Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data

Following the end of over a century of intensive commercial whaling in 1986, the monitoring and assessment of sperm whale populations is essential for guiding management and conservation decisions for their recovery. Species distribution models (SDMs) are a useful tool for examining and predicting c...

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Published in:Frontiers in Remote Sensing
Main Authors: Yvonne M. Barkley, Taiki Sakai, Erin M. Oleson, Erik C. Franklin
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2022
Subjects:
Online Access:https://doi.org/10.3389/frsen.2022.940186
https://doaj.org/article/ab46434226e84809ae341b27cd53f9bc
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spelling ftdoajarticles:oai:doaj.org/article:ab46434226e84809ae341b27cd53f9bc 2023-05-15T18:26:26+02:00 Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data Yvonne M. Barkley Taiki Sakai Erin M. Oleson Erik C. Franklin 2022-10-01T00:00:00Z https://doi.org/10.3389/frsen.2022.940186 https://doaj.org/article/ab46434226e84809ae341b27cd53f9bc EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/frsen.2022.940186/full https://doaj.org/toc/2673-6187 2673-6187 doi:10.3389/frsen.2022.940186 https://doaj.org/article/ab46434226e84809ae341b27cd53f9bc Frontiers in Remote Sensing, Vol 3 (2022) sperm whales species distribution modeling passive acoustics Hawaiian Islands cetacean distribution Geophysics. Cosmic physics QC801-809 Meteorology. Climatology QC851-999 article 2022 ftdoajarticles https://doi.org/10.3389/frsen.2022.940186 2022-12-30T19:52:39Z Following the end of over a century of intensive commercial whaling in 1986, the monitoring and assessment of sperm whale populations is essential for guiding management and conservation decisions for their recovery. Species distribution models (SDMs) are a useful tool for examining and predicting cetacean distribution patterns and typically incorporate visual, ship-based observations. However, understanding sperm whale distribution and habitat use based solely on surface visual observations is challenging due to the significant amount of time sperm whales spend foraging at depth. For the endangered sperm whale population occurring in Hawaiian waters, we used visual and passive acoustic data collected during four annual NOAA marine mammal line-transect surveys and a suite of biologically relevant environmental variables to develop SDMs within a generalized additive modeling framework to study the distribution of sperm whale groups throughout the island chain. Additionally, the passive acoustic data allowed us to differentiate sperm whale groups as foraging or non-foraging based on their click types to account for differences in distribution and behavior within the archipelago. Foraging groups were predicted primarily in the northwestern region of the archipelago between Laysan Island and Pearl and Hermes Reef as well as north of Maui and Hawaiʻi in the main Hawaiian Islands. Non-foraging groups were predicted to be more uniformly distributed throughout the archipelago. Foraging whale models selected temperature at 584 m depth, surface chlorophyll, and location, while the only significant variables for non-foraging whale models included the standard deviation of sea surface height and location. Each variable provides insight into the oceanographic processes influencing prey abundance and, thus, sperm whale foraging behavior. This study furthers our understanding of the distribution patterns for the sperm whale population in Hawaiʻi and contributes methods for building SDMs with visual and passive acoustic data ... Article in Journal/Newspaper Sperm whale Directory of Open Access Journals: DOAJ Articles Frontiers in Remote Sensing 3
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic sperm whales
species distribution modeling
passive acoustics
Hawaiian Islands
cetacean distribution
Geophysics. Cosmic physics
QC801-809
Meteorology. Climatology
QC851-999
spellingShingle sperm whales
species distribution modeling
passive acoustics
Hawaiian Islands
cetacean distribution
Geophysics. Cosmic physics
QC801-809
Meteorology. Climatology
QC851-999
Yvonne M. Barkley
Taiki Sakai
Erin M. Oleson
Erik C. Franklin
Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
topic_facet sperm whales
species distribution modeling
passive acoustics
Hawaiian Islands
cetacean distribution
Geophysics. Cosmic physics
QC801-809
Meteorology. Climatology
QC851-999
description Following the end of over a century of intensive commercial whaling in 1986, the monitoring and assessment of sperm whale populations is essential for guiding management and conservation decisions for their recovery. Species distribution models (SDMs) are a useful tool for examining and predicting cetacean distribution patterns and typically incorporate visual, ship-based observations. However, understanding sperm whale distribution and habitat use based solely on surface visual observations is challenging due to the significant amount of time sperm whales spend foraging at depth. For the endangered sperm whale population occurring in Hawaiian waters, we used visual and passive acoustic data collected during four annual NOAA marine mammal line-transect surveys and a suite of biologically relevant environmental variables to develop SDMs within a generalized additive modeling framework to study the distribution of sperm whale groups throughout the island chain. Additionally, the passive acoustic data allowed us to differentiate sperm whale groups as foraging or non-foraging based on their click types to account for differences in distribution and behavior within the archipelago. Foraging groups were predicted primarily in the northwestern region of the archipelago between Laysan Island and Pearl and Hermes Reef as well as north of Maui and Hawaiʻi in the main Hawaiian Islands. Non-foraging groups were predicted to be more uniformly distributed throughout the archipelago. Foraging whale models selected temperature at 584 m depth, surface chlorophyll, and location, while the only significant variables for non-foraging whale models included the standard deviation of sea surface height and location. Each variable provides insight into the oceanographic processes influencing prey abundance and, thus, sperm whale foraging behavior. This study furthers our understanding of the distribution patterns for the sperm whale population in Hawaiʻi and contributes methods for building SDMs with visual and passive acoustic data ...
format Article in Journal/Newspaper
author Yvonne M. Barkley
Taiki Sakai
Erin M. Oleson
Erik C. Franklin
author_facet Yvonne M. Barkley
Taiki Sakai
Erin M. Oleson
Erik C. Franklin
author_sort Yvonne M. Barkley
title Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
title_short Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
title_full Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
title_fullStr Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
title_full_unstemmed Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data
title_sort examining distribution patterns of foraging and non-foraging sperm whales in hawaiian waters using visual and passive acoustic data
publisher Frontiers Media S.A.
publishDate 2022
url https://doi.org/10.3389/frsen.2022.940186
https://doaj.org/article/ab46434226e84809ae341b27cd53f9bc
genre Sperm whale
genre_facet Sperm whale
op_source Frontiers in Remote Sensing, Vol 3 (2022)
op_relation https://www.frontiersin.org/articles/10.3389/frsen.2022.940186/full
https://doaj.org/toc/2673-6187
2673-6187
doi:10.3389/frsen.2022.940186
https://doaj.org/article/ab46434226e84809ae341b27cd53f9bc
op_doi https://doi.org/10.3389/frsen.2022.940186
container_title Frontiers in Remote Sensing
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