Evidence map›Paper›PMID 42103779›Full record

ArticleScientific data2026

A global dataset of soil organic carbon accumulation rate in coastal ecosystems.

Lihua Pang, Tianping Xu, Zhan Hu, Baoshan Cui, Na Zhang, Liming Xue, Shuai Liu, Shoufeng Chi, Zezheng Liu

Abstract read
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Lihua PangSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Tianping XuSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Zhan HuSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Baoshan CuiSchool of Environment, State Key Laboratory of Wetland Conservation and Restoration, Beijing Normal University, Beijing, 100875, China.
Na ZhangSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Liming XueSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Shuai LiuSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Shoufeng ChiYantai Marine Environment Monitoring and Forecasting Center, Shandong, China.
Zezheng LiuSchool of Marine Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China. liuzzh23@mail.sysu.edu.cn.

Funding

National Natural Science Foundation of China 42306187
6 · The paper itself

Abstract

Coastal ecosystems are increasingly recognized as a crucial nature-based climate solution due to their remarkable capacity for carbon sequestration. However, the spatial distribution and quantification of soil organic carbon accumulation rate (OCAR) at the global scale remain limited. Here, we assemble an open global dataset of soil OCAR in coastal ecosystems from a systematic literature review. The dataset comprises 8,998 field observations from 247 peer-reviewed articles, encompassing four distinct ecosystem types (mangroves, salt marshes, seagrasses, and tidal flats). Furthermore, the dataset includes publication details of the source articles, geographical and ecological attributes of the sampling sites, and information for each observation. The dataset can be employed to more precisely quantify and map global coastal soil carbon sequestration capacity, enabling the development of global spatiotemporal prediction models. This dataset serves as a vital scientific foundation for informing management strategies of coastal ecosystems and guiding future carbon credit markets.

Identifiers

PMID42103779
PMCPMC13369862

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Registered trials

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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.