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dc.contributor.authorBortolotto, Guilherme Augusto
dc.contributor.authorDanilewicz, Daniel
dc.contributor.authorHammond, Philip Steven
dc.contributor.authorThomas, Leonard Joseph
dc.contributor.authorZerbini, Alexandre N
dc.date.accessioned2018-12-27T00:34:53Z
dc.date.available2018-12-27T00:34:53Z
dc.date.issued2017-12-27
dc.identifier250609859
dc.identifierf57d7712-3d7f-4fcf-99a6-81ff71c95a24
dc.identifier85039936650
dc.identifier000418811000015
dc.identifier.citationBortolotto , G A , Danilewicz , D , Hammond , P S , Thomas , L J & Zerbini , A N 2017 , ' Whale distribution in a breeding area : spatial models of habitat use and abundance of western South Atlantic humpback whales ' , Marine Ecology Progress Series , vol. 585 , pp. 213-227 . https://doi.org/10.3354/meps12393en
dc.identifier.issn0171-8630
dc.identifier.otherORCID: /0000-0002-2381-8302/work/47531630
dc.identifier.otherORCID: /0000-0002-7436-067X/work/40075005
dc.identifier.otherORCID: /0000-0002-5343-6575/work/58055829
dc.identifier.urihttps://hdl.handle.net/10023/16764
dc.descriptionGA Bortolotto PhD is funded by the Brazilian National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Science Without Borders, scholarship #208203/2014 - 1). Cetacean International Society granted GA Bortolotto with small grants which contributed to the development of this study.en
dc.description.abstractThe western South Atlantic humpback whale population was severely depleted by commercial whaling in the late 19th and 20th centuries, and today inhabits a human-impacted environment in its wintering grounds off the Brazilian coast. We identified distribution patterns related to environmental features and provide new estimates of population size, which can inform future management actions. We fitted spatial models to line transect data from 2 research cruises conducted in 2008 and 2012 to investigate (1) habitat use and (2) abundance of humpback whales wintering in the Brazilian continental shelf. Potential explanatory variables were year, depth, seabed slope, sea-surface temperature (SST), northing and easting, current speed, wind speed, distance to coastline and to the continental shelf break, and shelter (a combination of wind speed and SST categories). Whale density was higher in slower currents, at shorter distances to both the coastline and shelf break, and at SSTs between 24 and 25°C. The distribution of whales was also strongly related to shelter. For abundance estimation, easting and northing were included in the model instead of SST; estimates were 14264 whales (CV = 0.084) for 2008 and 20389 (CV = 0.071) for 2012. Environmental variables explained well the variation in whale density; higher density was found to the south of the Abrolhos Archipelago, and shelter seems to be important for these animals in their breeding area. Estimated distribution patterns presented here can be used to mitigate potential human-related impacts, such as supporting protection in the population’s core habitat near the Abrolhos Archipelago.
dc.format.extent1993721
dc.language.isoeng
dc.relation.ispartofMarine Ecology Progress Seriesen
dc.subjectShelteren
dc.subjectConservationen
dc.subjectDensity surface modelen
dc.subjectCetaceanen
dc.subjectLine transecten
dc.subjectReproductionen
dc.subjectGE Environmental Sciencesen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subject.lccGEen
dc.subject.lccQH301en
dc.titleWhale distribution in a breeding area : spatial models of habitat use and abundance of western South Atlantic humpback whalesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
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. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.identifier.doi10.3354/meps12393
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-12-27


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