title: Mutation size optimizes speciation in an evolutionary model.
abstract: The role of mutation rate in optimizing key features of evolutionary dynamics has recently been investigated in various computational models. Here, we address the related question of how maximum mutation size affects the formation of species in a simple computational evolutionary model. We find that the number of species is maximized for intermediate values of a mutation size parameter mu; the result is observed for evolving organisms on a randomly changing landscape as well as in a version of the model where negative feedback exists between the local population size and the fitness provided by the landscape. The same result is observed for various distributions of mutation values within the limits set by mu. When organisms with various values of mu compete against each other, those with intermediate mu values are found to survive. The surviving values of mu from these competition simulations, however, do not necessarily coincide with the values that maximize the number of species. These results suggest that various complex factors are involved in determining optimal mutation parameters for any population, and may also suggest approaches for building a computational bridge between the (micro) dynamics of mutations at the level of individual organisms and (macro) evolutionary dynamics at the species level.
authors.affiliation: Department of Physics and Astronomy and Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri, United States of America.
authors.forename: Nathan D
authors.initials: ND
authors.lastname: Dees
authors.forename: Sonya
authors.initials: S
authors.lastname: Bahar
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019143:Evolution, Molecular; D025461:Feedback, Physiological; D049810:Genetic Speciation; D008957:Models, Genetic; D009154:Mutation; D013997:Time Factors