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Cited by 38Animal Vocal Communication and BehaviorWildlife Ecology and ConservationMarine animal studies overview

Disentangling canid howls across multiple species and subspecies: Structure in a complex communication channel

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Kershenbaum, Arik, Root-Gutteridge, Holly, Habib, Bilal, Koler-Matznick, Janice, Mitchell, Brian, Palacios, Vicente, Waller, Sara·2016·Behavioural Processes
DOI 10.1016/j.beproc.2016.01.006
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Abstract

Wolves, coyotes, and other canids are members of a diverse genus of top predators of considerable conservation and management interest. Canid howls are long-range communication signals, used both for territorial defence and group cohesion. Previous studies have shown that howls can encode individual and group identity. However, no comprehensive study has investigated the nature of variation in canid howls across the wide range of species. We analysed a database of over 2000 howls recorded from 13 different canid species and subspecies. We applied a quantitative similarity measure to compare the modulation pattern in howls from different populations, and then applied an unsupervised clustering algorithm to group the howls into natural units of distinct howl types. We found that different species and subspecies showed markedly different use of howl types, indicating that howl modulation is not arbitrary, but can be used to distinguish one population from another. We give an example of the conservation importance of these findings by comparing the howls of the critically endangered red wolves to those of sympatric coyotes Canis latrans, with whom red wolves may hybridise, potentially compromising reintroduced red wolf populations. We believe that quantitative cross-species comparisons such as these can provide important understanding of the nature and use of communication in socially cooperative species, as well as support conservation and management of wolf populations.

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  • Classification of calls from different species and subspecies is robust.

    “Classification of calls from different species and subspecies is robust (Fagerlund, 2007;Kershenbaum et al., 2016)”

    From Applications of machine learning in animal behaviour studies (2017) · cites this paper as Kershenbaum et al., 2016

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Authors
Kershenbaum, A., Root-Gutteridge, H., Habib, B., Koler-Matznick, J., Mitchell, B., Palacios, V., & Waller, S.
Affiliations
  • University of Cambridge (GB)
  • Wildlife Institute of India (IN)
  • University of Vermont (US)
  • Universitat de València (ES)
  • Montana State University (US)
Corresponding author
Kershenbaum, Arik
ORCID
Venue
Behavioural Processes
Publisher
Elsevier BV
Published
2016-03
Volume
124
Pages
149-157
ISSN
0376-6357 (ISSN-L)
DOI
10.1016/j.beproc.2016.01.006
OpenAlex
W2277041418
Cited by
38
References
83
Citations by year
2026: 1 · 2025: 5 · 2024: 3 · 2023: 5 · 2022: 4 · 2021: 6 · 2020: 1 · 2019: 1 · 2018: 4 · 2017: 5 · 2016: 2
FWCI
4.37
Type
journal article
Language
en
Open access
Licence
Locations
  • Behavioural Processes (acceptedVersion)
  • PubMed (publishedVersion)
  • Apollo (University of Cambridge) (acceptedVersion, cc-by-nc-nd)
  • Montana State University ScholarWorks (Montana State University) (submittedVersion, cc-by-nc-nd)
Funders
  • University of Tennessee
  • National Institute for Mathematical and Biological Synthesis
  • University of Cambridge
  • National Science Foundation (DBI-1300426)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Developmental Biology › Animal Vocal Communication and Behavior
  • Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
  • Physical Sciences › Environmental Science › Ecology › Marine animal studies overview
Keywords
vocal communication, red wolf, coyote, acoustic similarity, hybridization, wolf reintroduction, wolf conservation, territorial defense, group cohesion
MeSH terms
Acoustics, Animals, Behavior, Animal, Conservation of Natural Resources, Species Specificity, Vocalization, Animal, Wolves, Canidae, Coyotes

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