Evidence map›Paper›PMID 38868509›Full record

ArticleiMeta2024

Soil enzyme profile analysis for indicating decomposer micro-food web.

Wen Xing, Ning Hu, Zhongfang Li, Liangshan Feng, Weidong Zhang, Gerhard Du Preez, Huimin Zhang, Dongchu Li, Shunbao Lu, Scott X Chang and 2 more

Abstract read
In one paragraph

Article in iMeta, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

12 authors.

Wen XingGuangxi Key Laboratory of Health Care Food Science and Technology, School of Food and Biological Engineering Hezhou University Hezhou China.ORCID 0000-0002-8804-2453
Ning HuGuangxi Key Laboratory of Health Care Food Science and Technology, School of Food and Biological Engineering Hezhou University Hezhou China.
Zhongfang LiGuangxi Key Laboratory of Health Care Food Science and Technology, School of Food and Biological Engineering Hezhou University Hezhou China.
Liangshan FengLiaoning Academy of Agricultural Sciences Shenyang China.
Weidong ZhangInstitute of Applied Ecology Chinese Academy of Sciences Shenyang China.
Gerhard Du PreezUnit for Environmental Sciences and Management North-West University Potchefstroom South Africa.
Huimin ZhangInstitute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China.
Dongchu LiInstitute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China.
Shunbao LuJiangxi Normal University Nanchang China.
Scott X ChangDepartment of Renewable Resources University of Alberta Edmonton Alberta Canada.
Qingwen ZhangInstitute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences Beijing China.ORCID 0000-0002-0247-3886
Yilai LouInstitute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences Beijing China.ORCID 0000-0002-5106-9951

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly diverse exoenzymes mediate the energy flow from substrates to the multitrophic microbiota within the soil decomposer micro-food web. Here, we used a "soil enzyme profile analysis" approach to establish a series of enzyme profile indices; those indices were hypothesized to reflect micro-food web features. We systematically evaluated the shifts in enzyme profile indices in relation to the micro-food web features in the restoration of an abandoned cropland to a natural area. We found that enzymatic C:N stoichiometry and decomposability index were significantly associated with substrate availability. Furthermore, the higher Shannon diversity index in the exoenzyme profile, especially for the C-degrading hydrolase, corresponded to a greater microbiota community diversity. The increased complexity and stability of the exoenzyme network reflected similar changes with the micro-food web networks. In addition, the gross activity of the enzyme profile as a parameter for soil multifunctionality, effectively predicted the substrate content, microbiota community size, diversity, and network complexity. Ultimately, the proposed enzymic channel index was closely associated with the traditional decomposition channel indices derived from microorganisms and nematodes. Our results showed that soil enzyme profile analysis reflected very well the decomposer food web features. Our study has important implications for projecting future climate change or anthropogenic disturbance impacts on soil decomposer micro-food web features by using soil enzyme profile analysis.

Indexed as

co‐occurrence networkdecomposition channelfood webmicrobiomenematodeprotozoasoil exoenzyme

Identifiers

PMID38868509
PMCPMC10989158

What OpenQuestion holds

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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.