Soil enzyme profile analysis for indicating decomposer micro‐food web

Author:

Xing Wen12ORCID,Hu Ning1,Li Zhongfang1,Feng Liangshan3,Zhang Weidong4,Du Preez Gerhard5,Zhang Huimin6,Li Dongchu6,Lu Shunbao7,Chang Scott X.8,Zhang Qingwen2ORCID,Lou Yilai2ORCID

Affiliation:

1. Guangxi Key Laboratory of Health Care Food Science and Technology, School of Food and Biological Engineering Hezhou University Hezhou China

2. Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural Sciences Beijing China

3. Liaoning Academy of Agricultural Sciences Shenyang China

4. Institute of Applied Ecology Chinese Academy of Sciences Shenyang China

5. Unit for Environmental Sciences and Management North‐West University Potchefstroom South Africa

6. Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China

7. Jiangxi Normal University Nanchang China

8. Department of Renewable Resources University of Alberta Edmonton Alberta Canada

Abstract

AbstractHighly 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.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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