Our research focuses on the eco-evolutionary dynamics of large and complex ecological networks, with a central interest in understanding how species embedded in complex networks respond to environmental perturbation. Species embedded in such networks do not respond to environmental perturbation in isolation; their responses depend on who they interact with, how strongly they interact, and whether the traits underlying those interactions can dynamically change. We combine dynamical systems theory, quantitative and population genetics, and network ecology to study the dynamical evolution of mutualistic networks, trophic food webs, and other complex multispecies communities.
Another major theme of our work is to understand resilience, tipping points, and recovery in these ecological networks, and how evolutionary dynamics feedback to impact them. Ecological systems such as plant–pollinator networks, plant–herbivore networks, and food webs can exhibit multiple stable states and can undergo sudden transitions to undesirable states such as community collapses in response to perturbation. We study how network structure, species roles, genetic and/or phenotypic variation, and eco-evolutionary feedbacks influence the ability of ecological networks to resist perturbations, recover from collapse, or be restored through targeted interventions.
More broadly, we are interested in all things that revolve around eco-evo and evo-eco dynamics. A central question that motivates our work is why individuals vary so much within species, and what the causes and consequences of this variation are. We study how individual variation drives species interactions, community dynamics, evolvability, coexistence, and long-term evolutionary outcomes. We ask why some species and communities adapt more rapidly than others, how evolvability is shaped by and transmitted through ecological networks, and how factors such as individual variation, stage structure, epistasis, and genomic conflict etc., influence persistence, speciation, and extinction. Although much of our work is theoretical and computational, we aim to connect these models to empirical and field-studies in ecology and evolution.