Cantrell R S, Cosner C
Department of Mathematics, University of Miami, Coral Gables, FL 33124, USA. [rsc;gcc]@math.miami.edu
J Math Biol. 2004 Feb;48(2):187-217. doi: 10.1007/s00285-003-0229-3. Epub 2003 Aug 20.
We use a scaling procedure based on averaging Poisson distributed random variables to derive population level models from local models of interactions between individuals. The procedure is suggested by using the idea of hydrodynamic limits to derive reaction-diffusion models for population interactions from interacting particle systems. The scaling procedure is formal in the sense that we do not address the issue of proving that it converges; instead we focus on methods for computing the results of the scaling or deriving properties of rescaled systems. To that end we treat the scaling procedure as a transform, in analogy with the Laplace or Fourier transform, and derive operational formulas to aid in the computation of rescaled systems or the derivation of their properties. Since the limiting procedure is adapted from work by Durrett and Levin, we refer to the transform as the Durrett-Levin transform. We examine the effects of rescaling in various standard models, including Lotka-Volterra models, Holling type predator-prey models, and ratio-dependent models. The effects of scaling are mostly quantitative in models with smooth interaction terms, but ratio-dependent models are profoundly affected by the scaling. The scaling transforms ratio-dependent terms that are singular at the origin into smooth terms. Removing the singularity at the origin eliminates some of the unique dynamics that can arise in ratio-dependent models.
我们使用一种基于平均泊松分布随机变量的缩放程序,从个体间相互作用的局部模型推导出总体水平模型。该程序是通过利用流体动力学极限的思想,从相互作用粒子系统推导出种群相互作用的反应扩散模型而提出的。缩放程序在形式上是这样的,即我们不解决证明其收敛的问题;相反,我们专注于计算缩放结果或推导重标度系统性质的方法。为此,我们将缩放程序视为一种变换,类似于拉普拉斯变换或傅里叶变换,并推导运算公式以帮助计算重标度系统或推导其性质。由于极限程序改编自杜雷特(Durrett)和莱文(Levin)的工作,我们将该变换称为杜雷特 - 莱文变换。我们研究了缩放对各种标准模型的影响,包括洛特卡 - 沃尔泰拉(Lotka - Volterra)模型、霍林(Holling)型捕食者 - 猎物模型和比率依赖模型。在具有平滑相互作用项的模型中,缩放的影响大多是定量的,但比率依赖模型受到缩放的影响很大。缩放将在原点处奇异的比率依赖项变换为平滑项。消除原点处的奇异性消除了比率依赖模型中可能出现的一些独特动力学。