Thermodynamic modelling predicts energetic bottleneck for seabirds wintering in the northwest Atlantic
Bibliographic record
Abstract
Studying the energetics of marine top predators such as seabirds is essential to understand processes underlying adult winter survival and its impact on population dynamics. Winter survival is believed to be the single most important life-history trait in long-lived species but its determinants are largely unknown. Seabirds are inaccessible during this season, so conventional metabolic studies are extremely challenging and new approaches are needed. This paper describes and uses a state-of-the-art mechanistic model, Niche Mapper, to predict energy expenditure and food requirements of the two main seabird species wintering in the northwest Atlantic. We found that energy demand increased throughout the winter phase in both species. Across this period, mean estimated daily energy requirements were 1306 kJ day(-1) for Brünnich's guillemots (Uria lomvia) and 430 kJ day(-1) for little auks (Alle alle) wintering off Greenland and Newfoundland. Mean estimated daily food requirements were 547 g wet food day(-1) for Brünnich's guillemots, and 289 g wet food day(-1) for little auks. For both species and both wintering sites, our model predicts a sharp increase in energy expenditure between November and December, primarily driven by climatic factors such as air temperature and wind speed. These findings strongly suggest the existence of an energetic bottleneck for North Atlantic seabirds towards the end of the year, a challenging energetic phase which might explain recurrent events of winter mass-mortality, so called 'seabird winter wrecks'. Our study therefore emphasizes the relevance of thermodynamics/biophysical modelling for investigating the energy balance of wintering marine top predators and its interplay with survival and population dynamics in the context of global change.
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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 | 0.000 | 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) | 0.000 | 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".