Data from: The genetics of adaptation to discrete heterogeneous environments: frequent mutation or large-effect alleles can allow range expansion
Gilbert, Kimberly J., University of British Columbia
Whitlock, Michael C., University of British Columbia
Published Dec 15, 2016 on Dryad.
Cite this dataset
Gilbert, Kimberly J.; Whitlock, Michael C. (2016). Data from: The genetics of adaptation to discrete heterogeneous environments: frequent mutation or large-effect alleles can allow range expansion [Dataset]. Dryad. https://doi.org/10.5061/dryad.k6636
Range expansions are complex evolutionary and ecological processes. From an evolutionary standpoint, a populations' adaptive capacity can determine the success or failure of expansion. Using individual-based simulations, we model range expansion over a two-dimensional, approximately continuous landscape. We investigate the ability of populations to adapt across patchy environmental gradients and examine how the effect sizes of mutations influence the ability to adapt to novel environments during range expansion. We find that genetic architecture and landscape patchiness both have the ability to change the outcome of adaptation and expansion over the landscape. Adaptation to new environments succeeds via many mutations of small effect or few of large effect, but not via the intermediate between these cases. Higher genetic variance contributes to increased ability to adapt, but an alternative route of successful adaptation can proceed from low genetic variance scenarios with alleles of sufficiently large effect. Steeper environmental gradients can prevent adaptation and range expansion on both linear and patchy landscapes. When the landscape is partitioned into local patches with sharp changes in phenotypic optimum, the local magnitude of change between subsequent patches in the environment determines the success of adaptation to new patches during expansion.
Zip folder of Nemo simulation inputs and output data.
This zip folder contains scripts for generating input files for the modified version of Nemo described in text and available on Github, and requires the aNEMOne R package also described in text and on Github. Output stats files from Nemo are also included which are summary statistics over the whole landscape through time for each simulation. These can be used to generate all of the expansion rate results. Files within the "ind_seln" folders contain output data on individual fitness values across the landscape at a given point in time. These can be used to generate all of the fitness results and spatial-specific information. Files within the "Quanti" folder contain output data on genotypes across all loci for every individual across the landscape at a given time point. These can be used to generate the values of effect size differences in the two-patch models. There is also a folder labeled "Compiled_SimulationResults" which contains the relevant calculations from all of the above described output file sets.