Evidence map›Paper›PMID 41189012›Full record

ArticleEnvironmental microbiology reports2025

Ecological Modules Link Soil Aggregate Stability, Chemical Properties and Fungal Communities Under Plant Species-Based Revegetation.

Zijian Ding, Jiahuan Li, Long Bai

Abstract read
In one paragraph

Article in Environmental microbiology reports, 2025. 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

3 authors.

Zijian DingCollege of Horticulture, Shenyang Agricultural University, Shenyang, China.ORCID https://orcid.org/0009-0006-6996-8564
Jiahuan LiCollege of Horticulture, Shenyang Agricultural University, Shenyang, China.ORCID https://orcid.org/0000-0003-4191-6683
Long BaiCollege of Horticulture, Shenyang Agricultural University, Shenyang, China.ORCID https://orcid.org/0000-0003-0185-6030

Funding

Shenyang Agricultural University X2021012The Educational Department of Liaoning Province LJKMZ20221053
6 · The paper itself

Abstract

The establishment of native grassland species is widely implemented on abandoned land as a strategy to restore degraded soils. However, its effects on soil properties are highly species-specific, as plant-driven physicochemical changes subsequently reshape microbial community structure. The linkages between soil physicochemical properties and microbial communities following native grassland establishment remain poorly understood. To address this knowledge gap, we examined the effects of 11 native grassland species on soil physicochemical properties and fungal community structure. Using co-occurrence network analysis, we elucidate how plants drive fungal community reorganisation through soil-mediated trophic pathways. The results showed that soil aggregate stability, chemical properties, and fungal communities differed significantly among the 11 species. Soil chemical properties, such as pH and EC, correlated with symbiotic fungi dominated modules; both soil aggregate stability and chemical properties were linked to pathogenic fungi dominated modules, while saprophytic fungi dominated modules displayed no linkage to either soil aggregate stability or chemical properties. These findings establish that fungal trophic modes govern species-dependent restoration outcomes via modular soil-microbe linkages, thereby offering predictive frameworks for species-specific management of abandoned soils.

Indexed as

FungiMycobiomePlantsSoilSoil MicrobiologyEcosystemGrasslandSoilfungal communitygrassland speciesmicrobial networksoil aggregate stabilitysoil chemical propertiestrophic mode

Identifiers

PMID41189012
PMCPMC12586355

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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.