A global dataset of taxa to support calibration of invasion risk screening applications

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.