A new study on DTBird, an advanced detection and deterrent system, reveals significant potential for reducing eagle collisions at wind farms. Conducted from 2017 to 2024, the research spanned two locations: the Manzana Wind Power Project in California and Goodnoe Hills Wind Farm in Washington. DTBird's automated system uses cameras to detect birds and deploys audio signals to deter them from dangerous areas around turbines.
Results indicate a 20-30% reduction in eagles entering high-risk zones, with a higher effectiveness rate (up to 40%) for eagles identified as having a moderate to high risk of collision. This promising data highlights DTBird’s potential in mitigating eagle fatalities, particularly for golden eagles, a species frequently impacted by wind energy infrastructure.
The DTBird system employs high-resolution cameras and speakers placed strategically on wind turbines. When the cameras detect an object resembling a bird within a pre-set distance, the system triggers warning sounds, escalating to stronger dissuasion signals if the bird approaches closer. During active deterrence periods, eagle presence near turbines dropped by 24-27% compared to control conditions without deterrent signals.
One of the key findings was the system’s improved detection accuracy, particularly for eagle-like targets within 80-160 meters of the turbine. However, initial deployments faced challenges with false positive detections from insects, turbine blades, and sky artifacts. Adjustments made in 2023 reduced false positives from 3.9 to 0.8 per turbine per day, enhancing the reliability of the technology.
The investment in DTBird technology involves initial costs of $18,000-$22,000 per unit, with additional expenses for installation and maintenance. While the system represents a substantial upfront investment, its effectiveness in reducing collision risk and subsequent potential legal liabilities under wildlife protection laws may offer significant long-term benefits for wind energy operators.
The study underscores the importance of site-specific considerations for future installations of DTBird systems. Performance was slightly better in California’s desert landscape compared to Washington’s grassland terrain. The research also pointed to potential improvements in camera resolution and AI algorithms to further enhance detection capabilities.
Overall, the findings support DTBird as a promising tool for balancing renewable energy goals with wildlife conservation, offering a scalable solution for protecting eagle populations while advancing sustainable wind energy projects.
