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dc.contributor.advisorBuckland, S. T. (Stephen T.)
dc.contributor.advisorLangrock, Roland
dc.contributor.authorGlennie, Richard
dc.coverage.spatialx, 258 p.en_US
dc.date.accessioned2018-11-15T08:58:52Z
dc.date.available2018-11-15T08:58:52Z
dc.date.issued2018-12-06
dc.identifier.urihttp://hdl.handle.net/10023/16467
dc.description.abstractDistance sampling and spatial capture-recapture are statistical methods to estimate the number of animals in a wild population based on encounters between these animals and scientific detectors. Both methods estimate the probability an animal is detected during a survey, but do not explicitly model animal movement. The primary challenge is that animal movement in these surveys is unobserved; one must average over all possible paths each animal could have travelled during the survey. In this thesis, a general statistical model, with distance sampling and spatial capture-recapture as special cases, is presented that explicitly incorporates animal movement. An efficient algorithm to integrate over all possible movement paths, based on quadrature and hidden Markov modelling, is given to overcome the computational obstacles. For distance sampling, simulation studies and case studies show that incorporating animal movement can reduce the bias in estimated abundance found in conventional models and expand application of distance sampling to surveys that violate the assumption of no animal movement. For spatial capture-recapture, continuous-time encounter records are used to make detailed inference on where animals spend their time during the survey. In surveys conducted in discrete occasions, maximum likelihood models that allow for mobile activity centres are presented to account for transience, dispersal, and heterogeneous space use. These methods provide an alternative when animal movement causes bias in standard methods and the opportunity to gain richer inference on how animals move, where they spend their time, and how they interact.en_US
dc.language.isoenen_US
dc.publisherUniversity of St Andrews
dc.subjectDistance samplingen_US
dc.subjectCapture recaptureen_US
dc.subjectAnimal movementen_US
dc.subjectHidden Markov modelen_US
dc.subjectContinuous time modelsen_US
dc.subjectEncounter modelsen_US
dc.subjectPath integrationen_US
dc.subject.lccQL751.65S73G6
dc.subject.lcshAnimal behaviour--Statistical methodsen
dc.subject.lcshSampling (Statistics)en
dc.subject.lcshAnimal locomotionen
dc.titleIncorporating animal movement with distance sampling and spatial capture-recaptureen_US
dc.typeThesisen_US
dc.contributor.sponsorCarnegie Trust for the Universities of Scotlanden_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.rights.embargodate2020-11-06
dc.rights.embargoreasonThesis restricted in accordance with University regulations. Print and electronic copy restricted until 6th November 2020en


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