Event

Cooperation between organisms is a major driving force of biological organization at all levels, from single cells to whole ecosystems. Understanding the evolutionary dynamics of cooperation and other social traits therefore is a central goal of evolutionary theory. I will talk about my recent work that aims to advance the frontiers of social evolution theory in two directions.

The first direction is integrating evolutionary dynamics of social behaviors with the dynamics of the proximate mechanisms producing the behaviors. I will present a general framework that brings together the evolutionary effects of behavioral dynamics with those of genetic relatedness. This model reveals that both behavioral flexibility and population structure have symmetric effects on evolutionary dynamics when acting separately. However, they interact synergistically when they both operate, which can support significantly higher levels of cooperation than the sum of each mechanism by itself. Our results also highlight the crucial role of proximate mechanisms in determining the location of evolutionary equilibria and whether populations will approach them.

The second research direction takes aim at one of the central tenets of evolutionary game theory, which regards the structure of a social interaction (e.g., a prisoner’s dilemma game) as given, and analyzes the evolution of behaviors in such fixed contexts. Instead, I ask when and how natural selection might modify the social interaction setup to promote cooperation, especially in contexts where only imperfect information is available to individuals. I use a mathematical formalism that is new to biology –called mechanism design– that allows obtaining results independent of game structures. I apply this methodology to the problem of reproductive skew in social breeders. This new approach can explain previously problematic patterns in the data and suggests new questions for empirical and theoretical research.