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dc.contributor.authorThomas, Len
dc.contributor.authorBuckland, Stephen Terrence
dc.contributor.authorRexstad, Eric
dc.contributor.authorLaake, J L
dc.contributor.authorStrindberg, S
dc.contributor.authorHedley, S L
dc.contributor.authorBishop, J R B
dc.contributor.authorMarques, Tiago A.
dc.date.accessioned2009-11-23T14:21:42Z
dc.date.available2009-11-23T14:21:42Z
dc.date.issued2010
dc.identifier.citationJournal of Applied Ecology 47 (1): 5-14 2010en_US
dc.identifier.issn0021-8901en_US
dc.identifier.otherStAndrews.ResExp.Output.OutputID.31422en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1365-2664.2009.01737.xen_US
dc.identifier.urihttps://hdl.handle.net/10023/817
dc.description.abstract1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial pre-requisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: CDS (conventional distance sampling), which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; MCDS (multiple covariate distance sampling), which allows covariates in addition to distance; and MRDS (mark-recapture distance sampling), which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the DSM (density surface modelling) analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of-the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.en_US
dc.language.isoenen_US
dc.rightsPublished as a Wiley InterScience OnlineOpen research articleen_us
dc.subjectdistance samplingen_US
dc.subjectline transect samplingen_US
dc.subjectpoint transect samplingen_US
dc.subjectpopulation densityen_US
dc.subjectpopulation abundanceen_US
dc.subjectsighting surveysen_US
dc.subjectsurvey designen_US
dc.subjectwildlife surveysen_US
dc.subject.lccQAen_US
dc.subject.lccQHen_US
dc.subject.lccQLen_US
dc.titleDistance software: design and analysis of distance sampling surveys for estimating population sizeen_US
dc.typeJournal articleen_US
dc.audience.mediatorSchool : Mathematics and Statisticsen_US
dc.audience.mediatorDepartment : Statisticsen_US
dc.description.versionhttps://doi.org/Publisher PDFen_US
dc.publicationstatusPublisheden_US
dc.statusPeer revieweden_US


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