‹ › ×

    FRED
    • Contact
    • GDPR policy
    • Imprint
    • About
    • Sign Up
    • Login
    • SEARCH
    • Search and find
    • Packages
    • Map
    • By Category ...
      • Study sites
      • Sampling sites
      • Parameters
      • Sampling types
      • Species groups
      • Current DOIs

    810 EPTO in Chinese streams

    DOI Info:

    • DOI: 10.18728/igb-fred-810.3
    • Citation suggestion: https://orcid.org/0000-0002-7884-097X, Fengzhi He, Qinghua Cai (2023-01-12 ) EPTO in Chinese streams. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-810.3
    • Previous DOI version :10.18728/igb-fred-788.2
    • DOI history

      Date DOI PackageId Note
      2022-05-0310.18728/igb-fred-717.0717
      2022-07-0410.18728/igb-fred-752.1752
      2022-11-1510.18728/igb-fred-788.2788
      2023-01-1210.18728/igb-fred-810.3810this package latest
    Title
    EPTO in Chinese streams
    Sampling interval
    Irregular Interval
    Description

    EPTO in Chinese streams

     

    Study site: China. Authors: Fengzhi He & Qinghua Cai.

     

    Contact details:

    Fengzhi He. E-mail: fengzhi.he@igb-berlin.de. ORCID: https:/orcid.org/0000-0002-7594-8205. Affiliation: Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).

    Qinghua Cai.   Affiliation: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China. University of Chinese Academy of Sciences, Beijing, 100049, China.

     

     

    Coordinates of the bounding box (ulx, uly, lrx, lry): 99.4022777777778, 40.3630333333333, 117.7515, 25.460583

    Centroid coordinates (x,y): 107.275222,29.383597

    Number of records: 4062

     

    The dataset includes records in areas: 

    Not protected on the observation date (0)

    Protected on the observation date (1)

    Protected on a date following the observation date (2)

    using the November 2022 version of the Protected Planet WDPA WD-OECM dataset 

        (Protected Planet: World Database on Protected Areas (WDPA) 

        and World Database on Other Effective Area-based Conservation Measures (WD-OECM), UNEP-WCMC and IUCN, 2022). 

        Please see publication for further information.

     

    Freshwater Ecoregions of the World (FEOW, Abell et al., 2008) covered: 636,725,764-766

     

    Taxonomic focus of the study: all benthic community

     

    Survey methods: Kick net, Surber net, aquatic D-net

     

    Study site
    _global
    GeoNode references

    GeoNode layers

    • EPTO_in_Chinese_streams
    Contact
    Afroditi Grigoropoulou
    Licence for data
    All rights reserved. Please send a request to Afroditi Grigoropoulou if you like to use this data. Mind our data policy: IGB Data Policy

    Metadata files

    TitleUpload dateFiletypeLicenceActions
    Column_explanation.pdf15. Nov. 2022 14:07.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    EPTO_in_Chinese_streams.csv 15. Nov. 2022 14:07 datatable: .csv Download

    Machine Readable Metadata Files

    FRED provides all metadata of this package in a maschine readable format. There is a pure XML file and one EML file in Ecological Metadata Language. Both files are published under the freeODC-ByLicence.

    • EPTO_in_Chinese_streams.xml
    • EPTO_in_Chinese_streams.eml

    You are about to leaving FRED and visting a third party website. We are not responsible for the content or availability of linked sites.

    To remain on our site, click Cancel.

    Parsing data File

    Estimated Time:

    Why does it take so much time?

    While parsing a file, the database has to perform various tasks, some of them needs a lot of CPU and memory for larger files.

    • preprocessing: means automatic detection of headlines, table body, format values or csv-separators
    • copying: means read the file cell by cell and copy all elements to the database. During this format settings can be calculated (for example iso-time)
    • analyzing: check out for different data types (can be time, numeric or text)