The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Carbon‐based primary productivity modeling with vertically resolved photoacclimation
Open accessAbstract
Net primary production (NPP) is commonly modeled as a function of chlorophyll concentration (Chl), even though it has been long recognized that variability in intracellular chlorophyll content from light acclimation and nutrient stress confounds the relationship between Chl and phytoplankton biomass. It was suggested previously that satellite estimates of backscattering can be related to phytoplankton carbon biomass (C) under conditions of a conserved particle size distribution or a relatively stable relationship between C and total particulate organic carbon. Together, C and Chl can be used to describe physiological state (through variations in Chl:C ratios) and NPP. Here, we fully develop the carbon‐based productivity model (CbPM) to include information on the subsurface light field and nitracline depths to parameterize photoacclimation and nutrient stress throughout the water column. This depth‐resolved approach produces profiles of biological properties (Chl, C, NPP) that are broadly consistent with observations. The CbPM is validated using regional in situ data sets of irradiance‐derived products, phytoplankton chlorophyll:carbon ratios, and measured NPP rates. CbPM‐based distributions of global NPP are significantly different in both space and time from previous Chl‐based estimates because of the distinction between biomass and physiological influences on global Chl fields. The new model yields annual, areally integrated water column production of ∼52 Pg C a −1 for the global oceans.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Photosynthetic rates derived from satellite‐based chlorophyll concentration
Behrenfeld, M. J., & Falkowski, P. G. (1997) · Limnology and Oceanography · doi:10.4319/lo.1997.42.1.0001 · Cited by 2,866
Self-citationA mesoscale phytoplankton bloom in the polar Southern Ocean stimulated by iron fertilization
Boyd, P. W., Watson, A. J., Law, C. S., Abraham, E. R., Trull, T., Murdoch, R., Bakker, D. C. E., Bowie, A. R., Buesseler, K. O., Chang, H., et al. (2000) · Nature · doi:10.1038/35037500 · Cited by 1,612
Ricchiazzi, P., Yang, S., Gautier, C., & Sowle, D. (1998) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1998)079<2101:sarats>2.0.co;2 · Cited by 1,578
An estimate of global primary production in the ocean from satellite radiometer data
Longhurst, A., Sathyendranath, S., Platt, T., & Caverhill, C. (1995) · Journal of Plankton Research · doi:10.1093/plankt/17.6.1245 · Cited by 1,480
Bio‐optical properties of oceanic waters: A reappraisal
Morel, A., & Maritorena, S. (2001) · Journal of Geophysical Research: Oceans · doi:10.1029/2000jc000319 · Cited by 1,184
Carbon‐based ocean productivity and phytoplankton physiology from space
Behrenfeld, M. J., Boss, E., Siegel, D. A., & Shea, D. M. (2005) · Global Biogeochemical Cycles · doi:10.1029/2004gb002299 · Cited by 1,148
Self-citationA dynamic regulatory model of phytoplanktonic acclimation to light, nutrients, and temperature
Geider, R. J., Maclntyre, H. L., & Kana, T. M. (1998) · Limnology and Oceanography · doi:10.4319/lo.1998.43.4.0679 · Cited by 966
Optimization of a semianalytical ocean color model for global-scale applications
Maritorena, S., Siegel, D. A., & Peterson, A. R. (2002) · Applied Optics · doi:10.1364/ao.41.002705 · Cited by 933
Self-citationThe Deep Chlorophyll Maximum: Comparing Vertical Profiles of Chlorophyll a
Cullen, J. J. (1982) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/f82-108 · Cited by 848
MacIntyre, H. L., Kana, T. M., Anning, T., & Geider, R. J. (2002) · Journal of Phycology · doi:10.1046/j.1529-8817.2002.00094.x · Cited by 830
Cited by
Recovery potential of the world's coral reef fishes
MacNeil, M. A., Graham, N. A. J., Cinner, J. E., Wilson, S. K., Williams, I. D., Maina, J., Newman, S., Friedlander, A. M., Jupiter, S., Polunin, N. V. C., et al. (2015) · Nature · doi:10.1038/nature14358 · Cited by 375
Drivers and uncertainties of future global marine primary production in marine ecosystem models
Laufkötter, C., Vogt, M., Gruber, N., Aita-Noguchi, M., Aumont, O., Bopp, L., Buitenhuis, E., Doney, S. C., Dunne, J., Hashioka, T., et al. (2015) · Biogeosciences · doi:10.5194/bg-12-6955-2015 · Cited by 369
Quantifying the Carbon Export and Sequestration Pathways of the Ocean's Biological Carbon Pump
Nowicki, M., DeVries, T., & Siegel, D. A. (2022) · Global Biogeochemical Cycles · doi:10.1029/2021gb007083 · Cited by 317
Self-citationGómez-Letona, M., Ramos, A. G., Coca, J., & Arístegui, J. (2017) · Frontiers in Marine Science · doi:10.3389/fmars.2017.00370 · Cited by 57
Siemer, J. P., Machín, F., González‐Vega, A., Arrieta, J. M., Gutiérrez‐Guerra, M. A., Pérez‐Hernández, M. D., Vélez‐Belchí, P., Hernández‐Guerra, A., & Fraile‐Nuez, E. (2021) · Journal of Geophysical Research: Oceans · doi:10.1029/2021jc017268 · Cited by 50
Metadata
- Authors
- Westberry, T., Behrenfeld, M. J., Siegel, D. A., & Boss, E.
- Venue
- Global Biogeochemical Cycles
- Publisher
- American Geophysical Union (AGU)
- Published
- 2008-06
- Volume
- 22
- Issue
- 2
- ISSN
- 0886-6236 (ISSN-L)
- 1944-9224
- OpenAlex
- W2121131753
- Cited by
- 760
- References
- 53
- FWCI
- 11.68
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Carbon‐based primary productivity modeling with vertically resolved photoacclimation. https://app.cochat.ai/papers/10.1029/2007gb003078
- The paper
- Westberry, T., Behrenfeld, M. J., Siegel, D. A., & Boss, E. (2008). Carbon‐based primary productivity modeling with vertically resolved photoacclimation. Global Biogeochemical Cycles. https://doi.org/10.1029/2007gb003078
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.