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dc.contributor.authorRaudino, Holly C.
dc.contributor.authorBouchet, Phil J.
dc.contributor.authorDouglas, Corrine
dc.contributor.authorDouglas, Ryan
dc.contributor.authorWaples, Kelly
dc.date.accessioned2023-02-02T10:30:17Z
dc.date.available2023-02-02T10:30:17Z
dc.date.issued2023-01-18
dc.identifier283208258
dc.identifierf405c6f9-c8d4-4b0a-84fd-3cb7e691a025
dc.identifier000922583000001
dc.identifier85147228776
dc.identifier.citationRaudino , H C , Bouchet , P J , Douglas , C , Douglas , R & Waples , K 2023 , ' Aerial abundance estimates for two sympatric dolphin species at a regional scale using distance sampling and density surface modeling ' , Frontiers in Ecology and Evolution , vol. 10 , 1086686 . https://doi.org/10.3389/fevo.2022.1086686en
dc.identifier.issn2296-701X
dc.identifier.otherJisc: 874947
dc.identifier.otherORCID: /0000-0002-2144-2049/work/128096962
dc.identifier.urihttps://hdl.handle.net/10023/26885
dc.descriptionFunding: This research was funded by the Chevron-operated Wheatstone LNG Project’s State Environmental Offsets Program administered by the Department of Biodiversity, Conservation and Attractions. The Wheatstone Project is a joint venture between Australian subsidiaries of Chevron, Kuwaut Foreign Petroleum Exploration Company (KUFPEC), and Apache Corporation and Kyushu Electric Power Company, together with PE Wheatstone Pty Ltd (part-owned by TEPCO). This project was also supported by Woodside through the Pluto LNG Environmental Offsets Program.en
dc.description.abstractMonitoring wildlife populations over scales relevant to management is critical to supporting conservation decision-making in the face of data deficiency, particularly for rare species occurring across large geographic ranges. The Pilbara region of Western Australia is home to two sympatric and morphologically similar species of coastal dolphins—the Indo-pacific bottlenose dolphin (Tursiops aduncus) and Australian humpback dolphin (Sousa sahulensis)—both of which are believed to be declining in numbers and facing increasing pressures from the combined impacts of environmental change and extensive industrial activities. The aim of this study was to develop spatially explicit models of bottlenose and humpback dolphin abundance in Pilbara waters that could inform decisions about coastal development at a regional scale. Aerial line transect surveys were flown from a fixed-wing aircraft in the austral winters of 2015, 2016, and 2017 across a total area of 33,420 km2. Spatio-temporal patterns in dolphin density were quantified using a density surface modeling (DSM) approach, accounting for imperfect detection as well as both perception and availability bias. We estimated the abundance of bottlenose dolphins at 3,713 (95% CI = 2,679–5,146; average density of 0.189 ± 0.046 SD individuals per km2) in 2015, 2,638 (95% CI = 1,670–4,168; 0.159 ± 0.135 individuals per km2) in 2016 and 1,635 (95% CI = 1,031–2,593; 0.101 ± 0.103 individuals per km2) in 2017. Too few humpback dolphins were detected in 2015 to model abundance, but their estimated abundance was 1,546 (95% CI = 942–2,537; 0.097 ± 0.03 individuals per km2) and 2,690 (95% CI = 1,792–4,038; 0.169 ± 0.064 individuals per km2) in 2016 and 2017, respectively. Dolphin densities were greatest in nearshore waters, with hotspots in Exmouth Gulf, the Dampier Archipelago, and Great Sandy Islands. Our results provide a benchmark on which future risk assessments can be based to better understand the overlap between pressures and important dolphin habitats in tropical northwestern Australia.
dc.format.extent13
dc.format.extent5097131
dc.language.isoeng
dc.relation.ispartofFrontiers in Ecology and Evolutionen
dc.subjectEcology and Evolutionen
dc.subjectAerial surveyen
dc.subjectCetaceanen
dc.subjectConservationen
dc.subjectDistributionen
dc.subjectManagementen
dc.subjectPopulation sizeen
dc.subjectQH301 Biologyen
dc.subjectQL Zoologyen
dc.subjectDASen
dc.subjectMCCen
dc.subject.lccQH301en
dc.subject.lccQLen
dc.titleAerial abundance estimates for two sympatric dolphin species at a regional scale using distance sampling and density surface modelingen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doi10.3389/fevo.2022.1086686
dc.description.statusPeer revieweden


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