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.

Modelling the biogeochemical cycles of elements limiting primary production in the English channel .2. Sensitivity analyses

A general framework for an ecological model of the English Channel was described in the first of this pair of papers. In this study, it was used to investigate the sensitivity of the model to various factors: model structure, parameter values, boundary conditions and forcing variables. These sensitivity analyses show how important quota formulation for phytoplankton growth is, particularly for growth of dinoflagellates. They also stress the major influence of variables and parameters related to nitrogen. The role played by rivers and particularly the river Seine was investigated. Their influence on global English Channel phytoplanktonic production seems to be relatively low, even though nutrient inputs determine the intensity of blooms in the Bay of Seine. The geographical position of the river Seine's estuary makes it important in fluxes through the Straits of Dover. Finally, the multi-annual study highlights the general stability of the English Channel ecosystem. These global considerations are discussed and further improvements to the model are proposed.

A coupled movement and bioenergetics model to explore the spawning migration of anchovy in the Bay of Biscay

Adult anchovies in the Bay of Biscay perform north to south migration from late winter to early summer for spawning. However, what triggers and drives the geographic shift of the population remains unclear and poorly understood. An individual-based fish model has been implemented to explore the potential mechanisms that control anchovy's movement routes toward its spawning habitats. To achieve this goal, two fish movement behaviors – gradient detection through restricted area search and kinesis – simulated fish response to its dynamic environment. A bioenergetics model was used to represent individual growth and reproduction along the fish trajectory. The environmental forcing (food, temperature) of the model was provided by a coupled physical–biogeochemical model. We followed a hypothesis-testing strategy to actualize a series of simulations using different cues and computational assumptions. The gradient detection behavior was found as the most suitable mechanism to recreate the observed shift of anchovy distribution under the combined effect of sea-surface temperature and zooplankton. In addition, our results suggested that southward movement occurred more actively from early April to middle May following favorably the spatio-temporal evolution of zooplankton and temperature. In terms of fish bioenergetics, individuals who ended up in the southern part of the bay presented better condition based on energy content, proposing the resulting energy gain as an ecological explanation for this migration. The kinesis approach resulted in a moderate performance, producing distribution pattern with the highest spread. Finally, model performance was not significantly affected by changes on the starting date, initial fish distribution and number of particles used in the simulations, whereas it was drastically influenced by the adopted cues.