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The goal of the Structural Ecology Group is to understand and quantify the uncertainty (probability) associated with the persistence (or risk) of multispecies communities under changing environments. This uncertainty comes from two main sources: the unknown exact equations governing the dynamics of a population’s interactions with other populations and abiotic factors, and how and when environmental variations can change these dynamics. To assess this uncertainty, the Group adopts both a probabilistic and a systems approach rooted on the notion of structural stability. 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 the range of conditions compatible with their persistence. In this line, the group develops novel parametric and nonparametric methods to estimate such probabilities and to be able to understand and predict the behavior of entire ecological communities under environmental change.
The goal of the Structural Ecology Group is to understand and quantify the uncertainty (probability) associated with the persistence (or risk) of multispecies communities under changing environments. This uncertainty comes from two main sources: the unknown exact equations governing the dynamics of a population’s interactions with other populations and abiotic factors, and how and when environmental variations can change these dynamics. To assess this uncertainty, the Group adopts both a probabilistic and a systems approach rooted on the notion of structural stability. 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 the range of conditions compatible with their persistence. In this line, the group develops novel parametric and nonparametric methods to estimate such probabilities and to be able to understand and predict the behavior of entire ecological communities under environmental change.
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Proceedings of the National Academy of Sciences of the United States of Americano. 6 (2024): e2312521121-e2312521121
JOURNAL OF THE ROYAL SOCIETY INTERFACEno. 208 (2023): 20230349-20230349
THEORETICAL ECOLOGYno. 3 (2023): 225-238
Journal of theoretical biology (2023): 111674-111674
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