Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca)

dc.contributor.authorNykänen, Milaja
dc.contributor.authorJessopp, Mark J.
dc.contributor.authorDoyle, Thomas K.
dc.contributor.authorHarman, Luke A.
dc.contributor.authorCañadas, Ana
dc.contributor.authorBreen, Patricia
dc.contributor.authorHunt, William
dc.contributor.authorMackey, Mick
dc.contributor.authorÓ Cadhla, Oliver
dc.contributor.authorReid, David
dc.contributor.authorRogan, Emer
dc.contributor.funderDepartment of Culture, Heritage and the Gaeltachten
dc.contributor.funderUniversity College Corken
dc.contributor.funderDepartment of Agriculture, Food and the Marineen
dc.contributor.funderDepartment of Communications, Climate Action and Environment, Irelanden
dc.contributor.funderALNILAM Research and Conservation Ltd.en
dc.description.abstractThere is worldwide concern about the status of elasmobranchs, primarily as a result of overfishing and bycatch with subsequent ecosystem effects following the removal of top predators. Whilst abundant and wide-ranging, blue sharks (Prionace glauca) are the most heavily exploited shark species having suffered marked declines over the past decades, and there is a call for robust abundance estimates. In this study, we utilized depth data collected from two blue sharks using pop-up satellite archival tags, and modelled the proportion of time the sharks were swimming in the top 1-meter layer and could therefore be detected by observers conducting aerial surveys. The availability models indicated that the tagged sharks preferred surface waters whilst swimming over the continental shelf and during daytime, with a model-predicted average proportion of time spent at the surface of 0.633 (SD = 0.094) for on-shelf, and 0.136 (SD = 0.075) for off-shelf. These predicted values were then used to account for availability bias in abundance estimates for the species over a large area in the Northeast Atlantic, derived through distance sampling using aerial survey data collected in 2015 and 2016 and modelled with density surface models. Further, we compared abundance estimates corrected with model-predicted availability to uncorrected estimates and to estimates that incorporated the average time the sharks were available for detection. The mean abundance (number of individuals) corrected with modelled availability was 15,320 (CV = 0.28) in 2015 and 11,001 (CV = 0.27) in 2016. Depending on the year, these estimates were ~7 times higher compared to estimates without the bias correction, and ~3 times higher compared to the abundances corrected with average availability. When the survey area contains habitat heterogeneity that may affect surfacing patterns of animals, modelling animals’ availability provides a robust alternative to correcting for availability bias and highlights the need for caution when applying “average” correction factors.en
dc.description.sponsorshipDepartment of Communications, Climate Action and Environment (ObSERVE programme); Department of Culture, Heritage and the Gaeltacht (ObSERVE programme); (University College Cork (UCC Strategic Research Fund 2013); Department of Agriculture, Food and the Marine’s (Competitive Research Funding programme: Project FishKosm)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.identifier.citationNykänen, M., Jessopp, M., Doyle, T.K., Harman, L.A., Cañadas, A., Breen, P., Hunt, W., Mackey, M., Ó Cadhla, O., Reid, D. and Rogan, E., 2018. Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca). PloS one, 13(9), e0203122 (18 pp.). DOI:10.1371/journal.pone.0203122en
dc.identifier.journaltitlePLoS ONEen
dc.rights© 2018 Nykänen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.subjectBlue sharks (Prionace glauca)en
dc.titleUsing tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca)en
dc.typeArticle (peer-reviewed)en
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