Kinship dynamics and the evolution of mammalian reproductive strategies

Objective

The study of differences in behaviour and life-history between the sexes or across age classes is central in the biological and social sciences, but our understanding of the causes of these differences is limited. Why do social and reproductive individual traits -such as the propensity to compete or affiliate with groupmates and the reproductive pace or success- differ among individuals of different ages within the same sex? I hypothesize that kinship dynamics, the changes in local relatedness that occur in group living animals as a consequence of mating (in/out of the group) and sex-biased dispersal (male/female/both sex dispersal) patterns, constitute a major driver of these differences. Building on recent work which showed that kinship dynamics can drive the evolution of menopause, I will develop a theoretical model that simulates kinship dynamics and their influence on both male and female reproductive strategies. The outcome of my model will be testable predictions (i) on when relationships among groupmates shift from support to hostility due to changes in local relatedness (e.g., low relatedness, less support) and how does this impact reproductive success; (ii) on the potential for close kin to compensate for low affiliation rates with less related group member; and (iii) on when individuals should invest in female versus male offspring. Then, I will comparatively test the resulting predictions using long-term behavioural and demographic data from six gregarious mammals, including humans, which exhibit different sex-biased dispersal and mating patterns. The combination of modelling with empirical analyses on these complementary systems provide a unique framework to test the influence of kinship dynamics on reproductive traits. This project bridges kin and sexual selection to close a key gap in our understanding of reproductive behaviour and life-history, and may provide innovative insights for future research in evolutionary biology and the social sciences.