Evidence map›Paper›PMID 37612426›Full record

ArticleISME communications2023

Integrating microbial community properties, biomass and necromass to predict cropland soil organic carbon.

Chao Wang, Xu Wang, Yang Zhang, Ember Morrissey, Yue Liu, Lifei Sun, Lingrui Qu, Changpeng Sang, Hong Zhang, Guochen Li and 2 more

Abstract read
In one paragraph

Article in ISME communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Climate warming reduces soil gaseous nitrogen losses in a temperate forest.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Article
  9. Suitable Planting Area Prediction for TwoPlants (Basel, Switzerland) · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. 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

12 authors.

Chao WangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. cwang@iae.ac.cn.ORCID http://orcid.org/0000-0002-5756-7505
Xu WangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Yang ZhangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Ember MorrisseyDivision of Plant and Soil Sciences, West Virginia University, Morgantown, 26506, USA.ORCID http://orcid.org/0000-0002-5810-1096
Yue LiuCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Lifei SunCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Lingrui QuCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Changpeng SangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Hong ZhangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Guochen LiCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. ligc@iae.ac.cn.ORCID http://orcid.org/0000-0002-0743-8692
Lili ZhangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Yunting FangCAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.ORCID http://orcid.org/0000-0001-7531-546X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Manipulating microorganisms to increase soil organic carbon (SOC) in croplands remains a challenge. Soil microbes are important drivers of SOC sequestration, especially via their necromass accumulation. However, microbial parameters are rarely used to predict cropland SOC stocks, possibly due to uncertainties regarding the relationships between microbial carbon pools, community properties and SOC. Herein we evaluated the microbial community properties (diversity and network complexity), microbial carbon pools (biomass and necromass carbon) and SOC in 468 cropland soils across northeast China. We found that not only microbial necromass carbon but also microbial community properties (diversity and network complexity) and biomass carbon were correlated with SOC. Microbial biomass carbon and diversity played more important role in predicting SOC for maize, while microbial network complexity was more important for rice. Models to predict SOC performed better when the microbial community and microbial carbon pools were included simultaneously. Taken together our results suggest that microbial carbon pools and community properties influence SOC accumulation in croplands, and management practices that improve these microbial parameters may increase cropland SOC levels.

Identifiers

PMID37612426
PMCPMC10447565

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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.