Evolutionary trees and the fossil record: new approaches to phylogenetic paleobiology
A new special issue from the Journal of Paleontology, brings together a collection of 17 papers focused on different aspects of echinoderm paleobiology. Author David F. Wright discusses his article ‘Bayesian estimation of fossil phylogenies and the evolution of early to middle Paleozoic crinoids (Echinodermata)’.
Trees have long served as a metaphor for life and its diversity in the iconography of natural history. As models for the Tree of Life, evolutionary trees (called phylogenies) form the cornerstone of evolutionary biology. Why are some groups of organisms more diverse than others? Do certain traits evolve more frequently than others? What traits are associated with increased extinction risk? To address these questions, scientists must first have knowledge of genealogical relationships among species. As a paleontologist, I am broadly interested the development of new approaches to inferring phylogenies of fossil species and how we use them to answer questions about patterns of large-scale macroevolutionary change.
It is often stated that a great advantage of paleontology among the evolutionary sciences is its temporal dimension. In fact, it is for this reason that fossil data are routinely used for calibrating molecular phylogenies of living species to estimate divergence times among lineages. Thus, it is ironic that the use of temporal data for estimating fossil phylogenies has had a contentious history imbued with occasionally acrimonious debate. Key concerns involve the quality of the fossil record and the potential conflation of stratigraphy with homology in stratocladistic studies. As a result, temporal data has since played a reduced role in reconstructing relationships among fossil species.
However, macroevolutionary events are functions of time. The ability to estimate patterns of trait change, diversification, and phylogenetic relationships are not generally independent of one another. Moreover, incomplete and/or time-heterogeneous fossil sampling should be accounted for rather than ignored in paleontological research. To help overcome these issues, phylogenetic paleobiologists have increasingly been interested in statistical approaches to phylogenetics that attempt to more fully account for the idiosyncrasies of fossil data.
For example, I applied Bayesian “tip-dating” methods to estimate phylogenetic relationships among early to middle Paleozoic crinoids (Echinodermata) (Wright, 2017). Using a recently developed model called the fossilized birth-death process (FBD), this approach integrates fossil morphology with stratigraphic data to infer time-scaled phylogenetic trees while accounting for incomplete sampling and diversification dynamics. Because the implementation of the FBD process I used allows for fossils to be placed along branches of the tree, I was able to statistically evaluate pre-existing hypotheses of ancestor-descendant relationships—something previously difficult to test statistically in paleontological systematics. In addition, I tested alternative models of morphologic evolution and found evidence for substantial heterogeneity in evolutionary rate across lineages and among traits, providing phylogenetic context to earlier studies of morphological disparity. Finally, I was able to show that previous phylogenies for this group are statistically unlikely, highlighting the need for taxonomic revision.
In paleontology, paradigm shifts do not typically arise from new fossil discoveries; they emerge from new ways we study and think about fossils. One of the reasons I’m most excited about tip-dating is that it allows us to go beyond figuring out relationships to testing macroevolutionary patterns. As paleontologists, if we seriously consider the temporal dimension to be the strength of our evolutionary perspective, these new advancements allow us to more effectively practice what we preach.
Author David F. Wright is currently a Peter Buck Fellow in the Department of Paleobiology, National Museum of Natural History, Smithsonian Institution.
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