Evidence map›Paper›PMID 35369529›Full record

ArticleFrontiers in microbiology2022

Effect of Alteration in Precipitation Amount on Soil Microbial Community in a Semi-Arid Grassland.

Junyong Li, Girmaye Benti, Dong Wang, Zhongling Yang, Rui Xiao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.1field-weighted citation impact, top 6% of its field
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

7 citing papers in PubMed, 24 citations in OpenAlex.

  1. Plant influence shapesMicrobiology spectrum · 2026
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  6. Effect of Arbuscular Mycorrhiza FungusInternational journal of environmental research and public health · 2023
    Article
  7. 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

5 authors at 1 institution in 1 country.

Junyong LiSchool of Life Sciences, Henan University, Kaifeng, China.
Girmaye BentiSchool of Life Sciences, Henan University, Kaifeng, China.
Dong WangSchool of Life Sciences, Henan University, Kaifeng, China.
Zhongling YangSchool of Life Sciences, Henan University, Kaifeng, China.
Rui XiaoSchool of Life Sciences, Henan University, Kaifeng, China.
Henan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate models predict significant changes in precipitation magnitude in semi-arid grasslands, so it is vital to improve our understanding of how changing precipitation affects microbial communities in grassland ecosystems. Using a long-term field manipulation experiment, we evaluated the responses of microbial communities to a decrease (DP) and an increase (IP) in precipitation on a semi-arid grassland in northern China. The results showed that bacterial species richness decreased significantly with DP but remained stable under IP. Relative abundance of oligotrophic, slow-growing bacterial phyla (e.g., Chloroflexi and Acidobacteria) increased with DP but decreased with IP, whereas the relative abundance of copiotrophic, fast-growing bacterial phyla (e.g., Proteobacteria and Bacteroidetes) decreased with DP but increased with IP. In contrast, diversity, species composition, and relative abundance of different fungal phyla change little with DP or IP. These results indicate a greater sensitivity of bacteria to precipitation changes than fungi, and the sensitivity of bacteria to DP was higher than IP. Our findings are important for understanding soil microbial dynamics under future climate change scenarios.

Indexed as

bacterial and fungal communitieschanging precipitationcommunity compositiondiversitygrasslands

Identifiers

PMID35369529
PMCPMC8969558
OpenAlexW4220953965

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.