Microbial carbon fixation and its influencing factors in saline lake water

Distribution patterns and co-occurrence network of eukaryotic algae in different salinity waters of Yuncheng Salt Lake, China

The community structure and co-occurrence pattern of eukaryotic algae in Yuncheng Salt Lake were analyzed based on marker gene analysis of the 18S rRNA V4 region to understand the species composition and their synergistic adaptations to the environmental factors in different salinity waters. The results showed indicated that the overall algal composition of Yuncheng Salt Lake showed a Chlorophyta-Pyrrophyta-Bacillariophyta type structure. Chlorophyta showed an absolute advantage in all salinity waters. In addition, Cryptophyta dominated in the least saline waters; Pyrrophyta and Bacillariophyta were the dominant phyla in the waters with salinity ranging from 13.2 to 18%. Picochlorum, Nannochloris, Ulva, and Tetraselmis of Chlorophyta, Biecheleria and Oxyrrhis of Pyrrophyta, Halamphora, Psammothidium, and Navicula of Bacillariophyta, Guillardia and Rhodomonas of Cryptophyta were not observed in previous surveys of the Yuncheng Salt Lake, suggesting that the algae are undergoing a constant turnover as the water environment of the Salt Lake continues to change. The network diagram demonstrated that the algae were strongly influenced by salinity, NO3-, and pH, changes in these environmental factors would lead to changes in the algal community structure, thus affecting the stability of the network structure.

Characteristics of microbial community structure and influencing factors of Yangcheng Lake and rivers entering Yangcheng Lake during the wet season

Yangcheng Lake, a typical fishery lake in the middle and lower reaches of the Yangtze River, is threatened by eutrophication. As the main performers of biogeochemical cycles, microorganisms affect the ecological stability of the lake. To study the structural characteristics of the microbial community in Yangcheng Lake and rivers entering Yangcheng Lake and the response relationship with environmental factors, the microbial community was categorized based on the contour of Yangcheng Lake, the major rivers entering Yangcheng Lake, and the pollution sources. The distribution characteristics of seven physicochemical indices were analyzed, including total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), water temperature (WT), pH, dissolved oxygen (DO), and ratio of total nitrogen to total phosphorus (TN/TP). Characterization of microbial community structure based on 16S rRNA high-flux sequencing technology and ANOSIM analysis were used to explore the differences in the relative abundance of microorganisms at each sampling point in the lake and rivers, and redundancy analysis (RDA) was used to analyze the relationship between the microbial community and physicochemical factors. The results showed that the dominant phyla, genera of microorganisms, and the total number of OTUs in the lake and rivers were similar. The dominant phyla included Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, and Verrucomicrobia; the dominant genera included the hgcI clade, CL500-29 marine group, Microcystis PCC-7914, Chloroplast_norank, Clade III_norank, and Flavobacterium. ANOSIM analyses revealed that the microbial community of Yangcheng Lake exhibited an association with geographical space, while the microbial community in the rivers that was linked to the type of pollution source. Redundancy analysis (RDA) indicated that dissolved oxygen (DO), total nitrogen (TN), and pH were significantly correlated with the dominant phyla in Yangcheng Lake (p < 0.05), while total nitrogen (TN), water temperature(WT), and the ratio of total nitrogen to total phosphorus (TN/TP) were significantly related with the dominant genera in Yangcheng Lake (p < 0.05). Total nitrogen (TN) was also significantly linked to the dominant phyla and genera of the tributaries (p < 0.05). Despite the structural similarities in microbial communities between Yangcheng Lake and its inflowing rivers, environmental factors demonstrated significant associations with these communities, providing crucial data support for pollution prevention and the ecological restoration of Yangcheng Lake.