The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.
A model‐data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis
Open accessAbstract
Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low‐temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf‐to‐canopy scaling and better values of model parameters that control the maximum potential GPP, such as εmax (LUE), Vcmax (unstressed Rubisco catalytic capacity) or Jmax (the maximum electron transport rate).
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
A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species
Farquhar, G. D., von Caemmerer, S., & Berry, J. A. (1980) · Planta · doi:10.1007/bf00386231 · Cited by 8,796
Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves
von Caemmerer, S., & Farquhar, G. D. (1981) · Planta · doi:10.1007/bf00384257 · Cited by 4,696
Baldocchi, D., Falge, E. M., Gu, L., Olson, R., Hollinger, D. Y., Running, S. W., Anthoni, P. M., Bernhofer, C., Davis, K. J., Evans, R., et al. (2001) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(2001)082<2415:fantts>2.3.co;2 · Cited by 3,787
Self-citationSitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., et al. (2003) · Global Change Biology · doi:10.1046/j.1365-2486.2003.00569.x · Cited by 3,238
Terrestrial ecosystem production: A process model based on global satellite and surface data
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M., Mooney, H. A., & Klooster, S. A. (1993) · Global Biogeochemical Cycles · doi:10.1029/93gb02725 · Cited by 2,986
Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rödenbeck, C., Arain, M. A., Baldocchi, D., Bonan, G. B., et al. (2010) · Science · doi:10.1126/science.1184984 · Cited by 2,831
Self-citationSolar Radiation and Productivity in Tropical Ecosystems
Monteith, J. L. (1972) · The Journal of Applied Ecology · doi:10.2307/2401901 · Cited by 2,724
Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009
Zhao, M., & Running, S. W. (2010) · Science · doi:10.1126/science.1192666 · Cited by 2,674
TRY – a global database of plant traits
KATTGE, J., DÍAZ, S., LAVOREL, S., PRENTICE, I. C., LEADLEY, P., BÖNISCH, G., GARNIER, E., WESTOBY, M., REICH, P. B., WRIGHT, I. J., et al. (2011) · Global Change Biology · doi:10.1111/j.1365-2486.2011.02451.x · Cited by 2,638
Self-citationDevelopment of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data
Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, Z., Yang, L., & Merchant, J. W. (2000) · International Journal of Remote Sensing · doi:10.1080/014311600210191 · Cited by 2,580
Cited by
Wei, Y., Liu, S., Huntzinger, D. N., Michalak, A. M., Viovy, N., Post, W. M., Schwalm, C. R., Schaefer, K., Jacobson, A. R., Lu, C., et al. (2014) · Geoscientific Model Development · doi:10.5194/gmd-7-2875-2014 · Cited by 271
Self-citationZhang, Y., Guanter, L., Berry, J. A., van der Tol, C., Yang, X., Tang, J., & Zhang, F. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.10.016 · Cited by 266
Ozone and haze pollution weakens net primary productivity in China
Yue, X., Unger, N., Harper, K., Xia, X., Liao, H., Zhu, T., Xiao, J., Feng, Z., & Li, J. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-6073-2017 · Cited by 258
Joiner, J., Yoshida, Y., Zhang, Y., Duveiller, G., Jung, M., Lyapustin, A., Wang, Y., & Tucker, C. J. (2018) · Remote Sensing · doi:10.3390/rs10091346 · Cited by 258
Metadata
- Authors
- Schaefer, K., Schwalm, C. R., Williams, C., Arain, M. A., Barr, A., Chen, J. M., Davis, K. J., Dimitrov, D., Hilton, T. W., Hollinger, D. Y., Humphreys, E., Poulter, B., Raczka, B. M., Richardson, A. D., Sahoo, A., Thornton, P., Vargas, R., Verbeeck, H., Anderson, R., Baker, I., Black, T. A., Bolstad, P., Chen, J., Curtis, P. S., Desai, A. R., Dietze, M., Dragoni, D., Gough, C., Grant, R. F., Gu, L., Jain, A., Kucharik, C., Law, B., Liu, S., Lokipitiya, E., Margolis, H. A., Matamala, R., McCaughey, J. H., Monson, R., Munger, J. W., Oechel, W., Peng, C., Price, D. T., Ricciuto, D., Riley, W. J., Roulet, N., Tian, H., Tonitto, C., Torn, M., Weng, E., & Zhou, X.
- Venue
- Journal of Geophysical Research: Biogeosciences
- Publisher
- American Geophysical Union (AGU)
- Published
- 2012-07-19
- Volume
- 117
- Issue
- G3
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W2150922151
- Cited by
- 355
- References
- 92
- FWCI
- 27.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: A model‐data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis. https://app.cochat.ai/papers/10.1029/2012jg001960
- The paper
- Schaefer, K., Schwalm, C. R., Williams, C., Arain, M. A., Barr, A., Chen, J. M., Davis, K. J., Dimitrov, D., Hilton, T. W., Hollinger, D. Y., Humphreys, E., Poulter, B., Raczka, B. M., Richardson, A. D., Sahoo, A., Thornton, P., Vargas, R., Verbeeck, H., Anderson, R., . . . Zhou, X. (2012). A model‐data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis. Journal of Geophysical Research: Biogeosciences. https://doi.org/10.1029/2012jg001960
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.