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将个体运动行为整合到扩散函数中。

Integrating individual movement behaviour into dispersal functions.

作者信息

Heinz Simone K, Wissel Christian, Conradt Larissa, Frank Karin

机构信息

Department of Ecological Modelling, UFZ-Centre for Environmental Research Leipzig Halle, UFZ, P.O. Box 500136, 04301 Leipzig, Germany.

出版信息

J Theor Biol. 2007 Apr 21;245(4):601-9. doi: 10.1016/j.jtbi.2006.12.009. Epub 2006 Dec 12.

Abstract

Dispersal functions are an important tool for integrating dispersal into complex models of population and metapopulation dynamics. Most approaches in the literature are very simple, with the dispersal functions containing only one or two parameters which summarise all the effects of movement behaviour as for example different movement patterns or different perceptual abilities. The summarising nature of these parameters makes assessing the effect of one particular behavioural aspect difficult. We present a way of integrating movement behavioural parameters into a particular dispersal function in a simple way. Using a spatial individual-based simulation model for simulating different movement behaviours, we derive fitting functions for the functional relationship between the parameters of the dispersal function and several details of movement behaviour. This is done for three different movement patterns (loops, Archimedean spirals, random walk). Additionally, we provide measures which characterise the shape of the dispersal function and are interpretable in terms of landscape connectivity. This allows an ecological interpretation of the relationships found.

摘要

扩散函数是将扩散整合到种群和集合种群动态复杂模型中的重要工具。文献中的大多数方法都非常简单,扩散函数仅包含一两个参数,这些参数概括了移动行为的所有影响,例如不同的移动模式或不同的感知能力。这些参数的概括性质使得评估某一特定行为方面的影响变得困难。我们提出了一种将移动行为参数以简单方式整合到特定扩散函数中的方法。使用基于空间个体的模拟模型来模拟不同的移动行为,我们推导了扩散函数参数与移动行为的几个细节之间函数关系的拟合函数。这是针对三种不同的移动模式(环路、阿基米德螺旋线、随机游走)进行的。此外,我们提供了表征扩散函数形状且可根据景观连通性进行解释的度量。这使得能够对所发现的关系进行生态学解释。

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