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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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Dugnol, B., Fernández, C., Galiano, G., & Velasco, J. (2007). Implementation of a diffusive differential reassignment method for signal enhancement: An application to wolf population counting. Appl Math Comput, 193.
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Dugnol, B., Fernández, C., & Galiano, G. (2007). Wolf population counting by spectrogram image processing. Appl Math Comput, 186.
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Fritts, S. H., Bangs, E. E., & Gore, J. F. (1994). The relationship of wolf recovery to habitat conservation and biodiversity in the northwestern United States. Landsc Urban Plan, 28.
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Iliopoulos, Y., Youlatos, D., & Sgardelis, S. (2013). Wolf pack rendezvous site selection in Greece is mainly affected by anthropogenic landscape features. Eur J Wildl Res, 60.
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Galaverni, M., Palumbo, D., Fabbri, E., Caniglia, R., Greco, C., & Randi, E. (2012). Monitoring wolves (Canis lupus) by non-invasive genetics and camera trapping: A small-scale pilot study. Eur J Wildl Res, 58.
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Nowak, S., Jedrzejewski, W., Schmidt, K., Theuerkauf, J., Myslajek, R. W., & Jedrzejewska, B. (2006). Howling activity of free-ranging wolves (Canis lupus) in the Bialowieza Primeval Forest and the Western Beskidy Mountains (Poland). J Ethol, 25.
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Passilongo, D., Marchetto, M., & Apollonio, M. (2017). Singing in a wolf chorus: structure and complexity of a multicomponent acoustic behaviour. Hysterix, 28(2), 180–185.
Abstract: Wolf choruses ( Canis lupus ) are complex, multicomponent signals, composed by a series of different vocalizations emitted by a pack. Although howls, the main component, have been highly studied, poor attention has been drawn upon the other vocalizations of the chorus. In this study, we investigate the structure of the chorus by means of the analysis and the quantification of the different components, taking advantage both of the digital sound recording and analysis, and of the modern statistical methodologies. We provide for the first time a detailed, objective description of the types of call emitted during the wolf howlings, combining spectrographic examinations, spectral analyses and automated classifications, with the aim to identify different types of call. Our results show that wolf choruses have a rich, complex structure, that reveals six other types of call, to be added to those howls already described in literature. Wolf choruses are typically composed by other three different types of calls: the bark, i.e. relatively long calls characterized by low frequencies and the presence of harsh components (deterministic chaos); the whimper, characterized by a harmonic structure and a very short duration; and the growl, a call with a noisy structure, low frequencies but relative long duration. Although further investigations are necessary to understand the meaning of the different calls, this research provides a basis for those studies that aim to compare wolves and other canids vocal behaviour.
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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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