Evidence map›Paper›PMID 39109210›Full record

ArticleFrontiers in microbiology2024

Mixed planting of subtropical Chinese fir in South China improves microbial carbon source metabolism and functional diversity through the accumulation of nutrients from soil aggregates.

Jiazhen Deng, Jingda Hu, Yongzhen Huang, Shengqiang Wang, Shaoming Ye

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. 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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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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.

Jiazhen DengGuangxi Colleges and Universities Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi University, Nanning, China.
Jingda HuGuangxi Colleges and Universities Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi University, Nanning, China.
Yongzhen HuangState Dongmen Forestry Farm of Guangxi Zhuang Autonomous Region, Chongzuo, China.
Shengqiang WangGuangxi Colleges and Universities Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi University, Nanning, China.
Shaoming YeGuangxi Colleges and Universities Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Guangxi University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Soil microbial functional traits are key indicators of soil microbial ecological traits; however, how mixing patterns of Chinese fir and broadleaved trees drive soil microbial functional trait variation at the aggregate scale and how soil microbial functional traits are linked to soil fertility factors have largely not been determined. Methods: In this study, soil from the 0-20 cm depths in three Chinese fir plantations was collected, and the soil samples were separated into >2 mm (large macro-aggregate), 0.25-2 mm (macro-aggregate) and <0.25 mm (micro-aggregate) by complying with an optimal moisture sieving procedure. The metabolic activities, functional diversity and different carbon sources utilization characteristics of the soil microorganisms were determined by the Biolog Eco microplate method. Results: In all Chinese fir plantations, micro-aggregates (<0.25 mm) consistently exhibited the highest levels of microbial metabolic activity, a more uniform carbon source utilisation capacity, and the highest microbial diversity. Micro-aggregates also showed elevated levels of soil organic carbon (OC), total nitrogen (TN), total phosphorus (TP), and higher ratios of C/N and C/P compared to large macro-aggregates and macro-aggregates, indicating that micro-aggregates contain more resources available to soil microorganisms. Soil OC, TN, and TP content were enhanced by integration with Discussion: In summary, mixed cultivation and aggregate size influenced microbial functional properties via soil nutrient alterations. Consequently, adopting a mixed cultivation approach of Chinese fir and broadleaved trees is advocated in the subtropical regions of Guangxi. Employing a diversity of tree species, including

Indexed as

Biolog Eco microplatecarbon metabolism activityChinese firmixed plantationsoil aggregatesoil microbial functional diversity

Identifiers

PMID39109210
PMCPMC11301763

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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.