Projects

2022–2026

HorizonEurope — NaturaConnect

Designing a resilient and coherent Trans-European Network for Nature and People (read more)

NaturaConnect is funded by the European Commission as a 4-years project from 2022-2026. It is coordinated by P. Visconti (IIASA, Vienna) and involves 14 other academic and NGO partners.

In NaturaConnect, our team leads WP3 on biodiversity modelling and scenarios where we will predict the overall biodiversity in Europe (plants, insects, soil biodiversity, vertebrates) under current and future conditions. We develop several novel species distribution models that incorporate trophic information, links between plants and insects, etc... We are also involved in WP4 on modelling ecosystem services (based on species providers), WP5 scenario building, and WP8 where we lead the French case study in collaboration with the OFB & PatriNat).

People involved in the group are: A. Thomas, G. Deschamp, M. Tzivanopoulou, M. Guéguen, L. O'Connor, P. Gaüzere, A. Thomas, S. Si Moussi, J. Renaud, Y. Hu.

2024–2027

HorizonEurope — Obsgession

Observation of Ecosystem Changes for Action (read more)

Obsgession is funded by the European Commission as a 4-years project from 2024-2027. It is coordinated by Prof. Petteri Vihervaara (Finnish Environment Institute (SYKE)) and involves 11 other academic and SME partners.

In Obsgession, our team leads WP3 on Detection, attribution, and modelling biodiversity and ecosystem changes. We are developping tools and workflow to detect and attribute biodiversity changes and apply them to sets of spatial and temporal datasets. We are co-leading together with Univ. Zurich, Task 5.1 on investigating and predicting biodiversity change in the European Alps by multi-scale, multi-modal, and multi-temporal remote-sensed and in-situ data.

People involved in the group are: A. Thomas, J. Estopinan, P. Gaüzere, A. Thomas, S. Si Moussi, S. Cerna, Philippe Choler, Matthias Grenié and VIncent Miele.

2025–2029

ANR REFRAME

Response-Effect FRAMEwork in plants: revealing direct and indirect pathways

REFRAME is funded by the ANR as a four-year project and is led by Cyrille Violle (CEFE-Montpellier). It involves 3 other partners. The grand challenge of the REFRAME project is to integrate ecological complexity into the response-effect framework by revealing and quantifying both direct and indirect pathways (Figure 1). We will focus on three critical ecosystem functions: primary productivity, litter decomposition, and nitrogen cycling. REFRAME aims to reformulate the response-effect framework, providing a predictive framework for biodiversity and ecosystem science, combining ecology and evolutionary biology. .

People involved in the group are: T. Münkemüller, P. Choler, S. Lavorel, M. de la Gastine, G. Poggiato, A. Saillard

2025–2028

ADONIS

Quantifying and attributing vegetation change in France

ADONIS is a multi-year project co-funded by the Office Français pour la Biodiversité (OFB) and we work together with the National Botanical Conservatories (CBNs). We developped tools and methods to quantify past recent vegetatino trends using the CBN retrospective data and attibute those chnages to environmental variations

People involved in the group are: Pierre Gaüzere, Romain Goury

2026–2034

PEPR Dynabiod

Dynamics of Terrestrial Biodiversity in the Anthropocene: Understanding to Take Action

Dynabiod aims to understand how plants and invertebrates—the cornerstones of our ecosystems—are affected by human activities and environmental changes, so that we can take faster and more effective action to conserve species and preserve the benefits of their ecosystem roles. Co-led by the CNRS (W. Thuiller) and the National Museum of Natural History (Emmanuelle Porcher & Rodolphe Rougerie), it is funded by the ANR for 8 years and 40M euro. It involves > 20 research units in France and outersea territories and more than 100 scientists and technicians.

People involved in the group are: S. Si-Moussi, V. Miele, M. Grenié, T. Munkemuller, S. Lavergne, L. Gallien, C. Penone, G. Poggiato, A. Saillard, S. Mulero, F. Boyer, V. Lefort, etc...

2026–2030

HorizonEurope NatureRestoreR

Guiding nature restoration through integrated ecological modelling

NatureRestoreR is funded by the European Commission as a 4-years project from 2026-2030. It is coordinated by A Schippers (Radboud Univ., Holland) and involves 12 other academic and NGO partners.

In NaturaRestoreR, our team leads WP4 on estimating the extent and condition of terrestrial habitats through a new, systematic and replicable modelling approachb. We are also involve in WP3 on estimating ecological needs of terrestrial species (together with Sapienza Univ) and WP5 on the link betweeen habitats and ecosystem services. Finally, we co-lead a task in WP7 together with Patrinat (I. Laigle and A. Carré) on the French case study restoration .

People involved in the group are: S. Si-Moussi, N. Fermon, F. Veillon, M. Guéguen

2026–2028

AlpiConnect

Landscape Connectivity of Iconic Vertebrate Species in Alpine Habitats.

AlpiConnect is a two--year project co-funded by the Office Français pour la Biodiversité (OFB). The AlpiConnect project aims to mobilize and synthesize all available knowledge (data and methods) on landscape connectivity for iconic vertebrate wildlife in French Alpine regions (the Alps and the Pyrenees), and to work toward integrating this knowledge into public policy.

People involved in the group are: Marie-Caroline Prima

2026–2029

MIAI Cluster IA - XLBiod

Explainable Latent Spaces for Biodiversity Modeling.

XLBiod is a three-year funded chair in AI, co-led by S. Si-Moussi (LECA-Grenoble) and H. Hendrikx (INRIA-Grenoble). XLBiod aims to leverage artificial intelligence to better understand biodiversity drivers and predict future impacts. We will design a framework to obtain models that transform raw data into explainable representations that are suited for downstream ecological research. More specifically, we will investigate (i) by-design explainable models, (ii) the way ecological factors (e.g., functional traits) structure representation spaces, in particular when varying the learning tasks, and (iii) the level of consistency between different views (e.g., representations of plants and invertebrates) of a same ecological site. We will thus tackle the full chain, from methodological advances in Machine Learning (ML) to new ecological insights, designing state-of-the-art ML models to process new ecological data.

People involved in the group are: V. Miele