Variation in lineage richness among clades, regions, and time periods ultimately reflects variation in the rates of speciation (in the case of macroevolution, and transmission in the case of viral evolution) and extinction. The branching pattern of phylogenetic trees is often the best source of evidence we have about these rates; over the last 30 years, countless studies have estimated lineage diversification rates using increasingly sophisticated approaches and correlated them with all sorts of biological variables. In this talk, I will address an emerging and fundamental challenge to this entire enterprise. First, I will discuss a previously hidden identifiability problem, which I will argue has been misleading inferences for decades -- and which is likely responsible for the suspiciously low estimates of extinction rates that are often reported in empirical macroevolutionary studies. I will then discuss how these results from macroevolution apply to epidemiological inferences made from viral phylogenies; I will argue that many conclusions from the emerging field of ‘phylodynamics’ may not be as robust as they appear. I will conclude by discussing some solutions to these methodological challenges that my group is currently working on.
Matt Pennell is an Associate Professor of Quantitative and Computational Biology at the University of Southern California. He earned his Ph.D. in Bioinformatics and Computational Biology from the University of Idaho and then moved to the University of British Columbia to be a Killam/NSERC Postdoctoral Fellow and subsequently, a faculty member in the Department of Zoology. In his research, he uses phylogenetic trees, graphical depictions of historical relationships, to study evolution at multiple scales—from the grandest (e.g., the origin of major groups of organisms) to the smallest (e.g., the transmission of viruses and the development of the adaptive immune system within an individual) of scales. While superficially disparate, these projects all revolve around a few common themes: he aims to define the outer boundaries of our knowledge and understand what we can and cannot learn about evolution from different types of data. In recognition of his contributions, he was awarded the Theodosius Dobzhansky Prize from the Society for the Study of Evolution, the Jasper Loftus-Hills Young Investigator Prize from the American Society of Naturalists, and a Canada Research Chair from the Government of Canada.