| Records |
| Author |
Sueur, J.; Aubin, T.; Simonis, C. |
| Title |
Seewave: a free modular tool for sound analysis and synthesis |
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Journal Article |
| Year |
2008 |
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Bioacoustics |
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18 |
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Equine Behaviour @ team @ Sueur2008 |
Serial  |
6490 |
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| Author |
Marescot, L.; Pradel, R.; Duchamp, C.; Cubaynes, S.; Mrboutin, E.; Choquet, R. |
| Title |
Capture – recapture population growth rate as a robust tool against detection heterogeneity for population management |
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Journal Article |
| Year |
2011 |
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Ecol Appl |
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21 |
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Equine Behaviour @ team @ Marescot2011 |
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6491 |
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| Author |
Morgan, T.W.; Elliott, C.L. |
| Title |
Comparison of remotely-triggered cameras vs. howling surveys for estimating coyote (Canis latrans) Abundance in central Kentucky |
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Journal Article |
| Year |
2011 |
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J Ky Acad Science |
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72 |
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Equine Behaviour @ team @ Morgan2011 |
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6492 |
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VSO Downloader. Copyright VSO Software SARL. VSO-Software SARL Bat A, 1er Etage,109 Avenue de Lespinet, 31400 Toulouse |
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Equine Behaviour @ team @ ref52 |
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6493 |
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4Free Video Converter. 4 Free Studio. Copyright© 2000~2015 4Free Video Converter Inc. a Multimedia Utility Company |
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no |
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Equine Behaviour @ team @ ref53 |
Serial |
6494 |
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| Author |
Gazzola, A.; Avanzinelli, E.; Mauri, L.; Scandura, M.; Apollonio, M. |
| Title |
Temporal changes of howling in south European wolf packs |
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Journal Article |
| Year |
2002 |
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Ital J Zool |
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69 |
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no |
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Equine Behaviour @ team @ Gazzola2002 |
Serial |
6495 |
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| Author |
Boersma, P.; Weenink, D. |
| Title |
Praat: doing phonetics by computer |
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2009 |
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no |
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Equine Behaviour @ team @ Boersma2009 |
Serial |
6496 |
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| Title |
Animal Acoustic Communication: Sound Analysis and Research Methods |
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Book Whole |
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1998 |
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Springer |
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Berlin |
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no |
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Equine Behaviour @ team @ ref56 |
Serial |
6497 |
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Passilongo, D.; Mattioli, L.; Bassi, E.; Szabó, L.; Apollonio, M. |
| Title |
Visualizing sound: counting wolves by using a spectral view of the chorus howling |
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Journal Article |
| Year |
2015 |
Publication |
Frontiers in Zoology |
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Front. Zool. |
| Volume |
12 |
Issue |
1 |
Pages |
22 |
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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. |
| Title |
The Acoustic Structure Of Wolf Howls In Some Eastern Tuscany (Central Italy) Free Ranging Packs |
Type |
Journal Article |
| Year |
2010 |
Publication |
Bioacoustics |
Abbreviated Journal |
Bioacoustics |
| Volume |
19 |
Issue |
3 |
Pages |
159-175 |
| Keywords |
Canis lupus, acoustic structure, mammal communication, sonogram, fundamental frequency. |
| 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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Equine Behaviour @ team @ |
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6499 |
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