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Get Free AccessBacterial communities play a key role in maintaining ecosystem multifunctionality. With increasing land use intensity, soil biogeochemical and microbial characteristics change significantly and may influence the resulting multifunctionality of the ecosystem. The relationship between soil microbial communities and resistance of multiple ecosystem functions under land use change have not previously been assessed in the Karst region of Southwest China. Soils from four karst ecosystems (Primary forest; Secondary forest; Abandoned land; Cultivated land) were analyzed for microbial communities as predictor of multifunctional resistance to land use change by using high-throughput sequencing, structural equation modelling and random forest modelling. The resistance of Proteobacteria was highest in the forest, and the resistance of Verrucomicrobia highest in the abandoned and cultivated land. With increasing land use intensity, C-cycling functional resistance decreased by 77%, nitrogen and phosphorus functional resistance increased by 17% and 19% in abandoned land, compared to secondary forest. Structural equation modellings suggested the bacteria communities have the largest direct positive effect on multifunctional, and N-related functional resistance. Among bacterial communities, Verrucomicrobia and Chloroflexi were the two most important groups that affected soil multifunctional resistance. Regrading specific ecosystem function, Chthonomonadetes, Chloroflexia and OPB35_soil_group were the best predictor of TOC,TN and TP, respectively. Our results suggest strong links between microbial community composition and multifunctional resistance in various karst ecosystems, and provide insights into the importance of microbial community composition for recovering the ecosystems following human intervention.
liyang Yang, Romain L. Barnard, Jing Tian, Yakov Kuzyakov (2020). Bacterial communities drive the resistance of soil multifunctionality to land use change. Authorea (Authorea), DOI: 10.22541/au.159301774.46237138.
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Type
Preprint
Year
2020
Authors
4
Datasets
0
Total Files
0
Language
English
Journal
Authorea (Authorea)
DOI
10.22541/au.159301774.46237138
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