population dynamic processes: Topics by Science.gov

Sample records for population dynamic processes

Individual movement behavior, matrix heterogeneity, and the dynamics of spatially structured populations.

PubMed

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.
Population Dynamics of Genetic Regulatory Networks

NASA Astrophysics Data System (ADS)

Braun, Erez

2005-03-01

Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.
Geographic variation in density-dependent dynamics impacts the synchronizing effect of dispersal and regional stochasticity

Treesearch

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...
Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

PubMed

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.
Inferring infection hazard in wildlife populations by linking data across individual and population scales.

PubMed

Pepin, Kim M; Kay, Shannon L; Golas, Ben D; Shriner, Susan S; Gilbert, Amy T; Miller, Ryan S; Graham, Andrea L; Riley, Steven; Cross, Paul C; Samuel, Michael D; Hooten, Mevin B; Hoeting, Jennifer A; Lloyd-Smith, James O; Webb, Colleen T; Buhnerkempe, Michael G

2017-03-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease. © 2017 John Wiley & Sons Ltd/CNRS.
Inferring infection hazard in wildlife populations by linking data across individual and population scales

USGS Publications Warehouse

Pepin, Kim M.; Kay, Shannon L.; Golas, Ben D.; Shriner, Susan A.; Gilbert, Amy T.; Miller, Ryan S.; Graham, Andrea L.; Riley, Steven; Cross, Paul C.; Samuel, Michael D.; Hooten, Mevin B.; Hoeting, Jennifer A.; Lloyd-Smith, James O.; Webb, Colleen T.; Buhnerkempe, Michael G.

2017-01-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.
Gaussian process-based Bayesian nonparametric inference of population size trajectories from gene genealogies.

PubMed

Palacios, Julia A; Minin, Vladimir N

2013-03-01

Changes in population size influence genetic diversity of the population and, as a result, leave a signature of these changes in individual genomes in the population. We are interested in the inverse problem of reconstructing past population dynamics from genomic data. We start with a standard framework based on the coalescent, a stochastic process that generates genealogies connecting randomly sampled individuals from the population of interest. These genealogies serve as a glue between the population demographic history and genomic sequences. It turns out that only the times of genealogical lineage coalescences contain information about population size dynamics. Viewing these coalescent times as a point process, estimating population size trajectories is equivalent to estimating a conditional intensity of this point process. Therefore, our inverse problem is similar to estimating an inhomogeneous Poisson process intensity function. We demonstrate how recent advances in Gaussian process-based nonparametric inference for Poisson processes can be extended to Bayesian nonparametric estimation of population size dynamics under the coalescent. We compare our Gaussian process (GP) approach to one of the state-of-the-art Gaussian Markov random field (GMRF) methods for estimating population trajectories. Using simulated data, we demonstrate that our method has better accuracy and precision. Next, we analyze two genealogies reconstructed from real sequences of hepatitis C and human Influenza A viruses. In both cases, we recover more believed aspects of the viral demographic histories than the GMRF approach. We also find that our GP method produces more reasonable uncertainty estimates than the GMRF method. Copyright © 2013, The International Biometric Society.
[The impact of the social economic conditions on the reproduction processes].

PubMed

Leonova, N G

2007-01-01

The social economic conditions of population reproduction in the Trans-Dniester Region with the emphasis on its specifics are analyzed. The natural dynamics of population is estimated including gender and age peculiarities, marriage and divorces statistics, migration processes and population health in the region. It is shown that the population reproduction dynamics follows the natural laws and processes. The role of the post-Soviet period social economic conditions harmful to health are considered. The interdependencies between the social economic development and population reproduction are revealed. The recommendations related to the means of the further enhancement of social economic conditions as related to population reproduction in the Trans-Dniester Region are proposed.
Alternating event processes during lifetimes: population dynamics and statistical inference.

PubMed

Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng

2018-01-01

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.
SPATIAL SCALE OF AUTOCORRELATION IN WISCONSIN FROG AND TOAD SURVEY DATA

EPA Science Inventory

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 ...
Biomolecular Modeling in a Process Dynamics and Control Course

ERIC Educational Resources Information Center

Gray, Jeffrey J.

2006-01-01

I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large-scale…
POPULATION DYNAMICS OF AMBIENT AND ALTERED EARTHWORM COMMUNITIES IN ROW-CROP AGROECOSYSTEMS IN OHIO, USA

EPA Science Inventory

Although earthworms are known to influence agroecosystem processes, there are relatively few long-term studies addressing population dynamics under cropping systems in which earthworm populations were intentionally altered. We assessed earthworm communities from fall 1994 to spr...
NexGen PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We examine how the integration of evolutionary and ecological processes in population dynamics – an emerging framework in ecology – could be incorporated into population viability analysis (PVA). Driven by parallel, complementary advances in population genomics and computational ...
Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.

2015-01-01

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.
Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

Bateman, Andrew W; Ozgul, Arpat; Coulson, Tim; Clutton-Brock, Tim H

2012-05-01

1. For social species, the link between individual behaviour and population dynamics is mediated by group-level demography. 2. Populations of obligate cooperative breeders are structured into social groups, which may be subject to inverse density dependence (Allee effects) that result from a dependence on conspecific helpers, but evidence for population-wide Allee effects is rare. 3. We use field data from a long-term study of cooperative meerkats (Suricata suricatta; Schreber, 1776) - a species for which local Allee effects are not reflected in population-level dynamics - to empirically model interannual group dynamics. 4. Using phenomenological population models, modified to incorporate environmental conditions and potential Allee effects, we first investigate overall patterns of group dynamics and find support only for conventional density dependence that increases after years of low rainfall. 5. To explain the observed patterns, we examine specific demographic rates and assess their contributions to overall group dynamics. Although per-capita meerkat mortality is subject to a component Allee effect, it contributes relatively little to observed variation in group dynamics, and other (conventionally density dependent) demographic rates - especially emigration - govern group dynamics. 6. Our findings highlight the need to consider demographic processes and density dependence in subpopulations before drawing conclusions about how behaviour affects population processes in socially complex systems. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.
Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

Treesearch

Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

2017-01-01

The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...
Stochastic gain in finite populations

NASA Astrophysics Data System (ADS)

Röhl, Torsten; Traulsen, Arne; Claussen, Jens Christian; Schuster, Heinz Georg

2008-08-01

Flexible learning rates can lead to increased payoffs under the influence of noise. In a previous paper [Traulsen , Phys. Rev. Lett. 93, 028701 (2004)], we have demonstrated this effect based on a replicator dynamics model which is subject to external noise. Here, we utilize recent advances on finite population dynamics and their connection to the replicator equation to extend our findings and demonstrate the stochastic gain effect in finite population systems. Finite population dynamics is inherently stochastic, depending on the population size and the intensity of selection, which measures the balance between the deterministic and the stochastic parts of the dynamics. This internal noise can be exploited by a population using an appropriate microscopic update process, even if learning rates are constant.
Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

PubMed

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.
Dispersal, density dependence, and population dynamics of a fungal microbe on leaf surfaces.

PubMed

Woody, Scott T; Ives, Anthony R; Nordheim, Erik V; Andrews, John H

2007-06-01

Despite the ubiquity and importance of microbes in nature, little is known about their natural population dynamics, especially for those that occupy terrestrial habitats. Here we investigate the dynamics of the yeast-like fungus Aureobasidium pullulans (Ap) on apple leaves in an orchard. We asked three questions. (1) Is variation in fungal population density among leaves caused by variation in leaf carrying capacities and strong density-dependent population growth that maintains densities near carrying capacity? (2) Do resident populations have competitive advantages over immigrant cells? (3) Do Ap dynamics differ at different times during the growing season? To address these questions, we performed two experiments at different times in the growing season. Both experiments used a 2 x 2 factorial design: treatment 1 removed fungal cells from leaves to reveal density-dependent population growth, and treatment 2 inoculated leaves with an Ap strain engineered to express green fluorescent protein (GFP), which made it possible to track the fate of immigrant cells. The experiments showed that natural populations of Ap vary greatly in density due to sustained differences in carrying capacities among leaves. The maintenance of populations close to carrying capacities indicates strong density-dependent processes. Furthermore, resident populations are strongly competitive against immigrants, while immigrants have little impact on residents. Finally, statistical models showed high population growth rates of resident cells in one experiment but not in the other, suggesting that Ap experiences relatively "good" and "bad" periods for population growth. This picture of Ap dynamics conforms to commonly held, but rarely demonstrated, expectations of microbe dynamics in nature. It also highlights the importance of local processes, as opposed to immigration, in determining the abundance and dynamics of microbes on surfaces in terrestrial systems.
Rapid evolution leads to differential population dynamics and top-down control in resurrected Daphnia populations.

PubMed

Goitom, Eyerusalem; Kilsdonk, Laurens J; Brans, Kristien; Jansen, Mieke; Lemmens, Pieter; De Meester, Luc

2018-01-01

There is growing evidence of rapid genetic adaptation of natural populations to environmental change, opening the perspective that evolutionary trait change may subsequently impact ecological processes such as population dynamics, community composition, and ecosystem functioning. To study such eco-evolutionary feedbacks in natural populations, however, requires samples across time. Here, we capitalize on a resurrection ecology study that documented rapid and adaptive evolution in a natural population of the water flea Daphnia magna in response to strong changes in predation pressure by fish, and carry out a follow-up mesocosm experiment to test whether the observed genetic changes influence population dynamics and top-down control of phytoplankton. We inoculated populations of the water flea D. magna derived from three time periods of the same natural population known to have genetically adapted to changes in predation pressure in replicate mesocosms and monitored both Daphnia population densities and phytoplankton biomass in the presence and absence of fish. Our results revealed differences in population dynamics and top-down control of algae between mesocosms harboring populations from the time period before, during, and after a peak in fish predation pressure caused by human fish stocking. The differences, however, deviated from our a priori expectations. An S-map approach on time series revealed that the interactions between adults and juveniles strongly impacted the dynamics of populations and their top-down control on algae in the mesocosms, and that the strength of these interactions was modulated by rapid evolution as it occurred in nature. Our study provides an example of an evolutionary response that fundamentally alters the processes structuring population dynamics and impacts ecosystem features.

Incorporating evolutionary processes into population viability models.

PubMed

Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G

2015-06-01

We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. © 2014 Society for Conservation Biology.
Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process

NASA Astrophysics Data System (ADS)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-01

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.
Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

PubMed

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.
An individual-based model of zebrafish population dynamics accounting for energy dynamics.

PubMed

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

2015-01-01

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

PubMed Central

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

2015-01-01

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

PubMed

Hite, Jessica L; Cressler, Clayton E

2018-05-05

What drives the evolution of parasite life-history traits? Recent studies suggest that linking within- and between-host processes can provide key insight into both disease dynamics and parasite evolution. Still, it remains difficult to understand how to pinpoint the critical factors connecting these cross-scale feedbacks, particularly under non-equilibrium conditions; many natural host populations inherently fluctuate and parasites themselves can strongly alter the stability of host populations. Here, we develop a general model framework that mechanistically links resources to parasite evolution across a gradient of stable and unstable conditions. First, we dynamically link resources and between-host processes (host density, stability, transmission) to virulence evolution, using a 'non-nested' model. Then, we consider a 'nested' model where population-level processes (transmission and virulence) depend on resource-driven changes to individual-level (within-host) processes (energetics, immune function, parasite production). Contrary to 'non-nested' model predictions, the 'nested' model reveals complex effects of host population dynamics on parasite evolution, including regions of evolutionary bistability; evolution can push parasites towards strongly or weakly stabilizing strategies. This bistability results from dynamic feedbacks between resource-driven changes to host density, host immune function and parasite production. Together, these results highlight how cross-scale feedbacks can provide key insights into the structuring role of parasites and parasite evolution.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Author(s).
Integrating host, natural enemy, and other processes in population models of the pine sawfly

Treesearch

A. A. Sharov

1991-01-01

Explanation of population dynamics is one of the main problems in population ecology. There are two main approaches to the explanation: the factor approach and the dynamic approach. According to the first, an explanation is obtained when the effect of various environmental factors on population density is revealed. Such analysis is performed using well developed...
Dynamic Noise and its Role in Understanding Epidemiological Processes

NASA Astrophysics Data System (ADS)

Stollenwerk, Nico; Aguiar, Maíra

2010-09-01

We investigate the role of dynamic noise in understanding epidemiological systems, such as influenza or dengue fever by deriving stochastic ordinary differential equations from markov processes for discrete populations. This approach allows for an easy analysis of dynamical noise transitions between co-existing attractors.
Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.
Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

Game theory ideas provide a useful framework for studying evolutionary dynamics in a well-mixed environment. This approach, however, typically enforces a strictly fixed overall population size, deemphasizing natural growth processes. We study a competitive Lotka-Volterra model, with number fluctuations, that accounts for natural population growth and encompasses interaction scenarios typical of evolutionary games. We show that, in an appropriate limit, the model describes standard evolutionary games with both genetic drift and overall population size fluctuations. However, there are also regimes where a varying population size can strongly influence the evolutionary dynamics. We focus on the strong mutualism scenario and demonstrate that standard evolutionary game theory fails to describe our simulation results. We then analytically and numerically determine fixation probabilities as well as mean fixation times using matched asymptotic expansions, taking into account the population size degree of freedom. These results elucidate the interplay between population dynamics and evolutionary dynamics in well-mixed systems.
Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications

EPA Science Inventory

Eco-evolutionary population models are powerful new tools for exploring howevolutionary processes influence plant and animal population dynamics andvice-versa. The need to manage for climate change and other dynamicdisturbance regimes is creating a demand for the incorporation of...
Coevolutionary dynamics in large, but finite populations

NASA Astrophysics Data System (ADS)

Traulsen, Arne; Claussen, Jens Christian; Hauert, Christoph

2006-07-01

Coevolving and competing species or game-theoretic strategies exhibit rich and complex dynamics for which a general theoretical framework based on finite populations is still lacking. Recently, an explicit mean-field description in the form of a Fokker-Planck equation was derived for frequency-dependent selection with two strategies in finite populations based on microscopic processes [A. Traulsen, J. C. Claussen, and C. Hauert, Phys. Rev. Lett. 95, 238701 (2005)]. Here we generalize this approach in a twofold way: First, we extend the framework to an arbitrary number of strategies and second, we allow for mutations in the evolutionary process. The deterministic limit of infinite population size of the frequency-dependent Moran process yields the adjusted replicator-mutator equation, which describes the combined effect of selection and mutation. For finite populations, we provide an extension taking random drift into account. In the limit of neutral selection, i.e., whenever the process is determined by random drift and mutations, the stationary strategy distribution is derived. This distribution forms the background for the coevolutionary process. In particular, a critical mutation rate uc is obtained separating two scenarios: above uc the population predominantly consists of a mixture of strategies whereas below uc the population tends to be in homogeneous states. For one of the fundamental problems in evolutionary biology, the evolution of cooperation under Darwinian selection, we demonstrate that the analytical framework provides excellent approximations to individual based simulations even for rather small population sizes. This approach complements simulation results and provides a deeper, systematic understanding of coevolutionary dynamics.
The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics.

PubMed

Turcotte, Martin M; Reznick, David N; Hare, J Daniel

2011-11-01

Rapid evolution challenges the assumption that evolution is too slow to impact short-term ecological dynamics. This insight motivates the study of 'Eco-Evolutionary Dynamics' or how evolution and ecological processes reciprocally interact on short time scales. We tested how rapid evolution impacts concurrent population dynamics using an aphid (Myzus persicae) and an undomesticated host (Hirschfeldia incana) in replicated wild populations. We manipulated evolvability by creating non-evolving (single clone) and potentially evolving (two-clone) aphid populations that contained genetic variation in intrinsic growth rate. We observed significant evolution in two-clone populations whether or not they were exposed to predators and competitors. Evolving populations grew up to 42% faster and attained up to 67% higher density, compared with non-evolving control populations but only in treatments exposed to competitors and predators. Increased density also correlates with relative fitness of competing clones suggesting a full eco-evolutionary dynamic cycle defined as reciprocal interactions between evolution and density. © 2011 Blackwell Publishing Ltd/CNRS.
Climate effects and feedback structure determining weed population dynamics in a long-term experiment.

PubMed

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements.
Climate Effects and Feedback Structure Determining Weed Population Dynamics in a Long-Term Experiment

PubMed Central

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements. PMID:22272362
Allee effects and the spatial dynamics of a locally endangered butterfly, the high brown fritillary (Argynnis adippe).

PubMed

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.
Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

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.
Structural drift: the population dynamics of sequential learning.

PubMed

Crutchfield, James P; Whalen, Sean

2012-01-01

We introduce a theory of sequential causal inference in which learners in a chain estimate a structural model from their upstream "teacher" and then pass samples from the model to their downstream "student". It extends the population dynamics of genetic drift, recasting Kimura's selectively neutral theory as a special case of a generalized drift process using structured populations with memory. We examine the diffusion and fixation properties of several drift processes and propose applications to learning, inference, and evolution. We also demonstrate how the organization of drift process space controls fidelity, facilitates innovations, and leads to information loss in sequential learning with and without memory.
Deterministic processes guide long-term synchronised population dynamics in replicate anaerobic digesters

PubMed Central

Vanwonterghem, Inka; Jensen, Paul D; Dennis, Paul G; Hugenholtz, Philip; Rabaey, Korneel; Tyson, Gene W

2014-01-01

A replicate long-term experiment was conducted using anaerobic digestion (AD) as a model process to determine the relative role of niche and neutral theory on microbial community assembly, and to link community dynamics to system performance. AD is performed by a complex network of microorganisms and process stability relies entirely on the synergistic interactions between populations belonging to different functional guilds. In this study, three independent replicate anaerobic digesters were seeded with the same diverse inoculum, supplied with a model substrate, α-cellulose, and operated for 362 days at a 10-day hydraulic residence time under mesophilic conditions. Selective pressure imposed by the operational conditions and model substrate caused large reproducible changes in community composition including an overall decrease in richness in the first month of operation, followed by synchronised population dynamics that correlated with changes in reactor performance. This included the synchronised emergence and decline of distinct Ruminococcus phylotypes at day 148, and emergence of a Clostridium and Methanosaeta phylotype at day 178, when performance became stable in all reactors. These data suggest that many dynamic functional niches are predictably filled by phylogenetically coherent populations over long time scales. Neutral theory would predict that a complex community with a high degree of recognised functional redundancy would lead to stochastic changes in populations and community divergence over time. We conclude that deterministic processes may play a larger role in microbial community dynamics than currently appreciated, and under controlled conditions it may be possible to reliably predict community structural and functional changes over time. PMID:24739627
Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

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.

Exploring Population Admixture Dynamics via Empirical and Simulated Genome-wide Distribution of Ancestral Chromosomal Segments

PubMed Central

Jin, Wenfei; Wang, Sijia; Wang, Haifeng; Jin, Li; Xu, Shuhua

2012-01-01

The processes of genetic admixture determine the haplotype structure and linkage disequilibrium patterns of the admixed population, which is important for medical and evolutionary studies. However, most previous studies do not consider the inherent complexity of admixture processes. Here we proposed two approaches to explore population admixture dynamics, and we demonstrated, by analyzing genome-wide empirical and simulated data, that the approach based on the distribution of chromosomal segments of distinct ancestry (CSDAs) was more powerful than that based on the distribution of individual ancestry proportions. Analysis of 1,890 African Americans showed that a continuous gene flow model, in which the African American population continuously received gene flow from European populations over about 14 generations, best explained the admixture dynamics of African Americans among several putative models. Interestingly, we observed that some African Americans had much more European ancestry than the simulated samples, indicating substructures of local ancestries in African Americans that could have been caused by individuals from some particular lineages having repeatedly admixed with people of European ancestry. In contrast, the admixture dynamics of Mexicans could be explained by a gradual admixture model in which the Mexican population continuously received gene flow from both European and Amerindian populations over about 24 generations. Our results also indicated that recent gene flows from Sub-Saharan Africans have contributed to the gene pool of Middle Eastern populations such as Mozabite, Bedouin, and Palestinian. In summary, this study not only provides approaches to explore population admixture dynamics, but also advances our understanding on population history of African Americans, Mexicans, and Middle Eastern populations. PMID:23103229
Coordinated dynamic encoding in the retina using opposing forms of plasticity

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2011-01-01

The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice, and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This novel dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals, and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails. PMID:21909086
How Does a Divided Population Respond to Change?

PubMed

Qubbaj, Murad R; Muneepeerakul, Rachata; Aggarwal, Rimjhim M; Anderies, John M

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics--as opposed to an independent process--of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions.
Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR-fingerprinting.

PubMed

da Silva-Filho, Eurípedes Alves; Brito dos Santos, Scheila Karina; Resende, Alecsandra do Monte; de Morais, José Otamar Falcão; de Morais, Marcos Antonio; Ardaillon Simões, Diogo

2005-07-01

Yeast population used in industrial production of fuel-ethanol may vary according to the plant process condition and to the environmental stresses imposed to yeast cells. Therefore, yeast strains isolated from a particular industrial process may be adapted to such conditions and should be used as starter strain instead of less adapted commercial strains. This work reports the use of PCR-fingerprinting method based on microsatellite primer (GTG)5 to characterize the yeast population dynamics along the fermentation period in six distilleries. The results show that indigenous fermenting strains present in the crude substrate can be more adapted to the industrial process than commercial strains. We also identified new strains that dominate the yeast population and were more present either in molasses or sugar cane fermenting distilleries. Those strains were proposed to be used as starters in those industrial processes. This is the first report on the use of molecular markers to discriminate Saccharomyces cerevisiae strains from fuel-ethanol producing process.
Environmental variability and population dynamics: Do European and North American ducks play by the same rules?

USGS Publications Warehouse

Pöysä, Hannu; Rintala, Jukka; Johnson, Douglas H.; Kauppinen, Jukka; Lammi, Esa; Nudds, Thomas D.; Väänänen, Veli-Matti

2016-01-01

Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between-year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively “fast species” and governed by environmental variability) and diving (relatively “slow species” and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.
Environmental variability and population dynamics: do European and North American ducks play by the same rules?

PubMed

Pöysä, Hannu; Rintala, Jukka; Johnson, Douglas H; Kauppinen, Jukka; Lammi, Esa; Nudds, Thomas D; Väänänen, Veli-Matti

2016-10-01

Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between-year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively "fast species" and governed by environmental variability) and diving (relatively "slow species" and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.
Microbial Community Structures and Dynamics in the O3/BAC Drinking Water Treatment Process

PubMed Central

Tian, Jian; Lu, Jun; Zhang, Yu; Li, Jian-Cheng; Sun, Li-Chen; Hu, Zhang-Li

2014-01-01

Effectiveness of drinking water treatment, in particular pathogen control during the water treatment process, is always a major public health concern. In this investigation, the application of PCR-DGGE technology to the analysis of microbial community structures and dynamics in the drinking water treatment process revealed several dominant microbial populations including: α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Bacteroidetes, Actinobacteria Firmicutes and Cyanobacteria. α-Proteobacteria and β-Proteobacteria were the dominant bacteria during the whole process. Bacteroidetes and Firmicutes were the dominant bacteria before and after treatment, respectively. Firmicutes showed season-dependent changes in population dynamics. Importantly, γ-Proteobacteria, which is a class of medically important bacteria, was well controlled by the O3/biological activated carbon (BAC) treatment, resulting in improved effluent water bio-safety. PMID:24937529
Mathematical modeling in biological populations through branching processes. Application to salmonid populations.

PubMed

Molina, Manuel; Mota, Manuel; Ramos, Alfonso

2015-01-01

This work deals with mathematical modeling through branching processes. We consider sexually reproducing animal populations where, in each generation, the number of progenitor couples is determined in a non-predictable environment. By using a class of two-sex branching processes, we describe their demographic dynamics and provide several probabilistic and inferential contributions. They include results about the extinction of the population and the estimation of the offspring distribution and its main moments. We also present an application to salmonid populations.
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.
Stationary stability for evolutionary dynamics in finite populations

DOE PAGES

Harper, Marc; Fryer, Dashiell

2016-08-25

Here, we demonstrate a vast expansion of the theory of evolutionary stability to finite populations with mutation, connecting the theory of the stationary distribution of the Moran process with the Lyapunov theory of evolutionary stability. We define the notion of stationary stability for the Moran process with mutation and generalizations, as well as a generalized notion of evolutionary stability that includes mutation called an incentive stable state (ISS) candidate. For sufficiently large populations, extrema of the stationary distribution are ISS candidates and we give a family of Lyapunov quantities that are locally minimized at the stationary extrema and at ISSmore » candidates. In various examples, including for the Moran andWright–Fisher processes, we show that the local maxima of the stationary distribution capture the traditionally-defined evolutionarily stable states. The classical stability theory of the replicator dynamic is recovered in the large population limit. Finally we include descriptions of possible extensions to populations of variable size and populations evolving on graphs.« less
Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163
Olive Fruit Fly (Bactrocera oleae) Population Dynamics in the Eastern Mediterranean: Influence of Exogenous Uncertainty on a Monophagous Frugivorous Insect

PubMed Central

Ordano, Mariano; Engelhard, Izhar; Rempoulakis, Polychronis; Nemny-Lavy, Esther; Blum, Moshe; Yasin, Sami; Lensky, Itamar M.; Papadopoulos, Nikos T.; Nestel, David

2015-01-01

Despite of the economic importance of the olive fly (Bactrocera oleae) and the large amount of biological and ecological studies on the insect, the factors driving its population dynamics (i.e., population persistence and regulation) had not been analytically investigated until the present study. Specifically, our study investigated the autoregressive process of the olive fly populations, and the joint role of intrinsic and extrinsic factors molding the population dynamics of the insect. Accounting for endogenous dynamics and the influences of exogenous factors such as olive grove temperature, the North Atlantic Oscillation and the presence of potential host fruit, we modeled olive fly populations in five locations in the Eastern Mediterranean region. Our models indicate that the rate of population change is mainly shaped by first and higher order non-monotonic, endogenous dynamics (i.e., density-dependent population feedback). The olive grove temperature was the main exogenous driver, while the North Atlantic Oscillation and fruit availability acted as significant exogenous factors in one of the five populations. Seasonal influences were also relevant for three of the populations. In spite of exogenous effects, the rate of population change was fairly stable along time. We propose that a special reproductive mechanism, such as reproductive quiescence, allows populations of monophagous fruit flies such as the olive fly to remain stable. Further, we discuss how weather factors could impinge constraints on the population dynamics at the local level. Particularly, local temperature dynamics could provide forecasting cues for management guidelines. Jointly, our results advocate for establishing monitoring programs and for a major focus of research on the relationship between life history traits and populations dynamics. PMID:26010332
Bottom-up processes drive reproductive success in an apex predator.

PubMed

Schmidt, Joshua H; McIntyre, Carol L; Roland, Carl A; MacCluskie, Margaret C; Flamme, Melanie J

2018-02-01

One of the central goals of the field of population ecology is to identify the drivers of population dynamics, particularly in the context of predator-prey relationships. Understanding the relative role of top-down versus bottom-up drivers is of particular interest in understanding ecosystem dynamics. Our goal was to explore predator-prey relationships in a boreal ecosystem in interior Alaska through the use of multispecies long-term monitoring data. We used 29 years of field data and a dynamic multistate site occupancy modeling approach to explore the trophic relationships between an apex predator, the golden eagle, and cyclic populations of the two primary prey species available to eagles early in the breeding season, snowshoe hare and willow ptarmigan. We found that golden eagle reproductive success was reliant on prey numbers, but also responded prior to changes in the phase of the snowshoe hare population cycle and failed to respond to variation in hare cycle amplitude. There was no lagged response to ptarmigan populations, and ptarmigan populations recovered quickly from the low phase. Together, these results suggested that eagle reproduction is largely driven by bottom-up processes, with little evidence of top-down control of either ptarmigan or hare populations. Although the relationship between golden eagle reproductive success and prey abundance had been previously established, here we established prey populations are likely driving eagle dynamics through bottom-up processes. The key to this insight was our focus on golden eagle reproductive parameters rather than overall abundance. Although our inference is limited to the golden eagle-hare-ptarmigan relationships we studied, our results suggest caution in interpreting predator-prey abundance patterns among other species as strong evidence for top-down control.
Source-sink dynamics sustain central stonerollers (Campostoma anomalum) in a heavily urbanized catchment

Treesearch

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

Treesearch

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...
Demography of the Early Neolithic Population in Central Balkans: Population Dynamics Reconstruction Using Summed Radiocarbon Probability Distributions

PubMed Central

2016-01-01

The Central Balkans region is of great importance for understanding the spread of the Neolithic in Europe but the Early Neolithic population dynamics of the region is unknown. In this study we apply the method of summed calibrated probability distributions to a set of published radiocarbon dates from the Republic of Serbia in order to reconstruct population dynamics in the Early Neolithic in this part of the Central Balkans. The results indicate that there was a significant population growth after ~6200 calBC, when the Neolithic was introduced into the region, followed by a bust at the end of the Early Neolithic phase (~5400 calBC). These results are broadly consistent with the predictions of the Neolithic Demographic Transition theory and the patterns of population booms and busts detected in other regions of Europe. These results suggest that the cultural process that underlies the patterns observed in Central and Western Europe was also in operation in the Central Balkan Neolithic and that the population increase component of this process can be considered as an important factor for the spread of the Neolithic as envisioned in the demic diffusion hypothesis. PMID:27508413
Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.
Comparative phylogeny and historical perspectives on population genetics of the Pacific hawksbill (Eretmochelys imbricata) and green turtles (Chelonia mydas), inferred from feeding populations in the Yaeyama Islands, Japan.

PubMed

Nishizawa, Hideaki; Okuyama, Junichi; Kobayashi, Masato; Abe, Osamu; Arai, Nobuaki

2010-01-01

Mitochondrial DNA sequence polymorphisms and patterns of genetic diversity represent the genealogy and relative impacts of historical, geographic, and demographic events on populations. In this study, historical patterns of population dynamics and differentiation in hawksbill (Eretmochelys imbricata) and green turtles (Chelonia mydas) in the Pacific were estimated from feeding populations in the Yaeyama Islands, Japan. Phylogenetic relationships of the haplotypes indicated that hawksbill and green turtles in the Pacific probably underwent very similar patterns and processes of population dynamics over the last million years, with population subdivision during the early Pleistocene and population expansion after the last glacial maximum. These significant contemporary historical events were suggested to have been caused by climatic and sea-level fluctuations. On the other hand, comparing our results to long-term population dynamics in the Atlantic, population subdivisions during the early Pleistocene were specific to Pacific hawksbill and green turtles. Therefore, regional differences in historical population dynamics are suggested. Despite limited sampling locations, these results are the first step in estimating the historical trends in Pacific sea turtles by using phylogenetics and population genetics.
Development of Envelope Curves for Predicting Void Dimensions from Overturned Trees

DTIC Science & Technology

2014-07-01

transport due to tree root throw: integrating tree population dynamics, wildfire, and geomorphic response (Gallaway et al. 2009...Johnson. 2009. Sediment transport due to tree root throw: Integrating tree population dynamics, wildfire and geomorphic response. Earth Surface Processes...environment, but not vegetation (Peterson and Leach 2008) ............................................................ 17 4.7 Pedologic and geomorphic impacts
Dynamical role of predators in population cycles of a forest insect: an experimental test.

Treesearch

P. Turchin; A.D. Taylor; J.D. Reeve

1999-01-01

Population cycles occur frequently in forest insects.Time-series analysis of fluctuations in one such insect, the southern pine beetle (Dendroctonus frontalis), suggests that beetle dynamics are dominated by an ecological process acting in a delayed density-dependent manner.The hypothesis that delayed density-dependence in this insect results from its interaction with...

Density-Dependent Regulation of Brook Trout Population Dynamics along a Core-Periphery Distribution Gradient in a Central Appalachian Watershed

PubMed Central

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
Relation between the Electromagnetic Processes in the Near-Earth Space and Dynamics of the Biological Resources in Russian Arctic

NASA Astrophysics Data System (ADS)

Makarova, L. N.; Shirochkov, A. V.

It is a well-established fact that the electromagnetic processes of different kind occurring in the near- Earth space produce significant effects in the Earth's atmosphere at all altitudes including the ground surface. There are some indications that these processes could influence at least indirectly the human health conditions. In this study we explore relation between perturbations in the solar wind (dynamics of its density, velocity, intensity of the interplanetary magnetic field) and long- term changes in population of some species of Arctic fauna (lemmings, polar foxes, deers, wolves, elks etc.) It was found out that the best statistical coupling between various Space Weather parameters and the changes in populations of the Arctic fauna species appears when the solar wind dynamic pressure magnitude is taken as one of these parameters. It was shown that the secular variations of the solar UV radiation expressed as the Total Solar Irradiance appears to be a space parameter, showing the best correlation with the changes in population of the Arctic fauna species. Such high correlation coefficients as 0.8 are obtained. It is premature now to discuss exact physical mechanisms, which could explain the obtained relations. A possible mutual dependence of some climatic factors and fauna population in Arctic on the Space Weather parameters is discussed in this connection. Conclusion is made that the electromagnetic fields of space origin is an important factor determining dynamics of population of the Arctic fauna species.
Strong optical field ionisation of solids

NASA Astrophysics Data System (ADS)

McDonald, C. R.; Ben Taher, A.; Brabec, T.

2017-11-01

Population transfer from the valence to conduction band in the presence of an intense laser field is explored theoretically in semiconductors and dielectrics. Experiments performed on dielectrics exposed to an intense laser field have divulged a population dynamics between valence and conduction band that differs from that observed in semiconductors. Our paper explores two aspects of ionisation in solids. (i) Contemporary ionisation theories do not take account of the coupling between the valence and conduction bands resulting in the absence the dynamic Stark shift. Our single-particle analysis identifies the absence of the dynamic Stark shift as a possible cause for the contrasting ionisation behaviours observed in dielectric and semiconductor materials. The dynamic Stark shift results in an increased bandgap as the laser intensity is increased. This suppresses ionisation to an extent where the main population dynamics results from virtual oscillations in the conduction band population. The dynamic Stark shift mainly affects larger bandgap materials which can be exposed to decidedly higher laser intensities. (ii) In the presence of laser dressed virtual population of the conduction band, elastic collisions potentially transmute virtual into real population resulting in ionisation. This process is explored in the context of the relaxation time approximation.
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.
A kinetic theory for age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Chou, Tom; Greenman, Chris

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but they are structurally unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Conversely, current theories that include size-dependent population dynamics (e.g., carrying capacity) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a BBGKY-like hierarchy. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution. NSF.
Metapopulation dynamics and the evolution of dispersal

NASA Astrophysics Data System (ADS)

Parvinen, Kalle

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

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2016-01-01

The importance of transient dynamics of structured populations is increasingly recognized in ecology, yet these implications are not largely considered in conservation practices. We investigate transient and long-term population dynamics to demonstrate the process and utility of incorporating transient dynamics into conservation research and to better understand the population management of slow life-history species; these species can be theoretically highly sensitive to short- and long-term transient effects. We are specifically interested in the effects of anthropogenic removal of individuals from populations, such as caused by harvest, poaching, translocation, or incidental take. We use the sandhill crane (Grus canadensis) as an exemplar species; it is long-lived, has low reproduction, late maturity, and multiple populations are subject to sport harvest. We found sandhill cranes to have extremely high potential, but low likelihood for transient dynamics, even when the population is being harvested. The typically low population growth rate of slow life-history species appears to buffer against many perturbations causing large transient effects. Transient dynamics will dominate population trajectories of these species when stage structures are highly biased towards the younger and non-reproducing individuals, a situation that may be rare in established populations of long-lived animals. However, short-term transient population growth can be highly sensitive to vital rates that are relatively insensitive under equilibrium, suggesting that stage structure should be known if perturbation analysis is used to identify effective conservation strategies. For populations of slow life-history species that are not prone to large perturbations to their most productive individuals, population growth may be approximated by equilibrium dynamics.
The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.
Increased natural mortality at low abundance can generate an Allee effect in a marine fish.

PubMed

Kuparinen, Anna; Hutchings, Jeffrey A

2014-10-01

Negative density-dependent regulation of population dynamics promotes population growth at low abundance and is therefore vital for recovery following depletion. Inversely, any process that reduces the compensatory density-dependence of population growth can negatively affect recovery. Here, we show that increased adult mortality at low abundance can reverse compensatory population dynamics into its opposite-a demographic Allee effect. Northwest Atlantic cod (Gadus morhua) stocks collapsed dramatically in the early 1990s and have since shown little sign of recovery. Many experienced dramatic increases in natural mortality, ostensibly attributable in some populations to increased predation by seals. Our findings show that increased natural mortality of a magnitude observed for overfished cod stocks has been more than sufficient to fundamentally alter the dynamics of density-dependent population regulation. The demographic Allee effect generated by these changes can slow down or even impede the recovery of depleted populations even in the absence of fishing.
Kinetic theory of age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Greenman, Chris D.; Chou, Tom

2016-01-01

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but are unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Stochastic theories that treat semi-Markov age-dependent processes using, e.g., the Bellman-Harris equation do not resolve a population's age structure and are unable to quantify population-size dependencies. Conversely, current theories that include size-dependent population dynamics (e.g., mathematical models that include carrying capacity such as the logistic equation) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new, fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a Bogoliubov--Born--Green--Kirkwood--Yvon-like hierarchy. Explicit solutions are derived in three limits: no birth, no death, and steady state. These are then compared with their corresponding mean-field results. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution.
Public goods games in populations with fluctuating size.

PubMed

McAvoy, Alex; Fraiman, Nicolas; Hauert, Christoph; Wakeley, John; Nowak, Martin A

2018-05-01

Many mathematical frameworks of evolutionary game dynamics assume that the total population size is constant and that selection affects only the relative frequency of strategies. Here, we consider evolutionary game dynamics in an extended Wright-Fisher process with variable population size. In such a scenario, it is possible that the entire population becomes extinct. Survival of the population may depend on which strategy prevails in the game dynamics. Studying cooperative dilemmas, it is a natural feature of such a model that cooperators enable survival, while defectors drive extinction. Although defectors are favored for any mixed population, random drift could lead to their elimination and the resulting pure-cooperator population could survive. On the other hand, if the defectors remain, then the population will quickly go extinct because the frequency of cooperators steadily declines and defectors alone cannot survive. In a mutation-selection model, we find that (i) a steady supply of cooperators can enable long-term population survival, provided selection is sufficiently strong, and (ii) selection can increase the abundance of cooperators but reduce their relative frequency. Thus, evolutionary game dynamics in populations with variable size generate a multifaceted notion of what constitutes a trait's long-term success. Copyright © 2018 Elsevier Inc. All rights reserved.
Modeling snag dynamics in northern Arizona mixed-conifer and ponderosa pine forests

Treesearch

Joseph L. Ganey; Scott C. Vojta

2007-01-01

Snags (standing dead trees) are important components of forested habitats that contribute to ecological decay and recycling processes as well as providing habitat for many life forms. As such, snags are of special interest to land managers, but information on dynamics of snag populations is lacking. We modeled trends in snag populations in mixed-conifer and ponderosa...
Efficient characterisation of large deviations using population dynamics

NASA Astrophysics Data System (ADS)

Brewer, Tobias; Clark, Stephen R.; Bradford, Russell; Jack, Robert L.

2018-05-01

We consider population dynamics as implemented by the cloning algorithm for analysis of large deviations of time-averaged quantities. We use the simple symmetric exclusion process with periodic boundary conditions as a prototypical example and investigate the convergence of the results with respect to the algorithmic parameters, focussing on the dynamical phase transition between homogeneous and inhomogeneous states, where convergence is relatively difficult to achieve. We discuss how the performance of the algorithm can be optimised, and how it can be efficiently exploited on parallel computing platforms.
Linking body mass and group dynamics in an obligate cooperative breeder.

PubMed

Ozgul, Arpat; Bateman, Andrew W; English, Sinead; Coulson, Tim; Clutton-Brock, Tim H

2014-11-01

Social and environmental factors influence key life-history processes and population dynamics by affecting fitness-related phenotypic traits such as body mass. The role of body mass is particularly pronounced in cooperative breeders due to variation in social status and consequent variation in access to resources. Investigating the mechanisms underlying variation in body mass and its demographic consequences can help elucidate how social and environmental factors affect the dynamics of cooperatively breeding populations. In this study, we present an analysis of the effect of individual variation in body mass on the temporal dynamics of group size and structure of a cooperatively breeding mongoose, the Kalahari meerkat, Suricata suricatta. First, we investigate how body mass interacts with social (dominance status and number of helpers) and environmental (rainfall and season) factors to influence key life-history processes (survival, growth, emigration and reproduction) in female meerkats. Next, using an individual-based population model, we show that the models explicitly including individual variation in body mass predict group dynamics better than those ignoring this morphological trait. Body mass influences group dynamics mainly through its effects on helper emigration and dominant reproduction. Rainfall has a trait-mediated, destabilizing effect on group dynamics, whereas the number of helpers has a direct and stabilizing effect. Counteracting effects of number of helpers on different demographic rates, despite generating temporal fluctuations, stabilizes group dynamics in the long term. Our study demonstrates that social and environmental factors interact to produce individual variation in body mass and accounting for this variation helps to explain group dynamics in this cooperatively breeding population. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

PubMed Central

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.

PubMed

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.
Dancing to the rhythms of the Pleistocene? Early Middle Paleolithic population dynamics in NW Iberia (Duero Basin and Cantabrian Region)

NASA Astrophysics Data System (ADS)

Sánchez Yustos, Policarpo; Diez Martín, Fernando

2015-08-01

The Northwest of Iberia has yielded one of the most complete European Middle Paleolithic records. Despite this wealth of information, very little is known about population dynamics during this period. For that reason, the main concern of this paper is to provide socio-environmental models that may help explain Early Middle Paleolithic (EMP) population dynamics in NW Iberia, assessing to what extent they were shaped by climate forces. The archaeological record is analyzed on the basis of the heuristics of ecological models, already employed in the European Pleistocene record but never at a regional scale, in order to detect long-term changes in the composition of EMP populations, and the environmental, biological and sociocultural process influencing those changes. According to the models proposed, we have detected a long-term population dynamic between MIS 11 and MIS 6, characterized by low environmental stress, high biological productivity, interaction among populations and sociocultural complexity. Eventually, this population dynamic was broken due to an extreme climate phase in late MIS 6 that had a profound impact on populations and sociocultural structures. As a result, the Upper Pleistocene population of NW Iberia was concentrated in the Cantabrian region. This area became an isolated Neanderthal glacial refugium that hosted a population with different origins and fragile long-term demographic stability.
Structured population dynamics: continuous size and discontinuous stage structures.

PubMed

Buffoni, Giuseppe; Pasquali, Sara

2007-04-01

A nonlinear stochastic model for the dynamics of a population with either a continuous size structure or a discontinuous stage structure is formulated in the Eulerian formalism. It takes into account dispersion effects due to stochastic variability of the development process of the individuals. The discrete equations of the numerical approximation are derived, and an analysis of the existence and stability of the equilibrium states is performed. An application to a copepod population is illustrated; numerical results of Eulerian and Lagrangian models are compared.
Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305
Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

G-quadruplex dynamics.

PubMed

Harkness, Robert W; Mittermaier, Anthony K

2017-11-01

G-quadruplexes (GQs) are four-stranded nucleic acid secondary structures formed by guanosine (G)-rich DNA and RNA sequences. It is becoming increasingly clear that cellular processes including gene expression and mRNA translation are regulated by GQs. GQ structures have been extensively characterized, however little attention to date has been paid to their conformational dynamics, despite the fact that many biological GQ sequences populate multiple structures of similar free energies, leading to an ensemble of exchanging conformations. The impact of these dynamics on biological function is currently not well understood. Recently, structural dynamics have been demonstrated to entropically stabilize GQ ensembles, potentially modulating gene expression. Transient, low-populated states in GQ ensembles may additionally regulate nucleic acid interactions and function. This review will underscore the interplay of GQ dynamics and biological function, focusing on several dynamic processes for biological GQs and the characterization of GQ dynamics by nuclear magnetic resonance (NMR) spectroscopy in conjunction with other biophysical techniques. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.
The escalatory Red Queen: Population extinction and replacement following arms race dynamics in poplar rust.

PubMed

Persoons, Antoine; Hayden, Katherine J; Fabre, Bénédicte; Frey, Pascal; De Mita, Stéphane; Tellier, Aurélien; Halkett, Fabien

2017-04-01

Host-parasite systems provide convincing examples of Red Queen co-evolutionary dynamics. Yet, a key process underscored in Van Valen's theory - that arms race dynamics can result in extinction - has never been documented. One reason for this may be that most sampling designs lack the breadth needed to illuminate the rapid pace of adaptation by pathogen populations. In this study, we used a 25-year temporal sampling to decipher the demographic history of a plant pathogen: the poplar rust fungus, Melampsora larici-populina. A major adaptive event occurred in 1994 with the breakdown of R7 resistance carried by several poplar cultivars widely planted in Western Europe since 1982. The corresponding virulence rapidly spread in M. larici-populina populations and nearly reached fixation in northern France, even on susceptible hosts. Using both temporal records of virulence profiles and temporal population genetic data, our analyses revealed that (i) R7 resistance breakdown resulted in the emergence of a unique and homogeneous genetic group, the so-called cultivated population, which predominated in northern France for about 20 years, (ii) selection for Vir7 individuals brought with it multiple other virulence types via hitchhiking, resulting in an overall increase in the population-wide number of virulence types and (iii) - above all - the emergence of the cultivated population superseded the initial population which predominated at the same place before R7 resistance breakdown. Our temporal analysis illustrates how antagonistic co-evolution can lead to population extinction and replacement, hence providing direct evidence for the escalation process which is at the core of Red Queen dynamics. © 2016 John Wiley & Sons Ltd.
Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.
Fixation, transient landscape, and diffusion dilemma in stochastic evolutionary game dynamics

NASA Astrophysics Data System (ADS)

Zhou, Da; Qian, Hong

2011-09-01

Agent-based stochastic models for finite populations have recently received much attention in the game theory of evolutionary dynamics. Both the ultimate fixation and the pre-fixation transient behavior are important to a full understanding of the dynamics. In this paper, we study the transient dynamics of the well-mixed Moran process through constructing a landscape function. It is shown that the landscape playing a central theoretical “device” that integrates several lines of inquiries: the stable behavior of the replicator dynamics, the long-time fixation, and continuous diffusion approximation associated with asymptotically large population. Several issues relating to the transient dynamics are discussed: (i) multiple time scales phenomenon associated with intra- and inter-attractoral dynamics; (ii) discontinuous transition in stochastically stationary process akin to Maxwell construction in equilibrium statistical physics; and (iii) the dilemma diffusion approximation facing as a continuous approximation of the discrete evolutionary dynamics. It is found that rare events with exponentially small probabilities, corresponding to the uphill movements and barrier crossing in the landscape with multiple wells that are made possible by strong nonlinear dynamics, plays an important role in understanding the origin of the complexity in evolutionary, nonlinear biological systems.
Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522
Aspiration dynamics of multi-player games in finite populations

PubMed Central

Du, Jinming; Wu, Bin; Altrock, Philipp M.; Wang, Long

2014-01-01

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics. PMID:24598208
Aspiration dynamics of multi-player games in finite populations.

PubMed

Du, Jinming; Wu, Bin; Altrock, Philipp M; Wang, Long

2014-05-06

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.
Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a step...dynamics using differential equations. 15. SUBJECT TERMS Differential Equations, Markov Population Process, S-I-R Epidemic, Lanchester Model 16...infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability
The one-third law of evolutionary dynamics.

PubMed

Ohtsuki, Hisashi; Bordalo, Pedro; Nowak, Martin A

2007-11-21

Evolutionary game dynamics in finite populations provide a new framework for studying selection of traits with frequency-dependent fitness. Recently, a "one-third law" of evolutionary dynamics has been described, which states that strategy A fixates in a B-population with selective advantage if the fitness of A is greater than that of B when A has a frequency 13. This relationship holds for all evolutionary processes examined so far, from the Moran process to games on graphs. However, the origin of the "number"13 is not understood. In this paper we provide an intuitive explanation by studying the underlying stochastic processes. We find that in one invasion attempt, an individual interacts on average with B-players twice as often as with A-players, which yields the one-third law. We also show that the one-third law implies that the average Malthusian fitness of A is positive.
Fast stochastic algorithm for simulating evolutionary population dynamics

NASA Astrophysics Data System (ADS)

Tsimring, Lev; Hasty, Jeff; Mather, William

2012-02-01

Evolution and co-evolution of ecological communities are stochastic processes often characterized by vastly different rates of reproduction and mutation and a coexistence of very large and very small sub-populations of co-evolving species. This creates serious difficulties for accurate statistical modeling of evolutionary dynamics. In this talk, we introduce a new exact algorithm for fast fully stochastic simulations of birth/death/mutation processes. It produces a significant speedup compared to the direct stochastic simulation algorithm in a typical case when the total population size is large and the mutation rates are much smaller than birth/death rates. We illustrate the performance of the algorithm on several representative examples: evolution on a smooth fitness landscape, NK model, and stochastic predator-prey system.
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.
Processes on the emergent landscapes of biochemical reaction networks and heterogeneous cell population dynamics: differentiation in living matters

PubMed Central

Li, Fangting

2017-01-01

The notion of an attractor has been widely employed in thinking about the nonlinear dynamics of organisms and biological phenomena as systems and as processes. The notion of a landscape with valleys and mountains encoding multiple attractors, however, has a rigorous foundation only for closed, thermodynamically non-driven, chemical systems, such as a protein. Recent advances in the theory of nonlinear stochastic dynamical systems and its applications to mesoscopic reaction networks, one reaction at a time, have provided a new basis for a landscape of open, driven biochemical reaction systems under sustained chemostat. The theory is equally applicable not only to intracellular dynamics of biochemical regulatory networks within an individual cell but also to tissue dynamics of heterogeneous interacting cell populations. The landscape for an individual cell, applicable to a population of isogenic non-interacting cells under the same environmental conditions, is defined on the counting space of intracellular chemical compositions x = (x1,x2, … ,xN) in a cell, where xℓ is the concentration of the ℓth biochemical species. Equivalently, for heterogeneous cell population dynamics xℓ is the number density of cells of the ℓth cell type. One of the insights derived from the landscape perspective is that the life history of an individual organism, which occurs on the hillsides of a landscape, is nearly deterministic and ‘programmed’, while population-wise an asynchronous non-equilibrium steady state resides mostly in the lowlands of the landscape. We argue that a dynamic ‘blue-sky’ bifurcation, as a representation of Waddington's landscape, is a more robust mechanism for a cell fate decision and subsequent differentiation than the widely pictured pitch-fork bifurcation. We revisit, in terms of the chemostatic driving forces upon active, living matter, the notions of near-equilibrium thermodynamic branches versus far-from-equilibrium states. The emergent landscape perspective permits a quantitative discussion of a wide range of biological phenomena as nonlinear, stochastic dynamics. PMID:28490602
Phylodynamics with Migration: A Computational Framework to Quantify Population Structure from Genomic Data.

PubMed

Kühnert, Denise; Stadler, Tanja; Vaughan, Timothy G; Drummond, Alexei J

2016-08-01

When viruses spread, outbreaks can be spawned in previously unaffected regions. Depending on the time and mode of introduction, each regional outbreak can have its own epidemic dynamics. The migration and phylodynamic processes are often intertwined and need to be taken into account when analyzing temporally and spatially structured virus data. In this article, we present a fully probabilistic approach for the joint reconstruction of phylodynamic history in structured populations (such as geographic structure) based on a multitype birth-death process. This approach can be used to quantify the spread of a pathogen in a structured population. Changes in epidemic dynamics through time within subpopulations are incorporated through piecewise constant changes in transmission parameters.We analyze a global human influenza H3N2 virus data set from a geographically structured host population to demonstrate how seasonal dynamics can be inferred simultaneously with the phylogeny and migration process. Our results suggest that the main migration path among the northern, tropical, and southern region represented in the sample analyzed here is the one leading from the tropics to the northern region. Furthermore, the time-dependent transmission dynamics between and within two HIV risk groups, heterosexuals and injecting drug users, in the Latvian HIV epidemic are investigated. Our analyses confirm that the Latvian HIV epidemic peaking around 2001 was mainly driven by the injecting drug user risk group. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Slow-fast stochastic diffusion dynamics and quasi-stationarity for diploid populations with varying size.

PubMed

Coron, Camille

2016-01-01

We are interested in the long-time behavior of a diploid population with sexual reproduction and randomly varying population size, characterized by its genotype composition at one bi-allelic locus. The population is modeled by a 3-dimensional birth-and-death process with competition, weak cooperation and Mendelian reproduction. This stochastic process is indexed by a scaling parameter K that goes to infinity, following a large population assumption. When the individual birth and natural death rates are of order K, the sequence of stochastic processes indexed by K converges toward a new slow-fast dynamics with variable population size. We indeed prove the convergence toward 0 of a fast variable giving the deviation of the population from quasi Hardy-Weinberg equilibrium, while the sequence of slow variables giving the respective numbers of occurrences of each allele converges toward a 2-dimensional diffusion process that reaches (0,0) almost surely in finite time. The population size and the proportion of a given allele converge toward a Wright-Fisher diffusion with stochastically varying population size and diploid selection. We insist on differences between haploid and diploid populations due to population size stochastic variability. Using a non trivial change of variables, we study the absorption of this diffusion and its long time behavior conditioned on non-extinction. In particular we prove that this diffusion starting from any non-trivial state and conditioned on not hitting (0,0) admits a unique quasi-stationary distribution. We give numerical approximations of this quasi-stationary behavior in three biologically relevant cases: neutrality, overdominance, and separate niches.
Weak ergodicity of population evolution processes.

PubMed

Inaba, H

1989-10-01

The weak ergodic theorems of mathematical demography state that the age distribution of a closed population is asymptotically independent of the initial distribution. In this paper, we provide a new proof of the weak ergodic theorem of the multistate population model with continuous time. The main tool to attain this purpose is a theory of multiplicative processes, which was mainly developed by Garrett Birkhoff, who showed that ergodic properties generally hold for an appropriate class of multiplicative processes. First, we construct a general theory of multiplicative processes on a Banach lattice. Next, we formulate a dynamical model of a multistate population and show that its evolution operator forms a multiplicative process on the state space of the population. Subsequently, we investigate a sufficient condition that guarantees the weak ergodicity of the multiplicative process. Finally, we prove the weak and strong ergodic theorems for the multistate population and resolve the consistency problem.
Stochastic Dynamics through Hierarchically Embedded Markov Chains

NASA Astrophysics Data System (ADS)

Vasconcelos, Vítor V.; Santos, Fernando P.; Santos, Francisco C.; Pacheco, Jorge M.

2017-02-01

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects—such as mutations in evolutionary dynamics and a random exploration of choices in social systems—including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.
Relation between the electromagnetic processes in the near-Earth space and dynamics of the biological resources in Russian Arctic

NASA Astrophysics Data System (ADS)

Makarova, L. N.; Shirochkov, A. V.; Tumanov, I. L.

The start of the satellite era in the Space explorations led to new and more profound knowledge of the solar physics and the sources of its activity. From these points of view, it is worthy to examine again the relations between biological processes and the solar activity. We explore the relation between dynamics of the solar activity (including the solar wind) and changes in population of some species of Arctic fauna (lemmings, polar foxes, caribous, wolves, elks, etc.). The data include statistical rows of various lengths (30 80 years). The best correlation between two data sets is found when the solar wind dynamic pressure as well as variations of the total solar irradiance (i.e., level of the solar UV radiation) is taken as the space parameters. Probably the electromagnetic fields of space origin are an important factor determining dynamics of population of the Arctic fauna species.
Stochastic Dynamics through Hierarchically Embedded Markov Chains.

PubMed

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.
Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2018-07-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.
Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Preoutbreak dynamics of a recently established invasive herbivore: roles of natural enemies and habitat structure in stage-specific performance of gypsy moth (Lepidoptera: Lymantriidae) populations in northeastern Wisconsin

Treesearch

Rebecca Hoffman Gray; Craig G. Lorimer; Patrick C. Tobin; Kenneth F. Raffa

2008-01-01

A major challenge to addressing biological invasions is that the need for emergency responses often precludes opportunities to analyze the dynamics between initial establishment and population eruption. Thus, a broader understanding of underlying processes and management opportunities is often lacking. We examined the effects of habitat structure and natural enemies on...
Diachronic investigations of mitochondrial and Y-chromosomal genetic markers in pre-Columbian Andean highlanders from South Peru.

PubMed

Fehren-Schmitz, Lars; Warnberg, Ole; Reindel, Markus; Seidenberg, Verena; Tomasto-Cagigao, Elsa; Isla-Cuadrado, Johny; Hummel, Susanne; Herrmann, Bernd

2011-03-01

This study examines the reciprocal effects of cultural evolution, and population dynamics in pre-Columbian southern Peru by the analysis of DNA from pre-Columbian populations that lived in the fringe area between the Andean highlands and the Pacific coast. The main objective is to reveal whether the transition from the Middle Horizon (MH: 650-1000 AD) to the Late Intermediate Period (LIP: 1000-1400 AD) was accompanied or influenced by population dynamic processes. Tooth samples from 90 individuals from several archaeological sites, dating to the MH and LIP, in the research area were collected to analyse mitochodrial, and Y-chromosomal genetic markers. Coding region polymorphisms were successfully analysed and replicated for 72 individuals, as were control region sequences for 65 individuals and Y-chromosomal single nucleotide polymorphisms (SNPs) for 19 individuals, and these were compared to a large set of ancient and modern indigenous South American populations. The diachronic comparison of the upper valley samples from both time periods reveals no genetic discontinuities accompanying the cultural dynamic processes. A high genetic affinity for other ancient and modern highland populations can be observed, suggesting genetic continuity in the Andean highlands at the latest from the MH. A significant matrilineal differentiation to ancient Peruvian coastal populations can be observed suggesting a differential population history. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.
Factors affecting unintentional harvesting selectivity in a monomorphic species.

PubMed

Bunnefeld, Nils; Baines, David; Newborn, David; Milner-Gulland, E J

2009-03-01

1. Changes in the abundance of populations have always perplexed ecologists but long-term studies are revealing new insights into population dynamic processes. Long-term data are often derived from harvest records although many wild populations face high harvesting pressures leading to overharvesting and extinction. Additionally, harvest records used to describe population processes such as fluctuations in abundance and reproductive success often assume a random off-take. 2. Selective harvesting based on phenotypic characteristics occurs in many species (e.g. trophy hunting, fisheries) and has important implications for population dynamics, conservation and management. 3. In species with no marked morphological differences between the age and sex classes, such as the red grouse Lagopus lagopus scoticus during the shooting season, hunters cannot consciously select for a specific sex or age class during the shooting process but harvest records could still give a biased reflection of the population structure because of differences in behaviour between age and sex classes. 4. This study compared age and sex ratios in the bag with those in the population before shooting for red grouse at different points in the shooting season and different densities, which has rarely been tested before. 5. More young than old grouse were shot at large bag sizes and vice versa for small bag sizes than would be expected from the population composition before shooting. The susceptibility of old males to shooting compared to females increased with bag size and was high at the first time the area was shot but decreased with the number of times an area was harvested. 6. These findings stress that the assumption made in many studies that harvest records reflect the age and sex ratio of the population and therefore reflect productivity can be misleading. 7. In this paper, as in the literature, it is also shown that number of grouse shot reflects grouse density and therefore that hunting selectivity might influence population dynamics in a cyclic species. 8. The study is not only relevant for red grouse but applies to systems showing interactions between selective harvesting and wider ecological processes, such as age- and sex-related parasitism and territoriality, which may drive population fluctuations.
Small-scale fisheries, population dynamics, and resource use in Africa: the case of Moree, Ghana.

PubMed

Marquette, Catherine M; Koranteng, Kwame A; Overå, Ragnhild; Aryeetey, Ellen Bortei-Doku

2002-06-01

We consider population dynamics and sustainable use and development of fishery resources in Moree, a small-scale fishing and coastal community of 20,000 people in the Central Region of Ghana near Cape Coast. Moree suggests that relationships between population dynamics and fishery resources are more complex than the concept of Malthusian overfishing implies. Reasons include changing biophysical characteristics of the upwelling system along the coast of West Africa; qualitative as well as quantitative changes in fishing activity throughout the year; the market nature of fishing activity and nonlocal demands for fish; regular fishery migration; and institutions regulating fishery resource access at home and at migration destinations. Population and resource relationships in Moree may be the effects of fishery resource and economic changes on migration rather than population pressure on fishery resources. Fisheries management policies must take into account processes that lie beyond the influence of local fishermen.
Extinction in neutrally stable stochastic Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.
Extinction in neutrally stable stochastic Lotka-Volterra models.

PubMed

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

Populations of competing biological species exhibit a fascinating interplay between the nonlinear dynamics of evolutionary selection forces and random fluctuations arising from the stochastic nature of the interactions. The processes leading to extinction of species, whose understanding is a key component in the study of evolution and biodiversity, are influenced by both of these factors. Here, we investigate a class of stochastic population dynamics models based on generalized Lotka-Volterra systems. In the case of neutral stability of the underlying deterministic model, the impact of intrinsic noise on the survival of species is dramatic: It destroys coexistence of interacting species on a time scale proportional to the population size. We introduce a new method based on stochastic averaging which allows one to understand this extinction process quantitatively by reduction to a lower-dimensional effective dynamics. This is performed analytically for two highly symmetrical models and can be generalized numerically to more complex situations. The extinction probability distributions and other quantities of interest we obtain show excellent agreement with simulations.
POPULATION DYNAMICS OF SMALL MAMMALS ACROSS A NITROGEN AMENDED LANDSCAPE

EPA Science Inventory

Biogeochemical alterations of the nitrogen cycle from anthropogenic activities could have significant effects on ecological processes at the population, community and ecosystem levels. Nitrogen additions in grasslands have produced qualitative and quantitative changes in vegetat...
Stochastic evolution in populations of ideas

PubMed Central

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games. PMID:28098244
Stochastic evolution in populations of ideas

NASA Astrophysics Data System (ADS)

Nicole, Robin; Sollich, Peter; Galla, Tobias

2017-01-01

It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games.
Bacteriophage ecology in environmental biotechnology processes.

PubMed

Shapiro, Orr H; Kushmaro, Ariel

2011-06-01

Heterotrophic bacteria are an integral part of any environmental biotechnology process (EBP). Therefore, factors controlling bacterial abundance, activity, and community composition are central to the understanding of such processes. Among these factors, top-down control by bacteriophage predation has so far received very limited attention. With over 10(8) particles per ml, phage appear to be the most numerous biological entities in EBP. Phage populations in EBP appear to be highly dynamic and to correlate with the population dynamics of their hosts and genomic evidence suggests bacteria evolve to avoid phage predation. Clearly, there is much to learn regarding bacteriophage in EBP before we can truly understand the microbial ecology of these globally important systems. Copyright © 2011 Elsevier Ltd. All rights reserved.
Radiation belt seed population and its association with the relativistic electron dynamics: A statistical study: Radiation Belt Seed Population

DOE PAGES

Tang, C. L.; Wang, Y. X.; Ni, B.; ...

2017-05-19

Using the Van Allen Probes data, we study the radiation belt seed population and it associated with the relativistic electron dynamics during 74 geomagnetic storm events. Based on the flux changes of 1 MeV electrons before and after the storm peak, these storm events are divided into two groups of “non-preconditioned” and “preconditioned”. The statistical study shows that the storm intensity is of significant importance for the distribution of the seed population (336 keV electrons) in the outer radiation belt. However, substorm intensity can also be important to the evolution of the seed population for some geomagnetic storm events. Formore » non-preconditioned storm events, the correlation between the peak fluxes and their L-shell locations of the seed population and relativistic electrons (592 keV, 1.0 MeV, 1.8 MeV, and 2.1 MeV) is consistent with the energy-dependent dynamic processes in the outer radiation belt. For preconditioned storm events, the correlation between the features of the seed population and relativistic electrons is not fully consistent with the energy-dependent processes. It is suggested that the good correlation between the radiation belt seed population and ≤1.0 MeV electrons contributes to the prediction of the evolution of ≤1.0 MeV electrons in the Earth’s outer radiation belt during periods of geomagnetic storms.« less
Radiation belt seed population and its association with the relativistic electron dynamics: A statistical study: Radiation Belt Seed Population

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, C. L.; Wang, Y. X.; Ni, B.

Using the Van Allen Probes data, we study the radiation belt seed population and it associated with the relativistic electron dynamics during 74 geomagnetic storm events. Based on the flux changes of 1 MeV electrons before and after the storm peak, these storm events are divided into two groups of “non-preconditioned” and “preconditioned”. The statistical study shows that the storm intensity is of significant importance for the distribution of the seed population (336 keV electrons) in the outer radiation belt. However, substorm intensity can also be important to the evolution of the seed population for some geomagnetic storm events. Formore » non-preconditioned storm events, the correlation between the peak fluxes and their L-shell locations of the seed population and relativistic electrons (592 keV, 1.0 MeV, 1.8 MeV, and 2.1 MeV) is consistent with the energy-dependent dynamic processes in the outer radiation belt. For preconditioned storm events, the correlation between the features of the seed population and relativistic electrons is not fully consistent with the energy-dependent processes. It is suggested that the good correlation between the radiation belt seed population and ≤1.0 MeV electrons contributes to the prediction of the evolution of ≤1.0 MeV electrons in the Earth’s outer radiation belt during periods of geomagnetic storms.« less
Variability in primary productivity determines metapopulation dynamics

PubMed Central

2016-01-01

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

PubMed

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.
Integrating count and detection–nondetection data to model population dynamics

USGS Publications Warehouse

Zipkin, Elise F.; Rossman, Sam; Yackulic, Charles B.; Wiens, David; Thorson, James T.; Davis, Raymond J.; Grant, Evan H. Campbell

2017-01-01

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.
Integrating count and detection-nondetection data to model population dynamics.

PubMed

Zipkin, Elise F; Rossman, Sam; Yackulic, Charles B; Wiens, J David; Thorson, James T; Davis, Raymond J; Grant, Evan H Campbell

2017-06-01

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture-recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection-nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection-nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection-nondetection data (1995-2014) with newly collected count data (2015-2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance. © 2017 by the Ecological Society of America.
Distribution of correlated spiking events in a population-based approach for Integrate-and-Fire networks.

PubMed

Zhang, Jiwei; Newhall, Katherine; Zhou, Douglas; Rangan, Aaditya

2014-04-01

Randomly connected populations of spiking neurons display a rich variety of dynamics. However, much of the current modeling and theoretical work has focused on two dynamical extremes: on one hand homogeneous dynamics characterized by weak correlations between neurons, and on the other hand total synchrony characterized by large populations firing in unison. In this paper we address the conceptual issue of how to mathematically characterize the partially synchronous "multiple firing events" (MFEs) which manifest in between these two dynamical extremes. We further develop a geometric method for obtaining the distribution of magnitudes of these MFEs by recasting the cascading firing event process as a first-passage time problem, and deriving an analytical approximation of the first passage time density valid for large neuron populations. Thus, we establish a direct link between the voltage distributions of excitatory and inhibitory neurons and the number of neurons firing in an MFE that can be easily integrated into population-based computational methods, thereby bridging the gap between homogeneous firing regimes and total synchrony.
Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

PubMed

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

2014-01-01

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

PubMed Central

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

2014-01-01

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

NASA Astrophysics Data System (ADS)

Toledo-Aceves, Tarin; Hernández-Apolinar, Mariana; Valverde, Teresa

2014-08-01

Large numbers of epiphytes are extracted from cloud forests for ornamental use and illegal trade in Latin America. We examined the potential effects of different harvesting regimes on the population dynamics of the epiphytic bromeliads Tillandsia multicaulis and Tillandsia punctulata. The population dynamics of these species were studied over a 2-year period in a tropical montane cloud forest in Veracruz, Mexico. Prospective and retrospective analyses were used to identify which demographic processes and life-cycle stages make the largest relative contribution to variation in population growth rate (λ). The effect of simulated harvesting levels on population growth rates was analysed for both species. λ of both populations was highly influenced by survival (stasis), to a lesser extent by growth, and only slightly by fecundity. Vegetative growth played a central role in the population dynamics of these organisms. The λ value of the studied populations did not differ significantly from unity: T. multicaulis λ (95% confidence interval) = 0.982 (0.897-1.060) and T. punctulata λ = 0.967 (0.815-1.051), suggesting population stability. However, numerical simulation of different levels of extraction showed that λ would drop substantially even under very low (2%) harvesting levels. Matrix analysis revealed that T. multicaulis and T. punctulata populations are likely to decline and therefore commercial harvesting would be unsustainable. Based on these findings, management recommendations are outlined.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.
Innovations in Play Therapy: Issues, Process, and Special Populations.

ERIC Educational Resources Information Center

Landreth, Garry L., Ed.

This book is a compilation of discussions on current issues in play therapy. It is designed to help therapists fill in the gaps about working with special populations, which is often not directly addressed in other play therapy resources. The object of the book is to bring together information related to issues and dynamics of the process of this…
The σ law of evolutionary dynamics in community-structured population.

PubMed

Tang, Changbing; Li, Xiang; Cao, Lang; Zhan, Jingyuan

2012-08-07

Evolutionary game dynamics in finite populations provide a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call σ law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B in weak selection if and only if σR+S>T+σP. This relationship holds for a wide variety of structured populations with mutation rate and weak selection under certain assumptions. In this paper, we propose a model of games based on a community-structured population and revisit this law under the Moran process. By calculating the average payoffs of A and B individuals with the method of effective sojourn time, we find that σ features not only the structured population characteristics, but also the reaction rate between individuals. That is to say, an interaction between two individuals are not uniform, and we can take σ as a reaction rate between any two individuals with the same strategy. We verify this viewpoint by the modified replicator equation with non-uniform interaction rates in a simplified version of the prisoner's dilemma game (PDG). Copyright © 2012 Elsevier Ltd. All rights reserved.
Bivalves: From individual to population modelling

NASA Astrophysics Data System (ADS)

Saraiva, S.; van der Meer, J.; Kooijman, S. A. L. M.; Ruardij, P.

2014-11-01

An individual based population model for bivalves was designed, built and tested in a 0D approach, to simulate the population dynamics of a mussel bed located in an intertidal area. The processes at the individual level were simulated following the dynamic energy budget theory, whereas initial egg mortality, background mortality, food competition, and predation (including cannibalism) were additional population processes. Model properties were studied through the analysis of theoretical scenarios and by simulation of different mortality parameter combinations in a realistic setup, imposing environmental measurements. Realistic criteria were applied to narrow down the possible combination of parameter values. Field observations obtained in the long-term and multi-station monitoring program were compared with the model scenarios. The realistically selected modeling scenarios were able to reproduce reasonably the timing of some peaks in the individual abundances in the mussel bed and its size distribution but the number of individuals was not well predicted. The results suggest that the mortality in the early life stages (egg and larvae) plays an important role in population dynamics, either by initial egg mortality, larvae dispersion, settlement failure or shrimp predation. Future steps include the coupling of the population model with a hydrodynamic and biogeochemical model to improve the simulation of egg/larvae dispersion, settlement probability, food transport and also to simulate the feedback of the organisms' activity on the water column properties, which will result in an improvement of the food quantity and quality characterization.
Simulation of Population Processes with a Programmable Pocket Calculator.

ERIC Educational Resources Information Center

Kidd, N. A. C.

1979-01-01

Presents a set of simulation models for use in teaching population dynamics. These models are designed specifically for use with a programmable pocket calculator, and can be used to demonstrate growth of populations with discrete or overlapping generations and also to explore effects of density-dependent and -independent mortality. (Author/CS)
Dynamics of buckbrush populations under simulated forest restoration alternatives

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...
Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...
Mammal population regulation, keystone processes and ecosystem dynamics.

PubMed Central

Sinclair, A R E

2003-01-01

The theory of regulation in animal populations is fundamental to understanding the dynamics of populations, the causes of mortality and how natural selection shapes the life history of species. In mammals, the great range in body size allows us to see how allometric relationships affect the mode of regulation. Resource limitation is the fundamental cause of regulation. Top-down limitation through predators is determined by four factors: (i). body size; (ii). the diversity of predators and prey in the system; (iii). whether prey are resident or migratory; and (iv). the presence of alternative prey for predators. Body size in mammals has two important consequences. First, mammals, particularly large species, can act as keystones that determine the diversity of an ecosystem. I show how keystone processes can, in principle, be measured using the example of the wildebeest in the Serengeti ecosystem. Second, mammals act as ecological landscapers by altering vegetation succession. Mammals alter physical structure, ecological function and species diversity in most terrestrial biomes. In general, there is a close interaction between allometry, population regulation, life history and ecosystem dynamics. These relationships are relevant to applied aspects of conservation and pest management. PMID:14561329
A Biologically Informed, Mechanistic Model of Desert Shrub Population Dynamics Bearing on Arid Landscape Evolution

NASA Astrophysics Data System (ADS)

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

In arid landscapes, desert shrubs individually and collectively modify how sediment is transported (e.g by wind, overland-flow, and rain-splash). Addressing how desert shrubs modify landscapes on geomorphic timescales therefore necessitates spanning multiple shrub lifetimes and accounting for how processes affecting shrub dynamics on these longer timescales (e.g. fire, grazing, drought, and climate change) may in turn impact sediment transport. To fulfill this need, we present a mechanistic model of the spatiotemporal dynamics of a desert-shrub population that uses a simple accounting framework and tracks individual shrubs as they enter, age, and exit the population (via recruitment, growth, and mortality). Our model is novel insomuch as it (1) features a strong biophysical foundation, (2) mimics well-documented aspects of how shrub populations respond to changes in precipitation, and (3) possesses the process granularity appropriate for use in geomorphic simulations. In a complimentary abstract (Fathel et al. 2014), we demonstrate the potential of this biological model by coupling it to a physical model of rain-splash sediment transport: We mechanistically reproduce the empirical observation that the erosion rate of a hillslope decreases as its vegetation coverage increases and we predict erosion rates under different climate-change scenarios.
Evolutionary dynamics of public goods games with diverse contributions in finite populations

NASA Astrophysics Data System (ADS)

Wang, Jing; Wu, Bin; Chen, Xiaojie; Wang, Long

2010-05-01

The public goods game is a powerful metaphor for exploring the maintenance of social cooperative behavior in a group of interactional selfish players. Here we study the emergence of cooperation in the public goods games with diverse contributions in finite populations. The theory of stochastic process is innovatively adopted to investigate the evolutionary dynamics of the public goods games involving a diversity of contributions. In the limit of rare mutations, the general stationary distribution of this stochastic process can be analytically approximated by means of diffusion theory. Moreover, we demonstrate that increasing the diversity of contributions greatly reduces the probability of finding the population in a homogeneous state full of defectors. This increase also raises the expectation of the total contribution in the entire population and thus promotes social cooperation. Furthermore, by investigating the evolutionary dynamics of optional public goods games with diverse contributions, we find that nonparticipation can assist players who contribute more in resisting invasion and taking over individuals who contribute less. In addition, numerical simulations are performed to confirm our analytical results. Our results may provide insight into the effect of diverse contributions on cooperative behaviors in the real world.
Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference.

PubMed

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.
History of research on modelling gypsy moth population ecology

Treesearch

J. J. Colbert

1991-01-01

History of research to develop models of gypsy moth population dynamics and some related studies are described. Empirical regression-based models are reviewed, and then the more comprehensive process models are discussed. Current model- related research efforts are introduced.
Simulation model of Skeletonema costatum population dynamics in northern San Francisco Bay, California

USGS Publications Warehouse

Cloern, J.E.; Cheng, R.T.

1981-01-01

A pseudo-two-dimensional model is developed to simulate population dynamics of one dominant phytoplankton species (Skeletonema costatum) in northern San Francisco Bay. The model is formulated around a conceptualization of this estuary as two distinct but coupled subsystems-a deep (10-20 m) central channel and lateral areas with shallow (<2 m) water and slow circulation. Algal growth rates are governed by solar irradiation, temperature and salinity, while population losses are assumed to result from grazing bycalanoid copepods. Consequences of estuarine gravitational circulation are approximated simply by reducing convective-dispersive transport in that section of the channel (null zone) where residual bottom currents are near zero, and lateral mixing is treated as a bulkexchange process between the channel and the shoals. Model output is consistent with the hypothesis that, because planktonic algae are light-limited, shallow areas are the sites of active population growth. Seasonal variation in the location of the null zone (a response to variable river discharge) is responsible for maintaining the spring bloom of neritic diatoms in the seaward reaches of the estuary (San Pablo Bay) and the summer bloom upstream (Suisun Bay). Model output suggests that these spring and summer blooms result from the same general process-establishment of populations over the shoals, where growth rates are rapid, coupled with reduced particulate transport due to estuarine gravitational circulation. It also suggests, however, that the relative importance of physical and biological processes to phytoplankton dynamics is different in San Pablo and Suisun Bays. Finally, the model has helped us determine those processes having sufficient importance to merit further refinement in the next generation of models, and it has given new direction to field studies. ?? 1981 Academic Press Inc. (London) Ltd.
Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

PubMed Central

Lacy, Robert C.; Miller, Philip S.; Nyhus, Philip J.; Pollak, J. P.; Raboy, Becky E.; Zeigler, Sara L.

2013-01-01

Wildlife population models have been criticized for their narrow disciplinary perspective when analyzing complexity in coupled biological – physical – human systems. We describe a “metamodel” approach to species risk assessment when diverse threats act at different spatiotemporal scales, interact in non-linear ways, and are addressed by distinct disciplines. A metamodel links discrete, individual models that depict components of a complex system, governing the flow of information among models and the sequence of simulated events. Each model simulates processes specific to its disciplinary realm while being informed of changes in other metamodel components by accessing common descriptors of the system, populations, and individuals. Interactions among models are revealed as emergent properties of the system. We introduce a new metamodel platform, both to further explain key elements of the metamodel approach and as an example that we hope will facilitate the development of other platforms for implementing metamodels in population biology, species risk assessments, and conservation planning. We present two examples – one exploring the interactions of dispersal in metapopulations and the spread of infectious disease, the other examining predator-prey dynamics – to illustrate how metamodels can reveal complex processes and unexpected patterns when population dynamics are linked to additional extrinsic factors. Metamodels provide a flexible, extensible method for expanding population viability analyses beyond models of isolated population demographics into more complete representations of the external and intrinsic threats that must be understood and managed for species conservation. PMID:24349567
Nonequilibrium Population Dynamics of Phenotype Conversion of Cancer Cells

PubMed Central

Zhou, Joseph Xu; Pisco, Angela Oliveira; Qian, Hong; Huang, Sui

2014-01-01

Tumorigenesis is a dynamic biological process that involves distinct cancer cell subpopulations proliferating at different rates and interconverting between them. In this paper we proposed a mathematical framework of population dynamics that considers both distinctive growth rates and intercellular transitions between cancer cell populations. Our mathematical framework showed that both growth and transition influence the ratio of cancer cell subpopulations but the latter is more significant. We derived the condition that different cancer cell types can maintain distinctive subpopulations and we also explain why there always exists a stable fixed ratio after cell sorting based on putative surface markers. The cell fraction ratio can be shifted by changing either the growth rates of the subpopulations (Darwinism selection) or by environment-instructed transitions (Lamarckism induction). This insight can help us to understand the dynamics of the heterogeneity of cancer cells and lead us to new strategies to overcome cancer drug resistance. PMID:25438251
Nonlinear dynamics of trions under strong optical excitation in monolayer MoSe2.

PubMed

Ye, Jialiang; Yan, Tengfei; Niu, Binghui; Li, Ying; Zhang, Xinhui

2018-02-05

By employing ultrafast transient reflection measurements based on two-color pump-probe spectroscopy, the population and valley polarization dynamics of trions in monolayer MoSe 2 were investigated at relatively high excitation densities under near-resonant excitation. Both the nonlinear dynamic photobleaching of the trion resonance and the redshift of the exciton resonance were found to be responsible for the excitation-energy- and density-dependent transient reflection change as a result of many-body interactions. Furthermore, from the polarization-resolved measurements, it was revealed that the initial fast population and polarization decay process upon strong photoexcitation observed for trions was determined by trion formation, transient phase-space filling and the short valley lifetime of excitons. The results provide a basic understanding of the nonlinear dynamics of population and valley depolarization of trions, as well as exciton-trion correlation in atomically thin MoSe 2 and other transition metal dichalcogenide materials.
Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223
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.
Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844
Modeling of Nonlinear Dynamics and Synchronized Oscillations of Microbial Populations, Carbon and Oxygen Concentrations, Induced by Root Exudation in the Rhizosphere

NASA Astrophysics Data System (ADS)

Molz, F. J.; Faybishenko, B.; Jenkins, E. W.

2012-12-01

Mass and energy fluxes within the soil-plant-atmosphere continuum are highly coupled and inherently nonlinear. The main focus of this presentation is to demonstrate the results of numerical modeling of a system of 4 coupled, nonlinear ordinary differential equations (ODEs), which are used to describe the long-term, rhizosphere processes of soil microbial dynamics, including the competition between nitrogen-fixing bacteria and those unable to fix nitrogen, along with substrate concentration (nutrient supply) and oxygen concentration. Modeling results demonstrate the synchronized patterns of temporal oscillations of competing microbial populations, which are affected by carbon and oxygen concentrations. The temporal dynamics and amplitude of the root exudation process serve as a driving force for microbial and geochemical phenomena, and lead to the development of the Gompetzian dynamics, synchronized oscillations, and phase-space attractors of microbial populations and carbon and oxygen concentrations. The nonlinear dynamic analysis of time series concentrations from the solution of the ODEs was used to identify several types of phase-space attractors, which appear to be dependent on the parameters of the exudation function and Monod kinetic parameters. This phase space analysis was conducted by means of assessing the global and local embedding dimensions, correlation time, capacity and correlation dimensions, and Lyapunov exponents of the calculated model variables defining the phase space. Such results can be used for planning experimental and theoretical studies of biogeochemical processes in the fields of plant nutrition, phyto- and bio-remediation, and other ecological areas.

Informations in Models of Evolutionary Dynamics

NASA Astrophysics Data System (ADS)

Rivoire, Olivier

2016-03-01

Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.
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.
Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics

PubMed Central

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
Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics.

PubMed

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.
Microbial dynamics in mixed culture biofilms of bacteria surviving sanitation of conveyor belts in salmon-processing plants.

PubMed

Langsrud, S; Moen, B; Møretrø, T; Løype, M; Heir, E

2016-02-01

The microbiota surviving sanitation of salmon-processing conveyor belts was identified and its growth dynamics further investigated in a model mimicking processing surfaces in such plants. A diverse microbiota dominated by Gram-negative bacteria was isolated after regular sanitation in three salmon processing plants. A cocktail of 14 bacterial isolates representing all genera isolated from conveyor belts (Listeria, Pseudomonas, Stenotrophomonas, Brochothrix, Serratia, Acinetobacter, Rhodococcus and Chryseobacterium) formed stable biofilms on steel coupons (12°C, salmon broth) of about 10(9) CFU cm(-2) after 2 days. High-throughput sequencing showed that Listeria monocytogenes represented 0·1-0·01% of the biofilm population and that Pseudomonas spp dominated. Interestingly, both Brochothrix sp. and a Pseudomonas sp. dominated in the surrounding suspension. The microbiota surviving sanitation is dominated by Pseudomonas spp. The background microbiota in biofilms inhibit, but do not eliminate L. monocytogenes. The results highlights that sanitation procedures have to been improved in the salmon-processing industry, as high numbers of a diverse microbiota survived practical sanitation. High-throughput sequencing enables strain level studies of population dynamics in biofilm. © 2015 The Society for Applied Microbiology.
Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

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.
Efficacy of identifying neural components in the face and emotion processing system in schizophrenia using a dynamic functional localizer.

PubMed

Arnold, Aiden E G F; Iaria, Giuseppe; Goghari, Vina M

2016-02-28

Schizophrenia is associated with deficits in face perception and emotion recognition. Despite consistent behavioural results, the neural mechanisms underlying these cognitive abilities have been difficult to isolate, in part due to differences in neuroimaging methods used between studies for identifying regions in the face processing system. Given this problem, we aimed to validate a recently developed fMRI-based dynamic functional localizer task for use in studies of psychiatric populations and specifically schizophrenia. Previously, this functional localizer successfully identified each of the core face processing regions (i.e. fusiform face area, occipital face area, superior temporal sulcus), and regions within an extended system (e.g. amygdala) in healthy individuals. In this study, we tested the functional localizer success rate in 27 schizophrenia patients and in 24 community controls. Overall, the core face processing regions were localized equally between both the schizophrenia and control group. Additionally, the amygdala, a candidate brain region from the extended system, was identified in nearly half the participants from both groups. These results indicate the effectiveness of a dynamic functional localizer at identifying regions of interest associated with face perception and emotion recognition in schizophrenia. The use of dynamic functional localizers may help standardize the investigation of the facial and emotion processing system in this and other clinical populations. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Why do populations of southern pine beetle (Coleoptera: Scolytidae) fluctuate?

Treesearch

P. Turchin; P.L. Lorio; A.D. Taylor; R.F. Billings

1991-01-01

It is widely believed that population outbreaks of the southern pine beetle (Dendroctonus frontalis Zimm.) are caused by vagaries of climate, such as periods of severe drought.According to this view, D. frontalis population dynamics are dominated by density-independent processes.We have statistically analyzed a 30-yr record of D. frontalis activity in east Texas and...
Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations.

PubMed

Lenski, Richard E

2017-10-01

Evolution is an on-going process, and it can be studied experimentally in organisms with rapid generations. My team has maintained 12 populations of Escherichia coli in a simple laboratory environment for >25 years and 60 000 generations. We have quantified the dynamics of adaptation by natural selection, seen some of the populations diverge into stably coexisting ecotypes, described changes in the bacteria's mutation rate, observed the new ability to exploit a previously untapped carbon source, characterized the dynamics of genome evolution and used parallel evolution to identify the genetic targets of selection. I discuss what the future might hold for this particular experiment, briefly highlight some other microbial evolution experiments and suggest how the fields of experimental evolution and microbial ecology might intersect going forward.
Influence of habitat quality, population size, patch size, and connectivity on patch-occupancy dynamics of the middle spotted woodpecker.

PubMed

Robles, Hugo; Ciudad, Carlos

2012-04-01

Despite extensive research on the effects of habitat fragmentation, the ecological mechanisms underlying colonization and extinction processes are poorly known, but knowledge of these mechanisms is essential to understanding the distribution and persistence of populations in fragmented habitats. We examined these mechanisms through multiseason occupancy models that elucidated patch-occupancy dynamics of Middle Spotted Woodpeckers (Dendrocopos medius) in northwestern Spain. The number of occupied patches was relatively stable from 2000 to 2010 (15-24% of 101 patches occupied every year) because extinction was balanced by recolonization. Larger and higher quality patches (i.e., higher density of oaks >37 cm dbh [diameter at breast height]) were more likely to be occupied. Habitat quality (i.e., density of large oaks) explained more variation in patch colonization and extinction than did patch size and connectivity, which were both weakly associated with probabilities of turnover. Patches of higher quality were more likely to be colonized than patches of lower quality. Populations in high-quality patches were less likely to become extinct. In addition, extinction in a patch was strongly associated with local population size but not with patch size, which means the latter may not be a good surrogate of population size in assessments of extinction probability. Our results suggest that habitat quality may be a primary driver of patch-occupancy dynamics and may increase the accuracy of models of population survival. We encourage comparisons of competing models that assess occupancy, colonization, and extinction probabilities in a single analytical framework (e.g., dynamic occupancy models) so as to shed light on the association of habitat quality and patch geometry with colonization and extinction processes in different settings and species. ©2012 Society for Conservation Biology.
Counter-diabatic driving for Dirac dynamics

NASA Astrophysics Data System (ADS)

Fan, Qi-Zhen; Cheng, Xiao-Hang; Chen, Xi

2018-03-01

In this paper, we investigate the fast quantum control of Dirac equation dynamics by counter-diabatic driving, sharing the concept of shortcut to adiabaticity. We systematically calculate the counter-diabatic terms in different Dirac systems, like graphene and trapped ions. Specially, the fast and robust population inversion processes are achieved in Dirac system, taking into account the quantum simulation with trapped ions. In addition, the population transfer between two bands can be suppressed by counter-diabatic driving in graphene system, which might have potential applications in opt-electric devices.
IN-STREAM AND WATERSHED PREDICTORS OF GENETIC DIVERSITY, EFFECTIVE POPULATION SIZE AND IMMIGRATION ACROSS RIVER-STREAM NETWORKS

EPA Science Inventory

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...
Dynamical equivalence, the origin of the Galactic field stellar and binary population, and the initial radius-mass relation of embedded clusters

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Kroupa, Pavel; Rocha-Pinto, Helio J.; Giersz, Mirek

2018-03-01

In order to allow a better understanding of the origin of Galactic field populations, dynamical equivalence of stellar-dynamical systems has been postulated by Kroupa and Belloni et al. to allow mapping of solutions of the initial conditions of embedded clusters such that they yield, after a period of dynamical processing, the Galactic field population. Dynamically equivalent systems are defined to initially and finally have the same distribution functions of periods, mass ratios and eccentricities of binary stars. Here, we search for dynamically equivalent clusters using the MOCCA code. The simulations confirm that dynamically equivalent solutions indeed exist. The result is that the solution space is next to identical to the radius-mass relation of Marks & Kroupa, ( r_h/pc )= 0.1^{+0.07}_{-0.04} ( M_ecl/M_{⊙} )^{0.13± 0.04}. This relation is in good agreement with the oIMF. This is achieved by applying a similar procedurebserved density of molecular cloud clumps. According to the solutions, the time-scale to reach dynamical equivalence is about 0.5 Myr which is, interestingly, consistent with the lifetime of ultra-compact H II regions and the time-scale needed for gas expulsion to be active in observed very young clusters as based on their dynamical modelling.
Hydration dynamics promote bacterial coexistence on rough surfaces

PubMed Central

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
Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

Watanabe, Kei; Funahashi, Shintaro; Stokes, Mark G.

2017-01-01

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM. SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding. PMID:28559375
What can we learn from resource pulses?

PubMed

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.
A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.
Differential dynamic microscopy of weakly scattering and polydisperse protein-rich clusters

NASA Astrophysics Data System (ADS)

Safari, Mohammad S.; Vorontsova, Maria A.; Poling-Skutvik, Ryan; Vekilov, Peter G.; Conrad, Jacinta C.

2015-10-01

Nanoparticle dynamics impact a wide range of biological transport processes and applications in nanomedicine and natural resource engineering. Differential dynamic microscopy (DDM) was recently developed to quantify the dynamics of submicron particles in solutions from fluctuations of intensity in optical micrographs. Differential dynamic microscopy is well established for monodisperse particle populations, but has not been applied to solutions containing weakly scattering polydisperse biological nanoparticles. Here we use bright-field DDM (BDDM) to measure the dynamics of protein-rich liquid clusters, whose size ranges from tens to hundreds of nanometers and whose total volume fraction is less than 10-5. With solutions of two proteins, hemoglobin A and lysozyme, we evaluate the cluster diffusion coefficients from the dependence of the diffusive relaxation time on the scattering wave vector. We establish that for weakly scattering populations, an optimal thickness of the sample chamber exists at which the BDDM signal is maximized at the smallest sample volume. The average cluster diffusion coefficient measured using BDDM is consistently lower than that obtained from dynamic light scattering at a scattering angle of 90∘. This apparent discrepancy is due to Mie scattering from the polydisperse cluster population, in which larger clusters preferentially scatter more light in the forward direction.
Stochastic seasonality and nonlinear density-dependent factors regulate population size in an African rodent

USGS Publications Warehouse

Leirs, H.; Stenseth, N.C.; Nichols, J.D.; Hines, J.E.; Verhagen, R.; Verheyen, W.

1997-01-01

Ecology has long been troubled by the controversy over how populations are regulated. Some ecologists focus on the role of environmental effects, whereas others argue that density-dependent feedback mechanisms are central. The relative importance of both processes is still hotly debated, but clear examples of both processes acting in the same population are rare. Keyfactor analysis (regression of population changes on possible causal factors) and time-series analysis are often used to investigate the presence of density dependence, but such approaches may be biased and provide no information on actual demographic rates. Here we report on both density-dependent and density-independent effects in a murid rodent pest species, the multimammate rat Mastomys natalensis (Smith, 1834), using statistical capture-recapture models. Both effects occur simultaneously, but we also demonstrate that they do not affect all demographic rates in the same way. We have incorporated the obtained estimates of demographic rates in a population dynamics model and show that the observed dynamics are affected by stabilizing nonlinear density-dependent components coupled with strong deterministic and stochastic seasonal components.
A high-resolution genetic signature of demographic and spatial expansion in epizootic rabies virus

PubMed Central

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

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

PubMed

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).
PCR-DGGE analysis of lactic acid bacteria and yeast dynamics during the production processes of three varieties of Panettone.

PubMed

Garofalo, C; Silvestri, G; Aquilanti, L; Clementi, F

2008-07-01

To study lactic acid bacteria (LAB) and yeast dynamics during the production processes of sweet-leavened goods manufactured with type I sourdoughs. Fourteen sourdough and dough samples were taken from a baking company in central Italy during the production lines of three varieties of Panettone. The samples underwent pH measurements and plating analysis on three solid media. The microbial DNA was extracted from both the (sour)doughs and the viable LAB and yeast cells collected in bulk, and subjected to PCR-denaturing gradient gel electrophoresis (DGGE) analysis. The molecular fingerprinting of the cultivable plus noncultivable microbial populations provide evidence of the dominance of Lactobacillus sanfranciscensis, Lactobacillus brevis and Candida humilis in the three fermentation processes. The DGGE profiles of the cultivable communities reveal a bacterial shift in the final stages of two of the production processes, suggesting an effect of technological parameters on the selection of the dough microflora. Our findings confirm the importance of using a combined analytical approach to explore microbial communities that develop during the leavening process of sweet-leavened goods. In-depth studies of sourdough biodiversity and population dynamics occurring during sourdough fermentation are fundamental for the control of the leavening process and the manufacture of standardized, high-quality products.
Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants.

PubMed

Miller, Tom E X

2007-07-01

1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.
Phase synchronization motion and neural coding in dynamic transmission of neural information.

PubMed

Wang, Rubin; Zhang, Zhikang; Qu, Jingyi; Cao, Jianting

2011-07-01

In order to explore the dynamic characteristics of neural coding in the transmission of neural information in the brain, a model of neural network consisting of three neuronal populations is proposed in this paper using the theory of stochastic phase dynamics. Based on the model established, the neural phase synchronization motion and neural coding under spontaneous activity and stimulation are examined, for the case of varying network structure. Our analysis shows that, under the condition of spontaneous activity, the characteristics of phase neural coding are unrelated to the number of neurons participated in neural firing within the neuronal populations. The result of numerical simulation supports the existence of sparse coding within the brain, and verifies the crucial importance of the magnitudes of the coupling coefficients in neural information processing as well as the completely different information processing capability of neural information transmission in both serial and parallel couplings. The result also testifies that under external stimulation, the bigger the number of neurons in a neuronal population, the more the stimulation influences the phase synchronization motion and neural coding evolution in other neuronal populations. We verify numerically the experimental result in neurobiology that the reduction of the coupling coefficient between neuronal populations implies the enhancement of lateral inhibition function in neural networks, with the enhancement equivalent to depressing neuronal excitability threshold. Thus, the neuronal populations tend to have a stronger reaction under the same stimulation, and more neurons get excited, leading to more neurons participating in neural coding and phase synchronization motion.
The effect of EIF dynamics on the cryopreservation process of a size distributed cell population.

PubMed

Fadda, S; Briesen, H; Cincotti, A

2011-06-01

Typical mathematical modeling of cryopreservation of cell suspensions assumes a thermodynamic equilibrium between the ice and liquid water in the extracellular solution. This work investigates the validity of this assumption by introducing a population balance approach for dynamic extracellular ice formation (EIF) in the absence of any cryo-protectant agent (CPA). The population balance model reflects nucleation and diffusion-limited growth in the suspending solution whose driving forces are evaluated in the relevant phase diagram. This population balance description of the extracellular compartment has been coupled to a model recently proposed in the literature [Fadda et al., AIChE Journal, 56, 2173-2185, (2010)], which is capable of quantitatively describing and predicting internal ice formation (IIF) inside the cells. The cells are characterized by a size distribution (i.e. through another population balance), thus overcoming the classic view of a population of identically sized cells. From the comparison of the system behavior in terms of the dynamics of the cell size distribution it can be concluded that the assumption of a thermodynamic equilibrium in the extracellular compartment is not always justified. Depending on the cooling rate, the dynamics of EIF needs to be considered. Copyright © 2011 Elsevier Inc. All rights reserved.
Storm-time radiation belt electron dynamics: Repeatability in the outer radiation belt

NASA Astrophysics Data System (ADS)

Murphy, K. R.; Mann, I. R.; Rae, J.; Watt, C.; Boyd, A. J.; Turner, D. L.; Claudepierre, S. G.; Baker, D. N.; Spence, H. E.; Reeves, G. D.; Blake, J. B.; Fennell, J. F.

2017-12-01

During intervals of enhanced solar wind driving the outer radiation belt becomes extremely dynamic leading to geomagnetic storms. During these storms the flux of energetic electrons can vary by over 4 orders of magnitude. Despite recent advances in understanding the nature of competing storm-time electron loss and acceleration processes the dynamic behavior of the outer radiation belt remains poorly understood; the outer radiation belt can exhibit either no change, an enhancement, or depletion in radiation belt electrons. Using a new analysis of the total radiation belt electron content, calculated from the Van Allen probes phase space density (PSD), we statistically analyze the time-dependent and global response of the outer radiation belt during storms. We demonstrate that by removing adiabatic effects there is a clear and repeatable sequence of events in storm-time radiation belt electron dynamics. Namely, the relativistic (μ=1000 MeV/G) and ultra-relativistic (μ=4000 MeV/G) electron populations can be separated into two phases; an initial phase dominated by loss followed by a second phase dominated by acceleration. At lower energies, the radiation belt seed population of electrons (μ=150 MeV/G) shows no evidence of loss but rather a net enhancement during storms. Further, we investigate the dependence of electron dynamics as a function of the second adiabatic invariant, K. These results demonstrate a global coherency in the dynamics of the source, relativistic and ultra-relativistic electron populations as function of the second adiabatic invariant K. This analysis demonstrates two key aspects of storm-time radiation belt electron dynamics. First, the radiation belt responds repeatably to solar wind driving during geomagnetic storms. Second, the response of the radiation belt is energy dependent, relativistic electrons behaving differently than lower energy seed electrons. These results have important implications in radiation belt research. In particular, the repeatability in electron dynamics coupled with observations of processes leading to electron loss (EMIC waves) and acceleration (VLF or ULF waves) can be used to diagnose the relative importance of physical processes in radiation belt dynamics during storms.
A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes.

PubMed

Ponciano, José Miguel

2017-11-22

Using a nonparametric Bayesian approach Palacios and Minin (2013) dramatically improved the accuracy, precision of Bayesian inference of population size trajectories from gene genealogies. These authors proposed an extension of a Gaussian Process (GP) nonparametric inferential method for the intensity function of non-homogeneous Poisson processes. They found that not only the statistical properties of the estimators were improved with their method, but also, that key aspects of the demographic histories were recovered. The authors' work represents the first Bayesian nonparametric solution to this inferential problem because they specify a convenient prior belief without a particular functional form on the population trajectory. Their approach works so well and provides such a profound understanding of the biological process, that the question arises as to how truly "biology-free" their approach really is. Using well-known concepts of stochastic population dynamics, here I demonstrate that in fact, Palacios and Minin's GP model can be cast as a parametric population growth model with density dependence and environmental stochasticity. Making this link between population genetics and stochastic population dynamics modeling provides novel insights into eliciting biologically meaningful priors for the trajectory of the effective population size. The results presented here also bring novel understanding of GP as models for the evolution of a trait. Thus, the ecological principles foundation of Palacios and Minin (2013)'s prior adds to the conceptual and scientific value of these authors' inferential approach. I conclude this note by listing a series of insights brought about by this connection with Ecology. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.
Population clocks: motor timing with neural dynamics

PubMed Central

Buonomano, Dean V.; Laje, Rodrigo

2010-01-01

An understanding of sensory and motor processing will require elucidation of the mechanisms by which the brain tells time. Open questions relate to whether timing relies on dedicated or intrinsic mechanisms and whether distinct mechanisms underlie timing across scales and modalities. Although experimental and theoretical studies support the notion that neural circuits are intrinsically capable of sensory timing on short scales, few general models of motor timing have been proposed. For one class of models, population clocks, it is proposed that time is encoded in the time-varying patterns of activity of a population of neurons. We argue that population clocks emerge from the internal dynamics of recurrently connected networks, are biologically realistic and account for many aspects of motor timing. PMID:20889368
Interlinkages between bacterial populations dynamics and the operational parameters in a moving bed membrane bioreactor treating urban sewage.

PubMed

Reboleiro-Rivas, P; Martín-Pascual, J; Morillo, J A; Juárez-Jiménez, B; Poyatos, J M; Rodelas, B; González-López, J

2016-01-01

Bacteria are key players in biological wastewater treatments (WWTs), thus a firm knowledge of the bacterial population dynamics is crucial to understand environmental/operational factors affecting the efficiency and stability of the biological depuration process. Unfortunately, little is known about the microbial ecology of the advanced biological WWTs combining suspended biomass (SB) and attached biofilms (AB). This study explored in depth the bacterial community structure and population dynamics in each biomass fraction from a pilot-scale moving bed membrane bioreactor (MBMBR) treating municipal sewage, by means of temperature-gradient gel electrophoresis (TGGE) and 454-pyrosequencing. Eight experimental phases were conducted, combining different carrier filling ratios, hydraulic retention times and concentrations of mixed liquor total suspended solids. The bacterial community, dominated by Proteobacteria (20.9-53.8%) and Actinobacteria (20.6-57.6%), was very similar in both biomass fractions and able to maintain its functional stability under all the operating conditions, ensuring a successful and steady depuration process. Multivariate statistical analysis demonstrated that solids concentration, carrier filling ratio, temperature and organic matter concentration in the influent were the significant factors explaining population dynamics. Bacterial diversity increased as carrier filling ratio increased (from 20% to 35%, v/v), and solids concentration was the main factor triggering the shifts of the community structure. These findings provide new insights on the influence of operational parameters on the biology of the innovative MBMBRs. Copyright © 2015 Elsevier Ltd. All rights reserved.
Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.
Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844
Dispersal-mediated effect of microhabitat availability and density dependence determine population dynamics of a forest floor web spider.

PubMed

Takada, Mayura B; Miyashita, Tadashi

2014-09-01

Landscapes in nature can be viewed as a continuum of small total habitable area with high fragmentation to widely spreading habitats. The dispersal-mediated rescue effect predominates in the former landscapes, while classical density-dependent processes generally prevail in widely spread habitats. A similar principle should be applied to populations of organisms utilizing microhabitats in limited supply. To test this hypothesis, we examined the population dynamics of a web spider, Neriene brongersmai, in 16 populations with varying degrees of microhabitat availability, and we explored whether: (i) high microhabitat availability improves survival rate during density-independent movement, while the resultant high density reduces survival rate in a density-dependent manner; and (ii) temporal population stability increases with microhabitat availability at the population level. Furthermore, we conducted two types of field experiments to verify whether high microhabitat availability actually reduces mortality associated with web-site movement. Field observations revealed that demographic change in N. brongersmai populations was affected by three factors at different stages, namely the microhabitat limitation from the early to late juvenile stages, the density dependence from the late juvenile to adult stages and the food limitation from the adult to the next early juvenile stages. In addition, there was a tendency for a positive association between population stability and microhabitat availability at the population level. A small-scale experiment, where the frequency of spider web relocation was equalized artificially, revealed that high microhabitat availability elevated the survival rate during a movement event between web-sites. The larger spatiotemporal scale experiment also revealed an improved spider survival rate following treatment with high microhabitat availability, even though spider density was kept at a relatively low level. The population dynamics of N. brongersmai can be determined primarily by density-independent processes based on web-site fragmentation and density-dependent processes driven by interference competition. We conclude that depending on the amount of habitat resources, the relative importance of the two contrasting paradigms-equilibrium and non-equilibrium-appears to vary, even within a particular system. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
The evolution and devolution of cognitive control: The costs of deliberation in a competitive world

PubMed Central

Tomlin, Damon; Rand, David G.; Ludvig, Elliot A.; Cohen, Jonathan D.

2015-01-01

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale. PMID:26078086
The evolution and devolution of cognitive control: The costs of deliberation in a competitive world.

PubMed

Tomlin, Damon; Rand, David G; Ludvig, Elliot A; Cohen, Jonathan D

2015-06-16

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale.
Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

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.
Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974-2006

USGS Publications Warehouse

Taylor, Rebecca L.; Udevitz, Mark S.

2015-01-01

Global climate change may fundamentally alter population dynamics of many species for which baseline population parameter estimates are imprecise or lacking. Historically, the Pacific walrus is thought to have been limited by harvest, but it may become limited by global warming-induced reductions in sea ice. Loss of sea ice, on which walruses rest between foraging bouts, may reduce access to food, thus lowering vital rates. Rigorous walrus survival rate estimates do not exist, and other population parameter estimates are out of date or have well-documented bias and imprecision. To provide useful population parameter estimates we developed a Bayesian, hidden process demographic model of walrus population dynamics from 1974 through 2006 that combined annual age-specific harvest estimates with five population size estimates, six standing age structure estimates, and two reproductive rate estimates. Median density independent natural survival was high for juveniles (0.97) and adults (0.99), and annual density dependent vital rates rose from 0.06 to 0.11 for reproduction, 0.31 to 0.59 for survival of neonatal calves, and 0.39 to 0.85 for survival of older calves, concomitant with a population decline. This integrated population model provides a baseline for estimating changing population dynamics resulting from changing harvests or sea ice.
A generative inference framework for analysing patterns of cultural change in sparse population data with evidence for fashion trends in LBK culture.

PubMed

Kandler, Anne; Shennan, Stephen

2015-12-06

Cultural change can be quantified by temporal changes in frequency of different cultural artefacts and it is a central question to identify what underlying cultural transmission processes could have caused the observed frequency changes. Observed changes, however, often describe the dynamics in samples of the population of artefacts, whereas transmission processes act on the whole population. Here we develop a modelling framework aimed at addressing this inference problem. To do so, we firstly generate population structures from which the observed sample could have been drawn randomly and then determine theoretical samples at a later time t2 produced under the assumption that changes in frequencies are caused by a specific transmission process. Thereby we also account for the potential effect of time-averaging processes in the generation of the observed sample. Subsequent statistical comparisons (e.g. using Bayesian inference) of the theoretical and observed samples at t2 can establish which processes could have produced the observed frequency data. In this way, we infer underlying transmission processes directly from available data without any equilibrium assumption. We apply this framework to a dataset describing pottery from settlements of some of the first farmers in Europe (the LBK culture) and conclude that the observed frequency dynamic of different types of decorated pottery is consistent with age-dependent selection, a preference for 'young' pottery types which is potentially indicative of fashion trends. © 2015 The Author(s).
Inferring individual-level processes from population-level patterns in cultural evolution.

PubMed

Kandler, Anne; Wilder, Bryan; Fortunato, Laura

2017-09-01

Our species is characterized by a great degree of cultural variation, both within and between populations. Understanding how group-level patterns of culture emerge from individual-level behaviour is a long-standing question in the biological and social sciences. We develop a simulation model capturing demographic and cultural dynamics relevant to human cultural evolution, focusing on the interface between population-level patterns and individual-level processes. The model tracks the distribution of variants of cultural traits across individuals in a population over time, conditioned on different pathways for the transmission of information between individuals. From these data, we obtain theoretical expectations for a range of statistics commonly used to capture population-level characteristics (e.g. the degree of cultural diversity). Consistent with previous theoretical work, our results show that the patterns observed at the level of groups are rooted in the interplay between the transmission pathways and the age structure of the population. We also explore whether, and under what conditions, the different pathways can be distinguished based on their group-level signatures, in an effort to establish theoretical limits to inference. Our results show that the temporal dynamic of cultural change over time retains a stronger signature than the cultural composition of the population at a specific point in time. Overall, the results suggest a shift in focus from identifying the one individual-level process that likely produced the observed data to excluding those that likely did not. We conclude by discussing the implications for empirical studies of human cultural evolution.
The evidence for Allee effects

Treesearch

Andrew M. Kramer; Brian Dennis; Andrew M. Liebhold; John M. Drake

2009-01-01

Allee effects are an important dynamic phenomenon believed to be manifested in several population processes, notably extinction and invasion. Though widely cited in these contexts, the evidence for their strength and prevalence has not been critically evaluated. We review results from 91 studies on Allee effects in natural animal populations. We focus on empirical...
Mussel dynamics model: A hydroinformatics tool for analyzing the effects of different stressors on the dynamics of freshwater mussel communities

USGS Publications Warehouse

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.

Seasonal population dynamics of the invasive polychaete genus Marenzelleria spp. in contrasting soft-sediment habitats

NASA Astrophysics Data System (ADS)

Kauppi, L.; Norkko, A.; Norkko, J.

2018-01-01

Three species of the invasive polychaete genus Marenzelleria are among the dominant benthic taxa in many, especially deeper, areas in the Baltic Sea. The population dynamics of the polychaetes in the Baltic are, however, still largely unknown. We conducted monthly samplings of the benthic communities and environmental parameters at five sites with differing depths and sediment characteristics in the northern Baltic Sea (59°50.896‧, 23°15.092‧) to study the population dynamics, productivity and growth of Marenzelleria spp. from April 2013 to June 2014. The species of Marenzelleria occurring at the study sites were identified by genetic analyses. At the deepest site (33 m) only M. arctia was present, while all three species were found at the shallower, muddy sites (up to 20 m depth). At the shallow (6 m) sandy site only M. viridis and M. neglecta occurred. The sites differed in the seasonal dynamics of the Marenzelleria spp. population, reflecting the different species identities. The muddy sites up to 20 m depth showed clear seasonal dynamics, with the population practically disappearing by winter, whereas more stable populations occurred at the deepest site and at the sandy site. The highest density, biomass and production were observed at the 20 m deep, organic-rich muddy site where all three species recruited. The seasonally very high densities are likely to have important consequences for organic matter processing, and species interactions at these sites. The observed high productivity of the populations has possibly facilitated their establishment, and considerably increased secondary production in especially the deeper areas.
Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

PubMed

Takahashi, Yuma; Kagawa, Kotaro; Svensson, Erik I; Kawata, Masakado

2014-07-18

The effect of evolutionary changes in traits and phenotypic/genetic diversity on ecological dynamics has received much theoretical attention; however, the mechanisms and ecological consequences are usually unknown. Female-limited colour polymorphism in damselflies is a counter-adaptation to male mating harassment, and thus, is expected to alter population dynamics through relaxing sexual conflict. Here we show the side effect of the evolution of female morph diversity on population performance (for example, population productivity and sustainability) in damselflies. Our theoretical model incorporating key features of the sexual interaction predicts that the evolution of increased phenotypic diversity will reduce overall fitness costs to females from sexual conflict, which in turn will increase productivity, density and stability of a population. Field data and mesocosm experiments support these model predictions. Our study suggests that increased phenotypic diversity can enhance population performance that can potentially reduce extinction rates and thereby influence macroevolutionary processes.
Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

PubMed

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change.
The evolution of labile traits in sex- and age-structured populations.

PubMed

Childs, Dylan Z; Sheldon, Ben C; Rees, Mark

2016-03-01

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data-driven framework for incorporating such traits into demographic models has not yet been developed. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well-established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro-evolutionary dynamics in an IPM framework. We show how to embed quantitative genetic models of inheritance of labile traits into age-structured, two-sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg-laying date evolution, parameterized using data from a population of Great tits (Parus major). We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age-structured Price equation (ASPE) for two-sex populations, and apply this to examine the age-specific contributions of different processes to change in the mean phenotype and breeding value. The data-driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation. © 2016 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Estimation by capture-recapture of recruitment and dispersal over several sites

USGS Publications Warehouse

Lebreton, J.D.; Hines, J.E.; Pradel, R.; Nichols, J.D.; Spendelow, J.A.

2003-01-01

Dispersal in animal populations is intimately linked with accession to reproduction, i.e. recruitment, and population regulation. Dispersal processes are thus a key component of population dynamics to the same extent as reproduction or mortality processes. Despite the growing interest in spatial aspects of population dynamics, the methodology for estimating dispersal, in particular in relation with recruitment, is limited. In many animal populations, in particular vertebrates, the impossibility of following individuals over space and time in an exhaustive way leads to the need to frame the estimation of dispersal in the context of capture-recapture methodology. We present here a class of age-dependent multistate capture-recapture models for the simultaneous estimation of natal dispersal, breeding dispersal, and age-dependent recruitment. These models are suitable for populations in which individuals are marked at birth and then recaptured over several sites. Under simple constraints, they can be used in populations where non-breeders are not observed, as is often the case with colonial waterbirds monitored on their breeding grounds. Biological questions can be addressed by comparing models differing in structure, according to the generalized linear model philosophy broadly used in capture-recapture methodology. We illustrate the potential of this approach by an analysis of recruitment and dispersal in the roseate tern Sterna dougallii.
Individual heterogeneity in life histories and eco-evolutionary dynamics

PubMed Central

Vindenes, Yngvild; Langangen, Øystein

2015-01-01

Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics. PMID:25807980
The western spruce budworm model: structure and content.

Treesearch

K.A. Sheehan; W.P. Kemp; J.J. Colbert; N.L. Crookston

1989-01-01

The Budworm Model predicts the amounts of foliage destroyed annually by the western spruce budworm, Choristoneura occidentalis Freeman, in a forest stand. The model may be used independently, or it may be linked to the Stand Prognosis Model to simulate the dynamics of forest stands. Many processes that affect budworm population dynamics are...
Replicator dynamics with turnover of players

NASA Astrophysics Data System (ADS)

Juul, Jeppe; Kianercy, Ardeshir; Bernhardsson, Sebastian; Pigolotti, Simone

2013-08-01

We study adaptive dynamics in games where players abandon the population at a given rate and are replaced by naive players characterized by a prior distribution over the admitted strategies. We demonstrate how such a process leads macroscopically to a variant of the replicator equation, with an additional term accounting for player turnover. We study how Nash equilibria and the dynamics of the system are modified by this additional term for prototypical examples such as the rock-paper-scissors game and different classes of two-action games played between two distinct populations. We conclude by showing how player turnover can account for nontrivial departures from Nash equilibria observed in data from lowest unique bid auctions.
Development of working hypotheses linking management of the Missouri River to population dynamics of Scaphirhynchus albus (pallid sturgeon)

USGS Publications Warehouse

Jacobson, Robert B.; Parsley, Michael J.; Annis, Mandy L.; Colvin, Michael E.; Welker, Timothy L.; James, Daniel A.

2016-01-20

The initial set of candidate hypotheses provides a useful starting point for quantitative modeling and adaptive management of the river and species. We anticipate that hypotheses will change from the set of working management hypotheses as adaptive management progresses. More importantly, hypotheses that have been filtered out of our multistep process are still being considered. These filtered hypotheses are archived and if existing hypotheses are determined to be inadequate to explain observed population dynamics, new hypotheses can be created or filtered hypotheses can be reinstated.
Immune Response to a Variable Pathogen: A Stochastic Model with Two Interlocked Darwinian Entities

PubMed Central

Kuhn, Christoph

2012-01-01

This paper presents the modeling of a host immune system, more precisely the immune effector cell and immune memory cell population, and its interaction with an invading pathogen population. It will tackle two issues of interest; on the one hand, in defining a stochastic model accounting for the inherent nature of organisms in population dynamics, namely multiplication with mutation and selection; on the other hand, in providing a description of pathogens that may vary their antigens through mutations during infection of the host. Unlike most of the literature, which models the dynamics with first-order differential equations, this paper proposes a Galton-Watson type branching process to describe stochastically by whole distributions the population dynamics of pathogens and immune cells. In the first model case, the pathogen of a given type is either eradicated or shows oscillatory chronic response. In the second model case, the pathogen shows variational behavior changing its antigen resulting in a prolonged immune reaction. PMID:23424603
Immune response to a variable pathogen: a stochastic model with two interlocked Darwinian entities.

PubMed

Kuhn, Christoph

2012-01-01

This paper presents the modeling of a host immune system, more precisely the immune effector cell and immune memory cell population, and its interaction with an invading pathogen population. It will tackle two issues of interest; on the one hand, in defining a stochastic model accounting for the inherent nature of organisms in population dynamics, namely multiplication with mutation and selection; on the other hand, in providing a description of pathogens that may vary their antigens through mutations during infection of the host. Unlike most of the literature, which models the dynamics with first-order differential equations, this paper proposes a Galton-Watson type branching process to describe stochastically by whole distributions the population dynamics of pathogens and immune cells. In the first model case, the pathogen of a given type is either eradicated or shows oscillatory chronic response. In the second model case, the pathogen shows variational behavior changing its antigen resulting in a prolonged immune reaction.
A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank

Treesearch

Susan E. Meyer; Dana Quinney; Jay Weaver

2006-01-01

Population viability analysis (PVA) is a valuable tool for rare plant conservation, but PVA for plants with persistent seed banks is difficult without reliable information on seed bank processes. We modeled the population dynamics of the Snake River Plains ephemeral Lepidium papilliferum using data from an 11-yr artificial seed bank experiment to estimate age-specific...
Wildlife disease ecology from the individual to the population: Insights from a long-term study of a naturally infected European badger population.

PubMed

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.
Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.
[Dynamics of adaptation processes and morbidity risk for the popupation of the territory of industrial cities].

PubMed

Prusakov, V M; Prusakova, A V

2014-01-01

There was investigated the character of the adaptation processes in the population residing in conditions ofprolonged exposure to environmental pollution in the territory of the industrial cities of the Irkutsk region in order to identify the possible periodicity of their manifestations in the formation of the morbidity risk for the population of different age groups. Under conditions of prolonged exposure to air pollution and other adverse unfavorable factors of industrial cities in the population of all age groups long cyclic changes of adaptation processes in the body in the form of repeated 11-15-years cycles in which a period of relative destabilization of physiological functions with lowered resistance is replaced by the period with the state of elevated nonspecific resistance were established to be observed. Undulating changes of the dynamics of the relative risks of general morbidity should be considered in the assessment of the medical and environmental situation in the territory and making the managing decisions at the base on the data of public health monitoring.
Modeling the dynamical interaction between epidemics on overlay networks

NASA Astrophysics Data System (ADS)

Marceau, Vincent; Noël, Pierre-André; Hébert-Dufresne, Laurent; Allard, Antoine; Dubé, Louis J.

2011-08-01

Epidemics seldom occur as isolated phenomena. Typically, two or more viral agents spread within the same host population and may interact dynamically with each other. We present a general model where two viral agents interact via an immunity mechanism as they propagate simultaneously on two networks connecting the same set of nodes. By exploiting a correspondence between the propagation dynamics and a dynamical process performing progressive network generation, we develop an analytical approach that accurately captures the dynamical interaction between epidemics on overlay networks. The formalism allows for overlay networks with arbitrary joint degree distribution and overlap. To illustrate the versatility of our approach, we consider a hypothetical delayed intervention scenario in which an immunizing agent is disseminated in a host population to hinder the propagation of an undesirable agent (e.g., the spread of preventive information in the context of an emerging infectious disease).
Understanding Past Population Dynamics: Bayesian Coalescent-Based Modeling with Covariates

PubMed Central

Gill, Mandev S.; Lemey, Philippe; Bennett, Shannon N.; Biek, Roman; Suchard, Marc A.

2016-01-01

Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman’s coalescent process enables inference of past population dynamics directly from molecular sequence data, and researchers have developed a number of flexible coalescent-based models for Bayesian nonparametric estimation of the effective population size as a function of time. Major goals of demographic reconstruction include identifying driving factors of effective population size, and understanding the association between the effective population size and such factors. Building upon Bayesian nonparametric coalescent-based approaches, we introduce a flexible framework that incorporates time-varying covariates that exploit Gaussian Markov random fields to achieve temporal smoothing of effective population size trajectories. To approximate the posterior distribution, we adapt efficient Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. Incorporating covariates into the demographic inference framework enables the modeling of associations between the effective population size and covariates while accounting for uncertainty in population histories. Furthermore, it can lead to more precise estimates of population dynamics. We apply our model to four examples. We reconstruct the demographic history of raccoon rabies in North America and find a significant association with the spatiotemporal spread of the outbreak. Next, we examine the effective population size trajectory of the DENV-4 virus in Puerto Rico along with viral isolate count data and find similar cyclic patterns. We compare the population history of the HIV-1 CRF02_AG clade in Cameroon with HIV incidence and prevalence data and find that the effective population size is more reflective of incidence rate. Finally, we explore the hypothesis that the population dynamics of musk ox during the Late Quaternary period were related to climate change. [Coalescent; effective population size; Gaussian Markov random fields; phylodynamics; phylogenetics; population genetics. PMID:27368344
Age structure and cooperation in coevolutionary games on dynamic network

NASA Astrophysics Data System (ADS)

Qin, Zilong; Hu, Zhenhua; Zhou, Xiaoping; Yi, Jingzhang

2015-04-01

Our proposed model imitates the growth of a population and describes the age structure and the level of cooperation in games on dynamic network with continuous changes of structure and topology. The removal of nodes and links caused by age-dependent attack, together with the nodes addition standing for the newborns of population, badly ruins Matthew effect in this coevolutionary process. Though the network is generated by growth and preferential attachment, it degenerates into random network and it is no longer heterogeneous. When the removal of nodes and links is equal to the addition of nodes and links, the size of dynamic network is maintained in steady-state, so is the low level of cooperation. Severe structure variation, homogeneous topology and continuous invasion of new defection jointly make dynamic network unsuitable for the survival of cooperator even when the probability with which the newborn players initially adopt the strategy cooperation is high, while things change slightly when the connections of newborn players are restricted. Fortunately, moderate interactions in a generation trigger an optimal recovering process to encourage cooperation. The model developed in this paper outlines an explanation of the cohesion changes in the development process of an organization. Some suggestions for cooperative behavior improvement are given in the end.
Rapid contemporary evolution and clonal food web dynamics

PubMed Central

Jones, Laura E.; Becks, Lutz; Ellner, Stephen P.; Hairston, Nelson G.; Yoshida, Takehito; Fussmann, Gregor F.

2009-01-01

Character evolution that affects ecological community interactions often occurs contemporaneously with temporal changes in population size, potentially altering the very nature of those dynamics. Such eco-evolutionary processes may be most readily explored in systems with short generations and simple genetics. Asexual and cyclically parthenogenetic organisms such as microalgae, cladocerans and rotifers, which frequently dominate freshwater plankton communities, meet these requirements. Multiple clonal lines can coexist within each species over extended periods, until either fixation occurs or a sexual phase reshuffles the genetic material. When clones differ in traits affecting interspecific interactions, within-species clonal dynamics can have major effects on the population dynamics. We first consider a simple predator–prey system with two prey genotypes, parametrized with data from a well-studied experimental system, and explore how the extent of differences in defence against predation within the prey population determine dynamic stability versus instability of the system. We then explore how increased potential for evolution affects the community dynamics in a more general community model with multiple predator and multiple prey genotypes. These examples illustrate how microevolutionary ‘details’ that enhance or limit the potential for heritable phenotypic change can have significant effects on contemporaneous community-level dynamics and the persistence and coexistence of species. PMID:19414472
A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape

PubMed Central

2017-01-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection—a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies. PMID:28678792

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

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
Stochastic population dynamics of a montane ground-dwelling squirrel.

PubMed

Hostetler, Jeffrey A; Kneip, Eva; Van Vuren, Dirk H; Oli, Madan K

2012-01-01

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990-2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λ(s) was 0.92, suggesting a declining population; however, the 95% CI on λ(s) included 1.0 (0.52-1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration.
Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel

PubMed Central

Hostetler, Jeffrey A.; Kneip, Eva; Van Vuren, Dirk H.; Oli, Madan K.

2012-01-01

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λs was 0.92, suggesting a declining population; however, the 95% CI on λs included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration. PMID:22479616
Characterizing Total Radiation Belt Electron Content Using Van Allen Probes Data

NASA Astrophysics Data System (ADS)

Huang, C. L.; Spence, H. E.; Boyd, A. J.; Jordan, A.; Paulson, K. W.; Zhang, J.; Blake, J. B.; Kletzing, C.

2014-12-01

The comprehensive particle and wave measurements of the Van Allen Probes enable us to monitor the entire radiation belt near the equator from L-shells of 2.5 to 6. Using the particle measurements, we create an improved, high-level quantity representing the entire outer belt. This quantity, the total radiation belt electron content (TRBEC), is the half-orbit sum of outer belt electrons over the radiation belt energy ranges of importance and all pitch angles using data from RBSP-ECT instrument on board both spacecraft. The goal is to characterize statistically the dynamics of the entire radiation belt by comparing TRBEC with solar wind parameters, magnetospheric waves, and electron seed population. When comparing TRBEC with solar wind velocity, our result shows a triangle-distribution similar to that which Reeves et al. (2011) found using geosynchronous electron flux. We also correlate TRBEC with other solar wind parameters to identify which solar wind conditions effectively enhance or deplete radiation belt electrons. In addition, plasma waves in the inner magnetosphere, via wave-particle interaction, are key elements affecting the dynamics of the radiation belt. Therefore, we compare TRBEC with integrated EMIC and chorus (upper and lower bands) wave power calculated from EMFISIS wave measurements to determine the relative importance between each wave-particle process. Finally, we demonstrate the ~100 keV seed population's characteristics that correspond to the MeV population enhancement. While the gross features of the two populations are similar, the MeV population's dynamics lag behind those of the seed population by 5 to 60 hours, which implies the acceleration or loss processes vary by event.
Development of conceptual ecological models linking management of the Missouri River to pallid sturgeon population dynamics

USGS Publications Warehouse

Jacobson, Robert B.; Parsley, Michael J.; Annis, Mandy L.; Colvin, Michael E.; Welker, Timothy L.; James, Daniel A.

2015-01-01

This report documents the process of developing and refining conceptual ecological models (CEMs) for linking river management to pallid sturgeon (Scaphirhynchus albus) population dynamics in the Missouri River. The refined CEMs are being used in the Missouri River Pallid Sturgeon Effects Analysis to organize, document, and formalize an understanding of pallid sturgeon population responses to past and future management alternatives. The general form of the CEMs, represented by a population-level model and component life-stage models, was determined in workshops held in the summer of 2013. Subsequently, the Missouri River Pallid Sturgeon Effects Analysis team designed a general hierarchical structure for the component models, refined the graphical structure, and reconciled variation among the components and between models developed for the upper river (Upper Missouri & Yellowstone Rivers) and the lower river (Missouri River downstream from Gavins Point Dam). Importance scores attributed to the relations between primary biotic characteristics and survival were used to define a candidate set of working dominant hypotheses about pallid sturgeon population dynamics. These CEMs are intended to guide research and adaptive-management actions to benefit pallid sturgeon populations in the Missouri River.
Adult Demography and Larval Processes in Coastal Benthic Populations: Intertidal Barnacles in Southern California and Baja California

DTIC Science & Technology

2005-09-01

mechanism for near-shore concentration and estuarine recruitment of post-larval Penaeus plebejus Hess ( Decapoda , Penaeidae). Estuarine, Coastal and...the physical The dynamics of coastal populations is highly processes that are likely to affect the distribution dependent on the mechanisms and...help. I was lucky to land on a lab where, depending on the lunar phase, time of year, and who knows what other environmental variables, I would find a
Computational and experimental single cell biology techniques for the definition of cell type heterogeneity, interplay and intracellular dynamics.

PubMed

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.
Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.
Recruitment dynamics in complex life cycles. [of organisms living in marine rocky zone

NASA Technical Reports Server (NTRS)

Roughgarden, Jonathan; Possingham, Hugh; Gaines, Steven

1988-01-01

Factors affecting marine population fluctuations are discussed with particular attention given to a common barnacle species of the Pacific coast of North America. It is shown how models combining larval circulation with adult interactions can potentially forecast population fluctuations. These findings demonstrate how processes in different ecological habitats are coupled.
Emerging prion disease drives host selection in a wildlife population

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Johnson, Chad J.; Adams, Marie; McKenzie, Debbie I.

2012-01-01

Infectious diseases are increasingly recognized as an important force driving population dynamics, conservation biology, and natural selection in wildlife populations. Infectious agents have been implicated in the decline of small or endangered populations and may act to constrain population size, distribution, growth rates, or migration patterns. Further, diseases may provide selective pressures that shape the genetic diversity of populations or species. Thus, understanding disease dynamics and selective pressures from pathogens is crucial to understanding population processes, managing wildlife diseases, and conserving biological diversity. There is ample evidence that variation in the prion protein gene (PRNP) impacts host susceptibility to prion diseases. Still, little is known about how genetic differences might influence natural selection within wildlife populations. Here we link genetic variation with differential susceptibility of white-tailed deer to chronic wasting disease (CWD), with implications for fitness and disease-driven genetic selection. We developed a single nucleotide polymorphism (SNP) assay to efficiently genotype deer at the locus of interest (in the 96th codon of the PRNP gene). Then, using a Bayesian modeling approach, we found that the more susceptible genotype had over four times greater risk of CWD infection; and, once infected, deer with the resistant genotype survived 49% longer (8.25 more months). We used these epidemiological parameters in a multi-stage population matrix model to evaluate relative fitness based on genotype-specific population growth rates. The differences in disease infection and mortality rates allowed genetically resistant deer to achieve higher population growth and obtain a long-term fitness advantage, which translated into a selection coefficient of over 1% favoring the CWD-resistant genotype. This selective pressure suggests that the resistant allele could become dominant in the population within an evolutionarily short time frame. Our work provides a rare example of a quantifiable disease-driven selection process in a wildlife population, demonstrating the potential for infectious diseases to alter host populations. This will have direct bearing on the epidemiology, dynamics, and future trends in CWD transmission and spread. Understanding genotype-specific epidemiology will improve predictive models and inform management strategies for CWD-affected cervid populations.
Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less
Genetic algorithm enhanced by machine learning in dynamic aperture optimization

NASA Astrophysics Data System (ADS)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.
Genetic algorithm enhanced by machine learning in dynamic aperture optimization

DOE PAGES

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; ...

2018-05-29

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given “elite” status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitnessmore » of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. Furthermore, the machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.« less
Building the bridge between animal movement and population dynamics.

PubMed

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.
Population turnover and adaptation in heterogeneous environments

NASA Astrophysics Data System (ADS)

Campos, Paulo R. A.; de Oliveira, Viviane M.

2012-02-01

We study adaptive dynamics in a structured population model of asexual individuals which takes into account environmental heterogeneity among the subpopulations. The key purpose of the present work is to address how population turnovers, i.e. extinction events followed by recolonization, affect the rate of fixation of advantageous mutations. This model is a generalization of our previous model to address the interplay between environmental correlation and evolutionary forces on the adaptive process. The incorporation of population turnovers into the model enables us to make a direct correspondence between the model and host-parasite dynamics (epidemiological models). Strikingly, contrary to the intuitive and usual deleterious effect associated to extinction events, it is observed that population turnovers can in fact speed up adaptation as heterogeneity rises. On the other side, in nearly homogeneous population turnovers have a neutral effect on fixation rates, but a detrimental outcome is also achieved when extinction events become very common. In resume, population turnover outcomes on fixation rates of advantageous mutations are strongly influenced by the selective correlation among the subpopulations (demes).
Common factors drive disease and coarse woody debris dynamics in forests impacted by sudden oak death

Treesearch

Richard C. Cobb; Maggie N. Chan; Ross K. Meentemeyer; David M. Rizzo

2011-01-01

Disease ecology has made important steps in describing how epidemiological processes control the impact of pathogens on populations and communities but fewer field or theoretical studies address disease effects at the ecosystem level. We demonstrate that the same epidemiological mechanisms drive disease intensity and coarse woody debris (CWD) dynamics...
Ecological communities with Lotka-Volterra dynamics

NASA Astrophysics Data System (ADS)

Bunin, Guy

2017-04-01

Ecological communities in heterogeneous environments assemble through the combined effect of species interaction and migration. Understanding the effect of these processes on the community properties is central to ecology. Here we study these processes for a single community subject to migration from a pool of species, with population dynamics described by the generalized Lotka-Volterra equations. We derive exact results for the phase diagram describing the dynamical behaviors, and for the diversity and species abundance distributions. A phase transition is found from a phase where a unique globally attractive fixed point exists to a phase where multiple dynamical attractors exist, leading to history-dependent community properties. The model is shown to possess a symmetry that also establishes a connection with other well-known models.
Ecological communities with Lotka-Volterra dynamics.

PubMed

Bunin, Guy

2017-04-01

Ecological communities in heterogeneous environments assemble through the combined effect of species interaction and migration. Understanding the effect of these processes on the community properties is central to ecology. Here we study these processes for a single community subject to migration from a pool of species, with population dynamics described by the generalized Lotka-Volterra equations. We derive exact results for the phase diagram describing the dynamical behaviors, and for the diversity and species abundance distributions. A phase transition is found from a phase where a unique globally attractive fixed point exists to a phase where multiple dynamical attractors exist, leading to history-dependent community properties. The model is shown to possess a symmetry that also establishes a connection with other well-known models.
The role of local populations within a landscape context: Defining and classifying sources and sinks

USGS Publications Warehouse

Runge, J.P.; Runge, M.C.; Nichols, J.D.

2006-01-01

The interaction of local populations has been the focus of an increasing number of studies in the past 30 years. The study of source-sink dynamics has especially generated much interest. Many of the criteria used to distinguish sources and sinks incorporate the process of apparent survival (i.e., the combined probability of true survival and site fidelity) but not emigration. These criteria implicitly treat emigration as mortality, thus biasing the classification of sources and sinks in a manner that could lead to flawed habitat management. Some of the same criteria require rather restrictive assumptions about population equilibrium that, when violated, can also generate misleading inference. Here, we expand on a criterion (denoted ?contribution? or Cr) that incorporates successful emigration in differentiating sources and sinks and that makes no restrictive assumptions about dispersal or equilibrium processes in populations of interest. The metric Cr is rooted in the theory of matrix population models, yet it also contains clearly specified parameters that have been estimated in previous empirical research. We suggest that estimates of emigration are important for delineating sources and sinks and, more generally, for evaluating how local populations interact to generate overall system dynamics. This suggestion has direct implications for issues such as species conservation and habitat management.
Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Inferring individual-level processes from population-level patterns in cultural evolution

PubMed Central

Wilder, Bryan

2017-01-01

Our species is characterized by a great degree of cultural variation, both within and between populations. Understanding how group-level patterns of culture emerge from individual-level behaviour is a long-standing question in the biological and social sciences. We develop a simulation model capturing demographic and cultural dynamics relevant to human cultural evolution, focusing on the interface between population-level patterns and individual-level processes. The model tracks the distribution of variants of cultural traits across individuals in a population over time, conditioned on different pathways for the transmission of information between individuals. From these data, we obtain theoretical expectations for a range of statistics commonly used to capture population-level characteristics (e.g. the degree of cultural diversity). Consistent with previous theoretical work, our results show that the patterns observed at the level of groups are rooted in the interplay between the transmission pathways and the age structure of the population. We also explore whether, and under what conditions, the different pathways can be distinguished based on their group-level signatures, in an effort to establish theoretical limits to inference. Our results show that the temporal dynamic of cultural change over time retains a stronger signature than the cultural composition of the population at a specific point in time. Overall, the results suggest a shift in focus from identifying the one individual-level process that likely produced the observed data to excluding those that likely did not. We conclude by discussing the implications for empirical studies of human cultural evolution. PMID:28989786
Maintenance of algal endosymbionts in Paramecium bursaria: a simple model based on population dynamics.

PubMed

Iwai, Sosuke; Fujiwara, Kenji; Tamura, Takuro

2016-09-01

Algal endosymbiosis is widely distributed in eukaryotes including many protists and metazoans, and plays important roles in aquatic ecosystems, combining phagotrophy and phototrophy. To maintain a stable symbiotic relationship, endosymbiont population size in the host must be properly regulated and maintained at a constant level; however, the mechanisms underlying the maintenance of algal endosymbionts are still largely unknown. Here we investigate the population dynamics of the unicellular ciliate Paramecium bursaria and its Chlorella-like algal endosymbiont under various experimental conditions in a simple culture system. Our results suggest that endosymbiont population size in P. bursaria was not regulated by active processes such as cell division coupling between the two organisms, or partitioning of the endosymbionts at host cell division. Regardless, endosymbiont population size was eventually adjusted to a nearly constant level once cells were grown with light and nutrients. To explain this apparent regulation of population size, we propose a simple mechanism based on the different growth properties (specifically the nutrient requirements) of the two organisms, and based from this develop a mathematical model to describe the population dynamics of host and endosymbiont. The proposed mechanism and model may provide a basis for understanding the maintenance of algal endosymbionts. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.
Cooperation guided by the coexistence of imitation dynamics and aspiration dynamics in structured populations

NASA Astrophysics Data System (ADS)

Xu, Kuangyi; Li, Kun; Cong, Rui; Wang, Long

2017-02-01

In the framework of the evolutionary game theory, two fundamentally different mechanisms, the imitation process and the aspiration-driven dynamics, can be adopted by players to update their strategies. In the former case, individuals imitate the strategy of a more successful peer, while in the latter case individuals change their strategies based on a comparison of payoffs they collect in the game to their own aspiration levels. Here we explore how cooperation evolves for the coexistence of these two dynamics. Intriguingly, cooperation reaches its lowest level when a certain moderate fraction of individuals pick aspiration-level-driven rule while the others choose pairwise comparison rule. Furthermore, when individuals can adjust their update rules besides their strategies, either imitation dynamics or aspiration-driven dynamics will finally take over the entire population, and the stationary cooperation level is determined by the outcome of competition between these two dynamics. We find that appropriate synergetic effects and moderate aspiration level boost the fixation probability of aspiration-driven dynamics most effectively. Our work may be helpful in understanding the cooperative behavior induced by the coexistence of imitation dynamics and aspiration dynamics in the society.
Ranking landscape development scenarios affecting natterjack toad (Bufo calamita) population dynamics in Central Poland.

PubMed

Franz, Kamila W; Romanowski, Jerzy; Johst, Karin; Grimm, Volker

2013-01-01

When data are limited it is difficult for conservation managers to assess alternative management scenarios and make decisions. The natterjack toad (Bufo calamita) is declining at the edges of its distribution range in Europe and little is known about its current distribution and abundance in Poland. Although different landscape management plans for central Poland exist, it is unclear to what extent they impact this species. Based on these plans, we investigated how four alternative landscape development scenarios would affect the total carrying capacity and population dynamics of the natterjack toad. To facilitate decision-making, we first ranked the scenarios according to their total carrying capacity. We used the software RAMAS GIS to determine the size and location of habitat patches in the landscape. The estimated carrying capacities were very similar for each scenario, and clear ranking was not possible. Only the reforestation scenario showed a marked loss in carrying capacity. We therefore simulated metapopulation dynamics with RAMAS taking into account dynamical processes such as reproduction and dispersal and ranked the scenarios according to the resulting species abundance. In this case, we could clearly rank the development scenarios. We identified road mortality of adults as a key process governing the dynamics and separating the different scenarios. The renaturalisation scenario clearly ranked highest due to its decreased road mortality. Taken together our results suggest that road infrastructure development might be much more important for natterjack toad conservation than changes in the amount of habitat in the semi-natural river valley. We gained these insights by considering both the resulting metapopulation structure and dynamics in the form of a PVA. We conclude that the consideration of dynamic processes in amphibian conservation management may be indispensable for ranking management scenarios.
Differential dynamics of spatial attention, position, and color coding within the parietofrontal network.

PubMed

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.
The within-host population dynamics of Mycobacterium tuberculosis vary with treatment efficacy.

PubMed

Trauner, Andrej; Liu, Qingyun; Via, Laura E; Liu, Xin; Ruan, Xianglin; Liang, Lili; Shi, Huimin; Chen, Ying; Wang, Ziling; Liang, Ruixia; Zhang, Wei; Wei, Wang; Gao, Jingcai; Sun, Gang; Brites, Daniela; England, Kathleen; Zhang, Guolong; Gagneux, Sebastien; Barry, Clifton E; Gao, Qian

2017-04-19

Combination therapy is one of the most effective tools for limiting the emergence of drug resistance in pathogens. Despite the widespread adoption of combination therapy across diseases, drug resistance rates continue to rise, leading to failing treatment regimens. The mechanisms underlying treatment failure are well studied, but the processes governing successful combination therapy are poorly understood. We address this question by studying the population dynamics of Mycobacterium tuberculosis within tuberculosis patients undergoing treatment with different combinations of antibiotics. By combining very deep whole genome sequencing (~1000-fold genome-wide coverage) with sequential sputum sampling, we were able to detect transient genetic diversity driven by the apparently continuous turnover of minor alleles, which could serve as the source of drug-resistant bacteria. However, we report that treatment efficacy has a clear impact on the population dynamics: sufficient drug pressure bears a clear signature of purifying selection leading to apparent genetic stability. In contrast, M. tuberculosis populations subject to less drug pressure show markedly different dynamics, including cases of acquisition of additional drug resistance. Our findings show that for a pathogen like M. tuberculosis, which is well adapted to the human host, purifying selection constrains the evolutionary trajectory to resistance in effectively treated individuals. Nonetheless, we also report a continuous turnover of minor variants, which could give rise to the emergence of drug resistance in cases of drug pressure weakening. Monitoring bacterial population dynamics could therefore provide an informative metric for assessing the efficacy of novel drug combinations.
Coupling between populations of copepod taxa within an estuarine ecosystem and the adjacent offshore regions

NASA Astrophysics Data System (ADS)

McGinty, N.; Johnson, M. P.; Power, A. M.

2012-07-01

Population dynamics in open systems are complicated by the interactions of local demography and local environmental forcing with processes occurring at larger scales. A local system such as an estuary or bay may contain a zooplankton population that effectively becomes independent of regional dynamics or the local dynamics may be closely coupled to a broader scale pattern. As an alternative, the details of migration and advection may mean that dynamics in a local system are coupled to other specific areas rather than tracking the overall dynamics at a larger scale. We used a reconstructed time series (1973-1987) for copepod taxa to examine the extent to which zooplankton dynamics in Galway Bay reflect processes in broader areas of the NE Atlantic. Continuous Plankton Recorder (CPR) counts were used to establish time series for nine offshore ecoregions, with the regions themselves defined using underlying patterns of chlorophyll variability. The open nature of Galway Bay was reflected in strong associations between bay zooplankton counts and offshore CPR data in a majority of cases (7/10). For each zooplankton taxon, there were large differences among regions in the degree of association with Galway Bay time series. Akaike weights indicated that one ecoregion tended to be the dominant link for each taxon. This indicates that the zooplankton of the Bay reflect more than the local modification of a regional signal and that different zooplankton in the bay may have separate source regions. The data from Galway Bay also fall within a 'sampling shadow' of the CPR. Later years of the time series showed evidence for changes in phenology, with spring zooplankton peaks generally occurring earlier in the year for smaller species.
Critical short-time dynamics in a system with interacting static and diffusive populations

NASA Astrophysics Data System (ADS)

Argolo, C.; Quintino, Yan; Gleria, Iram; Lyra, M. L.

2012-01-01

We study the critical short-time dynamical behavior of a one-dimensional model where diffusive individuals can infect a static population upon contact. The model presents an absorbing phase transition from an active to an inactive state. Previous calculations of the critical exponents based on quasistationary quantities have indicated an unusual crossover from the directed percolation to the diffusive contact process universality classes. Here we show that the critical exponents governing the slow short-time dynamic evolution of several relevant quantities, including the order parameter, its relative fluctuations, and correlation function, reinforce the lack of universality in this model. Accurate estimates show that the critical exponents are distinct in the regimes of low and high recovery rates.
Dynamic Modeling of Yield and Particle Size Distribution in Continuous Bayer Precipitation

NASA Astrophysics Data System (ADS)

Stephenson, Jerry L.; Kapraun, Chris

Process engineers at Alcoa's Point Comfort refinery are using a dynamic model of the Bayer precipitation area to evaluate options in operating strategies. The dynamic model, a joint development effort between Point Comfort and the Alcoa Technical Center, predicts process yields, particle size distributions and occluded soda levels for various flowsheet configurations of the precipitation and classification circuit. In addition to rigorous heat, material and particle population balances, the model includes mechanistic kinetic expressions for particle growth and agglomeration and semi-empirical kinetics for nucleation and attrition. The kinetic parameters have been tuned to Point Comfort's operating data, with excellent matches between the model results and plant data. The model is written for the ACSL dynamic simulation program with specifically developed input/output graphical user interfaces to provide a user-friendly tool. Features such as a seed charge controller enhance the model's usefulness for evaluating operating conditions and process control approaches.
A general stochastic model for sporophytic self-incompatibility.

PubMed

Billiard, Sylvain; Tran, Viet Chi

2012-01-01

Disentangling the processes leading populations to extinction is a major topic in ecology and conservation biology. The difficulty to find a mate in many species is one of these processes. Here, we investigate the impact of self-incompatibility in flowering plants, where several inter-compatible classes of individuals exist but individuals of the same class cannot mate. We model pollen limitation through different relationships between mate availability and fertilization success. After deriving a general stochastic model, we focus on the simple case of distylous plant species where only two classes of individuals exist. We first study the dynamics of such a species in a large population limit and then, we look for an approximation of the extinction probability in small populations. This leads us to consider inhomogeneous random walks on the positive quadrant. We compare the dynamics of distylous species to self-fertile species with and without inbreeding depression, to obtain the conditions under which self-incompatible species can be less sensitive to extinction while they can suffer more pollen limitation. © Springer-Verlag 2011
Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.
Dynamic occupancy models for explicit colonization processes

USGS Publications Warehouse

Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

2016-01-01

The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.
Characterization of bacterial community dynamics in a full-scale drinking water treatment plant.

PubMed

Li, Cuiping; Ling, Fangqiong; Zhang, Minglu; Liu, Wen-Tso; Li, Yuxian; Liu, Wenjun

2017-01-01

Understanding the spatial and temporal dynamics of microbial communities in drinking water systems is vital to securing the microbial safety of drinking water. The objective of this study was to comprehensively characterize the dynamics of microbial biomass and bacterial communities at each step of a full-scale drinking water treatment plant in Beijing, China. Both bulk water and biofilm samples on granular activated carbon (GAC) were collected over 9months. The proportion of cultivable cells decreased during the treatment processes, and this proportion was higher in warm season than cool season, suggesting that treatment processes and water temperature probably had considerable impact on the R2A cultivability of total bacteria. 16s rRNA gene based 454 pyrosequencing analysis of the bacterial community revealed that Proteobacteria predominated in all samples. The GAC biofilm harbored a distinct population with a much higher relative abundance of Acidobacteria than water samples. Principle coordinate analysis and one-way analysis of similarity indicated that the dynamics of the microbial communities in bulk water and biofilm samples were better explained by the treatment processes rather than by sampling time, and distinctive changes of the microbial communities in water occurred after GAC filtration. Furthermore, 20 distinct OTUs contributing most to the dissimilarity among samples of different sampling locations and 6 persistent OTUs present in the entire treatment process flow were identified. Overall, our findings demonstrate the significant effects that treatment processes have on the microbial biomass and community fluctuation and provide implications for further targeted investigation on particular bacteria populations. Copyright © 2016. Published by Elsevier B.V.
Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less
Linking demographic processes and foraging ecology in wandering albatross-Conservation implications.

PubMed

Weimerskirch, Henri

2018-07-01

Population dynamics and foraging ecology are two fields of the population ecology that are generally studied separately. Yet, foraging determines allocation processes and therefore demography. Studies on wandering albatrosses Diomedea exulans over the past 50 years have contributed to better understand the links between population dynamics and foraging ecology. This article reviews how these two facets of population ecology have been combined to better understand ecological processes, but also have contributed fundamentally for the conservation of this long-lived threatened species. Wandering albatross research has combined a 50-year long-term study of marked individuals with two decades of tracking studies that have been initiated on this species, favoured by its large size and tameness. At all stages of their life history, the body mass of individuals plays a central role in allocation processes, in particular in influencing adult and juvenile survival, decisions to recruit into the population or to invest into provisioning the offspring or into maintenance. Strong age-related variations in demographic parameters are observed and are linked to age-related differences in foraging distribution and efficiency. Marked sex-specific differences in foraging distribution, foraging efficiency and changes in mass over lifetime are directly related to the strong sex-specific investment in breeding and survival trajectories of the two sexes, with body mass playing a pivotal role especially in males. Long-term study has allowed determining the sex-specific and age-specific demographic causes of population decline, and the tracking studies have been able to derive where and how these impacts occur, in particular the role of long-line fisheries. © 2018 The Author. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
A combined crossed-beam and theoretical study of the reaction dynamics of O(3P) + C2H3 → C2H2 + OH: analysis of the nascent OH products with the preferential population of the Π(A') component.

PubMed

Park, Min-Jin; Jang, Su-Chan; Choi, Jong-Ho

2012-11-28

The gas-phase reaction dynamics of ground-state atomic oxygen [O((3)P) from the photo-dissociation of NO(2)] with vinyl radicals [C(2)H(3) from the supersonic flash pyrolysis of vinyl iodide, C(2)H(3)I] has been investigated using a combination of high-resolution laser-induced fluorescence spectroscopy in a crossed-beam configuration and ab initio calculations. Unlike the previous gas-phase bulk kinetic experiments by Baulch et al. [J. Phys. Chem. Ref. Data 34, 757 (2005)], a new exothermic channel of O((3)P) + C(2)H(3) → C(2)H(2) + OH (X (2)Π: υ" = 0) has been identified for the first time, and the population analysis shows bimodal nascent rotational distributions of OH products with low- and high-N" components with a ratio of 2.4:1. No spin-orbit propensities were observed, and the averaged ratios of Π(A('))∕Π(A") were determined to be 1.66 ± 0.27. On the basis of computations at the CBS-QB3 theory level and comparison with prior theory, the microscopic mechanisms responsible for the nascent populations can be understood in terms of two competing dynamical pathways: a direct abstraction process in the low-N" regime as the major pathway and an addition-complex forming process in the high-N" regime as the minor pathway. Particularly, during the bond cleavage process of the weakly bound van der Waals complex C(2)H(2)-OH, the characteristic pathway from the low dihedral-angle geometry was consistent with the observed preferential population of the Π(A') component in the nascent OH products. A molecular-level discussion of the reactivity, mechanism, and dynamical features of the title reaction are presented together with a comparison to gas-phase oxidation reactions of a series of prototypical hydrocarbon radicals.
Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks.

PubMed

Billiard, Sylvain; Ferrière, Régis; Méléard, Sylvie; Tran, Viet Chi

2015-11-01

How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.
Accommodating environmental variation in population models: metaphysiological biomass loss accounting.

PubMed

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.
Ultrafast dynamics of photoactive yellow protein via the photoexcitation and emission processes.

PubMed

Nakamura, Ryosuke; Hamada, Norio; Ichida, Hideki; Tokunaga, Fumio; Kanematsu, Yasuo

2007-01-01

Pump-dump fluorescence spectroscopy was performed for photoactive yellow protein (PYP) at room temperature. The effect of the dump pulse on the population of the potential energy surface of the electronic excited state was examined as depletion in the stationary fluorescence intensity. The dynamic behavior of the population in the electronic excited state was successfully probed in the various combinations of the pump-dump delay, the dump-pulse wavelength, the dump-pulse energy and the observation wavelength. The experimental results were compared with the results obtained by the femtosecond time-resolved fluorescence spectroscopy.
Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

Network dynamics underlying the formation of sparse, informative representations in the hippocampus.

PubMed

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.
Population dynamics can be more important than physiological limits for determining range shifts under climate change.

PubMed

Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

2013-10-01

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.
Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity.

PubMed

Frickel, Jens; Theodosiou, Loukas; Becks, Lutz

2017-10-17

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus-host and prey-predator) with a more complex three-species system (virus-host-predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host-virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host-virus coevolution in the complex system and that the virus' effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species.
Molecular Clock of Neutral Mutations in a Fitness-Increasing Evolutionary Process

PubMed Central

Iijima, Leo; Suzuki, Shingo; Hashimoto, Tomomi; Oyake, Ayana; Kobayashi, Hisaka; Someya, Yuki; Narisawa, Dai; Yomo, Tetsuya

2015-01-01

The molecular clock of neutral mutations, which represents linear mutation fixation over generations, is theoretically explained by genetic drift in fitness-steady evolution or hitchhiking in adaptive evolution. The present study is the first experimental demonstration for the molecular clock of neutral mutations in a fitness-increasing evolutionary process. The dynamics of genome mutation fixation in the thermal adaptive evolution of Escherichia coli were evaluated in a prolonged evolution experiment in duplicated lineages. The cells from the continuously fitness-increasing evolutionary process were subjected to genome sequencing and analyzed at both the population and single-colony levels. Although the dynamics of genome mutation fixation were complicated by the combination of the stochastic appearance of adaptive mutations and clonal interference, the mutation fixation in the population was simply linear over generations. Each genome in the population accumulated 1.6 synonymous and 3.1 non-synonymous neutral mutations, on average, by the spontaneous mutation accumulation rate, while only a single genome in the population occasionally acquired an adaptive mutation. The neutral mutations that preexisted on the single genome hitchhiked on the domination of the adaptive mutation. The successive fixation processes of the 128 mutations demonstrated that hitchhiking and not genetic drift were responsible for the coincidence of the spontaneous mutation accumulation rate in the genome with the fixation rate of neutral mutations in the population. The molecular clock of neutral mutations to the fitness-increasing evolution suggests that the numerous neutral mutations observed in molecular phylogenetic trees may not always have been fixed in fitness-steady evolution but in adaptive evolution. PMID:26177190
Molecular Clock of Neutral Mutations in a Fitness-Increasing Evolutionary Process.

PubMed

Kishimoto, Toshihiko; Ying, Bei-Wen; Tsuru, Saburo; Iijima, Leo; Suzuki, Shingo; Hashimoto, Tomomi; Oyake, Ayana; Kobayashi, Hisaka; Someya, Yuki; Narisawa, Dai; Yomo, Tetsuya

2015-07-01

The molecular clock of neutral mutations, which represents linear mutation fixation over generations, is theoretically explained by genetic drift in fitness-steady evolution or hitchhiking in adaptive evolution. The present study is the first experimental demonstration for the molecular clock of neutral mutations in a fitness-increasing evolutionary process. The dynamics of genome mutation fixation in the thermal adaptive evolution of Escherichia coli were evaluated in a prolonged evolution experiment in duplicated lineages. The cells from the continuously fitness-increasing evolutionary process were subjected to genome sequencing and analyzed at both the population and single-colony levels. Although the dynamics of genome mutation fixation were complicated by the combination of the stochastic appearance of adaptive mutations and clonal interference, the mutation fixation in the population was simply linear over generations. Each genome in the population accumulated 1.6 synonymous and 3.1 non-synonymous neutral mutations, on average, by the spontaneous mutation accumulation rate, while only a single genome in the population occasionally acquired an adaptive mutation. The neutral mutations that preexisted on the single genome hitchhiked on the domination of the adaptive mutation. The successive fixation processes of the 128 mutations demonstrated that hitchhiking and not genetic drift were responsible for the coincidence of the spontaneous mutation accumulation rate in the genome with the fixation rate of neutral mutations in the population. The molecular clock of neutral mutations to the fitness-increasing evolution suggests that the numerous neutral mutations observed in molecular phylogenetic trees may not always have been fixed in fitness-steady evolution but in adaptive evolution.
Trends in snag populations in drought-stressed mixed-conifer and ponderosa pine forests (1997-2007)

Treesearch

Joseph L. Ganey; Scott C. Vojta

2012-01-01

Snags provide important biological legacies, resources for numerous species of native wildlife, and contribute to decay dynamics and ecological processes in forested ecosystems. We monitored trends in snag populations from 1997 to 2007 in drought-stressed mixed-conifer and ponderosa pine (Pinus ponderosa Dougl. ex Laws) forests, northern Arizona. Median snag density...
Model of white oak flower survival and maturation

Treesearch

David R. Larsen; Robert A. Cecich

1997-01-01

A stochastic model of oak flower dynamics is presented that integrates a number of factors which appear to affect the oak pistillate flower development process. The factors are modeled such that the distribution of the predicted flower populations could have come from the same distribution as the observed flower populations. Factors included in the model are; the range...
Population perspective is widening. Interview: Louise Lassonde.

PubMed

1992-01-01

Commentary is provided on the link between poverty and population growth, the link between population growth and the environment, solutions in general and at the village level, integrated programs, urban growth, and critical policies. Developing countries do recognize that rural poverty is part of the cycle of urban migration and population dynamics. Poverty also must be treated separately from population growth issues. An important issue is the reproductive health of women, their economic opportunities, and empowerment in decision making and access to information. Another important issue is the link between human species survival and the biosphere. Both issues need to be addressed and there is no contradiction between the issues; each is reinforcing of the other in policy. At the village level improving the personal, social, and environmental gains for women in villages with high fertility and soil erosion, deforestation, and water shortages serves both concerns. Programmatically, this means more information for women, better reproductive health services for women, improved social services, tree planting programs, water use programs, and environmental protection programs. Central planning is needed, but also decentralization in implementation and decision making. Urban population growth does not lend itself to ready-made solutions. The positive is that it offers modernization and the possibility of improved social services; the negative is how to provide the services. Both population dynamics and underlying infrastructure and urban management must work together. Recommendations are 3-fold. 1) Technology, the production/consumption process, and population dynamics are the major driving forces of environmental change. 2) The planning approach needs to be reconsidered: population dynamics and implications must be integrated at every level of planning. 3) Policies that recognize the aforementioned points will induce political will to implement activities and programs.
Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

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.

PubMed

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).
Long-term population cycles in human societies.

PubMed

Turchin, Peter

2009-04-01

Human population dynamics are usually conceptualized as either boundless growth or growth to an equilibrium. The implicit assumption underlying these paradigms is that any feedback processes regulating population density, if they exist, operate on a fast-time-scale, and therefore we do not expect to observe population oscillations in human population numbers. This review asks, are population processes in historical and prehistorical human populations characterized by second-order feedback loops, that is, regulation involving lags? If yes, then the implications for forecasting future population change are obvious--what may appear as inexplicable, exogenously driven reverses in population trends may actually be a result of feedbacks operating with substantial time lags. This survey of a variety of historical and archeological data indicates that slow oscillations in population numbers, with periods of roughly two to three centuries, are observed in a number of world regions and historical periods. Next, a potential explanation for this pattern, the demographic-structural theory, is discussed. Finally, the implications of these results for global population forecasts is discussed.
A new logistic dynamic particle swarm optimization algorithm based on random topology.

PubMed

Ni, Qingjian; Deng, Jianming

2013-01-01

Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.
Hierarchical coarse-graining model for photosystem II including electron and excitation-energy transfer processes.

PubMed

Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi

2014-03-01

We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Ecological change points: The strength of density dependence and the loss of history.

PubMed

Ponciano, José M; Taper, Mark L; Dennis, Brian

2018-05-01

Change points in the dynamics of animal abundances have extensively been recorded in historical time series records. Little attention has been paid to the theoretical dynamic consequences of such change-points. Here we propose a change-point model of stochastic population dynamics. This investigation embodies a shift of attention from the problem of detecting when a change will occur, to another non-trivial puzzle: using ecological theory to understand and predict the post-breakpoint behavior of the population dynamics. The proposed model and the explicit expressions derived here predict and quantify how density dependence modulates the influence of the pre-breakpoint parameters into the post-breakpoint dynamics. Time series transitioning from one stationary distribution to another contain information about where the process was before the change-point, where is it heading and how long it will take to transition, and here this information is explicitly stated. Importantly, our results provide a direct connection of the strength of density dependence with theoretical properties of dynamic systems, such as the concept of resilience. Finally, we illustrate how to harness such information through maximum likelihood estimation for state-space models, and test the model robustness to widely different forms of compensatory dynamics. The model can be used to estimate important quantities in the theory and practice of population recovery. Copyright © 2018 Elsevier Inc. All rights reserved.
Population dynamics in controlled unsteady-state systems: An application to the degradation of glyphosate in a sequencing batch reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Devarakonda, M.S.

1988-01-01

Control over population dynamics and organism selection in a biological waste treatment system provides an effective means of engineering process efficiency. Examples of applications of organism selection include control of filamentous organisms, biological nutrient removal, industrial waste treatment requiring the removal of specific substrates, and hazardous waste treatment. Inherently, full scale biological waste treatment systems are unsteady state systems due to the variations in the waste streams and mass flow rates of the substrates. Some systems, however, have the capacity to impose controlled selective pressures on the biological population by means of their operation. An example of such a systemmore » is the Sequencing Batch Reactor (SBR) which was the experimental system utilized in this research work. The concepts of organism selection were studied in detail for the biodegradation of a herbicide waste stream, with glyphosate as the target compound. The SBR provided a reactor configuration capable of exerting the necessary selective pressures to select and enrich for a glyphosate degrading population. Based on results for bench scale SBRs, a hypothesis was developed to explain population dynamics in glyphosate degrading systems.« less
Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

PubMed

MacLean, Adam L; Lo Celso, Cristina; Stumpf, Michael P H

2017-01-01

Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely-or in cases even poorly-understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever-increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self-renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. Stem Cells 2017;35:80-88. © 2016 AlphaMed Press.
Population shuffling between ground and high energy excited states

PubMed Central

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-01-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a “top-down” temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche− rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. PMID:26316263
Population shuffling between ground and high energy excited states.

PubMed

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-11-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a "top-down" temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche - rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. © 2015 The Protein Society.
Nonlinear effects of climate and density in the dynamics of a fluctuating population of reindeer.

PubMed

Tyler, Nicholas J C; Forchhammer, Mads C; Øritsland, Nils Are

2008-06-01

Nonlinear and irregular population dynamics may arise as a result of phase dependence and coexistence of multiple attractors. Here we explore effects of climate and density in the dynamics of a highly fluctuating population of wild reindeer (Rangifer tarandus platyrhynchus) on Svalbard observed over a period of 29 years. Time series analyses revealed that density dependence and the effects of local climate (measured as the degree of ablation [melting] of snow during winter) on numbers were both highly nonlinear: direct negative density dependence was found when the population was growing (Rt > 0) and during phases of the North Atlantic Oscillation (NAO) characterized by winters with generally high (1979-1995) and low (1996-2007) indices, respectively. A growth-phase-dependent model explained the dynamics of the population best and revealed the influence of density-independent processes on numbers that a linear autoregressive model missed altogether. In particular, the abundance of reindeer was enhanced by ablation during phases of growth (Rt > 0), an observation that contrasts with the view that periods of mild weather in winter are normally deleterious for reindeer owing to icing of the snowpack. Analyses of vital rates corroborated the nonlinearity described in the population time series and showed that both starvation mortality in winter and fecundity were nonlinearly related to fluctuations in density and the level of ablation. The erratic pattern of growth of the population of reindeer in Adventdalen seems, therefore, to result from a combination of the effects of nonlinear density dependence, strong density-dependent mortality, and variable density independence related to ablation in winter.
Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

Bacterial population dynamics during the ensiling of Medicago sativa (alfalfa) and subsequent exposure to air.

PubMed

McGarvey, J A; Franco, R B; Palumbo, J D; Hnasko, R; Stanker, L; Mitloehner, F M

2013-06-01

To describe, at high resolution, the bacterial population dynamics and chemical transformations during the ensiling of alfalfa and subsequent exposure to air. Samples of alfalfa, ensiled alfalfa and silage exposed to air were collected and their bacterial population structures compared using 16S rRNA gene libraries containing approximately 1900 sequences each. Cultural and chemical analyses were also performed to complement the 16S gene sequence data. Sequence analysis revealed significant differences (P < 0·05) in the bacterial populations at each time point. The alfalfa-derived library contained mostly sequences associated with the Gammaproteobacteria (including the genera: Enterobacter, Erwinia and Pantoea); the ensiled material contained mostly sequences associated with the lactic acid bacteria (LAB) (including the genera: Lactobacillus, Pediococcus and Lactococcus). Exposure to air resulted in even greater percentages of LAB, especially among the genus Lactobacillus, and a significant drop in bacterial diversity. In-depth 16S rRNA gene sequence analysis revealed significant bacterial population structure changes during ensiling and again during exposure to air. This in-depth description of the bacterial population dynamics that occurred during ensiling and simulated feed out expands our knowledge of these processes. © 2013 The Society for Applied Microbiology No claim to US Government works.
Frontal Cortex Activation Causes Rapid Plasticity of Auditory Cortical Processing

PubMed Central

Winkowski, Daniel E.; Bandyopadhyay, Sharba; Shamma, Shihab A.

2013-01-01

Neurons in the primary auditory cortex (A1) can show rapid changes in receptive fields when animals are engaged in sound detection and discrimination tasks. The source of a signal to A1 that triggers these changes is suspected to be in frontal cortical areas. How or whether activity in frontal areas can influence activity and sensory processing in A1 and the detailed changes occurring in A1 on the level of single neurons and in neuronal populations remain uncertain. Using electrophysiological techniques in mice, we found that pairing orbitofrontal cortex (OFC) stimulation with sound stimuli caused rapid changes in the sound-driven activity within A1 that are largely mediated by noncholinergic mechanisms. By integrating in vivo two-photon Ca2+ imaging of A1 with OFC stimulation, we found that pairing OFC activity with sounds caused dynamic and selective changes in sensory responses of neural populations in A1. Further, analysis of changes in signal and noise correlation after OFC pairing revealed improvement in neural population-based discrimination performance within A1. This improvement was frequency specific and dependent on correlation changes. These OFC-induced influences on auditory responses resemble behavior-induced influences on auditory responses and demonstrate that OFC activity could underlie the coordination of rapid, dynamic changes in A1 to dynamic sensory environments. PMID:24227723
Introduction: demography and cultural macroevolution.

PubMed

Steele, James; Shennan, Stephen

2009-04-01

The papers in this special issue of Human Biology, which derive from a conference sponsored by the Arts and Humanities Research Council (AHRC) Center for the Evolution of Cultural Diversity, lay some of the foundations for an empirical macroevolutionary analysis of cultural dynamics. Our premise here is that cultural dynamics-including the stability of traditions and the rate of origination of new variants-are influenced by independently occurring demographic processes (population size, structure, and distribution as these vary over time as a result of changes in rates of fertility, mortality, and migration). The contributors focus on three sets of problems relevant to empirical studies of cultural macroevolution: large-scale reconstruction of past population dynamics from archaeological and genetic data; juxtaposition of models and evidence of cultural dynamics using large-scale archaeological and historical data sets; and juxtaposition of models and evidence of cultural dynamics from large-scale linguistic data sets. In this introduction we outline some of the theoretical and methodological issues and briefly summarize the individual contributions.
Signatures of large-scale and local climates on the demography of white-tailed ptarmigan in Rocky Mountain National Park, Colorado, USA.

PubMed

Wang, Guiming; Hobbs, N Thompson; Galbraith, Hector; Giesen, Kenneth M

2002-09-01

Global climate change may impact wildlife populations by affecting local weather patterns, which, in turn, can impact a variety of ecological processes. However, it is not clear that local variations in ecological processes can be explained by large-scale patterns of climate. The North Atlantic oscillation (NAO) is a large-scale climate phenomenon that has been shown to influence the population dynamics of some animals. Although effects of the NAO on vertebrate population dynamics have been studied, it remains uncertain whether it broadly predicts the impact of weather on species. We examined the ability of local weather data and the NAO to explain the annual variation in population dynamics of white-tailed ptarmigan ( Lagopus leucurus) in Rocky Mountain National Park, USA. We performed canonical correlation analysis on the demographic subspace of ptarmigan and local-climate subspace defined by the empirical orthogonal function (EOF) using data from 1975 to 1999. We found that two subspaces were significantly correlated on the first canonical variable. The Pearson correlation coefficient of the first EOF values of the demographic and local-climate subspaces was significant. The population density and the first EOF of local-climate subspace influenced the ptarmigan population with 1-year lags in the Gompertz model. However, the NAO index was neither related to the first two EOF of local-climate subspace nor to the first EOF of the demographic subspace of ptarmigan. Moreover, the NAO index was not a significant term in the Gompertz model for the ptarmigan population. Therefore, local climate had stronger signature on the demography of ptarmigan than did a large-scale index, i.e., the NAO index. We conclude that local responses of wildlife populations to changing climate may not be adequately explained by models that project large-scale climatic patterns.
Implications of recurrent disturbance for genetic diversity.

PubMed

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.
Identifying the key biophysical drivers, connectivity outcomes, and metapopulation consequences of larval dispersal in the sea.

PubMed

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.
Black hole binaries dynamically formed in globular clusters

NASA Astrophysics Data System (ADS)

Park, Dawoo; Kim, Chunglee; Lee, Hyung Mok; Bae, Yeong-Bok; Belczynski, Krzysztof

2017-08-01

We investigate properties of black hole (BH) binaries formed in globular clusters via dynamical processes, using directN-body simulations. We pay attention to effects of BH mass function on the total mass and mass ratio distributions of BH binaries ejected from clusters. First, we consider BH populations with two different masses in order to learn basic differences from models with single-mass BHs only. Secondly, we consider continuous BH mass functions adapted from recent studies on massive star evolution in a low metallicity environment, where globular clusters are formed. In this work, we consider only binaries that are formed by three-body processes and ignore stellar evolution and primordial binaries for simplicity. Our results imply that most BH binary mergers take place after they get ejected from the cluster. Also, mass ratios of dynamically formed binaries should be close to 1 or likely to be less than 2:1. Since the binary formation efficiency is larger for higher-mass BHs, it is likely that a BH mass function sampled by gravitational-wave observations would be weighed towards higher masses than the mass function of single BHs for a dynamically formed population. Applying conservative assumptions regarding globular cluster populations such as small BH mass fraction and no primordial binaries, the merger rate of BH binaries originated from globular clusters is estimated to be at least 6.5 yr-1 Gpc-3. Actual rate can be up to more than several times of our conservative estimate.
Robust state preparation in quantum simulations of Dirac dynamics

NASA Astrophysics Data System (ADS)

Song, Xue-Ke; Deng, Fu-Guo; Lamata, Lucas; Muga, J. G.

2017-02-01

A nonrelativistic system such as an ultracold trapped ion may perform a quantum simulation of a Dirac equation dynamics under specific conditions. The resulting Hamiltonian and dynamics are highly controllable, but the coupling between momentum and internal levels poses some difficulties to manipulate the internal states accurately in wave packets. We use invariants of motion to inverse engineer robust population inversion processes with a homogeneous, time-dependent simulated electric field. This exemplifies the usefulness of inverse-engineering techniques to improve the performance of quantum simulation protocols.
Political dynamics determined by interactions between political leaders and voters.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernard, Michael Lewis; Bier, Asmeret; Backus, George A.

2010-03-01

The political dynamics associated with an election are typically a function of the interplay between political leaders and voters, as well as endogenous and exogenous factors that impact the perceptions and goals of the electorate. This paper describes an effort by Sandia National Laboratories to model the attitudes and behaviors of various political groups along with that population's primary influencers, such as government leaders. To accomplish this, Sandia National Laboratories is creating a hybrid system dynamics-cognitive model to simulate systems- and individual-level political dynamics in a hypothetical society. The model is based on well-established psychological theory, applied to both individualsmore » and groups within the modeled society. Confidence management processes are being incorporated into the model design process to increase the utility of the tool and assess its performance. This project will enhance understanding of how political dynamics are determined in democratic society.« less
Individual-based approach to epidemic processes on arbitrary dynamic contact networks

NASA Astrophysics Data System (ADS)

Rocha, Luis E. C.; Masuda, Naoki

2016-08-01

The dynamics of contact networks and epidemics of infectious diseases often occur on comparable time scales. Ignoring one of these time scales may provide an incomplete understanding of the population dynamics of the infection process. We develop an individual-based approximation for the susceptible-infected-recovered epidemic model applicable to arbitrary dynamic networks. Our framework provides, at the individual-level, the probability flow over time associated with the infection dynamics. This computationally efficient framework discards the correlation between the states of different nodes, yet provides accurate results in approximating direct numerical simulations. It naturally captures the temporal heterogeneities and correlations of contact sequences, fundamental ingredients regulating the timing and size of an epidemic outbreak, and the number of secondary infections. The high accuracy of our approximation further allows us to detect the index individual of an epidemic outbreak in real-life network data.
Population dynamics of mottled sculpin (PISCES) in a variable environment: information theoretic approaches

Treesearch

Gary D. Grossman; Robert E Ratajczak; J. Todd Petty; Mark D. Hunter; James T. Peterson; Gael Grenouillet

2006-01-01

We used strong inference with Akaike's Information Criterion (AIC) to assess the processes capable of explaining long-term (1984-1995) variation in the per capita rate of change of mottled sculpin (Cottus bairdi) populations in the Coweeta Creek drainage (USA). We sampled two fourth- and one fifth-order sites (BCA [uppermost], BCB, and CC [lowermost])...
Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon

Treesearch

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...
Changes in snag populations in northern Arizona mixed-conifer and ponderosa pine forests, 1997-2002

Treesearch

Joseph L. Ganey; Scott C. Vojta

2005-01-01

Snags (standing dead trees) are important components of forests that contribute to ecological processes and provide habitat for many life forms. We monitored dynamics of snag populations on 1-ha plots in southwestern mixed-conifer (n = 53 plots) and ponderosa pine (Pinus ponderosa, n = 60 plots) forests in north-central Arizona from 1997 to 2002. Of...
Comparative trends in log populations in northern Arizona mixed-conifer and ponderosa pine forests following severe drought

Treesearch

Joseph L. Ganey; Scott C. Vojta

2017-01-01

Logs provide an important form of coarse woody debris in forest systems, contributing to numerous ecological processes and affecting wildlife habitat and fuel complexes. Despite this, little information is available on the dynamics of log populations in southwestern ponderosa pine (Pinus ponderosa) and especially mixed-conifer forests. A recent episode of elevated tree...
Learning to Estimate Dynamical State with Probabilistic Population Codes.

PubMed

Makin, Joseph G; Dichter, Benjamin K; Sabes, Philip N

2015-11-01

Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH)-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.
Learning to Estimate Dynamical State with Probabilistic Population Codes

PubMed Central

Sabes, Philip N.

2015-01-01

Tracking moving objects, including one’s own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, “probabilistic population codes.” We show that a recurrent neural network—a modified form of an exponential family harmonium (EFH)—that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. PMID:26540152
Are genes faster than crabs? Mitochondrial introgression exceeds larval dispersal during population expansion of the invasive crab Carcinus maenas.

PubMed

Darling, John A; Tsai, Yi-Hsin Erica; Blakeslee, April M H; Roman, Joe

2014-10-01

Biological invasions offer unique opportunities to investigate evolutionary dynamics at the peripheries of expanding populations. Here, we examine genetic patterns associated with admixture between two distinct invasive lineages of the European green crab, Carcinus maenas L., independently introduced to the northwest Atlantic. Previous investigations based on mitochondrial DNA sequences demonstrated that larval dispersal driven by advective currents could explain observed southward displacement of an admixture zone between the two invasions. Comparison of published mitochondrial results with new nuclear data from nine microsatellite loci, however, reveals striking discordance in their introgression patterns. Specifically, introgression of mitochondrial genomes relative to nuclear background suggests that demographic processes such as sex-biased reproductive dynamics and population size imbalances-and not solely larval dispersal-play an important role in driving the evolution of the genetic cline. In particular, the unpredicted introgression of mitochondrial alleles against the direction of mean larval dispersal in the region is consistent with recent models invoking similar demographic processes to explain movements of genes into invading populations. These observations have important implications for understanding historical shifts in C. maenas range limits, and more generally for inferences of larval dispersal based on genetic data.
Are genes faster than crabs? Mitochondrial introgression exceeds larval dispersal during population expansion of the invasive crab Carcinus maenas

PubMed Central

Darling, John A.; Tsai, Yi-Hsin Erica; Blakeslee, April M. H.; Roman, Joe

2014-01-01

Biological invasions offer unique opportunities to investigate evolutionary dynamics at the peripheries of expanding populations. Here, we examine genetic patterns associated with admixture between two distinct invasive lineages of the European green crab, Carcinus maenas L., independently introduced to the northwest Atlantic. Previous investigations based on mitochondrial DNA sequences demonstrated that larval dispersal driven by advective currents could explain observed southward displacement of an admixture zone between the two invasions. Comparison of published mitochondrial results with new nuclear data from nine microsatellite loci, however, reveals striking discordance in their introgression patterns. Specifically, introgression of mitochondrial genomes relative to nuclear background suggests that demographic processes such as sex-biased reproductive dynamics and population size imbalances—and not solely larval dispersal—play an important role in driving the evolution of the genetic cline. In particular, the unpredicted introgression of mitochondrial alleles against the direction of mean larval dispersal in the region is consistent with recent models invoking similar demographic processes to explain movements of genes into invading populations. These observations have important implications for understanding historical shifts in C. maenas range limits, and more generally for inferences of larval dispersal based on genetic data. PMID:26064543
Dispersal of Mycobacterium tuberculosis via the Canadian fur trade

PubMed Central

Pepperell, Caitlin S.; Granka, Julie M.; Alexander, David C.; Behr, Marcel A.; Chui, Linda; Gordon, Janet; Guthrie, Jennifer L.; Jamieson, Frances B.; Langlois-Klassen, Deanne; Long, Richard; Nguyen, Dao; Wobeser, Wendy; Feldman, Marcus W.

2011-01-01

Patterns of gene flow can have marked effects on the evolution of populations. To better understand the migration dynamics of Mycobacterium tuberculosis, we studied genetic data from European M. tuberculosis lineages currently circulating in Aboriginal and French Canadian communities. A single M. tuberculosis lineage, characterized by the DS6Quebec genomic deletion, is at highest frequency among Aboriginal populations in Ontario, Saskatchewan, and Alberta; this bacterial lineage is also dominant among tuberculosis (TB) cases in French Canadians resident in Quebec. Substantial contact between these human populations is limited to a specific historical era (1710–1870), during which individuals from these populations met to barter furs. Statistical analyses of extant M. tuberculosis minisatellite data are consistent with Quebec as a source population for M. tuberculosis gene flow into Aboriginal populations during the fur trade era. Historical and genetic analyses suggest that tiny M. tuberculosis populations persisted for ∼100 y among indigenous populations and subsequently expanded in the late 19th century after environmental changes favoring the pathogen. Our study suggests that spread of TB can occur by two asynchronous processes: (i) dispersal of M. tuberculosis by minimal numbers of human migrants, during which small pathogen populations are sustained by ongoing migration and slow disease dynamics, and (ii) expansion of the M. tuberculosis population facilitated by shifts in host ecology. If generalizable, these migration dynamics can help explain the low DNA sequence diversity observed among isolates of M. tuberculosis and the difficulties in global elimination of tuberculosis, as small, widely dispersed pathogen populations are difficult both to detect and to eradicate. PMID:21464295
The need for sustained and integrated high-resolution mapping of dynamic coastal environments

USGS Publications Warehouse

Stockdon, Hilary F.; Lillycrop, Jeff W.; Howd, Peter A.; Wozencraft, Jennifer M.

2007-01-01

The evolution of the United States' coastal zone response to both human activities and natural processes is dynamic. Coastal resource and population protection requires understanding, in detail, the processes needed for change as well as the physical setting. Sustained coastal area mapping allows change to be documented and baseline conditions to be established, as well as future behavior to be predicted in conjunction with physical process models. Hyperspectral imagers and airborne lidars, as well as other recent mapping technology advances, allow rapid national scale land use information and high-resolution elevation data collection. Coastal hazard risk evaluation has critical dependence on these rich data sets. A fundamental storm surge model parameter in predicting flooding location, for example, is coastal elevation data, and a foundation in identifying the most vulnerable populations and resources is land use maps. A wealth of information for physical change process study, coastal resource and community management and protection, and coastal area hazard vulnerability determination, is available in a comprehensive national coastal mapping plan designed to take advantage of recent mapping technology progress and data distribution, management, and collection.

Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

NASA Astrophysics Data System (ADS)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.
Life-History and Spatial Determinants of Somatic Growth Dynamics in Komodo Dragon Populations

PubMed Central

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
Population biological principles of drug-resistance evolution in infectious diseases.

PubMed

zur Wiesch, Pia Abel; Kouyos, Roger; Engelstädter, Jan; Regoes, Roland R; Bonhoeffer, Sebastian

2011-03-01

The emergence of resistant pathogens in response to selection pressure by drugs and their possible disappearance when drug use is discontinued are evolutionary processes common to many pathogens. Population biological models have been used to study the dynamics of resistance in viruses, bacteria, and eukaryotic microparasites both at the level of the individual treated host and of the treated host population. Despite the existence of generic features that underlie such evolutionary dynamics, different conclusions have been reached about the key factors affecting the rate of resistance evolution and how to best use drugs to minimise the risk of generating high levels of resistance. Improved understanding of generic versus specific population biological aspects will help to translate results between different studies, and allow development of a more rational basis for sustainable drug use than exists at present. Copyright © 2011 Elsevier Ltd. All rights reserved.
Vulnerability of a killer whale social network to disease outbreaks

NASA Astrophysics Data System (ADS)

Guimarães, Paulo R., Jr.; de Menezes, Márcio Argollo; Baird, Robin W.; Lusseau, David; Guimarães, Paulo; Dos Reis, Sérgio F.

2007-10-01

Emerging infectious diseases are among the main threats to conservation of biological diversity. A crucial task facing epidemiologists is to predict the vulnerability of populations of endangered animals to disease outbreaks. In this context, the network structure of social interactions within animal populations may affect disease spreading. However, endangered animal populations are often small and to investigate the dynamics of small networks is a difficult task. Using network theory, we show that the social structure of an endangered population of mammal-eating killer whales is vulnerable to disease outbreaks. This feature was found to be a consequence of the combined effects of the topology and strength of social links among individuals. Our results uncover a serious challenge for conservation of the species and its ecosystem. In addition, this study shows that the network approach can be useful to study dynamical processes in very small networks.
Effect of temperature on the population dynamics of Aedes aegypti

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Tokachil, Mohd Najir

2015-10-01

Aedes aegypti is one of the main vectors in the transmission of dengue fever. Its abundance may cause the spread of the disease to be more intense. In the study of its biological life cycle, temperature was found to increase the development rate of each stage of this species and thus, accelerate the process of the development from egg to adult. In this paper, a Lefkovitch matrix model will be used to study the stage-structured population dynamics of Aedes aegypti. In constructing the transition matrix, temperature will be taken into account. As a case study, temperature recorded at the Subang Meteorological Station for year 2006 until 2010 will be used. Population dynamics of Aedes aegypti at maximum, average and minimum temperature for each year will be simulated and compared. It is expected that the higher the temperature, the faster the mosquito will breed. The result will be compared to the number of dengue fever incidences to see their relationship.
The roles of competition and habitat in the dynamics of populations and species distributions Ecology

Treesearch

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,...
Eco-evolutionary feedbacks drive species interactions

PubMed Central

Andrade-Domínguez, Andrés; Salazar, Emmanuel; del Carmen Vargas-Lagunas, María; Kolter, Roberto; Encarnación, Sergio

2014-01-01

In the biosphere, many species live in close proximity and can thus interact in many different ways. Such interactions are dynamic and fall along a continuum between antagonism and cooperation. Because interspecies interactions are the key to understanding biological communities, it is important to know how species interactions arise and evolve. Here, we show that the feedback between ecological and evolutionary processes has a fundamental role in the emergence and dynamics of species interaction. Using a two-species artificial community, we demonstrate that ecological processes and rapid evolution interact to influence the dynamics of the symbiosis between a eukaryote (Saccharomyces cerevisiae) and a bacterium (Rhizobium etli). The simplicity of our experimental design enables an explicit statement of causality. The niche-constructing activities of the fungus were the key ecological process: it allowed the establishment of a commensal relationship that switched to ammensalism and provided the selective conditions necessary for the adaptive evolution of the bacteria. In this latter state, the bacterial population radiates into more than five genotypes that vary with respect to nutrient transport, metabolic strategies and global regulation. Evolutionary diversification of the bacterial populations has strong effects on the community; the nature of interaction subsequently switches from ammensalism to antagonism where bacteria promote yeast extinction. Our results demonstrate the importance of the evolution-to-ecology pathway in the persistence of interactions and the stability of communities. Thus, eco-evolutionary dynamics have the potential to transform the structure and functioning of ecosystems. Our results suggest that these dynamics should be considered to improve our understanding of beneficial and detrimental host–microbe interactions. PMID:24304674
Can Evolution Supply What Ecology Demands?

PubMed

Kokko, Hanna; Chaturvedi, Anurag; Croll, Daniel; Fischer, Martin C; Guillaume, Frédéric; Karrenberg, Sophie; Kerr, Ben; Rolshausen, Gregor; Stapley, Jessica

2017-03-01

A simplistic view of the adaptive process pictures a hillside along which a population can climb: when ecological 'demands' change, evolution 'supplies' the variation needed for the population to climb to a new peak. Evolutionary ecologists point out that this simplistic view can be incomplete because the fitness landscape changes dynamically as the population evolves. Geneticists meanwhile have identified complexities relating to the nature of genetic variation and its architecture, and the importance of epigenetic variation is under debate. In this review, we highlight how complexity in both ecological 'demands' and the evolutionary 'supply' influences organisms' ability to climb fitness landscapes that themselves change dynamically as evolution proceeds, and encourage new synthetic effort across research disciplines towards ecologically realistic studies of adaptation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Surface intervalley scattering on GaAs(110) studied with picosecond laser photoemission

NASA Astrophysics Data System (ADS)

Haight, R.; Silberman, J. A.

1990-01-01

Laser-based photoemission sources provide the unique opportunity to study dynamic electronic processes at surfaces and interfaces. Using angle-resolved, laser photoemission with < 1 ps time resolution, we have directly observed a new surface band at the X¯ point in the GaAs(110) surface Brillouin zone. The appearance of electron population in this valley occurs only as a result of scattering from the directly photoexcited valley at overlineГ. The momentum resolution of our experiment has permitted us to isolate the dynamic electron population changes at both overlineГ and X¯ and to deduce the scattering time between the two valleys.
Understanding and predicting ecological dynamics: Are major surprises inevitable

USGS Publications Warehouse

Doak, Daniel F.; Estes, James A.; Halpern, Benjamin S.; Jacob, Ute; Lindberg, D.R.; Lovvorn, James R.; Monson, Daniel H.; Tinker, M. Tim; Williams, Terrie M.; Wootton, J. Timothy; Carroll, Ian; Emmerson, Mark; Micheli, Fiorenza; Novak, Mark

2008-01-01

Ecological surprises, substantial and unanticipated changes in the abundance of one or more species that result from previously unsuspected processes, are a common outcome of both experiments and observations in community and population ecology. Here, we give examples of such surprises along with the results of a survey of well-established field ecologists, most of whom have encountered one or more surprises over the course of their careers. Truly surprising results are common enough to require their consideration in any reasonable effort to characterize nature and manage natural resources. We classify surprises as dynamic-, pattern-, or intervention-based, and we speculate on the common processes that cause ecological systems to so often surprise us. A long-standing and still growing concern in the ecological literature is how best to make predictions of future population and community dynamics. Although most work on this subject involves statistical aspects of data analysis and modeling, the frequency and nature of ecological surprises imply that uncertainty cannot be easily tamed through improved analytical procedures, and that prudent management of both exploited and conserved communities will require precautionary and adaptive management approaches.
Electron-nuclear corellations for photoinduced dynamics in molecular dimers

NASA Astrophysics Data System (ADS)

Kilin, Dmitri S.; Pereversev, Yuryi V.; Prezhdo, Oleg V.

2003-03-01

Ultrafast photoinduced dynamics of electronic excitation in molecular dimers is drastically affected by dynamic reorganization of of inter- and intra- molecular nuclear configuration modelled by quantized nuclear degree of freedom [1]. The dynamics of the electronic population and nuclear coherence is analyzed with help of both numerical solution of the chain of coupled differential equations for mean coordinate, population inversion, electronic-vibrational correlation etc.[2] and by propagating the Gaussian wavepackets in relevant adiabatic potentials. Intriguing results were obtained in the approximation of small energy difference and small change of nuclear equilibrium configuration for excited electronic states. In the limiting case of resonance between electronic states energy difference and frequency of the nuclear mode these results have been justified by comparison to exactly solvable Jaynes-Cummings model. It has been found that the photoinduced processes in dimer are arranged according to their time scales:(i) fast scale of nuclear motion,(ii) intermediate scale of dynamical redistribution of electronic population between excited states as well as growth and dynamics of electronic -nuclear correlation,(iii) slow scale of electronic population approaching to the quasiequilibrium distribution, decay of electronic-nuclear correlation, and diminishing the amplitude of mean coordinate oscillations, accompanied by essential growth of the nuclear coordinate dispersion associated with the overall nuclear wavepacket width. Demonstrated quantum-relaxational features of photoinduced vibronic dinamical processess in molecular dimers are obtained by simple method, applicable to large biological systems with many degrees of freedom. [1] J. A. Cina, D. S. Kilin, T. S. Humble, J. Chem. Phys. (2003) in press. [2] O. V. Prezhdo, J. Chem. Phys. 117, 2995 (2002).
Temporal dynamics of genetic variability in a mountain goat (Oreamnos americanus) population.

PubMed

Ortego, Joaquín; Yannic, Glenn; Shafer, Aaron B A; Mainguy, Julien; Festa-Bianchet, Marco; Coltman, David W; Côté, Steeve D

2011-04-01

The association between population dynamics and genetic variability is of fundamental importance for both evolutionary and conservation biology. We combined long-term population monitoring and molecular genetic data from 123 offspring and their parents at 28 microsatellite loci to investigate changes in genetic diversity over 14 cohorts in a small and relatively isolated population of mountain goats (Oreamnos americanus) during a period of demographic increase. Offspring heterozygosity decreased while parental genetic similarity and inbreeding coefficients (F(IS) ) increased over the study period (1995-2008). Immigrants introduced three novel alleles into the population and matings between residents and immigrants produced more heterozygous offspring than local crosses, suggesting that immigration can increase population genetic variability. The population experienced genetic drift over the study period, reflected by a reduced allelic richness over time and an 'isolation-by-time' pattern of genetic structure. The temporal decline of individual genetic diversity despite increasing population size probably resulted from a combination of genetic drift due to small effective population size, inbreeding and insufficient counterbalancing by immigration. This study highlights the importance of long-term genetic monitoring to understand how demographic processes influence temporal changes of genetic diversity in long-lived organisms. © 2011 Blackwell Publishing Ltd.
Reversible Nuclear-Lipid-Droplet Morphology Induced by Oleic Acid: A Link to Cellular-Lipid Metabolism

PubMed Central

Lagrutta, Lucía C.; Montero-Villegas, Sandra; Layerenza, Juan P.; Sisti, Martín S.; García de Bravo, Margarita M.

2017-01-01

Neutral lipids—involved in many cellular processes—are stored as lipid droplets (LD), those mainly cytosolic (cLD) along with a small nuclear population (nLD). nLD could be involved in nuclear-lipid homeostasis serving as an endonuclear buffering system that would provide or incorporate lipids and proteins involved in signalling pathways as transcription factors and as enzymes of lipid metabolism and nuclear processes. Our aim was to determine if nLD constituted a dynamic domain. Oleic-acid (OA) added to rat hepatocytes or HepG2 cells in culture produced cellular-phenotypic LD modifications: increases in TAG, CE, C, and PL content and in cLD and nLD numbers and sizes. LD increments were reversed on exclusion of OA and were prevented by inhibition of acyl-CoA synthetase (with Triacsin C) and thus lipid biosynthesis. Under all conditions, nLD corresponded to a small population (2–10%) of total cellular LD. The anabolism triggered by OA, involving morphologic and size changes within the cLD and nLD populations, was reversed by a net balance of catabolism, upon eliminating OA. These catabolic processes included lipolysis and the mobilization of hydrolyzed FA from the LD to cytosolic-oxidation sites. These results would imply that nLD are actively involved in nuclear processes that include lipids. In conclusion, nLD are a dynamic nuclear domain since they are modified by OA through a reversible mechanism in combination with cLD; this process involves acyl-CoA-synthetase activity; ongoing TAG, CE, and PL biosynthesis. Thus, liver nLD and cLD are both dynamic cellular organelles. PMID:28125673
Complex dynamics of selection and cellular memory in adaptation to a changing environment

NASA Astrophysics Data System (ADS)

Kussell, Edo; Lin, Wei-Hsiang

We study a synthetic evolutionary system in bacteria in which an antibiotic resistance gene is controlled by a stochastic on/off switching promoter. At the population level, this system displays all the basic ingredients for evolutionary selection, including diversity, fitness differences, and heritability. At the single cell level, physiological processes can modulate the ability of selection to act. We expose the stochastic switching strains to pulses of antibiotics of different durations in periodically changing environments using microfluidics. Small populations are tracked over a large number of periods at single cell resolution, allowing the visualization and quantification of selective sweeps and counter-sweeps at the population level, as well as detailed single cell analysis. A simple model is introduced to predict long-term population growth rates from single cell measurements, and reveals unexpected aspects of population dynamics, including cellular memory that acts on a fast timescale to modulate growth rates. This work is supported by NIH Grant No. R01-GM097356.
Dynamics of a neutral delay equation for an insect population with long larval and short adult phases

NASA Astrophysics Data System (ADS)

Gourley, Stephen A.; Kuang, Yang

We present a global study on the stability of the equilibria in a nonlinear autonomous neutral delay differential population model formulated by Bocharov and Hadeler. This model may be suitable for describing the intriguing dynamics of an insect population with long larval and short adult phases such as the periodical cicada. We circumvent the usual difficulties associated with the study of the stability of a nonlinear neutral delay differential model by transforming it to an appropriate non-neutral nonautonomous delay differential equation with unbounded delay. In the case that no juveniles give birth, we establish the positivity and boundedness of solutions by ad hoc methods and global stability of the extinction and positive equilibria by the method of iteration. We also show that if the time adjusted instantaneous birth rate at the time of maturation is greater than 1, then the population will grow without bound, regardless of the population death process.
The Dynamical Imprint of Lost Protoplanets on the Trans-Neptunian Populations, and Limits on the Primordial Size Distribution of Trans-Neptunian Objects at Pluto and Larger Sizes.

NASA Astrophysics Data System (ADS)

Shannon, Andrew Brian; Dawson, Rebekah

2018-04-01

Planet formation remains a poorly understood process, in part because of our limited access to the intermediate phases of planetesimal and protoplanet growth. Today, the vast majority of the accessible remaining planetesimals and protoplanets reside within the Hot Trans-Neptunian Object population. This population has been depleted by 99% - 99.9% over the course of the Solar system's history, and as such the present day size-number distribution may be incomplete at the large size end. We show that such lost protoplanets would have left signatures in the dynamics of the present-day Trans-Neptunian Populations, and their primordial number can thus be statistically limited by considering the survival of ultra-wide binary TNOs, the Cold Classical Kuiper belt, and the resonant populations. We compare those limits to the predicted size-number distribution of various planetesimal and proto-planet growth models.
The malleability of gender stereotypes: influence of population size on perceptions of men and women in the past, present, and future.

PubMed

Garcia-Retamero, Rocio; Müller, Stephanie M; López-Zafra, Esther

2011-01-01

Recent studies on the malleability of gender stereotypes show that they are flexible, dynamic structures that change with the passage of time. In a study, we examined perceptions about men and women of the past, present, and future in Spain and focused on the influence of an important demographic variable on these perceptions: the population size of people's location of residence. Results showed that people perceived an increase in similarity of men and women from the past to the present and from the present to the future. In less-populated locations, however, men and women were more gender stereotyped and, consequently, still perceived to be further from equality than those in more populated areas. We concluded that the study of dynamic gender stereotypes benefits from extensive research in populations that vary in their demographic characteristics and shows the importance of recent movements in rural areas supporting women's participation in the modernization process.
New insights into the nonadiabatic state population dynamics of model proton-coupled electron transfer reactions from the mixed quantum-classical Liouville approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shakib, Farnaz A.; Hanna, Gabriel, E-mail: gabriel.hanna@ualberta.ca

In a previous study [F. A. Shakib and G. Hanna, J. Chem. Phys. 141, 044122 (2014)], we investigated a model proton-coupled electron transfer (PCET) reaction via the mixed quantum-classical Liouville (MQCL) approach and found that the trajectories spend the majority of their time on the mean of two coherently coupled adiabatic potential energy surfaces. This suggested a need for mean surface evolution to accurately simulate observables related to ultrafast PCET processes. In this study, we simulate the time-dependent populations of the three lowest adiabatic states in the ET-PT (i.e., electron transfer preceding proton transfer) version of the same PCET modelmore » via the MQCL approach and compare them to the exact quantum results and those obtained via the fewest switches surface hopping (FSSH) approach. We find that the MQCL population profiles are in good agreement with the exact quantum results and show a significant improvement over the FSSH results. All of the mean surfaces are shown to play a direct role in the dynamics of the state populations. Interestingly, our results indicate that the population transfer to the second-excited state can be mediated by dynamics on the mean of the ground and second-excited state surfaces, as part of a sequence of nonadiabatic transitions that bypasses the first-excited state surface altogether. This is made possible through nonadiabatic transitions between different mean surfaces, which is the manifestation of coherence transfer in MQCL dynamics. We also investigate the effect of the strength of the coupling between the proton/electron and the solvent coordinate on the state population dynamics. Drastic changes in the population dynamics are observed, which can be understood in terms of the changes in the potential energy surfaces and the nonadiabatic couplings. Finally, we investigate the state population dynamics in the PT-ET (i.e., proton transfer preceding electron transfer) and concerted versions of the model. The PT-ET results confirm the participation of all of the mean surfaces, albeit in different proportions compared to the ET-PT case, while the concerted results indicate that the mean of the ground- and first-excited state surfaces only plays a role, due to the large energy gaps between the ground- and second-excited state surfaces.« less
Fundamental properties of cooperative contagion processes

NASA Astrophysics Data System (ADS)

Chen, Li; Ghanbarnejad, Fakhteh; Brockmann, Dirk

2017-10-01

We investigate the effects of cooperativity between contagion processes that spread and persist in a host population. We propose and analyze a dynamical model in which individuals that are affected by one transmissible agent A exhibit a higher than baseline propensity of being affected by a second agent B and vice versa. The model is a natural extension of the traditional susceptible-infected-susceptible model used for modeling single contagion processes. We show that cooperativity changes the dynamics of the system considerably when cooperativity is strong. The system exhibits discontinuous phase transitions not observed in single agent contagion, multi-stability, a separation of the traditional epidemic threshold into different thresholds for inception and extinction as well as hysteresis. These properties are robust and are corroborated by stochastic simulations on lattices and generic network topologies. Finally, we investigate wave propagation and transients in a spatially extended version of the model and show that especially for intermediate values of baseline reproduction ratios the system is characterized by various types of wave-front speeds. The system can exhibit spatially heterogeneous stationary states for some parameters and negative front speeds (receding wave fronts). The two agent model can be employed as a starting point for more complex contagion processes, involving several interacting agents, a model framework particularly suitable for modeling the spread and dynamics of microbiological ecosystems in host populations.
Global attractors and extinction dynamics of cyclically competing species.

PubMed

Rulands, Steffen; Zielinski, Alejandro; Frey, Erwin

2013-05-01

Transitions to absorbing states are of fundamental importance in nonequilibrium physics as well as ecology. In ecology, absorbing states correspond to the extinction of species. We here study the spatial population dynamics of three cyclically interacting species. The interaction scheme comprises both direct competition between species as in the cyclic Lotka-Volterra model, and separated selection and reproduction processes as in the May-Leonard model. We show that the dynamic processes leading to the transient maintenance of biodiversity are closely linked to attractors of the nonlinear dynamics for the overall species' concentrations. The characteristics of these global attractors change qualitatively at certain threshold values of the mobility and depend on the relative strength of the different types of competition between species. They give information about the scaling of extinction times with the system size and thereby the stability of biodiversity. We define an effective free energy as the negative logarithm of the probability to find the system in a specific global state before reaching one of the absorbing states. The global attractors then correspond to minima of this effective energy landscape and determine the most probable values for the species' global concentrations. As in equilibrium thermodynamics, qualitative changes in the effective free energy landscape indicate and characterize the underlying nonequilibrium phase transitions. We provide the complete phase diagrams for the population dynamics and give a comprehensive analysis of the spatio-temporal dynamics and routes to extinction in the respective phases.

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity

PubMed Central

Frickel, Jens; Theodosiou, Loukas

2017-01-01

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus–host and prey–predator) with a more complex three-species system (virus–host–predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host–virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host–virus coevolution in the complex system and that the virus’ effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species. PMID:28973943
Spatial dynamics of invasion: the geometry of introduced species.

PubMed

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.
Evaluating mortality rates with a novel integrated framework for nonmonogamous species.

PubMed

Tenan, Simone; Iemma, Aaron; Bragalanti, Natalia; Pedrini, Paolo; De Barba, Marta; Randi, Ettore; Groff, Claudio; Genovart, Meritxell

2016-12-01

The conservation of wildlife requires management based on quantitative evidence, and especially for large carnivores, unraveling cause-specific mortalities and understanding their impact on population dynamics is crucial. Acquiring this knowledge is challenging because it is difficult to obtain robust long-term data sets on endangered populations and, usually, data are collected through diverse sampling strategies. Integrated population models (IPMs) offer a way to integrate data generated through different processes. However, IPMs are female-based models that cannot account for mate availability, and this feature limits their applicability to monogamous species only. We extended classical IPMs to a two-sex framework that allows investigation of population dynamics and quantification of cause-specific mortality rates in nonmonogamous species. We illustrated our approach by simultaneously modeling different types of data from a reintroduced, unhunted brown bear (Ursus arctos) population living in an area with a dense human population. In a population mainly driven by adult survival, we estimated that on average 11% of cubs and 61% of adults died from human-related causes. Although the population is currently not at risk, adult survival and thus population dynamics are driven by anthropogenic mortality. Given the recent increase of human-bear conflicts in the area, removal of individuals for management purposes and through poaching may increase, reversing the positive population growth rate. Our approach can be generalized to other species affected by cause-specific mortality and will be useful to inform conservation decisions for other nonmonogamous species, such as most large carnivores, for which data are scarce and diverse and thus data integration is highly desirable. © 2016 Society for Conservation Biology.
Ecological drivers of guanaco recruitment: variable carrying capacity and density dependence.

PubMed

Marino, Andrea; Pascual, Miguel; Baldi, Ricardo

2014-08-01

Ungulates living in predator-free reserves offer the opportunity to study the influence of food limitation on population dynamics without the potentially confounding effects of top-down regulation or livestock competition. We assessed the influence of relative forage availability and population density on guanaco recruitment in two predator-free reserves in eastern Patagonia, with contrasting scenarios of population density. We also explored the relative contribution of the observed recruitment to population growth using a deterministic linear model to test the assumption that the studied populations were closed units. The observed densities increased twice as fast as our theoretical populations, indicating that marked immigration has taken place during the recovery phase experienced by both populations, thus we rejected the closed-population assumption. Regarding the factors driving variation in recruitment, in the low- to medium-density setting, we found a positive linear relationship between recruitment and surrogates of annual primary production, whereas no density dependence was detected. In contrast, in the high-density scenario, both annual primary production and population density showed marked effects, indicating a positive relationship between recruitment and per capita food availability above a food-limitation threshold. Our results support the idea that environmental carrying capacity fluctuates in response to climatic variation, and that these fluctuations have relevant consequences for herbivore dynamics, such as amplifying density dependence in drier years. We conclude that including the coupling between environmental variability in resources and density dependence is crucial to model ungulate population dynamics; to overlook temporal changes in carrying capacity may even mask density dependence as well as other important processes.
Theoretical study of dynamic electron-spin-polarization via the doublet-quartet quantum-mixed state and time-resolved ESR spectra of the quartet high-spin state.

PubMed

Teki, Yoshio; Matsumoto, Takafumi

2011-04-07

The mechanism of the unique dynamic electron polarization of the quartet (S = 3/2) high-spin state via a doublet-quartet quantum-mixed state and detail theoretical calculations of the population transfer are reported. By the photo-induced electron transfer, the quantum-mixed charge-separate state is generated in acceptor-donor-radical triad (A-D-R). This mechanism explains well the unique dynamic electron polarization of the quartet state of A-D-R. The generation of the selectively populated quantum-mixed state and its transfer to the strongly coupled pure quartet and doublet states have been treated both by a perturbation approach and by exact numerical calculations. The analytical solutions show that generation of the quantum-mixed states with the selective populations after de-coherence and/or accompanying the (complete) dephasing during the charge-recombination are essential for the unique dynamic electron polarization. Thus, the elimination of the quantum coherence (loss of the quantum information) is the key process for the population transfer from the quantum-mixed state to the quartet state. The generation of high-field polarization on the strongly coupled quartet state by the charge-recombination process can be explained by a polarization transfer from the quantum-mixed charge-separate state. Typical time-resolved ESR patterns of the quantum-mixed state and of the strongly coupled quartet state are simulated based on the generation mechanism of the dynamic electron polarization. The dependence of the spectral pattern of the quartet high-spin state has been clarified for the fine-structure tensor and the exchange interaction of the quantum-mixed state. The spectral pattern of the quartet state is not sensitive towards the fine-structure tensor of the quantum-mixed state, because this tensor contributes only as a perturbation in the population transfer to the spin-sublevels of the quartet state. Based on the stochastic Liouville equation, it is also discussed why the selective population in the quantum-mixed state is generated for the "finite field" spin-sublevels. The numerical calculations of the elimination of the quantum coherence (de-coherence and/or dephasing) are demonstrated. A new possibility of the enhanced intersystem crossing pathway in solution is also proposed.
Theoretical study of optical pump process in solid gain medium based on four-energy-level model

NASA Astrophysics Data System (ADS)

Ma, Yongjun; Fan, Zhongwei; Zhang, Bin; Yu, Jin; Zhang, Hongbo

2018-04-01

A semiclassical algorithm is explored to a four-energy level model, aiming to find out the factors that affect the dynamics behavior during the pump process. The impacts of pump intensity Ω p , non-radiative transition rate γ 43 and decay rate of electric dipole δ 14 are discussed in detail. The calculation results show that large γ 43, small δ 14, and strong pumping Ω p are beneficial to the establishing of population inversion. Under strong pumping conditions, the entire pump process can be divided into four different phases, tentatively named far-from-equilibrium process, Rabi oscillation process, quasi dynamic equilibrium process and ‘equilibrium’ process. The Rabi oscillation can slow the pumping process and cause some instability. Moreover, the duration of the entire process is negatively related to Ω p and γ 43 whereas positively related to δ 14.
Disentangling the effects of climate, density dependence, and harvest on an iconic large herbivore's population dynamics.

PubMed

Koons, David N; Colchero, Fernando; Hersey, Kent; Gimenez, Olivier

2015-06-01

Understanding the relative effects of climate, harvest, and density dependence on population dynamics is critical for guiding sound population management, especially for ungulates in arid and semiarid environments experiencing climate change. To address these issues for bison in southern Utah, USA, we applied a Bayesian state-space model to a 72-yr time series of abundance counts. While accounting for known harvest (as well as live removal) from the population, we found that the bison population in southern Utah exhibited a strong potential to grow from low density (β0 = 0.26; Bayesian credible interval based on 95% of the highest posterior density [BCI] = 0.19-0.33), and weak but statistically significant density dependence (β1 = -0.02, BCI = -0.04 to -0.004). Early spring temperatures also had strong positive effects on population growth (Pfat1 = 0.09, BCI = 0.04-0.14), much more so than precipitation and other temperature-related variables (model weight > three times more than that for other climate variables). Although we hypothesized that harvest is the primary driving force of bison population dynamics in southern Utah, our elasticity analysis indicated that changes in early spring temperature could have a greater relative effect on equilibrium abundance than either harvest or. the strength of density dependence. Our findings highlight the utility of incorporating elasticity analyses into state-space population models, and the need to include climatic processes in wildlife management policies and planning.
Population dynamics of king eiders breeding in northern Alaska

USGS Publications Warehouse

Bentzen, Rebecca L.; Powell, Abby N.

2012-01-01

The North American population of king eiders (Somateria spectabilis) has declined by more than 50% since the late 1970s for unknown reasons. King eiders spend most of their lives in remote areas, forcing managers to make regulatory and conservation decisions based on very little information. We incorporated available published estimates of vital rates with new estimates to build a female, stage-based matrix population model for king eiders and examine the processes underlying population dynamics of king eiders breeding at 2 sites, Teshekpuk and Kuparuk, on the coastal plain of northern Alaska and wintering around the Bering Sea (2001–2010). We predicted a decreasing population (λ = 0.981, 95% CI: 0.978–0.985), and that population growth was most sensitive to changes in adult female survival (sensitivity = 0.92). Low duckling survival may be a bottleneck to productivity (variation in ducking survival accounted for 66% of retrospective variation in λ). Adult survival was high (0.94) and invariant (σ = 0.0002, 95% CI: 0.0000–0.0007); however, catastrophic events could have a major impact and we need to consider how to mitigate and manage threats to adult survival. A hypothetical oil spill affecting breeding females in a primary spring staging area resulted in a severe population decline; although, transient population dynamics were relatively stable. However, if no catastrophic events occur, the more variable reproductive parameters (duckling and nest survival) may be more responsive to management actions.
Differential influences of local subpopulations on regional diversity and differentiation for greater sage-grouse (Centrocercus urophasianus)

USGS Publications Warehouse

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.
Evolutionary game dynamics of controlled and automatic decision-making

NASA Astrophysics Data System (ADS)

Toupo, Danielle F. P.; Strogatz, Steven H.; Cohen, Jonathan D.; Rand, David G.

2015-07-01

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.
Evolutionary game dynamics of controlled and automatic decision-making.

PubMed

Toupo, Danielle F P; Strogatz, Steven H; Cohen, Jonathan D; Rand, David G

2015-07-01

We integrate dual-process theories of human cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and human cognition and suggest necessary conditions for the rise and fall of rationality.
Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

PubMed

Garcia, Leandro M T; Diez Roux, Ana V; Martins, André C R; Yang, Yong; Florindo, Alex A

2017-08-22

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults.
Interrogation of inhibitor of nuclear factor κB α/nuclear factor κB (IκBα/NF-κB) negative feedback loop dynamics: from single cells to live animals in vivo.

PubMed

Moss, Britney L; Elhammali, Adnan; Fowlkes, Tiffanie; Gross, Shimon; Vinjamoori, Anant; Contag, Christopher H; Piwnica-Worms, David

2012-09-07

Full understanding of the biological significance of negative feedback processes requires interrogation at multiple scales as follows: in single cells, cell populations, and live animals in vivo. The transcriptionally coupled IκBα/NF-κB negative feedback loop, a pivotal regulatory node of innate immunity and inflammation, represents a model system for multiscalar reporters. Using a κB(5)→IκBα-FLuc bioluminescent reporter, we rigorously evaluated the dynamics of ΙκBα degradation and subsequent NF-κB transcriptional activity in response to diverse modes of TNFα stimulation. Modulating TNFα concentration or pulse duration yielded complex, reproducible, and differential ΙκBα dynamics in both cell populations and live single cells. Tremendous heterogeneity in the transcriptional amplitudes of individual responding cells was observed, which was greater than the heterogeneity in the transcriptional kinetics of responsive cells. Furthermore, administration of various TNFα doses in vivo generated ΙκBα dynamic profiles in the liver resembling those observed in single cells and populations of cells stimulated with TNFα pulses. This suggested that dose modulation of circulating TNFα was perceived by hepatocytes in vivo as pulses of increasing duration. Thus, a robust bioluminescent reporter strategy enabled rigorous quantitation of NF-κB/ΙκBα dynamics in both live single cells and cell populations and furthermore, revealed reproducible behaviors that informed interpretation of in vivo studies.
Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.
Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865
Moving house: long-term dynamics of corticosterone secretion are unaltered in translocated populations of a rare reptile (the tuatara, Sphenodon punctatus).

PubMed

Anderson, Lindsay E; Cree, Alison; Towns, David R; Nelson, Nicola J

2015-01-01

Translocations are an important conservation tool used to restore at-risk species to their historical range. Unavoidable procedures during translocations, such as habitat disturbance, capture, handling, processing, captivity, transport and release to a novel environment, have the potential to be stressful for most species. In this study, we examined acute and chronic stress (through the measurement of the glucocorticoid corticosterone) in a rare reptile (the tuatara, Sphenodon punctatus). We found that: (i) the acute corticosterone response remains elevated during the initial translocation process but is not amplified by cumulative stressors; and (ii) the long-term dynamics of corticosterone secretion are similar in translocated and source populations. Taken together, our results show that translocated tuatara are generally resistant to cumulative acute stressors and show no hormonal sign of chronic stress. Translocation efforts in tuatara afford the potential to reduce extinction risk and restore natural ecosystems.
Identification of effective exciton-exciton annihilation in squaraine-squaraine copolymers.

PubMed

Hader, Kilian; May, Volkhard; Lambert, Christoph; Engel, Volker

2016-05-11

Ultrafast time-resolved transient absorption spectroscopy is able to monitor the fate of the excited state population in molecular aggregates or polymers. Due to many competing decay processes, the identification of exciton-exciton annihilation (EEA) is difficult. Here, we use a microscopic model to describe exciton annihilation processes in squaraine-squaraine copolymers. Transient absorption time traces measured at different laser powers exhibit an unusual time-dependence. The analysis points towards dynamics taking place on three time-scales. Immediately after laser-excitation a localization of excitons takes place within the femtosecond time-regime. This is followed by exciton-exciton annihilation which is responsible for a fast decay of the exciton population. At later times, excitations being localized on units which are not directly connected remain so that diffusion dominates the dynamics and leads to a slower decay. We thus provide evidence for EEA tracked by time-resolved spectroscopy which has not been reported that clearly before.
Impact of environmental colored noise in single-species population dynamics

NASA Astrophysics Data System (ADS)

Spanio, Tommaso; Hidalgo, Jorge; Muñoz, Miguel A.

2017-10-01

Variability on external conditions has important consequences for the dynamics and the organization of biological systems. In many cases, the characteristic timescale of environmental changes as well as their correlations play a fundamental role in the way living systems adapt and respond to it. A proper mathematical approach to understand population dynamics, thus, requires approaches more refined than, e.g., simple white-noise approximations. To shed further light onto this problem, in this paper we propose a unifying framework based on different analytical and numerical tools available to deal with "colored" environmental noise. In particular, we employ a "unified colored noise approximation" to map the original problem into an effective one with white noise, and then we apply a standard path integral approach to gain analytical understanding. For the sake of specificity, we present our approach using as a guideline a variation of the contact process—which can also be seen as a birth-death process of the Malthus-Verhulst class—where the propagation or birth rate varies stochastically in time. Our approach allows us to tackle in a systematic manner some of the relevant questions concerning population dynamics under environmental variability, such as determining the stationary population density, establishing the conditions under which a population may become extinct, and estimating extinction times. We focus on the emerging phase diagram and its possible phase transitions, underlying how these are affected by the presence of environmental noise time-correlations.
Determination of the formation of dark state via depleted spontaneous emission in a complex solvated molecule.

PubMed

Guo, Xunmin; Wang, Sufan; Xia, Andong; Su, Hongmei

2007-07-05

We present a general two-color two-pulse femtosecond pump-dump approach to study the specific population transfer along the reaction coordinate through the higher vibrational energy levels of excited states of a complex solvated molecule via the depleted spontaneous emission. The time-dependent fluorescence depletion provides the correlated dynamical information between the monitored fluorescence state and the SEP "dumped" dark states, and therefore allow us to obtain the dynamics of the formation of the dark states corresponding to the ultrafast photoisomerization processes. The excited-state dynamics of LDS 751 have been investigated as a function of solvent viscosity and solvent polarity, where a cooperative two-step isomerization process is clearly identified within LDS 751 upon excitation.
Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.
Bayesian Inference on the Effect of Density Dependence and Weather on a Guanaco Population from Chile

PubMed Central

Zubillaga, María; Skewes, Oscar; Soto, Nicolás; Rabinovich, Jorge E.; Colchero, Fernando

2014-01-01

Understanding the mechanisms that drive population dynamics is fundamental for management of wild populations. The guanaco (Lama guanicoe) is one of two wild camelid species in South America. We evaluated the effects of density dependence and weather variables on population regulation based on a time series of 36 years of population sampling of guanacos in Tierra del Fuego, Chile. The population density varied between 2.7 and 30.7 guanaco/km2, with an apparent monotonic growth during the first 25 years; however, in the last 10 years the population has shown large fluctuations, suggesting that it might have reached its carrying capacity. We used a Bayesian state-space framework and model selection to determine the effect of density and environmental variables on guanaco population dynamics. Our results show that the population is under density dependent regulation and that it is currently fluctuating around an average carrying capacity of 45,000 guanacos. We also found a significant positive effect of previous winter temperature while sheep density has a strong negative effect on the guanaco population growth. We conclude that there are significant density dependent processes and that climate as well as competition with domestic species have important effects determining the population size of guanacos, with important implications for management and conservation. PMID:25514510
Bayesian inference on the effect of density dependence and weather on a guanaco population from Chile.

PubMed

Zubillaga, María; Skewes, Oscar; Soto, Nicolás; Rabinovich, Jorge E; Colchero, Fernando

2014-01-01

Understanding the mechanisms that drive population dynamics is fundamental for management of wild populations. The guanaco (Lama guanicoe) is one of two wild camelid species in South America. We evaluated the effects of density dependence and weather variables on population regulation based on a time series of 36 years of population sampling of guanacos in Tierra del Fuego, Chile. The population density varied between 2.7 and 30.7 guanaco/km2, with an apparent monotonic growth during the first 25 years; however, in the last 10 years the population has shown large fluctuations, suggesting that it might have reached its carrying capacity. We used a Bayesian state-space framework and model selection to determine the effect of density and environmental variables on guanaco population dynamics. Our results show that the population is under density dependent regulation and that it is currently fluctuating around an average carrying capacity of 45,000 guanacos. We also found a significant positive effect of previous winter temperature while sheep density has a strong negative effect on the guanaco population growth. We conclude that there are significant density dependent processes and that climate as well as competition with domestic species have important effects determining the population size of guanacos, with important implications for management and conservation.
An open-population hierarchical distance sampling model

USGS Publications Warehouse

Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

2015-01-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
An open-population hierarchical distance sampling model.

PubMed

Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

2015-02-01

Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
Ecological correlates of population genetic structure: a comparative approach using a vertebrate metacommunity.

PubMed

Manier, Mollie K; Arnold, Stevan J

2006-12-07

Identifying ecological factors associated with population genetic differentiation is important for understanding microevolutionary processes and guiding the management of threatened populations. We identified ecological correlates of several population genetic parameters for three interacting species (two garter snakes and an anuran) that occupy a common landscape. Using multiple regression analysis, we found that species interactions were more important in explaining variation in population genetic parameters than habitat and nearest-neighbour characteristics. Effective population size was best explained by census size, while migration was associated with differences in species abundance. In contrast, genetic distance was poorly explained by the ecological correlates that we tested, but geographical distance was prominent in models for all species. We found substantially different population dynamics for the prey species relative to the two predators, characterized by larger effective sizes, lower gene flow and a state of migration-drift equilibrium. We also identified an escarpment formed by a series of block faults that serves as a barrier to dispersal for the predators. Our results suggest that successful landscape-level management should incorporate genetic and ecological data for all relevant species, because even closely associated species can exhibit very different population genetic dynamics on the same landscape.
Estimating species-specific suvival and movement when species identification is uncertain

USGS Publications Warehouse

Runge, J.P.; Hines, J.E.; Nichols, J.D.

2007-01-01

Incorporating uncertainty in the investigation of ecological studies has been the topic of an increasing body of research. In particular, mark?recapture methodology has shown that incorporating uncertainty in the probability of detecting individuals in populations enables accurate estimation of population-level processes such as survival, reproduction, and dispersal. Recent advances in mark?recapture methodology have included estimating population-level processes for biologically important groups despite the misassignment of individuals to those groups. Examples include estimating rates of apparent survival despite less than perfect accuracy when identifying individuals to gender or breeding state. Here we introduce a method for estimating apparent survival and dispersal in species that co-occur but that are difficult to distinguish. We use data from co-occurring populations of meadow voles (Microtus pennsylvanicus) and montane voles (M. montanus) in addition to simulated data to show that ignoring species uncertainty can lead to biased estimates of population processes. The incorporation of species uncertainty in mark?recapture studies should aid future research investigating ecological concepts such as interspecific competition, niche differentiation, and spatial population dynamics in sibling species.
Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo

2013-10-01

The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.
Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio

2013-10-01

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.
Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752
Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712
Continuous and discrete extreme climatic events affecting the dynamics of a high-arctic reindeer population.

PubMed

Chan, Kung-Sik; Mysterud, Atle; Øritsland, Nils Are; Severinsen, Torbjørn; Stenseth, Nils Chr

2005-10-01

Climate at northern latitudes are currently changing both with regard to the mean and the temporal variability at any given site, increasing the frequency of extreme events such as cold and warm spells. Here we use a conceptually new modelling approach with two different dynamic terms of the climatic effects on a Svalbard reindeer population (the Brøggerhalvøya population) which underwent an extreme icing event ("locked pastures") with 80% reduction in population size during one winter (1993/94). One term captures the continuous and linear effect depending upon the Arctic Oscillation and another the discrete (rare) "event" process. The introduction of an "event" parameter describing the discrete extreme winter resulted in a more parsimonious model. Such an approach may be useful in strongly age-structured ungulate populations, with young and very old individuals being particularly prone to mortality factors during adverse conditions (resulting in a population structure that differs before and after extreme climatic events). A simulation study demonstrates that our approach is able to properly detect the ecological effects of such extreme climate events.
Fitness-Balanced Escape Determines Resolution of Dynamic Founder Virus Escape Processes in HIV-1 Infection

PubMed Central

Sunshine, Justine E.; Larsen, Brendan B.; Maust, Brandon; Casey, Ellie; Deng, Wenje; Chen, Lennie; Westfall, Dylan H.; Kim, Moon; Zhao, Hong; Ghorai, Suvankar; Lanxon-Cookson, Erinn; Rolland, Morgane; Collier, Ann C.; Maenza, Janine; Mullins, James I.

2015-01-01

ABSTRACT To understand the interplay between host cytotoxic T-lymphocyte (CTL) responses and the mechanisms by which HIV-1 evades them, we studied viral evolutionary patterns associated with host CTL responses in six linked transmission pairs. HIV-1 sequences corresponding to full-length p17 and p24 gag were generated by 454 pyrosequencing for all pairs near the time of transmission, and seroconverting partners were followed for a median of 847 days postinfection. T-cell responses were screened by gamma interferon/interleukin-2 (IFN-γ/IL-2) FluoroSpot using autologous peptide sets reflecting any Gag variant present in at least 5% of sequence reads in the individual's viral population. While we found little evidence for the occurrence of CTL reversions, CTL escape processes were found to be highly dynamic, with multiple epitope variants emerging simultaneously. We found a correlation between epitope entropy and the number of epitope variants per response (r = 0.43; P = 0.05). In cases in which multiple escape mutations developed within a targeted epitope, a variant with no fitness cost became fixed in the viral population. When multiple mutations within an epitope achieved fitness-balanced escape, these escape mutants were each maintained in the viral population. Additional mutations found to confer escape but undetected in viral populations incurred high fitness costs, suggesting that functional constraints limit the available sites tolerable to escape mutations. These results further our understanding of the impact of CTL escape and reversion from the founder virus in HIV infection and contribute to the identification of immunogenic Gag regions most vulnerable to a targeted T-cell attack. IMPORTANCE Rapid diversification of the viral population is a hallmark of HIV-1 infection, and understanding the selective forces driving the emergence of viral variants can provide critical insight into the interplay between host immune responses and viral evolution. We used deep sequencing to comprehensively follow viral evolution over time in six linked HIV transmission pairs. We then mapped T-cell responses to explore if mutations arose due to adaption to the host and found that escape processes were often highly dynamic, with multiple mutations arising within targeted epitopes. When we explored the impact of these mutations on replicative capacity, we found that dynamic escape processes only resolve with the selection of mutations that conferred escape with no fitness cost to the virus. These results provide further understanding of the complicated viral-host interactions that occur during early HIV-1 infection and may help inform the design of future vaccine immunogens. PMID:26223634
Strategy selection in structured populations.

PubMed

Tarnita, Corina E; Ohtsuki, Hisashi; Antal, Tibor; Fu, Feng; Nowak, Martin A

2009-08-07

Evolutionary game theory studies frequency dependent selection. The fitness of a strategy is not constant, but depends on the relative frequencies of strategies in the population. This type of evolutionary dynamics occurs in many settings of ecology, infectious disease dynamics, animal behavior and social interactions of humans. Traditionally evolutionary game dynamics are studied in well-mixed populations, where the interaction between any two individuals is equally likely. There have also been several approaches to study evolutionary games in structured populations. In this paper we present a simple result that holds for a large variety of population structures. We consider the game between two strategies, A and B, described by the payoff matrix(abcd). We study a mutation and selection process. For weak selection strategy A is favored over B if and only if sigma a+b>c+sigma d. This means the effect of population structure on strategy selection can be described by a single parameter, sigma. We present the values of sigma for various examples including the well-mixed population, games on graphs, games in phenotype space and games on sets. We give a proof for the existence of such a sigma, which holds for all population structures and update rules that have certain (natural) properties. We assume weak selection, but allow any mutation rate. We discuss the relationship between sigma and the critical benefit to cost ratio for the evolution of cooperation. The single parameter, sigma, allows us to quantify the ability of a population structure to promote the evolution of cooperation or to choose efficient equilibria in coordination games.
Broadening our approaches to studying dispersal in raptors

USGS Publications Warehouse

Morrison, J.L.; Wood, P.B.

2009-01-01

Dispersal is a behavioral process having consequences for individual fitness and population dynamics. Recent advances in technology have spawned new theoretical examinations and empirical studies of the dispersal process in birds, providing opportunities for examining how this information may be applied to studies of the dispersal process in raptors. Many raptors are the focus of conservation efforts; thus, reliable data on all aspects of a species' population dynamics, including dispersal distances, movement rates, and mortality rates of dispersers, are required for population viability analyses that are increasingly used to inform management. Here, we address emerging issues and novel approaches used in the study of avian dispersal, and provide suggestions to consider when developing and implementing studies of dispersal in raptors. Clarifying study objectives is essential for selection of an appropriate methodology and sample size needed to obtain accurate estimates of movement distances and rates. Identifying an appropriate study-area size will allow investigators to avoid underestimating population connectivity and important population parameters. Because nomadic individuals of some species use temporary settling areas or home ranges before breeding, identification of these areas is critical for conservation efforts focusing on habitats other than breeding sites. Study designs for investigating raptor dispersal also should include analysis of environmental and social factors influencing dispersal, to improve our understanding of condition-dependent dispersal strategies. Finally, we propose a terminology for use in describing the variety of movements associated with dispersal behavior in raptors, and we suggest this terminology could be used consistently to facilitate comparisons among studies. ?? 2009 The Raptor Research Foundation, Inc.
Population genetic dynamics of an invasion reconstructed from the sediment egg bank.

PubMed

Möst, Markus; Oexle, Sarah; Marková, Silvia; Aidukaite, Dalia; Baumgartner, Livia; Stich, Hans-Bernd; Wessels, Martin; Martin-Creuzburg, Dominik; Spaak, Piet

2015-08-01

Biological invasions are a global issue with far-reaching consequences for single species, communities and whole ecosystems. Our understanding of modes and mechanisms of biological invasions requires knowledge of the genetic processes associated with successful invasions. In many instances, this information is particularly difficult to obtain as the initial phases of the invasion process often pass unnoticed and we rely on inferences from contemporary population genetic data. Here, we combined historic information with the genetic analysis of resting eggs to reconstruct the invasion of Daphnia pulicaria into Lower Lake Constance (LLC) in the 1970s from the resting egg bank in the sediments. We identified the invader as 'European D. pulicaria' originating from meso- and eutrophic lowland lakes and ponds in Central Europe. The founding population was characterized by extremely low genetic variation in the resting egg bank that increased considerably over time. Furthermore, strong evidence for selfing and/or biparental inbreeding was found during the initial phase of the invasion, followed by a drop of selfing rate to low levels in subsequent decades. Moreover, the increase in genetic variation was most pronounced during early stages of the invasion, suggesting additional introductions during this period. Our study highlights that genetic data covering the entire invasion process from its beginning can be crucial to accurately reconstruct the invasion history of a species. We show that propagule banks can preserve such information enabling the study of population genetic dynamics and sources of genetic variation in successful invasive populations. © 2015 John Wiley & Sons Ltd.
Allee effects may slow the spread of parasites in a coastal marine ecosystem.

PubMed

Krkošek, Martin; Connors, Brendan M; Lewis, Mark A; Poulin, Robert

2012-03-01

Allee effects are thought to mediate the dynamics of population colonization, particularly for invasive species. However, Allee effects acting on parasites have rarely been considered in the analogous process of infectious disease establishment and spread. We studied the colonization of uninfected wild juvenile Pacific salmon populations by ectoparasitic salmon lice (Lepeophtheirus salmonis) over a 4-year period. In a data set of 68,376 fish, we observed 85 occurrences of precopular pair formation among 1,259 preadult female and 613 adult male lice. The probability of pair formation was dependent on the local abundance of lice, but this mate limitation is likely offset somewhat by mate-searching dispersal of males among host fish. A mathematical model of macroparasite population dynamics that incorporates the empirical results suggests a high likelihood of a demographic Allee effect, which can cause the colonizing parasite populations to die out. These results may provide the first empirical evidence for Allee effects in a macroparasite. Furthermore, the data give a rare detailed view of Allee effects in colonization dynamics and suggest that Allee effects may dampen the spread of parasites in a coastal marine ecosystem.
Dynamics of the Rydberg state population of slow highly charged ions impinging a solid surface at arbitrary collision geometry

NASA Astrophysics Data System (ADS)

Nedeljković, N. N.; Majkić, M. D.; Božanić, D. K.; Dojčilović, R. J.

2016-06-01

We consider the population dynamics of the intermediate Rydberg states of highly charged ions (core charge Z\\gg 1, principal quantum number {n}{{A}}\\gg 1) interacting with solid surfaces at arbitrary collision geometry. The recently developed resonant two-state vector model for the grazing incidence (2012 J. Phys. B: At. Mol. Opt. Phys. 45 215202) is extended to the quasi-resonant case and arbitrary angle of incidence. According to the model, the population probabilities depend both on the projectile parallel and perpendicular velocity components, in a complementary way. A cascade neutralization process for {{{Xe}}}Z+ ions, for Z=15{--}45, interacting with a conductive-surface is considered by taking into account the population dynamics. For an arbitrary collision geometry and given range of ionic velocities, a micro-staircase model for the simultaneous calculation of the kinetic energy gain and the charge state of the ion in front of the surface is proposed. The relevance of the obtained results for the explanation of the formation of nanostructures on solid surfaces by slow highly charged ions for normal incidence geometry is briefly discussed.
Trees wanted--dead or alive! Host selection and population dynamics in tree-killing bark beetles.

PubMed

Kausrud, Kyrre L; Grégoire, Jean-Claude; Skarpaas, Olav; Erbilgin, Nadir; Gilbert, Marius; Økland, Bjørn; Stenseth, Nils Chr

2011-01-01

Bark beetles (Coleoptera: Curculionidae, Scolytinae) feed and breed in dead or severely weakened host trees. When their population densities are high, some species aggregate on healthy host trees so that their defences may be exhausted and the inner bark successfully colonized, killing the tree in the process. Here we investigate under what conditions participating with unrelated conspecifics in risky mass attacks on living trees is an adaptive strategy, and what this can tell us about bark beetle outbreak dynamics. We find that the outcome of individual host selection may deviate from the ideal free distribution in a way that facilitates the emergence of tree-killing (aggressive) behavior, and that any heritability on traits governing aggressiveness seems likely to exist in a state of flux or cycles consistent with variability observed in natural populations. This may have implications for how economically and ecologically important species respond to environmental changes in climate and landscape (forest) structure. The population dynamics emerging from individual behavior are complex, capable of switching between "endemic" and "epidemic" regimes spontaneously or following changes in host availability or resistance. Model predictions are compared to empirical observations, and we identify some factors determining the occurrence and self-limitation of epidemics.
Uncoupling the Effects of Seed Predation and Seed Dispersal by Granivorous Ants on Plant Population Dynamics

PubMed Central

Arnan, Xavier; Molowny-Horas, Roberto; Rodrigo, Anselm; Retana, Javier

2012-01-01

Secondary seed dispersal is an important plant-animal interaction, which is central to understanding plant population and community dynamics. Very little information is still available on the effects of dispersal on plant demography and, particularly, for ant-seed dispersal interactions. As many other interactions, seed dispersal by animals involves costs (seed predation) and benefits (seed dispersal), the balance of which determines the outcome of the interaction. Separate quantification of each of them is essential in order to understand the effects of this interaction. To address this issue, we have successfully separated and analyzed the costs and benefits of seed dispersal by seed-harvesting ants on the plant population dynamics of three shrub species with different traits. To that aim a stochastic, spatially-explicit individually-based simulation model has been implemented based on actual data sets. The results from our simulation model agree with theoretical models of plant response dependent on seed dispersal, for one plant species, and ant-mediated seed predation, for another one. In these cases, model predictions were close to the observed values at field. Nonetheless, these ecological processes did not affect in anyway a third species, for which the model predictions were far from the observed values. This indicates that the balance between costs and benefits associated to secondary seed dispersal is clearly related to specific traits. This study is one of the first works that analyze tradeoffs of secondary seed dispersal on plant population dynamics, by disentangling the effects of related costs and benefits. We suggest analyzing the effects of interactions on population dynamics as opposed to merely analyzing the partners and their interaction strength. PMID:22880125

Human population and atmospheric carbon dioxide growth dynamics: Diagnostics for the future

NASA Astrophysics Data System (ADS)

Hüsler, A. D.; Sornette, D.

2014-10-01

We analyze the growth rates of human population and of atmospheric carbon dioxide by comparing the relative merits of two benchmark models, the exponential law and the finite-time-singular (FTS) power law. The later results from positive feedbacks, either direct or mediated by other dynamical variables, as shown in our presentation of a simple endogenous macroeconomic dynamical growth model describing the growth dynamics of coupled processes involving human population (labor in economic terms), capital and technology (proxies by CO2 emissions). Human population in the context of our energy intensive economies constitutes arguably the most important underlying driving variable of the content of carbon dioxide in the atmosphere. Using some of the best databases available, we perform empirical analyses confirming that the human population on Earth has been growing super-exponentially until the mid-1960s, followed by a decelerated sub-exponential growth, with a tendency to plateau at just an exponential growth in the last decade with an average growth rate of 1.0% per year. In contrast, we find that the content of carbon dioxide in the atmosphere has continued to accelerate super-exponentially until 1990, with a transition to a progressive deceleration since then, with an average growth rate of approximately 2% per year in the last decade. To go back to CO2 atmosphere contents equal to or smaller than the level of 1990 as has been the broadly advertised goals of international treaties since 1990 requires herculean changes: from a dynamical point of view, the approximately exponential growth must not only turn to negative acceleration but also negative velocity to reverse the trend.
System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591
A combined crossed-beam and theoretical study of the reaction dynamics of O(3P) + C2H3 → C2H2 + OH: Analysis of the nascent OH products with the preferential population of the Π(A') component

NASA Astrophysics Data System (ADS)

Park, Min-Jin; Jang, Su-Chan; Choi, Jong-Ho

2012-11-01

The gas-phase reaction dynamics of ground-state atomic oxygen [O(3P) from the photo-dissociation of NO2] with vinyl radicals [C2H3 from the supersonic flash pyrolysis of vinyl iodide, C2H3I] has been investigated using a combination of high-resolution laser-induced fluorescence spectroscopy in a crossed-beam configuration and ab initio calculations. Unlike the previous gas-phase bulk kinetic experiments by Baulch et al. [J. Phys. Chem. Ref. Data 34, 757 (2005)], 10.1063/1.1748524, a new exothermic channel of O(3P) + C2H3 → C2H2 + OH (X 2Π: υ″ = 0) has been identified for the first time, and the population analysis shows bimodal nascent rotational distributions of OH products with low- and high-N″ components with a ratio of 2.4:1. No spin-orbit propensities were observed, and the averaged ratios of Π(A')/Π(A″) were determined to be 1.66 ± 0.27. On the basis of computations at the CBS-QB3 theory level and comparison with prior theory, the microscopic mechanisms responsible for the nascent populations can be understood in terms of two competing dynamical pathways: a direct abstraction process in the low-N″ regime as the major pathway and an addition-complex forming process in the high-N″ regime as the minor pathway. Particularly, during the bond cleavage process of the weakly bound van der Waals complex C2H2—OH, the characteristic pathway from the low dihedral-angle geometry was consistent with the observed preferential population of the Π(A') component in the nascent OH products. A molecular-level discussion of the reactivity, mechanism, and dynamical features of the title reaction are presented together with a comparison to gas-phase oxidation reactions of a series of prototypical hydrocarbon radicals.
Calculation of Disease Dynamics in a Population of Households

PubMed Central

Ross, Joshua V.; House, Thomas; Keeling, Matt J.

2010-01-01

Early mathematical representations of infectious disease dynamics assumed a single, large, homogeneously mixing population. Over the past decade there has been growing interest in models consisting of multiple smaller subpopulations (households, workplaces, schools, communities), with the natural assumption of strong homogeneous mixing within each subpopulation, and weaker transmission between subpopulations. Here we consider a model of SIRS (susceptible-infectious-recovered-susceptible) infection dynamics in a very large (assumed infinite) population of households, with the simplifying assumption that each household is of the same size (although all methods may be extended to a population with a heterogeneous distribution of household sizes). For this households model we present efficient methods for studying several quantities of epidemiological interest: (i) the threshold for invasion; (ii) the early growth rate; (iii) the household offspring distribution; (iv) the endemic prevalence of infection; and (v) the transient dynamics of the process. We utilize these methods to explore a wide region of parameter space appropriate for human infectious diseases. We then extend these results to consider the effects of more realistic gamma-distributed infectious periods. We discuss how all these results differ from standard homogeneous-mixing models and assess the implications for the invasion, transmission and persistence of infection. The computational efficiency of the methodology presented here will hopefully aid in the parameterisation of structured models and in the evaluation of appropriate responses for future disease outbreaks. PMID:20305791
VCGDB: a dynamic genome database of the Chinese population

PubMed Central

2014-01-01

Background The data released by the 1000 Genomes Project contain an increasing number of genome sequences from different nations and populations with a large number of genetic variations. As a result, the focus of human genome studies is changing from single and static to complex and dynamic. The currently available human reference genome (GRCh37) is based on sequencing data from 13 anonymous Caucasian volunteers, which might limit the scope of genomics, transcriptomics, epigenetics, and genome wide association studies. Description We used the massive amount of sequencing data published by the 1000 Genomes Project Consortium to construct the Virtual Chinese Genome Database (VCGDB), a dynamic genome database of the Chinese population based on the whole genome sequencing data of 194 individuals. VCGDB provides dynamic genomic information, which contains 35 million single nucleotide variations (SNVs), 0.5 million insertions/deletions (indels), and 29 million rare variations, together with genomic annotation information. VCGDB also provides a highly interactive user-friendly virtual Chinese genome browser (VCGBrowser) with functions like seamless zooming and real-time searching. In addition, we have established three population-specific consensus Chinese reference genomes that are compatible with mainstream alignment software. Conclusions VCGDB offers a feasible strategy for processing big data to keep pace with the biological data explosion by providing a robust resource for genomics studies; in particular, studies aimed at finding regions of the genome associated with diseases. PMID:24708222
Estimating Allee dynamics before they can be observed: polar bears as a case study.

PubMed

Molnár, Péter K; Lewis, Mark A; Derocher, Andrew E

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species.
Estimating Allee Dynamics before They Can Be Observed: Polar Bears as a Case Study

PubMed Central

Molnár, Péter K.; Lewis, Mark A.; Derocher, Andrew E.

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species. PMID:24427306
The dynamics of adapting, unregulated populations and a modified fundamental theorem.

PubMed

O'Dwyer, James P

2013-01-06

A population in a novel environment will accumulate adaptive mutations over time, and the dynamics of this process depend on the underlying fitness landscape: the fitness of and mutational distance between possible genotypes in the population. Despite its fundamental importance for understanding the evolution of a population, inferring this landscape from empirical data has been problematic. We develop a theoretical framework to describe the adaptation of a stochastic, asexual, unregulated, polymorphic population undergoing beneficial, neutral and deleterious mutations on a correlated fitness landscape. We generate quantitative predictions for the change in the mean fitness and within-population variance in fitness over time, and find a simple, analytical relationship between the distribution of fitness effects arising from a single mutation, and the change in mean population fitness over time: a variant of Fisher's 'fundamental theorem' which explicitly depends on the form of the landscape. Our framework can therefore be thought of in three ways: (i) as a set of theoretical predictions for adaptation in an exponentially growing phase, with applications in pathogen populations, tumours or other unregulated populations; (ii) as an analytically tractable problem to potentially guide theoretical analysis of regulated populations; and (iii) as a basis for developing empirical methods to infer general features of a fitness landscape.
Moran model as a dynamical process on networks and its implications for neutral speciation.

PubMed

de Aguiar, Marcus A M; Bar-Yam, Yaneer

2011-09-01

In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.
Moran model as a dynamical process on networks and its implications for neutral speciation

NASA Astrophysics Data System (ADS)

de Aguiar, Marcus A. M.; Bar-Yam, Yaneer

2011-03-01

In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.
Dynamics of valley pseudospin in single-layer WSe2. Inter-valley scattering mediated by electron-phonon interaction

NASA Astrophysics Data System (ADS)

Molina-Sanchez, Alejandro; Sangalli, Davide; Wirtz, Ludger; Marini, Andrea

In a time-dependent Kerr experiment a circularly polarized laser field is used to selectively populate the K+/- electronic valleys of single-layer WSe2. This carrier population corresponds to a finite pseudospin polarization that dictates the valleytronic properties of WSe2, but whose decay mechanism still remains largely debated. Time-dependent Kerr experiments provide an accurate way to visualize the pseudospin dynamics by measuring the rotation of a linearly polarized probe pulse applied after a circularly polarized and short pump pulse. We present here a clear, accurate and parameter-free description of the valley pseudospin dynamics in single-layer WSe2. By using an ab-initio approach we solve unambiguously the long standing debate about the dominant mechanism that drives the valley depolarization. Our results are in excellent agreement with recent time-dependent Kerr experiments. The decay dynamics and peculiar temperature dependence is explained in terms of electron phonon mediated processes that induce spin-flip inter-valley transitions.
Coherence and population dynamics of chlorophyll excitations in FCP complex: Two-dimensional spectroscopy study

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
Sintering of polydisperse viscous droplets

NASA Astrophysics Data System (ADS)

Wadsworth, Fabian B.; Vasseur, Jérémie; Llewellin, Edward W.; Dingwell, Donald B.

2017-03-01

Sintering—or coalescence—of compacts of viscous droplets is driven by the interfacial tension between the droplets and the interstitial gas phase. The process, which occurs in a range of industrial and natural settings, such as the manufacture of ceramics and the welding of volcanic ash, causes the compact to densify, to become stronger, and to become less permeable. We investigate the role of droplet polydispersivity in sintering dynamics by conducting experiments in which populations of glass spheres with different size distributions are heated to temperatures above the glass transition interval. We quantify the progress of sintering by tracking changes in porosity with time. The sintering dynamics is modeled by treating the system as a random distribution of interstitial gas bubbles shrinking under the action of interfacial tension only. We identify the scaling between the polydispersivity of the initial droplets and the dynamics of bulk densification. The framework that we develop allows the sintering dynamics of arbitrary polydisperse populations of droplets to be predicted if the initial droplet (or particle) size distribution is known.
Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series

PubMed Central

Ferguson, Jake M; Ponciano, José M

2014-01-01

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. PMID:24304946
Exporting Poor Health: The Irish in England

PubMed Central

Delaney, Liam; Fernihough, Alan; Smith, James P

2013-01-01

The Irish-born population in England typically were in worse health than both the native population and the Irish population in Ireland, a reversal of the commonly observed healthy migrant effect (HIE). Recent birth-cohorts living in England and born in Ireland, however, are healthier than the English population. The substantial Irish migrant health penalty arises principally for cohorts born between 1920 and 1960. This paper attempts to understand the processes that generated these changing migrant health patterns for Irish migrants to England. Our results suggest a strong role for economic selection in driving the dynamics of health differences between the Irish-born migrants and White English populations. PMID:24014181
A mechanism for pattern formation in dynamic populations by the effect of gregarious instinct

NASA Astrophysics Data System (ADS)

Mangioni, Sergio E.

2012-01-01

We introduced the gregarious instinct by means of a novel strategy that considers the average effect of the attractive forces between individuals within a given population. We watched how pattern formation can be explained by the effect of aggregation depending on conditions on food and / or mortality. We propose a model that describes the corresponding dynamic and by a linear stability analysis of homogeneous solutions and can identify and interpret the region of parameters where these patterns are stable. Then we test numerically these preliminary results and find stable patterns as solutions. Finally, we developed a simplified model allowing us to understand in greater detail the processes involved.
Artificial bee colony algorithm with dynamic multi-population

NASA Astrophysics Data System (ADS)

Zhang, Ming; Ji, Zhicheng; Wang, Yan

2017-07-01

To improve the convergence rate and make a balance between the global search and local turning abilities, this paper proposes a decentralized form of artificial bee colony (ABC) algorithm with dynamic multi-populations by means of fuzzy C-means (FCM) clustering. Each subpopulation periodically enlarges with the same size during the search process, and the overlapping individuals among different subareas work for delivering information acting as exploring the search space with diffusion of solutions. Moreover, a Gaussian-based search equation with redefined local attractor is proposed to further accelerate the diffusion of the best solution and guide the search towards potential areas. Experimental results on a set of benchmarks demonstrate the competitive performance of our proposed approach.
Spreading dynamics on complex networks: a general stochastic approach.

PubMed

Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.
Modelling approaches for relating effects of change in river flow to populations of Atlantic salmon and brown trout

Treesearch

John D. Armstrong; Keith H. Nislow

2012-01-01

Modelling approaches for relating discharge to the biology of Atlantic salmon, Salmo salar L., and brown trout, Salmo trutta L., growing in rivers are reviewed. Process-based and empirical models are set within a common framework of input of water flow and output of characteristics of fish, such as growth and survival, which relate directly to population dynamics. A...
Dynamics and regulation of the southern brook trout (Salvelinus fontinalis) population in an Appalachian stream

Treesearch

Gary D. Grossman; Robert E. Ratajczak; C. Michael Wagner; J. Todd Petty

2010-01-01

1. We used information theoretic statistics [Akaikeâs Information Criterion (AIC)] and regression analysis in a multiple hypothesis testing approach to assess the processes capable of explaining long-term demographic variation in a lightly exploited brook trout population in Ball Creek, NC. We sampled a 100-m-long second-order site during both spring and autumn 1991â...

Mitigating amphibian disease: strategies to maintain wild populations and control chytridiomycosis

USGS Publications Warehouse

Woodhams, Douglas C.; Bosch, Jaime; Briggs, Cheryl J.; Cashins, Scott; Davis, Leyla R.; Lauer, Antje; Muths, Erin L.; Puschendorf, Robert; Schmidt, Benedikt R.; Sheafor, Brandon; Voyles, Jamie

2011-01-01

Because sustainable conservation of amphibians in nature is dependent on long-term population persistence and co-evolution with potentially lethal pathogens, we suggest that disease mitigation not focus exclusively on the elimination or containment of the pathogen, or on the captive breeding of amphibian hosts. Rather, successful disease mitigation must be context specific with epidemiologically informed strategies to manage already infected populations by decreasing pathogenicity and host susceptibility. We propose population level treatments based on three steps: first, identify mechanisms of disease suppression; second, parameterize epizootiological models of disease and population dynamics for testing under semi-natural conditions; and third, begin a process of adaptive management in field trials with natural populations.
Dynamics of newly established elk populations

USGS Publications Warehouse

Sargeant, G.A.; Oehler, M.W.

2007-01-01

The dynamics of newly established elk (Cervus elaphus) populations can provide insights about maximum sustainable rates of reproduction, survival, and increase. However, data used to estimate rates of increase typically have been limited to counts and rarely have included complementary estimates of vital rates. Complexities of population dynamics cannot be understood without considering population processes as well as population states. We estimated pregnancy rates, survival rates, age ratios, and sex ratios for reintroduced elk at Theodore Roosevelt National Park, North Dakota, USA; combined vital rates in a population projection model; and compared model projections with observed elk numbers and population ratios. Pregnancy rates in January (early in the second trimester of pregnancy) averaged 54.1% (SE = 5.4%) for subadults and 91.0% (SE = 1.7%) for adults, and 91.6% of pregnancies resulted in recruitment at 8 months. Annual survival rates of adult females averaged 0.96 (95% CI = 0.94-0.98) with hunting included and 0.99 (95% CI = 0.97-0.99) with hunting excluded from calculations. Our fitted model explained 99.8% of past variation in population estimates and represents a useful new tool for short-term management planning. Although we found no evidence of temporal variation in vital rates, variation in population composition caused substantial variation in projected rates of increase (??=1.20-1.36). Restoring documented hunter harvests and removals of elk by the National Park Service led to a potential rate of ?? = 1.26. Greater rates of increase substantiated elsewhere were within the expected range of chance variation, given our model and estimates of vital rates. Rates of increase realized by small elk populations are too variable to support inferences about habitat quality or density dependence.
Reproductive Ecology of the Giant African Snail in South Florida: Implications for Eradication Programs.

PubMed

Roda, Amy; Nachman, Gösta; Weihman, Scott; Yong Cong, Mary; Zimmerman, Fredrick

2016-01-01

Giant African snail (Achatina fulica (Bowdich, 1822)), an important invasive snail, was recently found in South Florida, USA. An extensive eradication effort was initiated consisting of pesticide applications, debris removal and hand collections. We studied the reproduction capacity and population dynamics of snails collected from 22 populations for two years to help evaluate the likely success of the eradication program. A total of 23,890 snails, ranging from 25-131 mm, were measured, dissected and the number of eggs in each snail counted. Gravid snails ranged from 48-128 mm. Only 5% of snails had eggs, which were found year round. As the snails increased in size, they were more likely to include reproducing individuals. However, the percentage of gravid snails peaked when snails were approximately 90 mm. Although more prevalent, small (<65 mm) adults contributed fewer eggs to the population than the larger snails. We evaluated the effect of control measures on six populations having >1000 adult snails and used data from the two largest populations to investigate how environmental factors (temperature, humidity, and rainfall) interacted with population dynamics and control measures. More snails were collected in weeks with high humidity and more gravid snails were collected when the temperature was higher. The addition of metaldehyde pesticides had the greatest impact on population dynamics by reducing snail numbers. In populations with fewer snails, their numbers were already declining before the use of metaldehyde, although the new treatment accelerated the process. As a consequence of the eradication program, egg-producing snails were no longer collected from most populations by the end of the study. The aggressive and persistent control efforts apparently lead to reduced populations of egg producing snails, eventually resulting in local extinctions of this important pest.
Reproductive Ecology of the Giant African Snail in South Florida: Implications for Eradication Programs

PubMed Central

2016-01-01

Giant African snail (Achatina fulica (Bowdich, 1822)), an important invasive snail, was recently found in South Florida, USA. An extensive eradication effort was initiated consisting of pesticide applications, debris removal and hand collections. We studied the reproduction capacity and population dynamics of snails collected from 22 populations for two years to help evaluate the likely success of the eradication program. A total of 23,890 snails, ranging from 25–131 mm, were measured, dissected and the number of eggs in each snail counted. Gravid snails ranged from 48–128 mm. Only 5% of snails had eggs, which were found year round. As the snails increased in size, they were more likely to include reproducing individuals. However, the percentage of gravid snails peaked when snails were approximately 90 mm. Although more prevalent, small (<65 mm) adults contributed fewer eggs to the population than the larger snails. We evaluated the effect of control measures on six populations having >1000 adult snails and used data from the two largest populations to investigate how environmental factors (temperature, humidity, and rainfall) interacted with population dynamics and control measures. More snails were collected in weeks with high humidity and more gravid snails were collected when the temperature was higher. The addition of metaldehyde pesticides had the greatest impact on population dynamics by reducing snail numbers. In populations with fewer snails, their numbers were already declining before the use of metaldehyde, although the new treatment accelerated the process. As a consequence of the eradication program, egg-producing snails were no longer collected from most populations by the end of the study. The aggressive and persistent control efforts apparently lead to reduced populations of egg producing snails, eventually resulting in local extinctions of this important pest. PMID:27861504
Selective population rate coding: a possible computational role of gamma oscillations in selective attention.

PubMed

Masuda, Naoki

2009-12-01

Selective attention is often accompanied by gamma oscillations in local field potentials and spike field coherence in brain areas related to visual, motor, and cognitive information processing. Gamma oscillations are implicated to play an important role in, for example, visual tasks including object search, shape perception, and speed detection. However, the mechanism by which gamma oscillations enhance cognitive and behavioral performance of attentive subjects is still elusive. Using feedforward fan-in networks composed of spiking neurons, we examine a possible role for gamma oscillations in selective attention and population rate coding of external stimuli. We implement the concept proposed by Fries ( 2005 ) that under dynamic stimuli, neural populations effectively communicate with each other only when there is a good phase relationship among associated gamma oscillations. We show that the downstream neural population selects a specific dynamic stimulus received by an upstream population and represents it by population rate coding. The encoded stimulus is the one for which gamma rhythm in the corresponding upstream population is resonant with the downstream gamma rhythm. The proposed role for gamma oscillations in stimulus selection is to enable top-down control, a neural version of time division multiple access used in communication engineering.
Memory and obesity affect the population dynamics of asexual freshwater planarians

NASA Astrophysics Data System (ADS)

Dunkel, Jörn; Talbot, Jared; Schötz, Eva-Maria

2011-04-01

Asexual reproduction in multicellular organisms is a complex biophysical process that is not yet well understood quantitatively. Here, we report a detailed population study for the asexual freshwater planarian Schmidtea mediterranea, which can reproduce via transverse fission due to a large stem cell contingent. Our long-term observations of isolated non-interacting planarian populations reveal that the characteristic fission waiting time distributions for head and tail fragments differ significantly from each other. The stochastic fission dynamics of tail fragments exhibits non-negligible memory effects, implying that an accurate mathematical description of future data should be based on non-Markovian tree models. By comparing the effective growth of non-interacting planarian populations with those of self-interacting populations, we are able to quantify the influence of interactions between flatworms and physical conditions on the population growth. A surprising result is the non-monotonic relationship between effective population growth rate and nutrient supply: planarians exhibit a tendency to become 'obese' if the feeding frequency exceeds a critical level, resulting in a decreased reproduction activity. This suggests that these flatworms, which possess many genes homologous to those of humans, could become a new model system for studying dietary effects on reproduction and regeneration in multicellular organisms.
Density-dependent resistance of the gypsy moth, Lymantria dispar, to its nucleopolyhedrovirus

Treesearch

James R. Reilly; Ann E. Hajek

2007-01-01

The processes controlling disease resistance can strongly influence the population dynamics of insect outbreaks. Evidence that disease resistance is density-dependent is accumulating, but the exact form of this relationship is highly variable from species to species.
USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

EPA Science Inventory

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

PubMed

Kleshnina, Maria; Filar, Jerzy A; Ejov, Vladimir; McKerral, Jody C

2018-02-26

The adaptation process of a species to a new environment is a significant area of study in biology. As part of natural selection, adaptation is a mutation process which improves survival skills and reproductive functions of species. Here, we investigate this process by combining the idea of incompetence with evolutionary game theory. In the sense of evolution, incompetence and training can be interpreted as a special learning process. With focus on the social side of the problem, we analyze the influence of incompetence on behavior of species. We introduce an incompetence parameter into a learning function in a single-population game and analyze its effect on the outcome of the replicator dynamics. Incompetence can change the outcome of the game and its dynamics, indicating its significance within what are inherently imperfect natural systems.
Biogeochemistry of hypersaline microbial mats illustrates the dynamics of modern microbial ecosystems and the early evolution of the biosphere

NASA Technical Reports Server (NTRS)

Des Marais, David J.

2003-01-01

Photosynthetic microbial mats are remarkably complete self-sustaining ecosystems at the millimeter scale, yet they have substantially affected environmental processes on a planetary scale. These mats may be direct descendents of the most ancient biological communities in which even oxygenic photosynthesis might have developed. Photosynthetic mats are excellent natural laboratories to help us to learn how microbial populations associate to control dynamic biogeochemical gradients.
Perspective: Maximum caliber is a general variational principle for dynamical systems

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A.

2018-01-01

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics—such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production—are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.
Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.
Perspective: Maximum caliber is a general variational principle for dynamical systems.

PubMed

Dixit, Purushottam D; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A

2018-01-07

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics-such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production-are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.
Effect of global climate on termites population. Effect of termites population on global climate

NASA Astrophysics Data System (ADS)

Sapunov, Valentin

2010-05-01

The global climate is under control of factors having both earth and space origin. Global warming took place from XVII century till 1997. Then global cold snap began. This dynamics had effect on global distribution of some animals including termites. Direct human effect on climate is not significant. At the same time man plays role of trigger switching on significant biosphere processes controlling climate. The transformation of marginal lands, development of industry and building, stimulated increase of termite niche and population. Termite role in green house gases production increases too. It may have regular effect on world climate. The dry wood is substrate for metabolism of termites living under symbiosis with bacteria Hypermastigina (Flagellata). The use of dry wood by humanity increased from 18 *108 ton in XVIII to 9*109 to the middle of XX century. Then use of wood decreased because of a new technology development. Hence termite population is controlled by microevolution depending on dry wood and climate dynamics. Producing by them green house gases had reciprocal effect on world climate. It is possible to describe and predict dynamic of termite population using methods of mathematical ecology and analogs with other well studied insects (Colorado potatoes beetle, Chrisomelid beetle Zygogramma and so on). Reclamation of new ecological niche for such insects as termites needs 70 - 75 years. That is delay of population dynamics in relation to dynamics of dry wood production. General principles of population growth were described by G.Gause (1934) and some authors of the end of XX century. This works and analogs with other insects suggest model of termite distribution during XXI century. The extremum of population and its green house gases production would be gotten during 8 - 10 years. Then the number of specimens and sum biological mass would be stabilized and decreased. Termite gas production is not priority for climate regulation, but it has importance as fine regulator of global temperature and climate stability. Key words: termites, green house gases, mathematical modeling. Union symposia Biogeoscience BG2.1
A dynamic neural field model of temporal order judgments.

PubMed

Hecht, Lauren N; Spencer, John P; Vecera, Shaun P

2015-12-01

Temporal ordering of events is biased, or influenced, by perceptual organization-figure-ground organization-and by spatial attention. For example, within a region assigned figural status or at an attended location, onset events are processed earlier (Lester, Hecht, & Vecera, 2009; Shore, Spence, & Klein, 2001), and offset events are processed for longer durations (Hecht & Vecera, 2011; Rolke, Ulrich, & Bausenhart, 2006). Here, we present an extension of a dynamic field model of change detection (Johnson, Spencer, Luck, & Schöner, 2009; Johnson, Spencer, & Schöner, 2009) that accounts for both the onset and offset performance for figural and attended regions. The model posits that neural populations processing the figure are more active, resulting in a peak of activation that quickly builds toward a detection threshold when the onset of a target is presented. This same enhanced activation for some neural populations is maintained when a present target is removed, creating delays in the perception of the target's offset. We discuss the broader implications of this model, including insights regarding how neural activation can be generated in response to the disappearance of information. (c) 2015 APA, all rights reserved).
Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana.

PubMed

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.
Infection Dynamics of Coexisting Beta- and Gammaproteobacteria in the Nested Endosymbiotic System of Mealybugs▿

PubMed Central

Kono, Marie; Koga, Ryuichi; Shimada, Masakazu; Fukatsu, Takema

2008-01-01

We investigated the infection dynamics of endosymbiotic bacteria in the developmental course of the mealybugs Planococcus kraunhiae and Pseudococcus comstocki. Molecular phylogenetic analyses identified a betaproteobacterium and a gammaproteobacterium from each of the mealybug species. The former bacterium was related to the β-endosymbionts of other mealybugs, i.e., “Candidatus Tremblaya princeps,” and formed a compact clade in the Betaproteobacteria. Meanwhile, the latter bacterium was related to the γ-endosymbionts of other mealybugs but belonged to distinct clades in the Gammaproteobacteria. Whole-mount in situ hybridization confirmed the peculiar nested formation in the endosymbiotic system of the mealybugs: the β-endosymbiont cells were present in the cytoplasm of the bacteriocytes, and the γ-endosymbiont cells were located in the β-endosymbiont cells. In nymphal and female development, a large oval bacteriome consisting of a number of bacteriocytes was present in the abdomen, wherein the endosymbionts were harbored. In male development, strikingly, the bacteriome progressively degenerated in prepupae and pupae and became almost unrecognizable in adult males. In the degeneration process, the γ-endosymbionts disappeared more rapidly than the β-endosymbionts did. Quantitative PCR analyses revealed that (i) the population dynamics of the endosymbionts in female development reflected the reproductive activity of the insects, (ii) the population dynamics of the endosymbionts were strikingly different between female development and male development, (iii) the endosymbiont populations drastically decreased in male development, and (iv) the γ-endosymbiont populations decreased more rapidly than the β-endosymbiont populations in male development. Possible mechanisms underlying the uncoupled regulation of the β- and γ-endosymbiont populations are discussed in relation to the establishment and evolution of this unique prokaryote-prokaryote endosymbiotic system. PMID:18469124
Massive Black-Hole Binary Mergers: Dynamics, Environments & Expected Detections

NASA Astrophysics Data System (ADS)

Kelley, Luke Zoltan

2018-05-01

This thesis studies the populations and dynamics of massive black-hole binaries and their mergers, and explores the implications for electromagnetic and gravitational-wave signals that will be detected in the near future. Massive black-holes (MBH) reside in the centers of galaxies, and when galaxies merge, their MBH interact and often pair together. We base our study on the populations of MBH and galaxies from the `Illustris' cosmological hydrodynamic simulations. The bulk of the binary merger dynamics, however, are unresolved in cosmological simulations. We implement a suite of comprehensive physical models for the merger process, like dynamical friction and gravitational wave emission, which are added in post-processing. Contrary to many previous studies, we find that the most massive binaries with near equal-mass companions are the most efficient at coalescing; though the process still typically takes gigayears.From the data produced by these MBH binary populations and their dynamics, we calculate the expected gravitational wave (GW) signals: both the stochastic, GW background of countless unresolved sources, and the GW foreground of individually resolvable binaries which resound above the noise. Ongoing experiments, called pulsar timing arrays, are sensitive to both of these types of signals. We find that, while the current lack of detections is unsurprising, both the background and foreground will plausibly be detected in the next decade. Unlike previous studies which have predicted the foreground to be significantly harder to detect than the background, we find their typical amplitudes are comparable.With traditional electromagnetic observations, there has also been a dearth of confirmed detections of MBH binary systems. We use our binaries, combined with models of emission from accreting MBH systems, to make predictions for the occurrence rate of systems observable using photometric, periodic-variability surveys. These variables should be detectable in current surveys, and indeed, we expect many candidates recently identified to be true binaries - though a significant fraction are likely false positives. Overall, this thesis finds the science of MBH binaries at an exciting cusp: just before incredible breakthroughs in observations, both electromagnetically and in the new age of gravitational wave astrophysics.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Hyman, James M; Restrepo, Juan M; Rael, Rosalyn C

We propose a population dynamics model for quantifying the effects of polling data on the outcome of multi-party elections decided by a majority-rule voting process. We divide the population into two groups: committed voters impervious to polling data, and susceptible voters whose decision to vote is influenced by data, depending on its reliability. This population-based approach to modeling the process sidesteps the problem of upscaling models based upon the choices made by individuals. We find releasing poll data is not advantageous to leading candidates, but it can be exploited by those closely trailing. The analysis identifies the particular type ofmore » voting impetus at play in different stages of an election and could help strategists optimize their influence on susceptible voters.« less
[Gypsy moth Lymantria dispar L. in the South Urals: Patterns in population dynamics and modelling].

PubMed

Soukhovolsky, V G; Ponomarev, V I; Sokolov, G I; Tarasova, O V; Krasnoperova, P A

2015-01-01

The analysis is conducted on population dynamics of gypsy moth from different habitats of the South Urals. The pattern of cyclic changes in population density is examined, the assessment of temporal conjugation in time series of gypsy moth population dynamics from separate habitats of the South Urals is carried out, the relationships between population density and weather conditions are studied. Based on the results obtained, a statistical model of gypsy moth population dynamics in the South Urals is designed, and estimations are given of regulatory and modifying factors effects on the population dynamics.

Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

USGS Publications Warehouse

Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

2015-01-01

Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total abundance produced estimates that largely conformed to our a priori expectation. Although care must be taken to tailor models to match the study population and survey data available, we argue that hierarchical spatiotemporal statistical models represent a powerful way forward for estimating abundance and explaining variation in the distribution of dynamical populations.
A parallel implementation of an off-lattice individual-based model of multicellular populations

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

NASA Astrophysics Data System (ADS)

Le Bret, Theo; Pontzen, Andrew; Cooper, Andrew P.; Frenk, Carlos; Zolotov, Adi; Brooks, Alyson M.; Governato, Fabio; Parry, Owen H.

2017-07-01

We establish a controlled comparison between the properties of galactic stellar haloes obtained with hydrodynamical simulations and with 'particle tagging'. Tagging is a fast way to obtain stellar population dynamics: instead of tracking gas and star formation, it 'paints' stars directly on to a suitably defined subset of dark matter particles in a collisionless, dark-matter-only simulation. Our study shows that 'live' particle tagging schemes, where stellar masses are painted on to the dark matter particles dynamically throughout the simulation, can generate good fits to the hydrodynamical stellar density profiles of a central Milky Way-like galaxy and its most prominent substructure. Energy diffusion processes are crucial to reshaping the distribution of stars in infalling spheroidal systems and hence the final stellar halo. We conclude that the success of any particular tagging scheme hinges on this diffusion being taken into account, and discuss the role of different subgrid feedback prescriptions in driving this diffusion.
Future scenarios for energy consumption and carbon emissions due to demographic transitions in Chinese households

NASA Astrophysics Data System (ADS)

Yu, Biying; Wei, Yi-Ming; Kei, Gomi; Matsuoka, Yuzuru

2018-02-01

Population dynamics has been acknowledged as a key concern for projecting future emissions, partly because of the huge uncertainties related to human behaviour. However, the heterogeneous shifts of human behaviour in the process of demographic transition are not well explored when scrutinizing the impacts of population dynamics on carbon emissions. Here, we expand the existing population-economy-environment analytical structure to address the above limitations by representing the trend of demographic transitions to small-family and ageing society. We specifically accommodate for inter- and intra-life-stage variations in time allocation and consumption in the population rather than assuming a representative household, and take a less developed province, Sichuan, in China as the empirical context. Our results show that the demographic shift to small and ageing households will boost energy consumption and carbon emissions, driven by the joint variations in time-use and consumption patterns. Furthermore, biased pictures of changing emissions will emerge if the time effect is disregarded.
Lentiviral and targeted cellular barcoding reveals ongoing clonal dynamics of cell lines in vitro and in vivo

PubMed Central

2014-01-01

Background Cell lines are often regarded as clonal, even though this simplifies what is known about mutagenesis, transformation and other processes that destabilize them over time. Monitoring these clonal dynamics is important for multiple areas of biomedical research, including stem cell and cancer biology. Tracking the contributions of individual cells to large populations, however, has been constrained by limitations in sensitivity and complexity. Results We utilize cellular barcoding methods to simultaneously track the clonal contributions of tens of thousands of cells. We demonstrate that even with optimal culturing conditions, common cell lines including HeLa, K562 and HEK-293 T exhibit ongoing clonal dynamics. Starting a population with a single clone diminishes but does not eradicate this phenomenon. Next, we compare lentiviral and zinc-finger nuclease barcode insertion approaches, finding that the zinc-finger nuclease protocol surprisingly results in reduced clonal diversity. We also document the expected reduction in clonal complexity when cells are challenged with genotoxic stress. Finally, we demonstrate that xenografts maintain clonal diversity to a greater extent than in vitro culturing of the human non-small-cell lung cancer cell line HCC827. Conclusions We demonstrate the feasibility of tracking and quantifying the clonal dynamics of entire cell populations within multiple cultured cell lines. Our results suggest that cell heterogeneity should be considered in the design and interpretation of in vitro culture experiments. Aside from clonal cell lines, we propose that cellular barcoding could prove valuable in modeling the clonal behavior of heterogeneous cell populations over time, including tumor populations treated with chemotherapeutic agents. PMID:24886633
Duplicate retention in signalling proteins and constraints from network dynamics.

PubMed

Soyer, O S; Creevey, C J

2010-11-01

Duplications are a major driving force behind evolution. Most duplicates are believed to fix through genetic drift, but it is not clear whether this process affects all duplications equally or whether there are certain gene families that are expected to show neutral expansions under certain circumstances. Here, we analyse the neutrality of duplications in different functional classes of signalling proteins based on their effects on response dynamics. We find that duplications involving intermediary proteins in a signalling network are neutral more often than those involving receptors. Although the fraction of neutral duplications in all functional classes increase with decreasing population size and selective pressure on dynamics, this effect is most pronounced for receptors, indicating a possible expansion of receptors in species with small population size. In line with such an expectation, we found a statistically significant increase in the number of receptors as a fraction of genome size in eukaryotes compared with prokaryotes. Although not confirmative, these results indicate that neutral processes can be a significant factor in shaping signalling networks and affect proteins from different functional classes differently. © 2010 The Authors. Journal Compilation © 2010 European Society For Evolutionary Biology.
A cognitive-consistency based model of population wide attitude change.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lakkaraju, Kiran; Speed, Ann Elizabeth

Attitudes play a significant role in determining how individuals process information and behave. In this paper we have developed a new computational model of population wide attitude change that captures the social level: how individuals interact and communicate information, and the cognitive level: how attitudes and concept interact with each other. The model captures the cognitive aspect by representing each individuals as a parallel constraint satisfaction network. The dynamics of this model are explored through a simple attitude change experiment where we vary the social network and distribution of attitudes in a population.
A linear model of population dynamics

NASA Astrophysics Data System (ADS)

Lushnikov, A. A.; Kagan, A. I.

2016-08-01

The Malthus process of population growth is reformulated in terms of the probability w(n,t) to find exactly n individuals at time t assuming that both the birth and the death rates are linear functions of the population size. The master equation for w(n,t) is solved exactly. It is shown that w(n,t) strongly deviates from the Poisson distribution and is expressed in terms either of Laguerre’s polynomials or a modified Bessel function. The latter expression allows for considerable simplifications of the asymptotic analysis of w(n,t).
PROCEEDINGS OF THE CROSS DISCIPLINE ECOSYTEM MODELING AND ANALYSIS WORKSHOP

EPA Science Inventory

The complexity of environmental problems we face now and in the future is ever increasing. Process linkages among air, land, surface and subsurface water require interdisciplinary modeling approaches. The dynamics of land use change spurred by population and economic growth, ...
A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

PubMed

Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.
A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

PubMed Central

Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp. PMID:28303100
Information processing in the CNS: a supramolecular chemistry?

PubMed

Tozzi, Arturo

2015-10-01

How does central nervous system process information? Current theories are based on two tenets: (a) information is transmitted by action potentials, the language by which neurons communicate with each other-and (b) homogeneous neuronal assemblies of cortical circuits operate on these neuronal messages where the operations are characterized by the intrinsic connectivity among neuronal populations. In this view, the size and time course of any spike is stereotypic and the information is restricted to the temporal sequence of the spikes; namely, the "neural code". However, an increasing amount of novel data point towards an alternative hypothesis: (a) the role of neural code in information processing is overemphasized. Instead of simply passing messages, action potentials play a role in dynamic coordination at multiple spatial and temporal scales, establishing network interactions across several levels of a hierarchical modular architecture, modulating and regulating the propagation of neuronal messages. (b) Information is processed at all levels of neuronal infrastructure from macromolecules to population dynamics. For example, intra-neuronal (changes in protein conformation, concentration and synthesis) and extra-neuronal factors (extracellular proteolysis, substrate patterning, myelin plasticity, microbes, metabolic status) can have a profound effect on neuronal computations. This means molecular message passing may have cognitive connotations. This essay introduces the concept of "supramolecular chemistry", involving the storage of information at the molecular level and its retrieval, transfer and processing at the supramolecular level, through transitory non-covalent molecular processes that are self-organized, self-assembled and dynamic. Finally, we note that the cortex comprises extremely heterogeneous cells, with distinct regional variations, macromolecular assembly, receptor repertoire and intrinsic microcircuitry. This suggests that every neuron (or group of neurons) embodies different molecular information that hands an operational effect on neuronal computation.
Monoxenic liquid culture with Escherichia coli of the free-living nematode Panagrolaimus sp. (strain NFS 24-5), a potential live food candidate for marine fish and shrimp larvae.

PubMed

Ayub, Farhana; Seychelles, Laurent; Strauch, Olaf; Wittke, Martina; Ehlers, Ralf-Udo

2013-09-01

The free-living, bacterial-feeding nematode Panagrolaimus sp. (strain NFS 24-5) has potential for use as live food for marine shrimp and fish larvae. Mass production in liquid culture is a prerequisite for its commercial exploitation. Panagrolaimus sp. was propagated in monoxenic liquid culture on Escherichia coli and parameters, like nematode density, population dynamics and biomass were recorded and compared with life history table data. A mean maximum nematode density of 174,278 mL(-1) and a maximum of 251,000 mL(-1) were recorded on day 17 after inoculation. Highest average biomass was 40 g L(-1) at day 13. The comparison with life history table data indicated that the hypothetical potential of liquid culture is much higher than documented during this investigation. Nematode development is delayed in liquid culture and egg production per female is more than five times lower than reported from life history trait analysis. The latter assessed a nematode generation time of 7.1 days, whereas the process time at maximum nematode density in liquid culture was 16 days indicating that a reduction of the process time can be achieved by further investigating the influence of nematode inoculum density on population development. The results challenge future research to reduce process time and variability and improve population dynamics also during scale-up of the liquid culture process.
Chaotic Financial Tornadoes

NASA Astrophysics Data System (ADS)

Jakimowicz, Aleksander

In contemporary economies classic business cycles are increasingly changing their form undergoing a transformation into phenomena that have been nicknamed financial tornados. A generalization of the Lotka-Volterra model can be used to describe these fast-changing processes. Economically speaking, the most useful are such dynamical systems in which wormholes appear. This article features application of a model with one population of prey and two populations of predators in order to explain the global financial crisis and the consequent phenomena.
Dynamics of water bound to crystalline cellulose

DOE Office of Scientific and Technical Information (OSTI.GOV)

O’Neill, Hugh; Pingali, Sai Venkatesh; Petridis, Loukas

Interactions of water with cellulose are of both fundamental and technological importance. Here, we characterize the properties of water associated with cellulose using deuterium labeling, neutron scattering and molecular dynamics simulation. Quasi-elastic neutron scattering provided quantitative details about the dynamical relaxation processes that occur and was supported by structural characterization using small-angle neutron scattering and X-ray diffraction. We can unambiguously detect two populations of water associated with cellulose. The first is “non-freezing bound” water that gradually becomes mobile with increasing temperature and can be related to surface water. The second population is consistent with confined water that abruptly becomes mobilemore » at ~260 K, and can be attributed to water that accumulates in the narrow spaces between the microfibrils. Quantitative analysis of the QENS data showed that, at 250 K, the water diffusion coefficient was 0.85 ± 0.04 × 10-10 m2sec-1 and increased to 1.77 ± 0.09 × 10-10 m2sec-1 at 265 K. MD simulations are in excellent agreement with the experiments and support the interpretation that water associated with cellulose exists in two dynamical populations. Our results provide clarity to previous work investigating the states of bound water and provide a new approach for probing water interactions with lignocellulose materials.« less
The type VI secretion system impacts bacterial invasion and population dynamics in a model intestinal microbiota

NASA Astrophysics Data System (ADS)

Logan, Savannah L.; Shields, Drew S.; Hammer, Brian K.; Xavier, Joao B.; Parthasarathy, Raghuveer

Animal gastrointestinal tracts are home to a diverse community of microbes. The mechanisms by which microbial species interact and compete in this dense, physically dynamic space are poorly understood, limiting our understanding of how natural communities are assembled and how different communities could be engineered. Here, we focus on a physical mechanism for competition: the type VI secretion system (T6SS). The T6SS is a syringe-like organelle used by certain bacteria to translocate effector proteins across the cell membranes of target bacterial cells, killing them. Here, we use T6SS+ and T6SS- strains of V. cholerae, the pathogen that causes cholera in humans, and light sheet fluorescence microscopy for in vivo imaging to show that the T6SS provides an advantage to strains colonizing the larval zebrafish gut. Furthermore, we show that T6SS+ bacteria can invade and alter an existing population of a different species in the zebrafish gut, reducing its abundance and changing the form of its population dynamics. This work both demonstrates a mechanism for altering the gut microbiota with an invasive species and explores the processes controlling the stability and dynamics of the gut ecosystem. Research Corporation, Gordon and Betty Moore Foundation, and the Simons Foundation.
Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series.

PubMed

Ferguson, Jake M; Ponciano, José M

2014-02-01

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. © 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.
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.
Emerging Concepts of Data Integration in Pathogen Phylodynamics.

PubMed

Baele, Guy; Suchard, Marc A; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.
Emerging Concepts of Data Integration in Pathogen Phylodynamics

PubMed Central

Baele, Guy; Suchard, Marc A.; Rambaut, Andrew; Lemey, Philippe

2017-01-01

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics. PMID:28173504

Early dynamical evolution of substructured stellar clusters

NASA Astrophysics Data System (ADS)

Dorval, Julien; Boily, Christian

2015-08-01

It is now widely accepted that stellar clusters form with a high level of substructure (Kuhn et al. 2014, Bate 2009), inherited from the molecular cloud and the star formation process. Evidence from observations and simulations also indicate the stars in such young clusters form a subvirial system (Kirk et al. 2007, Maschberger et al. 2010). The subsequent dynamical evolution can cause important mass loss, ejecting a large part of the birth population in the field. It can also imprint the stellar population and still be inferred from observations of evolved clusters. Nbody simulations allow a better understanding of these early twists and turns, given realistic initial conditions. Nowadays, substructured, clumpy young clusters are usually obtained through pseudo-fractal growth (Goodwin et al. 2004) and velocity inheritance. Such models are visually realistics and are very useful, they are however somewhat artificial in their velocity distribution. I introduce a new way to create clumpy initial conditions through a "Hubble expansion" which naturally produces self consistent clumps, velocity-wise. A velocity distribution analysis shows the new method produces realistic models, consistent with the dynamical state of the newly created cores in hydrodynamic simulation of cluster formation (Klessen & Burkert 2000). I use these initial conditions to investigate the dynamical evolution of young subvirial clusters, up to 80000 stars. I find an overall soft evolution, with hierarchical merging leading to a high level of mass segregation. I investigate the influence of the mass function on the fate of the cluster, specifically on the amount of mass loss induced by the early violent relaxation. Using a new binary detection algorithm, I also find a strong processing of the native binary population.
Using multitype branching processes to quantify statistics of disease outbreaks in zoonotic epidemics

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Schneider, David J.; Myers, Christopher R.

2014-03-01

Branching processes have served as a model for chemical reactions, biological growth processes, and contagion (of disease, information, or fads). Through this connection, these seemingly different physical processes share some common universalities that can be elucidated by analyzing the underlying branching process. In this work we focus on coupled branching processes as a model of infectious diseases spreading from one population to another. An exceedingly important example of such coupled outbreaks are zoonotic infections that spill over from animal populations to humans. We derive several statistical quantities characterizing the first spillover event from animals to humans, including the probability of spillover, the first passage time distribution for human infection, and disease prevalence in the animal population at spillover. Large stochastic fluctuations in those quantities can make inference of the state of the system at the time of spillover difficult. Focusing on outbreaks in the human population, we then characterize the critical threshold for a large outbreak, the distribution of outbreak sizes, and associated scaling laws. These all show a strong dependence on the basic reproduction number in the animal population and indicate the existence of a novel multicritical point with altered scaling behavior. The coupling of animal and human infection dynamics has crucial implications, most importantly allowing for the possibility of large human outbreaks even when human-to-human transmission is subcritical.
Galactic civilizations: Population dynamics and interstellar diffusion

NASA Technical Reports Server (NTRS)

Newman, W. I.; Sagan, C.

1978-01-01

The interstellar diffusion of galactic civilizations is reexamined by potential theory; both numerical and analytical solutions are derived for the nonlinear partial differential equations which specify a range of relevant models, drawn from blast wave physics, soil science, and, especially, population biology. An essential feature of these models is that, for all civilizations, population growth must be limited by the carrying capacity of the environment. Dispersal is fundamentally a diffusion process; a density-dependent diffusivity describes interstellar emigration. Two models are considered: the first describing zero population growth (ZPG), and the second which also includes local growth and saturation of a planetary population, and for which an asymptotic traveling wave solution is found.
Trojan Binaries

NASA Astrophysics Data System (ADS)

Noll, K. S.

2017-12-01

The Jupiter Trojans, in the context of giant planet migration models, can be thought of as an extension of the small body populations found beyond Neptune in the Kuiper Belt. Binaries are a distinctive feature of small body populations in the Kuiper Belt with an especially high fraction apparent among the brightest Cold Classicals. The binary fraction, relative sizes, and separations in the dynamically excited populations (Scattered, Resonant) reflects processes that may have eroded a more abundant initial population. This trend continues in the Centaurs and Trojans where few binaries have been found. We review new evidence including a third resolved Trojan binary and lightcurve studies to understand how the Trojans are related to the small body populations that originated in the outer protoplanetary disk.
Comparison of reintroduction and enhancement effects on metapopulation viability

USGS Publications Warehouse

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

2015-01-01

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

PubMed Central

Mace, Georgina M.; Collen, Ben; Fuller, Richard A.; Boakes, Elizabeth H.

2010-01-01

Continuing downward trends in the population sizes of many species, in the conservation status of threatened species, and in the quality, extent and connectedness of habitats are of increasing concern. Identifying the attributes of declining populations will help predict how biodiversity will be impacted and guide conservation actions. However, the drivers of biodiversity declines have changed over time and average trends in abundance or distributional change hide significant variation among species. While some populations are declining rapidly, the majority remain relatively stable and others are increasing. Here we dissect out some of the changing drivers of population and geographic range change, and identify biological and geographical correlates of winners and losers in two large datasets covering local population sizes of vertebrates since 1970 and the distributions of Galliform birds over the last two centuries. We find weak evidence for ecological and biological traits being predictors of local decline in range or abundance, but stronger evidence for the role of local anthropogenic threats and environmental change. An improved understanding of the dynamics of threat processes and how they may affect different species will help to guide better conservation planning in a continuously changing world. PMID:20980321
Parallel paleogenomic transects reveal complex genetic history of early European farmers

PubMed Central

Lipson, Mark; Szécsényi-Nagy, Anna; Mallick, Swapan; Pósa, Annamária; Stégmár, Balázs; Keerl, Victoria; Rohland, Nadin; Stewardson, Kristin; Ferry, Matthew; Michel, Megan; Oppenheimer, Jonas; Broomandkhoshbacht, Nasreen; Harney, Eadaoin; Nordenfelt, Susanne; Llamas, Bastien; Mende, Balázs Gusztáv; Köhler, Kitti; Oross, Krisztián; Bondár, Mária; Marton, Tibor; Osztás, Anett; Jakucs, János; Paluch, Tibor; Horváth, Ferenc; Csengeri, Piroska; Koós, Judit; Sebők, Katalin; Anders, Alexandra; Raczky, Pál; Regenye, Judit; Barna, Judit P.; Fábián, Szilvia; Serlegi, Gábor; Toldi, Zoltán; Nagy, Emese Gyöngyvér; Dani, János; Molnár, Erika; Pálfi, György; Márk, László; Melegh, Béla; Bánfai, Zsolt; Domboróczki, László; Fernández-Eraso, Javier; Mujika-Alustiza, José Antonio; Fernández, Carmen Alonso; Echevarría, Javier Jiménez; Bollongino, Ruth; Orschiedt, Jörg; Schierhold, Kerstin; Meller, Harald; Cooper, Alan; Burger, Joachim; Bánffy, Eszter; Alt, Kurt W.; Lalueza-Fox, Carles; Haak, Wolfgang; Reich, David

2017-01-01

Ancient DNA studies have established that Neolithic European populations were descended from Anatolian migrants1–8 who received a limited amount of admixture from resident hunter-gatherers3–5,9. Many open questions remain, however, about the spatial and temporal dynamics of population interactions and admixture during the Neolithic period. Using the highest-resolution genome-wide ancient DNA data set assembled to date—a total of 180 samples, 130 newly reported here, from the Neolithic and Chalcolithic of Hungary (6000–2900 BCE, n = 100), Germany (5500–3000 BCE, n = 42), and Spain (5500–2200 BCE, n = 38)—we investigate the population dynamics of Neolithization across Europe. We find that genetic diversity was shaped predominantly by local processes, with varied sources and proportions of hunter-gatherer ancestry among the three regions and through time. Admixture between groups with different ancestry profiles was pervasive and resulted in observable population transformation across almost all cultural transitions. Our results shed new light on the ways that gene flow reshaped European populations throughout the Neolithic period and demonstrate the potential of time-series-based sampling and modeling approaches to elucidate multiple dimensions of historical population interactions. PMID:29144465
Multi-event capture–recapture modeling of host–pathogen dynamics among European rabbit populations exposed to myxoma and Rabbit Hemorrhagic Disease Viruses: common and heterogeneous patterns

PubMed Central

2014-01-01

Host–pathogen epidemiological processes are often unclear due both to their complexity and over-simplistic approaches used to quantify them. We applied a multi-event capture–recapture procedure on two years of data from three rabbit populations to test hypotheses about the effects on survival of, and the dynamics of host immunity to, both myxoma virus and Rabbit Hemorrhagic Disease Virus (MV and RHDV). Although the populations shared the same climatic and management conditions, MV and RHDV dynamics varied greatly among them; MV and RHDV seroprevalences were positively related to density in one population, but RHDV seroprevalence was negatively related to density in another. In addition, (i) juvenile survival was most often negatively related to seropositivity, (ii) RHDV seropositives never had considerably higher survival, and (iii) seroconversion to seropositivity was more likely than the reverse. We suggest seropositivity affects survival depending on trade-offs among antibody protection, immunosuppression and virus lethality. Negative effects of seropositivity might be greater on juveniles due to their immature immune system. Also, while RHDV directly affects survival through the hemorrhagic syndrome, MV lack of direct lethal effects means that interactions influencing survival are likely to be more complex. Multi-event modeling allowed us to quantify patterns of host–pathogen dynamics otherwise difficult to discern. Such an approach offers a promising tool to shed light on causative mechanisms. PMID:24708296
Integrative studies of cultural evolution: crossing disciplinary boundaries to produce new insights

PubMed Central

2018-01-01

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities—including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species—and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution. This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’. PMID:29440515
Bipartite graphs as models of population structures in evolutionary multiplayer games.

PubMed

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, "games on graphs" study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner's dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner's dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.
Integrative studies of cultural evolution: crossing disciplinary boundaries to produce new insights.

PubMed

Kolodny, Oren; Feldman, Marcus W; Creanza, Nicole

2018-04-05

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities-including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species-and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).
Trees Wanted—Dead or Alive! Host Selection and Population Dynamics in Tree-Killing Bark Beetles

PubMed Central

Kausrud, Kyrre L.; Grégoire, Jean-Claude; Skarpaas, Olav; Erbilgin, Nadir; Gilbert, Marius; Økland, Bjørn; Stenseth, Nils Chr.

2011-01-01

Bark beetles (Coleoptera: Curculionidae, Scolytinae) feed and breed in dead or severely weakened host trees. When their population densities are high, some species aggregate on healthy host trees so that their defences may be exhausted and the inner bark successfully colonized, killing the tree in the process. Here we investigate under what conditions participating with unrelated conspecifics in risky mass attacks on living trees is an adaptive strategy, and what this can tell us about bark beetle outbreak dynamics. We find that the outcome of individual host selection may deviate from the ideal free distribution in a way that facilitates the emergence of tree-killing (aggressive) behavior, and that any heritability on traits governing aggressiveness seems likely to exist in a state of flux or cycles consistent with variability observed in natural populations. This may have implications for how economically and ecologically important species respond to environmental changes in climate and landscape (forest) structure. The population dynamics emerging from individual behavior are complex, capable of switching between “endemic” and “epidemic” regimes spontaneously or following changes in host availability or resistance. Model predictions are compared to empirical observations, and we identify some factors determining the occurrence and self-limitation of epidemics. PMID:21647433
Modeling the spatial and temporal population dynamics of the copepod Centropages typicus in the northwestern Mediterranean Sea during the year 2001 using a 3D ecosystem model

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.
Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

NASA Astrophysics Data System (ADS)

Deng, Xinyi

2016-08-01

A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in population spiking data. Lastly, we proposed a general three-step paradigm that allows us to relate behavioral outcomes of various tasks to simultaneously recorded neural activity across multiple brain areas, which is a step towards closed-loop therapies for psychological diseases using real-time neural stimulation. These methods are suitable for real-time implementation for content-based feedback experiments.
New Technologies in Amplification: Applications to the Pediatric Population.

ERIC Educational Resources Information Center

Kopun, Judy

1995-01-01

Discussion of technological advances in amplification for children with hearing impairments focuses on the advantages and limitations of fitting children with devices that have features such as dynamic-range compression, multiband signal processing, multimemory capability, digital feedback reduction, and frequency transposition. (Author/DB)
Modelling Social Learning in Monkeys

ERIC Educational Resources Information Center

Kendal, Jeremy R.

2008-01-01

The application of modelling to social learning in monkey populations has been a neglected topic. Recently, however, a number of statistical, simulation and analytical approaches have been developed to help examine social learning processes, putative traditions, the use of social learning strategies and the diffusion dynamics of socially…
Effects of constant immigration on the dynamics and persistence of stable and unstable Drosophila populations

PubMed Central

Dey, Snigdhadip; Joshi, Amitabh

2013-01-01

Constant immigration can stabilize population size fluctuations but its effects on extinction remain unexplored. We show that constant immigration significantly reduced extinction in fruitfly populations with relatively stable or unstable dynamics. In unstable populations with oscillations of amplitude around 1.5 times the mean population size, persistence and constancy were unrelated. Low immigration enhanced persistence without affecting constancy whereas high immigration increased constancy without enhancing persistence. In relatively stable populations with erratic fluctuations of amplitude close to the mean population size, both low and high immigration enhanced persistence. In these populations, the amplitude of fluctuations relative to mean population size went down due to immigration, and their dynamics were altered to low-period cycles. The effects of immigration on the population size distribution and intrinsic dynamics of stable versus unstable populations differed considerably, suggesting that the mechanisms by which immigration reduced extinction risk depended on underlying dynamics in complex ways. PMID:23470546
Faunal isotope records reveal trophic and nutrient dynamics in twentieth century Yellowstone grasslands.

PubMed

Fox-Dobbs, Kena; Nelson, Abigail A; Koch, Paul L; Leonard, Jennifer A

2012-10-23

Population sizes and movement patterns of ungulate grazers and their predators have fluctuated dramatically over the past few centuries, largely owing to overharvesting, land-use change and historic management. We used δ(13)C and δ(15)N values measured from bone collagen of historic and recent gray wolves and their potential primary prey from Yellowstone National Park to gain insight into the trophic dynamics and nutrient conditions of historic and modern grasslands. The diet of reintroduced wolves closely parallels that of the historic population. We suggest that a significant shift in faunal δ(15)N values over the past century reflects impacts of anthropogenic environmental changes on grassland ecosystems, including grazer-mediated shifts in grassland nitrogen cycle processes.
Faunal isotope records reveal trophic and nutrient dynamics in twentieth century Yellowstone grasslands

PubMed Central

Fox-Dobbs, Kena; Nelson, Abigail A.; Koch, Paul L.; Leonard, Jennifer A.

2012-01-01

Population sizes and movement patterns of ungulate grazers and their predators have fluctuated dramatically over the past few centuries, largely owing to overharvesting, land-use change and historic management. We used δ13C and δ15N values measured from bone collagen of historic and recent gray wolves and their potential primary prey from Yellowstone National Park to gain insight into the trophic dynamics and nutrient conditions of historic and modern grasslands. The diet of reintroduced wolves closely parallels that of the historic population. We suggest that a significant shift in faunal δ15N values over the past century reflects impacts of anthropogenic environmental changes on grassland ecosystems, including grazer-mediated shifts in grassland nitrogen cycle processes. PMID:22675135
Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

2015-01-01

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

Effect of exogenous inoculants on enhancing oil recovery and indigenous bacterial community dynamics in long-term field pilot of low permeability reservoir.

PubMed

Li, Jing; Xue, Shuwen; He, Chunqiu; Qi, Huixia; Chen, Fulin; Ma, Yanling

2018-03-20

Pseudomonas aeruginosa DN1 strain and Bacillus subtilis QHQ110 strain were chosen as rhamnolipid and lipopeptide producer respectively, to evaluate the efficiency of exogenous inoculants on enhancing oil recovery (EOR) and to explore the relationship between injected bacteria and indigenous bacterial community dynamics in long-term filed pilot of Hujianshan low permeability water-flooded reservoir for 26 months. Core-flooding tests showed that the oil displacement efficiency increased by 18.46% with addition of exogenous consortia. Bacterial community dynamics using quantitative PCR and high-throughput sequencing revealed that the exogenous inoculants survived and could live together with indigenous bacterial populations. They gradually became the dominant community after the initial activation, while their comparative advantage weakened continually after 3 months of the first injection. The bacterial populations did not exert an observable change in the process of the second injection of exogenous inoculants. On account of facilitating oil emulsification and accelerating bacterial growth with oil as the carbon source by the injection of exogenous consortia, γ-proteobacteria was finally the prominent bacterial community at class level varying from 25.55 to 32.67%, and the dominant bacterial populations were increased by 2-3 orders of magnitude during the whole processes. The content of organic acids and rhamnolipids in reservoir were promoted with the change of bacterial community diversity, respectively. Cumulative oil increments reached 26,190 barrels for 13 months after the first injection, and 55,947 barrels of oil had been accumulated in all of A20 wells block through two rounds of bacterial consortia injection. The performance of EOR has a cumulative improvement by the injection of exogenous inoculants without observable inhibitory effect on the indigenous bacterial populations, demonstrating the application potential in low permeability water-flooded reservoirs.
Neighbouring populations, opposite dynamics: influence of body size and environmental variation on the demography of stream-resident brown trout (Salmo trutta).

PubMed

Fernández-Chacón, Albert; Genovart, Meritxell; Álvarez, David; Cano, José M; Ojanguren, Alfredo F; Rodriguez-Muñoz, Rolando; Nicieza, Alfredo G

2015-06-01

In organisms such as fish, where body size is considered an important state variable for the study of their population dynamics, size-specific growth and survival rates can be influenced by local variation in both biotic and abiotic factors, but few studies have evaluated the complex relationships between environmental variability and size-dependent processes. We analysed a 6-year capture-recapture dataset of brown trout (Salmo trutta) collected at 3 neighbouring but heterogeneous mountain streams in northern Spain with the aim of investigating the factors shaping the dynamics of local populations. The influence of body size and water temperature on survival and individual growth was assessed under a multi-state modelling framework, an extension of classical capture-recapture models that considers the state (i.e. body size) of the individual in each capture occasion and allows us to obtain state-specific demographic rates and link them to continuous environmental variables. Individual survival and growth patterns varied over space and time, and evidence of size-dependent survival was found in all but the smallest stream. At this stream, the probability of reaching larger sizes was lower compared to the other wider and deeper streams. Water temperature variables performed better in the modelling of the highest-altitude population, explaining over a 99 % of the variability in maturation transitions and survival of large fish. The relationships between body size, temperature and fitness components found in this study highlight the utility of multi-state approaches to investigate small-scale demographic processes in heterogeneous environments, and to provide reliable ecological knowledge for management purposes.
ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

PubMed

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.
System Dynamics based Dengue modeling environment to simulate evolution of Dengue infection under different climate scenarios

NASA Astrophysics Data System (ADS)

Anwar, R.; Khan, R.; Usmani, M.; Colwell, R. R.; Jutla, A.

2017-12-01

Vector borne infectious diseases such as Dengue, Zika and Chikungunya remain a public health threat. An estimate of the World Health Organization (WHO) suggests that about 2.5 billion people, representing ca. 40% of human population,are at increased risk of dengue; with more than 100 million infection cases every year. Vector-borne infections cannot be eradicated since disease causing pathogens survive in the environment. Over the last few decades dengue infection has been reported in more than 100 countries and is expanding geographically. Female Ae. Aegypti mosquito, the daytime active and a major vector for dengue virus, is associated with urban population density and regional climatic processes. However, mathematical quantification of relationships on abundance of vectors and climatic processes remain a challenge, particularly in regions where such data are not routinely collected. Here, using system dynamics based feedback mechanism, an algorithm integrating knowledge from entomological, meteorological and epidemiological processes is developed that has potential to provide ensemble simulations on risk of occurrence of dengue infection in human population. Using dataset from satellite remote sensing, the algorithm was calibrated and validated using actual dengue case data of Iquitos, Peru. We will show results on model capabilities in capturing initiation and peak in the observed time series. In addition, results from several simulation scenarios under different climatic conditions will be discussed.
Rapid response of a marine mammal species to holocene climate and habitat change.

PubMed

de Bruyn, Mark; Hall, Brenda L; Chauke, Lucas F; Baroni, Carlo; Koch, Paul L; Hoelzel, A Rus

2009-07-01

Environmental change drives demographic and evolutionary processes that determine diversity within and among species. Tracking these processes during periods of change reveals mechanisms for the establishment of populations and provides predictive data on response to potential future impacts, including those caused by anthropogenic climate change. Here we show how a highly mobile marine species responded to the gain and loss of new breeding habitat. Southern elephant seal, Mirounga leonina, remains were found along the Victoria Land Coast (VLC) in the Ross Sea, Antarctica, 2,500 km from the nearest extant breeding site on Macquarie Island (MQ). This habitat was released after retreat of the grounded ice sheet in the Ross Sea Embayment 7,500-8,000 cal YBP, and is within the range of modern foraging excursions from the MQ colony. Using ancient mtDNA and coalescent models, we tracked the population dynamics of the now extinct VLC colony and the connectivity between this and extant breeding sites. We found a clear expansion signal in the VLC population approximately 8,000 YBP, followed by directional migration away from VLC and the loss of diversity at approximately 1,000 YBP, when sea ice is thought to have expanded. Our data suggest that VLC seals came initially from MQ and that some returned there once the VLC habitat was lost, approximately 7,000 years later. We track the founder-extinction dynamics of a population from inception to extinction in the context of Holocene climate change and present evidence that an unexpectedly diverse, differentiated breeding population was founded from a distant source population soon after habitat became available.
Role of Demographic Dynamics and Conflict in the Population-Area Relationship for Human Languages

PubMed Central

Manrubia, Susanna C.; Axelsen, Jacob B.; Zanette, Damián H.

2012-01-01

Many patterns displayed by the distribution of human linguistic groups are similar to the ecological organization described for biological species. It remains a challenge to identify simple and meaningful processes that describe these patterns. The population size distribution of human linguistic groups, for example, is well fitted by a log-normal distribution that may arise from stochastic demographic processes. As we show in this contribution, the distribution of the area size of home ranges of those groups also agrees with a log-normal function. Further, size and area are significantly correlated: the number of speakers and the area spanned by linguistic groups follow the allometric relation , with an exponent varying accross different world regions. The empirical evidence presented leads to the hypothesis that the distributions of and , and their mutual dependence, rely on demographic dynamics and on the result of conflicts over territory due to group growth. To substantiate this point, we introduce a two-variable stochastic multiplicative model whose analytical solution recovers the empirical observations. Applied to different world regions, the model reveals that the retreat in home range is sublinear with respect to the decrease in population size, and that the population-area exponent grows with the typical strength of conflicts. While the shape of the population size and area distributions, and their allometric relation, seem unavoidable outcomes of demography and inter-group contact, the precise value of could give insight on the cultural organization of those human groups in the last thousand years. PMID:22815726
Diversity Generator Mechanisms Are Essential Components of Biological Systems: The Two Queen Hypothesis

PubMed Central

Muraille, Eric

2018-01-01

Diversity is widely known to fuel adaptation and evolutionary processes and increase robustness at the population, species and ecosystem levels. The Neo-Darwinian paradigm proposes that the diversity of biological entities is the consequence of genetic changes arising spontaneously and randomly, without regard for their usefulness. However, a growing body of evidence demonstrates that the evolutionary process has shaped mechanisms, such as horizontal gene transfer mechanisms, meiosis and the adaptive immune system, which has resulted in the regulated generation of diversity among populations. Though their origins are unrelated, these diversity generator (DG) mechanisms share common functional properties. They (i) contribute to the great unpredictability of the composition and/or behavior of biological systems, (ii) favor robustness and collectivism among populations and (iii) operate mainly by manipulating the systems that control the interaction of living beings with their environment. The definition proposed here for DGs is based on these properties and can be used to identify them according to function. Interestingly, prokaryotic DGs appear to be mainly reactive, as they generate diversity in response to environmental stress. They are involved in the widely described Red Queen/arms race/Cairnsian dynamic. The emergence of multicellular organisms harboring K selection traits (longer reproductive life cycle and smaller population size) has led to the acquisition of a new class of DGs that act anticipatively to stress pressures and generate a distinct dynamic called the “White Queen” here. The existence of DGs leads to the view of evolution as a more “intelligent” and Lamarckian-like process. Their repeated selection during evolution could be a neglected example of convergent evolution and suggests that some parts of the evolutionary process are tightly constrained by ecological factors, such as the population size, the generation time and the intensity of selective pressure. The ubiquity of DGs also suggests that regulated auto-generation of diversity is a fundamental property of life. PMID:29487592
Using binary statistics in Taurus-Auriga to distinguish between brown dwarf formation processes

NASA Astrophysics Data System (ADS)

Marks, M.; Martín, E. L.; Béjar, V. J. S.; Lodieu, N.; Kroupa, P.; Manjavacas, E.; Thies, I.; Rebolo López, R.; Velasco, S.

2017-08-01

Context. One of the key questions of the star formation problem is whether brown dwarfs (BDs) form in the manner of stars directly from the gravitational collapse of a molecular cloud core (star-like) or whether BDs and some very low-mass stars (VLMSs) constitute a separate population that forms alongside stars comparable to the population of planets, for example through circumstellar disk (peripheral) fragmentation. Aims: For young stars in Taurus-Auriga the binary fraction has been shown to be large with little dependence on primary mass above ≈ 0.2 M⊙, while for BDs the binary fraction is < 10%. Here we investigate a case in which BDs in Taurus formed dominantly, but not exclusively, through peripheral fragmentation, which naturally results in small binary fractions. The decline of the binary frequency in the transition region between star-like formation and peripheral formation is modelled. Methods: We employed a dynamical population synthesis model in which stellar binary formation is universal with a large binary fraction close to unity. Peripheral objects form separately in circumstellar disks with a distinctive initial mass function (IMF), their own orbital parameter distributions for binaries, and small binary fractions, according to observations and expectations from smoothed particle hydrodynamics (SPH) and grid-based computations. A small amount of dynamical processing of the stellar component was accounted for as appropriate for the low-density Taurus-Auriga embedded clusters. Results: The binary fraction declines strongly in the transition region between star-like and peripheral formation, exhibiting characteristic features. The location of these features and the steepness of this trend depend on the mass limits for star-like and peripheral formation. Such a trend might be unique to low density regions, such as Taurus, which host binary populations that are largely unprocessed dynamically in which the binary fraction is large for stars down to M-dwarfs and small for BDs. Conclusions: The existence of a strong decline in the binary fraction - primary mass diagram will become verifiable in future surveys on BD and VLMS binarity in the Taurus-Auriga star-forming region. The binary fraction - primary mass diagram is a diagnostic of the (non-)continuity of star formation along the mass scale, the separateness of the stellar and BD populations, and the dominant formation channel for BDs and BD binaries in regions of low stellar density hosting dynamically unprocessed populations.
High prevalence of HBV/A1 subgenotype in native south Americans may be explained by recent economic developments in the Amazon.

PubMed

Godoy, Bibiane A; Gomes-Gouvêa, Michele S; Zagonel-Oliveira, Marcelo; Alvarado-Mora, Mónica V; Salzano, Francisco M; Pinho, João R R; Fagundes, Nelson J R

2016-09-01

Native American populations present the highest prevalence of Hepatitis B Virus (HBV) infection in the Americas, which may be associated to severe disease outcomes. Ten HBV genotypes (A–J) have been described, displaying a remarkable geographic structure, which most likely reflects historic patterns of human migrations. In this study, we characterize the HBV strains circulating in a historical sample of Native South Americans to characterize the historical viral dynamics in this population. The sample consisted of 1070 individuals belonging to 38 populations collected between 1965 and 1997. Presence of HBV DNA was checked by quantitative real-time PCR, and determination of HBV genotypes and subgenotypes was performed through sequencing and phylogenetic analysis of a fragment including part of HBsAg and Pol coding regions (S/Pol). A Bayesian Skyline Plot analysis was performed to compare the viral population dynamics of HBV/A1 strains found in Native Americans and in the general Brazilian population. A total of 109 individuals were positive for HBV DNA (~ 10%), and 70 samples were successfully sequenced and genotyped. Subgenotype A1 (HBV/A1), related to African populations and the African slave trade, was the most prevalent (66–94%). The Skyline Plot analysis showed a marked population expansion of HBV/A1 in Native Americans occurring more recently (1945–1965) than in the general Brazilian population. Our results suggest that historic processes that contributed to formation of HBV/A1 circulating in Native American are related with more recent migratory waves towards the Amazon basin, which generated a different viral dynamics in this region.
Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804
Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.
A semigroup approach to the strong ergodic theorem of the multistate stable population process.

PubMed

Inaba, H

1988-01-01

"In this paper we first formulate the dynamics of multistate stable population processes as a partial differential equation. Next, we rewrite this equation as an abstract differential equation in a Banach space, and solve it by using the theory of strongly continuous semigroups of bounded linear operators. Subsequently, we investigate the asymptotic behavior of this semigroup to show the strong ergodic theorem which states that there exists a stable distribution independent of the initial distribution. Finally, we introduce the dual problem in order to obtain a logical definition for the reproductive value and we discuss its applications." (SUMMARY IN FRE) excerpt
Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

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.
Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.
Theoretical Approaches in Evolutionary Ecology: Environmental Feedback as a Unifying Perspective.

PubMed

Lion, Sébastien

2018-01-01

Evolutionary biology and ecology have a strong theoretical underpinning, and this has fostered a variety of modeling approaches. A major challenge of this theoretical work has been to unravel the tangled feedback loop between ecology and evolution. This has prompted the development of two main classes of models. While quantitative genetics models jointly consider the ecological and evolutionary dynamics of a focal population, a separation of timescales between ecology and evolution is assumed by evolutionary game theory, adaptive dynamics, and inclusive fitness theory. As a result, theoretical evolutionary ecology tends to be divided among different schools of thought, with different toolboxes and motivations. My aim in this synthesis is to highlight the connections between these different approaches and clarify the current state of theory in evolutionary ecology. Central to this approach is to make explicit the dependence on environmental dynamics of the population and evolutionary dynamics, thereby materializing the eco-evolutionary feedback loop. This perspective sheds light on the interplay between environmental feedback and the timescales of ecological and evolutionary processes. I conclude by discussing some potential extensions and challenges to our current theoretical understanding of eco-evolutionary dynamics.
Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

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.
Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics

PubMed Central

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
Foraminifera Record the Good Years More than the Bad

NASA Astrophysics Data System (ADS)

Hull, P. M.

2014-12-01

Past ocean conditions are primarily discerned from geochemical and community-based analyses of fossilized taxa, each of which have unique environmental niches and dynamics. A key requirement of such paleoceanographic studies is that some unbiased or well-constrained record of the living ecosystem and climate is deposited on the sea floor and preserved through the post-depositional processes that act to distort them. It is widely known that foraminiferal species exhibit varying seasonal preferences and that seasonality is a key variable to account for in paleoceanographic reconstructions. However, on longer time scales (> year), it is generally assumed that species record the 'average' environmental conditions or typical variance (e.g., El Nino intensity) that existed in a given, time-averaged sediment sample. Here I examine planktonic foraminiferal population dynamics on yearly and longer time scales, in order to quantify their effect on paleoceanographic reconstructions. Using a previously published record of >250 years of population dynamics in the Santa Barbara Basin sediments, I find that the majority of individuals in a given species lived during a small subset of the total years (~15- 37% of years depending on the species). Populations of shallow, mixed layer species primarily represent the warmest, youngest years, while thermocline species primarily represent the cooler, older years. Importantly, the seasonality of species does not always predict their interannual dynamics. The general importance of long time-scale population dynamics on paleoceanographic reconstructions will also be considered in a theoretical model parameterized with temporally explicit species co-variances and temperature variability. Such modeling is needed to constrain the relative impact that a very good year can have on our interpretation of the 'average' of hundreds to thousands of years.
Coupled stream and population dynamics: Modeling the role beaver (Castor canadensis) play in generating juvenile steelhead (Oncorhynchus mykiss) habitat

NASA Astrophysics Data System (ADS)

Jordan, C.; Bouwes, N.; Wheaton, J. M.; Pollock, M.

2013-12-01

Over the past several centuries, the population of North American Beaver has been dramatically reduced through fur trapping. As a result, the geomorphic impacts long-term beaver occupancy and activity can have on fluvial systems have been lost, both from the landscape and from our collective memory such that physical and biological models of floodplain system function neither consider nor have the capacity to incorporate the role beaver can play in structuring the dynamics of streams. Concomitant with the decline in beaver populations was an increasing pressure on streams and floodplains through human activity, placing numerous species of stream rearing fishes in peril, most notably the ESA listing of trout and salmon populations across the entirety of the Western US. The rehabilitation of stream systems is seen as one of the primary means by which population and ecosystem recovery can be achieved, yet the methods of stream rehabilitation are applied almost exclusively with the expected outcome of a static idealized stream planform, occasionally with an acknowledgement of restoring processes rather than form and only rarely with the goal of a beaver dominated riverscape. We have constructed an individual based model of trout and beaver populations that allows the exploration of fish population dynamics as a function of stream habitat quality and quantity. We based the simulation tool on Bridge Creek (John Day River basin, Oregon) where we have implemented a large-scale restoration experiment using wooden posts to provide beavers with stable platforms for dam building and to simulate the dams themselves. Extensive monitoring captured geomorphic and riparian changes, as well as fish and beaver population responses; information we use to parameterize the model as to the geomorphic and fish response to dam building beavers. In the simulation environment, stream habitat quality and quantity can be manipulated directly through rehabilitation actions and indirectly through the dynamics of the co-occurring beaver population. The model allowed to us to ask questions critical for designing restoration strategies based on dam building beaver activity, such as what beaver population growth rate is required to develop and maintain floodplain connectivity in an incised system, or what beaver population size is required to increase juvenile steelhead production? The model was sensitive to several variables including beaver colony size, dams and colony dynamics and site fidelity, and thus highlights further research needs to fill critical information gaps.
Distributions of occupied and vacant butterfly habitats in fragmented landscapes.

PubMed

Thomas, C D; Thomas, J A; Warren, M S

1992-12-01

We found several rare UK butterflies to be restricted to relatively large and non-isolated habitat patches, while small patches and those that are isolated from population sources remain vacant. These patterns of occurrence are generated by the dynamic processes of local extinction and colonization. Habitat patches act as terrestrial archipelagos in which long-term population persistence, and hence effective long-term conservation, rely on networks of suitable habitats, sufficiently close to allow natural dispersal.

Influence of Coherent Tunneling and Incoherent Hopping on the Charge Transfer Mechanism in Linear Donor-Bridge-Acceptor Systems.

PubMed

Li, Guangqi; Govind, Niranjan; Ratner, Mark A; Cramer, Christopher J; Gagliardi, Laura

2015-12-17

The mechanism of charge transfer has been observed to change from tunneling to hopping with increasing numbers of DNA base pairs in polynucleotides and with the length of molecular wires. The aim of this paper is to investigate this transition by examining the population dynamics using a tight-binding Hamiltonian with model parameters to describe a linear donor-bridge-acceptor (D-B-A) system. The model includes a primary vibration and an electron-vibration coupling at each site. A further coupling of the primary vibration with a secondary phonon bath allows the system to dissipate energy to the environment and reach a steady state. We apply the quantum master equation (QME) approach, based on second-order perturbation theory in a quantum dissipative system, to examine the dynamical processes involved in charge-transfer and follow the population transfer rate at the acceptor, ka, to shed light on the transition from tunneling to hopping. With a small tunneling parameter, V, the on-site population tends to localize and form polarons, and the hopping mechanism dominates the transfer process. With increasing V, the population tends to be delocalized and the tunneling mechanism dominates. The competition between incoherent hopping and coherent tunneling governs the mechanism of charge transfer. By varying V and the total number of sites, we also examine the onset of the transition from tunneling to hopping with increasing length.
Neuro-cognitive mechanisms of decision making in joint action: a human-robot interaction study.

PubMed

Bicho, Estela; Erlhagen, Wolfram; Louro, Luis; e Silva, Eliana Costa

2011-10-01

In this paper we present a model for action preparation and decision making in cooperative tasks that is inspired by recent experimental findings about the neuro-cognitive mechanisms supporting joint action in humans. It implements the coordination of actions and goals among the partners as a dynamic process that integrates contextual cues, shared task knowledge and predicted outcome of others' motor behavior. The control architecture is formalized by a system of coupled dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode task-relevant information about action means, task goals and context in the form of self-sustained activation patterns. These patterns are triggered by input from connected populations and evolve continuously in time under the influence of recurrent interactions. The dynamic model of joint action is evaluated in a task in which a robot and a human jointly construct a toy object. We show that the highly context sensitive mapping from action observation onto appropriate complementary actions allows coping with dynamically changing joint action situations. Copyright © 2010 Elsevier B.V. All rights reserved.
Dynamics of Predator-Prey Metapopulations with Allee Effects.

PubMed

Fan, Meng; Wu, Ping; Feng, Zhilan; Swihart, Robert K

2016-08-01

Allee effects increasingly are recognized as influential determinants of population dynamics, especially in disturbed landscapes. We developed a predator-prey metapopulation model to study the impact of an Allee effect on predator-prey. The model incorporates habitat destruction and predators with imperfect information about prey distribution. Criteria are established for the existence and stability of equilibria, and the possible existence of a limit cycle is discussed. Numerical bifurcation analysis of the model is carried out to examine the impact of Allee effects as well as other key processes on trophic dynamics. Inclusion of Allee effects produces a richer array of dynamics than earlier models in which it was absent. When prey interacts with generalist predators, Allee effects operate synergistically to depress prey populations. Allee effects are more likely to depress occupancy levels when destruction of habitat patches is moderate; at severe levels of destruction, Allee effects are swamped by demographic effects of habitat loss. Stronger Allee effects correspond to lower thresholds of predator colonization rates at which prey become extinct. We discuss implications of our model for conservation of rare species as well as pest management via biocontrol.
The density dilemma: limitations on juvenile production in threatened salmon populations

USGS Publications Warehouse

Walters, Annika W.; Copeland, Timothy; Venditti, David A.

2013-01-01

Density-dependent processes have repeatedly been shown to have a central role in salmonid population dynamics, but are often assumed to be negligible for populations at low abundances relative to historical records. Density dependence has been observed in overall spring/summer Snake River Chinook salmon Oncorhynchus tshawytscha production, but it is not clear how patterns observed at the aggregate level relate to individual populations within the basin. We used a Bayesian hierarchical modelling approach to explore the degree of density dependence in juvenile production for nine Idaho populations. Our results indicate that density dependence is ubiquitous, although its strength varies between populations. We also investigated the processes driving the population-level pattern and found density-dependent growth and mortality present for both common life-history strategies, but no evidence of density-dependent movement. Overwinter mortality, spatial clustering of redds and limited resource availability were identified as potentially important limiting factors contributing to density dependence. The ubiquity of density dependence for these threatened populations is alarming as stability at present low abundance levels suggests recovery may be difficult without major changes. We conclude that density dependence at the population level is common and must be considered in demographic analysis and management.
Genetic erosion impedes adaptive responses to stressful environments

PubMed Central

Bijlsma, R; Loeschcke, Volker

2012-01-01

Biodiversity is increasingly subjected to human-induced changes of the environment. To persist, populations continually have to adapt to these often stressful changes including pollution and climate change. Genetic erosion in small populations, owing to fragmentation of natural habitats, is expected to obstruct such adaptive responses: (i) genetic drift will cause a decrease in the level of adaptive genetic variation, thereby limiting evolutionary responses; (ii) inbreeding and the concomitant inbreeding depression will reduce individual fitness and, consequently, the tolerance of populations to environmental stress. Importantly, inbreeding generally increases the sensitivity of a population to stress, thereby increasing the amount of inbreeding depression. As adaptation to stress is most often accompanied by increased mortality (cost of selection), the increase in the ‘cost of inbreeding’ under stress is expected to severely hamper evolutionary adaptive processes. Inbreeding thus plays a pivotal role in this process and is expected to limit the probability of genetically eroded populations to successfully adapt to stressful environmental conditions. Consequently, the dynamics of small fragmented populations may differ considerably from large nonfragmented populations. The resilience of fragmented populations to changing and deteriorating environments is expected to be greatly decreased. Alleviating inbreeding depression, therefore, is crucial to ensure population persistence. PMID:25568035
Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

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.
Fixation Probability in a Haploid-Diploid Population

PubMed Central

Bessho, Kazuhiro; Otto, Sarah P.

2017-01-01

Classical population genetic theory generally assumes either a fully haploid or fully diploid life cycle. However, many organisms exhibit more complex life cycles, with both free-living haploid and diploid stages. Here we ask what the probability of fixation is for selected alleles in organisms with haploid-diploid life cycles. We develop a genetic model that considers the population dynamics using both the Moran model and Wright–Fisher model. Applying a branching process approximation, we obtain an accurate fixation probability assuming that the population is large and the net effect of the mutation is beneficial. We also find the diffusion approximation for the fixation probability, which is accurate even in small populations and for deleterious alleles, as long as selection is weak. These fixation probabilities from branching process and diffusion approximations are similar when selection is weak for beneficial mutations that are not fully recessive. In many cases, particularly when one phase predominates, the fixation probability differs substantially for haploid-diploid organisms compared to either fully haploid or diploid species. PMID:27866168
Approximate reduction of linear population models governed by stochastic differential equations: application to multiregional models.

PubMed

Sanz, Luis; Alonso, Juan Antonio

2017-12-01

In this work we develop approximate aggregation techniques in the context of slow-fast linear population models governed by stochastic differential equations and apply the results to the treatment of populations with spatial heterogeneity. Approximate aggregation techniques allow one to transform a complex system involving many coupled variables and in which there are processes with different time scales, by a simpler reduced model with a fewer number of 'global' variables, in such a way that the dynamics of the former can be approximated by that of the latter. In our model we contemplate a linear fast deterministic process together with a linear slow process in which the parameters are affected by additive noise, and give conditions for the solutions corresponding to positive initial conditions to remain positive for all times. By letting the fast process reach equilibrium we build a reduced system with a lesser number of variables, and provide results relating the asymptotic behaviour of the first- and second-order moments of the population vector for the original and the reduced system. The general technique is illustrated by analysing a multiregional stochastic system in which dispersal is deterministic and the rate growth of the populations in each patch is affected by additive noise.
Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles

PubMed Central

Wheeler, Richard John

2015-01-01

Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point “snapshot” of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes—cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)—as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods. PMID:26543196
Effects of population succession on demographic and genetic processes: predictions and tests in the daylily Hemerocallis thunbergii (Liliaceae).

PubMed

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.
Dynamical ion transfer between coupled Coulomb crystals in a double-well potential.

PubMed

Klumpp, Andrea; Zampetaki, Alexandra; Schmelcher, Peter

2017-09-01

We investigate the nonequilibrium dynamics of coupled Coulomb crystals of different sizes trapped in a double well potential. The dynamics is induced by an instantaneous quench of the potential barrier separating the two crystals. Due to the intra- and intercrystal Coulomb interactions and the asymmetric population of the potential wells, we observe a complex reordering of ions within the two crystals as well as ion transfer processes from one well to the other. The study and analysis of the latter processes constitutes the main focus of this work. In particular, we examine the dependence of the observed ion transfers on the quench amplitude performing an analysis for different crystalline configurations ranging from one-dimensional ion chains via two-dimensional zigzag chains and ring structures to three-dimensional spherical structures. Such an analysis provides us with the means to extract the general principles governing the ion transfer dynamics and we gain some insight on the structural disorder caused by the quench of the barrier height.
[Demographic processes in the countries of Eastern Europe 1945-1990].

PubMed

Shchepin, O P; Vladimirova, L I

1990-01-01

An analysis is made of changes in the demographic processes in the countries of Eastern Europe over the period from 1945 to 1990 within both the general regularities and national peculiarities according to the parameters of statics and dynamics of population movement. The positive tendencies in the demographic processes are pointed out, first of all in infant mortality rates and mean expectation of life at birth in Eastern European countries by decades reflecting the peculiarities of changes as compared with developed countries.
Water-level fluctuations and metapopulation dynamics as drivers of genetic diversity in populations of three Tanganyikan cichlid fish species

PubMed Central

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-01-01

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. PMID:23837841
Water-level fluctuations and metapopulation dynamics as drivers of genetic diversity in populations of three Tanganyikan cichlid fish species.

PubMed

Nevado, B; Mautner, S; Sturmbauer, C; Verheyen, E

2013-08-01

Understanding how genetic variation is generated and maintained in natural populations, and how this process unfolds in a changing environment, remains a central issue in biological research. In this work, we analysed patterns of genetic diversity from several populations of three cichlid species from Lake Tanganyika in parallel, using the mitochondrial DNA control region. We sampled populations inhabiting the littoral rocky habitats in both very deep and very shallow areas of the lake. We hypothesized that the former would constitute relatively older, more stable and genetically more diverse populations, because they should have been less severely affected by the well-documented episodes of dramatic water-level fluctuations. In agreement with our predictions, populations of all three species sampled in very shallow shorelines showed traces of stronger population growth than populations of the same species inhabiting deep shorelines. However, contrary to our working hypothesis, we found a significant trend towards increased genetic diversity in the younger, demographically less stable populations inhabiting shallow areas, in comparison with the older and more stable populations inhabiting the deep shorelines. We interpret this finding as the result of the establishment of metapopulation dynamics in the former shorelines, by the frequent perturbation and reshuffling of individuals between populations due to the lake-level fluctuations. The repeated succession of periods of allopatric separation and secondary contact is likely to have further increased the rapid pace of speciation in lacustrine cichlids. © 2013 John Wiley & Sons Ltd.
Nonlinear Socio-Ecological Dynamics and First Principles ofCollective Choice Behavior of ``Homo Socialis"

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.
Population Dynamics of Viral Inactivation

NASA Astrophysics Data System (ADS)

Freeman, Krista; Li, Dong; Behrens, Manja; Streletzky, Kiril; Olsson, Ulf; Evilevitch, Alex

We have investigated the population dynamics of viral inactivation in vitrousing time-resolved cryo electron microscopy combined with light and X-ray scattering techniques. Using bacteriophage λ as a model system for pressurized double-stranded DNA viruses, we found that virions incubated with their cell receptor eject their genome in a stochastic triggering process. The triggering of DNA ejection occurs in a non synchronized manner after the receptor addition, resulting in an exponential decay of the number of genome-filled viruses with time. We have explored the characteristic time constant of this triggering process at different temperatures, salt conditions, and packaged genome lengths. Furthermore, using the temperature dependence we determined an activation energy for DNA ejections. The dependences of the time constant and activation energy on internal DNA pressure, affected by salt conditions and encapsidated genome length, suggest that the triggering process is directly dependent on the conformational state of the encapsidated DNA. The results of this work provide insight into how the in vivo kinetics of the spread of viral infection are influenced by intra- and extra cellular environmental conditions. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1252522.
Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Fedorov, Vadim B.; Goropashnaya, Anna V.; Talbot, Sandra; Cook, Joseph A.

2011-01-01

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis. We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew (Sorex asper), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes.
Persistence and diversification of the Holarctic shrew, Sorex tundrensis (Family Soricidae), in response to climate change

USGS Publications Warehouse

Hope, Andrew G.; Waltari, Eric; Fedorov, V.B.; Goropashnaya, A.V.; Talbot, Sandra; Cook, Joseph A.

2014-01-01

Environmental processes govern demography, species movements, community turnover and diversification and yet in many respects these dynamics are still poorly understood at high latitudes. We investigate the combined effects of climate change and geography through time for a widespread Holarctic shrew, Sorex tundrensis. We include a comprehensive suite of closely related outgroup taxa and three independent loci to explore phylogeographic structure and historical demography. We then explore the implications of these findings for other members of boreal communities. The tundra shrew and its sister species, the Tien Shan shrew (Sorex asper), exhibit strong geographic population structure across Siberia and into Beringia illustrating local centres of endemism that correspond to Late Pleistocene refugia. Ecological niche predictions for both current and historical distributions indicate a model of persistence through time despite dramatic climate change. Species tree estimation under a coalescent process suggests that isolation between populations has been maintained across timeframes deeper than the periodicity of Pleistocene glacial cycling. That some species such as the tundra shrew have a history of persistence largely independent of changing climate, whereas other boreal species shifted their ranges in response to climate change, highlights the dynamic processes of community assembly at high latitudes.
Postdefoliation ecosystem carbon and water flux and canopy growth dynamics in sagebrush steppe bunchgrass

USDA-ARS?s Scientific Manuscript database

Developing land-use practices that lead to sustainable net primary productivity in rangelands are important, but understanding their consequences to population and community processes is not often accounted for in basic ecosystem studies. Grazed and ungrazed upland ecosystems generally do not diffe...
Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Scaling with known uncertainty: a synthesis

Treesearch

Jianguo Wu; Harbin Li; K. Bruce Jones; Orie L. Loucks

2006-01-01

Scale is a fundamental concept in ecology and all sciences (Levin 1992, Wu and Loucks 1995, Barenblatt 1996), which has received increasing attention in recent years. The previous chapters have demonstrated an immerse diversity of scaling issues present in different areas of ecology, covering species distribution, population dynamics, ecosystem processes, and...
Science priorities for the human dimensions of global change

NASA Technical Reports Server (NTRS)

1994-01-01

The topics covered include the following: defining research needs; understanding land use change; improving policy analysis -- research on the decision-making process; designing policy instruments and institutions to address energy-related environmental problems; assessing impacts, vulnerability, and adaptation to global changes; and understanding population dynamics and global change.
GROSS N TRANSFORMATION RATES AND MICROBIAL POPULATION DYNAMICS UNDER FIELD AND LABORATORY CONDITIONS FROM TWO DIFFERENT ECOSYSTEMS

EPA Science Inventory

Change of soil and environmental conditions can influence microbial activities and subsequent soil nitrogen (N) transformation processes. The objective of this study was to compare gross N transformation rates between field and laboratory incubation conditions using an old-field...
Lectures and Simulation Laboratories to Improve Learners' Conceptual Understanding

ERIC Educational Resources Information Center

Brophy, Sean P.; Magana, Alejandra J.; Strachan, Alejandro

2013-01-01

We studied the use of online molecular dynamics simulations (MD) to enhance student abilities to understand the atomic processes governing plastic deformation in materials. The target population included a second-year undergraduate engineering course in the School of Materials Engineering at Purdue University. The objectives of the study were to…
Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953
Pattern does not equal process: what does patch occupancy really tell us about metapopulation dynamics?

PubMed

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.
Impact of biostimulated redox processes on metal dynamics in an iron-rich creek soil of a former uranium mining area.

PubMed

Burkhardt, Eva-Maria; Akob, Denise M; Bischoff, Sebastian; Sitte, Jana; Kostka, Joel E; Banerjee, Dipanjan; Scheinost, Andreas C; Küsel, Kirsten

2010-01-01

Understanding the dynamics of metals and radionuclides in soil environments is necessary for evaluating risks to pristine sites. An iron-rich creek soil of a former uranium-mining district (Ronneburg, Germany) showed high porewater concentrations of heavy metals and radionuclides. Thus, this study aims to (i) evaluate metal dynamics during terminal electron accepting processes (TEAPs) and (ii) characterize active microbial populations in biostimulated soil microcosms using a stable isotope probing (SIP) approach. In biostimulated soil slurries, concentrations of soluble Co, Ni, Zn, As, and unexpectedly U increased during Fe(III)-reduction. This suggests that there was a release of sorbed metals and As during reductive dissolution of Fe(III)-oxides. Subsequent sulfate-reduction was concurrent with a decrease of U, Co, Ni, and Zn concentrations. The relative contribution of U(IV) in the solid phase changed from 18.5 to 88.7% after incubation. The active Fe(III)-reducing population was dominated by delta-Proteobacteria (Geobacter) in (13)C-ethanol amended microcosms. A more diverse community was present in (13)C-lactate amended microcosms including taxa related to Acidobacteria, Firmicutes, delta-Proteobacteria, and beta-Proteobacteria. Our results suggested that biostimulated Fe(III)-reducing communities facilitated the release of metals including U to groundwater which is in contrast to other studies.
Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation.

PubMed

Manesso, Erica; Teles, José; Bryder, David; Peterson, Carsten

2013-03-06

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.
Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.
Control of Abnormal Synchronization in Neurological Disorders

PubMed Central

Popovych, Oleksandr V.; Tass, Peter A.

2014-01-01

In the nervous system, synchronization processes play an important role, e.g., in the context of information processing and motor control. However, pathological, excessive synchronization may strongly impair brain function and is a hallmark of several neurological disorders. This focused review addresses the question of how an abnormal neuronal synchronization can specifically be counteracted by invasive and non-invasive brain stimulation as, for instance, by deep brain stimulation for the treatment of Parkinson’s disease, or by acoustic stimulation for the treatment of tinnitus. On the example of coordinated reset (CR) neuromodulation, we illustrate how insights into the dynamics of complex systems contribute to successful model-based approaches, which use methods from synergetics, non-linear dynamics, and statistical physics, for the development of novel therapies for normalization of brain function and synaptic connectivity. Based on the intrinsic multistability of the neuronal populations induced by spike timing-dependent plasticity (STDP), CR neuromodulation utilizes the mutual interdependence between synaptic connectivity and dynamics of the neuronal networks in order to restore more physiological patterns of connectivity via desynchronization of neuronal activity. The very goal is to shift the neuronal population by stimulation from an abnormally coupled and synchronized state to a desynchronized regime with normalized synaptic connectivity, which significantly outlasts the stimulation cessation, so that long-lasting therapeutic effects can be achieved. PMID:25566174
Engineering Microbial Metabolite Dynamics and Heterogeneity.

PubMed

Schmitz, Alexander C; Hartline, Christopher J; Zhang, Fuzhong

2017-10-01

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Selective predation and rapid evolution can jointly dampen effects of virulent parasites on Daphnia populations.

PubMed

Duffy, Meghan A; Hall, Spencer R

2008-04-01

Parasites are ubiquitous and often highly virulent, yet clear examples of parasite-driven changes in host density in natural populations are surprisingly scarce. Here, we illustrate an example of this phenomenon and offer a theoretically reasonable resolution. We document the effects of two parasites, the bacterium Spirobacillus cienkowskii and the yeast Metschnikowia bicuspidata, on a common freshwater invertebrate, Daphnia dentifera. We show that while both parasites were quite virulent to individual hosts, only bacterial epidemics were associated with significant changes in host population dynamics and density. Our theoretical results may help explain why yeast epidemics did not significantly affect population dynamics. Using a model parameterized with data we collected, we argue that two prominent features of this system, rapid evolution of host resistance to the parasite and selective predation on infected hosts, both decrease peak infection prevalence and can minimize decline in host density during epidemics. Taken together, our results show that understanding the outcomes of host-parasite interactions in this Daphnia-microparasite system may require consideration of ecological context and evolutionary processes and their interaction.
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.
Evolution on neutral networks accelerates the ticking rate of the molecular clock.

PubMed

Manrubia, Susanna; Cuesta, José A

2015-01-06

Large sets of genotypes give rise to the same phenotype, because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as the genotype mutates into another one on the same set. By linking every pair of genotypes that are mutually accessible through mutation, genotypes organize themselves into neutral networks (NNs). These networks are known to be heterogeneous and assortative, and these properties affect the evolutionary dynamics of the population. By studying the dynamics of populations on NNs with arbitrary topology, we analyse the effect of assortativity, of NN (phenotype) fitness and of network size. We find that the probability that the population leaves the network is smaller the longer the time spent on it. This progressive 'phenotypic entrapment' entails a systematic increase in the overdispersion of the process with time and an acceleration in the fixation rate of neutral mutations. We also quantify the variation of these effects with the size of the phenotype and with its fitness relative to that of neighbouring alternatives. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Evolution on neutral networks accelerates the ticking rate of the molecular clock

PubMed Central

Manrubia, Susanna; Cuesta, José A.

2015-01-01

Large sets of genotypes give rise to the same phenotype, because phenotypic expression is highly redundant. Accordingly, a population can accept mutations without altering its phenotype, as long as the genotype mutates into another one on the same set. By linking every pair of genotypes that are mutually accessible through mutation, genotypes organize themselves into neutral networks (NNs). These networks are known to be heterogeneous and assortative, and these properties affect the evolutionary dynamics of the population. By studying the dynamics of populations on NNs with arbitrary topology, we analyse the effect of assortativity, of NN (phenotype) fitness and of network size. We find that the probability that the population leaves the network is smaller the longer the time spent on it. This progressive ‘phenotypic entrapment’ entails a systematic increase in the overdispersion of the process with time and an acceleration in the fixation rate of neutral mutations. We also quantify the variation of these effects with the size of the phenotype and with its fitness relative to that of neighbouring alternatives. PMID:25392402
Biogeography of the Sulfolobus islandicus pan-genome

PubMed Central

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
A theoretical analysis of the Allee effect in wind-pollinated cordgrass plant invasions.

PubMed

Murphy, James T; Johnson, Mark P

2015-12-01

A new individual-based model is presented for investigating an important group of invasive plant species, from the genus Spartina, that threaten biodiversity in coastal and intertidal habitats around the world. The role of pollen limitation in influencing the early development of an invasion is explored in order to gain a greater understanding of the mechanistic basis for an apparent Allee effect (causal relationship between population size/density and mean individual fitness) observed in populations of invasive Spartina species. The model is used to explore how various factors such as atmospheric stability, wind direction/speed, pollen characteristics and spatial structure of the population affect the overall invasion dynamics and reproductive success. Comparisons were also made between invasive species of Spartina (S. alterniflora, S. anglica) and a non-invasive species (S. foliosa), showing a reduced Allee effect was associated with invasion success. Furthermore, the conclusions drawn here may give insights into some of the fundamental processes affecting the growth and population dynamics of other invasive wind-pollinated plants. Copyright © 2015 Elsevier Inc. All rights reserved.
Population dynamics of Hawaiian seabird colonies vulnerable to sea-level rise

USGS Publications Warehouse

Hatfield, Jeff S.; Reynolds, Michelle H.; Seavy, Nathaniel E.; Krause, Crystal M.

2012-01-01

Globally, seabirds are vulnerable to anthropogenic threats both at sea and on land. Seabirds typically nest colonially and show strong fidelity to natal colonies, and such colonies on low-lying islands may be threatened by sea-level rise. We used French Frigate Shoals, the largest atoll in the Hawaiian Archipelago, as a case study to explore the population dynamics of seabird colonies and the potential effects sea-level rise may have on these rookeries. We compiled historic observations, a 30-year time series of seabird population abundance, lidar-derived elevations, and aerial imagery of all the islands of French Frigate Shoals. To estimate the population dynamics of 8 species of breeding seabirds on Tern Island from 1980 to 2009, we used a Gompertz model with a Bayesian approach to infer population growth rates, density dependence, process variation, and observation error. All species increased in abundance, in a pattern that provided evidence of density dependence. Great Frigatebirds (Fregata minor), Masked Boobies (Sula dactylatra), Red-tailed Tropicbirds (Phaethon rubricauda), Spectacled Terns (Onychoprion lunatus), and White Terns (Gygis alba) are likely at carrying capacity. Density dependence may exacerbate the effects of sea-level rise on seabirds because populations near carrying capacity on an island will be more negatively affected than populations with room for growth. We projected 12% of French Frigate Shoals will be inundated if sea level rises 1 m and 28% if sea level rises 2 m. Spectacled Terns and shrub-nesting species are especially vulnerable to sea-level rise, but seawalls and habitat restoration may mitigate the effects of sea-level rise. Losses of seabird nesting habitat may be substantial in the Hawaiian Islands by 2100 if sea levels rise 2 m. Restoration of higher-elevation seabird colonies represent a more enduring conservation solution for Pacific seabirds.
Ecological implications of behavioural syndromes.

PubMed

Sih, Andrew; Cote, Julien; Evans, Mara; Fogarty, Sean; Pruitt, Jonathan

2012-03-01

Interspecific trait variation has long served as a conceptual foundation for our understanding of ecological patterns and dynamics. In particular, ecologists recognise the important role that animal behaviour plays in shaping ecological processes. An emerging area of interest in animal behaviour, the study of behavioural syndromes (animal personalities) considers how limited behavioural plasticity, as well as behavioural correlations affects an individual's fitness in diverse ecological contexts. In this article we explore how insights from the concept and study of behavioural syndromes provide fresh understanding of major issues in population ecology. We identify several general mechanisms for how population ecology phenomena can be influenced by a species or population's average behavioural type, by within-species variation in behavioural type, or by behavioural correlations across time or across ecological contexts. We note, in particular, the importance of behavioural type-dependent dispersal in spatial ecology. We then review recent literature and provide new syntheses for how these general mechanisms produce novel insights on five major issues in population ecology: (1) limits to species' distribution and abundance; (2) species interactions; (3) population dynamics; (4) relative responses to human-induced rapid environmental change; and (5) ecological invasions. © 2012 Blackwell Publishing Ltd/CNRS.
Linking killer whale survival and prey abundance: food limitation in the oceans' apex predator?

PubMed Central

Ford, John K. B.; Ellis, Graeme M.; Olesiuk, Peter F.; Balcomb, Kenneth C.

2010-01-01

Killer whales (Orcinus orca) are large predators that occupy the top trophic position in the world's oceans and as such may have important roles in marine ecosystem dynamics. Although the possible top-down effects of killer whale predation on populations of their prey have received much recent attention, little is known of how the abundance of these predators may be limited by bottom-up processes. Here we show, using 25 years of demographic data from two populations of fish-eating killer whales in the northeastern Pacific Ocean, that population trends are driven largely by changes in survival, and that survival rates are strongly correlated with the availability of their principal prey species, Chinook salmon (Oncorhynchus tshawytscha). Our results suggest that, although these killer whales may consume a variety of fish species, they are highly specialized and dependent on this single salmonid species to an extent that it is a limiting factor in their population dynamics. Other ecologically specialized killer whale populations may be similarly constrained to a narrow range of prey species by culturally inherited foraging strategies, and thus are limited in their ability to adapt rapidly to changing prey availability. PMID:19755531

Linking killer whale survival and prey abundance: food limitation in the oceans' apex predator?

PubMed

Ford, John K B; Ellis, Graeme M; Olesiuk, Peter F; Balcomb, Kenneth C

2010-02-23

Killer whales (Orcinus orca) are large predators that occupy the top trophic position in the world's oceans and as such may have important roles in marine ecosystem dynamics. Although the possible top-down effects of killer whale predation on populations of their prey have received much recent attention, little is known of how the abundance of these predators may be limited by bottom-up processes. Here we show, using 25 years of demographic data from two populations of fish-eating killer whales in the northeastern Pacific Ocean, that population trends are driven largely by changes in survival, and that survival rates are strongly correlated with the availability of their principal prey species, Chinook salmon (Oncorhynchus tshawytscha). Our results suggest that, although these killer whales may consume a variety of fish species, they are highly specialized and dependent on this single salmonid species to an extent that it is a limiting factor in their population dynamics. Other ecologically specialized killer whale populations may be similarly constrained to a narrow range of prey species by culturally inherited foraging strategies, and thus are limited in their ability to adapt rapidly to changing prey availability.
Task-phase-specific dynamics of basal forebrain neuronal ensembles

PubMed Central

Tingley, David; Alexander, Andrew S.; Kolbu, Sean; de Sa, Virginia R.; Chiba, Andrea A.; Nitz, Douglas A.

2014-01-01

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases. PMID:25309352
A study of the dynamics of multi-player games on small networks using territorial interactions.

PubMed

Broom, Mark; Lafaye, Charlotte; Pattni, Karan; Rychtář, Jan

2015-12-01

Recently, the study of structured populations using models of evolutionary processes on graphs has begun to incorporate a more general type of interaction between individuals, allowing multi-player games to be played among the population. In this paper, we develop a birth-death dynamics for use in such models and consider the evolution of populations for special cases of very small graphs where we can easily identify all of the population states and carry out exact analyses. To do so, we study two multi-player games, a Hawk-Dove game and a public goods game. Our focus is on finding the fixation probability of an individual from one type, cooperator or defector in the case of the public goods game, within a population of the other type. We compare this value for both games on several graphs under different parameter values and assumptions, and identify some interesting general features of our model. In particular there is a very close relationship between the fixation probability and the mean temperature, with high temperatures helping fitter individuals and punishing unfit ones and so enhancing selection, whereas low temperatures give a levelling effect which suppresses selection.
A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.
'Tales of Symphonia': extinction dynamics in response to past climate change in Madagascan rainforests.

PubMed

Virah-Sawmy, Malika; Bonsall, Michael B; Willis, Katherine J

2009-12-23

Madagascar's rainforests are among the most biodiverse in the world. Understanding the population dynamics of important species within these forests in response to past climatic variability provides valuable insight into current and future species composition. Here, we use a population-level approach to analyse palaeoecological records over the last 5300 years to understand how populations of Symphonia cf. verrucosa became locally extinct in some rainforest fragments along the southeast coast of Madagascar in response to rapid climate change, yet persisted in others. Our results indicate that regional (climate) variability contributed to synchronous decline of S. cf. verrucosa populations in these forests. Superimposed on regional fluctuations were local processes that could have contributed or mitigated extinction. Specifically, in the forest with low soil nutrients, population model predictions indicated that there was coexistence between S. cf. verrucosa and Erica spp., but in the nutrient-rich forest, interspecific effects between Symphonia and Erica spp. may have pushed Symphonia to extinction at the peak of climatic change. We also demonstrate that Symphonia is a good indicator of a threshold event, exhibiting erratic fluctuations prior to and long after the critical climatic point has passed.
Fifty-sixth Christmas Bird Count. 147. Southern Dorchester County, Md

USGS Publications Warehouse

Johnson, F.A.; Williams, B.K.; Nichols, J.D.; Hines, J.E.; Kendall, W.L.; Smith, G.W.; Caithamer, David F.

1956-01-01

Summary and Recommendations: We suggest that managers are approaching the limits of their ability to improve waterfowl harvest management, primarily because the information needed to make better decisions is being sacrificed by the current approach to setting regulations. We propose an actively adaptive management strategy in which regulatory decisions play a dominant role in reducing uncertainty about population dynamics. The proposed strategy recognizes 'value' in acquiring knowledge only to the extent that it contributes to the objective of optimizing harvests. To implement this strategy, managers will need: (1) a set of regulatory options, with possible constraints on their use; (2) quantifiable harvest management objectives; (3) a set of models that represent an array of meaningful hypotheses about the effects of regulations on populations; and (4) a measure of credibility (or likelihood) for each model, which can be updated regularly using information from waterfowl monitoring programs. Adaptive optimization is an iterative process in which the harvest-management policy converges over time to one that maximizes harvest under the most appropriate model. At each time step, an optimal regulatory decision is identified based on the state of the system and the model likelihoods. In the next time step, predicted population changes from the alternative models are compared with the actual changes provided by the monitoring program, The likelihoods are increased or decreased to the extent that predicted and actual population changes correspond. These updated likelihoods then are used in setting regulations in the next cycle and the process begins again. This iterative process produces the most informative regulations when uncertainty is prevalent and produces maximum sustainable yields as uncertainty is eliminated. We see no major obstacles to implementing this adaptive strategy, although there are a number of practical considerations. First and foremost, managers should assess the 'value' of learning. Only when there is a high degree of uncertainty about the effects of hunting regulations on population dynamics will the merit of our proposed strategy be evident. We suggest that this almost always will be true given our current understanding of the relationship between annual regulations, survival and population growth in waterfowl. Nonetheless, careful consideration should be given to formulating the set of alternative models. There is no value in distinguishing between models which differ in their mathematical formulation or biological realism, but which suggest similar harvest strategies. We suspect that 'mechanistic' models (i.e., those that attempt to capture the essence of biological processes) will make better candidates for model sets than so-called 'phenomenological' models. Assuming that all model sets include a good approximation of reality, learning rates will be dependent on the quality of monitoring programs. Fortunately, a variety of high-quality monitoring plans for many duck and goose populations of North America, when used with our adaptive approach, should provide new knowledge about population dynamics and response to hunting, and, thus, lead to improved management.
Dynamics of water bound to crystalline cellulose.

PubMed

O'Neill, Hugh; Pingali, Sai Venkatesh; Petridis, Loukas; He, Junhong; Mamontov, Eugene; Hong, Liang; Urban, Volker; Evans, Barbara; Langan, Paul; Smith, Jeremy C; Davison, Brian H

2017-09-19

Interactions of water with cellulose are of both fundamental and technological importance. Here, we characterize the properties of water associated with cellulose using deuterium labeling, neutron scattering and molecular dynamics simulation. Quasi-elastic neutron scattering provided quantitative details about the dynamical relaxation processes that occur and was supported by structural characterization using small-angle neutron scattering and X-ray diffraction. We can unambiguously detect two populations of water associated with cellulose. The first is "non-freezing bound" water that gradually becomes mobile with increasing temperature and can be related to surface water. The second population is consistent with confined water that abruptly becomes mobile at ~260 K, and can be attributed to water that accumulates in the narrow spaces between the microfibrils. Quantitative analysis of the QENS data showed that, at 250 K, the water diffusion coefficient was 0.85 ± 0.04 × 10 -10 m 2 sec -1 and increased to 1.77 ± 0.09 × 10 -10 m 2 sec -1 at 265 K. MD simulations are in excellent agreement with the experiments and support the interpretation that water associated with cellulose exists in two dynamical populations. Our results provide clarity to previous work investigating the states of bound water and provide a new approach for probing water interactions with lignocellulose materials.
An application of the Caputo-Fabrizio operator to replicator-mutator dynamics: Bifurcation, chaotic limit cycles and control

NASA Astrophysics Data System (ADS)

Doungmo Goufo, Emile Franc

2018-02-01

The physical behaviors of replicator-mutator processes found in theoretical biophysics, physical chemistry, biochemistry and population biology remain complex with unlimited expressibility. People languages, for instance, have impressively and unpredictably changed over the time in human history. This is mainly due to the collection of small changes and collaboration with other languages. In this paper, the Caputo-Fabrizio operator is applied to a replicator-mutator dynamic taking place in midsts with movement. The model is fully analyzed and solved numerically via the Crank-Nicolson scheme. Stability and convergence results are provided. A concrete application to replicator-mutator dynamics for a population with three strategies is performed with numerical simulations provided for some fixed values of the physical position of the population symbolized by r and the grid points. Physically, it happens that limit cycles appear, not only in function of the mutation parameter μ but also in function of the values given to r . The amplitudes of limit cycles also appear to be proportional to r but the stability of the system remains unaffected. However, those limit cycles instead of disappearing as expected, are immediately followed by chaotic and unpredictable behaviors certainly due to the non-singular kernel used in the model and suitable to non-linear dynamics. Hence, the appearance and disappearance of limit cycles might be controlled by the position variable r which can also apprehend chaos.
Fixation of strategies with the Moran and Fermi processes in evolutionary games

NASA Astrophysics Data System (ADS)

Liu, Xuesong; He, Mingfeng; Kang, Yibin; Pan, Qiuhui

2017-10-01

A model of stochastic evolutionary game dynamics with finite population was built. It combines the standard Moran and Fermi rules with two strategies cooperation and defection. We obtain the expressions of fixation probabilities and fixation times. The one-third rule which has been found in the frequency dependent Moran process also holds for our model. We obtain the conditions of strategy being an evolutionarily stable strategy in our model, and then make a comparison with the standard Moran process. Besides, the analytical results show that compared with the standard Moran process, fixation occurs with higher probabilities under a prisoner's dilemma game and coordination game, but with lower probabilities under a coexistence game. The simulation result shows that the fixation time in our mixed process is lower than that in the standard Fermi process. In comparison with the standard Moran process, fixation always takes more time on average in spatial populations, regardless of the game. In addition, the fixation time decreases with the growth of the number of neighbors.
From Shelf to Shelf: Assessing Historical and Contemporary Genetic Differentiation and Connectivity across the Gulf of Mexico in Gag, Mycteroperca microlepis

PubMed Central

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
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.
Simulations for designing and interpreting intervention trials in infectious diseases.

PubMed

Halloran, M Elizabeth; Auranen, Kari; Baird, Sarah; Basta, Nicole E; Bellan, Steven E; Brookmeyer, Ron; Cooper, Ben S; DeGruttola, Victor; Hughes, James P; Lessler, Justin; Lofgren, Eric T; Longini, Ira M; Onnela, Jukka-Pekka; Özler, Berk; Seage, George R; Smith, Thomas A; Vespignani, Alessandro; Vynnycky, Emilia; Lipsitch, Marc

2017-12-29

Interventions in infectious diseases can have both direct effects on individuals who receive the intervention as well as indirect effects in the population. In addition, intervention combinations can have complex interactions at the population level, which are often difficult to adequately assess with standard study designs and analytical methods. Herein, we urge the adoption of a new paradigm for the design and interpretation of intervention trials in infectious diseases, particularly with regard to emerging infectious diseases, one that more accurately reflects the dynamics of the transmission process. In an increasingly complex world, simulations can explicitly represent transmission dynamics, which are critical for proper trial design and interpretation. Certain ethical aspects of a trial can also be quantified using simulations. Further, after a trial has been conducted, simulations can be used to explore the possible explanations for the observed effects. Much is to be gained through a multidisciplinary approach that builds collaborations among experts in infectious disease dynamics, epidemiology, statistical science, economics, simulation methods, and the conduct of clinical trials.
A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

PubMed

Marken, John P; Halleran, Andrew D; Rahman, Atiqur; Odorizzi, Laura; LeFew, Michael C; Golino, Caroline A; Kemper, Peter; Saha, Margaret S

2016-01-01

Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.
The unforeseen challenge: from genotype-to-phenotype in cell populations

NASA Astrophysics Data System (ADS)

Braun, Erez

2015-02-01

Biological cells present a paradox, in that they show simultaneous stability and flexibility, allowing them to adapt to new environments and to evolve over time. The emergence of stable cell states depends on genotype-to-phenotype associations, which essentially reflect the organization of gene regulatory modes. The view taken here is that cell-state organization is a dynamical process in which the molecular disorder manifests itself in a macroscopic order. The genome does not determine the ordered cell state; rather, it participates in this process by providing a set of constraints on the spectrum of regulatory modes, analogous to boundary conditions in physical dynamical systems. We have developed an experimental framework, in which cell populations are exposed to unforeseen challenges; novel perturbations they had not encountered before along their evolutionary history. This approach allows an unbiased view of cell dynamics, uncovering the potential of cells to evolve and develop adapted stable states. In the last decade, our experiments have revealed a coherent set of observations within this framework, painting a picture of the living cell that in many ways is not aligned with the conventional one. Of particular importance here, is our finding that adaptation of cell-state organization is essentially an efficient exploratory dynamical process rather than one founded on random mutations. Based on our framework, a set of concepts underlying cell-state organization—exploration evolving by global, non-specific, dynamics of gene activity—is presented here. These concepts have significant consequences for our understanding of the emergence and stabilization of a cell phenotype in diverse biological contexts. Their implications are discussed for three major areas of biological inquiry: evolution, cell differentiation and cancer. There is currently no unified theoretical framework encompassing the emergence of order, a stable state, in the living cell. Hopefully, the integrated picture described here will provide a modest contribution towards a physics theory of the cell.
Predicting oscillatory dynamics in the movement of territorial animals.

PubMed

Giuggioli, L; Potts, J R; Harris, S

2012-07-07

Understanding ecological processes relies upon the knowledge of the dynamics of each individual component. In the context of animal population ecology, the way animals move and interact is of fundamental importance in explaining a variety of observed patterns. Here, we present a theoretical investigation on the movement dynamics of interacting scent-marking animals. We study how the movement statistics of territorial animals is responsible for the appearance of damped oscillations in the mean square displacement (MSD) of the animals. This non-monotonicity is shown to depend on one dimensionless parameter, given by the ratio of the correlation distance between successive steps to the size of the territory. As that parameter increases, the time dependence of the animal's MSD displays a transition from monotonic, characteristic of Brownian walks, to non-monotonic, characteristic of highly correlated walks. The results presented here represent a novel way of determining the degree of persistence in animal movement processes within confined regions.
Predicting oscillatory dynamics in the movement of territorial animals

PubMed Central

Giuggioli, L.; Potts, J. R.; Harris, S.

2012-01-01

Understanding ecological processes relies upon the knowledge of the dynamics of each individual component. In the context of animal population ecology, the way animals move and interact is of fundamental importance in explaining a variety of observed patterns. Here, we present a theoretical investigation on the movement dynamics of interacting scent-marking animals. We study how the movement statistics of territorial animals is responsible for the appearance of damped oscillations in the mean square displacement (MSD) of the animals. This non-monotonicity is shown to depend on one dimensionless parameter, given by the ratio of the correlation distance between successive steps to the size of the territory. As that parameter increases, the time dependence of the animal's MSD displays a transition from monotonic, characteristic of Brownian walks, to non-monotonic, characteristic of highly correlated walks. The results presented here represent a novel way of determining the degree of persistence in animal movement processes within confined regions. PMID:22262814
Neural mechanisms of movement planning: motor cortex and beyond.

PubMed

Svoboda, Karel; Li, Nuo

2018-04-01

Neurons in motor cortex and connected brain regions fire in anticipation of specific movements, long before movement occurs. This neural activity reflects internal processes by which the brain plans and executes volitional movements. The study of motor planning offers an opportunity to understand how the structure and dynamics of neural circuits support persistent internal states and how these states influence behavior. Recent advances in large-scale neural recordings are beginning to decipher the relationship of the dynamics of populations of neurons during motor planning and movements. New behavioral tasks in rodents, together with quantified perturbations, link dynamics in specific nodes of neural circuits to behavior. These studies reveal a neural network distributed across multiple brain regions that collectively supports motor planning. We review recent advances and highlight areas where further work is needed to achieve a deeper understanding of the mechanisms underlying motor planning and related cognitive processes. Copyright © 2017. Published by Elsevier Ltd.
Coupling dynamical and collisional evolution of small bodies:. an application to the early ejection of planetesimals from the Jupiter-Saturn region

NASA Astrophysics Data System (ADS)

Charnoz, Sébastien; Morbidelli, Alessandro

2003-11-01

We present a new algorithm designed to compute the collisional erosion of a population of small bodies undergoing a complex and rapid dynamical evolution induced by strong gravitational perturbations. Usual particle-in-a-box models have been extensively and successfully used to study the evolution of asteroids or KBOs. However, they cannot track the evolution of small bodies in rapid dynamical evolution, due to their oversimplified description of the dynamics. Our code is based on both (1) a direct simulation of the dynamical evolution which is used to compute local encounter rates and (2) a classical fragmentation model. Such a code may be used to track the erosional evolution of the planetesimal disk under the action of newly formed giant-planets, a passing star or a population of massive planetary-embryos. We present here an application to a problem related to the formation of the Oort cloud. The usually accepted formation scenario is that planetesimals, originally formed in the giant planet region, have been transported to the Oort cloud by gravitational scattering. However, it has been suggested that, during the initial transport phase, the mutual large encounter velocities might have induced a rapid and intense collisional evolution of the planetesimal population, potentially causing a significant reduction of the Oort cloud formation process. This mechanism is explored with our new algorithm. Because the advantages of our new approach are better highlighted for a population undergoing a violent dynamical evolution, we concentrate in this paper on the planetesimals originally in the Jupiter-Saturn region, although it is known that they are only minor contributors to the final Oort cloud population. A wide range of parameters is explored (mass of the particle disk, initial size-distribution, material strength): depending upon the assumed parameter values, we find that from 15 to 90% of the mass contained in bodies larger than 1 km survives the collisional process; for our preferred choice of the parameters this fraction is ˜70%. It is also found that the majority of planetesimals larger than 1-10 km are pristine, and not fragments. We show also that collisional damping may not prevent planetesimals from being ejected to the outer Solar System. Thus, although the collisional activity is high during the scattering by Jupiter and Saturn, collisional grinding does not lower by orders of magnitude the mass contained in bodies larger than 1 km, originally in the Jupiter-Saturn region. These conclusions seem to support the classical collisionless scenario of Oort cloud formation, at least for the Jupiter-Saturn region.
Invasive advance of an advantageous mutation: nucleation theory.

PubMed

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.
The interplay between seasonality and density: consequences for female breeding decisions in a small cyclic herbivore

PubMed Central

2014-01-01

Background Cyclic rodent population dynamics are subjected to both intrinsic regulatory processes such as density-dependence and extrinsic environmental forcing. Among extrinsic factors, seasonal environmental variation is understood to facilitate cycles. In rodents, these processes have been studied mostly independently and their relative importance for population dynamics is poorly known. Results We performed a detailed analysis of common vole (Microtus arvalis) reproduction in a cyclic population using a spatially extensive data set over 17 years in central-western France. Environmental seasonality was the main source of explained variation in common vole reproduction. Additionally, inter-annual variation in the environment explained a smaller part of the variance in reproduction in spring and summer than in winter, whereas the effect of density was only found in autumn and winter. In particular, we detected a strong impact of plant productivity on fecundity during the breeding season, with low vegetation productivity being able to bring vole reproduction nearly to a halt. In contrast, vole reproduction during autumn and winter was mainly shaped by intrinsic factors, with only the longer and heavier females being able to reproduce. The effect of population density on reproduction was negative, mediated by direct negative effects on the proportion of breeders in autumn and winter during outbreak years and by a delayed negative effect on litter size the following year. Conclusions During the main breeding season, variability of female vole reproduction is predominantly shaped by food resources, suggesting that only highly productive environment may induce vole outbreaks. During fall and winter, variability of female vole reproduction is mainly controlled by intrinsic factors, with high population density suppressing reproduction. This suggests, in this cyclic population, that negative direct density dependence on reproduction could explain winter declines after outbreaks. PMID:24886481

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