Light oiling of feathers increases flight energy expenditure in a migratory shorebird
Bibliographic record
Abstract
ABSTRACT Flying birds depend on their feathers to undertake most activities, and maintain them in peak condition through periodic molt and frequent preening. Even small exposures to crude oil reduce the integrity of feathers, and could impair flight performance. We trained wild western sandpipers (Calidris mauri) to perform endurance flights in a wind tunnel, and used magnetic resonance body composition analysis to measure energy expenditure after birds were exposed to weathered MC252 crude oil from the Deepwater Horizon oil spill. The cost of transport was 0.26±0.04 kJ km−1 in controls, and increased by 22% when the trailing edges of the wing and tail were oiled (<20% of body surface; considered light oiling). Additional crude oil on breast and back feathers (∼30% total surface; moderate oiling) increased the cost of transport by 45% above controls. Oiling tended to decrease flight control, and only half of moderately oiled birds completed the flight test. We then flew birds at a range of speeds to estimate basic kinematic parameters. At low speeds, light and moderately oiled birds had larger wingbeat amplitudes than controls, while moderately oiled birds showed greater wingbeat frequencies across all speeds, and a shift in optimal flight speed towards higher wind speeds. We suggest these changes reflect poorer lift production and increased drag on the wings and body. Oiling will increase the difficulty and energy costs of locomotion for daily and seasonal activities such as foraging, predator evasion, territory defense, courtship, chick provisioning, commuting and long-distance migration. These sub-lethal effects must be considered in oil spill impact assessments.
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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 | 0.000 | 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 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".