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Sankar, S; Polimene, L; Marin, L; Menon, NN; Samuelsen, A; Pastres, R; Ciavatta, S (2018)
Publisher: Elsevier
Languages: English
Types: Article
Subjects: ECL, MAR, OCE
Oxygen minimum zones (OMZs) are large, low-oxygen areas in the global oceans. Although OMZs represent a serious threat to ecosystem functioning and services, our capability of modelling the main biogeochemical processes driving OMZ dynamic are still limited. Here we performed a full sensitivity analysis of a complex ecosystem model to rank the most important biogeochemical parameters influencing the simulation of the OMZ at an oligotrophic site in the open Arabian Sea. We applied a one-dimensional configuration of the European Regional Seas Ecosystem Model (ERSEM) - here advanced by including denitrification - coupled with the General Ocean Turbulence Model (GOTM). The coupled model was skilled in simulating the vertical gradients of climatological data of oxygen and nutrients. The sensitivity analysis of the model was carried out in two steps: i) a preliminary Morris screening analysis of 207 ERSEM parameters, which selected the three most influential groups of parameters; and ii) a subsequent Monte Carlo sampling-based analysis for ranking the importance of the 38 parameters within the three selected groups. Overall, the four most important parameters for the simulation of the minimum oxygen concentration were found to be: 1) the cubic half saturation constant for oxygenic control of denitrification; 2) the parameter regulating the fraction of ingested matter excreted by heterotrophic nanoflagellates; 3) the bacterial efficiency at low oxygen levels; and 4) the specific rate of bacterial release of capsular material. Based on these findings, and assuming that the ranking of the model parameters reflects the relevance of the process they characterize, we present a conceptual model describing the most important biogeochemical processes affecting the OMZ at the study site. Our results suggest that including bacteria explicitly in ecosystem models is useful to simulate and predict OMZs, provided that efforts are invested in estimating parameters characterizing the microbial loop in marine ecosystems.

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