Metapopulation dynamics and the evolution of dispersal

NASA Astrophysics Data System (ADS)

Parvinen, Kalle

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

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

USGS Publications Warehouse

McKenna, James E.

2000-01-01

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

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

PubMed

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

2011-02-01

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

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

USGS Publications Warehouse

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.

PubMed

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.

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

PubMed

Kyogoku, Daisuke; Sota, Teiji

2017-05-17

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

Stochastic population dynamic models as probability networks

Treesearch

M.E. and D.C. Lee Borsuk

2009-01-01

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

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

PubMed

Yuan, Chenggui; Mao, Xuerong; Lygeros, John

2009-01-01

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

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

[Approximation to the dynamics of meningococcal meningitis through dynamic systems and time series].

PubMed

Canals, M

1996-02-01

Meningococcal meningitis is subjected to epidemiological surveillance due to its severity and the occasional presentation of epidemic outbreaks. This work analyses previous disease models, generate new ones and analyses monthly cases using ARIMA time series models. The results show that disease dynamics for closed populations is epidemic and the epidemic size is related to the proportion of carriers and the transmissiveness of the agent. In open populations, disease dynamics depends on the admission rate of susceptible and the relative admission of infected individuals. Our model considers a logistic populational growth and carrier admission proportional to populational size, generating an endemic dynamics. Considering a non-instantaneous system response, a greater realism is obtained establishing that the endemic situation may present a dynamics highly sensitive to initial conditions, depending on the transmissiveness and proportion of susceptible individuals in the population. Time series model showed an adequate predictive capacity in terms no longer than 10 months. The lack of long term predictability was attributed to local changes in the proportion of carriers or on transmissiveness that lead to chaotic dynamics over a seasonal pattern. Predictions for 1995 and 1996 were obtained.

Evolutionary Game Theory in Growing Populations

NASA Astrophysics Data System (ADS)

Melbinger, Anna; Cremer, Jonas; Frey, Erwin

2010-10-01

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

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

PubMed

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.

Dynamic Model for Life History of Scyphozoa

PubMed Central

Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

2015-01-01

A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish. PMID:26114642

Dynamic Model for Life History of Scyphozoa.

PubMed

Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

2015-01-01

A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish.

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

PubMed

Kooi, B W

2015-12-01

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

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

Evolutionary dynamics with fluctuating population sizes and strong mutualism.

PubMed

Chotibut, Thiparat; Nelson, David R

2015-08-01

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

Evolutionary dynamics with fluctuating population sizes and strong mutualism

NASA Astrophysics Data System (ADS)

Chotibut, Thiparat; Nelson, David R.

2015-08-01

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

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

USGS Publications Warehouse

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

2017-01-01

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

A quantitative model of honey bee colony population dynamics.

PubMed

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

2011-04-18

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

A new ODE tumor growth modeling based on tumor population dynamics

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

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

2015-10-22

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

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

USGS Publications Warehouse

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

2004-01-01

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

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

Stage-Structured Population Dynamics of AEDES AEGYPTI

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Budin, Harun; Ismail, Salemah

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

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

PubMed

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

2013-09-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2015-01-01

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

Evolution of specialization under non-equilibrium population dynamics.

PubMed

Nurmi, Tuomas; Parvinen, Kalle

2013-03-21

We analyze the evolution of specialization in resource utilization in a mechanistically underpinned discrete-time model using the adaptive dynamics approach. We assume two nutritionally equivalent resources that in the absence of consumers grow sigmoidally towards a resource-specific carrying capacity. The consumers use resources according to the law of mass-action with rates involving trade-off. The resulting discrete-time model for the consumer population has over-compensatory dynamics. We illuminate the way non-equilibrium population dynamics affect the evolutionary dynamics of the resource consumption rates, and show that evolution to the trimorphic coexistence of a generalist and two specialists is possible due to asynchronous non-equilibrium population dynamics of the specialists. In addition, various forms of cyclic evolutionary dynamics are possible. Furthermore, evolutionary suicide may occur even without Allee effects and demographic stochasticity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Recasting a model atomistic glassformer as a system of icosahedra

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

Pinney, Rhiannon; Bristol Centre for Complexity Science, University of Bristol, Bristol BS8 1TS; Liverpool, Tanniemola B.

2015-12-28

We consider a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. Upon cooling, these icosahedra organize into mesoclusters. We recast this glassformer as an effective system of icosahedra which we describe with a population dynamics model. This model we parameterize with data from the temperature regime accessible to molecular dynamics simulations. We then use the model to determine the population of icosahedra in mesoclusters at arbitrary temperature. Using simulation data to incorporate dynamics into the model, we predict relaxation behavior at temperatures inaccessible to conventional approaches. Our model predicts super-Arrhenius dynamics whose relaxation timemore » remains finite for non-zero temperature.« less

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

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

Complex Population Dynamics and the Coalescent Under Neutrality

PubMed Central

Volz, Erik M.

2012-01-01

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

Bounds on the dynamics of sink populations with noisy immigration.

PubMed

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

2014-03-01

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

Spectral analysis of a two-species competition model: Determining the effects of extreme conditions on the color of noise generated from simulated time series

NASA Astrophysics Data System (ADS)

Golinski, M. R.

2006-07-01

Ecologists have observed that environmental noise affects population variance in the logistic equation for one-species growth. Interactions between deterministic and stochastic dynamics in a one-dimensional system result in increased variance in species population density over time. Since natural populations do not live in isolation, the present paper simulates a discrete-time two-species competition model with environmental noise to determine the type of colored population noise generated by extreme conditions in the long-term population dynamics of competing populations. Discrete Fourier analysis is applied to the simulation results and the calculated Hurst exponent ( H) is used to determine how the color of population noise for the two species corresponds to extreme conditions in population dynamics. To interpret the biological meaning of the color of noise generated by the two-species model, the paper determines the color of noise generated by three reference models: (1) A two-dimensional discrete-time white noise model (0⩽ H<1/2); (2) A two-dimensional fractional Brownian motion model (H=1/2); and (3) A two-dimensional discrete-time model with noise for unbounded growth of two uncoupled species (1/2< H⩽1).

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

PubMed Central

Dann, Benjamin

2016-01-01

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

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

PubMed

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

2016-11-01

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

MODELING THE DYNAMICS OF WILDLIFE HABITAT AND POPULATIONS AT THE LANDSCAPE SCALE

EPA Science Inventory

A forest dynamics model (FORCLIM) was linked to a spatial wildlife population model (PATCH) to assess the effects of habitat change in a landscape on selected wildlife species. The habitat changes included forest responses to harvesting, development, and climate change on a west...

Population models for passerine birds: structure, parameterization, and analysis

USGS Publications Warehouse

Noon, B.R.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Population models have great potential as management tools, as they use infonnation about the life history of a species to summarize estimates of fecundity and survival into a description of population change. Models provide a framework for projecting future populations, determining the effects of management decisions on future population dynamics, evaluating extinction probabilities, and addressing a variety of questions of ecological and evolutionary interest. Even when insufficient information exists to allow complete identification of the model, the modelling procedure is useful because it forces the investigator to consider the life history of the species when determining what parameters should be estimated from field studies and provides a context for evaluating the relative importance of demographic parameters. Models have been little used in the study of the population dynamics of passerine birds because of: (1) widespread misunderstandings of the model structures and parameterizations, (2) a lack of knowledge of life histories of many species, (3) difficulties in obtaining statistically reliable estimates of demographic parameters for most passerine species, and (4) confusion about functional relationships among demographic parameters. As a result, studies of passerine demography are often designed inappropriately and fail to provide essential data. We review appropriate models for passerine bird populations and illustrate their possible uses in evaluating the effects of management or other environmental influences on population dynamics. We identify environmental influences on population dynamics. We identify parameters that must be estimated from field data, briefly review existing statistical methods for obtaining valid estimates, and evaluate the present status of knowledge of these parameters.

Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data.

PubMed

Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N

2014-04-01

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.

Mathematical modelling of vector-borne diseases and insecticide resistance evolution.

PubMed

Gabriel Kuniyoshi, Maria Laura; Pio Dos Santos, Fernando Luiz

2017-01-01

Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.

Modeled response of the West Nile virus vector Culex quinquefasciatus to changing climate using the dynamic mosquito simulation model

NASA Astrophysics Data System (ADS)

Morin, Cory W.; Comrie, Andrew C.

2010-09-01

Climate can strongly influence the population dynamics of disease vectors and is consequently a key component of disease ecology. Future climate change and variability may alter the location and seasonality of many disease vectors, possibly increasing the risk of disease transmission to humans. The mosquito species Culex quinquefasciatus is a concern across the southern United States because of its role as a West Nile virus vector and its affinity for urban environments. Using established relationships between atmospheric variables (temperature and precipitation) and mosquito development, we have created the Dynamic Mosquito Simulation Model (DyMSiM) to simulate Cx. quinquefasciatus population dynamics. The model is driven with climate data and validated against mosquito count data from Pasco County, Florida and Coachella Valley, California. Using 1-week and 2-week filters, mosquito trap data are reproduced well by the model ( P < 0.0001). Dry environments in southern California produce different mosquito population trends than moist locations in Florida. Florida and California mosquito populations are generally temperature-limited in winter. In California, locations are water-limited through much of the year. Using future climate projection data generated by the National Center for Atmospheric Research CCSM3 general circulation model, we applied temperature and precipitation offsets to the climate data at each location to evaluate mosquito population sensitivity to possible future climate conditions. We found that temperature and precipitation shifts act interdependently to cause remarkable changes in modeled mosquito population dynamics. Impacts include a summer population decline from drying in California due to loss of immature mosquito habitats, and in Florida a decrease in late-season mosquito populations due to drier late summer conditions.

Integral control for population management.

PubMed

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

2015-04-01

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

Evolutionary dynamics of fearfulness and boldness.

PubMed

Ji, Ting; Zhang, Boyu; Sun, Yuehua; Tao, Yi

2009-02-21

A negative relationship between reproductive effort and survival is consistent with life-history. Evolutionary dynamics and evolutionarily stable strategy (ESS) for the trade-off between survival and reproduction are investigated using a simple model with two phenotypes, fearfulness and boldness. The dynamical stability of the pure strategy model and analysis of ESS conditions reveal that: (i) the simple coexistence of fearfulness and boldness is impossible; (ii) a small population size is favorable to fearfulness, but a large population size is favorable to boldness, i.e., neither fearfulness, nor boldness is always favored by natural selection; and (iii) the dynamics of population density is crucial for a proper understanding of the strategy dynamics.

Human population dynamics in Europe over the Last Glacial Maximum.

PubMed

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

2015-07-07

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

Human population dynamics in Europe over the Last Glacial Maximum

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-10-15

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

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

NASA Astrophysics Data System (ADS)

Sánchez Yustos, Policarpo; Diez Martín, Fernando

2015-08-01

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

Interrelations of green oak leaf roller population and common oak: results of 30-year monitoring and mathematical modeling

Treesearch

V. V. Rubtsov; I. A. Utkina

2003-01-01

Long-term monitoring followed by mathematical modeling was used to describe the population dynamics of the green oak leaf roller Tortrix viridana L. over a period of 30 years and to study reactions of oak stands to different levels of defoliation. The mathematical model allows us to forecast the population dynamics of the green oak leaf roller and...

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

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.

How can we model selectively neutral density dependence in evolutionary games.

PubMed

Argasinski, Krzysztof; Kozłowski, Jan

2008-03-01

The problem of density dependence appears in all approaches to the modelling of population dynamics. It is pertinent to classic models (i.e., Lotka-Volterra's), and also population genetics and game theoretical models related to the replicator dynamics. There is no density dependence in the classic formulation of replicator dynamics, which means that population size may grow to infinity. Therefore the question arises: How is unlimited population growth suppressed in frequency-dependent models? Two categories of solutions can be found in the literature. In the first, replicator dynamics is independent of background fitness. In the second type of solution, a multiplicative suppression coefficient is used, as in a logistic equation. Both approaches have disadvantages. The first one is incompatible with the methods of life history theory and basic probabilistic intuitions. The logistic type of suppression of per capita growth rate stops trajectories of selection when population size reaches the maximal value (carrying capacity); hence this method does not satisfy selective neutrality. To overcome these difficulties, we must explicitly consider turn-over of individuals dependent on mortality rate. This new approach leads to two interesting predictions. First, the equilibrium value of population size is lower than carrying capacity and depends on the mortality rate. Second, although the phase portrait of selection trajectories is the same as in density-independent replicator dynamics, pace of selection slows down when population size approaches equilibrium, and then remains constant and dependent on the rate of turn-over of individuals.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Modeling the population dynamics of Pacific yew.

Treesearch

Richard T. Busing; Thomas A. Spies

1995-01-01

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

Unusual dynamics of extinction in a simple ecological model.

PubMed Central

Sinha, S; Parthasarathy, S

1996-01-01

Studies on natural populations and harvesting biological resources have led to the view, commonly held, that (i) populations exhibiting chaotic oscillations run a high risk of extinction; and (ii) a decrease in emigration/exploitation may reduce the risk of extinction. Here we describe a simple ecological model with emigration/depletion that shows behavior in contrast to this. This model displays unusual dynamics of extinction and survival, where populations growing beyond a critical rate can persist within a band of high depletion rates, whereas extinction occurs for lower depletion rates. Though prior to extinction at lower depletion rates the population exhibits chaotic dynamics with large amplitudes of variation and very low minima, at higher depletion rates the population persists at chaos but with reduced variation and increased minima. For still higher values, within the band of persistence, the dynamics show period reversal leading to stability. These results illustrate that chaos does not necessarily lead to population extinction. In addition, the persistence of populations at high depletion rates has important implications in the considerations of strategies for the management of biological resources. PMID:8643661

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

NASA Astrophysics Data System (ADS)

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

2002-06-01

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

Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

PubMed

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

2018-01-01

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.

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

PubMed

Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

2017-04-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

Numerical modeling of mosquito population dynamics of Aedes aegypti.

PubMed

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

2018-04-16

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

Olive Fruit Fly (Bactrocera oleae) Population Dynamics in the Eastern Mediterranean: Influence of Exogenous Uncertainty on a Monophagous Frugivorous Insect

PubMed Central

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

2015-01-01

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

The spatial dynamics of ecosystem engineers.

PubMed

Franco, Caroline; Fontanari, José F

2017-10-01

The changes on abiotic features of ecosystems have rarely been taken into account by population dynamics models, which typically focus on trophic and competitive interactions between species. However, understanding the population dynamics of organisms that must modify their habitats in order to survive, the so-called ecosystem engineers, requires the explicit incorporation of abiotic interactions in the models. Here we study a model of ecosystem engineers that is discrete both in space and time, and where the engineers and their habitats are arranged in patches fixed to the sites of regular lattices. The growth of the engineer population is modeled by Ricker equation with a density-dependent carrying capacity that is given by the number of modified habitats. A diffusive dispersal stage ensures that a fraction of the engineers move from their birth patches to neighboring patches. We find that dispersal influences the metapopulation dynamics only in the case that the local or single-patch dynamics exhibit chaotic behavior. In that case, it can suppress the chaotic behavior and avoid extinctions in the regime of large intrinsic growth rate of the population. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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

Crone, E.E.

1995-11-08

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

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

USGS Publications Warehouse

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

2006-01-01

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

Interacting Effects of Newcastle Disease Transmission and Illegal Trade on a Wild Population of White-Winged Parakeets in Peru: A Modeling Approach

PubMed Central

Daut, Elizabeth F.; Lahodny, Glenn; Peterson, Markus J.; Ivanek, Renata

2016-01-01

Illegal wildlife-pet trade can threaten wildlife populations directly from overharvest, but also indirectly as a pathway for introduction of infectious diseases. This study evaluated consequences of a hypothetical introduction of Newcastle disease (ND) into a wild population of Peru’s most trafficked psittacine, the white-winged parakeet (Brotogeris versicolurus), through release of infected confiscated individuals. We developed two mathematical models that describe ND transmission and the influence of illegal harvest in a homogeneous (model 1) and age-structured population of parakeets (model 2). Infection transmission dynamics and harvest were consistent for all individuals in model 1, which rendered it mathematically more tractable compared to the more complex, age-structured model 2 that separated the host population into juveniles and adults. We evaluated the interaction of ND transmission and harvest through changes in the basic reproduction number (R0) and short-term host population dynamics. Our findings demonstrated that ND introduction would likely provoke considerable disease-related mortality, up to 24% population decline in two years, but high harvest rates would dampen the magnitude of the outbreak. Model 2 produced moderate differences in disease dynamics compared to model 1 (R0 = 3.63 and 2.66, respectively), but highlighted the importance of adult disease dynamics in diminishing the epidemic potential. Therefore, we suggest that future studies should use a more realistic, age-structured model. Finally, for the presumptive risk that illegal trade of white-winged parakeets could introduce ND into wild populations, our results suggest that while high harvest rates may have a protective effect on the population by reducing virus transmission, the combined effects of high harvest and disease-induced mortality may threaten population survival. These results capture the complexity and consequences of the interaction between ND transmission and harvest in a wild parrot population and highlight the importance of preventing illegal trade. PMID:26816214

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Dynamic regimes of local homogeneous population model with time lag

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

Neverova, Galina; Frisman, Efim

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

A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations

PubMed Central

Tran, Annelise; L’Ambert, Grégory; Lacour, Guillaume; Benoît, Romain; Demarchi, Marie; Cros, Myriam; Cailly, Priscilla; Aubry-Kientz, Mélaine; Balenghien, Thomas; Ezanno, Pauline

2013-01-01

The mosquito Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) is an invasive species which has colonized Southern Europe in the last two decades. As it is a competent vector for several arboviruses, its spread is of increasing public health concern, and there is a need for appropriate monitoring tools. In this paper, we have developed a modelling approach to predict mosquito abundance over time, and identify the main determinants of mosquito population dynamics. The model is temperature- and rainfall-driven, takes into account egg diapause during unfavourable periods, and was used to model the population dynamics of Ae. albopictus in the French Riviera since 2008. Entomological collections of egg stage from six locations in Nice conurbation were used for model validation. We performed a sensitivity analysis to identify the key parameters of the mosquito population dynamics. Results showed that the model correctly predicted entomological field data (Pearson r correlation coefficient values range from 0.73 to 0.93). The model’s main control points were related to adult’s mortality rates, the carrying capacity in pupae of the environment, and the beginning of the unfavourable period. The proposed model can be efficiently used as a tool to predict Ae. albopictus population dynamics, and to assess the efficiency of different control strategies. PMID:23624579

Heterogeneous Structure of Stem Cells Dynamics: Statistical Models and Quantitative Predictions

PubMed Central

Bogdan, Paul; Deasy, Bridget M.; Gharaibeh, Burhan; Roehrs, Timo; Marculescu, Radu

2014-01-01

Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics. PMID:24769917

The effect of seasonal harvesting on stage-structured population models.

PubMed

Tang, Sanyi; Chen, Lansun

2004-04-01

In most models of population dynamics, increases in population due to birth are assumed to be time-independent, but many species reproduce only during a single period of the year. We propose an exploited single-species model with stage structure for the dynamics in a fish population for which births occur in a single pulse once per time period. Since birth pulse populations are often characterized with a discrete time dynamical system determined by its Poincaré map, we explore the consequences of harvest timing to equilibrium population sizes under seasonal dependence and obtain threshold conditions for their stability, and show that the timing of harvesting has a strong impact on the persistence of the fish population, on the volume of mature fish stock and on the maximum annual-sustainable yield. Moreover, our results imply that the population can sustain much higher harvest rates if the mature fish is removed as early in the season (after the birth pulse) as possible. Further, the effects of harvesting effort and harvest timing on the dynamical complexity are also investigated. Bifurcation diagrams are constructed with the birth rate (or harvesting effort or harvest timing) as the bifurcation parameter, and these are observed to display rich structure, including chaotic bands with periodic windows, pitch-fork and tangent bifurcations, non-unique dynamics (meaning that several attractors coexist) and attractor crisis. This suggests that birth pulse, in effect, provides a natural period or cyclicity that makes the dynamical behavior more complex.

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

NASA Astrophysics Data System (ADS)

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 computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Population dynamics of minimally cognitive individuals. Part I: Introducing knowledge into the dynamics

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

Schmieder, R.W.

The author presents a new approach for modeling the dynamics of collections of objects with internal structure. Based on the fact that the behavior of an individual in a population is modified by its knowledge of other individuals, a procedure for accounting for knowledge in a population of interacting objects is presented. It is assumed that each object has partial (or complete) knowledge of some (or all) other objects in the population. The dynamical equations for the objects are then modified to include the effects of this pairwise knowledge. This procedure has the effect of projecting out what the populationmore » will do from the much larger space of what it could do, i.e., filtering or smoothing the dynamics by replacing the complex detailed physical model with an effective model that produces the behavior of interest. The procedure therefore provides a minimalist approach for obtaining emergent collective behavior. The use of knowledge as a dynamical quantity, and its relationship to statistical mechanics, thermodynamics, information theory, and cognition microstructure are discussed.« less

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

PubMed

Keith, David A; Akçakaya, H Resit; Thuiller, Wilfried; Midgley, Guy F; Pearson, Richard G; Phillips, Steven J; Regan, Helen M; Araújo, Miguel B; Rebelo, Tony G

2008-10-23

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Assessing the importance of self-regulating mechanisms in diamondback moth population dynamics: application of discrete mathematical models.

PubMed

Nedorezov, Lev V; Löhr, Bernhard L; Sadykova, Dinara L

2008-10-07

The applicability of discrete mathematical models for the description of diamondback moth (DBM) (Plutella xylostella L.) population dynamics was investigated. The parameter values for several well-known discrete time models (Skellam, Moran-Ricker, Hassell, Maynard Smith-Slatkin, and discrete logistic models) were estimated for an experimental time series from a highland cabbage-growing area in eastern Kenya. For all sets of parameters, boundaries of confidence domains were determined. Maximum calculated birth rates varied between 1.086 and 1.359 when empirical values were used for parameter estimation. After fitting of the models to the empirical trajectory, all birth rate values resulted considerably higher (1.742-3.526). The carrying capacity was determined between 13.0 and 39.9DBM/plant, after fitting of the models these values declined to 6.48-9.3, all values well within the range encountered empirically. The application of the Durbin-Watson criteria for comparison of theoretical and experimental population trajectories produced negative correlations with all models. A test of residual value groupings for randomness showed that their distribution is non-stochastic. In consequence, we conclude that DBM dynamics cannot be explained as a result of intra-population self-regulative mechanisms only (=by any of the models tested) and that more comprehensive models are required for the explanation of DBM population dynamics.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

PubMed Central

Jacobs, Matthieu; Grégoire, Nicolas; Couet, William; Bulitta, Jurgen B.

2016-01-01

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 ultimately patients. PMID:26967893

Forecasting climate change impacts on plant populations over large spatial extents

DOE PAGES

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...

2016-10-24

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

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

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.

2016-01-01

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.

A Global Picture of the Gamma-Ricker Map: A Flexible Discrete-Time Model with Factors of Positive and Negative Density Dependence.

PubMed

Liz, Eduardo

2018-02-01

The gamma-Ricker model is one of the more flexible and general discrete-time population models. It is defined on the basis of the Ricker model, introducing an additional parameter [Formula: see text]. For some values of this parameter ([Formula: see text], population is overcompensatory, and the introduction of an additional parameter gives more flexibility to fit the stock-recruitment curve to field data. For other parameter values ([Formula: see text]), the gamma-Ricker model represents populations whose per-capita growth rate combines both negative density dependence and positive density dependence. The former can lead to overcompensation and dynamic instability, and the latter can lead to a strong Allee effect. We study the impact of the cooperation factor in the dynamics and provide rigorous conditions under which increasing the Allee effect strength stabilizes or destabilizes population dynamics, promotes or prevents population extinction, and increases or decreases population size. Our theoretical results also include new global stability criteria and a description of the possible bifurcations.

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

PubMed

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

2012-01-01

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

Climate Effects and Feedback Structure Determining Weed Population Dynamics in a Long-Term Experiment

PubMed Central

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

2012-01-01

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

Biophysical model for assessment of risk of acute exposures in combination with low level chronic irradiation

NASA Astrophysics Data System (ADS)

Smirnova, O. A.

A biophysical model is developed which describes the mortality dynamics in mammalian populations unexposed and exposed to radiation The model relates statistical biometric functions mortality rate life span probability density and life span probability with statistical characteristics and dynamics of a critical body system in individuals composing the population The model describing the dynamics of thrombocytopoiesis in nonirradiated and irradiated mammals is also developed this hematopoietic line being considered as the critical body system under exposures in question The mortality model constructed in the framework of the proposed approach was identified to reproduce the irradiation effects on populations of mice The most parameters of the thrombocytopoiesis model were determined from the data available in the literature on hematology and radiobiology the rest parameters were evaluated by fitting some experimental data on the dynamics of this system in acutely irradiated mice The successful verification of the thrombocytopoiesis model was fulfilled by the quantitative juxtaposition of the modeling predictions and experimental data on the dynamics of this system in mice exposed to either acute or chronic irradiation at wide ranges of doses and dose rates It is important that only experimental data on the mortality rate in nonirradiated population and the relevant statistical characteristics of the thrombocytopoiesis system in mice which are also available in the literature on radiobiology are needed for the final identification of

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

Treesearch

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

2017-01-01

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

Understanding Past Population Dynamics: Bayesian Coalescent-Based Modeling with Covariates

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-03-01

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

Accommodating environmental variation in population models: metaphysiological biomass loss accounting.

PubMed

Owen-Smith, Norman

2011-07-01

1. There is a pressing need for population models that can reliably predict responses to changing environmental conditions and diagnose the causes of variation in abundance in space as well as through time. In this 'how to' article, it is outlined how standard population models can be modified to accommodate environmental variation in a heuristically conducive way. This approach is based on metaphysiological modelling concepts linking populations within food web contexts and underlying behaviour governing resource selection. Using population biomass as the currency, population changes can be considered at fine temporal scales taking into account seasonal variation. Density feedbacks are generated through the seasonal depression of resources even in the absence of interference competition. 2. Examples described include (i) metaphysiological modifications of Lotka-Volterra equations for coupled consumer-resource dynamics, accommodating seasonal variation in resource quality as well as availability, resource-dependent mortality and additive predation, (ii) spatial variation in habitat suitability evident from the population abundance attained, taking into account resource heterogeneity and consumer choice using empirical data, (iii) accommodating population structure through the variable sensitivity of life-history stages to resource deficiencies, affecting susceptibility to oscillatory dynamics and (iv) expansion of density-dependent equations to accommodate various biomass losses reducing population growth rate below its potential, including reductions in reproductive outputs. Supporting computational code and parameter values are provided. 3. The essential features of metaphysiological population models include (i) the biomass currency enabling within-year dynamics to be represented appropriately, (ii) distinguishing various processes reducing population growth below its potential, (iii) structural consistency in the representation of interacting populations and (iv) capacity to accommodate environmental variation in space as well as through time. Biomass dynamics provide a common currency linking behavioural, population and food web ecology. 4. Metaphysiological biomass loss accounting provides a conceptual framework more conducive for projecting and interpreting the population consequences of climatic shifts and human transformations of habitats than standard modelling approaches. © 2011 The Author. Journal of Animal Ecology © 2011 British Ecological Society.

The impact of natural transformation on adaptation in spatially structured bacterial populations.

PubMed

Moradigaravand, Danesh; Engelstädter, Jan

2014-06-20

Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations.

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

PubMed Central

Lindström, J; Kokko, H

1998-01-01

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

The role of weak selection and high mutation rates in nearly neutral evolution.

PubMed

Lawson, Daniel John; Jensen, Henrik Jeldtoft

2009-04-21

Neutral dynamics occur in evolution if all types are 'effectively equal' in their reproductive success, where the definition of 'effectively equal' depends on the population size and the details of mutations. Empirically observed neutral genetic evolution in extremely large clonal populations can only be explained under current models if selection is completely absent. Such models typically consider the case where population dynamics occurs on a different timescale to evolution. However, this assumption is invalid when mutations are not rare in a whole population. We show that this has important consequences for the occurrence of neutral evolution in clonal populations. In highly connected type spaces, neutral dynamics can occur for all population sizes despite significant selective differences, via the forming of effectively neutral networks connecting rare neutral types. Biological implications include an explanation for the high diversity of rare types that survive in large clonal populations, and a theoretical justification for the use of neutral null models.

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

PubMed

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

2013-04-01

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

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

PubMed Central

Gerstner, Wulfram

2017-01-01

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957

Modeling structured population dynamics using data from unmarked individuals

USGS Publications Warehouse

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

2014-01-01

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

Model reduction for agent-based social simulation: coarse-graining a civil violence model.

PubMed

Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Model reduction for agent-based social simulation: Coarse-graining a civil violence model

NASA Astrophysics Data System (ADS)

Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

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

PubMed Central

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

2012-01-01

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

Development of conceptual ecological models linking management of the Missouri River to pallid sturgeon population dynamics

USGS Publications Warehouse

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

2015-01-01

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

Differential Equation Models for Sharp Threshold Dynamics

DTIC Science & Technology

2012-08-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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.

Immune Response to a Variable Pathogen: A Stochastic Model with Two Interlocked Darwinian Entities

PubMed Central

Kuhn, Christoph

2012-01-01

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

Immune response to a variable pathogen: a stochastic model with two interlocked Darwinian entities.

PubMed

Kuhn, Christoph

2012-01-01

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

Modeling wildlife populations with HexSim

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications including population viability analysis for on...

A Theoretical Approach to Understanding Population Dynamics with Seasonal Developmental Durations

NASA Astrophysics Data System (ADS)

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.

Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

PubMed

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

2017-08-22

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

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

PubMed

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.

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

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

A dynamic life table model of Psorophora columbiae in the southern Louisiana rice agroecosystem with supporting hydrologic submodel. Part 1. Analysis of literature and model development.

PubMed

Focks, D A; McLaughlin, R E; Smith, B M

1988-09-01

During the past decade, the rice agroecosystem and its associated mosquitoes have been the subject of an extensive research effort directed toward the development and implementation of integrated pest management (IPM) strategies. The objective of this work was to synthesize the literature and unpublished data on the rice agroecosystem into a comprehensive simulation model of the key elements of the system known to influence the population dynamics of Psorophora columbiae. Subsequent companion papers will present a validation of these models, provide an in-depth analysis of the population dynamics of Ps. columbiae, and evaluate current and proposed IPM strategies for this mosquito. This paper describes the development of 2 models: WaterMod: Because spatial and temporal distributions of surface water and soil moisture play a decisive role in the dynamics of Ps. columbiae, an essentially hydrological simulator was developed. Its purpose is to provide environmental inputs for a second model (PcSim) which simulates the population dynamics of Ps. columbiae. WaterMod utilizes data on weather, agricultural practices, and soil characteristics for a particular region to generate a data set containing daily estimates of soil moisture and depth of water table for 12 representative areas comprising the rice agroecosystem. This model could be used to provide hydrologic inputs for additional simulation models of other riceland mosquito species. PcSim: This model simulates the population dynamics of Ps. columbiae by using the computer to maintain a daily accounting of the absolute number of mosquitoes within each daily age class for each life stage. The model creates estimates of the number of eggs, larvae, pupae, and adults for a representative l-ha area of a rice agroecosystem.

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

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

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

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

Growth history and crown vine coverage are principal factors influencing growth and mortality rates of big-leaf mahogany Swietenia macrophylla in Brazil

Treesearch

James Grogan; R. Matthew Landis

2009-01-01

1. Current efforts to model population dynamics of high-value tropical timber species largely assume that individual growth history is unimportant to population dynamics, yet growth autocorrelation is known to adversely affect model predictions. In this study, we analyse a decade of annual census data from a natural population of big-leaf mahogany Swietenia macrophylla...

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

PubMed

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

2016-01-01

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

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

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

Effects of an invasive plant on population dynamics in toads.

PubMed

Greenberg, Daniel A; Green, David M

2013-10-01

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

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

PubMed Central

Huntsman, Brock M.; Petty, J. Todd

2014-01-01

Spatial population models predict strong density-dependence and relatively stable population dynamics near the core of a species' distribution with increasing variance and importance of density-independent processes operating towards the population periphery. Using a 10-year data set and an information-theoretic approach, we tested a series of candidate models considering density-dependent and density-independent controls on brook trout population dynamics across a core-periphery distribution gradient within a central Appalachian watershed. We sampled seven sub-populations with study sites ranging in drainage area from 1.3–60 km2 and long-term average densities ranging from 0.335–0.006 trout/m. Modeled response variables included per capita population growth rate of young-of-the-year, adult, and total brook trout. We also quantified a stock-recruitment relationship for the headwater population and coefficients of variability in mean trout density for all sub-populations over time. Density-dependent regulation was prevalent throughout the study area regardless of stream size. However, density-independent temperature models carried substantial weight and likely reflect the effect of year-to-year variability in water temperature on trout dispersal between cold tributaries and warm main stems. Estimated adult carrying capacities decreased exponentially with increasing stream size from 0.24 trout/m in headwaters to 0.005 trout/m in the main stem. Finally, temporal variance in brook trout population size was lowest in the high-density headwater population, tended to peak in mid-sized streams and declined slightly in the largest streams with the lowest densities. Our results provide support for the hypothesis that local density-dependent processes have a strong control on brook trout dynamics across the entire distribution gradient. However, the mechanisms of regulation likely shift from competition for limited food and space in headwater streams to competition for thermal refugia in larger main stems. It also is likely that source-sink dynamics and dispersal from small headwater habitats may partially influence brook trout population dynamics in the main stem. PMID:24618602

Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

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

2012-05-01

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

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

PubMed

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

2013-11-01

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

Public goods games in populations with fluctuating size.

PubMed

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

2018-05-01

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

Collective Dynamics for Heterogeneous Networks of Theta Neurons

NASA Astrophysics Data System (ADS)

Luke, Tanushree

Collective behavior in neural networks has often been used as an indicator of communication between different brain areas. These collective synchronization and desynchronization patterns are also considered an important feature in understanding normal and abnormal brain function. To understand the emergence of these collective patterns, I create an analytic model that identifies all such macroscopic steady-states attainable by a network of Type-I neurons. This network, whose basic unit is the model "theta'' neuron, contains a mixture of excitable and spiking neurons coupled via a smooth pulse-like synapse. Applying the Ott-Antonsen reduction method in the thermodynamic limit, I obtain a low-dimensional evolution equation that describes the asymptotic dynamics of the macroscopic mean field of the network. This model can be used as the basis in understanding more complicated neuronal networks when additional dynamical features are included. From this reduced dynamical equation for the mean field, I show that the network exhibits three collective attracting steady-states. The first two are equilibrium states that both reflect partial synchronization in the network, whereas the third is a limit cycle in which the degree of network synchronization oscillates in time. In addition to a comprehensive identification of all possible attracting macro-states, this analytic model permits a complete bifurcation analysis of the collective behavior of the network with respect to three key network features: the degree of excitability of the neurons, the heterogeneity of the population, and the overall coupling strength. The network typically tends towards the two macroscopic equilibrium states when the neuron's intrinsic dynamics and the network interactions reinforce each other. In contrast, the limit cycle state, bifurcations, and multistability tend to occur when there is competition between these network features. I also outline here an extension of the above model where the neurons' excitability now varies in time sinuosoidally, thus simulating a parabolic bursting network. This time-varying excitability can lead to the emergence of macroscopic chaos and multistability in the collective behavior of the network. Finally, I expand the single population model described above to examine a two-population neuronal network where each population has its own unique mixture of excitable and spiking neurons, as well as its own coupling strength (either excitatory or inhibitory in nature). Specifically, I consider the situation where the first population is only allowed to influence the second population without any feedback, thus effectively creating a feed-forward "driver-response" system. In this special arrangement, the driver's asymptotic macroscopic dynamics are fully explored in the comprehensive analysis of the single population. Then, in the presence of an influence from the driver, the modified dynamics of the second population, which now acts as a response population, can also be fully analyzed. As in the time-varying model, these modifications give rise to richer dynamics to the response population than those found from the single population formalism, including multi-periodicity and chaos.

Mapping migratory flyways in Asia using dynamic Brownian bridge movement models

USGS Publications Warehouse

Palm, E.C.; Newman, S.H.; Prosser, Diann J.; Xiao, Xiangming; Luo, Ze; Batbayar, Nyambayar; Balachandran, Sivananinthaperumal; Takekawa, John Y.

2015-01-01

The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.

Population turnover and adaptation in heterogeneous environments

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Stochastic gain in finite populations

NASA Astrophysics Data System (ADS)

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

2008-08-01

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

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

PubMed

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-11-01

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Resource-driven changes to host population stability alter the evolution of virulence and transmission.

PubMed

Hite, Jessica L; Cressler, Clayton E

2018-05-05

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

Bighorn sheep habitat studies, population dynamics, and population modeling in Bighorn Canyon National Recreation Area, Wyoming and Montana, 2000-2003

USGS Publications Warehouse

Singer, Francis J.; Schoenecker, Kathryn A.

2004-01-01

The bighorn sheep population of the greater Bighorn Canyon National Recreation Area (BICA) was extirpated in the 1800s, and then reintroduced in 1973. The herd increased to a peak population of about 211 animals (Kissell and others, 1996), but then declined sharply in 1995 and 1996. Causes for the decline were unknown. Numbers have remained around 100 ± 20 animals since 1998. Previous modeling efforts determined what areas were suitable bighorn sheep habitat (Gudorf and others, 1996). We tried to determine why sheep were not using areas that were modeled as suitable or acceptable habitat, and to evaluate population dynamics of the herd.

A Markov chain model for studying suicide dynamics: an illustration of the Rose theorem

PubMed Central

2014-01-01

Background High-risk strategies would only have a modest effect on suicide prevention within a population. It is best to incorporate both high-risk and population-based strategies to prevent suicide. This study aims to compare the effectiveness of suicide prevention between high-risk and population-based strategies. Methods A Markov chain illness and death model is proposed to determine suicide dynamic in a population and examine its effectiveness for reducing the number of suicides by modifying certain parameters of the model. Assuming a population with replacement, the suicide risk of the population was estimated by determining the final state of the Markov model. Results The model shows that targeting the whole population for suicide prevention is more effective than reducing risk in the high-risk tail of the distribution of psychological distress (i.e. the mentally ill). Conclusions The results of this model reinforce the essence of the Rose theorem that lowering the suicidal risk in the population at large may be more effective than reducing the high risk in a small population. PMID:24948330

Population Modelling with M&M's[R

ERIC Educational Resources Information Center

Winkel, Brian

2009-01-01

Several activities in which population dynamics can be modelled by tossing M&M's[R] candy are presented. Physical activities involving M&M's[R] can be modelled by difference equations and several population phenomena, including death and immigration, are studied. (Contains 1 note.)

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

PubMed

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

2016-10-01

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

Population Dynamics of an Insect Herbivore over 32 Years are Driven by Precipitation and Host-Plant Effects: Testing Model Predictions.

PubMed

Price, Peter W; Hunter, Mark D

2015-06-01

The interaction between the arroyo willow, Salix lasiolepis Bentham, and its specialist herbivore, the arroyo willow stem-galling sawfly, Euura lasiolepis Smith (Hymenoptera: Tenthredinidae), was studied for 32 yr in Flagstaff, AZ, emphasizing a mechanistic understanding of insect population dynamics. Long-term weather records were evaluated to provide a climatic context for this study. Previously, predictive models of sawfly dynamics were developed from estimates of sawfly gall density made between 1981 and 2002; one model each for drier and wetter sites. Predictor variables in these models included winter precipitation and the Palmer Drought Severity Index, which impact the willow growth, with strong bottom-up effects on sawflies. We now evaluate original model predictions of sawfly population dynamics using new data (from 2003-2012). Additionally, willow resources were evaluated in 1986 and in 2012, using as criteria clone area, shoot density, and shoot length. The dry site model accounted for 40% of gall population density variation between 2003 and 2012 (69% over the 32 yr), providing strong support for the bottom-up, mechanistic hypothesis that water supply to willow hosts impacts sawfly populations. The current drying trend stressed willow clones: in drier sites, willow resources declined and gall density decreased by 98%. The wet site model accounted for 23% of variation in gall population density between 2003 and 2012 (48% over 30 yr), consistent with less water limitation. Nonetheless, gall populations were reduced by 72%. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.

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

PubMed

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

2012-01-01

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

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

PubMed

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.

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

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

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

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

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

Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish.

PubMed

Sakaris, Peter C; Irwin, Elise R

2010-03-01

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotic fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

In the context of proactive disaster risk as well as immediate situational crisis management knowledge of locational social aspects in terms of spatio-temporal population distribution dynamics is considered among the most important factors for disaster impact minimization (Aubrecht et al., 2013a). This applies to both the pre-event stage for designing appropriate preparedness measures and to acute crisis situations when an event chain actually unfolds for efficient situation-aware response. The presented DynaPop population dynamics model is developed at the interface of those interlinked crisis stages and aims at providing basic input for social impact evaluation and decision support in crisis management. The model provides the starting point for assessing population exposure dynamics - thus here labeled as DynaPop-X - which can either be applied in a sense of illustrating the changing locations and numbers of affected people at different stages during an event or as ex-ante estimations of probable and maximum expected clusters of affected population (Aubrecht et al., 2013b; Freire & Aubrecht, 2012). DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation (Ahola et al., 2007; Bhaduri, 2008; Cockings et al., 2010). We will present ongoing developments particularly focusing on the implementation logic of the model using the emikat software tool, a data management system initially designed for inventorying and analysis of spatially resolved regional air pollutant emission scenarios. This study was performed in the framework of the EU CRISMA project. CRISMA is funded from the European Community's Seventh Framework Programme FP7/2007-2013 under grant agreement no. 284552. REFERENCES Ahola, T., Virrantaus, K., Krisp, J.K., Hunter, G.J. (2007) A spatio-temporal population model to support risk assessment and damage analysis for decision-making. International Journal of Geographical Information Science, 21(8), 935-953. Aubrecht, C., Fuchs, S., Neuhold, C. (2013a) Spatio-temporal aspects and dimensions in integrated disaster risk management. Natural Hazards, 68(3), 1205-1216. Aubrecht, C., Özceylan, D., Steinnocher, K., Freire, S. (2013b) Multi-level geospatial modeling of human exposure patterns and vulnerability indicators. Natural Hazards, 68(1), 147-163. Bhaduri, B. (2008) Population distribution during the day. In S. Shekhar & X. Hui, eds., Encyclopedia of GIS. Springer US, 880-885. Cockings, S., Martin, D. & Leung, S. (2010) Population 24/7: building space-time specific population surface models. In M. Haklay, J. Morley, & H. Rahemtulla, eds., Proceedings of the GIS Research UK 18th Annual conference. GISRUK 2010. London, UK, 41-47. Freire, S., Aubrecht, C. (2012) Integrating population dynamics into mapping human exposure to seismic hazard. Natural Hazards and Earth System Sciences, 12(11), 3533-3543.

Structural stability of nonlinear population dynamics.

PubMed

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

NASA Astrophysics Data System (ADS)

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.

An open-population hierarchical distance sampling model

USGS Publications Warehouse

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

2015-01-01

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

An open-population hierarchical distance sampling model.

PubMed

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

2015-02-01

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

Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics

PubMed Central

Puelma Touzel, Maximilian; Wolf, Fred

2015-01-01

The response of a neuronal population over a space of inputs depends on the intrinsic properties of its constituent neurons. Two main modes of single neuron dynamics–integration and resonance–have been distinguished. While resonator cell types exist in a variety of brain areas, few models incorporate this feature and fewer have investigated its effects. To understand better how a resonator’s frequency preference emerges from its intrinsic dynamics and contributes to its local area’s population firing rate dynamics, we analyze the dynamic gain of an analytically solvable two-degree of freedom neuron model. In the Fokker-Planck approach, the dynamic gain is intractable. The alternative Gauss-Rice approach lifts the resetting of the voltage after a spike. This allows us to derive a complete expression for the dynamic gain of a resonator neuron model in terms of a cascade of filters on the input. We find six distinct response types and use them to fully characterize the routes to resonance across all values of the relevant timescales. We find that resonance arises primarily due to slow adaptation with an intrinsic frequency acting to sharpen and adjust the location of the resonant peak. We determine the parameter regions for the existence of an intrinsic frequency and for subthreshold and spiking resonance, finding all possible intersections of the three. The expressions and analysis presented here provide an account of how intrinsic neuron dynamics shape dynamic population response properties and can facilitate the construction of an exact theory of correlations and stability of population activity in networks containing populations of resonator neurons. PMID:26720924

Ruffed grouse population dynamics in the central and southern Appalachians

Treesearch

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

2006-01-01

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

Population dynamics of Dactylella oviparasitica and Heterodera schachtii: Toward a decision model for sugar beet planting

USDA-ARS?s Scientific Manuscript database

A series of investigations were performed to examine the population dynamics of the sugarbeet cyst nematode, Heterodera schachtii, and the nematophagus fungus Dactylella oviparasitica. After two nematode generations, the population densities of H. schachtii were measured in relation to various initi...

Mathematical Modeling of Extinction of Inhomogeneous Populations

PubMed Central

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

The proper treatment of language acquisition and change in a population setting.

PubMed

Niyogi, Partha; Berwick, Robert C

2009-06-23

Language acquisition maps linguistic experience, primary linguistic data (PLD), onto linguistic knowledge, a grammar. Classically, computational models of language acquisition assume a single target grammar and one PLD source, the central question being whether the target grammar can be acquired from the PLD. However, real-world learners confront populations with variation, i.e., multiple target grammars and PLDs. Removing this idealization has inspired a new class of population-based language acquisition models. This paper contrasts 2 such models. In the first, iterated learning (IL), each learner receives PLD from one target grammar but different learners can have different targets. In the second, social learning (SL), each learner receives PLD from possibly multiple targets, e.g., from 2 parents. We demonstrate that these 2 models have radically different evolutionary consequences. The IL model is dynamically deficient in 2 key respects. First, the IL model admits only linear dynamics and so cannot describe phase transitions, attested rapid changes in languages over time. Second, the IL model cannot properly describe the stability of languages over time. In contrast, the SL model leads to nonlinear dynamics, bifurcations, and possibly multiple equilibria and so suffices to model both the case of stable language populations, mixtures of more than 1 language, as well as rapid language change. The 2 models also make distinct, empirically testable predictions about language change. Using historical data, we show that the SL model more faithfully replicates the dynamics of the evolution of Middle English.

Ecological change points: The strength of density dependence and the loss of history.

PubMed

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

2018-05-01

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

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

PubMed

Leaman, Eric J; Geuther, Brian Q; Behkam, Bahareh

2018-04-20

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

Predictive Modeling of Rice Yellow Stem Borer Population Dynamics under Climate Change Scenarios in Indramayu

NASA Astrophysics Data System (ADS)

Nurhayati, E.; Koesmaryono, Y.; Impron

2017-03-01

Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.

Integrating host, natural enemy, and other processes in population models of the pine sawfly

Treesearch

A. A. Sharov

1991-01-01

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

Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

Computer simulation of the coffee leaf miner using sexual Penna aging model

NASA Astrophysics Data System (ADS)

de Oliveira, A. C. S.; Martins, S. G. F.; Zacarias, M. S.

2008-01-01

Forecast models based on climatic conditions are of great interest in Integrated Pest Management (IPM) programs. The success of these models depends, among other factors, on the knowledge of the temperature effect on the pests’ population dynamics. In this direction, a computer simulation was made for the population dynamics of the coffee leaf miner, L. coffeella, at different temperatures, considering experimental data relative to the pest. The age structure was inserted into the dynamics through sexual Penna Model. The results obtained, such as life expectancy, growth rate and annual generations’ number, in agreement to those in laboratory and field conditions, show that the simulation can be used as a forecast model for controlling L. coffeella.

Population dynamics of HIV-1 inferred from gene sequences.

PubMed Central

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

1999-01-01

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

Bivalves: From individual to population modelling

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Population dynamics and the economics of invasive species management: the greenhouse whitefly in California-grown strawberries.

PubMed

McKee, Gregory J; Goodhue, Rachael E; Zalom, Frank G; Carter, Colin A; Chalfant, James A

2009-01-01

In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.

Machine Vision Within The Framework Of Collective Neural Assemblies

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1990-03-01

The proposed mechanism for designing a robust machine vision system is based on the dynamic activity generated by the various neural populations embedded in nervous tissue. It is postulated that a hierarchy of anatomically distinct tissue regions are involved in visual sensory information processing. Each region may be represented as a planar sheet of densely interconnected neural circuits. Spatially localized aggregates of these circuits represent collective neural assemblies. Four dynamically coupled neural populations are assumed to exist within each assembly. In this paper we present a state-variable model for a tissue sheet derived from empirical studies of population dynamics. Each population is modelled as a nonlinear second-order system. It is possible to emulate certain observed physiological and psychophysiological phenomena of biological vision by properly programming the interconnective gains . Important early visual phenomena such as temporal and spatial noise insensitivity, contrast sensitivity and edge enhancement will be discussed for a one-dimensional tissue model.

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

PubMed

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

2017-03-01

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

Incorporating evolutionary processes into population viability models.

PubMed

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

2015-06-01

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

A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability and sensitivity in pediatric planovalgus feet.

PubMed

Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B; D'Astous, Jacques L

2013-01-01

Several multisegment foot models have been proposed and some have been used to study foot pathologies. These models have been tested and validated on typically developed populations; however application of such models to feet with significant deformities presents an additional set of challenges. For the first time, in this study, a multisegment foot model is tested for repeatability in a population of children with symptomatic abnormal feet. The results from this population are compared to the same metrics collected from an age matched (8-14 years) typically developing population. The modified Shriners Hospitals for Children, Greenville (mSHCG) foot model was applied to ten typically developing children and eleven children with planovalgus feet by two clinicians. Five subjects in each group were retested by both clinicians after 4-6 weeks. Both intra-clinician and inter-clinician repeatability were evaluated using static and dynamic measures. A plaster mold method was used to quantify variability arising from marker placement error. Dynamic variability was measured by examining trial differences from the same subjects when multiple clinicians carried out the data collection multiple times. For hindfoot and forefoot angles, static and dynamic variability in both groups was found to be less than 4° and 6° respectively. The mSHCG model strategy of minimal reliance on anatomical markers for dynamic measures and inherent flexibility enabled by separate anatomical and technical coordinate systems resulted in a model equally repeatable in typically developing and planovalgus populations. Copyright © 2012 Elsevier B.V. All rights reserved.

Adaptive modeling of viral diseases in bats with a focus on rabies.

PubMed

Dimitrov, Dobromir T; Hallam, Thomas G; Rupprecht, Charles E; McCracken, Gary F

2008-11-07

Many emerging and reemerging viruses, such as rabies, SARS, Marburg, and Ebola have bat populations as disease reservoirs. Understanding the spillover from bats to humans and other animals, and the associated health risks requires an analysis of the disease dynamics in bat populations. Traditional compartmental epizootic models, which are relatively easy to implement and analyze, usually impose unrealistic aggregation assumptions about disease-related structure and depend on parameters that frequently are not measurable in field conditions. We propose a novel combination of computational and adaptive modeling approaches that address the maintenance of emerging diseases in bat colonies through individual (intra-host) models of the response of the host to a viral challenge. The dynamics of the individual models are used to define survival, susceptibility and transmission conditions relevant to epizootics as well as to develop and parametrize models of the disease evolution into uniform and diverse populations. Applications of the proposed approach to modeling the effects of immunological heterogeneity on the dynamics of bat rabies are presented.

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

PubMed

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.

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

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

History of research on modelling gypsy moth population ecology

Treesearch

J. J. Colbert

1991-01-01

History of research to develop models of gypsy moth population dynamics and some related studies are described. Empirical regression-based models are reviewed, and then the more comprehensive process models are discussed. Current model- related research efforts are introduced.

Comparing estimates of population change from occupancy and mark-recapture models for a territorial species

Treesearch

Mary M. Conner; John J. Keane; Claire V. Gallagher; Thomas E. Munton; Paula A. Shaklee

2016-01-01

Monitoring studies often use marked animals to estimate population abundance at small spatial scales. However, at smaller scales, occupancy sampling, which uses detection/nondetection data, may be useful where sites are approximately territories, and occupancy dynamics should be strongly correlated with population dynamics. Occupancy monitoring has advantages...

Beverton-Holt discrete pest management models with pulsed chemical control and evolution of pesticide resistance

NASA Astrophysics Data System (ADS)

Liang, Juhua; Tang, Sanyi; Cheke, Robert A.

2016-07-01

Pest resistance to pesticides is usually managed by switching between different types of pesticides. The optimal switching time, which depends on the dynamics of the pest population and on the evolution of the pesticide resistance, is critical. Here we address how the dynamic complexity of the pest population, the development of resistance and the spraying frequency of pulsed chemical control affect optimal switching strategies given different control aims. To do this, we developed novel discrete pest population growth models with both impulsive chemical control and the evolution of pesticide resistance. Strong and weak threshold conditions which guarantee the extinction of the pest population, based on the threshold values of the analytical formula for the optimal switching time, were derived. Further, we addressed switching strategies in the light of chosen economic injury levels. Moreover, the effects of the complex dynamical behaviour of the pest population on the pesticide switching times were also studied. The pesticide application period, the evolution of pesticide resistance and the dynamic complexity of the pest population may result in complex outbreak patterns, with consequent effects on the pesticide switching strategies.

The effect of EIF dynamics on the cryopreservation process of a size distributed cell population.

PubMed

Fadda, S; Briesen, H; Cincotti, A

2011-06-01

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

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Modeling snag dynamics in northern Arizona mixed-conifer and ponderosa pine forests

Treesearch

Joseph L. Ganey; Scott C. Vojta

2007-01-01

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

Optogenetic stimulation of a meso-scale human cortical model

NASA Astrophysics Data System (ADS)

Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi

2015-03-01

Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.

Building the bridge between animal movement and population dynamics.

PubMed

Morales, Juan M; Moorcroft, Paul R; Matthiopoulos, Jason; Frair, Jacqueline L; Kie, John G; Powell, Roger A; Merrill, Evelyn H; Haydon, Daniel T

2010-07-27

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

Structured population dynamics: continuous size and discontinuous stage structures.

PubMed

Buffoni, Giuseppe; Pasquali, Sara

2007-04-01

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

Effect of Inherited Genetic Information on Stochastic Predator-Prey Model

NASA Astrophysics Data System (ADS)

Duda, Artur; Dyś, Paweł; Nowicka, Alekandra; Dudek, Mirosław R.

We discuss the Lotka-Volterra dynamics of two populations, preys and predators, in the case when the predators posses a genetic information. The genetic information is inherited according to the rules of the Penna model of genetic evolution. Each individual of the predator population is uniquely determined by sex, genotype and phenotype. In our case, the genes are represented by 8-bit integers and the phenotypes are defined with the help of the 8-state Potts model Hamiltonian. We showed that during time evolution, the population of the predators can experience a series of dynamical phase transitions which are connected with the different types of the dominant phenotypes present in the population.

Eco-evolutionary dynamics in a coevolving host-virus system.

PubMed

Frickel, Jens; Sieber, Michael; Becks, Lutz

2016-04-01

Eco-evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco-evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco-evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host-virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade-off between host resistance and growth then maintained host diversity over time (trade-off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations. © 2016 John Wiley & Sons Ltd/CNRS.

Age or stage structure? A comparison of dynamic outcomes from discrete age- and stage-structured population models.

PubMed

Wikan, Arild

2012-06-01

Discrete stage-structured density-dependent and discrete age-structured density-dependent population models are considered. Regarding the former, we prove that the model at hand is permanent (i.e., that the population will neither go extinct nor exhibit explosive oscillations) and given density dependent fecundity terms we also show that species with delayed semelparous life histories tend to be more stable than species which possess precocious semelparous life histories. Moreover, our findings together with results obtained from other stage-structured models seem to illustrate a fairly general ecological principle, namely that iteroparous species are more stable than semelparous species. Our analysis of various age-structured models does not necessarily support the conclusions above. In fact, species with precocious life histories now appear to possess better stability properties than species with delayed life histories, especially in the iteroparous case. We also show that there are dynamical outcomes from semelparous age-structured models which we are not able to capture in corresponding stage-structured cases. Finally, both age- and stage-structured population models may generate periodic dynamics of low period (either exact or approximate). The important prerequisite is to assume density-dependent survival probabilities.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Sources, Sinks, and Model Accuracy

EPA Science Inventory

Spatial demographic models are a necessary tool for understanding how to manage landscapes sustainably for animal populations. These models, therefore, must offer precise and testable predications about animal population dynamics and how animal demographic parameters respond to ...

An analytical approach to top predator interference on the dynamics of a food chain model

NASA Astrophysics Data System (ADS)

Senthamarai, R.; Vijayalakshmi, T.

2018-04-01

In this paper, a nonlinear mathematical model is proposed and analyzed to study of top predator interference on the dynamics of a food chain model. The mathematical model is formulated using the system of non-linear ordinary differential equations. In this model, there are three state dimensionless variables, viz, size of prey population x, size of intermediate predator y and size of top predator population z. The analytical results are compared with the numerical simulation using MATLAB software and satisfactory results are noticed.

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

PubMed

Nedorezov, L V

2015-01-01

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

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

PubMed Central

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

Biomolecular Modeling in a Process Dynamics and Control Course

ERIC Educational Resources Information Center

Gray, Jeffrey J.

2006-01-01

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

Analysis of the impact of trap-neuter-return programs on populations of feral cats.

PubMed

Foley, Patrick; Foley, Janet E; Levy, Julie K; Paik, Terry

2005-12-01

To evaluate 2 county trap-neuter-return (TNR) programs for feral cat population management via mathematical modeling. Theoretical population model. Feral cats assessed from 1992 to 2003 in San Diego County, California (n = 14,452), and from 1998 to 2004 in Alachua County, Florida (11,822). Data were analyzed with a mathematical Ricker model to describe population dynamics of the feral cats and modifications to the dynamics that occurred as a result of the TNR programs. In both counties, results of analyses did not indicate a consistent reduction in per capita growth, the population multiplier, or the proportion of female cats that were pregnant. Success of feral cat management programs that use TNR can be monitored with an easily collected set of data and statistical analyses facilitated by population modeling techniques. Results may be used to suggest possible future monitoring and modification of TNR programs, which could result in greater success controlling and reducing feral cat populations.

Metamodels for Transdisciplinary Analysis of Wildlife Population Dynamics

PubMed Central

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

2013-01-01

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

Two disjunct Pleistocene populations and anisotropic postglacial expansion shaped the current genetic structure of the relict plant Amborella trichopoda

PubMed Central

Tournebize, Rémi; Manel, Stéphanie; Vigouroux, Yves; Munoz, François; de Kochko, Alexandre

2017-01-01

Past climate fluctuations shaped the population dynamics of organisms in space and time, and have impacted their present intra-specific genetic structure. Demo-genetic modelling allows inferring the way past demographic and migration dynamics have determined this structure. Amborella trichopoda is an emblematic relict plant endemic to New Caledonia, widely distributed in the understory of non-ultramafic rainforests. We assessed the influence of the last glacial climates on the demographic history and the paleo-distribution of 12 Amborella populations covering the whole current distribution. We performed coalescent genetic modelling of these dynamics, based on both whole-genome resequencing and microsatellite genotyping data. We found that the two main genetic groups of Amborella were shaped by the divergence of two ancestral populations during the last glacial maximum. From 12,800 years BP, the South ancestral population has expanded 6.3-fold while the size of the North population has remained stable. Recent asymmetric gene flow between the groups further contributed to the phylogeographical pattern. Spatially explicit coalescent modelling allowed us to estimate the location of ancestral populations with good accuracy (< 22 km) and provided indications regarding the mid-elevation pathways that facilitated post-glacial expansion. PMID:28820899

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

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

Mapping the ecological networks of microbial communities.

PubMed

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K; Weiss, Scott T; Liu, Yang-Yu

2017-12-11

Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.

Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish

USGS Publications Warehouse

Sakaris, P.C.; Irwin, E.R.

2010-01-01

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotie fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes. ?? 2010 by the Ecological Society of America.

Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications

EPA Science Inventory

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

Feeding modes in stream salmonid population models: Is drift feeding the whole story?

Treesearch

Bret Harvey; Steve Railsback

2014-01-01

Drift-feeding models are essential components of broader models that link stream habitat to salmonid populations and community dynamics. But is an additional feeding mode needed for understanding and predicting salmonid population responses to streamflow and other environmental factors? We addressed this question by applying two versions of the individual-based model...

The Allee effect, stochastic dynamics and the eradication of alien species

Treesearch

Andrew Liebhold; Jordi Bascompte; Jordi Bascompte

2003-01-01

Previous treatments of the population biology of eradication have assumed that eradication can only be achieved via 100% removal of the alien population. However, this assumption appears to be incorrect because stochastic dynamics and the Allee effect typically contribute to the extinction of very low-density populations. We explore a model that incorporates Allee...

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

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

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

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

PubMed Central

2014-01-01

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

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

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

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

Examining a scaled dynamical system of telomere shortening

NASA Astrophysics Data System (ADS)

Cyrenne, Benoit M.; Gooding, Robert J.

2015-02-01

A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced model that incorporates stem cells as progenitors of new cells, imposes the Hayflick limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected via the introduction of scaled populations, rate constants and time. The application of this model to available leukocyte baboon data is discussed.

A dynamic model of the marriage market-Part 2: simulation of marital states and application to empirical data.

PubMed

Matthews, A P; Garenne, M L

2013-09-01

A dynamic, two-sex, age-structured marriage model is presented. Part 1 focused on first marriage only and described a marriage market matching algorithm. In Part 2 the model is extended to include divorce, widowing, and remarriage. The model produces a self-consistent set of marital states distributed by age and sex in a stable population by means of a gender-symmetric numerical method. The model is compared with empirical data for the case of Zambia. Furthermore, a dynamic marriage function for a changing population is demonstrated in simulations of three hypothetical scenarios of elevated mortality in young to middle adulthood. The marriage model has its primary application to simulation of HIV-AIDS epidemics in African countries. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating Allee dynamics before they can be observed: polar bears as a case study.

PubMed

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

2014-01-01

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

Estimating Allee Dynamics before They Can Be Observed: Polar Bears as a Case Study

PubMed Central

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

2014-01-01

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

Double Trouble at High Density: Cross-Level Test of Resource-Related Adaptive Plasticity and Crowding-Related Fitness

PubMed Central

Gergs, André; Preuss, Thomas G.; Palmqvist, Annemette

2014-01-01

Population size is often regulated by negative feedback between population density and individual fitness. At high population densities, animals run into double trouble: they might concurrently suffer from overexploitation of resources and also from negative interference among individuals regardless of resource availability, referred to as crowding. Animals are able to adapt to resource shortages by exhibiting a repertoire of life history and physiological plasticities. In addition to resource-related plasticity, crowding might lead to reduced fitness, with consequences for individual life history. We explored how different mechanisms behind resource-related plasticity and crowding-related fitness act independently or together, using the water flea Daphnia magna as a case study. For testing hypotheses related to mechanisms of plasticity and crowding stress across different biological levels, we used an individual-based population model that is based on dynamic energy budget theory. Each of the hypotheses, represented by a sub-model, is based on specific assumptions on how the uptake and allocation of energy are altered under conditions of resource shortage or crowding. For cross-level testing of different hypotheses, we explored how well the sub-models fit individual level data and also how well they predict population dynamics under different conditions of resource availability. Only operating resource-related and crowding-related hypotheses together enabled accurate model predictions of D. magna population dynamics and size structure. Whereas this study showed that various mechanisms might play a role in the negative feedback between population density and individual life history, it also indicated that different density levels might instigate the onset of the different mechanisms. This study provides an example of how the integration of dynamic energy budget theory and individual-based modelling can facilitate the exploration of mechanisms behind the regulation of population size. Such understanding is important for assessment, management and the conservation of populations and thereby biodiversity in ecosystems. PMID:24626228

How Does a Divided Population Respond to Change?

PubMed

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

2015-01-01

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

GENETICS AND POPULATION-LEVEL RISK ASSESSMENT

EPA Science Inventory

Genetic variation defines population structure and provides the mechanism for populations to adapt to novel stressors. Despite its fundamental importance in understanding populations, genetic information has been included rarely in models of population dynamics (endangered speci...

Uncoupling the Effects of Seed Predation and Seed Dispersal by Granivorous Ants on Plant Population Dynamics

PubMed Central

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

2012-01-01

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

And So It Grows: Using a Computer-Based Simulation of a Population Growth Model to Integrate Biology & Mathematics

ERIC Educational Resources Information Center

Street, Garrett M.; Laubach, Timothy A.

2013-01-01

We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.

EVALUATION OF THE EFFICACY OF EXTRAPOLATION POPULATION MODELING TO PREDICT THE DYNAMICS OF AMERICAMYSIS BAHIA POPULATIONS IN THE LABORATORY

EPA Science Inventory

An age-classified projection matrix model has been developed to extrapolate the chronic (28-35d) demographic responses of Americamysis bahia (formerly Mysidopsis bahia) to population-level response. This study was conducted to evaluate the efficacy of this model for predicting t...

A Model with Darwinian Dynamics on a Rugged Landscape

NASA Astrophysics Data System (ADS)

Brotto, Tommaso; Bunin, Guy; Kurchan, Jorge

2017-02-01

We discuss the population dynamics with selection and random diffusion, keeping the total population constant, in a fitness landscape associated with Constraint Satisfaction, a paradigm for difficult optimization problems. We obtain a phase diagram in terms of the size of the population and the diffusion rate, with a glass phase inside which the dynamics keeps searching for better configurations, and outside which deleterious `mutations' spoil the performance. The phase diagram is analogous to that of dense active matter in terms of temperature and drive.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

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

2016-01-01

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

Benchmarking novel approaches for modelling species range dynamics.

PubMed

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

2016-08-01

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

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

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

PubMed Central

2017-01-01

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

Population mixture model for nonlinear telomere dynamics

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

A kinetic theory for age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Chou, Tom; Greenman, Chris

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

Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

PubMed

Heikkinen, Risto K; Bocedi, Greta; Kuussaari, Mikko; Heliölä, Janne; Leikola, Niko; Pöyry, Juha; Travis, Justin M J

2014-01-01

Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

Modeling the Dynamics of Disease States in Depression

PubMed Central

Demic, Selver; Cheng, Sen

2014-01-01

Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidity, disability, and risk for suicide. The disorder is clinically and etiologically heterogeneous. Despite intense research efforts, the response rates of antidepressant treatments are relatively low and the etiology and progression of MDD remain poorly understood. Here we use computational modeling to advance our understanding of MDD. First, we propose a systematic and comprehensive definition of disease states, which is based on a type of mathematical model called a finite-state machine. Second, we propose a dynamical systems model for the progression, or dynamics, of MDD. The model is abstract and combines several major factors (mechanisms) that influence the dynamics of MDD. We study under what conditions the model can account for the occurrence and recurrence of depressive episodes and how we can model the effects of antidepressant treatments and cognitive behavioral therapy within the same dynamical systems model through changing a small subset of parameters. Our computational modeling suggests several predictions about MDD. Patients who suffer from depression can be divided into two sub-populations: a high-risk sub-population that has a high risk of developing chronic depression and a low-risk sub-population, in which patients develop depression stochastically with low probability. The success of antidepressant treatment is stochastic, leading to widely different times-to-remission in otherwise identical patients. While the specific details of our model might be subjected to criticism and revisions, our approach shows the potential power of computationally modeling depression and the need for different type of quantitative data for understanding depression. PMID:25330102

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

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

A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS

EPA Science Inventory

Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...

Bridging the gap between habitat-modeling research and bird conservation with dynamic landscape and population models

Treesearch

Frank R., III Thompson

2009-01-01

Habitat models are widely used in bird conservation planning to assess current habitat or populations and to evaluate management alternatives. These models include species-habitat matrix or database models, habitat suitability models, and statistical models that predict abundance. While extremely useful, these approaches have some limitations.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

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

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

Outbreak and Extinction Dynamics in a Stochastic Ebola Model

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

Addawe, Joel; Pajimola, Aprimelle Kris

2016-10-01

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

Evolutionary dynamics of general group interactions in structured populations

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Assessing tiger population dynamics using photographic capture-recapture sampling

USGS Publications Warehouse

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

2006-01-01

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, ?robust design? capture?recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of =K' =Y' 0.10 ? 0.069 (values are estimated mean ? SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 ? 0.051, and the estimated probability that a newly caught animal was a transient was = 0.18 ? 0.11. During the period when the sampled area was of constant size, the estimated population size Nt varied from 17 ? 1.7 to 31 ? 2.1 tigers, with a geometric mean rate of annual population change estimated as = 1.03 ? 0.020, representing a 3% annual increase. The estimated recruitment of new animals, Bt, varied from 0 ? 3.0 to 14 ? 2.9 tigers. Population density estimates, D, ranged from 7.33 ? 0.8 tigers/100 km2 to 21.73 ? 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

Assessing tiger population dynamics using photographic capture-recapture sampling.

PubMed

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

2006-11-01

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

PubMed

Cushing, J M; Henson, Shandelle M

2018-02-03

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

Integrating count and detection–nondetection data to model population dynamics

USGS Publications Warehouse

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

2017-01-01

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

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

PubMed

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

2017-06-01

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

Climate-based models for West Nile Culex mosquito vectors in the Northeastern US

NASA Astrophysics Data System (ADS)

Gong, Hongfei; Degaetano, Arthur T.; Harrington, Laura C.

2011-05-01

Climate-based models simulating Culex mosquito population abundance in the Northeastern US were developed. Two West Nile vector species, Culex pipiens and Culex restuans, were included in model simulations. The model was optimized by a parameter-space search within biological bounds. Mosquito population dynamics were driven by major environmental factors including temperature, rainfall, evaporation rate and photoperiod. The results show a strong correlation between the timing of early population increases (as early warning of West Nile virus risk) and decreases in late summer. Simulated abundance was highly correlated with actual mosquito capture in New Jersey light traps and validated with field data. This climate-based model simulates the population dynamics of both the adult and immature mosquito life stage of Culex arbovirus vectors in the Northeastern US. It is expected to have direct and practical application for mosquito control and West Nile prevention programs.

Modeling sandhill crane population dynamics

USGS Publications Warehouse

Johnson, D.H.

1979-01-01

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

Calculation of Disease Dynamics in a Population of Households

PubMed Central

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

2010-01-01

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

Stochastic population dynamics in spatially extended predator-prey systems

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

USGS Publications Warehouse

Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith

2014-01-01

Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

Estimation of mussel population response to hydrologic alteration in a southeastern U.S. stream

USGS Publications Warehouse

Peterson, J.T.; Wisniewski, J.M.; Shea, C.P.; Rhett, Jackson C.

2011-01-01

The southeastern United States has experienced severe, recurrent drought, rapid human population growth, and increasing agricultural irrigation during recent decades, resulting in greater demand for the water resources. During the same time period, freshwater mussels (Unioniformes) in the region have experienced substantial population declines. Consequently, there is growing interest in determining how mussel population declines are related to activities associated with water resource development. Determining the causes of mussel population declines requires, in part, an understanding of the factors influencing mussel population dynamics. We developed Pradel reverse-time, tag-recapture models to estimate survival, recruitment, and population growth rates for three federally endangered mussel species in the Apalachicola- Chattahoochee-Flint River Basin, Georgia. The models were parameterized using mussel tag-recapture data collected over five consecutive years from Sawhatchee Creek, located in southwestern Georgia. Model estimates indicated that mussel survival was strongly and negatively related to high flows during the summer, whereas recruitment was strongly and positively related to flows during the spring and summer. Using these models, we simulated mussel population dynamics under historic (1940-1969) and current (1980-2008) flow regimes and under increasing levels of water use to evaluate the relative effectiveness of alternative minimum flow regulations. The simulations indicated that the probability of simulated mussel population extinction was at least 8 times greater under current hydrologic regimes. In addition, simulations of mussel extinction under varying levels of water use indicated that the relative risk of extinction increased with increased water use across a range of minimum flow regulations. The simulation results also indicated that our estimates of the effects of water use on mussel extinction were influenced by the assumptions about the dynamics of the system, highlighting the need for further study of mussel population dynamics. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

A Biologically Informed, Mechanistic Model of Desert Shrub Population Dynamics Bearing on Arid Landscape Evolution

NASA Astrophysics Data System (ADS)

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

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

BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on Myotis spp. of bats

PubMed Central

2014-01-01

Background Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI). Results BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course. Conclusions BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication. PMID:24955110

BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on Myotis spp. of bats

USGS Publications Warehouse

Erickson, Richard A.; Thogmartin, Wayne E.; Szymanski, Jennifer A.

2014-01-01

Background: Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI). Results: BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course. Conclusions: BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication.

BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on Myotis spp. of bats.

PubMed

Erickson, Richard A; Thogmartin, Wayne E; Szymanski, Jennifer A

2014-01-01

Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI). BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course. BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication.

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

PubMed

Hill, Andrew; Camacho, Oscar M

2017-06-01

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

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

PubMed

Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn

2018-02-01

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics

PubMed Central

Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn

2018-01-01

The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043

Swarming Patterns in a Two-Dimensional Kinematic Model for Biological Groups

NASA Astrophysics Data System (ADS)

Topaz, Chad

2004-03-01

We construct a continuum model for the motion of biological organisms experiencing social interactions and study its pattern-forming behavior. The model takes the form of a conservation law in two spatial dimensions. Social interactions are modeled in the velocity term, which is nonlocal in the population density. The dynamics of the model may be uniquely decomposed into incompressible motion and potential motion. For the purely incompressible case, the model resembles that for fluid dynamical vortex patches. There exist solutions that have constant population density and compact support for all time. Numerical simulations produce rotating structures with circular cores and spiral arms, reminiscent of naturally observed swarms such as ant mills. For the purely potential case, the model resembles a nonlocal (forwards or backwards) porous media equation, describing aggregation or dispersion of the population. For the aggregative case, the population clumps into regions of high and low density with a predictable characteristic length scale that is confirmed by numerical simulations.

Population growth rates: issues and an application.

PubMed Central

Godfray, H Charles J; Rees, Mark

2002-01-01

Current issues in population dynamics are discussed in the context of The Royal Society Discussion Meeting 'Population growth rate: determining factors and role in population regulation'. In particular, different views on the centrality of population growth rates to the study of population dynamics and the role of experiments and theory are explored. Major themes emerging include the role of modern statistical techniques in bringing together experimental and theoretical studies, the importance of long-term experimentation and the need for ecology to have model systems, and the value of population growth rate as a means of understanding and predicting population change. The last point is illustrated by the application of a recently introduced technique, integral projection modelling, to study the population growth rate of a monocarpic perennial plant, its elasticities to different life-history components and the evolution of an evolutionarily stable strategy size at flowering. PMID:12396521

Modelling and finite-time stability analysis of psoriasis pathogenesis

NASA Astrophysics Data System (ADS)

Oza, Harshal B.; Pandey, Rakesh; Roper, Daniel; Al-Nuaimi, Yusur; Spurgeon, Sarah K.; Goodfellow, Marc

2017-08-01

A new systems model of psoriasis is presented and analysed from the perspective of control theory. Cytokines are treated as actuators to the plant model that govern the cell population under the reasonable assumption that cytokine dynamics are faster than the cell population dynamics. The analysis of various equilibria is undertaken based on singular perturbation theory. Finite-time stability and stabilisation have been studied in various engineering applications where the principal paradigm uses non-Lipschitz functions of the states. A comprehensive study of the finite-time stability properties of the proposed psoriasis dynamics is carried out. It is demonstrated that the dynamics are finite-time convergent to certain equilibrium points rather than asymptotically or exponentially convergent. This feature of finite-time convergence motivates the development of a modified version of the Michaelis-Menten function, frequently used in biology. This framework is used to model cytokines as fast finite-time actuators.

Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery

USGS Publications Warehouse

Brown, Donald J.; Ribic, Christine; Donner, Deahn M.; Nelson, Mark D.; Bocetti, Carol I.; Deloria-Sheffield, Christie M.

2017-01-01

Long-term management planning for conservation-reliant migratory songbirds is particularly challenging because habitat quality in different stages and geographic locations of the annual cycle can have direct and carry-over effects that influence the population dynamics. The Neotropical migratory songbird Kirtland's warbler Setophaga kirtlandii (Baird 1852) is listed as endangered under the U.S. Endangered Species Act and Near Threatened under the IUCN Red List. This conservation-reliant species is being considered for U.S. federal delisting because the species has surpassed the designated 1000 breeding pairs recovery threshold since 2001.To help inform the delisting decision and long-term management efforts, we developed a population simulation model for the Kirtland's warbler that incorporated both breeding and wintering grounds habitat dynamics, and projected population viability based on current environmental conditions and potential future management scenarios. Future management scenarios included the continuation of current management conditions, reduced productivity and carrying capacity due to the changes in habitat suitability from the creation of experimental jack pine Pinus banksiana (Lamb.) plantations, and reduced productivity from alteration of the brown-headed cowbird Molothrus ater (Boddaert 1783) removal programme.Linking wintering grounds precipitation to productivity improved the accuracy of the model for replicating past observed population dynamics. Our future simulations indicate that the Kirtland's warbler population is stable under two potential future management scenarios: (i) continuation of current management practices and (ii) spatially restricting cowbird removal to the core breeding area, assuming that cowbirds reduce productivity in the remaining patches by ≤41%. The additional future management scenarios we assessed resulted in population declines.Synthesis and applications. Our study indicates that the Kirtland's warbler population is stable under current management conditions and that the jack pine plantation and cowbird removal programmes continue to be necessary for the long-term persistence of the species. This study represents one of the first attempts to incorporate full annual cycle dynamics into a population viability analysis for a migratory bird, and our results indicate that incorporating wintering grounds dynamics improved the model performance.

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

Forster, Robert Burke

2006-12-01

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

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

PubMed

Iwai, Sosuke; Fujiwara, Kenji; Tamura, Takuro

2016-09-01

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

Modeling oscillations and spiral waves in Dictyostelium populations

NASA Astrophysics Data System (ADS)

Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj

2015-06-01

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

Modelling population dynamics and response to management options in the poultry red mite Dermanyssus gallinae (Acari: Dermanyssidae).

PubMed

Huber, K; Zenner, L; Bicout, D J

2011-02-28

The poultry red mite Dermanyssus gallinae is a major pest and widespread ectoparasite of laying hens and other domestic and wild birds. Under optimal conditions, D. gallinae can complete its lifecycle in less than 10 days, leading to rapid proliferation of populations in poultry systems. This paper focuses on developing a theoretical model framework to describe the population dynamics of D. gallinae. This model is then used to test the efficacy and residual effect of different control options for managing D. gallinae. As well as allowing comparison between treatment options, the model also allows comparison of treatment efficacies to different D. gallinae life stages. Three different means for controlling D. gallinae populations were subjected to the model using computer simulations: mechanical cleaning (killing once at a given time all accessible population stages), sanitary clearance (starving the mite population for a given duration, e.g. between flocks) and acaricide treatment (killing a proportion of nymphs and adults during the persistence of the treatment). Simulations showed that mechanical cleaning and sanitary clearance alone could not eradicate the model D. gallinae population, although these methods did delay population establishment. In contrast, the complete eradication of the model D. gallinae population was achieved by several successive acaricide treatments in close succession, even when a relatively low treatment level was used. Copyright © 2010 Elsevier B.V. All rights reserved.

FISHERY-ORIENTED MODEL OF MARYLAND OYSTER POPULATIONS

EPA Science Inventory

We used time series data to calibrate a model of oyster population dynamics for Maryland's Chesapeake Bay. Model parameters were fishing mortality, natural mortality, recruitment, and carrying capacity. We calibrated for the Maryland bay as a whole and separately for 3 salinity z...

Modelling and observing the role of wind in Anopheles population dynamics around a reservoir.

PubMed

Endo, Noriko; Eltahir, Elfatih A B

2018-01-25

Wind conditions, as well as other environmental conditions, are likely to influence malaria transmission through the behaviours of Anopheles mosquitoes, especially around water-resource reservoirs. Wind-induced waves in a reservoir impose mortality on aquatic-stage mosquitoes. Mosquitoes' host-seeking activity is also influenced by wind through dispersion of [Formula: see text]. However, no malaria transmission model exists to date that simulated those impacts of wind mechanistically. A modelling framework for simulating the three important effects of wind on the behaviours of mosquito is developed: attraction of adult mosquitoes through dispersion of [Formula: see text] ([Formula: see text] attraction), advection of adult mosquitoes (advection), and aquatic-stage mortality due to wind-induced surface waves (waves). The framework was incorporated in a mechanistic malaria transmission simulator, HYDREMATS. The performance of the extended simulator was compared with the observed population dynamics of the Anopheles mosquitoes at a village adjacent to the Koka Reservoir in Ethiopia. The observed population dynamics of the Anopheles mosquitoes were reproduced with some reasonable accuracy in HYDREMATS that includes the representation of the wind effects. HYDREMATS without the wind model failed to do so. Offshore wind explained the increase in Anopheles population that cannot be expected from other environmental conditions alone. Around large water bodies such as reservoirs, the role of wind in the dynamics of Anopheles population, hence in malaria transmission, can be significant. Modelling the impacts of wind on the behaviours of Anopheles mosquitoes aids in reproducing the seasonality of malaria transmission and in estimation of the risk of malaria around reservoirs.

Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

PubMed

Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J

2017-10-10

Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

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

Modelling the Dynamics of Post-Vaccination Immunity Rate in a Population of Sahelian Sheep after a Vaccination Campaign against Peste des Petits Ruminants Virus

PubMed Central

Lancelot, Renaud; Lesnoff, Matthieu

2016-01-01

Background Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in offtake rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases. PMID:27603710

Dynamical properties of the Penna aging model applied to the population of wolves

NASA Astrophysics Data System (ADS)

Makowiec, Danuta

1997-02-01

The parameters of th Penna bit-string model of aging of biological systems are systematically tested to better understand the model itself as well as the results arising from applying this model to studies of the development of the stationary population of Alaska wolves.

Spread of a disease and its effect on population dynamics in an eco-epidemiological system

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Roy, Parimita

2014-12-01

In this paper, an eco-epidemiological model with simple law of mass action and modified Holling type II functional response has been proposed and analyzed to understand how a disease may spread among natural populations. The proposed model is a modification of the model presented by Upadhyay et al. (2008) [1]. Existence of the equilibria and their stability analysis (linear and nonlinear) has been studied. The dynamical transitions in the model have been studied by identifying the existence of backward Hopf-bifurcations and demonstrated the period-doubling route to chaos when the death rate of predator (μ1) and the growth rate of susceptible prey population (r) are treated as bifurcation parameters. Our studies show that the system exhibits deterministic chaos when some control parameters attain their critical values. Chaotic dynamics is depicted using the 2D parameter scans and bifurcation analysis. Possible implications of the results for disease eradication or its control are discussed.

A Compartmental Model for Zika Virus with Dynamic Human and Vector Populations

PubMed Central

Lee, Eva K; Liu, Yifan; Pietz, Ferdinand H

2016-01-01

The Zika virus (ZIKV) outbreak in South American countries and its potential association with microcephaly in newborns and Guillain-Barré Syndrome led the World Health Organization to declare a Public Health Emergency of International Concern. To understand the ZIKV disease dynamics and evaluate the effectiveness of different containment strategies, we propose a compartmental model with a vector-host structure for ZIKV. The model utilizes logistic growth in human population and dynamic growth in vector population. Using this model, we derive the basic reproduction number to gain insight on containment strategies. We contrast the impact and influence of different parameters on the virus trend and outbreak spread. We also evaluate different containment strategies and their combination effects to achieve early containment by minimizing total infections. This result can help decision makers select and invest in the strategies most effective to combat the infection spread. The decision-support tool demonstrates the importance of “digital disease surveillance” in response to waves of epidemics including ZIKV, Dengue, Ebola and cholera. PMID:28269870

Extinction in neutrally stable stochastic Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

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

Extinction in neutrally stable stochastic Lotka-Volterra models.

PubMed

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

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

The western spruce budworm model: structure and content.

Treesearch

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

1989-01-01

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

Comparative recruitment dynamics of Alewife and Bloater in Lakes Michigan and Huron

USGS Publications Warehouse

Collingsworth, Paris D.; Bunnell, David B.; Madenjian, Charles P.; Riley, Stephen C.

2014-01-01

The predictive power of recruitment models often relies on the identification and quantification of external variables, in addition to stock size. In theory, the identification of climatic, biotic, or demographic influences on reproductive success assists fisheries management by identifying factors that have a direct and reproducible influence on the population dynamics of a target species. More often, models are constructed as one-time studies of a single population whose results are not revisited when further data become available. Here, we present results from stock recruitment models for Alewife Alosa pseudoharengus and Bloater Coregonus hoyi in Lakes Michigan and Huron. The factors that explain variation in Bloater recruitment were remarkably consistent across populations and with previous studies that found Bloater recruitment to be linked to population demographic patterns in Lake Michigan. Conversely, our models were poor predictors of Alewife recruitment in Lake Huron but did show some agreement with previously published models from Lake Michigan. Overall, our results suggest that external predictors of fish recruitment are difficult to discern using traditional fisheries models, and reproducing the results from previous studies may be difficult particularly at low population sizes.

OSSOS: X. How to use a Survey Simulator: Statistical Testing of Dynamical Models Against the Real Kuiper Belt

NASA Astrophysics Data System (ADS)

Lawler, Samantha M.; Kavelaars, J. J.; Alexandersen, Mike; Bannister, Michele T.; Gladman, Brett; Petit, Jean-Marc; Shankman, Cory

2018-05-01

All surveys include observational biases, which makes it impossible to directly compare properties of discovered trans-Neptunian Objects (TNOs) with dynamical models. However, by carefully keeping track of survey pointings on the sky, detection limits, tracking fractions, and rate cuts, the biases from a survey can be modelled in Survey Simulator software. A Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so that the biased simulated objects can be directly compared with real discoveries. This methodology has been used with great success in the Outer Solar System Origins Survey (OSSOS) and its predecessor surveys. In this chapter, we give four examples of ways to use the OSSOS Survey Simulator to gain knowledge about the true structure of the Kuiper Belt. We demonstrate how to statistically compare different dynamical model outputs with real TNO discoveries, how to quantify detection biases within a TNO population, how to measure intrinsic population sizes, and how to use upper limits from non-detections. We hope this will provide a framework for dynamical modellers to statistically test the validity of their models.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

How Does a Divided Population Respond to Change?

PubMed Central

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

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics—as opposed to an independent process—of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions. PMID:26161859

Analysis and prediction of pest dynamics in an agroforestry context using Tiko'n, a generic tool to develop food web models

NASA Astrophysics Data System (ADS)

Rojas, Marcela; Malard, Julien; Adamowski, Jan; Carrera, Jaime Luis; Maas, Raúl

2017-04-01

While it is known that climate change will impact future plant-pest population dynamics, potentially affecting crop damage, agroforestry with its enhanced biodiversity is said to reduce the outbreaks of pest insects by providing natural enemies for the control of pest populations. This premise is known in the literature as the natural enemy hypothesis and has been widely studied qualitatively. However, disagreement still exists on whether biodiversity enhancement reduces pest outbreaks, showing the need of quantitatively understanding the mechanisms behind the interactions between pests and natural enemies, also known as trophic interactions. Crop pest models that study insect population dynamics in agroforestry contexts are very rare, and pest models that take trophic interactions into account are even rarer. This may be due to the difficulty of representing complex food webs in a quantifiable model. There is therefore a need for validated food web models that allow users to predict the response of these webs to changes in climate in agroforestry systems. In this study we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web models; the program uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. Tiko'n was run using coffee leaf miner (Leucoptera coffeella) and associated parasitoid data from a shaded coffee plantation, showing the mechanisms of insect population dynamics within a tri-trophic food web in an agroforestry system.

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

PubMed Central

Wesolowski, Amy; O’Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J.; Buckee, Caroline O.

2015-01-01

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. PMID:26158274

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

USGS Publications Warehouse

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

2012-01-01

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

Influence of body condition on the population dynamics of Atlantic salmon with consideration of the potential impact of sea lice.

PubMed

Susdorf, R; Salama, N K G; Lusseau, D

2017-11-21

Atlantic salmon Salmo salar is an iconic species of high conservation and economic importance. At sea, individuals typically are subject to sea lice infestation, which can have detrimental effects on their host. Over recent decades, the body condition and marine survival in NE Atlantic stocks have generally decreased, reflected in fewer adults returning to rivers, which is partly attributable to sea lice. We developed a deterministic stage-structured population model to assess condition-mediated population dynamics resulting in changing fecundity, age at sexual maturation and marine survival rate. The model is parameterized using data from the North Esk system, north-east Scotland. Both constant and density-dependent juvenile survival rates are considered. We show that even small sea lice-mediated changes in mean body condition of MSW can cause substantial population declines, whereas 1SW condition is less influential. Density dependence alleviates the condition-mediated population effect. The resilience of the population to demographic perturbations declines as adult condition is reduced. Indirect demographic changes in salmonid life-history traits (e.g., body condition) are often considered unimportant for population trajectory. The model shows that Atlantic salmon population dynamics can be highly responsive to sea lice-mediated effects on adult body condition, thus highlighting the importance of non-lethal parasitic long-term effects. © 2017 The Authors Journal of Fish Diseases Published by John Wiley & Sons Ltd.

Modeling the spatial and temporal dynamics of isolated emerald ash borer populations

Treesearch

Nathan W. Siegert; Andrew M. Liebhold; Deborah G. McCullough

2008-01-01

The ability to predict the distance and rate of emerald ash borer (EAB) spread in outlier populations is needed to continue development of effective management strategies for improved EAB control. We have developed a coupled map lattice model to estimate the spread and dispersal of isolated emerald ash borer populations. This model creates an artificial environment in...

Hydration dynamics promote bacterial coexistence on rough surfaces

PubMed Central

Wang, Gang; Or, Dani

2013-01-01

Identification of mechanisms that promote and maintain the immense microbial diversity found in soil is a central challenge for contemporary microbial ecology. Quantitative tools for systematic integration of complex biophysical and trophic processes at spatial scales, relevant for individual cell interactions, are essential for making progress. We report a modeling study of competing bacterial populations cohabiting soil surfaces subjected to highly dynamic hydration conditions. The model explicitly tracks growth, motion and life histories of individual bacterial cells on surfaces spanning dynamic aqueous networks that shape heterogeneous nutrient fields. The range of hydration conditions that confer physical advantages for rapidly growing species and support competitive exclusion is surprisingly narrow. The rapid fragmentation of soil aqueous phase under most natural conditions suppresses bacterial growth and cell dispersion, thereby balancing conditions experienced by competing populations with diverse physiological traits. In addition, hydration fluctuations intensify localized interactions that promote coexistence through disproportional effects within densely populated regions during dry periods. Consequently, bacterial population dynamics is affected well beyond responses predicted from equivalent and uniform hydration conditions. New insights on hydration dynamics could be considered in future designs of soil bioremediation activities, affect longevity of dry food products, and advance basic understanding of bacterial diversity dynamics and its role in global biogeochemical cycles. PMID:23051694

A Stochastic Super-Exponential Growth Model for Population Dynamics

NASA Astrophysics Data System (ADS)

Avila, P.; Rekker, A.

2010-11-01

A super-exponential growth model with environmental noise has been studied analytically. Super-exponential growth rate is a property of dynamical systems exhibiting endogenous nonlinear positive feedback, i.e., of self-reinforcing systems. Environmental noise acts on the growth rate multiplicatively and is assumed to be Gaussian white noise in the Stratonovich interpretation. An analysis of the stochastic super-exponential growth model with derivations of exact analytical formulae for the conditional probability density and the mean value of the population abundance are presented. Interpretations and various applications of the results are discussed.

Climate variability, rice production and groundwater depletion in India

NASA Astrophysics Data System (ADS)

Bhargava, Alok

2018-03-01

This paper modeled the proximate determinants of rice outputs and groundwater depths in 27 Indian states during 1980-2010. Dynamic random effects models were estimated by maximum likelihood at state and well levels. The main findings from models for rice outputs were that temperatures and rainfall levels were significant predictors, and the relationships were quadratic with respect to rainfall. Moreover, nonlinearities with respect to population changes indicated greater rice production with population increases. Second, groundwater depths were positively associated with temperatures and negatively with rainfall levels and there were nonlinear effects of population changes. Third, dynamic models for in situ groundwater depths in 11 795 wells in mainly unconfined aquifers, accounting for latitudes, longitudes and altitudes, showed steady depletion. Overall, the results indicated that population pressures on food production and environment need to be tackled via long-term healthcare, agricultural, and groundwater recharge policies in India.

Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids

USGS Publications Warehouse

Perry, Russell W.; Plumb, John M.; Jones, Edward C.; Som, Nicholas A.; Hetrick, Nicholas J.; Hardy, Thomas B.

2018-04-06

Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the physical stream structure, survival, growth, and movement processes ensures that simulations provide results that are relevant to the questions asked about the population under study.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

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

2018-02-20

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

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

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

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

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

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

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

Rapid processing of chemosensor transients in a neuromorphic implementation of the insect macroglomerular complex

PubMed Central

Pearce, Timothy C.; Karout, Salah; Rácz, Zoltán; Capurro, Alberto; Gardner, Julian W.; Cole, Marina

2012-01-01

We present a biologically-constrained neuromorphic spiking model of the insect antennal lobe macroglomerular complex that encodes concentration ratios of chemical components existing within a blend, implemented using a set of programmable logic neuronal modeling cores. Depending upon the level of inhibition and symmetry in its inhibitory connections, the model exhibits two dynamical regimes: fixed point attractor (winner-takes-all type), and limit cycle attractor (winnerless competition type) dynamics. We show that, when driven by chemosensor input in real-time, the dynamical trajectories of the model's projection neuron population activity accurately encode the concentration ratios of binary odor mixtures in both dynamical regimes. By deploying spike timing-dependent plasticity in a subset of the synapses in the model, we demonstrate that a Hebbian-like associative learning rule is able to organize weights into a stable configuration after exposure to a randomized training set comprising a variety of input ratios. Examining the resulting local interneuron weights in the model shows that each inhibitory neuron competes to represent possible ratios across the population, forming a ratiometric representation via mutual inhibition. After training the resulting dynamical trajectories of the projection neuron population activity show amplification and better separation in their response to inputs of different ratios. Finally, we demonstrate that by using limit cycle attractor dynamics, it is possible to recover and classify blend ratio information from the early transient phases of chemosensor responses in real-time more rapidly and accurately compared to a nearest-neighbor classifier applied to the normalized chemosensor data. Our results demonstrate the potential of biologically-constrained neuromorphic spiking models in achieving rapid and efficient classification of early phase chemosensor array transients with execution times well beyond biological timescales. PMID:23874265

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

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

USGS Publications Warehouse

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

1999-01-01

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

Modelling recolonization of second-growth forest stands by the north american red squirrel Tamiasciurus hudsonicus.

PubMed

Nyquist, B; Tyson, R; Larsen, K

2007-05-01

In this paper, we present a model for source-sink population dynamics where the locations of source and sink habitats change over time. We do this in the context of the population dynamics of the North American red squirrel, Tamiasciurus hudsonicus, within a forest environment subject to harvesting and regrowth. Harvested patches of forest are initially sinks, then eventually become source habitat again as the forest regrows. At the same time, each harvested patch is gradually recolonized by squirrels from other forest patches. We are interested in the interaction of forest harvesting dynamics with squirrel population dynamics. This depends on the harvesting schedule, and on the choices squirrels make when deciding whether to settle in a mature forest patch or in a recently harvested patch. We find that the time it takes for a second-growth forest patch to be recolonized at the mature forest level is longer than the time required for the habitat quality to be restored to the mature forest level. We also notice that recolonization pressure decreases squirrel populations in neighbouring patches. The connectivity between forest patches and the cutting schedule used also affect the time course of recolonization and steady-state population levels.

Kinetic theory of age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Greenman, Chris D.; Chou, Tom

2016-01-01

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

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

PubMed

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

2008-02-01

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

Projected continent-wide declines of the emperor penguin under climate change

NASA Astrophysics Data System (ADS)

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Serreze, Mark; Barbraud, Christophe; Weimerskirch, Henri; Caswell, Hal

2014-08-01

Climate change has been projected to affect species distribution and future trends of local populations, but projections of global population trends are rare. We analyse global population trends of the emperor penguin (Aptenodytes forsteri), an iconic Antarctic top predator, under the influence of sea ice conditions projected by coupled climate models assessed in the Intergovernmental Panel on Climate Change (IPCC) effort. We project the dynamics of all 45 known emperor penguin colonies by forcing a sea-ice-dependent demographic model with local, colony-specific, sea ice conditions projected through to the end of the twenty-first century. Dynamics differ among colonies, but by 2100 all populations are projected to be declining. At least two-thirds are projected to have declined by >50% from their current size. The global population is projected to have declined by at least 19%. Because criteria to classify species by their extinction risk are based on the global population dynamics, global analyses are critical for conservation. We discuss uncertainties arising in such global projections and the problems of defining conservation criteria for species endangered by future climate change.

Spatial evolutionary epidemiology of spreading epidemics

PubMed Central

2016-01-01

Most spatial models of host–parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. PMID:27798295

Spatial evolutionary epidemiology of spreading epidemics.

PubMed

Lion, S; Gandon, S

2016-10-26

Most spatial models of host-parasite interactions either neglect the possibility of pathogen evolution or consider that this process is slow enough for epidemiological dynamics to reach an equilibrium on a fast timescale. Here, we propose a novel approach to jointly model the epidemiological and evolutionary dynamics of spatially structured host and pathogen populations. Starting from a multi-strain epidemiological model, we use a combination of spatial moment equations and quantitative genetics to analyse the dynamics of mean transmission and virulence in the population. A key insight of our approach is that, even in the absence of long-term evolutionary consequences, spatial structure can affect the short-term evolution of pathogens because of the build-up of spatial differentiation in mean virulence. We show that spatial differentiation is driven by a balance between epidemiological and genetic effects, and this quantity is related to the effect of kin competition discussed in previous studies of parasite evolution in spatially structured host populations. Our analysis can be used to understand and predict the transient evolutionary dynamics of pathogens and the emergence of spatial patterns of phenotypic variation. © 2016 The Author(s).

A Markov model for the temporal dynamics of balanced random networks of finite size

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2014-01-01

The balanced state of recurrent networks of excitatory and inhibitory spiking neurons is characterized by fluctuations of population activity about an attractive fixed point. Numerical simulations show that these dynamics are essentially nonlinear, and the intrinsic noise (self-generated fluctuations) in networks of finite size is state-dependent. Therefore, stochastic differential equations with additive noise of fixed amplitude cannot provide an adequate description of the stochastic dynamics. The noise model should, rather, result from a self-consistent description of the network dynamics. Here, we consider a two-state Markovian neuron model, where spikes correspond to transitions from the active state to the refractory state. Excitatory and inhibitory input to this neuron affects the transition rates between the two states. The corresponding nonlinear dependencies can be identified directly from numerical simulations of networks of leaky integrate-and-fire neurons, discretized at a time resolution in the sub-millisecond range. Deterministic mean-field equations, and a noise component that depends on the dynamic state of the network, are obtained from this model. The resulting stochastic model reflects the behavior observed in numerical simulations quite well, irrespective of the size of the network. In particular, a strong temporal correlation between the two populations, a hallmark of the balanced state in random recurrent networks, are well represented by our model. Numerical simulations of such networks show that a log-normal distribution of short-term spike counts is a property of balanced random networks with fixed in-degree that has not been considered before, and our model shares this statistical property. Furthermore, the reconstruction of the flow from simulated time series suggests that the mean-field dynamics of finite-size networks are essentially of Wilson-Cowan type. We expect that this novel nonlinear stochastic model of the interaction between neuronal populations also opens new doors to analyze the joint dynamics of multiple interacting networks. PMID:25520644

Dynamic social networks based on movement

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

PubMed

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

2017-01-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

Dynamics of newly established elk populations

USGS Publications Warehouse

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

2007-01-01

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

The dynamics of sex ratio evolution: from the gene perspective to multilevel selection.

PubMed

Argasinski, Krzysztof

2013-01-01

The new dynamical game theoretic model of sex ratio evolution emphasizes the role of males as passive carriers of sex ratio genes. This shows inconsistency between population genetic models of sex ratio evolution and classical strategic models. In this work a novel technique of change of coordinates will be applied to the new model. This will reveal new aspects of the modelled phenomenon which cannot be shown or proven in the original formulation. The underlying goal is to describe the dynamics of selection of particular genes in the entire population, instead of in the same sex subpopulation, as in the previous paper and earlier population genetics approaches. This allows for analytical derivation of the unbiased strategic model from the model with rigorous non-simplified genetics. In effect, an alternative system of replicator equations is derived. It contains two subsystems: the first describes changes in gene frequencies (this is an alternative unbiased formalization of the Fisher-Dusing argument), whereas the second describes changes in the sex ratios in subpopulations of carriers of genes for each strategy. An intriguing analytical result of this work is that the fitness of a gene depends on the current sex ratio in the subpopulation of its carriers, not on the encoded individual strategy. Thus, the argument of the gene fitness function is not constant but is determined by the trajectory of the sex ratio among carriers of that gene. This aspect of the modelled phenomenon cannot be revealed by the static analysis. Dynamics of the sex ratio among gene carriers is driven by a dynamic "tug of war" between female carriers expressing the encoded strategic trait value and random partners of male carriers expressing the average population strategy (a primary sex ratio). This mechanism can be called "double-level selection". Therefore, gene interest perspective leads to multi-level selection.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.

PubMed

Priol, Pauline; Mazerolle, Marc J; Imbeau, Louis; Drapeau, Pierre; Trudeau, Caroline; Ramière, Jessica

2014-06-01

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.

Computer simulation of population dynamics inside the urban environment

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Theory of time-averaged neutral dynamics with environmental stochasticity

NASA Astrophysics Data System (ADS)

Danino, Matan; Shnerb, Nadav M.

2018-04-01

Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models; in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multispecies problem to two-species dynamics, and the large-N asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte Carlo simulations and from numerical solutions of the corresponding master equations.

Dynamically rich, yet parameter-sparse models for spatial epidemiology. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Jusup, Marko; Iwami, Shingo; Podobnik, Boris; Stanley, H. Eugene

2015-12-01

Since the very inception of mathematical modeling in epidemiology, scientists exploited the simplicity ingrained in the assumption of a well-mixed population. For example, perhaps the earliest susceptible-infectious-recovered (SIR) model developed by L. Reed and W.H. Frost in the 1920s [1], included the well-mixed assumption such that any two individuals in the population could meet each other. The problem was that, unlike many other simplifying assumptions used in epidemiological modeling whose validity holds in one situation or the other, well-mixed populations are almost non-existent in reality because the nature of human socio-economic interactions is, for the most part, highly heterogeneous (e.g. [2-6]).

Simulation of Population Processes with a Programmable Pocket Calculator.

ERIC Educational Resources Information Center

Kidd, N. A. C.

1979-01-01

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

Dynamics of buckbrush populations under simulated forest restoration alternatives

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

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

Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)

Treesearch

David W. Huffman; Margaret M. Moore

2008-01-01

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

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Modelling southern elephant seals Mirounga leonina using an individual-based model coupled with a dynamic energy budget

PubMed Central

Melbourne-Thomas, Jessica; Corney, Stuart P.; McMahon, Clive R.; Hindell, Mark A.

2018-01-01

Higher trophic-level species are an integral component of any marine ecosystem. Despite their importance, methods for representing these species in end-to-end ecosystem models often have limited representation of life histories, energetics and behaviour. We built an individual-based model coupled with a dynamic energy budget for female southern elephant seals Mirounga leonina to demonstrate a method for detailed representation of marine mammals. We aimed to develop a model which could i) simulate energy use and life histories, as well as breeding traits of southern elephant seals in an emergent manner, ii) project a stable population over time, and iii) have realistic population dynamics and structure based on emergent life history features (such as age at first breeding, lifespan, fecundity and (yearling) survival). We evaluated the model’s ability to represent a stable population over long time periods (>10 generations), including the sensitivity of the emergent properties to variations in key parameters. Analyses indicated that the model is sensitive to changes in resource availability and energy requirements for the transition from pup to juvenile, and juvenile to adult stage. This was particularly the case for breeding success and yearling survival. This model is suitable for use as a standalone tool for investigating the impacts of changes to behaviour and population responses of southern elephant seals. PMID:29596456

Population Dynamics of Belonolaimus longicaudatusin a Cotton Production System

PubMed Central

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

2000-01-01

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

Predator-prey model for the self-organization of stochastic oscillators in dual populations

NASA Astrophysics Data System (ADS)

Moradi, Sara; Anderson, Johan; Gürcan, Ozgür D.

2015-12-01

A predator-prey model of dual populations with stochastic oscillators is presented. A linear cross-coupling between the two populations is introduced following the coupling between the motions of a Wilberforce pendulum in two dimensions: one in the longitudinal and the other in torsional plain. Within each population a Kuramoto-type competition between the phases is assumed. Thus, the synchronization state of the whole system is controlled by these two types of competitions. The results of the numerical simulations show that by adding the linear cross-coupling interactions predator-prey oscillations between the two populations appear, which results in self-regulation of the system by a transfer of synchrony between the two populations. The model represents several important features of the dynamical interplay between the drift wave and zonal flow turbulence in magnetically confined plasmas, and a novel interpretation of the coupled dynamics of drift wave-zonal flow turbulence using synchronization of stochastic oscillator is discussed.

Dynamics of adaptive immunity against phage in bacterial populations

NASA Astrophysics Data System (ADS)

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

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

How Resource Phenology Affects Consumer Population Dynamics.

PubMed

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

2016-02-01

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

Deterministic processes guide long-term synchronised population dynamics in replicate anaerobic digesters

PubMed Central

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

2014-01-01

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

Equation-free modeling unravels the behavior of complex ecological systems

USGS Publications Warehouse

DeAngelis, Donald L.; Yurek, Simeon

2015-01-01

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

Critical short-time dynamics in a system with interacting static and diffusive populations

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

Influence of habitat quality, population size, patch size, and connectivity on patch-occupancy dynamics of the middle spotted woodpecker.

PubMed

Robles, Hugo; Ciudad, Carlos

2012-04-01

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

Capture-recapture methodology

USGS Publications Warehouse

Gould, William R.; Kendall, William L.

2013-01-01

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

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

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

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

Modeling the impact of the indigenous microbial population on the maximum population density of Salmonella on alfalfa.

PubMed

Rijgersberg, Hajo; Franz, Eelco; Nierop Groot, Masja; Tromp, Seth-Oscar

2013-07-01

Within a microbial risk assessment framework, modeling the maximum population density (MPD) of a pathogenic microorganism is important but often not considered. This paper describes a model predicting the MPD of Salmonella on alfalfa as a function of the initial contamination level, the total count of the indigenous microbial population, the maximum pathogen growth rate and the maximum population density of the indigenous microbial population. The model is parameterized by experimental data describing growth of Salmonella on sprouting alfalfa seeds at inoculum size, native microbial load and Pseudomonas fluorescens 2-79. The obtained model fits well to the experimental data, with standard errors less than ten percent of the fitted average values. The results show that the MPD of Salmonella is not only dictated by performance characteristics of Salmonella but depends on the characteristics of the indigenous microbial population like total number of cells and its growth rate. The model can improve the predictions of microbiological growth in quantitative microbial risk assessments. Using this model, the effects of preventive measures to reduce pathogenic load and a concurrent effect on the background population can be better evaluated. If competing microorganisms are more sensitive to a particular decontamination method, a pathogenic microorganism may grow faster and reach a higher level. More knowledge regarding the effect of the indigenous microbial population (size, diversity, composition) of food products on pathogen dynamics is needed in order to make adequate predictions of pathogen dynamics on various food products.

Climatic and density influences on recruitment in an irruptive population of Roosevelt elk

USGS Publications Warehouse

Starns, Heath D.; Ricca, Mark A.; Duarte, Adam; Weckerly, Floyd W.

2014-01-01

Current paradigms of ungulate population ecology recognize that density-dependent and independent mechanisms are not always mutually exclusive. Long-term data sets are necessary to assess the relative strength of each mechanism, especially when populations display irruptive dynamics. Using an 18-year time series of population abundances of Roosevelt elk (Cervus elaphus roosevelti) inhabiting Redwood National Park in northwestern California we assessed the influence of population size and climatic variation on elk recruitment and whether irruptive dynamics occurred. An information-theoretic model selection analysis indicated that abundance lagged 2 years and neither climatic factors nor a mix of abundance and climatic factors influenced elk recruitment. However, density-dependent recruitment differed between when the population was declining and when the population increased and then stabilized at an abundance lower than at the start of the decline. The population displayed irruptive dynamics.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Population variation and individual maximum size in two leech populations: energy extraction from cannibalism or niche widening?

PubMed

Persson, Lennart; Elliott, J Malcolm

2013-05-01

The theory of cannibal dynamics predicts a link between population dynamics and individual life history. In particular, increased individual growth has, in both modeling and empirical studies, been shown to result from a destabilization of population dynamics. We used data from a long-term study of the dynamics of two leech (Erpobdella octoculata) populations to test the hypothesis that maximum size should be higher in a cycling population; one of the study populations exhibited a delayed feedback cycle while the other population showed no sign of cyclicity. A hump-shaped relationship between individual mass of 1-year-old leeches and offspring density the previous year was present in both populations. As predicted from the theory, the maximum mass of individuals was much larger in the fluctuating population. In contrast to predictions, the higher growth rate was not related to energy extraction from cannibalism. Instead, the higher individual mass is suggested to be due to increased availability of resources due to a niche widening with increased individual body mass. The larger individual mass in the fluctuating population was related to a stronger correlation between the densities of 1-year-old individuals and 2-year-old individuals the following year in this population. Although cannibalism was the major mechanism regulating population dynamics, its importance was negligible in terms of providing cannibalizing individuals with energy subsequently increasing their fecundity. Instead, the study identifies a need for theoretical and empirical studies on the largely unstudied interplay between ontogenetic niche shifts and cannibalistic population dynamics.

A methodology for evaluation of parent-mutant competition using a generalized non-linear ecosystem model

Treesearch

Raymond L. Czaplewski

1973-01-01

A generalized, non-linear population dynamics model of an ecosystem is used to investigate the direction of selective pressures upon a mutant by studying the competition between parent and mutant populations. The model has the advantages of considering selection as operating on the phenotype, of retaining the interaction of the mutant population with the ecosystem as a...

NexGen PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models

EPA Science Inventory

We examine how the integration of evolutionary and ecological processes in population dynamics – an emerging framework in ecology – could be incorporated into population viability analysis (PVA). Driven by parallel, complementary advances in population genomics and computational ...

Individual-based modelling of population growth and diffusion in discrete time.

PubMed

Tkachenko, Natalie; Weissmann, John D; Petersen, Wesley P; Lake, George; Zollikofer, Christoph P E; Callegari, Simone

2017-01-01

Individual-based models (IBMs) of human populations capture spatio-temporal dynamics using rules that govern the birth, behavior, and death of individuals. We explore a stochastic IBM of logistic growth-diffusion with constant time steps and independent, simultaneous actions of birth, death, and movement that approaches the Fisher-Kolmogorov model in the continuum limit. This model is well-suited to parallelization on high-performance computers. We explore its emergent properties with analytical approximations and numerical simulations in parameter ranges relevant to human population dynamics and ecology, and reproduce continuous-time results in the limit of small transition probabilities. Our model prediction indicates that the population density and dispersal speed are affected by fluctuations in the number of individuals. The discrete-time model displays novel properties owing to the binomial character of the fluctuations: in certain regimes of the growth model, a decrease in time step size drives the system away from the continuum limit. These effects are especially important at local population sizes of <50 individuals, which largely correspond to group sizes of hunter-gatherers. As an application scenario, we model the late Pleistocene dispersal of Homo sapiens into the Americas, and discuss the agreement of model-based estimates of first-arrival dates with archaeological dates in dependence of IBM model parameter settings.

Population Dynamics of a Salmonella Lytic Phage and Its Host: Implications of the Host Bacterial Growth Rate in Modelling

PubMed Central

Santos, Sílvio B.; Carvalho, Carla; Azeredo, Joana; Ferreira, Eugénio C.

2014-01-01

The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist. PMID:25051248

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

USGS Publications Warehouse

Taylor, Rebecca L.; Udevitz, Mark S.

2015-01-01

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

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

PubMed

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 dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species.

New insights into the nonadiabatic state population dynamics of model proton-coupled electron transfer reactions from the mixed quantum-classical Liouville approach

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

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

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

SAM Works! A Systems Approach Model for Adult Education Programming.

ERIC Educational Resources Information Center

Murk, Peter J.; Wells, John H.

The Systems Approach Model (SAM) is a dynamic approach to planning adult and continuing education that is intended to provide the flexibility, creativity, and meaningfulness necessary to meet the needs and interests of an ever-expanding and ever-aging student population. The SAM model consists of the following dynamically interrelated and…

Special issue dedicated to the 70th birthday of Glenn F. Webb. Preface.

PubMed

Hinow, Peter; Magal, Pierre; Ruan, Shigui

2015-08-01

This special issue is dedicated to the 70th birthday of Glenn F. Webb. The topics of the 12 articles appearing in this special issue include evolutionary dynamics of population growth, spatio-temporal dynamics in reaction-diffusion biological models, transmission dynamics of infectious diseases, modeling of antibiotic-resistant bacteria in hospitals, analysis of Prion models, age-structured models in ecology and epidemiology, modeling of immune response to infections, modeling of cancer growth, etc. These topics partially represent the broad areas of Glenn's research interest.

Macroscopic neural mass model constructed from a current-based network model of spiking neurons.

PubMed

Umehara, Hiroaki; Okada, Masato; Teramae, Jun-Nosuke; Naruse, Yasushi

2017-02-01

Neural mass models (NMMs) are efficient frameworks for describing macroscopic cortical dynamics including electroencephalogram and magnetoencephalogram signals. Originally, these models were formulated on an empirical basis of synaptic dynamics with relatively long time constants. By clarifying the relations between NMMs and the dynamics of microscopic structures such as neurons and synapses, we can better understand cortical and neural mechanisms from a multi-scale perspective. In a previous study, the NMMs were analytically derived by averaging the equations of synaptic dynamics over the neurons in the population and further averaging the equations of the membrane-potential dynamics. However, the averaging of synaptic current assumes that the neuron membrane potentials are nearly time invariant and that they remain at sub-threshold levels to retain the conductance-based model. This approximation limits the NMM to the non-firing state. In the present study, we newly propose a derivation of a NMM by alternatively approximating the synaptic current which is assumed to be independent of the membrane potential, thus adopting a current-based model. Our proposed model releases the constraint of the nearly constant membrane potential. We confirm that the obtained model is reducible to the previous model in the non-firing situation and that it reproduces the temporal mean values and relative power spectrum densities of the average membrane potentials for the spiking neurons. It is further ensured that the existing NMM properly models the averaged dynamics over individual neurons even if they are spiking in the populations.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

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

PubMed

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

2018-08-14

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

Is the Voter Model a Model for Voters?

NASA Astrophysics Data System (ADS)

Fernández-Gracia, Juan; Suchecki, Krzysztof; Ramasco, José J.; San Miguel, Maxi; Eguíluz, Víctor M.

2014-04-01

The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anisotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of U.S. presidential elections as the stationary vote-share fluctuations across counties and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when the geographical space is coarse grained at different scales—from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations.

An Application of System Dynamics Analysis to Ecosystem Management at the Poinsett Weapons Range, Shaw AFB SC

DTIC Science & Technology

1997-12-01

younger trees with thinner sapwood and greater heartwood diameter than other trees in the area . The RCW requires approximately 6 inches in diameter...and management areas and have explored applications of system dynamics modeling at the graduate level. The attached application addresses specific...Population Sensitivity to Birth Rate 62 10. RCW Population with Variation of Relatedness Entity 64 11. RCW Population with Variation of Foraging Area

The evolution of labile traits in sex- and age-structured populations.

PubMed

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

2016-03-01

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

A discrete stage-structured model of California newt population dynamics during a period of drought.

PubMed

Jones, Marjorie T; Milligan, William R; Kats, Lee B; Vandergon, Thomas L; Honeycutt, Rodney L; Fisher, Robert N; Davis, Courtney L; Lucas, Timothy A

2017-02-07

We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short. Copyright © 2016 Elsevier Ltd. All rights reserved.

A discrete stage-structured model of California newt population dynamics during a period of drought

USGS Publications Warehouse

Jones, Marjorie T.; Milligan, William R.; Kats, Lee B.; Vandergon, Thomas L.; Honeycutt, Rodney L.; Fisher, Robert N.; Davis, Courtney L.; Lucas, Timothy A.

2017-01-01

We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short.

A coupled biophysical model for the distribution of the great scallop Pecten maximus in the English Channel

NASA Astrophysics Data System (ADS)

Le Goff, Clément; Lavaud, Romain; Cugier, Philippe; Jean, Fred; Flye-Sainte-Marie, Jonathan; Foucher, Eric; Desroy, Nicolas; Fifas, Spyros; Foveau, Aurélie

2017-03-01

In this paper we used a modelling approach integrating both physical and biological constraints to understand the biogeographical distribution of the great scallop Pecten maximus in the English Channel during its whole life cycle. A 3D bio-hydrodynamical model (ECO-MARS3D) providing environmental conditions was coupled to (i) a population dynamics model and (ii) an individual ecophysiological model (Dynamic Energy Budget model). We performed the coupling sequentially, which underlined the respective role of biological and physical factors in defining P. maximus distribution in the English Channel. Results show that larval dispersion by hydrodynamics explains most of the scallop distribution and enlighten the main known hotspots for the population, basically corresponding to the main fishing areas. The mechanistic description of individual bioenergetics shows that food availability and temperature control growth and reproduction and explain how populations may maintain themselves in particular locations. This last coupling leads to more realistic densities and distributions of adults in the English Channel. The results of this study improves our knowledge on the stock and distribution dynamics of P. maximus, and provides grounds for useful tools to support management strategies.

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

PubMed

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

2016-12-01

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

Dynamic analysis of a parasite population model.

PubMed

Sibona, G J; Condat, C A

2002-03-01

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

Dynamic analysis of a parasite population model

NASA Astrophysics Data System (ADS)

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

2002-03-01

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

Noise shaping in populations of coupled model neurons.

PubMed

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

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

Population clocks: motor timing with neural dynamics

PubMed Central

Buonomano, Dean V.; Laje, Rodrigo

2010-01-01

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

Structural drift: the population dynamics of sequential learning.

PubMed

Crutchfield, James P; Whalen, Sean

2012-01-01

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

Modeling Exponential Population Growth

ERIC Educational Resources Information Center

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…

Model of white oak flower survival and maturation

Treesearch

David R. Larsen; Robert A. Cecich

1997-01-01

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

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-06-01

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

Garter snake population dynamics from a 16-year study: considerations for ecological monitoring

Treesearch

Amy J. Lind; Hartwell H. Welsh Jr; David A. Tallmon

2005-01-01

Snakes have recently been proposed as model organisms for addressing both evolutionary and ecological questions. Because of their middle position in many food webs they may be useful indicators of trophic complexity and dynamics. However, reliable data on snake populations are rare due to the challenges of sampling these patchily distributed, cryptic, and often...

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

NASA Astrophysics Data System (ADS)

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.

A Role for M-Matrices in Modelling Population Growth

ERIC Educational Resources Information Center

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,…

The Expansion of National Educational Systems: Tests of a Population Ecology Model

ERIC Educational Resources Information Center

Nielsen, Francois; Hannan, Michael T.

1977-01-01

This paper investigates the expansion of enrollments in national systems of education during the 1950-1970 period from the point of view of the population ecology of organizations. A simplified dynamic model of the growth of a population of educational organizations is estimated using various techniques for pooling time series of data. (Author/JM)

An agent-based model of tsetse fly response to seasonal climatic drivers: Assessing the impact on sleeping sickness transmission rates.

PubMed

Alderton, Simon; Macleod, Ewan T; Anderson, Neil E; Palmer, Gwen; Machila, Noreen; Simuunza, Martin; Welburn, Susan C; Atkinson, Peter M

2018-02-01

This paper presents the development of an agent-based model (ABM) to incorporate climatic drivers which affect tsetse fly (G. m. morsitans) population dynamics, and ultimately disease transmission. The model was used to gain a greater understanding of how tsetse populations fluctuate seasonally, and investigate any response observed in Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) disease transmission, with a view to gaining a greater understanding of disease dynamics. Such an understanding is essential for the development of appropriate, well-targeted mitigation strategies in the future. The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The model incorporates climatic factors that affect pupal mortality, pupal development, birth rate, and death rate. In combination with fine scale demographic data such as ethnicity, age and gender for the human population in the region, as well as an animal census and a sample of daily routines, we create a detailed, plausible simulation model to explore tsetse population and disease transmission dynamics. The seasonally-driven model suggests that the number of infections reported annually in the simulation is likely to be a reasonable representation of reality, taking into account the high levels of under-detection observed. Similar infection rates were observed in human (0.355 per 1000 person-years (SE = 0.013)), and cattle (0.281 per 1000 cattle-years (SE = 0.025)) populations, likely due to the sparsity of cattle close to the tsetse interface. The model suggests that immigrant tribes and school children are at greatest risk of infection, a result that derives from the bottom-up nature of the ABM and conditioning on multiple constraints. This result could not be inferred using alternative population-level modelling approaches. In producing a model which models the tsetse population at a very fine resolution, we were able to analyse and evaluate specific elements of the output, such as pupal development and the progression of the teneral population, allowing the development of our understanding of the tsetse population as a whole. This is an important step in the production of a more accurate transmission model for rHAT which can, in turn, help us to gain a greater understanding of the transmission system as a whole.

LONG-TERM PROJECTIONS OF EASTERN OYSTER POPULATIONS UNDER VARIOUS MANAGEMENT SCENARIOS

EPA Science Inventory

Time series of fishery-dependent and fishery-independent data were used to parameterize a model of oyster population dynamics for Maryland's Chesapeake Bay. Model parameters are (1) fishing mortality, estimated from differences between predicted and reported landings scaled to a ...

Influence of network dynamics on the spread of sexually transmitted diseases.

PubMed

Risau-Gusman, Sebastián

2012-06-07

Network epidemiology often assumes that the relationships defining the social network of a population are static. The dynamics of relationships is only taken indirectly into account by assuming that the relevant information to study epidemic spread is encoded in the network obtained, by considering numbers of partners accumulated over periods of time roughly proportional to the infectious period of the disease. On the other hand, models explicitly including social dynamics are often too schematic to provide a reasonable representation of a real population, or so detailed that no general conclusions can be drawn from them. Here, we present a model of social dynamics that is general enough so its parameters can be obtained by fitting data from surveys about sexual behaviour, but that can still be studied analytically, using mean-field techniques. This allows us to obtain some general results about epidemic spreading. We show that using accumulated network data to estimate the static epidemic threshold lead to a significant underestimation of that threshold. We also show that, for a dynamic network, the relative epidemic threshold is an increasing function of the infectious period of the disease, implying that the static value is a lower bound to the real threshold. A practical example is given of how to apply the model to the study of a real population.

Influence of network dynamics on the spread of sexually transmitted diseases

PubMed Central

Risau-Gusman, Sebastián

2012-01-01

Network epidemiology often assumes that the relationships defining the social network of a population are static. The dynamics of relationships is only taken indirectly into account by assuming that the relevant information to study epidemic spread is encoded in the network obtained, by considering numbers of partners accumulated over periods of time roughly proportional to the infectious period of the disease. On the other hand, models explicitly including social dynamics are often too schematic to provide a reasonable representation of a real population, or so detailed that no general conclusions can be drawn from them. Here, we present a model of social dynamics that is general enough so its parameters can be obtained by fitting data from surveys about sexual behaviour, but that can still be studied analytically, using mean-field techniques. This allows us to obtain some general results about epidemic spreading. We show that using accumulated network data to estimate the static epidemic threshold lead to a significant underestimation of that threshold. We also show that, for a dynamic network, the relative epidemic threshold is an increasing function of the infectious period of the disease, implying that the static value is a lower bound to the real threshold. A practical example is given of how to apply the model to the study of a real population. PMID:22112655

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Wave of chaos in a spatial eco-epidemiological system: Generating realistic patterns of patchiness in rabbit-lynx dynamics.

PubMed

Upadhyay, Ranjit Kumar; Roy, Parimita; Venkataraman, C; Madzvamuse, A

2016-11-01

In the present paper, we propose and analyze an eco-epidemiological model with diffusion to study the dynamics of rabbit populations which are consumed by lynx populations. Existence, boundedness, stability and bifurcation analyses of solutions for the proposed rabbit-lynx model are performed. Results show that in the presence of diffusion the model has the potential of exhibiting Turing instability. Numerical results (finite difference and finite element methods) reveal the existence of the wave of chaos and this appears to be a dominant mode of disease dispersal. We also show the mechanism of spatiotemporal pattern formation resulting from the Hopf bifurcation analysis, which can be a potential candidate for understanding the complex spatiotemporal dynamics of eco-epidemiological systems. Implications of the asymptotic transmission rate on disease eradication among rabbit population which in turn enhances the survival of Iberian lynx are discussed. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

PubMed

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

2014-07-18

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

Antibiotic-induced population fluctuations and stochastic clearance of bacteria

PubMed Central

Le, Dai; Şimşek, Emrah; Chaudhry, Waqas

2018-01-01

Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinically-isolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria. PMID:29508699

Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants.

PubMed

Miller, Tom E X

2007-07-01

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

Comparison of reintroduction and enhancement effects on metapopulation viability

USGS Publications Warehouse

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

2015-01-01

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

Social Information Links Individual Behavior to Population and Community Dynamics.

PubMed

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

2018-05-07

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

Introduction to Population Modeling.

ERIC Educational Resources Information Center

Frauenthal, James C.

The focus is on the formulation and solution of mathematical models with the idea of a population employed mainly as a pedogogical tool. If the biological setting is stripped away, the material can be interpreted as topics or the qualitative behavior of differential and difference equations. The first group of models investigate the dynamics of a…

Statistical Physics of Population Genetics in the Low Population Size Limit

NASA Astrophysics Data System (ADS)

Atwal, Gurinder

The understanding of evolutionary processes lends itself naturally to theory and computation, and the entire field of population genetics has benefited greatly from the influx of methods from applied mathematics for decades. However, in spite of all this effort, there are a number of key dynamical models of evolution that have resisted analytical treatment. In addition, modern DNA sequencing technologies have magnified the amount of genetic data available, revealing an excess of rare genetic variants in human genomes, challenging the predictions of conventional theory. Here I will show that methods from statistical physics can be used to model the distribution of genetic variants, incorporating selection and spatial degrees of freedom. In particular, a functional path-integral formulation of the Wright-Fisher process maps exactly to the dynamics of a particle in an effective potential, beyond the mean field approximation. In the small population size limit, the dynamics are dominated by instanton-like solutions which determine the probability of fixation in short timescales. These results are directly relevant for understanding the unusual genetic variant distribution at moving frontiers of populations.

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

PubMed

Holland, E Penelope; James, Alex; Ruscoe, Wendy A; Pech, Roger P; Byrom, Andrea E

2015-01-01

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.

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

PubMed

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

2007-06-01

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

Modelling the transmission dynamics of Theileria annulata: model structure and validation for the Turkish context

PubMed Central

SUTTON, A. J.; KARAGENC, T.; BAKIRCI, S.; SARALI, H.; PEKEL, G.; MEDLEY, G. F.

2012-01-01

SUMMARY A mathematical model that describes the transmission dynamics of Theileria annulata is proposed that consists of 2 host components: the Hyalomma tick population and a compartmental model of T. annulata infection in the cattle population. The model was parameterized using data describing tick infestation and the infection status of cattle in Turkey from 2006 to 2008. The tick attachment rates are highly seasonal and because of the temporal separation of infectious and susceptible ticks virtually all ticks are infected by carrier cattle, so that annual peaks of disease in cattle do not impact on infection in the Hyalomma tick population. The impact of intervention measures that target the tick population both on the host and in the environment and their impact on the transmission of T. annulata were investigated. Interventions that have a limited ‘one-off’ impact and interventions that have a more permanent impact were both considered. The results from the model show the importance of targeting ticks during the period when they have left their first host as nymphs but have yet to feed on their second host. PMID:22309815

Cancer Evolution: Mathematical Models and Computational Inference

PubMed Central

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

2015-01-01

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

Dynamics of Predator-Prey Metapopulations with Allee Effects.

PubMed

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

2016-08-01

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

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

PubMed

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

2017-03-01

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

Dynamics of a neutral delay equation for an insect population with long larval and short adult phases

NASA Astrophysics Data System (ADS)

Gourley, Stephen A.; Kuang, Yang

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

Dynamics of a plant-herbivore-predator system with plant-toxicity

USGS Publications Warehouse

Feng, Zhilan; Qiu, Zhipeng; Liu, Rongsong; DeAngelis, Donald L.

2011-01-01

A system of ordinary differential equations is considered that models the interactions of two plant species populations, an herbivore population, and a predator population. We use a toxin-determined functional response to describe the interactions between plant species and herbivores and use a Holling Type II functional response to model the interactions between herbivores and predators. In order to study how the predators impact the succession of vegetation, we derive invasion conditions under which a plant species can invade into an environment in which another plant species is co-existing with a herbivore population with or without a predator population. These conditions provide threshold quantities for several parameters that may play a key role in the dynamics of the system. Numerical simulations are conducted to reinforce the analytical results. This model can be applied to a boreal ecosystem trophic chain to examine the possible cascading effects of predator-control actions when plant species differ in their levels of toxic defense.

Dynamics of a plant-herbivore-predator system with plant-toxicity.

PubMed

Feng, Zhilan; Qiu, Zhipeng; Liu, Rongsong; DeAngelis, Donald L

2011-02-01

A system of ordinary differential equations is considered that models the interactions of two plant species populations, an herbivore population, and a predator population. We use a toxin-determined functional response to describe the interactions between plant species and herbivores and use a Holling Type II functional response to model the interactions between herbivores and predators. In order to study how the predators impact the succession of vegetation, we derive invasion conditions under which a plant species can invade into an environment in which another plant species is co-existing with a herbivore population with or without a predator population. These conditions provide threshold quantities for several parameters that may play a key role in the dynamics of the system. Numerical simulations are conducted to reinforce the analytical results. This model can be applied to a boreal ecosystem trophic chain to examine the possible cascading effects of predator-control actions when plant species differ in their levels of toxic defense. Published by Elsevier Inc.

Threshold Dynamics of a Temperature-Dependent Stage-Structured Mosquito Population Model with Nested Delays.

PubMed

Wang, Xiunan; Zou, Xingfu

2018-05-21

Mosquito-borne diseases remain a significant threat to public health and economics. Since mosquitoes are quite sensitive to temperature, global warming may not only worsen the disease transmission case in current endemic areas but also facilitate mosquito population together with pathogens to establish in new regions. Therefore, understanding mosquito population dynamics under the impact of temperature is considerably important for making disease control policies. In this paper, we develop a stage-structured mosquito population model in the environment of a temperature-controlled experiment. The model turns out to be a system of periodic delay differential equations with periodic delays. We show that the basic reproduction number is a threshold parameter which determines whether the mosquito population goes to extinction or remains persistent. We then estimate the parameter values for Aedes aegypti, the mosquito that transmits dengue virus. We verify the analytic result by numerical simulations with the temperature data of Colombo, Sri Lanka where a dengue outbreak occurred in 2017.

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

USGS Publications Warehouse

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

2013-01-01

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

Density-dependence as a size-independent regulatory mechanism.

PubMed

de Vladar, Harold P

2006-01-21

The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.

Seasonal Population Dynamics of Three Potato Pests in Washington State.

PubMed

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

2016-08-01

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

Evolutionary suicide through a non-catastrophic bifurcation: adaptive dynamics of pathogens with frequency-dependent transmission.

PubMed

Boldin, Barbara; Kisdi, Éva

2016-03-01

Evolutionary suicide is a riveting phenomenon in which adaptive evolution drives a viable population to extinction. Gyllenberg and Parvinen (Bull Math Biol 63(5):981-993, 2001) showed that, in a wide class of deterministic population models, a discontinuous transition to extinction is a necessary condition for evolutionary suicide. An implicit assumption of their proof is that the invasion fitness of a rare strategy is well-defined also in the extinction state of the population. Epidemic models with frequency-dependent incidence, which are often used to model the spread of sexually transmitted infections or the dynamics of infectious diseases within herds, violate this assumption. In these models, evolutionary suicide can occur through a non-catastrophic bifurcation whereby pathogen adaptation leads to a continuous decline of host (and consequently pathogen) population size to zero. Evolutionary suicide of pathogens with frequency-dependent transmission can occur in two ways, with pathogen strains evolving either higher or lower virulence.

Modeling the dynamical interaction between epidemics on overlay networks

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

Integrating association data and disease dynamics: an illustration using African Buffalo in Kruger National Park

USGS Publications Warehouse

Cross, Paul C.; James O, Lloyd-Smith; Bowers, Justin A.; Hay, Craig T.; Hofmeyr, Markus; Getz, Wayne M.

2004-01-01

Recognition is a prerequisite for non-random association amongst individuals. We explore how non-random association patterns (i.e. who spends time with whom) affect disease dynamics. We estimated the amount of time individuals spent together per month using radio-tracking data from African buffalo and incorporated these data into a dynamic social network model. The dynamic nature of the network has a strong influence on simulated disease dynamics particularly for diseases with shorter infectious periods. Cluster analyses of the association data demonstrated that buffalo herds were not as well defined as previously thought. Associations were more tightly clustered in 2002 than 2003, perhaps due to drier conditions in 2003. As a result, diseases may spread faster during drought conditions due to increased population mixing. Association data are often collected but this is the first use of empirical data in a network disease model in a wildlife population.

Sea lice and salmon population dynamics: effects of exposure time for migratory fish.

PubMed

Krkosek, Martin; Morton, Alexandra; Volpe, John P; Lewis, Mark A

2009-08-07

The ecological impact of parasite transmission from fish farms is probably mediated by the migration of wild fishes, which determines the period of exposure to parasites. For Pacific salmon and the parasitic sea louse, Lepeophtheirus salmonis, analysis of the exposure period may resolve conflicting observations of epizootic mortality in field studies and parasite rejection in experiments. This is because exposure periods can differ by 2-3 orders of magnitude, ranging from months in the field to hours in experiments. We developed a mathematical model of salmon-louse population dynamics, parametrized by a study that monitored naturally infected juvenile salmon held in ocean enclosures. Analysis of replicated trials indicates that lice suffer high mortality, particularly during pre-adult stages. The model suggests louse populations rapidly decline following brief exposure of juvenile salmon, similar to laboratory study designs and data. However, when the exposure period lasts for several weeks, as occurs when juvenile salmon migrate past salmon farms, the model predicts that lice accumulate to abundances that can elevate salmon mortality and depress salmon populations. The duration of parasite exposure is probably critical to salmon-louse population dynamics, and should therefore be accommodated in coastal planning and management where fish farms are situated on wild fish migration routes.

[Modelling of selection acting upon the pleioptropic locus in an asynchronous population].

PubMed

Zhdanov, O L; Frisman, E Ia

2014-08-01

We created and examined a mathematical model describing the size and genetic composition dynamics in a population with two age classes, where the survival of both zygotes and adult individuals is determined by one pleioptropic locus. Even under present limitations, as the outside effects of a complex multigenic system are reduced to the case of single locus, our model demonstrates a wide range of different evolutionary scenarios for possible changes in the population dynamics. An increase in the reproductive potential and survival is accompanied by a transition from stable to oscillating population numbers. However, the evolutionary growth of these parameters may be nonmonotonic and may fluctuate significantly. In the case of antagonistic pleioptropy, an increase in one of these parameters usually leads to a predictable decrease in the other. This, in turn, may even stabilize the numbers and genetic compositions of the age groups. We demonstrated that selection acting on later stages of the life cycle is accompanied by destabilization of the Hardy-Weinberg equilibriums that link allele and genotype frequencies. We obtained a balance ratio, which allowed us to compare the combined fitness of the genotypes and to demonstrate that selection leads to the exclusion of the least adapted genotypes. Initial conditionsmay in some cases determine the genetic composition and pattern of population size dynamics.

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

PubMed

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

2009-10-13

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

Equilibrium analysis of a yellow Fever dynamical model with vaccination.

PubMed

Martorano Raimundo, Silvia; Amaku, Marcos; Massad, Eduardo

2015-01-01

We propose an equilibrium analysis of a dynamical model of yellow fever transmission in the presence of a vaccine. The model considers both human and vector populations. We found thresholds parameters that affect the development of the disease and the infectious status of the human population in the presence of a vaccine whose protection may wane over time. In particular, we derived a threshold vaccination rate, above which the disease would be eradicated from the human population. We show that if the mortality rate of the mosquitoes is greater than a given threshold, then the disease is naturally (without intervention) eradicated from the population. In contrast, if the mortality rate of the mosquitoes is less than that threshold, then the disease is eradicated from the populations only when the growing rate of humans is less than another threshold; otherwise, the disease is eradicated only if the reproduction number of the infection after vaccination is less than 1. When this reproduction number is greater than 1, the disease will be eradicated from the human population if the vaccination rate is greater than a given threshold; otherwise, the disease will establish itself among humans, reaching a stable endemic equilibrium. The analysis presented in this paper can be useful, both to the better understanding of the disease dynamics and also for the planning of vaccination strategies.

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

PubMed Central

Bartolino, Valerio; Tian, Huidong; Bergström, Ulf; Jounela, Pekka; Aro, Eero; Dieterich, Christian; Meier, H. E. Markus; Cardinale, Massimiliano; Bland, Barbara

2017-01-01

Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes. PMID:28207804

Disease Spread and Its Effect on Population Dynamics in Heterogeneous Environment

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Roy, Parimita

In this paper, an eco-epidemiological model in which both species diffuse along a spatial gradient has been shown to exhibit temporal chaos at a fixed point in space. The proposed model is a modification of the model recently presented by Upadhyay and Roy [2014]. The spatial interactions among the species have been represented in the form of reaction-diffusion equations. The model incorporates the intrinsic growth rate of fish population which varies linearly with the depth of water. Numerical results show that diffusion can drive otherwise stable system into aperiodic behavior with sensitivity to initial conditions. We show that spatially induced chaos plays an important role in spatial pattern formation in heterogeneous environment. Spatiotemporal distributions of species have been simulated using the diffusivity assumptions realistic for natural eco-epidemic systems. We found that in heterogeneous environment, the temporal dynamics of both the species are drastically different and show chaotic behavior. It was also found that the instability observed in the model is due to spatial heterogeneity and diffusion-driven. Cumulative death rate of predator has an appreciable effect on model dynamics as the spatial distribution of all constituent populations exhibit significant changes when this model parameter is changed and it acts as a regularizing factor.

An age-structured model for the coupled dynamics of HIV and HSV-2.

PubMed

Kapitanov, Georgi; Alvey, Christina; Vogt-Geisse, Katia; Feng, Zhilan

2015-08-01

Evidence suggests a strong correlation between the prevalence of HSV-2 (genital herpes) and the perseverance of the HIV epidemic. HSV-2 is an incurable viral infection, characterized by periodic reactivation. We construct a model of the co-infection dynamics between the two diseases by incorporating a time-since-infection variable to track the alternating periods of infectiousness of HSV-2. The model considers only heterosexual relationships and distinguishes three population groups: males, general population females, and female sex workers. We calculate the basic reproduction numbers for each disease that provide threshold conditions, which determine whether a disease dies out or becomes endemic in the absence of the other disease. We also derive the invasion reproduction numbers that determine whether or not a disease can invade into a population in which the other disease is endemic. The calculations of the invasion reproduction numbers suggest a new aspect in their interpretation - the class from which the initial disease carrier arises is important for understanding the invasion dynamics and biological interpretation of the expressions of the reproduction numbers. Sensitivity analysis is conducted to examine the role of model parameters in influencing the model outcomes. The results are discussed in the last section.

Bipartite graphs as models of population structures in evolutionary multiplayer games.

PubMed

Peña, Jorge; Rochat, Yannick

2012-01-01

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

Punctuated equilibrium and shock waves in molecular models of biological evolution.

PubMed

Saakian, David B; Ghazaryan, Makar H; Hu, Chin-Kun

2014-08-01

We consider the dynamics in infinite population evolution models with a general symmetric fitness landscape. We find shock waves, i.e., discontinuous transitions in the mean fitness, in evolution dynamics even with smooth fitness landscapes, which means that the search for the optimal evolution trajectory is more complicated. These shock waves appear in the case of positive epistasis and can be used to represent punctuated equilibria in biological evolution during long geological time scales. We find exact analytical solutions for discontinuous dynamics at the large-genome-length limit and derive optimal mutation rates for a fixed fitness landscape to send the population from the initial configuration to some final configuration in the fastest way.

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

PubMed

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.

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

PubMed Central

Pfeiffer, Dirk U.; Bendrey, Robin

2017-01-01

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. PMID:28386446

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

PubMed Central

Lythgoe, Katrina A.; Blanquart, François

2016-01-01

The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation. PMID:27706164

Plant toxicity, adaptive herbivory, and plant community dynamics

Treesearch

Zhilan Feng; Rongsong Liu; Donald L. DeAngelis; John P. Bryant; Knut Kielland; F. Stuart Chapin; Robert K. Swihart

2009-01-01

We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of...

Global dynamics of avian influenza epidemic models with psychological effect.

PubMed

Liu, Sanhong; Pang, Liuyong; Ruan, Shigui; Zhang, Xinan

2015-01-01

Cross-sectional surveys conducted in Thailand and China after the outbreaks of the avian influenza A H5N1 and H7N9 viruses show a high degree of awareness of human avian influenza in both urban and rural populations, a higher level of proper hygienic practice among urban residents, and in particular a dramatically reduced number of visits to live markets in urban population after the influenza A H7N9 outbreak in China in 2013. In this paper, taking into account the psychological effect toward avian influenza in the human population, a bird-to-human transmission model in which the avian population exhibits saturation effect is constructed. The dynamical behavior of the model is studied by using the basic reproduction number. The results demonstrate that the saturation effect within avian population and the psychological effect in human population cannot change the stability of equilibria but can affect the number of infected humans if the disease is prevalent. Numerical simulations are given to support the theoretical results and sensitivity analyses of the basic reproduction number in terms of model parameters that are performed to seek for effective control measures for avian influenza.

Linking body mass and group dynamics in an obligate cooperative breeder.

PubMed

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

2014-11-01

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

Sequence selection by dynamical symmetry breaking in an autocatalytic binary polymer model

NASA Astrophysics Data System (ADS)

Fellermann, Harold; Tanaka, Shinpei; Rasmussen, Steen

2017-12-01

Template-directed replication of nucleic acids is at the essence of all living beings and a major milestone for any origin of life scenario. We present an idealized model of prebiotic sequence replication, where binary polymers act as templates for their autocatalytic replication, thereby serving as each others reactants and products in an intertwined molecular ecology. Our model demonstrates how autocatalysis alters the qualitative and quantitative system dynamics in counterintuitive ways. Most notably, numerical simulations reveal a very strong intrinsic selection mechanism that favors the appearance of a few population structures with highly ordered and repetitive sequence patterns when starting from a pool of monomers. We demonstrate both analytically and through simulation how this "selection of the dullest" is caused by continued symmetry breaking through random fluctuations in the transient dynamics that are amplified by autocatalysis and eventually propagate to the population level. The impact of these observations on related prebiotic mathematical models is discussed.

Disorder and Chaos: Developing and Teaching an Interdisciplinary Course on Chemical Dynamics

ERIC Educational Resources Information Center

Desjardins, Steven G.

2008-01-01

In this paper we describe an interdisciplinary course on dynamics that is appropriate for nonscience majors. This course introduces ideas about mathematical modeling using examples based on pendulums, chemical kinetics, and population dynamics. The unique emphasis for a nonmajors course is on chemical reactions as dynamical systems that do more…

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

Cancer dormancy and criticality from a game theory perspective.

PubMed

Wu, Amy; Liao, David; Kirilin, Vlamimir; Lin, Ke-Chih; Torga, Gonzalo; Qu, Junle; Liu, Liyu; Sturm, James C; Pienta, Kenneth; Austin, Robert

2018-01-01

The physics of cancer dormancy, the time between initial cancer treatment and re-emergence after a protracted period, is a puzzle. Cancer cells interact with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer and dormancy. We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbations due to cell migration. We determine to what extent the time-dependence of the populations can be quantitively understood in spite of the underlying complexity of the individual agents and model the phenomena of dormancy.

Evolutionary dynamics of cooperation in neutral populations

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

Host population structure and treatment frequency maintain balancing selection on drug resistance

PubMed Central

Baskerville, Edward B.; Colijn, Caroline; Hanage, William; Fraser, Christophe; Lipsitch, Marc

2017-01-01

It is a truism that antimicrobial drugs select for resistance, but explaining pathogen- and population-specific variation in patterns of resistance remains an open problem. Like other common commensals, Streptococcus pneumoniae has demonstrated persistent coexistence of drug-sensitive and drug-resistant strains. Theoretically, this outcome is unlikely. We modelled the dynamics of competing strains of S. pneumoniae to investigate the impact of transmission dynamics and treatment-induced selective pressures on the probability of stable coexistence. We find that the outcome of competition is extremely sensitive to structure in the host population, although coexistence can arise from age-assortative transmission models with age-varying rates of antibiotic use. Moreover, we find that the selective pressure from antibiotics arises not so much from the rate of antibiotic use per se but from the frequency of treatment: frequent antibiotic therapy disproportionately impacts the fitness of sensitive strains. This same phenomenon explains why serotypes with longer durations of carriage tend to be more resistant. These dynamics may apply to other potentially pathogenic, microbial commensals and highlight how population structure, which is often omitted from models, can have a large impact. PMID:28835542

Dynamics of the Rydberg state population of slow highly charged ions impinging a solid surface at arbitrary collision geometry

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

PubMed Central

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

The Stochastic Multi-strain Dengue Model: Analysis of the Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Stollenwerk, Nico; Kooi, Bob W.

2011-09-01

Dengue dynamics is well known to be particularly complex with large fluctuations of disease incidences. An epidemic multi-strain model motivated by dengue fever epidemiology shows deterministic chaos in wide parameter regions. The addition of seasonal forcing, mimicking the vectorial dynamics, and a low import of infected individuals, which is realistic in the dynamics of infectious diseases epidemics show complex dynamics and qualitatively a good agreement between empirical DHF monitoring data and the obtained model simulation. The addition of noise can explain the fluctuations observed in the empirical data and for large enough population size, the stochastic system can be well described by the deterministic skeleton.

High-amplitude fluctuations and alternative dynamical states of midges in Lake Myvatn.

PubMed

Ives, Anthony R; Einarsson, Arni; Jansen, Vincent A A; Gardarsson, Arnthor

2008-03-06

Complex dynamics are often shown by simple ecological models and have been clearly demonstrated in laboratory and natural systems. Yet many classes of theoretically possible dynamics are still poorly documented in nature. Here we study long-term time-series data of a midge, Tanytarsus gracilentus (Diptera: Chironomidae), in Lake Myvatn, Iceland. The midge undergoes density fluctuations of almost six orders of magnitude. Rather than regular cycles, however, these fluctuations have irregular periods of 4-7 years, indicating complex dynamics. We fit three consumer-resource models capable of qualitatively distinct dynamics to the data. Of these, the best-fitting model shows alternative dynamical states in the absence of environmental variability; depending on the initial midge densities, the model shows either fluctuations around a fixed point or high-amplitude cycles. This explains the observed complex population dynamics: high-amplitude but irregular fluctuations occur because stochastic variability causes the dynamics to switch between domains of attraction to the alternative states. In the model, the amplitude of fluctuations depends strongly on minute resource subsidies into the midge habitat. These resource subsidies may be sensitive to human-caused changes in the hydrology of the lake, with human impacts such as dredging leading to higher-amplitude fluctuations. Tanytarsus gracilentus is a key component of the Myvatn ecosystem, representing two-thirds of the secondary productivity of the lake and providing vital food resources to fish and to breeding bird populations. Therefore the high-amplitude, irregular fluctuations in midge densities generated by alternative dynamical states dominate much of the ecology of the lake.

Growth dynamics and the evolution of cooperation in microbial populations

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Melbinger, Anna; Frey, Erwin

2012-02-01

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

Two-strain competition in quasineutral stochastic disease dynamics.

PubMed

Kogan, Oleg; Khasin, Michael; Meerson, Baruch; Schneider, David; Myers, Christopher R

2014-10-01

We develop a perturbation method for studying quasineutral competition in a broad class of stochastic competition models and apply it to the analysis of fixation of competing strains in two epidemic models. The first model is a two-strain generalization of the stochastic susceptible-infected-susceptible (SIS) model. Here we extend previous results due to Parsons and Quince [Theor. Popul. Biol. 72, 468 (2007)], Parsons et al. [Theor. Popul. Biol. 74, 302 (2008)], and Lin, Kim, and Doering [J. Stat. Phys. 148, 646 (2012)]. The second model, a two-strain generalization of the stochastic susceptible-infected-recovered (SIR) model with population turnover, has not been studied previously. In each of the two models, when the basic reproduction numbers of the two strains are identical, a system with an infinite population size approaches a point on the deterministic coexistence line (CL): a straight line of fixed points in the phase space of subpopulation sizes. Shot noise drives one of the strain populations to fixation, and the other to extinction, on a time scale proportional to the total population size. Our perturbation method explicitly tracks the dynamics of the probability distribution of the subpopulations in the vicinity of the CL. We argue that, whereas the slow strain has a competitive advantage for mathematically "typical" initial conditions, it is the fast strain that is more likely to win in the important situation when a few infectives of both strains are introduced into a susceptible population.

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

PubMed

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.

Evolutionary Dynamics of Fearfulness and Boldness: A Stochastic Simulation Model

PubMed Central

Lu, Nan; Ji, Ting; Zhang, Jia-Hua; Sun, Yue-Hua; Tao, Yi

2012-01-01

A stochastic simulation model is investigated for the evolution of anti-predator behavior in birds. The main goal is to reveal the effects of population size, predation threats, and energy lost per escape on the evolutionary dynamics of fearfulness and boldness. Two pure strategies, fearfulness and boldness, are assumed to have different responses for the predator attacks and nonlethal disturbance. On the other hand, the co-existence mechanism of fearfulness and boldness is also considered. For the effects of total population size, predation threats, and energy lost per escape, our main results show that: (i) the fearful (bold) individuals will be favored in a small (large) population, i.e. in a small (large) population, the fearfulness (boldness) can be considered to be an ESS; (ii) in a population with moderate size, fearfulness would be favored under moderate predator attacks; and (iii) although the total population size is the most important factor for the evolutionary dynamics of both fearful and bold individuals, the small energy lost per escape enables the fearful individuals to have the ability to win the advantage even in a relatively large population. Finally, we show also that the co-existence of fearful and bold individuals is possible when the competitive interactions between individuals are introduced. PMID:22412859

Evolutionary dynamics of fearfulness and boldness: a stochastic simulation model.

PubMed

Lu, Nan; Ji, Ting; Zhang, Jia-Hua; Sun, Yue-Hua; Tao, Yi

2012-01-01

A stochastic simulation model is investigated for the evolution of anti-predator behavior in birds. The main goal is to reveal the effects of population size, predation threats, and energy lost per escape on the evolutionary dynamics of fearfulness and boldness. Two pure strategies, fearfulness and boldness, are assumed to have different responses for the predator attacks and nonlethal disturbance. On the other hand, the co-existence mechanism of fearfulness and boldness is also considered. For the effects of total population size, predation threats, and energy lost per escape, our main results show that: (i) the fearful (bold) individuals will be favored in a small (large) population, i.e. in a small (large) population, the fearfulness (boldness) can be considered to be an ESS; (ii) in a population with moderate size, fearfulness would be favored under moderate predator attacks; and (iii) although the total population size is the most important factor for the evolutionary dynamics of both fearful and bold individuals, the small energy lost per escape enables the fearful individuals to have the ability to win the advantage even in a relatively large population. Finally, we show also that the co-existence of fearful and bold individuals is possible when the competitive interactions between individuals are introduced.

Simulation model of Skeletonema costatum population dynamics in northern San Francisco Bay, California

USGS Publications Warehouse

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

1981-01-01

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

Diversity waves in collapse-driven population dynamics

DOE PAGES

Maslov, Sergei; Sneppen, Kim

2015-09-14

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

Diversity waves in collapse-driven population dynamics

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

Maslov, Sergei; Sneppen, Kim

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

A quantitative dynamic systems model of health-related quality of life among older adults

PubMed Central

Roppolo, Mattia; Kunnen, E Saskia; van Geert, Paul L; Mulasso, Anna; Rabaglietti, Emanuela

2015-01-01

Health-related quality of life (HRQOL) is a person-centered concept. The analysis of HRQOL is highly relevant in the aged population, which is generally suffering from health decline. Starting from a conceptual dynamic systems model that describes the development of HRQOL in individuals over time, this study aims to develop and test a quantitative dynamic systems model, in order to reveal the possible dynamic trends of HRQOL among older adults. The model is tested in different ways: first, with a calibration procedure to test whether the model produces theoretically plausible results, and second, with a preliminary validation procedure using empirical data of 194 older adults. This first validation tested the prediction that given a particular starting point (first empirical data point), the model will generate dynamic trajectories that lead to the observed endpoint (second empirical data point). The analyses reveal that the quantitative model produces theoretically plausible trajectories, thus providing support for the calibration procedure. Furthermore, the analyses of validation show a good fit between empirical and simulated data. In fact, no differences were found in the comparison between empirical and simulated final data for the same subgroup of participants, whereas the comparison between different subgroups of people resulted in significant differences. These data provide an initial basis of evidence for the dynamic nature of HRQOL during the aging process. Therefore, these data may give new theoretical and applied insights into the study of HRQOL and its development with time in the aging population. PMID:26604722

A BASIC Program for Use in Teaching Population Dynamics.

ERIC Educational Resources Information Center

Kidd, N. A. C.

1984-01-01

Describes an interactive simulation model which can be used to demonstrate population growth with discrete or overlapping populations and the effects of random, constant, or density-dependent mortality. The program listing (for Commodore PET 4032 microcomputer) is included. (Author/DH)

A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2017-12-01

The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters

PubMed Central

Coe, Jason B.

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs—location, number of human dwellings, and urban area—to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities. PMID:29489854

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters.

PubMed

Flockhart, D T Tyler; Coe, Jason B

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs-location, number of human dwellings, and urban area-to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities.

Dynamics of a stochastic tuberculosis model with constant recruitment and varying total population size

NASA Astrophysics Data System (ADS)

Liu, Qun; Jiang, Daqing; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed

2017-03-01

In this paper, we develop a mathematical model for a tuberculosis model with constant recruitment and varying total population size by incorporating stochastic perturbations. By constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of an ergodic stationary distribution as well as extinction of the disease to the stochastic system.

Individual-based model formulation for cutthroat trout, Little Jones Creek, California

Treesearch

Steven F. Railsback; Bret C. Harvey

2001-01-01

This report contains the detailed formulation of an individual-based model (IBM) of cutthroat trout developed for three study sites on Little Jones Creek, Del Norte County, in northwestern California. The model was designed to support research on relations between habitat and fish population dynamics, the importance of small tributaries to trout populations, and the...

Models of Eucalypt phenology predict bat population flux.

PubMed

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

2016-10-01

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

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

NASA Astrophysics Data System (ADS)

Meijster, Tim; Warren, Nick; Heederik, Dick; Tielemans, Erik

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.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Mathematical modeling in biological populations through branching processes. Application to salmonid populations.

PubMed

Molina, Manuel; Mota, Manuel; Ramos, Alfonso

2015-01-01

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

An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: application to the Indian ocean skipjack tuna fishery.

PubMed

Faugeras, Blaise; Maury, Olivier

2005-10-01

We develop an advection-diffusion size-structured fish population dynamics model and apply it to simulate the skipjack tuna population in the Indian Ocean. The model is fully spatialized, and movements are parameterized with oceanographical and biological data; thus it naturally reacts to environment changes. We first formulate an initial-boundary value problem and prove existence of a unique positive solution. We then discuss the numerical scheme chosen for the integration of the simulation model. In a second step we address the parameter estimation problem for such a model. With the help of automatic differentiation, we derive the adjoint code which is used to compute the exact gradient of a Bayesian cost function measuring the distance between the outputs of the model and catch and length frequency data. A sensitivity analysis shows that not all parameters can be estimated from the data. Finally twin experiments in which pertubated parameters are recovered from simulated data are successfully conducted.

Qualitative and numerical investigations of the impact of a novel pathogen on a seabird colony

NASA Astrophysics Data System (ADS)

O'Regan, S. M.; Kelly, T. C.; Korobeinikov, A.; O'Callaghan, M. J. A.; Pokrovskii, A. V.

2008-11-01

Understanding the dynamics of novel pathogens in dense populations is crucial to public and veterinary health as well as wildlife ecology. Seabirds live in crowded colonies numbering several thousands of individuals. The long-term dynamics of avian influenza H5N1 virus in a seabird colony with no existing herd immunity are investigated using sophisticated mathematical techniques. The key characteristics of seabird population biology and the H5N1 virus are incorporated into a Susceptible-Exposed-Infected-Recovered (SEIR) model. Using the theory of integral manifolds, the SEIR model is reduced to a simpler system of two differential equations depending on the infected and recovered populations only, termed the IR model. The results of numerical experiments indicate that the IR model and the SEIR model are in close agreement. Using Lyapunov's direct method, the equilibria of the SEIR and the IR models are proven to be globally asymptotically stable in the positive quadrant.

A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management

USGS Publications Warehouse

Ackleh, Azmy S.; Carter, Jacoby; Chellamuthu, Vinodh K.; Ma, Baoling

2016-01-01

Chytridiomycosis is an emerging disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) that poses a serious threat to frog populations worldwide. Several studies have shown that inoculation of bacterial species Janthinobacterium lividum (Jl) can mitigate the impact of the disease. However, there are many questions regarding this interaction. A mathematical model of a frog population infected with chytridiomycosis is developed to investigate how the inoculation of Jl could reduce the impact of Bd disease on frogs. The model also illustrates the important role of temperature in disease dynamics. The model simulation results suggest possible control strategies for Jl to limit the impact of Bd in various scenarios. However, a better knowledge of Jl life cycle is needed to fully understand the interaction of Jl, Bd, temperature and frogs.

Applications of Perron-Frobenius theory to population dynamics.

PubMed

Li, Chi-Kwong; Schneider, Hans

2002-05-01

By the use of Perron-Frobenius theory, simple proofs are given of the Fundamental Theorem of Demography and of a theorem of Cushing and Yicang on the net reproductive rate occurring in matrix models of population dynamics. The latter result, which is closely related to the Stein-Rosenberg theorem in numerical linear algebra, is further refined with some additional nonnegative matrix theory. When the fertility matrix is scaled by the net reproductive rate, the growth rate of the model is $1$. More generally, we show how to achieve a given growth rate for the model by scaling the fertility matrix. Demographic interpretations of the results are given.

Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen.

PubMed

Malerba, Martino E; Heimann, Kirsten; Connolly, Sean R

2016-09-07

Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation by capture-recapture of recruitment and dispersal over several sites

USGS Publications Warehouse

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

2003-01-01

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

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

Evolution in Stage-Structured Populations

PubMed Central

Barfield, Michael; Holt, Robert D.; Gomulkiewicz, Richard

2016-01-01

For many organisms, stage is a better predictor of demographic rates than age. Yet no general theoretical framework exists for understanding or predicting evolution in stage-structured populations. Here, we provide a general modeling approach that can be used to predict evolution and demography of stage-structured populations. This advances our ability to understand evolution in stage-structured populations to a level previously available only for populations structured by age. We use this framework to provide the first rigorous proof that Lande’s theorem, which relates adaptive evolution to population growth, applies to stage-classified populations, assuming only normality and that evolution is slow relative to population dynamics. We extend this theorem to allow for different means or variances among stages. Our next major result is the formulation of Price’s theorem, a fundamental law of evolution, for stage-structured populations. In addition, we use data from Trillium grandiflorum to demonstrate how our models can be applied to a real-world population and thereby show their practical potential to generate accurate projections of evolutionary and population dynamics. Finally, we use our framework to compare rates of evolution in age- versus stage-structured populations, which shows how our methods can yield biological insights about evolution in stage-structured populations. PMID:21460563

Modeling tradeoffs in avian life history traits and consequences for population growth

USGS Publications Warehouse

Clark, M.E.; Martin, T.E.

2007-01-01

Variation in population dynamics is inherently related to life history characteristics of species, which vary markedly even within phylogenetic groups such as passerine birds. We computed the finite rate of population change (??) from a matrix projection model and from mark-recapture observations for 23 bird species breeding in northern Arizona. We used sensitivity analyses and a simulation model to separate contributions of different life history traits to population growth rate. In particular we focused on contrasting effects of components of reproduction (nest success, clutch size, number of clutches, and juvenile survival) versus adult survival on ??. We explored how changes in nest success or adult survival coupled to costs in other life history parameters affected ?? over a life history gradient provided by our 23 Arizona species, as well as a broader sample of 121 North American passerine species. We further examined these effects for more than 200 passeriform and piciform populations breeding across North America. Model simulations indicate nest success and juvenile survival exert the largest effects on population growth in species with moderate to high reproductive output, whereas adult survival contributed more to population growth in long-lived species. Our simulations suggest that monitoring breeding success in populations across a broad geographic area provides an important index for identifying neotropical migratory populations at risk of serious population declines and a potential method for identifying large-scale mechanisms regulating population dynamics. ?? 2007 Elsevier B.V. All rights reserved.

Larval connectivity of pearl oyster through biophysical modelling; evidence of food limitation and broodstock effect

NASA Astrophysics Data System (ADS)

Thomas, Yoann; Dumas, Franck; Andréfouët, Serge

2016-12-01

The black-lip pearl oyster (Pinctada margaritifera) is cultured extensively to produce black pearls, especially in French Polynesia atoll lagoons. This aquaculture relies on spat collection, a process that experiences spatial and temporal variability and needs to be optimized by understanding which factors influence recruitment. Here, we investigate the sensitivity of P. margaritifera larval dispersal to both physical and biological factors in the lagoon of Ahe atoll. Coupling a validated 3D larval dispersal model, a bioenergetics larval growth model following the Dynamic Energy Budget (DEB) theory, and a population dynamics model, the variability of lagoon-scale connectivity patterns and recruitment potential is investigated. The relative contribution of reared and wild broodstock to the lagoon-scale recruitment potential is also investigated. Sensitivity analyses pointed out the major effect of the broodstock population structure as well as the sensitivity to larval mortality rate and inter-individual growth variability to larval supply and to the subsequent settlement potential. The application of the growth model clarifies how trophic conditions determine the larval supply and connectivity patterns. These results provide new cues to understand the dynamics of bottom-dwelling populations in atoll lagoons, their recruitment, and discuss how to take advantage of these findings and numerical models for pearl oyster management.

Effects of developmental variability on the dynamics and self-organization of cell populations

NASA Astrophysics Data System (ADS)

Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard

2017-11-01

We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.

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

NASA Astrophysics Data System (ADS)

Bi, R.; Liu, H.

2016-02-01

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

Inferential and forward projection modeling to evaluate options for controlling invasive mammals on islands.

PubMed

Anderson, D P; McMurtrie, P; Edge, K-A; Baxter, P W J; Byrom, A E

2016-12-01

Successful pest-mammal eradications from remote islands have resulted in important biodiversity benefits. Near-shore islands can also serve as refuges for native biota but require ongoing effort to maintain low-pest or pest-free status. Three management options are available in the presence of reinvasion risk: (1) control-to-zero density, in which immigration may occur but reinvaders are removed; (2) sustained population suppression (to relatively low numbers); or (3) no action. Biodiversity benefits can result from options one and two. The management challenge is to make evidence-based decisions on the selection of an appropriate objective and to identify a financially feasible control strategy that has a high probability of success. This requires understanding the pest species population dynamics and how it will respond to a range of potential management strategies, each with an associated financial cost. We developed a two-stage modeling approach that consisted of (1) Bayesian inferential modeling to estimate parameters for a model of pest population dynamics and control, and (2) a forward projection model to simulate a range of plausible management scenarios and quantify the probability of obtaining zero density within four years. We applied the model to an ongoing, six-year trapping program to control stoats (Mustela erminea) on Resolution Island, New Zealand. Zero density has not yet been achieved. Results demonstrate that management objectives were impeded by a combination of a highly fecund population, insufficient trap attractiveness, and a substantial proportion of the population that did not enter traps. Immigration is known to occur because the founding population arrived on the island by swimming from the mainland. However, immigration rate during this study was indistinguishable from zero. The forward projection modeling showed that control-to-zero density was feasible but required greater than a two-fold budget increase to intensify the trapping rate relative to population growth. The two-stage modeling provides the foundation for a management program in which broad-scale trials of additional trapping effort or improved trap lures would test model predictions and increase our understanding of system dynamics. © 2016 by the Ecological Society of America.

Phenology and density-dependent dispersal predict patterns of mountain pine beetle (Dendroctonus ponderosae) impact

Treesearch

James A. Powell; Barbara J. Bentz

2014-01-01

For species with irruptive population behavior, dispersal is an important component of outbreak dynamics. We developed and parameterized a mechanistic model describing mountain pine beetle (Dendroctonus ponderosae Hopkins) population demographics and dispersal across a landscape. Model components include temperature-dependent phenology, host tree colonization...

ECOLOGICAL ENDPOINT MODELING FOR TMDLS: EFFECTS OF SEDIMENT ON FISH POPULATIONS

EPA Science Inventory

Sediment is one of the primary stressors of concern for Total Maximum Daily Loads (TMDLs) for streams, and often it is a concern because of its impact on ecological endpoints. A modeling approach relating sediment to stream fish population dynamics is presented. Equations are d...

Modeling a beaver population on the Prescott Peninsula, Massachusetts: Feasibility of LANDSAT as an input

NASA Technical Reports Server (NTRS)

Finn, J. T.; Howard, R.

1981-01-01

A preliminary dynamic model of beaver spatial distribution and population growth was developed. The feasibility of locating beaver ponds on LANDSAT digital tapes, and of using this information to provide initial conditions of beaver spatial distribution for the model, and to validate model predictions is discussed. The techniques used to identify beaver ponds on LANDSAT are described.

Mathematical Models Relating Effects of Xenobiotic Substances on Individuals and Populations

DTIC Science & Technology

1997-09-30

experimental information quantifying the impact of toxicants on the individual organisms within impacted, or potentially impacted populations. OBJECTIVES...The research has two main parts: (i) modeling the consequences for individuals of toxicant -induced changes in the rates of energy acquisition and...In modeling the response of individuals to toxicants , we use dynamic energy budget (DEB) models to describe the rules by which individual organisms

COULD ETHINYL ESTRADIOL AFFECT THE POPULATION BIOLOGY OF CUNNER, TAUTOGOLABRUS ADSPERSUS

EPA Science Inventory

Endocrine disrupting chemicals in the environment may disturb the population dynamics of wildlife by affecting reproductive output and embryonic development of organisms. This study used a population model to evaluate whether ethinyl estradiol (EE2 could affect cunner Tautogolabr...

A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank

Treesearch

Susan E. Meyer; Dana Quinney; Jay Weaver

2006-01-01

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

Effects of the distant population density on spatial patterns of demographic dynamics

NASA Astrophysics Data System (ADS)

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics.

PubMed

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500  m ) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics

PubMed Central

2017-01-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km. PMID:28878987

Dynamic complexities in a pest control model with birth pulse and harvesting

NASA Astrophysics Data System (ADS)

Goel, A.; Gakkhar, S.

2016-04-01

In this paper, an impulsive model is discussed for an integrated pest management approach comprising of chemical and mechanical controls. The pesticides and harvesting are used to control the stage-structured pest population. The mature pest give birth to immature pest in pulses at regular intervals. The pest is controlled by spraying chemical pesticides affecting immature as well as mature pest. The harvesting of both immature and mature pest further reduce the pest population. The discrete dynamical system obtained from stroboscopic map is analyzed. The threshold conditions for stability of pest-free state as well as non-trivial period-1 solution is obtained. The effect of pesticide spray timing and harvesting on immature as well as mature pest are shown. Finally, by numerical simulation with MATLAB, the dynamical behaviors of the model is found to be complex. Above the threshold level there is a characteristic sequence of bifurcations leading to chaotic dynamics. Route to chaos is found to be period-doubling. Period halving bifurcations are also observed.

Influence of demographic changes on the impact of vaccination against varicella and herpes zoster in Germany - a mathematical modelling study.

PubMed

Horn, Johannes; Damm, Oliver; Greiner, Wolfgang; Hengel, Hartmut; Kretzschmar, Mirjam E; Siedler, Anette; Ultsch, Bernhard; Weidemann, Felix; Wichmann, Ole; Karch, André; Mikolajczyk, Rafael T

2018-01-09

Epidemiological studies suggest that reduced exposure to varicella might lead to an increased risk for herpes zoster (HZ). Reduction of exposure to varicella is a consequence of varicella vaccination but also of demographic changes. We analyzed how the combination of vaccination programs and demographic dynamics will affect the epidemiology of varicella and HZ in Germany over the next 50 years. We used a deterministic dynamic compartmental model to assess the impact of different varicella and HZ vaccination strategies on varicella and HZ epidemiology in three demographic scenarios, namely the projected population for Germany, the projected population additionally accounting for increased immigration as observed in 2015/2016, and a stationary population. Projected demographic changes alone result in an increase of annual HZ cases by 18.3% and a decrease of varicella cases by 45.7% between 1990 and 2060. Independently of the demographic scenario, varicella vaccination reduces the cumulative number of varicella cases until 2060 by approximately 70%, but also increases HZ cases by 10%. Unlike the currently licensed live attenuated HZ vaccine, the new subunit vaccine candidate might completely counteract this effect. Relative vaccine effects were consistent across all demographic scenarios. Demographic dynamics will be a major determinant of HZ epidemiology in the next 50 years. While stationary population models are appropriate for assessing vaccination impact, models incorporating realistic population structures allow a direct comparison to surveillance data and can thus provide additional input for immunization decision-making and resource planning.

Invasion of cooperators in lattice populations: linear and non-linear public good games.

PubMed

Vásárhelyi, Zsóka; Scheuring, István

2013-08-01

A generalized version of the N-person volunteer's dilemma (NVD) Game has been suggested recently for illustrating the problem of N-person social dilemmas. Using standard replicator dynamics it can be shown that coexistence of cooperators and defectors is typical in this model. However, the question of how a rare mutant cooperator could invade a population of defectors is still open. Here we examined the dynamics of individual based stochastic models of the NVD. We analyze the dynamics in well-mixed and viscous populations. We show in both cases that coexistence between cooperators and defectors is possible; moreover, spatial aggregation of types in viscous populations can easily lead to pure cooperation. Furthermore we analyze the invasion of cooperators in populations consisting predominantly of defectors. In accordance with analytical results, in deterministic systems, we found the invasion of cooperators successful in the well-mixed case only if their initial concentration was higher than a critical threshold, defined by the replicator dynamics of the NVD. In the viscous case, however, not the initial concentration but the initial number determines the success of invasion. We show that even a single mutant cooperator can invade with a high probability, because the local density of aggregated cooperators exceeds the threshold defined by the game. Comparing the results to models using different benefit functions (linear or sigmoid), we show that the role of the benefit function is much more important in the well-mixed than in the viscous case. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

From cognitive networks to seizures: Stimulus evoked dynamics in a coupled cortical network

NASA Astrophysics Data System (ADS)

Lee, Jaejin; Ermentrout, Bard; Bodner, Mark

2013-12-01

Epilepsy is one of the most common neuropathologies worldwide. Seizures arising in epilepsy or in seizure disorders are characterized generally by uncontrolled spread of excitation and electrical activity to a limited region or even over the entire cortex. While it is generally accepted that abnormal excessive firing and synchronization of neuron populations lead to seizures, little is known about the precise mechanisms underlying human epileptic seizures, the mechanisms of transitions from normal to paroxysmal activity, or about how seizures spread. Further complication arises in that seizures do not occur with a single type of dynamics but as many different phenotypes and genotypes with a range of patterns, synchronous oscillations, and time courses. The concept of preventing, terminating, or modulating seizures and/or paroxysmal activity through stimulation of brain has also received considerable attention. The ability of such stimulation to prevent or modulate such pathological activity may depend on identifiable parameters. In this work, firing rate networks with inhibitory and excitatory populations were modeled. Network parameters were chosen to model normal working memory behaviors. Two different models of cognitive activity were developed. The first model consists of a single network corresponding to a local area of the brain. The second incorporates two networks connected through sparser recurrent excitatory connectivity with transmission delays ranging from approximately 3 ms within local populations to 15 ms between populations residing in different cortical areas. The effect of excitatory stimulation to activate working memory behavior through selective persistent activation of populations is examined in the models, and the conditions and transition mechanisms through which that selective activation breaks down producing spreading paroxysmal activity and seizure states are characterized. Specifically, we determine critical parameters and architectural changes that produce the different seizure dynamics in the networks. This provides possible mechanisms for seizure generation. Because seizures arise as attractors in a multi-state system, the system may possibly be returned to its baseline state through some particular stimulation. The ability of stimulation to terminate seizure dynamics in the local and distributed models is studied. We systematically examine when this may occur and the form of the stimulation necessary for the range of seizure dynamics. In both the local and distributed network models, termination is possible for all seizure types observed by stimulation possessing some particular configuration of spatial and temporal characteristics.

Discrete and Continuum Approximations for Collective Cell Migration in a Scratch Assay with Cell Size Dynamics.

PubMed

Matsiaka, Oleksii M; Penington, Catherine J; Baker, Ruth E; Simpson, Matthew J

2018-04-01

Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2009-04-01

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

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

PubMed

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

2013-07-01

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

Developing population models with data from marked individuals

USGS Publications Warehouse

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 is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

Dynamic Properties of the Alkaline Vesicle Population at Hippocampal Synapses

PubMed Central

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

2014-01-01

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

Spatiotemporal variation in survival rates: implications for population dynamics of yellow-bellied marmots.

PubMed

Ozgul, Arpat; Armitage, Kenneth B; Blumstein, Daniel T; Oli, Madan K

2006-04-01

Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.

The Dynamics of HPV Infection and Cervical Cancer Cells.

PubMed

Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan

2016-01-01

The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.

The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx

PubMed Central

Stenseth, Nils Chr.; Ehrich, Dorothee; Rueness, Eli Knispel; Lingjærde, Ole Chr.; Chan, Kung-Sik; Boutin, Stan; O'Donoghue, Mark; Robinson, David A.; Viljugrein, Hildegunn; Jakobsen, Kjetill S.

2004-01-01

The abundance of Canadian lynx follows 10-year density fluctuations across the Canadian subcontinent. These cyclic fluctuations have earlier been shown to be geographically structured into three climatic regions: the Atlantic, Continental, and Pacific zones. Recent genetic evidence revealed an essentially similar spatial structuring. Introducing a new population model, the “climate forcing of ecological and evolutionary patterns” model, we link the observed ecological and evolutionary patterns. Specifically, we demonstrate that there is greater phase synchrony within climatic zones than between them and show that external climatic forcing may act as a synchronizer. We simulated genetic drift by using data on population dynamics generated by the climate forcing of ecological and evolutionary patterns model, and we demonstrate that the observed genetic structuring can be seen as an emerging property of the spatiotemporal ecological dynamics. PMID:15067131

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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.

Understanding climate impacts on recruitment and spatial dynamics of Atlantic cod in the Gulf of Maine: Integration of observations and modeling

NASA Astrophysics Data System (ADS)

Runge, Jeffrey A.; Kovach, Adrienne I.; Churchill, James H.; Kerr, Lisa A.; Morrison, John R.; Beardsley, Robert C.; Berlinsky, David L.; Chen, Changsheng; Cadrin, Steven X.; Davis, Cabell S.; Ford, Kathryn H.; Grabowski, Jonathan H.; Howell, W. Huntting; Ji, Rubao; Jones, Rebecca J.; Pershing, Andrew J.; Record, Nicholas R.; Thomas, Andrew C.; Sherwood, Graham D.; Tallack, Shelly M. L.; Townsend, David W.

2010-10-01

We put forward a combined observing and modeling strategy for evaluating effects of environmental forcing on the dynamics of spatially structured cod populations spawning in the western Gulf of Maine. Recent work indicates at least two genetically differentiated complexes in this region: a late spring spawning, coastal population centered in Ipswich Bay, and a population that spawns in winter inshore and on nearshore banks in the Gulf of Maine and off southern New England. The two populations likely differ in trophic interactions and in physiological and behavioral responses to different winter and spring environments. Coupled physical-biological modeling has advanced to the point where within-decade forecasting of environmental conditions for recruitment to each of the two populations is feasible. However, the modeling needs to be supported by hydrographic, primary production and zooplankton data collected by buoys, and by data from remote sensing and fixed station sampling. Forecasts of environmentally driven dispersal and growth of planktonic early life stages, combined with an understanding of possible population-specific predator fields, usage of coastal habitat by juveniles and adult resident and migratory patterns, can be used to develop scenarios for spatially explicit population responses to multiple forcings, including climate change, anthropogenic impacts on nearshore juvenile habitat, connectivity among populations and management interventions such as regional fisheries closures.

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

PubMed

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

2016-06-01

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

Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers

USGS Publications Warehouse

Kesler, D.C.; Haig, S.M.

2007-01-01

Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.

Mathematical models to characterize early epidemic growth: A Review

PubMed Central

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-01-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-15 Ebola epidemic in West Africa. PMID:27451336

Mathematical models to characterize early epidemic growth: A review

NASA Astrophysics Data System (ADS)

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-09-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-2015 Ebola epidemic in West Africa.

Impact of time delay on the dynamics of SEIR epidemic model using cellular automata

NASA Astrophysics Data System (ADS)

Sharma, Natasha; Gupta, Arvind Kumar

2017-04-01

The delay of an infectious disease is significant when aiming to predict its strength and spreading patterns. In this paper the SEIR ​(susceptible-exposed-infected-recovered) epidemic spread with time delay is analyzed through a two-dimensional cellular automata model. The time delay corresponding to the infectious span, predominantly, includes death during the latency period in due course of infection. The advancement of whole system is described by SEIR transition function complemented with crucial factors like inhomogeneous population distribution, birth and disease independent mortality. Moreover, to reflect more realistic population dynamics some stochastic parameters like population movement and connections at local level are also considered. The existence and stability of disease free equilibrium is investigated. Two prime behavioral patterns of disease dynamics is found depending on delay. The critical value of delay, beyond which there are notable variations in spread patterns, is computed. The influence of important parameters affecting the disease dynamics on basic reproduction number is also examined. The results obtained show that delay plays an affirmative role to control disease progression in an infected host.

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

Relationship between the mechanisms of gamma rhythm generation and the magnitude of the macroscopic phase response function in a population of excitatory and inhibitory modified quadratic integrate-and-fire neurons

NASA Astrophysics Data System (ADS)

Akao, Akihiko; Ogawa, Yutaro; Jimbo, Yasuhiko; Ermentrout, G. Bard; Kotani, Kiyoshi

2018-01-01

Gamma oscillations are thought to play an important role in brain function. Interneuron gamma (ING) and pyramidal interneuron gamma (PING) mechanisms have been proposed as generation mechanisms for these oscillations. However, the relation between the generation mechanisms and the dynamical properties of the gamma oscillation are still unclear. Among the dynamical properties of the gamma oscillation, the phase response function (PRF) is important because it encodes the response of the oscillation to inputs. Recently, the PRF for an inhibitory population of modified theta neurons that generate an ING rhythm was computed by the adjoint method applied to the associated Fokker-Planck equation (FPE) for the model. The modified theta model incorporates conductance-based synapses as well as the voltage and current dynamics. Here, we extended this previous work by creating an excitatory-inhibitory (E-I) network using the modified theta model and described the population dynamics with the corresponding FPE. We conducted a bifurcation analysis of the FPE to find parameter regions which generate gamma oscillations. In order to label the oscillatory parameter regions by their generation mechanisms, we defined ING- and PING-type gamma oscillation in a mathematically plausible way based on the driver of the inhibitory population. We labeled the oscillatory parameter regions by these generation mechanisms and derived PRFs via the adjoint method on the FPE in order to investigate the differences in the responses of each type of oscillation to inputs. PRFs for PING and ING mechanisms are derived and compared. We found the amplitude of the PRF for the excitatory population is larger in the PING case than in the ING case. Finally, the E-I population of the modified theta neuron enabled us to analyze the PRFs of PING-type gamma oscillation and the entrainment ability of E and I populations. We found a parameter region in which PRFs of E and I are both purely positive in the case of PING oscillations. The different entrainment abilities of E and I stimulation as governed by the respective PRFs was compared to direct simulations of finite populations of model neurons. We find that it is easier to entrain the gamma rhythm by stimulating the inhibitory population than by stimulating the excitatory population as has been found experimentally.

The role of density-dependent individual growth in the persistence of freshwater salmonid populations.

PubMed

Vincenzi, Simone; Crivelli, Alain J; Jesensek, Dusan; De Leo, Giulio A

2008-06-01

Theoretical and empirical models of populations dynamics have paid little attention to the implications of density-dependent individual growth on the persistence and regulation of small freshwater salmonid populations. We have therefore designed a study aimed at testing our hypothesis that density-dependent individual growth is a process that enhances population recovery and reduces extinction risk in salmonid populations in a variable environment subject to disturbance events. This hypothesis was tested in two newly introduced marble trout (Salmo marmoratus) populations living in Slovenian streams (Zakojska and Gorska) subject to severe autumn floods. We developed a discrete-time stochastic individual-based model of population dynamics for each population with demographic parameters and compensatory responses tightly calibrated on data from individually tagged marble trout. The occurrence of severe flood events causing population collapses was explicitly accounted for in the model. We used the model in a population viability analysis setting to estimate the quasi-extinction risk and demographic indexes of the two marble trout populations when individual growth was density-dependent. We ran a set of simulations in which the effect of floods on population abundance was explicitly accounted for and another set of simulations in which flood events were not included in the model. These simulation results were compared with those of scenarios in which individual growth was modelled with density-independent Von Bertalanffy growth curves. Our results show how density-dependent individual growth may confer remarkable resilience to marble trout populations in case of major flood events. The resilience to flood events shown by the simulation results can be explained by the increase in size-dependent fecundity as a consequence of the drop in population size after a severe flood, which allows the population to quickly recover to the pre-event conditions. Our results suggest that density-dependent individual growth plays a potentially powerful role in the persistence of freshwater salmonids living in streams subject to recurrent yet unpredictable flood events.

A COMPUTATIONALLY EFFICIENT HYBRID APPROACH FOR DYNAMIC GAS/AEROSOL TRANSFER IN AIR QUALITY MODELS. (R826371C005)

EPA Science Inventory

Dynamic mass transfer methods have been developed to better describe the interaction of the aerosol population with semi-volatile species such as nitrate, ammonia, and chloride. Unfortunately, these dynamic methods are computationally expensive. Assumptions are often made to r...

Nonlinear effects of climate and density in the dynamics of a fluctuating population of reindeer.

PubMed

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

2008-06-01

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

Fish population dynamics in a seasonally varying wetland

USGS Publications Warehouse

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

2010-01-01

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

Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure

DTIC Science & Technology

2001-09-30

mutualism utilized modified Lotka - Volterra (L-V) competition equations in which the sign of the interspecific interaction term was changed from...within complex communities and ecosystems. Prior to the current award, the PIs formulated and tested general dynamic energy budget models...Nisbet, 1998; chapter 7) make a convincing case that ecosystems do truly have dynamics that can be described by relatively simple, general , models

Dynamical Zodiacal Cloud Models Constrained by High Resolution Spectroscopy of the Zodiacal Light

NASA Technical Reports Server (NTRS)

Ipatov, S. I.; Kutyrev, A. S.; Madsen, G. J.; Mather, J. C.; Moseley, S. H.; Reynolds, R. J.

2005-01-01

We have developed a set of self-consistent dynamical models of the Zodiacal cloud, following the orbital evolution of dust particles. Three populations were considered, originating from the Kuiper belt, asteroids and comets. Using the models developed, we investigated how the solar spectrum is changed by scattering by the zodiacal cloud grains and compared the obtained spectra with the observations.