Genetic diversity and population structure
The evaluation of linkage equilibrium and Hardy-Weinberg equilibrium of
loci was done using exact tests with the functions test_LD and
test_HW, respectively in the “genepop” package (v.1.1.7; Rousset,
2008). Descriptive summaries for each population across loci were
calculated using the divBasic function in the “diveRsity” package (v.
1.9.90; Keenan, McGinnity, Cross, Crozier, & Prodöhl, 2013).
Descriptive summaries for each locus across populations were calculated
using locus_table function in the “poppr” package (v. 2.8.6; Kamvar,
Brooks, & Grünwald, 2015; Kamvar, Tabima, & Grünwald, 2014).
Missing data were assessed using the info_table function in the
“poppr” package (v. 2.8.6; Kamvar et al., 2015; Kamvar et al., 2014)
and loci with more than 10% data missing and individuals with more than
20% data missing were removed. Descriptive summaries for populations
and loci were performed on the entire data set and again on the data set
after removing loci and individuals with unacceptable levels of missing
data. A population level phylogeny based on the neighbor-joining
clustering method using the Prevosti’s genetic distance model was
generated with bootstrapped support using 1000 replicates with the aboot
function in the “poppr” package (v. 2.8.6; Kamvar et al., 2015; Kamvar
et al., 2014) and plotted using the Interactive Tree of Life v4 (Letunic
& Bork, 2019).
Model-based putative population clustering was performed using STRUCTURE
v2.3.4 (Pritchard, Stephens, & Donnelly, 2000). The number of genetic
groups (K) present within the 509 individuals tested was determined
running a continuous series of K = 1-22. The program was run with a
burn-in of 30,000 and a run-length of 100,000 Markov Chain Monte Carlo
(MCMC) replications in 20 independent runs using the LOCPRIOR model
(sampling location information included) to account for weak structure
signals in the dataset. The most likely number of clusters was
determined using the Evanno method (Evanno, Regnaut, & Goudet, 2005) as
implemented in STRUCTURE HARVESTER v0.6.94 (Earl & vonHoldt, 2012). The
final analysis for K=3 was performed using a burn-in of 50,000 and
500,000 MCMC with 20 independent runs. Runs were summarized using CLUMPP
v.1.1.2b (Jakobsson & Rosenberg, 2007) utilizing the Greedy algorithm
and visualized with DISTRUCT v1.1 (Rosenberg, 2004).