Automatic Forest Biodiversity Sensors- BIOC@PT

It meets a triple aim of biovigilance, biodiversity monitoring and the study of spatiotemporal patterns of biodiversity. It involves automating field surveys (using sensors) and species determination (using artificial intelligence or metabarcoding techniques). Our exploratory approach concerns two important and relatively poorly known forest taxonomic groups (insects and bryophytes) and could be transferred to other groups. During the project, we are developing prototypes of insect sensors with automatic photographic traps, and testing their operation in forests. Automatic insect traps are selective (xylophagous Agrilus, flower-visiting insects) or generic (flying insects). During the project, we are also implementing a database of reference pictures (insects of the genus Agrilus, forest bryophyte spores), and we are developing neural networks designed to determine the species sampled by entomological sensors and airborne spore sensors (cyclone sampler). A metabarcoding feasibility test will be carried out on bryophyte spore samples, and the results compared with the visual recognition method using deep learning.

INRAE units involved :

• Département ECODIV
  • EFNO Research Unit - Forest Ecosystems
  • Herbivores Joint Research Unit 
  • USC ecodiv – Rouen University - Study and Understanding of BioDiversity Laboratory
  • USC LBLGC Joint Research Unit - woody and field crop biology laboratory
• Département  PHASE
  • UR Herbivore
• Département  ECOSOCIO
  • UR Herbivore

External Partnership :

• LLaboratoire IRBI Joint Research Unit CNRS - Tours University - Institute of Research on Insect Biology