Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorAoki, Kagari
dc.contributor.authorSato, Katsufumi
dc.contributor.authorIsojunno, Saana
dc.contributor.authorNarazaki, Tomoko
dc.contributor.authorMiller, Patrick J.O.
dc.date.accessioned2018-10-17T23:48:53Z
dc.date.available2018-10-17T23:48:53Z
dc.date.issued2017-10-18
dc.identifier.citationAoki , K , Sato , K , Isojunno , S , Narazaki , T & Miller , P J O 2017 , ' High diving metabolic rate indicated by high-speed transit to depth in negatively buoyant long-finned pilot whales ' , Journal of Experimental Biology , vol. 220 , no. 20 , pp. 3802-3811 . https://doi.org/10.1242/jeb.158287en
dc.identifier.issn0022-0949
dc.identifier.otherPURE: 251476039
dc.identifier.otherPURE UUID: fcea903a-5609-43d4-b6f4-bc094b5c8425
dc.identifier.otherRIS: urn:E66138ADA167102DC95EF4E99D8B9971
dc.identifier.otherScopus: 85031792759
dc.identifier.otherORCID: /0000-0002-2212-2135/work/38548519
dc.identifier.otherWOS: 000413196900026
dc.identifier.urihttps://hdl.handle.net/10023/16272
dc.descriptionThe US Office of Naval Research and Strategic Environmental Research and Development Program (SERDP) supported the fieldwork as a part of the 3S study collaboration. This study was also supported by the program Bio-Logging Science of the University of Tokyo (UTBLS).en
dc.description.abstractTo maximize foraging duration at depth, diving mammals are expected to use the lowest cost optimal speed during descent and ascent transit and to minimize the cost of transport by achieving neutral buoyancy. Here, we outfitted 18 deep-diving long-finned pilot whales with multi-sensor data loggers and found indications that their diving strategy is associated with higher costs than those of other deep-diving toothed whales. Theoretical models predict that optimal speed is proportional to (basal metabolic rate/drag)1/3 and therefore to body mass0.05. The transit speed of tagged animals (2.7±0.3 m s−1) was substantially higher than the optimal speed predicted from body mass (1.4–1.7 m s−1). According to the theoretical models, this choice of high transit speed, given a similar drag coefficient (median, 0.0035) to that in other cetaceans, indicated greater basal metabolic costs during diving than for other cetaceans. This could explain the comparatively short duration (8.9±1.5 min) of their deep dives (maximum depth, 444±85 m). Hydrodynamic gliding models indicated negative buoyancy of tissue body density (1038.8± 1.6 kg m–3, ±95% credible interval, CI) and similar diving gas volume (34.6±0.6 ml kg−1, ±95% CI) to those in other deep-diving toothed whales. High diving metabolic rate and costly negative buoyancy imply a ‘spend more, gain more’ strategy of long-finned pilot whales, differing from that in other deep-diving toothed whales, which limits the costs of locomotion during foraging. We also found that net buoyancy affected the optimal speed: high transit speeds gradually decreased during ascent as the whales approached neutral buoyancy owing to gas expansion.
dc.format.extent10
dc.language.isoeng
dc.relation.ispartofJournal of Experimental Biologyen
dc.rights© 2017. Published by The Company of Biologists Ltd. This work has been made available online in accordance with the publisher’s policies. This is the final published version of the work, which was originally published at https://doi.org/10.1242/jeb.158287en
dc.subjectBody conditionen
dc.subjectCetaceanen
dc.subjectDeep-diving marine mammalsen
dc.subjectForaging strategyen
dc.subjectGlobicephala melasen
dc.subjectSwimming kinematicsen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subjectSDG 14 - Life Below Wateren
dc.subject.lccQH301en
dc.titleHigh diving metabolic rate indicated by high-speed transit to depth in negatively buoyant long-finned pilot whalesen
dc.typeJournal articleen
dc.contributor.sponsorOffice of Naval Researchen
dc.description.versionPublisher PDFen
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. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. Centre for Social Learning & Cognitive Evolutionen
dc.contributor.institutionUniversity of St Andrews. Bioacoustics groupen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doihttps://doi.org/10.1242/jeb.158287
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-10-18
dc.identifier.grantnumberN00014140390en


This item appears in the following Collection(s)

Show simple item record