To fly or not to fly: high flight costs in a large sea duck do not imply an expensive lifestyle
Bibliographic record
Abstract
A perennial question in ornithology is whether flight has evolved mostly to facilitate access to food or as an anti-predator strategy. However, flight is an expensive mode of locomotion and species using flight regularly are associated with an expensive lifestyle. Using heart rate (HR) data loggers implanted in 13 female common eiders (Somateria mollissima), our objective was to test the hypothesis that a high level of flight activity increases their energy budget. We used the long-term recording (seven months) of HR as an index of energy expenditure and the HR flight signature to compile all flight events. Our results indicate that the eider is one of the thriftiest volant birds with only 10 minutes of flight time per day. Consequently, we were not able to detect any effect of flight activity on their energy budget despite very high flight costs (123-149 W), suggesting that flight was controlled by energy budget limitations. However, the low flight activity of that species may also be related to their prey landscape requiring few or no large-scale movements. Nevertheless, we suggest that the (fitness) benefits of keeping flight ability in this species exceed the costs by allowing a higher survival in relation to predation and environmental harshness.
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 | 0.001 |
| 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".