How should we define fitness in structured metapopulation models? Including an application to the calculation of evolutionarily stable dispersal strategies
How should we define fitness in structured metapopulation models? Including an application to the calculation of evolutionarily stable dispersal strategies
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我们应该如何定义结构化集合种群模型中的适应性？
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
M. Gyllenberg
中科院分区：
文献类型：
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作者：
Johan A. J. Metz;Johan A. J. Metz;M. Gyllenberg
我们定义了一个健身的概念，适用于结构化集合种群组成的无限多个平等耦合补丁。此外，我们引入了一个更容易计算的量Rm，它与适应度的关系与R 0与普通种群动态中的适应度的关系相同：突变体的Rm仅在居民种群动态收敛到一个点平衡时定义，并且Rm大于（小于）1当且仅当突变体适应度为正（负）时。Rm对应于由新生扩散者建立的局部菌落（平均小于一个）产生的新生扩散者的平均数量。给出了计算其数值的有效算法。作为这些概念的有用性的一个例子，我们计算进化稳定的条件扩散策略的个人，可以占当地人口密度在他们的扩散决策。在阈值密度<$以下，每个人都应该留下来，在阈值密度<$以上，每个人都应该离开，在阈值密度<$以下，每个人都应该留下来，在阈值密度<$以上，利润率被衡量为通过仅由非扩散者组成的血统产生的扩散者的平均数量。
We define a fitness concept applicable to structured metapopulations consisting of infinitely many equally coupled patches. In addition, we introduce a more easily calculated quantity Rm that relates to fitness in the same manner as R0 relates to fitness in ordinary population dynamics: the Rm of a mutant is only defined when the resident population dynamics converges to a point equilibrium and Rm is larger (smaller) than 1 if and only if mutant fitness is positive (negative). Rm corresponds to the average number of newborn dispersers resulting from the (on average less than one) local colony founded by a newborn disperser. Efficient algorithms for calculating its numerical value are provided. As an example of the usefulness of these concepts we calculate the evolutionarily stable conditional dispersal strategy for individuals that can account for the local population density in their dispersal decisions. Below a threshold density ã, at which staying and leaving are equality profitable, everybody should stay and above ã everybody should leave, where profitability is measured as the mean number of dispersers produced through lines of descent consisting of only non–dispersers.