Remote Sensing-Driven Pacific Oyster (Crassostrea gigas) Growth Modeling to Inform Offshore Aquaculture Site Selection

• Published in: Frontiers in Marine Science
• Main Authors: Palmer, Stephanie, Gernez, Pierre, Thomas, Yoann, Simis, Stefan, H.G., Miller, Peter, Glize, Philippe, Barillé, Laurent
• Other Authors: Mer, molécules et santé EA 2160 (MMS), Le Mans Université (UM)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Plymouth Marine Laboratory (PML), Syndicat Mixte pour le Développement de l'Aquaculture et de la Pêche en Pays de la Loire (SMIDAP), This work was part of the EU H2020 project Tools for Assessment and Planning of Aquaculture Sustainability (TAPAS), funded by the EU H2020 Research and Innovation Program under Grant Agreement No. 678396., European Project: 678396,H2020,H2020-SFS-2015-2,TAPAS(2016)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2020
• Subjects: marine spatial planning; satellite image; time series; bivalve; dynamic energy budget; growth modeling; MERIS; AVHRR; acl; [SDV.EE.ECO]Life Sciences [q-bio]/Ecology; environment/Ecosystems; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; Crassostrea gigas; Pacific oyster
• Online Access: https://hal.science/hal-02530657; https://hal.science/hal-02530657/document; https://hal.science/hal-02530657/file/Palmer_etal_FiMS_2020.pdf; https://doi.org/10.3389/fmars.2019.00802

International audience Aquaculture increasingly contributes to global seafood production, requiring new farm sites for continued growth. In France, oyster cultivation has conventionally taken place in the intertidal zone, where there is little or no further room for expansion. Despite interest in moving production further offshore, more information is needed regarding the biological potential for offshore oyster growth, including its spatial and temporal variability. This study shows the use of remotely-sensed chlorophyll-a and total suspended matter concentrations retrieved from the Medium Resolution Imaging Spectrometer (MERIS), and sea surface temperature from the Advanced Very High Resolution Radiometer (AVHRR), all validated using in situ matchup measurements, as input to run a Dynamic Energy Budget (DEB) Pacific oyster growth model for a study site along the French Atlantic coast (Bourgneuf Bay, France). Resulting oyster growth maps were calibrated and validated using in situ measurements of total oyster weight made throughout two growing seasons, from the intertidal zone, where cultivation currently takes place, and from experimental offshore sites, for both spat (R-2 = 0.91; RMSE = 1.60 g) and adults (R-2 = 0.95; RMSE = 4.34 g). Oyster growth time series are further digested into industry-relevant indicators, such as time to achieve market weight and quality index, elaborated in consultation with local producers and industry professionals, and which are also mapped. Offshore growth is found to be feasible and to be as much as two times faster than in the intertidal zone (p < 0.001). However, the potential for growth is also revealed to be highly variable across the investigated area. Mapping reveals a clear spatial gradient in production potential in the offshore environment, with the northeastern segment of the bay far better suited than the southwestern. Results also highlight the added value of spatiotemporal data, such as satellite image time series, to drive modeling in support of marine ...