ArticleScientific data2026
A global dataset of taxa to support calibration of invasion risk screening applications.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A global dataset of taxa to support calibration of invasion risk screening applications.Scientific data · 2026Article
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1 author.
Funding
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Abstract
In invasion science, risk analysis tools are widely used to support the prevention and management of non-native species introductions. Many decision-support frameworks, including those derived from Weed Risk Assessment methodologies such as the Invasiveness Screening Kit (ISK) family of tools, require calibration of outcome scores to distinguish between higher- and lower-risk species. A prerequisite for such calibration is the a priori categorisation of screened species as invasive or non-invasive based on evidence from their introduced range, when applicable. This paper provides a curated global dataset comprising 1,926 taxa identified from 209 applications of the ISK tools across 266 risk assessment areas worldwide, spanning over 21 years. The taxa were assigned de novo a priori invasion-status categorisations through a standardised verification workflow using authoritative databases and scientific literature. All verification steps and categorisation-evidence sources are recorded in the dataset, ensuring reproducibility of the evidence supporting each final taxon-level categorisation. This dataset provides a standardised reference resource to support calibration and comparative analyses of invasion risk screening applications.
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