Revathi Venkateswaran, V. | bioRxiv Science

bioRxiv2020

Consequences of combining life-history traits with sex-specific differences

Males and females evolved distinct life-history strategies, reflected in diverse inter-linked life-history traits. The sex that allocates more resources towards offspring relies on an increased life span, and long life requires an efficient immune system. The other sex needs to attract mates and thus allocates its resources towards ornamentation, which may negatively correlate with investment into the immune defense. Such sex-specific resource allocation trade-offs are not always strictly female or male-specific but may depend on the overall resources allocated towards life-history traits. Informed by experimental data, we designed a theoretical framework that combines multiple life-history traits. We disentangled specific life-history strategies from particular sex, allowing us to include species with reversed sex-roles and male parental investment. We computed the lifetime reproductive success (combining fitness components from diverse sex-specific life-history traits) observing a strong bias in adult sex ratio depending on sex-specific resource allocation towards life-history traits. Overall, our work provides a generalized method to combine various life-history traits with sex-specific differences to calculate lifetime reproductive success. The results explain specific population-level empirical observations as a consequence of sexual dimorphism in life-history traits.

evolutionary biology↗

bioRxiv2018

Evolutionary dynamics of multiple games

Evolutionary game theory has been successful in describing phenomena from bacterial population dynamics to the evolution of social behavior. Interactions between individuals are usually captured by a single game. In reality, however, individuals take part in many interactions. Here, we include multiple games and analyze their individual and combined evolutionary dynamics. A typical assumption is that the evolutionary dynamics of individual behavior can be understood by constructing one big comprehensive interactions structure, a single big game. But if any one of the multiple games has more than two strategies, then the combined dynamics cannot be understood by looking only at individual games. Devising a method to study multiple games - where each game could have an arbitrary number of players and strategies - we provide a concise replicator equation, and analyze its resulting dynamics. Moreover, in the case of finite populations, we formulate and calculate a basic and useful property of stochasticity, fixation probability. Our results reveal that even when interactions become incredibly complex, their properties can be captured by relatively simple concepts of evolutionary game(s) theory.

evolutionary biology↗