Approche écosystémique des Energies Marines Renouvelables : étude des effets sur le réseau trophique de la construction du parc éolien au large de Courseulles-sur-mer et du cumul d'impacts

Abstract

As part of the energy transition, the French government is planning the construction of eight Offshore Wind Farms (OWF) along the English Channel and Atlantic coasts including the Courseullessur-mer OWF. Until now, there is no holistic study on the OWF construction and operation effects on an ecosystem taken as a whole. This thesis is the first study to lay the foundations for an ecosystem approach of Marine Renewable Energy (MRE) through the Courseulles-sur-mer OWF example. For that a combination of innovative modelling tools was applied to 1) characterise the ecosystem structure and functioning before the OWF construction; 2) simulate the impacts of this future OWF on the ecosystem structure and functioning. A food-web model and three scenarios were constructed to investigate the “reef” and “reserve” effects induced by the OWF on the ecosystem. Ecological Network Analysis indices, other ecosystem attributes and Mean Trophic Level were derived to investigate the ecosystem health and state. However, being aware that this ecosystem is threatened by multiple perturbations, there is a need to understand how human activities interact to influence ecosystem functioning in a long term climate change context. Thus, a holistic view of cumulated impacts on the Courseulles-sur-mer’ ecosystem through the use of an oriented signed digraph was also developed. Results highlighted a combination of significant changes in the food-web structure and ecosystem functioning. These results can play a vital role in both decision making by improving long term planning for the marine environment but also as tool for communication with the public and so contribute to a better acceptability of MRE project.

Keyword: Bay of Seine, Ecopath model, qualitative model, holistic approach, Ecological Network Analysis (ENA)

Author

RAOUX Aurore

Year of defence
2017
Team
ECOFUNC