Modelling polar bear maternity den habitat in east Svalbard

We evaluated a novel tool that predicts possible maternity den habitat of the polar bear (Ursus maritimus) based on a physical snow transport model, a digital terrain model and weather data. We observed and compared den locations in three important denning areas in east Svalbard (Kongsøya, n = 288;...

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Published in:Polar Research
Main Authors: Benjamin Merkel, Jon Aars, Glen E. Liston
Format: Article in Journal/Newspaper
Language:English
Published: Norwegian Polar Institute 2020
Subjects:
Online Access:https://doi.org/10.33265/polar.v39.3447
https://doaj.org/article/90f716e02a4e4560a50888ceae79867a
id ftdoajarticles:oai:doaj.org/article:90f716e02a4e4560a50888ceae79867a
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spelling ftdoajarticles:oai:doaj.org/article:90f716e02a4e4560a50888ceae79867a 2023-05-15T15:05:21+02:00 Modelling polar bear maternity den habitat in east Svalbard Benjamin Merkel Jon Aars Glen E. Liston 2020-03-01T00:00:00Z https://doi.org/10.33265/polar.v39.3447 https://doaj.org/article/90f716e02a4e4560a50888ceae79867a EN eng Norwegian Polar Institute https://polarresearch.net/index.php/polar/article/view/3447/10243 https://doaj.org/toc/1751-8369 1751-8369 doi:10.33265/polar.v39.3447 https://doaj.org/article/90f716e02a4e4560a50888ceae79867a Polar Research, Vol 39, Iss 0, Pp 1-9 (2020) climate change reproduction snowdens-3d snowdrift model terrain model topography Environmental sciences GE1-350 Oceanography GC1-1581 article 2020 ftdoajarticles https://doi.org/10.33265/polar.v39.3447 2022-12-31T00:54:12Z We evaluated a novel tool that predicts possible maternity den habitat of the polar bear (Ursus maritimus) based on a physical snow transport model, a digital terrain model and weather data. We observed and compared den locations in three important denning areas in east Svalbard (Kongsøya, n = 288; Svenskøya, n = 86; Hopen, n = 115) with modelled snowdrift distributions for 24 years. Accounting for a likely position uncertainty of 100 m, 69% of all dens were located within year-specific modelled snowdrifts. These covered on average 1.8%, 2.1% and 24.7% of the three study islands, respectively. Our snowdrift model accurately predicted maternity den positions (R2 = 0.42, area under the receiving operating characteristic curve [AUC] = 0.85). A model based on slope and altitude, also predicted den positions reasonably well (R2 = 0.35, AUC = 0.88). Habitat maps identifying both current and future areas for maternity denning will become important in managing the Barents Sea population as well as other Arctic populations where changes in sea-ice conditions alter the accessibility to traditional denning areas. Article in Journal/Newspaper Arctic Barents Sea Climate change Hopen Kongsøya Kongsøya Polar Research Sea ice Svalbard Svenskøya Ursus maritimus Hopen Directory of Open Access Journals: DOAJ Articles Arctic Svalbard Barents Sea Hopen ENVELOPE(9.279,9.279,63.379,63.379) Polar Research 39 0
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic climate change
reproduction
snowdens-3d
snowdrift model
terrain model
topography
Environmental sciences
GE1-350
Oceanography
GC1-1581
spellingShingle climate change
reproduction
snowdens-3d
snowdrift model
terrain model
topography
Environmental sciences
GE1-350
Oceanography
GC1-1581
Benjamin Merkel
Jon Aars
Glen E. Liston
Modelling polar bear maternity den habitat in east Svalbard
topic_facet climate change
reproduction
snowdens-3d
snowdrift model
terrain model
topography
Environmental sciences
GE1-350
Oceanography
GC1-1581
description We evaluated a novel tool that predicts possible maternity den habitat of the polar bear (Ursus maritimus) based on a physical snow transport model, a digital terrain model and weather data. We observed and compared den locations in three important denning areas in east Svalbard (Kongsøya, n = 288; Svenskøya, n = 86; Hopen, n = 115) with modelled snowdrift distributions for 24 years. Accounting for a likely position uncertainty of 100 m, 69% of all dens were located within year-specific modelled snowdrifts. These covered on average 1.8%, 2.1% and 24.7% of the three study islands, respectively. Our snowdrift model accurately predicted maternity den positions (R2 = 0.42, area under the receiving operating characteristic curve [AUC] = 0.85). A model based on slope and altitude, also predicted den positions reasonably well (R2 = 0.35, AUC = 0.88). Habitat maps identifying both current and future areas for maternity denning will become important in managing the Barents Sea population as well as other Arctic populations where changes in sea-ice conditions alter the accessibility to traditional denning areas.
format Article in Journal/Newspaper
author Benjamin Merkel
Jon Aars
Glen E. Liston
author_facet Benjamin Merkel
Jon Aars
Glen E. Liston
author_sort Benjamin Merkel
title Modelling polar bear maternity den habitat in east Svalbard
title_short Modelling polar bear maternity den habitat in east Svalbard
title_full Modelling polar bear maternity den habitat in east Svalbard
title_fullStr Modelling polar bear maternity den habitat in east Svalbard
title_full_unstemmed Modelling polar bear maternity den habitat in east Svalbard
title_sort modelling polar bear maternity den habitat in east svalbard
publisher Norwegian Polar Institute
publishDate 2020
url https://doi.org/10.33265/polar.v39.3447
https://doaj.org/article/90f716e02a4e4560a50888ceae79867a
long_lat ENVELOPE(9.279,9.279,63.379,63.379)
geographic Arctic
Svalbard
Barents Sea
Hopen
geographic_facet Arctic
Svalbard
Barents Sea
Hopen
genre Arctic
Barents Sea
Climate change
Hopen
Kongsøya
Kongsøya
Polar Research
Sea ice
Svalbard
Svenskøya
Ursus maritimus
Hopen
genre_facet Arctic
Barents Sea
Climate change
Hopen
Kongsøya
Kongsøya
Polar Research
Sea ice
Svalbard
Svenskøya
Ursus maritimus
Hopen
op_source Polar Research, Vol 39, Iss 0, Pp 1-9 (2020)
op_relation https://polarresearch.net/index.php/polar/article/view/3447/10243
https://doaj.org/toc/1751-8369
1751-8369
doi:10.33265/polar.v39.3447
https://doaj.org/article/90f716e02a4e4560a50888ceae79867a
op_doi https://doi.org/10.33265/polar.v39.3447
container_title Polar Research
container_volume 39
container_issue 0
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