Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
Abstract Aim Our aim involved developing a method to analyse spatiotemporal distributions of Arctic marine mammals ( AMM s) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMM...
Published in: | Diversity and Distributions |
---|---|
Main Authors: | , |
Other Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2018
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1111/ddi.12776 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fddi.12776 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddi.12776 |
id |
crwiley:10.1111/ddi.12776 |
---|---|
record_format |
openpolar |
spelling |
crwiley:10.1111/ddi.12776 2024-06-02T08:00:14+00:00 Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals Mäkinen, Jussi Vanhatalo, Jarno McCarthy, Michael Academy of Finland Helsingin Yliopiston Tiedesäätiö Lloyd's Register Foundation 2018 http://dx.doi.org/10.1111/ddi.12776 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fddi.12776 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddi.12776 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Diversity and Distributions volume 24, issue 10, page 1381-1394 ISSN 1366-9516 1472-4642 journal-article 2018 crwiley https://doi.org/10.1111/ddi.12776 2024-05-03T11:59:51Z Abstract Aim Our aim involved developing a method to analyse spatiotemporal distributions of Arctic marine mammals ( AMM s) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMM s’ distributions and to analyse whether their distributions have shifted along with environmental changes. Location Arctic shelf area. The Kara Sea. Methods Our literature search focused on survey data regarding polar bears ( Ursus maritimus ), Atlantic walruses ( Odobenus rosmarus rosmarus ) and ringed seals ( Phoca hispida ). We mapped the data on a grid and built a hierarchical Poisson point process model to analyse species’ densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results The most important covariates explaining AMM s’ relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17‐year‐long study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species’ distributions compared to a solely environmental model. The decreasing ice cover seems to have ... Article in Journal/Newspaper Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* Wiley Online Library Arctic Kara Sea Diversity and Distributions 24 10 1381 1394 |
institution |
Open Polar |
collection |
Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
description |
Abstract Aim Our aim involved developing a method to analyse spatiotemporal distributions of Arctic marine mammals ( AMM s) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMM s’ distributions and to analyse whether their distributions have shifted along with environmental changes. Location Arctic shelf area. The Kara Sea. Methods Our literature search focused on survey data regarding polar bears ( Ursus maritimus ), Atlantic walruses ( Odobenus rosmarus rosmarus ) and ringed seals ( Phoca hispida ). We mapped the data on a grid and built a hierarchical Poisson point process model to analyse species’ densities. The heterogeneous data lacked information on survey intensity and we could model only the relative density of each species. We explained relative densities with environmental covariates and random effects reflecting excess spatiotemporal variation and the unknown, varying sampling effort. The relative density of polar bears was explained also by the relative density of seals. Results The most important covariates explaining AMM s’ relative densities were ice concentration and distance to the coast, and regarding polar bears, also the relative density of seals. The results suggest that due to the decrease in the average ice concentration, the relative densities of polar bears and walruses slightly decreased or stayed constant during the 17‐year‐long study period, whereas seals shifted their distribution from the Eastern to the Western Kara Sea. Main conclusions Point process modelling is a robust methodology to estimate distributions from heterogeneous observations, providing spatially explicit information about ecosystems and thus serves advances for conservation efforts in the Arctic. In a simple trophic system, a distribution model of a top predator benefits from utilizing prey species’ distributions compared to a solely environmental model. The decreasing ice cover seems to have ... |
author2 |
McCarthy, Michael Academy of Finland Helsingin Yliopiston Tiedesäätiö Lloyd's Register Foundation |
format |
Article in Journal/Newspaper |
author |
Mäkinen, Jussi Vanhatalo, Jarno |
spellingShingle |
Mäkinen, Jussi Vanhatalo, Jarno Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
author_facet |
Mäkinen, Jussi Vanhatalo, Jarno |
author_sort |
Mäkinen, Jussi |
title |
Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_short |
Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full |
Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_fullStr |
Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full_unstemmed |
Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_sort |
hierarchical bayesian model reveals the distributional shifts of arctic marine mammals |
publisher |
Wiley |
publishDate |
2018 |
url |
http://dx.doi.org/10.1111/ddi.12776 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fddi.12776 https://onlinelibrary.wiley.com/doi/pdf/10.1111/ddi.12776 |
geographic |
Arctic Kara Sea |
geographic_facet |
Arctic Kara Sea |
genre |
Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
genre_facet |
Arctic marine mammals Arctic Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
op_source |
Diversity and Distributions volume 24, issue 10, page 1381-1394 ISSN 1366-9516 1472-4642 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1111/ddi.12776 |
container_title |
Diversity and Distributions |
container_volume |
24 |
container_issue |
10 |
container_start_page |
1381 |
op_container_end_page |
1394 |
_version_ |
1800744217851461632 |