Agricultural practices influence soil microbiome assembly and interactions at different depths identified by machine learning.

ABSTRACT: Agricultural practices affect soil microbes which are critical to soil health and sustainable agriculture. To understand prokaryotic and fungal assembly under agricultural practices, we use machine learning-based methods. We show that fertility source is the most pronounced factor for microbial assembly especially for fungi, and its effect decreases with soil depths. Fertility source also shapes microbial co-occurrence patterns revealed by machine learning, leading to fungi-dominated modules sensitive to fertility down to 30 cm depth. Tillage affects soil microbiomes at 0-20 cm depth, enhancing dispersal and stochastic processes but potentially jeopardizing microbial interactions. Cover crop effects are less pronounced and lack depth-dependent patterns. Machine learning reveals that the im

SUBMITTER: Mo Y 

PROVIDER: S-EPMC11489707 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature