Microsatellites
We measured population genetic structure by Analysis of Molecular Variance (AMOVA) (Excoffier, Smouse, & Quattro, 1992) and by pairwise Fst values between populations in Arlequin v3.5.2.2 (Excoffier & Lischer, 2010). Significance was tested using 1,000 permutations. We generated several subsets to examine signatures of population differentiation related to the varying ecologies and potential barriers to dispersal across our collection sites. Specifically, our subsets were: a) all regions; b) all regions with the island excluded; c) ANF panhandle regions only (i.e., ARD and WRD); d) peninsular regions only (i.e., North Central near Gainesville and Central near Orlando); and e) ANF regions as one collective region and peninsular regions as one collective region. For each subset, we adjusted the allowed missing data (from 0.15 to 0.5) in order to include all nine loci in all analyses.
To further assess population genetic structure, we used the Bayesian clustering algorithm implemented through STRUCTURE v2.3.4 (Pritchard, Stephens, & Donnelly, 2000), which uses allele frequency data to assign individuals into genetic clusters (K). These analyses were executed with no prior population information and under the admixture model with correlated allele frequencies. In order to determine K, we assessed K = 1 through K = 10 with default parameters. To explore each K value, we performed 10 replicates with a burnin value of 50,000 and 500,000 MCMC iterations. We determined the optimal K value by assessing the maximum likelihood values and ΔK (Evanno, Regnaut, & Goudet, 2005) implemented in Structure Harvester v0.6.94 (Earl & von Holdt, 2012). We then averaged the 10 STRUCTURE replicates for the optimal K through the CLUMPAK pipeline (Kopelman, Mayzel, Jakobsson, Rosenberg, & Mayrose, 2015) and visualized the results in DISTRUCT v1.1 (Rosenberg, 2004).
We performed Mantel tests to test whether genetic distances correlate with geographic distance (isolation by distance; IBD). We generated several subsets to test for IBD. Specifically, we considered the following: a) all sampling sites across all regions; b) all sampling sites excluding the island; c) all sampling sites within the ANF; and d) all sampling sites within the peninsula. For measures of genetic distances, we used pairwise Fst values obtained from Arlequin and linearized them as Fst/(1-Fst) (Rousset, 1997). Negative Fst values, if present, were set to zero. Otherwise, the absolute difference between values would be inflated, when in actuality they are effectively zero (i.e., no genetic differentiation). We used Geographic Distance Matrix Generator v1.2.3 (Ersts, 2013) to generate pairwise geographic distances (in km) from the GPS coordinates of the sampling sites. We implemented Mantel tests using the ade4 package (Dray & Dufour, 2007) in R (Team, 2018) with 9,999 permutations.