Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca)
There 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...
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ftpubmed:oai:pubmedcentral.nih.gov:6133345 2023-05-15T17:41:41+02:00 Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) Nykänen, Milaja Jessopp, Mark Doyle, Thomas K. Harman, Luke A. Cañadas, Ana Breen, Patricia Hunt, William Mackey, Mick Cadhla, Oliver Ó Reid, David Rogan, Emer 2018-09-11 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133345/ http://www.ncbi.nlm.nih.gov/pubmed/30204764 https://doi.org/10.1371/journal.pone.0203122 en eng Public Library of Science http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133345/ http://www.ncbi.nlm.nih.gov/pubmed/30204764 http://dx.doi.org/10.1371/journal.pone.0203122 © 2018 Nykänen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. CC-BY Research Article Text 2018 ftpubmed https://doi.org/10.1371/journal.pone.0203122 2018-09-30T00:11:34Z There 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 ... Text Northeast Atlantic PubMed Central (PMC) PLOS ONE 13 9 e0203122 |
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Research Article Nykänen, Milaja Jessopp, Mark Doyle, Thomas K. Harman, Luke A. Cañadas, Ana Breen, Patricia Hunt, William Mackey, Mick Cadhla, Oliver Ó Reid, David Rogan, Emer Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
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Research Article |
description |
There 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 ... |
format |
Text |
author |
Nykänen, Milaja Jessopp, Mark Doyle, Thomas K. Harman, Luke A. Cañadas, Ana Breen, Patricia Hunt, William Mackey, Mick Cadhla, Oliver Ó Reid, David Rogan, Emer |
author_facet |
Nykänen, Milaja Jessopp, Mark Doyle, Thomas K. Harman, Luke A. Cañadas, Ana Breen, Patricia Hunt, William Mackey, Mick Cadhla, Oliver Ó Reid, David Rogan, Emer |
author_sort |
Nykänen, Milaja |
title |
Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
title_short |
Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
title_full |
Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
title_fullStr |
Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
title_full_unstemmed |
Using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (Prionace glauca) |
title_sort |
using tagging data and aerial surveys to incorporate availability bias in the abundance estimation of blue sharks (prionace glauca) |
publisher |
Public Library of Science |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133345/ http://www.ncbi.nlm.nih.gov/pubmed/30204764 https://doi.org/10.1371/journal.pone.0203122 |
genre |
Northeast Atlantic |
genre_facet |
Northeast Atlantic |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6133345/ http://www.ncbi.nlm.nih.gov/pubmed/30204764 http://dx.doi.org/10.1371/journal.pone.0203122 |
op_rights |
© 2018 Nykänen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1371/journal.pone.0203122 |
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PLOS ONE |
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13 |
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9 |
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e0203122 |
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