Phytoplankton versus macrophyte contribution to primary production and biogeochemical cycles of a coastal mesotidal system. A modelling approach

This study presents an assessment of the contributions of various primary producers to the global annual production and N/P cycles of a coastal system, namely the Arcachon Bay, by means of a numerical model. This 3D model fully couples hydrodynamic with ecological processes and simulates nitrogen, silicon and phosphorus cycles as well as phytoplankton, macroalgae and seagrasses. Total annual production rates for the different components were calculated for different years (2005, 2007 and 2009) during a time period of drastic reduction in seagrass beds since 2005. The total demand of nitrogen and phosphorus was also calculated and discussed with regards to the riverine inputs. Moreover, this study presents the first estimation of particulate organic carbon export to the adjacent open ocean. The calculated annual net production for the Arcachon Bay (except microphytobenthos, not included in the model) ranges between 22,850 and 35,300 tons of carbon. The main producers are seagrasses in all the years considered with a contribution ranging from 56% to 81% of global production. According to our model, the -30% reduction in seagrass bed surface between 2005 and 2007, led to an approximate 55% reduction in seagrass production, while during the same period of time, macroalgae and phytoplankton enhanced their productions by about +83% and +46% respectively. Nonetheless, the phytoplankton production remains about eightfold higher than the macroalgae production. Our results also highlight the importance of remineralisation inside the Bay, since riverine inputs only fulfill at maximum 73% nitrogen and 13% phosphorus demands during the years 2005, 2007 and 2009. Calculated advection allowed a rough estimate of the organic matter export: about 10% of the total production in the bay was exported, originating mainly from the seagrass compartment, since most of the labile organic matter was remineralised inside the bay.

Informing Marine Spatial Planning (MSP) with numerical modelling: A case-study on shellfish aquaculture in Malpeque Bay (Eastern Canada)

A moratorium on further bivalve leasing was established in 1999–2000 in Prince Edward Island (Canada). Recently, a marine spatial planning process was initiated explore potential mussel culture expansion in Malpeque Bay. This study focuses on the effects of a projected expansion scenario on productivity of existing leases and available suspended food resources. The aim is to provide a robust scientific assessment using available datasets and three modelling approaches ranging in complexity: (1) a connectivity analysis among culture areas; (2) a scenario analysis of organic seston dynamics based on a simplified biogeochemical model; and (3) a scenario analysis of phytoplankton dynamics based on an ecosystem model. These complementary approaches suggest (1) new leases can affect existing culture both through direct connectivity and through bay-scale effects driven by the overall increase in mussel biomass, and (2) a net reduction of phytoplankton within the bounds of its natural variation in the area.

Comparison and validation of physical wave parameterizations in spectral wave models

Recent developments in the physical parameterizations available in spectral wave models have already been validated, but there is little information on their relative performance especially with focus on the higher order spectral moments and wave partitions. This study concentrates on documenting their strengths and limitations using satellite measurements, buoy spectra, and a comparison between the different models. It is confirmed that all models perform well in terms of significant wave heights; however higher-order moments have larger errors. The partition wave quantities perform well in terms of direction and frequency but the magnitude and directional spread typically have larger discrepancies. The high-frequency tail is examined through the mean square slope using satellites and buoys. From this analysis it is clear that some models behave better than the others, suggesting their parameterizations match the physical processes reasonably well. However none of the models are entirely satisfactory, pointing to poorly constrained parameterizations or missing physical processes. The major space-time differences between the models are related to the swell field stressing the importance of describing its evolution. An example swell field confirms the wave heights can be notably different between model configurations while the directional distributions remain similar. It is clear that all models have difficulty in describing the directional spread. Therefore, knowledge of the source term directional distributions is paramount in improving the wave model physics in the future.

Modelling the biogeochemical cycles of elements limiting primary production in the English channel .1. Role of thermohaline stratification

This paper presents the general framework of an ecological model of the English Channel. The model is a result of combining a physical sub-model with a biological one. in the physical submodel, the Channel is divided into 71 boxes and water fluxes between them are calculated automatically. A 2-layer, vertical thermohaline model was then linked with the horizontal circulation scheme. This physical sub-model exhibits thermal stratification in the western Channel during spring and summer and haline stratification in the Bay of Seine due to high flow rates from the river. The biological sub-model takes 2 elements, nitrogen and silicon, into account and divides phytoplankton into diatoms and dinoflagellates. Results from this ecological model emphasize the influence of stratification on chlorophyll a concentrations as well as on primary production. Stratified waters appear to be much less productive than well-mixed ones. Nevertheless, when simulated production values are compared with literature data, calculated production is shown to be underestimated. This could be attributed to a lack of refinement of the 2-layer box-model or processes omitted from the biological model, such as production by nanoplankton.