Edward Grey Institute, Department of Zoology, University of Oxford, Oxford, UK.
Philos Trans R Soc Lond B Biol Sci. 2013 Jan 21;368(1613):20120356. doi: 10.1098/rstb.2012.0356. Print 2013 Mar 5.
Sexual selection is traditionally measured at the population level, assuming that populations lack structure. However, increasing evidence undermines this approach, indicating that intrasexual competition in natural populations often displays complex patterns of spatial and temporal structure. This complexity is due in part to the degree and mechanisms of polyandry within a population, which can influence the intensity and scale of both pre- and post-copulatory sexual competition. Attempts to measure selection at the local and global scale have been made through multi-level selection approaches. However, definitions of local scale are often based on physical proximity, providing a rather coarse measure of local competition, particularly in polyandrous populations where the local scale of pre- and post-copulatory competition may differ drastically from each other. These limitations can be solved by social network analysis, which allows us to define a unique sexual environment for each member of a population: 'local scale' competition, therefore, becomes an emergent property of a sexual network. Here, we first propose a novel quantitative approach to measure pre- and post-copulatory sexual selection, which integrates multi-level selection with information on local scale competition derived as an emergent property of networks of sexual interactions. We then use simple simulations to illustrate the ways in which polyandry can impact estimates of sexual selection. We show that for intermediate levels of polyandry, the proposed network-based approach provides substantially more accurate measures of sexual selection than the more traditional population-level approach. We argue that the increasing availability of fine-grained behavioural datasets provides exciting new opportunities to develop network approaches to study sexual selection in complex societies.
性选择传统上是在群体水平上进行测量的，假设群体缺乏结构。然而，越来越多的证据颠覆了这一观点，表明自然种群中的种内竞争常常表现出复杂的时空结构模式。这种复杂性部分归因于群体内多配偶制的程度和机制，这会影响到雌雄间竞争的强度和范围。通过多层次选择方法已经尝试在局部和全局范围内进行选择的测量。然而，局部尺度的定义通常基于物理接近度，这提供了对局部竞争的相当粗略的度量，特别是在多配偶制种群中，种内和种间竞争的局部尺度可能有很大的不同。这些局限性可以通过社会网络分析来解决，该方法允许我们为种群的每个成员定义一个独特的性环境：因此，“局部尺度”竞争成为性网络的一个突现属性。在这里，我们首先提出了一种新的定量方法来测量种内和种间的性选择，该方法将多层次选择与从性相互作用网络的突现属性中得出的局部尺度竞争信息相结合。然后，我们使用简单的模拟来阐明多配偶制对性选择估计的影响方式。我们表明，对于中等程度的多配偶制，所提出的基于网络的方法提供了比传统的基于群体水平的方法更准确的性选择测量方法。我们认为，细粒度行为数据集的日益普及为通过网络方法来研究复杂社会中的性选择提供了令人兴奋的新机会。
