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Occurrence cubes : a new paradigm for aggregating species occurrence data

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Abstract
In this paper we describe a method of aggregating species occurrence data into what we coined “occurrence cubes”. The aggregated data can be perceived as a cube with three dimensions - taxonomic, temporal and geographic - and takes into account the spatial uncertainty of each occurrence. The aggregation level of each of the three dimensions can be adapted to the scope. Built on Open Science principles, the method is easily automated and reproducible, and can be used for species trend indicators, maps and distribution models. We are using the method to aggregate species occurrence data for Europe per taxon, year and 1km2 European reference grid, to feed indicators and risk mapping/modelling for the Tracking Invasive Alien Species (TrIAS) project.

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MLA
Oldoni, Damiano, et al. “Occurrence Cubes : A New Paradigm for Aggregating Species Occurrence Data.” BioRxiv, 2020, doi:10.1101/2020.03.23.983601.
APA
Oldoni, D., Groom, Q., Adriaens, T., Davis, A., Reyserhove, L., Strubbe, D., … Desmet, P. (2020). Occurrence cubes : a new paradigm for aggregating species occurrence data. bioRxiv. https://doi.org/10.1101/2020.03.23.983601
Chicago author-date
Oldoni, Damiano, Quentin Groom, Tim Adriaens, Amy Davis, Lien Reyserhove, Diederik Strubbe, Sonia Vanderhoeven, and Peter Desmet. 2020. “Occurrence Cubes : A New Paradigm for Aggregating Species Occurrence Data.” BioRxiv. https://doi.org/10.1101/2020.03.23.983601.
Chicago author-date (all authors)
Oldoni, Damiano, Quentin Groom, Tim Adriaens, Amy Davis, Lien Reyserhove, Diederik Strubbe, Sonia Vanderhoeven, and Peter Desmet. 2020. “Occurrence Cubes : A New Paradigm for Aggregating Species Occurrence Data.” BioRxiv. doi:10.1101/2020.03.23.983601.
Vancouver
1.
Oldoni D, Groom Q, Adriaens T, Davis A, Reyserhove L, Strubbe D, et al. Occurrence cubes : a new paradigm for aggregating species occurrence data. bioRxiv. 2020.
IEEE
[1]
D. Oldoni et al., “Occurrence cubes : a new paradigm for aggregating species occurrence data,” bioRxiv. 2020.
@misc{8655526,
  abstract     = {In this paper we describe a method of aggregating species occurrence data into what we coined “occurrence cubes”. The aggregated data can be perceived as a cube with three dimensions - taxonomic, temporal and geographic - and takes into account the spatial uncertainty of each occurrence. The aggregation level of each of the three dimensions can be adapted to the scope. Built on Open Science principles, the method is easily automated and reproducible, and can be used for species trend indicators, maps and distribution models. We are using the method to aggregate species occurrence data for Europe per taxon, year and 1km2 European reference grid, to feed indicators and risk mapping/modelling for the Tracking Invasive Alien Species (TrIAS) project.},
  articleno    = {983601},
  author       = {Oldoni, Damiano and Groom, Quentin and Adriaens, Tim and Davis, Amy and Reyserhove, Lien and Strubbe, Diederik and Vanderhoeven, Sonia and Desmet, Peter},
  issn         = {2692-8205},
  language     = {eng},
  pages        = {12},
  series       = {bioRxiv},
  title        = {Occurrence cubes : a new paradigm for aggregating species occurrence data},
  url          = {http://dx.doi.org/10.1101/2020.03.23.983601},
  year         = {2020},
}

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