Data from: Environmental DNA metabarcoding revealed the impacts of anthropogenic activities on phytoplankton diversity in Dianchi Lake and its three inflow rivers

Phytoplankton diversity is closely related to environmental variables and has been widely used in ecological health assessment of rivers and lakes. Combining the 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 a 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). The OTU table is the original table about phytoplankton taxa. 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.

浮游植物多样性与环境变量紧密关联，已被广泛应用于河流与湖泊的生态健康评估工作。依托基于DNA的物种鉴定技术与高通量测序技术的双重优势，环境DNA（eDNA）宏条形码技术为水生生态系统的生物多样性监测提供了全新的技术路径。然而此前鲜有研究借助该技术，探究湖泊与其入流河流间浮游植物多样性的变异特征与相似性关系，以及环境变量对浮游植物群落的影响。本研究采用eDNA宏条形码技术，以中国污染最为严重的城市湖泊之一滇池及其主要入流河流（盘龙江、宝象河、柴河）为研究对象，系统探究浮游植物的空间分布格局，以及环境变量对浮游植物多样性的调控作用。操作分类单元（OTU）表为记录浮游植物分类群的原始数据表。本研究共检测得到243个独立的浮游植物分类群，涵盖9个门、30个纲、84个目与132个科；入流河流的分类群丰富度高于滇池。