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The temporal distribution of directional gradients under selection for an optimum

机译:选择最优方向下方向梯度的时间分布

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Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population- and individual-based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection.
机译:表型选择中的时间变化通常归因于环境变化,该变化导致使性状与适应性相关的适应性表面运动,但是这种联系很少凭经验建立。可以通过方向选择梯度随时间的变化和自相关来测量波动的表型选择。然而,这些梯度的动力学不仅取决于改变健身表面的环境变化,而且还取决于表型分布的演变。因此,目前尚不清楚选择梯度的变化在多大程度上可以使我们了解其波动的潜在驱动因素。为了研究这个问题,我们推导了在一个恒定的表型常数或以各种方式随机波动的表型最优选择下方向梯度的时间分布。我们的分析结果与基于人口和基于个体的模拟相结合,表明尽管可以区分某些特征模式,但最优值(包括恒定最优值)的非常不同的变化类型可以生成相似的选择梯度时间分布,因此很难推断潜在的波动选择过程。分析表型分布的变化以及选择梯度的变化应被证明对推断估计的波动选择的潜在机制更为有用。

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