Unifying much of this work is the development of new computational approaches for genomic, phenotypic, and fossil evidence to understand emergence of phenotypic innovation.

Population processes underlying episodes of phenotypic innovation

Can patterns in phylogenomic discordance (disagreement among gene trees) provide insight into historical population processes, especially during epochs of major evolutionary innovation? The emergence of phenotypic innovations is often episodic, occurring non-randomly during temporally short bursts. These dramatic periods are also often accompanied by high gene tree discordance. We aim to extend this knowledge to better understand whether these corresponding patterns may be shaped by shared underlying population-level processes. We are also interested in exploring how population processes inferred under the coalescent interact with complex morphological patterns at both shallow and deep timescales. We are particularly interested in applying these questions to understand the population processes that gave rise to the extraordinariy diversity of angiosperms that emerged in the Cretaceous period as part of an NSF-funded collaborative group across North America.

Organismal integration, constraint, and innovation

How have shifting patterns in evolutionary covariation and constraint contributed to the diverse morphologies displayed across the tree of life? This work involves both empirical work using museum specimens and methodological work to develop methods that accommodate large and noisy morphological datasets. We are particularly interested in applying these questions to understand how shifts in integration have corresponded to ecological evolution and morphological innovation in floral evolution in plants and skeletal evolution in primates.

Theory of evolutionary inference

How much can our data tell us about the past processes that shaped empirical patterns in morphological and molecular evolution? A consistent theme across all projects involves mapping out the inferential boundaries of evolutionary models to understand our capabilities and limitations when attempting to link the population processes driving major episodes of phenotypic change. One necessity also involves developing new, scaleable computational methods that link molecular and phenotypic evolution using varied data types.