Relation between beluga whale aggregations and sea temperature on climate change forecasts

Climate change has been shown to alter the spatial distribution of whales and other marine mammals. Fast changing ocean temperatures may also affect the spatial distribution of whales at a finer scale, namely within populations, including aggregation behaviour. Our ability to analyze the impact of c...

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Published in:Limnology and Oceanography
Main Authors: Rivas, Marga L., Guirado, Emilio, Ortega, Zaida
Format: Article in Journal/Newspaper
Language:unknown
Published: Frontiers Media SA 2024
Subjects:
Online Access:http://dx.doi.org/10.3389/fmars.2024.1359429
https://www.frontiersin.org/articles/10.3389/fmars.2024.1359429/full
id crfrontiers:10.3389/fmars.2024.1359429
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spelling crfrontiers:10.3389/fmars.2024.1359429 2024-03-31T07:51:09+00:00 Relation between beluga whale aggregations and sea temperature on climate change forecasts Rivas, Marga L. Guirado, Emilio Ortega, Zaida 2024 http://dx.doi.org/10.3389/fmars.2024.1359429 https://www.frontiersin.org/articles/10.3389/fmars.2024.1359429/full unknown Frontiers Media SA https://creativecommons.org/licenses/by/4.0/ Frontiers in Marine Science volume 11 ISSN 2296-7745 Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography journal-article 2024 crfrontiers https://doi.org/10.3389/fmars.2024.1359429 2024-03-05T00:11:09Z Climate change has been shown to alter the spatial distribution of whales and other marine mammals. Fast changing ocean temperatures may also affect the spatial distribution of whales at a finer scale, namely within populations, including aggregation behaviour. Our ability to analyze the impact of climate change on whale aggregation behavior, however, has been limited by our ability to collect spatial observation data over large areas. To overcome this limitation, this study analyzed open-access satellite imagery obtained between 2007 and 2020 in Canada, Russia, and Alaska using Deep Convolutional Neural Networks (CNN) to detect 1,980 beluga whales in 11 populations and to quantify their aggregation patterns within their populations. Subsequently, we examined the relationship between sea surface temperature (SST) and the intra-population spatial patterns of beluga whales during summer seasons, when these whales normally aggregate. We detected a negative correlation between SST and the frequency of beluga whale aggregation, suggesting that warming temperatures may impact beluga whale spatio-behavioral dynamics. Considering that the relative abundance of beluga whales is declining and the future SST projections in these Arctic Ocean locations, climate change may pose yet another threat to beluga whales and other ice-dependent species. Article in Journal/Newspaper Arctic Arctic Ocean Beluga Beluga whale Beluga* Climate change Alaska Frontiers (Publisher) Arctic Arctic Ocean Canada Limnology and Oceanography 58 1 363 375
institution Open Polar
collection Frontiers (Publisher)
op_collection_id crfrontiers
language unknown
topic Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
spellingShingle Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
Rivas, Marga L.
Guirado, Emilio
Ortega, Zaida
Relation between beluga whale aggregations and sea temperature on climate change forecasts
topic_facet Ocean Engineering
Water Science and Technology
Aquatic Science
Global and Planetary Change
Oceanography
description Climate change has been shown to alter the spatial distribution of whales and other marine mammals. Fast changing ocean temperatures may also affect the spatial distribution of whales at a finer scale, namely within populations, including aggregation behaviour. Our ability to analyze the impact of climate change on whale aggregation behavior, however, has been limited by our ability to collect spatial observation data over large areas. To overcome this limitation, this study analyzed open-access satellite imagery obtained between 2007 and 2020 in Canada, Russia, and Alaska using Deep Convolutional Neural Networks (CNN) to detect 1,980 beluga whales in 11 populations and to quantify their aggregation patterns within their populations. Subsequently, we examined the relationship between sea surface temperature (SST) and the intra-population spatial patterns of beluga whales during summer seasons, when these whales normally aggregate. We detected a negative correlation between SST and the frequency of beluga whale aggregation, suggesting that warming temperatures may impact beluga whale spatio-behavioral dynamics. Considering that the relative abundance of beluga whales is declining and the future SST projections in these Arctic Ocean locations, climate change may pose yet another threat to beluga whales and other ice-dependent species.
format Article in Journal/Newspaper
author Rivas, Marga L.
Guirado, Emilio
Ortega, Zaida
author_facet Rivas, Marga L.
Guirado, Emilio
Ortega, Zaida
author_sort Rivas, Marga L.
title Relation between beluga whale aggregations and sea temperature on climate change forecasts
title_short Relation between beluga whale aggregations and sea temperature on climate change forecasts
title_full Relation between beluga whale aggregations and sea temperature on climate change forecasts
title_fullStr Relation between beluga whale aggregations and sea temperature on climate change forecasts
title_full_unstemmed Relation between beluga whale aggregations and sea temperature on climate change forecasts
title_sort relation between beluga whale aggregations and sea temperature on climate change forecasts
publisher Frontiers Media SA
publishDate 2024
url http://dx.doi.org/10.3389/fmars.2024.1359429
https://www.frontiersin.org/articles/10.3389/fmars.2024.1359429/full
geographic Arctic
Arctic Ocean
Canada
geographic_facet Arctic
Arctic Ocean
Canada
genre Arctic
Arctic Ocean
Beluga
Beluga whale
Beluga*
Climate change
Alaska
genre_facet Arctic
Arctic Ocean
Beluga
Beluga whale
Beluga*
Climate change
Alaska
op_source Frontiers in Marine Science
volume 11
ISSN 2296-7745
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3389/fmars.2024.1359429
container_title Limnology and Oceanography
container_volume 58
container_issue 1
container_start_page 363
op_container_end_page 375
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