Abstract
AbstractSexual selection plays a crucial role in modern evolutionary theory, offering valuable insight into evolutionary patterns and species diversity. Recently, a comprehensive definition of sexual selection has been proposed, defining a trait as subject to sexual selection when variations in that trait are nonrandomly associated with variations in access to gametes, a limiting resource. Previous research on discrete traits demonstrated that non-random mating can be effectively quantified using the Kullback-Leibler symmetrized (Jeffreys) divergence, capturing information acquired through mating influenced by mutual mating propensities instead of random occurrences. This novel theoretical framework allows for detecting and assessing the strength of sexual selection and assortative mating.In this study, we aim to achieve two primary objectives. Firstly, we demonstrate the seamless alignment of the previous theoretical development, rooted in information theory and mutual mating propensity, with the new sexual selection definition. Secondly, we extend the theory to encompass quantitative traits. Our findings reveal that sexual selection and assortative mating can be quantified effectively for quantitative traits by measuring the information gain concerning the random mating pattern.Specifically, the gain in information within the sexual selection pattern can be expressed as a function of the sexual selection intensity index and the ratio of variances. Additionally, the measure capturing the underlying information of assortative mating is a function of the square of the correlation coefficient, taking values within the non-negative real number set [0, +∞).It is worth noting that the same divergence measure captures information acquired through mating for both discrete and quantitative traits. This presents a remarkable innovation as it provides a common context and simplifies the study of the patterns of sexual selection.
Publisher
Cold Spring Harbor Laboratory
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