The Clock Keeps Ticking: Circadian Rhythms of Free-Ranging Polar Bears
Bibliographic record
Abstract
) evolved under these unique conditions, where they rely on ice to hunt their main prey, seals. However, very little is known about the dynamics of their daily and seasonal activity patterns. For many organisms, activity is synchronized (entrained) to the earth's day/night cycle, in part via an endogenous (circadian) timekeeping mechanism. The present study used collar-mounted accelerometer and global positioning system data from 122 female polar bears in the Chukchi and Southern Beaufort Seas collected over an 8-year period to characterize activity patterns over the calendar year and to determine if circadian rhythms are expressed under the constant conditions found in the Arctic. We reveal that the majority of polar bears (80%) exhibited rhythmic activity for the duration of their recordings. Collectively within the rhythmic bear cohort, circadian rhythms were detected during periods of constant daylight (June-August; 24.40 ± 1.39 h, mean ± SD) and constant darkness (23.89 ± 1.72 h). Exclusive of denning periods (November-April), the time of peak activity remained relatively stable (acrophases: ~1200-1400 h) for most of the year, suggesting either entrainment or masking. However, activity patterns shifted during the spring feeding and seal pupping season, as evidenced by an acrophase inversion to ~2400 h in April, followed by highly variable timing of activity across bears in May. Intriguingly, despite the dynamic environmental photoperiodic conditions, unpredictable daily timing of prey availability, and high between-animal variability, the average duration of activity (alpha) remained stable (11.2 ± 2.9 h) for most of the year. Together, these results reveal a high degree of behavioral plasticity in polar bears while also retaining circadian rhythmicity. Whether this degree of plasticity will benefit polar bears faced with a loss of sea ice remains to be determined.
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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 | 0.000 |
| 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) | 0.001 | 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".