Where do we look? With what tools? We build software, simulations, and theories, to understand where we can monitor environmental processes, with a specific focus on biodiversity and disease.

When species interact, do they evolve differently? When species evolve, do they keep the same interactions? We use data analysis and simulation to explore some of these questions at the scale of ecological networks.

Between local networks and metawebs, what is the spatial structure of biotic interactions? Do networks respond to environmental gradients? We are interested in the reconstruction, prediction, and analysis of ecological network data.

Are interactions predictible? Can we build better models? How do we effectively use machine learning for this task? A big part of our research activity is to develop and benchmark models to predict interactions between species.

Data on species interactions is scarce. But why? Is it scarce everywhere in the same way? What can we do about it? We work on these questions by documenting gaps in the data, and by providing tools to deal with our data more effectively.

There are many hosts, and many, many more viruses. This creates a lot of interesting research questions about the integration of data, the prediction of interactions from very sparse information, and the transformation of these predictions into action.

Making sense of ecological networks is a very complicated process. We build tools and measures to understand their structure, and develop theory to understand how this structure emerges.

Interactions vary over time and space. But how? How much? Which mechanisms are responsible? We work on quantifying and understanding the variation of ecological interactions, and its consequences for ecological networks in space.

No one is perfect. We have been known to engage in wanton acts of community ecology over the years. Please excuse this weakness, and remember, the eigenvalues can’t hurt you (they are imaginary).

What if equations smelled really bad? Microbial systems, in nature on in the lab, are a fantastic way to test some ecological and evolutionary hypotheses about metabolic ecology, co-evolution, and community interactions.

Why do we work the way we do? Can we change it? Can we care for our community more? Design things more collaboratively? Can we share more equitably? We have strong opinions about these things.

This is a list of projects that are not fully related to what the lab is doing, but that we worked on because they we thought they were really cool.

Group members are encouraged to cultivate their own collaborations. These are some outcomes of research projects done while in the group, but not directly related to our core activities.

A collection of book reviews, and open editorial decisions that Timothée wrote from PCI Ecology.