Species Delimitation Using Bayes Factors: Simulations and Application to the Sceloporus scalaris Species Group (Squamata: Phrynosomatidae)

摘要: Current molecular methods of species delimitation are limited by the types models and scenarios that can be tested. Bayes factors allow for more flexibility in testing non-nested hypotheses individual assignment to alternative lineages. Here, we examined efficacy delimiting through simulations empirical data from Sceloporus scalaris group. Marginal-likelihood scores competing models, which factor values were compared, estimated with four different methods: harmonic mean estimation (HME), smoothed (sHME), path-sampling/thermodynamic integration (PS), stepping-stone (SS) analysis. We also performed model selection using a posterior simulation-based analog Akaike information criterion Markov chain Monte Carlo analysis (AICM). results then compared reversible-jump MCMC (rjMCMC) coalescent-based method Bayesian Phylogenetics Phylogeography (BPP *BEAST; BPP incomplete lineage sorting; marginal-likelihood estimation; Mexico; choice.)