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dc.contributor.authorFarhadinia, Mohammad S.
dc.contributor.authorMichelot, Théo
dc.contributor.authorJohnson, Paul J.
dc.contributor.authorHunter, Luke T. B.
dc.contributor.authorMacdonald, David W.
dc.date.accessioned2020-02-11T14:30:04Z
dc.date.available2020-02-11T14:30:04Z
dc.date.issued2020-02-10
dc.identifier.citationFarhadinia , M S , Michelot , T , Johnson , P J , Hunter , L T B & Macdonald , D W 2020 , ' Understanding decision making in a food-caching predator using hidden Markov models ' , Movement Ecology , vol. 8 , 9 . https://doi.org/10.1186/s40462-020-0195-zen
dc.identifier.issn2051-3933
dc.identifier.otherPURE: 266338679
dc.identifier.otherPURE UUID: c131ed49-4669-4347-a03d-345987c877db
dc.identifier.otherRIS: urn:E2C4E7F05D56D5EA9762B0865E8649D0
dc.identifier.otherRIS: Farhadinia2020
dc.identifier.otherScopus: 85079271096
dc.identifier.otherWOS: 000521006400002
dc.identifier.urihttp://hdl.handle.net/10023/19446
dc.descriptionFinancial support was provided by the People’s Trust for Endangered Species (PTES), Zoologische Gesellschaft für Arten- und Populationsschutz (ZGAP), Quagga Conservation Fund and IdeaWild.en
dc.description.abstractBackground Tackling behavioural questions often requires identifying points in space and time where animals make decisions and linking these to environmental variables. State-space modeling is useful for analysing movement trajectories, particularly with hidden Markov models (HMM). Yet importantly, the ontogeny of underlying (unobservable) behavioural states revealed by the HMMs has rarely been verified in the field. Methods Using hidden Markov models of individual movement from animal location, biotelemetry, and environmental data, we explored multistate behaviour and the effect of associated intrinsic and extrinsic drivers across life stages. We also decomposed the activity budgets of different movement states at two general and caching phases. The latter - defined as the period following a kill which likely involves the caching of uneaten prey - was subsequently confirmed by field inspections. We applied this method to GPS relocation data of a caching predator, Persian leopard Panthera pardus saxicolor in northeastern Iran. Results Multistate modeling provided strong evidence for an effect of life stage on the behavioural states and their associated time budget. Although environmental covariates (ambient temperature and diel period) and ecological outcomes (predation) affected behavioural states in non-resident leopards, the response in resident leopards was not clear, except that temporal patterns were consistent with a crepuscular and nocturnal movement pattern. Resident leopards adopt an energetically more costly mobile behaviour for most of their time while non-residents shift their behavioural states from high energetic expenditure states to energetically less costly encamped behaviour for most of their time, which is likely to be a risk avoidance strategy against conspecifics or humans. Conclusions This study demonstrates that plasticity in predator behaviour depending on life stage may tackle a trade-off between successful predation and avoiding the risks associated with conspecifics, human presence and maintaining home range. Range residency in territorial predators is energetically demanding and can outweigh the predator’s response to intrinsic and extrinsic variables such as thermoregulation or foraging needs. Our approach provides an insight into spatial behavior and decision making of leopards, and other large felids in rugged landscapes through the application of the HMMs in movement ecology.
dc.format.extent13
dc.language.isoeng
dc.relation.ispartofMovement Ecologyen
dc.rightsCopyright © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en
dc.subjectCaching behaviouren
dc.subjectHidden Markov modelsen
dc.subjectLife-stageen
dc.subjectMultistate animal movementen
dc.subjectPanthera pardus saxicoloren
dc.subjectRange residencyen
dc.subjectSatellite telemetryen
dc.subjectViterbi algorithmen
dc.subjectQA Mathematicsen
dc.subjectQL Zoologyen
dc.subjectDASen
dc.subject.lccQAen
dc.subject.lccQLen
dc.titleUnderstanding decision making in a food-caching predator using hidden Markov modelsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Statisticsen
dc.identifier.doihttps://doi.org/10.1186/s40462-020-0195-z
dc.description.statusPeer revieweden


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