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dc.contributor.authorLong, Jed
dc.contributor.authorNelson, Trisalyn
dc.date.accessioned2016-02-25T00:11:43Z
dc.date.available2016-02-25T00:11:43Z
dc.date.issued2015-04
dc.identifier.citationLong , J & Nelson , T 2015 , ' Home range and habitat analysis using dynamic time geography ' , Journal of Wildlife Management , vol. 79 , no. 3 , pp. 481-490 . https://doi.org/10.1002/jwmg.845en
dc.identifier.issn0022-541X
dc.identifier.otherPURE: 175215219
dc.identifier.otherPURE UUID: a0f85497-d032-44b9-98f9-f27075b05c50
dc.identifier.otherScopus: 84925667423
dc.identifier.otherWOS: 000351629900013
dc.identifier.urihttps://hdl.handle.net/10023/8307
dc.description.abstractWildlife home ranges continue to be a common spatial unit for modeling animal habitat selection. Telemetry data are increasing in spatial and temporal detail and new methods are being developed to incorporate fine resolution data into home range delineation. We extended a previously developed home range estimation technique that incorporates theory from time geography, the potential path area (PPA) home range, to allow the home range to be defined at multiple spatial scales depending on the observed rate of movement within the data. The benefits of this approach are demonstrated with a simulation study, which uses multi-state correlated random walks to represent dynamic movement phases to compare the modified PPA home range technique with a suite of other home range estimation methods (PPA home range, kernel density estimation, Brownian bridges, and dynamic Brownian bridges). We used a case study on caribou (Rangifer tarandus) movement from northern Canada to highlight the value of this approach for characterizing habitat conditions associated with wildlife habitat analysis. We used a simple habitat covariate, percent forest cover, to explore the potential for misleading habitat estimates when home ranges do not include potentially visited locations (omission area) or include areas not possibly visited (commission area). We highlight the advantages of the dynamic PPA home range in the context of quantifying omission and commission areas in other home range techniques. Finally, we provide our R code for calculating dynamic PPA home range estimates.
dc.language.isoeng
dc.relation.ispartofJournal of Wildlife Managementen
dc.rights© The Wildlife Society, 2015. This is the accepted version of the following article: Long, J. and Nelson, T. (2015), Home range and habitat analysis using dynamic time geography. The Journal of Wildlife Management, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/jwmg.845/abstracten
dc.subjectCaribou (Rangifer tarandus)en
dc.subjectCommission areaen
dc.subjectCorrelated random walken
dc.subjectOmission areaen
dc.subjectTelemetryen
dc.subjectQL Zoologyen
dc.subjectGE Environmental Sciencesen
dc.subjectDASen
dc.subject.lccQLen
dc.subject.lccGEen
dc.titleHome range and habitat analysis using dynamic time geographyen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews. Bell-Edwards Geographic Data Instituteen
dc.identifier.doihttps://doi.org/10.1002/jwmg.845
dc.description.statusPeer revieweden
dc.date.embargoedUntil2016-02-25
dc.identifier.urlhttp://onlinelibrary.wiley.com/doi/10.1002/jwmg.845/suppinfoen


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