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移动最优模型中的表型滞后与种群灭绝:小跳跃极限的启示

Phenotypic lag and population extinction in the moving-optimum model: insights from a small-jumps limit.

作者信息

Kopp Michael, Nassar Elma, Pardoux Etienne

机构信息

Aix Marseille Université, CNRS, Centrale Marseille, I2M, 3 Place Victor Hugo, 13331, Marseille Cedex 3, France.

Lebanese American University, Beirut Campus, P.O. Box 13-5053, Chouran Beirut, 1102 2801, Lebanon.

出版信息

J Math Biol. 2018 Nov;77(5):1431-1458. doi: 10.1007/s00285-018-1258-2. Epub 2018 Jul 6.

DOI:10.1007/s00285-018-1258-2
PMID:29980824
Abstract

Continuous environmental change-such as slowly rising temperatures-may create permanent maladaptation of natural populations: Even if a population adapts evolutionarily, its mean phenotype will usually lag behind the phenotype favored in the current environment, and if the resulting phenotypic lag becomes too large, the population risks extinction. We analyze this scenario using a moving-optimum model, in which one or more quantitative traits are under stabilizing selection towards an optimal value that increases at a constant rate. We have recently shown that, in the limit of infinitely small mutations and high mutation rate, the evolution of the phenotypic lag converges to an Ornstein-Uhlenbeck process around a long-term equilibrium value. Both the mean and the variance of this equilibrium lag have simple analytical formulas. Here, we study the properties of this limit and compare it to simulations of an evolving population with finite mutational effects. We find that the "small-jumps limit" provides a reasonable approximation, provided the mean lag is so large that the optimum cannot be reached by a single mutation. This is the case for fast environmental change and/or weak selection. Our analysis also provides insights into population extinction: Even if the mean lag is small enough to allow a positive growth rate, stochastic fluctuations of the lag will eventually cause extinction. We show that the time until this event follows an exponential distribution, whose mean depends strongly on a composite parameter that relates the speed of environmental change to the adaptive potential of the population.

摘要

持续的环境变化——比如气温缓慢上升——可能会导致自然种群出现永久性的适应不良:即便一个种群在进化上发生了适应,其平均表型通常仍会滞后于当前环境中所青睐的表型,而且如果由此产生的表型滞后变得过大,该种群就面临灭绝风险。我们使用一个移动最优模型来分析这种情况,在该模型中,一个或多个数量性状受到稳定选择,朝着以恒定速率增加的最优值发展。我们最近表明,在无限小突变和高突变率的极限情况下,表型滞后的进化会收敛到围绕一个长期平衡值的奥恩斯坦 - 乌伦贝克过程。这个平衡滞后的均值和方差都有简单的解析公式。在此,我们研究这个极限的性质,并将其与具有有限突变效应的进化种群的模拟结果进行比较。我们发现,“小跳跃极限”提供了一个合理的近似,前提是平均滞后足够大,以至于单个突变无法达到最优值。在环境变化快和/或选择弱的情况下就是如此。我们的分析还为种群灭绝提供了见解:即便平均滞后小到足以允许正增长率,滞后的随机波动最终仍会导致灭绝。我们表明,直到该事件发生的时间服从指数分布,其均值强烈依赖于一个综合参数,该参数将环境变化速度与种群的适应潜力联系起来。

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