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                <identifier>oai:data.mendeley.com/pw2m6v6smt.1</identifier>
                <datestamp>2026-02-04T20:28:25Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Halabuk, Andrej</dc:creator>
    <dc:title>Suitability-space species trait dataset for priority invasive alien plants (Ailanthus altissima; Acer negundo) in the Danubian riparian corridor</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>Description 
Woody invasive alien plant species (IAS) can be characterised by their realised suitability niche derived from modelled associations between occurrences and environmental gradients. This dataset serves as a species trait database in the form of model-derived “suitability-space traits” (predictor–suitability association signatures), together with harmonised 1-km predictors, domain tables, and scenario-specific normalised suitability surfaces for the Danubian riparian corridor. This enables users to fit alternative SDM model families, quantify predictor–suitability associations (“species suitability-space traits”), assess transferability across domains, and test bias-correction strategies using accessibility-linked predictors.

The release contains: (1) an AOI polygon (Danubian riparian corridor extent); (2) screened environmental predictors aligned to a common 1-km grid in ETRS89-LAEA (EPSG:3035), provided as transformed (where relevant) and z-standardised rasters (mean 0, SD 1) with the scaling table; (3) species-specific occurrence bundles (Ailanthus altissima; Acer negundo) with three 1-km aggregated domain tables: Danube calibration data using a target-group background (TGB) design (presence vs TGB pseudoabsence; includes spatial CV fold IDs), and two independent evaluation domains (Romania and Serbia) with 1-km presence/absence tables. All tables include a stable 1-km cell identifier (cell_id). (4) Scenario-specific PN suitability GeoTIFFs (Figs. S1–S8): each raster is probability-like normalised to sum to 1 within the Danube AOI.

PN GeoTIFF naming template
PN_{species}_{scenario}_1km_EPSG3035.tif, where species ∈ {Ailanthus_altissima, Acer_negundo} and scenario ∈ {S1_baseline, S2_bias_aware, S3_romania, S4_serbia_riparian}.

Primary occurrence sources (Danube calibration; opportunistic citizen science)
GBIF (Global Biodiversity Information Facility; aggregated backbone and publisher feeds): https://www.gbif.org

iNaturalist: https://www.inaturalist.org

Observation.org: https://observation.org

Pl@ntNet: https://plantnet.org

NABU|naturgucker: https://www.naturgucker.de
 ; https://www.nabu.de

External-domain evaluation data sources
Romania: Anastasiu, P. et al. (2024). Alien plant species distribution in Romania… Biodiversity Data Journal, 12, e119539. https://doi.org/10.3897/BDJ.12.e119539

Serbia: Anđelković, A. A. et al. (2022). Plant invasions in riparian areas… NeoBiota, 71, 23–48. https://doi.org/10.3897/neobiota.71.69716

This dataset accompanies the manuscript by Halabuk et al., “From citizen science records to invasive plant indicators: multi-domain evaluation and scenario-based model selection for the Danube corridor”.

Acknowledgement
Funded by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I01-03-V04-00005.</dc:description>
    <dc:subject>Biological Invasion</dc:subject>
    <dc:contributor>Gasparovicova, Petra</dc:contributor>
    <dc:contributor>Rusnak, Tomas</dc:contributor>
    <dc:contributor>Tomes, Jakub</dc:contributor>
    <dc:contributor>Halada, Lubos</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/pw2m6v6smt.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/pw2m6v6smt.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/pw2m6v6smt</dc:relation>
    <dc:date>2026-02-04T20:28:25Z</dc:date>
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