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Estimating the Active Space of Male Koala Bellows: Propagation of Cues to Size and Identity in a Eucalyptus Forest

Overview of attention for article published in PLOS ONE, September 2012
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Title
Estimating the Active Space of Male Koala Bellows: Propagation of Cues to Size and Identity in a Eucalyptus Forest
Published in
PLOS ONE, September 2012
DOI 10.1371/journal.pone.0045420
Pubmed ID
Authors

Benjamin D. Charlton, David Reby, William A. H. Ellis, Jacqui Brumm, W. Tecumseh Fitch

Abstract

Examining how increasing distance affects the information content of vocal signals is fundamental for determining the active space of a given species' vocal communication system. In the current study we played back male koala bellows in a Eucalyptus forest to determine the extent that individual classification of male koala bellows becomes less accurate over distance, and also to quantify how individually distinctive acoustic features of bellows and size-related information degrade over distance. Our results show that the formant frequencies of bellows derived from Linear Predictive Coding can be used to classify calls to male koalas over distances of 1-50 m. Further analysis revealed that the upper formant frequencies and formant frequency spacing were the most stable acoustic features of male bellows as they propagated through the Eucalyptus canopy. Taken together these findings suggest that koalas could recognise known individuals at distances of up to 50 m and indicate that they should attend to variation in the upper formant frequencies and formant frequency spacing when assessing the identity of callers. Furthermore, since the formant frequency spacing is also a cue to male body size in this species and its variation over distance remained very low compared to documented inter-individual variation, we suggest that male koalas would still be reliably classified as small, medium or large by receivers at distances of up to 150 m.

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Geographical breakdown

Country Count As %
United Kingdom 1 2%
Hungary 1 2%
Italy 1 2%
Austria 1 2%
Unknown 47 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 25%
Student > Ph. D. Student 10 20%
Student > Master 5 10%
Student > Doctoral Student 4 8%
Student > Postgraduate 4 8%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 47%
Environmental Science 11 22%
Business, Management and Accounting 2 4%
Engineering 2 4%
Psychology 1 2%
Other 1 2%
Unknown 10 20%