The O’Dwyer lab is focused on the question of how ecological mechanisms shift with spatial, temporal, and organizational scale. This question has led to applications in many areas of ecology, and we use and adapt whatever theoretical modeling tools we can get our hands on to answer it. We work with a broad range of ecological data, from tropical forests, to the human microbiome, to white-tailed deer.
Please see our publications page for specific projects, and a flavor of ongoing projects below.
Biodiversity in ecological communities is often described in terms of the phylogenetic tree characterizing the evolutionary relatedness of coexisting organisms—a kind of local version of the tree of life. We are drawing from methods of coarse-graining in theoretical physics to understand which ecological processes drive the structure in phylogenetic trees sampled from microbial communities across a variety of habitats. (O’Dwyer JP, Kembel SW, Sharpton TJ (2015),O’Dwyer JP, Kembel SW, Green JL (2012).)
Inference and Model Comparison in Ecology
Macroecology is the general term for aggregated, emergent patterns in ecology. With collaborators, the O’Dwyer lab explores the development of parsimonious, mechanistic models to predict these phenomena (O’Dwyer JP, Lake JK, Ostling A, Savage VM, Green JL (2009), Xiao X, O’Dwyer JP, White EP (2015),O’Dwyer JP, Rominger A, Xiao X (2017) ,D’Andrea R, O’Dwyer JP ).
Time series data
Phylogenetic diversity is a signature of ecological processes acting on potentially long timescales, deep into the tree of life. On timescales of tens to hundreds of generations, we are working with microbial time series data to understand what drives fluctuations of species abundances through time.
Complexity in Biological and Cultural Evolution
We are interested in quantitative comparisons of complexity and innovation across domains (O’Dwyer JP, Kandler A (2017)).
Behavior and Population Dynamics
How do individuals make decisions, and how the they balance prior experience with new information? We are interested in this question and how population-level variability in decision-making in predator-prey interactions upscales to affect population dynamics.