Data from: Measuring and interpreting sexual selection metrics - evaluation and guidelines

(1) Routine assessments of overall sexual selection, including comparisons of its direction and intensity between sexes or species, rely on summary metrics that capture the essence of sexual selection. Nearly all currently employed metrics require population-wide estimates of individual mating success and reproductive success. The resulting sexual selection metrics, however, can heavily and systematically vary with the chosen approaches in terms of sampling, measurement, and analysis.

(2) Our review illustrates this variation using the Bateman gradient, a particularly prominent sexual selection metric. It represents the selection gradient on mating success and – given the latter's pivotal role in defining sexual selection – reflects a trait-independent integrative proxy for the maximum strength of sexual selection. Drawing from a recent meta-analysis, we evaluate potential biases arising from study design, data collection, and parameter estimation, and provide suggestions to mitigate such biases in future studies.

(3) With respect to study design, we argue that currently almost inexistent manipulative studies must complement the dominating correlative studies to inform us about causality in sexual selection. With respect to data collection, we outline how different measures of mating and reproductive success affect the components of sexual (and natural) selection that are reflected in standard summary metrics. With respect to parameter estimation, we show the potential impact of decisions about data inclusion and the chosen quantitative approach on inferences of sexual selection and its sex difference.

(4) We expect this meta-analytical review to aid future studies in providing less biased and more informative estimates of sexual selection.

(1) 对整体性选择的常规评估，包括不同性别或物种间性选择方向与强度的比较，依赖于能够捕捉性选择本质的汇总指标。当前几乎所有常用的指标都需要基于种群层面的个体交配成功率与繁殖成功率估计值。然而，由此得到的性选择指标会因抽样、测量与分析所采用的方法不同，出现显著且系统性的差异。(2) 本综述以贝特曼梯度（Bateman gradient）——一种尤为关键的性选择指标——为例，阐明了这类差异。该指标代表了交配成功率上的选择梯度，且鉴于交配成功率在定义性选择中的核心作用，它可作为不依赖性状的整合性替代指标，用以衡量性选择的最大强度。我们依托一项近期的元分析（meta-analysis），评估了研究设计、数据收集与参数估计环节可能产生的偏倚，并为未来研究中如何规避这类偏倚提供了建议。(3) 就研究设计而言，我们提出当前几乎空白的操控性实验研究，应当补充占据主导地位的相关性研究，以阐明性选择中的因果关系。就数据收集而言，我们梳理了交配成功率与繁殖成功率的不同测量方式如何影响标准汇总指标所反映的性选择（以及自然选择）组分。就参数估计而言，我们展示了数据纳入标准与所选定量分析方法的决策，会如何影响性选择及其性别差异的推断结果。(4) 我们期望本元分析综述能够助力未来研究，得到偏差更低、信息量更丰富的性选择估计值。