Prioritizing management actions for invasive non-native plants through expert-based knowledge and species distribution models

Given the high number of non-native plants that are being introduced worldwide and the time required to process formal pest risk analyses, a framework for the prioritization of management actions is urgently required. We therefore propose a framework for a replicable and standardized prioritization for management actions (eradication, control and monitoring) of invasive non-native plants, combining expert knowledge, current and future climatic suitability estimated by species distribution models (SDMs), clustering and ordination techniques. Based on expert consultation and using Italy as case study, invasive non-native plant species were selected and three categories of management actions were identified: eradication, control and containment, and monitoring. Finally, two further classes of priorities were proposed for each of the management actions: "high" and "low" priority. Overall, SDMs highlighted a high and very high suitability for Continental and Mediterranean bioregions for most invasive plants. Cluster analysis revealed three distinct clusters with varying levels of suitability for the Italian bioregions. Cluster 1 exhibited a higher suitability across all Italian bioregions, whereas non-native plants grouped in Cluster 2 predominantly featured high suitability in Mediterranean areas. Finally, Cluster 3 showed the lowest suitability values. Two ordination analysis highlighted the variability in bioclimatic suitability for each non-native plant within each cluster, as well as their current distribution pattern. Lastly, a third ordination, integrating bioclimatic suitability and spatial patterns, has allowed the differentiation of management actions for each non-native plant at both national and bioregional scales. Specifically, seven non-native plants were earmarked for eradication action, six for monitoring action, while the remaining species were deemed suitable for control and containment. Our results and the methodology proposed meet the demand for replicable new early warning tools; that is to predict the location of new outbreaks, to establish priorities for eradication, control and containment, and to monitor invasive non-native species.