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Dose-dependent effect of compost amendment on soil bacterial community composition and co-occurrence network patterns in soybean agroecosystem

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posted on 2019-08-11, 14:35 authored by Wei Yang, Zhongzan Yang, Yupeng Guan, Cheng Zhai, Dengyu Shi, Jianghui Chen, Tao Wang, Siyu Gu

This study aimed to elucidate the effects of various doses of compost amendment on bacterial community compositions and co-occurrence network patterns across the growing season in black soil, Northeast China. Bacterial richness was unaffected by compost addition in seedling and flowering stage, whereas significantly enhanced by high level of compost addition (45,000 kg ha−1) in mature stage. Non-metric multidimensional scaling analysis revealed distinct bacterial communities in response to compost addition across the growing season. At phylum level, copiotrophic groups of bacteria including Bacteroidetes and Firmicutes gradually increased in relative abundance along with compost rate, while oligotrophic groups (Planctomycetes and Verrucomicrobia) showed opposite tendency. Notably, these enrichment or reduction was most pronounced in seedling stage. Abundant genera including Actinomadura, Aminobacter, Cellvibrio, Devosia, Luteimonas, Microbacterium, Nonomuraea, Promicromonospora were positively and consistently correlated with compost rate, whereas Arthrobacter, Flavisolibacter, Janthinobacterium, Kaistobacter negatively correlated. Network analysis indicated that compost amended soils (40.0, 49.0, and 64.0%) harbored more positive links than control (37.6%). In addition, the soil bacterial network connectivity and connectedness generally increased along with the compost rate, while modularity exhibited opposite trend. Overall, our findings show that compost addition modified the bacterial community compositions and network patterns in soybean agroecosystem in Northeast China.

Funding

This work was supported by Youth Innovative Talents Project of Heilongjiang [Grant number: UNPYSCT-2018172]; Post-doctoral Launch Foundation of Heilongjiang [Grant number: LBH-Q18016]; and National Key Research and Development Program of China [2017YFD0300502-2].

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