How and why does evolutionary history drive contemporary ecological dynamics? I approach this question both from a theoretical perspective, building and testing synthetic theories of biodiversity based on statistical mechanics, and from an empirical perspective, collecting new data about the evolution and ecology of arthropod groups, using it to test how their past rates of diversification drive their current distribution of diversity across geographic space.

Superstatistics of Phanerozoic biodiversity.  Modeling deep time evolution as a non-equilibrium statistical system.

Evolution and the Maximum Entropy Theory of Ecology. How does evolution drive communities away from statistical steady state? To answer this I explore macroecological patterns across the chronosequence of the Hawaiian Islands using the theoretical lens provided by the principle of maximum information entropy.

Scientific computing for macroecology. I build open source statistical software for macroecology.

The dream of the 90s: truly global analyses of biodiversity. Jim Brown imagined a science where we could study the entire populations of species across geographic space; I’m working on making that a reality using hierarchical modeling combined with digitized museum and citizen science biocollections data.

The dream of the 00s: massive genetic data for all. I’m again using hierarchical models to reconstruct abundance, body size and phylogenetic data from next generation sequencing of huge arthropod surveys.

Reconstructing evolutionary rates from molecular phylogenies. To understand how evolution shapes ecology we need better estimates of macroevolutionary rates; I’m designing new methods to estimate speciation, extinction and immigration from molecular phylogenies.