Investigation of mechanistic formulations depicting phytoplankton dynamics for models of marine pelagic ecosystems and description of a new model

International audienceRealistic modelling of marine ecosystems is necessary for improving our understanding of the ocean's biogeochemical state and for predicting their response to anthropic perturbations. An essential step in achieving this task is the use of mechanistic formulations to describe the biogeochemical processes involved in the dynamics of marine pelagic ecosystems. This study provides a review on some modelling strategies for some of the key processes involved in the dynamics of phytoplankton. It encompasses the most advanced work in terms of mechanistic understanding and, therefore, mainly deals with photosynthesis (including photoacclimation and photoinhibition), respiration, and nutrient uptake (including multi-limitation of algal growth by nutrients). We highlight, that in many ecosystem models, phytoplankton processes are still described more or less empirically, mainly due to a lack of biochemical knowledge, or if a mechanistic formulation exists, the parameters are often difficult to assess experimentally. As a result of this investigation, a preliminary structure for a generic phytoplankton model is delivered in the last section of this paper. This model includes a mechanistic representation of photosynthesis/photoinhibition based on photosystem II status, as well as new formulations for photoacclimation and dissolved organic matter exudation processes. The model sensitivity analysis with regard to its parameters and a comparison with chemostat experimental data are presented in a companion paper [Baklouti, M., Faure, V., Pawlowski, L., Sciandra, A., 2006. Investigation and sensitivity analysis of a mechanistic phytoplankton model implemented in a new modular numerical tool (Eco3M) dedicated to biogeochemical modelling. Progress in Oceanography]. Finally, this new class of multi-element, multi-species phytoplankton models will provide the basis for future studies on ecosystem modelling. (C) 2006 Elsevier Ltd. All rights reserved