Speaker: Sonya Bahar (University of Missouri at St. Louis)
The role of mutation rate in optimizing various features of evolutionary dynamics has recently been investigated in various computational models. Here, Professor Bahar's team addresses the question of how mutation rate can affect the formation of species in a simple computational evolutionary model. They find that the number of species is maximized for intermediate values of a mutation rate parameter; the result is observed in both cases where the evolving organisms exist on a randomly changing landscape as well as in a version of the model where negative feedback exists between the population of the organisms and the “health” of the landscape. The result is also observed for various implementations of the mutation rate dynamics. Allowing organisms with various mutation rates to “compete” against each other leads to the survival of organisms with a single mutation rate of an intermediate value, although this value does not necessarily correspond to the value giving the maximum number of species. These results provide a computational bridge between the dynamics of mutation rates on the level of individual organisms (micro) and “higher level” (macro) evolutionary dynamics at the species level.