Evidence map›Paper›PMID 41454011›Full record

ArticleScientific reports2025

Spatial distributions, driving factors, and future changes of soil organic carbon in China: arid regions vs. humid regions.

Bin Yang, Shihang Zhang, Xiaoguo Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
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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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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

3 authors.

Bin YangKey Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China.
Shihang ZhangKey Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China.
Xiaoguo WangKey Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China. xgwang@imde.ac.cn.

Funding

the National Key Research and Development Program of China 2023YFD1901204the National Natural Science Foundation of China 42171067
6 · The paper itself

Abstract

Soil carbon sequestration is of great significance for achieving China’s 2060 carbon neutrality goal. However, differences in carbon sequestration between arid and humid regions remain unclear. Here, based on the Chinese terrestrial ecosystems carbon density dataset, this study employed the random forest (RF) model to map soil organic carbon density (SOCD) (1 km × 1 km) in arid and humid regions, and assessed the spatial uncertainty. The results indicated: (1) The RF model can explain about 79%-88% of SOCD variation in 2020. (2) The SOCD in arid regions (4.03 kg C m−2 in 0–20 cm soil depth, and 9.84 kg C m−2 in 0–100 cm), were significantly lower than those in humid regions (5.54 kg C m−2, and 12.91 kg C m−2), and had greater spatial heterogeneity. (3) In arid regions, SOCD was mainly driven by mean annual precipitation (MAP), mean annual temperature (MAT), normalized difference vegetation index (NDVI), soil moisture (SM), and land use and land cover (LULC). In humid regions, it was driven by MAT, MAP, elevation, human footprint, and LULC. (4) SOCD exhibited a decreasing trend in arid regions, but exhibited an increasing trend in humid regions under different climate scenarios. The results of this study are of great significance for exploring the response of the SOC pool to climate change in arid and humid regions, identifying vulnerable areas and carbon sinks, and scientifically formulating regional carbon management policies to achieve the goal of carbon neutrality.

Indexed as

Arid regionDigital soil mappingDriving factorsHumid regionSoil organic carbonSpatial distribution

Identifiers

PMID41454011
PMCPMC12820361

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LicenceCC BY-NC-ND
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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.