IDENTIFYING THE PHYLOGENETIC STRUCTURE UNDERLYING LARGE DATASETS OF QUANTITATIVE PHENOTYPIC TRAITS

Discovery of the patterns underlying the diversification of phenotypes across the tree of life has long been a fundamental aim of evolutionary biology. Early theoretical and empirical contributions in this area have been foundational to paleontology and comparative biology by generating a stronger understanding of the variability in pattern across lineages throughout time, and linking these insights with knowledge of evolutionary processes. However, these early examinations were often restricted to only a few measurements representing only one or a small number of anatomical regions. Nevertheless, recent advancements in the quantification of morphology and vigorous sampling efforts have yielded much larger datasets that suggest the potential to address comparative questions across broad swaths of the tree of life using all aspects of organismal phenotype. In this contribution, I introduce and describe a new method through which to interrogate large datasets of phenotypic traits to reveal the shared and divergent patterns across anatomical regions that have driven their disparification through time by identifying modules thatdisplay similar patterns in rate and disparity across phylogenetic trees. By identifying this structure, the approach identifies specific patterns in mosaic evolution that describe change in phenotypes throughout time. Using both simulated and empirical datasets, I demonstrate the capability of the approach in identifying mosaic evolution, and the potential for their accommodation to contribute to a more detailed view of the patterns that describe the diversity of phenotypic evolution in tempo and mode across lineages and throughout evolutionary time.