Organic material mulching regulated core microbial groups to promote soil carbon and nitrogen cycling and improve faba bean productivity under a triple-cropping system in purple soil hilly region of southwest China

作者：Ke Ren, Wenfeng Song, Ze-Hui Wei, Lixia Song, Ming Liu, Yuling Zhou, Yi Zhen, Xinliang Wu, Kaiyuan Gu, Khanom Simarani, Longchang Wang · 发表于：Frontiers in Microbiology · 年份：2025 · DOI：10.3389/fmicb.2025.1602633 · 被引用次数：5 · 研究领域：Soil Carbon and Nitrogen Dynamics、Agronomic Practices and Intercropping Systems、Mycorrhizal Fungi and Plant Interactions

Background: Intensive agricultural production leads to the reduction of soil carbon (C) and nitrogen (N) reserves, and organic material mulching (OMM) can improve microbial community structure and promote C and N accumulation. The multi-cropping system based on legumes can provide abundant organic mulching material and improve soil quality, but the mechanism by which OMM provides ecological benefits via C and N cycling in this system is still unclear. Methods: L.) mulching (M), and straw and milk vetch mulching (SM). The dynamic changes in soil aggregates, C and N contents, enzyme activities, microbial communities and faba bean productivity under organic mulching were studied for 2 years (from October 2020 to May 2022). Results: The results demonstrated that supplementation of OMM (S, M, and SM) significantly improved the stability of soil aggregates, the nutrient (C and N) contents, and the activities of acquiring enzymes compared to CK. OMM promoted the establishment of key microbial communities dominated by Actinobacteria, Bacteroidetes, Ascomycota, and Basidiomycota. Predicted functional profiles based on PICRUSt and FUNGuild analyses suggest possible upregulation of up-regulated genetic information processing, metabolism, and organismal systems functional pathways. Additionally, the enhancement of soil C and N cycling efficiency may be associated with an increase in the proportion of saprotrophs and symbiotrophs. Both the random forest model (RFM) and partial least squar...