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Deciphering environmental factors driving soil microbial elevational distribution in the southeastern Qinghai-Tibetan Plateau

酸杆菌 生态学 地理距离 高原(数学) 环境科学 蛋白质细菌 生物多样性 群落结构 微生物种群生物学 α多样性 放线菌门 β多样性 生物 含水量 高度(三角形) 多样性指数 物种丰富度 数学分析 数学 人口 遗传学 人口学 16S核糖体RNA 岩土工程 几何学 社会学 细菌 工程类
作者
Qi Wang,Xia Wu,Lei Zhu,Jun Wan,Hong Jin,Tao Ke,Taiping Hou
出处
期刊:European Journal of Soil Biology [Elsevier BV]
卷期号:113: 103444-103444 被引量:5
标识
DOI:10.1016/j.ejsobi.2022.103444
摘要

Qinghai-Tibetan Plateau (QTP) has been ranked as one of the main hotspots of biodiversity. Many studies on microbial diversity and structure have been investigated in QTP, whereas the joint impacts of environmental properties and geographic distance that influence microbial communities along altitudinal gradient is yet poorly understood. In this paper, we investigated sites along the elevational gradient of 3270–4530 m on the southeast QTP in China, characterizing environmental properties, and systematically examined the composition, diversity patterns and the driving factors of soil microbial community structures. Elevation led to distinct changes in environmental properties. Bacterial α-diversity did not differ significantly among elevations, whereas fungal α-diversity showed a decrease pattern, which could be attributed to changes in temperature, soil moisture, pH and total carbon content. The dominant bacterial and fungal phyla were Actinobacteria (30.4%), Proteobacteria (24.1%) and Acidobacteria (14.7%), and Ascomycota (52.3%), Basidiomycota (32.6%) and Mortierellomycota (13.9%), respectively. Notable distance-decay of microbial community was observed across environmental factors and geographic distance. Partial Mantel tests indicated that differences in bacterial community were driven by the joint impacts of environmental factors and geographic distance, while differences in fungal community were primarily driven by a sole impact of environmental factors. The multiple regression on matrices (MRM) model explained 79% of the variability in bacterial community similarity, with pH being the most important variables, followed by soil moisture, elevation, AK content and geographic distance. The proportion of variance explained by MRM model was 55%, with elevation and TN content being the main variables altering the soil fungal structure. In summary, our findings suggested that α-diversity patterns, and the driving factors of the bacterial and fungal community structure were different, and environmental factors and geographic distance played different roles on the bacterial and fungal community structures.
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