Quantitative Approaches to Phylogenetics

Abstract

We review Hennigian, maximum likelihood, and different Bayesian approaches to quantitative phylogenetic analysis and discuss their strengths and weaknesses. We also discuss various protocols for assessing the relative robustness of one’s results. Hennigian approaches are justified by the Darwinian concepts of phylogenetic conservatism and the cohesion of homologies, embodied in Hennig’s Auxiliary Principle, and applied using outgroup comparisons. They use parsimony as an epistemological tool. Maximum likelihood and Bayesian likelihood approaches are based on an ontological use of parsimony, choosing the simplest model possible to explain the data. All methods identify the same core of unambiguous data in any given data set, producing highly similar results. Disagreements most often stem from insufficient numbers of unambiguous characters in one or more of the data types. Appeals to Popperian philosophy cannot justify any kind of phylogenetic analysis, because they argue from effect to cause rather than cause to effect. Nor can any approach be justified by statistical consistency, because all may be consistent or inconsistent depending on the data being analyzed. If analyses based on different types of data or using different methods of phylogeny reconstruction, or some combination of both, do not produce the same results, more data are needed.