Projects

PEG2 (2023-2026) - Predictive ecological eenomics - Funded by ANR (France)

Project leader: O François

Scientists involved from our team : Y Vigouroux, P Cubry, N Scarcelli, A Barnaud

The objective of this research project is to develop a set of statistical methods for predictive ecological genomics (PEG), leveraging the power of genomic and environmental DNA to predict biodiversity responses to climate change. The project will estimate the sensitivity of a particular population, species, or assemblage of species to projected environmental changes. The proposed methods are based on modern statistical approaches, including deep latent variable models and approximate Bayesian inference. Taking advantage of a close collaboration between mathematicians, computer scientists, population geneticists and ecologists, the PEG2 project will establish predictions for African crops and for Alpine biotopes threatened by climate change. The PEG2 project will provide a better understanding of population and ecological community responses to climate change, identify plant cultivars adapted to drought and warmer climates, and inform conservation of key or endangered group of species.