Effects of spatial and temporal heterogeneity on the genetic diversity of the alpine butterfly Parnassius smintheus
Abstract
Genetic diversity represents a population’s evolutionary potential, as well as its demographic and evolutionary history. Advances in DNA sequencing have allowed the development of new and potentially powerful methods to quantify this diversity. However, when using these methods best practices for sampling populations and analyzing data are still being developed. Furthermore, while effects of the landscape on spatial patterns of genetic variation have received considerable attention, we have a poorer understanding of how genetic diversity changes as a result of temporal variation in environmental and demographic variables. Here, I take advantage of advances in DNA sequencing to investigate genetic diversity at single nucleotide polymorphisms (SNPs) across space and time in a model system of the butterfly, Parnassius smintheus.
I used double digest restriction site associated DNA sequencing to genotype SNPs in P. smintheus from populations in Alberta, Canada. To develop recommendations for analyzing data, I tested the effect of varying the maximum amount of missing data (and therefore the number of SNPs) on common population genetic analyses. Most analyses were robust to varying amounts of missing data, except for population assignment tests where larger datasets (with more missing data) revealed higher-resolution population structure. I also examined the effect of sample size on the same set of analyses, finding that some (e.g., estimation of genetic differentiation) required as few as five individuals per population, while others (e.g., population assignment) required at least 15.
I used the SNP dataset to investigate factors shaping patterns of genetic diversity at different spatial scales and across time. At a larger spatial scale but a single time point, both weather (snow depth and mean minimum temperatures) and land cover (the distance between meadow patches) predicted genetic diversity and differentiation. At a smaller spatial but longer temporal scale, I used a smaller SNP dataset to show that genetic diversity is lost over repeated demographic bottlenecks driven by winter weather, and subsequently recovered through gene flow. My work contributes to understanding how genetic diversity is shaped in natural populations, and points to the importance of both land cover and weather (and specifically, variability in weather) to this process.