Accelerating invasion rates result from the evolution of density-dependent dispersal.
Evolutionary processes play an important role in shaping the dynamics of range expansions, and selection on dispersal propensity has been demonstrated to accelerate rates of advance. Previous theory has considered only the evolution of unconditional dispersal rates, but dispersal is often more complex. For example, many species emigrate in response to crowding. Here, we use an individual-based model to investigate the evolution of density dependent dispersal into empty habitat, such as during an invasion. The landscape is represented as a lattice and dispersal between populations follows a stepping-stone pattern. Individuals carry three 'genes' that determine their dispersal strategy when experiencing different population densities. For a stationary range we obtain results consistent with previous theoretical studies: few individuals emigrate from patches that are below equilibrium density. However, during the range expansion of a previously stationary population, we observe evolution towards dispersal strategies where considerable emigration occurs well below equilibrium density. This is true even for moderate costs to dispersal, and always results in accelerating rates of range expansion. Importantly, the evolution we observe at an expanding front depends upon fitness integrated over several generations and cannot be predicted by a consideration of lifetime reproductive success alone. We argue that a better understanding of the role of density dependent dispersal, and its evolution, in driving population dynamics is required especially within the context of range expansions.
Travis
Justin M J
JM
Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK. justin.travis@abdn.ac.uk
Mustin
Karen
K
Benton
Tim G
TG
Dytham
Calvin
C
D025041:Animal Migration; D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D008954:Models, Biological; D011156:Population Density; D011157:Population Dynamics