Inference of demographic history
The software DIYABC v2.1.0 (Cornuet et al., 2014) was implemented to investigate demographic history based on Approximated Bayesian Computation (ABC) using nuclear SSR markers. The three previously defined geographic groups were employed in the DIYABC analysis. We simulated and tested five potential scenarios of demographic history among the three groups that could have generated the current genetic variation (Fig. 3): s1, southward migration; s2, northward migration; s3-4, central origin; and s5: hybridization origin. We adopted a generalized stepwise mutation (GSM) model for repeat number mutation, and single nucleotide indels (SNI) were allowed. One million simulations were performed for each scenario. The strength of support for our scenarios was evaluated by comparing posterior probabilities via logistic regression using the top 1% of the simulated datasets according to the similarity of summary statistics to the observed data (Table S1). The methods for performing DIYABC and model evaluation were described in detail in the SMM.
We used VarEff (Nikolic & Chevalet, 2014) to test for changes in effective population size over the past 500 years, encompassing the increase in anthropogenic activities in Taiwan (i.e., when a large number of Han Chinese immigrated to Taiwan). We set a generic mutation rate prior of 0.000048 and adopted a GSM model with p = 0.4, as estimated by DIYABC (see Results). Additional parameters for each population are provided in Table S2. After 10,000 burn-in iterations, we ran 10,000 steps with 100 steps per batch and 100 steps between sampled steps to avoid autocorrelation, and a total of 10,000,000 MCMC iterations were employed.