Phylogenetic analysis

Phylogenetic analysis was performed using Bayesian inference (BI) and maximum likelihood analysis (ML). Two species (Vanellus vanellus GenBank no. KM577158 and Tringa glareolaKY128485) were used as outgroups. There were two datasets as follows: (1) concatenated nucleotide sequences of 13 protein-coding genes and 12S and 16S rRNA for nine species, and (2) 12S rRNA, COI, and Cyt b of 23 species (Table S1). To determine the optimal partitioning of the data, the best-fit partitioning scheme and the most appropriate nucleotide evolution model for each partition were implemented in PartitionFinder 2 using the greedy algorithm and Akaike information criterion (AICc) (Lanfear et al., 2017). The partitions and models are listed in Table S2. The BI method was performed using MrBayes 3.1.2 (Ronquist & Huelsenbeck, 2003). Two simultaneous runs (four Markov chains Monte Carlo chains) were conducted for 1.0 × 10⁶ generations with independent models, and every 1,000 generations were sampled. Stationarity was considered to have been reached when the average standard deviation of the split frequencies was below 0.01. The first 25% of the sampled trees and the estimated parameters were discarded as burn-in. The remaining trees were used to calculate the consensus tree and Bayesian posterior probabilities. ML analysis was performed using RAxML 8.1.17 (Stamatakis, 2014). Branch support was assessed using a rapid bootstrapping set to terminate automatically with 10 runs and 1,000 replications using the GTRGAMMA model.