Occurrence cubes: a new paradigm for aggregating species occurrence data

Damiano Oldoni; Quentin Groom; Tim Adriaens; Amy J.S. Davis; Lien Reyserhove; Diederik Strubbe; Sonia Vanderhoeven; Peter Desmet

doi:10.1101/2020.03.23.983601

Occurrence cubes: a new paradigm for aggregating species occurrence data

Damiano Oldoni, Quentin Groom, Tim Adriaens, Amy J.S. Davis, Lien Reyserhove, Diederik Strubbe, Sonia Vanderhoeven, Peter Desmet

Onderzoeksoutput: Bijdrage aan tijdschrift › Preprint

Uittreksel

In this paper we describe a method of aggregating species occurrence data into what we coined textquotedblleftoccurrence cubestextquotedblright. 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.

Oorspronkelijke taal	Engels
Aantal pagina’s	12
DOI's	https://doi.org/10.1101/2020.03.23.983601
Publicatiestatus	Gepubliceerd - 25-mrt.-2020

Thematische Lijst 2020

Invasieve soorten
Data & Infrastructuur

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10.1101/2020.03.23.983601Licentie: CC BY

https://www.biorxiv.org/content/early/2020/03/25/2020.03.23.983601Licentie: CC BY

1 Afgerond
1 Actief

B-Cubed - Biodiversity Building Blocks for policy
Desmet, P. (Projectleider), Adriaens, T. (Medewerker), Adriaenssens, V. (Medewerker), Cartuyvels, E. (Medewerker), Delva, S. (Medewerker), Govaert, S. (Medewerker), Hillaert, J. (Medewerker), Huybrechts, P. (Medewerker), Langeraert, W. (Medewerker), Oldoni, D. (Medewerker), Onkelinx, T. (Medewerker), Reyserhove, L. (Medewerker), Strubbe, D. (Medewerker), Van Calster, H. (Medewerker), Van Daele, T. (Medewerker), Van den Broeck, F. (Medewerker) & Vanderhaeghe, F. (Medewerker)
1/03/23 → 30/09/26
Project: Evinbo
TrIAS - Tracking Invasive Alien Species (EVINBO)
Adriaens, T. (Projectleider), D'hondt, B. (Medewerker), Delva, S. (Medewerker), Demolder, H. (Medewerker), Desmet, P. (Medewerker), Devisscher, S. (Medewerker), Oldoni, D. (Medewerker), Reyserhove, L. (Medewerker), Speybroeck, J. (Medewerker), Van Hoey, S. (Medewerker), Van Landuyt, W. (Medewerker) & Verzelen, Y. (Medewerker)
1/01/17 → 31/12/21
Project: Evinbo

3 Paper/Powerpoint/Abstract
1 Rapport niet door INBO uitgegeven
1 Poster
1 A2: Artikel in een tijdschrift met peer review, dat niet inbegrepen is in A1

B-Cubed: Leveraging analysis-ready biodiversity datasets and cloud computing for timely and actionable biodiversity monitoring
Groom, Q., Abraham, L., Adriaens, T., Breugelmans, L., Clarke, D. A., Fernández, M. A., Hendrickx, L., Hui, C., Kumschick, S., Martini, M., McGeoch, M., Metodiev, T., Miller, J., Oldoni, D., Pereira, H. M., Preda, C., Robertson, T., Rocchini, D., Seebens, H. & Teixeira, H. & 5 anderen, Trekels, M., Wilson, J. R., Yovcheva, N., Zengeya, T. & Desmet, P., 9-aug.-2023, blz. 1-3. 3 blz.
Onderzoeksoutput: Bijdrage aan congres › Paper/Powerpoint/Abstract

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1022 Downloads (Pure)
Tracking Invasive Alien Species (TrIAS): Building a data-driven framework to inform policy. Contract - BR/165/A1/TrIAS. Final Report.
Groom, Q. J., Vanderhoeven, S., Eggermont, H., Coupremanne, M., Adriaens, T., Desmet, P., Reyserhove, L., Oldoni, D., Strubbe, D., Backeljau, T., Barbier, Y., Brosens, D., Davis, A., Lens, L., Monty, A., Mahy, G., Jacquemart, A.-L., Verleye, T., Van Hoey, G. & Van De Kerchove, R. & 6 anderen, Backeljau, T., Dispas, M., Vilain, A., De Troch, R., Van Schaeybroeck, B. & Termonia, P., 2022, Brussels, Belgium. 52 blz.
Onderzoeksoutput: Boek/rapport › Rapport niet door INBO uitgegeven

Open Access
Bestand
A pipeline to feed headline indicators on the state of invasions and to prioritize emerging alien species for risk assessment
Adriaens, T., Van Daele, T., Groom, Q., Vanderhoeven, S., Davis, A., Strubbe, D., Reyserhove, L., Desmet, P. & Oldoni, D., 15-sep.-2020. 1 blz.
Onderzoeksoutput: Bijdrage aan congres › Poster

Open Access
Bestand

Dit citeren

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title = "Occurrence cubes: a new paradigm for aggregating species occurrence data",

abstract = "In this paper we describe a method of aggregating species occurrence data into what we coined textquotedblleftoccurrence cubestextquotedblright. 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.",

author = "Damiano Oldoni and Quentin Groom and Tim Adriaens and Davis, {Amy J.S.} and Lien Reyserhove and Diederik Strubbe and Sonia Vanderhoeven and Peter Desmet",

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T1 - Occurrence cubes: a new paradigm for aggregating species occurrence data

AU - Oldoni, Damiano

AU - Groom, Quentin

AU - Adriaens, Tim

AU - Davis, Amy J.S.

AU - Reyserhove, Lien

AU - Strubbe, Diederik

AU - Vanderhoeven, Sonia

AU - Desmet, Peter

PY - 2020/3/25

Y1 - 2020/3/25

N2 - In this paper we describe a method of aggregating species occurrence data into what we coined textquotedblleftoccurrence cubestextquotedblright. 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.

AB - In this paper we describe a method of aggregating species occurrence data into what we coined textquotedblleftoccurrence cubestextquotedblright. 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.

U2 - 10.1101/2020.03.23.983601

DO - 10.1101/2020.03.23.983601

M3 - Preprint

JO - bioRxiv

JF - bioRxiv

ER -

Occurrence cubes: a new paradigm for aggregating species occurrence data

Uittreksel

Thematische Lijst 2020

Toegang verkrijgen tot document

Vingerafdruk

Projecten

B-Cubed - Biodiversity Building Blocks for policy

TrIAS - Tracking Invasive Alien Species (EVINBO)

Onderzoeksoutput

B-Cubed: Leveraging analysis-ready biodiversity datasets and cloud computing for timely and actionable biodiversity monitoring

Tracking Invasive Alien Species (TrIAS): Building a data-driven framework to inform policy. Contract - BR/165/A1/TrIAS. Final Report.

A pipeline to feed headline indicators on the state of invasions and to prioritize emerging alien species for risk assessment

Dit citeren