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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Main Authors: 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.
Other Authors: Oceanography
Format: Report
Language:unknown
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10945/68543
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spelling 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
institution Open Polar
collection Naval Postgraduate School: Calhoun
op_collection_id ftnavalpschool
language unknown
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.
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