Realistic Population Dynamics Research Articles

Accounting for unobserved population dynamics and aging error in close-kin mark-recapture assessments.

Obtaining robust estimates of population abundance is a central challenge hindering the conservation and management of many threatened and exploited species. Close-kin mark-recapture (CKMR) is a genetics-based approach that has strong potential to improve the monitoring of data-limited species by enabling estimates of abundance, survival, and other parameters for populations that are challenging to assess. However, CKMR models have received limited sensitivity testing under realistic population dynamics and sampling scenarios, impeding the application of the method in population monitoring programs and stock assessments. Here, we use individual-based simulation to examine how unmodeled population dynamics and aging uncertainty affect the accuracy and precision of CKMR parameter estimates under different sampling strategies. We then present adapted models that correct the biases that arise from model misspecification. Our results demonstrate that a simple base-case CKMR model produces robust estimates of population abundance with stable populations that breed annually; however, if a population trend or non-annual breeding dynamics are present, or if year-specific estimates of abundance are desired, a more complex CKMR model must be constructed. In addition, we show that CKMR can generate reliable abundance estimates for adults from a variety of sampling strategies, including juvenile-focused sampling where adults are never directly observed (and aging error is minimal). Finally, we apply a CKMR model that has been adapted for population growth and intermittent breeding to two decades of genetic data from juvenile lemon sharks (Negaprion brevirostris) in Bimini, Bahamas, to demonstrate how application of CKMR to samples drawn solely from juveniles can contribute to monitoring efforts for highly mobile populations. Overall, this study expands our understanding of the biological factors and sampling decisions that cause bias in CKMR models, identifies key areas for future inquiry, and provides recommendations that can aid biologists in planning and implementing an effective CKMR study, particularly for long-lived data-limited species.

Numerical model of the spatio-temporal dynamics in a water strider group

The water strider group demonstrates a very complex dynamics consisting of competition for the food items, territoriality and aggression to the conspecific individuals, escaping from the predators, etc. The situation is even more complex due to the presence of different instars, which in most water strider species live in the same habitat and occupy the same niche. The presented swarm model of water striders demonstrates the realistic population dynamics. For the swarm formation in the model, attraction and repulsion forces were used. Animal motion in the model takes into account inertia and kinetic energy dissipation effects. The model includes three different rates related to the growth of individuals: food appearance rate, food assimilation rate, and stored energy loss rate. The results of our modeling show that the size distribution of individuals seems to be an adequate measure for population status, and it has a characteristic shape for different model parameter combinations. Distribution of the distances between nearest neighbors is other important measure of the population density and its dynamics. Parameters of the model can be tuned in such a way, that the shape of both distributions in a steady phase coincides with that shape observed in a natural population, which helps to understand the factors leading to particular momentary distribution of both parameters (size and distance) in the population. From this point of view, the model can predict how both distributions can further develop from certain state depending on particular combination of factors.

Two‐compartment age‐structured model of solitarious and gregarious locust population dynamics

We study a nonlinear age‐structured model of locust population dynamics with variable time of egg incubation that describes the phase shifting and behavior of desert locust, Schistocerca gregaria. The model is based on the 2‐compartment system of transport equations with nonlinear density‐dependent fertility rates with time delay in boundary conditions. It describes the dynamics of the density of 2 phases of locust's population—solitarious and gregarious. Such system is studied both theoretically and numerically. The analysis of asymptotical stability of the trivial and nontrivial equilibria of the autonomous system allows to understand the conditions and the particularities of bidirectional phase shifts between solitarious and gregarious S gregaria. We found that the parameter of maturation age was very important in the 2‐phase dynamics. We extrapolate that a rapid change in environmental conditions that may trigger the maturation process of dormant solitarious population may also decrease, overall, the maturation age and hence destabilize the solitarious subpopulation from a near zero population size towards much larger populations and hence initiate quickly good conditions for gregarization. We also observed that the most realistic population dynamics of locusts was when the attraction point of a stable solitarious population size was above the gregarization threshold. This means that solitarious populations may last through time only near a zero size, but as soon as environmental conditions become favorable to population increase, the gregarization may happen. This outlines the intrinsic character of outbreaking dynamics that a species such as desert locust displays.

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

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.

Predicting Heliothis (Helicoverpa armigera) pest population dynamics with an age-structured insect population model driven by satellite data

The cotton bollworm (Helicoverpa armigera) is among the most damaging agricultural insect pests in the world. The life cycle of H. armigera is temperature dependent and as such modeling its population dynamics for integrated pest management (IPM) purposes requires accurate temperature information throughout the area of interest, which is not always available. We present, for the first time, a continuous age-structured insect population model driven by satellite-derived land surface temperature (LST) to derive population dynamics of H. armigera. We use LST data from the Moderate resolution imaging spectroradiometer (MODIS) conducting model simulations and validating the model with H. armigera larvae counts from in-field scout reports in nine sweet corn (Zea mays convar) and four tomato (Solanum lycopersicum) crop fields in Northern Israel. We compared our results with a similar model that uses air temperature derived from the nearest weather station as an input. To accurately predict population dynamics, we used different model initiation scenarios considering pesticide application and migration patterns between neighboring corn and tomato fields, which were identified as sink and source of the adult population. Results show that our LST-driven model outperformed the model driven by ambient air temperature. Model simulations generally followed the larval population development observed in the field when the model was initiated the day before the first larvae were detected, providing realistic population dynamics. Simulations with different adult population migration rates showed the importance of including between-field migration in the LST-driven model. In conclusion, this study provides a basis for future development of real-time IPM support systems, particularly when combining a temperature-driven age-structured insect population model with real-time satellite-derived information.

Interaction rates, vital rates, background fitness and replicator dynamics: how to embed evolutionary game structure into realistic population dynamics

In this paper we are concerned with how aggregated outcomes of individual behaviours, during interactions with other individuals (games) or with environmental factors, determine the vital rates constituting the growth rate of the population. This approach needs additional elements, namely the rates of event occurrence (interaction rates). Interaction rates describe the distribution of the interaction events in time, which seriously affects the population dynamics, as is shown in this paper. This leads to the model of a population of individuals playing different games, where focal game affected by the considered trait can be extracted from the general model, and the impact on the dynamics of other events (which is not neutral) can be described by an average background fertility and mortality. This leads to a distinction between two types of background fitness, strategically neutral elements of the focal games (correlated with the focal game events) and the aggregated outcomes of other interactions (independent of the focal game). The new approach is useful for clarification of the biological meaning of concepts such as weak selection. Results are illustrated by a Hawk–Dove example.

Impact of time delay on the dynamics of SEIR epidemic model using cellular automata

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.

A moving target--incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations.

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.

Epidemiological modeling with a population density map-based cellular automata simulation system

We present a new numerical, two-dimensional cellular automata framework for simulation of the spread of an infectious disease in a region with non-homogenous spatial population distribution. For the simulation the real map of the population density in Poland is used, where the sources of the infection are located. Presented model is a combination of SEIR and IBM models complemented with additional factors like variable population density, death, birth and some stochastic parameters to reflect the more realistic population dynamics. In proposed model the states of individuals are tracked through time like in IBM model and the evolution of the whole system is described by SEIR transition function which determines how cells interact with their neighbours, influencing global behavior of the system. Presented model requires less complicated input than IBM models and is less expensive computationally. We explore influenza as the contagious disease in our map-based simulation. The results of the simulation show the spreading-rate of the disease and can be used to describe possible actions for preventing pandemic.

Preventing and Diagnosing Colorectal Cancer with a Limited Colonoscopy Resource

This paper explores how the capacity of colonoscopy services should be allocated for screening and diagnosis of colorectal cancer to improve health outcomes. Both of these services are important since screening prevents cancer by removing polyps, while diagnosis is required to start treatment for cancer. This paper first presents a basic compartmental model to illustrate the trade‐off between these two analytically. Further, a more realistic population dynamics model with resource constraints is introduced for colorectal cancer screening and analyzed numerically. The best resource allocation decisions are investigated with the objectives of minimizing mortality or incidence rates. We provide a sensitivity analysis with respect to policy and disease‐related parameters. We conclude that to minimize mortality, the capacity should be rationed to ensure that the wait for diagnosis is at reasonable levels. When the relevant performance measure is the incidence rate, screening is allocated more capacity compared to the case with mortality rate measure. We also show that benefits from increasing compliance to screening programs can only be realized if there is sufficient service capacity.

Is Catalytic Activity of Chaperones a Selectable Trait for the Emergence of Heat Shock Response?

Although heat shock response is ubiquitous in bacterial cells, the underlying physical chemistry behind heat shock response remains poorly understood. To study the response of cell populations to heat shock we employ a physics-based ab initio model of living cells where protein biophysics (i.e., folding and protein-protein interactions in crowded cellular environments) and important aspects of proteins homeostasis are coupled with realistic population dynamics simulations. By postulating a genotype-phenotype relationship we define a cell division rate in terms of functional concentrations of proteins and protein complexes, whose Boltzmann stabilities of folding and strengths of their functional interactions are exactly evaluated from their sequence information. We compare and contrast evolutionary dynamics for two models of chaperon action. In the active model, foldase chaperones function as nonequilibrium machines to accelerate the rate of protein folding. In the passive model, holdase chaperones form reversible complexes with proteins in their misfolded conformations to maintain their solubility. We find that only cells expressing foldase chaperones are capable of genuine heat shock response to the increase in the amount of unfolded proteins at elevated temperatures. In response to heat shock, cells’ limited resources are redistributed differently for active and passive models. For the active model, foldase chaperones are overexpressed at the expense of downregulation of high abundance proteins, whereas for the passive model; cells react to heat shock by downregulating their high abundance proteins, as their low abundance proteins are upregulated.

A spatially explicit agent-based model of the interactions between jaguar populations and their habitats

Agent-based models can predict system-level properties of populations from stochastic simulation of fine-scale movements. One important application to conservation lies in their ability to consider the impact of individual variation in movement and decision-making on populations under future landscape changes. Here, we present a spatially explicit agent-based simulation of a population of jaguars (Panthera onca) in a mixed forest and farmland landscape in Central America that demonstrates an application of least-cost modelling, a description of the way that agents move through their environment, to equilibrium population dynamics. We detail the construction and application of the model, and the processes of calibration, sensitivity analysis and validation with empirical field data. Simulated jaguars underwent feeding, reproduction, and mortality events typical of natural populations, resulting in realistic population dynamics and home range sizes. Jaguar agents located inside protected forest reserves exhibited higher fitness (fecundity, energy reserves, age and age of mortality) as well as lower energy- and habitat-related mortality than jaguar agents located outside these reserves. Changes in fecundity directly affected the dynamics of simulated populations to a larger degree than either mortality or agent–agent interactions. Model validation showed similar patterns to camera traps in the field, in terms of landscape utilisation and the spatial distribution of individuals. The model showed less sensitivity to socially motivated and fine-scale movements, apart from those directed towards feeding and reproduction, but reflected the interactions and movement of naturally occurring populations in this region. Applications of the model will include testing impacts on population dynamics of likely future changes in landscape structure and connectivity.

Inferring ecological mechanisms from hunting bag data in wildlife management: a reply to Blanco-Aguiar et al. (2012)

In a previous study, we suggested that hyperpredation by shared predators on red-legged partridges (Alectoris rufa), once a parasite (rabbit haemorrhagic disease, RHD) had decimated populations of rabbit (Oryctolagus cuniculus), the primary prey for most of the Mediterranean predators, was a major force driving partridge population dynamics in Spain years ago (Moleon et al., PLoS One 3:e2307, 2008). Recently, however, Blanco-Aguiar et al. (Eur J Wildl Res 58:433–439, 2012) have asserted that this conclusion is poorly evidence-based and can subsequently promote raptor persecution by hunters. In response to Blanco-Aguiar and colleagues, here we provide complementary insights that favour our earlier hypothesis. After explaining several key concepts of the hyperpredation process, we use additional data and analyses to show that (1) a synchronised regime shift (i.e. a step, abrupt change in population size) to significantly lower population levels in both the rabbit and partridge populations took place coinciding with the RHD outbreak; (2) rabbit and partridge population dynamics were highly synchronised after the RHD outbreak, but not before; (3) an enhanced spatial autocorrelation at all the spatial scales emerged after RHD for partridge populations; and (4) the main shared predators’ diet patterns were consistent with the hypothesis of enhanced predation pressure as a plausible mechanism behind the observed partridge dynamics. We support the idea that hunting bag data may be useful to infer realistic population dynamics and the ecological mechanisms explaining them, provided that (1) they are corrected by the number of hunting licenses; (2) appropriate statistical tools are employed; and (3) methodological constraints are adequately taken into account. Finally, we argue that the opinion of Blanco-Aguiar and colleagues that our original results can lead to raptor persecution is a misinterpretation of our study. In this sense, we make an appeal for the importance of accurately differentiating between the ultimate (e.g. infectious diseases favoured by humans) and the proximate (e.g. enhanced predation pressure) causes of the decline in prey of economic interest (e.g. game species) in order to avoid unnecessary, unfounded or presumed conflicts with lobbies of conservation concern (e.g. hunters).

A simple model for skewed species-lifetime distributions

A simple model of a biological community assembly is studied. Communities are assembled by successive migrations and extinctions of species. In the model, species are interacting with each other. The intensity of the interaction between each pair of species is denoted by an interaction coefficient. At each time step, a new species is introduced to the system with randomly assigned interaction coefficients. If the sum of the coefficients, which we call the fitness of a species, is negative, the species goes extinct. The species-lifetime distribution is found to be well characterized by a stretched exponential function with an exponent close to 1/2. This profile agrees not only with more realistic population dynamics models but also with fossil records. We also find that an age-independent and inversely diversity-dependent mortality, which is confirmed in the simulation, is a key mechanism accounting for the distribution.

From Individuals to Populations: A Symbolic Process Algebra Approach to Epidemiology

Is it possible to symbolically express and analyse an individual-based model of disease spread, including realistic population dynamics? This problem is addressed through the use of process algebra and a novel method for transforming process algebra into Mean Field Equations. A number of stochastic models of population growth are presented, exploring different representations based on alternative views of individual behaviour. The overall population dynamics in terms of mean field equations are derived using a formal and rigorous rewriting based method. These equations are easily compared with the traditionally used deterministic Ordinary Differential Equation models and allow evaluation of those ODE models, challenging their assumptions about system dynamics. The utility of our approach for epidemiology is confirmed by constructing a model combining population growth with disease spread and fitting it to data on HIV in the UK population.

Realistic population dynamics in epidemiological models: the impact of population decline on the dynamics of childhood infectious diseases: Measles in Italy as an example

Most contributions in the field of mathematical modelling of childhood infectious diseases transmission dynamics have focused on stationary or exponentially growing populations. In this paper an epidemiological model with realistic demography is used to investigate the impact of the non-equilibrium conditions typical of the transition to sustained below replacement fertility (BRF) recently observed in a number of western countries, upon the transmission dynamics of measles. The results depend on the manner we model the relation between the (changing) age distribution of the population and contacts. Under some circumstances the transitional ageing phase typical of BRF populations might complexly interact with epidemiological variables leading to (i) a substantial reduction in the amount of vaccination effort required for eliminating the disease; (ii) a significant magnification of the perverse impact of vaccination in terms of the burden of severe age related morbidity.

Evolving complex food webs

We describe the properties of a model which links the ecology of food web structure with the evolutionary dynamics of speciation and extinction events; the model describes the dynamics of ecological communities on an evolutionary timescale. Species are defined as sets of characteristic features, and these features are used to determine interaction scores between species. A realistic population dynamics, which incorporates these scores, is used to determine the changes in population sizes on ecological time scales and so determine mean population sizes. We display typical examples of food webs constructed using the model and comment on the good agreement which is found between the model predictions and data on real webs.

A dynamic multistate model of robustness and frailty

Dynamic multistate models can show realistic population dynamics over time, model complex cycles, and encompass the life history of a cohort. This paper uses a recently developed approach to obtain the analytic solution of a time‐dependent multidimensional differential equation. The illustrative robust/frail model presented shows that the assumption of fixed individual frailty can be abandoned in a two living state model that allows transitions between health statuses and nonproportional hazards of death.

Inter-site: a new tool for the simulation of spatially realistic population dynamics

The inter-site simulator, a new tool for simulating spatially realistic population dynamics, is presented. Based on a discrete-event simulation system in an object-oriented programming environment, this simulator aims to offer a general and user-extensible framework for the simulation of spatially structured populations, including metapopulation systems. The simulator is implemented in Python, a versatile member of a recent class of high-level scripting languages, and uses the Tcl/Tk/Tix libraries as GUI front-end. This paper outlines the theoretical concepts underlying the simulator, describes its architecture, and demonstrates the use of the system by re-constructing a classical, state-variable oriented model drawn from literature that investigates the relationship of meta-population persistence with spatial patch arrangement. The paper concludes with a brief discussion of the benefits and drawbacks of the simulation approach to ecological modeling, and with contemplating the future potential of the inter-site system.

Line narrowing in multiresonant third order molecular spectroscopies

A complete analysis of line narrowing in third order, steady-state spectroscopies is given in terms of a recently developed perturbative theory for the nonlinear susceptibility. This approach rigorously includes realistic population dynamics and feeding without significantly complicating the analytic solutions. Unrelaxed resonant emission (i.e., resonant fluorescence and Raman emission) and coherent anti-Stokes Raman scattering (CARS) are treated as examples. Inhomogeneous broadening is included by an analytic contour integration over an inhomogeneous strain distribution. Unlike most existing approaches to line narrowing, both coherent and incoherent spectroscopies are treated by this same formalism, allowing the capabilities of each to be compared. A novel pictorial representation wich facilitates rationalization of line narrowing and its absence in certain coherent spectroscopies is introduced. Feeding effects are shown to alter line-narrowing behavior in third order for incoherent resonant emission but only in fifth order for CARS.