Parnassius smintheus SNP and associated weather and landscape variables

Weather is an important short-term, local driver of population size and dispersal, which in turn contribute to patterns of genetic diversity and differentiation within species. Climate change is leading to greater weather variability and more frequent extreme weather events. While the effects of long-term and broad-scale mean climate conditions on genetic variation are well studied, our understanding of the effects of weather variability and extreme conditions on genetic variation is less developed. We assessed the influence of temperature and snow depth on genetic diversity and differentiation of populations of the alpine butterfly, Parnassius smintheus. We examined the relationships between a suite of variables, including those representing extreme conditions, and population-level genetic diversity and differentiation across 1453 single nucleotide polymorphisms, using both linear and gravity models. We additionally examined effects of land cover variables known to influence dispersal ..., We sampled 431 Parnassius smintheus whole body vouchers from 21 meadows in Alberta, Canada. DNA was extracted and genotyped using double digest restriction site associated DNA sequencing (ddRADseq). Reads were aligned to the congener Parnassius apollo using Bowtie2. After subsequent filtering (including maximum missing data per SNP of 85%, maximum missing data per individual 50%, minor allele frequency of 0.02), we retained 1453 SNPs for analysis. Expected heterozygosity and chord distance were estimated in R using the package adegenet (Jombart, 2008). 
Temperature variables were obtained from from Natural Resources Canada’s interpolated spatial models (Hutchinson et al., 2009) and estimated over 1960-2014. Snow variables were obtained as 1 km gridded snow depth estimates from the National Operational Hydrologic Remote Sensing Center’s SNODAS model (National Operational Hydrologic Remote Sensing Center, 2004) for 2010-2018., , # Parnassius smintheus SNP and associated weather and landscape variables

[https://doi.org/10.5061/dryad.v6wwpzh4n](https://doi.org/10.5061/dryad.v6wwpzh4n)

## Description of the data and file structure

We sampled 431 *Parnassius smintheus* whole body vouchers from 21 meadows in Alberta, Canada. DNA was extracted and genotyped using double digest restriction site associated DNA sequencing (ddRADseq). Reads were aligned to the congener *Parnassius apollo* using Bowtie2. After subsequent filtering (including maximum missing data per SNP of 85%, maximum missing data per individual 50%, minor allele frequency of 0.02), we retained 1453 SNPs for analysis. Expected heterozygosity and chord distance were estimated in R using the package *adegenet* (Jombart, 2008). 

Temperature variables were obtained from from Natural Resources Canada’s interpolated spatial models (Hutchinson et al., 2009) and estimated over 1960-2014. Snow variables were obtained as 1 km gridded snow depth estimates from ...,