Increased Arctic sea ice drift alters adult female polar bear movements and energetics
Bibliographic record
Abstract
Recent reductions in thickness and extent have increased drift rates of Arctic sea ice. Increased ice drift could significantly affect the movements and the energy balance of polar bears (Ursus maritimus) which forage, nearly exclusively, on this substrate. We used radio-tracking and ice drift data to quantify the influence of increased drift on bear movements, and we modeled the consequences for energy demands of adult females in the Beaufort and Chukchi seas during two periods with different sea ice characteristics. Westward and northward drift of the sea ice used by polar bears in both regions increased between 1987-1998 and 1999-2013. To remain within their home ranges, polar bears responded to the higher westward ice drift with greater eastward movements, while their movements north in the spring and south in fall were frequently aided by ice motion. To compensate for more rapid westward ice drift in recent years, polar bears covered greater daily distances either by increasing their time spent active (7.6%-9.6%) or by increasing their travel speed (8.5%-8.9%). This increased their calculated annual energy expenditure by 1.8%-3.6% (depending on region and reproductive status), a cost that could be met by capturing an additional 1-3 seals/year. Polar bears selected similar habitats in both periods, indicating that faster drift did not alter habitat preferences. Compounding reduced foraging opportunities that result from habitat loss; changes in ice drift, and associated activity increases, likely exacerbate the physiological stress experienced by polar bears in a warming Arctic.
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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 | 0.000 | 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".