Spatial ecology of species interactions
Why is there variation in the way species interact over space or time? We analyse spatially and temporally replicated datasets of surveys of species interactions to measure the variation in the structure of ecological networks, and describe its dynamics.
Prediction of species interactions
Can we predict inter-specific interactions? We are interested in developing predictive models that would use different sources of information (functional traits, local abundances, previous knowledge, …) to predict the probability that two species will interact.
Data science for biodiversity research
We believe that open data are a treasure trove of knowledge that has not been entirely used yet, and require ecologists to get curious about tools and practices from the field of data science. We explore applications of machine learning and deep learning to biodiversity.
Ecology of viral pathogens
Can we use ecological information to make predictions about emerging viral pathogens? We apply biotic interaction inference techniques, network analysis, and secies distributions models, to provide mapping of the risk posed by various groups of pathogens.
Functional consequences of network structure
We are interested in turning the structure of networks into a predictive variable for community ecology; we are particularly interested in the role of trophic interactions in ecosystem functioning.
Data and software tools
Addressing new questions often requires to develop new tools. We develop statistical and mathematical approaches, implement them, and release them as free and open-source software to make analyses reproducible and reliable.