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dc.contributor.authorPetersma, Felix T.
dc.contributor.authorThomas, Len
dc.contributor.authorThode, Aaron M.
dc.contributor.authorHarris, Danielle
dc.contributor.authorMarques, Tiago A.
dc.contributor.authorCheoo, Gisela V.
dc.contributor.authorKim, Katherine H.
dc.identifier.citationPetersma , F T , Thomas , L , Thode , A M , Harris , D , Marques , T A , Cheoo , G V & Kim , K H 2023 , ' Accommodating false positives within acoustic spatial capture–recapture, with variable source levels, noisy bearings and an inhomogeneous spatial density ' , Journal of Agricultural, Biological and Environmental Statistics .
dc.identifier.otherPURE: 291470781
dc.identifier.otherPURE UUID: edce5bc7-bbdc-44f2-9e49-cd7fd41f24f5
dc.identifier.otherORCID: /0000-0002-7436-067X/work/140362093
dc.identifier.otherORCID: /0000-0003-1447-1420/work/140362145
dc.identifier.otherORCID: /0000-0002-2581-1972/work/140362191
dc.identifier.otherScopus: 85166957409
dc.descriptionFunding: Tiago Marques was partly supported by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia, Portugal, through the project UIDB/00006/2020).en
dc.description.abstractPassive acoustic monitoring is a promising method for surveying wildlife populations that are easier to detect acoustically than visually. When animal vocalisations can be uniquely identified on an array of sensors, the potential exists to estimate population density through acoustic spatial capture–recapture (ASCR). However, sound classification is imperfect, and in some situations, a high proportion of sounds detected on just a single sensor (‘singletons’) are not from the target species. We present a case study of bowhead whale calls (Baleana mysticetus) collected in the Beaufort Sea in 2010 containing such false positives. We propose a novel extension of ASCR that is robust to false positives by truncating singletons and conditioning on calls being detected by at least two sensors. We allow for individual-level detection heterogeneity through modelling a variable sound source level, model inhomogeneous call spatial density, and include bearings with varying measurement error. We show via simulation that the method produces near-unbiased estimates when correctly specified. Ignoring source-level variation resulted in a strong negative bias, while ignoring inhomogeneous density resulted in severe positive bias. The case study analysis indicated a band of higher call density approximately 30 km from shore; 59.8% of singletons were estimated to have been false positives.
dc.relation.ispartofJournal of Agricultural, Biological and Environmental Statisticsen
dc.rightsCopyright © 2023 The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
dc.subjectBowhead whaleen
dc.subjectEstimating animal abundanceen
dc.subjectPassive acoustic density estimationen
dc.subjectSpatially explicit capture recapture (SECR)en
dc.subjectWildlife population assessmenten
dc.subjectQL Zoologyen
dc.titleAccommodating false positives within acoustic spatial capture–recapture, with variable source levels, noisy bearings and an inhomogeneous spatial densityen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.description.statusPeer revieweden

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