Published February 10, 2025 | Version v1
Journal article Open

Using Image-based AI for insect monitoring and conservation - InsectAI COST Action

Authors/Creators

  • 1. UK Centre for Ecology and Hydrology, Wallingford, United Kingdom
  • 2. Malta College of Arts, Science and Technology, Paola, Malta
  • 3. Friedrich Schiller University, Jena, Germany
  • 4. Luxembourg Institute of Science and Technology, Esch-Sur-Alzette, Luxembourg
  • 5. Centre for Functional Ecology, Associate Laboratory TERRA, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
  • 6. Norwegian Institute for Nature Research, Trondheim, Norway
  • 7. Université de Mons, Mons, Belgium
  • 8. Association Noé, Paris, France
  • 9. Meise Botanic Garden, Meise, Belgium
  • 10. Naturalis Biodiversity Center, Leiden, Netherlands
  • 11. University of Twente, Enschede, Netherlands
  • 12. Flumens, Kaunas, Lithuania
  • 13. Norwegian Biodiversity Information Centre, Trondheim, Norway
  • 14. Laboratory of Vector Ecology and Applied Entomology, Joint Services Health Unit, Akrotiri, Cyprus|The Cyprus Institute, Nicosia, Cyprus|Enalia Physis Environmental Research Centre, Nicosia, Cyprus
  • 15. Vermont Center for Ecostudies, Norwich, United States of America
  • 16. University of Mons, Mons, Belgium
  • 17. University College London, London, United Kingdom
  • 18. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
  • 19. Institute of Landscape Ecology & Centre for Integrative Biodiversity Research and Applied Ecology (CIBRA), University of Münster, Münster, Germany
  • 20. Biodiversity Unit, Department of Biology, Lund University, Lund, Sweden
  • 21. Charles University in Prague, Faculty of Science, Praha, Czech Republic
  • 22. Ovidius University of Constanta, Constanta, Romania
  • 23. McGill University; Mila Quebec AI Institute, Montreal, Canada
  • 24. Ökologische Beratung, Planung und Forschung, Reinach, Switzerland
  • 25. Centre for Ecology & Hydrology, Crowmarsh Gifford, Wallingford, Wallingford, United Kingdom|University of Exeter, Falmouth, United Kingdom
  • 26. University of Tartu, Tartu, Estonia
  • 27. Croatian Natural History Museum, Zagreb, Croatia
  • 28. Global Biodiversity Information Facility - Secretariat, Copenhagen Ø, Denmark
  • 29. German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Leipzig, Germany|Helmholtz – Centre for Environmental Research – UFZ, Leipzig, Germany|Friedrich Schiller University Jena, Institute of Biodiversity, Jena, Germany
  • 30. University of Copenhagen, Copenhagen, Denmark
  • 31. CESAM & Department of Biology, University of Aveiro, Aveiro, Portugal
  • 32. University of the Aegean, Μytilene, Greece
  • 33. Faculty of Pure and Applied Sciences, Open University of Cyprus, Nicosia, Cyprus
  • 34. European Commission, Joint Research Centre (JRC), Ispra, Italy
  • 35. Martin-Luther University, Department of Computer Science, Halle, Germany|German Centre for Integrative Biodiversity Research (iDiv) Halle Jena Leipzig, Leipzig, Germany
  • 36. Agroecology Lab, Université libre de Bruxelles (ULB), Brussel, Belgium
  • 37. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg
  • 38. Aarhus University, Aarhus, Denmark

Description

The InsectAI COST action will support insect monitoring and conservation at the national and continental scale in order to understand and counteract widespread insect declines. The Action will bring together a critical mass of researchers and stakeholders in image-based insect AI technologies to direct and drive the research agenda, build research capacity across Europe and support innovation and application.

There is mounting evidence that populations of insects around the world are in sharp decline. Understanding trends in species and their drivers is key to knowing the size of the challenge, its causes and how to address it. To identify solutions that lead to sustainable biodiversity alongside economic prosperity, insect monitoring should be efficient and provide standardised and frequently updated status indicators to guide conservation actions.

The EU Biodiversity Strategy 2030 identifies the critical challenge of delivering standardised information about the state of nature and image-based insect AI can contribute to this. Specifically, the EU Nature Restoration Law will likely set binding targets for the high resolution data that cameras can provide. Thus, outputs of the Action will contribute directly to EU policies implementation, where biodiversity monitoring is considered a key component.

The InsectAI COST Action will organise workshops, conferences, short-term scientific missions, hackathons, design-sprints and much more, across four Working Groups. These groups will address how image-based insect AI technologies can best address Societal Needs, support innovation in Image Collection hardware, create standardised approaches for Image Processing and develop novel Data Analysis and Integration methods for turning data into actionable insights.

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Additional details

Cites
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Publication: 10.1111/1755-0998.13567 (DOI)
Has part
Figure: 10.3897/rio.10.e134825.figure1 (DOI)

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