Evidence map›Paper›PMID 41719334›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Decadal extreme drought reduces alpine subsoil carbon stocks.

Ronglei Zhou, Jinsong Wang, Quancheng Wang, Ning Liu, Chenglong Ye, Jingjing Shi, Mengjie Liu, Zhangwei Gao, Houkun Chu, Zhenrui Zhang and 5 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Decadal extreme drought reduces alpine subsoil carbon stocks.Proceedings of the National Academy of Sciences of the United States of America · 2026
    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

15 authors.

Ronglei ZhouKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Jinsong WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-3425-7387
Quancheng WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Ning LiuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0009-0000-0857-7574
Chenglong YeCollege of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China.
Jingjing ShiCollege of Forestry, Beijing Forestry University, Beijing 100083, China.
Mengjie LiuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Zhangwei GaoCollege of Juncao Science and Ecology, Fujian Agriculture and Forestry University, Fuzhou 350000, China.
Houkun ChuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Zhenrui ZhangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Bin NiuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Song WangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Ruiyang ZhangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Dashuan TianKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Shuli NiuKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-2394-2864

Funding

MOST | National Natural Science Foundation of China (NSFC) 32241035MOST | National Natural Science Foundation of China (NSFC) 32588202National Key and Technology R&D Program of China 2022YFF0802102
6 · The paper itself

Abstract

Grassland soil organic carbon (SOC) stocks are increasingly vulnerable to intensified drought. Yet, how long-term, especially extreme, drought affects these C reserves across soil profiles remains unresolved. Here, we present the response of SOC stocks at various depths (0 to 60 cm) using an experiment involving a 10-year drought gradient (P, 1/2 P, 1/4 P, and 1/12 P, where P is ambient precipitation) in an alpine grassland. We found that extreme drought (1/12 P) caused significant SOC losses in the subsoil, whereas mild to moderate droughts had no significant effects on SOC at any depth. Under extreme drought, SOC stocks declined by 27% in the 20 to 30 cm layer and by 37% in the 30 to 40 cm layer, while no significant changes were observed in the topsoil (0 to 20 cm) and the deeper layer (40 to 60 cm). Subsoil C losses were primarily driven by reductions in mineral-associated organic C (MAOC) rather than particulate organic C. Multiyear extreme drought disrupted soil-microbe-mineral interactions, as indicated by reductions in soil nitrogen availability, microbial biomass, carbon use efficiency, and mineral-binding agents. These changes collectively undermined the formation and stabilization of MAOC. Our findings suggest that prolonged extreme drought can weaken subsoil C storage and stability, highlighting the need to incorporate subsoil processes into Earth System Models to better predict soil C-climate feedback under future drought scenarios.

Indexed as

extreme droughtmineral-associated organic CSOC stockssubsoil

Identifiers

PMID41719334
PMCPMC12933107

What OpenQuestion holds

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LicenceCC BY
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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.