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Fig. 9.12 Example of a
microphone array to collect
information on location of
vocalizing bats. Each node
is composed of four
microphones that create a
3D representation of the
sonic environment
(Reproduced with
permission from Blumstein
et al. 2011 )
Fig. 9.13 Example of sonic
distribution resulting from
the interpolation of the
acoustic complexity index
(ACI) from a 4
5 array of
microphones displaced at a
distance of 25 m to each
other in a dense
Mediterranean maqui (From
Farina and Pieretti,
Ecological Informatics
2014, in press)
The use of arrays of microphones allows many advantages such as knowing the
spatial disposition of the acoustic sources and the rate of interactions between a
sender and a respondent, but at the same time the great amount of data to be
processed requires powerful computation tools (for a review, see Blumstein
et al. 2011 ) (Fig. 9.12 ).
In particular, a set of spatially arranged microphones seems the most efficient
way to investigate the relationship between landscape patterns and the sonic
environment. In the literature there are not many examples of this technique (e.g.,
Pieretti and Farina, Ecological Informatics 2014, in press) that offer the possibility
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