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dc.contributor.authorBortolotto, Guilherme A.
dc.contributor.authorZerbini, Alexandre
dc.contributor.authorThomas, Len
dc.contributor.authorAndriolo, Artur
dc.contributor.authorHammond, Philip Steven
dc.date.accessioned2023-10-25T16:30:02Z
dc.date.available2023-10-25T16:30:02Z
dc.date.issued2023-10-05
dc.identifier283809324
dc.identifier3cfdbd1c-39ef-4416-adcd-8e739d3aced2
dc.identifier.citationBortolotto , G A , Zerbini , A , Thomas , L , Andriolo , A & Hammond , P S 2023 , ' Distribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modelling ' , Marine Ecology Progress Series , vol. 720 , pp. 161-174 . https://doi.org/10.3354/meps14404en
dc.identifier.issn0171-8630
dc.identifier.otherORCID: /0000-0002-7436-067X/work/145516746
dc.identifier.otherORCID: /0000-0002-2381-8302/work/145517068
dc.identifier.urihttps://hdl.handle.net/10023/28569
dc.descriptionFunding: The Monitoring Whales by Satellite Project (Projeto Monitoramento de Baleias por Satélite, PMBS) research cruises were sponsored by Shell Brasil. The Federal University of Rio Grande (FURG) and the R/V Atlântico Sul crew provided essential support during fieldwork. G.A.B.’s PhD work is funded by the Brazilian National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Science Without Borders, scholarship number 208203/2014-1).en
dc.description.abstractStatistical modelling of animal distributions has been widely applied to explain how mobile species use their habitats. The distribution of and habitat use by humpback whales Megaptera novaeangliae off the eastern coast of Brazil have previously been investigated by modelling visual survey data. Here, we modelled distribution in their breeding range using individual tracking data to compare ecological inferences with those from previous models from line transect data. A generalised estimating equation framework was used to model the tracking data and pseudo-absences as functions of spatial covariates. Covariates considered were latitude and longitude, sea surface temperature (SST), current and wind speeds near the surface, distances to shelf-break and the coast, sea bottom depth and slope, and a factor variable representing ‘shelter’. Two modelling exercises were developed: a habitat use model (HUM) and a distribution model (DIM). Covariates retained in the selected HUM were SST, distance to coast and shelf-break, current and wind speeds and shelter. Covariates retained in the selected DIM were latitude/longitude, current speed and distances to shelf-break and coast. The modelled relationships between whale occurrence and environmental covariates using tracking data were similar to those using line transect data. Distribution maps were also similar, supporting higher densities around the Abrolhos Archipelago and to its south. We showed that habitat use and distribution of this population in the area could be similarly inferred by modelling either line transect or tracking data. Using these 2 approaches in conjunction can strengthen the understanding of important ecological aspects of animal populations.
dc.format.extent14
dc.format.extent1288035
dc.language.isoeng
dc.relation.ispartofMarine Ecology Progress Seriesen
dc.subjectMegaptera novaeangliaeen
dc.subjectEcologyen
dc.subjectConservationen
dc.subjectMarine mammalsen
dc.subjectPopulation recoveryen
dc.subjectGC Oceanographyen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subjectMCCen
dc.subject.lccGCen
dc.subject.lccQH301en
dc.titleDistribution and habitat use modelling from satellite tracking data of humpback whales in Brazil agree with shipboard survey data modellingen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
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. Scottish Oceans Instituteen
dc.identifier.doi10.3354/meps14404
dc.description.statusPeer revieweden
dc.date.embargoedUntil2023-10-05


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