Journal article
Applying network analysis to birdsong research
Animal Behaviour, Vol.154, pp.95-109
2019
Abstract
By studying animal vocalizations such as birdsong, our capacity to record and interpret acoustic data has opened many opportunities for objective studies of animal behaviour, song evolution, physiology and ecology. However, the analysis of such data sets is often complex, and can vary between research teams, study species and theoretical approach. We test the use of network analysis in categorical birdsong data sets, focusing on four main applications: (1) quantifying and describing patterns of song sharing between individuals and/or populations; (2) understanding factors driving, and the implications of, an individual's position within a song-sharing network; (3) analysing (song or syllable) transfer patterns; and (4) investigating how environmental factors influence song-sharing networks. This exercise provides an excellent example of the advantages of sharing methodologies across disciplines within behavioural ecology and will hopefully inform future studies focused on different aspects of song sharing and cultural evolution by providing new tools and techniques for analysis.
Details
- Title
- Applying network analysis to birdsong research
- Authors
- Dominique A Potvin (Author) - University of the Sunshine Coast - School of Science & EngineeringKasha Strickland (Author) - University of the Sunshine Coast - School of Science & EngineeringElizabeth A MacDougall-Shackleton (Author) - University of Western Ontario, CanadaJoel W G Slade (Author) - University of Western Ontario, CanadaCeline H Frere (Author) - University of the Sunshine Coast - School of Science & Engineering
- Publication details
- Animal Behaviour, Vol.154, pp.95-109
- Publisher
- Elsevier Ltd.
- Date published
- 2019
- DOI
- 10.1016/j.anbehav.2019.06.012
- ISSN
- 0003-3472; 0003-3472
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; GeneCology Research Centre - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99451497502621
- Output Type
- Journal article
Metrics
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Behavioral Sciences
- Zoology
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