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

Modeling structured population dynamics using data from unmarked individuals

USGS Publications Warehouse

Grant, Evan H. Campbell; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew

2014-01-01

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.

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.

Computer simulation of population dynamics inside the urban environment

NASA Astrophysics Data System (ADS)

Andreev, A. S.; Inovenkov, I. N.; Echkina, E. Yu.; Nefedov, V. V.; Ponomarenko, L. S.; Tikhomirov, V. V.

2017-12-01

In this paper using a mathematical model of the so-called “space-dynamic” approach we investigate the problem of development and temporal dynamics of different urban population groups. For simplicity we consider an interaction of only two population groups inside a single urban area with axial symmetry. This problem can be described qualitatively by a system of two non-stationary nonlinear differential equations of the diffusion type with boundary conditions of the third type. The results of numerical simulations show that with a suitable choice of the diffusion coefficients and interaction functions between different population groups we can receive different scenarios of population dynamics: from complete displacement of one population group by another (originally more “aggressive”) to the “peaceful” situation of co-existence of them together.

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.

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

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.

A consumer-resource approach to the density-dependent population dynamics of mutualism.

PubMed

Holland, J Nathaniel; DeAngelis, Donald L

2010-05-01

Like predation and competition, mutualism is now recognized as a consumer-resource (C-R) interaction, including, in particular, bi-directional (e.g., coral, plant-mycorrhizae) and uni-directional (e.g., ant-plant defense, plant-pollinator) C-R mutualisms. Here, we develop general theory for the density-dependent population dynamics of mutualism based on the C-R mechanism of interspecific interaction. To test the influence of C-R interactions on the dynamics and stability of bi- and uni-directional C-R mutualisms, we developed simple models that link consumer functional response of one mutualistic species with the resources supplied by another. Phase-plane analyses show that the ecological dynamics of C-R mutualisms are stable in general. Most transient behavior leads to an equilibrium of mutualistic coexistence, at which both species densities are greater than in the absence of interactions. However, due to the basic nature of C-R interactions, certain density-dependent conditions can lead to C-R dynamics characteristic of predator-prey interactions, in which one species overexploits and causes the other to go extinct. Consistent with empirical phenomena, these results suggest that the C-R interaction can provide a broad mechanism for understanding density-dependent population dynamics of mutualism. By unifying predation, competition, and mutualism under the common ecological framework of consumer-resource theory, we may also gain a better understanding of the universal features of interspecific interactions in general.

A consumer-resource approach to the density-dependent population dynamics of mutualism

USGS Publications Warehouse

Holland, J. Nathaniel; DeAngelis, Donald L.

2010-01-01

Like predation and competition, mutualism is now recognized as a consumer resource (C-R) interaction, including, in particular, bi-directional (e.g., coral, plant- mycorrhizae) and uni-directional (e.g., ant-plant defense, plant-pollinator) C-R mutualisms. Here, we develop general theory for the density-dependent population dynamics of mutualism based on the C-R mechanism of interspecific interaction. To test the influence of C-R interactions on the dynamics and stability of bi- and uni-directional C-R mutualisms, we developed simple models that link consumer functional response of one mutualistic species with the resources supplied by another. Phase-plane analyses show that the ecological dynamics of C-R mutualisms are stable in general. Most transient behavior leads to an equilibrium of mutualistic coexistence, at which both species densities are greater than in the absence of interactions. However, due to the basic nature of C-R interactions, certain density-dependent conditions can lead to C-R dynamics characteristic of predator-prey interactions, in which one species overexploits and causes the other to go extinct. Consistent with empirical phenomena, these results suggest that the C-R interaction can provide a broad mechanism for understanding density-dependent population dynamics of mutualism. By unifying predation, competition, and mutualism under the common ecological framework of consumer-resource theory, we may also gain a better understanding of the universal features of interspecific interactions in general.

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

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.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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

Regional Population Dynamics

Treesearch

Andrew Birt

2011-01-01

The population dynamics of the southern pine beetle (SPB) exhibit characteristic fluctuations between relatively long endemic and shorter outbreak periods. Populations exhibit complex and hierarchical spatial structure with beetles and larvae aggregating within individual trees, infestations with multiple infested trees, and regional outbreaks that comprise a large...

Inferences about population dynamics from count data using multistate models: a comparison to capture–recapture approaches

PubMed Central

Zipkin, Elise F; Sillett, T Scott; Grant, Evan H Campbell; Chandler, Richard B; Royle, J Andrew

2014-01-01

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of

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.

Dynamic Properties of the Alkaline Vesicle Population at Hippocampal Synapses

PubMed Central

Röther, Mareike; Brauner, Jan M.; Ebert, Katrin; Welzel, Oliver; Jung, Jasmin; Bauereiss, Anna; Kornhuber, Johannes; Groemer, Teja W.

2014-01-01

In compensatory endocytosis, scission of vesicles from the plasma membrane to the cytoplasm is a prerequisite for intravesicular reacidification and accumulation of neurotransmitter molecules. Here, we provide time-resolved measurements of the dynamics of the alkaline vesicle population which appears upon endocytic retrieval. Using fast perfusion pH-cycling in live-cell microscopy, synapto-pHluorin expressing rat hippocampal neurons were electrically stimulated. We found that the relative size of the alkaline vesicle population depended significantly on the electrical stimulus size: With increasing number of action potentials the relative size of the alkaline vesicle population expanded. In contrast to that, increasing the stimulus frequency reduced the relative size of the population of alkaline vesicles. Measurement of the time constant for reacification and calculation of the time constant for endocytosis revealed that both time constants were variable with regard to the stimulus condition. Furthermore, we show that the dynamics of the alkaline vesicle population can be predicted by a simple mathematical model. In conclusion, here a novel methodical approach to analyze dynamic properties of alkaline vesicles is presented and validated as a convenient method for the detection of intracellular events. Using this method we show that the population of alkaline vesicles is highly dynamic and depends both on stimulus strength and frequency. Our results implicate that determination of the alkaline vesicle population size may provide new insights into the kinetics of endocytic retrieval. PMID:25079223

A system dynamics modelling approach to assess the impact of launching a new nicotine product on population health outcomes.

PubMed

Hill, Andrew; Camacho, Oscar M

2017-06-01

In 2012 the US FDA suggested the use of mathematical models to assess the impact of releasing new nicotine or tobacco products on population health outcomes. A model based on system dynamics methodology was developed to project the potential effects of a new nicotine product at a population level. A model representing traditional smoking populations (never, current and former smokers) and calibrated using historical data was extended to a two-product model by including electronic cigarettes use statuses. Smoking mechanisms, such as product initiation, switching, transition to dual use, and cessation, were represented as flows between smoking statuses (stocks) and the potential effect of smoking renormalisation through a feedback system. Mortality over a 50-year period (2000-2050) was the health outcome of interest, and was compared between two scenarios, with and without e-cigarettes being introduced. The results suggest that by 2050, smoking prevalence in adults was 12.4% in the core model and 9.7% (including dual users) in the counterfactual. Smoking-related mortality was 8.4% and 8.1%, respectively. The results suggested an overall beneficial effect from launching e-cigarettes and that system dynamics could be a useful approach to assess the potential population health effects of nicotine products when epidemiological data are not available. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Population dynamics and mutualism: Functional responses of benefits and costs

USGS Publications Warehouse

Holland, J. Nathaniel; DeAngelis, Donald L.; Bronstein, Judith L.

2002-01-01

We develop an approach for studying population dynamics resulting from mutualism by employing functional responses based on density‐dependent benefits and costs. These functional responses express how the population growth rate of a mutualist is modified by the density of its partner. We present several possible dependencies of gross benefits and costs, and hence net effects, to a mutualist as functions of the density of its partner. Net effects to mutualists are likely a monotonically saturating or unimodal function of the density of their partner. We show that fundamental differences in the growth, limitation, and dynamics of a population can occur when net effects to that population change linearly, unimodally, or in a saturating fashion. We use the mutualism between senita cactus and its pollinating seed‐eating moth as an example to show the influence of different benefit and cost functional responses on population dynamics and stability of mutualisms. We investigated two mechanisms that may alter this mutualism's functional responses: distribution of eggs among flowers and fruit abortion. Differences in how benefits and costs vary with density can alter the stability of this mutualism. In particular, fruit abortion may allow for a stable equilibrium where none could otherwise exist.

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

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

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

Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches

USGS Publications Warehouse

Grant, Evan H. Campbell; Zipkin, Elise; Scott, Sillett T.; Chandler, Richard; Royle, J. Andrew

2014-01-01

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive

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

Network evolution induced by the dynamical rules of two populations

NASA Astrophysics Data System (ADS)

Platini, Thierry; Zia, R. K. P.

2010-10-01

We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely extrovert (a) and introvert (b). In our model, each group is characterized by its size (Na and Nb) and preferred degree (κa and \\kappa_b\\ll \\kappa_a ). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees langkbbrang and langkabrang presents three time regimes and a non-monotonic behavior well captured by our theory. Surprisingly, when the population sizes are equal Na = Nb, the ratio of the restricted degree θ0 = langkabrang/langkbbrang appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t < t1 = κb) the total number of links presents a linear evolution, where the two populations are indistinguishable and where θ0 = 1. Interestingly, in the intermediate time regime (defined for t_1\\lt t\\lt t_2\\propto \\kappa_a and for which θ0 = 5), the system reaches a transient stationary state, where the number of contacts among introverts remains constant while the number of connections increases linearly in the extrovert population. Finally, due to the competing dynamics, the network presents a frustrated stationary state characterized by a ratio θ0 = 3.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

Long-term effective population size dynamics of an intensively monitored vertebrate population

PubMed Central

Mueller, A-K; Chakarov, N; Krüger, O; Hoffman, J I

2016-01-01

Long-term genetic data from intensively monitored natural populations are important for understanding how effective population sizes (Ne) can vary over time. We therefore genotyped 1622 common buzzard (Buteo buteo) chicks sampled over 12 consecutive years (2002–2013 inclusive) at 15 microsatellite loci. This data set allowed us to both compare single-sample with temporal approaches and explore temporal patterns in the effective number of parents that produced each cohort in relation to the observed population dynamics. We found reasonable consistency between linkage disequilibrium-based single-sample and temporal estimators, particularly during the latter half of the study, but no clear relationship between annual Ne estimates () and census sizes. We also documented a 14-fold increase in between 2008 and 2011, a period during which the census size doubled, probably reflecting a combination of higher adult survival and immigration from further afield. Our study thus reveals appreciable temporal heterogeneity in the effective population size of a natural vertebrate population, confirms the need for long-term studies and cautions against drawing conclusions from a single sample. PMID:27553455

The importance of temperature fluctuations in understanding mosquito population dynamics and malaria risk.

PubMed

Beck-Johnson, Lindsay M; Nelson, William A; Paaijmans, Krijn P; Read, Andrew F; Thomas, Matthew B; Bjørnstad, Ottar N

2017-03-01

Temperature is a key environmental driver of Anopheles mosquito population dynamics; understanding its central role is important for these malaria vectors. Mosquito population responses to temperature fluctuations, though important across the life history, are poorly understood at a population level. We used stage-structured, temperature-dependent delay-differential equations to conduct a detailed exploration of the impacts of diurnal and annual temperature fluctuations on mosquito population dynamics. The model allows exploration of temperature-driven temporal changes in adult age structure, giving insights into the population's capacity to vector malaria parasites. Because of temperature-dependent shifts in age structure, the abundance of potentially infectious mosquitoes varies temporally, and does not necessarily mirror the dynamics of the total adult population. In addition to conducting the first comprehensive theoretical exploration of fluctuating temperatures on mosquito population dynamics, we analysed observed temperatures at four locations in Africa covering a range of environmental conditions. We found both temperature and precipitation are needed to explain the observed malaria season in these locations, enhancing our understanding of the drivers of malaria seasonality and how temporal disease risk may shift in response to temperature changes. This approach, tracking both mosquito abundance and age structure, may be a powerful tool for understanding current and future malaria risk.

Population dynamics on heterogeneous bacterial substrates

NASA Astrophysics Data System (ADS)

Mobius, Wolfram; Murray, Andrew W.; Nelson, David R.

2012-02-01

How species invade new territories and how these range expansions influence the population's genotypes are important questions in the field of population genetics. The majority of work addressing these questions focuses on homogeneous environments. Much less is known about the population dynamics and population genetics when the environmental conditions are heterogeneous in space. To better understand range expansions in two-dimensional heterogeneous environments, we employ a system of bacteria and bacteriophage, the viruses of bacteria. Thereby, the bacteria constitute the environment in which a population of bacteriophages expands. The spread of phage constitutes itself in lysis of bacteria and thus formation of clear regions on bacterial lawns, called plaques. We study the population dynamics and genetics of the expanding page for various patterns of environments.

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.

Dynamic Approaches to Language Processing

ERIC Educational Resources Information Center

Srinivasan, Narayanan

2007-01-01

Symbolic rule-based approaches have been a preferred way to study language and cognition. Dissatisfaction with rule-based approaches in the 1980s lead to alternative approaches to study language, the most notable being the dynamic approaches to language processing. Dynamic approaches provide a significant alternative by not being rule-based and…

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

PubMed

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

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

Drivers of waterfowl population dynamics: from teal to swans

USGS Publications Warehouse

Koons, David N.; Gunnarsson, Gunnar; Schmutz, Joel A.; Rotella, Jay J.

2014-01-01

Waterfowl are among the best studied and most extensively monitored species in the world. Given their global importance for sport and subsistence hunting, viewing and ecosystem functioning, great effort has been devoted since the middle part of the 20th century to understanding both the environmental and demographic mechanisms that influence waterfowl population and community dynamics. Here we use comparative approaches to summarise and contrast our understanding ofwaterfowl population dynamics across species as short-lived as the teal Anas discors and A.crecca to those such as the swans Cygnus sp. which have long life-spans. Specifically, we focus on population responses to vital rate perturbations across life history strategies, discuss bottom-up and top-down responses of waterfowlpopulations to global change, and summarise our current understanding of density dependence across waterfowl species. We close by identifying research needs and highlight ways to overcome the challenges of sustainably managing waterfowl populations in the 21st century.

Mutator dynamics in sexual and asexual experimental populations of yeast.

PubMed

Raynes, Yevgeniy; Gazzara, Matthew R; Sniegowski, Paul D

2011-06-07

In asexual populations, mutators may be expected to hitchhike with associated beneficial mutations. In sexual populations, recombination is predicted to erode such associations, inhibiting mutator hitchhiking. To investigate the effect of recombination on mutators experimentally, we compared the frequency dynamics of a mutator allele (msh2Δ) in sexual and asexual populations of Saccharomyces cerevisiae. Mutator strains increased in frequency at the expense of wild-type strains in all asexual diploid populations, with some approaching fixation in 150 generations of propagation. Over the same period of time, mutators declined toward loss in all corresponding sexual diploid populations as well as in haploid populations propagated asexually. We report the first experimental investigation of mutator dynamics in sexual populations. We show that a strong mutator quickly declines in sexual populations while hitchhiking to high frequency in asexual diploid populations, as predicted by theory. We also show that the msh2Δ mutator has a high and immediate realized cost that is alone sufficient to explain its decline in sexual populations. We postulate that this cost is indirect; namely, that it is due to a very high rate of recessive lethal or strongly deleterious mutation. However, we cannot rule out the possibility that msh2Δ also has unknown directly deleterious effects on fitness, and that these effects may differ between haploid asexual and sexual populations. Despite these reservations, our results prompt us to speculate that the short-term cost of highly deleterious recessive mutations can be as important as recombination in preventing mutator hitchhiking in sexual populations.

Harvest and dynamics of duck populations

USGS Publications Warehouse

Sedinger, James S.; Herzog, Mark P.

2012-01-01

The role of harvest in the dynamics of waterfowl populations continues to be debated among scientists and managers. Our perception is that interested members of the public and some managers believe that harvest influences North American duck populations based on calls for more conservative harvest regulations. A recent review of harvest and population dynamics of North American mallard (Anas platyrhynchos) populations (Pöysä et al. 2004) reached similar conclusions. Because of the importance of this issue, we reviewed the evidence for an impact of harvest on duck populations. Our understanding of the effects of harvest is limited because harvest effects are typically confounded with those of population density; regulations are typically most liberal when populations are greatest. This problem also exists in the current Adaptive Harvest Management Program (Conn and Kendall 2004). Consequently, even where harvest appears additive to other mortality, this may be an artifact of ignoring effects of population density. Overall, we found no compelling evidence for strong additive effects of harvest on survival in duck populations that could not be explained by other factors.

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

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.

Evolutionary dynamics of cooperation in neutral populations

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2018-01-01

Cooperation is a difficult proposition in the face of Darwinian selection. Those that defect have an evolutionary advantage over cooperators who should therefore die out. However, spatial structure enables cooperators to survive through the formation of homogeneous clusters, which is the hallmark of network reciprocity. Here we go beyond this traditional setup and study the spatiotemporal dynamics of cooperation in a population of populations. We use the prisoner's dilemma game as the mathematical model and show that considering several populations simultaneously gives rise to fascinating spatiotemporal dynamics and pattern formation. Even the simplest assumption that strategies between different populations are payoff-neutral with one another results in the spontaneous emergence of cyclic dominance, where defectors of one population become prey of cooperators in the other population, and vice versa. Moreover, if social interactions within different populations are characterized by significantly different temptations to defect, we observe that defectors in the population with the largest temptation counterintuitively vanish the fastest, while cooperators that hang on eventually take over the whole available space. Our results reveal that considering the simultaneous presence of different populations significantly expands the complexity of evolutionary dynamics in structured populations, and it allows us to understand the stability of cooperation under adverse conditions that could never be bridged by network reciprocity alone.

Feedback between Population and Evolutionary Dynamics Determines the Fate of Social Microbial Populations

PubMed Central

Sanchez, Alvaro; Gore, Jeff

2013-01-01

The evolutionary spread of cheater strategies can destabilize populations engaging in social cooperative behaviors, thus demonstrating that evolutionary changes can have profound implications for population dynamics. At the same time, the relative fitness of cooperative traits often depends upon population density, thus leading to the potential for bi-directional coupling between population density and the evolution of a cooperative trait. Despite the potential importance of these eco-evolutionary feedback loops in social species, they have not yet been demonstrated experimentally and their ecological implications are poorly understood. Here, we demonstrate the presence of a strong feedback loop between population dynamics and the evolutionary dynamics of a social microbial gene, SUC2, in laboratory yeast populations whose cooperative growth is mediated by the SUC2 gene. We directly visualize eco-evolutionary trajectories of hundreds of populations over 50–100 generations, allowing us to characterize the phase space describing the interplay of evolution and ecology in this system. Small populations collapse despite continual evolution towards increased cooperative allele frequencies; large populations with a sufficient number of cooperators “spiral” to a stable state of coexistence between cooperator and cheater strategies. The presence of cheaters does not significantly affect the equilibrium population density, but it does reduce the resilience of the population as well as its ability to adapt to a rapidly deteriorating environment. Our results demonstrate the potential ecological importance of coupling between evolutionary dynamics and the population dynamics of cooperatively growing organisms, particularly in microbes. Our study suggests that this interaction may need to be considered in order to explain intraspecific variability in cooperative behaviors, and also that this feedback between evolution and ecology can critically affect the demographic fate

Assessing spatial coupling in complex population dynamics using mutual prediction and continuity statistics

USGS Publications Warehouse

Nichols, J.M.; Moniz, L.; Nichols, J.D.; Pecora, L.M.; Cooch, E.

2005-01-01

A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.

Combining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning

PubMed Central

Epstein, Joshua M.; Pankajakshan, Ramesh; Hammond, Ross A.

2011-01-01

We introduce a novel hybrid of two fields—Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)—as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulating how large, spatially-distributed populations might respond to a physically realistic contaminant plume. We demonstrate the overall feasibility of CFD-ABM evacuation design, using the case of a hypothetical aerosol release in Los Angeles to explore potential effectiveness of various policy regimes. We conclude by arguing that this new approach can be powerfully applied to arbitrary population centers, offering an unprecedented preparedness and catastrophic event response tool. PMID:21687788

Photographic mark-recapture analysis of local dynamics within an open population of dolphins.

PubMed

Fearnbach, H; Durban, J; Parsons, K; Claridge, D

2012-07-01

Identifying demographic changes is important for understanding population dynamics. However, this requires long-term studies of definable populations of distinct individuals, which can be particularly challenging when studying mobile cetaceans in the marine environment. We collected photo-identification data from 19 years (1992-2010) to assess the dynamics of a population of bottlenose dolphins (Tursiops truncatus) restricted to the shallow (<7 m) waters of Little Bahama Bank, northern Bahamas. This population was known to range beyond our study area, so we adopted a Bayesian mixture modeling approach to mark-recapture to identify clusters of individuals that used the area to different extents, and we specifically estimated trends in survival, recruitment, and abundance of a "resident" population with high probabilities of identification. There was a high probability (p= 0.97) of a long-term decrease in the size of this resident population from a maximum of 47 dolphins (95% highest posterior density intervals, HPDI = 29-61) in 1996 to a minimum of just 24 dolphins (95% HPDI = 14-37) in 2009, a decline of 49% (95% HPDI = approximately 5% to approximately 75%). This was driven by low per capita recruitment (average approximately 0.02) that could not compensate for relatively low apparent survival rates (average approximately 0.94). Notably, there was a significant increase in apparent mortality (approximately 5 apparent mortalities vs. approximately 2 on average) in 1999 when two intense hurricanes passed over the study area, with a high probability (p = 0.83) of a drop below the average survival probability (approximately 0.91 in 1999; approximately 0.94, on average). As such, our mark-recapture approach enabled us to make useful inference about local dynamics within an open population of bottlenose dolphins; this should be applicable to other studies challenged by sampling highly mobile individuals with heterogeneous space use.

Population dynamics of HIV-1 inferred from gene sequences.

PubMed Central

Grassly, N C; Harvey, P H; Holmes, E C

1999-01-01

A method for the estimation of population dynamic history from sequence data is described and used to investigate the past population dynamics of HIV-1 subtypes A and B. Using both gag and env gene alignments the effective population size of each subtype is estimated and found to be surprisingly small. This may be a result of the selective sweep of mutations through the population, or may indicate an important role of genetic drift in the fixation of mutations. The implications of these results for the spread of drug-resistant mutations and transmission dynamics, and also the roles of selection and recombination in shaping HIV-1 genetic diversity, are discussed. A larger estimated effective population size for subtype A may be the result of differences in time of origin, transmission dynamics, and/or population structure. To investigate the importance of population structure a model of population subdivision was fitted to each subtype, although the improvement in likelihood was found to be nonsignificant. PMID:9927440

Identifying consumer-resource population dynamics using paleoecological data.

PubMed

Einarsson, Árni; Hauptfleisch, Ulf; Leavitt, Peter R; Ives, Anthony R

2016-02-01

Ecologists have long been fascinated by cyclic population fluctuations, because they suggest strong interactions between exploiter and victim species. Nonetheless, even for populations showing high-amplitude fluctuations, it is often hard to identify which species are the key drivers of the dynamics, because data are generally only available for a single species. Here, we use a paleoecological approach to investigate fluctuations in the midge population in Lake Mývatn, Iceland, which ranges over several orders of magnitude in irregular, multigeneration cycles. Previous circumstantial evidence points to consumer-resource interactions between midges and their primary food, diatoms, as the cause of these high-amplitude fluctuations. Using a pair of sediment cores from the lake, we reconstructed 26 years of dynamics of midges using egg remains and of algal groups using diagnostic pigments. We analyzed these data using statistical methods that account for both the autocorrelated nature of paleoecological data and measurement error caused by the mixing of sediment layers. The analyses revealed a signature of consumer-resource interactions in the fluctuations of midges and diatoms: diatom abundance (as inferred from biomarker pigment diatoxanthin) increased when midge abundance was low, and midge abundance (inferred from egg capsules) decreased when diatom abundance was low. Similar patterns were not found for pigments characterizing the other dominant primary producer group in the lake (cyanobacteria), subdominant algae (cryptophytes), or ubiquitous but chemically unstable biomarkers of total algal abundance (chlorophyll a); however, a significant but weaker pattern was found for the chemically stable indicator of total algal populations (β-carotene) to which diatoms are the dominant contributor. These analyses provide the first paleoecological evaluation of specific trophic interactions underlying high amplitude population fluctuations in lakes.

Animal population dynamics: Identification of critical components

USGS Publications Warehouse

Emlen, J.M.; Pikitch, E.K.

1989-01-01

There is a growing interest in the use of population dynamics models in environmental risk assessment and the promulgation of environmental regulatory policies. Unfortunately, because of species and areal differences in the physical and biotic influences on population dynamics, such models must almost inevitably be both complex and species- or site-specific. Given the emormous variety of species and sites of potential concern, this fact presents a problem; it simply is not possible to construct models for all species and circumstances. Therefore, it is useful, before building predictive population models, to discover what input parameters are of critical importance to the desired output. This information should enable the construction of simpler and more generalizable models. As a first step, it is useful to consider population models as composed to two, partly separable classes, one comprising the purely mechanical descriptors of dynamics from given demographic parameter values, and the other describing the modulation of the demographic parameters by environmental factors (changes in physical environment, species interactions, pathogens, xenobiotic chemicals). This division permits sensitivity analyses to be run on the first of these classes, providing guidance for subsequent model simplification. We here apply such a sensitivity analysis to network models of mammalian and avian population dynamics.

How Resource Phenology Affects Consumer Population Dynamics.

PubMed

Bewick, Sharon; Cantrell, R Stephen; Cosner, Chris; Fagan, William F

2016-02-01

Climate change drives uneven phenology shifts across taxa, and this can result in changes to the phenological match between interacting species. Shifts in the relative phenology of partner species are well documented, but few studies have addressed the effects of such changes on population dynamics. To explore this, we develop a phenologically explicit model describing consumer-resource interactions. Focusing on scenarios for univoltine insects, we show how changes in resource phenology can be reinterpreted as transformations in the year-to-year recursion relationships defining consumer population dynamics. This perspective provides a straightforward path for interpreting the long-term population consequences of phenology change. Specifically, by relating the outcome of phenological shifts to species traits governing recursion relationships (e.g., consumer fecundity or competitive scenario), we demonstrate how changes in relative phenology can force systems into different dynamical regimes, with major implications for resource management, conservation, and other areas of applied dynamics.

Population response to climate change: linear vs. non-linear modeling approaches.

PubMed

Ellis, Alicia M; Post, Eric

2004-03-31

Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.

Modeling sandhill crane population dynamics

USGS Publications Warehouse

Johnson, D.H.

1979-01-01

The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

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...

Dynamics of weakly inhomogeneous oscillator populations: perturbation theory on top of Watanabe-Strogatz integrability

NASA Astrophysics Data System (ADS)

Vlasov, Vladimir; Rosenblum, Michael; Pikovsky, Arkady

2016-08-01

As has been shown by Watanabe and Strogatz (WS) (1993 Phys. Rev. Lett. 70 2391), a population of identical phase oscillators, sine-coupled to a common field, is a partially integrable system: for any ensemble size its dynamics reduce to equations for three collective variables. Here we develop a perturbation approach for weakly nonidentical ensembles. We calculate corrections to the WS dynamics for two types of perturbations: those due to a distribution of natural frequencies and of forcing terms, and those due to small white noise. We demonstrate that in both cases, the complex mean field for which the dynamical equations are written is close to the Kuramoto order parameter, up to the leading order in the perturbation. This supports the validity of the dynamical reduction suggested by Ott and Antonsen (2008 Chaos 18 037113) for weakly inhomogeneous populations.

Leading edge gypsy moth population dynamics

Treesearch

M. R. Carter; F. W. Ravlin; M. L. McManus

1991-01-01

Leading edge gypsy moth populations have been the focus of several intervention programs (MDIPM, AIPM). Knowledge of gypsy moth population dynamics in leading edge area is crucial for effective management. Populations in these areas tend to reach outbreak levels (noticeable defoliation) within three to four years after egg masses are first detected. Pheromone traps...

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.

The dynamics, transmission, and population impacts of avian malaria in native hawaiian birds: A modeling approach

USGS Publications Warehouse

Samuel, M.D.; Hobbelen, P.H.F.; Decastro, F.; Ahumada, J.A.; Lapointe, D.A.; Atkinson, C.T.; Woodworth, B.L.; Hart, P.J.; Duffy, D.C.

2011-01-01

We developed an epidemiological model of avian malaria (Plasmodium relictum) across an altitudinal gradient on the island of Hawaii that includes the dynamics of the host, vector, and parasite. This introduced mosquito-borne disease is hypothesized to have contributed to extinctions and major shifts in the altitudinal distribution of highly susceptible native forest birds. Our goal was to better understand how biotic and abiotic factors influence the intensity of malaria transmission and impact on susceptible populations of native Hawaiian forest birds. Our model illustrates key patterns in the malaria-forest bird system: high malaria transmission in low-elevation forests with minor seasonal or annual variation in infection;episodic transmission in mid-elevation forests with site-to-site, seasonal, and annual variation depending on mosquito dynamics;and disease refugia in high-elevation forests with only slight risk of infection during summer. These infection patterns are driven by temperature and rainfall effects on parasite incubation period and mosquito dynamics across an elevational gradient and the availability of larval habitat, especially in mid-elevation forests. The results from our model suggest that disease is likely a key factor in causing population decline or restricting the distribution of many susceptible Hawaiian species and preventing the recovery of other vulnerable species. The model also provides a framework for the evaluation of factors influencing disease transmission and alternative disease control programs, and to evaluate the impact of climate change on disease cycles and bird populations. ??2011 by the Ecological Society of America.

Dynamics of organic matter and microbial populations in amended soil: a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Gigliotti, Giovanni; Pezzolla, Daniela; Zadra, Claudia; Albertini, Emidio; Marconi, Gianpiero; Turchetti, Benedetta; Buzzini, Pietro

2013-04-01

The application of organic amendments to soils, such as pig slurry, sewage sludge and compost is considered a tool for improving soil fertility and enhancing C stock. The addition of these different organic materials allows a good supply of nutrients for plants but also contributes to C sequestration, affects the microbial activity and the transformation of soil organic matter (SOM). Moreover, the addition of organic amendment has gained importance as a source of greenhouse gas (GHG) emissions and then as a cause of the "Global Warming". Therefore, it is important to investigate the factors controlling the SOM mineralization in order to improve soil C sequestration and decreasing at the same time the GHG emissions. The quality of organic matter added to the soil will play an important role in these dynamics, affecting the microbial activity and the changes in microbial community structure. A laboratory, multidisciplinary experiment was carried out to test the effect of the amendment by anaerobic digested livestock-derived organic materials on labile organic matter evolution and on dynamics of microbial population, this latter both in terms of consistence of microbial biomass, as well as in terms of microbial biodiversity. Different approaches were used to study the microbial community structure: chemical (CO2 fluxes, WEOC, C-biomass, PLFA), microbiological (microbial enumeration) and molecular (DNA extraction and Roche 454, Next Generation Sequencing, NGS). The application of fresh digestate, derived from the anaerobic treatment of animal wastes, affected the short-term dynamics of microbial community, as reflected by the increase of CO2 emissions immediately after the amendment compared to the control soil. This is probably due to the addition of easily available C added with the digestate, demonstrating that this organic material was only partially stabilized by the anaerobic process. In fact, the digestate contained a high amounts of available C, which led to

Assessing tiger population dynamics using photographic capture-recapture sampling

USGS Publications Warehouse

Karanth, K.U.; Nichols, J.D.; Kumar, N.S.; Hines, J.E.

2006-01-01

healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

Assessing tiger population dynamics using photographic capture-recapture sampling.

PubMed

Karanth, K Ullas; Nichols, James D; Kumar, N Samba; Hines, James E

2006-11-01

that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

Connecting micro dynamics and population distributions in system dynamics models

PubMed Central

Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

2014-01-01

Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

USGS Publications Warehouse

Miller, David A.; Clark, W.R.; Arnold, S.J.; Bronikowski, A.M.

2011-01-01

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (??s) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on ?? s. The magnitude of variation in the proportion of gravid females and its effect on ??s was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on ??s was 4- 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories.

PubMed

Miller, David A; Clark, William R; Arnold, Stevan J; Bronikowski, Anne M

2011-08-01

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of

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.

Population dynamics of aberrant chromosome 1 in mice.

PubMed

Sabantsev, I; Spitsin, O; Agulnik, S; Ruvinsky, A

1993-05-01

Natural populations of two semispecies of house mouse, Mus musculus domesticus and M.m. musculus, were found to be polymorphic for an aberrant chromosome 1 bearing a large inserted block of homogeneously staining heterochromatin. Strong meiotic drive for the aberrant chromosome from M.m. musculus was previously observed in heterozygous female mice. There are at least three meiotic drive levels determined by different allelic variants of distorter. Homozygotes had low viability and females showed low fertility. Both homo- and heterozygous males had normal fertility and their segregation patterns did not deviate from normal. Computer simulations were performed of the dynamics of aberrant chromosome 1 in demes and populations. The data demonstrate that a spontaneous mutation (inversion) of an aberrant chromosome 1, once arisen, has a high probability of spreading in a population at high coefficients of meiotic drive and migration. In the long-term, the population attains a stationary state which is determined by the drive level and migration intensity. The state of stable genotypic equilibrium is independent of deme and population size, as well as of the initial concentration of the aberrant chromosome. As populations initially polymorphic for the distorters approach the stationary state, the stronger distorter is eliminated. The frequencies of the aberrant chromosome determined by computer analysis agree well with those obtained for the studied Asian M.m. musculus populations. The evolutionary pathways for the origin and fixation of the aberrant chromosome in natural populations are considered.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

Stage-Structured Population Dynamics of AEDES AEGYPTI

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Budin, Harun; Ismail, Salemah

Aedes aegypti is the main vector in the transmission of dengue fever, a vector-borne disease affecting world population living in tropical and sub-tropical countries. Better understanding of the dynamics of its population growth will help in the efforts of controlling the spread of this disease. In looking at the population dynamics of Aedes aegypti, this paper explored the stage-structured modeling of the population growth of the mosquito using the matrix population model. The life cycle of the mosquito was divided into five stages: eggs, larvae, pupae, adult1 and adult2. Developmental rates were obtained for the average Malaysian temperature and these were used in constructing the transition matrix for the matrix model. The model, which was based only on temperature, projected that the population of Aedes aegypti will blow up with time, which is not realistic. For further work, other factors need to be taken into account to obtain a more realistic result.

Spiking, Bursting, and Population Dynamics in a Network of Growth Transform Neurons.

PubMed

Gangopadhyay, Ahana; Chakrabartty, Shantanu

2018-06-01

This paper investigates the dynamical properties of a network of neurons, each of which implements an asynchronous mapping based on polynomial growth transforms. In the first part of this paper, we present a geometric approach for visualizing the dynamics of the network where each of the neurons traverses a trajectory in a dual optimization space, whereas the network itself traverses a trajectory in an equivalent primal optimization space. We show that as the network learns to solve basic classification tasks, different choices of primal-dual mapping produce unique but interpretable neural dynamics like noise shaping, spiking, and bursting. While the proposed framework is general enough, in this paper, we demonstrate its use for designing support vector machines (SVMs) that exhibit noise-shaping properties similar to those of modulators, and for designing SVMs that learn to encode information using spikes and bursts. It is demonstrated that the emergent switching, spiking, and burst dynamics produced by each neuron encodes its respective margin of separation from a classification hyperplane whose parameters are encoded by the network population dynamics. We believe that the proposed growth transform neuron model and the underlying geometric framework could serve as an important tool to connect well-established machine learning algorithms like SVMs to neuromorphic principles like spiking, bursting, population encoding, and noise shaping.

Prediction of population with Alzheimer's disease in the European Union using a system dynamics model.

PubMed

Tomaskova, Hana; Kuhnova, Jitka; Cimler, Richard; Dolezal, Ondrej; Kuca, Kamil

2016-01-01

Alzheimer's disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled. The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation. For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat. Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million. System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions.

Complex Population Dynamics and the Coalescent Under Neutrality

PubMed Central

Volz, Erik M.

2012-01-01

Estimates of the coalescent effective population size Ne can be poorly correlated with the true population size. The relationship between Ne and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of Ne such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics. PMID:22042576

Population dynamics in non-homogeneous environments

NASA Astrophysics Data System (ADS)

Alards, Kim M. J.; Tesser, Francesca; Toschi, Federico

2014-11-01

For organisms living in aquatic ecosystems the presence of fluid transport can have a strong influence on the dynamics of populations and on evolution of species. In particular, displacements due to self-propulsion, summed up with turbulent dispersion at larger scales, strongly influence the local densities and thus population and genetic dynamics. Real marine environments are furthermore characterized by a high degree of non-homogeneities. In the case of population fronts propagating in ``fast'' turbulence, with respect to the population duplication time, the flow effect can be studied by replacing the microscopic diffusivity with an effective turbulent diffusivity. In the opposite case of ``slow'' turbulence the advection by the flow has to be considered locally. Here we employ numerical simulations to study the influence of non-homogeneities in the diffusion coefficient of reacting individuals of different species expanding in a 2 dimensional space. Moreover, to explore the influence of advection, we consider a population expanding in the presence of simple velocity fields like cellular flows. The output is analyzed in terms of front roughness, front shape, propagation speed and, concerning the genetics, by means of heterozygosity and local and global extinction probabilities.

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

PubMed

McKay, Virginia R; Hoffer, Lee D; Combs, Todd B; Margaret Dolcini, M

2018-06-05

Sustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods. We used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables. Higher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years. Human resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on

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.

Nonlinear Relaxation in Population Dynamics

NASA Astrophysics Data System (ADS)

Cirone, Markus A.; de Pasquale, Ferdinando; Spagnolo, Bernardo

We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the ith population and on the distribution of the population and of the local field.

Relationship between ancient bridges and population dynamics in the lower Yangtze River Basin, China.

PubMed

Zhao, Yang; Jia, Xin; Lee, Harry F; Zhao, Hongqiang; Cai, Shuliang; Huang, Xianjin

2017-01-01

It has been suggested that population growth dynamics may be revealed by the geographic distribution and the physical structure of ancient bridges. Yet, this relationship has not been empirically verified. In this study, we applied the archaeological records for ancient bridges to reveal the population growth dynamics in the lower Yangtze River Basin in late imperial China. We investigated 89 ancient bridges in Yixing that were built during the Ming and Qing dynasties (AD1368-1911). Global Position System information and structure (length, width, and span) of those bridges was measured during our field investigations. Their distribution density was calculated by ArcGIS. The historical socio-economic dynamics of Yixing was inferred from the distribution and structure of ancient bridges. Based on the above information, the population growth dynamics in Yixing was projected. Our results show that 77 bridges were built in Yixing during the Qing dynasty, which is 6.41 times more than the number built during the Ming dynasty. In the Ming dynasty, bridges were built on pivotal routes; in the Qing dynasty, bridges were scattered across various places. Over the period, the density distribution of bridges shifted northwestward, while the average length and width of bridges decreased. The increasing number of bridges corresponded to population growth, largely attributable to massive clan migration from northern China during the Little Ice Age. The shift in the density distribution of bridges corresponded to the formation of settlements of large clans and the blossoming of Yixing Teapot handicrafts. The scattering and the reduction in average length and width of bridges was due to the dispersal of population and the associated formation of small settlements in the latter period. Our approach is innovative and robust, and could be employed to recover long-term historical population growth dynamics in other parts of China.

Relationship between ancient bridges and population dynamics in the lower Yangtze River Basin, China

PubMed Central

Zhao, Yang; Lee, Harry F.; Zhao, Hongqiang; Cai, Shuliang; Huang, Xianjin

2017-01-01

It has been suggested that population growth dynamics may be revealed by the geographic distribution and the physical structure of ancient bridges. Yet, this relationship has not been empirically verified. In this study, we applied the archaeological records for ancient bridges to reveal the population growth dynamics in the lower Yangtze River Basin in late imperial China. We investigated 89 ancient bridges in Yixing that were built during the Ming and Qing dynasties (AD1368–1911). Global Position System information and structure (length, width, and span) of those bridges was measured during our field investigations. Their distribution density was calculated by ArcGIS. The historical socio-economic dynamics of Yixing was inferred from the distribution and structure of ancient bridges. Based on the above information, the population growth dynamics in Yixing was projected. Our results show that 77 bridges were built in Yixing during the Qing dynasty, which is 6.41 times more than the number built during the Ming dynasty. In the Ming dynasty, bridges were built on pivotal routes; in the Qing dynasty, bridges were scattered across various places. Over the period, the density distribution of bridges shifted northwestward, while the average length and width of bridges decreased. The increasing number of bridges corresponded to population growth, largely attributable to massive clan migration from northern China during the Little Ice Age. The shift in the density distribution of bridges corresponded to the formation of settlements of large clans and the blossoming of Yixing Teapot handicrafts. The scattering and the reduction in average length and width of bridges was due to the dispersal of population and the associated formation of small settlements in the latter period. Our approach is innovative and robust, and could be employed to recover long-term historical population growth dynamics in other parts of China. PMID:28792976

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

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.

An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: combining index and demographic data.

USGS Publications Warehouse

Davis, Amy J.; Hooten, Mevin B.; Phillips, Michael L.; Doherty, Paul F.

2014-01-01

Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.

Building dynamic population graph for accurate correspondence detection.

PubMed

Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

2015-12-01

In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantum electron-vibrational dynamics at finite temperature: Thermo field dynamics approach

NASA Astrophysics Data System (ADS)

Borrelli, Raffaele; Gelin, Maxim F.

2016-12-01

Quantum electron-vibrational dynamics in molecular systems at finite temperature is described using an approach based on the thermo field dynamics theory. This formulation treats temperature effects in the Hilbert space without introducing the Liouville space. A comparison with the theoretically equivalent density matrix formulation shows the key numerical advantages of the present approach. The solution of thermo field dynamics equations with a novel technique for the propagation of tensor trains (matrix product states) is discussed. Numerical applications to model spin-boson systems show that the present approach is a promising tool for the description of quantum dynamics of complex molecular systems at finite temperature.

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.

Effects of an invasive plant on population dynamics in toads.

PubMed

Greenberg, Daniel A; Green, David M

2013-10-01

When populations decline in response to unfavorable environmental change, the dynamics of their population growth shift. In populations that normally exhibit high levels of variation in recruitment and abundance, as do many amphibians, declines may be difficult to identify from natural fluctuations in abundance. However, the onset of declines may be evident from changes in population growth rate in sufficiently long time series of population data. With data from 23 years of study of a population of Fowler's toad (Anaxyrus [ = Bufo] fowleri) at Long Point, Ontario (1989-2011), we sought to identify such a shift in dynamics. We tested for trends in abundance to detect a change point in population dynamics and then tested among competing population models to identify associated intrinsic and extrinsic factors. The most informative models of population growth included terms for toad abundance and the extent of an invasive marsh plant, the common reed (Phragmites australis), throughout the toads' marshland breeding areas. Our results showed density-dependent growth in the toad population from 1989 through 2002. After 2002, however, we found progressive population decline in the toads associated with the spread of common reeds and consequent loss of toad breeding habitat. This resulted in reduced recruitment and population growth despite the lack of significant loss of adult habitat. Our results underscore the value of using long-term time series to identify shifts in population dynamics coincident with the advent of population decline. © 2013 Society for Conservation Biology.

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.

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.

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.

A spatial age-structured model for describing sea lamprey (Petromyzon marinus) population dynamics

USGS Publications Warehouse

Robinson, Jason M.; Wilberg, Michael J.; Adams, Jean V.; Jones, Michael L.

2013-01-01

The control of invasive sea lampreys (Petromyzon marinus) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.

The dynamical systems approach to numerical integration

NASA Astrophysics Data System (ADS)

Wisdom, Jack

2018-03-01

The dynamical systems approach to numerical integration is reviewed and extended. The new method is compared to some alternative methods based on the Lie series approach. The test problem is the motion of the outer planets. The algorithms developed using the dynamical systems approach perform well.

Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culcidae), along an elevational gradient in Hawaii

USGS Publications Warehouse

Ahumada, Jorge A.; LaPointe, Dennis; Samuel, Michael D.

2004-01-01

We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere.

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

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.

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

2016-08-01

The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

Stochastic Gain in Population Dynamics

NASA Astrophysics Data System (ADS)

Traulsen, Arne; Röhl, Torsten; Schuster, Heinz Georg

2004-07-01

We introduce an extension of the usual replicator dynamics to adaptive learning rates. We show that a population with a dynamic learning rate can gain an increased average payoff in transient phases and can also exploit external noise, leading the system away from the Nash equilibrium, in a resonancelike fashion. The payoff versus noise curve resembles the signal to noise ratio curve in stochastic resonance. Seen in this broad context, we introduce another mechanism that exploits fluctuations in order to improve properties of the system. Such a mechanism could be of particular interest in economic systems.

Predicting population dynamics from the properties of individuals: a cross-level test of dynamic energy budget theory.

PubMed

Martin, Benjamin T; Jager, Tjalling; Nisbet, Roger M; Preuss, Thomas G; Grimm, Volker

2013-04-01

Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individual-based model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology.

Urban aerosols harbor diverse and dynamic bacterial populations

PubMed Central

Brodie, Eoin L.; DeSantis, Todd Z.; Parker, Jordan P. Moberg; Zubietta, Ingrid X.; Piceno, Yvette M.; Andersen, Gary L.

2007-01-01

Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe. PMID:17182744

Estimating Traveler Populations at Airport and Cruise Terminals for Population Distribution and Dynamics

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

Jochem, Warren C; Sims, Kelly M; Bright, Eddie A

In recent years, uses of high-resolution population distribution databases are increasing steadily for environmental, socioeconomic, public health, and disaster-related research and operations. With the development of daytime population distribution, temporal resolution of such databases has been improved. However, the lack of incorporation of transitional population, namely business and leisure travelers, leaves a significant population unaccounted for within the critical infrastructure networks, such as at transportation hubs. This paper presents two general methodologies for estimating passenger populations in airport and cruise port terminals at a high temporal resolution which can be incorporated into existing population distribution models. The methodologies are geographicallymore » scalable and are based on, and demonstrate how, two different transportation hubs with disparate temporal population dynamics can be modeled utilizing publicly available databases including novel data sources of flight activity from the Internet which are updated in near-real time. The airport population estimation model shows great potential for rapid implementation for a large collection of airports on a national scale, and the results suggest reasonable accuracy in the estimated passenger traffic. By incorporating population dynamics at high temporal resolutions into population distribution models, we hope to improve the estimates of populations exposed to or at risk to disasters, thereby improving emergency planning and response, and leading to more informed policy decisions.« less

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.

A framework for studying transient dynamics of population projection matrix models.

PubMed

Stott, Iain; Townley, Stuart; Hodgson, David James

2011-09-01

Empirical models are central to effective conservation and population management, and should be predictive of real-world dynamics. Available modelling methods are diverse, but analysis usually focuses on long-term dynamics that are unable to describe the complicated short-term time series that can arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor of transient population density, but criticises the utility of established indices of convergence times. Our findings should guide further development of analyses of transient population dynamics using PPMs or other empirical modelling techniques. © 2011 Blackwell Publishing Ltd/CNRS.

An Approach for Dynamic Grids

NASA Technical Reports Server (NTRS)

Slater, John W.; Liou, Meng-Sing; Hindman, Richard G.

1994-01-01

An approach is presented for the generation of two-dimensional, structured, dynamic grids. The grid motion may be due to the motion of the boundaries of the computational domain or to the adaptation of the grid to the transient, physical solution. A time-dependent grid is computed through the time integration of the grid speeds which are computed from a system of grid speed equations. The grid speed equations are derived from the time-differentiation of the grid equations so as to ensure that the dynamic grid maintains the desired qualities of the static grid. The grid equations are the Euler-Lagrange equations derived from a variational statement for the grid. The dynamic grid method is demonstrated for a model problem involving boundary motion, an inviscid flow in a converging-diverging nozzle during startup, and a viscous flow over a flat plate with an impinging shock wave. It is shown that the approach is more accurate for transient flows than an approach in which the grid speeds are computed using a finite difference with respect to time of the grid. However, the approach requires significantly more computational effort.

Predator-prey-subsidy population dynamics on stepping-stone domains with dispersal delays.

PubMed

Eide, Ragna M; Krause, Andrew L; Fadai, Nabil T; Van Gorder, Robert A

2018-08-14

We examine the role of the travel time of a predator along a spatial network on predator-prey population interactions, where the predator is able to partially or fully sustain itself on a resource subsidy. The impact of access to food resources on the stability and behaviour of the predator-prey-subsidy system is investigated, with a primary focus on how incorporating travel time changes the dynamics. The population interactions are modelled by a system of delay differential equations, where travel time is incorporated as discrete delay in the network diffusion term in order to model time taken to migrate between spatial regions. The model is motivated by the Arctic ecosystem, where the Arctic fox consumes both hunted lemming and scavenged seal carcass. The fox travels out on sea ice, in addition to quadrennially migrating over substantial distances. We model the spatial predator-prey-subsidy dynamics through a "stepping-stone" approach. We find that a temporal delay alone does not push species into extinction, but rather may stabilize or destabilize coexistence equilibria. We are able to show that delay can stabilize quasi-periodic or chaotic dynamics, and conclude that the incorporation of dispersal delay has a regularizing effect on dynamics, suggesting that dispersal delay can be proposed as a solution to the paradox of enrichment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Population and coherence dynamics in light harvesting complex II (LH2).

PubMed

Yeh, Shu-Hao; Zhu, Jing; Kais, Sabre

2012-08-28

The electronic excitation population and coherence dynamics in the chromophores of the photosynthetic light harvesting complex 2 (LH2) B850 ring from purple bacteria (Rhodopseudomonas acidophila) have been studied theoretically at both physiological and cryogenic temperatures. Similar to the well-studied Fenna-Matthews-Olson (FMO) protein, oscillations of the excitation population and coherence in the site basis are observed in LH2 by using a scaled hierarchical equation of motion approach. However, this oscillation time (300 fs) is much shorter compared to the FMO protein (650 fs) at cryogenic temperature. Both environment and high temperature are found to enhance the propagation speed of the exciton wave packet yet they shorten the coherence time and suppress the oscillation amplitude of coherence and the population. Our calculations show that a long-lived coherence between chromophore electronic excited states can exist in such a noisy biological environment.

The model of fungal population dynamics affected by nystatin

NASA Astrophysics Data System (ADS)

Voychuk, Sergei I.; Gromozova, Elena N.; Sadovskiy, Mikhail G.

Fungal diseases are acute problems of the up-to-day medicine. Significant increase of resistance of microorganisms to the medically used antibiotics and a lack of new effective drugs follows in a growth of dosage of existing chemicals to solve the problem. Quite often such approach results in side effects on humans. Detailed study of fungi-antibiotic dynamics can identify new mechanisms and bring new ideas to overcome the microbial resistance with a lower dosage of antibiotics. In this study, the dynamics of the microbial population under antibiotic treatment was investigated. The effects of nystatin on the population of Saccharomyces cerevisiae yeasts were used as a model system. Nystatin effects were investigated both in liquid and solid media by viability tests. Dependence of nystatin action on osmotic gradient was evaluated in NaCl solutions. Influences of glucose and yeast extract were additionally analyzed. A "stepwise" pattern of the cell death caused by nystatin was the most intriguing. This pattern manifested in periodical changes of the stages of cell death against stages of resistance to the antibiotic. The mathematical model was proposed to describe cell-antibiotic interactions and nystatin viability effects in the liquid medium. The model implies that antibiotic ability to cause a cells death is significantly affected by the intracellular compounds, which came out of cells after their osmotic barriers were damaged

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

NASA Astrophysics Data System (ADS)

Pizzolato, Nicola; Valenti, Davide; Adorno, Dominique Persano; Spagnolo, Bernardo

2009-09-01

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.

Stochastic population dynamic models as probability networks

Treesearch

M.E. and D.C. Lee Borsuk

2009-01-01

The dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and...

Modeling the population dynamics of Pacific yew.

Treesearch

Richard T. Busing; Thomas A. Spies

1995-01-01

A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-growth forest stands. Diameter growth at breast height ranged from 0 to 3 centimeters per decade...

AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

EPA Science Inventory

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

Numerical modeling of mosquito population dynamics of Aedes aegypti.

PubMed

Yamashita, William M S; Das, Shyam S; Chapiro, Grigori

2018-04-16

The global incidences of dengue virus have increased the interest in studying and understanding the mosquito population dynamics. It is predominantly spread by Aedes aegypti in the tropical and sub-tropical countries in the world. Understanding these dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. For this reason, a new model has been proposed to investigate the population dynamics of mosquitoes in a city. The present paper discusses the numerical modeling of population dynamics of Ae. aegypti mosquitoes in an urban neighborhood of a city using the finite volume method. The model describes how populations spread through the city assisted by the wind. This model allows incorporating external factors (wind and chemical insecticides) and topography data (streets, building blocks, parks, forests and beach). The proposed model has been successfully tested in examples involving two Brazilian cities (City center, Juiz de Fora and Copacabana Beach, Rio de Janeiro). Invasion phenomena of Ae. aegypti mosquitoes have been observed in each of the simulations. It was observed that, inside the blocks, the growth of the population for both winged and aquatic phase causes an infestation of Ae. aegypti in a short time. Within the blocks the mosquito population was concentrated and diffused slowly. In the streets, there was a long-distance spread, which was influenced by wind and diffusion with a low concentration of mosquito population. The model was also tested taking into account chemical insecticides spread in two different configurations. It has been observed that the insecticides have a significant effect on the mosquito population for both winged and aquatic phases when the chemical insecticides spread more uniformly along all the streets in a neighborhood of a city. The presented methodology can be employed to evaluate and to understand the epidemic risks in a specific

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

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.

Diversity waves in collapse-driven population dynamics

DOE PAGES

Maslov, Sergei; Sneppen, Kim

2015-09-14

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more » by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less

Diversity waves in collapse-driven population dynamics

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

Maslov, Sergei; Sneppen, Kim

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g.more » by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.« less

Population dynamics in an intermittent refuge

NASA Astrophysics Data System (ADS)

Colombo, E. H.; Anteneodo, C.

2016-10-01

Population dynamics is constrained by the environment, which needs to obey certain conditions to support population growth. We consider a standard model for the evolution of a single species population density, which includes reproduction, competition for resources, and spatial spreading, while subject to an external harmful effect. The habitat is spatially heterogeneous, there existing a refuge where the population can be protected. Temporal variability is introduced by the intermittent character of the refuge. This scenario can apply to a wide range of situations, from a laboratory setting where bacteria can be protected by a blinking mask from ultraviolet radiation, to large-scale ecosystems, like a marine reserve where there can be seasonal fishing prohibitions. Using analytical and numerical tools, we investigate the asymptotic behavior of the total population as a function of the size and characteristic time scales of the refuge. We obtain expressions for the minimal size required for population survival, in the slow and fast time scale limits.

Temperature-driven regime shifts in the dynamics of size-structured populations.

PubMed

Ohlberger, Jan; Edeline, Eric; Vøllestad, Leif Asbjørn; Stenseth, Nils C; Claessen, David

2011-02-01

Global warming impacts virtually all biota and ecosystems. Many of these impacts are mediated through direct effects of temperature on individual vital rates. Yet how this translates from the individual to the population level is still poorly understood, hampering the assessment of global warming impacts on population structure and dynamics. Here, we study the effects of temperature on intraspecific competition and cannibalism and the population dynamical consequences in a size-structured fish population. We use a physiologically structured consumer-resource model in which we explicitly model the temperature dependencies of the consumer vital rates and the resource population growth rate. Our model predicts that increased temperature decreases resource density despite higher resource growth rates, reflecting stronger intraspecific competition among consumers. At a critical temperature, the consumer population dynamics destabilize and shift from a stable equilibrium to competition-driven generation cycles that are dominated by recruits. As a consequence, maximum age decreases and the proportion of younger and smaller-sized fish increases. These model predictions support the hypothesis of decreasing mean body sizes due to increased temperatures. We conclude that in size-structured fish populations, global warming may increase competition, favor smaller size classes, and induce regime shifts that destabilize population and community dynamics.

Impacts of environmental variability on desiccation rate, plastic responses and population dynamics of Glossina pallidipes.

PubMed

Kleynhans, E; Clusella-Trullas, S; Terblanche, J S

2014-02-01

Physiological responses to transient conditions may result in costly responses with little fitness benefits, and therefore, a trade-off must exist between the speed of response and the duration of exposure to new conditions. Here, using the puparia of an important insect disease vector, Glossina pallidipes, we examine this potential trade-off using a novel combination of an experimental approach and a population dynamics model. Specifically, we explore and dissect the interactions between plastic physiological responses, treatment-duration and -intensity using an experimental approach. We then integrate these experimental results from organismal water-balance data and their plastic responses into a population dynamics model to examine the potential relative fitness effects of simulated transient weather conditions on population growth rates. The results show evidence for the predicted trade-off for plasticity of water loss rate (WLR) and the duration of new environmental conditions. When altered environmental conditions lasted for longer durations, physiological responses could match the new environmental conditions, and this resulted in a lower WLR and lower rates of population decline. At shorter time-scales however, a mismatch between acclimation duration and physiological responses was reflected by reduced overall population growth rates. This may indicate a potential fitness cost due to insufficient time for physiological adjustments to take place. The outcomes of this work therefore suggest plastic water balance responses have both costs and benefits, and these depend on the time-scale and magnitude of variation in environmental conditions. These results are significant for understanding the evolution of plastic physiological responses and changes in population abundance in the context of environmental variability. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Population pressure on coral atolls: trends and approaching limits.

PubMed

Rapaport, M

1990-09-01

Trends and approaching limits of population pressure on coral atolls is discussed by examining the atoll environment in terms of the physical geography, the production systems, and resource distribution. Atoll populations are grouped as dependent and independent, and demographic trends in population growth, migraiton, urbanization, and political dependency are reviewed. Examination of the carrying capacity includes a dynamic model, the influences of the West, and philopsophical considerations. The carrying capacity is the "maximal population supportable in a given area". Traditional models are criticized because of a lack in accounting for external linkages. The proposed model is dynamic and considers perceived needs and overseas linkages. It also explains regional disparities in population distribution, and provides a continuing model for population movement from outer islands to district centers and mainland areas. Because of increased expectations and perceived needs, there is a lower carrying capacity for outlying areas, and expanded capacity in district centers. This leads to urbanization, emigration, and carrying capacity overshot in regional and mainland areas. Policy intervention is necessary at the regional and island community level. Atolls, which are islands surrounding deep lagoons, exist in archipelagoes across the oceans, and are rich in aquatic life. The balance in this small land area with a vulnerable ecosystem may be easily disturbed by scarce water supplies, barren soils, rising sea levels in the future, hurricanes, and tsunamis. Traditionally, fisheries and horticulture (pit-taro, coconuts, and breadfruit) have sustained populations, but modern influences such as blasting, reef mining, new industrial technologies, population pressure, and urbanization threaten the balance. Population pressure, which has lead to pollution, epidemics, malnutrition, crime, social disintegration, and foreign dependence, is evidenced in the areas of Tuvalu, Kiribati

Human population dynamics in Europe over the Last Glacial Maximum.

PubMed

Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

2015-07-07

The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.

Population Density and Moment-based Approaches to Modeling Domain Calcium-mediated Inactivation of L-type Calcium Channels.

PubMed

Wang, Xiao; Hardcastle, Kiah; Weinberg, Seth H; Smith, Gregory D

2016-03-01

We present a population density and moment-based description of the stochastic dynamics of domain [Formula: see text]-mediated inactivation of L-type [Formula: see text] channels. Our approach accounts for the effect of heterogeneity of local [Formula: see text] signals on whole cell [Formula: see text] currents; however, in contrast with prior work, e.g., Sherman et al. (Biophys J 58(4):985-995, 1990), we do not assume that [Formula: see text] domain formation and collapse are fast compared to channel gating. We demonstrate the population density and moment-based modeling approaches using a 12-state Markov chain model of an L-type [Formula: see text] channel introduced by Greenstein and Winslow (Biophys J 83(6):2918-2945, 2002). Simulated whole cell voltage clamp responses yield an inactivation function for the whole cell [Formula: see text] current that agrees with the traditional approach when domain dynamics are fast. We analyze the voltage-dependence of [Formula: see text] inactivation that may occur via slow heterogeneous domain [[Formula: see text

Hamiltonian approach to slip-stacking dynamics

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

Lee, S. Y.; Ng, K. Y.

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. As a result, the dynamics can also be applied to other accelerator complexes.

Hamiltonian approach to slip-stacking dynamics

DOE PAGES

Lee, S. Y.; Ng, K. Y.

2017-06-29

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. As a result, the dynamics can also be applied to other accelerator complexes.

Predator-prey-subsidy population dynamics on stepping-stone domains.

PubMed

Shen, Lulan; Van Gorder, Robert A

2017-05-07

Predator-prey-subsidy dynamics on stepping-stone domains are examined using a variety of network configurations. Our problem is motivated by the interactions between arctic foxes (predator) and lemmings (prey) in the presence of seal carrion (subsidy) provided by polar bears. We use the n-Patch Model, which considers space explicitly as a "Stepping Stone" system. We consider the role that the carrying capacity, predator migration rate, input subsidy rate, predator mortality rate, and proportion of predators surviving migration play in the predator-prey-subsidy population dynamics. We find that for certain types of networks, added mobility will help predator populations, allowing them to survive or coexist when they would otherwise go extinct if confined to one location, while in other situations (such as when sparsely distributed nodes in the network have few resources available) the added mobility will hurt the predator population. We also find that a combination of favourable conditions for the prey and subsidy can lead to the formation of limit cycles (boom and bust dynamic) from stable equilibrium states. These modifications to the dynamics vary depending on the specific network structure employed, highlighting the fact that network structure can strongly influence the predator-prey-subsidy dynamics in stepping-stone domains. Copyright © 2017 Elsevier Ltd. All rights reserved.

A necessary condition for dispersal driven growth of populations with discrete patch dynamics.

PubMed

Guiver, Chris; Packman, David; Townley, Stuart

2017-07-07

We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bacterial population dynamics during uranium reduction andre-oxidation: Application of a novel high density oligonucleotidemicroarray approach

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

Brodie, Eoin L.; DeSantis, Todd Z.; Joyner, Dominique C.

2006-01-30

Reduction of soluble uranium U(VI) to less-soluble uraniumU(IV) is a promising approach to minimize migration from contaminatedaquifers. It is generally assumed that, under constant reducingconditions, U(IV) is stable and immobile; however, in a previous study,we documented reoxidation of U(IV) under continuous reducing conditions(Wan et al., Environ. Sci. Technol. 2005, 39:6162 6169). To determine ifchanges in microbial community composition were a factor in U(IV)reoxidation, we employed a high-density phylogenetic DNA microarray (16Smicroarray) containing 500,000 probes to monitor changes in bacterialpopulations during this remediation process. Comparison of the 16Smicroarray with clone libraries demonstrated successful detection andclassification of most clone groups. Analysis ofmore » the most dynamic groupsof 16S rRNA gene amplicons detected by the 16S microarray identified fiveclusters of bacterial subfamilies responding in a similar manner. Thisapproach demonstrated that amplicons of known metal-reducing bacteriasuch as Geothrix fermentans (confirmed by quantitative PCR) and thosewithin the Geobacteraceae were abundant during U(VI) reduction and didnot decline during the U(IV) reoxidation phase. Significantly, it appearsthat the observed reoxidation of uranium under reducing conditionsoccurred despite elevated microbial activity and the consistent presenceof metal-reducing bacteria. High-density phylogenetic microarraysconstitute a powerful tool, enabling the detection and monitoring of asubstantial portion of the microbial population in a routine, accurate,and reproducible manner.« less

Population dynamics of rural Ethiopia.

PubMed

Bariabagar, H

1978-01-01

2 rounds of the national sample surveys, conducted by the central statistical office of Ethiopia during 1964-1967 and 1969-1971, provide the only comprehensive demographic data for the country and are the basis for this discussion of rural Ethiopia's population dynamics. The population of Ethiopia is predominantly rural. Agglomerations of 2000 and over inhabitants constitute about 14% of the population, and this indicates that Ethiopia has a low level of urbanization. In rural Ethiopia, international migration was negligent in the 1970's and the age structure can be assumed to be the results of past trends of fertility and mortality conditions. The reported crude birthrate (38.2), crude death rate (12.3) and infant mortality rate (90) of rural Ethiopia fall short of the averages for African countries. Prospects of population growth of rural Ethiopia would be immense. At the rate of natural increase of between 2.4 and 3.0% per annum, the population would double in 24-29 years. Regarding population issues, the programs of the National Democratic Revolution of Ethiopia faces the following main challenging problems: 1) carrying out national population censuses in order to obtain basic information for socialist planning; 2) minimizing or curtailing the existing high urban growth rates; 3) reducing rapidly growing population; and 5) mobilizing Ethiopian women to participate in the social, economic and political life of the country in order to create favorable conditions for future fertility reduction.

Dynamic regime of coherent population trapping and optimization of frequency modulation parameters in atomic clocks.

PubMed

Yudin, V I; Taichenachev, A V; Basalaev, M Yu; Kovalenko, D V

2017-02-06

We theoretically investigate the dynamic regime of coherent population trapping (CPT) in the presence of frequency modulation (FM). We have formulated the criteria for quasi-stationary (adiabatic) and dynamic (non-adiabatic) responses of atomic system driven by this FM. Using the density matrix formalism for Λ system, the error signal is exactly calculated and optimized. It is shown that the optimal FM parameters correspond to the dynamic regime of atomic-field interaction, which significantly differs from conventional description of CPT resonances in the frame of quasi-stationary approach (under small modulation frequency). Obtained theoretical results are in good qualitative agreement with different experiments. Also we have found CPT-analogue of Pound-Driver-Hall regime of frequency stabilization.

Giant panda (Ailuropoda melanoleuca) population dynamics and bamboo (subfamily Bambusoideae) life history: a structured population approach to examining carrying capacity when the prey are semelparous

USGS Publications Warehouse

Carter, J.; Ackleh, A.S.; Leonard, B.P.; Wang, Hongfang

1999-01-01

The giant panda, Ailuropoda melanoleuca, is a highly specialized Ursid whose diet consists almost entirely of various species of bamboo. Bamboo (Bambusoideae) is a grass subfamily whose species often exhibit a synchronous semelparity. Synchronous semelparity can create local drops in carrying capacity for the panda. We modeled the interaction of pandas and their bamboo food resources with an age structured panda population model linked to a natural history model of bamboo biomass dynamics based on literature values of bamboo biomass, and giant panda life history dynamics. This paper reports the results of our examination of the interaction between pandas and their bamboo food resource and its implications for panda conservation. In the model all panda populations were well below the carrying capacity of the habitat. The giant panda populations growth was most sensitive to changes in birth rates and removal of reproductive aged individuals. Periodic starvation that has been documented in conjunction with bamboo die-offs is probably related to the inability to move to other areas within the region where bamboo is still available. Based on the results of this model, giant panda conservation should concentrate on keeping breeding individuals in the wild, keep corridors to different bamboo species open to pandas, and to concentrate research on bamboo life history.

A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic

NASA Astrophysics Data System (ADS)

Gariazzo, Claudio; Pelliccioni, Armando; Bolignano, Andrea

2016-04-01

A dynamic city-wide air pollution exposure assessment study has been carried out for the urban population of Rome, Italy, by using time resolved population distribution maps, derived by mobile phone traffic data, and modelled air pollutants (NO2, O3 and PM2.5) concentrations obtained by an integrated air dispersion modelling system. More than a million of persons were tracked during two months (March and April 2015) for their position within the city and its surroundings areas, with a time resolution of 15 min and mapped over an irregular grid system with a minimum resolution of 0.26 × 0.34 Km2. In addition, demographics information (as gender and age ranges) were available in a separated dataset not connected with the total population one. Such BigData were matched in time and space with air pollution model results and then used to produce hourly and daily resolved cumulative population exposures during the studied period. A significant mobility of population was identified with higher population densities in downtown areas during daytime increasing of up to 1000 people/Km2 with respect to nigh-time one, likely produced by commuters, tourists and working age population. Strong variability (up to ±50% for NO2) of population exposures were detected as an effect of both mobility and time/spatial changing in pollutants concentrations. A comparison with the correspondent stationary approach based on National Census data, allows detecting the inability of latter in estimating the actual variability of population exposure. Significant underestimations of the amount of population exposed to daily PM2.5 WHO guideline was identified for the Census approach. Very small differences (up to a few μg/m3) on exposure were detected for gender and age ranges population classes.

A quantitative model of honey bee colony population dynamics.

PubMed

Khoury, David S; Myerscough, Mary R; Barron, Andrew B

2011-04-18

Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonies regulate a stable population size. If death rates are sustained higher than this threshold rapid population decline is predicted and colony failure is inevitable. The model also predicts that high forager death rates draw hive bees into the foraging population at much younger ages than normal, which acts to accelerate colony failure. The model suggests that colony failure can be understood in terms of observed principles of honey bee population dynamics, and provides a theoretical framework for experimental investigation of the problem.

Stochastic hybrid delay population dynamics: well-posed models and extinction.

PubMed

Yuan, Chenggui; Mao, Xuerong; Lygeros, John

2009-01-01

Nonlinear differential equations have been used for decades for studying fluctuations in the populations of species, interactions of species with the environment, and competition and symbiosis between species. Over the years, the original non-linear models have been embellished with delay terms, stochastic terms and more recently discrete dynamics. In this paper, we investigate stochastic hybrid delay population dynamics (SHDPD), a very general class of population dynamics that comprises all of these phenomena. For this class of systems, we provide sufficient conditions to ensure that SHDPD have global positive, ultimately bounded solutions, a minimum requirement for a realistic, well-posed model. We then study the question of extinction and establish conditions under which an ecosystem modelled by SHDPD is doomed.

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

[The dynamics of heath indicators of population of industrial town].

PubMed

Kalinkin, D E; Karpov, A B; Takhauov, R M; Samoĭlova, Iu A

2013-01-01

The article presents the results of analysis of dynamics of health indicators of population of industrial town (medical demographic indicators, disability, morbidity of social hygienically important diseases) during 1970-2010. The classified administrative territorial municipality of Seversk constructed near the Siberian chemical industrial center, the internationally first-rate complex of nuclear industry enterprises was used as a research base. It is demonstrated that dynamics of health indicators of studied population had such negative tendencies as rapid population ageing, population loss due to decrease of natality and increase of mortality (population of able-bodied age included), prevalence of cardio-vascular diseases, malignant neoplasms and external causes, chronization of diseases. The established tendencies are to be considered in management decision making targeted to support and promote population health in industrial towns.

Evolutionary dynamics on any population structure

NASA Astrophysics Data System (ADS)

Allen, Benjamin; Lippner, Gabor; Chen, Yu-Ting; Fotouhi, Babak; Momeni, Naghmeh; Yau, Shing-Tung; Nowak, Martin A.

2017-03-01

Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times of random walks. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties.

Human population dynamics in Europe over the Last Glacial Maximum

PubMed Central

Tallavaara, Miikka; Luoto, Miska; Korhonen, Natalia; Järvinen, Heikki; Seppä, Heikki

2015-01-01

The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000–19,000 y ago (27–19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30–13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe. PMID:26100880

A dynamical-systems approach for computing ice-affected streamflow

USGS Publications Warehouse

Holtschlag, David J.

1996-01-01

A dynamical-systems approach was developed and evaluated for computing ice-affected streamflow. The approach provides for dynamic simulation and parameter estimation of site-specific equations relating ice effects to routinely measured environmental variables. Comparison indicates that results from the dynamical-systems approach ranked higher than results from 11 analytical methods previously investigated on the basis of accuracy and feasibility criteria. Additional research will likely lead to further improvements in the approach.

Tropical forest landscape dynamics: Population consequences for neotropical lianas, genus Passiflora

NASA Astrophysics Data System (ADS)

Plowes, Robert Merrick

patch extinction with potential to contribute later through both sexual and asexual dispersal. Plants that rely only on high dispersal were extinction prone in low connectivity landscapes. This novel approach of jointly analyzing spatially-explicit patch parameters and life history traits offers a comprehensive framework for further understanding the effects of patch dynamics on populations.

Bounds on the dynamics of sink populations with noisy immigration.

PubMed

Eager, Eric Alan; Guiver, Chris; Hodgson, Dave; Rebarber, Richard; Stott, Iain; Townley, Stuart

2014-03-01

Sink populations are doomed to decline to extinction in the absence of immigration. The dynamics of sink populations are not easily modelled using the standard framework of per capita rates of immigration, because numbers of immigrants are determined by extrinsic sources (for example, source populations, or population managers). Here we appeal to a systems and control framework to place upper and lower bounds on both the transient and future dynamics of sink populations that are subject to noisy immigration. Immigration has a number of interpretations and can fit a wide variety of models found in the literature. We apply the results to case studies derived from published models for Chinook salmon (Oncorhynchus tshawytscha) and blowout penstemon (Penstemon haydenii). Copyright © 2013 Elsevier Inc. All rights reserved.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

How Ebola impacts social dynamics in gorillas: a multistate modelling approach.

PubMed

Genton, Céline; Pierre, Amandine; Cristescu, Romane; Lévréro, Florence; Gatti, Sylvain; Pierre, Jean-Sébastien; Ménard, Nelly; Le Gouar, Pascaline

2015-01-01

Emerging infectious diseases can induce rapid changes in population dynamics and threaten population persistence. In socially structured populations, the transfers of individuals between social units, for example, from breeding groups to non-breeding groups, shape population dynamics. We suggest that diseases may affect these crucial transfers. We aimed to determine how disturbance by an emerging disease affects demographic rates of gorillas, especially transfer rates within populations and immigration rates into populations. We compared social dynamics and key demographic parameters in a gorilla population affected by Ebola using a long-term observation data set including pre-, during and post-outbreak periods. We also studied a population of undetermined epidemiological status in order to assess whether this population was affected by the disease. We developed a multistate model that can handle transition between social units while optimizing the number of states. During the Ebola outbreak, social dynamics displayed increased transfers from a breeding to a non-breeding status for both males and females. Six years after the outbreak, demographic and most of social dynamics parameters had returned to their initial rates, suggesting a certain resilience in the response to disruption. The formation of breeding groups increased just after Ebola, indicating that environmental conditions were still attractive. However, population recovery was likely delayed because compensatory immigration was probably impeded by the potential impact of Ebola in the surrounding areas. The population of undetermined epidemiological status behaved similarly to the other population before Ebola. Our results highlight the need to integrate social dynamics in host-population demographic models to better understand the role of social structure in the sensitivity and the response to disease disturbances. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Evolutionary dynamics of general group interactions in structured populations

NASA Astrophysics Data System (ADS)

Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

2016-02-01

The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions.

Heart Rate Fragmentation: A Symbolic Dynamical Approach.

PubMed

Costa, Madalena D; Davis, Roger B; Goldberger, Ary L

2017-01-01

Background: We recently introduced the concept of heart rate fragmentation along with a set of metrics for its quantification. The term was coined to refer to an increase in the percentage of changes in heart rate acceleration sign, a dynamical marker of a type of anomalous variability. The effort was motivated by the observation that fragmentation, which is consistent with the breakdown of the neuroautonomic-electrophysiologic control system of the sino-atrial node, could confound traditional short-term analysis of heart rate variability. Objective: The objectives of this study were to: (1) introduce a symbolic dynamical approach to the problem of quantifying heart rate fragmentation; (2) evaluate how the distribution of the different dynamical patterns ("words") varied with the participants' age in a group of healthy subjects and patients with coronary artery disease (CAD); and (3) quantify the differences in the fragmentation patterns between the two sample populations. Methods: The symbolic dynamical method employed here was based on a ternary map of the increment NN interval time series and on the analysis of the relative frequency of symbolic sequences (words) with a pre-defined set of features. We analyzed annotated, open-access Holter databases of healthy subjects and patients with CAD, provided by the University of Rochester Telemetric and Holter ECG Warehouse (THEW). Results: The degree of fragmentation was significantly higher in older individuals than in their younger counterparts. However, the fragmentation patterns were different in the two sample populations. In healthy subjects, older age was significantly associated with a higher percentage of transitions from acceleration/deceleration to zero acceleration and vice versa (termed "soft" inflection points). In patients with CAD, older age was also significantly associated with higher percentages of frank reversals in heart rate acceleration (transitions from acceleration to deceleration and vice

High population variability and source-sink dynamics in a solitary bee species.

PubMed

Franzén, Markus; Nilsson, Sven G

2013-06-01

Although solitary bees are considered to play key roles in ecosystem functions, surprisingly few studies have explored their population dynamics. We investigated the population dynamics of a rare, declining, solitary bee (Andrena humilis) in a landscape of 80 km2 in southern Sweden from 2003 to 2011. Only one population was persistent throughout all years studied; most likely this population supplied the surrounding landscape with 11 smaller, temporary local populations. Despite stable pollen availability, the size of the persistent population fluctuated dramatically in a two-year cycle over the nine years, with 490-1230 nests in odd-numbered years and 21-48 nests in even-numbered years. These fluctuations were not significantly related to climatic variables or pollen availability. Nineteen colonization and 14 extinction events were recorded. Occupancy decreased with distance from the persistent population and increased with increasing resource (pollen) availability. There were significant positive correlations between the size of the persistent population and patch occupancy and colonization. Colonizations were generally more common in patches closer to the persistent population, whereas extinctions were independent of distance from the persistent population. Our results highlight the complex population dynamics that exist for this solitary bee species, which could be due to source-sink dynamics, a prolonged diapause, or can represent a bet-hedging strategy to avoid natural enemies and survive in small habitat patches. If large fluctuations in solitary bee populations prove to be widespread, it will have important implications for interpreting ecological relationships, bee conservation, and pollination.

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.

Synchronous population dynamics in California butterflies explained by climatic forcing

PubMed Central

Shapiro, Arthur M.

2017-01-01

A long-standing challenge for population biology has been to understand why some species are characterized by populations that fluctuate in size independently, while populations of other species fluctuate synchronously across space. The effects of climatic variation and dispersal have been invoked to explain synchronous population dynamics, however an understanding of the relative influence of these drivers in natural populations is lacking. Here we compare support for dispersal- versus climate-driven models of interspecific variation in synchrony using 27 years of observations of 65 butterfly species at 10 sites spanning 2750 m of elevation in Northern California. The degree of spatial synchrony exhibited by each butterfly species was used as a response in a unique approach that allowed us to investigate whether interspecific variation in response to climate or dispersal propensity was most predictive of interspecific variation in synchrony. We report that variation in sensitivity to climate explained 50% of interspecific variation in synchrony, whereas variation in dispersal propensity explained 23%. Sensitivity to the El Niño Southern Oscillation, a primary driver of regional climate, was the best predictor of synchrony. Combining sensitivity to climate and dispersal propensity into a single model did not greatly increase model performance, confirming the primacy of climatic sensitivity for driving spatial synchrony in butterflies. Finally, we uncovered a relationship between spatial synchrony and population decline that is consistent with theory, but small in magnitude, which suggests that the degree to which populations fluctuate in synchrony is of limited use for understanding the ongoing decline of the Northern California butterfly fauna. PMID:28791146

Bridging the Timescales of Single-Cell and Population Dynamics

NASA Astrophysics Data System (ADS)

Jafarpour, Farshid; Wright, Charles S.; Gudjonson, Herman; Riebling, Jedidiah; Dawson, Emma; Lo, Klevin; Fiebig, Aretha; Crosson, Sean; Dinner, Aaron R.; Iyer-Biswas, Srividya

2018-04-01

How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division. These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to the replication-competent (stalked) stage of the Caulobacter crescentus life cycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For C. crescentus cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time and, thus, yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell-age distribution, and the quiescence timescale.

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning

PubMed Central

Dann, Benjamin

2016-01-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity. PMID:27814352

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.

PubMed

Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

2016-11-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.

Natural Selection in Large Populations

NASA Astrophysics Data System (ADS)

Desai, Michael

2011-03-01

I will discuss theoretical and experimental approaches to the evolutionary dynamics and population genetics of natural selection in large populations. In these populations, many mutations are often present simultaneously, and because recombination is limited, selection cannot act on them all independently. Rather, it can only affect whole combinations of mutations linked together on the same chromosome. Methods common in theoretical population genetics have been of limited utility in analyzing this coupling between the fates of different mutations. In the past few years it has become increasingly clear that this is a crucial gap in our understanding, as sequence data has begun to show that selection appears to act pervasively on many linked sites in a wide range of populations, including viruses, microbes, Drosophila, and humans. I will describe approaches that combine analytical tools drawn from statistical physics and dynamical systems with traditional methods in theoretical population genetics to address this problem, and describe how experiments in budding yeast can help us directly observe these evolutionary dynamics.

Uncovering the transmission dynamics of Plasmodium vivax using population genetics

PubMed Central

Barry, Alyssa E.; Waltmann, Andreea; Koepfli, Cristian; Barnadas, Celine; Mueller, Ivo

2015-01-01

Population genetic analysis of malaria parasites has the power to reveal key insights into malaria epidemiology and transmission dynamics with the potential to deliver tools to support control and elimination efforts. Analyses of parasite genetic diversity have suggested that Plasmodium vivax populations are more genetically diverse and less structured than those of Plasmodium falciparum indicating that P. vivax may be a more ancient parasite of humans and/or less susceptible to population bottlenecks, as well as more efficient at disseminating its genes. These population genetic insights into P. vivax transmission dynamics provide an explanation for its relative resilience to control efforts. Here, we describe current knowledge on P. vivax population genetic structure, its relevance to understanding transmission patterns and relapse and how this information can inform malaria control and elimination programmes. PMID:25891915

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

PubMed

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

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

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

PubMed Central

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

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

A new ODE tumor growth modeling based on tumor population dynamics

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

Oroji, Amin; Omar, Mohd bin; Yarahmadian, Shantia

2015-10-22

In this paper a new mathematical model for the population of tumor growth treated by radiation is proposed. The cells dynamics population in each state and the dynamics of whole tumor population are studied. Furthermore, a new definition of tumor lifespan is presented. Finally, the effects of two main parameters, treatment parameter (q), and repair mechanism parameter (r) on tumor lifespan are probed, and it is showed that the change in treatment parameter (q) highly affects the tumor lifespan.

Dynamic range adaptation in primary motor cortical populations

PubMed Central

Rasmussen, Robert G; Schwartz, Andrew; Chase, Steven M

2017-01-01

Neural populations from various sensory regions demonstrate dynamic range adaptation in response to changes in the statistical distribution of their input stimuli. These adaptations help optimize the transmission of information about sensory inputs. Here, we show a similar effect in the firing rates of primary motor cortical cells. We trained monkeys to operate a brain-computer interface in both two- and three-dimensional virtual environments. We found that neurons in primary motor cortex exhibited a change in the amplitude of their directional tuning curves between the two tasks. We then leveraged the simultaneous nature of the recordings to test several hypotheses about the population-based mechanisms driving these changes and found that the results are most consistent with dynamic range adaptation. Our results demonstrate that dynamic range adaptation is neither limited to sensory regions nor to rescaling of monotonic stimulus intensity tuning curves, but may rather represent a canonical feature of neural encoding. DOI: http://dx.doi.org/10.7554/eLife.21409.001 PMID:28417848

[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.

Population dynamics of Hawaiian seabird colonies vulnerable to sea-level rise.

PubMed

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

2012-08-01

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. Conservation Biology ©2012 Society for Conservation Biology. No claim to original

Microbial dynamics and biodiversity in table olive fermentation: culture-dependent and -independent approaches

PubMed Central

Botta, Cristian; Cocolin, Luca

2012-01-01

The microbial ecology of the table olive fermentation process is a complex set of dynamics in which the roles of the lactic acid bacteria (LAB) and yeast populations are closely related, and this synergism is of fundamental importance to obtain high quality products. Several studies on the ecology of table olives, both in spontaneous fermentations and in inoculated ones, have focused on the identification and characterization of yeasts, as they play a key role in the definition of the final organoleptic profiles through the production of volatile compounds. Moreover, these are able to promote the growth of LAB, which is responsible for the stabilization of the final product through the acidification activity and the inhibition of the growth of pathogenic bacteria. The current empirical production process of table olives could be improved through the development of mixed starter cultures. These can only be developed after a deep study of the population dynamics of yeasts and LAB by means of molecular methods. Until now, most studies have exploited culture-dependent approaches to define the natural microbiota of brine and olives. These approaches have identified two main species of LAB, namely Lactobacillus plantarum and L. pentosus, while, as far as yeasts are concerned, the most frequently isolated genera are Candida, Pichia, and Saccharomyces. However, there are a few studies in literature in which a culture-independent approach has been employed. This review summarizes the state of the art of the microbial ecology of table olive fermentations and it focuses on the different approaches and molecular methods that have been applied. PMID:22783248

Population dynamics and the ecological stability of obligate pollination mutualisms

USGS Publications Warehouse

Holland, J. Nathaniel; DeAngelis, Donald L.

2001-01-01

Mutualistic interactions almost always produce both costs and benefits for each of the interacting species. It is the difference between gross benefits and costs that determines the net benefit and the per-capita effect on each of the interacting populations. For example, the net benefit of obligate pollinators, such as yucca and senita moths, to plants is determined by the difference between the number of ovules fertilized from moth pollination and the number of ovules eaten by the pollinator's larvae. It is clear that if pollinator populations are large, then, because many eggs are laid, costs to plants are large, whereas, if pollinator populations are small, gross benefits are low due to lack of pollination. Even though the size and dynamics of the pollinator population are likely to be crucial, their importance has been neglected in the investigation of mechanisms, such as selective fruit abortion, that can limit costs and increase net benefits. Here, we suggest that both the population size and dynamics of pollinators are important in determining the net benefits to plants, and that fruit abortion can significantly affect these. We develop a model of mutualism between populations of plants and their pollinating seed-predators to explore the ecological consequences of fruit abortion on pollinator population dynamics and the net effect on plants. We demonstrate that the benefit to a plant population is unimodal as a function of pollinator abundance, relative to the abundance of flowers. Both selective abortion of fruit with eggs and random abortion of fruit, without reference to whether they have eggs or not, can limit pollinator population size. This can increase the net benefits to the plant population by limiting the number of eggs laid, if the pollination rate remains high. However, fruit abortion can possibly destabilize the pollinator population, with negative consequences for the plant population.

The Population Health Approach in Historical Perspective

PubMed Central

Szreter, Simon

2003-01-01

The origin of the population health approach is an historic debate over the relationship between economic growth and human health. In Britain and France, the Industrial Revolution disrupted population health and stimulated pioneering epidemiological studies, informing the early preventive public health movement. A century-long process of political adjustment between the forces of liberal democracy and propertied interests ensued. The 20th-century welfare states resulted as complex political mechanisms for converting economic growth into enhanced population health. However, the rise of a “neoliberal” agenda, denigrating the role of government, has once again brought to the fore the importance of prevention and a population health approach to map and publicize the health impacts of this new phase of “global” economic growth. PMID:12604486

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

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.

Evolutionary behaviour, trade-offs and cyclic and chaotic population dynamics.

PubMed

Hoyle, Andy; Bowers, Roger G; White, Andy

2011-05-01

Many studies of the evolution of life-history traits assume that the underlying population dynamical attractor is stable point equilibrium. However, evolutionary outcomes can change significantly in different circumstances. We present an analysis based on adaptive dynamics of a discrete-time demographic model involving a trade-off whose shape is also an important determinant of evolutionary behaviour. We derive an explicit expression for the fitness in the cyclic region and consequently present an adaptive dynamic analysis which is algebraic. We do this fully in the region of 2-cycles and (using a symbolic package) almost fully for 4-cycles. Simulations illustrate and verify our results. With equilibrium population dynamics, trade-offs with accelerating costs produce a continuously stable strategy (CSS) whereas trade-offs with decelerating costs produce a non-ES repellor. The transition to 2-cycles produces a discontinuous change: the appearance of an intermediate region in which branching points occur. The size of this region decreases as we move through the region of 2-cycles. There is a further discontinuous fall in the size of the branching region during the transition to 4-cycles. We extend our results numerically and with simulations to higher-period cycles and chaos. Simulations show that chaotic population dynamics can evolve from equilibrium and vice-versa.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

[Population dynamics and armed violence in Colombia, 1985-2010].

PubMed

Salaya, Hernán Eduardo; Rodríguez, Jesús

2014-09-01

Describe changes in the population structure of Colombia's municipalities in relation to internal displacement in response to armed violence. A descriptive ecological study was carried out. Secondary sources were consulted, taken from the Consolidated Registry of Displaced Population and from the National Administrative Department of Statistics, to calculate expulsion and reception rates for population displaced by violence from 2002 to 2010. Based on these rates, four groups were created of municipalities in the extreme quartile for each rate during the entire period, which were classified as high expulsion, low expulsion, high reception, and low reception. Subsequently, population pyramids and structure indicators were constructed for each group of municipalities for two comparative reference years (1985 and 2010). Municipalities with high expulsion or reception rates experienced a slower epidemiological transition, with lower mean ages and aging indices. The high expulsion group had the least regression, based on the Sundbärg index. In the high reception group, the masculinity ratio decreased the most, especially among the economically active population, and it had the highest population growth. Population dynamics in Colombia have been affected by armed violence and changes in these dynamics are not uniform across the country, leading to important social, economic, and cultural consequences. This study is useful for decision-making and public policy making.

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.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

The effects of host-feeding on stability of discrete-time host-parasitoid population dynamic models.

PubMed

Emerick, Brooks; Singh, Abhyudai

2016-02-01

Discrete-time models are the traditional approach for capturing population dynamics of a host-parasitoid system. Recent work has introduced a semi-discrete framework for obtaining model update functions that connect host-parasitoid population levels from year-to-year. In particular, this framework uses differential equations to describe the host-parasitoid interaction during the time of year when they come in contact, allowing specific behaviors to be mechanistically incorporated. We use the semi-discrete approach to study the effects of host-feeding, which occurs when a parasitoid consumes a potential host larva without ovipositing. We find that host-feeding by itself cannot stabilize the system, and both populations exhibit behavior similar to the Nicholson-Bailey model. However, when combined with stabilizing mechanisms such as density-dependent host mortality, host-feeding contracts the region of parameter space that allows for a stable host-parasitoid equilibrium. In contrast, when combined with a density-dependent parasitoid attack rate, host-feeding expands the non-zero equilibrium stability region. Our results show that host-feeding causes inefficiency in the parasitoid population, which yields a higher population of hosts per generation. This suggests that host-feeding may have limited long-term impact in terms of suppressing host levels for biological control applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous effects of food limitation and inducible resistance on herbivore population dynamics.

PubMed

Abbott, Karen C; Morris, William F; Gross, Kevin

2008-02-01

Many herbivore populations fluctuate temporally, but the causes of those fluctuations remain unclear. Plant inducible resistance can theoretically cause herbivore population fluctuations, because herbivory may induce plant changes that reduce the survival or reproduction of later-feeding herbivores. Herbivory can also simply reduce the quantity of food available for later feeders and this, too, can cause population fluctuations. Inducible resistance and food limitation often occur simultaneously, yet whether they jointly facilitate or suppress herbivore fluctuations remains largely unexplored. We present models that suggest that food limitation and inducible resistance may have synergistic effects on herbivore population dynamics. The population-level response of the food plant to herbivory and the details of how inducible resistance affects herbivore performance both influence the resulting herbivore dynamics. Our results identify some biological properties of plant-herbivore systems that might determine whether or not cycles occur, and suggest that future empirical and theoretical population dynamics studies should account for the effects of both food limitation and inducible resistance.

Social Information Links Individual Behavior to Population and Community Dynamics.

PubMed

Gil, Michael A; Hein, Andrew M; Spiegel, Orr; Baskett, Marissa L; Sih, Andrew

2018-05-07

When individual animals make decisions, they routinely use information produced intentionally or unintentionally by other individuals. Despite its prevalence and established fitness consequences, the effects of such social information on ecological dynamics remain poorly understood. Here, we synthesize results from ecology, evolutionary biology, and animal behavior to show how the use of social information can profoundly influence the dynamics of populations and communities. We combine recent theoretical and empirical results and introduce simple population models to illustrate how social information use can drive positive density-dependent growth of populations and communities (Allee effects). Furthermore, social information can shift the nature and strength of species interactions, change the outcome of competition, and potentially increase extinction risk in harvested populations and communities. Copyright © 2018 Elsevier Ltd. All rights reserved.

Interactions between demography and environmental effects are important determinants of population dynamics

PubMed Central

Gamelon, Marlène; Grøtan, Vidar; Nilsson, Anna L. K.; Engen, Steinar; Hurrell, James W.; Jerstad, Kurt; Phillips, Adam S.; Røstad, Ole W.; Slagsvold, Tore; Walseng, Bjørn; Stenseth, Nils C.; Sæther, Bernt-Erik

2017-01-01

Climate change will affect the population dynamics of many species, yet the consequences for the long-term persistence of populations are poorly understood. A major reason for this is that density-dependent feedback effects caused by fluctuations in population size are considered independent of stochastic variation in the environment. We show that an interplay between winter temperature and population density can influence the persistence of a small passerine population under global warming. Although warmer winters favor an increased mean population size, density-dependent feedback can cause the local population to be less buffered against occasional poor environmental conditions (cold winters). This shows that it is essential to go beyond the population size and explore climate effects on the full dynamics to elaborate targeted management actions. PMID:28164157

Integral control for population management.

PubMed

Guiver, Chris; Logemann, Hartmut; Rebarber, Richard; Bill, Adam; Tenhumberg, Brigitte; Hodgson, Dave; Townley, Stuart

2015-04-01

We present a novel management methodology for restocking a declining population. The strategy uses integral control, a concept ubiquitous in control theory which has not been applied to population dynamics. Integral control is based on dynamic feedback-using measurements of the population to inform management strategies and is robust to model uncertainty, an important consideration for ecological models. We demonstrate from first principles why such an approach to population management is suitable via theory and examples.

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Inferences about ungulate population dynamics derived from age ratios

USGS Publications Warehouse

Harris, N.C.; Kauffman, M.J.; Mills, L.S.

2008-01-01

Age ratios (e.g., calf:cow for elk and fawn:doe for deer) are used regularly to monitor ungulate populations. However, it remains unclear what inferences are appropriate from this index because multiple vital rate changes can influence the observed ratio. We used modeling based on elk (Cervus elaphus) life-history to evaluate both how age ratios are influenced by stage-specific fecundity and survival and how well age ratios track population dynamics. Although all vital rates have the potential to influence calf:adult female ratios (i.e., calf:xow ratios), calf survival explained the vast majority of variation in calf:adult female ratios due to its temporal variation compared to other vital rates. Calf:adult female ratios were positively correlated with population growth rate (??) and often successfully indicated population trajectories. However, calf:adult female ratios performed poorly at detecting imposed declines in calf survival, suggesting that only the most severe declines would be rapidly detected. Our analyses clarify that managers can use accurate, unbiased age ratios to monitor arguably the most important components contributing to sustainable ungulate populations, survival rate of young and ??. However, age ratios are not useful for detecting gradual declines in survival of young or making inferences about fecundity or adult survival in ungulate populations. Therefore, age ratios coupled with independent estimates of population growth or population size are necessary to monitor ungulate population demography and dynamics closely through time.

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

Theoretical approaches for dynamical ordering of biomolecular systems.

PubMed

Okumura, Hisashi; Higashi, Masahiro; Yoshida, Yuichiro; Sato, Hirofumi; Akiyama, Ryo

2018-02-01

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies. We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified. The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function. These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a model forecasting Dermanyssus gallinae's population dynamics for advancing Integrated Pest Management in laying hen facilities.

PubMed

Mul, Monique F; van Riel, Johan W; Roy, Lise; Zoons, Johan; André, Geert; George, David R; Meerburg, Bastiaan G; Dicke, Marcel; van Mourik, Simon; Groot Koerkamp, Peter W G

2017-10-15

The poultry red mite, Dermanyssus gallinae, is the most significant pest of egg laying hens in many parts of the world. Control of D. gallinae could be greatly improved with advanced Integrated Pest Management (IPM) for D. gallinae in laying hen facilities. The development of a model forecasting the pests' population dynamics in laying hen facilities without and post-treatment will contribute to this advanced IPM and could consequently improve implementation of IPM by farmers. The current work describes the development and demonstration of a model which can follow and forecast the population dynamics of D. gallinae in laying hen facilities given the variation of the population growth of D. gallinae within and between flocks. This high variation could partly be explained by house temperature, flock age, treatment, and hen house. The total population growth variation within and between flocks, however, was in part explained by temporal variation. For a substantial part this variation was unexplained. A dynamic adaptive model (DAP) was consequently developed, as models of this type are able to handle such temporal variations. The developed DAP model can forecast the population dynamics of D. gallinae, requiring only current flock population monitoring data, temperature data and information of the dates of any D. gallinae treatment. Importantly, the DAP model forecasted treatment effects, while compensating for location and time specific interactions, handling the variability of these parameters. The characteristics of this DAP model, and its compatibility with different mite monitoring methods, represent progression from existing approaches for forecasting D. gallinae that could contribute to advancing improved Integrated Pest Management (IPM) for D. gallinae in laying hen facilities. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Computational analysis of complex systems: Applications to population dynamics and networks

NASA Astrophysics Data System (ADS)

Molnar, Ferenc

In most complex evolving systems, we can often find a critical subset of the constituents that can initiate a global change in the entire system. For example, in complex networks, a critical subset of nodes can efficiently spread information, influence, or control dynamical processes over the entire network. Similarly, in nonlinear dynamics, we can locate key variables, or find the necessary parameters, to reach the attraction basin of a desired global state. In both cases, a fundamental goal is finding the ability to efficiently control these systems. We study two distinct complex systems in this dissertation, exploring these topics. First, we analyze a population dynamics model describing interactions of sex-structured population groups. Specifically, we analyze how a sex-linked genetic trait's ecological consequence (population survival or extinction) can be influenced by the presence of sex-specific cultural mortality traits, motivated by the desire to expand the theoretical understanding of the role of biased sex ratios in organisms. We analyze dynamics within a single population group, as well as between competing groups. We find that there is a finite range of sex ratio bias that can be maintained in stable equilibrium by sex-specific mortalities. We also find that the outcome of an invasion and the ensuing between-group competition depends not on larger equilibrium group densities, but on the higher allocation of sex-ratio genes. When we extend the model with diffusive dispersal, we find that a critical patch size for achieving positive growth only exists if the population expands into an empty environment. If a resident population is already present that can be exploited by the invading group, then any small seed of invader can advance from rarity, in the mean-field approximation, as long as the local competition dynamics favors the invader's survival. Most spatial models assume initial populations with a uniform distribution inside a finite patch; a

Change in the structures, dynamics and disease-related mortality rates of the population of Qatari nationals: 2007-2011.

PubMed

Al-Thani, Mohamed H; Sadoun, Eman; Al-Thani, Al-Anoud; Khalifa, Shamseldin A; Sayegh, Suzan; Badawi, Alaa

2014-12-01

Developing effective public health policies and strategies for interventions necessitates an assessment of the structure, dynamics, disease rates and causes of death in a population. Lately, Qatar has undertaken development resurgence in health and economy that resulted in improving the standard of health services and health status of the entire Qatari population (i.e., Qatari nationals and non-Qatari residents). No study has attempted to evaluate the population structure/dynamics and recent changes in disease-related mortality rates among Qatari nationals. The present study examines the population structure/dynamics and the related changes in the cause-specific mortality rates and disease prevalence in the Qatari nationals. This is a retrospective, analytic descriptive analysis covering a period of 5years (2007-2011) and utilizes a range of data sources from the State of Qatar including the population structure, disease-related mortality rates, and the prevalence of a range of chronic and infectious diseases. Factors reflecting population dynamics such as crude death (CDR), crude birth (CBR), total fertility (TFR) and infant mortality (IMR) rates were also calculated. The Qatari nationals is an expansive population with an annual growth rate of ∼4% and a stable male:female ratio. The CDR declined by 15% within the study period, whereas the CBR was almost stable. The total disease-specific death rate, however, was decreased among the Qatari nationals by 23% due to the decline in mortality rates attributed to diseases of the blood and immune system (43%), nervous system (44%) and cardiovascular system (41%). There was a high prevalence of a range of chronic diseases, whereas very low frequencies of the infectious diseases within the study population. Public health strategies, approaches and programs developed to reduce disease burden and the related death, should be tailored to target the population of Qatari nationals which exhibits characteristics that vary from

Growth dynamics and the evolution of cooperation in microbial populations

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Melbinger, Anna; Frey, Erwin

2012-02-01

Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.

Population Dynamics of Early Human Migration in Britain

PubMed Central

Vahia, Mayank N.; Ladiwala, Uma; Mahathe, Pavan; Mathur, Deepak

2016-01-01

Background Early human migration is largely determined by geography and human needs. These are both deterministic parameters when small populations move into unoccupied areas where conflicts and large group dynamics are not important. The early period of human migration into the British Isles provides such a laboratory which, because of its relative geographical isolation, may allow some insights into the complex dynamics of early human migration and interaction. Method and Results We developed a simulation code based on human affinity to habitable land, as defined by availability of water sources, altitude, and flatness of land, in choosing the path of migration. Movement of people on the British island over the prehistoric period from their initial entry points was simulated on the basis of data from the megalithic period. Topographical and hydro-shed data from satellite databases was used to define habitability, based on distance from water bodies, flatness of the terrain, and altitude above sea level. We simulated population movement based on assumptions of affinity for more habitable places, with the rate of movement tempered by existing populations. We compared results of our computer simulations with genetic data and show that our simulation can predict fairly accurately the points of contacts between different migratory paths. Such comparison also provides more detailed information about the path of peoples’ movement over ~2000 years before the present era. Conclusions We demonstrate an accurate method to simulate prehistoric movements of people based upon current topographical satellite data. Our findings are validated by recently-available genetic data. Our method may prove useful in determining early human population dynamics even when no genetic information is available. PMID:27148959

Breeding site heterogeneity reduces variability in frog recruitment and population dynamics

USGS Publications Warehouse

McCaffery, Rebecca M.; Eby, Lisa A.; Maxell, Bryce A.; Corn, Paul Stephen

2013-01-01

Environmental stochasticity can have profound effects on the dynamics and viability of wild populations, and habitat heterogeneity provides one mechanism by which populations may be buffered against the negative effects of environmental fluctuations. Heterogeneity in breeding pond hydroperiod across the landscape may allow amphibian populations to persist despite variable interannual precipitation. We examined recruitment dynamics over 10 yr in a high-elevation Columbia spotted frog (Rana luteiventris) population that breeds in ponds with a variety of hydroperiods. We combined these data with matrix population models to quantify the consequences of heterogeneity in pond hydroperiod on net recruitment (i.e. number of metamorphs produced) and population growth rates. We compared our heterogeneous system to hypothetical homogeneous environments with only ephemeral ponds, only semi-permanent ponds, and only permanent ponds. We also examined the effects of breeding pond habitat loss on population growth rates. Most eggs were laid in permanent ponds each year, but survival to metamorphosis was highest in the semi-permanent ponds. Recruitment success varied by both year and pond type. Net recruitment and stochastic population growth rate were highest under a scenario with homogeneous semi-permanent ponds, but variability in recruitment was lowest in the scenario with the observed heterogeneity in hydroperiods. Loss of pond habitat decreased population growth rate, with greater decreases associated with loss of permanent and semi-permanent habitat. The presence of a diversity of pond hydroperiods on the landscape will influence population dynamics, including reducing variability in recruitment in an uncertain climatic future.

Fish population dynamics in a seasonally varying wetland

USGS Publications Warehouse

DeAngelis, Donald L.; Trexler, Joel C.; Cosner, Chris; Obaza, Adam; Jopp, Fred

2010-01-01

Small fishes in seasonally flooded environments such as the Everglades are capable of spreading into newly flooded areas and building up substantial biomass. Passive drift cannot account for the rapidity of observed population expansions. To test the reaction-diffusion mechanism for spread of the fish, we estimated their diffusion coefficient and applied a reaction-diffusion model. This mechanism was also too weak to account for the spatial dynamics. Two other hypotheses were tested through modeling. The first--the 'refuge mechanism--hypothesizes that small remnant populations of small fishes survive the dry season in small permanent bodies of water (refugia), sites where the water level is otherwise below the surface. The second mechanism, which we call the 'dynamic ideal free distribution mechanism' is that consumption by the fish creates a prey density gradient and that fish taxis along this gradient can lead to rapid population expansion in space. We examined the two alternatives and concluded that although refugia may play an important role in recolonization by the fish population during reflooding, only the second, taxis in the direction of the flooding front, seems capable of matching empirical observations. This study has important implications for management of wetlands, as fish biomass is an essential support of higher trophic levels.

Galactic civilizations - Population dynamics and interstellar diffusion

NASA Technical Reports Server (NTRS)

Newman, W. I.; Sagan, C.

1981-01-01

A model is developed of the interstellar diffusion of galactic civilizations which takes into account the population dynamics of such civilizations. The problem is formulated in terms of potential theory, with a family of nonlinear partial differential and difference equations specifying population growth and diffusion for an organism with advantageous genes that undergoes random dispersal while increasing in population locally, and a population at zero population growth. In the case of nonlinear diffusion with growth and saturation, it is found that the colonization wavefront from the nearest independently arisen galactic civilization can have reached the earth only if its lifetime exceeds 2.6 million years, or 20 million years if discretization can be neglected. For zero population growth, the corresponding lifetime is 13 billion years. It is concluded that the earth is uncolonized not because interstellar spacefaring civilizations are rare, but because there are too many worlds to be colonized in the plausible colonization lifetime of nearby civilizations, and that there exist no very old galactic civilizations with a consistent policy of the conquest of inhabited worlds.

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

Capital, population and urban patterns.

PubMed

Zhang, W

1994-04-01

The author develops an approach to urban dynamics with endogenous capital and population growth, synthesizing the Alonso location model, the two-sector neoclassical growth model, and endogenous population theory. A dynamic model for an isolated island economy with endogenous capital, population, and residential structure is developed on the basis of Alonso's residential model and the two-sector neoclassical growth model. The model describes the interdependence between residential structure, economic growth, population growth, and economic structure over time and space. It has a unique long-run equilibrium, which may be either stable or unstable, depending upon the population dynamics. Applying the Hopf theorem, the author also shows that when the system is unstable, the economic geography exhibits permanent endogenous oscillations.

An Ecological Approach to Learning Dynamics

ERIC Educational Resources Information Center

Normak, Peeter; Pata, Kai; Kaipainen, Mauri

2012-01-01

New approaches to emergent learner-directed learning design can be strengthened with a theoretical framework that considers learning as a dynamic process. We propose an approach that models a learning process using a set of spatial concepts: learning space, position of a learner, niche, perspective, step, path, direction of a step and step…

Stochastic population dynamics in spatially extended predator-prey systems

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex

MODELING APPROACHES TO POPULATION-LEVEL RISK AESSESSMENT

EPA Science Inventory

A SETAC Pellston Workshop on Population-Level Risk Assessment was held in Roskilde, Denmark on 23-27 August 2003. One aspect of this workshop focused on modeling approaches for characterizing population-level effects of chemical exposure. The modeling work group identified th...

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

Causes and consequences of complex population dynamics in an annual plant, Cardamine pensylvanica

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

Crone, E.E.

1995-11-08

The relative importance of density-dependent and density-independent factors in determining the population dynamics of plants has been widely debated with little resolution. In this thesis, the author explores the effects of density-dependent population regulation on population dynamics in Cardamine pensylvanica, an annual plant. In the first chapter, she shows that experimental populations of C. pensylvanica cycled from high to low density in controlled constant-environment conditions. These cycles could not be explained by external environmental changes or simple models of direct density dependence (N{sub t+1} = f[N{sub t}]), but they could be explained by delayed density dependence (N{sub t+1} = f[N{submore » t}, N{sub t+1}]). In the second chapter, she shows that the difference in the stability properties of population growth models with and without delayed density dependence is due to the presence of Hopf as well as slip bifurcations from stable to chaotic population dynamics. She also measures delayed density dependence due to effects of parental density on offspring quality in C. pensylvanica and shows that this is large enough to be the cause of the population dynamics observed in C. pensylvanica. In the third chapter, the author extends her analyses of density-dependent population growth models to include interactions between competing species. In the final chapter, she compares the effects of fixed spatial environmental variation and variation in population size on the evolutionary response of C. pensylvanica populations.« less

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

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

Mosquito populations dynamics associated with climate variations.

PubMed

Wilke, André Barretto Bruno; Medeiros-Sousa, Antônio Ralph; Ceretti-Junior, Walter; Marrelli, Mauro Toledo

2017-02-01

Mosquitoes are responsible for the transmission of numerous serious pathogens. Members of the Aedes and Culex genera, which include many important vectors of mosquito-borne diseases, are highly invasive and adapted to man-made environments. They are spread around the world involuntarily by humans and are highly adapted to urbanized environments, where they are exposed to climate-related abundance drivers. We investigated Culicidae fauna in two urban parks in the city of São Paulo to analyze the correlations between climatic variables and the population dynamics of mosquitoes in these urban areas. Mosquitoes were collected monthly over one year, and sampling sufficiency was evaluated after morphological identification of the specimens. The average monthly temperature and accumulated rainfall for the collection month and previous month were used to explain climate-related abundance drivers for the six most abundant species (Aedes aegypti, Aedes albopictus, Aedes fluviatilis, Aedes scapularis, Culex nigripalpus and Culex quinquefasciatus) and then analyzed using generalized linear statistical models and the Akaike Information Criteria corrected for small samples (AICc). The strength of evidence in favor of each model was evaluated using Akaike weights, and the explanatory model power was measured by McFadden's Pseudo-R 2 . Associations between climate and mosquito abundance were found in both parks, indicating that predictive models based on climate variables can provide important information on mosquito population dynamics. We also found that this association is species-dependent. Urbanization processes increase the abundance of a few mosquito species that are well adapted to man-made environments and some of which are important vectors of pathogens. Predictive models for abundance based on climate variables may help elucidate the population dynamics of urban mosquitoes and their impact on the risk of disease transmission, allowing better predictive scenarios to be

Population dynamics and climate change: what are the links?

PubMed

Stephenson, Judith; Newman, Karen; Mayhew, Susannah

2010-06-01

Climate change has been described as the biggest global health threat of the 21(st) century. World population is projected to reach 9.1 billion by 2050, with most of this growth in developing countries. While the principal cause of climate change is high consumption in the developed countries, its impact will be greatest on people in the developing world. Climate change and population can be linked through adaptation (reducing vulnerability to the adverse effects of climate change) and, more controversially, through mitigation (reducing the greenhouse gases that cause climate change). The contribution of low-income, high-fertility countries to global carbon emissions has been negligible to date, but is increasing with the economic development that they need to reduce poverty. Rapid population growth endangers human development, provision of basic services and poverty eradication and weakens the capacity of poor communities to adapt to climate change. Significant mass migration is likely to occur in response to climate change and should be regarded as a legitimate response to the effects of climate change. Linking population dynamics with climate change is a sensitive issue, but family planning programmes that respect and protect human rights can bring a remarkable range of benefits. Population dynamics have not been integrated systematically into climate change science. The contribution of population growth, migration, urbanization, ageing and household composition to mitigation and adaptation programmes needs urgent investigation.

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.

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...

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.

EFFECTS OF CHRONIC STRESS ON WILDLIFE POPULATIONS: A POPULATION MODELING APPROACH AND CASE STUDY

EPA Science Inventory

This chapter describes a matrix modeling approach to characterize and project risks to wildlife populations subject to chronic stress. Population matrix modeling was used to estimate effects of one class of environmental contaminants, dioxin-like compounds (DLCs), to populations ...

Macroparasite dynamics of migratory host populations.

PubMed

Peacock, Stephanie J; Bouhours, Juliette; Lewis, Mark A; Molnár, Péter K

2018-03-01

Spatial variability in host density is a key factor affecting disease dynamics of wildlife, and yet there are few spatially explicit models of host-macroparasite dynamics. This limits our understanding of parasitism in migratory hosts, whose densities change considerably in both space and time. In this paper, we develop a model for host-macroparasite dynamics that considers the directional movement of host populations and their associated parasites. We include spatiotemporal changes in the mean and variance in parasite burden per host, as well as parasite-mediated host mortality and parasite-mediated migratory ability. Reduced migratory ability with increasing parasitism results in heavily infested hosts halting their migration, and higher parasite burdens in stationary hosts than in moving hosts. Simulations reveal the potential for positive feedbacks between parasite-reduced migratory ability and increasing parasite burdens at infection hotspots, such as stopover sites, that may lead to parasite-induced migratory stalling. This framework could help understand how global change might influence wildlife disease via changes to migratory patterns and parasite demographic rates. Copyright © 2018 Elsevier Inc. All rights reserved.

Social Determinants of Population Health: A Systems Sciences Approach

PubMed Central

Fink, David S.; Keyes, Katherine M.; Cerdá, Magdalena

2016-01-01

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective. PMID:27642548

Dynamics of a coherently driven micromaser by the Monte Carlo wavefunction approach

NASA Astrophysics Data System (ADS)

Bonacina, L.; Casagrande, F.; Lulli, A.

2000-08-01

Using a Monte Carlo wavefunction approach we investigate the dynamics of a micromaser driven by a resonant coherent field. At steady state, for increasing interaction times, the system exhibits driven Rabi oscillations, followed by collapse as the range of micromaser trapping states is approached. The system operates in regimes ranging from a strong to a weak amplifier. In the strong-amplifier regime the cavity mode shows a preferred phase and can exhibit quadrature squeezing and sub-Poissonian photon statistics. In the weak-amplifier regime the cavity mode has no preferred phase, is super-Poissonian and is influenced by trapping effects; no revival of Rabi oscillations occurs. The main predictions can be compared with experimental measurements on the populations of atoms leaving the cavity.

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

Dynamical Systems in Psychology: Linguistic Approaches

NASA Astrophysics Data System (ADS)

Sulis, William

Major goals for psychoanalysis and psychology are the description, analysis, prediction, and control of behaviour. Natural language has long provided the medium for the formulation of our theoretical understanding of behavior. But with the advent of nonlinear dynamics, a new language has appeared which offers promise to provide a quantitative theory of behaviour. In this paper, some of the limitations of natural and formal languages are discussed. Several approaches to understanding the links between natural and formal languages, as applied to the study of behavior, are discussed. These include symbolic dynamics, Moore's generalized shifts, Crutchfield's ɛ machines, and dynamical automata.

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...

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

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.

A generalized population dynamics model for reproductive interference with absolute density dependence.

PubMed

Kyogoku, Daisuke; Sota, Teiji

2017-05-17

Interspecific mating interactions, or reproductive interference, can affect population dynamics, species distribution and abundance. Previous population dynamics models have assumed that the impact of frequency-dependent reproductive interference depends on the relative abundances of species. However, this assumption could be an oversimplification inappropriate for making quantitative predictions. Therefore, a more general model to forecast population dynamics in the presence of reproductive interference is required. Here we developed a population dynamics model to describe the absolute density dependence of reproductive interference, which appears likely when encounter rate between individuals is important. Our model (i) can produce diverse shapes of isoclines depending on parameter values and (ii) predicts weaker reproductive interference when absolute density is low. These novel characteristics can create conditions where coexistence is stable and independent from the initial conditions. We assessed the utility of our model in an empirical study using an experimental pair of seed beetle species, Callosobruchus maculatus and Callosobruchus chinensis. Reproductive interference became stronger with increasing total beetle density even when the frequencies of the two species were kept constant. Our model described the effects of absolute density and showed a better fit to the empirical data than the existing model overall.

Ruffed grouse population dynamics in the central and southern Appalachians

Treesearch

John M. Giuliano Tirpak; C. Allan Miller; Thomas J. Allen; Steve Bittner; David A. Buehler; John W. Edwards; Craig A. Harper; William K. Igo; Gary W. Norman; M. Seamster; Dean F. Stauffer

2006-01-01

Ruffed grouse (Bonasa urnbellus; hereafter grouse) populations in the central and southern Appalachians are in decline. However, limited information on the dynamics of these populations prevents the development of effective management strategies to reverse these trends. We used radiotelemetry data collected on grouse to parameterize 6 models of...

Dynamics of climate-based malaria transmission model with age-structured human population

NASA Astrophysics Data System (ADS)

Addawe, Joel; Pajimola, Aprimelle Kris

2016-10-01

In this paper, we proposed to study the dynamics of malaria transmission with periodic birth rate of the vector and an age-structure for the human population. The human population is divided into two compartments: pre-school (0-5 years) and the rest of the human population. We showed the existence of a disease-free equilibrium point. Using published epidemiological parameters, we use numerical simulations to show potential effect of climate change in the dynamics of age-structured malaria transmission. Numerical simulations suggest that there exists an asymptotically attractive solution that is positive and periodic.

A Bayesian nonparametric approach to dynamical noise reduction

NASA Astrophysics Data System (ADS)

Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2018-06-01

We propose a Bayesian nonparametric approach for the noise reduction of a given chaotic time series contaminated by dynamical noise, based on Markov Chain Monte Carlo methods. The underlying unknown noise process (possibly) exhibits heavy tailed behavior. We introduce the Dynamic Noise Reduction Replicator model with which we reconstruct the unknown dynamic equations and in parallel we replicate the dynamics under reduced noise level dynamical perturbations. The dynamic noise reduction procedure is demonstrated specifically in the case of polynomial maps. Simulations based on synthetic time series are presented.

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population

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

Dynamical resource nexus assessments: from accounting to sustainability approaches

NASA Astrophysics Data System (ADS)

Salmoral, Gloria; Yan, Xiaoyu

2017-04-01

Continued economic development and population growth result in increasing pressures on natural resources, from local to international levels, for meeting societal demands on water, energy and food. To date there are a few tools that link models to identify the relationships and to account for flows of water, energy and food. However, these tools in general can offer only a static view often at national level and with annual temporal resolution. Moreover, they can only account flows but cannot consider the required amounts and conditions of the natural capital that supplies and maintains these flows. With the emerging nexus thinking, our research is currently focused on promoting dynamical environmental analyses beyond the conventional silo mentalities. Our study aims to show new advancements in existing tools (e.g., dynamical life cycle assessment) and develop novel environmental indicators relevant for the resource nexus assessment. We aim to provide a step forward when sustainability conditions and resilience thresholds are aligned with flows under production (e.g., food, water and energy), process level under analysis (e.g., local production, transport, manufacturing, final consumption, reuse, disposal) and existing biophysical local conditions. This approach would help to embrace and better characterise the spatiotemporal dynamics, complexity and existing links between and within the natural and societal systems, which are crucial to evaluate and promote more environmentally sustainable economic activities.

Population dynamics of bowfin in a south Georgia reservoir: latitudinal comparisons of population structure, growth, and mortality

USGS Publications Warehouse

Porter, Nicholas J.; Bonvechio, Timothy F.; McCormick, Joshua L.; Quist, Michael

2014-01-01

The objectives of this study were to evaluate the population dynamics of bowfin (Amia calva) in Lake Lindsay Grace, Georgia, and to compare those dynamics to other bowfin populations. Relative abundance of bowfin sampled in 2010 in Lake Lindsay Grace was low and variable (mean±SD; 2.7±4.7 fish per hour of electrofishing). Total length (TL) of bowfin collected in Lake Lindsay Grace varied from 233–683 mm. Age of bowfin in Lake Lindsay Grace varied from 0–5 yr. Total annual mortality (A) was estimated at 68%. Both sexes appeared to be fully mature by age 2 with gonadosomatic index values above 8 for females and close to 1 for males. The majority of females were older, longer, and heavier than males. Bowfin in Lake Lindsay Grace had fast growth up to age 4 and higher total annual mortality than the other populations examined in this study. A chi-square test indicated that size structure of bowfin from Lake Lindsay Grace was different than those of a Louisiana population and two bowfin populations from the upper Mississippi River. To further assess bowfin size structure, we proposed standard length (i.e., TL) categories: stock (200 mm, 8 inches), quality (350 mm, 14 inches), preferred (460 mm, 18 inches), memorable (560 mm, 22, inches), and trophy (710 mm, 28 inches). Because our knowledge of bowfin ecology is limited, additional understanding of bowfin population dynamics provides important insight that can be used in management of bowfin across their distribution.

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

Evolutionary Game Theory in Growing Populations

NASA Astrophysics Data System (ADS)

Melbinger, Anna; Cremer, Jonas; Frey, Erwin

2010-10-01

Existing theoretical models of evolution focus on the relative fitness advantages of different mutants in a population while the dynamic behavior of the population size is mostly left unconsidered. We present here a generic stochastic model which combines the growth dynamics of the population and its internal evolution. Our model thereby accounts for the fact that both evolutionary and growth dynamics are based on individual reproduction events and hence are highly coupled and stochastic in nature. We exemplify our approach by studying the dilemma of cooperation in growing populations and show that genuinely stochastic events can ease the dilemma by leading to a transient but robust increase in cooperation.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

PubMed Central

Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric

2016-01-01

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles. PMID:26943927

The Influence of Individual Variability on Zooplankton Population Dynamics under Different Environmental Conditions

NASA Astrophysics Data System (ADS)

Bi, R.; Liu, H.

2016-02-01

Understanding how biological components respond to environmental changes could be insightful to predict ecosystem trajectories under different climate scenarios. Zooplankton are key components of marine ecosystems and changes in their dynamics could have major impact on ecosystem structure. We developed an individual-based model of a common coastal calanoid copepod Acartia tonsa to examine how environmental factors affect zooplankton population dynamics and explore the role of individual variability in sustaining population under various environmental conditions consisting of temperature, food concentration and salinity. Total abundance, egg production and proportion of survival were used to measure population success. Results suggested population benefits from high level of individual variability under extreme environmental conditions including unfavorable temperature, salinity, as well as low food concentration, and selection on fast-growers becomes stronger with increasing individual variability and increasing environmental stress. Multiple regression analysis showed that temperature, food concentration, salinity and individual variability have significant effects on survival of A. tonsa population. These results suggest that environmental factors have great influence on zooplankton population, and individual variability has important implications for population survivability under unfavorable conditions. Given that marine ecosystems are at risk from drastic environmental changes, understanding how individual variability sustains populations could increase our capability to predict population dynamics in a changing environment.

A spatial ecosystem and populations dynamics model (SEAPODYM) Modeling of tuna and tuna-like populations

NASA Astrophysics Data System (ADS)

Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu

2008-09-01

An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

A bi-population based scheme for an explicit exploration/exploitation trade-off in dynamic environments

NASA Astrophysics Data System (ADS)

Ben-Romdhane, Hajer; Krichen, Saoussen; Alba, Enrique

2017-05-01

Optimisation in changing environments is a challenging research topic since many real-world problems are inherently dynamic. Inspired by the natural evolution process, evolutionary algorithms (EAs) are among the most successful and promising approaches that have addressed dynamic optimisation problems. However, managing the exploration/exploitation trade-off in EAs is still a prevalent issue, and this is due to the difficulties associated with the control and measurement of such a behaviour. The proposal of this paper is to achieve a balance between exploration and exploitation in an explicit manner. The idea is to use two equally sized populations: the first one performs exploration while the second one is responsible for exploitation. These tasks are alternated from one generation to the next one in a regular pattern, so as to obtain a balanced search engine. Besides, we reinforce the ability of our algorithm to quickly adapt after cnhanges by means of a memory of past solutions. Such a combination aims to restrain the premature convergence, to broaden the search area, and to speed up the optimisation. We show through computational experiments, and based on a series of dynamic problems and many performance measures, that our approach improves the performance of EAs and outperforms competing algorithms.

The Analysis of Cell Population Dynamics in Mammary Gland Development and Tumorigenesis

DTIC Science & Technology

2005-08-01

AD Award Number: DAMD17-03-1-0498 TITLE: The Analysis of Cell Population Dynamics in Mammary Gland Development and Tumorigenesis PRINCIPAL...Summary 1 Aug 2004 - 31 Jul 2005 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER The Analysis of Cell Population Dynamics in Mammary Gland Development and...STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The mammary gland is made up of several epithelial cell

Dynamic traffic assignment : genetic algorithms approach

DOT National Transportation Integrated Search

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Periodic matrix models for seasonal dynamics of structured populations with application to a seabird population.

PubMed

Cushing, J M; Henson, Shandelle M

2018-02-03

For structured populations with an annual breeding season, life-stage interactions and behavioral tactics may occur on a faster time scale than that of population dynamics. Motivated by recent field studies of the effect of rising sea surface temperature (SST) on within-breeding-season behaviors in colonial seabirds, we formulate and analyze a general class of discrete-time matrix models designed to account for changes in behavioral tactics within the breeding season and their dynamic consequences at the population level across breeding seasons. As a specific example, we focus on egg cannibalism and the daily reproductive synchrony observed in seabirds. Using the model, we investigate circumstances under which these life history tactics can be beneficial or non-beneficial at the population level in light of the expected continued rise in SST. Using bifurcation theoretic techniques, we study the nature of non-extinction, seasonal cycles as a function of environmental resource availability as they are created upon destabilization of the extinction state. Of particular interest are backward bifurcations in that they typically create strong Allee effects in population models which, in turn, lead to the benefit of possible (initial condition dependent) survival in adverse environments. We find that positive density effects (component Allee effects) due to increased adult survival from cannibalism and the propensity of females to synchronize daily egg laying can produce a strong Allee effect due to a backward bifurcation.

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

Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach

ERIC Educational Resources Information Center

Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh

2012-01-01

Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…

An approach of the exact linearization techniques to analysis of population dynamics of the mosquito Aedes aegypti.

PubMed

Dos Reis, Célia A; Florentino, Helenice de O; Cólon, Diego; Rosa, Suélia R Fleury; Cantane, Daniela R

2018-05-01

Dengue fever, chikungunya and zika are caused by different viruses and mainly transmitted by Aedes aegypti mosquitoes. These diseases have received special attention of public health officials due to the large number of infected people in tropical and subtropical countries and the possible sequels that those diseases can cause. In severe cases, the infection can have devastating effects, affecting the central nervous system, muscles, brain and respiratory system, often resulting in death. Vaccines against these diseases are still under development and, therefore, current studies are focused on the treatment of diseases and vector (mosquito) control. This work focuses on this last topic, and presents the analysis of a mathematical model describing the population dynamics of Aedes aegypti, as well as present the design of a control law for the mosquito population (vector control) via exact linearization techniques and optimal control. This control strategy optimizes the use of resources for vector control, and focuses on the aquatic stage of the mosquito life. Theoretical and computational results are also presented. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

SMALL POPULATIONS REQUIRE SPECIFIC MODELING APPROACHES FOR ASSESSING RISK

EPA Science Inventory

All populations face non-zero risks of extinction. However, the risks for small populations, and therefore the modeling approaches necessary to predict them, are different from those of large populations. These differences are currently hindering assessment of risk to small pop...

Seasonal Population Dynamics of Three Potato Pests in Washington State.

PubMed

D'Auria, Elizabeth M; Wohleb, Carrie H; Waters, Timothy D; Crowder, David W

2016-08-01

Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculella Zeller), the beet leafhopper (Circulifer tenellus Baker), and the green peach aphid (Myzus persicae Sulzer). Each of these pests directly damages potato foliage or tubers; C. tenellus and M. persicae also transmit pathogens that can drastically reduce potato yields. We monitored the seasonal population dynamics of these pests by conducting weekly sampling on a network of commercial farms from 2007 to 2014. Using these data, we developed phenology models to characterize the seasonal population dynamics of each pest based on accumulated degree-days (DD). All three pests exhibited consistent population dynamics across seasons that were mediated by temperature. Of the three pests, C. tenellus was generally the first detected in potato crops, with 90% of adults captured by 936 DD. In contrast, populations of P. operculella and M. persicae built up more slowly over the course of the season, with 90% cumulative catch by 1,590 and 2,634 DD, respectively. Understanding these seasonal patterns could help potato producers plan their IPM strategies while allowing them to move away from calendar-based applications of insecticides. More broadly, our results show how long-term monitoring studies that explore dynamics of multiple pest species can aid in developing IPM strategies in crop systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model

White-tailed deer population dynamics and adult female survival in the presence of a novel predator: Deer Population Dynamics

DOE PAGES

Chitwood, Michael C.; Lashley, Marcus A.; Kilgo, John C.; ...

2015-02-01

Recent localized declines in white-tailed deer ( Odocoileus virginianus) populations in the southeastern United States have been linked to increasing predation pressure from coyotes ( Canis latrans), a novel predator to the region. Studies have documented coyotes as the leading cause of mortality for neonates, and 1 study documented coyotes as a mortality factor for adult females. However, no study has used field-based vital rates to conduct sensitivity analyses or model deer population trajectories under potential harvest or predator removal strategies. We used low, medium, and high values of fawn survival, adult female survival, and fecundity data collected from Fortmore » Bragg Military Installation, North Carolina to demonstrate the current declining population trajectory for deer (λ = 0.905; low λ = 0.788, high λ = 1.003). Consistent with other studies of ungulates, we determined adult female survival was the most sensitive and elastic vital rate. Further, for 3 potential management (“what if”) scenarios, we projected the population for 10 years using estimated vital rates. Reducing adult female harvest (λ = 0.935; low λ = 0.875, high λ = 1.002) and coyote removal (λ = 0.995; low λ = 0.898, high λ = 1.081) reduced the current population decline, whereas combining both approaches (λ = 1.024; low λ = 0.898, high λ = 1.141) resulted in population increases. Our data indicate that for low-density deer populations with heavy predation pressure on neonates, protecting adult females from harvest may not completely offset population declines. Coyote removal might be a necessary strategy because it could possibly increase very low fawn survival, which appears to be the most important vital rate influencing λ in our study. However, managers may have to start with reductions in adult female harvest because coyote removal would have to be continuous and consistently effective, making it an impractical management approach by itself.« less

White-tailed deer population dynamics and adult female survival in the presence of a novel predator: Deer Population Dynamics

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

Chitwood, Michael C.; Lashley, Marcus A.; Kilgo, John C.

Recent localized declines in white-tailed deer ( Odocoileus virginianus) populations in the southeastern United States have been linked to increasing predation pressure from coyotes ( Canis latrans), a novel predator to the region. Studies have documented coyotes as the leading cause of mortality for neonates, and 1 study documented coyotes as a mortality factor for adult females. However, no study has used field-based vital rates to conduct sensitivity analyses or model deer population trajectories under potential harvest or predator removal strategies. We used low, medium, and high values of fawn survival, adult female survival, and fecundity data collected from Fortmore » Bragg Military Installation, North Carolina to demonstrate the current declining population trajectory for deer (λ = 0.905; low λ = 0.788, high λ = 1.003). Consistent with other studies of ungulates, we determined adult female survival was the most sensitive and elastic vital rate. Further, for 3 potential management (“what if”) scenarios, we projected the population for 10 years using estimated vital rates. Reducing adult female harvest (λ = 0.935; low λ = 0.875, high λ = 1.002) and coyote removal (λ = 0.995; low λ = 0.898, high λ = 1.081) reduced the current population decline, whereas combining both approaches (λ = 1.024; low λ = 0.898, high λ = 1.141) resulted in population increases. Our data indicate that for low-density deer populations with heavy predation pressure on neonates, protecting adult females from harvest may not completely offset population declines. Coyote removal might be a necessary strategy because it could possibly increase very low fawn survival, which appears to be the most important vital rate influencing λ in our study. However, managers may have to start with reductions in adult female harvest because coyote removal would have to be continuous and consistently effective, making it an impractical management approach by itself.« less

Population dynamics of Aphis gossypii Glover and in sole and intercropping systems of cotton and cowpea.

PubMed

Fernandes, Francisco S; Godoy, Wesley A C; Ramalho, Francisco S; Garcia, Adriano G; Santos, Bárbara D B; Malaquias, José B

2018-01-01

Population dynamics of aphids have been studied in sole and intercropping systems. These studies have required the use of more precise analytical tools in order to better understand patterns in quantitative data. Mathematical models are among the most important tools to explain the dynamics of insect populations. This study investigated the population dynamics of aphids Aphis gossypii and Aphis craccivora over time, using mathematical models composed of a set of differential equations as a helpful analytical tool to understand the population dynamics of aphids in arrangements of cotton and cowpea. The treatments were sole cotton, sole cowpea, and three arrangements of cotton intercropped with cowpea (t1, t2 and t3). The plants were infested with two aphid species and were evaluated at 7, 14, 28, 35, 42, and 49 days after the infestations. Mathematical models were used to fit the population dynamics of two aphid species. There were good fits for aphid dynamics by mathematical model over time. The highest population peak of both species A. gossypii and A. craccivora was found in the sole crops, and the lowest population peak was found in crop system t2. These results are important for integrated management programs of aphids in cotton and cowpea.

Dynamical approach to the cosmological constant.

PubMed

Mukohyama, Shinji; Randall, Lisa

2004-05-28

We consider a dynamical approach to the cosmological constant. There is a scalar field with a potential whose minimum occurs at a generic, but negative, value for the vacuum energy, and it has a nonstandard kinetic term whose coefficient diverges at zero curvature as well as the standard kinetic term. Because of the divergent coefficient of the kinetic term, the lowest energy state is never achieved. Instead, the cosmological constant automatically stalls at or near zero. The merit of this model is that it is stable under radiative corrections and leads to stable dynamics, despite the singular kinetic term. The model is not complete, however, in that some reheating is required. Nonetheless, our approach can at the very least reduce fine-tuning by 60 orders of magnitude or provide a new mechanism for sampling possible cosmological constants and implementing the anthropic principle.

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

The population dynamics of bacteria, phage and RM Systems

NASA Astrophysics Data System (ADS)

Guet, Calin; Levin, Bruce; Pleska, Maros

Viruses drive and mediate bacterial evolution as parasites and vectors of horizontal gene transfer, respectively. Temperate bacteriophages, defined by the ability to lysogenize a fraction of hosts and to transmit horizontally as well as vertically in the form of prophages, frequently carry genes that increase fitness or contribute to bacterial pathogenicity. Restriction-modification (RM) systems, which are widely diverse and ubiquitous among bacteria, can prevent infections leading to lysis, but their effect on lysogeny is not clear. We show that RM systems prevent lytic and lysogenic infections to the same extent and therefore represent a molecular barrier to prophage acquisition. Surprisingly, we find that this negative effect can be overcome and even reversed at the population level, as a consequence of dynamic interactions between viruses, hosts and RM systems. Thus the population dynamics of bacteria carrying RM systems impacts bacterial genome-wide evolution. .

Time-Dependent Thomas-Fermi Approach for Electron Dynamics in Metal Clusters

NASA Astrophysics Data System (ADS)

Domps, A.; Reinhard, P.-G.; Suraud, E.

1998-06-01

We propose a time-dependent Thomas-Fermi approach to the (nonlinear) dynamics of many-fermion systems. The approach relies on a hydrodynamical picture describing the system in terms of collective flow. We investigate in particular an application to electron dynamics in metal clusters. We make extensive comparisons with fully fledged quantal dynamical calculations and find overall good agreement. The approach thus provides a reliable and inexpensive scheme to study the electronic response of large metal clusters.

Phase-Space Transport of Stochastic Chaos in Population Dynamics of Virus Spread

NASA Astrophysics Data System (ADS)

Billings, Lora; Bollt, Erik M.; Schwartz, Ira B.

2002-06-01

A general way to classify stochastic chaos is presented and applied to population dynamics models. A stochastic dynamical theory is used to develop an algorithmic tool to measure the transport across basin boundaries and predict the most probable regions of transport created by noise. The results of this tool are illustrated on a model of virus spread in a large population, where transport regions reveal how noise completes the necessary manifold intersections for the creation of emerging stochastic chaos.

Long timestep dynamics of peptides by the dynamics driver approach.

PubMed

Derreumaux, P; Schlick, T

1995-04-01

Previous experience with the Langevin/implicit-Euler scheme for dynamics ("LI") on model systems (butane, water) has shown that LI is numerically stable for timesteps in the 5-20 fs range but quenches high-frequency modes. To explore applications to polypeptides, we apply LI to model systems (several dipeptides, a tetrapeptide, and a 13-residue oligoalanine) and also develop a new dynamics driver approach ("DA"). The DA scheme, based on LI, addresses the important issue of proper sampling, which is unlikely to be solved by small-timestep integration methods or implicit methods with intrinsic damping at room temperature, such as LI. Equilibrium averages, time-dependent molecular properties, and sampling trends at room temperature are reported for both LI and DA dynamics simulations, which are then compared to those generated by a standard explicit discretization of the Langevin equation with a 1 fs timestep. We find that LI's quenching effects are severe on both the fast and slow (due to vibrational coupling) frequency modes of all-atom polypeptides and lead to more restricted dynamics at moderate timesteps (40 fs). The DA approach empirically counteracts these damping effects by adding random atomic perturbations to the coordinates at each step (before the minimization of a dynamics function). By restricting the energetic fluctuations and controlling the kinetic energy, we are able with a 60 fs timestep to generate continuous trajectories that sample more of the relevant conformational space and also reproduce reasonably Boltzmann statistics. Although the timescale for transition may be accelerated by the DA approach, the transitional information obtained for the alanine dipeptide and the tetrapeptide is consistent with that obtained by several other theoretical approaches that focus specifically on the determination of pathways. While the trajectory for oligoalanine by the explicit scheme over the nanosecond timeframe remains in the vicinity of the full alpha R

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

Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer

PubMed Central

Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C.; Moen, Jon

2016-01-01

Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region’s most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species’ total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi

Long-Term Trends and Role of Climate in the Population Dynamics of Eurasian Reindeer.

PubMed

Uboni, Alessia; Horstkotte, Tim; Kaarlejärvi, Elina; Sévêque, Anthony; Stammler, Florian; Olofsson, Johan; Forbes, Bruce C; Moen, Jon

2016-01-01

Temperature is increasing in Arctic and sub-Arctic regions at a higher rate than anywhere else in the world. The frequency and nature of precipitation events are also predicted to change in the future. These changes in climate are expected, together with increasing human pressures, to have significant impacts on Arctic and sub-Arctic species and ecosystems. Due to the key role that reindeer play in those ecosystems, it is essential to understand how climate will affect the region's most important species. Our study assesses the role of climate on the dynamics of fourteen Eurasian reindeer (Rangifer tarandus) populations, using for the first time data on reindeer abundance collected over a 70-year period, including both wild and semi-domesticated reindeer, and covering more than half of the species' total range. We analyzed trends in population dynamics, investigated synchrony among population growth rates, and assessed the effects of climate on population growth rates. Trends in the population dynamics were remarkably heterogeneous. Synchrony was apparent only among some populations and was not correlated with distance among population ranges. Proxies of climate variability mostly failed to explain population growth rates and synchrony. For both wild and semi-domesticated populations, local weather, biotic pressures, loss of habitat and human disturbances appear to have been more important drivers of reindeer population dynamics than climate. In semi-domesticated populations, management strategies may have masked the effects of climate. Conservation efforts should aim to mitigate human disturbances, which could exacerbate the potentially negative effects of climate change on reindeer populations in the future. Special protection and support should be granted to those semi-domesticated populations that suffered the most because of the collapse of the Soviet Union, in order to protect the livelihood of indigenous peoples that depend on the species, and the multi

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Population ecology, nonlinear dynamics, and social evolution. I. Associations among nonrelatives.

PubMed

Avilés, Leticia; Abbot, Patrick; Cutter, Asher D

2002-02-01

Using an individual-based and genetically explicit simulation model, we explore the evolution of sociality within a population-ecology and nonlinear-dynamics framework. Assuming that individual fitness is a unimodal function of group size and that cooperation may carry a relative fitness cost, we consider the evolution of one-generation breeding associations among nonrelatives. We explore how parameters such as the intrinsic rate of growth and group and global carrying capacities may influence social evolution and how social evolution may, in turn, influence and be influenced by emerging group-level and population-wide dynamics. We find that group living and cooperation evolve under a wide range of parameter values, even when cooperation is costly and the interactions can be defined as altruistic. Greater levels of cooperation, however, did evolve when cooperation carried a low or no relative fitness cost. Larger group carrying capacities allowed the evolution of larger groups but also resulted in lower cooperative tendencies. When the intrinsic rate of growth was not too small and control of the global population size was density dependent, the evolution of large cooperative tendencies resulted in dynamically unstable groups and populations. These results are consistent with the existence and typical group sizes of organisms ranging from the pleometrotic ants to the colonial birds and the global population outbreaks and crashes characteristic of organisms such as the migratory locusts and the tree-killing bark beetles.

Elevated nonlinearity as an indicator of shifts in the dynamics of populations under stress.

PubMed

Dakos, Vasilis; Glaser, Sarah M; Hsieh, Chih-Hao; Sugihara, George

2017-03-01

Populations occasionally experience abrupt changes, such as local extinctions, strong declines in abundance or transitions from stable dynamics to strongly irregular fluctuations. Although most of these changes have important ecological and at times economic implications, they remain notoriously difficult to detect in advance. Here, we study changes in the stability of populations under stress across a variety of transitions. Using a Ricker-type model, we simulate shifts from stable point equilibrium dynamics to cyclic and irregular boom-bust oscillations as well as abrupt shifts between alternative attractors. Our aim is to infer the loss of population stability before such shifts based on changes in nonlinearity of population dynamics. We measure nonlinearity by comparing forecast performance between linear and nonlinear models fitted on reconstructed attractors directly from observed time series. We compare nonlinearity to other suggested leading indicators of instability (variance and autocorrelation). We find that nonlinearity and variance increase in a similar way prior to the shifts. By contrast, autocorrelation is strongly affected by oscillations. Finally, we test these theoretical patterns in datasets of fisheries populations. Our results suggest that elevated nonlinearity could be used as an additional indicator to infer changes in the dynamics of populations under stress. © 2017 The Author(s).

Argentine stem weevil ( Listronotus bonariensis, Coleoptera: Curculionidae) population dynamics in Canterbury, New Zealand dryland pasture.

PubMed

Goldson, S L; Barron, M C; Kean, J M; van Koten, C

2011-06-01

The Argentine stem weevil (Listronotus bonariensis) was an economically important pest in New Zealand pastures until the release of the parasitoid Microctonus hyperodae. This contribution uses historical data to investigate the regulation of the pest populations prior to, and somewhat during, the establishment of this parasitoid in dryland Canterbury, New Zealand. Thus, a significant goal of this study is to provide an L. bonariensis population dynamics baseline for any future work that aims to analyse the full effects of M. hyperodae on the weevil, now that equilibrium with the weevil host has been reached.The population dynamics of L. bonariensis, based on a life-table approach, were investigated using data collected regularly for eight years from populations in Canterbury, New Zealand. The key factor affecting end-of-season L. bonariensis density was found to be variation in second generation fourth instar prepupal and pupal mortality. This may have been caused by arrested development and ongoing mortality resulting from the onset of cooler autumnal conditions.A compensatory response was found in recruitment to the second summer weevil generation, whereby the realised fecundity of the emergent first summer generation of weevils was found to be negatively related to the density of adult weevils per ryegrass tiller. This is the first time that this has been found via long-term population analysis of L. bonariensis, although indications of this have been found elsewhere in caging, pot and small plot experiments.In this study, the effect of the parasitoid biocontrol agent Microctonus hyperodae on L. bonariensis population dynamics was unclear, as the analysis covered a period when the parasitoid Microctonus hyperodae was introduced and still establishing. It does, however, raise important questions for future analysis in terms of the interaction between parasitism and unrealised fecundity.The results in this contribution also highlighted regional differences

Heterogeneous population dynamics and scaling laws near epidemic outbreaks.

PubMed

Widder, Andreas; Kuehn, Christian

2016-10-01

In this paper, we focus on the influence of heterogeneity and stochasticity of the population on the dynamical structure of a basic susceptible-infected-susceptible (SIS) model. First we prove that, upon a suitable mathematical reformulation of the basic reproduction number, the homogeneous system and the heterogeneous system exhibit a completely analogous global behaviour. Then we consider noise terms to incorporate the fluctuation effects and the random import of the disease into the population and analyse the influence of heterogeneity on warning signs for critical transitions (or tipping points). This theory shows that one may be able to anticipate whether a bifurcation point is close before it happens. We use numerical simulations of a stochastic fast-slow heterogeneous population SIS model and show various aspects of heterogeneity have crucial influences on the scaling laws that are used as early-warning signs for the homogeneous system. Thus, although the basic structural qualitative dynamical properties are the same for both systems, the quantitative features for epidemic prediction are expected to change and care has to be taken to interpret potential warning signs for disease outbreaks correctly.

Population Dynamics of Belonolaimus longicaudatusin a Cotton Production System

PubMed Central

Crow, W. T.; Weingartner, D. P.; McSorley, R.; Dickson, D. W.

2000-01-01

Belonolaimus longicaudatus is a recognized pathogen of cotton (Gossypium hirsutum), but insufficient information is available on the population dynamics and economic thresholds of B. longicaudatus in cotton production. In this study, data collected from a field in Florida were used to develop models predicting population increases of B. longicaudatus on cotton and population declines under clean fallow. Population densities of B. longicaudatus increased on cotton, reaching a carrying capacity of 139 nematodes/130 cm³ of soil, but decreased exponentially during periods of bare fallow. The model indicated that population densities should decrease each year of monocropped cotton, if an alternate host is not present between sequential cotton crops. Economic thresholds derived from published damage functions and current prices for cotton and nematicides varied from 2 to 5 B. longicaudatus/130 cm³ of soil, depending on the nematicide used. PMID:19270968

Binary Populations and Stellar Dynamics in Young Clusters

NASA Astrophysics Data System (ADS)

Vanbeveren, D.; Belkus, H.; Van Bever, J.; Mennekens, N.

2008-06-01

We first summarize work that has been done on the effects of binaries on theoretical population synthesis of stars and stellar phenomena. Next, we highlight the influence of stellar dynamics in young clusters by discussing a few candidate UFOs (unconventionally formed objects) like intermediate mass black holes, η Car, ζ Pup, γ2 Velorum and WR 140.

Dynamic analysis of a parasite population model.

PubMed

Sibona, G J; Condat, C A

2002-03-01

We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.

Dynamic analysis of a parasite population model

NASA Astrophysics Data System (ADS)

Sibona, G. J.; Condat, C. A.

2002-03-01

We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.

Computational neuropharmacology: dynamical approaches in drug discovery.

PubMed

Aradi, Ildiko; Erdi, Péter

2006-05-01

Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

Population dynamics and angler exploitation of the unique muskellunge population in Shoepack Lake, Voyageurs National Park, Minnesota

USGS Publications Warehouse

Frohnauer, N.K.; Pierce, C.L.; Kallemeyn, L.W.

2007-01-01

A unique population of muskellunge Esox masquinongy inhabits Shoepack Lake in Voyageurs National Park, Minnesota. Little is known about its status, dynamics, and angler exploitation, and there is concern for the long-term viability of this population. We used intensive sampling and mark-recapture methods to quantify abundance, survival, growth, condition, age at maturity and fecundity and angler surveys to quantify angler pressure, catch rates, and exploitation. During our study, heavy rain washed out a dam constructed by beavers Castor canadensis which regulates the water level at the lake outlet, resulting in a nearly 50% reduction in surface area. We estimated a population size of 1,120 adult fish at the beginning of the study. No immediate reduction in population size was detected in response to the loss of lake area, although there was a gradual, but significant, decline in population size over the 2-year study. Adults grew less than 50 mm per year, and relative weight (W r) averaged roughly 80. Anglers were successful in catching, on average, two fish during a full day of angling, but harvest was negligible. Shoepack Lake muskellunge exhibit much slower growth rates and lower condition, but much higher densities and angler catch per unit effort (CPUE), than other muskellunge populations. The unique nature, limited distribution, and location of this population in a national park require special consideration for management. The results of this study provide the basis for assessing the long-term viability of the Shoepack Lake muskellunge population through simulations of long-term population dynamics and genetically effective population size. ?? Copyright by the American Fisheries Society 2007.

Cracks dynamics under tensional stress - a DEM approach

NASA Astrophysics Data System (ADS)

Debski, Wojciech; Klejment, Piotr; Kosmala, Alicja; Foltyn, Natalia; Szpindler, Maciej

2017-04-01

Breaking and fragmentation of solid materials is an extremely complex process involving scales ranging from an atomic scale (breaking inter-atomic bounds) up to thousands of kilometers in case of catastrophic earthquakes (in energy scale it ranges from single eV up to 1024 J). Such a large scale span of breaking processes opens lot of questions like, for example, scaling of breaking processes, existence of factors controlling final size of broken area, existence of precursors, dynamics of fragmentation, to name a few. The classical approach to study breaking process at seismological scales, i.e., physical processes in earthquake foci, is essentially based on two factors: seismic data (mostly) and the continuum mechanics (including the linear fracture mechanics). Such approach has been gratefully successful in developing kinematic (first) and dynamic (recently) models of seismic rupture and explaining many of earthquake features observed all around the globe. However, such approach will sooner or latter face a limitation due to a limited information content of seismic data and inherit limitations of the fracture mechanics principles. A way of avoiding this expected limitation is turning an attention towards a well established in physics method of computational simulations - a powerful branch of contemporary physics. In this presentation we discuss preliminary results of analysis of fracturing dynamics under external tensional forces using the Discrete Element Method approach. We demonstrate that even under a very simplified tensional conditions, the fragmentation dynamics is a very complex process, including multi-fracturing, spontaneous fracture generation and healing, etc. We also emphasis a role of material heterogeneity on the fragmentation process.

Force and Moment Approach for Achievable Dynamics Using Nonlinear Dynamic Inversion

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.; Bacon, Barton J.

1999-01-01

This paper describes a general form of nonlinear dynamic inversion control for use in a generic nonlinear simulation to evaluate candidate augmented aircraft dynamics. The implementation is specifically tailored to the task of quickly assessing an aircraft's control power requirements and defining the achievable dynamic set. The achievable set is evaluated while undergoing complex mission maneuvers, and perfect tracking will be accomplished when the desired dynamics are achievable. Variables are extracted directly from the simulation model each iteration, so robustness is not an issue. Included in this paper is a description of the implementation of the forces and moments from simulation variables, the calculation of control effectiveness coefficients, methods for implementing different types of aerodynamic and thrust vectoring controls, adjustments for control effector failures, and the allocation approach used. A few examples illustrate the perfect tracking results obtained.

Thermal noise model of antiferromagnetic dynamics: A macroscopic approach

NASA Astrophysics Data System (ADS)

Li, Xilai; Semenov, Yuriy; Kim, Ki Wook

In the search for post-silicon technologies, antiferromagnetic (AFM) spintronics is receiving widespread attention. Due to faster dynamics when compared with its ferromagnetic counterpart, AFM enables ultra-fast magnetization switching and THz oscillations. A crucial factor that affects the stability of antiferromagnetic dynamics is the thermal fluctuation, rarely considered in AFM research. Here, we derive from theory both stochastic dynamic equations for the macroscopic AFM Neel vector (L-vector) and the corresponding Fokker-Plank equation for the L-vector distribution function. For the dynamic equation approach, thermal noise is modeled by a stochastic fluctuating magnetic field that affects the AFM dynamics. The field is correlated within the correlation time and the amplitude is derived from the energy dissipation theory. For the distribution function approach, the inertial behavior of AFM dynamics forces consideration of the generalized space, including both coordinates and velocities. Finally, applying the proposed thermal noise model, we analyze a particular case of L-vector reversal of AFM nanoparticles by voltage controlled perpendicular magnetic anisotropy (PMA) with a tailored pulse width. This work was supported, in part, by SRC/NRI SWAN.

Noise-induced effects in population dynamics

NASA Astrophysics Data System (ADS)

Spagnolo, Bernardo; Cirone, Markus; La Barbera, Antonino; de Pasquale, Ferdinando

2002-03-01

We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of spatial patterns in the first case. In the other case we obtain the asymptotic behaviour of the time average of the ith population and discuss the effect of the noise on the probability distributions of the population and of the local field.

Omics and Environmental Science Genomic Approaches With Natural Fish Populations From Polluted Environments

PubMed Central

Bozinovic, Goran; Oleksiak, Marjorie F.

2010-01-01

Transcriptomics and population genomics are two complementary genomic approaches that can be used to gain insight into pollutant effects in natural populations. Transcriptomics identify altered gene expression pathways while population genomics approaches more directly target the causative genomic polymorphisms. Neither approach is restricted to a pre-determined set of genes or loci. Instead, both approaches allow a broad overview of genomic processes. Transcriptomics and population genomic approaches have been used to explore genomic responses in populations of fish from polluted environments and have identified sets of candidate genes and loci that appear biologically important in response to pollution. Often differences in gene expression or loci between polluted and reference populations are not conserved among polluted populations suggesting a biological complexity that we do not yet fully understand. As genomic approaches become less expensive with the advent of new sequencing and genotyping technologies, they will be more widely used in complimentary studies. However, while these genomic approaches are immensely powerful for identifying candidate gene and loci, the challenge of determining biological mechanisms that link genotypes and phenotypes remains. PMID:21072843

DynaPop-X: A population dynamics model applied to spatio-temporal exposure assessment - Implementation aspects from the CRISMA project

NASA Astrophysics Data System (ADS)

Aubrecht, Christoph; Steinnocher, Klaus; Humer, Heinrich; Huber, Hermann

2014-05-01

In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J

Single-virion sequencing of lamivudine-treated HBV populations reveal population evolution dynamics and demographic history.

PubMed

Zhu, Yuan O; Aw, Pauline P K; de Sessions, Paola Florez; Hong, Shuzhen; See, Lee Xian; Hong, Lewis Z; Wilm, Andreas; Li, Chen Hao; Hue, Stephane; Lim, Seng Gee; Nagarajan, Niranjan; Burkholder, William F; Hibberd, Martin

2017-10-27

Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients - once before antiviral treatment and once after viral rebound due to resistance. With single-virion sequencing, we obtained 248-8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

A covariant approach to entropic dynamics

NASA Astrophysics Data System (ADS)

Ipek, Selman; Abedi, Mohammad; Caticha, Ariel

2017-06-01

Entropic Dynamics (ED) is a framework for constructing dynamical theories of inference using the tools of inductive reasoning. A central feature of the ED framework is the special focus placed on time. In [2] a global entropic time was used to derive a quantum theory of relativistic scalar fields. This theory, however, suffered from a lack of explicit or manifest Lorentz symmetry. In this paper we explore an alternative formulation in which the relativistic aspects of the theory are manifest. The approach we pursue here is inspired by the methods of Dirac, Kuchař, and Teitelboim in their development of covariant Hamiltonian approaches. The key ingredient here is the adoption of a local notion of entropic time, which allows compatibility with an arbitrary notion of simultaneity. However, in order to ensure that the evolution does not depend on the particular sequence of hypersurfaces, we must impose a set of constraints that guarantee a consistent evolution.

Dynamic regimes of local homogeneous population model with time lag

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

Neverova, Galina; Frisman, Efim

We investigated Moran - Ricker model with time lag 1. It is made analytical and numerical study of the model. It is shown there is co-existence of various dynamic regimes under the same values of parameters. The model simultaneously possesses several different limit regimes: stable state, periodic fluctuations, and chaotic attractor. The research results show if present population size substantially depends on population number of previous year then it is observed quasi-periodic oscillations. Fluctuations with period 2 occur when the growth of population size is regulated by density dependence in the current year.

Dynamic assessments of population exposure to urban greenspace using multi-source big data.

PubMed

Song, Yimeng; Huang, Bo; Cai, Jixuan; Chen, Bin

2018-09-01

A growing body of evidence has proven that urban greenspace is beneficial to improve people's physical and mental health. However, knowledge of population exposure to urban greenspace across different spatiotemporal scales remains unclear. Moreover, the majority of existing environmental assessments are unable to quantify how residents enjoy their ambient greenspace during their daily life. To deal with this challenge, we proposed a dynamic method to assess urban greenspace exposure with the integration of mobile-phone locating-request (MPL) data and high-spatial-resolution remote sensing images. This method was further applied to 30 major cities in China by assessing cities' dynamic greenspace exposure levels based on residents' surrounding areas with different buffer scales (0.5km, 1km, and 1.5km). Results showed that regarding residents' 0.5-km surrounding environment, Wenzhou and Hangzhou were found to be with the greenest exposure experience, whereas Zhengzhou and Tangshan were the least ones. The obvious diurnal and daily variations of population exposure to their surrounding greenspace were also identified to be highly correlated with the distribution pattern of urban greenspace and the dynamics of human mobility. Compared with two common measurements of urban greenspace (green coverage rate and green area per capita), the developed method integrated the dynamics of population distribution and geographic locations of urban greenspace into the exposure assessment, thereby presenting a more reasonable way to assess population exposure to urban greenspace. Additionally, this dynamic framework could hold potential utilities in supporting urban planning studies and environmental health studies and advancing our understanding of the magnitude of population exposure to greenspace at different spatiotemporal scales. Copyright © 2018 Elsevier B.V. All rights reserved.

Proceedings: population dynamics, impacts, and integrated management of forest defoliating insects

Treesearch

M.L. McManus; A.M., eds. Liebhold

1998-01-01

This publication contains 52 research papers about the population ecology and management of forest insect defoliators. These papers were presented at a joint meeting of working parties S7.03.06, "Integrated Management of Forest Defoliating Insects", and S7.03.07, "Population dynamics of forest insects", of the International Union of Forestry...

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.

Sexual reproduction and population dynamics: the role of polygyny and demographic sex differences.

PubMed Central

Lindström, J; Kokko, H

1998-01-01

Most models of population dynamics do not take sexual reproduction into account (i.e., they do not consider the role of males). However, assumptions behind this practice--that no demographic sex differences exist and males are always abundant enough to fertilize all the females--are usually not justified in natural populations. On the contrary, demographic sex differences are common, especially in polygynous species. Previous models that consider sexual reproduction report a stabilizing effect through mixing of different genotypes, thus suggesting a decrease in the propensity for complex of dynamics in sexually reproducing populations. Here we show that considering the direct role of males in reproduction and density dependence leads to the conclusion that a two-sex model is not necessarily more stable compared with the corresponding one-sex model. Although solutions exist where sexual reproduction has a stabilizing effect even when no genotypic variability is included (primarily when associated with monogamy), factors like polygyny, sex differences in survival or density dependence, and possible alterations of the primary sex ratio (the Trivers-Willard mechanism), may enlarge the parametric region of complex dynamics. Sexual reproduction therefore does not necessarily increase the stability of population dynamics and can have destabilizing effects, at least in species with complicated mating systems and sexual dimorphism. PMID:9606132

Local interactions lead to pathogen-driven change to host population dynamics.

PubMed

Boots, Michael; Childs, Dylan; Reuman, Daniel C; Mealor, Michael

2009-10-13

Individuals tend to interact more strongly with nearby individuals or within particular social groups. Recent theoretical advances have demonstrated that these within-population relationships can have fundamental implications for ecological and evolutionary dynamics. In particular, contact networks are crucial to the spread and evolution of disease. However, the theory remains largely untested experimentally. Here, we manipulate habitat viscosity and thereby the frequency of local interactions in an insect-pathogen model system in which the virus had previously been shown to have little effect on host population dynamics. At high viscosity, the pathogen caused the collapse of dominant and otherwise stable host generation cycles. Modeling shows that this collapse can be explained by an increase in the frequency of intracohort interactions relative to intercohort interactions, leading to more disease transmission. Our work emphasizes that spatial structure can subtly mediate intraspecific competition and the effects of natural enemies. A decrease in dispersal in a population may actually (sometimes rather counterintuitively) intensify the effects of parasites. Broadly, because anthropological and environmental change often cause changes in population mixing, our work highlights the potential for dramatic changes in the effects of parasites on host populations.

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.

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.

Effective Population Size Dynamics and the Demographic Collapse of Bornean Orang-Utans

PubMed Central

Goossens, Benoit; Nater, Alexander; Morf, Nadja; Salmona, Jordi; Bruford, Michael W.; Van Schaik, Carel P.; Krützen, Michael; Chikhi, Lounès

2012-01-01

Bornean orang-utans experienced a major demographic decline and local extirpations during the Pleistocene and Holocene due to climate change, the arrival of modern humans, of farmers and recent commercially-driven habitat loss and fragmentation. The recent loss of habitat and its dramatic fragmentation has affected the patterns of genetic variability and differentiation among the remaining populations and increased the extinction risk of the most isolated ones. However, the contribution of recent demographic events to such genetic patterns is still not fully clear. Indeed, it can be difficult to separate the effects of recent anthropogenic fragmentation from the genetic signature of prehistoric demographic events. Here, we investigated the genetic structure and population size dynamics of orang-utans from different sites. Altogether 126 individuals were analyzed and a full-likelihood Bayesian approach was applied. All sites exhibited clear signals of population decline. Population structure is known to generate spurious bottleneck signals and we found that it does indeed contribute to the signals observed. However, population structure alone does not easily explain the observed patterns. The dating of the population decline varied across sites but was always within the 200–2000 years period. This suggests that in some sites at least, orang-utan populations were affected by demographic events that started before the recent anthropogenic effects that occurred in Borneo. These results do not mean that the recent forest exploitation did not leave its genetic mark on orang-utans but suggests that the genetic pool of orang-utans is also impacted by more ancient events. While we cannot identify the main cause for this decline, our results suggests that the decline may be related to the arrival of the first farmers or climatic events, and that more theoretical work is needed to understand how multiple demographic events impact the genome of species and how we can assess

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

Forster, Robert Burke

2006-12-01

This thesis explores how natural selection acts on organisms such as viruses that have either highly error-prone reproduction or face variable environmental conditions or both. By modeling population dynamics under these conditions, we gain a better understanding of the selective forces at work, both in our simulations and hopefully also in real organisms. With an understanding of the important factors in natural selection we can forecast not only the immediate fate of an existing population but also in what directions such a population might evolve in the future. We demonstrate that the concept of a quasispecies is relevant to evolution in a neutral fitness landscape. Motivated by RNA viruses such as HIV, we use RNA secondary structure as our model system and find that quasispecies effects arise both rapidly and in realistically small populations. We discover that the evolutionary effects of neutral drift, punctuated equilibrium and the selection for mutational robustness extend to the concept of a quasispecies. In our study of periodic environments, we consider the tradeoffs faced by quasispecies in adapting to environmental change. We develop an analytical model to predict whether evolution favors short-term or long-term adaptation and validate our model through simulation. Our results bear directly on the population dynamics of viruses such as West Nile that alternate between two host species. More generally, we discover that a selective pressure exists under these conditions to fuse or split genes with complementary environmental functions. Lastly, we study the general effects of frequency-dependent selection on two strains competing in a periodic environment. Under very general assumptions, we prove that stable coexistence rather than extinction is the likely outcome. The population dynamics of this system may be as simple as stable equilibrium or as complex as deterministic chaos.

Survival and Population Dynamics of the Marabou Stork in an Isolated Population, Swaziland

PubMed Central

Monadjem, Ara; Kane, Adam; Botha, Andre; Dalton, Desire; Kotze, Antoinette

2012-01-01

Investigating the ecology of long lived birds is particularly challenging owing to the time scales involved. Here an analysis is presented of a long term study of the survival and population dynamics of the marabou stork (Leptoptilos crumeniferus), a wide ranging scavenging bird from Sub-Saharan Africa. Using resightings data of tagged nestlings and free flying birds we show that the stork population can be divided into three general life stages with unique survival probabilities and fecundities. Fecundity of the storks is inversely related to rainfall during their breeding season. Corroborative evidence for a metapopulation structure is discussed highlighting the impact of the Swaziland birds on the ecology of the species in the broader region. The importance of tag loss or illegibility over time is highlighted. Clearly, any attempt at conserving a species will require a detailed understanding of its population structure, of the sort examined here. PMID:23029517

Population health diagnosis with an ecohealth approach

PubMed Central

Arenas-Monreal, Luz; Cortez-Lugo, Marlene; Parada-Toro, Irene; Pacheco-Magaña, Lilian E; Magaña-Valladares, Laura

2015-01-01

OBJECTIVE To analyze the characteristics of health diagnosis according to the ecohealth approach in rural and urban communities in Mexico. METHODS Health diagnosis were conducted in La Nopalera, from December 2007 to October 2008, and in Atlihuayan, from December 2010 to October 2011. The research was based on three principles of the ecohealth approach: transdisciplinarity, community participation, gender and equity. To collect information, a joint methodology and several techniques were used to stimulate the participation of inhabitants. The diagnostic exercise was carried out in five phases that went from collecting information to prioritization of problems. RESULTS The constitution of the transdisciplinary team, as well as the participation of the population and the principle of gender/equity were differentials between the communities. In the rural community, the active participation of inhabitants and authorities was achieved and the principles of transdisciplinarity and gender/equity were incorporated. CONCLUSIONS With all the difficulties that entails the boost in participation, the incorporation of gender/equity and transdisciplinarity in health diagnosis allowed a holistic public health approach closer to the needs of the population. PMID:26538099

Modelling the dynamics of feral alfalfa populations and its management implications.

PubMed

Bagavathiannan, Muthukumar V; Begg, Graham S; Gulden, Robert H; Van Acker, Rene C

2012-01-01

Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be

Effects of Peanut-Tobacco Rotations on Population Dynamics of Meloidogyne arenaria in Mixed Race Populations.

PubMed

Hirunsalee, A; Barker, K R; Beute, M K

1995-06-01

A 3-year microplot study was initiated to characterize the population dynamics, reproduction potential, and survivorship of single or mixed populations of Meloidogyne arenaria race 1 (Ma1) and race 2 (Ma2), as affected by crop rotations of peanut 'Florigiant' and M. incognita races 1 and 3-resistant 'McNair 373' and susceptible 'Coker 371-Gold' tobacco. Infection, reproduction, and root damage by Ma2 on peanut and by Ma1 on resistant tobacco were limited in the first year. Infection, reproduction, and root-damage potentials on susceptible tobacco were similar for Ma1 and Ma2. In the mixed (1:1) population, Ma1 was dominant on peanut and Ma2 was dominant on both tobacco cultivars. Crop rotation affected the population dynamics of different nematode races. For years 2 and 3, the low numbers of Ma1 and Ma2 from a previous-year poor host increased rapidly on suitable hosts. Ma1 had greater reproduction factors ([RF] = population density at harvest/population density at preplandng) than did Ma2 and Ma1 + Ma2 in second-year peanut plots following first-year resistant tobacco, and in third-year peanut plots following second-year tobacco. In mixed infestations, Ma1 predominated over Ma2 in previous-year peanut plots, whereas Ma2 predominated over Ma1 in previous-year tobacco plots. Moderate damage on resistant tobacco was induced by Ma1 in the second year. In the third year, moderate damage on peanut was associated with 'Ma2' from previous-year peanut plots. The resistant tobacco supported sufficient reproduction of Ma1 over 2 years to effect moderate damage and yield suppression to peanut in year 3.

Effects of Peanut-Tobacco Rotations on Population Dynamics of Meloidogyne arenaria in Mixed Race Populations

PubMed Central

Hirunsalee, Anan; Barker, K. R.; Beute, M. K.

1995-01-01

A 3-year microplot study was initiated to characterize the population dynamics, reproduction potential, and survivorship of single or mixed populations of Meloidogyne arenaria race 1 (Ma1) and race 2 (Ma2), as affected by crop rotations of peanut 'Florigiant' and M. incognita races 1 and 3-resistant 'McNair 373' and susceptible 'Coker 371-Gold' tobacco. Infection, reproduction, and root damage by Ma2 on peanut and by Ma1 on resistant tobacco were limited in the first year. Infection, reproduction, and root-damage potentials on susceptible tobacco were similar for Ma1 and Ma2. In the mixed (1:1) population, Ma1 was dominant on peanut and Ma2 was dominant on both tobacco cultivars. Crop rotation affected the population dynamics of different nematode races. For years 2 and 3, the low numbers of Ma1 and Ma2 from a previous-year poor host increased rapidly on suitable hosts. Ma1 had greater reproduction factors ([RF] = population density at harvest/population density at preplandng) than did Ma2 and Ma1 + Ma2 in second-year peanut plots following first-year resistant tobacco, and in third-year peanut plots following second-year tobacco. In mixed infestations, Ma1 predominated over Ma2 in previous-year peanut plots, whereas Ma2 predominated over Ma1 in previous-year tobacco plots. Moderate damage on resistant tobacco was induced by Ma1 in the second year. In the third year, moderate damage on peanut was associated with 'Ma2' from previous-year peanut plots. The resistant tobacco supported sufficient reproduction of Ma1 over 2 years to effect moderate damage and yield suppression to peanut in year 3. PMID:19277278

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

Auctions with Dynamic Populations: Efficiency and Revenue Maximization

NASA Astrophysics Data System (ADS)

Said, Maher

We study a stochastic sequential allocation problem with a dynamic population of privately-informed buyers. We characterize the set of efficient allocation rules and show that a dynamic VCG mechanism is both efficient and periodic ex post incentive compatible; we also show that the revenue-maximizing direct mechanism is a pivot mechanism with a reserve price. We then consider sequential ascending auctions in this setting, both with and without a reserve price. We construct equilibrium bidding strategies in this indirect mechanism where bidders reveal their private information in every period, yielding the same outcomes as the direct mechanisms. Thus, the sequential ascending auction is a natural institution for achieving either efficient or optimal outcomes.

Protein displacements under external forces: An atomistic Langevin dynamics approach.

PubMed

Gnandt, David; Utz, Nadine; Blumen, Alexander; Koslowski, Thorsten

2009-02-28

We present a fully atomistic Langevin dynamics approach as a method to simulate biopolymers under external forces. In the harmonic regime, this approach permits the computation of the long-term dynamics using only the eigenvalues and eigenvectors of the Hessian matrix of second derivatives. We apply this scheme to identify polymorphs of model proteins by their mechanical response fingerprint, and we relate the averaged dynamics of proteins to their biological functionality, with the ion channel gramicidin A, a phosphorylase, and neuropeptide Y as examples. In an environment akin to dilute solutions, even small proteins show relaxation times up to 50 ns. Atomically resolved Langevin dynamics computations have been performed for the stretched gramicidin A ion channel.

A self-cognizant dynamic system approach for prognostics and health management

NASA Astrophysics Data System (ADS)

Bai, Guangxing; Wang, Pingfeng; Hu, Chao

2015-03-01

Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

Dynamic Assessment: An Approach Toward Reducing Test Bias.

ERIC Educational Resources Information Center

Carlson, Jerry S.; Wiedl, Karl Heinz

Through dynamic testing (the notion that tailored testing can be extended to the use of a learning oriented approach to assessment), analysis were made of how motivational, personality, and cognitive style factors interact with assessment approaches to yield performance data. Testing procedures involving simple feedback, elaborated feedback, and…

Dynamical Systems Approaches to Emotional Development

ERIC Educational Resources Information Center

Camras, Linda A.; Witherington, David C.

2005-01-01

Within the last 20 years, transitions in the conceptualization of emotion and its development have given rise to calls for an explanatory framework that captures emotional development in all its organizational complexity and variability. Recent attempts have been made to couch emotional development in terms of a dynamical systems approach through…

Development of a Dynamic Energy Budget Modeling Approach to Investigate the Effects of Temperature and Resource Limitation on Mercury Bioaccumulation in Fundulus Heteroclitus

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population persistence and growth. To explore this approach, we are conducting growth and bioaccumulation studies that cont...

Development of a dynamic energy budget modeling approach to investigate the effects of temperature and resource limitation on mercury bioaccumulation in Fundulus heteroclitus.

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population survival and growth. To explore this approach, we are developing growth and bioaccumulation studies that contrib...

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.

Lineage dynamics and mutation-selection balance in non-adapting asexual populations

NASA Astrophysics Data System (ADS)

Pénisson, Sophie; Sniegowski, Paul D.; Colato, Alexandre; Gerrish, Philip J.

2013-02-01

In classical population genetics, mutation-selection balance refers to the equilibrium frequency of a deleterious allele established and maintained under two opposing forces: recurrent mutation, which tends to increase the frequency of the allele; and selection, which tends to decrease its frequency. In a haploid population, if μ denotes the per capita rate of production of the deleterious allele by mutation and s denotes the selective disadvantage of carrying the allele, then the classical mutation-selection balance frequency of the allele is approximated by μ/s. This calculation assumes that lineages carrying the mutant allele in question—the ‘focal allele’—do not accumulate deleterious mutations linked to the focal allele. In principle, indirect selection against the focal allele caused by such additional mutations can decrease the frequency of the focal allele below the classical mutation-selection balance. This effect of indirect selection will be strongest in an asexual population, in which the entire genome is in linkage. Here, we use an approach based on a multitype branching process to investigate this effect, analyzing lineage dynamics under mutation, direct selection, and indirect selection in a non-adapting asexual population. We find that the equilibrium balance between recurrent mutation to the focal allele and the forces of direct and indirect selection against the focal allele is closely approximated by γμ/(s + U) (s = 0 if the focal allele is neutral), where γ ≈ eθθ-(ω+θ)(ω + θ)(Γ(ω + θ) - Γ(ω + θ,θ)), \\theta =U/\\tilde {s}, and \\omega =s/\\tilde {s}; U denotes the genomic deleterious mutation rate and \\tilde {s} denotes the geometric mean selective disadvantage of deleterious mutations elsewhere on the genome. This mutation-selection balance for asexual populations can remain surprisingly invariant over wide ranges of the mutation rate.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy.

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

Population mixture model for nonlinear telomere dynamics

NASA Astrophysics Data System (ADS)

Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

2008-12-01

Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

Insights into nuclear dynamics using live-cell imaging approaches.

PubMed

Bigley, Rachel B; Payumo, Alexander Y; Alexander, Jeffrey M; Huang, Guo N

2017-03-01

The nucleus contains the genetic blueprint of the cell and myriad interactions within this subcellular structure are required for gene regulation. In the current scientific era, characterization of these gene regulatory networks through biochemical techniques coupled with systems-wide 'omic' approaches has become commonplace. However, these strategies are limited because they represent a mere snapshot of the cellular state. To obtain a holistic understanding of nuclear dynamics, relevant molecules must be studied in their native contexts in living systems. Live-cell imaging approaches are capable of providing quantitative assessment of the dynamics of gene regulatory interactions within the nucleus. We survey recent insights into what live-cell imaging approaches have provided the field of nuclear dynamics. In this review, we focus on interactions of DNA with other DNA loci, proteins, RNA, and the nuclear envelope. WIREs Syst Biol Med 2017, 9:e1372. doi: 10.1002/wsbm.1372 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

[Dynamic model of seasonal breeding rodent pest population controlled with short-acting sterilant].

PubMed

Liu, Han-wu; Jin, Zhen; Zhang, Feng-qin; Li, Qiu-ying

2013-04-01

Rodent pests bring great damage to human beings, while rodenticide and sterilant can be used to control the pests. After ingesting sterilant, rodent pests lose their fertility, but in some cases, the sterile individuals may gain their fertility again, produce offspring, and enlarge population size. In this paper, the dynamic models of rodent pest population under lethal control and shortacting contraception control were formulated, and, with the prerequisite of the seasonal breeding of rodent pest population, the models were used to regularly analyze their behaviors and the effects of the contraception rate, lethal rate, control interval, and sterilant valid period on the dynamics of the pest population. The results showed that larger contraception rate and lethal rate and shorter control interval could have better control effect, making the controlled population become smaller and even died out. Short-acting sterilant limited the control effect. At the later period of breeding season, the rodent pest population controlled with short-acting sterilant would have a weak recovery.

Dynamics of adaptive immunity against phage in bacterial populations

NASA Astrophysics Data System (ADS)

Bradde, Serena; Vucelja, Marija; Tesileanu, Tiberiu; Balasubramanian, Vijay

The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations oscillate, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a ``winner-take-all'' scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition rate.

Mortality and Population Dynamics of Bemisia tabaci within a Multi-Crop System

USDA-ARS?s Scientific Manuscript database

The population dynamics of mobile polyphagous pests is governed by a complex set of interacting factors that involve multiple host-plants, seasonality, movement and demography. Bemisia tabaci is a multivoltine insect with no diapause that maintains population continuity by moving from one host to a...

Rabies disease dynamics in naïve dog populations in Australia.

PubMed

Sparkes, Jessica; McLeod, Steven; Ballard, Guy; Fleming, Peter J S; Körtner, Gerhard; Brown, Wendy Y

2016-09-01

Currently, Australia is free from terrestrial rabies but an incursion from nearby Indonesia, where the virus is endemic, is a feasible threat. Here, we aimed to determine whether the response to a simulated rabies incursion would vary between three extant Australian dog populations; free-roaming domestic dogs from a remote indigenous community in northern Australia, and free-roaming domestic and wild dogs in peri-urban areas of north-east New South Wales. We further sought to predict how different management strategies impacted disease dynamics in these populations. We used simple stochastic state-transition models and dog demographic and contact rate data from the three dog populations to simulate rabies spread, and used global and local sensitivity analyses to determine effects of model parameters. To identify the most effective control options, dog removal and vaccination strategies were also simulated. Responses to simulated rabies incursions varied between the dog populations. Free-roaming domestic dogs from north-east New South Wales exhibited the lowest risk for rabies maintenance and spread. Due to low containment and high contact rates, rabies progressed rapidly through free-roaming dogs from the remote indigenous community in northern Australia. In contrast, rabies remained at relatively low levels within the north-east New South Wales wild dog population for over a year prior to an epidemic. Across all scenarios, sensitivity analyses revealed that contact rates and the probability of transmission were the most important drivers of the number of infectious individuals within a population. The number of infectious individuals was less sensitive to birth and death rates. Removal of dogs as a control strategy was not effective for any population modelled, while vaccination rates in excess of 70% of the population resulted in significant reductions in disease progression. The variability in response between these distinct dog groups to a rabies incursion

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.

Variation in the local population dynamics of the short-lived Opuntia macrorhiza (Cactaceae).

PubMed

Haridas, C V; Keeler, Kathleen H; Tenhumberg, Brigitte

2015-03-01

Spatiotemporal variation in demographic rates can have profound effects for population persistence, especially for dispersal-limited species living in fragmented landscapes. Long-term studies of plants in such habitats help with understanding the impacts of fragmentation on population persistence but such studies are rare. In this work, we reanalyzed demographic data from seven years of the short-lived cactus Opuntia macrorhiza var. macrorhiza at five plots in Boulder, Colorado. Previous work combining data from all years and all plots predicted a stable population (deterministic log lamda approximately 0). This approach assumed that all five plots were part of a single population. Since the plots were located in a suburban-agricultural interface separated by highways, grazing lands, and other barriers, and O. macrorhiza is likely dispersal limited, we analyzed the dynamics of each plot separately using stochastic matrix models assuming each plot represented a separate population. We found that the stochastic population growth rate log lamdaS varied widely between populations (log lamdaS = 0.1497, 0.0774, -0.0230, -0.2576, -0.4989). The three populations with the highest growth rates were located close together in space, while the two most isolated populations had the lowest growth rates suggesting that dispersal between populations is critical for the population viability of O. macrorhiza. With one exception, both our prospective (stochastic elasticity) and retrospective (stochastic life table response experiments) analysis suggested that means of stasis and growth, especially of smaller plants, were most important for population growth rate. This is surprising because recruitment is typically the most important vital rate in a short-lived species such as O. macrorhiza. We found that elasticity to the variance was mostly negligible, suggesting that O. macrorhiza populations are buffered against large temporal variation. Finally, single-year elasticities to means

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

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.

Positive and Negative Feedbacks and Free-Scale Pattern Distribution in Rural-Population Dynamics

PubMed Central

Alados, Concepción L.; Errea, Paz; Gartzia, Maite; Saiz, Hugo; Escós, Juan

2014-01-01

Depopulation of rural areas is a widespread phenomenon that has occurred in most industrialized countries, and has contributed significantly to a reduction in the productivity of agro-ecological resources. In this study, we identified the main trends in the dynamics of rural populations in the Central Pyrenees in the 20th C and early 21st C, and used density independent and density dependent models and identified the main factors that have influenced the dynamics. In addition, we investigated the change in the power law distribution of population size in those periods. Populations exhibited density-dependent positive feedback between 1960 and 2010, and a long-term positive correlation between agricultural activity and population size, which has resulted in a free-scale population distribution that has been disrupted by the collapse of the traditional agricultural society and by emigration to the industrialized cities. We concluded that complex socio-ecological systems that have strong feedback mechanisms can contribute to disruptive population collapses, which can be identified by changes in the pattern of population distribution. PMID:25474704

Temporal dynamics of linkage disequilibrium in two populations of bighorn sheep

PubMed Central

Miller, Joshua M; Poissant, Jocelyn; Malenfant, René M; Hogg, John T; Coltman, David W

2015-01-01

Linkage disequilibrium (LD) is the nonrandom association of alleles at two markers. Patterns of LD have biological implications as well as practical ones when designing association studies or conservation programs aimed at identifying the genetic basis of fitness differences within and among populations. However, the temporal dynamics of LD in wild populations has received little empirical attention. In this study, we examined the overall extent of LD, the effect of sample size on the accuracy and precision of LD estimates, and the temporal dynamics of LD in two populations of bighorn sheep (Ovis canadensis) with different demographic histories. Using over 200 microsatellite loci, we assessed two metrics of multi-allelic LD, D′, and χ′2. We found that both populations exhibited high levels of LD, although the extent was much shorter in a native population than one that was founded via translocation, experienced a prolonged bottleneck post founding, followed by recent admixture. In addition, we observed significant variation in LD in relation to the sample size used, with small sample sizes leading to depressed estimates of the extent of LD but inflated estimates of background levels of LD. In contrast, there was not much variation in LD among yearly cross-sections within either population once sample size was accounted for. Lack of pronounced interannual variability suggests that researchers may not have to worry about interannual variation when estimating LD in a population and can instead focus on obtaining the largest sample size possible. PMID:26380673

Heisenberg operator approach for spin squeezing dynamics

NASA Astrophysics Data System (ADS)

Bhattacherjee, Aranya Bhuti; Sharma, Deepti; Pelster, Axel

2017-12-01

We reconsider the one-axis twisting Hamiltonian, which is commonly used for generating spin squeezing, and treat its dynamics within the Heisenberg operator approach. To this end we solve the underlying Heisenberg equations of motion perturbatively and evaluate the expectation values of the resulting time-dependent Heisenberg operators in order to determine approximately the dynamics of spin squeezing. Comparing our results with those originating from exact numerics reveals that they are more accurate than the commonly used frozen spin approximation.

Long-term dynamics of Typha populations

USGS Publications Warehouse

Grace, J.B.; Wetzel, R.G.

1998-01-01

The zonation of Typha populations in an experimental pond in Michigan was re-examined 15 years after the original sampling to gain insight into the long-term dynamics. Current distributions of Typha populations were also examined in additional experimental ponds at the site that have been maintained for 23 years. The zonation between T. latifolia and T. angustifolia in the previously studied pond 15 years after the initial sampling revealed that the density and distribution of shoots had not changed significantly. Thus, it appears that previously reported results (based on 7- year old populations) have remained consistent over time. Additional insight into the interaction between these two taxa was sought by comparing mixed and monoculture stands in five experimental ponds that have remained undisturbed for their 23-year history. The maximum depth of T. latifolia, the shallow- water species, was not significantly reduced when growing in the presence of the more flood tolerant T. angustifolia. In contrast, the minimum depth of T. angustifolia was reduced from 0 to 37 cm when in the presence of T. latifolia. When total populations were compared between monoculture and mixed stands, the average density of T. angustifolia shoots was 59.4 percent lower in mixed stands while the density of T. latifolia was 32 percent lower, with T. angustifolia most affected at shallow depths (reduced by 92 percent) and T. latifolia most affected at the deepest depths (reduced by 60 percent). These long-term observations indicate that competitive displacement between Typha taxa has remained stable over time.

A qualitative approach for recovering relative depths in dynamic scenes

NASA Technical Reports Server (NTRS)

Haynes, S. M.; Jain, R.

1987-01-01

This approach to dynamic scene analysis is a qualitative one. It computes relative depths using very general rules. The depths calculated are qualitative in the sense that the only information obtained is which object is in front of which others. The motion is qualitative in the sense that the only required motion data is whether objects are moving toward or away from the camera. Reasoning, which takes into account the temporal character of the data and the scene, is qualitative. This approach to dynamic scene analysis can tolerate imprecise data because in dynamic scenes the data are redundant.

Dynamic denominators: the impact of seasonally varying population numbers on disease incidence estimates.

PubMed

Zu Erbach-Schoenberg, Elisabeth; Alegana, Victor A; Sorichetta, Alessandro; Linard, Catherine; Lourenço, Christoper; Ruktanonchai, Nick W; Graupe, Bonita; Bird, Tomas J; Pezzulo, Carla; Wesolowski, Amy; Tatem, Andrew J

2016-01-01

Reliable health metrics are crucial for accurately assessing disease burden and planning interventions. Many health indicators are measured through passive surveillance systems and are reliant on accurate estimates of denominators to transform case counts into incidence measures. These denominator estimates generally come from national censuses and use large area growth rates to estimate annual changes. Typically, they do not account for any seasonal fluctuations and thus assume a static denominator population. Many recent studies have highlighted the dynamic nature of human populations through quantitative analyses of mobile phone call data records and a range of other sources, emphasizing seasonal changes. In this study, we use mobile phone data to capture patterns of short-term human population movement and to map dynamism in population densities. We show how mobile phone data can be used to measure seasonal changes in health district population numbers, which are used as denominators for calculating district-level disease incidence. Using the example of malaria case reporting in Namibia we use 3.5 years of phone data to investigate the spatial and temporal effects of fluctuations in denominators caused by seasonal mobility on malaria incidence estimates. We show that even in a sparsely populated country with large distances between population centers, such as Namibia, populations are highly dynamic throughout the year. We highlight how seasonal mobility affects malaria incidence estimates, leading to differences of up to 30 % compared to estimates created using static population maps. These differences exhibit clear spatial patterns, with likely overestimation of incidence in the high-prevalence zones in the north of Namibia and underestimation in lower-risk areas when compared to using static populations. The results here highlight how health metrics that rely on static estimates of denominators from censuses may differ substantially once mobility and

Trust-based access control model from sociological approach in dynamic online social network environment.

PubMed

Baek, Seungsoo; Kim, Seungjoo

2014-01-01

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information.

Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

PubMed Central

Kim, Seungjoo

2014-01-01

There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information. PMID:25374943

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...

Changes in Land Surface Water Dynamics since the 1990s and Relation to Population Pressure

NASA Technical Reports Server (NTRS)

Prigent, C.; Papa, F.; Aires, F.; Jimenez, C.; Rossow, W. B.; Matthews, E.

2012-01-01

We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, in section 4, insisting on the potential applications of the wetland dataset.

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 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

Dynamics of a black-capped chickadee population, 1958-1983

USGS Publications Warehouse

Loery, G.; Nichols, J.D.

1985-01-01

The dynamics of a wintering population of Black-capped Chickadees (Parus atricapillus) were studied from 1958-1983 using capture-recapture methods. The Jolly-Seber model was used to obtain annual estimates of population size, survival rate, and recruitment. The average estimated population size over this period was ?160 birds. The average estimated number of new birds entering the population each year and alive at the time of sampling was ?57. The arithmetic mean annual survival rate estimate was ?0.59. We tested hypothesis about possible relationships between these population parameters and (1) the natural introduction of Tufted Titmice (Parus bicolor) to the area, (2) the clear-cutting of portions of nearby red pine (Pinus resinosa) plantations, and (3) natural variations in winter temperatures. The chickadee population exhibited a substantial short-term decline following titmouse establishment, produced by decreases in both survival rate and number of new recruits. Survival rate decline somewhat after the initiation of the pine clear-cutting, but population size was very similar before and after clear-cutting. Weighted least squares analyses provided no evidence of a relationship between survival rate and either of two winter temperature variables.

Spatial-temporal population dynamics across species range: From centre to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.; Schoenberger, M.; Brandle, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Spatial-temporal population dynamics across species range: from center to margin

USGS Publications Warehouse

Guo, Q.; Taper, M.L.; Schoenberger, M.; Brandl, J.

2005-01-01

Understanding the boundaries of species' ranges and the variations in population dynamics from the centre to margin of a species' range is critical. This study simulated spatial-temporal patterns of birth and death rates and migration across a species' range in different seasons. Our results demonstrated the importance of dispersal and migration in altering birth and death rates, balancing source and sink habitats, and governing expansion or contraction of species' ranges in changing environments. We also showed that the multiple equilibria of metapopulations across a species' range could be easily broken following climatic changes or physical disturbances either or local or regional. Although we refer to our models as describing the population dynamics across whole species' range, they should also apply to small-scale habitats (metapopulations) in which species abundance follows a humped pattern or to any ecosystem or landscape where strong central-marginal (C-M) environmental gradients exist. Conservation of both central and marginal populations would therefore be equally important considerations in making management decisions.

Soil-related variations in the population dynamics of six dipterocarp tree species with strong habitat preferences.

PubMed

Yamada, Toshihiro; Yamada, Yuko; Okuda, Toshinori; Fletcher, Christine

2013-07-01

Differences in the density of conspecific tree individuals in response to environmental gradients are well documented for many tree species, but how such density differences are generated and maintained is poorly understood. We examined the segregation of six dipterocarp species among three soil types in the Pasoh tropical forest, Malaysia. We examined how individual performance and population dynamics changed across the soil types using 10-year demographic data to compare tree performance across soil types, and constructed population matrix models to analyze the population dynamics. Species showed only minor changes in mortality and juvenile growth across soil types, although recruitment differed greatly. Clear, interspecific demographic trade-offs between growth and mortality were found in all soil types. The relative trade-offs by a species did not differ substantially among the soil types. Population sizes were projected to remain stable in all soil types for all species with one exception. Our life-table response experiment demonstrated that the population dynamics of a species differed only subtly among soil types. Therefore, species with strong density differences across soil types do not necessarily differ greatly in their population dynamics across the soil types. In contrast, interspecific differences in population dynamics were large. The trade-off between mortality and growth led to a negative correlation between the contributions of mortality and growth to variations in the population growth rate (λ) and thus reduced their net contributions. Recruitment had little impact on the variation in λ. The combination of these factors resulted in little variation in λ among species.

Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

PubMed

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2013-11-01

could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. © 2012 Blackwell Verlag GmbH.

POPULATION DYNAMICS OF HISPID COTTON RATS (SIGMODON HISPIDUS) ACROSS A NITROGEN AMENDED LANDSCAPE

EPA Science Inventory

Population dynamics of some small-mammal species appear to be regulated by plant-community structure, vegetative cover, plant diversity, and food quality. Thus, plant community changes associated with nitrogen additions would likely impact dynamics and structure of small-mammal ...

Current status and recent dynamics of the Black Brant Branta bernicla breeding population

USGS Publications Warehouse

Sedinger, James S.; Lensink, Calvin J.; Ward, David H.; Anthony, Michael W.; Wege, Michael L.; Byrd, G. Vernon

1993-01-01

We summarize current knowledge about the distribution of Pacific Black Brant and recent dynamics of colonies, particularly on the Yukon-Kuskokwim (Y-K) Delta, Alaska. About 20,000 nests are required to produce the number of young in the autumn flight using estimates of clutch size, hatching success and gosling survival based on colonies on the Y-K Delta. More than 80% of the nests in the population can be accounted for currently on the Y-K Delta. Most moulting individuals that did not breed, or were unsuccessful, are unaccounted for in late summer. Numbers of Black Brant nesting in major colonies on the Y-K Delta declined >60% in the early 1980s, most likely as a result of local subsistence harvest combined with predation by arctic foxes. Effective management of this population requires a better understanding of the distribution of breeding and moulting birds, the importance of breeding habitat to colony dynamics and the role of both sport and subsistence harvest in population dynamics.

The modern temperature-accelerated dynamics approach

DOE PAGES

Zamora, Richard J.; Uberuaga, Blas P.; Perez, Danny; ...

2016-06-01

Accelerated molecular dynamics (AMD) is a class of MD-based methods used to simulate atomistic systems in which the metastable state-to-state evolution is slow compared with thermal vibrations. Temperature-accelerated dynamics (TAD) is a particularly efficient AMD procedure in which the predicted evolution is hastened by elevating the temperature of the system and then recovering the correct state-to-state dynamics at the temperature of interest. TAD has been used to study various materials applications, often revealing surprising behavior beyond the reach of direct MD. This success has inspired several algorithmic performance enhancements, as well as the analysis of its mathematical framework. Recently, thesemore » enhancements have leveraged parallel programming techniques to enhance both the spatial and temporal scaling of the traditional approach. Here, we review the ongoing evolution of the modern TAD method and introduce the latest development: speculatively parallel TAD.« less

[On the relation between encounter rate and population density: Are classical models of population dynamics justified?].

PubMed

Nedorezov, L V

2015-01-01

A stochastic model of migrations on a lattice and with discrete time is considered. It is assumed that space is homogenous with respect to its properties and during one time step every individual (independently of local population numbers) can migrate to nearest nodes of lattice with equal probabilities. It is also assumed that population size remains constant during certain time interval of computer experiments. The following variants of estimation of encounter rate between individuals are considered: when for the fixed time moments every individual in every node of lattice interacts with all other individuals in the node; when individuals can stay in nodes independently, or can be involved in groups in two, three or four individuals. For each variant of interactions between individuals, average value (with respect to space and time) is computed for various values of population size. The samples obtained were compared with respective functions of classic models of isolated population dynamics: Verhulst model, Gompertz model, Svirezhev model, and theta-logistic model. Parameters of functions were calculated with least square method. Analyses of deviations were performed using Kolmogorov-Smirnov test, Lilliefors test, Shapiro-Wilk test, and other statistical tests. It is shown that from traditional point of view there are no correspondence between the encounter rate and functions describing effects of self-regulatory mechanisms on population dynamics. Best fitting of samples was obtained with Verhulst and theta-logistic models when using the dataset resulted from the situation when every individual in the node interacts with all other individuals.

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

A Supervised Approach to Windowing Detection on Dynamic Networks

DTIC Science & Technology

2017-07-01

A supervised approach to windowing detection on dynamic networks Benjamin Fish University of Illinois at Chicago 1200 W. Harrison St. Chicago...Using this framework, we introduce windowing algorithms that take a supervised approach : they leverage ground truth on training data to find a good...windowing of the test data. We compare the supervised approach to previous approaches and several baselines on real data. ACM Reference format: Benjamin

Population dynamics of the Concho water snake in rivers and reservoirs

USGS Publications Warehouse

Whiting, M.J.; Dixon, J.R.; Greene, B.D.; Mueller, J.M.; Thornton, O.W.; Hatfield, J.S.; Nichols, J.D.; Hines, J.E.

2008-01-01

The Concho Water Snake (Nerodia harteri paucimaculata) is confined to the Concho–Colorado River valley of central Texas, thereby occupying one of the smallest geographic ranges of any North American snake. In 1986, N. h. paucimaculata was designated as a federally threatened species, in large part because of reservoir projects that were perceived to adversely affect the amount of habitat available to the snake. During a ten-year period (1987–1996), we conducted capture–recapture field studies to assess dynamics of five subpopulations of snakes in both natural (river) and man-made (reservoir) habitats. Because of differential sampling of subpopulations, we present separate results for all five subpopulations combined (including large reservoirs) and three of the five subpopulations (excluding large reservoirs). We used multistate capture–recapture models to deal with stochastic transitions between pre-reproductive and reproductive size classes and to allow for the possibility of different survival and capture probabilities for the two classes. We also estimated both the finite rate of increase (λ) for a deterministic, stage-based, female-only matrix model using the average litter size, and the average rate of adult population change, λ ˆ, which describes changes in numbers of adult snakes, using a direct capture–recapture approach to estimation. Average annual adult survival was about 0.23 and similar for males and females. Average annual survival for subadults was about 0.14. The parameter estimates from the stage-based projection matrix analysis all yielded asymptotic values of λ < 1, suggesting populations that are not viable. However, the direct estimates of average adult λ for the three subpopulations excluding major reservoirs were λ ˆ  =  1.26, SE ˆ(λ ˆ)  =  0.18 and λ ˆ  =  0.99, SE ˆ(λ ˆ)  =  0.79, based on two different models. Thus, the direct estimation approach did not provide strong evidence of population

Development of a dynamic energy budget modeling approach to investigate the effects of temperature and resource limitation on mercury bioaccumulation in Fundulus heteroclitus-presentation

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population survival and growth. To explore this approach, we are conducting growth and bioaccumulation studies that contrib...

Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

PubMed

van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

2016-06-01

The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England.

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

Long-term dynamics of natural populations of Schistosoma mansoni among Rattus rattus in patchy environment.

PubMed

Théron, A; Pointier, J P; Morand, S; Imbert-Establet, D; Borel, G

1992-04-01

Dynamics of natural populations of Schistosoma mansoni were studied during 8 consecutive years among Rattus rattus populations from 8 transmission sites of the marshy forest focus of Guadeloupe (French West Indies). The schistosome population is over-dispersed (k = 0.119) within the murine hosts and ecological factors linked to the patchy environment may be responsible for such aggregated distribution. Analysis of the spatio-temporal variations in prevalences, intensities and abundances showed limited variations of the infection during the 8 years at the level of the whole parasite population but great spatial heterogeneity at the level of local schistosome populations. Inter-populational genetic variability linked to the degree of adaptation of this human parasite to the murine host may explain differences in transmission dynamics between the local populations of S. mansoni.

The dynamics of genetic draft in rapidly adapting populations.

PubMed

Kosheleva, Katya; Desai, Michael M

2013-11-01

The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of "genetic draft" affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie's original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald-Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen-Sznitman coalescent in the limit of very rapid adaptation.

Population Dynamics of Excited Atoms in Dissipative Cavities

NASA Astrophysics Data System (ADS)

Zou, Hong-Mei; Liu, Yu; Fang, Mao-Fa

2016-10-01

Population dynamics of excited atoms in dissipative cavities is investigated in this work. We present a method of controlling populations of excited atoms in dissipative cavities. For the initial state | e e> A B |00> a b , the repopulation of excited atoms can be obtained by using atom-cavity couplings and non-Markovian effects after the atomic excited energy decays to zero. For the initial state | g g> A B |11> a b , the two atoms can also be populated to the excited states from the initial ground states by using atom-cavity couplings and non-Markovian effects. And the stronger the atom-cavity coupling or the non-Markovian effect is, the larger the number of repopulation of excited atoms is. Particularly, when the atom-cavity coupling or the non-Markovian effect is very strong, the number of repopulation of excited atoms can be close to one in a short time and will tend to a steady value in a long time.

Disease dynamics in a dynamic social network

NASA Astrophysics Data System (ADS)

Christensen, Claire; Albert, István; Grenfell, Bryan; Albert, Réka

2010-07-01

We develop a framework for simulating a realistic, evolving social network (a city) into which a disease is introduced. We compare our results to prevaccine era measles data for England and Wales, and find that they capture the quantitative and qualitative features of epidemics in populations spanning two orders of magnitude. Our results provide unique insight into how and why the social topology of the contact network influences the propagation of the disease through the population. We argue that network simulation is suitable for concurrently probing contact network dynamics and disease dynamics in ways that prior modeling approaches cannot and it can be extended to the study of less well-documented diseases.

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.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

PubMed Central

Almquist, Joachim; Bendrioua, Loubna; Adiels, Caroline Beck; Goksör, Mattias; Hohmann, Stefan; Jirstrand, Mats

2015-01-01

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

DOE PAGES

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine; ...

2017-12-15

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

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

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and

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.

Population Dynamics of Southern Pine Beetle in Forest Landscapes

Treesearch

Andrew Birt

2011-01-01

Southern pine beetle (SPB) is an important pest of Southeastern United States pine forests. Periodic regional outbreaks are characterized by localized areas of tree mortality (infestations) surrounded by areas with little or no damage. Ultimately, this spatiotemporal pattern of tree mortality is driven by the dynamics of SPB populations—more specifically, by rates of...

An analytic approach to cyber adversarial dynamics

NASA Astrophysics Data System (ADS)

Sweeney, Patrick; Cybenko, George

2012-06-01

To date, cyber security investment by both the government and commercial sectors has been largely driven by the myopic best response of players to the actions of their adversaries and their perception of the adversarial environment. However, current work in applying traditional game theory to cyber operations typically assumes that games exist with prescribed moves, strategies, and payos. This paper presents an analytic approach to characterizing the more realistic cyber adversarial metagame that we believe is being played. Examples show that understanding the dynamic metagame provides opportunities to exploit an adversary's anticipated attack strategy. A dynamic version of a graph-based attack-defend game is introduced, and a simulation shows how an optimal strategy can be selected for success in the dynamic environment.

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.

Optimal growth entails risky localization in population dynamics

NASA Astrophysics Data System (ADS)

Gueudré, Thomas; Martin, David G.

2018-03-01

Essential to each other, growth and exploration are jointly observed in alive and inanimate entities, such as animals, cells or goods. But how the environment's structural and temporal properties weights in this balance remains elusive. We analyze a model of stochastic growth with time correlations and diffusive dynamics that sheds light on the way populations grow and spread over general networks. This model suggests natural explanations of empirical facts in econo-physics or ecology, such as the risk-return trade-off and the Zipf law. We conclude that optimal growth leads to a localized population distribution, but such risky position can be mitigated through the space geometry. These results have broad applicability and are subsequently illustrated over an empirical study of financial data.

Effects of temporal variation in temperature and density dependence on insect population dynamics

USDA-ARS?s Scientific Manuscript database

Understanding effects of environmental variation on insect populations is important in light of predictions about increasing future climatic variability. In order to understand the effects of changing environmental variation on population dynamics and life history evolution in insects one would need...

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

PubMed

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Accounting for Sampling Error When Inferring Population Synchrony from Time-Series Data: A Bayesian State-Space Modelling Approach with Applications

PubMed Central

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Background Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. Methodology/Principal findings The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. Conclusion/Significance The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in

COMPARISON OF SAMPLING TECHNIQUES USED IN STUDYING LEPIDOPTERA POPULATION DYNAMICS

EPA Science Inventory

Four methods (light traps, foliage samples, canvas bands, and gypsy moth egg mass surveys) that are used to study the population dynamics of foliage-feeding Lepidoptera were compared for 10 species, including gypsy moth, Lymantria dispar L. Samples were collected weekly at 12 sit...

Approaches for assessing risks to sensitive populations: Lessons learned from evaluating risks in the pediatric populations*

EPA Science Inventory

Assessing the risk profiles of potentially sensitive populations requires a 'tool chest' of methodological approaches to adequately characterize and evaluate these populations. At present, there is an extensive body of literature on methodologies that apply to the evaluation of...

Approaches to Vaccination Among Populations in Areas of Conflict

PubMed Central

Nnadi, Chimeremma; Etsano, Andrew; Uba, Belinda; Ohuabunwo, Chima; Melton, Musa; Nganda, Gatei wa; Esapa, Lisa; Bolu, Omotayo; Mahoney, Frank; Vertefeuille, John; Wiesen, Eric; Durry, Elias

2017-01-01

Vaccination is an important and cost-effective disease prevention and control strategy. Despite progress in vaccine development and immunization delivery systems worldwide, populations in areas of conflict (hereafter, “conflict settings”) often have limited or no access to lifesaving vaccines, leaving them at increased risk for morbidity and mortality related to vaccine-preventable disease. Without developing and refining approaches to reach and vaccinate children and other vulnerable populations in conflict settings, outbreaks of vaccine-preventable disease in these settings may persist and spread across subnational and international borders. Understanding and refining current approaches to vaccinating populations in conflict and humanitarian emergency settings may save lives. Despite major setbacks, the Global Polio Eradication Initiative has made substantial progress in vaccinating millions of children worldwide, including those living in communities affected by conflicts and other humanitarian emergencies. In this article, we examine key strategic and operational tactics that have led to increased polio vaccination coverage among populations living in diverse conflict settings, including Nigeria, Somalia, and Pakistan, and how these could be applied to reach and vaccinate populations in other settings across the world. PMID:28838202

Modelling the dynamics of traits involved in fighting-predators-prey system.

PubMed

Kooi, B W

2015-12-01

We study the dynamics of a predator-prey system where predators fight for captured prey besides searching for and handling (and digestion) of the prey. Fighting for prey is modelled by a continuous time hawk-dove game dynamics where the gain depends on the amount of disputed prey while the costs for fighting is constant per fighting event. The strategy of the predator-population is quantified by a trait being the proportion of the number of predator-individuals playing hawk tactics. The dynamics of the trait is described by two models of adaptation: the replicator dynamics (RD) and the adaptive dynamics (AD). In the RD-approach a variant individual with an adapted trait value changes the population's strategy, and consequently its trait value, only when its payoff is larger than the population average. In the AD-approach successful replacement of the resident population after invasion of a rare variant population with an adapted trait value is a step in a sequence changing the population's strategy, and hence its trait value. The main aim is to compare the consequences of the two adaptation models. In an equilibrium predator-prey system this will lead to convergence to a neutral singular strategy, while in the oscillatory system to a continuous singular strategy where in this endpoint the resident population is not invasible by any variant population. In equilibrium (low prey carrying capacity) RD and AD-approach give the same results, however not always in a periodically oscillating system (high prey carrying-capacity) where the trait is density-dependent. For low costs the predator population is monomorphic (only hawks) while for high costs dimorphic (hawks and doves). These results illustrate that intra-specific trait dynamics matters in predator-prey dynamics.

Experimental test of an eco-evolutionary dynamic feedback loop between evolution and population density in the green peach aphid.

PubMed

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

2013-05-01

An eco-evolutionary feedback loop is defined as the reciprocal impacts of ecology on evolutionary dynamics and evolution on ecological dynamics on contemporary timescales. We experimentally tested for an eco-evolutionary feedback loop in the green peach aphid, Myzus persicae, by manipulating initial densities and evolution. We found strong evidence that initial aphid density alters the rate and direction of evolution, as measured by changes in genotype frequencies through time. We also found that evolution of aphids within only 16 days, or approximately three generations, alters the rate of population growth and predicts density compared to nonevolving controls. The impact of evolution on population dynamics also depended on density. In one evolution treatment, evolution accelerated population growth by up to 10.3% at high initial density or reduced it by up to 6.4% at low initial density. The impact of evolution on population growth was as strong as or stronger than that caused by a threefold change in intraspecific density. We found that, taken together, ecological condition, here intraspecific density, alters evolutionary dynamics, which in turn alter concurrent population growth rate (ecological dynamics) in an eco-evolutionary feedback loop. Our results suggest that ignoring evolution in studies predicting population dynamics might lead us to over- or underestimate population density and that we cannot predict the evolutionary outcome within aphid populations without considering population size.

An Analytical Dynamics Approach to the Control of Mechanical Systems

NASA Astrophysics Data System (ADS)

Mylapilli, Harshavardhan

A new and novel approach to the control of nonlinear mechanical systems is presented in this study. The approach is inspired by recent results in analytical dynamics that deal with the theory of constrained motion. The control requirements on the dynamical system are viewed from an analytical dynamics perspective and the theory of constrained motion is used to recast these control requirements as constraints on the dynamical system. Explicit closed form expressions for the generalized nonlinear control forces are obtained by using the fundamental equation of mechanics. The control so obtained is optimal at each instant of time and causes the constraints to be exactly satisfied. No linearizations and/or approximations of the nonlinear dynamical system are made, and no a priori structure is imposed on the nature of nonlinear controller. Three examples dealing with highly nonlinear complex dynamical systems that are chosen from diverse areas of discrete and continuum mechanics are presented to demonstrate the control approach. The first example deals with the energy control of underactuated inhomogeneous nonlinear lattices (or chains), the second example deals with the synchronization of the motion of multiple coupled slave gyros with that of a master gyro, and the final example deals with the control of incompressible hyperelastic rubber-like thin cantilever beams. Numerical simulations accompanying these examples show the ease, simplicity and the efficacy with which the control methodology can be applied and the accuracy with which the desired control objectives can be met.

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

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