Van Cleve Jeremy
Department of Biology, University of Kentucky, Lexington, KY 40506, USA.
Theor Popul Biol. 2015 Aug;103:2-26. doi: 10.1016/j.tpb.2015.05.002. Epub 2015 May 21.
The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work.
即使经过了半个世纪的理论研究,社会性状的进化仍然是进化生物学中最引人入胜且争论激烈的话题之一。W.D. 汉密尔顿在1964年发表的论文为理解遗传相关性对社会行为进化的影响奠定了基础,在很大程度上塑造了该领域。早期的理论研究揭示了汉密尔顿法则在动力学模型中成立所需的两个关键假设:弱选择和加性遗传相互作用。然而,直到最近,群体遗传学和进化博弈论的分析方法才得到充分发展,使得能够在选择、突变和遗传漂变的共同作用下研究社会进化。我们回顾这些方法如何在弱突变情况下提出两个进化时间尺度:(i)一个短期时间尺度,进化发生在一组有限的等位基因之间;(ii)一个长期时间尺度,等位基因是连续的,群体从一个单态性状连续进化到另一个单态性状。我们展示了汉密尔顿法则如何在加性条件下从短期分析中得出,以及非加性遗传相互作用如何更一般地得到解释。这种短期方法重现、综合并推广了许多先前的结果,包括进化博弈论中的三分之一法则和经济博弈论中的风险占优。使用长期方法,我们说明了性状进化如何用扩散方程来描述,扩散方程是适应性动力学标准方程的随机类似物。扩散平稳分布中的峰值捕捉了进化博弈论中收敛稳定性的经典概念,并且通常取决于汉密尔顿法则中固有的加性遗传相互作用。令人惊讶的是,长期平稳分布的峰值可以预测简单类型非加性相互作用的影响。此外,这些峰值以一种短期方法难以复制的方式捕捉了社会收益的弱效应和强效应。总之,短期和长期方法的结果既表明了汉密尔顿的见解可能以意想不到的方式具有稳健性,也表明了当前的分析方法如何能够将我们对社会进化的理解扩展到远远超出汉密尔顿的原始工作。