Biogeography and life-history traits drive scalable prediction of plant invasions on islands

Biogeography and life-history traits drive scalable prediction of plant invasions on islands | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecography This is a preprint and has not been peer reviewed. Data may be preliminary. 12 May 2026 V1 Latest version Share on Biogeography and life-history traits drive scalable prediction of plant invasions on islands Authors : Raúl Orihuela-Rivero 0000-0001-6682-0106 [email protected] , Louis Jay-García 0000-0003-3764-7919 [email protected] , Elisa Charlier [email protected] , Jorge Alfredo Reyes-Betancort [email protected] , and Jairo Patiño [email protected] Authors Info & Affiliations https://doi.org/10.22541/authorea.15003142/v1 42 views 13 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Invasive non-native plant species pose a major threat to island biodiversity, yet existing risk assessment tools are often resource-intensive and difficult to apply at large scales. Here, we develop a predictive, low-effort, and scalable model to assess invasion risk in vascular plants on islands, using the Canary Islands as a model system. We compiled taxonomic, biological and biogeographical data for 578 non-native plant species with known invasion status, and trained a Bayesian Additive Regression Trees (BART) model. The resulting model was validated and applied to predict invasion probabilities for 8,739 species recorded in Europe, including both native and non-native taxa, not yet present in the archipelago. Following a reassessment to correct misclassified species introduced to the Canaries, the final model showed high predictive performance (AUC = 0.849, TSS = 0.584). Key predictors included biome, life form, family, dispersal mechanism and invaded range size. The model identified 248 plant species as potentially invasive, including 23 high-confidence taxa lacking regulatory status. This approach demonstrates that BART models can effectively support early detection and proactive prioritization of invasive non-native species. It offers a practical tool for updating species warning- and blacklists, guiding monitoring efforts, and informing biosecurity decisions in data-limited regions, particularly on islands. Supplementary Material File (supplemental-information.docx) supplemental-information Download 1.13 MB Information & Authors Information Version history V1 Version 1 12 May 2026 Collection Ecography Keywords ecology taxonomy island evolution invasion biology botany zoology Botany Ecology Evolution Invasion Biology island biogeography evolution botany conservation biology invasion biology metacommunities macroecology species distributions diversity conservation climate change Bayesian Additive Regression Trees biological invasions blacklist Canary Islands invasion risk prediction plant traits Spatial ecology temporal ecology biogeography macroecology Botany Ecology Evolution Invasion Biology macroecology biogeography ecology taxonomy island evolution invasion biology botany zoology island biogeography evolution botany conservation biology invasion biology environmental science human-nature interactions Island Biogeography Macroecology metacommunities macroecology species distributions diversity conservation climate change Authors Affiliations Raúl Orihuela-Rivero 0000-0001-6682-0106 [email protected] View all articles by this author Louis Jay-García 0000-0003-3764-7919 [email protected] View all articles by this author Elisa Charlier [email protected] Island Ecology and Evolution Research Group, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), La Laguna, Spain View all articles by this author Jorge Alfredo Reyes-Betancort [email protected] Island Ecology and Evolution Research Group, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), La Laguna, Spain View all articles by this author Jairo Patiño [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 42 views 13 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Raúl Orihuela-Rivero, Louis Jay-García, Elisa Charlier, et al. Biogeography and life-history traits drive scalable prediction of plant invasions on islands. Authorea . 12 May 2026. DOI: https://doi.org/10.22541/authorea.15003142/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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