Dataset Information

Data collected in an integrated ecological survey of rotifer communities and corresponding environmental variables in the highly polluted Haihe River Basin, China.

ABSTRACT: Here we presented two datasets (biological and environmental datasets) collected in a comprehensive large geographical scale (approximately 1.1×10⁵ km²) survey of rivers/streams in the Haihe River Basin (HRB), which has become the most polluted river basin in past two decades in China. The survey selected a total of 94 representative sampling sites in the plain region of HRB, where environmental pollution is more severe than the mountain region. The biological dataset contains the information on the identified rotifer species and their abundance, while the environmental dataset provides the measured environmental variables at each sampling site. Based on this ecological survey, we identified a total of 91 rotifer species and their abundance, as well as abundance of two crucial taxonomic groups on rotifers' food webs (i.e., protozoans and crustaceans), and also presented seven environmental variables, particularly those associated with nitrogen and phosphorus pollution.

SUBMITTER: Xiong W

PROVIDER: S-EPMC5767906 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Data collected in an integrated ecological survey of rotifer communities and corresponding environmental variables in the highly polluted Haihe River Basin, China.

Xiong Wei W Li Jie J Yang Yuzhan Y Wang Weimin W Shan Baoqing B Zhan Aibin A

Data in brief 20180103

Here we presented two datasets (biological and environmental datasets) collected in a comprehensive large geographical scale (approximately 1.1×10<sup>5</sup> km<sup>2</sup>) survey of rivers/streams in the Haihe River Basin (HRB), which has become the most polluted river basin in past two decades in China. The survey selected a total of 94 representative sampling sites in the plain region of HRB, where environmental pollution is more severe than the mountain region. The biological dataset conta ...[more]

PMID: 29349109

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Project description:Risks of pathogenic bacteria to the health of both human beings and water ecosystems have been widely acknowledged. However, traditional risk assessment methods based on fecal indicator bacteria and/or pure culture are not comprehensive at the community level, mainly owing to the limited taxonomic coverage. Here, we combined the technique of high-throughput sequencing and the concept of metacommunity to assess the potential pathogenic bacterial communities in an economically and ecologically crucial but highly polluted river-the North Canal River (NCR) in Haihe River Basin located in North China. NCR presented a significant environmental gradient, with the highest, moderate, and lowest levels of pollution in the up-, middle, and downstream. After multiple analyses, we successfully identified 48 genera, covering nine categories of potential pathogens (mainly human pathogens). The most abundant genus was Acinetobacter, which was rarely identified as a pathogen bacterium in previous studies of NCR. At the community level, we observed significant geographical variation of community composition and structure. Such a high level of geographical variation was mainly derived from differed abundance of species among sections along the river, especially the top seven Operational Taxonomic Units (OTUs). For example, relative abundance of OTU1 (Gammaproteobacteria/Acinetobacter) increased significantly from upstream towards downstream. Regarding the underlying mechanisms driving community geographical variation, environmental filtering was identified as the dominant ecological process and total nitrogen as the most influential environmental variable. Altogether, this study provided a comprehensive profile of potential pathogenic bacteria in NCR and revealed the underlying mechanisms of community succession. Owing to their high abundance and wide geographical distribution, we suggest that potential pathogens identified in this study should be incorporated into future monitoring and management programs in NCR. By revealing the correlation between environmental factors and community composition, the results obtained in this study have significant implications for early warning and risk assessment of potential pathogen bacteria, as well as management practices in highly polluted river ecosystems.

Project description:The Xiangjiang River Basin is an important part of the Yangtze River Basin and an important area in Hunan Province. Thus, taking steps to protect the ecological sustainability of the Xiangjiang River Basin, such as the construction of the protection of ecological security in Hunan Province and the Yangtze River Protection Law, is important for national projects However, research on the ecological quality of the Xiangjiang River Basin is mostly biased toward the evaluation of ecosystem services or an individual ecological index. Furthermore, a long-term evaluation of multiple indicators is lacking. Therefore, based on Google Earth Engine and geographic detectors, the remote sensing ecological index was used to evaluate this area. The year-by-year research on the Xiangjiang River Basin from 2001 to 2020 clarified its past ecological quality change trend, explored the reasons for the ecological quality change, and provided a basis for protecting its ecological quality. The following results are presented. (1) Regarding spatial distribution, areas with poor ecological environments are mainly distributed at the centers of Chang-Zhu-Tan, Hengyang, and various districts and counties. (2) Regarding the time variation, the ecological quality of the Xiangjiang River Basin from 2001 to 2020 showed a slight downward trend, with a downward slope of approximately - 0.0000357143; a rapid increase, with a growth rate of approximately 0.00395; And an overall improvement over 20 years. The areas with declining ecological quality are mainly located in the Chang-Zhu-Tan urban agglomeration, the city center of Hengyang, and the county centers of various county towns. (3) The factor detection results show that human factors play a key role in population density and land use, with average q values of 0.429 and 0.353, respectively. Among natural factors, elevation and slope play a key role, with average q values of 0.230 and 0.351, respectively; hence, Land use directly affect on the ecological quality in a location. These findings will provide important information for managers to formulate ecological restoration measures for the Xiangjiang River.

Dataset Information

Data collected in an integrated ecological survey of rotifer communities and corresponding environmental variables in the highly polluted Haihe River Basin, China.

Publications

Data collected in an integrated ecological survey of rotifer communities and corresponding environmental variables in the highly polluted Haihe River Basin, China.

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