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Application of tri-axial accelerometer data to the interpretation of movement and behaviour of threatened black cockatoos

Yeap, L.ORCID: 0000-0002-9419-5333, Warren, K.S.ORCID: 0000-0002-9328-2013, Bouten, W., Vaughan-Higgins, R.ORCID: 0000-0001-7609-9818, Jackson, B.ORCID: 0000-0002-8622-8035, Riley, K., Rycken, S. and Shephard, J.M. (2021) Application of tri-axial accelerometer data to the interpretation of movement and behaviour of threatened black cockatoos. Wildlife Research . Online Early.

Link to Published Version: https://doi.org/10.1071/WR20073
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Abstract

Context: Carnaby’s (Calyptorhychus latirostris), Baudin’s (Calyptorhynchus baudinii) and forest red-tailed black cockatoos (Calyptorhynchus banksii naso) are threatened parrot species endemic to south-western Australia. Behavioural monitoring has previously involved direct observation, which has proven challenging because of their cryptic nature, the type of habitat they move through and their speed of movement. The development of a model to accurately classify behaviour from tri-axial accelerometer data will provide greater insight into black cockatoo behaviour and ecology.

Aims: To develop an automated classifier model to classify accelerometer data from released black cockatoos to determine behaviour and activity budgets for three species of black cockatoo.

Methods: In the present study, we attached tri-axial accelerometers, housed in GPS tags, to four Carnaby’s cockatoos, three forest red-tailed black cockatoos and two Baudin’s cockatoos in captive care, undergoing rehabilitation for release back to the wild. Accelerometer data from these birds was coupled with 19 video files of the birds’ behaviour when flying, feeding and resting, to develop an automated behaviour classifier. The classifier was then used to annotate accelerometer data from 15 birds released after successful rehabilitation and to calculate activity budgets for these birds post-release.

Key results: We developed a classifier able to identify resting, flying and foraging behaviours from accelerometer data with 86% accuracy, as determined by the percentage of observed behaviours correctly identified by the classifier. The application of the classifier to accelerometer data from 15 released cockatoos enabled us to determine behaviours and activity budgets for all three species of black cockatoo. Black cockatoos spent most of their time at rest, followed by foraging with a short period of time flying.

Conclusions: Application of the classifier to data from released birds gives researchers the ability to remotely identify patterns of behaviour and calculate activity budgets.

Implications: Combining behaviour and activity budgets with location data provides useful insight into cockatoo movement, distribution, and habitat use. Such information is important for informing conservation efforts and addressing outstanding research objectives. Further studies including larger sample sizes of Baudin’s and forest red-tailed black cockatoos and comparing behaviour and activity between birds in breeding and non-breeding areas are warranted.

Item Type: Journal Article
Murdoch Affiliation(s): Veterinary Medicine
Harry Butler Institute
Publisher: CSIRO Publishing
Copyright: © CSIRO 2021
URI: http://researchrepository.murdoch.edu.au/id/eprint/61992
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