Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 355

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 access
Schaefer, Kevin, Schwalm, Christopher R., Williams, Chris, Arain, M. Altaf, Barr, Alan, Chen, Jing M., Davis, Kenneth J., Dimitrov, Dimitre, Hilton, Timothy W., Hollinger, David Y., Humphreys, Elyn, Poulter, Benjamin, Raczka, Brett M., Richardson, Andrew D., Sahoo, Alok, Thornton, Peter, Vargas, Rodrigo, Verbeeck, Hans, Anderson, Ryan, Baker, Ian, Black, T. Andrew, Bolstad, Paul, Chen, Jiquan, Curtis, Peter S., Desai, Ankur R., Dietze, Michael, Dragoni, Danilo, Gough, Christopher, Grant, Robert F., Gu, Lianhong, Jain, Atul, Kucharik, Chris, Law, Beverly, Liu, Shuguang, Lokipitiya, Erandathie, Margolis, Hank A., Matamala, Roser, McCaughey, J. Harry, Monson, Russ, Munger, J. William, Oechel, Walter, Peng, Changhui, Price, David T., Ricciuto, Dan, Riley, William J., Roulet, Nigel, Tian, Hanqin, Tonitto, Christina, Torn, Margaret, Weng, Ensheng, Zhou, Xiaolu·2012·Journal of Geophysical Research: Biogeosciences

Abstract

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1029/2012jg001960

Cites

92 of 92 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 92 references

Cited by

See all 355

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
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.