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        <titl xml:lang="sv"></titl>
        <parTitl xml:lang="en">Swedish Fungal Occurrence Records (1975–March 2024, filtered from GBIF)</parTitl>
        <IDNo agency="SND">doi-10-17044-scilifelab-30042580-0</IDNo>
        <IDNo agency="DOI">https://doi.org/10.17044/SCILIFELAB.30042580</IDNo>
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        <producer xml:lang="en" abbr="SND">Swedish National Data Service</producer>
        <producer xml:lang="sv" abbr="SND">Svensk nationell datatjänst</producer>
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      <holdings URI="https://doi.org/10.17044/SCILIFELAB.30042580">Landing page</holdings>
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    <citation>
      <titlStmt>
        <titl xml:lang="sv"></titl>
        <parTitl xml:lang="en">Swedish Fungal Occurrence Records (1975–March 2024, filtered from GBIF)</parTitl>
        <IDNo agency="SND">doi-10-17044-scilifelab-30042580-0</IDNo>
        <IDNo agency="DOI">https://doi.org/10.17044/SCILIFELAB.30042580</IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty xml:lang="en" affiliation="Science for Life Laboratory">Gomes de Almeida, Filipe</AuthEnty>
        <AuthEnty xml:lang="en" affiliation="Science for Life Laboratory">Baggström, Adrian</AuthEnty>
        <AuthEnty xml:lang="en" affiliation="Science for Life Laboratory">Andermann, Tobias</AuthEnty>
      </rspStmt>
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        <distrbtr xml:lang="en" abbr="SND" URI="https://snd.se">Swedish National Data Service</distrbtr>
        <distrbtr xml:lang="sv" abbr="SND" URI="https://snd.se">Svensk nationell datatjänst</distrbtr>
        <distDate xml:lang="en" date="2025-10-13" />
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      <holdings URI="https://doi.org/10.17044/SCILIFELAB.30042580">Landing page</holdings>
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      <abstract xml:lang="en" contentType="abstract">The data of all occurrence data of fungi in Sweden between January 1975 and March of 2024 was retrieved from the Global Biodiversity Information Facility (GBIF 2024, DOI: https://doi.org/10.15468/dl.rdtst7), totaling 4.354.001 occurrence records for 11.643 species. 

A series of cleaning processes were applied. First, using the software R (R Core Team 2023), duplicates and occurrences without longitude, latitude, species key, and date were removed. Second, only records derived from human observation, preserved specimens, and material citation, with coordinate uncertainty smaller than 1 km were maintained. Third, we used the R package CoordinateCleaner (Zizka et al. 2019) to remove suspicious occurrences coordinates falling into a capital city, country centroids, the GBIF headquarters, known biodiversity institutions, the sea, the point 0/0, if the latitude and longitude were equal, or if the occurrence was detected as a spatial outlier.

References: 

GBIF. (2024). "Global Biodiversity Information Facility Occurrence Download." Retrieved Accessed in 2024, from https://doi.org/10.15468/dl.rdtst7.

R Core Team. 2023. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria R Foundation for Statistical Computing.

Zizka, A., D. Silvestro, T. Andermann, J. Azevedo, C. Duarte Ritter, D. Edler, H. Farooq, A. Herdean, M. Ariza and R. Scharn. 2019. CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution 10(5): 744-751.</abstract>
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