Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model
Open accessAbstract
A global three‐dimensional marine ecosystem model with several key phytoplankton functional groups, multiple limiting nutrients, explicit iron cycling, and a mineral ballast/organic matter parameterization is run within a global ocean circulation model. The coupled biogeochemistry/ecosystem/circulation (BEC) model reproduces known basin‐scale patterns of primary and export production, biogenic silica production, calcification, chlorophyll, macronutrient and dissolved iron concentrations. The model captures observed high nitrate, low chlorophyll (HNLC) conditions in the Southern Ocean, subarctic and equatorial Pacific. Spatial distributions of nitrogen fixation are in general agreement with field data, with total N‐fixation of 55 Tg N. Diazotrophs directly account for a small fraction of primary production (0.5%) but indirectly support 10% of primary production and 8% of sinking particulate organic carbon (POC) export. Diatoms disproportionately contribute to export of POC out of surface waters, but CaCO 3 from the coccolithophores is the key driver of POC flux to the deep ocean in the model. An iron source from shallow ocean sediments is found critical in preventing iron limitation in shelf regions, most notably in the Arctic Ocean, but has a relatively localized impact. In contrast, global‐scale primary production, export production, and nitrogen fixation are all sensitive to variations in atmospheric mineral dust inputs. The residence time for dissolved iron in the upper ocean is estimated to be a few years to a decade. Most of the iron utilized by phytoplankton is from subsurface sources supplied by mixing, entrainment, and ocean circulation. However, owing to the short residence time of iron in the upper ocean, this subsurface iron pool is critically dependent on continual replenishment from atmospheric dust deposition and, to a lesser extent, lateral transport from shelf regions.
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Doney, S. C., Lima, I. D., Lindsay, K., et al. (2001) · Oceanography · doi:10.5670/oceanog.2001.10 · Cited by 41 · see citing works
Self-citationEquatorial nutrient trapping in biogeochemical ocean models: The role of advection numerics
Oschlies, A. (2000) · Global Biogeochemical Cycles · doi:10.1029/1999gb001217 · Cited by 34 · see citing works
Workshop highlights iron dynamics in ocean carbon cycle
Johnson, K. S., Moore, J. K., & Smith, W. O. J. (2002) · Eos · doi:10.1029/2002eo000338 · Cited by 12 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 6
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Cited by
Sorted by citations
Ocean Acidification: The Other CO <sub>2</sub> Problem
Doney, S. C., Fabry, V. J., Feely, R. A., & Kleypas, J. A. (2009) · Annual Review of Marine Science · doi:10.1146/annurev.marine.010908.163834 · Cited by 4,173 · see citing works
Self-citationModeling Diverse Communities of Marine Microbes
Follows, M. J., & Dutkiewicz, S. (2011) · Annual Review of Marine Science · doi:10.1146/annurev-marine-120709-142848 · Cited by 307 · see citing works
Jin, X., Gruber, N., Dunne, J. P., Sarmiento, J. L., & Armstrong, R. A. (2006) · Global Biogeochemical Cycles · doi:10.1029/2005gb002532 · Cited by 250 · see citing works
The Impact of Whaling on the Ocean Carbon Cycle: Why Bigger Was Better
Pershing, A. J., Christensen, L. B., Record, N. R., Sherwood, G. D., & Stetson, P. B. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012444 · Cited by 170 · see citing works
Marine wild-capture fisheries after nuclear war
Scherrer, K. J. N., Harrison, C. S., Heneghan, R. F., Galbraith, E., Bardeen, C. G., Coupe, J., Jägermeyr, J., Lovenduski, N. S., Luna, A., Robock, A., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2008256117 · Cited by 59 · see citing works
- Authors
- Moore, J. K., Doney, S. C., & Lindsay, K.
- Affiliations
- University of California, Irvine (US)
- Woods Hole Oceanographic Institution (US)
- NSF National Center for Atmospheric Research (US)
- Venue
- Global Biogeochemical Cycles
- Publisher
- American Geophysical Union (AGU)
- Published
- 2004-12
- Volume
- 18
- Issue
- 4
- ISSN
- 0886-6236 (ISSN-L)
- 1944-9224
- OpenAlex
- W2148343249
- Semantic Scholar
- 2e684eb0d11254cd305709493e75dccabef3588e
- Cited by
- 889
- References
- 108
- Citations by year
- 2026: 23 · 2025: 27 · 2024: 40 · 2023: 51 · 2022: 66 · 2021: 67 · 2020: 43 · 2019: 35 · 2018: 43 · 2017: 40 · 2016: 43 · 2015: 51 · 2014: 36 · 2013: 55 · 2012: 46
- FWCI
- 18.32
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Global Biogeochemical Cycles (publishedVersion)
- Open Access Server of the Woods Hole Scientific Community (Woods Hole Scientific Community) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- National Science Foundation
- National Center for Atmospheric Research
- Woods Hole Oceanographic Institution
- Goddard Space Flight Center
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Marine and coastal ecosystems
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- iron cycling, phytoplankton functional groups, nitrogen fixation, nitrogen-fixing bacteria, particulate organic carbon export, biogenic silica, coccolithophores, calcification, iron limitation, continental shelf sediments, Southern Ocean, Arctic Ocean, primary production
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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