MODELING THE IMPACT OF A CULTIVATED OYSTER POPULATION ON THE NITROGEN DYNAMICS - THE THAU LAGOON CASE (FRANCE)

The Thau lagoon (France) is an important site for the cultivation of Crassostrea gigas. The relationship between the oyster population and the environment was assessed through a model of trophic relationships. The results represent the initial step towards a more precise assessment of the biological fluxes in the lagoon. This preliminary model was based on the nitrogen dynamics among the following compartments: phytoplankton, zooplankton, oysters, detritus and dissolved inorganic nitrogen in the water column. Two other compartments were also considered in the sediment: detritus and dissolved nitrogen. The model considered the watershed input and seawater exchange between the lagoon and the open sea. The parameters were estimated from experiments on oyster ecophysiology, in situ primary production and biomass measurements, and by calibration of simulations against data series. The importance of vertical exchange of material between the water column and the sediment due to sedimentation, biodeposition by the cultivated oyster populations, and nutrient regeneration from the sediment, was supported by the model. Therefore, the model emphasized the impact resulting from oyster culture practices and the sediment contribution to nitrogen dynamics. Oysters could be considered as a nitrogen well that stabilizes the ecosystem by removing nitrogen over a longer time scale than zooplankton. Since grazing was dominated by the oyster compartment, zooplankton had a limited effect on phytoplankton dynamics. Moreover, model calculation demonstrated the critical role of detritus in oyster food ration. For instance, the sedimentation rate of particulate matter was doubled by the deposition by oysters. The model was sensitive to parameters controlling the primary production. For example, modifying these parameter values resulted in large winter accumulation of dissolved inorganic nitrogen, triggering a first phytoplankton bloom at the end of winter. This sensitivity stressed the importance of using experimental data for calibration of the model.