Animal-borne metrics enable acoustic detection of blue whale migration
Supplemental Information can be found online at https://doi.org/10.1016/j.cub.2020.08.105. The article of record as published may be located at http://dx.doi.org/10.1016/j.cub.2020.08.105 Linking individual and population scales is fundamental to many concepts in ecology [1], including migration [2,...
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ftnavalpschool:oai:calhoun.nps.edu:10945/68543 2024-06-09T07:44:56+00:00 Animal-borne metrics enable acoustic detection of blue whale migration Oestreich, William K. Fahlbusch, James A. Cade, David E. Calambokidis, John Margolina, Tetyana Joseph, John Friedlaender, Ari S. McKenna, Megan F. Stimpert, Alison K. Southall, Brandon L. Goldbogen, Jeremy A. Ryan, John P. Oceanography 2020-12-07 11 p. application/pdf https://hdl.handle.net/10945/68543 unknown Oestreich, William K., et al. "Animal-borne metrics enable acoustic detection of blue whale migration." Current Biology 30.23 (2020): 4773-4779. https://hdl.handle.net/10945/68543 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Report 2020 ftnavalpschool 2024-05-15T00:40:54Z Supplemental Information can be found online at https://doi.org/10.1016/j.cub.2020.08.105. The article of record as published may be located at http://dx.doi.org/10.1016/j.cub.2020.08.105 Linking individual and population scales is fundamental to many concepts in ecology [1], including migration [2, 3]. This behavior is a critical [4] yet increasingly threatened [5] part of the life history of diverse organisms. Research on migratory behavior is constrained by observational scale [2], limiting ecological understanding and precise management of migratory populations in expansive, inaccessible marine ecosystems [6]. This knowledge gap is magnified for dispersed oceanic predators such as endangered blue whales (Balaenoptera musculus). As capital breeders, blue whales migrate vast distances annually between foraging and breeding grounds, and their population fitness depends on synchrony of migration with phenology of prey populations [7, 8]. Despite previous studies of individual-level blue whale vocal behavior via bio-logging [9, 10] and population-level acoustic presence via passive acoustic monitoring [11], detection of the life history transition from foraging to migration remains challenging. Here, we integrate direct high-resolution measures of individual behavior and continuous broad-scale acoustic monitoring of regional song production (Figure 1A) to identify an acoustic signature of the transition from foraging to migration in the Northeast Pacific population. We find that foraging blue whales sing primarily at night, whereas migratory whales sing primarily during the day. The ability to acoustically detect population-level transitions in behavior provides a tool to more comprehensively study the life history, fitness, and plasticity of population behavior in a dispersed, capital breeding population. Real-time detection of this behavioral signal can also inform dynamic management efforts [12] to mitigate anthropogenic threats to this endangered population [13, 14]). W.K.O. is supported by the National ... Report Balaenoptera musculus Blue whale Naval Postgraduate School: Calhoun Pacific |
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Naval Postgraduate School: Calhoun |
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description |
Supplemental Information can be found online at https://doi.org/10.1016/j.cub.2020.08.105. The article of record as published may be located at http://dx.doi.org/10.1016/j.cub.2020.08.105 Linking individual and population scales is fundamental to many concepts in ecology [1], including migration [2, 3]. This behavior is a critical [4] yet increasingly threatened [5] part of the life history of diverse organisms. Research on migratory behavior is constrained by observational scale [2], limiting ecological understanding and precise management of migratory populations in expansive, inaccessible marine ecosystems [6]. This knowledge gap is magnified for dispersed oceanic predators such as endangered blue whales (Balaenoptera musculus). As capital breeders, blue whales migrate vast distances annually between foraging and breeding grounds, and their population fitness depends on synchrony of migration with phenology of prey populations [7, 8]. Despite previous studies of individual-level blue whale vocal behavior via bio-logging [9, 10] and population-level acoustic presence via passive acoustic monitoring [11], detection of the life history transition from foraging to migration remains challenging. Here, we integrate direct high-resolution measures of individual behavior and continuous broad-scale acoustic monitoring of regional song production (Figure 1A) to identify an acoustic signature of the transition from foraging to migration in the Northeast Pacific population. We find that foraging blue whales sing primarily at night, whereas migratory whales sing primarily during the day. The ability to acoustically detect population-level transitions in behavior provides a tool to more comprehensively study the life history, fitness, and plasticity of population behavior in a dispersed, capital breeding population. Real-time detection of this behavioral signal can also inform dynamic management efforts [12] to mitigate anthropogenic threats to this endangered population [13, 14]). W.K.O. is supported by the National ... |
author2 |
Oceanography |
format |
Report |
author |
Oestreich, William K. Fahlbusch, James A. Cade, David E. Calambokidis, John Margolina, Tetyana Joseph, John Friedlaender, Ari S. McKenna, Megan F. Stimpert, Alison K. Southall, Brandon L. Goldbogen, Jeremy A. Ryan, John P. |
spellingShingle |
Oestreich, William K. Fahlbusch, James A. Cade, David E. Calambokidis, John Margolina, Tetyana Joseph, John Friedlaender, Ari S. McKenna, Megan F. Stimpert, Alison K. Southall, Brandon L. Goldbogen, Jeremy A. Ryan, John P. Animal-borne metrics enable acoustic detection of blue whale migration |
author_facet |
Oestreich, William K. Fahlbusch, James A. Cade, David E. Calambokidis, John Margolina, Tetyana Joseph, John Friedlaender, Ari S. McKenna, Megan F. Stimpert, Alison K. Southall, Brandon L. Goldbogen, Jeremy A. Ryan, John P. |
author_sort |
Oestreich, William K. |
title |
Animal-borne metrics enable acoustic detection of blue whale migration |
title_short |
Animal-borne metrics enable acoustic detection of blue whale migration |
title_full |
Animal-borne metrics enable acoustic detection of blue whale migration |
title_fullStr |
Animal-borne metrics enable acoustic detection of blue whale migration |
title_full_unstemmed |
Animal-borne metrics enable acoustic detection of blue whale migration |
title_sort |
animal-borne metrics enable acoustic detection of blue whale migration |
publishDate |
2020 |
url |
https://hdl.handle.net/10945/68543 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
Balaenoptera musculus Blue whale |
genre_facet |
Balaenoptera musculus Blue whale |
op_relation |
Oestreich, William K., et al. "Animal-borne metrics enable acoustic detection of blue whale migration." Current Biology 30.23 (2020): 4773-4779. https://hdl.handle.net/10945/68543 |
op_rights |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. |
_version_ |
1801373831557808128 |