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Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. We used AudioMoth autonomous recorders to survey for the critically endangered Harlequin toad (Atelopus varius) in Panama. This sampling effort generated thousands of hours of audio recordings from stream-side transects. Atelopus varius has a distinctive call with fast amplitude modulation of about 120 pulses per second. We used the opens-source Repeat Interval-Based Bioacoustic Identification Tool (RIBBIT), which classifies anuran vocalizations in audio recordings based on their periodic structure, to detect A. varius vocalizations in the data. Here we provide 70 detected recordings of A. varius. These recordings represent a dramatic increase in the total number of openly available audio recordings of A. varius vocalizations.
These files were extracted from recordings taken by AudioMoth autonomous recording units in Panama in 2019. We used an automated detection method (the Repeat Interval-Based Bioacoustic Identification Tool, ie RIBBIT) to search for vocalizations of Atelopus varius in a large audio dataset. This dataset contains 70 60-second audio files which all contain vocalizations of Atelopus varius - all are from one stationary recorder during a three-day period, and possibly originate from a single individual frog. All 70 of these files were ranked by RIBBIT in the 72 top-scoring files out of several million inputs.
This dataset contains 70 audio files in .wav format, each 60 seconds long. The audio was recorded using AudioMoth acoustic recorders.
Signal processing, anuran, RIBBIT, vocalization, Panama, detection, call, autonomous recording units, Harlequin toad, Atelopus, frog, Atelopus varius, Vocalization, automated recognition, automated, FOS: Biological sciences, varius, Machine learning, ARU
Signal processing, anuran, RIBBIT, vocalization, Panama, detection, call, autonomous recording units, Harlequin toad, Atelopus, frog, Atelopus varius, Vocalization, automated recognition, automated, FOS: Biological sciences, varius, Machine learning, ARU
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