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Spread rate for a nonlinear stochastic invasion

机译:非线性随机入侵的扩散率

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Despite the recognized importance of stochastic factors, models for ecological invasions are almost exclusively formulated using deterministic equations [29]. Stochastic factors relevant to invasions can be either extrinsic (quantities such as temperature or habitat quality which vary randomly in time and space and are external to the population itself) or intrinsic (arising from a finite population of individuals each reproducing, dying, and interacting with other individuals in a probabilistic manner). It has been long conjectured [27] that intrinsic stochastic factors associated with interacting individuals can slow the spread of a population or disease, even in a uniform environment. While this conjecture has been borne out by numerical simulations, we are not aware of a thorough analytical investigation. In this paper we analyze the effect of intrinsic stochastic factors when individuals interact locally over small neighborhoods. We formulate a set of equations describing the dynamics of spatial moments of the population. Although the full equations cannot be expressed in closed form, a mixture of a moment closure and comparison methods can be used to derive upper and lower bounds for the expected density of individuals. Analysis of the upper solution gives a bound on the rate of spread of the stochastic invasion process which lies strictly below the rate of spread for the deterministic model. The slow spread is most evident when invaders occur in widely spaced high density foci. In this case spatial correlations between individuals mean that density dependent effects are significant even when expected population densities are low. Finally, we propose a heuristic formula for estimating the true rate of spread for the full nonlinear stochastic process based on a scaling argument for moments. [References: 38]
机译:尽管认识到随机因素的重要性,但几乎完全使用确定性方程式来制定生态入侵模型[29]。与入侵有关的随机因素可以是外在因素(温度或栖息地质量等数量,其在时间和空间上随机变化,并且在种群本身外部)或内在因素(来自有限数量的个体,每个个体都在繁殖,死亡和与之互动其他个人)。长期以来人们一直猜测[27],即使在一个统一的环境中,与个体互动相关的内在随机因素也会减缓人口或疾病的传播。尽管这个猜想已经通过数值模拟得到了证实,但我们还没有进行全面的分析研究。在本文中,我们分析了当个体在小邻里进行局部互动时内在随机因素的影响。我们制定了一组方程来描述人口的空间矩的动力学。尽管不能以闭合形式表示完整的方程式,但可以使用矩闭合和比较方法的混合来得出预期的个人密度的上限和下限。对上限解的分析给出了随机入侵过程扩展率的界限,该速率严格低于确定性模型的扩展率。当侵略者发生在间距较大的高密度病灶中时,传播速度很慢。在这种情况下,即使预期的人口密度较低,个体之间的空间相关性也意味着依赖密度的效应非常明显。最后,我们提出了一种启发式公式,用于基于矩的比例参数来估计整个非线性随机过程的真实扩散率。 [参考:38]

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