Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour

<jats:p>Context The ecology of cryptic animals is difficult to study without invasive tagging approaches or labour-intensive field surveys. Acoustic localisation provides an effective way to locate vocalising animals using acoustic recorders. Combining this with land cover classification gives...

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Main Authors: Bru, E, Smith, BR, Butkiewicz, H, Fontaine, AC, Dassow, A, Owens, JL, Root-Gutteridge, H, Schindler, L, Kershenbaum, A
Format: Article in Journal/Newspaper
Language:English
Published: CSIRO Publishing 2023
Subjects:
Online Access:https://www.repository.cam.ac.uk/handle/1810/346207
https://doi.org/10.17863/CAM.93627
id ftunivcam:oai:www.repository.cam.ac.uk:1810/346207
record_format openpolar
spelling ftunivcam:oai:www.repository.cam.ac.uk:1810/346207 2024-02-04T09:59:33+01:00 Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour Bru, E Smith, BR Butkiewicz, H Fontaine, AC Dassow, A Owens, JL Root-Gutteridge, H Schindler, L Kershenbaum, A 2023-02-06T16:50:45Z application/octet-stream https://www.repository.cam.ac.uk/handle/1810/346207 https://doi.org/10.17863/CAM.93627 eng eng CSIRO Publishing http://dx.doi.org/10.1071/wr22007 Wildlife Research https://www.repository.cam.ac.uk/handle/1810/346207 doi:10.17863/CAM.93627 All Rights Reserved http://www.rioxx.net/licenses/all-rights-reserved anthropogenic disturbance bioacoustics Canis latrans Canis lupus habitat selection howl multilateration passive acoustic monitoring remote sensing Article 2023 ftunivcam https://doi.org/10.17863/CAM.93627 2024-01-11T23:26:35Z <jats:p>Context The ecology of cryptic animals is difficult to study without invasive tagging approaches or labour-intensive field surveys. Acoustic localisation provides an effective way to locate vocalising animals using acoustic recorders. Combining this with land cover classification gives new insight into wild animal behaviour using non-invasive tools. Aims This study aims to demonstrate how acoustic localisation – combined with high-resolution land cover classification – permits the study of the ecology of vocalising animals in the wild. We illustrate this technique by investigating the effect of land cover and distances to anthropogenic features on coyote and wolf vocal behaviour. Methods We collected recordings over 13 days in Wisconsin, USA, and triangulated vocalising animals’ locations using acoustic localisation. We then mapped these locations onto land cover using a high-resolution land cover map we produced for the area. Key results Neither coyotes nor wolves vocalised more in one habitat type over another. Coyotes vocalised significantly closer to all human features than expected by chance, whereas wolves vocalised significantly further away. When vocalising closer to human features, coyotes selected forests but wolves showed no habitat preference. Conclusions This novel combination of two sophisticated, autonomous sensing-driven tools permits us to examine animal land use and behavioural ecology using passive sensors, with the aim of drawing ecologically important conclusions. Implications We envisage that this method can be used at larger scales to aid monitoring of vocally active animals across landscapes. Firstly, it permits us to characterise habitat use while vocalising, which is an essential behaviour for many species. Furthermore, if combined with additional knowledge of how a species’ habitat selection while vocalising relates to its general habitat use, this method could permit the derivation of future conclusions on prevailing landscape use. In summary, this study demonstrates the ... Article in Journal/Newspaper Canis lupus Apollo - University of Cambridge Repository
institution Open Polar
collection Apollo - University of Cambridge Repository
op_collection_id ftunivcam
language English
topic anthropogenic disturbance
bioacoustics
Canis latrans
Canis lupus
habitat selection
howl
multilateration
passive acoustic monitoring
remote sensing
spellingShingle anthropogenic disturbance
bioacoustics
Canis latrans
Canis lupus
habitat selection
howl
multilateration
passive acoustic monitoring
remote sensing
Bru, E
Smith, BR
Butkiewicz, H
Fontaine, AC
Dassow, A
Owens, JL
Root-Gutteridge, H
Schindler, L
Kershenbaum, A
Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
topic_facet anthropogenic disturbance
bioacoustics
Canis latrans
Canis lupus
habitat selection
howl
multilateration
passive acoustic monitoring
remote sensing
description <jats:p>Context The ecology of cryptic animals is difficult to study without invasive tagging approaches or labour-intensive field surveys. Acoustic localisation provides an effective way to locate vocalising animals using acoustic recorders. Combining this with land cover classification gives new insight into wild animal behaviour using non-invasive tools. Aims This study aims to demonstrate how acoustic localisation – combined with high-resolution land cover classification – permits the study of the ecology of vocalising animals in the wild. We illustrate this technique by investigating the effect of land cover and distances to anthropogenic features on coyote and wolf vocal behaviour. Methods We collected recordings over 13 days in Wisconsin, USA, and triangulated vocalising animals’ locations using acoustic localisation. We then mapped these locations onto land cover using a high-resolution land cover map we produced for the area. Key results Neither coyotes nor wolves vocalised more in one habitat type over another. Coyotes vocalised significantly closer to all human features than expected by chance, whereas wolves vocalised significantly further away. When vocalising closer to human features, coyotes selected forests but wolves showed no habitat preference. Conclusions This novel combination of two sophisticated, autonomous sensing-driven tools permits us to examine animal land use and behavioural ecology using passive sensors, with the aim of drawing ecologically important conclusions. Implications We envisage that this method can be used at larger scales to aid monitoring of vocally active animals across landscapes. Firstly, it permits us to characterise habitat use while vocalising, which is an essential behaviour for many species. Furthermore, if combined with additional knowledge of how a species’ habitat selection while vocalising relates to its general habitat use, this method could permit the derivation of future conclusions on prevailing landscape use. In summary, this study demonstrates the ...
format Article in Journal/Newspaper
author Bru, E
Smith, BR
Butkiewicz, H
Fontaine, AC
Dassow, A
Owens, JL
Root-Gutteridge, H
Schindler, L
Kershenbaum, A
author_facet Bru, E
Smith, BR
Butkiewicz, H
Fontaine, AC
Dassow, A
Owens, JL
Root-Gutteridge, H
Schindler, L
Kershenbaum, A
author_sort Bru, E
title Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
title_short Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
title_full Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
title_fullStr Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
title_full_unstemmed Combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
title_sort combining acoustic localisation and high-resolution land cover classification to study predator vocalisation behaviour
publisher CSIRO Publishing
publishDate 2023
url https://www.repository.cam.ac.uk/handle/1810/346207
https://doi.org/10.17863/CAM.93627
genre Canis lupus
genre_facet Canis lupus
op_relation https://www.repository.cam.ac.uk/handle/1810/346207
doi:10.17863/CAM.93627
op_rights All Rights Reserved
http://www.rioxx.net/licenses/all-rights-reserved
op_doi https://doi.org/10.17863/CAM.93627
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