I am a Quantitative Ecologist and Presidential Postdoctoral Fellow in Ecology, Evolution, and Behavior at Michigan State University. My research, broadly speaking, seeks to understand population- and community-level ecological processes across environmental gradients. I am interested in the role that cross-scale interactions between biotic and abiotic factors play in shaping these dynamics and how these contribute to observed patterns of biodiversity. I approach much this work through the lens of global change and ultimately aim to undertand and predict which species might be most sensitive to the impacts of these changes. I use a variety of animal species — primarily birds — to explore these questions across space, time, and levels of biological organization.
Methodologically, my research takes a cross-disciplinary approach, applying statistical and computational tools to integrate large-scale data streams from a variety of sources, including citizen science projects, satellite-based sensors, remote camera networks, and field-based efforts. I use a range of flexible quantitative methods in this work, including hierarchical Bayesian models and machine learning, to address both basic and applied questions in ecology.