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Data from: The genetic architecture of fitness drives population viability during rapid environmental change

Citation

Kardos, Marty; Luikart, Gordon (2020), Data from: The genetic architecture of fitness drives population viability during rapid environmental change, Dryad, Dataset, https://doi.org/10.5061/dryad.8w9ghx3jm

Abstract

The rapid global loss of biodiversity calls for improved predictions of how populations will evolve and respond demographically to ongoing environmental change. The heritability (h2) of selected traits has long been known to affect evolutionary and demographic responses to environmental change. However, effects of the genetic architecture underlying the h2 of a selected trait on population responses to selection are less well understood. We use deterministic models and stochastic simulations to show that the genetic architecture underlying h2 can dramatically affect population viability during environmental change. Polygenic trait architectures (many loci, each with a small phenotypic effect) conferred higher population viability than genetic architectures with the same initial h2 and large-effect loci under a wide range of scenarios. Population viability also depended strongly on the initial frequency of large-effect beneficial alleles, with moderately low initial allele frequencies conferring higher viability than rare or already-frequent large-effect alleles. Greater population viability associated with polygenic architectures appears to be due to higher short term evolutionary potential compared to architectures with large-effect loci. These results suggest that integrating information on the trait genetic architecture into quantitiative genetic analysis will substantially improve our understanding and prediction of evolutionary and demographic responses to environmental change.