Hening Alexandru, Nguyen Dang H, Yin George
Department of Mathematics, Tufts University, Bromfield-Pearson Hall, 503 Boston Avenue, Medford, MA, 02155, USA.
Department of Mathematics, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
J Math Biol. 2018 Feb;76(3):697-754. doi: 10.1007/s00285-017-1153-2. Epub 2017 Jul 3.
This work is devoted to studying the dynamics of a structured population that is subject to the combined effects of environmental stochasticity, competition for resources, spatio-temporal heterogeneity and dispersal. The population is spread throughout n patches whose population abundances are modeled as the solutions of a system of nonlinear stochastic differential equations living on [Formula: see text]. We prove that r, the stochastic growth rate of the total population in the absence of competition, determines the long-term behaviour of the population. The parameter r can be expressed as the Lyapunov exponent of an associated linearized system of stochastic differential equations. Detailed analysis shows that if [Formula: see text], the population abundances converge polynomially fast to a unique invariant probability measure on [Formula: see text], while when [Formula: see text], the population abundances of the patches converge almost surely to 0 exponentially fast. This generalizes and extends the results of Evans et al. (J Math Biol 66(3):423-476, 2013) and proves one of their conjectures. Compared to recent developments, our model incorporates very general density-dependent growth rates and competition terms. Furthermore, we prove that persistence is robust to small, possibly density dependent, perturbations of the growth rates, dispersal matrix and covariance matrix of the environmental noise. We also show that the stochastic growth rate depends continuously on the coefficients. Our work allows the environmental noise driving our system to be degenerate. This is relevant from a biological point of view since, for example, the environments of the different patches can be perfectly correlated. We show how one can adapt the nondegenerate results to the degenerate setting. As an example we fully analyze the two-patch case, [Formula: see text], and show that the stochastic growth rate is a decreasing function of the dispersion rate. In particular, coupling two sink patches can never yield persistence, in contrast to the results from the non-degenerate setting treated by Evans et al. which show that sometimes coupling by dispersal can make the system persistent.
这项工作致力于研究一个结构化种群的动态变化,该种群受到环境随机性、资源竞争、时空异质性和扩散的综合影响。种群分布在(n)个斑块中,其种群丰度被建模为定义在([公式:见正文])上的非线性随机微分方程组的解。我们证明,在没有竞争的情况下,总种群的随机增长率(r)决定了种群的长期行为。参数(r)可以表示为相关随机微分方程线性化系统的李雅普诺夫指数。详细分析表明,如果([公式:见正文]),种群丰度以多项式速度快速收敛到([公式:见正文])上的唯一不变概率测度,而当([公式:见正文])时,斑块的种群丰度几乎必然以指数速度快速收敛到(0)。这推广并扩展了埃文斯等人(《数学生物学杂志》66(3):423 - 476, 2013)的结果,并证明了他们的一个猜想。与最近的进展相比,我们的模型纳入了非常一般的密度依赖增长率和竞争项。此外,我们证明了持续性对于增长率、扩散矩阵和环境噪声协方差矩阵的小的、可能依赖密度的扰动是鲁棒的。我们还表明随机增长率连续依赖于系数。我们的工作允许驱动我们系统的环境噪声是退化的。从生物学角度来看这是相关的,因为例如不同斑块的环境可以是完全相关的。我们展示了如何将非退化结果适应到退化情形。作为一个例子,我们全面分析了双斑块情形([公式:见正文]),并表明随机增长率是扩散率的递减函数。特别地,与埃文斯等人处理的非退化情形的结果相反,耦合两个汇斑块永远不会产生持续性,他们的结果表明有时通过扩散耦合可以使系统持续。