<p>We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton-ecosystem model (OPEM), implemented in the University of Victoria Earth-System Climate Model (UVic-ESCM), using a Latin-Hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO<sub>3</sub><sup>−</sup>, PO<sub>4</sub><sup>3−</sup>, O<sub>2</sub>, and surface chlorophyll <i>a</i> concentrations. According to our metric the optimal model solutions comprise low rates of global N<sub>2</sub> fixation and denitrification. These two rate estimates turned out to be poorly constrained by the data. For identifying the “best” model solutions we therefore also consider the model’s ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO<sub>3</sub><sup>−</sup> inventory. Global O<sub>2</sub> varies by a factor of two and NO<sub>3</sub><sup>−</sup> by more than a factor of six among all simulations. Remineralisation rate is the most important parameter for O<sub>2</sub>, which is also affected by the subsistence N quota of ordinary phytoplankton (<i>Q</i><sup>N</sup><sub>0,phy</sub>) and zooplankton maximum specific ingestion rate. <i>Q</i><sup>N</sup><sub>0,phy</sub> is revealed as a major determinant of the oceanic NO<sub>3</sub><sup>−</sup> pool. This indicates that unraveling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via <i>Q</i><sup>N</sup><sub>0,phy</sub>, is a prerequisite for understanding the marine nitrogen inventory.