Evidence map›Paper›PMID 40330726›Full record

ArticleFrontiers in microbiology2025

Soil microbial networks' complexity as a primary driver of multifunctionality in photovoltaic power plants in the northwest region of China.

Liuqing Zhao, Sumeng Xu, Jinmei Zhao, Shujuan Chen, Xiaolong Liu, Xiuyuan Zheng, Xiuhui Wang, Zhao Zhu, Fei Gao, Bingzhe Fu and 1 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. 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
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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

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

11 authors.

Liuqing Zhao *Natural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Sumeng Xu *College of Grassland Agriculture, Northwest A&F University, Xianyang, Shaanxi, China.
Jinmei ZhaoNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Shujuan ChenNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Xiaolong LiuNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Xiuyuan ZhengNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Xiuhui WangNatural Resources Information Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Zhao ZhuNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Fei GaoNatural Resources Assets Statistics and Accounting Center of Ningxia Hui Autonomous Region, Yinchuan, Ningxia, China.
Bingzhe FuCollege of Forestry and Prataculture, Ningxia University, Yinchuan, China.
Shuxia LiCollege of Forestry and Prataculture, Ningxia University, Yinchuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Exploiting photovoltaic power generation as a novel source of clean energy has become increasingly common in recent times. Nevertheless, the impact of photovoltaic power plants (PVs) on soil microbial activity and several functions is unclear. Methods: The present investigation aims to collect soil samples from photovoltaic power plants in arid and semi-arid regions with different years of construction, determine the physicochemical properties of the soil, and employ high-throughput sequencing to obtain 16S rRNA and ITS genes from the PV. This approach examines the community composition of bacteria and fungi in plant soils. This dataset is adopted to explore the role of soil physicochemical characteristics and climatic factors in the variousness and complexness of the network of soil microbial communities in PVs. Results: The findings reveal that soil physicochemical properties exhibit a gradual increase over time, with bacterial and fungal diversity showing a corresponding gradual increase and reaching a maximum over a period of 5-10 years. Furthermore, it is observed that the topological properties of the microbial network underwent significant changes driven by microbial diversity. Bacterial and fungal diversity as well as network complexity also display positive and negative correlations, respectively. A positive and significant correlation is detected between the bacterial network complexity and the soil multifunctionality, whereas a substantial negative correlation is observed between the fungal network complexity and the soil multifunctionality. Discussion: In conclusion the environment is able to directly regulate soil microbial diversity, thereby affecting network complexity and driving soil multifunctionality. Such discoveries are aimed to have crucial ecological implications for predicting environmental-soil-microbial effects on soil multifunctionality in photovoltaic zones.

Indexed as

bacterial diversityfungal diversitymicrobial network complexityphotovoltaic power plants (PVs)soil multifunctionality

Identifiers

PMID40330726
PMCPMC12052761

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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.