Human activities, global warming, frequent extreme weather events, and changes in atmospheric composition affect the solar radiation reaching the Earth’s surface, affect mass and heat transfer at the air–water interface, and induce oscillations in wind-driven internal waves. This leads to changes in the spatiotemporal characteristics of thermal stratification in lakes, altering lake circulation patterns and vertical mass transfer. However, thermal stratification structures are often overlooked. The intensification of lake thermal stratification due to warming may lead to increased release of bottom pollutants, spreading through the dynamic behavior of the thermocline to the epilimnion. Moreover, the increased heat storage is beneficial for the growth and development of certain phytoplankton, resulting in rapid transitions of the original steady state of lakes. Consequently, water quality deterioration, ecological degradation, and declining biodiversity may occur. Conventional surface water monitoring may not provide comprehensive, accurate, and timely assessments. Model simulations can better predict future thermal stratification behaviors, reducing financial burdens, providing more refined assessments, and thus preventing subsequent environmental issues.

To explore the contamination status and identify the source of the heavy metals in the sediments in the major inflow rivers of Dianchi Lake in China, sediment samples were collected and analyzed. Specifically, the distribution, source, water quality, and health risk assessment of the heavy metals were analyzed using correlation analysis (CA), principal component analysis (PCA), the heavy metal contamination factor (C_f), the pollution load index (PLI), and the potential ecological risk index (PERI). Additionally, the chemical fractions were analyzed for mobility characteristics. The results indicate that the average concentration of the heavy metals in the sediment ranked in the descending order of Zn > Cr > Cu > Pb > As > Ni > Cd > Hg, and most of the elements existed in less-mobile forms. The C_fwas in the order of Hg > Zn > Cd > As > Pb > Cr > Ni; the accumulation of Hg, Zn, Cd, and As was obvious. Although the spatial variability of the heavy metal contents was pronounced, the synthetical evaluation index of the PLI and PERI both reached a high pollution level. The PCA and CA results indicate that industrial, transportation, and agricultural emissions were the dominant factors causing heavy metal pollution. These results provide important data for improving water resource management efficiency and heavy metal pollution prevention in Dianchi Lake.

The growth and reproduction of phytoplankton are closely associated with the changes of water environment; thus, phytoplankton have been taken as environmental indicator organisms and provided references for water environment protection. However, the phytoplankton community characteristics of Dianchi Lake (a seriously polluted lake in China) are unclear under the background of the cumulative effects of historical pollutants and current control measures, and environmental DNA (eDNA) metabarcoding monitoring has rarely been applied in phytoplankton research at Dianchi Lake. Therefore, this study investigated the temporal and spatial characteristics of phytoplankton community and the environmental stressors of Dianchi Lake via eDNA metabarcoding monitoring. A total of 10 phyla, 22 classes, 50 orders, 82 families, 108 genera and 108 species of phytoplankton were detected, and distinct temporal and spatial variations in the phytoplankton community (e.g., ASV number, dominant taxon, the relative abundance) were observed in Dianchi Lake. Microcystis dominated the prokaryotic phytoplankton community from the dry period to the wet period, but interestingly, the first dominant cyanobacteria genus was changed from Microcystis (dry period) to Planktothrix (wet period). Cryptophyta dominated in the eukaryotic phytoplankton community from the dry period to the wet period, and eukaryotic-phytoplankton-dominant genera included Cryptomonas, Aulacoseira, Plagioselmis and others. A temporal–spatial heterogeneity of the relationships between the phytoplankton community and environmental factors was shown in Dianchi Lake. Dissolved oxygen was the crucial environmental stressor influencing the phytoplankton community structure in Dianchi Lake during the dry period, while pH was the crucial one during the wet period. The impacts of total phosphorus and nitrogen also showed differences at different periods. This research provides an interesting perspective on phytoplankton diversity monitoring and the health assessment and restoration of Dianchi Lake.

Surveys of zooplankter and phytoplankton through environmental DNA (eDNA) and metagenomic technology across Dianchi Lake and the estuary of inflowing rivers was conducted, to evaluate the microbial diversity of Dianchi Lake and the estuary of four in flowing rivers. Diversity of plankton and the similarity of dominant species results revealed that the dominant eukaryotic phytoplankton in Dianchi Lake was Bacillatiophyta. The Shannon diversity index values of phytoplankton and zooplankton ranged from 3.68 to 18.36 and 0.54 to 2.49, respectively. The main genus taxa in the Dianchi Lake were similar with the inflowing river. The distribution map of Shannon diversity index gave overall insight into the variation of plankton diversity. The research proved that the eDNA technology was effective in biodiversity monitoring in aquatic ecosystem, and the inflowing river may impose an adverse influence on the ecosystem health of Dianchi Lake.