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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.14983 |
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| _version_ | 1866909913326813184 |
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| author | Snortland, Abigale Clerc, Jeff Hein, Cris Cotter, Emma |
| author_facet | Snortland, Abigale Clerc, Jeff Hein, Cris Cotter, Emma |
| contents | Quantifying the collision risk of birds and bats with offshore wind turbines requires an understanding of the drivers of flying animal behavior at offshore wind sites. An omnidirectional S-band radar system was deployed on a research barge on the Northeastern Shelf of the United States (40.9 deg N, 70.79 deg W) and collected data for a 5-week window during the 2024 autumn bird and bat migration. The barge also sup- ported two profiling lidar systems that measured the wind speed and direction. This study presents a first methodological approach for analyzing radar and lidar data together, providing a framework for future analyses of offshore bird and bat movements that can be used to improve collision risk models. Coupling the radar animal tracks with measured wind speed profiles revealed that wind is a driver of animal pres- ence, flight direction, flight height, and flight speed. Further, a hierarchical clustering methodology was developed to investigate behavior by approximate animal size. For example, smaller animals had con- centrated flight direction distributions aligned with the wind and flew at a variety of altitudes, whereas bigger animals flew in a wide variety of directions but were concentrated at low altitudes. Our results provide the first insights into animal behavior at offshore wind sites with paired radar and lidar data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14983 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Wind as Driver of Bird and Bat Abundance, Flight Direction, Altitude, and Speed on the North Atlantic Shelf Snortland, Abigale Clerc, Jeff Hein, Cris Cotter, Emma Biological Physics Quantifying the collision risk of birds and bats with offshore wind turbines requires an understanding of the drivers of flying animal behavior at offshore wind sites. An omnidirectional S-band radar system was deployed on a research barge on the Northeastern Shelf of the United States (40.9 deg N, 70.79 deg W) and collected data for a 5-week window during the 2024 autumn bird and bat migration. The barge also sup- ported two profiling lidar systems that measured the wind speed and direction. This study presents a first methodological approach for analyzing radar and lidar data together, providing a framework for future analyses of offshore bird and bat movements that can be used to improve collision risk models. Coupling the radar animal tracks with measured wind speed profiles revealed that wind is a driver of animal pres- ence, flight direction, flight height, and flight speed. Further, a hierarchical clustering methodology was developed to investigate behavior by approximate animal size. For example, smaller animals had con- centrated flight direction distributions aligned with the wind and flew at a variety of altitudes, whereas bigger animals flew in a wide variety of directions but were concentrated at low altitudes. Our results provide the first insights into animal behavior at offshore wind sites with paired radar and lidar data. |
| title | Wind as Driver of Bird and Bat Abundance, Flight Direction, Altitude, and Speed on the North Atlantic Shelf |
| topic | Biological Physics |
| url | https://arxiv.org/abs/2511.14983 |