ArticleEcology and evolution2023
Environmental DNA metabarcoding revealed the impacts of anthropogenic activities on phytoplankton diversity in Dianchi Lake and its three inflow rivers.
Article in Ecology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Predicting Algal Bloom Dynamics in Drinking Water Reservoirs Using High-Frequency In Situ Data and Machine Learning.Toxins · 2026Article
- Patagonian Fjords/Channels vs. Open Ocean: Phytoplankton Molecular Diversity on Southern Chilean Coast.Microorganisms · 2025Article
- Changes in Microbial Community Assemblages Due To Urban Pollution, Detected via rRNA Gene Amplicon Sequencing in the Magdalena River, Mexico City.Microbial ecology · 2025Article
- Analysis of water quality and the response of phytoplankton in the low-temperature environment of Majiagou Urban River, China.Heliyon · 2024Article
- Review
- Environmental DNA metabarcoding revealed the impacts of anthropogenic activities on phytoplankton diversity in Dianchi Lake and its three inflow rivers.Ecology and evolution · 2023Article
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Authors and funding
7 authors.
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Abstract
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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