Van Cleve Jeremy, Akçay Erol
National Evolutionary Synthesis Center (NESCent), 2024 W. Main Street, Suite A200, Durham, North Carolina 27705.
Evolution. 2014 Aug;68(8):2245-58. doi: 10.1111/evo.12438. Epub 2014 Jun 3.
Many organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to nonadditive ecological and fitness effects. Social evolution theory has long recognized that all of these factors can lead to different selection pressures but has only recently attempted to synthesize how these factors interact. Using models for both discrete and continuous phenotypes, we show that analyzing these factors in a consistent framework reveals that they interact with one another in ways previously overlooked. Specifically, behavioral responses (reciprocity), genetic relatedness, and synergy interact in nontrivial ways that cannot be easily captured by simple summary indices of assortment. We demonstrate the importance of these interactions by showing how they have been neglected in previous synthetic models of social behavior both within and between species. These interactions also affect the level of behavioral responses that can evolve in the long run; proximate biological mechanisms are evolutionarily stable when they generate enough responsiveness relative to the level of responsiveness that exactly balances the ecological costs and benefits. Given the richness of social behavior across taxa, these interactions should be a boon for empirical research as they are likely crucial for describing the complex relationship linking ecology, demography, and social behavior.
许多生物生活在由空间和类别构成结构的种群中,对其社会伙伴表现出可塑性反应,并受到非加性生态和适合度效应的影响。社会进化理论早就认识到,所有这些因素都可能导致不同的选择压力,但直到最近才尝试综合这些因素是如何相互作用的。通过使用离散和连续表型的模型,我们表明,在一个一致的框架中分析这些因素揭示出它们以以前被忽视的方式相互作用。具体而言,行为反应(互惠)、遗传相关性和协同作用以复杂的方式相互作用,而这些方式不易被简单的分类汇总指标所捕捉。我们通过展示它们在以前物种内和物种间社会行为的综合模型中是如何被忽视的,来证明这些相互作用的重要性。这些相互作用还会影响从长远来看能够进化的行为反应水平;当近因生物学机制产生的反应性相对于恰好平衡生态成本和收益的反应性水平足够高时,它们在进化上是稳定的。鉴于跨分类群社会行为的丰富性,这些相互作用应该对实证研究大有裨益,因为它们可能对于描述连接生态、人口统计学和社会行为的复杂关系至关重要。