Predictable shorebird departure patterns from a staging site can inform collision risks and mitigation of wind energy developments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High‐quality staging sites are critical for long‐distance migratory shorebirds to rest and refuel but are under threat from human development, including expansion of wind energy projects. However, predicting migration timing and movements in relation to weather conditions at staging sites can increase our understanding and mitigate effects of wind turbine collisions. Here we assessed northward migration timing and orientation in relation to environmental conditions at an inland staging area in Saskatchewan, Canada, with active and proposed wind energy developments. The area is known to host ~25% of North America's Sanderling Calidris alba population and 16 other Arctic‐breeding migrant shorebird species. We quantified arrival and departure time of day in relation to weather using data from 140 of 237 Sanderlings radiotagged locally and at a southern staging site in the Gulf of Mexico with the Motus Wildlife Tracking System (April–June, 2015–2017). Although Sanderling arrival times were not related to time of day or weather, departures were more likely at sunset in winds blowing towards the northwest at intermediate speeds (<22 km/h). Departure flights were also primarily oriented north‐northwest in the direction of a proposed wind energy development site at a mean ground speed of 21.4 m/s. Based on published climb rates and flight speed data, we estimated that shorebirds needed between 2 and 14 km setback distance to clear maximum turbine heights of 165 m. Given that departure events were predictable in time and space, adaptive mitigation may be useful for planning wind energy developments while reducing risk for staging Arctic‐breeding shorebirds.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it