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dc.contributor.authorPalmer, K. J.
dc.contributor.authorBrookes, Kate
dc.contributor.authorRendell, Luke
dc.date.accessioned2018-02-15T00:33:18Z
dc.date.available2018-02-15T00:33:18Z
dc.date.issued2017-08
dc.identifier.citationPalmer , K J , Brookes , K & Rendell , L 2017 , ' Categorizing click trains to increase taxonomic precision in echolocation click loggers ' Journal of the Acoustical Society of America , vol. 142 , no. 2 , pp. 863-877 . DOI: 10.1121/1.4996000en
dc.identifier.issn0001-4966
dc.identifier.otherPURE: 250926415
dc.identifier.otherPURE UUID: 87e5b840-f395-41d8-84ce-cb35829fe627
dc.identifier.otherScopus: 85027410519
dc.identifier.urihttp://hdl.handle.net/10023/12721
dc.descriptionL.R. and K.J.P. were supported by Marine Scotland Science and the Marine Alliance for Science and Technology for Scotland (MASTS) pooling initiative and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.en
dc.description.abstractPassive acoustic monitoring is an efficient way to study acoustically active animals but species identification remains a major challenge. C-PODs are popular logging devices that automatically detect odontocete echolocation clicks. However, the accompanying analysis software does not distinguish between delphinid species. Click train features logged by C-PODs were compared to frequency spectra from adjacently deployed continuous recorders. A generalized additive model was then used to categorize C-POD click trains into three groups: broadband click trains, produced by bottlenose dolphin (Tursiops truncatus) or common dolphin (Delphinus delphis), frequency-banded click trains, produced by Risso's (Grampus griseus) or white beaked dolphins (Lagenorhynchus albirostris), and unknown click trains. Incorrect categorization rates for broadband and frequency banded clicks were 0.02 (SD 0.01), but only 30% of the click trains met the categorization threshold. To increase the proportion of categorized click trains, model predictions were pooled within acoustic encounters and a likelihood ratio threshold was used to categorize encounters. This increased the proportion of the click trains meeting either the broadband or frequency banded categorization threshold to 98%. Predicted species distribution at the 30 study sites matched well to visual sighting records from the region.en
dc.format.extent15en
dc.language.isoeng
dc.relation.ispartofJournal of the Acoustical Society of Americaen
dc.rights© 2017, Acoustical Society of American. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1121/1.4996000en
dc.subjectPassive acoustic monitoringen
dc.subjectOdontoceteen
dc.subjectEcholocation click loggeren
dc.subjectGC Oceanographyen
dc.subjectQH301 Biologyen
dc.subjectAcoustics and Ultrasonicsen
dc.subjectNDASen
dc.subject.lccGCen
dc.subject.lccQH301en
dc.titleCategorizing click trains to increase taxonomic precision in echolocation click loggersen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Centre for Social Learning & Cognitive Evolutionen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Bioacoustics groupen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.identifier.doihttps://doi.org/10.1121/1.4996000
dc.description.statusPeer revieweden
dc.date.embargoedUntil14-02-20


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