Seminars on marine ecosystem modelling @ the Nansen Center

The FortHjort seminar on marine ecosystem modelling will take place at the Nansen Center.

Date & Time: Thursday 18.02.2016,  14:00 - 15:00
Location: Nansen Centre (in the cinema), Thormøhlens gate 47

The seminar comprises of the following three lectures:

Tatiana Tsagaraki, UiB: Modification of a 3D ecosystem model to study plankton community response to nutrient enrichment.
Abstract:The suitability of a 3D ecosystem model to study effects of nutrient enrichment from a fixed point source (fish farm) was studied in the oligotrophic eastern Mediterranean Sea. The focus was on the plankton community response from bacteria to mesozooplankton. Field results showed that the community response was maximized at intermediate distances from the fish farm and that all groups studied were affected by the point source, including Copepods. The field results were used to modify an ERSEM based biogeochemical model, where nutrient inputs to the system from the farm were added. The current velocity and direction were taken into account using drifters while model resolution was downscaled to 50m to better simulate the study area. Model results reflected the plankton response to the nutrient enrichment and simulation results identified changes in the food web structure close to the point source.

Mohamad Gharamti, NERSC: Tuning ocean biogeochemical parameters using efficient ensemble DA techniques: Application to the station M.
Given the recent international focus on developing new data assimilation systems for biological models, we present in this study the application of newly developed state-parameters estimation tool to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors.
The data assimilation scheme is based on the original Ensemble Kalman Filter (EnKF) algorithm and further applies a one-step-ahead smoothing to the state variables. Additionally, the update step of the filter is performed after transforming the state variables and parameters to a Gaussian space using different anamorphosis formulations. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. We test the performance of the new smoothing-based scheme against the standard EnKF in a one-dimensional configuration of the GOTM-NORWECOM system in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface chlorophyll-a measurements from Mike weather station (66° N, 2° E) to estimate different biological parameters of phytoplankton and zooplankton. We analyze the performance of the filters in terms of complexity and accuracy of the state and parameters estimates.

Cecilie Hansen, IMR: Evaluating biological indicators for trends in the Barents Sea using an end-to-end model (Atlantis)
The value of indicators as a way to monitor ecosystems are widely discussed and disagreed about. In our areas, the management plans for the Barents Seas have until recently been operating with totally 40 indicators that are being used to describe the state of the ecosystem through climate, environment and biota. Of these, 21 biological indicators can be calculated from the Atlantis ecosystem model, but what can they actually tell us and how sensitive are they to changes in e.g. fishing pressure?

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