Evolutionarily Stable Density-Dependent Dispersal

TL;DR

This study uses numerical simulations of a simple island model to investigate how dispersal strategies evolve under density dependence, revealing a unique stable dispersal pattern that increases with local density.

Contribution

It demonstrates that dispersal strategies can evolve freely without constraints, leading to a monotonic increase with density, and explores how system parameters influence this evolution.

Findings

Dispersal probability increases monotonically with density.

A unique stable dispersal schedule emerges over time.

Scaling laws relate dispersal strategies to system parameters.

Abstract

An ab-initio numerical study of the density-dependent, evolutionary stable dispersal strategy is presented. The simulations are based on a simple discretei generation island model with four processes: reproduction, dispersal, competition and local catastrophe. We do not impose any a priori constraints on the dispersal schedule, allowing the entire schedule to evolve. We find that the system converges at long times to a unique nontrivial dispersal schedule such that the dispersal probability is a monotonically increasing function of the density. We have explored the dependence of the selected dispersal strategy on the various system parameters: mean number of offspring, site carrying capacity, dispersal cost and system size. A few general scaling laws are seen to emerge from the data.