Measuring and interpreting sexual selection metrics: evaluation and guidelines. Issue 8 (20th December 2016)

• Record Type: Journal Article
• Authors: Anthes, Nils; Häderer, Ines K.; Michiels, Nico K.; Janicke, Tim
• Editors: Schielzeth, Holger
• Is Part Of: Methods in ecology and evolution. Volume 8:Issue 8(2017)
• Page Start: 918
• Page End: 931
• Publication Date: 2016-12-20
• Subjects: Bateman gradient -- causality -- selection gradient -- sex difference -- sexual selection; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12707
• Languages: English
• ISSNs: 2041-210X

Abstract

Summary: 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. 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. 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. We expect this meta‐analytical review to aid future studies in providing less biased and more informative estimates of sexual selection.