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Use of a Filter Cartridge for Filtration of Water Samples and Extraction of Environmental DNA
Published on: November 25, 2016
Estimating aquatic plant diversity and distribution in rivers from Jingjinji region, China, using environmental DNA
Fenfen Ji1, Liang Yan2, Saihong Yan2
1Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; Beijing Key Laboratory of Industrial Wastewater Treatment and Reuse, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Key Laboratory of Freshwater Animal Breeding, Ministry of Agriculture, College of Fisheries, Huazhong Agriculture University, Wuhan, 430070, China.
Abstract:
Traditional survey methods (TSMs) are difficult to use to perform a census of aquatic plant diversity completely in river ecosystems, and improved aquatic plant community monitoring programs are becoming increasingly crucial with a continuous decline in diversity. Although environmental DNA (eDNA) metabarcoding has been applied successfully to assess aquatic biodiversity, limited work has been reported regarding aquatic plant diversity in rivers. In this study, the efficiency of eDNA to estimate the aquatic plant diversity and spatial distribution of rivers from the Jingjinji (JJJ) region was evaluated by comparing results obtained by the TSM. Based on a combination of the two methods, 157 aquatic plant species, including 24 hydrophytes, 61 amphibious plants, and 72 mesophytes, were identified. The spatial patterns in species richness and abundance by eDNA exhibited agreement with the TSM results with a gradual decline from the mountain area (MA) to the agricultural area (AA) and then to the urban area (UA). Compared to the TSM, eDNA identified a significantly greater number of species per site (p < 0.01) and obtained a significantly higher abundance in hydrophytes (p < 0.01), supplementing the unavailable abundance data from the TSM. Furthermore, the aquatic plant assemblages from the different areas were discriminated well using eDNA (p < 0.05), but they were better discriminated by the TSM (p < 0.01). Thus, our study provides more detailed data on aquatic plant diversity in rivers from the JJJ region, which is essential for biodiversity conservation. Our findings also highlight that eDNA can be reliable for evaluating aquatic plant diversity and has the potential to respond to landscape heterogeneity in river ecosystems.
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