A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals
Foraging behaviour of marine predators inferred from the analysis of horizontal or vertical movements commonly lack quantitative information about foraging success. Several marine mammal species are known to perform dives where they passively drift in the water column, termed “drift” dives. The drif...
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ftpubmed:oai:pubmedcentral.nih.gov:6586652 2023-05-15T16:05:40+02:00 A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals Arce, Fernando Bestley, Sophie Hindell, Mark A. McMahon, Clive R. Wotherspoon, Simon 2019-06-20 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586652/ http://www.ncbi.nlm.nih.gov/pubmed/31222003 https://doi.org/10.1038/s41598-019-44970-1 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586652/ http://www.ncbi.nlm.nih.gov/pubmed/31222003 http://dx.doi.org/10.1038/s41598-019-44970-1 © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. CC-BY Article Text 2019 ftpubmed https://doi.org/10.1038/s41598-019-44970-1 2019-06-30T01:06:35Z Foraging behaviour of marine predators inferred from the analysis of horizontal or vertical movements commonly lack quantitative information about foraging success. Several marine mammal species are known to perform dives where they passively drift in the water column, termed “drift” dives. The drift rate is determined by the animal’s buoyancy, which can be used to make inference regarding body condition. Long term dive records retrieved via satellite uplink are often summarized before transmission. This loss of resolution hampers identification of drift dives. Here, we develop a flexible, hierarchically structured approach to identify drift dives and estimate the drift rate from the summarized time-depth profiles that are increasingly available to the global research community. Based on high-resolution dive data from southern elephant seals, we classify dives as drift/non-drift and apply a summarization algorithm. We then (i) automatically generate dive groups based on inflection point ordering using a ‘Reverse’ Broken-Stick Algorithm, (ii) develop a set of threshold criteria to apply across groups, ensuring non-drift dives are most efficiently rejected, and (iii) finally implement a custom Kalman filter to retain the remaining dives that are within the seals estimated drifting time series. Validation with independent data sets shows our method retains approximately 3% of all dives, of which 88% are true drift dives. The drift rate estimates are unbiased, with the upper 95% quantile of the mean squared error between the daily averaged summarized profiles using our method (SDDR) and the observed daily averaged drift rate (ODDR) being only 0.0015. The trend of the drifting time-series match expectations for capital breeders, showing the lowest body condition commencing foraging trips and a progressive improvement as they remain at sea. Our method offers sufficient resolution to track small changes in body condition at a fine temporal scale. This approach overcomes a long-term challenge for large existing and ... Text Elephant Seals Southern Elephant Seals PubMed Central (PMC) Scientific Reports 9 1 |
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Article Arce, Fernando Bestley, Sophie Hindell, Mark A. McMahon, Clive R. Wotherspoon, Simon A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
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description |
Foraging behaviour of marine predators inferred from the analysis of horizontal or vertical movements commonly lack quantitative information about foraging success. Several marine mammal species are known to perform dives where they passively drift in the water column, termed “drift” dives. The drift rate is determined by the animal’s buoyancy, which can be used to make inference regarding body condition. Long term dive records retrieved via satellite uplink are often summarized before transmission. This loss of resolution hampers identification of drift dives. Here, we develop a flexible, hierarchically structured approach to identify drift dives and estimate the drift rate from the summarized time-depth profiles that are increasingly available to the global research community. Based on high-resolution dive data from southern elephant seals, we classify dives as drift/non-drift and apply a summarization algorithm. We then (i) automatically generate dive groups based on inflection point ordering using a ‘Reverse’ Broken-Stick Algorithm, (ii) develop a set of threshold criteria to apply across groups, ensuring non-drift dives are most efficiently rejected, and (iii) finally implement a custom Kalman filter to retain the remaining dives that are within the seals estimated drifting time series. Validation with independent data sets shows our method retains approximately 3% of all dives, of which 88% are true drift dives. The drift rate estimates are unbiased, with the upper 95% quantile of the mean squared error between the daily averaged summarized profiles using our method (SDDR) and the observed daily averaged drift rate (ODDR) being only 0.0015. The trend of the drifting time-series match expectations for capital breeders, showing the lowest body condition commencing foraging trips and a progressive improvement as they remain at sea. Our method offers sufficient resolution to track small changes in body condition at a fine temporal scale. This approach overcomes a long-term challenge for large existing and ... |
format |
Text |
author |
Arce, Fernando Bestley, Sophie Hindell, Mark A. McMahon, Clive R. Wotherspoon, Simon |
author_facet |
Arce, Fernando Bestley, Sophie Hindell, Mark A. McMahon, Clive R. Wotherspoon, Simon |
author_sort |
Arce, Fernando |
title |
A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
title_short |
A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
title_full |
A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
title_fullStr |
A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
title_full_unstemmed |
A quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
title_sort |
quantitative, hierarchical approach for detecting drift dives and tracking buoyancy changes in southern elephant seals |
publisher |
Nature Publishing Group UK |
publishDate |
2019 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586652/ http://www.ncbi.nlm.nih.gov/pubmed/31222003 https://doi.org/10.1038/s41598-019-44970-1 |
genre |
Elephant Seals Southern Elephant Seals |
genre_facet |
Elephant Seals Southern Elephant Seals |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586652/ http://www.ncbi.nlm.nih.gov/pubmed/31222003 http://dx.doi.org/10.1038/s41598-019-44970-1 |
op_rights |
© The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
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CC-BY |
op_doi |
https://doi.org/10.1038/s41598-019-44970-1 |
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Scientific Reports |
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