Understanding and predicting the dynamics of ecological systems under environmental change

Our research program

In the face of larger and more frequent environmental variations, developing efficient and rigorous methodologies to understand and predict the dynamics of species (e.g., pathogens, viruses, plants, pollinators, mammals) in a given place (e.g., human host, natural habitat) across a period of time is of central importance for establishing successful strategies for sustaining ecosystem services that depend on biodiversity, such as: nutrient cycling, water purification, soil formation, CO2 sequestration, and human health.

Importantly, the main challenge that we need to overcome to address the problem above is ecological uncertainty. That is, uncertainty about the exact equations governing the dynamics of ecological systems, together with the high uncertainty regarding the initial conditions, parameter values, intrinsic randomness, and more importantly, how the changing environmental conditions will affect all of these dynamics.

To assess this uncertainty, we adopt a new approach we call structural ecology - a systematic and probabilistic approach rooted on the notion of structural stability to study ecological dynamics. Formally, a dynamical system is said to be structurally stable if the topology of the phase portrait is preserved under smooth changes of the vector field. Because is virtually impossible to know a priori all the changing biotic and biotic factors affecting the dynamics of biological populations, it is then necessary to quantify, from a probabilistic point of view (similar to quantum mechanics), the range of conditions compatible with their dynamics. In this line, the group develops novel parametric and nonparametric methods to estimate such probabilities and to be able to understand and predict the dynamics of ecological systems under environmental change.

Twitter: @MIT_ecology