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dc.contributor.authorArranz, P
dc.contributor.authorMiranda, D
dc.contributor.authorGkikopoulou, K C
dc.contributor.authorCardona, A
dc.contributor.authorAlcazar, J
dc.contributor.authorAguilar de Soto, N
dc.contributor.authorThomas, L
dc.contributor.authorMarques, T A
dc.date.accessioned2023-10-23T23:39:30Z
dc.date.available2023-10-23T23:39:30Z
dc.date.issued2023-04-24
dc.identifier285389759
dc.identifier3e8bd9b9-31f5-44dd-8519-f4b83648abb3
dc.identifier37092951
dc.identifier85153687507
dc.identifier.citationArranz , P , Miranda , D , Gkikopoulou , K C , Cardona , A , Alcazar , J , Aguilar de Soto , N , Thomas , L & Marques , T A 2023 , ' Comparison of visual and passive acoustic estimates of beaked whale density off El Hierro, Canary Islands ' , Journal of the Acoustical Society of America , vol. 153 , no. 4 , pp. 2469-2481 . https://doi.org/10.1121/10.0017921en
dc.identifier.issn0001-4966
dc.identifier.otherORCID: /0000-0002-7436-067X/work/134491265
dc.identifier.otherORCID: /0000-0002-2581-1972/work/134491394
dc.identifier.otherORCID: /0000-0002-9232-4138/work/134491692
dc.identifier.urihttps://hdl.handle.net/10023/28559
dc.descriptionFunding: P.A., D.M., K.G., T.A.M., A.C., and field work were funded by Office of Navel Research award #N000141612973 and research conducted under Spanish Ministry permit #28606/2016 and Canary government permit # 421373/2016. T.A.M. is thankful for partial support by CEAUL (funded by Fundação para a Ciência e a Tecnologia, Portugal, through the project UIDB/00006/2020) and time under the ACCURATE project funded by the U.S. Navy Living Marine Resources program (Contract #N3943019C2176).en
dc.description.abstractPassive acoustic monitoring (PAM) offers considerable potential for density estimation of cryptic cetaceans, such as beaked whales. However, comparative studies on the accuracy of PAM density estimates from these species are lacking. Concurrent, low-cost drifting PAM, with SoundTraps suspended at 200 m depth, and land-based sightings, were conducted off the Canary Islands. Beaked whale density was estimated using a cue-count method, with click production rate and the probability of click detection derived from digital acoustic recording tags (DTags), and distance sampling techniques, adapted to fixed-point visual surveys. Of 32 870 detections obtained throughout 206 h of PAM recordings, 68% were classified as "certain" beaked whale clicks. Acoustic detection probability was 0.15 [coefficient variation (CV) 0.24] and click production rate was 0.46 clicks s - 1 (CV 0.05). PAM density estimates were in the range of 21.5 or 48.6 whales per 1000 km2 [CV 0.50 or 0.44, 95% confidence interval (CI) 20.7-22.4 or 47-50.9), depending on whether "uncertain" clicks were considered. Density estimates from concurrent sightings resulted in 33.7 whales per 1000 km2 (CV 0.77, 95% CI 8.9-50.5). Cue-count PAM methods under application provide reliable estimates of beaked whale density, over relatively long time periods and in realistic scenarios, as these match the concurrent density estimates obtained from visual observations.
dc.format.extent13
dc.format.extent6637812
dc.language.isoeng
dc.relation.ispartofJournal of the Acoustical Society of Americaen
dc.subjectAnimalsen
dc.subjectWhalesen
dc.subjectVocalization, animalen
dc.subjectEcholocationen
dc.subjectSpainen
dc.subjectSound spectrographyen
dc.subjectTime factorsen
dc.subjectAcousticsen
dc.subjectGC Oceanographyen
dc.subjectQL Zoologyen
dc.subjectNDASen
dc.subjectACen
dc.subjectMCCen
dc.subject.lccGCen
dc.subject.lccQLen
dc.titleComparison of visual and passive acoustic estimates of beaked whale density off El Hierro, Canary Islandsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.identifier.doi10.1121/10.0017921
dc.description.statusPeer revieweden
dc.date.embargoedUntil2023-10-24


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