Issue |
Math. Model. Nat. Phenom.
Volume 11, Number 4, 2016
Ecology, Epidemiology and Evolution
|
|
---|---|---|
Page(s) | 154 - 166 | |
DOI | https://doi.org/10.1051/mmnp/201611411 | |
Published online | 19 July 2016 |
Rare Mutations Limit of a Steady State Dispersal Evolution Model
1
Sorbonne Universités, UPMC Univ Paris 06, CNRS, INRIA, UMR 7598 Laboratoire Jacques-Louis Lions Équipe MAMBA, 4, place Jussieu 75005, Paris, France
2
Department of Mathematics, University of Chicago, Chicago, IL 60637, USA
* Corresponding author. E-mail: benoit.perthame@upmc.fr, souganidis@math.uchicago.edu
The evolution of a dispersal trait is a classical question in evolutionary ecology, which has been widely studied with several mathematical models. The main question is to define the fittest dispersal rate for a population in a bounded domain, and, more recently, for traveling waves in the full space.
In the present study, we reformulate the problem in the context of adaptive evolution. We consider a population structured by space and a genetic trait acting directly on the dispersal (diffusion) rate under the effect of rare mutations on the genetic trait. We show that, as in simpler models, in the limit of vanishing mutations, the population concentrates on a single trait associated to the lowest dispersal rate. We also explain how to compute the evolution speed towards this evolutionary stable distribution.
The mathematical interest stems from the asymptotic analysis which requires a completely different treatment for each variable. For the space variable, the ellipticity leads to the use the maximum principle and Sobolev-type regularity results. For the trait variable, the concentration to a Dirac mass requires a different treatment. This is based on the WKB method and viscosity solutions leading to an effective Hamiltonian (effective fitness of the population) and a constrained Hamilton-Jacobi equation.
Mathematics Subject Classification: 35B25 / 35F21 / 92D15
Key words: dispersal evolution / nonlocal pde / constrained Hamilton-Jacobi equation / effective fitness
© EDP Sciences, 2016
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