Population genetic analyses
We conducted hierarchical clustering analyses of SNPs for the 16 sampled
localities in the population genetic dataset using principal components
analysis (PCA) and the program Structure 2.3.4 (Pritchard et al.2000). Principal Component Analyses (PCAs) were conducted usingglPca in adegenet (Jombart 2008) implemented in R 3.6.1 (R Core
Team 2019), and plotted with ggplot2 (Wickham 2009). Structure was set
to use the admixture model and correlated allele frequencies and was run
with and without using sampling locations as a prior (locpriorvs. nolocprior ). We tested K = 1-20 with 20 independent
replicates per value of K . Each value of K ran for 400,000
MCMC reps with a burn-in period of 200,000 and we averaged runs using
CLUMPAK v1.1 (Kopelman et al. 2015). Following the
recommendations of Janes et al. (2017), we considered multiple
metrics when determining the optimal value of K , including
comparison to the PCA, LnPr(X |K ) (Pritchardet al. 2000), ΔK (Evanno et al. 2005), and the
statistics proposed by Puechmaille (2016). We calculated the latter with
StructureSelector (Li & Liu 2017) using a population map corresponding
to collection localities, and a threshold for cluster placement set to
0.5.
SNP pairwise FST was calculated in R using StAMPP
(Pembleton et al. 2013) with 1,000 bootstrap permutations and a
Benjamini-Hochberg p-value correction. Expected and observed
heterozygosity (He and Ho ,
respectively) were calculated in dartR (Gruber & Georges, 2019).
Isolation by distance (IBD) analysis using Euclidean distance and a
Mantel test with 10,000 permutations was conducted using the R packages
sna (Butts 2019), geosphere (Hijmans 2019), and adegenet (Jombart 2008).
Due to potentially different biological scenarios impacting the
correlation between genetic and geographic distance (e.g. a single
genetic cline versus two or more distinct clines, Meirmans 2012; Teskeet al. 2018; Maitra et al. 2019), the densities between
points were visualized with a kernel density estimation function using
the package MASS (Venables & Ripley 2002).
PopART (Leigh & Bryant 2015) was used to construct a minimum spanning
network of COI haplotypes.