Variability in life-history switch points across and within populations explained by Adaptive Dynamics
Variability in life-history switch points across and within populations explained by Adaptive Dynamics
复制标题
DOI：
10.1098/rsif.2018.0371
复制
发表时间：
2018-11-01
影响因子：
3.9
通讯作者：
Hui, Cang
中科院分区：
文献类型：
--
作者：
Landi, Pietro;Vonesh, James R.;Hui, Cang
了解塑造生命史转换点（SP; e）时间的因素。G.孵化、变态和成熟）是进化生态学中的一个基本问题。以前的研究从适应度优化的角度研究这个问题，已经推进了我们对为什么生活史转变的时间可能因种群和环境而异的理解。然而，在自然界中，我们也经常观察到种群中个体之间的变异性。最优化理论，通常预测一个单一的最佳SP下的生理和环境的限制，为给定的环境，不能解释这种变化。在这里，我们重新审视一个单一的生活史SP之间的少年和成年阶段的自适应动力学（AD）的角度来看，明确考虑了人口动态和生活史策略的演变之间的反馈。AD模型，虽然结构简单，表现出不同的进化情景取决于人口和环境条件，包括损失的少年阶段，一个单一的最佳SP，替代最佳SP取决于初始表型，和同域共存的两个SP表型破坏性选择。这样的预测是一致的，与以前的优化方法在预测生活史SP的变异性跨环境和种群之间，此外，他们也解释了种群内的变异性同域破坏性选择。因此，我们的模型可以用作理解不同环境中生活史变异性的理论工具，特别是同一环境中物种内的生活史变异性。
Understanding the factors that shape the timing of life-history switch points (SPs; e. g. hatching, metamorphosis and maturation) is a fundamental question in evolutionary ecology. Previous studies examining this question from a fitness optimization perspective have advanced our understanding of why the timing of life-history transitions may vary across populations and environments. However, in nature we also often observe variability among individuals within populations. Optimization theory, which typically predicts a single optimal SP under physiological and environmental constraints for a given environment, cannot explain this variability. Here, we re-examine the evolution of a single life-history SP between juvenile and adult stages from an Adaptive Dynamics (AD) perspective, which explicitly considers the feedback between the dynamics of population and the evolution of life-history strategy. The AD model, although simple in structure, exhibits a diverse range of evolutionary scenarios depending upon demographic and environmental conditions, including the loss of the juvenile stage, a single optimal SP, alternative optimal SPs depending on the initial phenotype, and sympatric coexistence of two SP phenotypes under disruptive selection. Such predictions are consistent with previous optimization approaches in predicting life-history SP variability across environments and between populations, and in addition they also explain within-population variability by sympatric disruptive selection. Thus, our model can be used as a theoretical tool for understanding life-history variability across environments and, especially, within species in the same environment.