DOI: 10.6084/m9.figshare.3817146.v1
title: Data for "Acoustic degradation of bat contact calls" Chaverri & Carter

description: See Chaverri & Carter methods. Each row is a recording of a playback of a bat contact call recorded at a specific distance in a specific habitat type. For playbacks we used recordings of one contact call from each of 35 individual bats of four species: the common vampire bat (Desmodus rotundus, n = 9), the white-winged vampire bat (Diaemus youngi n = 10), Spix's disc-winged bat (Thyroptera tricolor, n = 10), and Thomas’s fruit-eating bat (Dermanura watsoni, n = 6). To record calls, we used an Avisoft CM16 microphone (frequency range 10–200 kHz, ±3dB frequency response 25-150kHz, Avisoft Bioacoustics, Berlin, Germany), an Avisoft UltraSoundGate 116 or 416 (16-bit resolution, 250 kHz sampling rate for phyllostomids, 384 kHz sampling rate for Thyroptera), and a PC laptop running Avisoft RECORDER. We recorded Desmodus and Diaemus individually in a small mesh cage within 10–30 cm of the microphone, Thyroptera at distances of 1-3 m within a large flight cage, and Dermanura underneath a tent-roost at a distance of 0.5-1 m. We conducted playbacks in the Golfito Wildlife Refuge and Barú Research Station, southwestern Costa Rica (mean annual temperatures of 24-28 °C and ca. 90% relative humidity) during the daytime (9 am-5 pm). To determine how signal degradation of bat social calls is affected by habitat, we performed playback sessions at each of five sites within secondary forests with high-density understory vegetation, five primary forest sites with low-density understory vegetation, and seven open area sites with no trees or shrubs within at least 5 m. In each playback session, we broadcast the 35 social calls four times with varying distances of 2, 4, 6 or 8 m between speaker and microphone. We mounted an Avisoft Ultrasonic Dynamic Speaker Vifa (frequency response curve at Avisoft.com) and an Avisoft CM16 microphone on tripods at 1.5 m above ground, pointing directly towards each other. In open and primary forest habitats there was always a clear line of sight between the microphone and speaker; in secondary forests this was not always the case, but we verified that both instruments were pointing directly towards each other. To digitize calls, we used an Avisoft UltraSoundGate player and recorder (216H and 116Hme, 16-bit resolution, 250 kHz sampling rate) connected to a laptop computer running Avisoft-RECORDER. Calls were always broadcast and received by the same speaker and microphone in all trials. We analyzed the recordings of calls that were played back using automated measurements in Avisoft SASLab Pro. To help match recorded calls to their original file, we used spectrogram cross-correlation in SASLab. After the automatic measurement procedure, we also manually inspected calls to determine if the start and end positions matched the signal’s waveform, and if signals were properly measured. We removed three measures of start frequency where Avisoft was actually measuring background noise. Of the 2380 recorded calls, 13 calls were not detected or analyzed by Avisoft, so we removed these observations from our statistical analysis, because it was not certain whether the missing call was due to degradation by habitat or technical problem. These included four Thyroptera calls in primary forest and nine calls from secondary forests (three Desmodus, one Dermanura, one Diaemus, and four Thyroptera calls). For each call recording, we extracted (FFT length 256, Frame size= 100%, FlatTop window) four signal measurements: call duration, peak frequency at the call start (“start frequency”), peak frequency of the call’s overall spectrum (“peak frequency”), and peak frequency at the call end (“end frequency”). We did not compare recordings of playbacks with the original files; we compared recordings of playbacks degraded over different distances. Recordings and analysis were either automated or blind to minimize observer bias.<br>