Recherche & Développement

Projet

DRACCAR-MMERMAID

Monitoring marine megafauna off Fécamp’s coasts in an offshore wind farm context

Motivation and background

The increasing number of Offshore Wind Farms (OWF) raises key environmental and societal issues as for their impacts on wildlife. Marine megafauna species, such as fish, seabirds and marine mammals, are at the heart of concerns. These species represent the high end of food webs, play key roles in ecosystem functioning and are also of socio-economic and cultural importance. They may be influenced by OWF, in their distribution, abundance and behaviour in relation to potential direct effects but also to a large array of ecological underlying effects. It is therefore essential to develop an integrative and long-term approach to improve our understanding of OWF effects on the marine environment.

DRACCAR-MMERMAID Project

Objective

  • To provide an integrative framework of advanced monitoring methods for efficient and relevant environmental impact assessments, using cutting edge technologies and methodological developments

Work planned

Identifying and use of complementary instruments to monitor simultaneously different marine megafauna compartments around an offshore structure

Development of algorithms for automated detections

Characterisation of the use of an OWF structure and surrounding areas by marine megafauna

Study of the spatial-temporal dynamic of the food web around an OWF structure

Assessment of the cumulative impacts of anthropogenic activities and climate change on the ecosystem’s structure and functioning at the local and regional levels

Elaboration of road map toward a monitoring network (standardisation of protocols and data acquisition)

Expected results

  • Knowledge on marine megafauna ecology in close vicinity of an OWF under construction.
  • Development of a cutting-edge continuous in situ monitoring approach
  • Integrated and robust sampling strategies to monitor simultaneously several compartments of marine megafauna.
  • State-of-the-art deep learning algorithms for videos, sonar and passive acoustic data to move toward automated data processing.
  • Advanced ecosystem models at local and regional scales
  • Innovative and replicable approach as a steppingstone toward a national observation network at sea.

Conclusion

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Partners

This project is led by France Energies Marines

Logo France Energies Marines
Logo EDF
Logo EDF Power Solutions
Logo Parc éolien en mer de Fécamp
Logo Université de Caen Normandie
Logo CeSigma
Logo ENSTA
Logo RTE
Logo TotalEnergies
Logo Université de Bretagne Occidentale
Logo Muséum National d'Histoire Naturelle
Logo IMT Atlantique
Logo Quiet Oceans
Logo Groupe Ornithologique Normand
Logo RWE
Logo Iberdrola
Logo Febus Optics
Logo Exail
Logo Skyborn
Logo UMS Patrimoine Naturel
Logo Université du Littoral Côte d'Opale
Logo GIS Eolien en mer

Funding

This project received French State funding managed by the National Research Agency under the France 2030 investment plan (ANR-10-IEED-0006-34). It also received financial support from the Normandy, Brittany, Occitanie and SUD Provence-Alpes-Côtes d’Azur regions, as well as from the European Union and the Directorate General for Energy and Climate (as part of the French Observatory for Offshore Wind Energy).

Logo France 2030
Logo Région Normandie
Logo Région Bretagne
Logo Région SUD Provence-Alpes-Côte d'Azur

Accredidation

This project has been certified by the maritime clusters Pôle Mer Bretagne Atlantique and Pôle Mer Méditerranée.

Logo Pôle Mer Bretagne Atlantique
Logo Pôle Mer Méditerranée

Pour aller plus loin

Newsletter 1

Découvrez la première newsletter du projet publiée en septembre 2024

Newsletter 2

Découvrez la deuxième newsletter du projet publiée en mai 2025

Flyer d'information

Parcourez ce flyer pour comprendre les grandes lignes du projet

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