Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean
Abstract Acoustic metrics (AM) assist our interpretation of acoustic environments by aggregating a complex signal into a unique number. Numerous AM have been developed for terrestrial ecosystems, with applications ranging from rapid biodiversity assessments to characterizing habitat quality. However...
Published in: | Remote Sensing in Ecology and Conservation |
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ftdoajarticles:oai:doaj.org/article:6b79802e771e47208a6858712ba6cbee 2023-05-15T13:32:03+02:00 Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean Irene T. Roca Ilse Van Opzeeland 2020-09-01T00:00:00Z https://doi.org/10.1002/rse2.129 https://doaj.org/article/6b79802e771e47208a6858712ba6cbee EN eng Wiley https://doi.org/10.1002/rse2.129 https://doaj.org/toc/2056-3485 2056-3485 doi:10.1002/rse2.129 https://doaj.org/article/6b79802e771e47208a6858712ba6cbee Remote Sensing in Ecology and Conservation, Vol 6, Iss 3, Pp 262-273 (2020) Acoustic metrics Antarctic community composition marine acoustic environments passive acoustic monitoring species diversity Technology T Ecology QH540-549.5 article 2020 ftdoajarticles https://doi.org/10.1002/rse2.129 2022-12-31T02:00:00Z Abstract Acoustic metrics (AM) assist our interpretation of acoustic environments by aggregating a complex signal into a unique number. Numerous AM have been developed for terrestrial ecosystems, with applications ranging from rapid biodiversity assessments to characterizing habitat quality. However, there has been comparatively little research aimed at understanding how these metrics perform to characterize the acoustic features of marine habitats and their relation with ecosystem biodiversity. Our objectives were to 1) assess whether AM are able to capture the spectral and temporal differences between two distinct Antarctic marine acoustic environment types (i.e., pelagic vs. on‐shelf), 2) evaluate the performance of a combination of AM compared to the signal full frequency spectrum to characterize marine mammals acoustic assemblages (i.e., species richness–SR–and species identity) and 3) estimate the contribution of SR to the local marine acoustic heterogeneity measured by single AM. We used 23 different AM to develop a supervised machine learning approach to discriminate between acoustic environments. AM performance was similar to the full spectrum, achieving correct classifications for SR levels of 58% and 92% for pelagic and on‐shelf sites respectively and > 88% for species identities. Our analyses show that a combination of AM is a promising approach to characterize marine acoustic communities. It allows an intuitive ecological interpretation of passive acoustic data, which in the light of ongoing environmental changes, supports the holistic approach needed to detect and understand trends in species diversity, acoustic communities and underwater habitat quality. Article in Journal/Newspaper Antarc* Antarctic Southern Ocean Directory of Open Access Journals: DOAJ Articles Antarctic Southern Ocean Remote Sensing in Ecology and Conservation 6 3 262 273 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Acoustic metrics Antarctic community composition marine acoustic environments passive acoustic monitoring species diversity Technology T Ecology QH540-549.5 |
spellingShingle |
Acoustic metrics Antarctic community composition marine acoustic environments passive acoustic monitoring species diversity Technology T Ecology QH540-549.5 Irene T. Roca Ilse Van Opzeeland Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
topic_facet |
Acoustic metrics Antarctic community composition marine acoustic environments passive acoustic monitoring species diversity Technology T Ecology QH540-549.5 |
description |
Abstract Acoustic metrics (AM) assist our interpretation of acoustic environments by aggregating a complex signal into a unique number. Numerous AM have been developed for terrestrial ecosystems, with applications ranging from rapid biodiversity assessments to characterizing habitat quality. However, there has been comparatively little research aimed at understanding how these metrics perform to characterize the acoustic features of marine habitats and their relation with ecosystem biodiversity. Our objectives were to 1) assess whether AM are able to capture the spectral and temporal differences between two distinct Antarctic marine acoustic environment types (i.e., pelagic vs. on‐shelf), 2) evaluate the performance of a combination of AM compared to the signal full frequency spectrum to characterize marine mammals acoustic assemblages (i.e., species richness–SR–and species identity) and 3) estimate the contribution of SR to the local marine acoustic heterogeneity measured by single AM. We used 23 different AM to develop a supervised machine learning approach to discriminate between acoustic environments. AM performance was similar to the full spectrum, achieving correct classifications for SR levels of 58% and 92% for pelagic and on‐shelf sites respectively and > 88% for species identities. Our analyses show that a combination of AM is a promising approach to characterize marine acoustic communities. It allows an intuitive ecological interpretation of passive acoustic data, which in the light of ongoing environmental changes, supports the holistic approach needed to detect and understand trends in species diversity, acoustic communities and underwater habitat quality. |
format |
Article in Journal/Newspaper |
author |
Irene T. Roca Ilse Van Opzeeland |
author_facet |
Irene T. Roca Ilse Van Opzeeland |
author_sort |
Irene T. Roca |
title |
Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
title_short |
Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
title_full |
Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
title_fullStr |
Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
title_full_unstemmed |
Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean |
title_sort |
using acoustic metrics to characterize underwater acoustic biodiversity in the southern ocean |
publisher |
Wiley |
publishDate |
2020 |
url |
https://doi.org/10.1002/rse2.129 https://doaj.org/article/6b79802e771e47208a6858712ba6cbee |
geographic |
Antarctic Southern Ocean |
geographic_facet |
Antarctic Southern Ocean |
genre |
Antarc* Antarctic Southern Ocean |
genre_facet |
Antarc* Antarctic Southern Ocean |
op_source |
Remote Sensing in Ecology and Conservation, Vol 6, Iss 3, Pp 262-273 (2020) |
op_relation |
https://doi.org/10.1002/rse2.129 https://doaj.org/toc/2056-3485 2056-3485 doi:10.1002/rse2.129 https://doaj.org/article/6b79802e771e47208a6858712ba6cbee |
op_doi |
https://doi.org/10.1002/rse2.129 |
container_title |
Remote Sensing in Ecology and Conservation |
container_volume |
6 |
container_issue |
3 |
container_start_page |
262 |
op_container_end_page |
273 |
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1766023774039179264 |