Environmental impact assessment (EIA) studies for offshore wind farm projects endeavour to consider the sensitivity of ecological compartments (benthos, fish, birds and marine mammals) to potential pressures/changes occurring in the ecosystem structure and functioning. EIA is expected to be conducted considering an integrated ecosystem approach, which is still a target to reach. In this context, and as a complementary approach to the traditional impact assessments, the objective of the ANR TROPHIK project is to develop an integrated ecosystem approach using several modelling tools for a holistic consideration of the food web. Here, we take into account the case of the Courseulles-sur-Mer offshore wind farm project located in the Bay of Seine. In this project, the potential impacts associated with this planned offshore wind farm are modelled. A model of the food web at the site of the construction was built to test possible reef- and reserve-effects, and to investigate the usefulness of Ecological Network Analysis (ENA) indices in the assessment of ecosystem health state. After the installation of the wind farm, our model showed that the ecosystem witnessed a change in its functioning mainly due to the important increase of the biomass of bivalves with the reef effect related to the installation of hard structures for the OWF. To go further into the integration of these results, we enlarged the description of the ecosystem functioning from a local to a larger spatial scale, where the initial zone was extended to the whole Bay of Seine using a spatial model. Different scenarios were built to test how the association of cumulative impacts, from climate change to fisheries, could affect the ecosystem. Finally, we propose a combined food-web and social network modelling approach to the Courseulles-sur-Mer model. The objectives of this latter analysis are to construct a decision-making process focusing on the network of actors involved, and to couple these social and ecological networks into a qualitative common model for a better understanding of the social-ecological system. Our approach aims to contribute to sustainable development through the analysis of interactions between the different categories of stakeholders groups, and can be applied in other offshore wind farm implementation in European waters.
- Food-web model
- Ecological network analysis
- Socio-ecological system
- Cumulative impacts
- Global change
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Araignous, E., Buszowski, J., Steenbeek, J., Bourdaud, P., Lasram, F., & Niquil, N. (in prep). Preliminary title: Spatialization of ecological network analysis indicators: The enaR software plug-in for Ecopath with Ecosim models. Planned submission to Environmental modelling and software.
Araújo, M. B., & New, M. (2007). Ensemble forecasting of species distributions. Trends in Ecology and Evolution, 22(1), 42–47.
Ben Rais Lasram, F., Hattab, T., Noguès, Q., Beaugrand, G., Dauvin, J.C., Halouani, G., et al. (in prep). A ready-to-use R script for projecting future patterns of marine species distributions at the local scale. Submitted to Ecological Informatics.
Borrett, S. R., & Lau, M. K. (2014). enaR: An R package for ecosystem network analysis. Methods in Ecology and Evolution, 5(11), 1206–1213.
Bourdaud, P., Araignous, E., Champagnat, J., Ben Rais Lasram, F., Halouani, G., Hattab, T., et al. (in prep). Preliminary title: Impact of climate change on the Bay of Seine ecosystem: Approach by forcing of niche models on a spatio-temporal trophic model. Planned submission ICES Journal of Marine Science.
Chaalali, A., Saint-Béat, B., Lassalle, G., Le Loc’h, F., Tecchio, S., Safi, G., et al. (2015). A new modeling approach to define marine ecosystems food-web status with uncertainty assessment. Progress in Oceanography, 135, 37–47.
Champagnat, J., Araignous, E., Bourdaud, P., Ben Rais Lasram, F., Halouani, G., Niquil, N. (in prep). Preliminary title Assessing the sensitivity of ecosystemic indicators to fishing: A trophic modelling of the Bay of Seine. Planned submission to Ecological Indicators.
Christensen, V., Walters, C. J., Ahrens, R., Alder, J., Buszowski, J., Christensen, L. B., et al. (2008). Models of the world’s large marine ecosystems. GEF/LME global project promoting ecosystem-based approaches to fisheries conservation and large marine ecosystems.
Cury, P., Shannon, L., & Shin, Y. J. (2003). The functioning of marine ecosystems: A fisheries perspective. Responsible Fisheries in the Marine Ecosystem, 103–123.
Finn, J. T. (1980). Flow analysis of models of the Hubbard Brook ecosystem. Ecology, 61(3), 562–571.
Fulton, E. A. (2010). Approaches to end-to-end ecosystem models. Journal of Marine Systems, 81(1–2), 171–183.
Guesnet, V., Lassalle, G., Chaalali, A., Kearney, K., Saint-Béat, B., Karimi, B., et al. (2015). Incorporating food-web parameter uncertainty into Ecopath-derived ecological network indicators. Ecological Modelling, 313, 29–40.
Halouani, G., Villanueva, M. C., Raoux, A., Dauvin, J. C, Ben Rais Lasram, F., Foucher, E., et al. (in prep). Preliminary title: A spatial food web model to investigate potential effects of an offshore wind farm. Planned submission to Journal of Marine Systems.
Haraldsson, M., Raoux, A., Riera, F., Hay, J., Dambacher, Niquil, N. (submitted). How to model Social-Ecological Systems?—A case study on the effects of a future offshore windfarm on the local society and ecosystem, and whether social compensation matters. Submitted to Marine Policy (under revision).
Hattab, T., Albouy, C., Lasram, F. B. R., Somot, S., Loc’h, L., & Leprieur, F. (2014). Towards a better understanding of potential impacts of climate change on marine species distribution: A multiscale modelling approach. Global Ecology and Biogeography, 23(12), 1417–1429.
Henkel, S. K., Suryan, R. M., & Lagerquist, B. A. (2014). Marine renewable energy and environmental interactions: Baseline Assessments of Seabirds, Marine Mammals, Sea Turtles and Benthic Communities on the Oregon Shelf. In M. A. Shields, A. Payne (Eds.), Marine renewable energy technology and environmental interactions (176 pp.). Springer Sciences.
Hosack, G. R., Li, H. W., & Rossignol, P. A. (2009). Sensitivity of system stability to model structure. Ecological Modelling., 220, 1054–1062.
Hughes, T. P., Bellwood, D. R., Folke, C., Steneck, R. S., & Wilson, J. (2005). New paradigms for supporting the resilience of marine ecosystems. Trends in Ecology & Evolution, 20, 380–386.
Knowlton, N. (1992). Thresholds and multiple stable states in coral reef community dynamics. American Zoologist, 32, 674–682.
Knowlton, N. (2004). Multiple stable states and the conservation of marine ecosystems. Progress in Oceanography, 60, 387–396.
Kones, J. K., Soetaert, K., van Oevelen, D., & Owino, J. O. (2009). Are network indices robust indicators of food web functioning? A Monte Carlo approach. Ecological Modelling, 220, 370–382.
Latham, L. G. (2006). Network flow analysis algorithms. Ecological Modelling, 192, 586–600.
Lassalle, G., Lobry, J., Le Loc’h, F., Bustamante, P., Certain, G., Delmas, D., et al. (2011). Lower trophic levels and detrital biomass control the Bay of Biscay continental shelf food web: Implications for ecosystem management. Progress in Oceanography, 91(4), 561–575.
Lassalle, G., Chouvelon, T., Bustamante, P., & Niquil, N. (2014). An assessment of the trophic structure of the Bay of Biscay continental shelf food web: Comparing estimates derived from an ecosystem model and isotopic data. Progress in Oceanography, 120, 205–215.
Libralato, S., Christensen, V., & Pauly, D. (2006). A method for identifying keystone species in food web models. Ecological Modelling, 195, 153–171.
Lindeboom, H. J., Kouwenhoven, H. J., Bergman, M. J. N., Bouma, S., Brasseur, S., Daan, R., et al. (2011). Short term ecological effects of an offshore wind farm in the Dutch coastal zone; A compilation. Environmental Research Letters, 6, 1–13.
Niquil, N., Le Loc’h, F., Tecchio, S., Chaalali, A., Vouriot, P., Mialet, B., et al. (2014). Ongoing research on ecosystem health indicators for food webs in the MSFD context. In Trans-Channel forum Proceedings “Science and Governance of the Channel Marine Ecosystem” (pp. 14–15), Caen, France.
Noguès, Q. (2018). Analyse de sensibilité du cumul de l’effet récif et de l’effet du changement climatique, sur différents indices ENA: Le cas du parc éolien offshore de Courseulles-sur-Mer. Université de Bordeaux - Master 2, mention Sciences de la Mer, parcours Biologie et écologie marines (45 pp.).
Norling, P., & Kautsky, N. (2008). Patches of the mussel Mytilus sp. are islands of high biodiversity in subtidal sediment habitats in the Baltic Sea. Aquatic Biololy, 4, 75–87.
Odum, E. P. (1969). The strategy of ecosystem development. Science,164, 262–270.
Odum, E. P. (1971). Fundamentals of ecology (574 pp.). Philadelphia, USA: W. B. Saunders Co.
Österblom, H., Merrie, A., Metian, M., Boonstra, W. J., Blenckner, T., Watson, J. R., et al. (2013). Modeling social-ecological scenarios in marine systems. Bioscience, 63, 735–744.
Pezy, J. P., Raoux, A., Niquil, N., Dauvin, J. C. (in press). Offshore renewable energy development in France with an emphasis on the eastern part of the English Channel: State at the end of 2017. In Proceedings of the Conference on Wind Energy and Wildlife Impacts, Estoril, September 2017.
Raoux, A. (2017). Approche écosystémique des Energies Marines Renouvelables: étude de l’impact sur le réseau trophique de la construction du parc éolien au large de Courseulles-sur-mer et du cumul d’impacts. Thèse de Doctorat, Université de Caen Normandie, France (293 pp.).
Raoux, A., Tecchio, S., Pezy, J. P., Degraer, S., Wilhelmsson, D., Cachera, M., et al. (2017). Benthic and fish aggregation inside an offshore wind farm: Which effects on the trophic web functioning? Ecological Indicators,72, 33–46.
Raoux, A., Dambacher, J. M., Pezy, J. P., Mazé, C., Dauvin, J. C., & Niquil, N. (2018). Assessing cumulative socio-ecological impacts of offshore wind farm development in the Bay of Seine (English Channel). Marine Policy, 89, 11–20.
Raoux, A., Lassalle, G., Pezy, J. P., Tecchio, S., Safi, G., Ernande, B., et al. (2019). Measuring sensitivity of two Ospar indicators for a coastal food web model under Offshore Wind Farm construction. Ecological Indicators, 96, 728–738.
Tiller, R., Gentry, R., & Richards, R. (2013). Stakeholder driven future scenarios as an element of interdisciplinary management tools; The case of future offshore aquaculture development and the potential effects on fishermen in Santa Barbara, California. Ocean & Coastal Management, 73, 127–135.
Tiller, R., & Richards, R. (2016). Once bitten, twice shy: Aquaculture, stakeholder adaptive capacity, and policy implications of iterative stakeholder workshops; the case of Frøya, Norway. Ocean & Coastal Management, 118, 98–109.
Ulanowicz, R. E. (1986). Growth and development: Ecosystems phenomenology (166 pp.). New York: Springer.
Walters, C. J., Christensen, V., & Pauly, D. (1997). Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries, 7, 139–172.
This work is supported by France Energies Marines (www.france-energies-marines.org). It is part of the project TROPHIK co-funded by the ANR (Agence Nationale de la Recherche), under the program “Investissements d’avenir” (ANR/FEM EMR-ITE 2015 number ANR-10-IEED-0006-12). It is also funded, in support of A Raoux’s Ph.D., by the Normandie Region and by the company “Eoliennes Offshore du Calvados” (EOC). We also acknowledge, the Centre Régional Informatique et d’Applications Numériques de Normandie, CRIANN for running the ENAtool and LIM-MCMC calculations and especially Béatrice Charton and Benoist Gaston for their help.
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Niquil, N. et al. (2020). Toward an Ecosystem Approach of Marine Renewable Energy: The Case of the Offshore Wind Farm of Courseulles-sur-Mer in the Bay of Seine. In: Nguyen, K., Guillou, S., Gourbesville, P., Thiébot, J. (eds) Estuaries and Coastal Zones in Times of Global Change. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-15-2081-5_9
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