A Comparison of Bat Calls Recorded by Two Acoustic Monitors

Kunberger, Jane M.; Long, Ashley M.

doi:10.3996/jfwm-22-028

Cited by 4 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Audio recordings were acquired using an Audiomoth v.1.2.0 acoustic logger (Open Acoustics Devices, UK) designed for long-term monitoring of environmental sounds including ultrasonic vocalisations (Hill et al 2019 ; Kunberger et al 2023 ). The microphone was placed in a supporting bracket on the left side of each cage at the roof (Fig.…”

Section: Methodsmentioning

confidence: 99%

Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus)

Harding,

Walker,

Hackett

et al. 2024

J Comp Physiol B

View full text Add to dashboard Cite

Vocalisations are increasingly being recognised as an important aspect of normal rodent behaviour yet little is known of how they interact with other spontaneous behaviours such as sleep and torpor, particularly in a social setting. We obtained chronic recordings of the vocal behaviour of adult male and female Djungarian hamsters (Phodopus sungorus) housed under short photoperiod (8 h light, 16 h dark, square wave transitions), in different social contexts. The animals were kept in isolation or in same-sex sibling pairs, separated by a grid which allowed non-physical social interaction. On approximately 20% of days hamsters spontaneously entered torpor, a state of metabolic depression that coincides with the rest phase of many small mammal species in response to actual or predicted energy shortages. Animals produced ultrasonic vocalisations (USVs) with a peak frequency of 57 kHz in both social and asocial conditions and there was a high degree of variability in vocalisation rate between subjects. Vocalisation rate was correlated with locomotor activity across the 24-h light cycle, occurring more frequently during the dark period when the hamsters were more active and peaking around light transitions. Solitary-housed animals did not vocalise whilst torpid and animals remained in torpor despite overlapping with vocalisations in social-housing. Besides a minor decrease in peak USV frequency when isolated hamsters were re-paired with their siblings, changing social contexts did not influence vocalisation behaviour or structure. In rare instances, temporally overlapping USVs occurred when animals were socially-housed and were grouped in such a way that could indicate coordination. We did not observe broadband calls (BBCs) contemporaneous with USVs in this paradigm, corroborating their correlation with physical aggression which was absent from our experiment. Overall, we find little evidence to suggest a direct social function of hamster USVs. We conclude that understanding the effects of vocalisations on spontaneous behaviours, such as sleep and torpor, will inform experimental design of future studies, especially where the role of social interactions is investigated.

show abstract

Section: Methodsmentioning

confidence: 99%

Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus)

Harding,

Walker,

Hackett

et al. 2024

J Comp Physiol B

View full text Add to dashboard Cite

show abstract

Comparing field performance of ultrasonic microphones to facilitate analysis of long‐term acoustic bat monitoring data

Goodwin,

Kirschbaum,

Gillam

2024

Wildlife Society Bulletin

View full text Add to dashboard Cite

Passive acoustic monitoring is a standard technique for studying bat ecology and behavior. However, an issue that has received little attention is how to appropriately analyze data within a long‐term acoustic monitoring dataset when the equipment has been replaced and updated. Equipment changes are often inevitable, especially for microphones, which need to be replaced regularly due to extended weather exposure and associated reductions in recording quality. We compared 2 ultrasonic microphone models (Wildlife Acoustics SMM‐U1 and SMM‐U2) by deploying them side‐by‐side with the same acoustic detector unit. We tested 9 or 10 microphones per model in field deployments lasting an average of 9 nights. We compared triggering frequency, species classification, detection rates, and echolocation call parameters (as indicators of signal quality) from both microphones. The vast majority (97%) of our 25,949 paired recordings were captured simultaneously by both microphones. Yet, the SMM‐U2 outperformed the SMM‐U1 in terms of proportion of files classifiable to the species level (70% versus 61%), rate of bat detections per night (1–6.5 more detections per night depending on species), and recording quality. Based on our results, we propose a correction factor to facilitate direct comparison of datasets collected with these 2 different microphones. Our study will assist bat researchers in selecting appropriate equipment and accounting for potential biases in long‐term acoustic monitoring programs.

show abstract

Using mobile device built-in microphones to monitor bats: a new opportunity for large-scale participatory science initiatives

Gili,

Bertolino,

Rolando

2024

Biodivers Conserv

View full text Add to dashboard Cite

Citizen science has become a crucial tool in biodiversity monitoring, often facilitated by the diffusion of mobile devices, such as smartphones and tablets. High costs of professional equipment often limit large-scale monitoring, particularly in bat monitoring programmes based on acoustic surveys. Here we present the potential of using mobile devices for bat monitoring, allowing for large-scale, volunteer-based monitoring programmes. We initially compared mobile devices’ performance with a professional bat detector for recording low-frequency bat calls. We then conducted a citizen science pilot study to test the method’s feasibility in a real-world setting, recording echolocation and social calls of nine European bat species. We found high similarity in spectrogram quality (0.74 ± 0.09 for Samsung, 0.90 ± 0.01 for Huawei, 0.86 ± 0.09 for Xiaomi, 0.69 ± 0.09 for Apple) and average peak frequency (differences of 0.2 ± 0.5 kHz for Samsung, 0.1 ± 0.7 kHz for Huawei, 0.5 ± 1.0 kHz for Xiaomi, 0.1 ± 0.8 kHz for Apple) between calls recorded by mobile devices and professional bat detectors. The number of recorded bat calls per sampling session was also similar. However, differences in sound quality and effectiveness among mobile device brands were found. iOS devices outperformed professional detectors at recording bat calls at increasing distances. The citizen science pilot study tested 35 mobile device models, all of which effectively recorded bats. This study suggests that mobile devices could be an accessible, no-cost tool for large-scale bat monitoring. Incorporating mobile devices into existing monitoring networks or creating new dedicated programmes could not only enhance data collection, but also boost public knowledge and awareness about bats, ultimately promoting informed decision-making and better conservation strategies.

show abstract

A Comparison of Bat Calls Recorded by Two Acoustic Monitors

Cited by 4 publications

References 32 publications

Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus)

Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus)

Comparing field performance of ultrasonic microphones to facilitate analysis of long‐term acoustic bat monitoring data

Using mobile device built-in microphones to monitor bats: a new opportunity for large-scale participatory science initiatives

Contact Info

Product

Resources

About