Increased Flight Altitudes among Migrating Golden Eagles Suggest Turbine Avoidance at a Rocky Mountain Wind Installation
Bibliographic record
Abstract
Potential wind-energy development in the eastern Rocky Mountain foothills of British Columbia, Canada, raises concerns due to its overlap with a golden eagle (Aquila chrysaetos) migration corridor. The Dokie 1 Wind Energy Project is the first development in this area and stands as a model for other projects in the area because of regional consistency in topographic orientation and weather patterns. We visually tracked golden eagles over three fall migration seasons (2009-2011), one pre- and two post-construction, to document eagle flight behaviour in relation to a ridge-top wind energy development. We estimated three-dimensional positions of eagles in space as they migrated through our study site. Flight tracks were then incorporated into GIS to ascertain flight altitudes for eagles that flew over the ridge-top area (or turbine string). Individual flight paths were designated to a category of collision-risk based on flight altitude (e.g. flights within rotor-swept height; ≤150 m above ground) and wind speed (winds sufficient for the spinning of turbines; >6.8 km/h at ground level). Eagles were less likely to fly over the ridge-top area within rotor-swept height (risk zone) as wind speed increased, but were more likely to make such crosses under headwinds and tailwinds compared to western crosswinds. Most importantly, we observed a smaller proportion of flights within the risk zone at wind speeds sufficient for the spinning of turbines (higher-risk flights) during post-construction compared to pre-construction, suggesting that eagles showed detection and avoidance of turbines during migration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".