Evolutionarily Stable and Convergent Stable Strategies in Reaction–Diffusion Models for Conditional Dispersal
Evolutionarily Stable and Convergent Stable Strategies in Reaction–Diffusion Models for Conditional Dispersal
复制标题
条件扩散的反应扩散模型中的进化稳定和收敛稳定策略
DOI：
10.1007/s11538-013-9901-y
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发表时间：
2014
影响因子：
3.5
通讯作者：
Y. Lou
中科院分区：
文献类型：
--
作者：
King;Y. Lou
我们考虑两个竞争物种的数学模型，以在空间变化但时间恒定的环境中条件扩散的演化。两个物种的不同之处仅在于它们的扩散策略，即随机扩散和沿资源梯度向上偏向移动的组合。黑斯廷斯表明，在没有偏向运动或平流的情况下，当且仅当突变体的随机扩散率小于居民时，突变体才能在罕见时入侵。当存在少量偏向运动或平流时，我们表明存在正随机扩散率，该速率既是局部进化稳定的又是收敛稳定的。我们对该模型的分析表明，随机和有偏差运动的平衡组合可能是种群更好的栖息地选择策略。
We consider a mathematical model of two competing species for the evolution of conditional dispersal in a spatially varying, but temporally constant environment. Two species are different only in their dispersal strategies, which are a combination of random dispersal and biased movement upward along the resource gradient. In the absence of biased movement or advection, Hastings showed that the mutant can invade when rare if and only if it has smaller random dispersal rate than the resident. When there is a small amount of biased movement or advection, we show that there is a positive random dispersal rate that is both locally evolutionarily stable and convergent stable. Our analysis of the model suggests that a balanced combination of random and biased movement might be a better habitat selection strategy for populations.