Nonlinear boundary conditions derived by singular pertubation in age structured population dynamics model

In this article, we derive Ricker’s [22, 23] type nonlinear boundary condition for an age structured population dynamic model by using a singular perturbation. The question addressed in this paper is the convergence of the singularly perturbed system. We first obtain a finite time convergence for a fixed initial distribution. Then we focus on the convergence uniformly of the singularly perturbed system with respect to the initial distribution in bounded sets.     

Continuous dependence results for a general model of size-dependent population dynamics

We are concerned with a general model of size structured population dynamics with the growth rate depending on the individual's size and time. In this paper, we shall study the continuous dependence of the solution on all given data such as aging and birth functions, growth rate functions and initial data.     

Synergetic Approach and modeling of fish population dynamics

In the last few years it has become increasingly obvious that one of the obstacles in the way of constructing good simulation models of the global ocean ecosystem is a poor understanding of the general principles of marine ecosystems processes. A great number of factors and relationships acting in the marine environment, in combination with the random character of change in many of them, call for the development of new approaches in modeling. In this paper a synergetic approach is proposed. A new paradigm for this approach is discussed. As an example a population with logistic natural growth under different conditions of exploitation is considered. It is shown that the simplest mechanism, that principally changes the behavior of a population in a fluctuating environment, includes fishing and migration. This mechanism explains catastrophic changes in population abundance in cases when no one factor may be seen as exclusive. It is shown that the characteristic level of population number does not correspond to the average balance between input (migration), output (fishing) and the growth of the population. The environment variability leads to stabilization far from equilibrium. This totally conforms to one of the fundamental results in Synergetics which assert that nonequilibrium in the presence of fluctuations may serve as a source of new order.     

Non-autonomous dynamics of a semi-Kolmogorov population model with periodic forcing

In this paper we study a semi-Kolmogorov type of population model, arising from a predator–prey system with indirect effects. In particular we are interested in investigating the population dynamics when the indirect effects are time dependent and periodic. We first prove the existence of a global pullback attractor. We then estimate the fractal dimension of the attractor, which is done for a subclass by using Leonov’s theorem and constructing a proper Lyapunov function. To have more insights about the dynamical behavior of the system we also study the coexistence of the three species. Numerical examples are provided to illustrate all the theoretical results.     

Global attractivity for impulsive population dynamics with delay arguments

This article investigates the global attractivity for impulsive population dynamics with delay arguments. Several sufficient conditions are obtained to ensure the global attractivity of the zero solution. These conditions do not require the boundedness of delay arguments, nor do they require some strict conditions on impulsive functions.     

A discrete time version for models of population dynamics in the presence of an infection

We present a set of difference equations which represents the discrete counterpart of a large class of continuous model concerning the dynamics of an infection in an organism or in a host population. The limiting behavior of the discrete model is studied and a threshold parameter playing the role of the basic reproduction number is derived.     

Variational formulation of an age-physiology dependent population dynamics

We transform a deterministic age-physiological factor population dynamics problem into its variational form. The internal/external heterogeneity of a population profoundly affects its dynamics, therefore, apart from age a, a second independent variable, g, say, referred to as the physiological parameter of individuals will also be a basis for classification. Using the well-known Ostrogradski or Gauss formula, we prove the existence and uniqueness theorems for the classical weak solution of the model.     

Recent progress on stage-structured population dynamics

A recent progress on stage-structured population dynamics is surveyed; the main emphasis is focused on the modelling and the analysis of different kinds of models.     

Optimal control for age-structured population dynamics of incomplete data

We are concerned with the control question for linear age-structured population dynamics of incomplete initial data. More precisely, the initial population age distribution is supposed to be unknown. We here generalize the notion of no-regret control of Lions (1992) [10] to such singular population dynamics, following the method by Nakoulima, Omrane and Vélin (2000) [16]. We prove that the problem we are considering has a unique no-regret control that we characterize by a singular optimality system.     

Existence and uniqueness for a kinetic model of population dynamics with character dependence and spatial structure

In this work, we consider a one species population dynamics model with character dependence, spatial structure and a nonlocal renewal process arising as a boundary condition. The individual interaction are based on Boltzmann kinetic-type modeling. Using fixed point arguments and the div-rot lemma, we prove that our model admits a unique global nonnegative solution.     

An innovative multistage, physiologically structured, population model to understand the European grapevine moth dynamics

We present a multistage, physiologically structured, population model for studying the dynamics of one of the most important grapevine insect pests. Growth of the population at each stage is modeled considering the climatic variations and the grape variety. A result of existence and uniqueness of solutions is presented for this original hyperbolic system as well as simulations of experimental field data.     

Biotic complexity of population dynamics

Changes in population size of animal species (lynx, muskrat, beaver, salmon, and fox), show diversification, episodic patterns in recurrence plots, novelty, nonrandom complexity, and asymmetric statistical distribution. These features of creativity characterize bios, a nonstationary pattern generated by bipolar feedback and multi‐agent predator–prey simulations, absent in chaotic attractors. Population series show partial‐autocorrelation, and the time series of the differences between consecutive terms also showed nonrandom patterns, differentiating bios from noise. As biotic patterns are found in quantum, cosmological, meteorological, biological, and economic processes, we propose that bipolar feedback is a generic process that contributes to the evolutionary generation of complexity at multiple levels of organization. © 2007 Wiley Periodicals, Inc. Complexity, 2008.     

An improved model of age-structured population dynamics

The classical model of age-dependent population dynamics is improved. Instead of the traditional renewal equation, a new approach is developed to describe the reproduction process of the population. The composition of a population is redefined to contain the pre-birth individuals, and the disadvantages of the classical model avoided. Moreover, the improved model turns out to be an initial value problem, which is mathematically more convenient to deal with. Existence and uniqueness results for the nonlinear nonautonomous system of model equations are obtained. It is shown that the classical model and its time delay generalization are two degenerate cases of the improved model.     

An experimental analysis of a population based approach for global optimization

In this paper we perform a computational analysis of a population based approach for global optimization, Population Basin Hopping (PBH), which was proven to be very efficient on very challenging global optimization problems by the authors (see ). The experimental analysis aims at understanding more deeply how the approach works and why it is successful on challenging problems.     

Cases,clusters, densities: Modeling the nonlinear dynamics of complex health trajectories

In the health informatics era, modeling longitudinal data remains problematic. The issue is method: health data are highly nonlinear and dynamic, multilevel and multidimensional, comprised of multiple major/minor trends, and causally complex—making curve fitting, modeling, and prediction difficult. The current study is fourth in a series exploring a case‐based density (CBD) approach for modeling complex trajectories, which has the following advantages: it can (1) convert databases into sets of cases (k dimensional row vectors; i.e., rows containing k elements); (2) compute the trajectory (velocity vector) for each case based on (3) a set of bio‐social variables called traces; (4) construct a theoretical map to explain these traces; (5) use vector quantization (i.e., k‐means, topographical neural nets) to longitudinally cluster case trajectories into major/minor trends; (6) employ genetic algorithms and ordinary differential equations to create a microscopic (vector field) model (the inverse problem) of these trajectories; (7) look for complex steady‐state behaviors (e.g., spiraling sources, etc) in the microscopic model; (8) draw from thermodynamics, synergetics and transport theory to translate the vector field (microscopic model) into the linear movement of macroscopic densities; (9) use the macroscopic model to simulate known and novel case‐based scenarios (the forward problem); and (10) construct multiple accounts of the data by linking the theoretical map and k dimensional profile with the macroscopic, microscopic and cluster models. Given the utility of this approach, our purpose here is to organize our method (as applied to recent research) so it can be employed by others. © 2015 Wiley Periodicals, Inc. Complexity 21: 160–180, 2016     

Dynamic equilibria of group vaccination strategies in a heterogeneous population

In this paper we present an evolutionary variational inequality model of vaccination strategies games in a population with a known vaccine coverage profile over a certain time interval. The population is considered to be heterogeneous, namely its individuals are divided into a finite number of distinct population groups, where each group has different perceptions of vaccine and disease risks. Previous game theoretical analyses of vaccinating behaviour have studied the strategic interaction between individuals attempting to maximize their health states, in situations where an individual’s health state depends upon the vaccination decisions of others due to the presence of herd immunity. Here we extend such analyses by applying the theory of evolutionary variational inequalities (EVI) to a (one parameter) family of generalized vaccination games. An EVI is used to provide conditions for existence of solutions (generalized Nash equilibria) for the family of vaccination games, while a projected dynamical system is used to compute approximate solutions of the EVI problem. In particular we study a population model with two groups, where the size of one group is strictly larger than the size of the other group (a majority/minority population). The smaller group is considered much less vaccination inclined than the larger group. Under these hypotheses, considering that the vaccine coverage of the entire population is measured during a vaccine scare period, we find that our model reproduces a feature of real populations: the vaccine averse minority will react immediately to a vaccine scare by dropping their strategy to a nonvaccinator one; the vaccine inclined majority does not follow a nonvaccinator strategy during the scare, although vaccination in this group decreases as well. Moreover we find that there is a delay in the majority’s reaction to the scare. This is the first time EVI problems are used in the context of mathematical epidemiology. The results presented emphasize the important role played by social heterogeneity in vaccination behaviour, while also highlighting the valuable role that can be played by EVI in this area of research.      

Baseline models of spatial population dynamics

To understand human population dynamics fully, before considering complex human agency it may be useful to construct baseline models to see where such agency may and may not be necessary. In fact, the dynamics of human populations may be amenable to mathematical modeling with relatively parsimonious mechanisms. We review some of the more prominent of such models, namely, the spatial Galton-Watson (GW) model, modifications of the GW model that add migration and immigration, and the Bolker-Pacala model, in which mortality (or birth rate) is affected by competition. We show that change in the distribution of population density over the last century for 12 American rural states may be captured by the simplest of the models, the spatial GW model.     

Modeling dynamics of cell population molecule expression distribution

This article introduces a novel approach to the study of the dynamics of the molecule expression level of large-size cell populations, whose goal is to understand how individual cell behavior propagates to population dynamics. A hybrid automaton framework is used which allows the simultaneous modeling of the formation and dissociation of cell-to-cell conjugations, and the molecular processes they control. Serial encounters among the cells are described by a stochastic approach under which the cell distribution over the state space is modeled and the dynamics of the state probability density functions is determined. This work is motivated by the investigation of T-cell receptor expression distribution. These receptors are essential for the antigen recognition and the regulation of the immune system. The results are illustrated with examples and validated with real data.