Huilin Yan, Panda Ye, Huigang Pei, Jiajia He, Yujiao Liu
This study characterized regional variation in faba bean rhizosphere bacterial communities across a broad survey of the Qinghai Plateau and examined their associations with soil and spatial factors. Rhizosphere soil samples were collected from 15 faba bean-growing field sites across Haidong City, Xining City, and Hainan Tibetan Autonomous Prefecture, Qinghai Province, China, spanning elevations from 1842.9 to 3206.3 m. Nine within-site subsamples were collected at each field site, with the field site treated as the independent unit of replication. Soil physicochemical properties were measured, and bacterial communities were characterized by high-throughput sequencing of the 16S rRNA gene. At the site level, bacterial alpha-diversity indices showed numerical variation among the three regional elevation groups, but did not differ significantly. Bacterial community composition differed among groups in the site-level PERMANOVA based on Bray-Curtis dissimilarities (pseudo-F2.12 = 1.789, R2 = 0.230, p = 0.031), although substantial overlap among sites remained. However, a conservative locality-level sensitivity analysis was not significant (p = 0.060). Geographic distance was significantly associated with bacterial community dissimilarity, whereas elevation difference showed no detectable independent association after controlling for geographic distance, indicating a substantial contribution of spatial structure to the observed community differentiation. Dominant phylum-level composition was broadly conserved across sites, while genus-level relative abundances showed descriptive spatial variation. Neither RAVD-based compositional consistency nor community-level niche breadth differed significantly among groups. Among the measured soil properties, only pH differed significantly, whereas most nutrient variables did not. Overall, the study revealed spatially structured regional differentiation in faba bean rhizosphere bacterial communities across the Qinghai Plateau. The observed patterns likely reflect the combined influence of geographic structure, elevation, background soil conditions, agricultural management, plant phenology, and other unmeasured environmental factors, which could not be independently disentangled in the present survey.