Title: Effects of dispersal patterns on population dynamics and synchrony
Authors: Janica Ylikarjula
Systems Analysis Laboratory
Helsinki University of Technology
P.O. Box 1100, 02015 HUT, FINLAND

Susanna Alaja
Division of Population Biology
Department of Ecology and Systematics
University of Helsinki
P.O. Box 17, 00014 University of Helsinki, FINLAND

Jouni Laakso
Department of Biological and Environmental Science
University of Jyväskylä
P.O. Box 35, 40351 Jyväskylä, FINLAND

David Tesar
Division of Population Biology
Department of Ecology and Systematics
University of Helsinki
P.O. Box 17, 00014 University of Helsinki, FINLAND

Date: April 2000
Status: Systems Analysis Laboratory Research Reports E7 April 2000
Abstract: In this paper we examine the effects of different dispersal patterns on the dynamics of two and a larger number of coupled populations and on the level of synchrony in local population dynamics. In these systems local population renewal is governed by the Ricker model, which is characterized by a single parameter, the intrinsic rate of increase r. Dispersal is assumed to be global and dispersal rules explored here include a pattern where a constant fraction of every local population disperses in each generation. In addition, we study the effects of another density-independent and three density-dependent dispersal rules. We also consider asymmetrical dispersal and the presence of environmental heterogeneity. According to our results, the effects of density-independent and density-dependent dispersal rules do not show any consistent difference. However, we found that both population dynamics and the level of synchrony differ markedly between two and a larger number of local populations. For two patches different dispersal rules give very versatile results, whereas for a larger number of local populations the dispersal patterns produce qualitatively similar dynamics. For example, for the values of r yielding stable or periodic dynamics in a single population, the dynamics do not change when the patches are coupled with dispersal. In addition, for the values of parameter r producing chaotic dynamics in a single population, dispersal has a stabilizing effect on the dynamics. Increasing r may destabilize the dynamics, but increasing the asymmetry of dispersal or assuming environmental heterogeneity again stabilizes the dynamics. High intensity of dispersal does not guarantee synchrony in fluctuations of local populations. The level of synchrony depends also on dispersal rule, the number of local populations and intrinsic growth rate.
Keywords: theoretical biology, spatial models, bifurcation theory, density-independent and density-dependent dispersal, environmental heterogeneity