Nonlinear dynamics in a business-cycle model with logistic population growth

International Nuclear Information System (INIS)

Brianzoni, Serena; Mammana, Cristiana; Michetti, Elisabetta

2009-01-01

We consider a discrete-time growth model of the Solow type where workers and shareholders have different but constant saving rates and the population growth dynamics is described by the logistic equation able to exhibit complicated dynamics. We show conditions for the resulting system having a compact global attractor and we describe its structure. We also perform a mainly numerical analysis using the critical lines method able to describe the strange attractor and the absorbing area, in order to show how cyclical or complex fluctuations may be produced in a business-cycle model. We study the dynamic behaviour of the model under different ranges of the main parameters, i.e. the elasticity of substitution between the two production factors and the one in the logistic equation (namely μ). We prove the existence of complex dynamics when the elasticity of substitution between production factors drops below one (so that capital income declines) or μ increases (so that the amplitude of movements in the population growth rate increases).

Cellular-automata model of the dwarf shrubs populations and communities dynamics

Directory of Open Access Journals (Sweden)

A. S. Komarov

2015-06-01

Full Text Available The probabilistic cellular-automata model of development and long-time dynamics of dwarf shrub populations and communities is developed. It is based on the concept of discrete description of the plant ontogenesis and joint model approaches in terms of probabilistic cellular automata and L-systems by Lindenmayer. Short representation of the basic model allows evaluation of the approach and software implementation. The main variables of the model are a number of partial bushes in clones or area projective cover. The model allows us to investigate the conditions of self-maintenance and sustainability population under different environmental conditions (inaccessibility of the territory for settlement, mosaic moisture conditions of soil and wealth. The model provides a forecast of the total biomass dynamics shrubs and their fractions (stems, leaves, roots, fine roots, fruits on the basis of the data obtained in the discrete description of ontogenesis and further information on the productivity of the plant fractions. The inclusion of the joint dynamics of biomass of shrubs and soil in EFIMOD models cycle of carbon and nitrogen to evaluate the role of shrubs in these circulations, especially at high impact, such as forest fires and clear cutting, allow forecasting of the dynamics of populations and ecosystem functions of shrubs (regulation of biogeochemical cycles maintaining biodiversity, participation in the creation of non-wood products with changing climatic conditions and strong damaging effects (logging, fires; and application of the models developed to investigate the stability and productivity of shrubs and their participation in the cycle of carbon and nitrogen in different climatic and edaphic conditions.

Integrating count and detection–nondetection data to model population dynamics

Science.gov (United States)

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.

Population Model with a Dynamic Food Supply

Science.gov (United States)

Dickman, Ronald; da Silva Nascimento, Jonas

2009-09-01

We propose a simple population model including the food supply as a dynamic variable. In the model, survival of an organism depends on a certain minimum rate of food consumption; a higher rate of consumption is required for reproduction. We investigate the stationary behavior under steady food input, and the transient behavior of growth and decay when food is present initially but is not replenished. Under a periodic food supply, the system exhibits period-doubling bifurcations and chaos in certain ranges of the reproduction rate. Bifurcations and chaos are favored by a slow reproduction rate and a long period of food-supply oscillation.

Border Collision Bifurcations in a Generalized Model of Population Dynamics

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Lilia M. Ladino

2016-01-01

Full Text Available We analyze the dynamics of a generalized discrete time population model of a two-stage species with recruitment and capture. This generalization, which is inspired by other approaches and real data that one can find in literature, consists in considering no restriction for the value of the two key parameters appearing in the model, that is, the natural death rate and the mortality rate due to fishing activity. In the more general case the feasibility of the system has been preserved by posing opportune formulas for the piecewise map defining the model. The resulting two-dimensional nonlinear map is not smooth, though continuous, as its definition changes as any border is crossed in the phase plane. Hence, techniques from the mathematical theory of piecewise smooth dynamical systems must be applied to show that, due to the existence of borders, abrupt changes in the dynamic behavior of population sizes and multistability emerge. The main novelty of the present contribution with respect to the previous ones is that, while using real data, richer dynamics are produced, such as fluctuations and multistability. Such new evidences are of great interest in biology since new strategies to preserve the survival of the species can be suggested.

About a dynamic model of interaction of insect population with food plant

Directory of Open Access Journals (Sweden)

L.V. Nedorezov

2011-12-01

Full Text Available In present paper there is the consideration of mathematical model of food plant (resource - consumer (insect population - pathogen system dynamics which is constructed as a system of ordinary differential equations. The dynamic regimes of model are analyzed and, in particular, with the help of numerical methods it is shown that trigger regimes (regimes with two stable attractors can be realized in model under very simple assumptions about ecological and intra-population processes functioning. Within the framework of model it was assumed that the rate of food flow into the system is constant and functioning of intra-population selfregulative mechanisms can be described by Verhulst model. As it was found, trigger regimes are different with respect to their properties: in particular, in model the trigger regimes with one of stable stationary points on the coordinate plane can be realized (it corresponds to the situation when sick individuals in population are absent and their appearance in small volume leads to their asymptotic elimination; also the regimes with several nonzero stationary states and stable periodic fluctuations were found.

Metastable states and quasicycles in a stochastic Wilson-Cowan model of neuronal population dynamics

KAUST Repository

Bressloff, Paul C.

2010-01-01

We analyze a stochastic model of neuronal population dynamics with intrinsic noise. In the thermodynamic limit N→∞, where N determines the size of each population, the dynamics is described by deterministic Wilson-Cowan equations. On the other hand

Application of homotopy-perturbation method to nonlinear population dynamics models

International Nuclear Information System (INIS)

Chowdhury, M.S.H.; Hashim, I.; Abdulaziz, O.

2007-01-01

In this Letter, the homotopy-perturbation method (HPM) is employed to derive approximate series solutions of nonlinear population dynamics models. The nonlinear models considered are the multispecies Lotka-Volterra equations. The accuracy of this method is examined by comparison with the available exact and the fourth-order Runge-Kutta method (RK4)

Individual based model of slug population and spatial dynamics

NARCIS (Netherlands)

Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.

2006-01-01

The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field

Discrete two-sex models of population dynamics: On modelling the mating function

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Bessa-Gomes, Carmen; Legendre, Stéphane; Clobert, Jean

2010-09-01

Although sexual reproduction has long been a central subject of theoretical ecology, until recently its consequences for population dynamics were largely overlooked. This is now changing, and many studies have addressed this issue, showing that when the mating system is taken into account, the population dynamics depends on the relative abundance of males and females, and is non-linear. Moreover, sexual reproduction increases the extinction risk, namely due to the Allee effect. Nevertheless, different studies have identified diverse potential consequences, depending on the choice of mating function. In this study, we investigate the consequences of three alternative mating functions that are frequently used in discrete population models: the minimum; the harmonic mean; and the modified harmonic mean. We consider their consequences at three levels: on the probability that females will breed; on the presence and intensity of the Allee effect; and on the extinction risk. When we consider the harmonic mean, the number of times the individuals of the least abundant sex mate exceeds their mating potential, which implies that with variable sex-ratios the potential reproductive rate is no longer under the modeller's control. Consequently, the female breeding probability exceeds 1 whenever the sex-ratio is male-biased, which constitutes an obvious problem. The use of the harmonic mean is thus only justified if we think that this parameter should be re-defined in order to represent the females' breeding rate and the fact that females may reproduce more than once per breeding season. This phenomenon buffers the Allee effect, and reduces the extinction risk. However, when we consider birth-pulse populations, such a phenomenon is implausible because the number of times females can reproduce per birth season is limited. In general, the minimum or modified harmonic mean mating functions seem to be more suitable for assessing the impact of mating systems on population dynamics.

Seasonal dynamics of snail populations in coastal Kenya: Model calibration and snail control

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Gurarie, D.; King, C. H.; Yoon, N.; Wang, X.; Alsallaq, R.

2017-10-01

A proper snail population model is important for accurately predicting Schistosoma transmission. Field data shows that the overall snail population and that of shedding snails have a strong pattern of seasonal variation. Because human hosts are infected by the cercariae released from shedding snails, the abundance of the snail population sets ultimate limits on human infection. For developing a predictive dynamic model of schistosome infection and control strategies we need realistic snail population dynamics. Here we propose two such models based on underlying environmental factors and snail population biology. The models consist of two-stage (young-adult) populations with resource-dependent reproduction, survival, maturation. The key input in the system is seasonal rainfall which creates snail habitats and resources (small vegetation). The models were tested, calibrated and validated using dataset collected in Msambweni (coastal Kenya). Seasonal rainfall in Msambweni is highly variable with intermittent wet - dry seasons. Typical snail patterns follow precipitation peaks with 2-4-month time-lag. Our models are able to reproduce such seasonal variability over extended period of time (3-year study). We applied them to explore the optimal seasonal timing for implementing snail control.

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

Science.gov (United States)

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.

Numeric, Agent-based or System dynamics model? Which modeling approach is the best for vast population simulation?

Science.gov (United States)

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

2018-02-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25 % of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Science.gov (United States)

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

Richards-like two species population dynamics model.

Science.gov (United States)

Ribeiro, Fabiano; Cabella, Brenno Caetano Troca; Martinez, Alexandre Souto

2014-12-01

The two-species population dynamics model is the simplest paradigm of inter- and intra-species interaction. Here, we present a generalized Lotka-Volterra model with intraspecific competition, which retrieves as particular cases, some well-known models. The generalization parameter is related to the species habitat dimensionality and their interaction range. Contrary to standard models, the species coupling parameters are general, not restricted to non-negative values. Therefore, they may represent different ecological regimes, which are derived from the asymptotic solution stability analysis and are represented in a phase diagram. In this diagram, we have identified a forbidden region in the mutualism regime, and a survival/extinction transition with dependence on initial conditions for the competition regime. Also, we shed light on two types of predation and competition: weak, if there are species coexistence, or strong, if at least one species is extinguished.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

Science.gov (United States)

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.

Modeling population dynamics of mitochondria in mammalian cells

Science.gov (United States)

Kornick, Kellianne; Das, Moumita

Mitochondria are organelles located inside eukaryotic cells and are essential for several key cellular processes such as energy (ATP) production, cell signaling, differentiation, and apoptosis. All organisms are believed to have low levels of variation in mitochondrial DNA (mtDNA), and alterations in mtDNA are connected to a range of human health conditions, including epilepsy, heart failure, Parkinsons disease, diabetes, and multiple sclerosis. Therefore, understanding how changes in mtDNA accumulate over time and are correlated to changes in mitochondrial function and cell properties can have a profound impact on our understanding of cell physiology and the origins of some diseases. Motivated by this, we develop and study a mathematical model to determine which cellular parameters have the largest impact on mtDNA population dynamics. The model consists of coupled ODEs to describe subpopulations of healthy and dysfunctional mitochondria subject to mitochondrial fission, fusion, autophagy, and mutation. We study the time evolution and stability of each sub-population under specific selection biases and pressures by tuning specific terms in our model. Our results may provide insights into how sub-populations of mitochondria survive and evolve under different selection pressures. This work was supported by a Grant from the Moore Foundation.

Modeling the influence of polls on elections: a population dynamics approach

Energy Technology Data Exchange (ETDEWEB)

Hyman, James M [Los Alamos National Laboratory; Restrepo, Juan M [UNIV OF ARIZONA; Rael, Rosalyn C [UNIV OF ARIZONA

2009-01-01

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

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics.

Science.gov (United States)

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

The cultural implications of growth: Modeling nonlinear interaction of trait selection and population dynamics

Science.gov (United States)

Antoci, Angelo; Galeotti, Marcello; Russu, Paolo; Luigi Sacco, Pier

2018-05-01

In this paper, we study a nonlinear model of the interaction between trait selection and population dynamics, building on previous work of Ghirlanda et al. [Theor. Popul. Biol. 77, 181-188 (2010)] and Antoci et al. [Commun. Nonlinear Sci. Numer. Simul. 58, 92-106 (2018)]. We establish some basic properties of the model dynamics and present some simulations of the fine-grained structure of alternative dynamic regimes for chosen combinations of parameters. The role of the parameters that govern the reinforcement/corruption of maladaptive vs. adaptive traits is of special importance in determining the model's dynamic evolution. The main implication of this result is the need to pay special attention to the structural forces that may favor the emergence and consolidation of maladaptive traits in contemporary socio-economies, as it is the case, for example, for the stimulation of dysfunctional consumption habits and lifestyles in the pursuit of short-term profits.

Perturbation analysis of transient population dynamics using matrix projection models

DEFF Research Database (Denmark)

Stott, Iain

2016-01-01

Non-stable populations exhibit short-term transient dynamics: size, growth and structure that are unlike predicted long-term asymptotic stable, stationary or equilibrium dynamics. Understanding transient dynamics of non-stable populations is important for designing effective population management...... these methods to know exactly what is being measured. Despite a wealth of existing methods, I identify some areas that would benefit from further development....

Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

Directory of Open Access Journals (Sweden)

Céline Christiansen-Jucht

2015-05-01

Full Text Available Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.

Successional changes in trophic interactions support a mechanistic model of post-fire population dynamics.

Science.gov (United States)

Smith, Annabel L

2018-01-01

Models based on functional traits have limited power in predicting how animal populations respond to disturbance because they do not capture the range of demographic and biological factors that drive population dynamics, including variation in trophic interactions. I tested the hypothesis that successional changes in vegetation structure, which affected invertebrate abundance, would influence growth rates and body condition in the early-successional, insectivorous gecko Nephrurus stellatus. I captured geckos at 17 woodland sites spanning a succession gradient from 2 to 48 years post-fire. Body condition and growth rates were analysed as a function of the best-fitting fire-related predictor (invertebrate abundance or time since fire) with different combinations of the co-variates age, sex and location. Body condition in the whole population was positively affected by increasing invertebrate abundance and, in the adult population, this effect was most pronounced for females. There was strong support for a decline in growth rates in weight with time since fire. The results suggest that increased early-successional invertebrate abundance has filtered through to a higher trophic level with physiological benefits for insectivorous geckos. I integrated the new findings about trophic interactions into a general conceptual model of mechanisms underlying post-fire population dynamics based on a long-term research programme. The model highlights how greater food availability during early succession could drive rapid population growth by contributing to previously reported enhanced reproduction and dispersal. This study provides a framework to understand links between ecological and physiological traits underlying post-fire population dynamics.

Studies on the population dynamics of a rumor-spreading model in online social networks

Science.gov (United States)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

Structural stability of nonlinear population dynamics.

Science.gov (United States)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

Science.gov (United States)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

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

Science.gov (United States)

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.

Dynamic Properties of the Solow Model with Increasing or Decreasing Population and Time-to-Build Technology

Directory of Open Access Journals (Sweden)

Luca Guerrini

2013-01-01

Full Text Available We introduce a time-to-build technology in a Solow model with nonconstant population. Our analysis shows that the population dynamics may be a source of stability switches and Hopf bifurcations. The analytical results are obtained using the recent technique introduced by Beretta and Kuang (2002 in the studying of delayed differential equations with delay-dependent coefficients in characteristic equation. Numerical simulations are performed in order to illustrate the main dynamic features of the model.

Metastable states and quasicycles in a stochastic Wilson-Cowan model of neuronal population dynamics

KAUST Repository

Bressloff, Paul C.

2010-11-03

We analyze a stochastic model of neuronal population dynamics with intrinsic noise. In the thermodynamic limit N→∞, where N determines the size of each population, the dynamics is described by deterministic Wilson-Cowan equations. On the other hand, for finite N the dynamics is described by a master equation that determines the probability of spiking activity within each population. We first consider a single excitatory population that exhibits bistability in the deterministic limit. The steady-state probability distribution of the stochastic network has maxima at points corresponding to the stable fixed points of the deterministic network; the relative weighting of the two maxima depends on the system size. For large but finite N, we calculate the exponentially small rate of noise-induced transitions between the resulting metastable states using a Wentzel-Kramers- Brillouin (WKB) approximation and matched asymptotic expansions. We then consider a two-population excitatory or inhibitory network that supports limit cycle oscillations. Using a diffusion approximation, we reduce the dynamics to a neural Langevin equation, and show how the intrinsic noise amplifies subthreshold oscillations (quasicycles). © 2010 The American Physical Society.

Population dynamics and population control of Galium aparine L.

NARCIS (Netherlands)

Weide, van der R.Y.

1993-01-01

The population biology of Galium aparine L. needs to be better understood, in order to be able to rationalize decisions about the short- and long-term control of this weed species for different cropping practices.

A population dynamics model was developed to

Modeling population dynamics of solitary bees in relation to habitat quality

Directory of Open Access Journals (Sweden)

K. Ulbrich

2001-09-01

Full Text Available To understand associations between habitat, individual behaviour, and population development of solitary bees we developed an individual-based model. This model is based on field observations of Osmia rufa (L (Apoideae: Megachilidae and describes population dynamics of solitary bees. Model rules are focused on maternal investment, in particular on the female’s individual decisions about sex and size of progeny. In the present paper, we address the effect of habitat quality on population size and sex ratio. We examine how food availability and the risk of parasitism influence long-term population development. It can be shown how population properties result from individual maternal investment which is described as a functional response to fluctuations of environmental conditions. We found that habitat quality can be expressed in terms of cell construction time. This interface factor influences the rate of open cell parasitism as the risk for a brood cell to be parasitized is positively correlated with the time of its construction. Under conditions of scarce food and under resulting long provision times even low parasitism rates lead to a high extinction risk of the population, whereas in rich habitats probabilities of extinction are low even for high rates of parasitism. For a given level of food and parasitism there is an optimum time for cell construction which minimizes the extinction risk of the population. Model results demonstrate that under fluctuating environmental conditions, decreasing habitat quality leads to a decrease in population size but also to rapid shifts in sex ratio.

Stage-Structured Population Dynamics of AEDES AEGYPTI

Science.gov (United States)

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.

Dynamical analysis of a model of social behavior: Criminal vs non-criminal population

International Nuclear Information System (INIS)

Abbas, Syed; Tripathi, Jai Prakash; Neha, A.A.

2017-01-01

Highlights: • A new social model of interaction between criminal and non-criminal population is proposed • The effect of law enforcement is studied • Many real life situations are analyzed • List of open problems is given for future work. - Abstract: In this paper, we construct a model motivated by the well known predator-prey model to study the interaction between criminal population and non-criminal population. Our aim is to study various possibilities of interactions between them. First we model it using simple predator-prey model, then we modify it by considering the logistic growth of non-criminal population. We clearly deduce that the model with logistic growth is better than classical one. More precisely, the role of carrying capacity on the dynamics of criminal minded population is discussed. Further, we incorporate law enforcement term in the model and study its effect. The result obtained suggest that by incorporating enforcement law, the criminal population reduces from the very beginning, which resembles with real life situation. Our result indicates that the criminal minded population exist as long as coefficient of enforcement l_c does not cross a threshold value and after this value the criminal minded population extinct. In addition, we also discuss the occurrence of saddle-node bifurcation in case of model system with law enforcement. Numerical examples and simulations are presented to illustrate the obtained results.

Dynamical systems in population biology

CERN Document Server

Zhao, Xiao-Qiang

2017-01-01

This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology. Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied...

Dynamics of a physiologically structured population in a time-varying environment

DEFF Research Database (Denmark)

Heilmann, Irene Louise Torpe; Starke, Jens; Andersen, Ken Haste

2016-01-01

Physiologically structured population models have become a valuable tool to model the dynamics of populations. In a stationary environment such models can exhibit equilibrium solutions as well as periodic solutions. However, for many organisms the environment is not stationary, but varies more...... or less regularly. In order to understand the interaction between an external environmental forcing and the internal dynamics in a population, we examine the response of a physiologically structured population model to a periodic variation in the food resource. We explore the addition of forcing in two...... cases: (A) where the population dynamics is in equilibrium in a stationary environment, and (B) where the population dynamics exhibits a periodic solution in a stationary environment. When forcing is applied in case A, the solutions are mainly periodic. In case B the forcing signal interacts...

Application of a dynamic population-based model for evaluation of exposure reduction strategies in the baking industry

NARCIS (Netherlands)

Meijster, T.; Warren, N.; Heederik, D.; Tielemans, E.

2009-01-01

Recently a dynamic population model was developed that simulates a population of bakery workers longitudinally through time and tracks the development of work-related sensitisation and respiratory symptoms in each worker. Input for this model comes from cross-sectional and longitudinal

A dynamic population-based model for the development of work-related respiratory health effects among bakery workers.

NARCIS (Netherlands)

Warren, N.; Meijster, T.; Heederik, D.; Tielemans, E.

2009-01-01

OBJECTIVES: This paper presents a dynamic population-based model for the development of sensitisation and respiratory symptoms in bakery workers. The model simulates a population of individual workers longitudinally and tracks the development of work-related sensitisation and respiratory symptoms in

A dynamic population-based model for the development of work-related respiratory health effects among bakery workers

NARCIS (Netherlands)

Warren, N.; Meijster, T.; Heederik, D.; Tielemans, E.

2009-01-01

Objectives: This paper presents a dynamic population-based model for the development of sensitisation and respiratory symptoms in bakery workers. The model simulates a population of individual workers longitudinally and tracks the development of work-related sensitisation and respiratory symptoms in

Population dynamics model for plasmid bearing and plasmid lacking ...

African Journals Online (AJOL)

Streptokinase production in bioreactor is well associated to cell population dynamics. It is an established fact that two types of cell populations are found to emerge from the initial pool of recombinant cell population. This phenomenon leads to an undesired loss in yield of the product. Primary metabolites, like acetic acid etc ...

Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse.

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Kamil Erguler

Full Text Available The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations.

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

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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.

Maintenance of algal endosymbionts in Paramecium bursaria: a simple model based on population dynamics.

Science.gov (United States)

Iwai, Sosuke; Fujiwara, Kenji; Tamura, Takuro

2016-09-01

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

Modelling multi-pulse population dynamics from ultrafast spectroscopy.

Directory of Open Access Journals (Sweden)

Luuk J G W van Wilderen

2011-03-01

Full Text Available Current advanced laser, optics and electronics technology allows sensitive recording of molecular dynamics, from single resonance to multi-colour and multi-pulse experiments. Extracting the occurring (bio- physical relevant pathways via global analysis of experimental data requires a systematic investigation of connectivity schemes. Here we present a Matlab-based toolbox for this purpose. The toolbox has a graphical user interface which facilitates the application of different reaction models to the data to generate the coupled differential equations. Any time-dependent dataset can be analysed to extract time-independent correlations of the observables by using gradient or direct search methods. Specific capabilities (i.e. chirp and instrument response function for the analysis of ultrafast pump-probe spectroscopic data are included. The inclusion of an extra pulse that interacts with a transient phase can help to disentangle complex interdependent pathways. The modelling of pathways is therefore extended by new theory (which is included in the toolbox that describes the finite bleach (orientation effect of single and multiple intense polarised femtosecond pulses on an ensemble of randomly oriented particles in the presence of population decay. For instance, the generally assumed flat-top multimode beam profile is adapted to a more realistic Gaussian shape, exposing the need for several corrections for accurate anisotropy measurements. In addition, the (selective excitation (photoselection and anisotropy of populations that interact with single or multiple intense polarised laser pulses is demonstrated as function of power density and beam profile. Using example values of real world experiments it is calculated to what extent this effectively orients the ensemble of particles. Finally, the implementation includes the interaction with multiple pulses in addition to depth averaging in optically dense samples. In summary, we show that mathematical

Modelling multi-pulse population dynamics from ultrafast spectroscopy.

Science.gov (United States)

van Wilderen, Luuk J G W; Lincoln, Craig N; van Thor, Jasper J

2011-03-21

Current advanced laser, optics and electronics technology allows sensitive recording of molecular dynamics, from single resonance to multi-colour and multi-pulse experiments. Extracting the occurring (bio-) physical relevant pathways via global analysis of experimental data requires a systematic investigation of connectivity schemes. Here we present a Matlab-based toolbox for this purpose. The toolbox has a graphical user interface which facilitates the application of different reaction models to the data to generate the coupled differential equations. Any time-dependent dataset can be analysed to extract time-independent correlations of the observables by using gradient or direct search methods. Specific capabilities (i.e. chirp and instrument response function) for the analysis of ultrafast pump-probe spectroscopic data are included. The inclusion of an extra pulse that interacts with a transient phase can help to disentangle complex interdependent pathways. The modelling of pathways is therefore extended by new theory (which is included in the toolbox) that describes the finite bleach (orientation) effect of single and multiple intense polarised femtosecond pulses on an ensemble of randomly oriented particles in the presence of population decay. For instance, the generally assumed flat-top multimode beam profile is adapted to a more realistic Gaussian shape, exposing the need for several corrections for accurate anisotropy measurements. In addition, the (selective) excitation (photoselection) and anisotropy of populations that interact with single or multiple intense polarised laser pulses is demonstrated as function of power density and beam profile. Using example values of real world experiments it is calculated to what extent this effectively orients the ensemble of particles. Finally, the implementation includes the interaction with multiple pulses in addition to depth averaging in optically dense samples. In summary, we show that mathematical modelling is

Evolutionary dynamics with fluctuating population sizes and strong mutualism

Science.gov (United States)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

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

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

Science.gov (United States)

Chotibut, Thiparat; Nelson, David R

2015-08-01

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

The finite state projection approach to analyze dynamics of heterogeneous populations

Science.gov (United States)

Johnson, Rob; Munsky, Brian

2017-06-01

Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.

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

Energy Technology Data Exchange (ETDEWEB)

Jochem, Warren C [ORNL; Sims, Kelly M [ORNL; Bright, Eddie A [ORNL; Urban, Marie L [ORNL; Rose, Amy N [ORNL; Coleman, Phil R [ORNL; Bhaduri, Budhendra L [ORNL

2013-01-01

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 geographically 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.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

Science.gov (United States)

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

Population and evolutionary dynamics in spatially structured seasonally varying environments.

Science.gov (United States)

Reid, Jane M; Travis, Justin M J; Daunt, Francis; Burthe, Sarah J; Wanless, Sarah; Dytham, Calvin

2018-03-25

Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life-history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco-evolutionary theory and models have not yet fully encompassed within-individual and among-individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life-history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal-tracking technologies are increasingly demonstrating substantial within-population variation in the occurrence and form of migration versus year-round residence, generating diverse forms of 'partial migration' spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year-round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio-temporal population dynamics, we define a 'partially migratory meta-population' system as a spatially structured set of locations that can

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

Science.gov (United States)

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

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Science.gov (United States)

Rodhouse, Thomas J.; Ormsbee, Patricia C.; Irvine, Kathryn M.; Vierling, Lee A.; Szewczak, Joseph M.; Vierling, Kerri T.

2012-01-01

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species–energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients.

Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

Science.gov (United States)

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...

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

Science.gov (United States)

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

Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

Science.gov (United States)

Maslov, Sergei; Sneppen, Kim

2017-01-01

Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity. PMID:28051127

How Resource Phenology Affects Consumer Population Dynamics.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Evolutionary dynamics of cooperation in neutral populations

Science.gov (United States)

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.

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

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Justin V. Remais

2013-07-01

Full Text Available 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.

Science.gov (United States)

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.

A model of population dynamics of TB in a prison system and application to South Africa

OpenAIRE

Witbooi, Peter; Vyambwera, Sibaliwe Maku

2017-01-01

Background Tuberculosis (TB) continues to spread in South African prisons in particular, as prisons are over-capacitated and have poor ventilation. The awaiting trial detainees are not screened on admission and are at high risk of getting infected with TB. Results We propose a compartmental model to describe the population dynamics of TB disease in prisons. Our model considers the inflow of susceptible, exposed and TB infectives into the prison population. Removal of individuals out of the pr...

Bounds on the dynamics of sink populations with noisy immigration.

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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.

Steady states and outbreaks of two-phase nonlinear age-structured model of population dynamics with discrete time delay.

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Akimenko, Vitalii; Anguelov, Roumen

2017-12-01

In this paper we study the nonlinear age-structured model of a polycyclic two-phase population dynamics including delayed effect of population density growth on the mortality. Both phases are modelled as a system of initial boundary values problem for semi-linear transport equation with delay and initial problem for nonlinear delay ODE. The obtained system is studied both theoretically and numerically. Three different regimes of population dynamics for asymptotically stable states of autonomous systems are obtained in numerical experiments for the different initial values of population density. The quasi-periodical travelling wave solutions are studied numerically for the autonomous system with the different values of time delays and for the system with oscillating death rate and birth modulus. In both cases it is observed three types of travelling wave solutions: harmonic oscillations, pulse sequence and single pulse.

Strongly Deterministic Population Dynamics in Closed Microbial Communities

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Zak Frentz

2015-10-01

Full Text Available Biological systems are influenced by random processes at all scales, including molecular, demographic, and behavioral fluctuations, as well as by their interactions with a fluctuating environment. We previously established microbial closed ecosystems (CES as model systems for studying the role of random events and the emergent statistical laws governing population dynamics. Here, we present long-term measurements of population dynamics using replicate digital holographic microscopes that maintain CES under precisely controlled external conditions while automatically measuring abundances of three microbial species via single-cell imaging. With this system, we measure spatiotemporal population dynamics in more than 60 replicate CES over periods of months. In contrast to previous studies, we observe strongly deterministic population dynamics in replicate systems. Furthermore, we show that previously discovered statistical structure in abundance fluctuations across replicate CES is driven by variation in external conditions, such as illumination. In particular, we confirm the existence of stable ecomodes governing the correlations in population abundances of three species. The observation of strongly deterministic dynamics, together with stable structure of correlations in response to external perturbations, points towards a possibility of simple macroscopic laws governing microbial systems despite numerous stochastic events present on microscopic levels.

Stochastic population dynamics of a montane ground-dwelling squirrel.

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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 (λbounce 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.

Bivalves: From individual to population modelling

NARCIS (Netherlands)

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

2014-01-01

An individual based population model for bivalves was designed, built and tested in a 0D approach, to simulate the population dynamics of a mussel bed located in an intertidal area. The processes at the individual level were simulated following the dynamic energy budget theory, whereas initial egg

Effects of an invasive plant on population dynamics in toads.

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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.

Early animal farming and zoonotic disease dynamics: modelling brucellosis transmission in Neolithic goat populations.

Science.gov (United States)

Fournié, Guillaume; Pfeiffer, Dirk U; Bendrey, Robin

2017-02-01

Zoonotic pathogens are frequently hypothesized as emerging with the origins of farming, but evidence of this is elusive in the archaeological records. To explore the potential impact of animal domestication on zoonotic disease dynamics and human infection risk, we developed a model simulating the transmission of Brucella melitensis within early domestic goat populations. The model was informed by archaeological data describing goat populations in Neolithic settlements in the Fertile Crescent, and used to assess the potential of these populations to sustain the circulation of Brucella . Results show that the pathogen could have been sustained even at low levels of transmission within these domestic goat populations. This resulted from the creation of dense populations and major changes in demographic characteristics. The selective harvesting of young male goats, likely aimed at improving the efficiency of food production, modified the age and sex structure of these populations, increasing the transmission potential of the pathogen within these populations. Probable interactions between Neolithic settlements would have further promoted pathogen maintenance. By fostering conditions suitable for allowing domestic goats to become reservoirs of Brucella melitensis , the early stages of agricultural development were likely to promote the exposure of humans to this pathogen.

A Bayesian approach to identifying and compensating for model misspecification in population models.

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Thorson, James T; Ono, Kotaro; Munch, Stephan B

2014-02-01

State-space estimation methods are increasingly used in ecology to estimate productivity and abundance of natural populations while accounting for variability in both population dynamics and measurement processes. However, functional forms for population dynamics and density dependence often will not match the true biological process, and this may degrade the performance of state-space methods. We therefore developed a Bayesian semiparametric state-space model, which uses a Gaussian process (GP) to approximate the population growth function. This offers two benefits for population modeling. First, it allows data to update a specified "prior" on the population growth function, while reverting to this prior when data are uninformative. Second, it allows variability in population dynamics to be decomposed into random errors around the population growth function ("process error") and errors due to the mismatch between the specified prior and estimated growth function ("model error"). We used simulation modeling to illustrate the utility of GP methods in state-space population dynamics models. Results confirmed that the GP model performs similarly to a conventional state-space model when either (1) the prior matches the true process or (2) data are relatively uninformative. However, GP methods improve estimates of the population growth function when the function is misspecified. Results also demonstrated that the estimated magnitude of "model error" can be used to distinguish cases of model misspecification. We conclude with a discussion of the prospects for GP methods in other state-space models, including age and length-structured, meta-analytic, and individual-movement models.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling.

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Matthieu Jacobs

2016-03-01

Full Text Available Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS were performed for models with one susceptible bacterial population without (M1 or with a resting stage (M2, a one population model with adaptive resistance (M5, models with pre-existing susceptible and resistant populations without (M3 or with (M4 inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6. For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h. Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10% and had good imprecision (<30%. However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and

Critical Domain Problem for the Reaction–Telegraph Equation Model of Population Dynamics

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Weam Alharbi

2018-04-01

Full Text Available A telegraph equation is believed to be an appropriate model of population dynamics as it accounts for the directional persistence of individual animal movement. Being motivated by the problem of habitat fragmentation, which is known to be a major threat to biodiversity that causes species extinction worldwide, we consider the reaction–telegraph equation (i.e., telegraph equation combined with the population growth on a bounded domain with the goal to establish the conditions of species survival. We first show analytically that, in the case of linear growth, the expression for the domain’s critical size coincides with the critical size of the corresponding reaction–diffusion model. We then consider two biologically relevant cases of nonlinear growth, i.e., the logistic growth and the growth with a strong Allee effect. Using extensive numerical simulations, we show that in both cases the critical domain size of the reaction–telegraph equation is larger than the critical domain size of the reaction–diffusion equation. Finally, we discuss possible modifications of the model in order to enhance the positivity of its solutions.

Simplified Model for the Population Dynamics Involved in a Malaria Crisis

International Nuclear Information System (INIS)

Kenfack-Jiotsa, A.; Fotsa-Ngaffo, F.

2009-12-01

We adapt a simple model of predator-prey to the population involved in a crisis of malaria. The study is made only in the stream blood inside the human body except for the liver. Particularly we look at the dynamics of the malaria parasites 'merozoites' and their interaction with the blood components, more specifically the red blood cells (RBC) and the immune response grouped under the white blood cells (WBC). The stability analysis of the system reveals an important practical direction to investigate as regards the ratio WBC over RBC since it is a fundamental parameter that characterizes stable regions. The model numerically presents a wide range of possible features of the disease. Even with its simplified form, the model not only recovers well-known results but in addition predicts possible hidden phenomenon and an interesting clinical feature a malaria crisis. (author)

Incorporating territory compression into population models

NARCIS (Netherlands)

Ridley, J; Komdeur, J; Sutherland, WJ; Sutherland, William J.

The ideal despotic distribution, whereby the lifetime reproductive success a territory's owner achieves is unaffected by population density, is a mainstay of behaviour-based population models. We show that the population dynamics of an island population of Seychelles warblers (Acrocephalus

A dynamical model of terrorism

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Firdaus Udwadia

2006-01-01

Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.

Coupled stream and population dynamics: Modeling the role beaver (Castor canadensis) play in generating juvenile steelhead (Oncorhynchus mykiss) habitat

Science.gov (United States)

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

2013-12-01

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

Null Controllability of a Nonlinear Dissipative System and Application to the Detection of the Incomplete Parameter for a Nonlinear Population Dynamics Model

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Yacouba Simporé

2016-01-01

Full Text Available We first prove a null controllability result for a nonlinear system derived from a nonlinear population dynamics model. In order to tackle the controllability problem we use an adapted Carleman inequality. Next we consider the nonlinear population dynamics model with a source term called the pollution term. In order to obtain information on the pollution term we use the method of sentinel.

Integral projection models for finite populations in a stochastic environment.

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Vindenes, Yngvild; Engen, Steinar; Saether, Bernt-Erik

2011-05-01

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.

Building the bridge between animal movement and population dynamics.

Science.gov (United States)

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.

Bivalves: From individual to population modelling

Science.gov (United States)

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

2014-11-01

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

The ArcSDE GIS Dynamic Population Model Tool for Savannah River Site Emergency Response

International Nuclear Information System (INIS)

MCLANE, TRACY; JONES, DWIGHT

2005-01-01

The Savannah River Site (SRS) is a 310-square-mile Department of Energy site located near Aiken, South Carolina. With a workforce of over 10,000 employees and subcontractors, SRS emergency personnel must be able to respond to an emergency event in a timely and effective manner, in order to ensure the safety and security of the Site. Geographic Information Systems (GIS) provides the technology needed to give managers and emergency personnel the information they need to make quick and effective decisions. In the event of a site evacuation, knowing the number of on-site personnel to evacuate from a given area is an essential piece of information for emergency staff. SRS has developed a GIS Dynamic Population Model Tool to quickly communicate real-time information that summarizes employee populations by facility area and building and then generates dynamic maps that illustrate output statistics

Rethinking the logistic approach for population dynamics of mutualistic interactions.

Science.gov (United States)

García-Algarra, Javier; Galeano, Javier; Pastor, Juan Manuel; Iriondo, José María; Ramasco, José J

2014-12-21

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

SIR dynamics in structured populations with heterogeneous connectivity

OpenAIRE

Volz, Erik

2005-01-01

Most epidemic models assume equal mixing among members of a population. An alternative approach is to model a population as random network in which individuals may have heterogeneous connectivity. This paper builds on previous research by describing the exact dynamical behavior of epidemics as they occur in random networks. A system of nonlinear differential equations is presented which describes the behavior of epidemics spreading through random networks with arbitrary degree distributions. ...

Simulation modelling of population dynamics of mosquito vectors for rift valley Fever virus in a disease epidemic setting.

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Clement N Mweya

Full Text Available Rift Valley Fever (RVF is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics.Time-varying distributed delays (TVDD and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district.Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

Simulation modelling of population dynamics of mosquito vectors for rift valley Fever virus in a disease epidemic setting.

Science.gov (United States)

Mweya, Clement N; Holst, Niels; Mboera, Leonard E G; Kimera, Sharadhuli I

2014-01-01

Rift Valley Fever (RVF) is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics. Time-varying distributed delays (TVDD) and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district. Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

Hierarchical modelling of temperature and habitat size effects on population dynamics of North Atlantic cod

DEFF Research Database (Denmark)

Mantzouni, Irene; Sørensen, Helle; O'Hara, Robert B.

2010-01-01

and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified......Understanding how temperature affects cod (Gadus morhua) ecology is important for forecasting how populations will develop as climate changes in future. The effects of spawning-season temperature and habitat size on cod recruitment dynamics have been investigated across the North Atlantic. Ricker...

Slow and fast dynamics model of a Malaria with Sickle-Cell genetic disease with multi-stage infections of the mosquitoes population

Science.gov (United States)

Dewi Siawanta, Shanti; Adi-Kusumo, Fajar; Irwan Endrayanto, Aluicius

2018-03-01

Malaria, which is caused by Plasmodium, is a common disease in tropical areas. There are three types of Plasmodium i.e. Plasmodium Vivax, Plasmodium Malariae, and Plasmodium Falciparum. The most dangerous cases of the Malaria are mainly caused by the Plasmodium Falciparum. One of the important characteristics for the Plasmodium infection is due to the immunity of erythrocyte that contains HbS (Haemoglobin Sickle-cell) genes. The individuals who has the HbS gene has better immunity against the disease. In this paper, we consider a model that shows the spread of malaria involving the interaction between the mosquitos population, the human who has HbS genes population and the human with normal gene population. We do some analytical and numerical simulation to study the basic reproduction ratio and the slow-fast dynamics of the phase-portrait. The slow dynamics in our model represents the response of the human population with HbS gene to the Malaria disease while the fast dynamics show the response of the human population with the normal gene to the disease. The slow and fast dynamics phenomena are due to the fact that the population of the individuals who have HbS gene is much smaller than the individuals who has normal genes.

A model for population dynamics of the mimetic butterfly Papilio polytes in the Sakishima Islands, Japan.

Science.gov (United States)

Sekimura, Toshio; Fujihashi, Yuta; Takeuchi, Yasuhiro

2014-11-21

We present a mathematical model for population dynamics of the mimetic swallowtail butterfly Papilio polytes in the Sakishima Islands, Japan. The model includes four major variables, that is, population densities of three kinds of butterflies (two female forms f. cyrus, f. polytes and the unpalatable butterfly Pachliopta aristolochiae) and their predator. It is well-known that the non-mimic f. cyrus resembles and attracts the male most, and the mimic f. polytes mimics the model butterfly P. aristolochiae. Based on experimental evidence, we assume that two forms f. cyrus and f. polytes interact under intraspecific competition for resources including the male, and the growth rate of f. cyrus is higher than that of f. polytes. We further assume that both the benefit of mimicry for the mimic f. polytes and the cost for the model are dependent on their relative frequencies, i.e. the motality of the mimic by predation decreases with increase in frequency of the model, while the motality of the model increases as the frequency of the mimic increases. Taking the density-dependent effect through carrying capacity into account, we set up a model system consisting of three ordinary differential equations (ODEs), analyze it mathematically and provide computer simulations that confirm the analytical results. Our results reproduce field records on population dynamics of P. polytes in the Miyako-jima Island. They also explain the positive dependence of the relative abundance (RA) of the mimic on the advantage index (AI) of the mimicry in the Sakishima Islands defined in Section 2. Copyright © 2014 Elsevier Ltd. All rights reserved.

Population dynamics of light-limited phytoplankton : Microcosm experiments

NARCIS (Netherlands)

Huisman, Jef

This paper investigates the extent to which the predictions of an elementary model for light-limited growth are matched by laboratory experiments with light-limited phytoplankton. The model and experiments link the population dynamics of phytoplankton species with changes in the light gradient

Particle algorithms for population dynamics in flows

International Nuclear Information System (INIS)

Perlekar, Prasad; Toschi, Federico; Benzi, Roberto; Pigolotti, Simone

2011-01-01

We present and discuss particle based algorithms to numerically study the dynamics of population subjected to an advecting flow condition. We discuss few possible variants of the algorithms and compare them in a model compressible flow. A comparison against appropriate versions of the continuum stochastic Fisher equation (sFKPP) is also presented and discussed. The algorithms can be used to study populations genetics in fluid environments.

Effects of wind farms on harbour porpoise behaviour and population dynamics

DEFF Research Database (Denmark)

Nabe-Nielsen, Jacob; Tougaard, Jakob; Teilmann, Jonas

We developed an individual-based simulation model in order to study the cumulative impacts of wind farms and ship traffic on the long-term survival and population dynamics of the harbour porpoise (Phocoena phocoena) in Kattegat and the Belt Seas. The model is based on knowl- edge of the porpoises...... at distances >1 km. Our simulations suggest that operating wind farms and wind farms under construction do not affect the size or dynamics of the harbour porpoise population in Kattegat. Ship traffic may, in contrast, cause the population size to decrease....

Using dynamic stochastic modelling to estimate population risk factors in infectious disease: the example of FIV in 15 cat populations.

Directory of Open Access Journals (Sweden)

David Fouchet

Full Text Available BACKGROUND: In natural cat populations, Feline Immunodeficiency Virus (FIV is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS: To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION: Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease.

Estimating spatio-temporal dynamics of size-structured populations

DEFF Research Database (Denmark)

Kristensen, Kasper; Thygesen, Uffe Høgsbro; Andersen, Ken Haste

2014-01-01

with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between size classes within each trawl haul due to clustering...... of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort...

A probabilistic transmission and population dynamic model to assess tuberculosis infection risk.

Science.gov (United States)

Liao, Chung-Min; Cheng, Yi-Hsien; Lin, Yi-Jun; Hsieh, Nan-Hung; Huang, Tang-Luen; Chio, Chia-Pin; Chen, Szu-Chieh; Ling, Min-Pei

2012-08-01

The purpose of this study was to examine tuberculosis (TB) population dynamics and to assess potential infection risk in Taiwan. A well-established mathematical model of TB transmission built on previous models was adopted to study the potential impact of TB transmission. A probabilistic risk model was also developed to estimate site-specific risks of developing disease soon after recent primary infection, exogenous reinfection, or through endogenous reactivation (latently infected TB) among Taiwan regions. Here, we showed that the proportion of endogenous reactivation (53-67%) was larger than that of exogenous reinfection (32-47%). Our simulations showed that as epidemic reaches a steady state, age distribution of cases would finally shift toward older age groups dominated by latently infected TB cases as a result of endogenous reactivation. A comparison of age-weighted TB incidence data with our model simulation output with 95% credible intervals revealed that the predictions were in an apparent agreement with observed data. The median value of overall basic reproduction number (R₀) in eastern Taiwan ranged from 1.65 to 1.72, whereas northern Taiwan had the lowest R₀ estimate of 1.50. We found that total TB incidences in eastern Taiwan had 25-27% probabilities of total proportion of infected population exceeding 90%, whereas there were 36-66% probabilities having exceeded 20% of total proportion of infected population attributed to latently infected TB. We suggested that our Taiwan-based analysis can be extended to the context of developing countries, where TB remains a substantial cause of elderly morbidity and mortality. © 2012 Society for Risk Analysis.

Mathematical Modeling of Extinction of Inhomogeneous Populations

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Karev, G.P.; Kareva, I.

2016-01-01

Mathematical models of population extinction have a variety of applications in such areas as ecology, paleontology and conservation biology. Here we propose and investigate two types of sub-exponential models of population extinction. Unlike the more traditional exponential models, the life duration of sub-exponential models is finite. In the first model, the population is assumed to be composed clones that are independent from each other. In the second model, we assume that the size of the population as a whole decreases according to the sub-exponential equation. We then investigate the “unobserved heterogeneity”, i.e. the underlying inhomogeneous population model, and calculate the distribution of frequencies of clones for both models. We show that the dynamics of frequencies in the first model is governed by the principle of minimum of Tsallis information loss. In the second model, the notion of “internal population time” is proposed; with respect to the internal time, the dynamics of frequencies is governed by the principle of minimum of Shannon information loss. The results of this analysis show that the principle of minimum of information loss is the underlying law for the evolution of a broad class of models of population extinction. Finally, we propose a possible application of this modeling framework to mechanisms underlying time perception. PMID:27090117

An open-population hierarchical distance sampling model

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

2015-01-01

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

An open-population hierarchical distance sampling model.

Science.gov (United States)

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

2015-02-01

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

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

Science.gov (United States)

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

2011-01-01

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

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

Science.gov (United States)

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.

On the population dynamics of the malaria vector

International Nuclear Information System (INIS)

Ngwa, G.A.

2005-10-01

A deterministic differential equation model for the population dynamics of the human malaria vector is derived and studied. Conditions for the existence and stability of a non-zero steady state vector population density are derived. These reveal that a threshold parameter, the vectorial basic reproduction number, exist and the vector can establish itself in the community if and only if this parameter exceeds unity. When a non-zero steady state population density exists, it can be stable but it can also be driven to instability via a Hopf Bifurcation to periodic solutions, as a parameter is varied in parameter space. By considering a special case, an asymptotic perturbation analysis is used to derive the amplitude of the oscillating solutions for the full non-linear system. The present modelling exercise and results show that it is possible to study the population dynamics of disease vectors, and hence oscillatory behaviour as it is often observed in most indirectly transmitted infectious diseases of humans, without recourse to external seasonal forcing. (author)

Stochastic population dynamics in spatially extended predator-prey systems

Science.gov (United States)

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

Evolutionary Dynamics and Diversity in Microbial Populations

Science.gov (United States)

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.

A Theoretical Approach to Understanding Population Dynamics with Seasonal Developmental Durations

Science.gov (United States)

Lou, Yijun; Zhao, Xiao-Qiang

2017-04-01

There is a growing body of biological investigations to understand impacts of seasonally changing environmental conditions on population dynamics in various research fields such as single population growth and disease transmission. On the other side, understanding the population dynamics subject to seasonally changing weather conditions plays a fundamental role in predicting the trends of population patterns and disease transmission risks under the scenarios of climate change. With the host-macroparasite interaction as a motivating example, we propose a synthesized approach for investigating the population dynamics subject to seasonal environmental variations from theoretical point of view, where the model development, basic reproduction ratio formulation and computation, and rigorous mathematical analysis are involved. The resultant model with periodic delay presents a novel term related to the rate of change of the developmental duration, bringing new challenges to dynamics analysis. By investigating a periodic semiflow on a suitably chosen phase space, the global dynamics of a threshold type is established: all solutions either go to zero when basic reproduction ratio is less than one, or stabilize at a positive periodic state when the reproduction ratio is greater than one. The synthesized approach developed here is applicable to broader contexts of investigating biological systems with seasonal developmental durations.

Biology as population dynamics: heuristics for transmission risk.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A probabilistic cellular automata model for the dynamics of a population driven by logistic growth and weak Allee effect

Science.gov (United States)

Mendonça, J. R. G.

2018-04-01

We propose and investigate a one-parameter probabilistic mixture of one-dimensional elementary cellular automata under the guise of a model for the dynamics of a single-species unstructured population with nonoverlapping generations in which individuals have smaller probability of reproducing and surviving in a crowded neighbourhood but also suffer from isolation and dispersal. Remarkably, the first-order mean field approximation to the dynamics of the model yields a cubic map containing terms representing both logistic and weak Allee effects. The model has a single absorbing state devoid of individuals, but depending on the reproduction and survival probabilities can achieve a stable population. We determine the critical probability separating these two phases and find that the phase transition between them is in the directed percolation universality class of critical behaviour.

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

Science.gov (United States)

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

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

Science.gov (United States)

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

2015-01-01

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health

Use of models in small mammal population studies

International Nuclear Information System (INIS)

Conley, W.; Nichols, J.D.

1978-01-01

The role of models as contributors to the understanding of natural populations of small mammals is reviewed. A philosophy of model use and projections for future work are also included. Categories of biological phenomena reviewed include models on population dynamics (demographic variables and population regulation, dispersal, sex-ratios, predation, population cycles), population responses to environmental conditions, genetics of small mammal populations, competitive interactions, ecosystems and small mammal functions, and control and management of small mammal populations

Master Middle Ware: A Tool to Integrate Water Resources and Fish Population Dynamics Models

Science.gov (United States)

Yi, S.; Sandoval Solis, S.; Thompson, L. C.; Kilduff, D. P.

2017-12-01

Linking models that investigate separate components of ecosystem processes has the potential to unify messages regarding management decisions by evaluating potential trade-offs in a cohesive framework. This project aimed to improve the ability of riparian resource managers to forecast future water availability conditions and resultant fish habitat suitability, in order to better inform their management decisions. To accomplish this goal, we developed a middleware tool that is capable of linking and overseeing the operations of two existing models, a water resource planning tool Water Evaluation and Planning (WEAP) model and a habitat-based fish population dynamics model (WEAPhish). First, we designed the Master Middle Ware (MMW) software in Visual Basic for Application® in one Excel® file that provided a familiar framework for both data input and output Second, MMW was used to link and jointly operate WEAP and WEAPhish, using Visual Basic Application (VBA) macros to implement system level calls to run the models. To demonstrate the utility of this approach, hydrological, biological, and middleware model components were developed for the Butte Creek basin. This tributary of the Sacramento River, California is managed for both hydropower and the persistence of a threatened population of spring-run Chinook salmon (Oncorhynchus tschawytscha). While we have demonstrated the use of MMW for a particular watershed and fish population, MMW can be customized for use with different rivers and fish populations, assuming basic data requirements are met. This model integration improves on ad hoc linkages for managing data transfer between software programs by providing a consistent, user-friendly, and familiar interface across different model implementations. Furthermore, the data-viewing capabilities of MMW facilitate the rapid interpretation of model results by hydrologists, fisheries biologists, and resource managers, in order to accelerate learning and management decision

Populational Growth Models Proportional to Beta Densities with Allee Effect

Science.gov (United States)

Aleixo, Sandra M.; Rocha, J. Leonel; Pestana, Dinis D.

2009-05-01

We consider populations growth models with Allee effect, proportional to beta densities with shape parameters p and 2, where the dynamical complexity is related with the Malthusian parameter r. For p>2, these models exhibit a population dynamics with natural Allee effect. However, in the case of 1models do not include this effect. In order to inforce it, we present some alternative models and investigate their dynamics, presenting some important results.

Dynamics and Biocontrol: The Indirect Effects of a Predator Population on a Host-Vector Disease Model

Directory of Open Access Journals (Sweden)

Fengyan Zhou

2014-01-01

Full Text Available A model of the interactions among a host population, an insect-vector population, which transmits virus from hosts to hosts, and a vector predator population is proposed based on virus-host, host-vector, and prey (vector-enemy theories. The model is investigated to explore the indirect effect of natural enemies on host-virus dynamics by reducing the vector densities, which shows the basic reproduction numbers R01 (without predators and R02 (with predators that provide threshold conditions on determining the uniform persistence and extinction of the disease in a host population. When the model is absent from predator, the disease is persistent if R01>1; in such a case, by introducing predators of a vector, then the insect-transmitted disease will be controlled if R02<1. From the point of biological control, these results show that an additional predator population of the vector may suppress the spread of vector-borne diseases. In addition, there exist limit cycles with persistence of the disease or without disease in presence of predators. Finally, numerical simulations are conducted to support analytical results.

Computer simulation of population dynamics inside the urban environment

Science.gov (United States)

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.

Matrix population models from 20 studies of perennial plant populations

Science.gov (United States)

Ellis, Martha M.; Williams, Jennifer L.; Lesica, Peter; Bell, Timothy J.; Bierzychudek, Paulette; Bowles, Marlin; Crone, Elizabeth E.; Doak, Daniel F.; Ehrlen, Johan; Ellis-Adam, Albertine; McEachern, Kathryn; Ganesan, Rengaian; Latham, Penelope; Luijten, Sheila; Kaye, Thomas N.; Knight, Tiffany M.; Menges, Eric S.; Morris, William F.; den Nijs, Hans; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Shelly, J. Stephen; Stanley, Amanda; Thorpe, Andrea; Tamara, Ticktin; Valverde, Teresa; Weekley, Carl W.

2012-01-01

Demographic transition matrices are one of the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long-term demographic monitoring. These data were assembled as part of the 'Testing Matrix Models' working group through the National Center for Ecological Analysis and Synthesis (NCEAS). In sum, these data represent 82 populations with >460 total population-years of data. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics.

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

Science.gov (United States)

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.

Endogenous Population Dynamics and Economic Growth with Free Trade between Countries

Directory of Open Access Journals (Sweden)

Wei-Bin Zhang

2016-05-01

Full Text Available This paper builds a model to deal with dynamic interdependence between different countries' birth rates, mortality rates, populations, wealth accumulation, and time distributions between working, leisure and children caring. The model shows the role of human capital, technological and preference changes on national differences in birth rates, mortality rates, time distributions, population change, and wealth accumulation. The economic mechanisms of wealth accumulation, production and trade are based the Solow growth model and the Oniki-Uzawa trade model. We use the utility function proposed by Zhang to describe the behavior of households. We model national and gender differences in human capital, propensity to have children, propensity to use leisure time, and children caring efficiency. We describe the dynamics of global economic growth, trade patterns, national differences in wealth, income, birth rates, mortality rates, and populations with differential equations. We simulate the model to show the motion of the system and identify the existence of equilibrium point. We also examine the effects of changes in the propensity to have children, the propensity to save, woman's propensity to use leisure, woman's human capital, and woman's emotional involvement in children caring on the dynamics of the global and national economies.

Explorations in combining cognitive models of individuals and system dynamics models of groups.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.

2008-07-01

This report documents a demonstration model of interacting insurgent leadership, military leadership, government leadership, and societal dynamics under a variety of interventions. The primary focus of the work is the portrayal of a token societal model that responds to leadership activities. The model also includes a linkage between leadership and society that implicitly represents the leadership subordinates as they directly interact with the population. The societal model is meant to demonstrate the efficacy and viability of using System Dynamics (SD) methods to simulate populations and that these can then connect to cognitive models depicting individuals. SD models typically focus on average behavior and thus have limited applicability to describe small groups or individuals. On the other hand, cognitive models readily describe individual behavior but can become cumbersome when used to describe populations. Realistic security situations are invariably a mix of individual and population dynamics. Therefore, the ability to tie SD models to cognitive models provides a critical capability that would be otherwise be unavailable.

Effects of demographic structure on key properties of stochastic density-independent population dynamics.

Science.gov (United States)

Vindenes, Yngvild; Sæther, Bernt-Erik; Engen, Steinar

2012-12-01

The development of stochastic demography has largely been based on age structured populations, although other types of demographic structure, especially permanent and dynamic heterogeneity, are likely common in natural populations. The combination of stochasticity and demographic structure is a challenge for analyses of population dynamics and extinction risk, because the population structure will fluctuate around the stable structure and the population size shows transient fluctuations. However, by using a diffusion approximation for the total reproductive value, density-independent dynamics of structured populations can be described with only three population parameters: the expected population growth rate, the environmental variance and the demographic variance. These parameters depend on population structure via the state-specific vital rates and transition rates. Once they are found, the diffusion approximation represents a substantial reduction in model complexity. Here, we review and compare the key population parameters across a wide range of demographic structure, from the case of no structure to the most general case of dynamic heterogeneity, and for both discrete and continuous types. We focus on the demographic variance, but also show how environmental stochasticity can be included. This study brings together results from recent models, each considering a specific type of population structure, and places them in a general framework for structured populations. Comparison across different types of demographic structure reveals that the reproductive value is an essential concept for understanding how population structure affects stochastic dynamics and extinction risk. Copyright © 2011 Elsevier Inc. All rights reserved.

Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

Science.gov (United States)

Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, M; Verschwele, A

2015-04-01

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Delay differential systems for tick population dynamics.

Science.gov (United States)

Fan, Guihong; Thieme, Horst R; Zhu, Huaiping

2015-11-01

Ticks play a critical role as vectors in the transmission and spread of Lyme disease, an emerging infectious disease which can cause severe illness in humans or animals. To understand the transmission dynamics of Lyme disease and other tick-borne diseases, it is necessary to investigate the population dynamics of ticks. Here, we formulate a system of delay differential equations which models the stage structure of the tick population. Temperature can alter the length of time delays in each developmental stage, and so the time delays can vary geographically (and seasonally which we do not consider). We define the basic reproduction number [Formula: see text] of stage structured tick populations. The tick population is uniformly persistent if [Formula: see text] and dies out if [Formula: see text]. We present sufficient conditions under which the unique positive equilibrium point is globally asymptotically stable. In general, the positive equilibrium can be unstable and the system show oscillatory behavior. These oscillations are primarily due to negative feedback within the tick system, but can be enhanced by the time delays of the different developmental stages.

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

Energy Technology Data Exchange (ETDEWEB)

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{sub 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.

Population dynamics of Eldana saccharina Walker (Lepidoptera: Pyralidae): application of a biophysical model to understand phenological variation in an agricultural pest.

Science.gov (United States)

Kleynhans, E; Barton, M G; Conlong, D E; Terblanche, J S

2017-08-08

Understanding pest population dynamics and seasonal phenology is a critical component of modern integrated pest-management programs. Accurate forecasting allows timely, cost-effective interventions, including maximum efficacy of, for example, biological control and/or sterile insect technique. Due to the variation in life stage-related sensitivity toward climate, insect pest population abundance models are often not easily interpreted or lack direct relevance to management strategies in the field. Here we apply a process-based (biophysical) model that incorporates climate data with life stage-dependent physiology and life history to attempt to predict Eldana saccharina life stage and generation turnover in sugarcane fields. Fitness traits are modelled at two agricultural locations in South Africa that differ in average temperature (hereafter a cold and a warm site). We test whether the life stage population structures in the field entering winter and local climate during winter directly affect development rates, and therefore interact to determine the population dynamics and phenological responses of E. saccharina in subsequent spring and summer seasons. The model predicts that: (1) E. saccharina can cycle through more generations at the warm site where fewer hours of cold and heat stress are endured, and (2) at the cold site, overwintering as pupae (rather than larvae) confer higher relative fitness and fecundity in the subsequent summer adult moths. The model predictions were compared with a large dataset of field observations from scouting records. Model predictions for larval presence (or absence) generally overlapped well with positive (or negative) scout records. These results are important for integrated pest management strategies by providing a useful foundation for future population dynamics models, and are applicable to a variety of agricultural landscapes, but especially the sugarcane industry of South Africa.

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

Science.gov (United States)

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.

Population balance models: a useful complementary modelling framework for future WWTP modelling

DEFF Research Database (Denmark)

Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

2015-01-01

Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling...

A Mathematical Model of Economic Population Dynamics in a Country That Has Optimal Zakat Management

Science.gov (United States)

Subhan, M.

2018-04-01

Zakat is the main tools against two issues in Islamic economy: economic justice and helping the poor. However, no government of Islamic countries can solve the economic disparity today. A mathematical model could give some understanding about this phenomenon. The goal of this research is to obtain a mathematical model that can describe the dynamic of economic group population. The research is theoretical based on relevance references. From the analytical and numerical simulation, we conclude that well-manage zakat and full comitment of the wealthy can achieve wealth equilibrium that represents minimum poverty.

Population Balance Models: A useful complementary modelling framework for future WWTP modelling

DEFF Research Database (Denmark)

Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

2014-01-01

Population Balance Models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by statistical distributions. This has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit...

Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia

Science.gov (United States)

Brehme, Marc; Koschmieder, Steffen; Montazeri, Maryam; Copland, Mhairi; Oehler, Vivian G.; Radich, Jerald P.; Brümmendorf, Tim H.; Schuppert, Andreas

2016-04-01

Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34+ similarity as a disease progression marker to patient-derived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients’ disease history within chronic phase (CP) and significantly separates “early” from “late” CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis.

HUMTRN and EFFECTS: Age and sex specific dosimetric and physiological human population dynamics models for dose assessment

International Nuclear Information System (INIS)

Gallegos, A.F.; Wenzel, W.J.

1989-01-01

A human simulation model called HUMTRN and a population risk assessment model called EFFECTS were developed at Los Alamos National Laboratory as a major component of the BIOTRAN environmental risk assessment model. HUMTRN simulates growth using dietary and physiological characteristics and kinetics of radionuclides to predict radiation doses to selected organs of both sexes in different age groups. The model called EFFECTS was interfaced with output from HUMTRN to predict cancer risks in a dynamic human population. EFFECTS is based on the National Research Council Committee on the Biological Effects of Ionizing Radiation (BEIR)-III radiation cancer mortality estimates from the U.S. population mortality and natality estimates for both sexes between the ages of 1 and 70. These models track radiation intake from air, water, and food, calculate uptake in major growing organs, and estimate cancer mortality risks. This report documents the use of an IBM Personal Computer AT to run HUMTRN and EFFECTS. Air, water, and food contaminant concentrations are provided as input to HUMTRN, which then provides input for EFFECTS. The limitations of this approach are also discussed

A dynamic activity-based population modelling approach to evaluate exposure to air pollution: Methods and application to a Dutch urban area

International Nuclear Information System (INIS)

Beckx, Carolien; Int Panis, Luc; Arentze, Theo; Janssens, Davy; Torfs, Rudi; Broekx, Steven; Wets, Geert

2009-01-01

Recent air quality studies have highlighted that important differences in pollutant concentrations can occur over the day and between different locations. Traditional exposure analyses, however, assume that people are only exposed to pollution at their place of residence. Activity-based models, which recently have emerged from the field of transportation research, offer a technique to micro-simulate activity patterns of a population with a high resolution in space and time. Due to their characteristics, this model can be applied to establish a dynamic exposure assessment to air pollution. This paper presents a new exposure methodology, using a micro-simulator of activity-travel behaviour, to develop a dynamic exposure assessment. The methodology is applied to a Dutch urban area to demonstrate the advantages of the approach for exposure analysis. The results for the exposure to PM 10 and PM 2.5 , air pollutants considered as hazardous for human health, reveal large differences between the static and the dynamic approach, mainly due to an underestimation of the number of hours spent in the urban region by the static method. We can conclude that this dynamic population modelling approach is an important improvement over traditional methods and offers a new and more sensitive way for estimating population exposure to air pollution. In the light of the new European directive, aimed at reducing the exposure of the population to PM 2.5 , this new approach contributes to a much more accurate exposure assessment that helps evaluate policies to reduce public exposure to air pollution

Phenotypic equilibrium as probabilistic convergence in multi-phenotype cell population dynamics.

Directory of Open Access Journals (Sweden)

Da-Quan Jiang

Full Text Available We consider the cell population dynamics with n different phenotypes. Both the Markovian branching process model (stochastic model and the ordinary differential equation (ODE system model (deterministic model are presented, and exploited to investigate the dynamics of the phenotypic proportions. We will prove that in both models, these proportions will tend to constants regardless of initial population states ("phenotypic equilibrium" under weak conditions, which explains the experimental phenomenon in Gupta et al.'s paper. We also prove that Gupta et al.'s explanation is the ODE model under a special assumption. As an application, we will give sufficient and necessary conditions under which the proportion of one phenotype tends to 0 (die out or 1 (dominate. We also extend our results to non-Markovian cases.

Fish population dynamics

National Research Council Canada - National Science Library

Gulland, J. A

1977-01-01

This book describes how the dynamics of fish populations can be analysed in terms of the factors affecting their rates of growth, mortality and reproduction, with particular emphasis on the effects of fishing...

Implementing a generic method for bias correction in statistical models using random effects, with spatial and population dynamics examples

DEFF Research Database (Denmark)

Thorson, James T.; Kristensen, Kasper

2016-01-01

Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques...... configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon......-method to a spatial regression model when estimating an index of population abundance, and compare results with an alternative bias-correction algorithm that involves Markov-chain Monte Carlo sampling. This example shows that the epsilon-method leads to a biologically significant difference in estimates of average...

A model of population dynamics of TB in a prison system and application to South Africa.

Science.gov (United States)

Witbooi, Peter; Vyambwera, Sibaliwe Maku

2017-11-29

Tuberculosis (TB) continues to spread in South African prisons in particular, as prisons are over-capacitated and have poor ventilation. The awaiting trial detainees are not screened on admission and are at high risk of getting infected with TB. We propose a compartmental model to describe the population dynamics of TB disease in prisons. Our model considers the inflow of susceptible, exposed and TB infectives into the prison population. Removal of individuals out of the prison population can be either by death or by being released from prison, as compared to a general population in which removal is only by death. We describe conditions, including non-inflow of infectives into the prison, which will ensure that TB can be eradicated from the prison population. The model is calibrated for the South African prison system, by using data in existing literature. The model can be used to make quantitative projections of TB prevalence and to measure the effect of interventions. Illustrative simulations in this regard are presented. The model can be used for other prison populations too, if data is available to calculate the model parameters. Various simulations generated with our model serve to illustrate how it can be utilized in making future projections of the levels of prevalence of TB, and to quantify the effect of interventions such as screening, treatment or reduction of transmission parameter values through improved living conditions for inmates. This makes it particularly useful as there are various targets set by the World Health Organization and by governments, for reduction of TB prevalence and ultimately its eradication. Towards eradication of TB from a prison system, the theorem on global stability of the disease-free state is a useful indicator.

A stage-based model of manatee population dynamics

Science.gov (United States)

Runge, M.C.; Langtimm, C.A.; Kendall, W.L.

2004-01-01

A stage-structured population model for the Florida manatee (Trichechus manatus latirostris) was developed that explicitly incorporates uncertainty in parameter estimates. The growth rates calculated with this model reflect the status of the regional populations over the most recent 10-yr period. The Northwest and Upper St. Johns River regions have growth rates (8) of 1.037 (95% interval, 1.016?1.056) and 1.062 (1.037?1.081), respectively. The Southwest region has a growth rate of 0.989 (0.946?1.024), suggesting this population has been declining at about 1.1% per year. The estimated growth rate in the Atlantic region is 1.010 (0.988?1.029), but there is some uncertainty about whether adult survival rates have been constant over the last 10 yr; using the mean survival rates from the most recent 5-yr period, the estimated growth rate in this region is 0.970 (0.938?0.998). Elasticity analysis indicates that the most effective management actions should seek to increase adult survival rates. Decomposition of the uncertainty in the growth rates indicates that uncertainty about population status can best be reduced through increased monitoring of adult survival rate.

Population dynamics at high Reynolds number

NARCIS (Netherlands)

Perlekar, P.; Benzi, R.; Nelson, D.R.; Toschi, F.

2010-01-01

We study the statistical properties of population dynamics evolving in a realistic two-dimensional compressible turbulent velocity field. We show that the interplay between turbulent dynamics and population growth and saturation leads to quasi-localization and a remarkable reduction in the carrying

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

Science.gov (United States)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

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

Critical dynamics in population vaccinating behavior.

Science.gov (United States)

Pananos, A Demetri; Bury, Thomas M; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P; Nyhan, Brendan; Salathé, Marcel; Bauch, Chris T

2017-12-26

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena-special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles-mumps-rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014-2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior-disease systems, the population responds to the outbreak by moving away from the tipping point, causing "critical speeding up" whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. Copyright © 2017 the Author(s). Published by PNAS.

Ruffed grouse population dynamics in the central and southern Appalachians

Science.gov (United States)

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...

How Levins’ dynamics emerges from a Ricker metapopulation model

KAUST Repository

Elí as-Wolff, F.; Eriksson, Anders; Manica, A.; Mehlig, B.

2015-01-01

Understanding the dynamics of metapopulations close to extinction is of vital importance for management. Levins-like models, in which local patches are treated as either occupied or empty, have been used extensively to explore the extinction dynamics of metapopulations, but they ignore the important role of local population dynamics. In this paper, we consider a stochastic metapopulation model where local populations follow a stochastic, density-dependent dynamics (the Ricker model), and use this framework to investigate the behaviour of the metapopulation on the brink of extinction. We determine under which circumstances the metapopulation follows a time evolution consistent with Levins’ dynamics. We derive analytical expressions for the colonisation and extinction rates (c and e) in Levins-type models in terms of reproduction, survival and dispersal parameters of the local populations, providing an avenue to parameterising Levins-like models from the type of information on local demography that is available for a number of species. To facilitate applying our results, we provide a numerical algorithm for computing c and e.

How Levins’ dynamics emerges from a Ricker metapopulation model

KAUST Repository

Elías-Wolff, F.

2015-09-24

Understanding the dynamics of metapopulations close to extinction is of vital importance for management. Levins-like models, in which local patches are treated as either occupied or empty, have been used extensively to explore the extinction dynamics of metapopulations, but they ignore the important role of local population dynamics. In this paper, we consider a stochastic metapopulation model where local populations follow a stochastic, density-dependent dynamics (the Ricker model), and use this framework to investigate the behaviour of the metapopulation on the brink of extinction. We determine under which circumstances the metapopulation follows a time evolution consistent with Levins’ dynamics. We derive analytical expressions for the colonisation and extinction rates (c and e) in Levins-type models in terms of reproduction, survival and dispersal parameters of the local populations, providing an avenue to parameterising Levins-like models from the type of information on local demography that is available for a number of species. To facilitate applying our results, we provide a numerical algorithm for computing c and e.

Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

Directory of Open Access Journals (Sweden)

E Penelope Holland

Full Text Available Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

Application of a dynamic population-based model for evaluation of exposure reduction strategies in the baking industry

Energy Technology Data Exchange (ETDEWEB)

Meijster, Tim; Tielemans, Erik [TNO Quality of Life, Business unit Quality and Safety, Zeist (Netherlands); Warren, Nick [Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire (United Kingdom); Heederik, Dick, E-mail: Tim.meijster@tno.n [Utrecht University, Institute of Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht (Netherlands)

2009-02-01

Recently a dynamic population model was developed that simulates a population of bakery workers longitudinally through time and tracks the development of work-related sensitisation and respiratory symptoms in each worker. Input for this model comes from cross-sectional and longitudinal epidemiological studies which allowed estimation of exposure response relationships and disease transition probabilities This model allows us to study the development of diseases and transitions between disease states over time in relation to determinants of disease including flour dust and/or allergen exposure. Furthermore it enables more realistic modelling of the health impact of different intervention strategies at the workplace (e.g. changes in exposure may take several years to impact on ill-health and often occur as a gradual trend). A large dataset of individual full-shift exposure measurements and real-time exposure measurements were used to obtain detailed insight into the effectiveness of control measures and other determinants of exposure. Given this information a population wide reduction of the median exposure with 50% was evaluated in this paper.

Experiments with mathematical models to simulate hepatitis A population dynamics under different levels of endemicity

Directory of Open Access Journals (Sweden)

Mariana Alves de Guimaraens

Full Text Available Heterogeneous access to sanitation services is a characteristic of communities in Brazil. This heterogeneity leads to different patterns of hepatitis A endemicity: areas with low infection rates have higher probability of outbreaks, and areas with higher infection rates have high prevalence and low risk of outbreaks. Here we develop a mathematical model to study the effect of variable exposure to infection on the epidemiological dynamics of hepatitis A. Differential equations were used to simulate population dynamics and were numerically solved using the software StellaTM. The model uses parameters from serological surveys in the Greater Metropolitan Rio de Janeiro, in areas with different sanitation conditions. Computer simulation experiments show that the range of infection rates observed in these communities are characteristic of high and low levels of hepatitis A endemicity. We also found that the functional relationship between sanitation and exposure to infection is an important component of the model. The analysis of the public health impact of partial sanitation requires a better understanding of this relationship.

A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes.

Science.gov (United States)

Louarn, Gaëtan; Faverjon, Lucas

2018-04-18

Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models. A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability. The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources. A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to

Structured population dynamics: continuous size and discontinuous stage structures.

Science.gov (United States)

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.

A dynamic birth-death model via Intrinsic Linkage

Directory of Open Access Journals (Sweden)

Robert Schoen

2013-05-01

Full Text Available BACKGROUND Dynamic population models, or models with changing vital rates, are only beginning to receive serious attention from mathematical demographers. Despite considerable progress, there is still no general analytical solution for the size or composition of a population generated by an arbitrary sequence of vital rates. OBJECTIVE The paper introduces a new approach, Intrinsic Linkage, that in many cases can analytically determine the birth trajectory of a dynamic birth-death population. METHODS Intrinsic Linkage assumes a weighted linear relationship between (i the time trajectory of proportional increases in births in a population and (ii the trajectory of the intrinsic rates of growth of the projection matrices that move the population forward in time. Flexibility is provided through choice of the weighting parameter, w, that links these two trajectories. RESULTS New relationships are found linking implied intrinsic and observed population patterns of growth. Past experience is "forgotten" through a process of simple exponential decay. When the intrinsic growth rate trajectory follows a polynomial, exponential, or cyclical pattern, the population birth trajectory can be expressed analytically in closed form. Numerical illustrations provide population values and relationships in metastable and cyclically stable models. Plausible projection matrices are typically found for a broad range of values of w, although w appears to vary greatly over time in actual populations. CONCLUSIONS The Intrinsic Linkage approach extends current techniques for dynamic modeling, revealing new relationships between population structures and the changing vital rates that generate them.

Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

Science.gov (United States)

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

Allee effects on population dynamics with delay

International Nuclear Information System (INIS)

Celik, C.; Merdan, H.; Duman, O.; Akin, O.

2008-01-01

In this paper, we study the stability analysis of equilibrium points of population dynamics with delay when the Allee effect occurs at low population density. Mainly, our mathematical results and numerical simulations point to the stabilizing effect of the Allee effects on population dynamics with delay

Climate effects and feedback structure determining weed population dynamics in a long-term experiment.

Science.gov (United States)

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

Science.gov (United States)

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

Climate effects and feedback structure determining weed population dynamics in a long-term experiment.

Directory of Open Access Journals (Sweden)

Mauricio Lima

Full Text Available 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.

Network evolution induced by the dynamical rules of two populations

Science.gov (United States)

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 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.

Social Information Links Individual Behavior to Population and Community Dynamics.

Science.gov (United States)

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.

Urban eco-efficiency and system dynamics modelling

Energy Technology Data Exchange (ETDEWEB)

Hradil, P., Email: petr.hradil@vtt.fi

2012-06-15

Assessment of urban development is generally based on static models of economic, social or environmental impacts. More advanced dynamic models have been used mostly for prediction of population and employment changes as well as for other macro-economic issues. This feasibility study was arranged to test the potential of system dynamic modelling in assessing eco-efficiency changes during urban development. (orig.)

Endogenous Population Dynamics and Economic Growth with Free Trade between Countries

OpenAIRE

Wei-Bin Zhang

2016-01-01

This paper builds a model to deal with dynamic interdependence between different countries' birth rates, mortality rates, populations, wealth accumulation, and time distributions between working, leisure and children caring. The model shows the role of human capital, technological and preference changes on national differences in birth rates, mortality rates, time distributions, population change, and wealth accumulation. The economic mechanisms of wealth accumulation, production and trade ar...

On the apllication of single specie dynamic population model | Iguda ...

African Journals Online (AJOL)

The Method of mathematical models of Malthus and Verhults were applied on ten years data collected from Magaram Poultry Farm to determine the nature of population growth, population decay or constant ... Keywords: Birth rate, sustainable population, overcrowding, harvesting, independent t-test and one way Anova.

Population dynamics on heterogeneous bacterial substrates

Science.gov (United States)

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.

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

Science.gov (United States)

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.

Mathematical modeling of an urban pigeon population subject to local management strategies.

Science.gov (United States)

Haidar, I; Alvarez, I; Prévot, A C

2017-06-01

This paper addresses the issue of managing urban pigeon population using some possible actions that make it reach a density target with respect to socio-ecological constraints. A mathematical model describing the dynamic of this population is introduced. This model incorporates the effect of some regulatory actions on the dynamic of this population. We use mathematical viability theory, which provides a framework to study compatibility between dynamics and state constraints. The viability study shows when and how it is possible to regulate the pigeon population with respect to the constraints. Copyright © 2017 Elsevier Inc. All rights reserved.

On the stochastic approach to marine population dynamics

Directory of Open Access Journals (Sweden)

Eduardo Ferrandis

2007-03-01

Full Text Available The purpose of this article is to deepen and structure the statistical basis of marine population dynamics. The starting point is the correspondence between the concepts of mortality, survival and lifetime distribution. This is the kernel of the possibilities that survival analysis techniques offer to marine population dynamics. A rigorous definition of survival and mortality based on their properties and their probabilistic versions is briefly presented. Some well established models for lifetime distribution, which generalise the usual simple exponential distribution, might be used with their corresponding survivals and mortalities. A critical review of some published models is also made, including original models proposed in the way opened by Caddy (1991 and Sparholt (1990, which allow for a continuously decreasing natural mortality. Considering these elements, the pure death process dealt with in the literature is used as a theoretical basis for the evolution of a marine cohort. The elaboration of this process is based on Chiang´s study of the probability distribution of the life table (Chiang, 1960 and provides specific structured models for stock evolution as a Markovian process. These models may introduce new ideas in the line of thinking developed by Gudmundsson (1987 and Sampson (1990 in order to model the evolution of a marine cohort by stochastic processes. The suitable approximation of these processes by means of Gaussian processes may allow theoretical and computational multivariate Gaussian analysis to be applied to the probabilistic treatment of fisheries issues. As a consequence, the necessary catch equation appears as a stochastic integral with respect to the mentioned Markovian process of the stock. The solution of this equation is available when the mortalities are proportional, hence the use of the proportional hazards model (Cox, 1959. The assumption of these proportional mortalities leads naturally to the construction of a

Population dynamics in variable environments

CERN Document Server

Tuljapurkar, Shripad

1990-01-01

Demography relates observable facts about individuals to the dynamics of populations. If the dynamics are linear and do not change over time, the classical theory of Lotka (1907) and Leslie (1945) is the central tool of demography. This book addresses the situation when the assumption of constancy is dropped. In many practical situations, a population will display unpredictable variation over time in its vital rates, which must then be described in statistical terms. Most of this book is concerned with the theory of populations which are subject to random temporal changes in their vital rates, although other kinds of variation (e. g. , cyclical) are also dealt with. The central questions are: how does temporal variation work its way into a population's future, and how does it affect our interpretation of a population's past. The results here are directed at demographers of humans and at popula­ tion biologists. The uneven mathematical level is dictated by the material, but the book should be accessible to re...

Structured population models in biology and epidemiology

CERN Document Server

Ruan, Shigui

2008-01-01

This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

Sensitivity Analysis for Assessing Effects of Tree Population Dynamics on Soil Bioturbation

Science.gov (United States)

Martin, Y. E.; Johnson, E. A.

2012-12-01

Bioturbation due to tree root throw is thought to be an important process in soil production and soil mixing. Despite progress in our understanding of root throw processes, the tree population dynamics affecting the occurrence and timing of root throw events remain much less well explained. Unfortunately, research about forest dynamics is not always undertaken from the perspective of those interested in tree death, tree topple and associated root throw. As a result, the necessary field data about tree population dynamics is often unavailable for many locations. The acquisition of such data would allow for improved interpretation of root throw observations and for incorporation within numerical models of tree root throw occurrence. The present study uses our earlier tree population dynamics model calibrated for subalpine forests in the Canadian Rockies to test the sensitivity of forest parameters within the model that determine tree death, tree topple, root throw and soil bioturbation. Crown wildfire disturbance is the primary driver of tree population dynamics, with wind throw being mainly of local importance. The recruitment and mortality of trees during multiple generations of forest determine the number of live trees on the landscape at any given time. Tree death may occur due to competition/thinning of trees between wildfire events or as a result of the wildfire itself. Unless trees die due to sudden wind throw events (as mentioned above, this is only of local significance in our study area), they remain standing for some time period after tree death and before tree topple; these trees are referred to as standing dead trees. The duration of this time window and several other factors influence if a tree breaks at its base or upheaves a relatively intact root plate with attached sediment. Our field research has also suggested that a minimum dbh is required before a root plate is large enough to upheave notable amounts of sediment. Modelling results in this study

The population dynamical implications of male-biased parasitism in different mating systems.

Directory of Open Access Journals (Sweden)

Martin R Miller

2007-07-01

Full Text Available Although there is growing evidence that males tend to suffer higher levels of parasitism than females, the implications of this for the population dynamics of the host population are not yet understood. Here we build on an established 'two-sex' model and investigate how increased susceptibility to infection in males affects the dynamics, under different mating systems. We investigate the effect of pathogenic disease at different case mortalities, under both monogamous and polygynous mating systems. If the case mortality is low, then male-biased parasitism appears similar to unbiased parasitism in terms of its effect on the population dynamics. At higher case mortalities, we identified significant differences between male-biased and unbiased parasitism. A host population may therefore be differentially affected by male-biased and unbiased parasitism. The dynamical outcome is likely to depend on a complex interaction between the host's mating system and demography, and the parasite virulence.

Population dynamical responses to climate change

DEFF Research Database (Denmark)

Forchhammer, Mads; Schmidt, Niels Martin; Høye, Toke Thomas

2008-01-01

approaches, we analyse concurrently the influence of climatic variability and trophic interactions on the temporal population dynamics of species in the terrestrial vertebrate community at Zackenberg. We describe and contrast the population dynamics of three predator species (arctic fox Alopex lagopus, stoat...... of arctic fox were not significantly related to changes in lemming abundance, both the stoat and the breeding of long-tailed skua were mainly related to lemming dynamics. The predator-prey system at Zackenberg differentiates from previously described systems in high-arctic Greenland, which, we suggest...

Models of Eucalypt phenology predict bat population flux.

Science.gov (United States)

Giles, John R; Plowright, Raina K; Eby, Peggy; Peel, Alison J; McCallum, Hamish

2016-10-01

Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86-93% accuracy. Negative binomial models explained 43-53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology

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

Science.gov (United States)

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

A dynamic simulation model of land-use, population, and rural livelihoods in the central Rift Valley of Ethiopia

OpenAIRE

Garedew, Efrem; Sandewall, Mats; Söderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years a...

Impact of external sources of infection on the dynamics of bovine tuberculosis in modelled badger populations

Directory of Open Access Journals (Sweden)

Hardstaff Joanne L

2012-06-01

Full Text Available Abstract Background The persistence of bovine TB (bTB in various countries throughout the world is enhanced by the existence of wildlife hosts for the infection. In Britain and Ireland, the principal wildlife host for bTB is the badger (Meles meles. The objective of our study was to examine the dynamics of bTB in badgers in relation to both badger-derived infection from within the population and externally-derived, trickle-type, infection, such as could occur from other species or environmental sources, using a spatial stochastic simulation model. Results The presence of external sources of infection can increase mean prevalence and reduce the threshold group size for disease persistence. Above the threshold equilibrium group size of 6–8 individuals predicted by the model for bTB persistence in badgers based on internal infection alone, external sources of infection have relatively little impact on the persistence or level of disease. However, within a critical range of group sizes just below this threshold level, external infection becomes much more important in determining disease dynamics. Within this critical range, external infection increases the ratio of intra- to inter-group infections due to the greater probability of external infections entering fully-susceptible groups. The effect is to enable bTB persistence and increase bTB prevalence in badger populations which would not be able to maintain bTB based on internal infection alone. Conclusions External sources of bTB infection can contribute to the persistence of bTB in badger populations. In high-density badger populations, internal badger-derived infections occur at a sufficient rate that the additional effect of external sources in exacerbating disease is minimal. However, in lower-density populations, external sources of infection are much more important in enhancing bTB prevalence and persistence. In such circumstances, it is particularly important that control strategies to

Impact of external sources of infection on the dynamics of bovine tuberculosis in modelled badger populations.

Science.gov (United States)

Hardstaff, Joanne L; Bulling, Mark T; Marion, Glenn; Hutchings, Michael R; White, Piran C L

2012-06-27

The persistence of bovine TB (bTB) in various countries throughout the world is enhanced by the existence of wildlife hosts for the infection. In Britain and Ireland, the principal wildlife host for bTB is the badger (Meles meles). The objective of our study was to examine the dynamics of bTB in badgers in relation to both badger-derived infection from within the population and externally-derived, trickle-type, infection, such as could occur from other species or environmental sources, using a spatial stochastic simulation model. The presence of external sources of infection can increase mean prevalence and reduce the threshold group size for disease persistence. Above the threshold equilibrium group size of 6-8 individuals predicted by the model for bTB persistence in badgers based on internal infection alone, external sources of infection have relatively little impact on the persistence or level of disease. However, within a critical range of group sizes just below this threshold level, external infection becomes much more important in determining disease dynamics. Within this critical range, external infection increases the ratio of intra- to inter-group infections due to the greater probability of external infections entering fully-susceptible groups. The effect is to enable bTB persistence and increase bTB prevalence in badger populations which would not be able to maintain bTB based on internal infection alone. External sources of bTB infection can contribute to the persistence of bTB in badger populations. In high-density badger populations, internal badger-derived infections occur at a sufficient rate that the additional effect of external sources in exacerbating disease is minimal. However, in lower-density populations, external sources of infection are much more important in enhancing bTB prevalence and persistence. In such circumstances, it is particularly important that control strategies to reduce bTB in badgers include efforts to minimise such

Linking animal population dynamics to alterations in foraging behaviour

DEFF Research Database (Denmark)

Nabe-Nielsen, Jacob; Sibly, Richard; Tougaard, Jakob

Background/Question/Methods The survival of animal populations is strongly influenced by the individuals’ ability to forage efficiently, yet there are few studies of how populations respond when disturbances cause animals to deviate from their natural foraging behavior. Animals that respond...... that are increasingly exposed to noise from ships, wind turbines, etc. In the present study we investigate how the dynamics of the harbor porpoise population (Phocoena phocoena) in the inner Danish waters is influenced by disturbances using an agent- based simulation model. In the model animal movement, and hence...... the animals’ ability to forage efficiently and to sustain their energy intake, is influenced by noise emitted from wind turbines and ships. The energy levels in turn affect their survival. The fine-scale movements of the simulated animals was governed by a spatial memory, which allowed the model to produce...

Stochastic population dynamics of a montane ground-dwelling squirrel.

Directory of Open Access Journals (Sweden)

Jeffrey A Hostetler

Full Text Available 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.

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

Skeeter Buster: a stochastic, spatially explicit modeling tool for studying Aedes aegypti population replacement and population suppression strategies.

Directory of Open Access Journals (Sweden)

Krisztian Magori

2009-09-01

Full Text Available Dengue is the most important mosquito-borne viral disease affecting humans. The only prevention measure currently available is the control of its vectors, primarily Aedes aegypti. Recent advances in genetic engineering have opened the possibility for a new range of control strategies based on genetically modified mosquitoes. Assessing the potential efficacy of genetic (and conventional strategies requires the availability of modeling tools that accurately describe the dynamics and genetics of Ae. aegypti populations.We describe in this paper a new modeling tool of Ae. aegypti population dynamics and genetics named Skeeter Buster. This model operates at the scale of individual water-filled containers for immature stages and individual properties (houses for adults. The biology of cohorts of mosquitoes is modeled based on the algorithms used in the non-spatial Container Inhabiting Mosquitoes Simulation Model (CIMSiM. Additional features incorporated into Skeeter Buster include stochasticity, spatial structure and detailed population genetics. We observe that the stochastic modeling of individual containers in Skeeter Buster is associated with a strongly reduced temporal variation in stage-specific population densities. We show that heterogeneity in container composition of individual properties has a major impact on spatial heterogeneity in population density between properties. We detail how adult dispersal reduces this spatial heterogeneity. Finally, we present the predicted genetic structure of the population by calculating F(ST values and isolation by distance patterns, and examine the effects of adult dispersal and container movement between properties.We demonstrate that the incorporated stochasticity and level of spatial detail have major impacts on the simulated population dynamics, which could potentially impact predictions in terms of control measures. The capacity to describe population genetics confers the ability to model the outcome

The effect of temperature on Anopheles mosquito population dynamics and the potential for malaria transmission.

Directory of Open Access Journals (Sweden)

Lindsay M Beck-Johnson

Full Text Available The parasites that cause malaria depend on Anopheles mosquitoes for transmission; because of this, mosquito population dynamics are a key determinant of malaria risk. Development and survival rates of both the Anopheles mosquitoes and the Plasmodium parasites that cause malaria depend on temperature, making this a potential driver of mosquito population dynamics and malaria transmission. We developed a temperature-dependent, stage-structured delayed differential equation model to better understand how climate determines risk. Including the full mosquito life cycle in the model reveals that the mosquito population abundance is more sensitive to temperature than previously thought because it is strongly influenced by the dynamics of the juvenile mosquito stages whose vital rates are also temperature-dependent. Additionally, the model predicts a peak in abundance of mosquitoes old enough to vector malaria at more accurate temperatures than previous models. Our results point to the importance of incorporating detailed vector biology into models for predicting the risk for vector borne diseases.

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

Science.gov (United States)

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).

Market Squid Population Dynamics

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains population dynamics data on paralarvae, juvenile and adult market squid collected off California and the US Pacific Northwest. These data were...

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

Science.gov (United States)

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.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

Science.gov (United States)

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.

Fast stochastic algorithm for simulating evolutionary population dynamics

Science.gov (United States)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

feedback between population and evolutionary dynamics determines the fate of social microbial populations.

Directory of Open Access Journals (Sweden)

Alvaro Sanchez

Full Text Available 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

Modeling the impacts of hunting on the population dynamics of red howler monkeys (Alouatta seniculus)

Science.gov (United States)

Wiederholt, Ruscena; Fernandez-Duque, Eduardo; Diefenbach, Duane R.; Rudran, Rasanayagam

2010-01-01

Overexploitation of wildlife populations occurs across the humid tropics and is a significant threat to the long-term survival of large-bodied primates. To investigate the impacts of hunting on primates and ways to mitigate them, we developed a spatially explicit, individual-based model for a landscape that included hunted and un-hunted areas. We used the large-bodied neotropical red howler monkey (Alouatta seniculus) as our case study species because its life history characteristics make it vulnerable to hunting. We modeled the influence of different rates of harvest and proportions of landscape dedicated to un-hunted reserves on population persistence, population size, social dynamics, and hunting yields of red howler monkeys. In most scenarios, the un-hunted populations maintained a constant density regardless of hunting pressure elsewhere, and allowed the overall population to persist. Therefore, the overall population was quite resilient to extinction; only in scenarios without any un-hunted areas did the population go extinct. However, the total and hunted populations did experience large declines over 100 years under moderate and high hunting pressure. In addition, when reserve area decreased, population losses and losses per unit area increased disproportionately. Furthermore, hunting disrupted the social structure of troops. The number of male turnovers and infanticides increased in hunted populations, while birth rates decreased and exacerbated population losses due to hunting. Finally, our results indicated that when more than 55% of the landscape was harvested at high (30%) rates, hunting yields, as measured by kilograms of biomass, were less than those obtained from moderate harvest rates. Additionally, hunting yields, expressed as the number of individuals hunted/year/km2, increased in proximity to un-hunted areas, and suggested that dispersal from un-hunted areas may have contributed to hunting sustainability. These results indicate that un

Boom or bust? A comparative analysis of transient population dynamics in plants

DEFF Research Database (Denmark)

Stott, Iain; Franco, Miguel; Carslake, David

2010-01-01

researchers as further possible effectors of complicated dynamics. Previously published methods of transient analysis have tended to require knowledge of initial population structure. However, this has been overcome by the recent development of the parametric Kreiss bound (which describes how large...... a population must become before reaching its maximum possible transient amplification following a disturbance) and the extension of this and other transient indices to simultaneously describe both amplified and attenuated transient dynamics. We apply the Kreiss bound and other transient indices to a data base...... worrying artefact of basic model parameterization. Synthesis. Transient indices describe how big or how small plant populations can get, en route to long-term stable rates of increase or decline. The patterns we found in the potential for transient dynamics, across many species of plants, suggest...

Integrating stochastic age-structured population dynamics into complex fisheries economic models for management evaluations: the North Sea saithe fishery as a case study

NARCIS (Netherlands)

Simons, S.L.; Bartelings, H.; Hamon, K.G.; Kempf, A.J.; Doring, R.; Temming, A.

2014-01-01

There is growing interest in bioeconomic models as tools for understanding pathways of fishery behaviour in order to assess the impact of alternative policies on natural resources. A model system is presented that combines stochastic age-structured population dynamics with complex fisheries

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Ability of matrix models to explain the past and predict the future of plant populations.

Science.gov (United States)

McEachern, Kathryn; Crone, Elizabeth E.; Ellis, Martha M.; Morris, William F.; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlen, Johan; Kaye, Thomas N.; Knight, Tiffany M.; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer I.; Doak, Daniel F.; Ganesan, Rengaian; Thorpe, Andrea S.; Menges, Eric S.

2013-01-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Ability of matrix models to explain the past and predict the future of plant populations.

Science.gov (United States)

Crone, Elizabeth E; Ellis, Martha M; Morris, William F; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlén, Johan; Kaye, Thomas N; Knight, Tiffany M; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer L; Doak, Daniel F; Ganesan, Rengaian; McEachern, Kathyrn; Thorpe, Andrea S; Menges, Eric S

2013-10-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models. © 2013 Society for Conservation Biology.

Interacting trophic forcing and the population dynamics of herring

DEFF Research Database (Denmark)

Lindegren, Martin; Ostman, Orjan; Gardmark, Anna

2011-01-01

-up nor top-down, but rather through multiple external and internal drivers. While in many studies single drivers have been identified, potential synergies of multiple factors, as well as their relative importance in regulating population dynamics of small pelagic fish, is a largely unresolved issue....... Using a statistical, age-structured modeling approach, we demonstrate the relative importance and influence of bottom-up (e.g., climate, zooplankton availability) and top-down (i.e., fishing and predation) factors on the population dynamics of Bothnian Sea herring (Clupea harengus) throughout its life...... cycle. Our results indicate significant bottom-up effects of zooplankton and interspecific competition from sprat (Sprattus sprattus), particularly on younger age classes of herring. Although top-down forcing through fishing and predation by grey seals (Halichoerus grypus) and Atlantic cod (Gadus morhua...

Towards a novel model for studying the nutritional stage dynamics of the Colombian population by age and socioeconomic status.

Science.gov (United States)

Meisel, Jose D; Sarmiento, Olga L; Olaya, Camilo; Lemoine, Pablo D; Valdivia, Juan A; Zarama, Roberto

2018-01-01

Low-and middle-income countries (LMICs) are experiencing a nutritional transition in which the burden of obesity tends to shift towards the lower-socioeconomic status (SES) group. We propose a system dynamics (SD) model for assessing the nutritional stage dynamics of the Colombian urban population by age and SES projected to 2030. This SD model captures the ageing population according to body mass index (BMI) categories and SES. In this model, the transference rates (TRs) between BMI categories by age and SES are estimated using a heuristic based on data obtained from national surveys. The simulation results show that the Colombian population, particularly those aged 20 to 39 years with a lower SES, is moving towards the overweight and obese categories. The TRs for overweight and obese categories in the lower SES group (the mean TR from not overweight to overweight = 0.0215 (per year) and mean TR from overweight to obese = 0.0098 (per year)) are increasing more rapidly than the those in the middle (the mean TR from not overweight to overweight = 0.0162 (per year) and mean TR from overweight to obese = 0.0065 (per year)) and higher SES groups (the mean TR from not overweight to overweight = 0.0166 and mean TR from overweight to obese = 0.0054 (per year)). Additionally, from 2005 to 2010, individuals aged 20 to 39 years had the highest TRs towards the overweight and obese categories (from 0.026 to 0.036 per year and from 0.0064 to 0.012 per year, respectively). The TRs also indicated that children aged 0 to 14 years are moving from the obese to overweight and from the overweight to not overweight categories. These TRs show that the Colombian population is experiencing an SES-related nutritional transition that is affecting the lower SES population. The proposed model could be implemented to assess the nutritional transitions experienced in other LMICs.

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

Science.gov (United States)

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.

Developing population models with data from marked individuals

Science.gov (United States)

Hae Yeong Ryu,; Kevin T. Shoemaker,; Eva Kneip,; Anna Pidgeon,; Patricia Heglund,; Brooke Bateman,; Thogmartin, Wayne E.; Reşit Akçakaya,

2016-01-01

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

Science.gov (United States)

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

2018-03-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

Science.gov (United States)

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

2018-01-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

Model for Measuring the Entrepreneurship of the Population

OpenAIRE

Drejeris, Rolandas; Beinoraitė, Šarūnė

2014-01-01

Population entrepreneurship is an important factor in the progress of economic development. This paper proposes a model of entrepreneurship measurement for comparing the level of entrepreneurship. The model consists of two main components, including criteria for the selection and determination of entrepreneurship by adapting the multi­criteria evaluation method TOPSIS. The most important criteria for identifying entrepreneurship cover the dynamics of the unemployment rate, the population of p...

Network evolution induced by the dynamical rules of two populations

International Nuclear Information System (INIS)

Platini, Thierry; Zia, R K P

2010-01-01

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 (N a and N b ) and preferred degree (κ a and κ b 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 (k bb ) and (k ab ) presents three time regimes and a non-monotonic behavior well captured by our theory. Surprisingly, when the population sizes are equal N a = N b , the ratio of the restricted degree θ 0 = (k ab )/(k bb ) appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t 1 = κ b ) the total number of links presents a linear evolution, where the two populations are indistinguishable and where θ 0 = 1. Interestingly, in the intermediate time regime (defined for t 1 2 ∝κ a and for which θ 0 = 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 θ 0 = 3

Modeling of Nonlinear Dynamics and Synchronized Oscillations of Microbial Populations, Carbon and Oxygen Concentrations, Induced by Root Exudation in the Rhizosphere

Science.gov (United States)

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

2012-12-01

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

Consequences of population models on the dynamics of food chains.

NARCIS (Netherlands)

Kooi, B.W.; Boer, M.P.; Kooijman, S.A.L.M.

1998-01-01

A class of bioenergetic ecological models is studied for the dynamics of food chains with a nutrient at the base. A constant influx rate of the nutrient and a constant efflux rate for all trophic levels is assumed. Starting point is a simple model where prey is converted into predator with a fixed

Impact of climate change on fish population dynamics in the baltic sea: a dynamical downscaling investigation

DEFF Research Database (Denmark)

Mackenzie, Brian R; Meier, H E Markus; Lindegren, Martin

2012-01-01

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics...... and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated...... to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass...

The demography of climate-driven and density-regulated population dynamics in a perennial plant

DEFF Research Database (Denmark)

Dahlgren, Johan; Bengstsson, Karin; Ehrlén, Johan

2016-01-01

Identifying the internal and external drivers of population dynamics is a key objective in ecology, currently accentuated by the need to forecast the effects of climate change on species distributions and abundances. The interplay between environmental and density effects is one particularly...... important aspect of such forecasts. We examined the simultaneous impact of climate and intraspecific density on vital rates of the dwarf shrub Fumana procumbens over 20 yr, using generalized additive mixed models. We then analyzed effects on population dynamics using integral projection models...... to be driven solely by the environment can overestimate extinction risks if there is density dependence. We conclude that density regulation can dampen effects of climate change on Fumana population size, and discuss the need to quantify density dependence in predictions of population responses...

Periodic solutions of nonautonomous differential systems modeling obesity population

International Nuclear Information System (INIS)

Arenas, Abraham J.; Gonzalez-Parra, Gilberto; Jodar, Lucas

2009-01-01

In this paper we study the periodic behaviour of the solutions of a nonautonomous model for obesity population. The mathematical model represented by a nonautonomous system of nonlinear ordinary differential equations is used to model the dynamics of obese populations. Numerical simulations suggest periodic behaviour of subpopulations solutions. Sufficient conditions which guarantee the existence of a periodic positive solution are obtained using a continuation theorem based on coincidence degree theory.

Periodic solutions of nonautonomous differential systems modeling obesity population

Energy Technology Data Exchange (ETDEWEB)

Arenas, Abraham J. [Departamento de Matematicas y Estadistica, Universidad de Cordoba Monteria (Colombia)], E-mail: aarenas@sinu.unicordoba.edu.co; Gonzalez-Parra, Gilberto [Departamento de Calculo, Universidad de los Andes, Merida (Venezuela, Bolivarian Republic of)], E-mail: gcarlos@ula.ve; Jodar, Lucas [Instituto de Matematica Multidisciplinar, Universidad Politecnica de Valencia Edificio 8G, 2o, 46022 Valencia (Spain)], E-mail: ljodar@imm.upv.es

2009-10-30

In this paper we study the periodic behaviour of the solutions of a nonautonomous model for obesity population. The mathematical model represented by a nonautonomous system of nonlinear ordinary differential equations is used to model the dynamics of obese populations. Numerical simulations suggest periodic behaviour of subpopulations solutions. Sufficient conditions which guarantee the existence of a periodic positive solution are obtained using a continuation theorem based on coincidence degree theory.

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

Science.gov (United States)

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.

Benchmarking novel approaches for modelling species range dynamics.

Science.gov (United States)

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

Population dynamics of three songbird species in a nestbox population in Central Europe show effects of density, climate and competitive interactions

NARCIS (Netherlands)

Smallegange, I.M.; van der Meer, J.; Fiedler, W.

2011-01-01

Unravelling the contributions of density-dependent and density-independent factors in determining species population dynamics is a challenge, especially if the two factors interact. One approach is to apply stochastic population models to long-term data, yet few studies have included interactions

The demographic drivers of local population dynamics in two rare migratory birds.

Science.gov (United States)

Schaub, Michael; Reichlin, Thomas S; Abadi, Fitsum; Kéry, Marc; Jenni, Lukas; Arlettaz, Raphaël

2012-01-01

The exchange of individuals among populations can have strong effects on the dynamics and persistence of a given population. Yet, estimation of immigration rates remains one of the greatest challenges for animal demographers. Little empirical knowledge exists about the effects of immigration on population dynamics. New integrated population models fitted using Bayesian methods enable simultaneous estimation of fecundity, survival and immigration, as well as the growth rate of a population of interest. We applied this novel analytical framework to the demography of two populations of long-distance migratory birds, hoopoe Upupa epops and wryneck Jynx torquilla, in a study area in south-western Switzerland. During 2002-2010, the hoopoe population increased annually by 11%, while the wryneck population remained fairly stable. Apparent juvenile and adult survival probability was nearly identical in both species, but fecundity and immigration were slightly higher in the hoopoe. Hoopoe population growth rate was strongly correlated with juvenile survival, fecundity and immigration, while that of wrynecks strongly correlated only with immigration. This indicates that demographic components impacting the arrival of new individuals into the populations were more important for their dynamics than demographic components affecting the loss of individuals. The finding that immigration plays a crucial role in the population growth rates of these two rare species emphasizes the need for a broad rather than local perspective for population studies, and the development of wide-scale conservation actions.

Chaos and order in stateless societies: Intercommunity exchange as a factor impacting the population dynamical patterns

International Nuclear Information System (INIS)

Medvinsky, Alexander B.; Rusakov, Alexey V.

2011-01-01

Highlights: → We model community dynamics in stateless societies. → Intercommunity barter is shown to be a factor impacting the societies dynamics. → Increase in the human population growth rate can lead to appearance of chaos. → Secular and millennial cycles are found to arise as a result of the barter. - Abstract: The once abstract notions of dynamical chaos now appear naturally in various systems [Kaplan D, Glass L. Understanding nonlinear dynamics. New York: Springer; 1995]. As a result, future trajectories of the systems may be difficult to predict. In this paper, we demonstrate the appearance of chaotic dynamics in model human communities, which consist of producers of agricultural product and producers of agricultural equipment. In the case of a solitary community, the horizon of predictability of the human population dynamics is shown to be dependent on both intrinsic instability of the dynamics and the chaotic attractor sizes. Since a separate community is usually a part of a larger commonality, we study the dynamics of social systems consisting of two interacting communities. We show that intercommunity barter can lead to stabilization of the dynamics in one of the communities, which implies persistence of stable equilibrium under changes of the maximum value of the human population growth rate. However, in the neighboring community, the equilibrium turns into a stable limit cycle as the maximum value of the human population growth rate increases. Following an increase in the maximum value of the human population growth rate leads to period-doubling bifurcations resulting in chaotic dynamics. The horizon of predictability of the chaotic oscillations is found to be limited by 5 years. We demonstrate that the intercommunity interaction can lead to the appearance of long-period harmonics in the chaotic time series. The period of the harmonics is of order 100 and 1000 years. Hence the long-period changes in the population size may be considered as an

Chaos and order in stateless societies: Intercommunity exchange as a factor impacting the population dynamical patterns

Energy Technology Data Exchange (ETDEWEB)

Medvinsky, Alexander B., E-mail: medvinsky@iteb.ru [Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino 142290, Moscow Region (Russian Federation); Rusakov, Alexey V. [Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino 142290, Moscow Region (Russian Federation)

2011-06-15

Highlights: > We model community dynamics in stateless societies. > Intercommunity barter is shown to be a factor impacting the societies dynamics. > Increase in the human population growth rate can lead to appearance of chaos. > Secular and millennial cycles are found to arise as a result of the barter. - Abstract: The once abstract notions of dynamical chaos now appear naturally in various systems [Kaplan D, Glass L. Understanding nonlinear dynamics. New York: Springer; 1995]. As a result, future trajectories of the systems may be difficult to predict. In this paper, we demonstrate the appearance of chaotic dynamics in model human communities, which consist of producers of agricultural product and producers of agricultural equipment. In the case of a solitary community, the horizon of predictability of the human population dynamics is shown to be dependent on both intrinsic instability of the dynamics and the chaotic attractor sizes. Since a separate community is usually a part of a larger commonality, we study the dynamics of social systems consisting of two interacting communities. We show that intercommunity barter can lead to stabilization of the dynamics in one of the communities, which implies persistence of stable equilibrium under changes of the maximum value of the human population growth rate. However, in the neighboring community, the equilibrium turns into a stable limit cycle as the maximum value of the human population growth rate increases. Following an increase in the maximum value of the human population growth rate leads to period-doubling bifurcations resulting in chaotic dynamics. The horizon of predictability of the chaotic oscillations is found to be limited by 5 years. We demonstrate that the intercommunity interaction can lead to the appearance of long-period harmonics in the chaotic time series. The period of the harmonics is of order 100 and 1000 years. Hence the long-period changes in the population size may be considered as an

JOB DISCRIMINATION AGAINST WOMEN AND ENDOGENOUS POPULATION CHANGE IN A GENERALIZED SOLOW GROWTH MODEL

Directory of Open Access Journals (Sweden)

Wei-Bin ZHANG

2017-06-01

Full Text Available This study examines economic growth and population change with discrimination against women in the labor market within the analytical framework of Solow’s neoclassical growth model. The study models dynamic interactions between wealth accumulation, time distribution between work, children caring, and leisure, population change with endogenous birth and mortality rates with gender discrimination. The production technology and markets are built on Solow’s neoclassical growth model. The basic mechanisms for population changes in the Barro-Becker fertility choice model and the Haavelmo population model are integrated to model the population change. This study also takes account of discrimination against woman in the labor market. We synthesize these dynamic forces in a compact framework by applying Zhang’s utility function. The model properties are studied by simulation. We find equilibrium points and illustrate motion of the dynamic system. We also examine the effects of changes in the discrimination against woman, the propensity to save, woman’s propensity to pursue leisure activities, the propensity to have children, woman’s human capital and man’s emotional involvement in children caring.

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

Science.gov (United States)

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.

General two-species interacting Lotka-Volterra system: Population dynamics and wave propagation

Science.gov (United States)

Zhu, Haoqi; Wang, Mao-Xiang; Lai, Pik-Yin

2018-05-01

The population dynamics of two interacting species modeled by the Lotka-Volterra (LV) model with general parameters that can promote or suppress the other species is studied. It is found that the properties of the two species' isoclines determine the interaction of species, leading to six regimes in the phase diagram of interspecies interaction; i.e., there are six different interspecific relationships described by the LV model. Four regimes allow for nontrivial species coexistence, among which it is found that three of them are stable, namely, weak competition, mutualism, and predator-prey scenarios can lead to win-win coexistence situations. The Lyapunov function for general nontrivial two-species coexistence is also constructed. Furthermore, in the presence of spatial diffusion of the species, the dynamics can lead to steady wavefront propagation and can alter the population map. Propagating wavefront solutions in one dimension are investigated analytically and by numerical solutions. The steady wavefront speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. In addition to the inter- and intraspecific interaction parameters, the intrinsic speed parameters of each species play a decisive role in species populations and wave properties. In some regimes, both species can copropagate with the same wave speeds in a finite range of parameters. Our results are further discussed in the light of possible biological relevance and ecological implications.

Scaling up population dynamic processes in a ladybird–aphid

Czech Academy of Sciences Publication Activity Database

Houdková, Kateřina; Kindlmann, Pavel

2006-01-01

Roč. 48, - (2006), s. 323-332 ISSN 1438-3896 R&D Projects: GA ČR(CZ) GEDIV/06/E013; GA MŠk(CZ) LC06073; GA AV ČR(CZ) IAA6087301; GA ČR(CZ) GD206/03/H034 Keywords : Aphids * Egg window * Ladybirds * Metapopulation * Model * Population dynamics Subject RIV: EH - Ecology, Behaviour Impact factor: 1.534, year: 2006

Location Aggregation of Spatial Population CTMC Models

Directory of Open Access Journals (Sweden)

Luca Bortolussi

2016-10-01

Full Text Available In this paper we focus on spatial Markov population models, describing the stochastic evolution of populations of agents, explicitly modelling their spatial distribution, representing space as a discrete, finite graph. More specifically, we present a heuristic approach to aggregating spatial locations, which is designed to preserve the dynamical behaviour of the model whilst reducing the computational cost of analysis. Our approach combines stochastic approximation ideas (moment closure, linear noise, with computational statistics (spectral clustering to obtain an efficient aggregation, which is experimentally shown to be reasonably accurate on two case studies: an instance of epidemic spreading and a London bike sharing scenario.

A stochastic population model to evaluate Moapa dace (Moapa coriacea) population growth under alternative management scenarios

Science.gov (United States)

Perry, Russell W.; Jones, Edward; Scoppettone, G. Gary

2015-07-14

The primary goal of this research project was to evaluate the response of Moapa dace (Moapa coriacea) to the potential effects of changes in the amount of available habitat due to human influences such as ground water pumping, barriers to movement, and extirpation of Moapa dace from the mainstem Muddy River. To understand how these factors affect Moapa dace populations and to provide a tool to guide recovery actions, we developed a stochastic model to simulate Moapa dace population dynamics. Specifically, we developed an individual based model (IBM) to incorporate the critical components that drive Moapa dace population dynamics. Our model is composed of several interlinked submodels that describe changes in Moapa dace habitat as translated into carrying capacity, the influence of carrying capacity on demographic rates of dace, and the consequent effect on equilibrium population sizes. The model is spatially explicit and represents the stream network as eight discrete stream segments. The model operates at a monthly time step to incorporate seasonally varying reproduction. Growth rates of individuals vary among stream segments, with growth rates increasing along a headwater to mainstem gradient. Movement and survival of individuals are driven by density-dependent relationships that are influenced by the carrying capacity of each stream segment.

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

Science.gov (United States)

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.

Cellular population dynamics control the robustness of the stem cell niche

Directory of Open Access Journals (Sweden)

Adam L. MacLean

2015-11-01

Full Text Available Within populations of cells, fate decisions are controlled by an indeterminate combination of cell-intrinsic and cell-extrinsic factors. In the case of stem cells, the stem cell niche is believed to maintain ‘stemness’ through communication and interactions between the stem cells and one or more other cell-types that contribute to the niche conditions. To investigate the robustness of cell fate decisions in the stem cell hierarchy and the role that the niche plays, we introduce simple mathematical models of stem and progenitor cells, their progeny and their interplay in the niche. These models capture the fundamental processes of proliferation and differentiation and allow us to consider alternative possibilities regarding how niche-mediated signalling feedback regulates the niche dynamics. Generalised stability analysis of these stem cell niche systems enables us to describe the stability properties of each model. We find that although the number of feasible states depends on the model, their probabilities of stability in general do not: stem cell–niche models are stable across a wide range of parameters. We demonstrate that niche-mediated feedback increases the number of stable steady states, and show how distinct cell states have distinct branching characteristics. The ecological feedback and interactions mediated by the stem cell niche thus lend (surprisingly high levels of robustness to the stem and progenitor cell population dynamics. Furthermore, cell–cell interactions are sufficient for populations of stem cells and their progeny to achieve stability and maintain homeostasis. We show that the robustness of the niche – and hence of the stem cell pool in the niche – depends only weakly, if at all, on the complexity of the niche make-up: simple as well as complicated niche systems are capable of supporting robust and stable stem cell dynamics.

Allee effects on population dynamics in continuous (overlapping) case

International Nuclear Information System (INIS)

Merdan, H.; Duman, O.; Akin, O.; Celik, C.

2009-01-01

This paper presents the stability analysis of equilibrium points of a continuous population dynamics with delay under the Allee effect which occurs at low population density. The mathematical results and numerical simulations show the stabilizing role of the Allee effects on the stability of the equilibrium point of this population dynamics.

Model for Measuring the Entrepreneurship of the Population

Directory of Open Access Journals (Sweden)

Šarūnė Beinoraitė

2014-09-01

Full Text Available Population entrepreneurship is an important factor in the progress of economic development. This paper proposes a model of entrepreneurship measurement for comparing the level of entrepreneurship. The model consists of two main components, including criteria for the selection and determination of entrepreneurship by adapting the multi­criteria evaluation method TOPSIS. The most important criteria for identifying entrepreneurship cover the dynamics of the unemployment rate, the population of personal characteristics, geographical location, broadband Internet penetration per 1000 inhabitants, issued business licenses per thousand population, competitiveness, innovation, registered enterprises per thousand population, the promotion of a entrepreneurship program, the average wage level, the number of loans taken for business per thousand population, the number of bankrupt enterprises per thousand population, the level of education, the subscription of newspapers and magazines on business.

Analysis of Population Dynamics in World Economy

OpenAIRE

Martin, Gress

2011-01-01

Population dynamics is an important topic in current world economy. The size and growth of population have an impact on economic growth and development of individual countries and vice versa, economic development influences demographic variables in a country. The aim of the article is to analyze historical development of world population, population stock change and relations between population stock change and economic development.

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

Science.gov (United States)

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

Rapid evolution leads to differential population dynamics and top-down control in resurrected Daphnia populations.

Science.gov (United States)

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.

Random and non-random mating populations: Evolutionary dynamics in meiotic drive.

Science.gov (United States)

Sarkar, Bijan

2016-01-01

Game theoretic tools are utilized to analyze a one-locus continuous selection model of sex-specific meiotic drive by considering nonequivalence of the viabilities of reciprocal heterozygotes that might be noticed at an imprinted locus. The model draws attention to the role of viability selections of different types to examine the stable nature of polymorphic equilibrium. A bridge between population genetics and evolutionary game theory has been built up by applying the concept of the Fundamental Theorem of Natural Selection. In addition to pointing out the influences of male and female segregation ratios on selection, configuration structure reveals some noted results, e.g., Hardy-Weinberg frequencies hold in replicator dynamics, occurrence of faster evolution at the maximized variance fitness, existence of mixed Evolutionarily Stable Strategy (ESS) in asymmetric games, the tending evolution to follow not only a 1:1 sex ratio but also a 1:1 different alleles ratio at particular gene locus. Through construction of replicator dynamics in the group selection framework, our selection model introduces a redefining bases of game theory to incorporate non-random mating where a mating parameter associated with population structure is dependent on the social structure. Also, the model exposes the fact that the number of polymorphic equilibria will depend on the algebraic expression of population structure. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamics of weed populations : spatial pattern formation and implications for control

NARCIS (Netherlands)

Wallinga, J.

1998-01-01

Modelling studies were carried out to analyse spatio-temporal dynamics of annual weed populations and to identify the key factors that determine the long-term herbicide use of weed control programmes. Three different weed control programmes were studied.

In the first weed

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

Science.gov (United States)

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.

Mussel dynamics model: A hydroinformatics tool for analyzing the effects of different stressors on the dynamics of freshwater mussel communities

Science.gov (United States)

Morales, Y.; Weber, L.J.; Mynett, A.E.; Newton, T.J.

2006-01-01

A model for simulating freshwater mussel population dynamics is presented. The model is a hydroinformatics tool that integrates principles from ecology, river hydraulics, fluid mechanics and sediment transport, and applies the individual-based modelling approach for simulating population dynamics. The general model layout, data requirements, and steps of the simulation process are discussed. As an illustration, simulation results from an application in a 10 km reach of the Upper Mississippi River are presented. The model was used to investigate the spatial distribution of mussels and the effects of food competition in native unionid mussel communities, and communities infested by Dreissena polymorpha, the zebra mussel. Simulation results were found to be realistic and coincided with data obtained from the literature. These results indicate that the model can be a useful tool for assessing the potential effects of different stressors on long-term population dynamics, and consequently, may improve the current understanding of cause and effect relationships in freshwater mussel communities. ?? 2006 Elsevier B.V. All rights reserved.

Population dynamics of Greater Scaup breeding on the Yukon-Kuskokwim Delta, Alaska

Science.gov (United States)

Flint, Paul L.; Grand, J. Barry; Fondell, Thomas F.; Morse, Julie A.

2006-01-01

Populations of greater scaup (Aythya marila) remained relatively stable during a period when populations of lesser scaup (A. affinis) have declined from historic levels. To assist in describing these differences in population trends, from 1991 through 2000, we studied the survival, nesting ecology, and productivity of greater scaup on the Yukon-Kuskokwim Delta (Y-K Delta), Alaska, to develop a model of population dynamics. We located nests, radio-marked females for renesting studies, estimated duckling survival, and leg-banded females to examine nest site fidelity and annual survival.

Central-marginal population dynamics in species invasions

Directory of Open Access Journals (Sweden)

Qinfeng eGuo

2014-06-01

Full Text Available The species’ range limits and associated central-marginal (C-M; i.e., from species range center to margin population dynamics continue to draw increasing attention because of their importance for current emerging issues such as biotic invasions and epidemic diseases under global change. Previous studies have mainly focused on species borders and C-M process in natural settings for native species. More recently, growing efforts are devoted to examine the C-M patterns and process for invasive species partly due to their relatively short history, highly dynamic populations, and management implications. Here I examine recent findings and information gaps related to (1 the C-M population dynamics linked to species invasions, and (2 the possible effects of climate change and land use on the C-M patterns and processes. Unlike most native species that are relatively stable (some even having contracting populations or ranges, many invasive species are still spreading fast and form new distribution or abundance centers. Because of the strong nonlinearity of population demographic or vital rates (i.e. birth, death, immigration and emigration across the C-M gradients and the increased complexity of species ranges due to habitat fragmentation, multiple introductions, range-wide C-M comparisons and simulation involving multiple vital rates are needed in the future.

Dynamic population artificial bee colony algorithm for multi-objective optimal power flow

Directory of Open Access Journals (Sweden)

Man Ding

2017-03-01

Full Text Available This paper proposes a novel artificial bee colony algorithm with dynamic population (ABC-DP, which synergizes the idea of extended life-cycle evolving model to balance the exploration and exploitation tradeoff. The proposed ABC-DP is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. ABC-DP is then used for solving the optimal power flow (OPF problem in power systems that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results, which are also compared to nondominated sorting genetic algorithm II (NSGAII and multi-objective ABC (MOABC, are presented to illustrate the effectiveness and robustness of the proposed method.

Biomolecular Modeling in a Process Dynamics and Control Course

Science.gov (United States)

Gray, Jeffrey J.

2006-01-01

I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large­-scale…

The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

Directory of Open Access Journals (Sweden)

Yun Jian

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

On Oscillatory Pattern of Malaria Dynamics in a Population with Temporary Immunity

Directory of Open Access Journals (Sweden)

J. Tumwiine

2007-01-01

Full Text Available We use a model to study the dynamics of malaria in the human and mosquito population to explain the stability patterns of malaria. The model results show that the disease-free equilibrium is globally asymptotically stable and occurs whenever the basic reproduction number, R0 is less than unity. We also note that when R0>1, the disease-free equilibrium is unstable and the endemic equilibrium is stable. Numerical simulations show that recoveries and temporary immunity keep the populations at oscillation patterns and eventually converge to a steady state.

Population Dynamics of Patients with Bacterial Resistance in Hospital Environment

Directory of Open Access Journals (Sweden)

Leilei Qu

2016-01-01

Full Text Available During the past decades, the increase of antibiotic resistance has become a major concern worldwide. The researchers found that superbugs with new type of resistance genes (NDM-1 have two aspects of transmission characteristics; the first is that the antibiotic resistance genes can horizontally transfer among bacteria, and the other is that the superbugs can spread between humans through direct contact. Based on these two transmission mechanisms, we study the dynamics of population in hospital environment where superbugs exist. In this paper, we build three mathematic models to illustrate the dynamics of patients with bacterial resistance in hospital environment. The models are analyzed using stability theory of differential equations. Positive equilibrium points of the system are investigated and their stability analysis is carried out. Moreover, the numerical simulation of the proposed model is also performed which supports the theoretical findings.

Nonlinear Relaxation in Population Dynamics

Science.gov (United States)

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.

Fortune favours the brave: Movement responses shape demographic dynamics in strongly competing populations.

Science.gov (United States)

Potts, Jonathan R; Petrovskii, Sergei V

2017-05-07

Animal movement is a key mechanism for shaping population dynamics. The effect of interactions between competing animals on a population's survival has been studied for many decades. However, interactions also affect an animal's subsequent movement decisions. Despite this, the indirect effect of these decisions on animal survival is much less well-understood. Here, we incorporate movement responses to foreign animals into a model of two competing populations, where inter-specific competition is greater than intra-specific competition. When movement is diffusive, the travelling wave moves from the stronger population to the weaker. However, by incorporating behaviourally induced directed movement towards the stronger population, the weaker one can slow the travelling wave down, even reversing its direction. Hence movement responses can switch the predictions of traditional mechanistic models. Furthermore, when environmental heterogeneity is combined with aggressive movement strategies, it is possible for spatially segregated co-existence to emerge. In this situation, the spatial patterns of the competing populations have the unusual feature that they are slightly out-of-phase with the environmental patterns. Finally, incorporating dynamic movement responses can also enable stable co-existence in a homogeneous environment, giving a new mechanism for spatially segregated co-existence. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamics of a population of oscillatory and excitable elements.

Science.gov (United States)

O'Keeffe, Kevin P; Strogatz, Steven H

2016-06-01

We analyze a variant of a model proposed by Kuramoto, Shinomoto, and Sakaguchi for a large population of coupled oscillatory and excitable elements. Using the Ott-Antonsen ansatz, we reduce the behavior of the population to a two-dimensional dynamical system with three parameters. We present the stability diagram and calculate several of its bifurcation curves analytically, for both excitatory and inhibitory coupling. Our main result is that when the coupling function is broad, the system can display bistability between steady states of constant high and low activity, whereas when the coupling function is narrow and inhibitory, one of the states in the bistable regime can show persistent pulsations in activity.

Generalized Models from Beta(p, 2) Densities with Strong Allee Effect: Dynamical Approach

OpenAIRE

Aleixo, Sandra M.; Rocha, J. Leonel

2012-01-01

A dynamical approach to study the behaviour of generalized populational growth models from Beta(p, 2) densities, with strong Allee effect, is presented. The dynamical analysis of the respective unimodal maps is performed using symbolic dynamics techniques. The complexity of the correspondent discrete dynamical systems is measured in terms of topological entropy. Different populational dynamics regimes are obtained when the intrinsic growth rates are modified: extinction, bistability, chaotic ...

Multiple bifurcations and periodic 'bubbling' in a delay population model

International Nuclear Information System (INIS)

Peng Mingshu

2005-01-01

In this paper, the flip bifurcation and periodic doubling bifurcations of a discrete population model without delay influence is firstly studied and the phenomenon of Feigenbaum's cascade of periodic doublings is also observed. Secondly, we explored the Neimark-Sacker bifurcation in the delay population model (two-dimension discrete dynamical systems) and the unique stable closed invariant curve which bifurcates from the nontrivial fixed point. Finally, a computer-assisted study for the delay population model is also delved into. Our computer simulation shows that the introduction of delay effect in a nonlinear difference equation derived from the logistic map leads to much richer dynamic behavior, such as stable node → stable focus → an lower-dimensional closed invariant curve (quasi-periodic solution, limit cycle) or/and stable periodic solutions → chaotic attractor by cascading bubbles (the combination of potential period doubling and reverse period-doubling) and the sudden change between two different attractors, etc

Disentangling the effects of climate, density dependence, and harvest on an iconic large herbivore's population dynamics

DEFF Research Database (Denmark)

Koons, David; Colchero, Fernando; Hersey, Kent

2015-01-01

Understanding the relative effects of climate, harvest, and density dependence on population dynamics is critical for guiding sound population management, especially for ungulates in arid and semi-arid environments experiencing climate change. To address these issues for bison in southern Utah, we...... than precipitation and other temperature-related variables (model weight > 3 times more than that for other climate variables). Although we hypothesized that harvest is the primary driving force of bison population dynamics in southern Utah, our elasticity analysis indicated that changes in early...... spring temperature could have a greater ‘relative effect’ on equilibrium abundance than either harvest or the strength of density dependence. Our findings highlight the utility of incorporating elasticity analyses into state-space population models, and the need to include climatic processes in wildlife...

Stochastic models for structured populations scaling limits and long time behavior

CERN Document Server

Meleard, Sylvie

2015-01-01

In this contribution, several probabilistic tools to study population dynamics are developed. The focus is on scaling limits of qualitatively different stochastic individual based models and the long time behavior of some classes of limiting processes. Structured population dynamics are modeled by measure-valued processes describing the individual behaviors and taking into account the demographic and mutational parameters, and possible interactions between individuals. Many quantitative parameters appear in these models and several relevant normalizations are considered, leading  to infinite-dimensional deterministic or stochastic large-population approximations. Biologically relevant questions are considered, such as extinction criteria, the effect of large birth events, the impact of  environmental catastrophes, the mutation-selection trade-off, recovery criteria in parasite infections, genealogical properties of a sample of individuals. These notes originated from a lecture series on Structured P...

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

Science.gov (United States)

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.

A Role for M-Matrices in Modelling Population Growth

Science.gov (United States)

James, Glyn; Rumchev, Ventsi

2006-01-01

Adopting a discrete-time cohort-type model to represent the dynamics of a population, the problem of achieving a desired total size of the population under a balanced growth (contraction) and the problem of maintaining the desired size, once achieved, are studied. Properties of positive-time systems and M-matrices are used to develop the results,…

Modeling Exponential Population Growth

Science.gov (United States)

McCormick, Bonnie

2009-01-01

The concept of population growth patterns is a key component of understanding evolution by natural selection and population dynamics in ecosystems. The National Science Education Standards (NSES) include standards related to population growth in sections on biological evolution, interdependence of organisms, and science in personal and social…

Cell mass and cell cycle dynamics of an asynchronous budding yeast population

DEFF Research Database (Denmark)

Lencastre Fernandes, Rita; Carlquist, Magnus; Lundin, Luisa

2013-01-01

of model predictions for cell property distributions against experimental data is scarce. This study focuses on the experimental and mathematical description of the dynamics of cell size and cell cycle position distributions, of a population of Saccharomyces cerevisiae, in response to the substrate...

Dynamic complexities in a seasonal prevention epidemic model with birth pulses

International Nuclear Information System (INIS)

Gao Shujing; Chen Lansun; Sun Lihua

2005-01-01

In most of population dynamics, increases in population due to birth are assumed to be time-dependent, but many species reproduce only during a single period of the year. In this paper, we propose an epidemic model with density-dependent birth pulses and seasonal prevention. Using the discrete dynamical system determined by stroboscopic map, we obtain the local or global stability, numerical simulation shows there is a characteristic sequence of bifurcations, leading to chaotic dynamics, which implies that the dynamical behaviors of the epidemic model with birth pulses and seasonal prevention are very complex, including small amplitude oscillations, large-amplitude multi-annual cycles and chaos. This suggests that birth pulse, in effect, provides a natural period or cyclicity that may lead a period-doubling route to chaos

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

Science.gov (United States)

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

Seven challenges in modeling pathogen dynamics within-host and across scales

OpenAIRE

Julia R. Gog; Lorenzo Pellis; James L.N. Wood; Angela R. McLean; Nimalan Arinaminpathy; James O. Lloyd-Smith

2015-01-01

© 2014 The Authors. The population dynamics of infectious disease is a mature field in terms of theory and to some extent, application. However for microparasites, the theory and application of models of the dynamics within a single infected host is still an open field. Further, connecting across the scales - from cellular to host level, to population level - has potential to vastly improve our understanding of pathogen dynamics and evolution. Here, we highlight seven challenges in the follow...

Uncoupling the effects of seed predation and seed dispersal by granivorous ants on plant population dynamics.

Directory of Open Access Journals (Sweden)

Xavier Arnan

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

Mean-field dynamics of a population of stochastic map neurons

Science.gov (United States)

Franović, Igor; Maslennikov, Oleg V.; Bačić, Iva; Nekorkin, Vladimir I.

2017-07-01

We analyze the emergent regimes and the stimulus-response relationship of a population of noisy map neurons by means of a mean-field model, derived within the framework of cumulant approach complemented by the Gaussian closure hypothesis. It is demonstrated that the mean-field model can qualitatively account for stability and bifurcations of the exact system, capturing all the generic forms of collective behavior, including macroscopic excitability, subthreshold oscillations, periodic or chaotic spiking, and chaotic bursting dynamics. Apart from qualitative analogies, we find a substantial quantitative agreement between the exact and the approximate system, as reflected in matching of the parameter domains admitting the different dynamical regimes, as well as the characteristic properties of the associated time series. The effective model is further shown to reproduce with sufficient accuracy the phase response curves of the exact system and the assembly's response to external stimulation of finite amplitude and duration.

Dynamical community structure of populations evolving on genotype networks

International Nuclear Information System (INIS)

Capitán, José A.; Aguirre, Jacobo; Manrubia, Susanna

2015-01-01

Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics

Outbreak and Extinction Dynamics in a Stochastic Ebola Model

Science.gov (United States)

Nieddu, Garrett; Bianco, Simone; Billings, Lora; Forgoston, Eric; Kaufman, James

A zoonotic disease is a disease that can be passed between animals and humans. In many cases zoonotic diseases can persist in the animal population even if there are no infections in the human population. In this case we call the infected animal population the reservoir for the disease. Ebola virus disease (EVD) and SARS are both notable examples of such diseases. There is little work devoted to understanding stochastic disease extinction and reintroduction in the presence of a reservoir. Here we build a stochastic model for EVD and explicitly consider the presence of an animal reservoir. Using a master equation approach and a WKB ansatz, we determine the associated Hamiltonian of the system. Hamilton's equations are then used to numerically compute the 12-dimensional optimal path to extinction, which is then used to estimate mean extinction times. We also numerically investigate the behavior of the model for dynamic population size. Our results provide an improved understanding of outbreak and extinction dynamics in diseases like EVD.

Discrete time population dynamics of a two-stage species with recruitment and capture

International Nuclear Information System (INIS)

Ladino, Lilia M.; Mammana, Cristiana; Michetti, Elisabetta; Valverde, Jose C.

2016-01-01

This work models and analyzes the dynamics of a two-stage species with recruitment and capture factors. It arises from the discretization of a previous model developed by Ladino and Valverde (2013), which represents a progress in the knowledge of the dynamics of exploited populations. Although the methods used here are related to the study of discrete-time systems and are different from those related to continuous version, the results are similar in both the discrete and the continuous case what confirm the skill in the selection of the factors to design the model. Unlike for the continuous-time case, for the discrete-time one some (non-negative) parametric constraints are derived from the biological significance of the model and become fundamental for the proofs of such results. Finally, numerical simulations show different scenarios of dynamics related to the analytical results which confirm the validity of the model.

Extinction transition in stochastic population dynamics in a random, convective environment

International Nuclear Information System (INIS)

Juhász, Róbert

2013-01-01

Motivated by modeling the dynamics of a population living in a flowing medium where the environmental factors are random in space, we have studied an asymmetric variant of the one-dimensional contact process, where the quenched random reproduction rates are systematically greater in one direction than in the opposite one. The spatial disorder turns out to be a relevant perturbation but, according to results of Monte Carlo simulations, the behavior of the model at the extinction transition is different from the (infinite-randomness) critical behavior of the disordered symmetric contact process. Depending on the strength a of the asymmetry, the critical population drifts either with a finite velocity or with an asymptotically vanishing velocity as x(t) ∼ t μ(a) , where μ(a) < 1. Dynamical quantities are non-self-averaging at the extinction transition; the survival probability, for instance, shows multiscaling, i.e. it is characterized by a broad spectrum of effective exponents. For a sufficiently weak asymmetry, a Griffiths phase appears below the extinction transition, where the survival probability decays as a non-universal power of the time while, above the transition, another extended phase emerges, where the front of the population advances anomalously with a diffusion exponent continuously varying with the control parameter. (paper)

Population dynamics of minimally cognitive individuals. Part 2: Dynamics of time-dependent knowledge

Energy Technology Data Exchange (ETDEWEB)

Schmieder, R.W.

1995-07-01

The dynamical principle for a population of interacting individuals with mutual pairwise knowledge, presented by the author in a previous paper for the case of constant knowledge, is extended to include the possibility that the knowledge is time-dependent. Several mechanisms are presented by which the mutual knowledge, represented by a matrix K, can be altered, leading to dynamical equations for K(t). The author presents various examples of the transient and long time asymptotic behavior of K(t) for populations of relatively isolated individuals interacting infrequently in local binary collisions. Among the effects observed in the numerical experiments are knowledge diffusion, learning transients, and fluctuating equilibria. This approach will be most appropriate to small populations of complex individuals such as simple animals, robots, computer networks, agent-mediated traffic, simple ecosystems, and games. Evidence of metastable states and intermittent switching leads them to envision a spectroscopy associated with such transitions that is independent of the specific physical individuals and the population. Such spectra may serve as good lumped descriptors of the collective emergent behavior of large classes of populations in which mutual knowledge is an important part of the dynamics.

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

Science.gov (United States)

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Population dynamics of active and total ciliate populations in arable soil amended with wheat

DEFF Research Database (Denmark)

Ekelund, F.; Frederiksen, Helle B.; Ronn, R.

2002-01-01

of the population may be encysted. The factors governing the dynamics of active and encysted cells in the soil are not well understood. Our objective was to determine the dynamics of active and encysted populations of ciliates during the decomposition of freshly added organic material. We monitored, in soil...... microcosms, the active and total populations of ciliates, their potential prey (bacteria and small protozoa), their potential competitors (amoebae, flagellates, and nematodes), and their potential predators (nematodes). We sampled with short time intervals (2 to 6 days) and generated a data set, suitable...

Evolutionary game dynamics in a growing structured population

Energy Technology Data Exchange (ETDEWEB)

Poncela, Julia; Gomez-Gardenes, Jesus; Moreno, Yamir [Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, E-50009 Zaragoza (Spain); Traulsen, Arne [Emmy-Noether Group for Evolutionary Dynamics, Department of Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, August-Thienemann-Strasse 2, 24306 Ploen (Germany)], E-mail: traulsen@evolbio.mpg.de

2009-08-15

We discuss a model for evolutionary game dynamics in a growing, network-structured population. In our model, new players can either make connections to random preexisting players or preferentially attach to those that have been successful in the past. The latter depends on the dynamics of strategies in the game, which we implement following the so-called Fermi rule such that the limits of weak and strong strategy selection can be explored. Our framework allows to address general evolutionary games. With only two parameters describing the preferential attachment and the intensity of selection, we describe a wide range of network structures and evolutionary scenarios. Our results show that even for moderate payoff preferential attachment, over represented hubs arise. Interestingly, we find that while the networks are growing, high levels of cooperation are attained, but the same network structure does not promote cooperation as a static network. Therefore, the mechanism of payoff preferential attachment is different to those usually invoked to explain the promotion of cooperation in static, already-grown networks.

Evolutionary game dynamics in a growing structured population

International Nuclear Information System (INIS)

Poncela, Julia; Gomez-Gardenes, Jesus; Moreno, Yamir; Traulsen, Arne

2009-01-01

We discuss a model for evolutionary game dynamics in a growing, network-structured population. In our model, new players can either make connections to random preexisting players or preferentially attach to those that have been successful in the past. The latter depends on the dynamics of strategies in the game, which we implement following the so-called Fermi rule such that the limits of weak and strong strategy selection can be explored. Our framework allows to address general evolutionary games. With only two parameters describing the preferential attachment and the intensity of selection, we describe a wide range of network structures and evolutionary scenarios. Our results show that even for moderate payoff preferential attachment, over represented hubs arise. Interestingly, we find that while the networks are growing, high levels of cooperation are attained, but the same network structure does not promote cooperation as a static network. Therefore, the mechanism of payoff preferential attachment is different to those usually invoked to explain the promotion of cooperation in static, already-grown networks.

DYNAMICS OF Cercospora zeina POPULATIONS IN MAIZE-BASED ...

African Journals Online (AJOL)

ACSS

DYNAMICS OFCercospora zeina POPULATIONS IN MAIZE-BASED AGRO- ..... Population differentiation of Cercospora zeina in three districts of Uganda based on analysis of molecular variance ..... interactions: The example of the Erysiphe.

Modelling biological invasions: Individual to population scales at interfaces

KAUST Repository

Belmonte-Beitia, J.

2013-10-01

Extracting the population level behaviour of biological systems from that of the individual is critical in understanding dynamics across multiple scales and thus has been the subject of numerous investigations. Here, the influence of spatial heterogeneity in such contexts is explored for interfaces with a separation of the length scales characterising the individual and the interface, a situation that can arise in applications involving cellular modelling. As an illustrative example, we consider cell movement between white and grey matter in the brain which may be relevant in considering the invasive dynamics of glioma. We show that while one can safely neglect intrinsic noise, at least when considering glioma cell invasion, profound differences in population behaviours emerge in the presence of interfaces with only subtle alterations in the dynamics at the individual level. Transport driven by local cell sensing generates predictions of cell accumulations along interfaces where cell motility changes. This behaviour is not predicted with the commonly used Fickian diffusion transport model, but can be extracted from preliminary observations of specific cell lines in recent, novel, cryo-imaging. Consequently, these findings suggest a need to consider the impact of individual behaviour, spatial heterogeneity and especially interfaces in experimental and modelling frameworks of cellular dynamics, for instance in the characterisation of glioma cell motility. © 2013 Elsevier Ltd.

Modelling biological invasions: Individual to population scales at interfaces

KAUST Repository

Belmonte-Beitia, J.; Woolley, T.E.; Scott, J.G.; Maini, P.K.; Gaffney, E.A.

2013-01-01

Extracting the population level behaviour of biological systems from that of the individual is critical in understanding dynamics across multiple scales and thus has been the subject of numerous investigations. Here, the influence of spatial heterogeneity in such contexts is explored for interfaces with a separation of the length scales characterising the individual and the interface, a situation that can arise in applications involving cellular modelling. As an illustrative example, we consider cell movement between white and grey matter in the brain which may be relevant in considering the invasive dynamics of glioma. We show that while one can safely neglect intrinsic noise, at least when considering glioma cell invasion, profound differences in population behaviours emerge in the presence of interfaces with only subtle alterations in the dynamics at the individual level. Transport driven by local cell sensing generates predictions of cell accumulations along interfaces where cell motility changes. This behaviour is not predicted with the commonly used Fickian diffusion transport model, but can be extracted from preliminary observations of specific cell lines in recent, novel, cryo-imaging. Consequently, these findings suggest a need to consider the impact of individual behaviour, spatial heterogeneity and especially interfaces in experimental and modelling frameworks of cellular dynamics, for instance in the characterisation of glioma cell motility. © 2013 Elsevier Ltd.

Effect of temperature on the population dynamics of Aedes aegypti

Science.gov (United States)

Yusoff, Nuraini; Tokachil, Mohd Najir

2015-10-01

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

Population viability analysis: using a modeling tool to assess the viability of tapir populations in fragmented landscapes.

Science.gov (United States)

Medici, Emília Patrícia; Desbiez, Arnaud Leonard Jean

2012-12-01

A population viability analysis (PVA) was conducted of the lowland tapir populations in the Atlantic Forest of the Pontal do Paranapanema region, Brazil, including Morro do Diabo State Park (MDSP) and surrounding forest fragments. Results from the model projected that the population of 126 tapirs in MDSP is likely to persist over the next 100 years; however, 200 tapirs would be required to maintain a viable population. Sensitivity analysis showed that sub-adult mortality and adult mortality have the strongest influence on the dynamics of lowland tapir populations. High road-kill has a major impact on the MDSP tapir population and can lead to population extinction. Metapopulation modeling showed that dispersal of tapirs from MDSP to the surrounding fragments can be detrimental to the overall metapopulation, as fragments act as sinks. Nevertheless, the model showed that under certain conditions the maintenance of the metapopulation dynamics might be determinant for the persistence of tapirs in the region, particularly in the smaller fragments. The establishment of corridors connecting MDSP to the forest fragments models resulted in an increase in the stochastic growth rate, making tapirs more resilient to threats and catastrophes, but only if rates of mortality were not increased when using corridors. The PVA showed that the conservation of tapirs in the Pontal region depends on: the effective protection of MDSP; maintenance and, whenever possible, enhancement of the functional connectivity of the landscape, reducing mortality during dispersal and threats in the unprotected forest fragments; and neutralization of all threats affecting tapirs in the smaller forest fragments. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

POPULATION DYNAMICS OF PSEUDO-NITZSCHIA SPECIES ...

African Journals Online (AJOL)

nb

current study aimed at assessing the population dynamics of Pseudo-nitzschia ... and to the developing aquaculture industry ... B. Hotel. Pangani Island. Bongoyo Island. Mbudya Island. Msasani Bay ... Salinity values did not show clear trends.

Cost-effectiveness of screening programs for Chlamydia trachomatis - A population-based dynamic approach

NARCIS (Netherlands)

Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ

2000-01-01

Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general

Mapping of the stochastic Lotka-Volterra model to models of population genetics and game theory

Science.gov (United States)

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

2017-08-01

The relationship between the M -species stochastic Lotka-Volterra competition (SLVC) model and the M -allele Moran model of population genetics is explored via timescale separation arguments. When selection for species is weak and the population size is large but finite, precise conditions are determined for the stochastic dynamics of the SLVC model to be mappable to the neutral Moran model, the Moran model with frequency-independent selection, and the Moran model with frequency-dependent selection (equivalently a game-theoretic formulation of the Moran model). We demonstrate how these mappings can be used to calculate extinction probabilities and the times until a species' extinction in the SLVC model.

Representation of dynamical stimuli in populations of threshold neurons.

Directory of Open Access Journals (Sweden)

Tatjana Tchumatchenko

2011-10-01

Full Text Available Many sensory or cognitive events are associated with dynamic current modulations in cortical neurons. This raises an urgent demand for tractable model approaches addressing the merits and limits of potential encoding strategies. Yet, current theoretical approaches addressing the response to mean- and variance-encoded stimuli rarely provide complete response functions for both modes of encoding in the presence of correlated noise. Here, we investigate the neuronal population response to dynamical modifications of the mean or variance of the synaptic bombardment using an alternative threshold model framework. In the variance and mean channel, we provide explicit expressions for the linear and non-linear frequency response functions in the presence of correlated noise and use them to derive population rate response to step-like stimuli. For mean-encoded signals, we find that the complete response function depends only on the temporal width of the input correlation function, but not on other functional specifics. Furthermore, we show that both mean- and variance-encoded signals can relay high-frequency inputs, and in both schemes step-like changes can be detected instantaneously. Finally, we obtain the pairwise spike correlation function and the spike triggered average from the linear mean-evoked response function. These results provide a maximally tractable limiting case that complements and extends previous results obtained in the integrate and fire framework.

Mean-field games with logistic population dynamics

KAUST Repository

Gomes, Diogo A.; De Lima Ribeiro, Ricardo

2013-01-01

In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.

Mean-field games with logistic population dynamics

KAUST Repository

Gomes, Diogo A.

2013-12-01

In its standard form, a mean-field game can be defined by coupled system of equations, a Hamilton-Jacobi equation for the value function of agents and a Fokker-Planck equation for the density of agents. Traditionally, the latter equation is adjoint to the linearization of the former. Since the Fokker-Planck equation models a population dynamic, we introduce natural features such as seeding and birth, and nonlinear death rates. In this paper we analyze a stationary meanfield game in one dimension, illustrating various techniques to obtain regularity of solutions in this class of systems. In particular we consider a logistic-type model for birth and death of the agents which is natural in problems where crowding affects the death rate of the agents. The introduction of these new terms requires a number of new ideas to obtain wellposedness. In a forthcoming publication we will address higher dimensional models. ©2013 IEEE.

Comparison of the iPCoD and DEPONS models for modelling population consequences of noise on harbour porpoises

DEFF Research Database (Denmark)

Nabe-Nielsen, Jacob; Harwood, John

Two different frameworks have been developed to assess the potential effects of noise associated with offshore renewable energy developments on harbour porpoise populations: The Interim Population Consequences of Disturbance (iPCoD) and Disturbance Effects of Noise on the Harbour Porpoise...... Population in the North Sea (DEPONS). Although both models simulate population dynamics based on the birth and survival rates of individual animals, they model survival in a different way. iPCoD uses average survival rates derived from data from North Sea animals. In the DEPONS model, survival emerges from...

Spatial and temporal dynamics of the genetic organization of small mammal populations

International Nuclear Information System (INIS)

Smith, M.H.; Manlove, M.N.; Joule, J.

1978-01-01

A functional population is a group of organisms and their offspring that contributes to a common gene pool within a certain area and time period. It is also the unit of evolution and should be viewed both in quantitative and qualitative terms. Selection, drift, dispersal, and mutation can alter the composition of populations. Spatial heterogeneity in allele frequencies argues for a conceptual model that has a series of relatively small populations semi-isolated from one another. Because of the relatively high levels of genetic variability characteristic of most mammalian species, significant amounts of gene flow between these spatially subdivided populations must occur when longer time periods are considered. Fluctuations in the genetic structure of populations seem to be important in altering the fitness of the individuals within the populations. The interaction of populations through gene flow is important in changing the levels of intrapopulational genetic variability. Populations can be characterized as existing on a continuum from relatively stable to unstable numbers and by other associated changes in their characteristics. Temporal changes in allele frequency occur in a variety of mammals. Conceptually, a species can be viewed as a series of dynamic populations that vary in numbers and quality in both a spatial and temporal context even over short distances and time periods. Short term changes in the quality of individuals in a population can be important in altering the short term dynamics of a population

A linear model of population dynamics

Science.gov (United States)

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

2016-08-01

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

Dynamics of sexual populations structured by a space variable and a phenotypical trait

KAUST Repository

Mirrahimi, Sepideh

2013-03-01

We study sexual populations structured by a phenotypic trait and a space variable, in a non-homogeneous environment. Departing from an infinitesimal model, we perform an asymptotic limit to derive the system introduced in Kirkpatrick and Barton (1997). We then perform a further simplification to obtain a simple model. Thanks to this simpler equation, we can describe rigorously the dynamics of the population. In particular, we provide an explicit estimate of the invasion speed, or extinction speed of the species. Numerical computations show that this simple model provides a good approximation of the original infinitesimal model, and in particular describes quite well the evolution of the species\\' range. © 2013 Elsevier Inc.

Dynamics of sexual populations structured by a space variable and a phenotypical trait

KAUST Repository

Mirrahimi, Sepideh; Raoul, Gaë l

2013-01-01

We study sexual populations structured by a phenotypic trait and a space variable, in a non-homogeneous environment. Departing from an infinitesimal model, we perform an asymptotic limit to derive the system introduced in Kirkpatrick and Barton (1997). We then perform a further simplification to obtain a simple model. Thanks to this simpler equation, we can describe rigorously the dynamics of the population. In particular, we provide an explicit estimate of the invasion speed, or extinction speed of the species. Numerical computations show that this simple model provides a good approximation of the original infinitesimal model, and in particular describes quite well the evolution of the species' range. © 2013 Elsevier Inc.

The impact of rapid evolution on population dynamics in the wild: experimental test of eco-evolutionary dynamics.

Science.gov (United States)

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.

Dynamics of a Lotka-Volterra type model with applications to marine phage population dynamics

International Nuclear Information System (INIS)

Gavin, C; Pokrovskii, A; Prentice, M; Sobolev, V

2006-01-01

The famous Lotka-Volterra equations play a fundamental role in the mathematical modeling of various ecological and chemical systems. A new modification of these equations has been recently suggested to model the structure of marine phage populations, which are the most abundant biological entities in the biosphere. The purpose of the paper is: (i) to make some methodical remarks concerning this modification; (ii) to discuss new types of canards which arise naturally in this context; (iii) to present results of some numerical experiments

Population-level consequences of herbivory, changing climate, and source-sink dynamics on a long-lived invasive shrub.

Science.gov (United States)

van Klinken, R D; Pichancourt, J B

2015-12-01

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net

Dynamics and forecast in a simple model of sustainable development for rural populations.

Science.gov (United States)

Angulo, David; Angulo, Fabiola; Olivar, Gerard

2015-02-01

Society is becoming more conscious on the need to preserve the environment. Sustainable development schemes have grown rapidly as a tool for managing, predicting and improving the growth path in different regions and economy sectors. We introduce a novel and simple mathematical model of ordinary differential equations (ODEs) in order to obtain a dynamical description for each one of the sustainability components (economy, social development and environment conservation), together with their dependence with demographic dynamics. The main part in the modeling task is inspired by the works by Cobb, Douglas, Brander and Taylor. This is completed through some new insights by the authors. A model application is presented for three specific geographical rural regions in Caldas (Colombia).

Population dynamics and flight phenology model of codling moth differ between commercial and abandoned apple orchard ecosystems

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Neelendra K Joshi

2016-09-01

Full Text Available Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM, Cydia pomonella (L. (Lepidoptera: Tortricidae, which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight and egg-hatch allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e.,1970’s model. In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology.

Seasonal population dynamics of Brachyiulus jawlowskii (Diplopoda, Julidae in the Dnieper river arena

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N. G. Gudym

2016-06-01

Full Text Available We have researched the population dynamics of Brachyiulus jawlowskii Lohmander, 1928 in the arena of the Dnepr river (within the "Dnieper-Orilsky” Nature Reserve and also present a full picture of the habitat distribution of Julidae within the researched area. The tested models were basic types of arena biogeocenosis: sand steppe, black maple forests, artificial pine plantations, deciduous forest, meadow and swamp. Variation in population density of B. jawlowskii is determined by biotopical features. The swamp and meadow habitats can be characterized by the highest level of population dynamics. B. jawlowskii plays the greatest role in the herpetobiont grouping in swamp and oak forest habitats (6.7% and 4.6% respectively. In other types of habitat this species composes 0.1–3.5% of the total abundance of this group. The highest abundance dynamic was reached by the Julidae cenopopulations which inhabit the swamp, oak forest and meadow habitats. B. jawlowskii occupies a relatively significant share in the herpetobiont communities of these habitats. Thus, the indicators of absolute number of this species and its relative participation in the herpertobiont grouping indicate the preference of this species for marsh, oak forest and meadow habitats. These habitats can be characterized by an excessive or moderate level of edaphotopic humidification. The ecosystem of the steppe zone of Ukraine is subject to significant human impact. In nature reserves, this effect is minimized, which permits research to be conducted on regimes of natural population dynamics. We established that B. jawlowskii inhabits all habitats investigated within the arena zone of the Dnepr river. This indicates that this is an environmentally flexible Julidae species. The population dynamics of B. jawlowskii can be characterized by three distinct periods: spring-summer, summer and autumn. Each of these periods is characterized by a distinct population dynamic, but throughout the

A Stochastic Model for Malaria Transmission Dynamics

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Rachel Waema Mbogo

2018-01-01

Full Text Available Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis. In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics. Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions. The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp. The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out. Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans. These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.

Stabilization and complex dynamics in a predator-prey model with predator suffering from an infectious disease

NARCIS (Netherlands)

Kooi, B.W.; Voorn, van G.A.K.; Das, pada Krishna

2011-01-01

We study the effects of a non-specified infectious disease of the predator on the dynamics a predator–prey system, by evaluating the dynamics of a three-dimensional model. The predator population in this (PSI) model is split into a susceptible and an unrecoverable infected population, while all

Stabilization and complex dynamics in a predator-prey model with predator suffering from an infectious disease.

NARCIS (Netherlands)

Kooi, B.W.; van Voorn, G.A.K.; Pada Das, K.

2011-01-01

We study the effects of a non-specified infectious disease of the predator on the dynamics a predator-prey system, by evaluating the dynamics of a three-dimensional model. The predator population in this (PSI) model is split into a susceptible and an unrecoverable infected population, while all

Current and Future Dynamics of the Red-Cockaded Woodpecker Population Inhabiting the Savannah River National Environmental Research Park: Managing For Population Growth

International Nuclear Information System (INIS)

Walters, J.R.; Taylor, T.B.; Daniels, S.J.; Crowder, L.B.; Pridd, J.A.

2001-01-01

Research aimed to study the dynamics of the SRS population of Red-Cockaded woodpecker and compare to those of other populations to identify factors limiting population growth; recruitment clusters were evaluated to determine what properties of individual cavity trees, surrounding habitat and the surrounding landscape might limit occupancy through natural dispersal. A spatial simulation model was used to project expected dispersal rates and population growth under current conditions and compare those estimates to observed dispersal and population growth. Red cockaded woodpecker populations at SRS are stable considering size. Research reveals that closer placement of recruitment clusters to active territories would produce higher growth rates while decreasing management intensity

Current and Future Dynamics of the Red-Cockaded Woodpecker Population Inhabiting the Savannah River National Environmental Research Park: Managing For Population Growth

Energy Technology Data Exchange (ETDEWEB)

Walters, J.R.; Taylor, T.B.; Daniels, S.J.; Crowder, L.B.; Pridd, J.A.

2001-01-01

Research aimed to study the dynamics of the SRS population of Red-Cockaded woodpecker and compare to those of other populations to identify factors limiting population growth; recruitment clusters were evaluated to determine what properties of individual cavity trees, surrounding habitat and the surrounding landscape might limit occupancy through natural dispersal. A spatial simulation model was used to project expected dispersal rates and population growth under current conditions and compare those estimates to observed dispersal and population growth. Red cockaded woodpecker populations at SRS are stable considering size. Research reveals that closer placement of recruitment clusters to active territories would produce higher growth rates while decreasing management intensity.

Population dynamics of Trichuris suis in trickle-infected pigs.

Science.gov (United States)

Nejsum, P; Thamsborg, S M; Petersen, H H; Kringel, H; Fredholm, M; Roepstorff, A

2009-05-01

The population dynamics of Trichuris suis in pigs was studied during long-term experimental infections. Twenty-three 10-week-old pigs were inoculated with 5 T. suis eggs/kg/day. Seven, 8, and 8 pigs were necropsied at weeks 4, 8, and 14 post-start of infection (p.i.), respectively. The median numbers of worms in the colon were 538 (min-max: 277-618), 332 (14-1140) and 0 (0-4) at 4, 8, and 14 weeks p.i. respectively, suggesting an increased aggregation of the worms with time and acquisition of nearly sterile immunity. The serum levels of T. suis specific antibodies (IgG1, IgG2 and IgA) peaked at week 8 p.i. By week 14 p.i. the IgG2 and IgA antibody levels remained significantly elevated above the level of week 0. The population dynamics of T. suis trickle infections in pigs is discussed with focus on interpretation of diagnostic and epidemiological data of pigs, the use of pigs as a model for human Trichuris trichiura infections and the novel approach of using T. suis eggs in the treatment of patients with inflammatory bowel disease.

From complex spatial dynamics to simple Markov chain models: do predators and prey leave footprints?

DEFF Research Database (Denmark)

Nachman, Gøsta Støger; Borregaard, Michael Krabbe

2010-01-01

to another, are then depicted in a state transition diagram, constituting the "footprints" of the underlying population dynamics. We investigate to what extent changes in the population processes modeled in the complex simulation (i.e. the predator's functional response and the dispersal rates of both......In this paper we present a concept for using presence-absence data to recover information on the population dynamics of predator-prey systems. We use a highly complex and spatially explicit simulation model of a predator-prey mite system to generate simple presence-absence data: the number...... of transition probabilities on state variables, and combine this information in a Markov chain transition matrix model. Finally, we use this extended model to predict the long-term dynamics of the system and to reveal its asymptotic steady state properties....

Population dynamics of graphene driven by a few-cycle laser pulse

Science.gov (United States)

Ding, Chunling; Yu, Rong; Hao, Xiangying; Zhang, Duo; Zu, Fengxia

2017-06-01

We study the time evolution of the populations in a two-dimensional (2D) graphene system by employing a few-cycle laser pulse with a linear polarization. Specifically, we present a comparative numerical analysis of the population dynamics of graphene in three different model configurations. Our results show that the Rabi-like oscillations and intraband population inversion can be observed in the population spectrum, which originated from the periodicity of a few-cycle laser pulse and the intraband Coulomb scattering. Also, coherent population oscillations are produced across the Dirac point when the Rabi frequency of the laser field which is used to couple the interband transition is much larger than that couples the intraband transition, and vice versa. These investigations may be helpful to enhance the performance of graphene-based ultrafast electronic and optoelectronic devices, including light-emitting devices, touch screens, photodetectors, and ultrafast lasers.

Memory and obesity affect the population dynamics of asexual freshwater planarians

International Nuclear Information System (INIS)

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

2011-01-01

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

Data-driven modelling of structured populations a practical guide to the integral projection model

CERN Document Server

Ellner, Stephen P; Rees, Mark

2016-01-01

This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in B...

Capital, population and urban patterns.

Science.gov (United States)

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.

Population Dynamics Modeling of Arapaima gigas Modelagem da dinâmica populacional de Arapaima gigas

Directory of Open Access Journals (Sweden)

Eliane dos Santos de Souza Coutinho

2010-01-01

Full Text Available Pirarucu (Arapaima gigas has been of the most important natural fishing resources of the Amazon region. Due to its economic importance, and the necessity to preserve the species hand, field research concerning the habits and behavior of the pirarucu has been increasing for the last 20 years. The aim of this paper is to present a mathematical model for the pirarucu population dynamics considering the species peculiarities, particularly the male parental care over the offspring. The solution of the dynamical systems indicates three possible equilibrium points for the population. The first corresponds to extinction; the third corresponds to a stable population close to the environmental carrying capacity. The second corresponds to an unstable equilibrium located between extinction and full use of the carrying capacity. It is shown that lack of males’ parental care closes the gap between the point corresponding to the unstable equilibrium and the point of stable non-trivial equilibrium. If guarding failure reaches a critical point the two points coincide and the population tends irreversibly to extinction. If some event tends to destabilize the population equilibrium, as for instance inadequate parental care, the model responds in such a way as to restore the trajectory towards the stable equilibrium point avoiding the route to extinction. The parameters introduced to solve the system of equations are partially derived from limited but reliable field data collected at the Mamirauá Sustainable Development Reserve (MSDR in the Brazilian Amazonian Region.Pirarucu (Arapaima gigas tem sido um dos mais importantes recursos pesqueiros naturais da Amazônia. Devido à sua importância econômica, por um lado, e a necessidade de preservar a espécie, por outro lado, o domínio da investigação relativa a hábitos e comportamento do pirarucu tem sido crescente nos últimos 20 anos. O objetivo deste trabalho é apresentar um modelo matemático para a din

Five challenges in modelling interacting strain dynamics

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Paul S. Wikramaratna

2015-03-01

Full Text Available Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called “strain space”. We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures.

Investigation of the Nonlinear Model of the Cellular Population System Development

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M. S. Vinogradova

2014-01-01

Full Text Available An isolated population system is considered which consists of two types of human stem cells: normal cells and cells with chromosomal anomalies (abnormal. In the paper the nonlinear dynamic model which describes dynamics of cell populations developing in vitro is elaborated. The model allows to investigate the processes of the formation of the abnormal cells population from the abnormal cells population of normal cells as well as joint development of these populations. The model takes into account the limited resources.An important feature of the developed model is the use of biological characteristics of processes in the cell population system, such as the proportion of cells, divided over a specified time, the proportion of cells whish are not divided, and which are "lost" and which are passed in the population of abnormal cells from the normal population. This approach allows a more detailed analysis of the impact of various "primary" parameters on the evolution of the population system.Under cultivation of cell populations in vitro a struggle for resources primarily affects the processes of the cell reproduction. This is reflected in the existence of the dividing cells frequency dependence of the total population of normal and abnormal cells. For the account of such dependencies different non-linear functions are typically used. However, the use of such non-linear relationships leads to the difficulties in finding confidence intervals for the estimates of the model parameters at subsequent stages of research. At the same time, the problem of the system parameters estimating and finding of the corresponding confidence intervals for estimates can be solved easy in case when the nonlinear system is linear with respect to the unknown parameters. In the paper it is achieved due to the piecewise linear approximation of nonlinear dependencies.An important feature of the model is a different view of the right part of the differential equations system

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Science.gov (United States)

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

2014-01-01

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

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Directory of Open Access Journals (Sweden)

Johannes P M Heinonen

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

First Results of Modeling Radiation Belt Electron Dynamics with the SAMI3 Plasmasphere Model

Science.gov (United States)

Komar, C. M.; Glocer, A.; Huba, J.; Fok, M. C. H.; Kang, S. B.; Buzulukova, N.

2017-12-01

The radiation belts were one of the first discoveries of the Space Age some sixty years ago and radiation belt models have been improving since the discovery of the radiation belts. The plasmasphere is one region that has been critically important to determining the dynamics of radiation belt populations. This region of space plays a critical role in describing the distribution of chorus and magnetospheric hiss waves throughout the inner magnetosphere. Both of these waves have been shown to interact with energetic electrons in the radiation belts and can result in the energization or loss of radiation belt electrons. However, radiation belt models have been historically limited in describing the distribution of cold plasmaspheric plasma and have relied on empirically determined plasmasphere models. Some plasmasphere models use an azimuthally symmetric distribution of the plasmasphere which can fail to capture important plasmaspheric dynamics such as the development of plasmaspheric drainage plumes. Previous work have coupled the kinetic bounce-averaged Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model used to model ring current and radiation belt populations with the Block-adaptive Tree Solar wind Roe-type Upwind Scheme (BATSRUS) global magnetohydrodynamic model to self-consistently obtain the magnetospheric magnetic field and ionospheric potential. The present work will utilize this previous coupling and will additionally couple the SAMI3 plasmasphere model to better represent the dynamics on the plasmasphere and its role in determining the distribution of waves throughout the inner magnetosphere. First results on the relevance of chorus, hiss, and ultralow frequency waves on radiation belt electron dynamics will be discussed in context of the June 1st, 2013 storm-time dropout event.

Population Dynamics and Cost-Benefit Analysis. An Attempt to Relate Population Dynamics via Lifetime Reproductive Success to Short-Term Decisions

NARCIS (Netherlands)

Tinbergen, J.M.; Balen, J.H. van; Drent, P.J.; Cavé, A.J.; Mertens, J.A.L.; Boer-Hazewinkel, J. den

1987-01-01

1. The aim of this article is to explore whether cost-benefit analysis of behaviour may help to understand the population dynamics of a species. The Great Tit is taken as an example. 2. The lifetime reproductive success in different populations of Great Tits amounts from 0.7 (Hoge Veluwe, Wytham) to

Equivalent Dynamic Models.

Science.gov (United States)

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

Science.gov (United States)

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

Population dynamics of rural Ethiopia.

Science.gov (United States)

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.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

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Giovanni Dalmasso

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

Analytical properties of a three-compartmental dynamical demographic model

Science.gov (United States)

Postnikov, E. B.

2015-07-01

The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.

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

Science.gov (United States)

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

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

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

Science.gov (United States)

Gangopadhyay, Ahana; Chakrabartty, Shantanu

2017-04-27

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 ΣΔ 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.

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

Science.gov (United States)

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.

The evolution of wealth transmission in human populations: a stochastic model

International Nuclear Information System (INIS)

Augustins, G; Etienne, L; Ferrer, R; Godelle, B; Rousset, F; Ferdy, J-B; Pitard, E

2014-01-01

Reproductive success and survival are influenced by wealth in human populations. Wealth is transmitted to offsprings and strategies of transmission vary over time and among populations, the main variation being how equally wealth is transmitted to children. Here we propose a model where we simulate both the dynamics of wealth in a population and the evolution of a trait that determines how wealth is transmitted from parents to offspring, in a darwinian context

Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population

Directory of Open Access Journals (Sweden)

A. H. Sallam

2015-03-01

Full Text Available Prediction accuracy of genomic selection (GS has been previously evaluated through simulation and cross-validation; however, validation based on progeny performance in a plant breeding program has not been investigated thoroughly. We evaluated several prediction models in a dynamic barley breeding population comprised of 647 six-row lines using four traits differing in genetic architecture and 1536 single nucleotide polymorphism (SNP markers. The breeding lines were divided into six sets designated as one parent set and five consecutive progeny sets comprised of representative samples of breeding lines over a 5-yr period. We used these data sets to investigate the effect of model and training population composition on prediction accuracy over time. We found little difference in prediction accuracy among the models confirming prior studies that found the simplest model, random regression best linear unbiased prediction (RR-BLUP, to be accurate across a range of situations. In general, we found that using the parent set was sufficient to predict progeny sets with little to no gain in accuracy from generating larger training populations by combining the parent set with subsequent progeny sets. The prediction accuracy ranged from 0.03 to 0.99 across the four traits and five progeny sets. We explored characteristics of the training and validation populations (marker allele frequency, population structure, and linkage disequilibrium, LD as well as characteristics of the trait (genetic architecture and heritability, . Fixation of markers associated with a trait over time was most clearly associated with reduced prediction accuracy for the mycotoxin trait DON. Higher trait in the training population and simpler trait architecture were associated with greater prediction accuracy.

Seasonal dynamics of SAR11 populations in the euphotic and mesopelagic zones of the northwestern Sargasso Sea

DEFF Research Database (Denmark)

Carlson, Craig A; Morris, Robert; Parsons, Rachel

2009-01-01

, resolving their temporal dynamics can provide important insights to the cycling of organic and inorganic nutrients. This quantitative time-series data revealed distinct annual distribution patterns of SAR11 abundance in the euphotic (0-120) and upper mesopelagic (160-300 m) zones that were reproducibly...... correlated with seasonal mixing and stratification of the water column. Terminal restriction fragment length polymorphism (T-RFLP) data generated from a decade of samples collected at BATS were combined with the FISH data to model the annual dynamics of SAR11 subclade populations. 16S rRNA gene clone...... the Sargasso Sea surface layer, and revealed new details of their population dynamics....

Spatial structures in a simple model of population dynamics for parasite-host interactions

Energy Technology Data Exchange (ETDEWEB)

Dong, J. J.; Skinner, B.; Breecher, N.; Schmittmann, B.; Zia, R. K. P.

2015-08-01

Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the populations long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocity generally increases the parasite population.

Dynamics of Population on the Verge of Extinction

OpenAIRE

Oborny, B.; Meszena, G.; Szabo, G.

2005-01-01

Theoretical considerations suggest that extinction in dispersal-limited populations is necessarily a threshold-like process that is analogous to a critical phase transition in physics. We use this analogy to find robust, common features in the dynamics of extinctions, and suggest early warning signals which may indicate that a population is endangered. As the critical threshold of extinction is approached, the population spontaneously fragments into discrete subpopulations and, consequently, ...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A Gompertz population model with Allee effect and fuzzy initial values

Science.gov (United States)

Amarti, Zenia; Nurkholipah, Nenden Siti; Anggriani, Nursanti; Supriatna, Asep K.

2018-03-01

Growth and population dynamics models are important tools used in preparing a good management for society to predict the future of population or species. This has been done by various known methods, one among them is by developing a mathematical model that describes population growth. Models are usually formed into differential equations or systems of differential equations, depending on the complexity of the underlying properties of the population. One example of biological complexity is Allee effect. It is a phenomenon showing a high correlation between very small population size and the mean individual fitness of the population. In this paper the population growth model used is the Gompertz equation model by considering the Allee effect on the population. We explore the properties of the solution to the model numerically using the Runge-Kutta method. Further exploration is done via fuzzy theoretical approach to accommodate uncertainty of the initial values of the model. It is known that an initial value greater than the Allee threshold will cause the solution rises towards carrying capacity asymptotically. However, an initial value smaller than the Allee threshold will cause the solution decreases towards zero asymptotically, which means the population is eventually extinct. Numerical solutions show that modeling uncertain initial value of the critical point A (the Allee threshold) with a crisp initial value could cause the extinction of population of a certain possibilistic degree, depending on the predetermined membership function of the initial value.

Sepsis progression and outcome: a dynamical model

Directory of Open Access Journals (Sweden)

Gessler Damian DG

2006-02-01

Full Text Available Abstract Background Sepsis (bloodstream infection is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions. Results We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC, a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system. Conclusion The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates.

Accidental release of chlorine in Chicago: Coupling of an exposure model with a Computational Fluid Dynamics model

Science.gov (United States)

Sanchez, E. Y.; Colman Lerner, J. E.; Porta, A.; Jacovkis, P. M.

2013-01-01

The adverse health effects of the release of hazardous substances into the atmosphere continue being a matter of concern, especially in densely populated urban regions. Emergency responders need to have estimates of these adverse health effects in the local population to aid planning, emergency response, and recovery efforts. For this purpose, models that predict the transport and dispersion of hazardous materials are as necessary as those that estimate the adverse health effects in the population. In this paper, we present the results obtained by coupling a Computational Fluid Dynamics model, FLACS (FLame ACceleration Simulator), with an exposure model, DDC (Damage Differential Coupling). This coupled model system is applied to a scenario of hypothetical release of chlorine with obstacles, such as buildings, and the results show how it is capable of predicting the atmospheric dispersion of hazardous chemicals, and the adverse health effects in the exposed population, to support decision makers both in charge of emergency planning and in charge of real-time response. The results obtained show how knowing the influence of obstacles in the trajectory of the toxic cloud and in the diffusion of the pollutants transported, and obtaining dynamic information of the potentially affected population and of associated symptoms, contribute to improve the planning of the protection and response measures.

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

Science.gov (United States)

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.

Modeling Asteroid Dynamics using AMUSE: First Test Cases

NARCIS (Netherlands)

Frantseva, Kateryna; Mueller, Michael; van der Tak, Floris; Helmich, Frank P.

2015-01-01

We are creating a dynamic model of the current asteroid population. The goal is to reproduce measured impact rates in the current Solar System, from which we'll derive delivery rates of water and organic material by tracing low-albedo C-class asteroids (using the measured albedo distribution from

Spatio-temporal dynamics of a fish predator: Density-dependent and hydrographic effects on Baltic Sea cod population.

Directory of Open Access Journals (Sweden)

Valerio Bartolino

Full Text Available Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes.

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

Energy Technology Data Exchange (ETDEWEB)

Jaworska, J.S.; Hallam, T.G.; Schultz, T.W. [Univ. of Tennessee, Knoxville, TN (United States)

1996-03-01

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