Integrating individual movement behaviour into dispersal functions
Integrating individual movement behaviour into dispersal functions
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DOI：
10.1016/j.jtbi.2006.12.009
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发表时间：
2007-04-21
影响因子：
2
通讯作者：
Frank, Karin
中科院分区：
文献类型：
--
作者：
Heinz, Simone K.;Wissel, Christian;Frank, Karin
扩散函数是将扩散整合到种群和元种群动态的复杂模型中的重要工具。文献中的大多数方法都非常简单，散布函数只包含一个或两个参数，这些参数概括了运动行为的所有影响，例如不同的运动模式或不同的感知能力。这些参数的总结性使评估某一特定行为方面的影响变得困难。我们提出了一种将运动行为参数以一种简单的方式整合到特定的分散函数中的方法。利用基于空间个体的模拟模型来模拟不同的运动行为，我们推导了分散函数参数与运动行为几个细节之间的函数关系的拟合函数。这是针对三种不同的运动模式（循环，阿基米德螺旋，随机游走）进行的。此外，我们还提供了表征扩散功能形状的测量方法，并可以根据景观连通性进行解释。这允许对所发现的关系进行生态学解释。(c) 2006 Elsevier Ltd.版权所有。
Dispersal functions are an important toot 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. (c) 2006 Elsevier Ltd. All rights reserved.