CoChat
Sign Up
Cited by 504Plant Water Relations and Carbon DynamicsRemote Sensing in AgricultureLand Use and Ecosystem Services

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink

Open access
Chen, Jing M., Ju, Weimin, Ciais, Philippe, Viovy, Nicolas, Liu, Ronggao, Liu, Yang, Lu, Xuehe·2019·Nature Communications
DOI 10.1038/s41467-019-12257-8PMC PMC6751163
Open this paper in CoChat — free accountOpen PDF

Abstract

Abstract Satellite observations show that leaf area index (LAI) has increased globally since 1981, but the impact of this vegetation structural change on the global terrestrial carbon cycle has not been systematically evaluated. Through process-based diagnostic ecosystem modeling, we find that the increase in LAI alone was responsible for 12.4% of the accumulated terrestrial carbon sink (95 ± 5 Pg C) from 1981 to 2016, whereas other drivers of CO 2 fertilization, nitrogen deposition, and climate change (temperature, radiation, and precipitation) contributed to 47.0%, 1.1%, and −28.6% of the sink, respectively. The legacy effects of past changes in these drivers prior to 1981 are responsible for the remaining 65.5% of the accumulated sink from 1981 to 2016. These results refine the attribution of the land sink to the various drivers and would help constrain prognostic models that often have large uncertainties in simulating changes in vegetation and their impacts on 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 · 10.1038/s41467-019-12257-8

Cites

49 of 49 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Global map indicating the trend of LAI from 1981 to 2016. The gray color indicates non-vegetated areas and the white color denotes that the trend is statistically insignificant (p > 0.05). Positive values indicate increasing trends of growing season mean LAI and vice versa
Fig. 1 Global map indicating the trend of LAI from 1981 to 2016. The gray color indicates non-vegetated areas and the white color denotes that the trend is statistically insignificant (p > 0.05). Positive values indicate increasing trends of growing season mean LAI and vice versaCC BY · PubMed Central
Fig. 2 Comparison of the simulated annual land sink (NEP) by BEPS and the residual land sink (RLS) estimated by the Global Carbon Project. The pink red error bars are the SDs of the annual land sink simulated using three different LAI datasets. The solid red line indicates the accumulated carbon sink simulated using three LAI datasets. For the accumulated simulated land sink* (light solid blue line), pixels with >20% areal changes in short vegetation or tree canopy are excluded in the accumulation. For the accumulated simulated land sink** (dashed red line), pixels with >30% changes are excluded. The solid dark line indicates the accumulated residual land sink estimated by the Global Carbon Project. The solid blue line is the mean of accumulated land sinks simulated by 15 TRENDY models, and the shaded gray area represents its uncertainty (mean ± SD). The shaded light yellow area represents the range of accumulated land sinks simulated using three different LAI datasets
Fig. 2 Comparison of the simulated annual land sink (NEP) by BEPS and the residual land sink (RLS) estimated by the Global Carbon Project. The pink red error bars are the SDs of the annual land sink simulated using three different LAI datasets. The solid red line indicates the accumulated carbon sink simulated using three LAI datasets. For the accumulated simulated land sink* (light solid blue line), pixels with >20% areal changes in short vegetation or tree canopy are excluded in the accumulation. For the accumulated simulated land sink** (dashed red line), pixels with >30% changes are excluded. The solid dark line indicates the accumulated residual land sink estimated by the Global Carbon Project. The solid blue line is the mean of accumulated land sinks simulated by 15 TRENDY models, and the shaded gray area represents its uncertainty (mean ± SD). The shaded light yellow area represents the range of accumulated land sinks simulated using three different LAI datasetsCC BY · PubMed Central
Fig. 3 The accumulated terrestrial carbon sink from 1981 to 2016, after subtracting the baseline sink of 62.1 Pg C due to long-term changes (legacy effects). Through numerical experiments, the variations of the accumulated sink with time due to the various drivers are calculated, showing that CO2 fertilization (without LAI changes), LAI, nitrogen deposition, and climate are responsible for the sinks of 44.6, 11.7, 1.1, and −27.1 Pg C over this period, respectively. These sinks contribute 47.0%, 12.4%, 1.1%, and −28.6% to the total accumulated residual land sink (95 ± 5 Pg C) over this period, respectively. For example, the accumulated CO2 enhancement is calculated by holding other drivers at the baseline, while changing CO2 according to the global mean CO2 data
Fig. 3 The accumulated terrestrial carbon sink from 1981 to 2016, after subtracting the baseline sink of 62.1 Pg C due to long-term changes (legacy effects). Through numerical experiments, the variations of the accumulated sink with time due to the various drivers are calculated, showing that CO2 fertilization (without LAI changes), LAI, nitrogen deposition, and climate are responsible for the sinks of 44.6, 11.7, 1.1, and −27.1 Pg C over this period, respectively. These sinks contribute 47.0%, 12.4%, 1.1%, and −28.6% to the total accumulated residual land sink (95 ± 5 Pg C) over this period, respectively. For example, the accumulated CO2 enhancement is calculated by holding other drivers at the baseline, while changing CO2 according to the global mean CO2 dataCC BY · PubMed Central
Fig. 4 Attribution of the global land sink to various factors by region averaged over the period from 1981 to 2016. The values shown are regional and global totals of mean land sinks simulated with an individual diver (CO2, LAI, nitrogen deposition, and climate) changing historically and other factors being remained temporally unchanged minus the lase sinks due to long-term changes (legacy effects)
Fig. 4 Attribution of the global land sink to various factors by region averaged over the period from 1981 to 2016. The values shown are regional and global totals of mean land sinks simulated with an individual diver (CO2, LAI, nitrogen deposition, and climate) changing historically and other factors being remained temporally unchanged minus the lase sinks due to long-term changes (legacy effects)CC BY · PubMed Central

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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 49 references

Research works printed but not linked: 1

  1. Chen, J. M. in Comprehensive Remote Sensing, Vol. 3 (ed. Liang, S.) Pages 53–77, ISBN 9780128032213, https://doi.org/10.1016/B978-0-12-409548-9.10540-82018 (Elsevier, Oxford, 2017). · DOI

Cited by

Sorted by citations

Items 401–500 of 504

Related

See all

Metadata

Authors
Chen, J. M., Ju, W., Ciais, P., Viovy, N., Liu, R., Liu, Y., & Lu, X.
Affiliations
  • University of Toronto (CA)
  • Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN)
  • Centre National de la Recherche Scientifique (FR)
  • Chinese Academy of Sciences (CN)
  • Nanjing University (CN)
Corresponding author
Ju, Weimin
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-09-18
Volume
10
Issue
1
Pages
4259-4259
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-019-12257-8
PMC
PMC6751163
OpenAlex
W2973497171
Cited by
492
References
49
Citations by year
2026: 50 · 2025: 89 · 2024: 119 · 2023: 93 · 2022: 75 · 2021: 41 · 2020: 22 · 2019: 3
FWCI
18.14
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
National Key R&D Program of China
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
Keywords
terrestrial carbon sink, leaf area index, CO2 fertilization, nitrogen deposition, legacy effects, carbon cycle, satellite remote sensing of vegetation, ecosystem modeling

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