摘要
为了阐明镉污染对农田土壤微生物的影响,本研究在湖南省株洲农业生产区采集轻度、中度镉污染稻田土壤,分析了微生物群落的变化特征,讨论了土壤理化性质对微生物群落组装的影响,并利用网络分析手段研究微生物网络的差异。结果表明:镉污染加重显著改变了细菌和古菌的α多样性,而未对真菌的α多样性产生显著影响;轻、中度镉污染区微生物群落结构存在显著差异,细菌和古菌群落主要受土壤pH、总镉(CdT)、有效镉(Cd_(A))、有效磷(AP)和微生物量碳(MBC)的影响,真菌群落主要受pH、CdT、Cd_(A)、硝态氮(NO_(3)^(-))和铵态氮(NH_(4)^(+))影响;共现网络分析发现,中度镉污染降低了微生物共现网络连接数、节点平均度和图密度,说明镉污染加重会影响微生物之间的相互作用,降低微生物网络的复杂性。
To elucidate the impacts of cadmium pollution on soil microorganisms,soil samples were collected from lightly and moderately cadmium polluted farmlands in Zhuzhou of Hunan Province.This study analyzed the varia-tions of bacteria,fungi and archaea communities,assessed the effects of soil physicochemical properties on soil mi-crobial community structure,and explored the variation of soil microbial networks by network analysis.The results showed cadmium pollution significantly altered the alpha diversity indices of bacteria and archaea,but did not sig-nificantly affect the alpha diversity indices of fungi.There were significant differences in microbial community struc-ture between lightly and moderately cadmium polluted farmlands.Soil pH,total cadmium(CdT),available cadmi-um(Cd_(A)),available phosphorus(AP),and microbial biomass carbon(MBC)significantly affected bacteria and archaea,while fungi were mainly affected by pH,CdT,Cd_(A),nitrate nitrogen(NO_(3)^(-)),and ammonium nitrogen(NH_(4)^(+)).Co-occurrence network analysis revealed that moderate cadmium pollution reduced the number of connec-tions,average node degree,and graph density in the microbial co-occurrence network,indicating that increased cadmium pollution affects interactions between microbes and reduces the complexity of microbial networks.
作者
张蓓蓓
王薪琪
李卓晴
杜辉辉
刘孝利
铁柏清
雷鸣
ZHANG Beibei;WANG Xingqi;LI Zhuoqing;DU Huihui;LIU Xiaoli;TIE Boqing;LEI Ming(Collage of Environment&Ecology,Hunan Agricultural University,Changsha 410000,China)
出处
《生态学杂志》
CAS
CSCD
北大核心
2024年第11期3376-3382,共7页
Chinese Journal of Ecology
基金
国家重点研发计划项目(2022YFD1700101和2018YFD0800700)
长沙市自然科学基金项目(kq2202217)资助。
关键词
镉
稻田
高通量测序
群落结构
共现网络分析
cadmium
rice field
high-throughput sequencing
microbial community structure
co-occurrence net-work analysis