Density estimation of nightjars using ARUs

Current PhD student in the group, Haley Holiman, is leading research on using ARUs to estimate density of birds, with a primary focus on eastern whip-poor-wills in managed forests. Forest management aimed at promoting oak and hickory regeneration is prevalent in the Central Hardwoods Region of the United States. Oak-hickory forests within the region provide vital habitat for wildlife while also serving as a valuable timber resource. Changes in forest disturbance regimes across the area, however, can result in poor oak recruitment with a subsequent compositional shift away from oak dominance. To address this issue, the Hardwoods Ecosystem Experiment (HEE) was initiated as a 100–year multi-disciplinary study to evaluate the impacts of forest management techniques, such as prescribed burns and selective harvests, on oak recruitment, timber production, and wildlife use across Indiana, USA. Eastern whip-poor-wills (Antrostomus vociferus) are a species of conservation concern in Indiana and throughout the continental U.S., yet the species’ response to silvicultural techniques remains relatively unexplored. Here we present preliminary results from a pilot study during May – July 2024 aimed at assessing: 1.) approaches for optimizing density estimation using passive acoustic monitoring (PAM) and 2.) investigating effects of forest management on nightjar abundance. Preliminary results suggest that PAM provides comparable estimates of nightjar density to traditional point counts (PC), and density estimates appear consistent across control, even-, and uneven-aged forest management plots. Future work will include expanding the study across the entire HEE, optimizing PAM sampling protocols for density estimation of nightjars, and relating management practices to nightjar abundance. Additionally, we will explore data integration techniques for density estimation with paired PAM and PC deployments. Ultimately, we will apply our density estimation protocol using acoustics to other species of concern in the region.

An overview of our density estimation workflow

Preliminary findings following our initial pilot study on the HEE