Estimating Avian Populations with Passive Acoustic Technology and Song Behavior

The need for improvements in avian wildlife monitoring efficiency, accuracy, and scope has led to use of new technologies such as autonomous recording units (ARUs). As a monitoring tool, passive acoustic recording has numerous benefits, but it is still limited to use in human-accessible areas. There is also need for monitoring technologies in areas that are inaccessible. Military installations, which host a disproportionately large number of threatened, endangered, and at-risk species compared to other federal lands, pose the accessibility problem with sizeable impact areas that are too hazardous for humans to access. This thesis introduces the Balloon Aerial Recording System (BARS), a novel technology that fuses acoustic and aerial strategies to address the problem of ground-based land accessibility. The primary objectives of this thesis were to create models that could be used to predict male songbird abundance from song cue-count data and to establish and implement an analytical pathway for bird population estimation from acoustic data recorded with the BARS. ARUs were used to study the song rates/behaviors of Prairie Warbler (Setophaga discolor), Bachman’s Sparrow (Peucaea aestivalis), Field Sparrow (Spizella pusilla), Grasshopper Sparrow (Ammodramous savannarum), and Henslow’s Sparrow (Ammodramus henslowii) across 3 military installations. Point-count and line-transect field tests were implemented to directly compare BARS data with that of human-observer techniques in both real-bird communities and simulated-bird communities (with known populations). Both thesis objectives were met for each focal species except Grasshopper Sparrow. Based on negative binomial regression models, song activity was positively related to male abundance and was negatively related to either day of breeding season or time of day. Song activity was also influenced by temperature, wind speed, or atmospheric pressure for some species. The BARS analytical method successfully predicted densities of Prairie Warbler, Bachman’s Sparrow, and Henslow’s Sparrow. Field tests of the BARS with simulated-bird communities revealed that species-specific footprints of detection are needed to further improve density estimates. Through this study, the BARS system has been validated and shown to be useful for documenting presence/absence of rare species, relative abundance of more common species, and in some cases, actual estimation of densities.