Phytoplankton diversity is closely related to environmental variables and has been widely used in ecological health assessment of rivers and lakes. Combining advantages of DNA‐based identification and high‐throughput sequencing technology, environmental DNA (eDNA) metabarcoding permits a new measurement for biodiversity monitoring in aquatic ecosystems. However, it had rarely been used to explore the variability and similarity of phytoplankton diversity between lake and its inflow rivers and the effects of environmental variables on phytoplankton. This study utilized eDNA metabarcoding to investigate the spatial distribution of phytoplankton and the impacts of environmental variables on the phytoplankton diversity in Dianchi Lake (one of the most polluted urban lakes in China) and its main inflow rivers (Panlong River, Baoxiang River, and Chai River). A total of 243 distinct phytoplankton taxa were detected, covering 9 phyla, 30 classes, 84 orders, and 132 families, and the taxonomic richness of rivers was higher than that of Dianchi Lake. Distinct biodiversity patterns (e.g., community structure, dominant taxon, ɑ‐diversity) were exhibited among Dianchi Lake and its three inflow rivers, but similar biodiversity patterns were also observed in Dianchi Lake and the estuarine sites. The patterns of phytoplankton diversity were closely related to environmental variables, which were associated with pollution sources from different anthropogenic activities (e.g., urbanization, water diversion, industrial and agricultural activities). The primary environmental variables correlated with phytoplankton diversity varied in different habitats. The total phosphorus (TP) and chemical oxygen demand (COD) positively correlated with the phytoplankton community structures in Dianchi Lake, whereas negatively correlated in Panlong River and Baoxiang River. The total nitrogen (TN) positively correlated with the phytoplankton community structures in Baoxiang River and Chai River but negatively correlated in Dianchi Lake. Overall, this study provides insights on the phytoplankton diversity monitoring and the conservation of its diversity and healthy management of Dianchi Lake.

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Fish are among the main target groups when conducting biomonitoring and ecological assessment of aquatic environments. Environmental DNA (eDNA) metabarcoding provides a unique opportunity to enhance biomonitoring throughput, precision, and standardization. However, few fish monitoring studies based on eDNA metabarcoding have been conducted at the basin scale. Taking Dianchi Lake and the three inflowing rivers (Panlong River, Baoxiang River, and Chai River) as research objects, this study monitored fish diversity via eDNA metabarcoding, and the Fish Index of Biological Integrity (F-IBI) was constructed and applied for the ecological assessment of the aquatic environment. Here, we detected 41 species belonging to 9 orders, 15 families, and 35 genera in the sampling areas, including 17 native fish species such as Hemiculter leucisculus, Cyprinus carpio, and Silurus soldatovi. Distinct diversity patterns were observed among Dianchi Lake and the three inflowing rivers. Particularly, the fish diversity of Panlong River was richer than that of Dianchi Lake, Baoxiang River, and Chai River. Water temperature (WT), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) significantly influenced the distribution of fish communities in most sampling sites of the Dianchi Lake basin (p < 0.05). Moreover, according to the F-IBI assessment system, 25% of the sampling sites were defined as ‘fine’ or above, and 75% were ‘impaired’ or below. This study provided insights into the ecological restoration and precise management of the aquatic environment of the Dianchi Lake basin.