Evidence map›Paper›PMID 42853790›Full record

ArticlePloS one2026

Land use change reshaped soil carbon dynamics in Northern China.

Yuanyuan Tang, Yuchun Yang, Guohong Du, Yanbing Qi

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yuanyuan TangCollege of Resources and Environment, Xichang University, Xichang, Sichuan, China.
Yuchun YangCollege of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, China.
Guohong DuCollege of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, China.
Yanbing QiCollege of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, China.ORCID https://orcid.org/0000-0002-3217-1037

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Northern China has experienced some of the most intensive land use changes globally, yet the consequent impacts on soil carbon dynamics and regional source-sink patterns, particularly the divergent responses of soil organic carbon (SOC) and soil inorganic carbon (SIC), remain poorly quantified. This study examined how land use change reshapes SOC and SIC pools and modulates their sensitivity to environmental drivers. Using nationwide soil survey data from the 1980s and 2010s, we applied random forest models and partial least squares structural equation modeling to disentangle the responces SOC and SIC pools for land use and environmental change. Results revealed that Northern China functioned as a net soil carbon source over the 30-year interval, losing approximately 0.56 Gt of SOC and 0.56 Gt of SIC. Land use type emerged as the dominant control on carbon source-sink patterns. Grassland transitioned into strong carbon sources driven primarily by SIC losses of 1.51 Gt, whereas unutilized land exhibited estimated net carbon gains with apparent SIC accumulation of 2.06 Gt. Beyond altering carbon stocks, land use change reversed regional source-sink patterns and markedly heightened the sensitivity of soil carbon dynamics to environmental changes with explanatory strength increment of 0.11 for SOC and 0.09 for SIC, respectively. Specifically, SOC responded primarily to biotic drivers such as vegetation productivity, while SIC exhibited tighter coupling with increasing atmospheric CO2 fluctuations. The main contribution of this study is revealing how SOC and SIC respond differently to environmental drivers following land use change. Practically, these results indicate that regional carbon management strategies must fully consider land use change effects and explicitly include soil inorganic carbon in carbon neutrality accounting frameworks.

Indexed as

CarbonSoilChinaEcosystemCarbonSoil

Identifiers

PMID42853790
PMCPMC13652200

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.