2.4.2 Bayes Factor species delimitation implemented in SNAPP
As an alternative to BPP+gdi , we used Bayes factor species delimitation (BFD*) analyses in SNAPP v.1.3 (Bryant et al. 2012). For the SNAPP analyses, 500 variable sites evenly distributed across the dataset were extracted using a custom script and uploaded to a SNAPP template in BEAUTi v.2.6.3 (Bouckaert et al., 2019). Alternative species models were subsequently assigned based on prior species delimitation inferences from ASAP, BPP, and well-supported clades inferred from in the ML analyses (see results) recovered within distinct ASAP partitions. Due to computational limitations in SNAPP, we divided the ML tree into three major clades, with each clade run as a separate analysis in BEAST v2.6.3 (see Dryad file S54).
Substitution rates were calculated directly in BEAUTi using the entire 500 SNP dataset. Coalescence rate was set at 10.0 and specified to sample. Priors for both lambda and theta were set using a gamma distribution. Lambda was set to have a distribution of G(2, 500). Theta was set to have a distribution of G(1, 250). The chain length was set to 1,000,000, sampling every 1,000 generations. We utilized the BFD* methods outlined by Leaché et al. (2014). Marginal likelihood values were obtained using a path-sampling analysis in BEAST with 48 steps, chain length of 1,000,000 generations and 10% burn-in. Resulting log files were analyzed in Tracer v.1.7.1 (Rambaut and Drummond, 2005) to assess ESS values and convergence of runs. Each model was run four times and the marginal likelihood value was averaged across each clade in order to further ensure convergence.