Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distrib...
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ftdryad:oai:v1.datadryad.org:10255/dryad.178434 2023-05-15T14:24:36+02:00 Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals Mäkinen, Jussi Vanhatalo, Jarno The Arctic Ocean The Kara Sea 2018-06-21T13:38:20Z http://hdl.handle.net/10255/dryad.178434 https://doi.org/10.5061/dryad.22c867m unknown doi:10.5061/dryad.22c867m/1 doi:10.1111/ddi.12776 doi:10.5061/dryad.22c867m Mäkinen J, Vanhatalo J (2018) Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals. Diversity and Distributions 24(10): 1381-1394. http://hdl.handle.net/10255/dryad.178434 Arctic marine mammals data integration extensive transect survey hierarchical Bayesian modelling Poisson point process species distribution Article 2018 ftdryad https://doi.org/10.5061/dryad.22c867m https://doi.org/10.5061/dryad.22c867m/1 https://doi.org/10.1111/ddi.12776 2020-01-01T16:08:29Z Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distributions and to analyze 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 analyze 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 AMMs’ 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-yearlong 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 led to changes in AMMs’ distributions in the marginal Arctic region. Article in Journal/Newspaper Arctic Arctic marine mammals Arctic Arctic Ocean Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* Dryad Digital Repository (Duke University) Arctic Arctic Ocean Kara Sea |
institution |
Open Polar |
collection |
Dryad Digital Repository (Duke University) |
op_collection_id |
ftdryad |
language |
unknown |
topic |
Arctic marine mammals data integration extensive transect survey hierarchical Bayesian modelling Poisson point process species distribution |
spellingShingle |
Arctic marine mammals data integration extensive transect survey hierarchical Bayesian modelling Poisson point process species distribution Mäkinen, Jussi Vanhatalo, Jarno Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
topic_facet |
Arctic marine mammals data integration extensive transect survey hierarchical Bayesian modelling Poisson point process species distribution |
description |
Aim: Our aim involved developing a method to analyze spatiotemporal distributions of Arctic marine mammals (AMMs) using heterogeneous open source data, such as scientific papers and open repositories. Another aim was to quantitatively estimate the effects of environmental covariates on AMMs’ distributions and to analyze 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 analyze 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 AMMs’ 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-yearlong 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 led to changes in AMMs’ distributions in the marginal Arctic region. |
format |
Article in Journal/Newspaper |
author |
Mäkinen, Jussi Vanhatalo, Jarno |
author_facet |
Mäkinen, Jussi Vanhatalo, Jarno |
author_sort |
Mäkinen, Jussi |
title |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_short |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_fullStr |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_full_unstemmed |
Data from: Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals |
title_sort |
data from: hierarchical bayesian model reveals the distributional shifts of arctic marine mammals |
publishDate |
2018 |
url |
http://hdl.handle.net/10255/dryad.178434 https://doi.org/10.5061/dryad.22c867m |
op_coverage |
The Arctic Ocean The Kara Sea |
geographic |
Arctic Arctic Ocean Kara Sea |
geographic_facet |
Arctic Arctic Ocean Kara Sea |
genre |
Arctic Arctic marine mammals Arctic Arctic Ocean Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
genre_facet |
Arctic Arctic marine mammals Arctic Arctic Ocean Kara Sea Odobenus rosmarus Phoca hispida Ursus maritimus walrus* |
op_relation |
doi:10.5061/dryad.22c867m/1 doi:10.1111/ddi.12776 doi:10.5061/dryad.22c867m Mäkinen J, Vanhatalo J (2018) Hierarchical Bayesian model reveals the distributional shifts of Arctic marine mammals. Diversity and Distributions 24(10): 1381-1394. http://hdl.handle.net/10255/dryad.178434 |
op_doi |
https://doi.org/10.5061/dryad.22c867m https://doi.org/10.5061/dryad.22c867m/1 https://doi.org/10.1111/ddi.12776 |
_version_ |
1766297035003133952 |