buzzfindr: Automating the detection of feeding buzzes in bat echolocation recordings

Quantification of bat communities and habitat heavily rely on non-invasive acoustic bat surveys the scope of which has greatly amplified with advances in remote monitoring technologies. Despite the unprecedented amount of acoustic data being collected, analysis of these data is often limited to simple species classification which provides little information on habitat function. Feeding buzzes, the rapid sequences of echolocation pulses emitted by bats during the terminal phase of prey capture, have historically been used to evaluate foraging habitat quality. Automated identification of feeding buzzes in recordings could benefit conservation by helping identify critical foraging habitat. I tested if detection of feeding buzzes in recordings could be automated with bat recordings from Ontario, Canada. Data were obtained using three different recording devices. The signal detection method involved sequentially scanning narrow frequency bands with the “Bioacoustics” R package signal detecti..., I compiled data to train the feeding buzz classifier from recordings of bats made at five locations throughout Ontario, Canada, with three different recording devices over three years (see Table 1). Due to data sharing agreements, the precise locations of the recording sites cannot be provided. Recordings were from four bat species: Silver-haired Bat (Lasionycteris noctivagans), Big Brown Bat (Eptesicus fuscus), Hoary Bat (Lasiurus cinereus), and Little Brown Myotis (Myotis lucifugus). I compiled recordings of feeding buzzes and recordings without feeding buzzes by visually inspecting spectrograms of the recordings with program Audacity 2.4.2 (Boston, MA). Calls were selected irrespective of their signal-to-noise-ratio. I highlighted each observed feeding buzz from the approximate start of the buzz to just after the last perceived call in the buzz sequence and saved the highlighted sequence as a separate file. For recordings without buzzes, the entire file was used.
I tested two instanc..., , # buzzfindr: Automating the detection of feeding buzzes in bat echolocation recordings

Enclosed files consist of recordings used to train and test a classifier for automated detection of feeding buzzes in recordings of bat echolocation. The R script for developing and testing the classifier is also included. The associated manuscript is currently in revision phase.

## Description of the data and file structure

The following excerpt from the manuscript in progress described the recordings:

**Files for training the classifier-**
I compiled data to train the feeding buzz classifier from recordings of bats made at five locations throughout Ontario, Canada, with three different recording devices over three years (see Table 1). The three devices were the Song Meter SM2BAT+ coupled with a SMX-US microphone, the Song Meter SM4BAT-FS coupled with a SMM-U2 microphone, and the Song Meter Mini Bat with an integrated microphone, all manufactured by Wildlife Acoustics Inc. Recordings were made wi...