Visualizing Conflicting Evolutionary Hypotheses in Large Collections of Trees: Using Consensus Networks to Study the Origins of Placentals and Hexapods

Abstract. — Many phylogenetic methods produce large collections of trees as opposed to a single tree, which allows the explo-ration of support for various evolutionary hypotheses. However, to be useful, the information contained in large collections of trees should be summarized; frequently this is achieved by constructing a consensus tree. Consensus trees display only those signals that are present in a large proportion of the trees. However, by their very nature consensus trees require that any conflicts between the trees are necessarily disregarded. We present a method that extends the notion of consensus trees to allow the visualization of conflicting hypotheses in a consensus network. We demonstrate the utility of this method in highlighting differences amongst maximum likelihood bootstrap values and Bayesian posterior probabilities in the placental mammal phylogeny, and also in comparing the phylogenetic signal contained in amino acid versus nucleotide characters for hexapod monophyly. [Bayesian posterior probabilities; consensus trees; hexapods; median networks; nonparametric bootstrap; placental mammals; phylogenetic trees; quartet puzzling.] The estimation of phylogenetic trees remains a central task in evolutionary biology. Many methods have been developed for constructing trees (Swofford et al., 1996). However, a single point estimate of the optimal tree with no measure of reliability is not always useful (Penny an