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    812 Comparative phylogeography of alpine/subalpine Himalopsyche of the Tibeto-Himalayan region: An assessment of mountain geo-biodiversity hypothesis

    Title
    Comparative phylogeography of alpine/subalpine Himalopsyche of the Tibeto-Himalayan region: An assessment of mountain geo-biodiversity hypothesis
    Description

    Distribution range size change from the LGM to present day of H. tibetana, H. digitata, H. gregoryi, and H. platon, which are endemic to the Qinghai-Tibet Plateau. The species distribution modelling of each species at different time scenarios are constructed with an ensemble method using the R package biomod2.

    Keywords
    mountain biodiversity, caddisfly, Himalopsyche, Himalayas, Hengduan mountains
    Study site
    lake level and area data for 31 lakes from 1992 to 2015
    Sampling locations
    H. gregoryi & H. platon
    location
    28.450581302836, 99.84375
    location
    type
    Aquatic insects
    state
    China
    code
    description
    H. tibetana &H. digitata
    location
    27.718384062583826, 84.462890625
    location
    type
    Aquatic insects
    state
    Nepal
    code
    description
    GeoNode references

    GeoNode maps

    • Comparative Phylogeography
    Contact
    Xiling Deng
    Licence for data
    All rights reserved. Please send a request to Xiling Deng if you like to use this data. Mind our data policy: IGB Data Policy

    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.

    • Comparative_phylogeography_of_alpine/subalpine_Himalopsyche_of_the_Tibeto-Himalayan_region:_An_assessment_of_mountain_geo-biodiversity_hypothesis.xml
    • Comparative_phylogeography_of_alpine/subalpine_Himalopsyche_of_the_Tibeto-Himalayan_region:_An_assessment_of_mountain_geo-biodiversity_hypothesis.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)