@ARTICLE{TreeBASE2Ref18658, author = {Seraina Klopfstein and Christian Kropf and Donald L. J. Quicke}, title = {An Evaluation of Phylogenetic Informativeness Profiles and the Molecular Phylogeny of Diplazontinae (Hymenoptera, Ichneumonidae)}, year = {2010}, keywords = {}, doi = {10.1093/sysbio/syp105}, url = {}, pmid = {}, journal = {Systematic Biology}, volume = {59}, number = {2}, pages = {226--241}, abstract = {How to quantify the phylogenetic information content of a dataset is a longstanding question in phylogenetics, influencing both the assessment of data quality in completed studies and the planning of future phylogenetic projects. Recently, Townsend (2007, Profiling Phylogenetic Informativeness. Syst.Biol. 56, pp. 222-231) developed a method to profile the phylogenetic informativeness of a dataset through time by linking its site-specific rates of change to its power to resolve relationships at different time scales. Here, we evaluate the performance of Townsend s method in the case of two standard genetic markers for phylogenetic reconstruction, 28S rDNA and CO1 mtDNA, with maximum-parsimony, maximum-likelihood and Bayesian analyses of relationships within a group of parasitoid wasps (Hym.: Ichneumonidae, Diplazontinae). Retrieving phylogenetic informativeness profiles of the two genes from our own and from three additional datasets, we find that the method repeatedly overestimates the performance of the more quickly evolving CO1 compared to 28S. We explore possible reasons for this bias, including phylogenetic uncertainty, violation of the molecular clock assumption, model misspecification and nonstationary nucleotide composition. As none of these provides a sufficient explanation of the observed discrepancy, we use simulated datasets, based on an idealized setting, to show that the optimum evolutionary rate decreases with increasing number of taxa. We suggest that this relationship could explain why the formula derived by Townsend from the four-taxon case overrates the performance of higher versus lower rates of evolution in our case, and that caution should be taken when the method is applied to datasets including more than four taxa.} }

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