A delayed response in area-concentrated search can improve foraging success.

A delayed response in area-concentrated search can improve foraging success. | 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 delayed response in area-concentrated search can improve foraging success. Thotsapol Chaianunporn, Thomas Hovestadt This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5294009/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Area-concentrated search (ACS) is a simple movement rule implying that an animal searches for resources using a 'state-dependent correlated random walk'. Accordingly, a forager increases its searching intensity by reducing the directionality of movement ('intensive search mode' or ISM) when it detects a resource item, but if it searches unsuccessfully for a while, it returns to a more straight-line movement to search for new resource locations elsewhere ('extensive search mode' or ESM). In this study, we propose a modified ACS, called delayed-response ACS (dACS), which would be more efficient in resource collecting than the standard ACS. Methods Instead of immediately switching from ESM to ISM upon encountering a resource as done in the standard ACS, an individual foraging in the dACS mode delays this switch for x steps (the delay parameter) so that it continues moving in a straight line for a while before switching to ISM. We simulated the movement paths of an individual with ACS compared with dACS in a continuous landscape with a single resource cluster and varied two different movement parameters, that is x and the half-saturation constant h that affects how quickly the forager returns to straight line movement, and two landscape parameters, i.e., cluster size and resource density. Results Our results show that an individual with a suitable delay parameter x for the dACS achieves substantially higher foraging success than an individual with standard ACS (x=0). Optimal foraging success occurs when x is approximately similar to the patch radius r. This is because, with dACS, an individual can penetrate deeper into a cluster and stay longer within it, ultimately increasing the number of resources collected. Modifying the half-saturation constant h also affects foraging success but effects depend on resource density and cluster size. Generally, h modulates the optimal x value only slightly. Conclusions An individual following a dACS with an adequate delay x can collect more resources from a patch than one using standard ACS; this hold in particular if patches are small or resource density is low. dACS can be interpreted as a survey movement within a resource cluster before switching from ESM to ISM. The dACS rule does not rely on complex spatial memory but only on memorizing whether resources were found or not. It may thus occur also in a wide range of taxa, from organisms without a central nervous system to animals with complex brain systems. area-concentrated search individual-based model delayed-response spatial memory survey movement Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5294009","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":368554961,"identity":"8a59a9fd-7e73-42c5-aa63-85cdec6db396","order_by":0,"name":"Thotsapol Chaianunporn","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Thotsapol","middleName":"","lastName":"Chaianunporn","suffix":""},{"id":368554962,"identity":"55766fe8-b9b7-49b2-a910-bffcb646d147","order_by":1,"name":"Thomas Hovestadt","email":"data:image/png;base64,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","orcid":"","institution":"University of Würzburg","correspondingAuthor":true,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Hovestadt","suffix":""}],"badges":[],"createdAt":"2024-10-19 10:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5294009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5294009/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70741683,"identity":"e2aaaefc-442e-4873-9844-88dbebf585a0","added_by":"auto","created_at":"2024-12-06 07:47:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7018447,"visible":true,"origin":"","legend":"","description":"","filename":"DelayedMovementProject.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5294009/v1_covered_db375b7e-b2fe-4bb0-8cee-4abc26a9753a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A delayed response in area-concentrated search can improve foraging success.","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"area-concentrated search, individual-based model, delayed-response, spatial memory, survey movement","lastPublishedDoi":"10.21203/rs.3.rs-5294009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5294009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground Area-concentrated search (ACS) is a simple movement rule implying that an animal searches for resources using a 'state-dependent correlated random walk'. Accordingly, a forager increases its searching intensity by reducing the directionality of movement ('intensive search mode' or ISM) when it detects a resource item, but if it searches unsuccessfully for a while, it returns to a more straight-line movement to search for new resource locations elsewhere ('extensive search mode' or ESM). In this study, we propose a modified ACS, called delayed-response ACS (dACS), which would be more efficient in resource collecting than the standard ACS.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods Instead of immediately switching from ESM to ISM upon encountering a resource as done in the standard ACS, an individual foraging in the dACS mode delays this switch for x steps (the delay parameter) so that it continues moving in a straight line for a while before switching to ISM. We simulated the movement paths of an individual with ACS compared with dACS in a continuous landscape with a single resource cluster and varied two different movement parameters, that is x and the half-saturation constant h that affects how quickly the forager returns to straight line movement, and two landscape parameters, i.e., cluster size and resource density.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults Our results show that an individual with a suitable delay parameter x for the dACS achieves substantially higher foraging success than an individual with standard ACS (x=0). Optimal foraging success occurs when x is approximately similar to the patch radius r. This is because, with dACS, an individual can penetrate deeper into a cluster and stay longer within it, ultimately increasing the number of resources collected. Modifying the half-saturation constant h also affects foraging success but effects depend on resource density and cluster size. Generally, h modulates the optimal x value only slightly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions An individual following a dACS with an adequate delay x can collect more resources from a patch than one using standard ACS; this hold in particular if patches are small or resource density is low. dACS can be interpreted as a survey movement within a resource cluster before switching from ESM to ISM. The dACS rule does not rely on complex spatial memory but only on memorizing whether resources were found or not. 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