eDNA metabarcoding revealed the seasonal and spatial variation of phytoplankton functional groups in the Chai river and their relationship with environmental factors

Lv, Jiacheng; Lin, Yuanyuan; Zhao, Zheng; Zhou, Xinyu

doi:10.1080/02705060.2023.2176374

Cited by 5 publications

(2 citation statements)

References 46 publications

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“…This is achieved by detecting eDNA that is released into the environment from aquatic animals and plants ( Fabrin et al, 2020 ; Jo et al, 2020 ). The analysis of the biological community and its relative abundance using eDNA metabarcoding technology, which combines high-throughput sequencing (HTS) with DNA sequences from various environmental samples, is widely employed in freshwater ecosystem’s protection ( Lv et al, 2023 ). The eDNA metabarcoding approach offers comprehensive depiction about zooplankton biodiversity and help to conserve biodiversity ( Xiong et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Metabarcoding of zooplankton communities of Dianchi Lake based on the mitochondrial cytochrome oxidase subunit 1 gene

Cen,

Xu,

Yin

et al. 2024

Front. Microbiol.

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Freshwater lakes as an essential component of the ecosystem, provide ecological resources in addition to economic source for humans. Under recent climate change scenario, preserving the biodiversity of freshwater ecosystems is crucial. This study aimed to characterize the diversity of zooplankton communities in Dianchi Lake, located in Kunming Municipality, Yunnan Province, China, using Illumina high-throughput sequencing of the cytochrome oxidase subunit 1 (COI) gene marker. A total of 18 water samples were collected including 16 from the outer sea area of Dianchi Lake: 4 from the east (E1-4), 4 from the west (W1-4), 4 from the south (S1-4), and 4 from the north (N1-4), and: 2 from the Caohai area (C1-2) as research sites. All environmental parameters including pH, ammonium (NH4+), total nitrogen (TN), total phosphorus (TP), chlorophyll a content (CHLA) were found to be insignificant (p > 0.05), except for chemical oxygen demand (COD) and transparency (T), which were found to be significant (p < 0.05). Alpha diversity indices including ACE, Chao1, Shannon, and Simpson showed non-significant differences (p > 0.05), indicating no variation in the richness of zooplankton communities at different locations of Dianchi Lake. However, principal coordinate analysis (PCoA) showed that most of the samples from East, West, and South groups were close to each other, showing more similarities among them, while Caohai and North group samples were distant from each other, showing more differences with other groups. Rotifera, Arthropoda, and Chordata were the top three phyla, while Keratella, Macrothrix, and Brachionus were the dominant genera. Mantel test analysis showed that COD and transparency were important environmental factors that shaped the Rotifera community structure of Dianchi Lake. In conclusion, this study provides insights on conserving the diversity of zooplankton communities in Dianchi Lake, especially by controlling COD and maintaining water transparency, in order to preserve its ecological resources and economic significance.

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Section: Introductionmentioning

confidence: 99%

Metabarcoding of zooplankton communities of Dianchi Lake based on the mitochondrial cytochrome oxidase subunit 1 gene

Cen,

Xu,

Yin

et al. 2024

Front. Microbiol.

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“…Environmental DNA (eDNA) metabarcoding has provided an effective method for the monitoring of aquatic biodiversity in recent years [26][27][28][29]. According to the differences in DNA fragments between species, eDNA metabarcoding discloses the environmental biome structure rapidly and accurately, which vastly promotes the efficiency of phytoplankton monitoring, and has been widely applied in studying phytoplankton diversity [30][31][32][33][34]. However, eDNA metabarcoding has rarely been applied to Dianchi Lake; Zhang et al [35] discussed the precision of eDNA metabarcoding in the monitoring of eukaryotic algae and identified 75 genera of eukaryotic algae in Dianchi Lake, and Lin et al [36] explored the distribution patterns of phytoplankton and the influence factors in Dianchi Lake and its three inflow rivers in the intermediate water season.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variations in Phytoplankton Community in Dianchi Lake Using eDNA Metabarcoding

Lin,

Xu,

Shen

et al. 2023

Water

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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.

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Impacts of anthropogenic activities on eukaryotic phytoplankton communities in Panlong River via eDNA biomonitoring

Lin,

Shen,

et al. 2024

Hydrobiologia

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eDNA metabarcoding revealed the seasonal and spatial variation of phytoplankton functional groups in the Chai river and their relationship with environmental factors

Cited by 5 publications

References 46 publications

Metabarcoding of zooplankton communities of Dianchi Lake based on the mitochondrial cytochrome oxidase subunit 1 gene

Metabarcoding of zooplankton communities of Dianchi Lake based on the mitochondrial cytochrome oxidase subunit 1 gene

Spatial and Temporal Variations in Phytoplankton Community in Dianchi Lake Using eDNA Metabarcoding

Impacts of anthropogenic activities on eukaryotic phytoplankton communities in Panlong River via eDNA biomonitoring

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