Speaker
Description
Evolutionary graph theory has shown that population structure can strongly impact evolution, in particular by affecting the fixation probability of mutants. Natural microbial populations often have complex spatial structures, where these effects can be crucial. However, making the link with update rules is not always easy. We proposed a model for describing deme-structured populations on graphs, with a well-mixed deme on each node of the graph. By tuning migration asymmetry in the rare migration regime, the star graph transitions from amplifying to suppressing natural selection, and the predictions of evolutionary graph theory are recovered for specific migration asymmetries. When increasing the frequency of migrations, suppression of selection becomes pervasive. Our model also provides an advance toward connecting theoretical predictions to recent experiments considering spatially structured populations.
