Morphological Phylogenetics Evaluated Using Novel Evolutionary Simulations.

ABSTRACT: Evolutionary inferences require reliable phylogenies. Morphological data have traditionally been analyzed using maximum parsimony, but recent simulation studies have suggested that Bayesian analyses yield more accurate trees. This debate is ongoing, in part, because of ambiguity over modes of morphological evolution and a lack of appropriate models. Here, we investigate phylogenetic methods using two novel simulation models-one in which morphological characters evolve stochastically along lineages and another in which individuals undergo selection. Both models generate character data and lineage splitting simultaneously: the resulting trees are an emergent property, rather than a fixed parameter. Standard consensus methods for Bayesian searches (Mki) yield fewer incorrect nodes and quartet

SUBMITTER: Keating JN 

PROVIDER: S-EPMC7440746 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature