Müller J, Hense B A, Fuchs T M, Utz M, Pötzsche Ch
TU München, Centre for Math. Sciences, Boltzmannstr. 3, D-85747 Garching, Germany; Helmholtz Center Munich, Institut für Biomathematik und Biometrie, Helmholtz Zentrum München, Ingolstädter Landstr. 1, D-85764 Neuherberg, Germany.
J Theor Biol. 2013 Nov 7;336:144-57. doi: 10.1016/j.jtbi.2013.07.017. Epub 2013 Jul 27.
We investigate the evolution of bet-hedging in a population that experiences a stochastically switching environment by means of adaptive dynamics. The aim is to extend known results to the situation at hand, and to deepen the understanding of the range of validity of these results. We find three different types of evolutionarily stable strategies (ESSs) depending on the frequency at which the environment changes: for a rapid change, a monomorphic phenotype adapted to the mean environment; for an intermediate range, a bimorphic bet-hedging phenotype; for slowly changing environments, a monomorphic phenotype adapted to the current environment. While the last result is only obtained by means of heuristic arguments and simulations, the first two results are based on the analysis of Lyapunov exponents for stochastically switching systems.
我们通过适应性动力学研究了在经历随机切换环境的种群中避险策略的演变。目的是将已知结果扩展到手头的情况，并加深对这些结果有效性范围的理解。根据环境变化的频率，我们发现了三种不同类型的进化稳定策略（ESS）：对于快速变化，是一种适应平均环境的单态表型；对于中等范围，是一种双态避险表型；对于缓慢变化的环境，是一种适应当前环境的单态表型。虽然最后一个结果仅通过启发式论证和模拟获得，但前两个结果基于对随机切换系统李雅普诺夫指数的分析。
