Bayesian and likelihood placement of fossils on phylogenies from quantitative morphometries

Abstract

AbstractJointly developing a comprehensive tree of life from living and fossil taxa has long been a fundamental goal in evolutionary biology. One major challenge has stemmed from difficulties in merging evidence from extant and extinct organisms. While these efforts have resulted in varying stages of synthesis, they have been hindered by their dependence on qualitative descriptions of morphology. Though rarely applied to phylogenetic inference, traditional and geometric morphometric data can improve these issues by generating more rigorous ways to quantify variation in morphological structures. They may also facilitate the rapid and objective aggregation of large morphological datasets. I describe a new Bayesian method that leverages quantitative trait data to reconstruct the positions of fossil taxa on fixed reference trees composed of extant taxa. Unlike most formulations of phylogenetic Brownian motion models, this method expresses branch lengths in units of morphological disparity, suggesting a new framework through which to construct Bayesian node calibration priors for molecular dating and explore comparative patterns in morphological disparity. I am hopeful that the approach described here will help to facilitate a deeper integration of neo- and paleontological data to move morphological phylogenetics further into the genomic era.