Evol Ecol Res 18: 515-530 (2017) Full PDF if your library subscribes.
Diversity and abundance of bacteria in the surface seawater of the Changjiang Estuary and its adjacent areas
Shuai-Bing Wang*, Jian-Xin Wang*, Xiao-Hui Liu, Ying-Ping Fan, Ran Jiang, Ming-Hua Liu, Xue-Zhu Liu and Dong-Mei Wu
Marine Microorganism Ecological & Application Lab, Zhejiang Ocean University, Zhejiang, China
Correspondence: J.-X. Wang, Marine Microorganism Ecological & Application Lab, Zhejiang Ocean University, No. 1 South Haida Road, Zhejiang 316022, China.
Question: What is the diversity and abundance of bacteria in the surface seawater of Changjiang Estuary and its adjacent areas?
Methods: We sequenced 1038 clones from surface seawater at ten different sites of Changjiang Estuary and its adjacent areas. We used culture-independent molecular approaches based on 16S rRNA genes to investigate diversity and abundance. We also used redundancy analysis to determine the relationship between bacterial diversity in surface seawater and various environmental parameters.
Results: Correlation analysis between environmental parameters and bacterial biomass indicated that dissolved oxygen and pH were statistically significantly correlated with bacterial biomass. Phylogenetic analysis of clone libraries indicated that Proteobacteria was the dominant taxon in all samples, followed by Bacteroidetes, Actinobacteria, Cyanobacteria, Firmicutes, Chloroflexi, Acidobacteria, Planctomycetes, Fibrobacteres, Verrucomicrobia, and Tenericutes. α-Proteobacteria was the dominant taxon within Proteobacteria. Cluster analysis and multidimensional scaling analysis revealed that bacterial communities could be classified into three groups (A02, A05/B03, and A01/A04/C04/A03/B02/C03/C05). Redundancy analysis indicated there were significant positive correlations between the distribution of bacterial community structure and pH, total suspended solids, total phosphorus, and dissolved oxygen.
Keywords: bacterioplankton, biomass, Changjiang Estuary, diversity, environmental variables, redundancy analysis.
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