Use of multiple modes of flight subsidy by a soaring terrestrial bird, the golden eagle<i>Aquila chrysaetos</i>, when on migration
Bibliographic record
Abstract
Large birds regularly use updrafts to subsidize flight. Although most research on soaring bird flight has focused on use of thermal updrafts, there is evidence suggesting that many species are likely to use multiple modes of subsidy. We tested the degree to which a large soaring species uses multiple modes of subsidy to provide insights into the decision-making that underlies flight behaviour. We statistically classified more than 22 000 global positioning satellite-global system for mobile communications telemetry points collected at 30-s intervals to identify the type of subsidized flight used by 32 migrating golden eagles during spring in eastern North America. Eagles used subsidized flight on 87% of their journey. They spent 41.9% ± 1.5 ([Formula: see text], range: 18-56%) of their subsidized northbound migration using thermal soaring, 45.2% ± 2.1 (12-65%) of time gliding between thermals, and 12.9% ± 2.2 (1-55%) of time using orographic updrafts. Golden eagles responded to the variable local-scale meteorological events they encountered by switching flight behaviour to take advantage of multiple modes of subsidy. Orographic soaring occurred more frequently in morning and evening, earlier in the migration season, and when crosswinds and tail winds were greatest. Switching between flight modes allowed migration for relatively longer periods each day and frequent switching behaviour has implications for a better understanding of avian flight behaviour and of the evolution of use of subsidy in flight.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".