Evidence map›Paper›PMID 42591495›Full record

ArticleFrontiers in microbiology2026

Microbial network and its relationship with plants reflect the restoration of grasslands during a five-year period.

Minghui Zhang, Chunnan Fan, Jinping Zheng, Qiang Liu, Fang Yu

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. 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

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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

5 authors.

Minghui ZhangForestry College, Beihua University, Jilin, China.
Chunnan FanForestry College, Beihua University, Jilin, China.
Jinping ZhengForestry College, Beihua University, Jilin, China.
Qiang LiuForestry College, Beihua University, Jilin, China.
Fang YuForestry College, Beihua University, Jilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The ecological restoration of degraded grassland has been widely studied in terms of plants, soil, and microbes. The microbial network and its relationship with plants are essential indicators of the grassland restoration process. Across restoration statuses, how the microbial network affects plant-microbe interactions and reflects grassland restoration remains unclear. Methods: We examined changes in soil microbial networks, plant biomass, and soil properties across early, moderate, and late restoration, as well as stable community status, over a 5-year restoration period. We calculated the grassland restoration index (GRI) to evaluate the restoration process and constructed microbial co-occurrence networks to assess changes in microbial communities over 5 years. Results: Our results showed the dominant species shifting from Kochia sieversiana to Chloris virgata in early restoration status, and the bacterial network complexity fluctuated over the 5 years, indicating a restoration in early restoration status. In moderate and late restoration statuses, the complexity of bacterial networks gradually increased, suggesting the increased recovery potential in the grassland. However, the GRI showed that the moderate and late restoration statuses did not progress to the next successional status over the 5 years. Moreover, the random forest regression model revealed that high soil pH may limit the restoration process by regulating soil microbial networks. Conclusion: Our study illuminates the signaling roles of soil microbial networks in the restoration process and suggests that moderate and late restoration statuses may take longer to recover to a stable community status. We emphasized that soil pH may be a key constraint in the different restoration statuses, warranting further experimental testing of pH regulation as a restoration intervention.

Indexed as

grasslandmicrobe-plant interactionsmicrobial networkrestoration processsoil properties

Identifiers

PMID42591495
PMCPMC13462077

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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.