Bayesian inference provides a powerful framework for integrating different sources of information (in particular, molecules and fossils) to derive estimates of species divergence times. Indeed, it is currently the only framework that can adequately account for uncertainties in fossil calibrations. We use 2 Bayesian Markov chain Monte Carlo programs, MULTIDIVTIME and MCMCTREE, to analyze 3 empirical datasets to estimate divergence times in amphibians, actinopterygians, and felids. We evaluate the impact of various factors, including the priors on rates and times, fossil calibrations, substitution model, the violation of the molecular clock and the rate-drift model, and the exact and approximate likelihood calculation. Assuming the molecular clock caused seriously biased time estimates when the clock is violated, but 2 different rate-drift models produced similar estimates. The prior on times, which incorporates fossil-calibration information, had the greatest impact on posterior time estimation. In particular, the strategies used by the 2 programs to incorporate minimum- and maximum-age bounds led to very different time priors and were responsible for large differences in posterior time estimates in a previous study. The results highlight the critical importance of fossil calibrations to molecular dating and the need for probabilistic modeling of fossil depositions, preservations, and sampling to provide statistical summaries of information in the fossil record concerning species divergence times.
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