Hibernation and seasonal fasting in bears: the energetic costs and consequences for polar bears
Bibliographic record
Abstract
Global warming has the potential to reduce arctic sea ice and thereby increase the length of summer-fall fasting when polar bears (Ursus maritimus) lose access to most marine mammals. To evaluate the consequences of such changes, we compared the cost of fasting by polar bears with hibernation by brown bears (U. arctos), American black bears (U. americanus), and polar bears and made projections about tissue reserves polar bears will need to survive and reproduce as fasts become longer. Hibernating polar bears expend energy at the same rate per unit mass as do brown bears and black bears. However, daily mass losses, energy expenditures, and the losses of lean mass are much higher in fasting, active polar bears than in hibernating bears. The average pregnant polar bear living around Hudson Bay during the 1980s and 1990s could fast for 10.0 ± 2.3 months (X̄ ± SD), and the average lactating female with cubs born during the preceding winter could fast for 4.2 ±1.9 months. Thus, some pregnant or lactating females with lower levels of body fat content were already approaching or beyond the constraint of being able to produce cubs and survive the required 8 months of fasting if producing new offspring or 4 months if accompanied by older offspring. Pregnant or lactating females and their dependent offspring have the most tenuous future as global warming occurs. Thus, we predict a significant reduction in productivity with even modest increases in global warming for polar bears living in the very southern part of their range and are concerned about more northern populations depending on their ability to accumulate increasing amounts of fat.
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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 | 0.001 |
| 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 | 0.001 | 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".