Stochastic Evolutionary Demography under a Fluctuating Optimum Phenotype.

Stochastic Evolutionary Demography under a Fluctuating Optimum Phenotype.
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DOI:
10.1086/694121
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发表时间:
2017-12
期刊:
The American naturalist
影响因子:
--
通讯作者:
Ashander J
Ashander J
中科院分区:
其他
文献类型:
--
作者:
Chevin LM;Cotto O;Ashander J

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许多自然种群表现出丰度的时间波动,这与随机变化环境的外部强迫一致。由于适应性来自表型和环境之间的相互作用,这种人口波动可能包括波动的表型选择的实质性贡献。我们研究了随机种群动态的人口暴露于随机(加上可能的方向)的变化,在最佳表型的数量性状的演变,响应于这个移动的最佳。我们推导出简单的分析预测的分布对数人口的大小随时间的推移,瞬态和稳态下Gompertz密度调节。这些预测与基于人口和个人的模拟结果吻合得很好。对数种群大小近似为反伽马分布,负偏斜导致相对于高种群大小的低数量过多,从而相对于具有相同均值和方差的对称(例如正态)分布增加了灭绝风险。我们的分析揭示了对数种群规模的均值和方差如何随着平均表型偏离最优值的方差和自相关性而变化。我们将我们的研究结果在随机环境中的进化救援的分析,并表明,在最佳的随机波动可以大大增加灭绝的风险,既降低了预期的增长率,并增加了几个数量级的种群规模的方差。
Many natural populations exhibit temporal fluctuations in abundance that are consistent with external forcing by a randomly changing environment. As fitness emerges from an interaction between the phenotype and the environment, such demographic fluctuations probably include a substantial contribution from fluctuating phenotypic selection. We study the stochastic population dynamics of a population exposed to random (plus possibly directional) changes in the optimum phenotype for a quantitative trait that evolves in response to this moving optimum. We derive simple analytical predictions for the distribution of log-population size over time, both transiently and at stationarity under Gompertz density regulation. These predictions are well matched by population- and individual-based simulations. The log-population size is approximately reverse gamma distributed, with a negative skew causing an excess of low relative to high population sizes, thus increasing extinction risk relative to a symmetric (e.g. normal) distribution with the same mean and variance. Our analysis reveals how the mean and variance of log population size change with the variance and autocorrelation of deviations of the evolving mean phenotype from the optimum. We apply our results to the analysis of evolutionary rescue in a stochastic environment, and show that random fluctuations in the optimum can substantially increase extinction risk, by both reducing the expected growth rate and increasing the variance of population size by several orders of magnitude.
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