论文标题
随机环境中的种群动态
Population dynamics in stochastic environments
论文作者
论文摘要
人群由整数个体组成,并受到随机速度可能有所不同的随机出生死亡过程。有用数量(例如最终固定的机会)满足适当的差异(主)方程,但是这些方程式的封闭式解决方案很少见。人群遗传学,生态学和进化等领域的分析见解几乎完全依赖于扩散近似(DA)的不受控制的应用,该扩散近似(DA)假设相关数量在整个整体集中的平稳性。在这里,我们将渐近匹配技术与一阶(控制因子)WKB方法相结合,以获得一种理论,其适用性范围更宽。这使我们能够从更一般的理论中重新逐步识别其局限性,并在失败时提出替代性分析解决方案和可扩展的数值技术。我们进行分析,以计算波动环境中的固定概率,突出了(平均)(平均)有害和有益的突变体侵袭与弱选择和强烈选择之间的复杂区别之间的差异。
Populations are made up of an integer number of individuals and are subject to stochastic birth-death processes whose rates may vary in time. Useful quantities, like the chance of ultimate fixation, satisfy an appropriate difference (master) equation, but closed-form solutions of these equations are rare. Analytical insights in fields like population genetics, ecology and evolution rely, almost exclusively, on an uncontrolled application of the diffusion approximation (DA) which assumes the smoothness of the relevant quantities over the set of integers. Here we combine asymptotic matching techniques with a first-order (controlling-factor) WKB method to obtain a theory whose range of applicability is much wider. This allows us to rederive DA from a more general theory, to identify its limitations, and to suggest alternative analytical solutions and scalable numerical techniques when it fails. We carry out our analysis for the calculation of the fixation probability in a fluctuating environment, highlighting the difference between (on average) deleterious and beneficial mutant invasion and the intricate distinction between weak and strong selection.