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    772 Aquatic Insects - LACIA-INPA

    DOI Info:

    • DOI: 10.18728/igb-fred-772.2
    • Citation suggestion: Renato Tavares Martins, Ricardo Koroiva, Paulo Vilela Cruz, Jeane Marcelle Cavado Nascimento, Neusa Hamada (2022-11-15 ) Aquatic Insects - LACIA-INPA. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/igb-fred-772.2
    • Previous DOI version :10.18728/igb-fred-746.1
    • DOI history

      Date DOI PackageId Note
      2022-05-0310.18728/igb-fred-711.0711
      2022-07-0410.18728/igb-fred-746.1746
      2022-11-1510.18728/igb-fred-772.2772this package latest
    Title
    Aquatic Insects - LACIA-INPA
    Sampling interval
    Irregular Interval
    Description

    Aquatic Insects – LACIA-INPA

     

    Study site: South America. Authors: Renato Tavares Martins, Ricardo Koroiva, Paulo Vilela Cruz, Jeane Marcelle Cavado Nascimento & Neusa Hamada. More accurate coordinates, species names and sampling days available upon communication with the authors.

     

    Contact details:

    Ricardo Koroiva. E-mail: ricardo.koroiva@gmail.com. ORCID: https:/orcid.org/0000-0002-6658-0824. Affiliation: Universidade Federal da Paraíba - UFPB Instituto Nacional do Semiárido - INSA.

    Paulo Vilela Cruz. E-mail: pvilelacruz@gmail.com. ORCID: https://orcid.org/0000-0003-2426-4628. Affiliation: Universidade Federal de Rondônia - UNIR Instituto Nacional de Pesquisas da Amazônia - INPA.

    Jeane Marcelle Cavalcante Do Nascimento. E-mail: jeanemarcelle@gmail.com. ORCID: https://orcid.org/0000-0002-5428-7495. Affiliation: Instituto Nacional de Pesquisas da Amazônia - INPA.

    Renato Tavares Martins. E-mail: martinsrt@gmail.com. ORCID: https:/orcid.org/0000-0003-3464-7905. Affiliation: Instituto Nacional de Pesquisas da Amazônia - INPA.

    Neusa Hamada. E-mail: neusaha@gmail.com. ORCID: https://orcid.org/0000-0002-3526-5426. Affiliation: Instituto Nacional de Pesquisas da Amazônia - INPA.

     

    Data contributors:

    Couceiro/Hamada

    Martins/Hamada

    Hamada

    Hamada/Brito

    Hamada/Martins

    Paulo Vilela Cruz/Neusa Hamada

    Ricardo Koroiva

     

     

    Coordinates of the bounding box (ulx, uly, lrx, lry): -108.5, 40.43, -35.6, -31.18

    Centroid coordinates (x,y): -56.733287,-3.666366

    Number of records: 3885

     

    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: 202,311,314-316,319,321-325,327-329,331,332,339,343,344,346,352

     

    Study site
    _global
    GeoNode references

    GeoNode layers

    • Aquatic_Insects_LACIA_INPA
    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 11:26.pdfODC-By Download

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    Aquatic_Insects_-_LACIA-INPA.csv 15. Nov. 2022 11:26 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.

    • Aquatic_Insects_-_LACIA-INPA.xml
    • Aquatic_Insects_-_LACIA-INPA.eml

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    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)