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Passilongo, D.; Mattioli, L.; Bassi, E.; Szabó, L.; Apollonio, M. |
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Title |
Visualizing sound: counting wolves by using a spectral view of the chorus howling |
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Journal Article |
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Year |
2015 |
Publication |
Frontiers in Zoology |
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Front. Zool. |
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12 |
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1 |
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22 |
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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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1742-9994 |
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Equine Behaviour @ team @ Passilongo2015 |
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6498 |
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Passilongo, D.; Buccianti, A.; Dessi-Fulgheri, F.; Gazzola, A.; Zaccaronii, M.; Apollonio, M. |
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Title |
The Acoustic Structure Of Wolf Howls In Some Eastern Tuscany (Central Italy) Free Ranging Packs |
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Journal Article |
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2010 |
Publication |
Bioacoustics |
Abbreviated Journal |
Bioacoustics |
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19 |
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3 |
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159-175 |
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Canis lupus, acoustic structure, mammal communication, sonogram, fundamental frequency. |
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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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Equine Behaviour @ team @ |
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6499 |
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Charif, R.A.; Waack, A.M.; Strickman, L.M. |
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Title |
Raven Pro 1.3 User's Manual |
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2008 |
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Cornell Laboratory of Ornithology |
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Ithaca, New York |
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Equine Behaviour @ team @ Charif2008 |
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6488 |
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Author |
Primack, R.B. |
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Title |
Essentials of conservation biology |
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2010 |
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Edition |
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Fifth |
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Equine Behaviour @ team @ Primack2010 |
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6444 |
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Title |
Wolves in Europe: status and perspectives |
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1993 |
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Munich Wildlife Society |
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Ettal, Germany |
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Equine Behaviour @ team @ ref8 |
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6449 |
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Author |
Boitani, L. |
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Title |
Patterns of homesites attendance in two Minnesota wolf packs |
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1982 |
Publication |
Wolves of the World: Perspectives of Behavior, Ecology and Conservation |
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Noyes, Park Ridge |
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New York |
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Harrington, F.H.; Paquet, P.C. |
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Equine Behaviour @ team @ Boitani1982 |
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6474 |
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Author |
Core Development Team, R. |
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Title |
R: a language and environment for statistical computing |
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2011 |
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R foundation for statistical computing |
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Vienna, Austria |
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Equine Behaviour @ team @ Core Development Team2011 |
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6489 |
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Title |
Animal Acoustic Communication: Sound Analysis and Research Methods |
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1998 |
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Springer |
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Berlin |
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Equine Behaviour @ team @ ref56 |
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6497 |
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Author |
Mech, L.D. |
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Title |
The Wolf: The Ecology and Behaviour of an Endangered Species |
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1970 |
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The Natural History Press, Garden City |
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New York |
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Equine Behaviour @ team @ Mech1970 |
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6480 |
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Author |
Pimlott, D.H. |
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Title |
The use of tape-recorded wolf howls to locate timber wolves |
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1960 |
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Twenty-second Midwest Wildlife Congress |
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Toronto |
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Call Number |
Equine Behaviour @ team @ Pimlott1960 |
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6454 |
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