Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling
Summary The Greenland Sea is an important breeding ground for harp and hooded seals. Estimates of annual seal pup production are critical factors in the estimation of abundance that is needed for management of the species. These estimates are usually based on counts from aerial photographic surveys....
Published in: | Journal of the Royal Statistical Society: Series C (Applied Statistics) |
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Oxford University Press (OUP)
2020
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Online Access: | http://dx.doi.org/10.1111/rssc.12397 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Frssc.12397 https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12397 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssc.12397 https://academic.oup.com/jrsssc/article-pdf/69/2/327/49339836/jrsssc_69_2_327.pdf |
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croxfordunivpr:10.1111/rssc.12397 2024-09-15T18:09:24+00:00 Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling Jullum, Martin Thorarinsdottir, Thordis Bachl, Fabian E. Research Council of Norway Engineering and Physical Sciences Research Council Norwegian Institute of Marine Research 2020 http://dx.doi.org/10.1111/rssc.12397 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Frssc.12397 https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12397 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssc.12397 https://academic.oup.com/jrsssc/article-pdf/69/2/327/49339836/jrsssc_69_2_327.pdf en eng Oxford University Press (OUP) https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model Journal of the Royal Statistical Society Series C: Applied Statistics volume 69, issue 2, page 327-352 ISSN 0035-9254 1467-9876 journal-article 2020 croxfordunivpr https://doi.org/10.1111/rssc.12397 2024-08-05T04:33:54Z Summary The Greenland Sea is an important breeding ground for harp and hooded seals. Estimates of annual seal pup production are critical factors in the estimation of abundance that is needed for management of the species. These estimates are usually based on counts from aerial photographic surveys. However, only a minor part of the whelping region can be photographed, because of its large extent. To estimate total seal pup production, we propose a Bayesian hierarchical modelling approach motivated by viewing the seal pup appearances as a realization of a log-Gaussian Cox process by using covariate information from satellite imagery as a proxy for ice thickness. For inference, we utilize the stochastic partial differential equation module of the integrated nested Laplace approximation framework. In a case-study using survey data from 2012, we compare our results with existing methodology in a comprehensive cross-validation study. The results of the study indicate that our method improves local estimation performance, and that the increased uncertainty of prediction of our method is required to obtain calibrated count predictions. This suggests that the sampling density of the survey design may not be sufficient to obtain reliable estimates of seal pup production. Article in Journal/Newspaper Greenland Greenland Sea Oxford University Press Journal of the Royal Statistical Society: Series C (Applied Statistics) 69 2 327 352 |
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Open Polar |
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Oxford University Press |
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croxfordunivpr |
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English |
description |
Summary The Greenland Sea is an important breeding ground for harp and hooded seals. Estimates of annual seal pup production are critical factors in the estimation of abundance that is needed for management of the species. These estimates are usually based on counts from aerial photographic surveys. However, only a minor part of the whelping region can be photographed, because of its large extent. To estimate total seal pup production, we propose a Bayesian hierarchical modelling approach motivated by viewing the seal pup appearances as a realization of a log-Gaussian Cox process by using covariate information from satellite imagery as a proxy for ice thickness. For inference, we utilize the stochastic partial differential equation module of the integrated nested Laplace approximation framework. In a case-study using survey data from 2012, we compare our results with existing methodology in a comprehensive cross-validation study. The results of the study indicate that our method improves local estimation performance, and that the increased uncertainty of prediction of our method is required to obtain calibrated count predictions. This suggests that the sampling density of the survey design may not be sufficient to obtain reliable estimates of seal pup production. |
author2 |
Research Council of Norway Engineering and Physical Sciences Research Council Norwegian Institute of Marine Research |
format |
Article in Journal/Newspaper |
author |
Jullum, Martin Thorarinsdottir, Thordis Bachl, Fabian E. |
spellingShingle |
Jullum, Martin Thorarinsdottir, Thordis Bachl, Fabian E. Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
author_facet |
Jullum, Martin Thorarinsdottir, Thordis Bachl, Fabian E. |
author_sort |
Jullum, Martin |
title |
Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
title_short |
Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
title_full |
Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
title_fullStr |
Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
title_full_unstemmed |
Estimating Seal Pup Production in The Greenland Sea by Using Bayesian Hierarchical Modelling |
title_sort |
estimating seal pup production in the greenland sea by using bayesian hierarchical modelling |
publisher |
Oxford University Press (OUP) |
publishDate |
2020 |
url |
http://dx.doi.org/10.1111/rssc.12397 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Frssc.12397 https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12397 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssc.12397 https://academic.oup.com/jrsssc/article-pdf/69/2/327/49339836/jrsssc_69_2_327.pdf |
genre |
Greenland Greenland Sea |
genre_facet |
Greenland Greenland Sea |
op_source |
Journal of the Royal Statistical Society Series C: Applied Statistics volume 69, issue 2, page 327-352 ISSN 0035-9254 1467-9876 |
op_rights |
https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model |
op_doi |
https://doi.org/10.1111/rssc.12397 |
container_title |
Journal of the Royal Statistical Society: Series C (Applied Statistics) |
container_volume |
69 |
container_issue |
2 |
container_start_page |
327 |
op_container_end_page |
352 |
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1810446947544203264 |