CAREER: Reducing barriers for comparative methods

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A major question in evolutionary biology is how and why species have changed over time. From observing species in the present, for example, we know that competition can drive species to become different. Rather than remaining two species with similar sizes, those competing species can change, with one becoming larger or smaller than the other. Similar processes of change likely occurred in the past. There are other questions about past processes: how did the extinction of non-avian dinosaurs affect mammal evolution, how have human diseases evolved as humans settled more in cities, and so forth. Evolutionary biologists address these questions by writing a model to describe the process and then estimating aspects of the model: how strongly do species repel each other, what was the rate increase in mammals, how has virulence changed through time. However, for many of these questions, developing the models has been intractable, leaving these questions largely unanswerable. This project will develop tools to make creating these models much easier. It does so by using computers to simulate evolution under a particular model and tries adjusting the model parameters to best predict observed data, an approach known as approximate Bayesian computation. This will be enhanced by hackathons, intense meetings where scientists and developers gather to create or extend software, and which also serve to increase the programming skills and tools of biologists. An additional outcome of this project is the creation of an open course to teach cutting edge methods for understanding the past using family trees of current and extinct species.This project combines new approaches for approximate Bayesian computation (ABC) for comparative methods as a way to implement new models with meetings to have new and experienced coders work together on projects (hackathons) as well as a new open phylogenetics course. The ABC approach will be written in R, given R's widespread usage in the comparative methods user community, and uses a discrete time model that allows biologists to code a model for movement in one generation and then uses this model on a phylogenetic tree. Prototype code is already available (package TreEvo) and will be developed under an open source model. Together, the research and teaching will speed up methods development, broaden the pool (in number and diversity) of people who can create new approaches to answer their questions, and strengthen phylogenetic training in general.