Evidence map›Paper›PMID 40804442›Full record

ArticleScientific reports2025

Assessing the potential for carbon storage enhancement in forests of Xinjiang Uygur autonomous region, China.

Zhizhong Chen, Mei Zan, Jingjing Kong

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
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 authors.

Zhizhong Chen *School of Geographic Science and Tourism, Xinjiang Normal University, Ürümqi, China.
Mei Zan *School of Geographic Science and Tourism, Xinjiang Normal University, Ürümqi, China. 107622007010058@xjnu.edu.cn.
Jingjing KongSchool of Geographic Science and Tourism, Xinjiang Normal University, Ürümqi, China.

Funding

National Natural Science Foundation of China 42261013Natural Science Foundation of Xinjiang Uygur Autonomous Region 2023D01A49
6 · The paper itself

Abstract

Forest carbon sink potential assessment in arid regions remains a critical challenge for climate change mitigation. This study integrates multi-source remote sensing and forest inventory data to model Xinjiang's forest age and carbon density (2019 baseline: 186.76 Mg/hm

Indexed as

Carbon sink potentialCarbon stockEconomic costForest tree height in xinjiangImpact factorsPredictive modelling

Identifiers

PMID40804442
PMCPMC12350637

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.