Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology.
Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data s...
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ftcdlib:oai:escholarship.org:ark:/13030/qt5q9460x7 2023-05-15T14:50:57+02:00 Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. Oliver, Ruth Y Ellis, Daniel PW Chmura, Helen E Krause, Jesse S Pérez, Jonathan H Sweet, Shannan K Gough, Laura Wingfield, John C Boelman, Natalie T eaaq1084 2018-06-01 application/pdf https://escholarship.org/uc/item/5q9460x7 unknown eScholarship, University of California qt5q9460x7 https://escholarship.org/uc/item/5q9460x7 public Science advances, vol 4, iss 6 Animals Wild Songbirds Breeding Vocalization Animal Animal Migration Environment Seasons Population Dynamics Arctic Regions Climate Change Climate Action article 2018 ftcdlib 2022-07-25T17:30:52Z Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data sets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. We devised automated signal processing and machine learning approaches to estimate dates on which songbird communities arrived at arctic breeding grounds. Acoustically estimated dates agreed well with those determined via traditional surveys and were strongly related to the landscape's snow-free dates. We found that environmental conditions heavily influenced daily variation in songbird vocal activity, especially before egg laying. Our novel approaches demonstrate that variation in avian migratory arrival can be detected autonomously. Large-scale deployment of this innovation in wildlife monitoring would enable the coverage necessary to assess and forecast changes in bird migration in the face of climate change. Article in Journal/Newspaper Arctic Climate change University of California: eScholarship Arctic |
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Open Polar |
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University of California: eScholarship |
op_collection_id |
ftcdlib |
language |
unknown |
topic |
Animals Wild Songbirds Breeding Vocalization Animal Animal Migration Environment Seasons Population Dynamics Arctic Regions Climate Change Climate Action |
spellingShingle |
Animals Wild Songbirds Breeding Vocalization Animal Animal Migration Environment Seasons Population Dynamics Arctic Regions Climate Change Climate Action Oliver, Ruth Y Ellis, Daniel PW Chmura, Helen E Krause, Jesse S Pérez, Jonathan H Sweet, Shannan K Gough, Laura Wingfield, John C Boelman, Natalie T Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
topic_facet |
Animals Wild Songbirds Breeding Vocalization Animal Animal Migration Environment Seasons Population Dynamics Arctic Regions Climate Change Climate Action |
description |
Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data sets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. We devised automated signal processing and machine learning approaches to estimate dates on which songbird communities arrived at arctic breeding grounds. Acoustically estimated dates agreed well with those determined via traditional surveys and were strongly related to the landscape's snow-free dates. We found that environmental conditions heavily influenced daily variation in songbird vocal activity, especially before egg laying. Our novel approaches demonstrate that variation in avian migratory arrival can be detected autonomously. Large-scale deployment of this innovation in wildlife monitoring would enable the coverage necessary to assess and forecast changes in bird migration in the face of climate change. |
format |
Article in Journal/Newspaper |
author |
Oliver, Ruth Y Ellis, Daniel PW Chmura, Helen E Krause, Jesse S Pérez, Jonathan H Sweet, Shannan K Gough, Laura Wingfield, John C Boelman, Natalie T |
author_facet |
Oliver, Ruth Y Ellis, Daniel PW Chmura, Helen E Krause, Jesse S Pérez, Jonathan H Sweet, Shannan K Gough, Laura Wingfield, John C Boelman, Natalie T |
author_sort |
Oliver, Ruth Y |
title |
Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
title_short |
Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
title_full |
Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
title_fullStr |
Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
title_full_unstemmed |
Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology. |
title_sort |
eavesdropping on the arctic: automated bioacoustics reveal dynamics in songbird breeding phenology. |
publisher |
eScholarship, University of California |
publishDate |
2018 |
url |
https://escholarship.org/uc/item/5q9460x7 |
op_coverage |
eaaq1084 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_source |
Science advances, vol 4, iss 6 |
op_relation |
qt5q9460x7 https://escholarship.org/uc/item/5q9460x7 |
op_rights |
public |
_version_ |
1766322005685043200 |