Semester of Graduation

Spring 2022


Master of Science (MS)


Renewable Natural Resources

Document Type



In the southeastern U.S., where forests are the primary land cover type and trees are often harvested for production purposes, understanding how forestry practices influence bat distributions is critical for bat conservation and management. It is also important for researchers to quantify and report variation in the performance of automated recordings units (ARUs) used to survey for bats because several key features of ARUs (e.g., microphone sensitivity, triggering thresholds) can influence an ARUs ability to detect bat calls. My goals were (1) to examine the influence of forest management practices on seasonal bat species occurrence and activity in central Louisiana, and (2) to compare the number of bat call files, echolocation pulses, and species recorded by two ultrasonic ARUs (i.e., AudioMoths and Song Meter SM4BAT-FS monitors) and identified using automated classification software (i.e., SonoBat). For (1), I deployed ARUs at sites representing five pine management treatments and bottomland hardwood forests to record bat calls. I also collected environmental data at the landscape and local scales. I detected Eptesicus fuscus, Lasiurus borealis/L. seminolus, Myotis species, Perimyotis subflavus, Tadarida brasiliensis, and Aeorestes cinereus during both seasons, and additionally detected Nycticeius humeralis during the breeding season. I found that activity was higher at group selection harvest, red-cockaded woodpecker, and clearcut treatments and that habitat use was different between periods for some species. I used ARU data that I collected at the study sites described above and at an urban greenspace in Baton Rouge to address (2). I found that SonoBat identified more call files to species, call files with high-frequency bat calls, echolocation pulses, and species from SM4BAT recordings compared to AudioMoth recordings, but that SonoBat identified a similar number of call files with low-frequency bat calls between monitors. My research identifies forest management practices and habitat characteristics that promote bat species diversity and activity. In addition, my research demonstrates that SM4BATs provide more comprehensive data that can be used with automated classification software than the version of AudioMoths I used, which has implications for survey results and comparability across studies.

Committee Chair

Long, Ashley M.