A Spatial Probability Model for the Arrival and Establishment of Coconut Rhinoceros Beetle

A Spatial Probability Model for the Arrival and Establishment of Coconut Rhinoceros Beetle | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Spatial Probability Model for the Arrival and Establishment of Coconut Rhinoceros Beetle Sulav Paudel, John M. Kean, Craig B. Phillips, Sarah Mansfield, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8428630/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Coconut rhinoceros beetle (CRB, Oryctes Rhinoceros , L.) is a destructive pest of coconut and oil palms globally. Native to Southeast Asia, the pest has progressively invaded the Pacific and more recently non-Pacific regions, causing severe ecological and economic damage. After decades of suppression through biological control with a viral pathogen, a new wave of invasions began in 2007, largely driven by human-mediated dispersal. We describe a spatial probability model for the introduction and establishment of CRB by integrating ecological suitability and human-mediated pathways that address critical gaps in existing CRB risk assessments. The model was first developed and tested using data from Vanuatu and subsequently validated with independent datasets from Solomon Islands and Mexico. The model’s performance was evaluated using multiple approaches, including correlation analysis, risk distribution metrics, precision-recall curves (PR AUC) and spatial risk maps. Predictor variables showed significant correlations with CRB invasion score, with population and port connectivity being dominant drivers in Vanuatu and the Solomon Islands, while elevation suitability was more influential in Mexico. Probability score distribution revealed that most Global Biodiversity Information Facility (GBIF) presence points fell above the 90th percentile, and none had zero CRB scores, aligning with model expectations. Similarly, known historical invasion areas for all three countries closely aligned with high-risk sites predicted by the current model. The model achieved high predictive performance, with PR AUC values exceeding 0.99 across all regions. Coconut rhinoceros beetle spatial model risk assessment precision recall curve Global Biodiversity Information Facility Full Text Supplementary Files SupplementaryInformationCRBmodelpaper.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Jan, 2026 Reviewers invited by journal 19 Jan, 2026 Editor invited by journal 17 Jan, 2026 Editor assigned by journal 23 Dec, 2025 First submitted to journal 22 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8428630","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":577131036,"identity":"51299e30-53b0-40a0-bb2e-f208c6cbce26","order_by":0,"name":"Sulav Paudel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABIUlEQVRIie2RMWuDQBTHTwp2OXA9KdSv8LqUBFryVRQhk5A1gw0XBJ2aruZb+BGUB+dykPUKDpWCsyCUZCl1CKaQI7Rbof6m47378b97j5CRkT/JFT8eXCNvT+X8gmIMCinSXytIf6I4qbfuKKkcKP0cH8KnhWVh0S3DilgJN+v9uQLKi24oae4y2bgYiHK6Tee+LUVDmMyvgWkU5nE7JWhkKgAMTAGgKNhrjn3LNRloHxYdemWWqUWLk08Bs92uOwyKq/mM8mLWEvT6lD4rDgFIYJ5SNFMAWceTFhp/Kxsonjc5MDW/n3KBlMkitvm54iQ+KndZPW5Kv37bf6zAesH3Vx7irZVEwtZM7Jg15ONQo99WpmNQVhcujYyMjPxXvgDannYcSra6IgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7562-2846","institution":"AgResearch Ltd Lincoln Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Sulav","middleName":"","lastName":"Paudel","suffix":""},{"id":577131037,"identity":"df8f0498-e06c-4239-9dc9-8db59e53ca25","order_by":1,"name":"John M. 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Native to Southeast Asia, the pest has progressively invaded the Pacific and more recently non-Pacific regions, causing severe ecological and economic damage. After decades of suppression through biological control with a viral pathogen, a new wave of invasions began in 2007, largely driven by human-mediated dispersal. We describe a spatial probability model for the introduction and establishment of CRB by integrating ecological suitability and human-mediated pathways that address critical gaps in existing CRB risk assessments. The model was first developed and tested using data from Vanuatu and subsequently validated with independent datasets from Solomon Islands and Mexico.\u003c/p\u003e \u003cp\u003eThe model\u0026rsquo;s performance was evaluated using multiple approaches, including correlation analysis, risk distribution metrics, precision-recall curves (PR AUC) and spatial risk maps. Predictor variables showed significant correlations with CRB invasion score, with population and port connectivity being dominant drivers in Vanuatu and the Solomon Islands, while elevation suitability was more influential in Mexico. Probability score distribution revealed that most Global Biodiversity Information Facility (GBIF) presence points fell above the 90th percentile, and none had zero CRB scores, aligning with model expectations. Similarly, known historical invasion areas for all three countries closely aligned with high-risk sites predicted by the current model. 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