植物群落和土壤理化性质对碧塔海湿地土壤细菌群落的影响

土壤微生物是湿地生态系统中土壤-植物系统生源要素迁移转化的引擎。探究湿地生态系统地上植物群落、土壤理化性质和空间结构与土壤细菌间的相互关系是维护湿地生态系统健康和稳定的关键。本研究运用双向指示种分析法(TWINSPAN)对碧塔海湿地采集的35个样方中的植物群落进行分类,并采用高通量测序技术对样方的表层土壤细菌进行测序,分析植物群落、土壤理化性质和空间结构与细菌群落间的关系。结果表明: 双向指示种分析将样方的植物群落划分为3种群落类型,相同类型的植物群落在外貌和结构上相似,说明基于双向指示种分析的数量分类方法在高原湿地生态系统植物群落分类中有较好的适用性;细菌相对丰度统计结果表明,酸杆菌门(21.0%)、绿弯菌门(15.5%)、变形菌门(15.3%)和拟杆菌门 (10.1%)是碧塔海湿地总丰度高于10%的门类,相似性分析(ANOSIM)显示,不同植物群落类型对应的土壤细菌群落存在显著差异,说明植物群落对土壤细菌组成有一定的影响;典范对应分析(CCA)结果显示,植物群落的多样性、含水率、pH、铁和空间结构是影响土壤细菌群落的重要因素。方差分解结果显示,细菌群落既受单一环境变量的影响,也受环境变量间复合作用的影响。综上,地上植物群落、土壤理化环境和空间结构共同塑造细菌群落,地上植物群落-细菌-土壤理化性质是不可分割的整体。

Effects of plant community and soil properties on soil bacterial community in Bitahai Wetland,Southwest China

Soil microorganism was the engine of the migration and transformation of biological elements in the soil-plant system of wetland ecosystems. Exploring the relationship between plant community, soil properties, and spatial structure with soil microorganisms is the key to maintain the health and stability of wetlands. In order to examine the effects of plant community, soil properties, and spatial structure on the bacterial community in wetlands, we used two-way indicator species analysis (TWINSPAN) to classify plant communities from 35 samples collected in Bitahai Wetland. We measured microbial community composition at the surface soil of the samples using high-throughput sequencing technology, and analyzed the relationship among plant community, soil pro-perties and spatial structure with bacterial community. The results showed that plant communities could classified into three different types by TWINSPAN. The physiognomy and structure of plant communities in same community type were relatively consistent. We found that quantitative classification had good applicability in vegetation classification of plateau wetland ecosystem. Acidobacteriota (21.0%), Chloroflexi (15.5%), Proteobacteria (15.3%) and Bacteroidetes (10.1%) had higher population densities (≥10%) in Bitahai Wetland. Analysis of similarities (ANOSIM) showed that different plant community types differed significantly in bacterial community composition, suggesting that plant communities could affect bacterial community. Cano-nical correspondence analysis (CCA) results showed that plant diversity, soil water content (SWC), pH, iron (Fe) and spatial structure were the dominated factors that significantly affecting bacterial community. The variance partitioning analysis (VPA) results showed that bacterial community was affected by single environment factors and their interactions. Our results highlighted that bacterial community is shaped by plant community, soil properties and spatial structure, with their effects being indivisible.