Speaker
Description
Population structure can strongly affect evolutionary dynamics. A popular way to describe such structures are graphs. A quantity of great interest in the study of evolutionary graphs is the probability that a novel beneficial mutation spreads through the entire population. Here, we propose an alternative way to understand the forces driving fixation by viewing graphs as life cycles. Adapting methods from evolutionary demography, we quantify the invasion fitness and the effective population size for different graphs. Both invasion fitness and effective population size appear in an approximation of the fixation probability of an advantageous mutant. The method is very general and applies to weighted graphs with node dependent fitness. However, we focus on analytical results for undirected graphs with node independent fitness. The method also contributes to conceptually integrate evolutionary graph theory with theoretical genetics of structured populations.
