DOI: 10.5061/dryad.9s4mw6mn3
title: Rana sierrae annotated aquatic soundscapes (2022)

description: This dataset is associated with the following manuscript, which contains
 details in the methodology of data collection and annotation: 
 Lapp, S., Smith, T. C., Wilhelm, A, Knapp, R., Kitzes, J. In press.
 Aquatic soundscape recordings reveal diverse vocalizations and nocturnal
 activity of an endangered frog. The American Naturalist. Rana sierrae (the
 Sierra Nevada yellow-legged frog) is an endangered species residing in
 high-elevation lakes in the Sierra Nevada mountains. The species is highly
 aquatic and, unlike most amphibians, primarily vocalizes while underwater.
 As a result, its vocalizations have rarely been recorded and its vocal
 repertoire is not well studied. This dataset contains an annotated set of
 underwater soundscape recordings
 containing 1236 annotations of R. sierrae vocalizations.
 We annotated five distinct vocalization types of R. sierrae, only two of
 which have been previously documented for this species. Besides the calls
 of R. sierrae, these audio recordings also contain stridulation sounds
 (not annotated), which were most likely produced by members of the family
 Corixidae or other aquatic invertebrates that stridulate
 underwater. 
description: The audio in this dataset is a set of 672 10-second audio files
 recorded at a spacing of 15 minutes over the course of 7 days on a single
 underwater audio recorder. The recorder, an AudioMoth version 1.2.0 in an
 underwater case, was deployed approximately 0.5 m from the shoreline, on
 the bottom of a lake in the Sierra Nevada in which R. sierrae breed and
 overwinter.  The annotations of the five call types
 correspond to the descriptions in the associated manuscript:
 A primary vocalization "meow" described in Vredenburg
 et al 2007 B stuttered vocalization, also described in
 Vredenburg et al 2007 C chuck, double/triple chuck
 calls D short downward single note E
 frequency-modulated call X: could not determine if
 sound is <em>R. sierrae</em> or not; these were excluded from
 training and validation of the CNN in the manuscript
 Files were annotated by Sam Lapp using Raven Pro with closed-back
 headphones while viewing spectrogram. Only calls that could both be heard
 and seen on spectrogram were annotated. This dataset also contains one-hot
 labels (0/1 per class per audio clip) for 2-second segments of audio. To
 generate these labels, we considered<em> R. sierrae
 </em>vocalizations to be present in a 2-second sample if any
 <em>R. sierrae</em> annotation overlapped with the sample by
 at least 0.2 seconds or if greater than 50% of an annotation box
 overlapped in time with the sample. A notebook in the associated GitHub
 repository demonstrates how the Raven annotations were converted
 to one-hot labels. Works Cited 
 Vredenburg VT, Bingham R, Knapp R,
 Morgan JAT, Moritz C, Wake D. 2007. Concordant molecular and phenotypic
 data delineate new taxonomy and conservation priorities for the endangered
 mountain yellow-legged frog. Journal of Zoology 271:361–374.
description: Audio files are provided in .mp3 format and are compatible with
 any program that supports this format. For instance, audio can be played
 and viewed as a spectrogram in the free Audacity software. Annotation
 files are provided in two formats: (1) Raven annotation
 tables, which can be opened along with audio files in Raven Lite (free) or Raven Pro (paid) software to view, create, and manipulate annotation boxes on spectrograms. Note that even without Raven Lite / Pro, the annotation files can be loaded, explored, and manipulated using the free and open-source python package OpenSoundscape. (2) A .csv file containing a table of 0/1 (present/absent, also known as "one-hot") labels for each call type for 2-second audio segments. This file can be opened with text or table editors, or loaded into Python using the pandas package.
description: # Rana sierrae annotated soundscape recordings Audio files and Raven
 annotations for Rana sierrae (Sierra Nevada Yellow-legged frog)
 vocalization types, from aquatic soundscape recordings. Name:
 rana\_sierrae\_2022 Version: 1.0 This dataset is associated with the
 following manuscript, which provides details on the methodology of data
 collection an annotation: Lapp, S., Smith, T. C., Wilhelm, A, Knapp, R.,
 Kitzes, J. In press. Aquatic soundscape recordings reveal diverse
 vocalizations and nocturnal activity of an endangered frog. The American
 Naturalist. ## Data and file structure This dataset contains audio files
 annotated in Raven Pro for Rana sierrae vocalization types. Frequency-time
 boxes were drawn around all sounds identifiable as vocalizations of Rana
 sierrae. Five vocalization types are annotated, and are described in the
 associated manuscript. In total, the dataset contains 1236 annotations of
 Rana sierrae vocalizations. Other sounds in the aquatic soundscape include
 stridulations most likely produced by members of the family Corixidae or
 other aquatic invertebrates. ### Audio: Audio files are provided in mp3
 format in the `mp3` subdirectory. The dataset contains 672 10-second
 files. These are the first 10 seconds of each audio file recorded during
 the week of June 20-26 2022 on one device (Device 3 in the associated
 paper; North corner of lake; this device had the highest activity level).
 The underwater AudioMoth 1.2.0 recorder in underwater case recorded 1
 minute starting every 15 minutes 24 hours per day, resulting in
 (24*4*7)=672 audio recordings. ### Annotations: Files were annotated by
 Sam Lapp using Raven Pro with closed-back headphones while viewing
 spectrogram. Only calls that could both be heard and seen on spectrogram
 were annotated. Multiple vocalizations were included in a single
 annotation box if they were separated by greater than 1 second of
 intervening time without vocalizations of the same type. Labels correspond
 to the associated manuscript: A primary vocalization B stuttered
 vocalization described in Vredenburg et al C chuck, double/triple chuck
 calls D short downward single note E frequency-modulated call X: could not
 determine if sound is R. sierrae or not; these are excluded from training
 and validation of the CNN ### Raven annotation files The subdirectory
 `raven_selection_tables` contains one Raven-formatted text file (tab
 separated values format) for each audio file. The file
 `audio_and_raven_files.csv` is a table that lists each audio file and the
 corresponding raven annotation file. The filename for each annotation file
 matches the corresponding audio file (for instance,
 sine2022a\_MSD-0558\_20220620\_000000\_0-10s.mp3 and
 sine2022a\_MSD-0558\_20220620\_000000\_0-10s.Table.1.selections.txt). ###
 One-hot labels This dataset also includes the file `(labels_2s.csv)`,
 which contains one-hot labels (0/1 per class per audio clip) for 2-second
 segments of audio. To generate these labels, we considered R. sierrae
 vocalizations to be present in a 2-second sample if any R. sierrae
 annotation overlapped with the sample by at least 0.2 seconds or if
 greater than 50% of an annotation box overlapped in time with the sample.
 A notebook in the associated [GitHub
 repository](https://github.com/kitzeslab/rana-sierrae-cnn) documents how
 the Raven annotations were converted to one-hot labels. ## Sharing/Access
 information This data is publicly available here. Associated scripts for
 data analysis are located in a [GitHub
 repository](https://github.com/kitzeslab/rana-sierrae-cnn). -Sam Lapp
 November 2023