Project Title

Evaluating Bat Roost Abundance: A Comparison of Drone-Acquired Thermal Imagery and Acoustic Recordings with Visual Observers

Authors' Affiliations

Karah Jaffe, Department of Biological Sciences, East Tennessee State University, Johnson City, TN. Aaron Corcoran, Department of Biology, University of Colorado at Colorado Springs, CO. Richard Carter, Department of Biological Sciences, East Tennessee State University, Johnson City, TN. Gerardo Arceo-Gómez, Department of Biological Sciences, East Tennessee State University, Johnson City, TN.

Location

Culp Ballroom

Start Date

4-7-2022 9:00 AM

End Date

4-7-2022 12:00 PM

Poster Number

68

Faculty Sponsor’s Department

Biological Sciences

Name of Project's Faculty Sponsor

Richard Carter

Classification of First Author

Graduate Student-Master’s

Competition Type

Competitive

Type

Poster Presentation

Project's Category

Ecology

Abstract or Artist's Statement

Population trend analysis is an essential aspect of wildlife conservation and management. Bat roosts provide an opportunity to sample populations while gathered in high concentrations. Roost emergences have been historically surveyed by visual counts in real-time, either with the naked eye or through night-vision goggles. Comparing the efficacy and precision of historically accepted methods with novel methods can provide guidance on the use of new technologies in the field. This project aims to compare the precision of survey methodologies, i.e., drone-acquired thermal imagery, passive acoustic estimates, and visual counts, for counting bats during emergence events. We compared the variation of counts collected by the three methods between survey nights. The comparison result adheres to the rationale that precise methods will have less variation between nights and that less precise methods will have more variation. We conducted three simultaneous emergence count surveys for ten nights at two emergence sites. Surveys were temporally synchronized to compare counts. Visual count tallies were collected throughout the emergence with handheld counter app. Passive acoustic detectors were stationed at emergence entrances. The generated acoustic files were analyzed for root-mean-square (RMS) pressure and correlated to the emergence counts from the thermal video to estimate population density of emergence. A drone was equipped with a thermal camera and piloted 30m above ground level. Thermal video imagery was captured at nadir view throughout the emergence with landings to replace drone battery. Thermal imagery was manually counted and semi-automatic counted with ThruTracker (sonarjamming.com) software. Preliminary results show that thermal imagery and visual counts were not significantly different in measures of variation or average while acoustic estimates could not be established at low-density emergences.

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Apr 7th, 9:00 AM Apr 7th, 12:00 PM

Evaluating Bat Roost Abundance: A Comparison of Drone-Acquired Thermal Imagery and Acoustic Recordings with Visual Observers

Culp Ballroom

Population trend analysis is an essential aspect of wildlife conservation and management. Bat roosts provide an opportunity to sample populations while gathered in high concentrations. Roost emergences have been historically surveyed by visual counts in real-time, either with the naked eye or through night-vision goggles. Comparing the efficacy and precision of historically accepted methods with novel methods can provide guidance on the use of new technologies in the field. This project aims to compare the precision of survey methodologies, i.e., drone-acquired thermal imagery, passive acoustic estimates, and visual counts, for counting bats during emergence events. We compared the variation of counts collected by the three methods between survey nights. The comparison result adheres to the rationale that precise methods will have less variation between nights and that less precise methods will have more variation. We conducted three simultaneous emergence count surveys for ten nights at two emergence sites. Surveys were temporally synchronized to compare counts. Visual count tallies were collected throughout the emergence with handheld counter app. Passive acoustic detectors were stationed at emergence entrances. The generated acoustic files were analyzed for root-mean-square (RMS) pressure and correlated to the emergence counts from the thermal video to estimate population density of emergence. A drone was equipped with a thermal camera and piloted 30m above ground level. Thermal video imagery was captured at nadir view throughout the emergence with landings to replace drone battery. Thermal imagery was manually counted and semi-automatic counted with ThruTracker (sonarjamming.com) software. Preliminary results show that thermal imagery and visual counts were not significantly different in measures of variation or average while acoustic estimates could not be established at low-density emergences.