Ex ante analyses to predict the efficacy of natural enemies in biological control

Ex ante analyses to predict the efficacy of natural enemies in biological control | 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 Article Ex ante analyses to predict the efficacy of natural enemies in biological control Andrew Paul Gutierrez, Luigi Ponti, Peter Neuenschwander, John S. Yaninek, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7456361/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Global annual losses from invasive species are more than one trillion US$. Furthermore, the success rate of biological control (BC) efforts against invasive species is historically low, largely because the pre-release efficacy of putative natural enemies is unknown. Reviews of prior BC efforts have not led to the development of a roadmap to increase the success rate. As an alternative, we deconstructed the highly successful biological control of the invasive cassava mealybug (CM) and cassava green mite (CGM) in Africa using a mechanistic meta population tri-trophic physiologically based demographic model (PBDM) that predicts the efficacy of the natural enemies across vast ecological zones. The model enabled parsing the contribution of each natural enemy and native fungal pathogens to the control of CM and CGM and the recovery of cassava yield. The analysis reveals control would have failed if only some of the natural enemy species had been introduced. PBDMs analyses of other BC efforts show why success or failure occurred and strongly suggests similar analyses could predict pre-release efficacy of natural enemies in future BC programs globally against invasive plant and arthropod species. Such analyses would be an important component in increasing global food security. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Plant sciences biological control physiologically based demographic model time varying life tables bioeconomic analysis Full Text Additional Declarations No competing interests reported. Supplementary Files Exantebiocontrolsupplementaryinformation82225.docx Cite Share Download PDF Status: Published Journal Publication published 29 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 30 Sep, 2025 Reviews received at journal 30 Sep, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor invited by journal 28 Aug, 2025 Editor assigned by journal 27 Aug, 2025 Submission checks completed at journal 26 Aug, 2025 First submitted to journal 25 Aug, 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. 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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-7456361","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":509797558,"identity":"2d5a4d4a-c345-4b26-afc3-a786bd126d28","order_by":0,"name":"Andrew Paul Gutierrez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABJ0lEQVRIie2Pv0rFMBSHT7mgSyWbpFTsK6QUehX6CD6AY7LU5SKCy90UhLood634CC6FQudeCvcuLV0jLhXBTegiZDT9MziY4iiYb0hOwvn4nQOg0fxB0M1usxZQyNK4Hn66g16oFby9c99M2IwKBbA6kxK1Qk7KmQdQjk+pkLz/n1DwYscG4IdzVESvnyI49+on1jYEHLSfK5Szd0tA6x3H7NY7oOGlzz9SLAdzHx6pQqE+NqFlCTciG9OCZbxKOoWSF4XiNHNhAr9K6vWgpHGViknltE8pKclZZLVSSdB9NpmC+cK3TbJxE84iG8KQxXwvO6IEK3dBcbf+snBIvZVFELDVqkqfxTJwkP2zMo43XDOzD+478UT7NwzRB+e/69ZoNJp/wxcDHGiFdNMmqgAAAABJRU5ErkJggg==","orcid":"","institution":"University of California","correspondingAuthor":true,"prefix":"","firstName":"Andrew","middleName":"Paul","lastName":"Gutierrez","suffix":""},{"id":509797559,"identity":"684cc42a-1dcd-482c-bfb0-ca9fb53e4a98","order_by":1,"name":"Luigi Ponti","email":"","orcid":"","institution":"Centro Ricerche Casaccia","correspondingAuthor":false,"prefix":"","firstName":"Luigi","middleName":"","lastName":"Ponti","suffix":""},{"id":509797565,"identity":"8591e5f7-d15c-403a-98f3-f619773716bd","order_by":2,"name":"Peter Neuenschwander","email":"","orcid":"","institution":"International Institute of Tropical Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Neuenschwander","suffix":""},{"id":509797566,"identity":"fccd1b2f-8627-452e-aa1f-441ee50bf96b","order_by":3,"name":"John S. 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