Assimilation experiments with data from the Bermuda Atlantic Time-series Study (BATS, 1989¯1993) were performed with a simple mixed-layer ecosystem model of dissolvedinorganic nitrogen (N), phytoplankton (P) and herbivorous zooplankton (H). Our aim is to optimize the biological model parameters, such that the misfits between model results andobservations are minimized. The utilized assimilation method is the variational adjoint technique, starting from a wide range of first-parameter guesses. A twin experiment displayedtwo kinds of solutions, when Gaussian noise was added to the model-generated data. The expected solution refers to the global minimum of the misfit model-data function, whereasthe other solution is biologically implausible and is associated with a local minimum. Experiments with real data showed either bottom-up or top-down controlled ecosystemdynamics, depending on the deep nutrient availability. To confine the solutions, an additional constraint on zooplankton biomass was added to the optimization procedure. Thisinclusion did not produce optimal model results that were consistent with observations. The modelled zooplankton biomass still exceeded the observations. From the model-datadiscrepancies systematic model errors could be determined, in particular when the chlorophyll concentration started to decline before primary production reached its maximum. Adirect comparision of measured 14C-production data with modelled phytoplankton production rates is inadequate at BATS, at least when a constant carbon to nitrogen C : N ratio isassumed for data assimilation.
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