%0 Dataset
%T A monthly resolved 16S and 18S rRNA sequencing dataset of planktonic microbial communities from Danjiangkou Reservoir, China (2023–2024)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U https://www.ncdc.ac.cn/portal/metadata/98942754-4936-4a1a-90cb-e243900e8e56
%W NCDC
%R 10.12072/ncdc.db7826.2026
%A LV Xucong
%A YUAN Huatao
%A DONG Jing
%A GAO Xiaofei
%A ZHANG Jingxiao
%A zhu peng hui
%A GAO Yunni
%A LI Xuejun
%K microbial diversity;water ecosystem
%X Microbial communities are an important part of freshwater ecosystems and play an important role in biogeochemical cycles, organic matter transformation, and water quality regulation. However, medium-and long-term, high-temporal resolution microbial community data sets in large freshwater reservoirs are still lacking. Danjiangkou Reservoir is an important freshwater reservoir in China and an important water source for the Middle Route of the South-to-North Water Diversion Project. Establishing systematic microbial data resources is of great significance for ecological monitoring and water resources management. This study constructed a month-scale microbial community dataset covering 2023-2024 in Danjiangkou Reservoir. During the study, monthly surface water samples were collected at 5 representative sampling points in the reservoir, and high-throughput sequencing technology for 16S ribosomal RNA genes and 18S ribosomal RNA genes was used to characterize bacterial and eukaryotic microbial communities. The dataset includes raw sequencing data, amplicon sequence variation (ASV) abundance matrix, and classification annotation files. Quality control procedures, including sequence quality filtering, removal of low-quality reads, and taxonomic annotation assessment, were performed to ensure the reliability and usability of the dataset. This dataset provides a comprehensive resource for assessing microbial biodiversity, supporting freshwater ecosystem monitoring, facilitating comparative studies of reservoir microbial communities, and promoting the integration and reuse of microbial data in broader ecological and environmental research.