Bioacoustic Detection of Wolves: Identifying Subspecies and Individuals by Howls

Hanne Lyngholm Larsen*, Cino Pertoldi, Niels Madsen, Ettore Randi, Astrid Vik Stronen, Holly Root-Gutteridge, Sussie Pagh


Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

4 Citationer (Scopus)
62 Downloads (Pure)


Wolves (Canis lupus) are generally monitored by visual observations, camera traps, and DNA traces. In this study, we evaluated acoustic monitoring of wolf howls as a method for monitoring wolves, which may permit detection of wolves across longer distances than that permitted by camera traps. We analyzed acoustic data of wolves’ howls collected from both wild and captive ones. The analysis focused on individual and subspecies recognition. Furthermore, we aimed to determine the usefulness of acoustic monitoring in the field given the limited data for Eurasian wolves. We analyzed 170 howls from 16 individual wolves from 3 subspecies: Arctic (Canis lupus arctos), Eurasian (C. l. lupus), and Northwestern wolves (C. l. occidentalis). Variables from the fundamental frequency (f0) (lowest frequency band of a sound signal) were extracted and used in discriminant analysis, classification matrix, and pairwise post-hoc Hotelling test. The results indicated that Arctic and Eurasian wolves had subspecies identifiable calls, while Northwestern wolves did not, though this sample size was small. Identification on an individual level was successful for all subspecies. Individuals were correctly classified with 80%–100% accuracy, using discriminant function analysis. Our findings suggest acoustic monitoring could be a valuable and cost-effective tool that complements camera traps, by improving long-distance detection of wolves.

Udgave nummer5
StatusUdgivet - 1 mar. 2022

Bibliografisk note

Funding Information:
Funding: The study was supported by the Aalborg Zoo Conservation Foundation (AZCF; grant numbers: 2020-3, 2021-7).

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


Dyk ned i forskningsemnerne om 'Bioacoustic Detection of Wolves: Identifying Subspecies and Individuals by Howls'. Sammen danner de et unikt fingeraftryk.