in Europe over the Last Glacial Maximum
Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki
2015-01-01
The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000–19,000 y ago (27–19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30–13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe. PMID:26100880
Network dynamics underlying the formation of sparse, informative representations in the hippocampus.
Karlsson, Mattias P; Frank, Loren M
2008-12-24
During development, activity-dependent processes increase the specificity of neural responses to stimuli, but the role that this type of process plays in adult plasticity is unclear. We examined the dynamics of hippocampal activity as animals learned about new environments to understand how neural selectivity changes with experience. Hippocampal principal neurons fire when the animal is located in a particular subregion of its environment, and in any given environment the hippocampal representation is sparse: less than half of the neurons in areas CA1 and CA3 are active whereas the rest are essentially silent. Here we show that different dynamics govern the evolution of this sparsity in CA1 and upstream area CA3. CA1, but not CA3, produces twice as many spikes in novel compared with familiar environments. This high rate firing continues during sharp wave ripple events in a subsequent rest period. The overall CA1 population rate declines and the number of active cells decreases as the environment becomes familiar and task performance improves, but the decline in rate is not uniform across neurons. Instead, the activity of cells with initial peak spatial rates above approximately 12 Hz is enhanced, whereas the activity of cells with lower initial peak rates is suppressed. The result of these changes is that the active CA1 population comes to consist of a relatively small group of cells with strong spatial tuning. This process is not evident in CA3, indicating that a region-specific and long timescale process operates in CA1 to create a sparse, spatially informative population of neurons.
Bubonic plague: a metapopulation model of a zoonosis.
Keeling, M J; Gilligan, C A
2000-01-01
Bubonic plague (Yersinia pestis) is generally thought of as a historical disease; however, it is still responsible for around 1000-3000 deaths each year worldwide. This paper expands the analysis of a model for bubonic plague that encompasses the disease dynamics in rat, flea and human populations. Some key variables of the deterministic model, including the force of infection to humans, are shown to be robust to changes in the basic parameters, although variation in the flea searching efficiency, and the movement rates of rats and fleas will be considered throughout the paper. The stochastic behaviour of the corresponding metapopulation model is discussed, with attention focused on the dynamics of rats and the force of infection at the local spatial scale. Short-lived local epidemics in rats govern the invasion of the disease and produce an irregular pattern of human cases similar to those observed. However, the endemic behaviour in a few rat subpopulations allows the disease to persist for many years. This spatial stochastic model is also used to identify the criteria for the spread to human populations in terms of the rat density. Finally, the full stochastic model is reduced to the form of a probabilistic cellular automaton, which allows the analysis of a large number of replicated epidemics in large populations. This simplified model enables us to analyse the spatial properties of rat epidemics and the effects of movement rates, and also to test whether the emergent metapopulation behaviour is a property of the local dynamics rather than the precise details of the model. PMID:11413636
Estimating golden-cheeked warbler immigration: Implications for the spatial scale of conservation
Duarte, A.; Weckerly, F.W.; Schaub, M.; Hatfield, Jeffrey S.
2016-01-01
Understanding the factors that drive population dynamics is fundamental to species conservation and management. Since the golden-cheeked warbler Setophaga chrysoparia was first listed as endangered, much effort has taken place to monitor warbler abundance, occupancy, reproduction and survival. Yet, despite being directly related to local population dynamics, movement rates have not been estimated for the species. We used an integrated population model to investigate the relationship between immigration rate, fledging rate, survival probabilities and population growth rate for warblers in central Texas, USA. Furthermore, using a deterministic projection model, we examined the response required by vital rates to maintain a viable population across varying levels of immigration. Warbler abundance fluctuated with an overall positive trend across years. In the absence of immigration, the abundance would have decreased. However, the population could remain viable without immigration if both adult and juvenile survival increased by almost half or if juvenile survival more than doubled. We also investigated the response required by fledging rates across a range of immigration in order to maintain a viable population. Overall, we found that immigration was required to maintain warbler target populations, indicating that warbler conservation and management programs need to be implemented at larger spatial scales than current efforts to be effective. This study also demonstrates that by using limited data within integrated population models, biologists are able to monitor multiple key demographic parameters simultaneously to gauge the efficacy of strategies designed to maximize warbler viability in a changing landscape.
Massonnet, Blandine; Simon, Jean-Christophe; Weisser, Wolfgang W
2002-12-01
We investigated population dynamics, genetic diversity and spatial structure in the aphid species Macrosiphoniella tanacetaria, a specialist herbivore feeding on tansy, Tanacetum vulgare. Tansy plants (genets) consist of many shoots (ramets), and genets are grouped in sites. Thus, aphids feeding on tansy can cluster at the level of ramets, genets and sites. We studied aphid population dynamics in 1997 and 2001 and found that within sites: (i). at any time, aphids used only a fraction of the available ramets and genets; (ii). at the level of ramets, most aphid colonies survived only one week; (iii). at the level of genets, mean survival time was less than 4 weeks; and (iv). colonization and extinction events occurred throughout the season. We sampled aphids in seven sites in the Alsace region, France (4-45 km apart) and two sites in Germany in 1999 to study genetic structure within and between populations. Genetic analyses using nine microsatellite loci showed that: (i). genotypic variability was high, (ii). none of the populations was in Hardy-Weinberg equilibrium, (iii). heterozygote deficits and linkage disequilibria were frequent, and (iv). all populations were genetically differentiated, even at a small geographical scale. Renewed sampling of the Alsace sites in 2001 showed that three populations had become extinct and significant genetic changes had occurred in the remaining four populations. The frequencies of extinction and colonization events at several spatial scales suggest a hierarchical metapopulation structure for M. tanacetaria. Frequent population turnover and drift are likely causes for the genetic differentiation of M. tanacetaria populations.
Haiganoush K. Preisler; Jeffrey A. Hicke; Alan A. Ager; Jane L. Hayes
2012-01-01
Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process...
Aspiration dynamics in structured population acts as if in a well-mixed one.
Du, Jinming; Wu, Bin; Wang, Long
2015-01-26
Understanding the evolution of human interactive behaviors is important. Recent experimental results suggest that human cooperation in spatial structured population is not enhanced as predicted in previous works, when payoff-dependent imitation updating rules are used. This constraint opens up an avenue to shed light on how humans update their strategies in real life. Studies via simulations show that, instead of comparison rules, self-evaluation driven updating rules may explain why spatial structure does not alter the evolutionary outcome. Though inspiring, there is a lack of theoretical result to show the existence of such evolutionary updating rule. Here we study the aspiration dynamics, and show that it does not alter the evolutionary outcome in various population structures. Under weak selection, by analytical approximation, we find that the favored strategy in regular graphs is invariant. Further, we show that this is because the criterion under which a strategy is favored is the same as that of a well-mixed population. By simulation, we show that this holds for random networks. Although how humans update their strategies is an open question to be studied, our results provide a theoretical foundation of the updating rules that may capture the real human updating rules.
The effect of travel loss on evolutionarily stable distributions of populations in space.
Deangelis, Donald L; Wolkowicz, Gail S K; Lou, Yuan; Jiang, Yuexin; Novak, Mark; Svanbäck, Richard; Araújo, Márcio S; Jo, Youngseung; Cleary, Erin A
2011-07-01
A key assumption of the ideal free distribution (IFD) is that there are no costs in moving between habitat patches. However, because many populations exhibit more or less continuous population movement between patches and traveling cost is a frequent factor, it is important to determine the effects of costs on expected population movement patterns and spatial distributions. We consider a food chain (tritrophic or bitrophic) in which one species moves between patches, with energy cost or mortality risk in movement. In the two-patch case, assuming forced movement in one direction, an evolutionarily stable strategy requires bidirectional movement, even if costs during movement are high. In the N-patch case, assuming that at least one patch is linked bidirectionally to all other patches, optimal movement rates can lead to source-sink dynamics where patches with negative growth rates are maintained by other patches with positive growth rates. As well, dispersal between patches is not balanced (even in the two-patch case), leading to a deviation from the IFD. Our results indicate that cost-associated forced movement can have important consequences for spatial metapopulation dynamics. Relevance to marine reserve design and the study of stream communities subject to drift is discussed.
A model for a spatially structured metapopulation accounting for within patch dynamics.
Smith, Andrew G; McVinish, Ross; Pollett, Philip K
2014-01-01
We develop a stochastic metapopulation model that accounts for spatial structure as well as within patch dynamics. Using a deterministic approximation derived from a functional law of large numbers, we develop conditions for extinction and persistence of the metapopulation in terms of the birth, death and migration parameters. Interestingly, we observe the Allee effect in a metapopulation comprising two patches of greatly different sizes, despite there being decreasing patch specific per-capita birth rates. We show that the Allee effect is due to the way the migration rates depend on the population density of the patches. Copyright © 2013 Elsevier Inc. All rights reserved.
Patrick C. Tobin; Laura M. Blackburn; Rebecca H. Gray; Christopher T. Lettau; Andrew M. Liebhold; Kenneth F. Raffa
2013-01-01
The ability to ascertain abundance and spatial extent of a nascent population of a non-native species can inform management decisions. Following initial detection, delimiting surveys, which involve the use of a finer network of samples around the focal point of a newly detected colony, are often used to quantify colony size, spatial extent, and the location of the...
Stochasticity and Spatial Interaction Govern Stem Cell Differentiation Dynamics
NASA Astrophysics Data System (ADS)
Smith, Quinton; Stukalin, Evgeny; Kusuma, Sravanti; Gerecht, Sharon; Sun, Sean X.
2015-07-01
Stem cell differentiation underlies many fundamental processes such as development, tissue growth and regeneration, as well as disease progression. Understanding how stem cell differentiation is controlled in mixed cell populations is an important step in developing quantitative models of cell population dynamics. Here we focus on quantifying the role of cell-cell interactions in determining stem cell fate. Toward this, we monitor stem cell differentiation in adherent cultures on micropatterns and collect statistical cell fate data. Results show high cell fate variability and a bimodal probability distribution of stem cell fraction on small (80-140 μm diameter) micropatterns. On larger (225-500 μm diameter) micropatterns, the variability is also high but the distribution of the stem cell fraction becomes unimodal. Using a stochastic model, we analyze the differentiation dynamics and quantitatively determine the differentiation probability as a function of stem cell fraction. Results indicate that stem cells can interact and sense cellular composition in their immediate neighborhood and adjust their differentiation probability accordingly. Blocking epithelial cadherin (E-cadherin) can diminish this cell-cell contact mediated sensing. For larger micropatterns, cell motility adds a spatial dimension to the picture. Taken together, we find stochasticity and cell-cell interactions are important factors in determining cell fate in mixed cell populations.
Epstein, Joshua M.; Pankajakshan, Ramesh; Hammond, Ross A.
2011-01-01
We introduce a novel hybrid of two fields—Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)—as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool. PMID:21687788
Natural image sequences constrain dynamic receptive fields and imply a sparse code.
Häusler, Chris; Susemihl, Alex; Nawrot, Martin P
2013-11-06
In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu
2008-09-01
An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization [Senina, I., Sibert, J., Lehodey, P., 2008. Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: application to skipjack tuna. Progress in Oceanography]. Once this evaluation and parameterization is complete, it may be possible to use the model for management of tuna stocks in the context of climate and ecosystem variability, and to investigate potential changes due to anthropogenic activities including global warming and fisheries pressures and management scenarios.
Boza, Gergely; Kun, Ádám; Scheuring, István; Dieckmann, Ulf
2012-01-01
There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species. Such interactions will often involve plasticity in investment behavior, in response to the interacting partner's investments. Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions, a key phenomenon strongly supported by experimental observations. In particular, we present a comprehensive analysis of a continuous reciprocal investment game between mutualists, both in well-mixed and spatially structured populations, and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism. We demonstrate that mutualistic partners invariably follow investment cycles, during which mutualism first increases, before both partners eventually reduce their investments to zero, so that these cycles always conclude with full defection. We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle. Although mutualistic partners perpetually change their strategies, the community-level distribution of investment levels becomes stationary. In spatially structured populations, the maintenance of polymorphism is further facilitated by dynamic mosaic structures, in which mutualistic partners form expanding and collapsing spatial bubbles or clusters. Additionally, we reveal strategy-diversity thresholds, both for well-mixed and spatially structured mutualistic communities, and discuss factors for meeting these thresholds, and thus maintaining mutualism. Our results demonstrate that interspecific mutualism, when considered as plastic investment behavior, can be unstable, and, in agreement with empirical observations, may involve a polymorphism of investment levels, varying both in space and in time. Identifying the mechanisms maintaining such polymorphism, and hence mutualism in natural communities, provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions. PMID:23166478
Boza, Gergely; Kun, Adám; Scheuring, István; Dieckmann, Ulf
2012-01-01
There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species. Such interactions will often involve plasticity in investment behavior, in response to the interacting partner's investments. Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions, a key phenomenon strongly supported by experimental observations. In particular, we present a comprehensive analysis of a continuous reciprocal investment game between mutualists, both in well-mixed and spatially structured populations, and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism. We demonstrate that mutualistic partners invariably follow investment cycles, during which mutualism first increases, before both partners eventually reduce their investments to zero, so that these cycles always conclude with full defection. We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle. Although mutualistic partners perpetually change their strategies, the community-level distribution of investment levels becomes stationary. In spatially structured populations, the maintenance of polymorphism is further facilitated by dynamic mosaic structures, in which mutualistic partners form expanding and collapsing spatial bubbles or clusters. Additionally, we reveal strategy-diversity thresholds, both for well-mixed and spatially structured mutualistic communities, and discuss factors for meeting these thresholds, and thus maintaining mutualism. Our results demonstrate that interspecific mutualism, when considered as plastic investment behavior, can be unstable, and, in agreement with empirical observations, may involve a polymorphism of investment levels, varying both in space and in time. Identifying the mechanisms maintaining such polymorphism, and hence mutualism in natural communities, provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions.
López-Carr, David; Pricope, Narcisa G.; Aukema, Juliann E.; Jankowska, Marta M.; Funk, Christopher C.; Husak, Gregory J.; Michaelsen, Joel C.
2014-01-01
We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.
SALMOD: A population model for salmonids: user's manual. Version W3
Bartholow, John; Heasley, John; Laake, Jeff; Sandelin, Jeff; Coughlan, Beth A.K.; Moos, Alan
2002-01-01
SALMOD is a computer model that simulates the dynamics of freshwater salmonid populations, both anadromous and resident. The conceptual model was developed in a workshop setting (Williamson et al. 1993) using fish experts concerned with Trinity River chinook restoration. The model builds on the foundation laid by similar models (see Cheslak and Jacobson 1990). The model’s premise that that egg and fish mortality are directly related to spatially and temporally variable micro- and macrohabitat limitations, which themselves are related to the timing and amount of streamflow and other meteorological variables. Habitat quality and capacity are characterized by the hydraulic and thermal properties of individual mesohabitats, which we use as spatial “computation units” in the model. The model tracks a population of spatially distinct cohorts that originate as gees and grow from one life stage to another as a function of local water temperature. Individual cohorts either remain in the computational unit in which they emerged or move, in whole or in part, to nearby units (see McCormick et al. 1998). Model processes include spawning (with red superimposition and incubation losses), growth (including egg maturation), mortality, and movement (freshet-induced, habitat-induced, and seasonal). Model processes are implemented such that the user (modeler) has the ability to more-or-less program the model on the fly to create the dynamics thought to animate the population. SALMOD then tabulates the various causes of mortality and the whereabouts of fish.
NASA Astrophysics Data System (ADS)
Sonis, M.
Socio-ecological dynamics emerged from the field of Mathematical SocialSciences and opened up avenues for re-examination of classical problems of collective behavior in Social and Spatial sciences. The ``engine" of this collective behavior is the subjective mental evaluation of level of utilities in the future, presenting sets of composite socio-economic-temporal-locational advantages. These dynamics present new laws of collective multi-population behavior which are the meso-level counterparts of the utility optimization individual behavior. The central core of the socio-ecological choice dynamics includes the following first principle of the collective choice behavior of ``Homo Socialis" based on the existence of ``collective consciousness": the choice behavior of ``Homo Socialis" is a collective meso-level choice behavior such that the relative changes in choice frequencies depend on the distribution of innovation alternatives between adopters of innovations. The mathematical basis of the Socio-Ecological Dynamics includes two complementary analytical approaches both based on the use of computer modeling as a theoretical and simulation tool. First approach is the ``continuous approach" --- the systems of ordinary and partial differential equations reflecting the continuous time Volterra ecological formalism in a form of antagonistic and/or cooperative collective hyper-games between different sub-sets of choice alternatives. Second approach is the ``discrete approach" --- systems of difference equations presenting a new branch of the non-linear discrete dynamics --- the Discrete Relative m-population/n-innovations Socio-Spatial Dynamics (Dendrinos and Sonis, 1990). The generalization of the Volterra formalism leads further to the meso-level variational principle of collective choice behavior determining the balance between the resulting cumulative social spatio-temporal interactions among the population of adopters susceptible to the choice alternatives and the cumulative equalization of the power of elites supporting different choice alternatives. This balance governs the dynamic innovation choice process and constitutes the dynamic meso-level counterpart of the micro-economic individual utility maximization principle.
2012-01-01
The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. PMID:22591595
Bellesia, Giovanni; Bales, Benjamin B.
2016-10-10
Here, we investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been “extended” and considered as a prototype reaction-diffusion system. These results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatialmore » stochastic simulation methods for the study of biochemical networks in vivo where the “well-mixed” approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.« less
Stratification Modelling of Key Bacterial Taxa Driven by Metabolic Dynamics in Meromictic Lakes.
Zhu, Kaicheng; Lauro, Federico M; Su, Haibin
2018-06-22
In meromictic lakes, the water column is stratified into distinguishable steady layers with different physico-chemical properties. The bottom portion, known as monimolimnion, has been studied for the functional stratification of microbial populations. Recent experiments have reported the profiles of bacterial and nutrient spatial distributions, but quantitative understanding is invoked to unravel the underlying mechanism of maintaining the discrete spatial organization. Here a reaction-diffusion model is developed to highlight the spatial pattern coupled with the light-driven metabolism of bacteria, which is resilient to a wide range of dynamical correlation between bacterial and nutrient species at the molecular level. Particularly, exact analytical solutions of the system are presented together with numerical results, in a good agreement with measurements in Ace lake and Rogoznica lake. Furthermore, one quantitative prediction is reported here on the dynamics of the seasonal stratification patterns in Ace lake. The active role played by the bacterial metabolism at microscale clearly shapes the biogeochemistry landscape of lake-wide ecology at macroscale.
Medvedinskiĭ, A B; Tikhonova, I A; Li, B L; Malchow, H
2003-01-01
The dynamics of aquatic biological communities in a patchy environment is of great interest in respect to interrelations between phenomena at various spatial and time scales. To study the complex plankton dynamics in relation to variations of such a biologically essential parameter as the fish predation rate, we use a simple reaction-diffusion model of trophic interactions between phytoplankton, zooplankton, and fish. We suggest that plankton is distributed between two habitats one of which is fish-free due to hydrological inhomogeneity, while the other is fish-populated. We show that temporal variations in the fish predation rate do not violate the strong correspondence between the character of spatial distribution of plankton and changes of plankton biomass in time: regular temporal oscillations of plankton biomass correspond to large-scale plankton patches, while chaotic oscillations correspond to small-scale plankton patterns. As in the case of the constant fish predation rate, the chaotic plankton dynamics is characterized by coexistence of the chaotic attractor and limit cycle.
Charles B. Yackulic; Janice Reid; James D. Nichols; James E. Hines; Raymond Davis; Eric Forsman
2014-01-01
The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competitionâs importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl,...
Ising-like patterns of spatial synchrony in population biology
NASA Astrophysics Data System (ADS)
Noble, Andrew; Hastings, Alan; Machta, Jon
2014-03-01
Systems of coupled dynamical oscillators can undergo a phase transition between synchronous and asynchronous phases. In the case of coupled map lattices, the spontaneous symmetry breaking of a temporal-phase order parameter is known to exhibit Ising-like critical behavior. Here, we investigate a noisy coupled map motivated by the study of spatial synchrony in ecological populations far from the extinction threshold. Ising-like patterns of criticality, as well as spinodal decomposition and homogeneous nucleation, emerge from the nonlinear interactions of environmental fluctuations in habitat quality, local density-dependence in reproduction, and dispersal. In the mean-field limit, the correspondence to the Ising model is exact: the fixed points of our dynamical system are given by the equation of state for Weiss mean-field theory under an appropriate mapping of parameters. We have strong evidence that a quantitative correspondence persists, both near and far from the critical point, in the presence of fluctuations. Our results provide a formal connection between equilibrium statistical physics and population biology. This work is supported by the National Science Foundation under Grant No. 1344187.
Indigenous migration dynamics in the Ecuadorian Amazon: a longitudinal and hierarchical analysis
Davis, Jason; Sellers, Samuel; Gray, Clark; Bilsborrow, Richard
2017-01-01
Amazonian indigenous populations are approaching a critical stage in their history in which increasing education and market integration, rapid population growth and degradation of natural resources threaten the survival of their traditions and livelihoods. A topic that has hardly been touched upon in this context is migration and population mobility. We address this by analysing a unique longitudinal dataset from the Ecuadorian Amazon on the spatial mobility of five indigenous groups and mestizo co-residents. Analyses reveal traditional and new forms of population mobility and migrant selectivity, including gendered forms of marriage migration and rural-urban moves driven by education. These results illustrate a dynamic present and an uncertain future for indigenous populations in which rural, natural-resource-based lifeways may well be sustained but with increasing links to urban areas. PMID:29129939
Vangestel, C; Mergeay, J; Dawson, D A; Callens, T; Vandomme, V; Lens, L
2012-01-01
House sparrow (Passer domesticus) populations have suffered major declines in urban as well as rural areas, while remaining relatively stable in suburban ones. Yet, to date no exhaustive attempt has been made to examine how, and to what extent, spatial variation in population demography is reflected in genetic population structuring along contemporary urbanization gradients. Here we use putatively neutral microsatellite loci to study if and how genetic variation can be partitioned in a hierarchical way among different urbanization classes. Principal coordinate analyses did not support the hypothesis that urban/suburban and rural populations comprise two distinct genetic clusters. Comparison of FST values at different hierarchical scales revealed drift as an important force of population differentiation. Redundancy analyses revealed that genetic structure was strongly affected by both spatial variation and level of urbanization. The results shown here can be used as baseline information for future genetic monitoring programmes and provide additional insights into contemporary house sparrow dynamics along urbanization gradients. PMID:22588131
Vangestel, C; Mergeay, J; Dawson, D A; Callens, T; Vandomme, V; Lens, L
2012-09-01
House sparrow (Passer domesticus) populations have suffered major declines in urban as well as rural areas, while remaining relatively stable in suburban ones. Yet, to date no exhaustive attempt has been made to examine how, and to what extent, spatial variation in population demography is reflected in genetic population structuring along contemporary urbanization gradients. Here we use putatively neutral microsatellite loci to study if and how genetic variation can be partitioned in a hierarchical way among different urbanization classes. Principal coordinate analyses did not support the hypothesis that urban/suburban and rural populations comprise two distinct genetic clusters. Comparison of FST values at different hierarchical scales revealed drift as an important force of population differentiation. Redundancy analyses revealed that genetic structure was strongly affected by both spatial variation and level of urbanization. The results shown here can be used as baseline information for future genetic monitoring programmes and provide additional insights into contemporary house sparrow dynamics along urbanization gradients.
Spatiotemporal distribution of Holocene populations in North America
Chaput, Michelle A.; Kriesche, Björn; Betts, Matthew; Martindale, Andrew; Kulik, Rafal; Schmidt, Volker; Gajewski, Konrad
2015-01-01
As the Cordilleran and Laurentide Ice Sheets retreated, North America was colonized by human populations; however, the spatial patterns of subsequent population growth are unclear. Temporal frequency distributions of aggregated radiocarbon (14C) dates are used as a proxy of population size and can be used to track this expansion. The Canadian Archaeological Radiocarbon Database contains more than 35,000 14C dates and is used in this study to map the spatiotemporal demographic changes of Holocene populations in North America at a continental scale for the past 13,000 y. We use the kernel method, which converts the spatial distribution of 14C dates into estimates of population density at 500-y intervals. The resulting maps reveal temporally distinct, dynamic patterns associated with paleodemographic trends that correspond well to genetic, archaeological, and ethnohistoric evidence of human occupation. These results have implications for hypothesizing and testing migration routes into and across North America as well as the relative influence of North American populations on the evolution of the North American ecosystem. PMID:26351683
NASA Astrophysics Data System (ADS)
Breau, Sébastien; Shin, Michael; Burkhart, Nick
2018-01-01
The spatial configurations of changes in the distribution of incomes within Canada's eight largest metropolitan areas are examined using a new approach based on dynamic local indicators of spatial association. These changes are characterized by increasing spatial polarization (or divergence) between higher- and lower-income neighbourhoods in Montreal, Toronto, Ottawa-Gatineau, Calgary and Vancouver. Though patterns of spatial polarization are less pronounced in Edmonton, Winnipeg and Quebec City, several lower-income neighbourhoods in these cities nevertheless appear to be losing ground relative to other neighbourhoods. These neighbourhoods are typically characterized by higher levels of precarious employment and higher shares of visible minority and recent immigrant populations.
McDonald, Jenni L; Robertson, Andrew; Silk, Matthew J
2018-01-01
Long-term individual-based datasets on host-pathogen systems are a rare and valuable resource for understanding the infectious disease dynamics in wildlife. A study of European badgers (Meles meles) naturally infected with bovine tuberculosis (bTB) at Woodchester Park in Gloucestershire (UK) has produced a unique dataset, facilitating investigation of a diverse range of epidemiological and ecological questions with implications for disease management. Since the 1970s, this badger population has been monitored with a systematic mark-recapture regime yielding a dataset of >15,000 captures of >3,000 individuals, providing detailed individual life-history, morphometric, genetic, reproductive and disease data. The annual prevalence of bTB in the Woodchester Park badger population exhibits no straightforward relationship with population density, and both the incidence and prevalence of Mycobacterium bovis show marked variation in space. The study has revealed phenotypic traits that are critical for understanding the social structure of badger populations along with mechanisms vital for understanding disease spread at different spatial resolutions. Woodchester-based studies have provided key insights into how host ecology can influence infection at different spatial and temporal scales. Specifically, it has revealed heterogeneity in epidemiological parameters; intrinsic and extrinsic factors affecting population dynamics; provided insights into senescence and individual life histories; and revealed consistent individual variation in foraging patterns, refuge use and social interactions. An improved understanding of ecological and epidemiological processes is imperative for effective disease management. Woodchester Park research has provided information of direct relevance to bTB management, and a better appreciation of the role of individual heterogeneity in disease transmission can contribute further in this regard. The Woodchester Park study system now offers a rare opportunity to seek a dynamic understanding of how individual-, group- and population-level processes interact. The wealth of existing data makes it possible to take a more integrative approach to examining how the consequences of individual heterogeneity scale to determine population-level pathogen dynamics and help advance our understanding of the ecological drivers of host-pathogen systems. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Linking genetic and environmental factors in amphibian disease risk
Savage, Anna E; Becker, Carlos G; Zamudio, Kelly R
2015-01-01
A central question in evolutionary biology is how interactions between organisms and the environment shape genetic differentiation. The pathogen Batrachochytrium dendrobatidis (Bd) has caused variable population declines in the lowland leopard frog (Lithobates yavapaiensis); thus, disease has potentially shaped, or been shaped by, host genetic diversity. Environmental factors can also influence both amphibian immunity and Bd virulence, confounding our ability to assess the genetic effects on disease dynamics. Here, we used genetics, pathogen dynamics, and environmental data to characterize L. yavapaiensis populations, estimate migration, and determine relative contributions of genetic and environmental factors in predicting Bd dynamics. We found that the two uninfected populations belonged to a single genetic deme, whereas each infected population was genetically unique. We detected an outlier locus that deviated from neutral expectations and was significantly correlated with mortality within populations. Across populations, only environmental variables predicted infection intensity, whereas environment and genetics predicted infection prevalence, and genetic diversity alone predicted mortality. At one locality with geothermally elevated water temperatures, migration estimates revealed source–sink dynamics that have likely prevented local adaptation. We conclude that integrating genetic and environmental variation among populations provides a better understanding of Bd spatial epidemiology, generating more effective conservation management strategies for mitigating amphibian declines. PMID:26136822
Cooke, Steven J.; Martins, Eduardo G; Struthers, Daniel P; Gutowsky, Lee F G; Powers, Michael H.; Doka, Susan E.; Dettmers, John M.; Crook, David A; Lucas, Martyn C.; Holbrook, Christopher; Krueger, Charles C.
2016-01-01
Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.
Cooke, Steven J; Martins, Eduardo G; Struthers, Daniel P; Gutowsky, Lee F G; Power, Michael; Doka, Susan E; Dettmers, John M; Crook, David A; Lucas, Martyn C; Holbrook, Christopher M; Krueger, Charles C
2016-04-01
Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.
Crandall, Eric D.; Liggins, Libby; Bongaerts, Pim; Treml, Eric A.
2016-01-01
Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations. PMID:29491947
Riginos, Cynthia; Crandall, Eric D; Liggins, Libby; Bongaerts, Pim; Treml, Eric A
2016-12-01
Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations.
NASA Astrophysics Data System (ADS)
Widiatmaka, Widiatmaka; Ambarwulan, Wiwin; Firmansyah, Irman; Munibah, Khursatul; Santoso, Paulus B. K.
2015-04-01
Indonesia is the country with the 4th largest population in the worlds; the population reached more than 237 million people. With rice as the staple food for more than 95 percent of the population, there is an important role of paddy field in Indonesian food security. Actually, paddy field in Java has produced 52,6% of the total rice production in Indonesia, showing the very high dependence of Indonesia on food production from paddy fields in Java island. Karawang Regency is one of the regions in West Java Province that contribute to the national food supply, due to its high soil fertility and its high extent of paddy field. Dynamics of land use change in this region are high because of its proximity to urban area; this dynamics has led to paddy field conversion to industry and residential landuse, which in turn change the regional rice production capacity. Decreasing paddy field landuse in this region could be serve as an example case of the general phenomena which occurred in Javanese rice production region. The objective of this study were: (i) to identify the suitable area for paddy field, (ii) to modelize the decreasing of paddy field in socio-economic context of the region, and (iii) to plan the spatial priority area of paddy field protection according to model prediction. A land evaluation for paddy was completed after a soil survey, while IKONOS imagery was analyzed to delineate paddy fields. Dynamic system model of paddy field land use is built, and then based on the model built, the land area of paddy field untill 2040 in some scenarios was developped. The research results showed that the land suitability class for paddy fields in Karawang Regency ranged from very suitable (S1) to marginally suitable (S3), with various land characteristics as limiting factors. The model predicts that if the situation of paddy field land use change continues in its business as usual path, paddy field area that would exist in the region in 2040 will stay half of the recent area. Based on the model, the scenario were developed for the protection of priority area. With such scenario, paddy field remains close to the value predicted oficially. Spatial information then can play a role by presenting the scenario spatially. Combining spatial information with land suitability, priority areas of paddy field protection can be delineated. Policies that followed also then be compiled, including the location of protection. Key-words: Land evaluation, food security, spatial information
White, Lauren A; Forester, James D; Craft, Meggan E
2018-05-01
Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
NASA Astrophysics Data System (ADS)
Steyn-Ross, Moira L.; Steyn-Ross, D. A.
2016-02-01
Mean-field models of the brain approximate spiking dynamics by assuming that each neuron responds to its neighbors via a naive spatial average that neglects local fluctuations and correlations in firing activity. In this paper we address this issue by introducing a rigorous formalism to enable spatial coarse-graining of spiking dynamics, scaling from the microscopic level of a single type 1 (integrator) neuron to a macroscopic assembly of spiking neurons that are interconnected by chemical synapses and nearest-neighbor gap junctions. Spiking behavior at the single-neuron scale ℓ ≈10 μ m is described by Wilson's two-variable conductance-based equations [H. R. Wilson, J. Theor. Biol. 200, 375 (1999), 10.1006/jtbi.1999.1002], driven by fields of incoming neural activity from neighboring neurons. We map these equations to a coarser spatial resolution of grid length B ℓ , with B ≫1 being the blocking ratio linking micro and macro scales. Our method systematically eliminates high-frequency (short-wavelength) spatial modes q ⃗ in favor of low-frequency spatial modes Q ⃗ using an adiabatic elimination procedure that has been shown to be equivalent to the path-integral coarse graining applied to renormalization group theory of critical phenomena. This bottom-up neural regridding allows us to track the percolation of synaptic and ion-channel noise from the single neuron up to the scale of macroscopic population-average variables. Anticipated applications of neural regridding include extraction of the current-to-firing-rate transfer function, investigation of fluctuation criticality near phase-transition tipping points, determination of spatial scaling laws for avalanche events, and prediction of the spatial extent of self-organized macrocolumnar structures. As a first-order exemplar of the method, we recover nonlinear corrections for a coarse-grained Wilson spiking neuron embedded in a network of identical diffusively coupled neurons whose chemical synapses have been disabled. Intriguingly, we find that reblocking transforms the original type 1 Wilson integrator into a type 2 resonator whose spike-rate transfer function exhibits abrupt spiking onset with near-vertical takeoff and chaotic dynamics just above threshold.
Fish everywhere, all the time: modeling fish in the riverscape
From 2002-2006, EPA’s Western Ecology Division conducted innovative research on the population dynamics of fish within an entire stream network. Employing individual tagging and tracking technology, we examined spatial patterns of juvenile coho salmon (Oncorhynchus kisutch...
Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...
Separating spatial search and efficiency rates as components of predation risk
DeCesare, Nicholas J.
2012-01-01
Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk. PMID:22977145
Dynamical evolution and spatial mixing of multiple population globular clusters
NASA Astrophysics Data System (ADS)
Vesperini, Enrico; McMillan, Stephen L. W.; D'Antona, Francesca; D'Ercole, Annibale
2013-03-01
Numerous spectroscopic and photometric observational studies have provided strong evidence for the widespread presence of multiple stellar populations in globular clusters. In this paper, we study the long-term dynamical evolution of multiple population clusters, focusing on the evolution of the spatial distributions of the first- (FG) and second-generation (SG) stars. In previous studies, we have suggested that SG stars formed from the ejecta of FG AGB stars are expected initially to be concentrated in the cluster inner regions. Here, by means of N-body simulations, we explore the time-scales and the dynamics of the spatial mixing of the FG and the SG populations and their dependence on the SG initial concentration. Our simulations show that, as the evolution proceeds, the radial profile of the SG/FG number ratio, NSG/NFG, is characterized by three regions: (1) a flat inner part; (2) a declining part in which FG stars are increasingly dominant and (3) an outer region where the NSG/NFG profile flattens again (the NSG/NFG profile may rise slightly again in the outermost cluster regions). Until mixing is complete and the NSG/NFG profile is flat over the entire cluster, the radial variation of NSG/NFG implies that the fraction of SG stars determined by observations covering a limited range of radial distances is not, in general, equal to the SG global fraction, (NSG/NFG)glob. The distance at which NSG/NFG equals (NSG/NFG)glob is approximately between 1 and 2 cluster half-mass radii. The time-scale for complete mixing depends on the SG initial concentration, but in all cases complete mixing is expected only for clusters in advanced evolutionary phases, having lost at least 60-70 per cent of their mass due to two-body relaxation (in addition to the early FG loss due to the cluster expansion triggered by SNII ejecta and gas expulsion).The results of our simulations suggest that in many Galactic globular clusters the SG should still be more spatially concentrated than the FG.
Gonzalez, Publio; Cumbrera, Alberto; Rivero, Alina; Avila, Mario; Armién, Aníbal G.; Koster, Frederick; Glass, Gregory
2016-01-01
Background Hotspot detection and characterization has played an increasing role in understanding the maintenance and transmission of zoonotic pathogens. Identifying the specific environmental factors (or their correlates) that influence reservoir host abundance help increase understanding of how pathogens are maintained in natural systems and are crucial to identifying disease risk. However, most recent studies are performed at macro-scale and describe broad temporal patterns of population abundances. Few have been conducted at a microscale over short time periods that better capture the dynamical patterns of key populations. These finer resolution studies may better define the likelihood of local pathogen persistence. This study characterizes the landscape distribution and spatio-temporal dynamics of Oligoryzomys fulvescens (O. fulvescens), an important mammalian reservoir in Central America. Methods Information collected in a longitudinal study of rodent populations in the community of Agua Buena in Tonosí, Panama, between April 2006 and December 2009 was analyzed using non-spatial analyses (box plots) and explicit spatial statistical tests (correlograms, SADIE and LISA). A 90 node grid was built (raster format) to design a base map. The area between the nodes was 0.09 km2 and the total study area was 6.43 km2 (2.39 x 2.69 km). The temporal assessment dataset was divided into four periods for each year studied: the dry season, rainy season, and two months-long transitions between seasons (the months of April and December). Results There were heterogeneous patterns in the population densities and degrees of dispersion of O. fulvescens that varied across seasons and among years. The species typically was locally absent during the late transitional months of the season, and re-established locally in subsequent years. These populations re-occurred in the same area during the first three years but subsequently re-established further south in the final year of the study. Spatial autocorrelation analyses indicated local populations encompassed approximately 300–600 m. The borders between suitable and unsuitable habitats were sharply demarcated over short distances. Conclusion Oligoryzomys fulvescens showed a well-defined spatial pattern that evolved over time, and led to a pattern of changing aggregation. Thus, hot spots of abundance showed a general shifting pattern that helps explain the intermittent risk from pathogens transmitted by this species. This variation was associated with seasonality, as well as anthropogenic pressures that occurred with agricultural activities. These factors help define the characteristics of the occurrence, timing, intensity and duration of synanthropic populations affected by human populations and, consequently, possible exposure that local human populations experience. PMID:26894436
Armién, Blas; Ortiz, Paulo Lazaro; Gonzalez, Publio; Cumbrera, Alberto; Rivero, Alina; Avila, Mario; Armién, Aníbal G; Koster, Frederick; Glass, Gregory
2016-02-01
Hotspot detection and characterization has played an increasing role in understanding the maintenance and transmission of zoonotic pathogens. Identifying the specific environmental factors (or their correlates) that influence reservoir host abundance help increase understanding of how pathogens are maintained in natural systems and are crucial to identifying disease risk. However, most recent studies are performed at macro-scale and describe broad temporal patterns of population abundances. Few have been conducted at a microscale over short time periods that better capture the dynamical patterns of key populations. These finer resolution studies may better define the likelihood of local pathogen persistence. This study characterizes the landscape distribution and spatio-temporal dynamics of Oligoryzomys fulvescens (O. fulvescens), an important mammalian reservoir in Central America. Information collected in a longitudinal study of rodent populations in the community of Agua Buena in Tonosí, Panama, between April 2006 and December 2009 was analyzed using non-spatial analyses (box plots) and explicit spatial statistical tests (correlograms, SADIE and LISA). A 90 node grid was built (raster format) to design a base map. The area between the nodes was 0.09 km(2) and the total study area was 6.43 km(2) (2.39 x 2.69 km). The temporal assessment dataset was divided into four periods for each year studied: the dry season, rainy season, and two months-long transitions between seasons (the months of April and December). There were heterogeneous patterns in the population densities and degrees of dispersion of O. fulvescens that varied across seasons and among years. The species typically was locally absent during the late transitional months of the season, and re-established locally in subsequent years. These populations re-occurred in the same area during the first three years but subsequently re-established further south in the final year of the study. Spatial autocorrelation analyses indicated local populations encompassed approximately 300-600 m. The borders between suitable and unsuitable habitats were sharply demarcated over short distances. Oligoryzomys fulvescens showed a well-defined spatial pattern that evolved over time, and led to a pattern of changing aggregation. Thus, hot spots of abundance showed a general shifting pattern that helps explain the intermittent risk from pathogens transmitted by this species. This variation was associated with seasonality, as well as anthropogenic pressures that occurred with agricultural activities. These factors help define the characteristics of the occurrence, timing, intensity and duration of synanthropic populations affected by human populations and, consequently, possible exposure that local human populations experience.
The effects of landscape modifications on the long-term persistence of animal populations.
Nabe-Nielsen, Jacob; Sibly, Richard M; Forchhammer, Mads C; Forbes, Valery E; Topping, Christopher J
2010-01-28
The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.
Monitoring survival rates of landbirds at varying spatial scales: An application of the MAPS Program
Rosenberg, D.K.; DeSante, D.F.; Hines, J.E.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry
2000-01-01
Survivorship is a primary demographic parameter affecting population dynamics, and thus trends in species abundance. The Monitoring Avian Productivity and Survivorship (MAPS) program is a cooperative effort designed to monitor landbird demographic parameters. A principle goal of MAPS is to estimate annual survivorship and identify spatial patterns and temporal trends in these rates. We evaluated hypotheses of spatial patterns in survival rates among a collection of neighboring sampling sites, such as within national forests, among biogeographic provinces, and between breeding populations that winter in either Central or South America, and compared these geographic-specific models to a model of a common survival rate among all sampling sites. We used data collected during 1992-1995 from Swainson's Thrush (Cathorus ustulatus) populations in the western region of the United States. We evaluated the ability to detect spatial and temporal patterns of survivorship with simulated data. We found weak evidence of spatial differences in survival rates at the local scale of 'location,' which typically contained 3 mist-netting stations. There was little evidence of differences in survival rates among biogeographic provinces or between populations that winter in either Central or South America. When data were pooled for a regional estimate of survivorship, the percent relative bias due to pooling 'locations' was 12 years of monitoring. Detection of spatial patterns and temporal trends in survival rates from local to regional scales will provide important information for management and future research directed toward conservation of landbirds.
Grant, Evan H. Campbell; Zipkin, Elise; Scott, Sillett T.; Chandler, Richard; Royle, J. Andrew
2014-01-01
Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.
Reproductive responses to spatial and temporal prey availability in a coastal Arctic fox population.
Eide, Nina E; Stien, Audun; Prestrud, Pål; Yoccoz, Nigel G; Fuglei, Eva
2012-05-01
1. Input of external subsidies in the Arctic may have substantial effects on predator populations that otherwise would have been limited by low local primary productivity. 2. We explore life-history traits, age-specific fecundity, litter sizes and survival, and the population dynamics of an Arctic fox (Vulpes lagopus) population to explore the influence of the spatial distribution and temporal availability of its main prey; including both resident and migrating (external) prey resources. 3. This study reveals that highly predictable cross-boundary subsidies from the marine food web, acting through seasonal access to seabirds, sustain larger local Arctic fox populations. Arctic fox dens located close to the coast in Svalbard were found to have higher occupancy rates, as expected from both high availability and high temporal and spatial predictability of prey resources (temporally stable external subsidies). Whereas the occupancy rate of inland dens varied between years in relation to the abundance of reindeer carcasses (temporally varying resident prey). 4. With regard to demography, juvenile Arctic foxes in Svalbard have lower survival rates and a high age of first reproduction compared with other populations. We suggest this may be caused by a lack of unoccupied dens and a saturated population. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.
Spatial self-organization in hybrid models of multicellular adhesion
NASA Astrophysics Data System (ADS)
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
Farine, Damien R.; Firth, Josh A.; Aplin, Lucy M.; Crates, Ross A.; Culina, Antica; Garroway, Colin J.; Hinde, Camilla A.; Kidd, Lindall R.; Milligan, Nicole D.; Psorakis, Ioannis; Radersma, Reinder; Verhelst, Brecht; Voelkl, Bernhard; Sheldon, Ben C.
2015-01-01
Both social and ecological factors influence population process and structure, with resultant consequences for phenotypic selection on individuals. Understanding the scale and relative contribution of these two factors is thus a central aim in evolutionary ecology. In this study, we develop a framework using null models to identify the social and spatial patterns that contribute to phenotypic structure in a wild population of songbirds. We used automated technologies to track 1053 individuals that formed 73 737 groups from which we inferred a social network. Our framework identified that both social and spatial drivers contributed to assortment in the network. In particular, groups had a more even sex ratio than expected and exhibited a consistent age structure that suggested local association preferences, such as preferential attachment or avoidance. By contrast, recent immigrants were spatially partitioned from locally born individuals, suggesting differential dispersal strategies by phenotype. Our results highlight how different scales of social decision-making, ranging from post-natal dispersal settlement to fission–fusion dynamics, can interact to drive phenotypic structure in animal populations. PMID:26064644
Hydration dynamics promote bacterial coexistence on rough surfaces
Wang, Gang; Or, Dani
2013-01-01
Identification of mechanisms that promote and maintain the immense microbial diversity found in soil is a central challenge for contemporary microbial ecology. Quantitative tools for systematic integration of complex biophysical and trophic processes at spatial scales, relevant for individual cell interactions, are essential for making progress. We report a modeling study of competing bacterial populations cohabiting soil surfaces subjected to highly dynamic hydration conditions. The model explicitly tracks growth, motion and life histories of individual bacterial cells on surfaces spanning dynamic aqueous networks that shape heterogeneous nutrient fields. The range of hydration conditions that confer physical advantages for rapidly growing species and support competitive exclusion is surprisingly narrow. The rapid fragmentation of soil aqueous phase under most natural conditions suppresses bacterial growth and cell dispersion, thereby balancing conditions experienced by competing populations with diverse physiological traits. In addition, hydration fluctuations intensify localized interactions that promote coexistence through disproportional effects within densely populated regions during dry periods. Consequently, bacterial population dynamics is affected well beyond responses predicted from equivalent and uniform hydration conditions. New insights on hydration dynamics could be considered in future designs of soil bioremediation activities, affect longevity of dry food products, and advance basic understanding of bacterial diversity dynamics and its role in global biogeochemical cycles. PMID:23051694
Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments.
Lambert, Guillaume; Vyawahare, Saurabh; Austin, Robert H
2014-08-06
One of the predictions of game theory is that cooperative behaviours are vulnerable to exploitation by selfish individuals, but this result seemingly contradicts the survival of cooperation observed in nature. In this review, we will introduce game theoretical concepts that lead to this conclusion and show how the spatial competition dynamics between microorganisms can be used to model the survival and maintenance of cooperation. In particular, we focus on how Escherichia coli bacteria with a growth advantage in stationary phase (GASP) phenotype maintain a proliferative phenotype when faced with overcrowding to gain a fitness advantage over wild-type populations. We review recent experimental approaches studying the growth dynamics of competing GASP and wild-type strains of E. coli inside interconnected microfabricated habitats and use a game theoretical approach to analyse the observed inter-species interactions. We describe how the use of evolutionary game theory and the ideal free distribution accurately models the spatial distribution of cooperative and selfish individuals in spatially heterogeneous environments. Using bacteria as a model system of cooperative and selfish behaviours may lead to a better understanding of the competition dynamics of other organisms-including tumour-host interactions during cancer development and metastasis.
Identifying spatio-temporal dynamics of Ebola in Sierra Leone using virus genomes
Proctor, Joshua L.
2017-01-01
Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources. Despite recent progress in analysing and modelling EBOV epidemiological data, a complete characterization of the spatio-temporal spread of Ebola cases remains a challenge. In this work, we offer a novel perspective on the EBOV epidemic in Sierra Leone that uses individual virus genome sequences to inform population-level, spatial models. Calibrated to phylogenetic linkages of virus genomes, these spatial models provide unique insight into the disease mobility of EBOV in Sierra Leone without the need for human mobility data. Consistent with other investigations, our results show that the spread of EBOV during the beginning and middle portions of the epidemic strongly depended on the size of and distance between populations. Our phylodynamic analysis also revealed a change in model preference towards a spatial model with power-law characteristics in the latter portion of the epidemic, correlated with the timing of major intervention campaigns. More generally, we believe this framework, pairing molecular diagnostics with a dynamic model selection procedure, has the potential to be a powerful forecasting tool along with offering operationally relevant guidance for surveillance and sampling strategies during an epidemic. PMID:29187639
de Vargas Roditi, Laura; Claassen, Manfred
2015-08-01
Novel technological developments enable single cell population profiling with respect to their spatial and molecular setup. These include single cell sequencing, flow cytometry and multiparametric imaging approaches and open unprecedented possibilities to learn about the heterogeneity, dynamics and interplay of the different cell types which constitute tissues and multicellular organisms. Statistical and dynamic systems theory approaches have been applied to quantitatively describe a variety of cellular processes, such as transcription and cell signaling. Machine learning approaches have been developed to define cell types, their mutual relationships, and differentiation hierarchies shaping heterogeneous cell populations, yielding insights into topics such as, for example, immune cell differentiation and tumor cell type composition. This combination of experimental and computational advances has opened perspectives towards learning predictive multi-scale models of heterogeneous cell populations. Copyright © 2014 Elsevier Ltd. All rights reserved.
What can we learn from resource pulses?
Yang, Louie H; Bastow, Justin L; Spence, Kenneth O; Wright, Amber N
2008-03-01
An increasing number of studies in a wide range of natural systems have investigated how pulses of resource availability influence ecological processes at individual, population, and community levels. Taken together, these studies suggest that some common processes may underlie pulsed resource dynamics in a wide diversity of systems. Developing a common framework of terms and concepts for the study of resource pulses may facilitate greater synthesis among these apparently disparate systems. Here, we propose a general definition of the resource pulse concept, outline some common patterns in the causes and consequences of resource pulses, and suggest a few key questions for future investigations. We define resource pulses as episodes of increased resource availability in space and time that combine low frequency (rarity), large magnitude (intensity), and short duration (brevity), and emphasize the importance of considering resource pulses at spatial and temporal scales relevant to specific resource-onsumer interactions. Although resource pulses are uncommon events for consumers in specific systems, our review of the existing literature suggests that pulsed resource dynamics are actually widespread phenomena in nature. Resource pulses often result from climatic and environmental factors, processes of spatiotemporal accumulation and release, outbreak population dynamics, or a combination of these factors. These events can affect life history traits and behavior at the level of individual consumers, numerical responses at the population level, and indirect effects at the community level. Consumers show strategies for utilizing ephemeral resources opportunistically, reducing resource variability by averaging over larger spatial scales, and tolerating extended interpulse periods of reduced resource availability. Resource pulses can also create persistent effects in communities through several mechanisms. We suggest that the study of resource pulses provides opportunities to understand the dynamics of many specific systems, and may also contribute to broader ecological questions at individual, population, and community levels.
IMPORTANCE OF MOVEMENT VARIES IN STATIC AND DYNAMIC LANDSCAPES
The relative sensitivity of spatially explicit population models (SEPMs) to movement parameters is a topic of ongoing debate among theoretical ecologists. In this study, we add additional realism to this debate by examining a SEPM's sensitivity to dispersal ability in static vs....
RELATIONSHIPS OF NATURAL ENEMIES AND NON-PREY FOODS
USDA-ARS?s Scientific Manuscript database
There are very few entomophagous species so maladapted as to rely on prey as their sole nutritional resource. Although a rich source of nutrients, prey/host availability to predators and parasitoids is restricted temporally by ephemeral population dynamics, spatial differences in microclimate, struc...
Morales, Y.; Weber, L.J.; Mynett, A.E.; Newton, T.J.
2006-01-01
A model for simulating freshwater mussel population dynamics is presented. The model is a hydroinformatics tool that integrates principles from ecology, river hydraulics, fluid mechanics and sediment transport, and applies the individual-based modelling approach for simulating population dynamics. The general model layout, data requirements, and steps of the simulation process are discussed. As an illustration, simulation results from an application in a 10 km reach of the Upper Mississippi River are presented. The model was used to investigate the spatial distribution of mussels and the effects of food competition in native unionid mussel communities, and communities infested by Dreissena polymorpha, the zebra mussel. Simulation results were found to be realistic and coincided with data obtained from the literature. These results indicate that the model can be a useful tool for assessing the potential effects of different stressors on long-term population dynamics, and consequently, may improve the current understanding of cause and effect relationships in freshwater mussel communities. ?? 2006 Elsevier B.V. All rights reserved.
Modeling Global Spatial-Temporal Evolution of Society: Hyperbolic Growth and Historical Cycles
NASA Astrophysics Data System (ADS)
Kurkina, E. S.
2011-09-01
The global historical processes are under consideration; and laws of global evolution of the world community are studied. The world community is considered as a united complex self-developing and self-organizing system. It supposed that the main driving force of social-economical evolution was the positive feedback between the population size and the level of technological development, which was a cause of growth in blow-up regime both of population and of global economic indexes. The study is supported by the results of mathematical modeling founded on a nonlinear heat equation with a source. Every social-economical epoch characterizes by own specific spatial distributed structures. So the global dynamics of world community during the whole history is investigated throughout the prism of the developing of spatial-temporal structures. The model parameters have been chosen so that 1) total population follows stable hyperbolic growth, consistently with the demographic data; 2) the evolution of the World-System goes through 11 stages corresponding to the main historical epochs.
Group Threat and Policy Change: The Spatial Dynamics of Prohibition Politics, 1890-1919.
Andrews, Kenneth T; Seguin, Charles
2015-09-01
The authors argue that group threat is a key driver of the adoption of new and controversial policies. Conceptualizing threat in spatial terms, they argue that group threat is activated through the joint occurrence of (1) proximity to threatening groups and (2) the population density of threatened groups. By analyzing the adoption of county and state "dry laws" banning alcohol from 1890 to 1919, they first show that prohibition victories were driven by the relative strength of supportive constituencies such as native whites and rural residents, vis-à-vis opponents such as Irish, Italian, or German immigrants or Catholics. Second, they show that threat contributed to prohibition victories: counties bordering large immigrant or urban populations, which did not themselves contain similar populations, were more likely to adopt dry laws. Threat arises primarily from interactions between spatially proximate units at the local level, and therefore higher-level policy change is not reducible to the variables driving local policy.
Visualizing diurnal population change in urban areas for emergency management.
Kobayashi, Tetsuo; Medina, Richard M; Cova, Thomas J
2011-01-01
There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.
Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons
Wilson, Hugh R.; Cowan, Jack D.
1972-01-01
Coupled nonlinear differential equations are derived for the dynamics of spatially localized populations containing both excitatory and inhibitory model neurons. Phase plane methods and numerical solutions are then used to investigate population responses to various types of stimuli. The results obtained show simple and multiple hysteresis phenomena and limit cycle activity. The latter is particularly interesting since the frequency of the limit cycle oscillation is found to be a monotonic function of stimulus intensity. Finally, it is proved that the existence of limit cycle dynamics in response to one class of stimuli implies the existence of multiple stable states and hysteresis in response to a different class of stimuli. The relation between these findings and a number of experiments is discussed. PMID:4332108
Yang, Yuyin; Dai, Yu; Li, Ningning; Li, Bingxin; Xie, Shuguang; Liu, Yong
2017-02-01
Anaerobic ammonium-oxidizing (anammox) process can play an important role in freshwater nitrogen cycle. However, the distribution of anammox bacteria in freshwater lake and the associated environmental factors remain essentially unclear. The present study investigated the temporal and spatial dynamics of sediment anammox bacterial populations in eutrotrophic Dianchi Lake and mesotrophic Erhai Lake on the Yunnan Plateau (southwestern China). The remarkable spatial change of anammox bacterial abundance was found in Dianchi Lake, while the relatively slight spatial shift occurred in Erhai Lake. Dianchi Lake had greater anammox bacterial abundance than Erhai Lake. In both Dianchi Lake and Erhai Lake, anammox bacteria were much more abundant in summer than in spring. Anammox bacterial community richness, diversity, and structure in these two freshwater lakes were subjected to temporal and spatial variations. Sediment anammox bacterial communities in Dianchi Lake and Erhai Lake were dominated by Candidatus Brocadia and a novel phylotype followed by Candidatus Kuenenia; however, these two lakes had distinct anammox bacterial community structure. In addition, trophic status determined sediment anammox bacterial community structure.
Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II
DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.
2017-01-01
Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.
Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707
Tournebize, Rémi; Manel, Stéphanie; Vigouroux, Yves; Munoz, François; de Kochko, Alexandre
2017-01-01
Past climate fluctuations shaped the population dynamics of organisms in space and time, and have impacted their present intra-specific genetic structure. Demo-genetic modelling allows inferring the way past demographic and migration dynamics have determined this structure. Amborella trichopoda is an emblematic relict plant endemic to New Caledonia, widely distributed in the understory of non-ultramafic rainforests. We assessed the influence of the last glacial climates on the demographic history and the paleo-distribution of 12 Amborella populations covering the whole current distribution. We performed coalescent genetic modelling of these dynamics, based on both whole-genome resequencing and microsatellite genotyping data. We found that the two main genetic groups of Amborella were shaped by the divergence of two ancestral populations during the last glacial maximum. From 12,800 years BP, the South ancestral population has expanded 6.3-fold while the size of the North population has remained stable. Recent asymmetric gene flow between the groups further contributed to the phylogeographical pattern. Spatially explicit coalescent modelling allowed us to estimate the location of ancestral populations with good accuracy (< 22 km) and provided indications regarding the mid-elevation pathways that facilitated post-glacial expansion. PMID:28820899
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kostova, T; Carlsen, T
We present a study, based on simulations with SERDYCA, a spatially-explicit individual based model of rodent dynamics, on the connection between population persistence and the presence of inhomogeneities in the habitat. We are specifically interested on the effect that inhomogeneities that do not fragment the environment, have on population persistence. Our results suggest that a certain percentage of inhomogeneities can increase the average time to extinction of the population. Inhomogeneities decrease the population density and can increase the ratio of juveniles in the population thus providing a better chance for the population to restore itself after a severe period withmore » critically low population density. We call this the ''inhomogeneity localization effect''.« less
Spatio-Temporal Patterning in Primary Motor Cortex at Movement Onset.
Best, Matthew D; Suminski, Aaron J; Takahashi, Kazutaka; Brown, Kevin A; Hatsopoulos, Nicholas G
2017-02-01
Voluntary movement initiation involves the engagement of large populations of motor cortical neurons around movement onset. Despite knowledge of the temporal dynamics that lead to movement, the spatial structure of these dynamics across the cortical surface remains unknown. In data from 4 rhesus macaques, we show that the timing of attenuation of beta frequency local field potential oscillations, a correlate of locally activated cortex, forms a spatial gradient across primary motor cortex (MI). We show that these spatio-temporal dynamics are recapitulated in the engagement order of ensembles of MI neurons. We demonstrate that these patterns are unique to movement onset and suggest that movement initiation requires a precise spatio-temporal sequential activation of neurons in MI. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Effects of developmental variability on the dynamics and self-organization of cell populations
NASA Astrophysics Data System (ADS)
Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard
2017-11-01
We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.
Noble, Andrew E.; Machta, Jonathan; Hastings, Alan
2015-01-01
Understanding the synchronization of oscillations across space is fundamentally important to many scientific disciplines. In ecology, long-range synchronization of oscillations in spatial populations may elevate extinction risk and signal an impending catastrophe. The prevailing assumption is that synchronization on distances longer than the dispersal scale can only be due to environmental correlation (the Moran effect). In contrast, we show how long-range synchronization can emerge over distances much longer than the length scales of either dispersal or environmental correlation. In particular, we demonstrate that the transition from incoherence to long-range synchronization of two-cycle oscillations in noisy spatial population models is described by the Ising universality class of statistical physics. This result shows, in contrast to all previous work, how the Ising critical transition can emerge directly from the dynamics of ecological populations. PMID:25851364
Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan
2016-01-01
Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.
Latitude delineates patterns of biogeography in terrestrial Streptomyces.
Choudoir, Mallory J; Doroghazi, James R; Buckley, Daniel H
2016-12-01
The biogeography of Streptomyces was examined at regional spatial scales to identify factors that govern patterns of microbial diversity. Streptomyces are spore forming filamentous bacteria which are widespread in soil. Streptomyces strains were isolated from perennial grass habitats sampled across a spatial scale of more than 6000 km. Previous analysis of this geographically explicit culture collection provided evidence for a latitudinal diversity gradient in Streptomyces species. Here the hypothesis that this latitudinal diversity gradient is a result of evolutionary dynamics associated with historical demographic processes was evaluated. Historical demographic phenomena have genetic consequences that can be evaluated through analysis of population genetics. Population genetic approaches were applied to analyze population structure in six of the most numerically abundant and geographically widespread Streptomyces phylogroups from our culture collection. Streptomyces population structure varied at regional spatial scales, and allelic diversity correlated with geographic distance. In addition, allelic diversity and gene flow are partitioned by latitude. Finally, it was found that nucleotide diversity within phylogroups was negatively correlated with latitude. These results indicate that phylogroup diversification is constrained by dispersal limitation at regional spatial scales, and they are consistent with the hypothesis that historical demographic processes have influenced the contemporary biogeography of Streptomyces. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.
Statistical Physics of Population Genetics in the Low Population Size Limit
NASA Astrophysics Data System (ADS)
Atwal, Gurinder
The understanding of evolutionary processes lends itself naturally to theory and computation, and the entire field of population genetics has benefited greatly from the influx of methods from applied mathematics for decades. However, in spite of all this effort, there are a number of key dynamical models of evolution that have resisted analytical treatment. In addition, modern DNA sequencing technologies have magnified the amount of genetic data available, revealing an excess of rare genetic variants in human genomes, challenging the predictions of conventional theory. Here I will show that methods from statistical physics can be used to model the distribution of genetic variants, incorporating selection and spatial degrees of freedom. In particular, a functional path-integral formulation of the Wright-Fisher process maps exactly to the dynamics of a particle in an effective potential, beyond the mean field approximation. In the small population size limit, the dynamics are dominated by instanton-like solutions which determine the probability of fixation in short timescales. These results are directly relevant for understanding the unusual genetic variant distribution at moving frontiers of populations.
Invasive advance of an advantageous mutation: nucleation theory.
O'Malley, Lauren; Basham, James; Yasi, Joseph A; Korniss, G; Allstadt, Andrew; Caraco, Thomas
2006-12-01
For sedentary organisms with localized reproduction, spatially clustered growth drives the invasive advance of a favorable mutation. We model competition between two alleles where recurrent mutation introduces a genotype with a rate of local propagation exceeding the resident's rate. We capture ecologically important properties of the rare invader's stochastic dynamics by assuming discrete individuals and local neighborhood interactions. To understand how individual-level processes may govern population patterns, we invoke the physical theory for nucleation of spatial systems. Nucleation theory discriminates between single-cluster and multi-cluster dynamics. A sufficiently low mutation rate, or a sufficiently small environment, generates single-cluster dynamics, an inherently stochastic process; a favorable mutation advances only if the invader cluster reaches a critical radius. For this mode of invasion, we identify the probability distribution of waiting times until the favored allele advances to competitive dominance, and we ask how the critical cluster size varies as propagation or mortality rates vary. Increasing the mutation rate or system size generates multi-cluster invasion, where spatial averaging produces nearly deterministic global dynamics. For this process, an analytical approximation from nucleation theory, called Avrami's Law, describes the time-dependent behavior of the genotype densities with remarkable accuracy.
Effects of habitat fragmentation on passerine birds breeding in Intermountain shrubsteppe
Knick, S.T.; Rotenberry, J.T.
2002-01-01
Habitat fragmentation and loss strongly influence the distribution and abundance of passerine birds breeding in Intermountain shrubsteppe. Wildfires, human activities, and change in vegetation communities often are synergistic in these systems and can result in radical conversion from shrubland to grasslands dominated by exotic annuals at large temporal and spatial scales from which recovery to native conditions is unlikely. As a result, populations of 5 of the 12 species in our review of Intermountain shrubsteppe birds are undergoing significant declines; 5 species are listed as at-risk or as candidates for protection in at least one state. The process by which fragmentation affects bird distributions in these habitats remains unknown because most research has emphasized the detection of population trends and patterns of habitat associations at relatively large spatial scales. Our research indicates that the distribution of shrubland-obligate species, such as Brewer's Sparrows (Spizella breweri), Sage Sparrows (Amphispiza belli), and Sage Thrashers (Oreoscoptes montanus), was highly sensitive to fragmentation of shrublands at spatial scales larger than individual home ranges. In contrast, the underlying mechanisms for both habitat change and bird population dynamics may operate independently of habitat boundaries. We propose alternative, but not necessarily exclusive, mechanisms to explain the relationship between habitat fragmentation and bird distribution and abundance. Fragmentation might influence productivity through differences in breeding density, nesting success, or predation. However, local and landscape variables were not significant determinants either of success, number fledged, or probability of predation or parasitism (although our tests had relatively low statistical power). Alternatively, relative absence of natal philopatry and redistribution by individuals among habitats following fledging or post-migration could account for the pattern of distribution and abundance. Thus, boundary dynamics may be important in determining the distribution of shrubland-obligate species but insignificant relative to the mechanisms causing the pattern of habitat and bird distribution. Because of the dichotomy in responses, Intermountain shrubsteppe systems present a unique challenge in understanding how landscape composition, configuration, and change influence bird population dynamics.
A necessary condition for dispersal driven growth of populations with discrete patch dynamics.
Guiver, Chris; Packman, David; Townley, Stuart
2017-07-07
We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Temporal and Spatial Dynamics of Diel-Cycling Hypoxia in Four Northern Gulf of Mexico Estuaries
Eutrophication of coastal ecosystems has accelerated in recent decades due to population growth and associated nutrient pollution, resulting in increased incidence of hypoxia. Shallow and highly productive estuaries and embayments are particularly susceptible to diel-cycling hypo...
The effect of travel loss on evolutionarily stable distributions of populations in space
DeAngelis, D.L.; Wolkowicz, G.S.K.; Lou, Y.; Jiang, Y.; Novak, M.; Svanback, R.; Araujo, M.S.; Jo, Y.S.; Cleary, E.A.
2011-01-01
A key assumption of the ideal free distribution (IFD) is that there are no costs in moving between habitat patches. However, because many populations exhibit more or less continuous population movement between patches and traveling cost is a frequent factor, it is important to determine the effects of costs on expected population movement patterns and spatial distributions. We consider a food chain (tritrophic or bitrophic) in which one species moves between patches, with energy cost or mortality risk in movement. In the two-patch case, assuming forced movement in one direction, an evolutionarily stable strategy requires bidirectional movement, even if costs during movement are high. In the N-patch case, assuming that at least one patch is linked bidirectionally to all other patches, optimal movement rates can lead to source-sink dynamics where patches with negative growth rates are maintained by other patches with positive growth rates. As well, dispersal between patches is not balanced (even in the two-patch case), leading to a deviation from the IFD. Our results indicate that cost-associated forced movement can have important consequences for spatial metapopulation dynamics. Relevance to marine reserve design and the study of stream communities subject to drift is discussed. ?? 2011 by The University of Chicago.
Decision Accuracy and the Role of Spatial Interaction in Opinion Dynamics
NASA Astrophysics Data System (ADS)
Torney, Colin J.; Levin, Simon A.; Couzin, Iain D.
2013-04-01
The opinions and actions of individuals within interacting groups are frequently determined by both social and personal information. When sociality (or the pressure to conform) is strong and individual preferences are weak, groups will remain cohesive until a consensus decision is reached. When group decisions are subject to a bias, representing for example private information known by some members of the population or imperfect information known by all, then the accuracy achieved for a fixed level of bias will increase with population size. In this work we determine how the scaling between accuracy and group size can be related to the microscopic properties of the decision-making process. By simulating a spatial model of opinion dynamics we show that the relationship between the instantaneous fraction of leaders in the population ( L), system size ( N), and accuracy depends on the frequency of individual opinion switches and the level of population viscosity. When social mixing is slow, and individual opinion changes are frequent, accuracy is determined by the absolute number of informed individuals. As mixing rates increase, or the rate of opinion updates decrease, a transition occurs to a regime where accuracy is determined by the value of L√{ N}. We investigate the transition between different scaling regimes analytically by examining a well-mixed limit.
NASA Astrophysics Data System (ADS)
Aubrecht, Christoph; Steinnocher, Klaus; Humer, Heinrich; Huber, Hermann
2014-05-01
In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J.K., Hunter, G.J. (2007) A spatio-temporal population model to support risk assessment and damage analysis for decision-making. International Journal of Geographical Information Science, 21(8), 935-953. Aubrecht, C., Fuchs, S., Neuhold, C. (2013a) Spatio-temporal aspects and dimensions in integrated disaster risk management. Natural Hazards, 68(3), 1205-1216. Aubrecht, C., Özceylan, D., Steinnocher, K., Freire, S. (2013b) Multi-level geospatial modeling of human exposure patterns and vulnerability indicators. Natural Hazards, 68(1), 147-163. Bhaduri, B. (2008) Population distribution during the day. In S. Shekhar & X. Hui, eds., Encyclopedia of GIS. Springer US, 880-885. Cockings, S., Martin, D. & Leung, S. (2010) Population 24/7: building space-time specific population surface models. In M. Haklay, J. Morley, & H. Rahemtulla, eds., Proceedings of the GIS Research UK 18th Annual conference. GISRUK 2010. London, UK, 41-47. Freire, S., Aubrecht, C. (2012) Integrating population dynamics into mapping human exposure to seismic hazard. Natural Hazards and Earth System Sciences, 12(11), 3533-3543.
Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin
2017-07-31
Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.
Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces
Kim, Minsu; Or, Dani
2016-01-01
Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803
Expansion Under Climate Change: The Genetic Consequences.
Garnier, Jimmy; Lewis, Mark A
2016-11-01
Range expansion and range shifts are crucial population responses to climate change. Genetic consequences are not well understood but are clearly coupled to ecological dynamics that, in turn, are driven by shifting climate conditions. We model a population with a deterministic reaction-diffusion model coupled to a heterogeneous environment that develops in time due to climate change. We decompose the resulting travelling wave solution into neutral genetic components to analyse the spatio-temporal dynamics of its genetic structure. Our analysis shows that range expansions and range shifts under slow climate change preserve genetic diversity. This is because slow climate change creates range boundaries that promote spatial mixing of genetic components. Mathematically, the mixing leads to so-called pushed travelling wave solutions. This mixing phenomenon is not seen in spatially homogeneous environments, where range expansion reduces genetic diversity through gene surfing arising from pulled travelling wave solutions. However, the preservation of diversity is diminished when climate change occurs too quickly. Using diversity indices, we show that fast expansions and range shifts erode genetic diversity more than slow range expansions and range shifts. Our study provides analytical insight into the dynamics of travelling wave solutions in heterogeneous environments.
Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus
Talbi, Chiraz; Lemey, Philippe; Suchard, Marc A.; Abdelatif, Elbia; Elharrak, Mehdi; Jalal, Nourlil; Faouzi, Abdellah; Echevarría, Juan E.; Vazquez Morón, Sonia; Rambaut, Andrew; Campiz, Nicholas; Tatem, Andrew J.; Holmes, Edward C.; Bourhy, Hervé
2010-01-01
Understanding the role of humans in the dispersal of predominately animal pathogens is essential for their control. We used newly developed Bayesian phylogeographic methods to unravel the dynamics and determinants of the spread of dog rabies virus (RABV) in North Africa. Each of the countries studied exhibited largely disconnected spatial dynamics with major geo-political boundaries acting as barriers to gene flow. Road distances proved to be better predictors of the movement of dog RABV than accessibility or raw geographical distance, with occasional long distance and rapid spread within each of these countries. Using simulations that bridge phylodynamics and spatial epidemiology, we demonstrate that the contemporary viral distribution extends beyond that expected for RABV transmission in African dog populations. These results are strongly supportive of human-mediated dispersal, and demonstrate how an integrated phylogeographic approach will turn viral genetic data into a powerful asset for characterizing, predicting, and potentially controlling the spatial spread of pathogens. PMID:21060816
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 approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075
Paukert, C.P.; Makinster, A.S.
2009-01-01
We investigated the spatial variation of flathead catfish (Pylodictis olivaris) relative abundance and growth in the 274 km long Kansas River to determine if population dynamics of catfish are related to urbanization. Electrofishing was conducted at 462 random sites throughout the river in summer, 2005-2006 to collect fish. Relative abundance of age 1 fish (???200mm), subadult (>200-400mm) and adult fish (>400 mm) ranged from 0.34 to 14.67 fish h-1, mean length at age 1 was 165 (range: 128-195) mm total length (TL) and mean length at age 3 was 376 mm TL (range: 293-419mm TL). The proportion of land use within 200 m of the river edge was between 0 and 0.54 urban. River reaches with high relative abundance of age 1 flathead catfish had high relative abundance of subadult and adult catfish. River reaches with fast flathead catfish growth to age 1 had fast growth to age 3. High urban land use and riprap in the riparian area were evident in river reaches near the heavily populated Kansas City and Topeka, Kansas, USA. Reaches with increased number of log jams and islands had decreased riparian agriculture. Areas of low urbanization had faster flathead catfish growth (r = 0.67, p = 0.005). Relative abundance of flathead catfish was higher in more agricultural areas (r = -0.57, p = 0.02). Changes in land use in riverine environments may alter population dynamics of a fish species within a river. Spatial differences in population dynamics need to be considered when evaluating riverine fish populations. Published in 2008 by John Wiley & Sons Ltd.
Exploring space-time structure of human mobility in urban space
NASA Astrophysics Data System (ADS)
Sun, J. B.; Yuan, J.; Wang, Y.; Si, H. B.; Shan, X. M.
2011-03-01
Understanding of human mobility in urban space benefits the planning and provision of municipal facilities and services. Due to the high penetration of cell phones, mobile cellular networks provide information for urban dynamics with a large spatial extent and continuous temporal coverage in comparison with traditional approaches. The original data investigated in this paper were collected by cellular networks in a southern city of China, recording the population distribution by dividing the city into thousands of pixels. The space-time structure of urban dynamics is explored by applying Principal Component Analysis (PCA) to the original data, from temporal and spatial perspectives between which there is a dual relation. Based on the results of the analysis, we have discovered four underlying rules of urban dynamics: low intrinsic dimensionality, three categories of common patterns, dominance of periodic trends, and temporal stability. It implies that the space-time structure can be captured well by remarkably few temporal or spatial predictable periodic patterns, and the structure unearthed by PCA evolves stably over time. All these features play a critical role in the applications of forecasting and anomaly detection.
Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics
NASA Astrophysics Data System (ADS)
Roca, Carlos P.; Cuesta, José A.; Sánchez, Angel
2009-12-01
Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines.
Mass and energy budgets of animals: Behavioral and ecological implications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Porter, W.P.
1991-11-01
The two major aims of our lab are as follows: First, to develop and field-test general mechanistic models that predict animal life history characteristics as influenced by climate and the physical, physiological behavioral characteristics of species. This involves: understanding how animal time and energy budgets are affected by climate and animal properties; predicting growth and reproductive potential from time and energy budgets; predicting mortality based on climate and time and energy budgets; and linking these individual based models to population dynamics. Second to conduct empirical studies of animal physiological ecology, particularly the effects of temperature on time and energy budgets.more » The physiological ecology of individual animals is the key link between the physical environment and population-level phenomena. We address the macroclimate to microclimate linkage on a broad spatial scale; address the links between individuals and population dynamics for lizard species; test the endotherm energetics and behavior model using beaver; address the spatial variation in climate and its effects on individual energetics, growth and reproduction; and address patchiness in the environment and constraints they may impose on individual energetics, growth and reproduction. These projects are described individually in the following section. 24 refs., 9 figs.« less
Heterogeneity, Mixing, and the Spatial Scales of Mosquito-Borne Pathogen Transmission
Perkins, T. Alex; Scott, Thomas W.; Le Menach, Arnaud; Smith, David L.
2013-01-01
The Ross-Macdonald model has dominated theory for mosquito-borne pathogen transmission dynamics and control for over a century. The model, like many other basic population models, makes the mathematically convenient assumption that populations are well mixed; i.e., that each mosquito is equally likely to bite any vertebrate host. This assumption raises questions about the validity and utility of current theory because it is in conflict with preponderant empirical evidence that transmission is heterogeneous. Here, we propose a new dynamic framework that is realistic enough to describe biological causes of heterogeneous transmission of mosquito-borne pathogens of humans, yet tractable enough to provide a basis for developing and improving general theory. The framework is based on the ecological context of mosquito blood meals and the fine-scale movements of individual mosquitoes and human hosts that give rise to heterogeneous transmission. Using this framework, we describe pathogen dispersion in terms of individual-level analogues of two classical quantities: vectorial capacity and the basic reproductive number, . Importantly, this framework explicitly accounts for three key components of overall heterogeneity in transmission: heterogeneous exposure, poor mixing, and finite host numbers. Using these tools, we propose two ways of characterizing the spatial scales of transmission—pathogen dispersion kernels and the evenness of mixing across scales of aggregation—and demonstrate the consequences of a model's choice of spatial scale for epidemic dynamics and for estimation of , both by a priori model formulas and by inference of the force of infection from time-series data. PMID:24348223
Local interactions lead to pathogen-driven change to host population dynamics.
Boots, Michael; Childs, Dylan; Reuman, Daniel C; Mealor, Michael
2009-10-13
Individuals tend to interact more strongly with nearby individuals or within particular social groups. Recent theoretical advances have demonstrated that these within-population relationships can have fundamental implications for ecological and evolutionary dynamics. In particular, contact networks are crucial to the spread and evolution of disease. However, the theory remains largely untested experimentally. Here, we manipulate habitat viscosity and thereby the frequency of local interactions in an insect-pathogen model system in which the virus had previously been shown to have little effect on host population dynamics. At high viscosity, the pathogen caused the collapse of dominant and otherwise stable host generation cycles. Modeling shows that this collapse can be explained by an increase in the frequency of intracohort interactions relative to intercohort interactions, leading to more disease transmission. Our work emphasizes that spatial structure can subtly mediate intraspecific competition and the effects of natural enemies. A decrease in dispersal in a population may actually (sometimes rather counterintuitively) intensify the effects of parasites. Broadly, because anthropological and environmental change often cause changes in population mixing, our work highlights the potential for dramatic changes in the effects of parasites on host populations.
Farm-scale variation of soil quality indices and association with edaphic properties
USDA-ARS?s Scientific Manuscript database
Soil organisms are indicators of dynamic soil quality because their community structure and population density are sensitive to management changes. However, edaphic properties can also affect soil organisms and high spatial variability can confound their utility for soil evaluation. In the present...
Vehicle-related air pollution has an intrinsically dynamic nature. Recent field measurements and modeling work have demonstrated that near-road topography may modify levels of air pollutants reaching populations residing and working in close proximity to roadways. However, the ma...
Spatially cascading effect of perturbations in experimental meta-ecosystems.
Harvey, Eric; Gounand, Isabelle; Ganesanandamoorthy, Pravin; Altermatt, Florian
2016-09-14
Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows. © 2016 The Author(s).
Coarse climate change projections for species living in a fine-scaled world.
Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R
2017-01-01
Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change. © 2016 John Wiley & Sons Ltd.
Building the bridge between animal movement and population dynamics.
Morales, Juan M; Moorcroft, Paul R; Matthiopoulos, Jason; Frair, Jacqueline L; Kie, John G; Powell, Roger A; Merrill, Evelyn H; Haydon, Daniel T
2010-07-27
While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.
Hierarchical spatiotemporal matrix models for characterizing invasions
Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew
2007-01-01
The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.
Hierarchical spatiotemporal matrix models for characterizing invasions
Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew
2007-01-01
The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.
NASA Astrophysics Data System (ADS)
Jusup, Marko; Iwami, Shingo; Podobnik, Boris; Stanley, H. Eugene
2015-12-01
Since the very inception of mathematical modeling in epidemiology, scientists exploited the simplicity ingrained in the assumption of a well-mixed population. For example, perhaps the earliest susceptible-infectious-recovered (SIR) model developed by L. Reed and W.H. Frost in the 1920s [1], included the well-mixed assumption such that any two individuals in the population could meet each other. The problem was that, unlike many other simplifying assumptions used in epidemiological modeling whose validity holds in one situation or the other, well-mixed populations are almost non-existent in reality because the nature of human socio-economic interactions is, for the most part, highly heterogeneous (e.g. [2-6]).
Carstens, Julienne L; Correa de Sampaio, Pedro; Yang, Dalu; Barua, Souptik; Wang, Huamin; Rao, Arvind; Allison, James P; LeBleu, Valerie S; Kalluri, Raghu
2017-04-27
The exact nature and dynamics of pancreatic ductal adenocarcinoma (PDAC) immune composition remains largely unknown. Desmoplasia is suggested to polarize PDAC immunity. Therefore, a comprehensive evaluation of the composition and distribution of desmoplastic elements and T-cell infiltration is necessary to delineate their roles. Here we develop a novel computational imaging technology for the simultaneous evaluation of eight distinct markers, allowing for spatial analysis of distinct populations within the same section. We report a heterogeneous population of infiltrating T lymphocytes. Spatial distribution of cytotoxic T cells in proximity to cancer cells correlates with increased overall patient survival. Collagen-I and αSMA + fibroblasts do not correlate with paucity in T-cell accumulation, suggesting that PDAC desmoplasia may not be a simple physical barrier. Further exploration of this technology may improve our understanding of how specific stromal composition could impact T-cell activity, with potential impact on the optimization of immune-modulatory therapies.
Characterizing habitat suitability for a central-place forager in a dynamic marine environment.
Briscoe, Dana K; Fossette, Sabrina; Scales, Kylie L; Hazen, Elliott L; Bograd, Steven J; Maxwell, Sara M; McHuron, Elizabeth A; Robinson, Patrick W; Kuhn, Carey; Costa, Daniel P; Crowder, Larry B; Lewison, Rebecca L
2018-03-01
Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions ( Zalophus californianus ) are central-place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near-real-time remotely sensed satellite oceanography, animal tracking data ( n = 72) from November to February over multiple years (2003-2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool ( <14°C ), productive waters, shallow depths, increased eddy activity, and positive sea-level anomalies. Predictive habitat maps generated from these biophysical associations suggest winter foraging areas are spatially consistent in the nearshore and offshore environments, except during the 2004-2005 winter, which coincided with an El Niño event. Here, we show how a species distribution model can provide broadscale information on the distribution of female California sea lions during an important life history stage and its implications for population dynamics and spatial management.
Effects of Interaction Imbalance in a Strongly Repulsive One-Dimensional Bose Gas
NASA Astrophysics Data System (ADS)
Barfknecht, R. E.; Foerster, A.; Zinner, N. T.
2018-05-01
We calculate the spatial distributions and the dynamics of a few-body two-component strongly interacting Bose gas confined to an effectively one-dimensional trapping potential. We describe the densities for each component in the trap for different interaction and population imbalances. We calculate the time evolution of the system and show that, for a certain ratio of interactions, the minority population travels through the system as an effective wave packet.
NASA Astrophysics Data System (ADS)
Zhang, Shaojun; Wu, Ye; Huang, Ruikun; Wang, Jiandong; Yan, Han; Zheng, Yali; Hao, Jiming
2016-08-01
Vehicle emissions containing air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in eastern Asia. A high-resolution emission inventory is a useful tool compared with traditional tools (e.g. registration data-based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macau, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multimodels. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays in 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macau. Second, based on a localized vehicle emission model (e.g. the emission factor model for the Beijing vehicle fleet - Macau, EMBEV-Macau), this study established a link-based vehicle emission inventory in Macau with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD (AMS/EPA Regulatory Model) model to map concentrations of CO and primary PM2.5 contributed by local vehicle emissions during weekdays in November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 26 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that the estimated CO2 emissions from gasoline vehicles agreed well with the statistical fuel consumption in Macau. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in eastern Asia.
Regis, Lêda N; Acioli, Ridelane Veiga; Silveira, José Constantino; de Melo-Santos, Maria Alice Varjal; da Cunha, Mércia Cristiane Santana; Souza, Fátima; Batista, Carlos Alberto Vieira; Barbosa, Rosângela Maria Rodrigues; de Oliveira, Cláudia Maria Fontes; Ayres, Constância Flávia Junqueira; Monteiro, Antonio Miguel Vieira; Souza, Wayner Vieira
2014-09-01
Aedes aegypti has played a major role in the dramatic expansion of dengue worldwide. The failure of control programs in reducing the rhythm of global dengue expansion through vector control suggests the need for studies to support more appropriated control strategies. We report here the results of a longitudinal study on Ae. aegypti population dynamics through continuous egg sampling aiming to characterize the infestation of urban areas of a Brazilian oceanic island, Fernando de Noronha. The spatial and temporal distribution of the dengue vector population in urban areas of the island was described using a monitoring system (SMCP-Aedes) based on a 103-trap network for Aedes egg sampling, using GIS and spatial statistics analysis tools. Mean egg densities were estimated over a 29-month period starting in 2011 and producing monthly maps of mosquito abundance. The system detected continuous Ae. aegypti oviposition in most traps. The high global positive ovitrap index (POI=83.7% of 2815 events) indicated the frequent presence of blood-fed-egg laying females at every sampling station. Egg density (eggs/ovitrap/month) reached peak values of 297.3 (0 - 2020) in May and 295 (0 - 2140) in August 2012. The presence of a stable Ae. aegypti population established throughout the inhabited areas of the island was demonstrated. A strong association between egg abundance and rainfall with a 2-month lag was observed, which combined with a first-order autocorrelation observed in the series of egg counts can provide an important forecasting tool. This first description of the characteristics of the island infestation by the dengue vector provides baseline information to analyze relationships between the spatial distribution of the vector and dengue cases, and to the development of integrated vector control strategies. Copyright © 2014 Elsevier B.V. All rights reserved.
Trzcinski, M Kurtis; Walde, Sandra J; Taylor, Philip D
2008-11-01
1. Theory predicting that populations with high maximum rates of increase (r(max)) will be less stable, and that metapopulations with high average r(max) will be less synchronous, was tested using a small protist, Bodo, that inhabits pitcher plant leaves (Sarracenia purpurea L.). The effects of predators and resources on these relationships were also determined. 2. Abundance data collected for a total of 60 populations of Bodo, over a period of 3 months, at six sites in three bogs in eastern Canada, were used to test these predictions. Mosquitoes were manipulated in half the leaves partway through the season to increase the range of predation rates. 3. Dynamics differed greatly among leaves and sites, but most populations exhibited one or more episodes of rapid increase followed by a population crash. Estimates of r(max) obtained using a linear mixed-effects model, ranged from 1 x 5 to 2 x 7 per day. Resource levels (captured insect) and midge abundances affected r(max). 4. Higher r(max) was associated with greater temporal variability and lower synchrony as predicted. However, in contrast to expectations, populations with higher r(max) also had lower mean abundance and were more suppressed by predators. 5. This study demonstrates that the link between r(max) and temporal variability is key to understanding the dynamics of populations that spend little time near equilibrium, and to predicting and interpreting the effects of community structure on the dynamics of such populations.
In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...
In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...
Stages and Spatial Scales of Recruitment Limitation in Southern Appalachain Forests
James S. Clark; Eric Macklin; Leslie Wood
1998-01-01
Recruitment limitation of tree population dynamics is poorly understood, because fecundity and dispersal are difficult to characterize in closed stands. We present an approach that estimates seed production and dispersal under closed canopies and four limitations on recruitment: tree density and location, fecundity, seed dispersal, and establishment. Consistent...
Population dynamics of stored maize insect pests in warehouses in two districts of Ghana
USDA-ARS?s Scientific Manuscript database
Understanding what insect species are present and their temporal and spatial patterns of distribution is important for developing a successful integrated pest management strategy for food storage in warehouses. Maize in many countries in Africa is stored in bags in warehouses, but little monitoring ...
We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was bas...
Spatial and numerical relationships of arthropod communities associated with key pests of maize
USDA-ARS?s Scientific Manuscript database
Pest management largely focuses on managing individual pest species with little concern for the diverse communities that co-occur with key pests and potentially shape their population dynamics. During anthesis, we described the foliar arthropod communities on 53 maize farms throughout the region of ...
Tropical forest landscape dynamics: Population consequences for neotropical lianas, genus Passiflora
NASA Astrophysics Data System (ADS)
Plowes, Robert Merrick
Treefall gaps in rainforest landscapes play a crucial role in providing opportunities for establishment and growth of rare, light-demanding plants such as Passifora vines in Corcovado rainforests, Costa Rica. This study considers the interplay of landscape dynamics with plant life history traits and strategies in an ephemeral patch network. In Chapter One, I show how patch quality dynamics and propagule dispersal affect colonization of treefall gaps by Passifora vitifolia. Recruitment required high patch quality, exceeding 3 hours of sunlight and patches closed after about 6 years. Colonization by seed dispersal (80%) was constrained by patch quality and isolation, while clonal growth from dormant plants (20%) was limited to rare adjacent patches. Since patch turnover is critical in these systems, Chapter Two is focused on factors affecting canopy structure. I showed that prior landuse altered the dynamics of frequent, small-scale disturbances during succession following a single, large deforestation event. Here, I used Landsat subpixel analysis, aerial photographs and field surveys to demonstrate major changes in dynamics of regenerating canopies following release from agricultural activity in 1975. Little work has considered the role of life history traits in persistence of patchy populations, and so in Chapter Three I asked what life history strategies are used by 9 Passiflora species that occur in these transient forest gaps. Although Passiflora species exhibited differences in dormancy or dispersal strategies, abundance was not associated with any one strategy. Elasticities of vital rates (stasis, growth and fecundity) of P. vitifolia differed empirically in old growth and regenerating forests. To explore population responses to changes in landscape parameters or life history strategies, I created a spatially-explicit individual-based model. Simulations indicate that plant types with a dormancy phase have a greater suite of responses since they persist after patch extinction with potential to contribute later through both sexual and asexual dispersal. Plants that rely only on high dispersal were extinction prone in low connectivity landscapes. This novel approach of jointly analyzing spatially-explicit patch parameters and life history traits offers a comprehensive framework for further understanding the effects of patch dynamics on populations.
Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.
Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B
2007-11-01
Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda.
Optogenetic stimulation of a meso-scale human cortical model
NASA Astrophysics Data System (ADS)
Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi
2015-03-01
Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.
Global change and terrestrial plant community dynamics
Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...
2016-02-29
Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less
Global change and terrestrial plant community dynamics
Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.
2016-01-01
Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338
NASA Astrophysics Data System (ADS)
Xu, Qiuju; Belmonte, Andrew; deForest, Russ; Liu, Chun; Tan, Zhong
2017-04-01
In this paper, we study a fitness gradient system for two populations interacting via a symmetric game. The population dynamics are governed by a conservation law, with a spatial migration flux determined by the fitness. By applying the Galerkin method, we establish the existence, regularity and uniqueness of global solutions to an approximate system, which retains most of the interesting mathematical properties of the original fitness gradient system. Furthermore, we show that a Turing instability occurs for equilibrium states of the fitness gradient system, and its approximations.
Coberly, L Caitlin; Wei, Wei; Sampson, Koffi Y; Millstein, Jack; Wichman, Holly A; Krone, Stephen M
2009-04-01
We present a joint experimental/theoretical investigation into the roles of spatial structure and time in the competition between two pathogens for a single host. We suggest a natural mechanism by which competing pathogens can coexist when host evolution and competitive dynamics occur on similar timescales. Our experimental system consisted of a single bacterial host species and two competing bacteriophage strains grown on agar plates, with a serial transfer of samples of the bacteriophage population to fresh host populations after each incubation cycle. The experiments included two incubation times and two transfer protocols that either maintained or disrupted the spatial structure of the viruses at each transfer. The same bacteriophage acted as the dominant competitor under both transfer protocols. A striking difference between the treatments is that the weak competitor was able to persist in the long-incubation experiments but not in the short-incubation experiments. Mathematical and experimental evidence suggest that coexistence is due to the appearance of resistant mutant host cells that provide a transient "spatiotemporal refuge" for the weaker competitor. Our mathematical model is individual based, captures the stochastic spatial dynamics down to the level of individual cells, and helps to explain the differences in behavior under the various experimental conditions.
Araújo, Rita M; Serrão, Ester A; Sousa-Pinto, Isabel; Åberg, Per
2014-01-01
Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species' distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (λ(s)) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with λ(s) much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to λ(s) that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals' life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations.
Direct reciprocity in spatial populations enhances R-reciprocity as well as ST-reciprocity.
Miyaji, Kohei; Tanimoto, Jun; Wang, Zhen; Hagishima, Aya; Ikegaya, Naoki
2013-01-01
As is well-known, spatial reciprocity plays an important role in facilitating the emergence of cooperative traits, and the effect of direct reciprocity is also obvious for explaining the cooperation dynamics. However, how the combination of these two scenarios influences cooperation is still unclear. In the present work, we study the evolution of cooperation in 2 × 2 games via considering both spatial structured populations and direct reciprocity driven by the strategy with 1-memory length. Our results show that cooperation can be significantly facilitated on the whole parameter plane. For prisoner's dilemma game, cooperation dominates the system even at strong dilemma, where maximal social payoff is still realized. In this sense, R-reciprocity forms and it is robust to the extremely strong dilemma. Interestingly, when turning to chicken game, we find that ST-reciprocity is also guaranteed, through which social average payoff and cooperation is greatly enhanced. This reciprocity mechanism is supported by mean-field analysis and different interaction topologies. Thus, our study indicates that direct reciprocity in structured populations can be regarded as a more powerful factor for the sustainability of cooperation.
Upadhyay, Ranjit Kumar; Roy, Parimita; Venkataraman, C; Madzvamuse, A
2016-11-01
In the present paper, we propose and analyze an eco-epidemiological model with diffusion to study the dynamics of rabbit populations which are consumed by lynx populations. Existence, boundedness, stability and bifurcation analyses of solutions for the proposed rabbit-lynx model are performed. Results show that in the presence of diffusion the model has the potential of exhibiting Turing instability. Numerical results (finite difference and finite element methods) reveal the existence of the wave of chaos and this appears to be a dominant mode of disease dispersal. We also show the mechanism of spatiotemporal pattern formation resulting from the Hopf bifurcation analysis, which can be a potential candidate for understanding the complex spatiotemporal dynamics of eco-epidemiological systems. Implications of the asymptotic transmission rate on disease eradication among rabbit population which in turn enhances the survival of Iberian lynx are discussed. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
Zipkin, Elise F; Sillett, T Scott; Grant, Evan H Campbell; Chandler, Richard B; Royle, J Andrew
2014-01-01
Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales. PMID:24634726
Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat
Erickson, Richard A.; Thogmartin, Wayne E.; Diffendorfer, James E.; Russell, Robin E.; Szymanski, Jennifer A.
2016-01-01
Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat (Myotis sodalis), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans, disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity.
Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat.
Erickson, Richard A; Thogmartin, Wayne E; Diffendorfer, Jay E; Russell, Robin E; Szymanski, Jennifer A
2016-01-01
Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat ( Myotis sodalis ), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans , disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity.
van der Meer, Sascha; Jacquemyn, Hans
2015-01-01
Due to changes in land use, the natural habitats of an increasing number of plant species have become more and more fragmented. In landscapes that consist of patches of suitable habitat, the frequency and extent of long-distance seed dispersal can be expected to be an important factor determining local genetic diversity and regional population structure of the remaining populations. In plant species that are restricted to riparian habitats, rivers can be expected to have a strong impact on the dynamics and spatial genetic structure of populations as they may enable long-distance seed dispersal and thus maintain gene flow between fragmented populations. In this study, we used polymorphic microsatellite markers to investigate the genetic diversity and the spatial genetic structure of 28 populations of Saxifraga granulata along two rivers in central Belgium. We hypothesized that rivers might be essential for gene flow among increasingly isolated populations of this species. Genetic diversity was high (HS = 0.68), which to a certain extent can be explained by the octoploid nature of S. granulata in the study area. Populations along the Dijle and Demer rivers were also highly differentiated (G” ST = 0.269 and 0.164 and D EST = 0.190 and 0.124, respectively) and showed significant isolation-by-distance, indicating moderate levels of gene flow primarily between populations that are geographically close to each other. Along the river Demer population genetic diversity was higher upstream than downstream, suggesting that seed dispersal via the water was not the primary mode of dispersal. Overall, these results indicate that despite increasing fragmentation populations along both rivers were highly genetically diverse. The high ploidy level and longevity of S. granulata have most likely buffered negative effects of fragmentation on genetic diversity and the spatial genetic structure of populations in riparian grasslands. PMID:26079603
Fish population dynamics in a seasonally varying wetland
DeAngelis, Donald L.; Trexler, Joel C.; Cosner, Chris; Obaza, Adam; Jopp, Fred
2010-01-01
Small fishes in seasonally flooded environments such as the Everglades are capable of spreading into newly flooded areas and building up substantial biomass. Passive drift cannot account for the rapidity of observed population expansions. To test the reaction-diffusion mechanism for spread of the fish, we estimated their diffusion coefficient and applied a reaction-diffusion model. This mechanism was also too weak to account for the spatial dynamics. Two other hypotheses were tested through modeling. The first--the 'refuge mechanism--hypothesizes that small remnant populations of small fishes survive the dry season in small permanent bodies of water (refugia), sites where the water level is otherwise below the surface. The second mechanism, which we call the 'dynamic ideal free distribution mechanism' is that consumption by the fish creates a prey density gradient and that fish taxis along this gradient can lead to rapid population expansion in space. We examined the two alternatives and concluded that although refugia may play an important role in recolonization by the fish population during reflooding, only the second, taxis in the direction of the flooding front, seems capable of matching empirical observations. This study has important implications for management of wetlands, as fish biomass is an essential support of higher trophic levels.
König, Sara; Worrich, Anja; Banitz, Thomas; Harms, Hauke; Kästner, Matthias; Miltner, Anja; Wick, Lukas Y.; Frank, Karin; Thullner, Martin; Centler, Florian
2018-01-01
Bacterial degradation of organic compounds is an important ecosystem function with relevance to, e.g., the cycling of elements or the degradation of organic contaminants. It remains an open question, however, to which extent ecosystems are able to maintain such biodegradation function under recurrent disturbances (functional resistance) and how this is related to the bacterial biomass abundance. In this paper, we use a numerical simulation approach to systematically analyze the dynamic response of a microbial population to recurrent disturbances of different spatial distribution. The spatially explicit model considers microbial degradation, growth, dispersal, and spatial networks that facilitate bacterial dispersal mimicking effects of mycelial networks in nature. We find: (i) There is a certain capacity for high resistance of biodegradation performance to recurrent disturbances. (ii) If this resistance capacity is exceeded, spatial zones of different biodegradation performance develop, ranging from no or reduced to even increased performance. (iii) Bacterial biomass and biodegradation dynamics respond inversely to the spatial fragmentation of disturbances: overall biodegradation performance improves with increasing fragmentation, but bacterial biomass declines. (iv) Bacterial dispersal networks can enhance functional resistance against recurrent disturbances, mainly by reactivating zones in the core of disturbed areas, even though this leads to an overall reduction of bacterial biomass. PMID:29696013
Schmidt, Tom L.; Barton, Nicholas H.; Rašić, Gordana; Turley, Andrew P.; Montgomery, Brian L.; Iturbe-Ormaetxe, Inaki; Cook, Peter E.; Ryan, Peter A.; Ritchie, Scott A.; Hoffmann, Ary A.; O’Neill, Scott L.
2017-01-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100–200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation. PMID:28557993
Schmidt, Tom L; Barton, Nicholas H; Rašić, Gordana; Turley, Andrew P; Montgomery, Brian L; Iturbe-Ormaetxe, Inaki; Cook, Peter E; Ryan, Peter A; Ritchie, Scott A; Hoffmann, Ary A; O'Neill, Scott L; Turelli, Michael
2017-05-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100-200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation.
Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference.
Suchow, Jordan W; Bourgin, David D; Griffiths, Thomas L
2017-07-01
Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.
2010-01-01
Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752
DOE Office of Scientific and Technical Information (OSTI.GOV)
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,more » 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.« less
Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J
2010-05-01
Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.
Hossack, Blake R.; Honeycutt, Richard
2017-01-01
Drought has fueled an increased frequency and severity of large wildfires in many ecosystems. Despite an increase in research on wildfire effects on vertebrates, the vast majority of it has focused on short-term (< 5 years) effects and there is still little information on the time scale of population recovery for species that decline in abundance after fire. In 2003, a large wildfire in Montana (USA) burned the watersheds of four of eight streams that we sampled for larval Rocky Mountain tailed frogs (Ascaphus montanus) in 2001. Surveys during 2004–2005 revealed reduced abundance of larvae in burned streams relative to unburned streams, with greater declines associated with increased fire extent. Rocky Mountain tailed frogs have low vagility and have several unusual life-history traits that could slow population recovery, including an extended larval period (4 years), delayed sexual maturity (6–8 years), and low fecundity (< 50 eggs/year). To determine if abundance remained depressed since the 2003 wildfire, we repeated surveys during 2014–2015 and found relative abundance of larvae in burned and unburned streams had nearly converged to pre-fire conditions within two generations. The negative effects of burn extent on larval abundance weakened> 58% within 12 years after the fire. We also found moderate synchrony among populations in unburned streams and negative spatial autocorrelation among populations in burned streams. We suspect negative spatial autocorrelation among spatially-clustered burned streams reflected increased post-fire patchiness in resources and different rates of local recovery. Our results add to a growing body of work that suggests populations in intact ecosystems tend to be resilient to habitat changes caused by wildfire. Our results also provide important insights into recovery times of populations that have been negatively affected by severe wildfire.
Samuel A. Cushman; Bradley W. Compton; Kevin McGarigal
2010-01-01
Habitat loss and fragmentation are widely believed to be the most important drivers of extinction (Leakey and Lewin 1995). The habitats in which organisms live are spatially structured at a number of scales, and these patterns interact with organism perception and behavior to drive population dynamics and community structure (Johnson et al. 1992). Anthropogenic habitat...
NASA Astrophysics Data System (ADS)
Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca
2013-04-01
In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.
The Conundrum of Impacts of Climate Change on Urbanization and the Urban Heat Island Effect
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.
2011-01-01
The twenty-first century is the first urban century according to the United Nations Development Program. The focus on cities reflects awareness of the growing percentage of the world's population that lives in urban areas. In 2000, approximately 3 billion people representing about 40% of the global population resided in urban areas. The United Nations estimates that by 2025, 60% of the world s population will live in urban areas. As a consequence, the number of megacities (those cities with populations of 10 million inhabitants or more) will increase by 100 by 2025. Thus, there is a critical need to understand the spatial growth of urban areas and what the impacts are on the environment. Moreover, there is a critical need to assess how under global climate change, cities will affect the local, regional, and even global climate. As urban areas increase in size, it is anticipated there will be a concomitant growth of the Urban Heat Island effect (UHI), and the attributes that are related to its spatial and temporal dynamics. Therefore, how climate change, including the dynamics of the UHI, will affect the urban environment, must be explored to help mitigate potential impacts on the environment (e.g., air quality, heat stress, vectorborne disease) and on human health and well being, to develop adaptation schemes to cope with these impacts.
Interplay between population firing stability and single neuron dynamics in hippocampal networks
Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna
2015-01-01
Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699
Yang, Rui; Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso
2010-06-01
Evolutionary-game based models of nonhierarchical, cyclically competing populations have become paradigmatic for addressing the fundamental problem of species coexistence in spatially extended ecosystems. We study the role of intraspecific competition in the coexistence and find that the competition can strongly promote the coexistence for high individual mobility in the sense that stable coexistence can arise in parameter regime where extinction would occur without the competition. The critical value of the competition rate beyond which the coexistence is induced is found to be independent of the mobility. We derive a theoretical model based on nonlinear partial differential equations to predict the critical competition rate and the boundaries between the coexistence and extinction regions in a relevant parameter space. We also investigate pattern formation and well-mixed spatiotemporal population dynamics to gain further insights into our findings. (c) 2010 American Institute of Physics.
Gridded population projections for the coastal zone under the Shared Socioeconomic Pathways
NASA Astrophysics Data System (ADS)
Merkens, Jan-Ludolf; Reimann, Lena; Hinkel, Jochen; Vafeidis, Athanasios T.
2016-10-01
Existing quantifications of the Shared Socioeconomic Pathways (SSP) used for climate impact assessment do not account for subnational population dynamics such as coastward-migration that can be critical for coastal impact assessment. This paper extends the SSPs by developing spatial projections of global coastal population distribution for the five basic SSPs. Based on a series of coastal migration drivers we develop coastal narratives for each SSP. These narratives account for differences in coastal and inland population developments in urban and rural areas. To spatially distribute population, we use the International Institute for Applied Systems Analysis (IIASA) national population and urbanisation projections and employ country-specific growth rates, which differ for coastal and inland as well as for urban and rural regions, to project coastal population for each SSP. These rates are derived from spatial analysis of historical population data and adjusted for each SSP based on the coastal narratives. Our results show that, compared to the year 2000 (638 million), the population living in the Low Elevated Coastal Zone (LECZ) increases by 58% to 71% until 2050 and exceeds one billion in all SSPs. By the end of the 21st century, global coastal population declines to 830-907 million in all SSPs except for SSP3, where coastal population growth continues and reaches 1.184 billion. Overall, the population living in the LECZ is higher by 85 to 239 million compared to the original IIASA projections. Asia expects the highest absolute growth (238-303 million), Africa the highest relative growth (153% to 218%). Our results highlight regions where high coastal population growth is expected and will therefore face an increased exposure to coastal flooding.
Miller, David A.; Clark, W.R.; Arnold, S.J.; Bronikowski, A.M.
2011-01-01
Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution. ?? 2011 by the Ecological Society of America.
Miller, David A; Clark, William R; Arnold, Stevan J; Bronikowski, Anne M
2011-08-01
Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.
NASA Astrophysics Data System (ADS)
Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.
2017-02-01
We show the existence of chimeralike states in two distinct groups of identical populations of globally coupled Stuart-Landau oscillators. The existence of chimeralike states occurs only for a small range of frequency difference between the two populations, and these states disappear for an increase of mismatch between the frequencies. Here the chimeralike states are characterized by the synchronized oscillations in one population and desynchronized oscillations in another population. We also find that such states observed in two distinct groups of identical populations of nonlocally coupled oscillators are different from the above case in which coexisting domains of synchronized and desynchronized oscillations are observed in one population and the second population exhibits synchronized oscillations for spatially prepared initial conditions. Perturbation from such spatially prepared initial condition leads to the existence of imperfectly synchronized states. An imperfectly synchronized state represents the existence of solitary oscillators which escape from the synchronized group in population I and synchronized oscillations in population II. Also the existence of chimera state is independent of the increase of frequency mismatch between the populations. We also find the coexistence of different dynamical states with respect to different initial conditions, which causes multistability in the globally coupled system. In the case of nonlocal coupling, the system does not show multistability except in the cluster state region.
Dynamic assessments of population exposure to urban greenspace using multi-source big data.
Song, Yimeng; Huang, Bo; Cai, Jixuan; Chen, Bin
2018-09-01
A growing body of evidence has proven that urban greenspace is beneficial to improve people's physical and mental health. However, knowledge of population exposure to urban greenspace across different spatiotemporal scales remains unclear. Moreover, the majority of existing environmental assessments are unable to quantify how residents enjoy their ambient greenspace during their daily life. To deal with this challenge, we proposed a dynamic method to assess urban greenspace exposure with the integration of mobile-phone locating-request (MPL) data and high-spatial-resolution remote sensing images. This method was further applied to 30 major cities in China by assessing cities' dynamic greenspace exposure levels based on residents' surrounding areas with different buffer scales (0.5km, 1km, and 1.5km). Results showed that regarding residents' 0.5-km surrounding environment, Wenzhou and Hangzhou were found to be with the greenest exposure experience, whereas Zhengzhou and Tangshan were the least ones. The obvious diurnal and daily variations of population exposure to their surrounding greenspace were also identified to be highly correlated with the distribution pattern of urban greenspace and the dynamics of human mobility. Compared with two common measurements of urban greenspace (green coverage rate and green area per capita), the developed method integrated the dynamics of population distribution and geographic locations of urban greenspace into the exposure assessment, thereby presenting a more reasonable way to assess population exposure to urban greenspace. Additionally, this dynamic framework could hold potential utilities in supporting urban planning studies and environmental health studies and advancing our understanding of the magnitude of population exposure to greenspace at different spatiotemporal scales. Copyright © 2018 Elsevier B.V. All rights reserved.
Green, David S; Matthews, Sean M; Swiers, Robert C; Callas, Richard L; Scott Yaeger, J; Farber, Stuart L; Schwartz, Michael K; Powell, Roger A
2018-05-01
Determining how species coexist is critical for understanding functional diversity, niche partitioning and interspecific interactions. Identifying the direct and indirect interactions among sympatric carnivores that enable their coexistence is particularly important to elucidate because they are integral for maintaining ecosystem function. We studied the effects of removing nine fishers (Pekania pennanti) on their population dynamics and used this perturbation to elucidate the interspecific interactions among fishers, grey foxes (Urocyon cinereoargenteus) and ringtails (Bassariscus astutus). Grey foxes (family: Canidae) are likely to compete with fishers due to their similar body sizes and dietary overlap, and ringtails (family: Procyonidae), like fishers, are semi-arboreal species of conservation concern. We used spatial capture-recapture to investigate fisher population numbers and dynamic occupancy models that incorporated interspecific interactions to investigate the effects members of these species had on the colonization and persistence of each other's site occupancy. The fisher population showed no change in density for up to 3 years following the removals of fishers for translocations. In contrast, fisher site occupancy decreased in the years immediately following the translocations. During this same time period, site occupancy by grey foxes increased and remained elevated through the end of the study. We found a complicated hierarchy among fishers, foxes and ringtails. Fishers affected grey fox site persistence negatively but had a positive effect on their colonization. Foxes had a positive effect on ringtail site colonization. Thus, fishers were the dominant small carnivore where present and negatively affected foxes directly and ringtails indirectly. Coexistence among the small carnivores we studied appears to reflect dynamic spatial partitioning. Conservation and management efforts should investigate how intraguild interactions may influence the recolonization of carnivores to previously occupied landscapes. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Tantowijoyo, W; Arguni, E; Johnson, P; Budiwati, N; Nurhayati, P I; Fitriana, I; Wardana, S; Ardiansyah, H; Turley, A P; Ryan, P; O'Neill, S L; Hoffmann, A A
2016-01-01
of mosquito vector populations, particularly through Wolbachia endosymbionts. The success of these strategies depends on understanding the dynamics of vector populations. In preparation for Wolbachia releases around Yogyakarta, we have studied Aedes populations in five hamlets. Adult monitoring with BioGent- Sentinel (BG-S) traps indicated that hamlet populations had different dynamics across the year; while there was an increase in Aedes aegypti (L.) and Aedes albopictus (Skuse) numbers in the wet season, species abundance remained relatively stable in some hamlets but changed markedly (>2 fold) in others. Local rainfall a month prior to monitoring partly predicted numbers of Ae. aegypti but not Ae. albopictus. Site differences in population size indicated by BG-S traps were also evident in ovitrap data. Egg or larval collections with ovitraps repeated at the same location suggested spatial autocorrelation (<250 m) in the areas of the hamlets where Ae. aegypti numbers were high. Overall, there was a weak negative association (r<0.43) between Ae. aegypti and Ae. albopictus numbers in ovitraps when averaged across collections. Ae. albopictus numbers in ovitraps and BG-S traps were positively correlated with vegetation around areas where traps were placed, while Ae. aegypti were negatively correlated with this feature. These data inform intervention strategies by defining periods when mosquito densities are high, highlighting the importance of local site characteristics on populations, and suggesting relatively weak interactions between Ae. aegypti and Ae. albopictus. They also indicate local areas within hamlets where consistently high mosquito densities may influence Wolbachia invasions and other interventions.
The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx
Stenseth, Nils Chr.; Ehrich, Dorothee; Rueness, Eli Knispel; Lingjærde, Ole Chr.; Chan, Kung-Sik; Boutin, Stan; O'Donoghue, Mark; Robinson, David A.; Viljugrein, Hildegunn; Jakobsen, Kjetill S.
2004-01-01
The abundance of Canadian lynx follows 10-year density fluctuations across the Canadian subcontinent. These cyclic fluctuations have earlier been shown to be geographically structured into three climatic regions: the Atlantic, Continental, and Pacific zones. Recent genetic evidence revealed an essentially similar spatial structuring. Introducing a new population model, the “climate forcing of ecological and evolutionary patterns” model, we link the observed ecological and evolutionary patterns. Specifically, we demonstrate that there is greater phase synchrony within climatic zones than between them and show that external climatic forcing may act as a synchronizer. We simulated genetic drift by using data on population dynamics generated by the climate forcing of ecological and evolutionary patterns model, and we demonstrate that the observed genetic structuring can be seen as an emerging property of the spatiotemporal ecological dynamics. PMID:15067131
Jordan, Nicholas R.; Forester, James D.
2018-01-01
Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized. PMID:29771923
Synchrony, Weather, and Cycles in Southern Pine Beetle (Coleoptera: Curculionidae).
Reeve, John D
2018-02-08
Spatial synchrony and cycles are common features of forest insect pests, but are often studied as separate phenomenon. Using time series of timber damage caused by Dendroctonus frontalis Zimmermann (Coleoptera: Curculionidae) (southern pine beetle) in 10 states within the southern United States, this study examines synchrony in D. frontalis abundance, the synchronizing effects of temperature extremes, and the evidence for shared cycles among state populations. Cross-correlation and cluster analyses are used to quantify synchrony across a range of geographic distances and to identify groups of states with synchronous dynamics. Similar techniques are used to quantify spatial synchrony in temperature extremes and to examine their relationship to D. frontalis fluctuations. Cross-wavelet analysis is then used to examine pairs of time series for shared cycles. These analyses suggest there is substantial synchrony among states in D. frontalis fluctuations, and there are regional groups of states with similar dynamics. Synchrony in D. frontalis fluctuations also appears related to spatial synchrony in summer and winter temperature extremes. The cross-wavelet results suggest that D. frontalis dynamics may differ among regions and are not stationary. Significant oscillations were present in some states over certain time intervals, suggesting an endogenous feedback mechanism. Management of D. frontalis outbreaks could potentially benefit from a multistate regional approach because populations are synchronous on this level. Extreme summer temperatures are likely to become the most important synchronizing agent due to climate change. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Spatially heterogeneous stochasticity and the adaptive diversification of dormancy.
Rajon, E; Venner, S; Menu, F
2009-10-01
Diversified bet-hedging, a strategy that leads several individuals with the same genotype to express distinct phenotypes in a given generation, is now well established as a common evolutionary response to environmental stochasticity. Life-history traits defined as diversified bet-hedging (e.g. germination or diapause strategies) display marked differences between populations in spatial proximity. In order to find out whether such differences can be explained by local adaptations to spatially heterogeneous environmental stochasticity, we explored the evolution of bet-hedging dormancy strategies in a metapopulation using a two-patch model with patch differences in stochastic juvenile survival. We found that spatial differences in the level of environmental stochasticity, restricted dispersal, increased fragmentation and intermediate survival during dormancy all favour the adaptive diversification of bet-hedging dormancy strategies. Density dependency also plays a major role in the diversification of dormancy strategies because: (i) it may interact locally with environmental stochasticity and amplify its effects; however, (ii) it can also generate chaotic population dynamics that may impede diversification. Our work proposes new hypotheses to explain the spatial patterns of bet-hedging strategies that we hope will encourage new empirical studies of this topic.
Nathan W. Siegert; Deborah G. McCullough; Andrew M. Liebhold; Frank W. Telewski
2007-01-01
Emerald ash borer (Agrilus planipennis Fairmaire; Coleoptera: Buprestidae) was identified in June 2002 as the cause of widespread ash (Fraxinus spp.) mortality in southeastern lower Michigan and Windsor, Ontario. Localized outlier populations have since been discovered across much of lower Michigan and in areas of Indiana, Ohio and...
Growth and demography of Pinaleno high elevation forests
Christopher O' Connor; Donald A. Falk; Ann M. Lynch; Craig P. Wilcox; Thomas W. Swetnam; Tyson L. Swetnam
2010-01-01
The project goal is to understand how multiple disturbance events including fire, insect outbreaks, and climate variability interact in space and time, and how they combine to influence forest species composition, spatial structure, and tree population dynamics in high elevation forests of the Pinaleno Mountains. Information from each of these components is needed in...
Demographic and habitat requirements for conservation of bull trout
Bruce E. Rieman; John D. Mclntyre
1993-01-01
Elements in bull trout biology, population dynamics, habitat, and biotic interactions important to conservation of the species are identified. Bull trout appear to have more specific habitat requirements than other salmonids, but no critical thresholds of acceptable habitat condition were found. Size, temporal variation, and spatial distribution are likely to influence...
Spatial and temporal distribution patterns of ear-feeding insect damage in pre-harvest corn
USDA-ARS?s Scientific Manuscript database
The key ear-feeding insects in the southeastern coastal plain region are the corn earworm, Helicoverpa zea (Boddie), the maize weevil, Sitophilus zeamais Motschulsky, and the brown stink bug, Euschistus servus (Say), in recent years. The population dynamics of E. servus and S. zeamais were monitore...
Modeling the Impact of Spatial Structure on Growth Dynamics of Invasive Plant Species
NASA Astrophysics Data System (ADS)
Murphy, James T.; Johnson, Mark P.; Walshe, Ray
2013-07-01
Invasive nonindigenous plant species can have potentially serious detrimental effects on local ecosystems and, as a result, costly control efforts often have to be put in place to protect habitats. An example of an invasive problem on a global scale involves the salt marsh grass species from the genus Spartina. The spread of Spartina anglica in Europe and Asia has drawn much concern due to its ability to convert coastal habitats into cord-grass monocultures and to alter the native food webs. However, the patterns of invasion of Spartina species are amenable to spatially-explicit modeling strategies that take into account both temporal and spatio-temporal processes. In this study, an agent-based model of Spartina growth on a simulated mud flat environment was developed in order to study the effects of spatial pattern and initial seedling placement on the invasion dynamics of the population. The spatial pattern of an invasion plays a key role in the rate of spread of the species and understanding this can lead to significant cost savings when designing efficient control strategies. We present here a model framework that can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on invasion dynamics. This would be a useful tool for assessing eradication strategies and choosing optimal control solutions in order to be able to minimize future control costs.
Statistical physics of the spatial Prisoner's Dilemma with memory-aware agents
NASA Astrophysics Data System (ADS)
Javarone, Marco Alberto
2016-02-01
We introduce an analytical model to study the evolution towards equilibrium in spatial games, with `memory-aware' agents, i.e., agents that accumulate their payoff over time. In particular, we focus our attention on the spatial Prisoner's Dilemma, as it constitutes an emblematic example of a game whose Nash equilibrium is defection. Previous investigations showed that, under opportune conditions, it is possible to reach, in the evolutionary Prisoner's Dilemma, an equilibrium of cooperation. Notably, it seems that mechanisms like motion may lead a population to become cooperative. In the proposed model, we map agents to particles of a gas so that, on varying the system temperature, they randomly move. In doing so, we are able to identify a relation between the temperature and the final equilibrium of the population, explaining how it is possible to break the classical Nash equilibrium in the spatial Prisoner's Dilemma when considering agents able to increase their payoff over time. Moreover, we introduce a formalism to study order-disorder phase transitions in these dynamics. As result, we highlight that the proposed model allows to explain analytically how a population, whose interactions are based on the Prisoner's Dilemma, can reach an equilibrium far from the expected one; opening also the way to define a direct link between evolutionary game theory and statistical physics.
Yurek, Simeon; DeAngelis, Donald L.; Trexler, Joel C.; Klassen, Stephen; Larsen, Laurel G.
2016-01-01
In flood-pulsed ecosystems, hydrology and landscape structure mediate transfers of energy up the food chain by expanding and contracting in area, enabling spatial expansion and growth of fish populations during rising water levels, and subsequent concentration during the drying phase. Connectivity of flooded areas is dynamic as waters rise and fall, and is largely determined by landscape geomorphology and anisotropy. We developed a methodology for simulating fish dispersal and concentration on spatially-explicit, dynamic floodplain wetlands with pulsed food web dynamics, to evaluate how changes in connectivity through time contribute to the concentration of fish biomass that is essential for higher trophic levels. The model also tracks a connectivity index (DCI) over different compass directions to see if fish biomass dynamics can be related in a simple way to topographic pattern. We demonstrate the model for a seasonally flood-pulsed, oligotrophic system, the Everglades, where flow regimes have been greatly altered. Three dispersing populations of functional fish groups were simulated with empirically-based dispersal rules on two landscapes, and two twelve-year time series of managed water levels for those areas were applied. The topographies of the simulations represented intact and degraded ridge-and-slough landscapes (RSL). Simulation results showed large pulses of biomass concentration forming during the onset of the drying phase, when water levels were falling and fish began to converge into the sloughs. As water levels fell below the ridges, DCI declined over different directions, closing down dispersal lanes, and fish density spiked. Persistence of intermediate levels of connectivity on the intact RSL enabled persistent concentration events throughout the drying phase. The intact landscape also buffered effects of wet season population growth. Water level reversals on both landscapes negatively affected fish densities by depleting fish populations without allowing enough time for them to regenerate. Testable, spatiotemporal predictions of the timing, location, duration, and magnitude of fish concentration pulses were produced by the model, and can be applied to restoration planning.
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 bring metapopulation strength and persistence up to a level above the current level. Copyright © 2016 Elsevier Ltd. All rights reserved.
Xu, Hongwei; Logan, John R.; Short, Susan E.
2014-01-01
Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980
Clinchy, Michael; Haydon, Daniel T; Smith, Andrew T
2002-04-01
Patch occupancy surveys are commonly used to parameterize metapopulation models. If isolation predicts patch occupancy, this is generally attributed to a balance between distance-dependent recolonization and spatially independent extinctions. We investigated whether similar patterns could also be generated by a process of spatially correlated extinctions following a unique colonization event (analogous to nonequilibrium processes in island biogeography). We simulated effects of spatially correlated extinctions on patterns of patch occupancy among pikas (Ochotona princeps) at Bodie, California, using randomly located extinction disks to represent the likely effects of predation. Our simulations produced similar patterns to those cited as evidence of balanced metapopulation dynamics. Simulations using a variety of disk sizes and patch configurations confirmed that our results are potentially applicable to a broad range of species and sites. Analyses of the observed patterns of patch occupancy at Bodie revealed little evidence of rescue effects and strong evidence that most recolonizations are ephemeral in nature. Persistence will be overestimated if static or declining patterns of patch occupancy are mistakenly attributed to dynamically stable metapopulation processes. Consequently, simple patch occupancy surveys should not be considered as substitutes for detailed experimental tests of hypothesized population processes, particularly when conservation concerns are involved.
Huntsman, Brock M.; Petty, J. Todd
2014-01-01
Spatial population models predict strong density-dependence and relatively stable population dynamics near the core of a species' distribution with increasing variance and importance of density-independent processes operating towards the population periphery. Using a 10-year data set and an information-theoretic approach, we tested a series of candidate models considering density-dependent and density-independent controls on brook trout population dynamics across a core-periphery distribution gradient within a central Appalachian watershed. We sampled seven sub-populations with study sites ranging in drainage area from 1.3–60 km2 and long-term average densities ranging from 0.335–0.006 trout/m. Modeled response variables included per capita population growth rate of young-of-the-year, adult, and total brook trout. We also quantified a stock-recruitment relationship for the headwater population and coefficients of variability in mean trout density for all sub-populations over time. Density-dependent regulation was prevalent throughout the study area regardless of stream size. However, density-independent temperature models carried substantial weight and likely reflect the effect of year-to-year variability in water temperature on trout dispersal between cold tributaries and warm main stems. Estimated adult carrying capacities decreased exponentially with increasing stream size from 0.24 trout/m in headwaters to 0.005 trout/m in the main stem. Finally, temporal variance in brook trout population size was lowest in the high-density headwater population, tended to peak in mid-sized streams and declined slightly in the largest streams with the lowest densities. Our results provide support for the hypothesis that local density-dependent processes have a strong control on brook trout dynamics across the entire distribution gradient. However, the mechanisms of regulation likely shift from competition for limited food and space in headwater streams to competition for thermal refugia in larger main stems. It also is likely that source-sink dynamics and dispersal from small headwater habitats may partially influence brook trout population dynamics in the main stem. PMID:24618602
Codeço, Cláudia Torres; Honório, Nildimar Alves; Ríos-Velásquez, Cláudia M; Santos, Maria da Conceição Alves dos; Mattos, Ingrid Vieira de; Luz, Sérgio Bessa; Reis, Izabel Cristina; Cunha, Guilherme Bernardino da; Rosa-Freitas, Maria Goreti; Tsouris, Pantelis; Castro, Márcia Gonçalves de; Hayd, Ramão Luciano Nogueira; Luitgards-Moura, José Francisco
2009-07-01
Roraima is the northernmost state of Brazil, bordering both Venezuela and Guyana. Appropriate climate and vector conditions for dengue transmission together with its proximity to countries where all four dengue serotypes circulate make this state, particularly the capital Boa Vista, strategically important for dengue surveillance in Brazil. Nonetheless, few studies have addressed the population dynamics of Aedes aegypti in Boa Vista. In this study, we report temporal and spatial variations in Ae. aegypti population density using ovitraps in two highly populated neighbourhoods; Centro and Tancredo Neves. In three out of six surveys, Ae. aegypti was present in more than 80% of the sites visited. High presence levels of this mosquito suggest ubiquitous human exposure to the vector, at least during part of the year. The highest infestation rates occurred during the peak of the rainy seasons, but a large presence was also observed during the early dry season (although with more variation among years). Spatial distribution of positive houses changed from a sparse and local pattern to a very dense pattern during the dry-wet season transition. These results suggest that the risk of dengue transmission and the potential for the new serotype invasions are high for most of the year.
Focal Points, Endogenous Processes, and Exogenous Shocks in the Autism Epidemic
Liu, Kayuet; Bearman, Peter S.
2014-01-01
Autism prevalence has increased rapidly in the United States during the past two decades. We have previously shown that the diffusion of information about autism through spatially proximate social relations has contributed significantly to the epidemic. This study expands on this finding by identifying the focal points for interaction that drive the proximity effect on subsequent diagnoses. We then consider how diffusion dynamics through interaction at critical focal points, in tandem with exogenous shocks, could have shaped the spatial dynamics of autism in California. We achieve these goals through an empirically calibrated simulation model of the whole population of 3- to 9-year-olds in California. We show that in the absence of interaction at these foci—principally malls and schools—we would not observe an autism epidemic. We also explore the idea that epigenetic changes affecting one generation in the distal past could shape the precise spatial patterns we observe among the next generation. PMID:26166907
DANGOL, Dharma Raj; MAHARJAN, Keshav Lall
2013-01-01
This paper describes changes of species composition and population of flora in space and time in western Chitwan, Nepal. This paper also discusses on the changes in flora due to flood and human activities. To illustrate these changes, we used survey data collected from January to April of 1996, 2000, and 2007 from the Barandabhar forest, National Park forest and the forests along the Narayani River banks, grasslands of National Park and common lands of western Chitwan as a part of longitudinal study on “reciprocal relation of population and the environment”. From these data, density values were calculated to analyze spatial and temporal changes in flora species composition and population. We also noted the changes of top species in time and space in due course of time. If the species and its rank not changed, their densities (population) values of flora species changed. We found that changes in species composition, population, appearance or disappearance of flora from a particular space (research plot) were noted as a result of natural forces or human activities. PMID:25061414
Dangol, Dharma Raj; Maharjan, Keshav Lall
2012-06-30
This paper describes changes of species composition and population of flora in space and time in western Chitwan, Nepal. This paper also discusses on the changes in flora due to flood and human activities. To illustrate these changes, we used survey data collected from January to April of 1996, 2000, and 2007 from the Barandabhar forest, National Park forest and the forests along the Narayani River banks, grasslands of National Park and common lands of western Chitwan as a part of longitudinal study on "reciprocal relation of population and the environment". From these data, density values were calculated to analyze spatial and temporal changes in flora species composition and population. We also noted the changes of top species in time and space in due course of time. If the species and its rank not changed, their densities (population) values of flora species changed. We found that changes in species composition, population, appearance or disappearance of flora from a particular space (research plot) were noted as a result of natural forces or human activities.
Risk and resilience in the late glacial: A case study from the western Mediterranean
NASA Astrophysics Data System (ADS)
Barton, C. Michael; Aura Tortosa, J. Emili; Garcia-Puchol, Oreto; Riel-Salvatore, Julien G.; Gauthier, Nicolas; Vadillo Conesa, Margarita; Pothier Bouchard, Geneviève
2018-03-01
The period spanning the Last Glacial Maximum through early Holocene encompasses dramatic and rapid environmental changes that offered both increased risk and new opportunities to human populations of the Mediterranean zone. The regional effects of global climate change varied spatially with latitude, topography, and distance from a shifting coastline; and human adaptations to these changes played out at these regional scales. To better understand the spatial and temporal dynamics of climate change and human social-ecological-technological systems (or SETS) during the transition from full glacial to interglacial, we carried out a meta-analysis of archaeological and paleoenvironmental datasets across the western Mediterranean region. We compiled information on prehistoric technology, land-use, and hunting strategies from 291 archaeological assemblages, recovered from 122 sites extending from southern Spain, through Mediterranean France, to northern and peninsular Italy, as well as 2,386 radiocarbon dates from across this region. We combine these data on human ecological dynamics with paleoenvironmental information derived from global climate models, proxy data, and estimates of coastlines modeled from sea level estimates and digital terrain. The LGM represents an ecologically predictable period for over much of the western Mediterranean, while the remainder of the Pleistocene was increasingly unpredictable, making it a period of increased ecological risk for hunter-gatherers. In response to increasing spatial and temporal uncertainty, hunter-gatherers reorganized different constituents of their SETS, allowing regional populations to adapt to these conditions up to a point. Beyond this threshold, rapid environmental change resulted in significant demographic change in Mediterranean hunter-gatherer populations.
Santos-Vega, Mauricio; Bouma, Menno J; Kohli, Vijay; Pascual, Mercedes
2016-01-01
Background The world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria. Methodology/principal findings Statistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors. Conclusion/significance Climate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission ‘hotspots’. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a “radical cure”. PMID:27906962
Santos-Vega, Mauricio; Bouma, Menno J; Kohli, Vijay; Pascual, Mercedes
2016-12-01
The world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria. Statistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors. Climate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission 'hotspots'. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a "radical cure".
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.
Space use and habitat selection by resident and transient red wolves (Canis rufus)
Hinton, Joseph W.; Proctor, Christine; Kelly, Marcella J.; van Manen, Frank T.; Vaughan, Michael R.; Chamberlain, Michael J.
2016-01-01
Recovery of large carnivores remains a challenge because complex spatial dynamics that facilitate population persistence are poorly understood. In particular, recovery of the critically endangered red wolf (Canis rufus) has been challenging because of its vulnerability to extinction via human-caused mortality and hybridization with coyotes (Canis latrans). Therefore, understanding red wolf space use and habitat selection is important to assist recovery because key aspects of wolf ecology such as interspecific competition, foraging, and habitat selection are well-known to influence population dynamics and persistence. During 2009–2011, we used global positioning system (GPS) radio-telemetry to quantify space use and 3rd-order habitat selection for resident and transient red wolves on the Albemarle Peninsula of eastern North Carolina. The Albemarle Peninsula was a predominantly agricultural landscape in which red wolves maintained spatially stable home ranges that varied between 25 km2 and 190 km2. Conversely, transient red wolves did not maintain home ranges and traversed areas between 122 km2 and 681 km2. Space use by transient red wolves was not spatially stable and exhibited shifting patterns until residency was achieved by individual wolves. Habitat selection was similar between resident and transient red wolves in which agricultural habitats were selected over forested habitats. However, transients showed stronger selection for edges and roads than resident red wolves. Behaviors of transient wolves are rarely reported in studies of space use and habitat selection because of technological limitations to observed extensive space use and because they do not contribute reproductively to populations. Transients in our study comprised displaced red wolves and younger dispersers that competed for limited space and mating opportunities. Therefore, our results suggest that transiency is likely an important life-history strategy for red wolves that facilitates metapopulation dynamics through short- and long-distance movements and eventual replacement of breeding residents lost to mortality.
Space Use and Habitat Selection by Resident and Transient Red Wolves (Canis rufus).
Hinton, Joseph W; Proctor, Christine; Kelly, Marcella J; van Manen, Frank T; Vaughan, Michael R; Chamberlain, Michael J
2016-01-01
Recovery of large carnivores remains a challenge because complex spatial dynamics that facilitate population persistence are poorly understood. In particular, recovery of the critically endangered red wolf (Canis rufus) has been challenging because of its vulnerability to extinction via human-caused mortality and hybridization with coyotes (Canis latrans). Therefore, understanding red wolf space use and habitat selection is important to assist recovery because key aspects of wolf ecology such as interspecific competition, foraging, and habitat selection are well-known to influence population dynamics and persistence. During 2009-2011, we used global positioning system (GPS) radio-telemetry to quantify space use and 3rd-order habitat selection for resident and transient red wolves on the Albemarle Peninsula of eastern North Carolina. The Albemarle Peninsula was a predominantly agricultural landscape in which red wolves maintained spatially stable home ranges that varied between 25 km2 and 190 km2. Conversely, transient red wolves did not maintain home ranges and traversed areas between 122 km2 and 681 km2. Space use by transient red wolves was not spatially stable and exhibited shifting patterns until residency was achieved by individual wolves. Habitat selection was similar between resident and transient red wolves in which agricultural habitats were selected over forested habitats. However, transients showed stronger selection for edges and roads than resident red wolves. Behaviors of transient wolves are rarely reported in studies of space use and habitat selection because of technological limitations to observed extensive space use and because they do not contribute reproductively to populations. Transients in our study comprised displaced red wolves and younger dispersers that competed for limited space and mating opportunities. Therefore, our results suggest that transiency is likely an important life-history strategy for red wolves that facilitates metapopulation dynamics through short- and long-distance movements and eventual replacement of breeding residents lost to mortality.
Space Use and Habitat Selection by Resident and Transient Red Wolves (Canis rufus)
Hinton, Joseph W.; Proctor, Christine; Kelly, Marcella J.; van Manen, Frank T.; Vaughan, Michael R.; Chamberlain, Michael J.
2016-01-01
Recovery of large carnivores remains a challenge because complex spatial dynamics that facilitate population persistence are poorly understood. In particular, recovery of the critically endangered red wolf (Canis rufus) has been challenging because of its vulnerability to extinction via human-caused mortality and hybridization with coyotes (Canis latrans). Therefore, understanding red wolf space use and habitat selection is important to assist recovery because key aspects of wolf ecology such as interspecific competition, foraging, and habitat selection are well-known to influence population dynamics and persistence. During 2009–2011, we used global positioning system (GPS) radio-telemetry to quantify space use and 3rd-order habitat selection for resident and transient red wolves on the Albemarle Peninsula of eastern North Carolina. The Albemarle Peninsula was a predominantly agricultural landscape in which red wolves maintained spatially stable home ranges that varied between 25 km2 and 190 km2. Conversely, transient red wolves did not maintain home ranges and traversed areas between 122 km2 and 681 km2. Space use by transient red wolves was not spatially stable and exhibited shifting patterns until residency was achieved by individual wolves. Habitat selection was similar between resident and transient red wolves in which agricultural habitats were selected over forested habitats. However, transients showed stronger selection for edges and roads than resident red wolves. Behaviors of transient wolves are rarely reported in studies of space use and habitat selection because of technological limitations to observed extensive space use and because they do not contribute reproductively to populations. Transients in our study comprised displaced red wolves and younger dispersers that competed for limited space and mating opportunities. Therefore, our results suggest that transiency is likely an important life-history strategy for red wolves that facilitates metapopulation dynamics through short- and long-distance movements and eventual replacement of breeding residents lost to mortality. PMID:28002495
Impacts of introduced Rangifer on ecosystem processes of maritime tundra on subarctic islands
Ricca, Mark; Miles, A. Keith; Van Vuren, Dirk H.; Eviner, Valerie T.
2016-01-01
Introductions of mammalian herbivores to remote islands without predators provide a natural experiment to ask how temporal and spatial variation in herbivory intensity alter feedbacks between plant and soil processes. We investigated ecosystem effects resulting from introductions of Rangifer tarandus (hereafter “Rangifer”) to native mammalian predator- and herbivore-free islands in the Aleutian archipelago of Alaska. We hypothesized that the maritime tundra of these islands would experience either: (1) accelerated ecosystem processes mediated by positive feedbacks between increased graminoid production and rapid nitrogen cycling; or (2) decelerated processes mediated by herbivory that stimulated shrub domination and lowered soil fertility. We measured summer plant and soil properties across three islands representing a chronosequence of elapsed time post-Rangifer introduction (Atka: ~100 yr; Adak: ~50; Kagalaska: ~0), with distinct stages of irruptive population dynamics of Rangifer nested within each island (Atka: irruption, K-overshoot, decline, K-re-equilibration; Adak: irruption, K-overshoot; Kagalaska: initial introduction). We also measured Rangifer spatial use within islands (indexed by pellet group counts) to determine how ecosystem processes responded to spatial variation in herbivory. Vegetation community response to herbivory varied with temporal and spatial scale. When comparing temporal effects using the island chronosequence, increased time since herbivore introduction led to more graminoids and fewer dwarf-shrubs, lichens, and mosses. Slow-growingCladonia lichens that are highly preferred winter forage were decimated on both long-termRangifer-occupied islands. In addition, linear relations between more concentrated Rangifer spatial use and reductions in graminoid and forb biomass within islands added spatial heterogeneity to long-term patterns identified by the chronosequence. These results support, in part, the hypothesis that Rangifer population persistence on islands is facilitated by successful exploitation of graminoid biomass as winter forage after palatable lichens are decimated. However, the shift from shrubs to graminoids was expected to enhance rates of nitrogen cycling, yet rates of net N-mineralization, NH4+ pools, and soil δ15N declined markedly along the chronosequence and were weakly associated with spatial use within islands. Overall plant and soil patterns were disrupted but responded differently to intermediate (50 yr) and long-term (100 yr) herbivory, and were correlated with distinct stages of irruptive population dynamics.
Badgley, Brian D; Ferguson, John; Vanden Heuvel, Amy; Kleinheinz, Gregory T; McDermott, Colleen M; Sandrin, Todd R; Kinzelman, Julie; Junion, Emily A; Byappanahalli, Muruleedhara N; Whitman, Richard L; Sadowsky, Michael J
2011-01-01
High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples. Copyright © 2010 Elsevier Ltd. All rights reserved.
Badgley, B.D.; Ferguson, J.; Heuvel, A.V.; Kleinheinz, G.T.; McDermott, C.M.; Sandrin, T.R.; Kinzelman, J.; Junion, E.A.; Byappanahalli, M.N.; Whitman, R.L.; Sadowsky, M.J.
2011-01-01
High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.
NASA Astrophysics Data System (ADS)
Daly, Aisling J.; Baetens, Jan M.; De Baets, Bernard
2016-12-01
Biodiversity has a critical impact on ecosystem functionality and stability, and thus the current biodiversity crisis has motivated many studies of the mechanisms that sustain biodiversity, a notable example being non-transitive or cyclic competition. We therefore extend existing microscopic models of communities with cyclic competition by incorporating resource dependence in demographic processes, characteristics of natural systems often oversimplified or overlooked by modellers. The spatially explicit nature of our individual-based model of three interacting species results in the formation of stable spatial structures, which have significant effects on community functioning, in agreement with experimental observations of pattern formation in microbial communities.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Butkus, Vytautas; Gelzinis, Andrius; Valkunas, Leonas
2015-06-07
Energy transfer processes and coherent phenomena in the fucoxanthin–chlorophyll protein complex, which is responsible for the light harvesting function in marine algae diatoms, were investigated at 77 K by using two-dimensional electronic spectroscopy. Experiments performed on femtosecond and picosecond timescales led to separation of spectral dynamics, witnessing evolutions of coherence and population states of the system in the spectral region of Q{sub y} transitions of chlorophylls a and c. Analysis of the coherence dynamics allowed us to identify chlorophyll (Chl) a and fucoxanthin intramolecular vibrations dominating over the first few picoseconds. Closer inspection of the spectral region of the Q{submore » y} transition of Chl c revealed previously not identified, mutually non-interacting chlorophyll c states participating in femtosecond or picosecond energy transfer to the Chl a molecules. Consideration of separated coherent and incoherent dynamics allowed us to hypothesize the vibrations-assisted coherent energy transfer between Chl c and Chl a and the overall spatial arrangement of chlorophyll molecules.« less
Neal, Allison T; Ross, Max S; Schall, Jos J; Vardo-Zalik, Anne M
2016-10-18
The geographic scale and degree of genetic differentiation for arthropod vectors that transmit parasites play an important role in the distribution, prevalence and coevolution of pathogens of human and wildlife significance. We determined the genetic diversity and population structure of the sand fly Lutzomyia vexator over spatial scales from 0.56 to 3.79 km at a study region in northern California. The study was provoked by observations of differentiation at fine spatial scales of a lizard malaria parasite vectored by Lu. vexator. A microsatellite enrichment/next-generation sequencing protocol was used to identify variable microsatellite loci within the genome of Lu. vexator. Alleles present at these loci were examined in four populations of Lu. vexator in Hopland, CA. Population differentiation was assessed using Fst and D (of Cavalli-Sforza and Edwards), and the program Structure was used to determine the degree of subdivision present. The effective population size for the sand fly populations was also calculated. Eight microsatellite markers were characterized and revealed high genetic diversity (uHe = 0.79-0.92, Na = 12-24) and slight but significant differentiation across the fine spatial scale examined (average pairwise D = 0.327; F ST = 0.0185 (95 % bootstrapped CI: 0.0102-0.0264). Even though the insects are difficult to capture using standard methods, the estimated population size was thousands per local site. The results argue that Lu. vexator at the study sites are abundant and not highly mobile, which may influence the overall transmission dynamics of the lizard malaria parasite, Plasmodium mexicanum, and other parasites transmitted by this species.
Scale-dependent seasonal pool habitat use by sympatric Wild Brook Trout and Brown Trout populations
Davis, Lori A.; Wagner, Tyler
2016-01-01
Sympatric populations of native Brook Trout Salvelinus fontinalis and naturalized Brown Trout Salmo truttaexist throughout the eastern USA. An understanding of habitat use by sympatric populations is of importance for fisheries management agencies because of the close association between habitat and population dynamics. Moreover, habitat use by stream-dwelling salmonids may be further complicated by several factors, including the potential for fish to display scale-dependent habitat use. Discrete-choice models were used to (1) evaluate fall and early winter daytime habitat use by sympatric Brook Trout and Brown Trout populations based on available residual pool habitat within a stream network and (2) assess the sensitivity of inferred habitat use to changes in the spatial scale of the assumed available habitat. Trout exhibited an overall preference for pool habitats over nonpool habitats; however, the use of pools was nonlinear over time. Brook Trout displayed a greater preference for deep residual pool habitats than for shallow pool and nonpool habitats, whereas Brown Trout selected for all pool habitat categories similarly. Habitat use by both species was found to be scale dependent. At the smallest spatial scale (50 m), habitat use was primarily related to the time of year and fish weight. However, at larger spatial scales (250 and 450 m), habitat use varied over time according to the study stream in which a fish was located. Scale-dependent relationships in seasonal habitat use by Brook Trout and Brown Trout highlight the importance of considering scale when attempting to make inferences about habitat use; fisheries managers may want to consider identifying the appropriate spatial scale when devising actions to restore and protect Brook Trout populations and their habitats.
Urban dogs in rural areas: Human-mediated movement defines dog populations in southern Chile.
Villatoro, Federico J; Sepúlveda, Maximiliano A; Stowhas, Paulina; Silva-Rodríguez, Eduardo A
2016-12-01
Management strategies for dog populations and their diseases include reproductive control, euthanasia and vaccination, among others. However, the effectiveness of these strategies can be severely affected by human-mediated dog movement. If immigration is important, then the location of origin of dogs imported by humans will be fundamental to define the spatial scales over which population management and research should apply. In this context, the main objective of our study was to determine the spatial extent of dog demographic processes in rural areas and the proportion of dogs that could be labeled as immigrants at multiple spatial scales. To address our objective we conducted surveys in households located in a rural landscape in southern Chile. Interviews allowed us to obtain information on the demographic characteristics of dogs in these rural settings, human influence on dog mortality and births, the localities of origin of dogs living in rural areas, and the spatial extent of human-mediated dog movement. We found that most rural dogs (64.1%) were either urban dogs that had been brought to rural areas (40.0%), or adopted dogs that had been previously abandoned in rural roads (24.1%). Some dogs were brought from areas located as far as ∼700km away from the study area. Human-mediated movement of dogs, especially from urban areas, seems to play a fundamental role in the population dynamics of dogs in rural areas. Consequently, local scale efforts to manage dog populations or their diseases are unlikely to succeed if implemented in isolation, simply because dogs can be brought from surrounding urban areas or even distant locations. We suggest that efforts to manage or study dog populations and related diseases should be implemented using a multi-scale approach. Copyright © 2016 Elsevier B.V. All rights reserved.
Coevolutionary dynamics of aspiration and strategy in spatial repeated public goods games
NASA Astrophysics Data System (ADS)
Wu, Te; Fu, Feng; Wang, Long
2018-06-01
The evolutionary dynamics remain largely unknown for spatial populations where individuals are more likely to interact repeatedly. Under this settings, individuals can make their decisions to cooperate or not based on the decisions previously adopted by others in their neighborhoods. Using repeated public goods game, we construct a spatial model and use a statistical physics approach to study the coevolutionary dynamics of aspiration and strategy. Individuals each have an aspiration towards the groups they are involved. According to the outcome of each group, individuals have assessment of whether their aspirations are satisfied. If satisfied, they cooperate next round. Otherwise, they switch to defecting. Results show threshold phenomenon for harsh collective dilemma: cooperators sticking to high levels of aspiration can prevail over defectors, while cooperators with other levels are invariably wiped out. When the collective dilemma is relaxed, cooperation is greatly facilitated by inducing a high level of diversity of aspiration. Snapshots further show the spatial patterns of how this coevolutionary process leads to the emergence of an optimal solution associated with aspiration level, whose corresponding strategy are most prevalent. This optimal solution lies in one and the highest aspiration level allowed, and depends on the intensity of the social dilemma. By removing the memory effect, our results also confirm that repeated interactions can promote cooperation, but to a limited degree.
Dynamics of land change in India: a fine-scale spatial analysis
NASA Astrophysics Data System (ADS)
Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.
2015-12-01
Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.
Variability in primary productivity determines metapopulation dynamics
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
Variability in primary productivity determines metapopulation dynamics.
Fernández, Néstor; Román, Jacinto; Delibes, Miguel
2016-04-13
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. © 2016 The Authors.
Dynamics of Reactive Microbial Hotspots in Concentration Gradient.
NASA Astrophysics Data System (ADS)
Hubert, A.; Farasin, J.; Tabuteau, H.; Dufresne, A.; Meheust, Y.; Le Borgne, T.
2017-12-01
In subsurface environments, bacteria play a major role in controlling the kinetics of a broad range of biogeochemical reactions. In such environments, nutrients fluxes and solute concentrations needed for bacteria metabolism may be highly variable in space and intermittent in time. This can lead to the formation of reactive hotspots where and when conditions are favorable to particular microorganisms, hence inducing biogeochemical reaction kinetics that differ significantly from those measured in homogeneous model environments. To investigate the impact of chemical gradients on the spatial structure and temporal dynamics of subsurface microorganism populations, we develop microfluidic cells allowing for a precise control of flow and chemical gradient conditions, as well as quantitative monitoring of the bacteria's spatial distribution and biofilm development. Using the non-motile Escherichia coli JW1908-1 strain and Gallionella capsiferriformans ES-2 as model organisms, we investigate the behavior and development of bacteria over a range of single and double concentration gradients in the concentrations of nutrients, electron donors and electron acceptors. We measure bacterial activity and population growth locally in precisely known hydrodynamic and chemical environments. This approach allows time-resolved monitoring of the location and intensity of reactive hotspots in micromodels as a function of the flow and chemical gradient conditions. We compare reactive microbial hotspot dynamics in our micromodels to classic growth laws and well-known growth parameters for the laboratory model bacteria Escherichia coli.We also discuss consequences for the formation and temporal dynamics of biofilms in the subsurface.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bentz, B.J.; Powell, J.A.; Logan, J.A.
1996-12-01
Colonization of a host tree by the mountain pine beetle (Dendroctonus ponderosae) involves chemical communication that enables a massive aggregation of beetles on a single resource, thereby ensuring host death and subsequent beetle population survival. Beetle populations have evolved a mechanism for termination of colonization on a lodgepole pine tree at optimal beetle densities, with a concomitant switch of attacks to nearby trees. Observations of the daily spatial and temporal attack process of mountain pine beetles (nonepidemic) attacking lodgepole pine suggest that beetles switch attacks to a new host tree before the original focus tree is fully colonized, and thatmore » verbenone, an antiaggregating pheromone, may be acting within a tree rather than between trees.« less
Unifying models of dialect spread and extinction using surface tension dynamics
2018-01-01
We provide a unified mathematical explanation of two classical forms of spatial linguistic spread. The wave model describes the radiation of linguistic change outwards from a central focus. Changes can also jump between population centres in a process known as hierarchical diffusion. It has recently been proposed that the spatial evolution of dialects can be understood using surface tension at linguistic boundaries. Here we show that the inclusion of long-range interactions in the surface tension model generates both wave-like spread, and hierarchical diffusion, and that it is surface tension that is the dominant effect in deciding the stable distribution of dialect patterns. We generalize the model to allow population mixing which can induce shrinkage of linguistic domains, or destroy dialect regions from within. PMID:29410847
Competitive intransitivity, population interaction structure, and strategy coexistence.
Laird, Robert A; Schamp, Brandon S
2015-01-21
Intransitive competition occurs when competing strategies cannot be listed in a hierarchy, but rather form loops-as in the game rock-paper-scissors. Due to its cyclic competitive replacement, competitive intransitivity promotes strategy coexistence, both in rock-paper-scissors and in higher-richness communities. Previous work has shown that this intransitivity-mediated coexistence is strongly influenced by spatially explicit interactions, compared to when populations are well mixed. Here, we extend and broaden this line of research and examine the impact on coexistence of intransitive competition taking place on a continuum of small-world networks linking spatial lattices and regular random graphs. We use simulations to show that the positive effect of competitive intransitivity on strategy coexistence holds when competition occurs on networks toward the spatial end of the continuum. However, in networks that are sufficiently disordered, increasingly violent fluctuations in strategy frequencies can lead to extinctions and the prevalence of monocultures. We further show that the degree of disorder that leads to the transition between these two regimes is positively dependent on population size; indeed for very large populations, intransitivity-mediated strategy coexistence may even be possible in regular graphs with completely random connections. Our results emphasize the importance of interaction structure in determining strategy dynamics and diversity. Copyright © 2014 Elsevier Ltd. All rights reserved.
Coexistence in streams: Do source-sink dynamics allow salamanders to persist with fish predators?
Sepulveda, A.J.; Lowe, W.H.
2011-01-01
Theory suggests that source-sink dynamics can allow coexistence of intraguild predators and prey, but empirical evidence for this coexistence mechanism is limited. We used capture-mark-recapture, genetic methods, and stable isotopes to test whether source-sink dynamics promote coexistence between stream fishes, the intraguild predator, and stream salamanders (Dicamptodon aterrimus), the intraguild prey. Salamander populations from upstream reaches without fish were predicted to maintain or supplement sink populations in downstream reaches with fish. We found instead that downstream reaches with fish were not sinks even though fish consumed salamander larvae-apparent survival, recruitment, and population growth rate did not differ between upstream and downstream reaches. There was also no difference between upstream and downstream reaches in net emigration. We did find that D. aterrimus moved frequently along streams, but believe that this is a response to seasonal habitat changes rather than intraguild predation. Our study provides empirical evidence that local-scale mechanisms are more important than dispersal dynamics to coexistence of streams salamanders and fish. More broadly, it shows the value of empirical data on dispersal and gene flow for distinguishing between local and spatial mechanisms of coexistence. ?? 2011 Springer-Verlag.
Messinger, Susanna M; Ostling, Annette
2013-11-01
Predation interactions are an important element of ecological communities. Population spatial structure has been shown to influence predator evolution, resulting in the evolution of a reduced predator attack rate; however, the evolutionary role of traits governing predator and prey ecology is unknown. The evolutionary effect of spatial structure on a predator's attack rate has primarily been explored assuming a fixed metapopulation spatial structure, and understood in terms of group selection. But endogenously generated, emergent spatial structure is common in nature. Furthermore, the evolutionary influence of ecological traits may be mediated through the spatial self-structuring process. Drawing from theory on pathogens, the evolutionary effect of emergent spatial structure can be understood in terms of self-shading, where a voracious predator limits its long-term invasion potential by reducing local prey availability. Here we formalize the effects of self-shading for predators using spatial moment equations. Then, through simulations, we show that in a spatial context self-shading leads to relationships between predator-prey ecology and the predator's attack rate that are not expected in a non-spatial context. Some relationships are analogous to relationships already shown for host-pathogen interactions, but others represent new trait dimensions. Finally, since understanding the effects of ecology using existing self-shading theory requires simplifications of the emergent spatial structure that do not apply well here, we also develop metrics describing the complex spatial structure of the predator and prey populations to help us explain the evolutionary effect of predator and prey ecology in the context of self-shading. The identification of these metrics may provide a step towards expansion of the predictive domain of self-shading theory to more complex spatial dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.
Using population genetic tools to develop a control strategy for feral cats (Felis catus) in Hawai'i
Hansen, H.; Hess, S.C.; Cole, D.; Banko, P.C.
2007-01-01
Population genetics can provide information about the demographics and dynamics of invasive species that is beneficial for developing effective control strategies. We studied the population genetics of feral cats on Hawai'i Island by microsatellite analysis to evaluate genetic diversity and population structure, assess gene flow and connectivity among three populations, identify potential source populations, characterise population dynamics, and evaluate sex-biased dispersal. High genetic diversity, low structure, and high number of migrants per generation supported high gene flow that was not limited spatially. Migration rates revealed that most migration occurred out of West Mauna Kea. Effective population size estimates indicated increasing cat populations despite control efforts. Despite high gene flow, relatedness estimates declined significantly with increased geographic distance and Bayesian assignment tests revealed the presence of three population clusters. Genetic structure and relatedness estimates indicated male-biased dispersal, primarily from Mauna Kea, suggesting that this population should be targeted for control. However, recolonisation seems likely, given the great dispersal ability that may not be inhibited by barriers such as lava flows. Genetic monitoring will be necessary to assess the effectiveness of future control efforts. Management of other invasive species may benefit by employing these population genetic tools. ?? CSIRO 2007.
Lemey, Philippe; Rambaut, Andrew; Bedford, Trevor; Faria, Nuno; Bielejec, Filip; Baele, Guy; Russell, Colin A; Smith, Derek J; Pybus, Oliver G; Brockmann, Dirk; Suchard, Marc A
2014-02-01
Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.
Spatially explicit modeling in ecology: A review
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.
The Evolution of Phenotypic Switching in Subdivided Populations
Carja, Oana; Liberman, Uri; Feldman, Marcus W.
2014-01-01
Stochastic switching is an example of phenotypic bet hedging, where offspring can express a phenotype different from that of their parents. Phenotypic switching is well documented in viruses, yeast, and bacteria and has been extensively studied when the selection pressures vary through time. However, there has been little work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in determining the evolutionary dynamics of phenotypic switching. We find that the stable switching rate is mainly determined by the rate of environmental change and the migration rate. This stable rate is also a decreasing function of the recombination rate, although this is a weaker effect than those of either the period of environmental change or the migration rate. This study highlights the interplay of spatial and temporal environmental variability, offering new insights into how migration can influence the evolution of phenotypic switching rates, mutation rates, or other sources of phenotypic variation. PMID:24496012
Large scale, synchronous variability of marine fish populations driven by commercial exploitation.
Frank, Kenneth T; Petrie, Brian; Leggett, William C; Boyce, Daniel G
2016-07-19
Synchronous variations in the abundance of geographically distinct marine fish populations are known to occur across spatial scales on the order of 1,000 km and greater. The prevailing assumption is that this large-scale coherent variability is a response to coupled atmosphere-ocean dynamics, commonly represented by climate indexes, such as the Atlantic Multidecadal Oscillation and North Atlantic Oscillation. On the other hand, it has been suggested that exploitation might contribute to this coherent variability. This possibility has been generally ignored or dismissed on the grounds that exploitation is unlikely to operate synchronously at such large spatial scales. Our analysis of adult fishing mortality and spawning stock biomass of 22 North Atlantic cod (Gadus morhua) stocks revealed that both the temporal and spatial scales in fishing mortality and spawning stock biomass were equivalent to those of the climate drivers. From these results, we conclude that greater consideration must be given to the potential of exploitation as a driving force behind broad, coherent variability of heavily exploited fish species.
Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases
NASA Astrophysics Data System (ADS)
Belik, Vitaly; Geisel, Theo; Brockmann, Dirk
2011-08-01
We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.
Investigating Bacterial-Animal Symbioses with Light Sheet Microscopy
Taormina, Michael J.; Jemielita, Matthew; Stephens, W. Zac; Burns, Adam R.; Troll, Joshua V.; Parthasarathy, Raghuveer; Guillemin, Karen
2014-01-01
SUMMARY Microbial colonization of the digestive tract is a crucial event in vertebrate development, required for maturation of host immunity and establishment of normal digestive physiology. Advances in genomic, proteomic, and metabolomic technologies are providing a more detailed picture of the constituents of the intestinal habitat, but these approaches lack the spatial and temporal resolution needed to characterize the assembly and dynamics of microbial communities in this complex environment. We report the use of light sheet microscopy to provide high resolution imaging of bacterial colonization of the zebrafish intestine. The methodology allows us to characterize bacterial population dynamics across the entire organ and the behaviors of individual bacterial and host cells throughout the colonization process. The large four-dimensional datasets generated by these imaging approaches require new strategies for image analysis. When integrated with other “omics” datasets, information about the spatial and temporal dynamics of microbial cells within the vertebrate intestine will provide new mechanistic insights into how microbial communities assemble and function within hosts. PMID:22983029
Brenda Rashleigh; Gary D. Grossman
2005-01-01
We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...
Within-population spatial synchrony in mast seeding of North American oaks.
A.V. Liebhold; M. Sork; O.N. Peltonen; Westfall R. Bjørnstad; J. Elkinton; M. H. J. Knops
2004-01-01
Mast seeding, the synchronous production of large crops of seeds, has been frequently documented in oak species. In this study we used several North American oak data-sets to quantify within-stand (10 km) synchrony in mast dynamics. Results indicated that intraspecific synchrony in seed production always exceeded interspecific synchrony and was essentially constant...
Catherine A. Eyre; Melina Kozanitas; Matteo Garbelotto
2013-01-01
We present a study of the epidemiology of sudden oak death (SOD) in California within a watershed based on temporally and spatially replicated surveys of symptoms, viability of the pathogen from symptomatic leaves, and genetic analyses using polymorphic SSR markers.Phytophthora ramorum is sensitive to climate; its...
Understanding and responding to earthquake hazards
NASA Technical Reports Server (NTRS)
Raymond, C. A.; Lundgren, P. R.; Madsen, S. N.; Rundle, J. B.
2002-01-01
Advances in understanding of the earthquake cycle and in assessing earthquake hazards is a topic of great importance. Dynamic earthquake hazard assessments resolved for a range of spatial scales and time scales will allow a more systematic approach to prioritizing the retrofitting of vulnerable structures, relocating populations at risk, protecting lifelines, preparing for disasters, and educating the public.
Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D
2008-11-07
Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.
Noise-induced effects in population dynamics
NASA Astrophysics Data System (ADS)
Spagnolo, Bernardo; Cirone, Markus; La Barbera, Antonino; de Pasquale, Ferdinando
2002-03-01
We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of spatial patterns in the first case. In the other case we obtain the asymptotic behaviour of the time average of the ith population and discuss the effect of the noise on the probability distributions of the population and of the local field.
Owen-Smith, Norman
2011-07-01
1. There is a pressing need for population models that can reliably predict responses to changing environmental conditions and diagnose the causes of variation in abundance in space as well as through time. In this 'how to' article, it is outlined how standard population models can be modified to accommodate environmental variation in a heuristically conducive way. This approach is based on metaphysiological modelling concepts linking populations within food web contexts and underlying behaviour governing resource selection. Using population biomass as the currency, population changes can be considered at fine temporal scales taking into account seasonal variation. Density feedbacks are generated through the seasonal depression of resources even in the absence of interference competition. 2. Examples described include (i) metaphysiological modifications of Lotka-Volterra equations for coupled consumer-resource dynamics, accommodating seasonal variation in resource quality as well as availability, resource-dependent mortality and additive predation, (ii) spatial variation in habitat suitability evident from the population abundance attained, taking into account resource heterogeneity and consumer choice using empirical data, (iii) accommodating population structure through the variable sensitivity of life-history stages to resource deficiencies, affecting susceptibility to oscillatory dynamics and (iv) expansion of density-dependent equations to accommodate various biomass losses reducing population growth rate below its potential, including reductions in reproductive outputs. Supporting computational code and parameter values are provided. 3. The essential features of metaphysiological population models include (i) the biomass currency enabling within-year dynamics to be represented appropriately, (ii) distinguishing various processes reducing population growth below its potential, (iii) structural consistency in the representation of interacting populations and (iv) capacity to accommodate environmental variation in space as well as through time. Biomass dynamics provide a common currency linking behavioural, population and food web ecology. 4. Metaphysiological biomass loss accounting provides a conceptual framework more conducive for projecting and interpreting the population consequences of climatic shifts and human transformations of habitats than standard modelling approaches. © 2011 The Author. Journal of Animal Ecology © 2011 British Ecological Society.
Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat
Thogmartin, Wayne E.; Diffendorfer, Jay E.; Russell, Robin E.; Szymanski, Jennifer A.
2016-01-01
Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat (Myotis sodalis), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans, disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity. PMID:28028486
Swarming Patterns in a Two-Dimensional Kinematic Model for Biological Groups
NASA Astrophysics Data System (ADS)
Topaz, Chad
2004-03-01
We construct a continuum model for the motion of biological organisms experiencing social interactions and study its pattern-forming behavior. The model takes the form of a conservation law in two spatial dimensions. Social interactions are modeled in the velocity term, which is nonlocal in the population density. The dynamics of the model may be uniquely decomposed into incompressible motion and potential motion. For the purely incompressible case, the model resembles that for fluid dynamical vortex patches. There exist solutions that have constant population density and compact support for all time. Numerical simulations produce rotating structures with circular cores and spiral arms, reminiscent of naturally observed swarms such as ant mills. For the purely potential case, the model resembles a nonlocal (forwards or backwards) porous media equation, describing aggregation or dispersion of the population. For the aggregative case, the population clumps into regions of high and low density with a predictable characteristic length scale that is confirmed by numerical simulations.