A single bio-energetics growth and reproduction model for the oyster Crassostrea gigas in six Atlantic ecosystems

Many studies based on bioenergetics growth models have investigated the effects of environmental factors on oyster (Crassostrea gigas) growth and physiology. However, most of these models are site-specific and cannot be applied to other culture sites without the re-estimation of parameters or re-formulation of some processes. We aimed to develop a generic growth model suitable for application in contrasting environments, with a constant set of parameters. We tested the oyster-DEB model (Bourlès et al. 2009) for the stimulation of C. gigas growth in different cohorts (spats and adults) at major shellfish culture sites in France, in several years: Arcachon (1993–1994); Marennes-Oléron (2007); Quiberon (1999, 2000, 2001); Brest Harbour (2008); Mont-Saint-Michel Bay (2003); Baie-des-Veys (2002). These different ecosystems offer a wide range of values for the two forcing variables of the model: water temperature (range: 6-24 °C) and phytoplankton concentration (annual average: 110–700 × 103 cell L-1). The validation data (dry flesh mass of C. gigas) were obtained from various growth surveys carried out by IFREMER. The oyster-DEB model simulated the oyster growth dynamics of both spat and adult stages of C. gigas accurately over time at the various culture sites. The model captures: i) the active spring growth; ii) the timing and amplitude of spawning events; and iii) the lean periods (i.e. loss of dry flesh mass) in autumn and winter. The half-saturation coefficient Xk is the only model parameter that varied between sites and years. This environment-specific coefficient reflects variability in the food of the oysters: quantitative and qualitative effects of the inorganic material and of the phytoplankton species on the feeding response of C. gigas. With a single set of parameters (other than for Xk), this is thus the first bio-energetic growth model for C. gigas robust enough and of a sufficiently generic nature for the accurate simulation of oyster growth in different Atlantic ecosystems.