title: Demographic stochasticity and evolution of dispersion I. Spatially homogeneous environments.
abstract: The selection of dispersion is a classical problem in ecology and evolutionary biology. Deterministic dynamical models of two competing species differing only in their passive dispersal rates suggest that the lower mobility species has a competitive advantage in inhomogeneous environments, and that dispersion is a neutral characteristic in homogeneous environments. Here we consider models including local population fluctuations due to both individual movements and random birth and death events to investigate the effect of demographic stochasticity on the competition between species with different dispersal rates. In this paper, the first of two, we focus on homogeneous environments where deterministic models predict degenerate dynamics in the sense that there are many (marginally) stable equilibria with the species' coexistence ratio depending only on initial data. When demographic stochasticity is included the situation changes. A novel large carrying capacity ([Formula: see text]) asymptotic analysis, confirmed by direct numerical simulations, shows that a preference for faster dispersers emerges on a precisely defined [Formula: see text] time scale. We conclude that while there is no evolutionarily stable rate for competitors to choose in these models, the selection mechanism quantified here is the essential counterbalance in spatially inhomogeneous models including demographic fluctuations which do display an evolutionarily stable dispersal rate.
authors.affiliation: Department of Physics, University of Michigan, Ann Arbor, MI, 48109-1020, USA, yentingl@umich.edu.
authors.forename: Yen Ting
authors.initials: YT
authors.lastname: Lin
authors.forename: Hyejin
authors.initials: H
authors.lastname: Kim
authors.forename: Charles R
authors.initials: CR
authors.lastname: Doering
mesh_terms: D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D017753:Ecosystem; D053476:Extinction, Biological; D055641:Mathematical Concepts; D008954:Models, Biological; D009010:Monte Carlo Method; D011157:Population Dynamics; D011338:Probability Theory; D013269:Stochastic Processes; D049490:Systems Biology