Plankton growth dynamic driven by plankton body size in deterministic and stochastic environments

In this paper, we establish a new phytoplankton–zooplankton model by considering the effects of plankton body size and stochastic environmental fluctuations. Mathematical theory work mainly gives the existence of boundary and positive equilibria and shows their local as well as global stability in the deterministic model. Additionally, we explore the dynamics of V-geometric ergodicity, stochastic ultimate boundedness, stochastic permanence, persistence in the mean, stochastic extinction, and the existence of a unique ergodic stationary distribution in the corresponding stochastic version. Numerical simulation work mainly reveals that plankton body size can generate great influences on the interactions between phytoplankton and zooplankton, which in turn proves the effectiveness of mathematical theory analysis. It is worth emphasizing that for the small value of phytoplankton cell size, the increase of zooplankton body size can not change the phytoplankton density or zooplankton density; for the middle value of phytoplankton cell size, the increase of zooplankton body size can decrease zooplankton density or phytoplankton density; for the large value of phytoplankton cell size, the increase of zooplankton body size can increase zooplankton density but decrease phytoplankton density. Besides, it should be noted that the increase of zooplankton body size cannot affect the effect of random environmental disturbance, while the increase of phytoplankton cell size can weaken its effect. There results may enrich the dynamics of phytoplankton-zooplankton models.     

Effects of environmental fluctuation and time delay on ratio dependent hyperparasitism model

A model of host–parasitoid–hyperparasitoid is considered with ratio dependence between parasitoid and hyperparasitoid. First, the conditions for local stability and increasing host fitness due to the effect of hyperparasitism are deduced. Next, we study the effects of stochastic environmental fluctuations and discrete time delay on the system behavior and calculate the corresponding populations variances. Numerical simulations illustrate that populations densities oscillate randomly around equilibrium points. Also, in contrast to previous literature, the simulations carried out here indicate that populations variances oscillate with the increase of time delay.     

THE IMPACT OF AGE-, SPACE-AND STOCHASTIC-STRUCTURE ON THE EXTINCTION PROBABILITY OF A CHINOOK SALMON METAPOPULATION

ABSTRACT. Using a mechanistic model, based on chinook life history, incorporating environmental and demographic stochasticity, we investigate how the probability of extinction is controlled by age, space and stochastic structure. Environmental perturbations of age dependent survivorships, combined with mixing of year classes in the spawning population, can lower the probability of extinction dramatically. This is an analog of the more familiar metapopulation result where dispersal between asynchronously fluctuating populations enhances persistence. For a two-river chinook metapopulation, dispersal between rivers with asynchronous environmental perturbations also dramatically enhances persistence, and anti-synchronous population fluctuations provide an even greater persistence probability. Anti-synchronous fluctuations would most likely occur in pristine habitat with naturally high levels of heterogeneity. Fifty percent dispersal between two populations provides the greatest insurance against extinction, a rate unrealistically high for salmon. In contrast, dispersal between exactly correlated populations with large amplitude environmental perturbations does not help persistence, no matter how high the dispersal rate. This is in spite of weak asynchrony provided by demographic stochasticity. Dispersal between rivers, one degraded and the other pristine, can substantially increase the probability of metapopulation extinction. Population structure, combined with asynchronous environmental perturbations and dispersal (or age class mixing) lowers the probability of chinook extinction dramatically but is almost useless when survivorships are impaired.     

Stationary distribution and extinction of a stochastic one-prey two-predator model with Holling type II functional response

In this article, we investigate a stochastic one-prey two-predator model with Holling type II functional response. We first establish sufficient conditions for persistence and extinction of prey and predator populations, then by constructing a suitable stochastic Lyapunov function, we establish sharp sufficient criteria for the existence of a unique ergodic stationary distribution of the positive solutions to the model. The results show that the smaller white noise can ensure the persistence of prey and predator populations while the larger white noise can lead to the extinction of prey and predator populations.     

Dynamics of a Stochastic Predator–Prey Model with Stage Structure for Predator and Holling Type II Functional Response

In this paper, we develop and study a stochastic predator–prey model with stage structure for predator and Holling type II functional response. First of all, by constructing a suitable stochastic Lyapunov function, we establish sufficient conditions for the existence and uniqueness of an ergodic stationary distribution of the positive solutions to the model. Then, we obtain sufficient conditions for extinction of the predator populations in two cases, that is, the first case is that the prey population survival and the predator populations extinction; the second case is that all the prey and predator populations extinction. The existence of a stationary distribution implies stochastic weak stability. Numerical simulations are carried out to demonstrate the analytical results.     

A stochastic modified Beverton–Holt model with the Allee effect

In this paper, we consider a discrete stochastic Beverton–Holt model with the Allee effect. We study the effects of demographic and environmental fluctuations on the dynamics of the model. Moreover, we investigate the potential function, the attainment time and quasi-stationary distributions of the system.     

个体投资治理污染的随机增长模型

本文研究了个体投资治理污染的随机增长模型.利用随机最优化的方法,得出了随机扰动、个体环保投资及环保技术对福利和经济增长的影响.对我国制定环保政策具有一定的积极作用.     

Global properties of a two-scale network stochastic delayed human epidemic dynamic model

Complex population structure and the large-scale inter-patch connection human transportation underlie the recent rapid spread of infectious diseases of humans. Furthermore, the fluctuations in the endemicity of the diseases within patch dwelling populations are closely related with the hereditary features of the infectious agent. We present an SIR delayed stochastic dynamic epidemic process in a two-scale dynamic structured population. The disease confers temporary natural or infection-acquired immunity to recovered individuals. The time delay accounts for the time-lag during which naturally immune individuals become susceptible. We investigate the stochastic asymptotic stability of the disease free equilibrium of the scale structured mobile population, under environmental fluctuations and the impact on the emergence, propagation and resurgence of the disease. The presented results are demonstrated by numerical simulation results.     

Non‐linear systems in plankton population dynamics and nitrogen cycles

In this paper we propose a new perspective of population dynamics of plankton, by considering some effects of global ecological cycles, in which a mixed population of plankton is embedded. The propagation of plankton is extremely influenced by various material cycles, such as Nitrogen cycles. Taking this global effect into consideration, we will construct a mathematical model of non‐linear system. Our model is a non‐linear, non‐equilibrium system based on a stochastic model realizing population dynamics of a mixed population of two species of plankton which is placed in a global nitrogen cycle. We show, in this article, that our model gives a new mathematical foundation of phenomena such as water blooms and the predominance of one type of plankton against the other. We calculate the probability of the occurrence of the water bloom of a mixed population and that is where one type of plankton predominates. We show, as a characteristic feature of our model, that the function of predominance has some discontinuity and that there exists a threshold point among the initial values, with respect to the type of plankton that predominates the other. In other words, there is a sort of phase transition in dynamic changes of plankton population, as a result of global ecological cycles. Copyright © 2000 John Wiley & Sons, Ltd.     

Optimal strategy of vaccination and treatment in an SIRS model with Markovian switching

Medical treatment and vaccination decisions are often sequential and uncertain. Markov decision process is an appropriate means to model and handle such stochastic dynamic decisions. This paper studies the near‐optimality of a stochastic SIRS epidemic model that incorporates vaccination and saturated treatment with regime switching. The stochastic model takes white noises and color noise into account. We first prove some priori estimates of the susceptible, infected, and recovered populations. Moreover, we establish some sufficient and necessary conditions of the near‐optimality by Pontryagin stochastic maximum principle. Our results show that the two kinds of environmental noises have great impacts on the infectious diseases. Finally, we illustrate our conclusions through numerical simulations.     

Emergent dynamics of the first‐order stochastic Cucker‐Smale model and application to finance

In this paper, we study stochastic aggregation properties of the financial model for the N‐asset price process whose dynamics is modeled by the weakly geometric Brownian motions with stochastic drifts. For the temporal evolution of stochastic components of drift coefficients, we employ a stochastic first‐order Cucker‐Smale model with additive noises. The asset price processes are weakly interacting via the stochastic components of drift coefficients. For the aggregation estimates, we use the macro‐micro decomposition of the fluctuations around the average process and show that the fluctuations around the average value satisfies a practical aggregation estimate over a time‐independent symmetric network topology so that we can control the differences of drift coefficients by tuning the coupling strength. We provide numerical examples and compare them with our analytical results. We also discuss some financial implications of our proposed model.     

Low dimensional homeochaos in coevolving host–parasitoid dimorphic populations: Extinction thresholds under local noise

A discrete time model describing the population dynamics of coevolution between host and parasitoid haploid populations with a dimorphic matching allele coupling is investigated under both determinism and stochastic population disturbances. The role of the properties of the attractors governing the survival of both populations is analyzed considering equal mutation rates and focusing on host and parasitoid growth rates involving chaos. The purely deterministic model reveals a wide range of ordered and chaotic Red Queen dynamics causing cyclic and aperiodic fluctuations of haplotypes within each species. A Ruelle–Takens–Newhouse route to chaos is identified by increasing both host and parasitoid growth rates. From the bifurcation diagram structure and from numerical stability analysis, two different types of chaotic sets are roughly differentiated according to their size in phase space and to their largest Lyapunov exponent: the Confined and Expanded attractors. Under the presence of local population noise, these two types of attractors have a crucial role in the survival of both coevolving populations. The chaotic confined attractors, which have a low largest positive Lyapunov exponent, are shown to involve a very low extinction probability under the influence of local population noise. On the contrary, the expanded chaotic sets (with a higher largest positive Lyapunov exponent) involve higher host and parasitoid extinction probabilities under the presence of noise. The asynchronies between haplotypes in the chaotic regime combined with low dimensional homeochaos tied to the confined attractors is suggested to reinforce the long-term persistence of these coevolving populations under the influence of stochastic disturbances. These ideas are also discussed in the framework of spatially-distributed host–parasitoid populations.     

Stochastic Epidemic SEIRS Models with a Constant Latency Period

In this paper, we consider the stability of a class of deterministic and stochastic SEIRS epidemic models with delay. Indeed, we assume that the transmission rate could be stochastic and the presence of a latency period of r consecutive days, where r is a fixed positive integer, in the “exposed” individuals class E. Studying the eigenvalues of the linearized system, we obtain conditions for the stability of the free disease equilibrium, in both the cases of the deterministic model with and without delay. In this latter case, we also get conditions for the stability of the coexistence equilibrium. In the stochastic case, we are able to derive a concentration result for the random fluctuations and then, using the Lyapunov method, to check that under suitable assumptions the free disease equilibrium is still stable.     

Impact of noise in a phytoplankton-zooplankton system

In this paper, we investigate the dynamics of a delayed toxic phytoplankton-two zooplankton system incorporating the effects of Levy noise and white noise. The value of this study lies in two aspects: Mathematically, we first prove the existence of a unique global positive solution of the system, and then we investigate the sufficient conditions that guarantee the stochastic extinction and persistence in the mean of each population. Ecologically, via numerical simulations, we find that the effect of white noise or Levy noise on the stochastic extinction and persistence of phytoplankton and zooplankton are similar, but the synergistic effects of the two noises on the stochastic extinction and persistence of these plankton are stronger than that of single noise. In addition, an increase in the toxin liberation rate or the intraspecific competition rate of zooplankton was found to be capable to increase the biomass of the phytoplankton but decrease the biomass of zooplankton. These results may help us to better understand the phytoplankton-zooplankton dynamics in the fluctuating environments.     

A common age effect model for the mortality of multiple populations

We introduce a model for the mortality rates of multiple populations. To build the proposed model we investigate to what extent a common age effect can be found among the mortality experiences of several countries and use a common principal component analysis to estimate a common age effect in an age–period model for multiple populations. The fit of the proposed model is then compared to age–period models fitted to each country individually, and to the fit of the model proposed by Li and Lee (2005).Although we do not consider stochastic mortality projections in this paper, we argue that the proposed common age effect model can be extended to a stochastic mortality model for multiple populations, which allows to generate mortality scenarios simultaneously for all considered populations. This is particularly relevant when mortality derivatives are used to hedge the longevity risk in an annuity portfolio as this often means that the underlying population for the derivatives is not the same as the population in the annuity portfolio.     

基于随机时滞模型的学习成绩波动规律

依据学习机制和教育心理学、认知心理学等有关研究成果,运用动力系统、随机过程等理论,构建描述学习成绩变化的随机时滞模型,并通过模型动力学性态的研究来揭示学习成绩波动特性,预测学习成绩对学习系统中内外因素的反应,分析造成学习成绩波动的原因,探讨相应的教学干预策略.结果表明,学习成绩波动是由4种动力学模式主导;学习成绩对学习系统内外因素具有高度的敏感性.这将从理论上加深对认知涌现机制的认识,并对于拓展和改进教学思维有积极意义.     

Exclusion and persistence in deterministic and stochastic chemostat models

We first introduce and analyze a variant of the deterministic single-substrate chemostat model. In this model, microbe removal and growth rates depend on biomass concentration, with removal terms increasing faster than growth terms. Using a comparison principle we show that persistence of all species is possible in this scenario. Then we turn to modelling the influence of random fluctuations by setting up and analyzing a stochastic differential equation. In particular, we show that random effects may lead to extinction in scenarios where the deterministic model predicts persistence. On the other hand, we also establish some stochastic persistence results.     

Survival analysis of a single-species population model with fluctuations and migrations between patches

We formulate a single-species population model with fluctuations and migrations between two different patches (the nature reserve and the natural environment) to describe the situation that endangered species often meets with. Firstly, we prove that there exists a unique global positive solution to a stochastic single-species model with any positive initial value. Then, sufficient conditions that guarantee extinction and persistence in the mean of solutions are derived as the main results. It turns out that, under moderate fluctuation conditions, migration rates play significant roles for the persistence of endangered species in nature reserve and the natural environment. We further provide the sustainable strategies for local managers to avoid the extinction of endangered species, and separately carry out illustrative examples and numerical simulations at the end of this contribution.