Abstract
Wind turbines intersect airspace used by both migratory birds and bats, yet most monitoring approaches rely on single sensing modalities that capture only part of this system. Here, we integrate synchronized three-dimensional (3-D) thermal videography, ultrasonic acoustic monitoring, and regional weather radar data to characterize wildlife activity at two inland wind turbines during fall migration in Iowa, USA. Across 38 nights in late summer and autumn of 2022, we recorded 12,047 3-D flight tracks within rotor-swept altitudes, 2,249 bat echolocation sequences, and cumulative radar-derived migration traffic of approximately 2.0 million birds/km. Thermal video detections were strongly correlated with radar-derived migration intensity but not with acoustic detections. This pattern is consistent with birds comprising the majority of thermal video detections during peak migration. Thousands of flight trajectories occurred within 30–150 m above ground level and within 200 m of turbine monopoles, demonstrating frequent use of altitudes associated with collision risk. Fine-scale trajectory analysis revealed strong avoidance of flight paths directed toward the rotor-swept zone (RSZ), with targets 3.6 times more likely to fly toward the RSZ when turbines were stationary than when producing power. Angular divergence from turbine bearing also increased with decreasing distance, with a steeper avoidance gradient near operating turbines, consistent with birds actively responding to cues associated with blade rotation. Our results demonstrate how a sensor-fusion framework improves inference about taxonomic composition, airspace use, and behavioral responses near wind turbines. The strong relationship between regional radar activity and turbine-level detections highlights the potential of publicly available radar data to support wind energy siting by identifying areas with lower migratory bird traffic without extensive on-site monitoring. Understanding the sensory basis of the avoidance behavior documented here could also inform the design of deterrent systems for infrastructure where bird collisions are a concern. Integrating complementary monitoring technologies provides a scalable approach for understanding wildlife–turbine interactions and guiding responsible wind energy development.