Model Misspecication and Probabilistic Tests of Topology: Evidence from Empirical Data Sets

Abstract.—Probabilistic tests of topology offer apowerfulmeansof evaluating competing phylogenetic hypotheses. The performance of the nonparametric Shimodaira–Hasegawa (SH) test, the parametric Swofford–Olsen–Waddell–Hillis (SOWH) test, and Bayesian posterior probabilities were explored for ve data sets for which all the phylogenetic relationships are known with a very high degree of cer-tainty. These results are consistent with previous simulation studies that have indicated a tendency for the SOWH test to be prone to generating Type 1 errors because of model misspecication coupled with branch length heterogeneity. These results also suggest that the SOWH test may accord overcon-dence in the true topology when the null hypothesis is in fact correct. In contrast, the SH test was observed to be muchmore conservative, even under high substitution rates and branch length hetero-geneity. For some of those data sets where the SOWH test proved misleading, the Bayesian posterior probabilities were also misleading. The results of all tests were strongly inuenced by the exact sub-stitution model assumptions. Simple models, especially those that assume rate homogeneity among sites, had a higher Type 1 error rate and were more likely to generate misleading posterior probabili-ties. For some of these data sets, the commonly used substitution models appear to be inadequate for estimating appropriate levels of uncertainty with the SOWH test and Bayesian methods. Reasons fo