Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping

Marine protected areas (MPAs) underpin the sustainable management of marine ecosystems but require accurate knowledge of species distributions. Recently, advances in tracking technology and habitat modelling have enabled the production of large-scale species distribution models (SDM), which provide...

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Published in:Biological Conservation
Main Authors: Cleasby, Ian R., Owen, Ellie, Wilson, Linda, Wakefield, Ewan D., O'Connell, Peadar, Bolton, Mark
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2020
Subjects:
Online Access:https://eprints.gla.ac.uk/209651/
https://eprints.gla.ac.uk/209651/1/209651.pdf
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spelling ftuglasgow:oai:eprints.gla.ac.uk:209651 2023-05-15T13:12:18+02:00 Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping Cleasby, Ian R. Owen, Ellie Wilson, Linda Wakefield, Ewan D. O'Connell, Peadar Bolton, Mark 2020-01 text https://eprints.gla.ac.uk/209651/ https://eprints.gla.ac.uk/209651/1/209651.pdf en eng Elsevier https://eprints.gla.ac.uk/209651/1/209651.pdf Cleasby, I. R., Owen, E., Wilson, L., Wakefield, E. D. <http://eprints.gla.ac.uk/view/author/31199.html> , O'Connell, P. and Bolton, M. (2020) Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping. Biological Conservation <https://eprints.gla.ac.uk/view/journal_volume/Biological_Conservation.html>, 241, 108375. (doi:10.1016/j.biocon.2019.108375 <https://doi.org/10.1016/j.biocon.2019.108375>) cc_by_4 CC-BY Articles PeerReviewed 2020 ftuglasgow https://doi.org/10.1016/j.biocon.2019.108375 2022-09-22T22:15:42Z Marine protected areas (MPAs) underpin the sustainable management of marine ecosystems but require accurate knowledge of species distributions. Recently, advances in tracking technology and habitat modelling have enabled the production of large-scale species distribution models (SDM), which provide the basis for hotspot mapping. In the UK, hotspot mapping to inform seabird MPA identification has involved converting observed or predicted distributions to polygons using either Maximum Curvature or Getis-Ord (Gi*) analysis. Here, we apply both mapping techniques to UK-wide, breeding season SDM predictions for four seabird species (Black-legged Kittiwakes Rissa tridactyla, Common Guillemots Uria aalge, Razorbills Alca torda and European Shags Phalacrocorax aristotelis) in order to compare their performance and inform seabird MPA. When using Maximum Curvature, grid cells within the identified maximum curvature boundaries were defined as hotspots. For Getis-Ord analysis, we defined hotspots as either (1) grid cells containing the top 1% or (2) the top 5% Gi* scores or (3) cells in which Gi* scores were statistically significant. Hotspots based upon Maximum Curvature or statistically significant Gi* scores covered the greatest area and were generally larger than current marine Special Protection Areas. Hotspots based on the top 1% or top 5% of Gi* scores were smaller and were concentrated around the largest breeding colonies. All hotspot methods consistently identified several high-density areas that should be prioritised for seabird conservation. Ultimately, the choice of hotspot identification method should be informed by considering species ecology alongside conservation goals to ensure hotspots are of sufficient size to protect target populations. Article in Journal/Newspaper Alca torda rissa tridactyla Uria aalge uria University of Glasgow: Enlighten - Publications Biological Conservation 241 108375
institution Open Polar
collection University of Glasgow: Enlighten - Publications
op_collection_id ftuglasgow
language English
description Marine protected areas (MPAs) underpin the sustainable management of marine ecosystems but require accurate knowledge of species distributions. Recently, advances in tracking technology and habitat modelling have enabled the production of large-scale species distribution models (SDM), which provide the basis for hotspot mapping. In the UK, hotspot mapping to inform seabird MPA identification has involved converting observed or predicted distributions to polygons using either Maximum Curvature or Getis-Ord (Gi*) analysis. Here, we apply both mapping techniques to UK-wide, breeding season SDM predictions for four seabird species (Black-legged Kittiwakes Rissa tridactyla, Common Guillemots Uria aalge, Razorbills Alca torda and European Shags Phalacrocorax aristotelis) in order to compare their performance and inform seabird MPA. When using Maximum Curvature, grid cells within the identified maximum curvature boundaries were defined as hotspots. For Getis-Ord analysis, we defined hotspots as either (1) grid cells containing the top 1% or (2) the top 5% Gi* scores or (3) cells in which Gi* scores were statistically significant. Hotspots based upon Maximum Curvature or statistically significant Gi* scores covered the greatest area and were generally larger than current marine Special Protection Areas. Hotspots based on the top 1% or top 5% of Gi* scores were smaller and were concentrated around the largest breeding colonies. All hotspot methods consistently identified several high-density areas that should be prioritised for seabird conservation. Ultimately, the choice of hotspot identification method should be informed by considering species ecology alongside conservation goals to ensure hotspots are of sufficient size to protect target populations.
format Article in Journal/Newspaper
author Cleasby, Ian R.
Owen, Ellie
Wilson, Linda
Wakefield, Ewan D.
O'Connell, Peadar
Bolton, Mark
spellingShingle Cleasby, Ian R.
Owen, Ellie
Wilson, Linda
Wakefield, Ewan D.
O'Connell, Peadar
Bolton, Mark
Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
author_facet Cleasby, Ian R.
Owen, Ellie
Wilson, Linda
Wakefield, Ewan D.
O'Connell, Peadar
Bolton, Mark
author_sort Cleasby, Ian R.
title Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
title_short Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
title_full Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
title_fullStr Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
title_full_unstemmed Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
title_sort identifying important at-sea areas for seabirds using species distribution models and hotspot mapping
publisher Elsevier
publishDate 2020
url https://eprints.gla.ac.uk/209651/
https://eprints.gla.ac.uk/209651/1/209651.pdf
genre Alca torda
rissa tridactyla
Uria aalge
uria
genre_facet Alca torda
rissa tridactyla
Uria aalge
uria
op_relation https://eprints.gla.ac.uk/209651/1/209651.pdf
Cleasby, I. R., Owen, E., Wilson, L., Wakefield, E. D. <http://eprints.gla.ac.uk/view/author/31199.html> , O'Connell, P. and Bolton, M. (2020) Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping. Biological Conservation <https://eprints.gla.ac.uk/view/journal_volume/Biological_Conservation.html>, 241, 108375. (doi:10.1016/j.biocon.2019.108375 <https://doi.org/10.1016/j.biocon.2019.108375>)
op_rights cc_by_4
op_rightsnorm CC-BY
op_doi https://doi.org/10.1016/j.biocon.2019.108375
container_title Biological Conservation
container_volume 241
container_start_page 108375
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