ALTERNATIVE PREDICTIONS FOR OPTIMAL DISPERSAL IN RESPONSE TO LOCAL CATASTROPHIC MORTALITY

What dispersal strategy should be employed by an organism in response to local catastrophic mortality? Here we contrast predictions from an analytical solution derived from an ESS model which optimizes competit ive ability (Comins et al., 1980) with those from a stochastic, branch ing process model (Karlson and Taylor, 1992) which maximizes survivors hip of a clonal lineage. The optimal dispersal fraction varies directl y with the probability of local extinction in the ESS model, yet varie s inversely with this probability over much of the parameter space in the latter model. In order to conform more closely with the assumption s of the ESS model, we have modified the branching process model to ha ve a random, Poisson-distributed number of offspring and compared the predictions of these models. Both models invoke dispersal as an escape from local extinction and predict mixed dispersal strategies over a w ide range of conditions. However, increasing local catastrophic mortal ity favors more dispersal in the ESS model, but it can be so severe in the branching process model that no dispersal strategy is adaptive. I n this model, the predicted optimal proportion of dispersed offspring is highest at low to intermediate levels of catastrophic mortality dep ending on the total number of offspring produced. We suggest that this observed discrepancy is sufficiently large to warrant empirical tests of these qualitatively different predictions. (C) 1995 Academic Press , Inc.