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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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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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Passilongo, D., Mattioli, L., Bassi, E., Szabó, L., & Apollonio, M. (2015). Visualizing sound: counting wolves by using a spectral view of the chorus howling. Front. Zool., 12(1), 22.
Abstract: Monitoring large carnivores is a central issue in conservation biology. The wolf (Canis lupus) is the most studied large carnivore in the world. After a massive decline and several local extinctions, mostly due to direct persecutions, wolves are now recolonizing many areas of their historical natural range. One of the main monitoring techniques is the howling survey, which is based on the wolves' tendency to use vocalisations to mark territory ownership in response to howls of unknown individuals. In most cases wolf howling sessions are useful for the localisation of the pack, but they provide only an aural estimation of the chorus size.
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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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Mladenoff, D. J., Sickley, T. A., & Wydeven, A. P. (1999). Predicting gray wolf landscape recolonization: logistic regression models vs. new field data. Ecol Appl, 9.
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Dickman AJ, Macdonald EA, Macdonald DW. A review of financial instruments to pay for predator conservation and encourage human-carnivore coexistence. Proc Natl Acad Sci. 2011;108:19836-6.
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Primack, R. B. (2010). Essentials of conservation biology. Fifth: Edition.
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Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C., Ritchie, E. G., & Hebblewhite, M. (2014). Status and ecological effects of the world's largest carnivores. Science, 343.
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Walpole, M. J., & Leader-Williams, N. (2002). Tourism and flagship species in conservation. Biodivers Conserv, 11.
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