Coordinating institution : University of Picardie Jules Verne
Partner institutions : INRAE | CNRS | University of Freiburg | Claude Bernard University Lyon 1 | Inria | Ghent University | ONF | CNPF | French Federation of Regional Natural Parks | FCBA Technological Institute | Pro Silva France | ADEME
Project leader : Guillaume Decocq (University of Picardie Jules Verne)
Project duration : 48 months | 1 October 2025 → 30 September 2029

French forests are currently facing unprecedented pressure due to the intensity and rapid pace of climate change. In order for them to continue providing the many ecosystem services on which our society depends, it is essential to support their adaptation and strengthen their resilience. The MADE IN France project, developed within the framework of the PEPR FORESTT programme, fully aligns with this ambition.

The project brings together cutting-edge approaches in ecology, applied mathematics, and artificial intelligence (AI) to support future silvicultural decisions, structured around three main pillars :

1. Optimising species assemblages for more resilient forests

The objective is to identify, for each region and forest site type, a range of tree species - native or exotic - that are better suited to withstand future conditions. By combining ecological niche theory, functional ecology, modelling, and AI, MADE IN France aims to design forest stands with high functional complementarity and redundancy, ensuring greater stability in the face of disturbances.

2. Characterising the integration of species into forest ecosystems

The project examines the ecological impacts (both positive and negative) of different species and their mixtures, drawing on a database compiled from the scientific literature as well as new field observations. The goal is to produce simple indicators to monitor these effects and to assess the benefit/risk balance in support of informed forest management.

3. Modelling stand dynamics under constraints

MADE IN France develops innovative models capable of simulating forest dynamics while accounting for climatic, environmental, and demographic disturbances. These hybrid models will make it possible to explore a range of management scenarios across multiple spatial and temporal scales, integrating species interactions and silvicultural practices.

The ultimate ambition of the project is to create a decision-support toolbox for adaptive forest management. These tools will, for example, help identify the most suitable species mixtures according to ecological and socio-economic constraints, and guide silviculture towards robust, scientifically grounded, and sustainable strategies.