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dc.contributor.authorPirotta, Enrico
dc.contributor.authorBooth, Cormac
dc.contributor.authorCalambokidis, John
dc.contributor.authorCosta, Daniel
dc.contributor.authorFahlbusch, James
dc.contributor.authorFriedlaender, Ari
dc.contributor.authorGoldbogen, Jeremy
dc.contributor.authorHarwood, John
dc.contributor.authorHazen, Elliot
dc.contributor.authorNew, Leslie
dc.contributor.authorSantora, Jarrod A
dc.contributor.authorWatwood, Stephanie
dc.contributor.authorWertman, Christina
dc.contributor.authorSouthall, Brandon
dc.date.accessioned2022-04-18T11:30:01Z
dc.date.available2022-04-18T11:30:01Z
dc.date.issued2022-12-23
dc.identifier278617445
dc.identifier00671bfe-53fd-4546-ae89-3b23608cd4c5
dc.identifier85128214006
dc.identifier000782735400001
dc.identifier.citationPirotta , E , Booth , C , Calambokidis , J , Costa , D , Fahlbusch , J , Friedlaender , A , Goldbogen , J , Harwood , J , Hazen , E , New , L , Santora , J A , Watwood , S , Wertman , C & Southall , B 2022 , ' From individual responses to population effects : integrating a decade of multidisciplinary research on blue whales and sonar ' , Animal Conservation , vol. 25 , no. 6 , pp. 796-810 . https://doi.org/10.1111/acv.12785en
dc.identifier.issn1367-9430
dc.identifier.otherORCID: /0000-0003-3541-3676/work/111976187
dc.identifier.urihttps://hdl.handle.net/10023/25201
dc.descriptionFunding: Office of Naval Research (GrantNumber(s): N00014-19-1-2464).en
dc.description.abstractAs ecosystems transform under climate change and expanding human activities, multidisciplinary integration of empirical research, conceptual frameworks and modelling methods is required to predict, monitor and manage the cascading effects on wildlife populations. For example, exposure to anthropogenic noise can lead to changes in the behaviour and physiology of individual marine mammals, but management is complicated by uncertainties on the long-term effects at a population level. We build on a decade of diverse efforts to demonstrate the strengths of integrating research on multiple stressors for assessing population-level effects. Using the case study of blue whales exposed to military sonar in the eastern north Pacific, we model how behavioural responses and environmental effects induced by climate change affect female survival and reproductive success. Environmental changes were predicted to severely affect vital rates, while the current regime of sonar activities was not. Simulated disturbance had a stronger effect on reproductive success than adult survival, as predicted by life-history theory. We show that information on prey resources is critical for robust predictions, as are data on baseline behavioural patterns, energy budgets, body condition and contextual responses to noise. These results will support effective management of the interactions between sonar operations and blue whales in the study area, while providing pragmatic guidance for future data collection to reduce key uncertainties. Our study provides important lessons for the successful integration of multidisciplinary research to inform the assessment of the effects of noise and other anthropogenic stressors on marine predator populations in the context of a changing environment.
dc.format.extent15
dc.format.extent1313457
dc.language.isoeng
dc.relation.ispartofAnimal Conservationen
dc.subjectAnthropogenic disturbanceen
dc.subjectSpatial planningen
dc.subjectPopulation consequences of disturbanceen
dc.subjectMilitary sonaren
dc.subjectMechanistic modellingen
dc.subjectMarine mammalsen
dc.subjectData integrationen
dc.subjectClimate changeen
dc.subjectQH301 Biologyen
dc.subjectDASen
dc.subjectSDG 13 - Climate Actionen
dc.subjectSDG 14 - Life Below Wateren
dc.subjectMCCen
dc.subject.lccQH301en
dc.titleFrom individual responses to population effects : integrating a decade of multidisciplinary research on blue whales and sonaren
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. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doi10.1111/acv.12785
dc.description.statusPeer revieweden


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