MASSIF

Coordinating institution : INRAE
Partner institutions : CNRS | INP Toulouse | Sorbonne University | National Museum of Natural History | ONF
Project leader : Carole Kerdelhué (INRAE)
Project duration : 48 months | 1 October 2025 → 30 September 2029

Forest ecosystems face multiple major threats that jeopardize their resilience and the maintenance of their ecological functions. Establishing long-term biodiversity monitoring observatories, both taxonomic and functional, is therefore of critical importance, particularly as forests provide habitat and refuge for numerous species.

Insects, which represent the majority of biological diversity, are key players in many ecosystem services (pollination, organic matter cycling, trophic networks, pest regulation). The observed decline in entomological diversity in forests thus poses a serious threat to ecosystem resilience. Conversely, some insects, whether native pests or invasive exotic species, pose a growing threat to forest health under changing climatic conditions (ecosystem disservices).

However, monitoring hyperdiverse insect communities faces major challenges that limit large-scale deployment. Given the importance of taxonomic and functional diversity in forest insects and the pressures associated with global change, it is now essential to implement monitoring systems that combine long-term biodiversity observation with bio-surveillance devices to ensure the early detection of emerging or invasive species. Innovative technologies based on genetic, optical, and algorithmic tools are now available and could be deployed at large scale.

This project will develop high-throughput molecular identification methods, as well as optical and photographic tools for monitoring forest insects, leveraging recent advances in artificial intelligence (AI), whether embedded or not. We will focus on functionally and patrimonially significant groups that are abundant and diverse, including guilds involved in ecosystem services or disservices. The proposed interdisciplinary consortium involves units with complementary expertise.

To achieve its objectives, the project is structured into four thematic workpackages (WPs) :

• WP1 focuses on developing two essential reference databases for the project : a DNA barcode database and a photographic database centered on expertly identified specimens.
• WP2 aims to select, train, and evaluate AI algorithms for species detection, identification, and counting, both under laboratory conditions and in field-deployed systems.
• WP3 is dedicated to instrumentation, aiming to deploy efficient traps and develop a prototype for image acquisition and onboard analysis (development of autonomous, non-destructive, and energy-efficient multi-sensor systems).
• WP4 covers field deployment of these prototypes, comparison of identification methods (human expertise, molecular, and AI), development of analysis tools, and optimization of large-scale monitoring setups (Renecofor plots, ONF networks).

The project will also include two cross-cutting WPs :

• WP0 is dedicated to governance and dissemination of results and knowledge.
• WP5, in connection with the PC NUM-DATA, will focus on secure data management, development of digital tools ensuring interoperability, dissemination of databases and statistical tools, and long-term maintenance of this infrastructure. Data sharing will follow FAIR principles.

The project will provide the necessary tools for monitoring insect fauna and forest health, complementing data collected under the X-RISKS and MONITOR projects.