Suter, S. M., Giordano, M., Nietlispach, S., Apollonio, M., & Passilongo, D. (2016). Non-invasive acoustic detection of wolves. Bioacoustics, .
Abstract: Monitoring wolves (Canis lupus) is a difficult and often expensive task due to high mobility,pack dynamic, shyness and nocturnal activity of this species. Wolves communicate acoustically trough howling, within pack and with packs of the neighbourhood. A wolf howl is a low frequency vocalization that can be transmitted over long distances and thus be used
for monitoring tasks. Animated howling survey is a current method to monitor wolves indifferent areas all over the world. Animated howling, however, may be invasive to residential wolf packs and could create possible negative reactions from local human population. Here we show that it is possible to detect wolves by recording spontaneous howling events. We measured the sound pressure level of wolf howls on captive individuals and we further found that simulated howling may be recorded and clearly identified up to a distance of 3 km. We finally conducted non-invasive acoustic detection of wolves in a free ranging population. The use of passive sound recorders may provide a powerful non-invasive tool for future wolf monitoring and thus help to established sustainable management plans for this species.
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Grönemann, K. (2015). Konfliktfeld Pferd und Wolf – Eine Untersuchung zu Einstellungen, Erwartungen und Befürchtungen von Pferdehaltern und Reitsportlern in Niedersachsen. Master's thesis, University Hildesheim, Hildesheim.
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Passilongo, D., Buccianti, A., Dessi-Fulgheri, F., Gazzola, A., Zaccaronii, M., & Apollonio, M. (2010). The Acoustic Structure Of Wolf Howls In Some Eastern Tuscany (Central Italy) Free Ranging Packs. Bioacoustics, 19(3), 159–175.
Abstract: Italian wolf howls are described for the first time from observations between 2003–2008 of a population living in eastern Tuscany, central Italy. A sample of 37 howls selected among single responses and 128 howls included in the choruses of 7 free ranging packs was recorded and analysed. The mean fundamental frequency of the howls ranged between 274–908 Hz. Two main structures recognised by means of multivariate explorative analysis, in particular Principal Component and Cluster Analysis, were ascribed to breaking and flat howls. Discriminant Function Analysis was applied to the recognised groups with the aim to find a general rule for classification. Howls with different features were correctly assigned to the groups obtained by explorative analysis in 95.8% of cases. The analysis of the variables characterising the structure of the howls suggests that maximum frequency and range of fundamental frequency are the most important parameters for classification, while duration does not appear to play any significant role.
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Apollonio, M., Mattioli, L., Scandura, M., Mauri, L., Gazzola, A., & Avanzinelli, E. (2004). Wolves in the Casentinesi Forests: insights for wolf conservation in Italy from a protected area with a rich wild prey community. Biol Conserv, 120.
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Berger, K. M. (2006). Carnivore-Livestock conflicts: effects of subsidized predator control and economic correlates on the sheep industry. Conserv Biol, 20.
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Blanco, J. C., & Yolanda, C. (2012). Surveying wolves without snow: a critical review of the methods used in Spain. Hystrix. Ital J Mammal, 23.
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Boersma, P., & Weenink, D. (2009). Praat: doing phonetics by computer.
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Boitani, L. (1982). Patterns of homesites attendance in two Minnesota wolf packs. In F. H. Harrington, & P. C. Paquet (Eds.), Wolves of the World: Perspectives of Behavior, Ecology and Conservation. New York: Noyes, Park Ridge.
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Breitenmoser, U. (1998). Large predators in the Alps: the fall and rise of man's competitors. Biol Conserv, 83.
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Burch, J. W., Layne, G. A., Follmann, E. H., & Rexstad, E. A. (2005). Evaluation of Wolf Density Estimation from Radiotelemetry Data. Wildl Soc Bull, 33.
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