Ocelot (Leopardus pardalis) density and activity pattern in a biological corridor, northeastern Mexico

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Abstract The ocelot (Leopardus pardalis Linnaeus, 1758) is one of six felid species found in Mexico, yet its ecology remains poorly understood. In this study, we assessed the ocelot density and activity pattern in the El Cielo-Sierra de Tamalave (EC-ST) biological corridor located in Tamaulipas, northeastern Mexico. We used camera trapping (52 double stations) to identify individuals based on their coat patterns. To estimate population density, we used the random thinning spatial capture-recapture method (rt-SCR), which integrates spatial information from photographs where individual identification is not possible. This approach allows us to retain and utilize data that would otherwise be discarded, thereby maximizing the use of all available data. We analysed ocelot’s activity pattern using circular statistics, and temporal overlap was assessed with potential competitors and prey. The estimated ocelot density was 3.73 (95% CRI: 2.84-4.85) individuals per 100 km², similar to estimates in nearby regions such as Sierra del Abra Tanchipa, San Luis Potosi, Mexico. The ocelot showed a nocturnal activity pattern, likely associated with hunting behaviour, and high temporal overlap with prey species such as rodents, rabbits, and deer. Temporal avoidance of apex predators (Panthera onca, Puma concolor, and Ursus americanus) suggests strategies to reduce risk, while overlap with mesocarnivore like Urocyon cinereoargenteus may indicate coexistence probably by prey partitioning. Our findings highlight the importance of combining density and activity analyses, show that rt-SCR provided reliable and precise estimates under our study conditions. This supports more accurate conservation planning in ocelot populations like those in the EC-ST biological corridor.
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Ocelot (Leopardus pardalis) density and activity pattern in a biological corridor, northeastern Mexico | 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 Ocelot (Leopardus pardalis) density and activity pattern in a biological corridor, northeastern Mexico Gabriela Rubí Mendoza-Gutiérrez, José Jiménez, Zavdiel Alfonso Manuel-de la Rosa, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7491469/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract The ocelot (Leopardus pardalis Linnaeus, 1758) is one of six felid species found in Mexico, yet its ecology remains poorly understood. In this study, we assessed the ocelot density and activity pattern in the El Cielo-Sierra de Tamalave (EC-ST) biological corridor located in Tamaulipas, northeastern Mexico. We used camera trapping (52 double stations) to identify individuals based on their coat patterns. To estimate population density, we used the random thinning spatial capture-recapture method (rt-SCR), which integrates spatial information from photographs where individual identification is not possible. This approach allows us to retain and utilize data that would otherwise be discarded, thereby maximizing the use of all available data. We analysed ocelot’s activity pattern using circular statistics, and temporal overlap was assessed with potential competitors and prey. The estimated ocelot density was 3.73 (95% CRI: 2.84-4.85) individuals per 100 km², similar to estimates in nearby regions such as Sierra del Abra Tanchipa, San Luis Potosi, Mexico. The ocelot showed a nocturnal activity pattern, likely associated with hunting behaviour, and high temporal overlap with prey species such as rodents, rabbits, and deer. Temporal avoidance of apex predators (Panthera onca, Puma concolor, and Ursus americanus) suggests strategies to reduce risk, while overlap with mesocarnivore like Urocyon cinereoargenteus may indicate coexistence probably by prey partitioning. Our findings highlight the importance of combining density and activity analyses, show that rt-SCR provided reliable and precise estimates under our study conditions. This supports more accurate conservation planning in ocelot populations like those in the EC-ST biological corridor. activity pattern camera trapping density northeastern Mexico ocelot random thinning spatial capture-recapture Full Text Additional Declarations No competing interests reported. Supplementary Files ESM1.pdf ESM2.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Jan, 2026 Reviews received at journal 14 Dec, 2025 Reviews received at journal 24 Nov, 2025 Reviewers agreed at journal 22 Nov, 2025 Reviewers agreed at journal 19 Nov, 2025 Reviewers invited by journal 12 Oct, 2025 Editor assigned by journal 04 Sep, 2025 Submission checks completed at journal 04 Sep, 2025 First submitted to journal 29 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. 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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Mexico","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"european-journal-of-wildlife-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejwr","sideBox":"Learn more about [European Journal of Wildlife Research](http://link.springer.com/journal/10344)","snPcode":"10344","submissionUrl":"https://submission.nature.com/new-submission/10344/3","title":"European Journal of Wildlife Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"activity pattern, camera trapping, density, northeastern Mexico, ocelot, random thinning spatial capture-recapture","lastPublishedDoi":"10.21203/rs.3.rs-7491469/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7491469/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The ocelot (Leopardus pardalis Linnaeus, 1758) is one of six felid species found in Mexico, yet its ecology remains poorly understood. In this study, we assessed the ocelot density and activity pattern in the El Cielo-Sierra de Tamalave (EC-ST) biological corridor located in Tamaulipas, northeastern Mexico. We used camera trapping (52 double stations) to identify individuals based on their coat patterns. To estimate population density, we used the random thinning spatial capture-recapture method (rt-SCR), which integrates spatial information from photographs where individual identification is not possible. This approach allows us to retain and utilize data that would otherwise be discarded, thereby maximizing the use of all available data. We analysed ocelot’s activity pattern using circular statistics, and temporal overlap was assessed with potential competitors and prey. The estimated ocelot density was 3.73 (95% CRI: 2.84-4.85) individuals per 100 km², similar to estimates in nearby regions such as Sierra del Abra Tanchipa, San Luis Potosi, Mexico. The ocelot showed a nocturnal activity pattern, likely associated with hunting behaviour, and high temporal overlap with prey species such as rodents, rabbits, and deer. Temporal avoidance of apex predators (Panthera onca, Puma concolor, and Ursus americanus) suggests strategies to reduce risk, while overlap with mesocarnivore like Urocyon cinereoargenteus may indicate coexistence probably by prey partitioning. Our findings highlight the importance of combining density and activity analyses, show that rt-SCR provided reliable and precise estimates under our study conditions. This supports more accurate conservation planning in ocelot populations like those in the EC-ST biological corridor.","manuscriptTitle":"Ocelot (Leopardus pardalis) density and activity pattern in a biological corridor, northeastern Mexico","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-25 17:07:12","doi":"10.21203/rs.3.rs-7491469/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-21T05:37:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T00:47:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T21:29:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175935867658475185779963537681012742063","date":"2025-11-22T17:38:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279214328806675262988958946035220661416","date":"2025-11-19T20:15:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-12T05:59:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-04T04:30:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T04:29:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Wildlife Research","date":"2025-08-29T20:37:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-wildlife-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejwr","sideBox":"Learn more about [European Journal of Wildlife Research](http://link.springer.com/journal/10344)","snPcode":"10344","submissionUrl":"https://submission.nature.com/new-submission/10344/3","title":"European Journal of Wildlife Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b0cba4f2-e351-4ab1-b12a-16ab72f8e3ce","owner":[],"postedDate":"October 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-26T04:08:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-25 17:07:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7491469","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7491469","identity":"rs-7491469","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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