Research Interests

Forecasting the soil microbiome

Despite the importance of soil biodiversity for the future of human systems, we have very few tools for predicting changes in the soil microbiome across space and time. To fill this gap, we developed Bayesian predictive models of soil fungal and bacterial abundances, which also help us disentangle the complex ecological forces shaping soil microbial communities. The first paper on this project was published here, with a corresponding BU article here. More info on ecological forecasting: Ecological Forecasting Initiative

Microbial networks

Microbes interact closely with their environments and other microbes. This can take the form of fierce competition for nutrients, cooperation to carry out biogeochemical transformations, predation, and more. These interactions can be represented (visually or mathematically) by networks. However, identifying interactions in a complex microbial community is difficult. I develop methods for combining experimental and field data to better understand microbial interactions. In collaboration with the Segre Lab.

Mass extinction dynamics

How do current extinctions compare to the mass extinctions throughout the entire history of life? As an undergraduate at Swarthmore College, I addressed this question with Professor Steve Wang in the Department of Mathematics and Statistics. We combined fossil data with modern extinction risks to explore how extinctions affect older or newer lineages. We concluded that age selectivity could be used to distinguish mass extinctions from background extinctions, and our current trajectory is within the “mass extinction” category. Read more about this project here.