Automated acoustic monitoring is gaining momentum worldwide. Alberta is stepping up to the game by implementing automated recording unit (ARU) based monitoring programs. An improved command line tool is here to help in the process.
The Bioacoustic Unit of the Alberta Biodiversity Monitoring Institute (ABMI) and the Bayne lab at the University of Alberta collaborates on best practices for using acoustic technology. The amount of information collected each year by these organizations is measured in dozens of terabytes, and is steadily increasing. Efficient and secure storage for all these files is the most immediate challenge, but the next one is closing the gap between data collection and data processing.
Processing all the recordings from the field
requires significant computing resources.
The first step is converting the
wac files to
wav, so that a a wider
variety of software tools can be used to analyze the information in the files.
wac format is a proprietary file format developed by
a company that specializes in bioacoustics monitoring systems.
The fact that the acoustic units manufactured by Wildlife Acoustics
are widely used in Alberta might represent a vendor lock-in.
Luckily for us, the pressure on the company
(see here and here, thanks Luis J. Villanueva-Rivera)
led to the company releasing a command line tool under the GPL license
wav file conversion (see source code here, here, and here).
The story might have ended right there. But the
C code worked with
standard input and output. It took some time and help (thanks John) to figure out exactly
how one should use the command line tool. Here is the solution:
cat input_file.wac | ./wac2wavcmd > output_file.wav
Isn’t that ugly? One would expect something like:
./wac2wavcmd input_file.wac output_file.wav
The good news is that the modified version (also released under GPL license) does just that.
It has been tested on Linux, Mac OS X and Windows 10.
It also removes all the clutter the original program prints to the
terminal. The only difference is that the program is called
wac2wawcmd. See the description and source code on
(Note: the leading
./ can be omitted if the program is added to the path.)
We are one step closer to a truly cloud based bioacoustic platform!
It all started with this paper in Methods in Ecol. Evol. where we looked at detectability of many species. So we wanted to use life history traits to validate our results. But we had to cut the manuscript, and there was this leftover with some neat patterns, but without much focus. It took a few years, and the most positive peer-review experience ever, and the paper is now early view in Ecography. This post is a quick summary of the goodies stuffed inside the lhreg R package that makes the whole analysis reproducible, and provides some functions for similar PGLMM models.
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