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Predictive model of sperm whale prey capture attempts from time-depth data

dc.contributor.authorPérez-Jorge, Sergi
dc.contributor.authorOliveira, Cláudia
dc.contributor.authorIglesias Rivas, Esteban
dc.contributor.authorPrieto, Rui
dc.contributor.authorCascão, Irma
dc.contributor.authorWensveen, Paul J.
dc.contributor.authorMiller, Patrick J. O.
dc.contributor.authorSilva, Mónica A.
dc.date.accessioned2023-07-10T14:17:31Z
dc.date.available2023-07-10T14:17:31Z
dc.date.issued2023
dc.description.abstractBackgroundHigh-resolution sound and movement recording tags offer unprecedented insights into the fine-scale foraging behaviour of cetaceans, especially echolocating odontocetes, enabling the estimation of a series of foraging metrics. However, these tags are expensive, making them inaccessible to most researchers. Time-Depth Recorders (TDRs), which have been widely used to study diving and foraging behaviour of marine mammals, offer a more affordable alternative. Unfortunately, data collected by TDRs are bi-dimensional (time and depth only), so quantifying foraging effort from those data is challenging.MethodsA predictive model of the foraging effort of sperm whales (Physeter macrocephalus) was developed to identify prey capture attempts (PCAs) from time-depth data. Data from high-resolution acoustic and movement recording tags deployed on 12 sperm whales were downsampled to 1 Hz to match the typical TDR sampling resolution and used to predict the number of buzzes (i.e., rapid series of echolocation clicks indicative of PCAs). Generalized linear mixed models were built for dive segments of different durations (30, 60, 180 and 300 s) using multiple dive metrics as potential predictors of PCAs.ResultsAverage depth, variance of depth and variance of vertical velocity were the best predictors of the number of buzzes. Sensitivity analysis showed that models with segments of 180 s had the best overall predictive performance, with a good area under the curve value (0.78 +/- 0.05), high sensitivity (0.93 +/- 0.06) and high specificity (0.64 +/- 0.14). Models using 180 s segments had a small difference between observed and predicted number of buzzes per dive, with a median of 4 buzzes, representing a difference in predicted buzzes of 30%.ConclusionsThese results demonstrate that it is possible to obtain a fine-scale, accurate index of sperm whale PCAs from time-depth data alone. This work helps leveraging the potential of time-depth data for studying the foraging ecology of sperm whales and the possibility of applying this approach to a wide range of echolocating cetaceans. The development of accurate foraging indices from low-cost, easily accessible TDR data would contribute to democratize this type of research, promote long-term studies of various species in several locations, and enable analyses of historical datasets to investigate changes in cetacean foraging activity.pt_PT
dc.description.sponsorshipWATCH IT-Acores-01-0145-FEDER-000057; META-FA_06_2017_017; SUMMER-H2020 GA 817806; 3/SRMCT/DRAM/2019; RAGES-SUB/ENV.C.2-GA 110661; INTERTAGUA-MAC2/1.1a/385; SUMMER-H2020 GA 817806; AZORES2020pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1186/s40462-023-00393-2pt_PT
dc.identifier.issn2051-3933
dc.identifier.urihttp://hdl.handle.net/10400.1/19825
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherBMCpt_PT
dc.relationMovement ecology of whales: investigating environmental, social and physiological motivations
dc.relationUAc - Okeanos R&D Centre - University of the Azores
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPhyseter macrocephaluspt_PT
dc.subjectVertical movementpt_PT
dc.subjectBuzzespt_PT
dc.subjectForaging behaviourpt_PT
dc.subjectLow-resolution datapt_PT
dc.subjectTime-depth recorderspt_PT
dc.titlePredictive model of sperm whale prey capture attempts from time-depth datapt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMovement ecology of whales: investigating environmental, social and physiological motivations
oaire.awardTitleUAc - Okeanos R&D Centre - University of the Azores
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Investigador FCT/IF%2F00943%2F2013%2FCP1199%2FCT0001/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05634%2F2020/PT
oaire.citation.issue1pt_PT
oaire.citation.titleMovement Ecologypt_PT
oaire.citation.volume11pt_PT
oaire.fundingStreamInvestigador FCT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameIglesias Rivas
person.givenNameEsteban
person.identifier.orcid0000-0002-7667-2036
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscoverybf1120b4-01e7-43ba-b594-02c16d88db4c
relation.isProjectOfPublication2ef999ed-6746-4317-8e35-53d0cdc0f821
relation.isProjectOfPublication3ea5a88e-e7d6-47ec-a2ac-195197093a3c
relation.isProjectOfPublication.latestForDiscovery3ea5a88e-e7d6-47ec-a2ac-195197093a3c

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