Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 738

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Effect of increasing CO 2 on the terrestrial carbon cycle

Open access
Schimel, David, Stephens, Britton B., Fisher, Joshua B.·2015·Proceedings of the National Academy of Sciences

Abstract

Significance: Feedbacks from terrestrial ecosystems to atmospheric CO 2 concentrations contribute the second-largest uncertainty to projections of future climate. These feedbacks, acting over huge regions and long periods of time, are extraordinarily difficult to observe and quantify directly. We evaluated in situ, atmospheric, and simulation estimates of the effect of CO 2 on carbon storage, subject to mass balance constraints. Multiple lines of evidence suggest significant tropical uptake for CO 2 , approximately balancing net deforestation and confirming a substantial negative global feedback to atmospheric CO 2 and climate. This reconciles two approaches that have previously produced contradictory results. We provide a consistent explanation of the impacts of CO 2 on terrestrial carbon across the 12 orders of magnitude between plant stomata and the global carbon cycle.

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 · 10.1073/pnas.1407302112

Cites

5 of 5 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 5 references

Cited by

See all 738

Metadata

Authors
Schimel, D., Stephens, B. B., & Fisher, J. B.
Venue
Proceedings of the National Academy of Sciences
Published
2014-12-29
Volume
112
Issue
2
Pages
436-441
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2161324066
Cited by
738
References
5
FWCI
27.41
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: Effect of increasing CO 2 on the terrestrial carbon cycle. https://app.cochat.ai/papers/10.1073/pnas.1407302112
The paper
Schimel, D., Stephens, B. B., & Fisher, J. B. (2015). Effect of increasing CO 2 on the terrestrial carbon cycle. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1407302112

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.