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Cited by 461

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Biogenic Carbon Cycling in the Upper Ocean: Effects of Microbial Respiration

Rivkin, Richard B., Legendre, Louis·2001·Science

Abstract

Food-web processes are important controls of oceanic biogenic carbon flux and ocean-atmosphere carbon dioxide exchange. Two key controlling parameters are the growth efficiencies of the principal trophic components and the rate of carbon remineralization. We report that bacterial growth efficiency is an inverse function of temperature. This relationship permits bacterial respiration in the euphotic zone to be computed from temperature and bacterial production. Using the temperature-growth efficiency relationship, we show that bacterial respiration generally accounts for most community respiration. This implies that a larger fraction of assimilated carbon is respired at low than at high latitudes, so a greater proportion of production can be exported in polar than in tropical regions. Because bacterial production is also a function of temperature, it should be possible to compute euphotic zone heterotrophic respiration at large scales using remotely sensed information.

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Metadata

Authors
Rivkin, R. B., & Legendre, L.
Venue
Science
Published
2001-03-23
Volume
291
Issue
5512
Pages
2398-2400
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1965801259
Cited by
461
References
20
FWCI
14.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Biogenic Carbon Cycling in the Upper Ocean: Effects of Microbial Respiration. https://app.cochat.ai/papers/10.1126/science.291.5512.2398
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Rivkin, R. B., & Legendre, L. (2001). Biogenic Carbon Cycling in the Upper Ocean: Effects of Microbial Respiration. Science. https://doi.org/10.1126/science.291.5512.2398

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.