Gilpin William, Feldman Marcus W
Department of Applied Physics, Stanford University, Stanford, California, United States of America.
Department of Biology, Stanford University, Stanford, California, United States of America.
PLoS Comput Biol. 2017 Jul 5;13(7):e1005644. doi: 10.1371/journal.pcbi.1005644. eCollection 2017 Jul.
In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.
在许多生态系统中，自然选择发生的速度足够快，能够影响种群动态，进而影响未来的选择。这表明将经典种群动态模型扩展以纳入此类生态进化过程的重要性。在此，我们描述了一个捕食者 - 猎物模型，其中猎物种群增长取决于依赖猎物密度的适应度景观。我们表明，即使在没有外部环境变化或噪声的情况下，这个两物种生态系统也能够呈现混沌状态，并且混沌动态的出现是适应度景观在稳定选择和干扰选择时期之间可逆交替的结果。我们将适应度函数与统计力学中的自由能进行类比，这使我们能够运用一阶相变的物理理论来理解混沌捕食者 - 猎物动态中快速循环的出现。我们使用定量技术来研究我们的模型与复杂生态系统观测研究的相关性，发现进化驱动的混沌动态在“混沌边缘”赋予群落稳定性，同时在干扰选择时期为物种形成创造了广泛的机会分布——这是实验研究中混沌生态进化动态的一个潜在可观测特征。
