2.5.1 Population genomic structure
We used “poppr” v2.9.3 (Kamvar 2023) to produce a multidimensional scaling (MDS) plot of all individuals based on a matrix of Prevosti’s genetic distances. To focus in more detail on the King Island population, we then repeated the MDS analysis using only the 15 individuals sampled from King Island. We then created a pairwise Weir and Cockerham (1984) fixation index (FST) matrix in “StAMPP” v1.6.3 (Pembleton 2013) with 999 bootstraps to assess significance of the estimated differentiation between populations. To assess isolation by distance at the individual level, we fitted a linear model of all standardised pairwise FST values against the geographic distance between samples (Rousset, 1997).
We used the alternating projected least squares algorithm implemented in “tess3r” to assign individuals to ancestral population genomic clusters, investigate patterns of admixture between populations and assess hierarchical population structure. This method applies a model of genetic structure featuring a number of ancestral populations (k ), allowing assessment of values for k that have low cross-entropy metrics (Frichot et al., 2014; Frichot & François, 2015). It also incorporates the spatial location of sampling, to remove potential bias associated with isolation-by-distance. We calculated cross-entropy criteria for values of k between 1 and 15, and visualised a cross-entropy scree-plot to identify a plateau or substantial change in curvature in the plot. We then extracted the matrices of individual admixture coefficients for the most relevant values of k for inference and plotted these as stacked bar plots to visualize hierarchical population structure. We then interpolated several values of k (2–4) across the landscape within the range of the scrubtit, based on the geographical location of samples. We then repeated this analysis using only the King Island scrubtit data for values of k from 1 to 5.