Skip to main content
Dryad logo

The code used to simulate range expansion in "The effect of the recombination rate between adaptive loci on the capacity of a population to expand its range"

Citation

Eriksson, Martin; Rafajlović, Marina (2021), The code used to simulate range expansion in "The effect of the recombination rate between adaptive loci on the capacity of a population to expand its range" , Dryad, Dataset, https://doi.org/10.5061/dryad.95x69p8h5

Abstract

Previous theoretical work on range expansions over heterogeneous environments showed that there is a critical environmental gradient where range expansion stops. For populations with freely recombining loci underlying the trait under selection (hereafter adaptive loci), the critical gradient in one-dimensional habitats depends on the fitness cost of dispersal, and the strength of selection relative to genetic drift. Here, we extend the previous work in two directions and ask: What is the role of the recombination rate between the adaptive loci during range expansions? And what effect does the ability of selfing as opposed to obligate outcrossing have on range expansions? To answer these questions, we use computer simulations. We demonstrate that, while reduced recombination rates between adaptive loci slow down range expansions due to poor purging of locally deleterious alleles at the expansion front, they may also allow a species to occupy a greater range. In addition, we find that the allowance of selfing may improve the ability of populations to expand their ranges. We conclude that during range expansions there is a trade-off between positive and negative effects of recombination within and between individuals.

Methods

This is a custom-made code, written in Matlab. 

Usage Notes

For the explanation of how to use the code, please see ReadMeFirst.txt.

Funding

Hasselblad Foundation Grant for Female Researchers, Award: 2019-2020

Svenska Forskningsrådet Formas, Award: 2019-00882

Göteborgs Universitet

Hasselblad Foundation Grant for Female Researchers, Award: 2019-2020