2.4 | Population structure, mismatch distribution analysis, and neutrality detection
The population structure of nrDNA and cpDNA sequences was inferred using the Bayesian clustering procedure implemented in STRUCTURE v.2.3.4 (Evanno et al., 2005) without prior structure information; this software identifies the most probable number (K ) of genetic clusters of origin of the sampled individuals and assigns individuals to clusters. We used MCMC iterations as implemented in STRUCTURE to explore the parameter space considering individual memberships to K clusters, ranging from K = 1 (null hypothesis of panmixia) to K = 8 (the total number of populations sampled). Three independent runs were performed with an admixture model at 105 MCMC iterations and a 105 burn-in period. The most likely number of population groups (K , indicating the number of true clusters in the data) and the model values (ΔK , according to the second-order rate of change of cluster K that best fits the data) were calculated in STRUCTURE HARVESTER (Earl & vonHoldt, 2012). The graphical representation of results was performed in the CLUMPAK server (http://clumpak.tau.ac.il/index.html).
An analysis of molecular variance (AMOVA) was conducted on nrDNA and cpDNA sequences separately to test genetic differentiation within populations, among groups, and populations within groups using GenAlEx v.6.503 (Peakall & Smouse, 2012). Population pairwiseF ST was measured using DNASP v.6.12.01, and population pairwise geographic distances were calculated by GenAlEx. To test whether there was local genetic variation attributable to isolation-by-distance among populations, the estimates ofF ST/(1-F ST) and the corresponding natural logarithm of geographic distances (in km) between all pairwise combinations of the eight populations were regressed and subjected to a Mantel test (Mantel, 1967) with 999 random permutations in GenAlEx.
The genealogical relationships between ribotypes/chlorotypes based on the Medium-Joining model were inferred using NETWORK v.4.6.1.0 (http://www.fluxus-Engineering.com/). To identify and quantify potential genetic discontinuities and biogeographic boundaries acting as major genetic barriers among P. heterotricha populations from both nrITS and cpDNA datasets, we calculated the Monmonierʼs maximum-difference algorithm in Barrier v.2.2 (Manni et al., 2004). The robustness of these barriers was assessed by bootstrapping genetic distances.
In order to detect possible recent range expansions, Tajimaʼs D (Tajima, 1989) and FuʼsF s (Fu, 1997) were calculated to test the deviations from the null hypothesis of constant population size and neutral evolution for each DNA fragment. Pairwise mismatch distribution and neutrality tests for all populations were conducted in DNASP using the nrITS and cpDNA datasets separately.