Taking the Bite Out of Winter: Common Murres (Uria aalge) Push Their Dive Limits to Surmount Energy Constraints
Bibliographic record
Abstract
Diving seabirds that overwinter at high latitudes experience persistent cold exposure, short days and associated declines in ocean productivity that can challenge their ability to balance daily energy budgets. We used dive-immersion geo-locators to test the hypothesis that pursuit-diving Common murres (Uria aalge) will respond to the challenges of winter in the North Atlantic through increased daily energy expenditures (DEE) that will be met by increased foraging effort and adjustments in dive tactics. Largely flightless in winter (<5% of daylight hours flying), murres spent most of their time on the water (>85% resting and swimming). Accordingly, when sea surface temperatures (SST) were consistently near freezing in late winter (1.9 ± 0.8°C), mean DEE (2463.2 ± 10.9 kJ day−1) exceeded the theoretical limit to sustainable energy expenditure in vertebrates (i.e., 7 X Basal Metabolic Rate or 2450 kJ day−1 for murres). Consistently deep (70% >50 m) and long dives in late winter, 38% of which exceeded their calculated aerobic dive limit indicate that targeted prey was distributed in deep (dark) waters. Consequently, foraging was largely diurnal; likely because capture efficiency of deep-water prey is poor under low light. Murres responded to these late winter time and energy constraints with a nearly two-fold increase in daily time spent diving (95.2 ± 5.6 and 178.3 ± 6.3 min day−1 during early and late winter, respectively), an increase in dive bout frequency and duration, and correspondingly less time resting between bouts. Uniquely adapted for deep-diving, pursuit-diving can push their dive limits to maximize daily energy intake when energy demands are high and prey are distributed in deep water. Our study highlights late winter as an extremely challenging phase in the annual cycle of North Atlantic murres and provides critical insights into the behavioral mechanisms underlying their winter survival.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".