Li, Na, Somes, Christopher J. , Landolfi, Angela , Chien, Chia-Te , Pahlow, Markus and Oschlies, Andreas (2024) Global impact of benthic denitrification on marine N2 fixation and primary production simulated by a variable-stoichiometry Earth system model. Biogeosciences (BG), 21 (19). pp. 4361-4380. DOI 10.5194/bg-21-4361-2024.

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Abstract

Nitrogen (N) is a crucial limiting nutrient for phytoplankton growth in the ocean. The main source of bioavailable N in the ocean is delivered by N2-fixing diazotrophs in the surface layer. Since field observations of N2 fixation are spatially and temporally sparse, the fundamental processes and mechanisms controlling N2 fixation are not well understood and constrained. Here, we implement benthic denitrification in an Earth system model (ESM) of intermediate complexity (UVic ESCM 2.9) coupled to an optimality-based plankton–ecosystem model (OPEM v1.1). Benthic denitrification occurs mostly in coastal upwelling regions and on shallow continental shelves, and it is the largest N loss process in the global ocean. We calibrate our model against three different combinations of observed Chl, , , O2, and . The inclusion of N* provides a powerful constraint on biogeochemical model behavior. Our new model version including benthic denitrification simulates higher global rates of N2 fixation with a more realistic distribution extending to higher latitudes that are supported by independent estimates based on geochemical data. The volume and water-column denitrification rates of the oxygen-deficient zone (ODZ) are reduced in the new version, indicating that including benthic denitrification may improve global biogeochemical models that commonly overestimate anoxic zones. With the improved representation of the ocean N cycle, our new model configuration also yields better global net primary production (NPP) when compared to the independent datasets not included in the calibration. Benthic denitrification plays an important role shaping N2 fixation and NPP throughout the global ocean in our model, and it should be considered when evaluating and predicting their response to environmental change.

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