General functional response and recruitment in a predator–prey system with capture on both species

This work provides a mathematical model for a predator‐prey system with general functional response and recruitment, which also includes capture on both species, and analyzes its qualitative dynamics. The model is formulated considering a population growth based on a general form of recruitment and predator functional response, as well as the capture on both prey and predators at a rate proportional to their populations. In this sense, it is proved that the dynamics and bifurcations are determined by a two‐dimensional threshold parameter. Finally, numerical simulations are performed using some ecological observations on two real species, which validate the theoretical results obtained. Copyright © 2014 John Wiley & Sons, Ltd.     

A continuous parametric shape model

In this paper we propose a flexible continuous parametric shape model for star-shaped planar objects. The model is based on a polar Fourier expansion of the normalized radius-vector function. The expected phase amplitudes are modelled by a simple regression with parameters having nice geometric interpretations. The suggestedgeneralized p-order model is an extension of first- and second-order Gaussian shape models, and in particular the Gaussian assumption is relaxed. The statistical analysis is straightforward, as demonstrated by an application concerning shape discrimination of two cell nuclei populations.     

Optimal training sample allocation and asymptotic expansions for error rates in discriminant analysis

The sample-based rule obtained from Bayes classification rule by replacing the unknown parameters by ML estimates from a stratified training sample is used for the classification of a random observationX into one ofL populations. The asymptotic expansions in terms of the inverses of the training sample sizes for cross-validation, apparent and plug-in error rates are found. These are used to compare estimation methods of the error rate for a wide range of regular distributions as probability models for considered populations. The optimal training sample allocation minimizing the asymptotic expected error regret is found in the cases of widely applicable, positively skewed distributions (Rayleigh and Maxwell distributions). These probability models for populations are often met in ecology and biology. The results indicate that equal training sample sizes for each populations sometimes are not optimal, even when prior probabilities of populations are equal.     

Stability and bifurcation in epidemic models describing the transmission of toxoplasmosis in human and cat populations

A five‐dimensional ordinary differential equation model describing the transmission of Toxoplamosis gondii disease between human and cat populations is studied in this paper. Self‐diffusion modeling the spatial dynamics of the T. gondii disease is incorporated in the ordinary differential equation model. The normalized version of both models where the unknown functions are the proportions of the susceptible, infected, and controlled individuals in the total population are analyzed. The main results presented herein are that the ODE model undergoes a trans‐critical bifurcation, the system has no periodic orbits inside the positive octant, and the endemic equilibrium is globally asymptotically stable when we restrict the model to inside of the first octant. Furthermore, a local linear stability analysis for the spatially homogeneous equilibrium points of the reaction diffusion model is carried out, and the global stability of both the disease‐free and endemic equilibria are established for the reaction–diffusion system when restricted to inside of the first octant. Finally, numerical simulations are provided to support our theoretical results and to predict some scenarios about the spread of the disease. Copyright © 2017 John Wiley & Sons, Ltd.     

Nonlinear Integroparabolic Equations on Unbounded Domains: Existence of Classical Solutions with Special Properties

Classical solvability is established for a certain nonlinear integrodifferential parabolic equation, on unbounded domains in several dimensions. The model equation of the Fokker-Planck type represents a regularized version of an equation recently derived by J. A. Acebrón and R. Spigler for the physical problem of describing the time evolution of large populations of nonlinearly globally coupled random oscillators. Precise estimates are obtained for the decay of convolutions with fundamental solutions of linear parabolic equations on unbounded domains in R ⁿ . Existence of a classical solution with special properties is established.     

Global properties of a class of HIV infection models with Beddington–DeAngelis functional response

In this paper, the global properties of a class of human immunodeficiency virus (HIV) models with Beddington–DeAngelis functional response are investigated. Lyapunov functions are constructed to establish the global asymptotic stability of the uninfected and infected steady states of three HIV infection models. The first model considers the interaction process of the HIV and the CD4 ⁺ T cells and takes into account the latently and actively infected cells. The second model describes two co‐circulation populations of target cells, representing CD4 ⁺ T cells and macrophages. The third model is a two‐target‐cell model taking into account the latently and actively infected cells. We have proven that if the basic reproduction number R₀ is less than unity, then the uninfected steady state is globally asymptotically stable, and if R₀ > 1, then the infected steady state is globally asymptotically stable. Copyright © 2012 John Wiley & Sons, Ltd.     

The E(NK) model: Extending the NK model to incorporate gene‐by‐environment interactions and epistasis for diploid genomes

The haploid NK model developed by Kauffman can be extended to diploid genomes and to incorporate gene‐by‐environment interaction effects in combination with epistasis. To provide the flexibility to include a wide range of forms of gene‐by‐environment interactions, a target population of environment types (TPE) is defined. The TPE consists of a set of E different environment types, each with their own frequency of occurrence. Each environment type conditions a different NK gene network structure or series of gene effects for a given network structure, providing the framework for defining gene‐by‐environment interactions. Thus, different NK models can be partially or completely nested within the E environment types of a TPE, giving rise to the E(NK) model for a biological system. With this model it is possible to examine how populations of genotypes evolve in context with properties of the environment that influence the contributions of genes to the fitness values of genotypes. We are using the E(NK) model to investigate how both epistasis and gene‐by‐environment interactions influence the genetic improvement of quantitative traits by plant breeding strategies applied to agricultural systems. © 2002 Wiley Periodicals, Inc.     

Efficient Computation of the Joint Sample Frequency Spectra for Multiple Populations

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this article, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study, we demonstrate our improvements to numerical stability and computational complexity.     

A Preliminary Test in Discriminant Analysis

One of the aims of discriminant analysis is the allocation of unknown entities to populations that are knowna priori. Considerkpopulations. LetXdenote the vector of observations on an experimental unit, whose origin is uncertain. For the general parametric case, a test is proposed to verify the hypothesis thatXis coming from a new population. The case of normal population with equal variance is fully derived.     

AN INDIVIDUAL‐BASED MODEL FOR FERAL HOGS IN GREAT SMOKY MOUNTAINS NATIONAL PARK

The expansion of feral hog (Sus scrofa) populations in the United States has resulted in increased efforts to develop and implement control strategies designed to minimize the impacts done by this invasive species. We describe an individual‐based model for feral hogs in Great Smoky Mountains National Park (GSMNP). The objectives of the model are to provide an understanding of the population dynamics of this feral hog population and to determine the efficacy of the annual harvest as a population control method. Results suggest that the dynamics of the population are driven by fall hard mast production and the GSMNP harvests currently limit growth of the population, but these control efforts have not reduced the population.     

Modeling and simulation of cell populations interaction

Regenerative medicine and cell therapy provide great hopes for the use of adult and stem cells. The latter are far less present in tissue than the former and must be expanded using cell culture. Stem cells culture requires the conservation of their proliferation and self-renewal capabilities. Still, the complex interaction between cell populations, for example in primary cell cultures, are not well-known and may account for part of the variability of such cultures. In order to represent and understand the evolution of cultured stem cells, we present here a mathematical model of cell proliferation and differentiation. Based on the formalism of cellular automata, this model simulates the evolution of several cell classes (which may represent either different levels of differentiation or different cell types) in an environment modeling the growth medium. We model the cell cycle as on the one hand a quiescence phase during which a cell rests, and on the other hand a division phase during which the cell starts the division process. In order to represent cell–cell interaction, the transition probability between those phases depends on the local composition of the growth medium depending itself on neighboring cells. An interaction between cellular populations is represented by a quantitative parameter which has a direct impact on cellular proliferation. Differentiation results in a change of the cell class and depends on the biological model studied : it may result from an asymmetric division or be a consequence of the local composition of the growth medium. This mathematical model aims at a better understanding of the interactions between cell populations in a culture. By defining constraints on the potential or the type of the cells at the end of a culture, it will then be possible to find optimal experimental conditions for cell production.     

OPTIMAL CONTROL APPLIED TO RIFT VALLEY FEVER

Abstract Rift Valley Fever (RVF) virus is a mosquito‐born pathogen that infects livestock but it also has the capability to infect humans through direct or indirect contact with blood or organs of infected animals and by bites from infected mosquitos. The economic and social cost of the disease to rural populations can lead to a cascade of negative effects on the sustainability of animal and human populations. Vaccines exist to protect against this disease. Through a compartment model depicting the interactions leading to the spread of RVF in Aedes and Culex mosquitos and a livestock population, an optimal control problem is developed to minimize the number of vaccinated livestock at the final time while minimizing the negative effects of the infected Aedes and Culex mosquitos and the cost of the vaccination process. The unique optimal vaccination strategy is produced for given high transmission parameters and numerical results portray that vaccination depends on the level of effectiveness of the protocol.     

Stability in predator – prey models and discretization of a modified Volterra – Lotka model

We consider n  2 populations of animals that are living in mutual predator – prey relations or are pairwise neutral to each other. We assume the temporal development of the population densities to be described by a system of differential equations which has an equilibrium state solution. We derive sufficient conditions for this equilibrium state to be stable by Lyapunov's method. The results supplement those published elsewhere.

Further we consider a modification of the Volterra – Lotka model which admits an asymptotically stable steady state solution. This model is discretized in two ways and we investigate how small the time step size has to be chosen in order to guarantee that the steady state solution is an attractive fixed point of the discretized model. This investigation is connected with the determination of the model parameters from given data.     

A Mathematical Model of Prostate Tumor Growth Under Hormone Therapy with Mutation Inhibitor

This paper extends Jackson’s model describing the growth of a prostate tumor with hormone therapy to a new one with hypothetical mutation inhibitors. The new model not only considers the mutation by which androgen-dependent (AD) tumor cells mutate into androgen-independent (AI) ones but also introduces inhibition which is assumed to change the mutation rate. The tumor consists of two types of cells (AD and AI) whose proliferation and apoptosis rates are functions of androgen concentration. The mathematical model represents a free-boundary problem for a nonlinear system of parabolic equations, which describe the evolution of the populations of the above two types of tumor cells. The tumor surface is a free boundary, whose velocity is equal to the cell’s velocity there. Global existence and uniqueness of solutions of this model is proved. Furthermore, explicit formulae of tumor volume at any time t are found in androgen-deprived environment under the assumption of radial symmetry, and therefore the dynamics of tumor growth under androgen-deprived therapy could be predicted by these formulae. Qualitative analysis and numerical simulation show that controlling the mutation may improve the effect of hormone therapy or delay a tumor relapse.     

INVESTIGATING THE VIABILITY OF SQUIRREL POPULATIONS; A MODELING APPROACH FOR THE ISLAND OF LESVOS,GREECE

ABSTRACT. Habitat loss and fragmentation are considered to be the most important factors responsible for population decreases in small mammal populations. Particularly important is also the effect of insularity that can act syn‐ergistically with the previous factors. Population Viability Analysis (PVA) combines the spatial component of the problem with the species population structure offering an integrated platform for testing and assessing the effects of critical parameters upon the population viability. Various management options can also be quantified and tested. In the case of Sciurus anomalous, a vulnerable squirrel species endemic in Lesvos, a series of threats and management problems were identified and assessed. A stochastic simulation model was developed and parameterized with field data for the species using the program Ramas/GIS. The results suggested that special attention has to be paid to the planning of road system networks and to stopping illegal hunting, especially when extinction risks for vulnerable populations are higher with the above threats.     

Subset selection procedures for restricted families of probability distributions

In this paper we are interested in studying multiple decision procedures fork (k≧2) populations which are themselves unknown but which one assumed to belong to a restricted family. We propose to study a selection procedure for distributions associated with these populations which are convex-ordered with respect to a specified distributionG assuming that there exists a best one. The procedure described here is based on a statistic which is a linear function of the firstr order statistics and which reduces to the total life statistics whenG is exponential. The infimum of the probability of a correct selection and an asymptotic expression for this probability are obtained using the subset selection approach. Some other properties of this procedure are discussed. Asymptotic relative efficiencies of this rule with respect to some selection procedures proposed by Barlow and Gupta [3] for the star-ordered distributions and by Gupta [8] for the gamma populations with known shape parameters are obtained. A selection procedure for selecting the best population using the indifference zone approach is also studied. This research was supported by the Office of Naval Research Contract N00014-75-C-0455 at Purdue University. Reproduction in whole or in part is permitted for any purpose of the United States Government. Ming-Wei Lu is now at the Department of Vital and Health Statistics, Michigan.     

Dynamics of populations with age-difference and diffusion: localization

In this paper we study the behavior of the solutions of the Gurtin-MacCamy model for the dynamics of populations with diffusion and age-dependence We give sufficient conditions on the birth and death modules for the population to remain localized in a fixed interval or to ultimately cover all the domain R.     

A two-sample procedure for selecting the population with the largest mean fromk normal populations

Summary A two-sample procedure is given for selecting the population with the largest mean fromk normal populations with known variances. Thek populations are screened through the first sample for possible elimination of those populations which have considerably smaller means. The second sample is drawn from the non-eliminated populations only. The two-sample procedure is compared with the fixed sample procedure of Bechhofer [2]. The ratio of the expected total number of observations required in the first case to the total number of observations required in the second case for the same level of the probability of a correct selection measures the relative advantage of experimenting in two stages. Fork=2 it is shown that the ratio is bounded below by 1/4. Fork=2 the probability of a correct selection can be computed from the tables of the bivariate normal distribution function. Fork≧3 a lower bound on the probability of a correct selection is derived which can be computed with the help of available tables. An upper bound is also given for the expected sample size. The author's work was partly supported by the National Science Foundation Grant No. GP-7496 at Indiana University.     

A MODEL TO DETECT GRAZING SENSITIVITY OF MYOPORUM PLATYCARPUM IN THE ARID RANGELANDS OF SOUTH AUSTRALIA

ABSTRACT. Herbivores, particularly introduced ones such as sheep and rabbits, have reduced the levels of regeneration of a number of species of native trees and shrubs in the arid rangelands of southern Australia since European settlement. These reduced levels of regeneration mean that populations of some species are declining while others, less palatable to herbivores, are being maintained, hence gradually altering the composition and/or overall cover of vegetation. In the long term, this could result in loss of palatable species valuable to the pastoral industry for animal production, and/or the dominance of large areas by undesirable “woody weed” species. To investigate the effects of grazing, we develop a model which projects the long‐term survival rate of a focus species, Myoporum platycarpum, under grazing and nongrazing regimes. The technique we are applying is an extension of the Leslie growth model, where the vital rates are linked to random rainfall events and deterministic grazing. The effect of grazing is incorporated into the model based upon data primarily collected from the TGB Osborn Koonamore Vegetation Reserve, 400 km north of Adelaide in South Australia within and without the exclosure. The results suggest that only with higher than average rainfall for extended periods will the species of interest, M. platycarpum, survive under grazing.     

Data Surrogation Error in p-Median Models

The p-median model locates facilities to provide optimal service to target populations. Where, for some reason, an inappropriate variable is used to stand in for a target population's demand, less than ideal facility systems can result. This effect is termed surrogation error. In this paper, I introduce this concept and perform an experiment which, with data for 25 Canadian cities, demonstrates that significant surrogation error can occur if general population is used in place of children or senior populations. I identify some of the correlates of surrogation error and conclude with a warning to location scientists to be conscious of, and to try to avoid, this problem.