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The Baie des Veys (Normandy, France) has abundant stocks of shellfish (oyster and cockle farms). Water quality in the bay is affected by pollutant inputs from a 3500 km2 watershed and notably occasional episodes of contamination by faecal coliforms. In order to characterise enterobacterial loads and develop a plan of action to improve the quality of seawater and shellfish in the bay, a two-stage modelling procedure was adopted. This focused on Escherichia coli and included a catchment model describing the E. coli releases, and the transport and die-off of this bacteria up to the coast. The output from this model then served as input for a marine model used to determine the concentration of E. coli in seawater. A total 60 scenarios were tested, including different wind, tidal, rainfall and temperature conditions and accidental pollution events, for both current situations and future scenarios. The modelling results highlighted the impact of rainfall on E. coli loadings to the sea, as well as the effects of sluice gates and tidal cycles, which dictated the use of an hourly timescale for the modelling process. The coupled models also made it possible to identify the origin of these enterobacteria as found in shellfish harvesting areas, both in terms of the contributing watercourses and the sources of contamination of those watercourses. The tool can accordingly be used to optimise remedial action. [ABSTRACT FROM AUTHOR]

Abstract: It is well known that temporal changes in bivalve body mass are strongly correlated with temporal variations in water temperature and food supply. In order to study the influence of the year-to-year variability of environmental factors on oyster growth, we coupled a biogeochemical sub-model, which simulates trophic resources of oysters (i.e. phytoplankton biomass via chlorophyll a), and an ecophysiological sub-model, which simulates growth and reproduction (i.e. gametogenesis and spawning), using mechanistic bases. The biogeochemical sub-model successfully simulated phytoplankton dynamics using river nutrient inputs and meteorological factors as forcing functions. Adequate simulation of oyster growth dynamics requires a relevant food quantifier compatible with outputs of the biogeochemical sub-model (i.e. chlorophyll a concentration). We decided to use the phytoplankton carbon concentration as quantifier for food, as it is a better estimator of the energy really available to oysters. The transformation of chlorophyll a concentration into carbon concentration using a variable chlorophyll a to carbon ratio enabled us to improve the simulation of oyster growth especially during the starvation period (i.e. autumn and winter). Once validated, the coupled model was a suitable tool to study the influence of the year-to-year variability of phytoplankton dynamics and water temperature on the gonado-somatic growth of the Pacific oyster. Four years with highly contrasted meteorological conditions (river inputs, water temperature and light) 2000, 2001, 2002 and 2003, were simulated. The years were split into two groups, wet years (2000 and 2001) and dry years (2002 and 2003). Significant variability of the response of oysters to environmental conditions was highlighted between the four scenarios. In the wet years, an increase in loadings of river nutrients and suspended particulate matter led to a shift in the initiation and the magnitude of the phytoplanktonic spring bloom, and consequently to a shift in oyster growth patterns. In contrast, in the dry years, an increase in water temperature—especially during summer—resulted in early spawning. Thus, the gonado-somatic growth pattern of oysters was shown to be sensitive to variations in river loadings and water temperature. In this context, the physiological status of oysters is discussed using a relevant indicator of energy needs. [Copyright &y& Elsevier]