Landolfi, Angela; Dietze, Heiner; Koeve, Wolfgang; Oschlies, Andreas (2013): Model results of sensitivity experiments for marine nitrogen cycle in four NetCDF files [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.833155, Supplement to: Landolfi, A et al. (2013): Overlooked runaway feedback in the marine nitrogen cycle: the vicious cycle. Biogeosciences, 10(3), 1351-1363, https://doi.org/10.5194/bg-10-1351-2013
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Abstract:
The marine nitrogen (N) inventory is thought to be stabilized by negative feedback mechanisms that reduce N inventory excursions relative to the more slowly overturning phosphorus inventory. Using a global biogeochemical ocean circulation model we show that negative feedbacks stabilizing the N inventory cannot persist if a close spatial association of N2 fixation and denitrification occurs. In our idealized model experiments, nitrogen deficient waters, generated by denitrification, stimulate local N2 fixation activity. But, because of stoichiometric constraints, the denitrification of newly fixed nitrogen leads to a net loss of N. This can enhance the N deficit, thereby triggering additional fixation in a vicious cycle, ultimately leading to a runaway N loss. To break this vicious cycle, and allow for stabilizing negative feedbacks to occur, inputs of new N need to be spatially decoupled from denitrification. Our idealized model experiments suggest that factors such as iron limitation or dissolved organic matter cycling can promote such decoupling and allow for negative feedbacks that stabilize the N inventory. Conversely, close spatial co-location of N2 fixation and denitrification could lead to net N loss.
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# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
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1 | File format | File format | Landolfi, Angela | modelled | ||
2 | File size | File size | kByte | Landolfi, Angela | modelled | |
3 | Uniform resource locator/link to model result file | URL model | Landolfi, Angela | modelled | ||
4 | Description | Description | Landolfi, Angela | modelled |
License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Size:
16 data points