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Monitoring bloom-forming Aphanizomenon using environmental DNA metabarcoding: Method development, validation, and
Dexiang Sun1, Shiguo Li2, Wei Xiong3
1Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Horticulture and Landscape Architecture, Northeast Agricultural University, Harbin 150030, China.
New primers and environmental DNA (eDNA) metabarcoding enable efficient field monitoring of Aphanizomenon blooms. This accurate method correlates well with cell counts, offering a high-throughput tool for freshwater ecosystem surveillance.
Area of Science:
- Environmental Science
- Ecology
- Molecular Biology
Background:
- Harmful algal blooms (HABs) are a significant global environmental issue.
- Accurate monitoring of bloom-forming genera is vital for HAB management.
- Traditional methods are labor-intensive and require expertise, limiting large-scale surveillance.
Purpose of the Study:
- To develop Aphanizomenon-specific PCR primers.
- To validate environmental DNA (eDNA) metabarcoding for field-based monitoring of Aphanizomenon.
- To identify environmental drivers of Aphanizomenon distribution.
Main Methods:
- Development and testing of novel Aphanizomenon-specific PCR primers.
- Application of eDNA metabarcoding for monitoring in 37 freshwater sites.
- Statistical analysis correlating eDNA sequence abundance with microscopic cell counts and environmental variables.
Main Results:
- Newly developed primers demonstrated high sensitivity and specificity for Aphanizomenon.
- eDNA metabarcoding showed significant correlations with microscopic cell density in spring and summer.
- Key environmental drivers identified include temperature, total nitrogen, dissolved oxygen, and total phosphorus.
Conclusions:
- eDNA metabarcoding with novel primers provides an accurate, efficient, and high-throughput tool for Aphanizomenon bloom monitoring.
- This method overcomes limitations of traditional techniques for large-scale surveillance.
- Understanding environmental drivers aids in predicting and managing Aphanizomenon blooms.
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