Soil Bacterial Diversity and Community Structure of Cotton Rhizosphere under Mulched Drip-Irrigation in Arid and Semi-arid Regions of Northwest China

Xinjiang is situated in an arid and semi-arid region, where abundant heat and sunlight create highly favorable conditions for cotton cultivation. Xinjiang's cotton output accounts for nearly one-quarter of global production. Moreover, the implementation of advanced planting techniques, such as 'dwarfing, high-density, early-maturing' strategies combined with mulched drip irrigation, ensures stable and high yields in this region. Despite these advancements, limited research has focused on the microbial mechanisms in cotton fields employing these advanced planting methods. In this study, high-throughput sequencing technology was utilized to investigate the diversity and composition of bacterial and phoD (Alkaline phosphatases encoding gene) communities in the rhizosphere of cotton grown under different yield levels in Xinjiang Province, China. The Mantel test, redundancy analysis (RDA) and partial least squares path modeling (PLS-PM) were employed to explore the interactions between soil bacterial and phoD communities, their network structures, and environmental factors. The bacterial and phoD communities in the cotton rhizosphere were predominantly composed of nine bacterial phyla (i.e., Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes, Chloroflexi, Bacteroidetes, Rokubacteria, Firmicutes, and Nitrospirae) and five phoD phyla (i.e., Proteobacteria, Actinobacteria, Planctomycetes, Acidobacteria, and Firmicutes), respectively. Alpha diversity analysis indicated that the medium yield cotton field (MYF) exhibited higher bacterial richness and diversity indices compared to low yield (LYF) and high yield (HYF) fields. The symbiotic network analysis of LYF revealed greater values of average degree, number of edges, and modularity, suggesting a more complex network structure in both bacterial and phoD communities. The Mantel test, RDA, and PLS-PM model identified soil pH, electrical conductivity (EC), organic phosphorus (OP), available phosphorus (AP), total nitrogen (TN), microbial biomass carbon (MBC), and clay content as the main driving factors influencing changes in the rhizosphere bacterial community diversity and network structure. These findings provide a theoretical basis for future research aimed at improving soil quality and cotton yield.