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dc.contributor.authorIsojunno, S.
dc.contributor.authorMiller, P.J.O.
dc.date.accessioned2015-02-16T17:01:09Z
dc.date.available2015-02-16T17:01:09Z
dc.date.issued2015-01-21
dc.identifier.citationIsojunno , S & Miller , P J O 2015 , ' Sperm whale response to tag boat presence : biologically informed hidden state models quantify lost feeding opportunities ' Ecosphere , vol. 6 , no. 1 . https://doi.org/10.1890/ES14-00130.1en
dc.identifier.issn2150-8925
dc.identifier.otherPURE: 168675833
dc.identifier.otherPURE UUID: bb33f00c-e39a-4f14-9bf4-1ac8764d7122
dc.identifier.otherScopus: 84922032807
dc.identifier.otherWOS: 000350440400006
dc.identifier.otherORCID: /0000-0002-2212-2135/work/37031847
dc.identifier.urihttp://hdl.handle.net/10023/6112
dc.descriptionThe authors acknowledge the UK Ministry of Defence, U.S. Office of Naval Research, and World Wildlife Fund (Norway) for funding this research.en
dc.description.abstractAnimal-attached sensors provide invaluable data to describe behavior of cryptic species, such as cetaceans, and are increasingly used to assess anthropogenic disturbance effects. Tag deployment and handling may itself alter the behavior of study animals and there is a need to assess if and when behavior recovers to an undisturbed level. Not all behavioral changes have fitness consequences, and our goal is to derive metrics that can be linked to fitness implications, such as time and energy allocation to different functional behaviors. Here we detail an approach that incorporates biological knowledge and multiple streams of tag-recorded data in a hidden state-switching model to estimate time series of functional behavioral st ates for 12 sperm whales off Norway. Foraging, recovery and resting states were specified in the hidden state model by state-dependent likelihood structures. Comparison of hidden state models revealed a parsimonious set of input time series, and supported the inclusion of a less informed 'silent active' state. There was a high agreement between state estimates and expert classifications. We then used the estimated states in time series models to test three hypotheses for behavioral change during suction-cup tag deployment procedures: change in behavioral states, change in prey capture attempts and locomotion cost, given behavioral state. Sperm whales spent 34% less time at the sea surface and 60% more time in non-foraging silent active state in the presence of the tag boat (''tagging period'' 0.1-2.8 h) than during post-tagging baseline period (1.8-20.8 h). No comparable pre-tagging baseline data were available. Nevertheless, time-decaying models of tagging effects were not retained in model selection, indicating a short-term effect that ceased immediately after the tagging period. We did not find changes in energetic proxies, given behavioral state, however changes in functional state budget indicate costs in terms of lost feeding opportunities and recovery time at surface. These results are useful to quantitatively identify data periods that should not be considered baseline behavior within tag recordings. This functional state approach proves effective to quantify disturbance in terms of time and energy allocation that is based upon general principles that can be applied to other species and biologging applications.
dc.language.isoeng
dc.relation.ispartofEcosphereen
dc.rights© 2015 Isojunno and Miller. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/3.0/en
dc.subjectBayesianen
dc.subjectDTAGen
dc.subjectFunctional stateen
dc.subjectNorthern Norwayen
dc.subjectPhyseter microcephalusen
dc.subjectResearch effectsen
dc.subjectState-dependent likelihooden
dc.subjectState-switching modelen
dc.subjectSuction-cup tag attachmenten
dc.subjectTime-series modelen
dc.subjectQH301 Biologyen
dc.subjectQL Zoologyen
dc.subject.lccQH301en
dc.subject.lccQLen
dc.titleSperm whale response to tag boat presence : biologically informed hidden state models quantify lost feeding opportunitiesen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews.Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews.Centre for Social Learning & Cognitive Evolutionen
dc.contributor.institutionUniversity of St Andrews.Bioacoustics groupen
dc.contributor.institutionUniversity of St Andrews.Sea Mammal Research Uniten
dc.identifier.doihttps://doi.org/10.1890/ES14-00130.1
dc.description.statusPeer revieweden


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