Biogeographic characterization of blue whale song worldwide: Using song to identify populations

Blue whale songs provide a measure for characterising worldwide blue whale population structure. These songs are divided into nine regional types, which maintain a stable character. Five of the nine song types have been recorded over time spans greater than 30 years showing no significant change in...

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Main Authors: McDonald, Mark A, Mesnick, Sarah L, Hildebrand, John A
Format: Article in Journal/Newspaper
Language:English
Published: eScholarship, University of California 2006
Subjects:
Online Access:http://www.escholarship.org/uc/item/5r16c2mz
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spelling ftcdlib:qt5r16c2mz 2023-05-15T15:45:03+02:00 Biogeographic characterization of blue whale song worldwide: Using song to identify populations McDonald, Mark A Mesnick, Sarah L Hildebrand, John A 55 - 65 2006-01-01 application/pdf http://www.escholarship.org/uc/item/5r16c2mz english eng eScholarship, University of California qt5r16c2mz http://www.escholarship.org/uc/item/5r16c2mz public McDonald, Mark A; Mesnick, Sarah L; & Hildebrand, John A. (2006). Biogeographic characterization of blue whale song worldwide: Using song to identify populations. Journal of Cetacean Research and Management, 8(1), 55 - 65. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/5r16c2mz Blue Whale Population Biogeography article 2006 ftcdlib 2016-04-02T18:34:08Z Blue whale songs provide a measure for characterising worldwide blue whale population structure. These songs are divided into nine regional types, which maintain a stable character. Five of the nine song types have been recorded over time spans greater than 30 years showing no significant change in character. The nine song types can be divided into those containing only simple tonal components (high latitude North Pacific, North Atlantic and Southern Ocean song types), those comprised of complex pulsed units in addition to the tonal components (Pacific Ocean margin song types from California, Chile and New Zealand), and those which have the greatest complexity of all and the longest cycling times (Indian Ocean song types from Sri Lanka, Fremantle and Diego Garcia). We suggest that temporally stable differences in song provide another characteristic for comparison with genetic and morphological data when defining blue whale populations. Furthermore, as Mellinger and Barlow (2003) recommend, when there is a lack of other data or lack of clarity in other data sets, evidence of distinct differences in songs between areas should be used as a provisional hypothesis about population structure when making management decisions. Worldwide study is needed to better understand the various populations and subspecies within species like the blue whale that have large geographic distributions and have both migrating and resident populations. Article in Journal/Newspaper Blue whale North Atlantic Southern Ocean University of California: eScholarship Barlow ENVELOPE(-62.483,-62.483,-62.967,-62.967) Indian New Zealand Pacific Southern Ocean
institution Open Polar
collection University of California: eScholarship
op_collection_id ftcdlib
language English
topic Blue Whale
Population
Biogeography
spellingShingle Blue Whale
Population
Biogeography
McDonald, Mark A
Mesnick, Sarah L
Hildebrand, John A
Biogeographic characterization of blue whale song worldwide: Using song to identify populations
topic_facet Blue Whale
Population
Biogeography
description Blue whale songs provide a measure for characterising worldwide blue whale population structure. These songs are divided into nine regional types, which maintain a stable character. Five of the nine song types have been recorded over time spans greater than 30 years showing no significant change in character. The nine song types can be divided into those containing only simple tonal components (high latitude North Pacific, North Atlantic and Southern Ocean song types), those comprised of complex pulsed units in addition to the tonal components (Pacific Ocean margin song types from California, Chile and New Zealand), and those which have the greatest complexity of all and the longest cycling times (Indian Ocean song types from Sri Lanka, Fremantle and Diego Garcia). We suggest that temporally stable differences in song provide another characteristic for comparison with genetic and morphological data when defining blue whale populations. Furthermore, as Mellinger and Barlow (2003) recommend, when there is a lack of other data or lack of clarity in other data sets, evidence of distinct differences in songs between areas should be used as a provisional hypothesis about population structure when making management decisions. Worldwide study is needed to better understand the various populations and subspecies within species like the blue whale that have large geographic distributions and have both migrating and resident populations.
format Article in Journal/Newspaper
author McDonald, Mark A
Mesnick, Sarah L
Hildebrand, John A
author_facet McDonald, Mark A
Mesnick, Sarah L
Hildebrand, John A
author_sort McDonald, Mark A
title Biogeographic characterization of blue whale song worldwide: Using song to identify populations
title_short Biogeographic characterization of blue whale song worldwide: Using song to identify populations
title_full Biogeographic characterization of blue whale song worldwide: Using song to identify populations
title_fullStr Biogeographic characterization of blue whale song worldwide: Using song to identify populations
title_full_unstemmed Biogeographic characterization of blue whale song worldwide: Using song to identify populations
title_sort biogeographic characterization of blue whale song worldwide: using song to identify populations
publisher eScholarship, University of California
publishDate 2006
url http://www.escholarship.org/uc/item/5r16c2mz
op_coverage 55 - 65
long_lat ENVELOPE(-62.483,-62.483,-62.967,-62.967)
geographic Barlow
Indian
New Zealand
Pacific
Southern Ocean
geographic_facet Barlow
Indian
New Zealand
Pacific
Southern Ocean
genre Blue whale
North Atlantic
Southern Ocean
genre_facet Blue whale
North Atlantic
Southern Ocean
op_source McDonald, Mark A; Mesnick, Sarah L; & Hildebrand, John A. (2006). Biogeographic characterization of blue whale song worldwide: Using song to identify populations. Journal of Cetacean Research and Management, 8(1), 55 - 65. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/5r16c2mz
op_relation qt5r16c2mz
http://www.escholarship.org/uc/item/5r16c2mz
op_rights public
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