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Visualizing sound: counting wolves by using a spectral view of the chorus howling
Daniela Passilongo1, Luca Mattioli2, Elena Bassi1
1Department of Science for Nature and Environmental Resources, University of Sassari, via Muroni 25, I-07100 Sassari, Italy.
Introduction:
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. We tested and present a new bioacoustic approach to estimate chorus size by recording wolves' replies and visualising choruses through spectrograms and spectral envelopes. To test the methodology, we compared: a) the values detected by visual inspections with the true chorus size to test for accuracy; b) the bioacoustic estimations of a sample of free-ranging wolves' replies developed by different operators to test for precision of the method; c) the aural field estimation of chorus size of a sample of free-ranging wolves' replies with the sonogram analysis of the same recordings to test for difference between methods.
Results:
Visual inspection of the chorus by spectrogram and spectrum proved to be useful in determining the number of concurrent voices in a wolf chorus. Estimations of chorus size were highly correlated with the number of wolves counted in a pack, and 92 % of 29 known chorus sizes were recognized by means of bioacoustic analysis. On the basis of spectrographic evidence, it was also possible to identify up to seven concurrent vocalisations in a chorus of nine wolves. Spectral analysis of 37 free ranging wolves' replies showed a high correlation between the chorus size estimations of the different operators (92.8 %), but a low correlation with the aural estimation (59.2 %).
Conclusions:
Wolf howling monitoring technique could be improved by recording wolves' replies and by using bioacoustic tools such as spectrograms and spectral envelopes to determine the size of the wolf chorus. Compared with other monitoring techniques (i.e., genetic analysis), bioacoustic analysis requires widely available informatic tools (i.e., sound recording set of devices and sound analysis software) and a low budget. Information obtained by means of chorus analysis can also be combined with that provided by other techniques. Moreover, howls can be recorded and stored in audio file format with a good resolution (i.e. in "Wave" format), thus representing a useful tool for future listening and investigations, which can be countlessly employed without risks of time deterioration.
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