Migration phenology and seasonal fidelity of an Arctic marine predator in relation to sea ice dynamics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding how seasonal environmental conditions affect the timing and distribution of synchronized animal movement patterns is a central issue in animal ecology. Migration, a behavioural adaptation to seasonal environmental fluctuations, is a fundamental part of the life history of numerous species. However, global climate change can alter the spatiotemporal distribution of resources and thus affect the seasonal movement patterns of migratory animals. We examined sea ice dynamics relative to migration patterns and seasonal geographical fidelity of an Arctic marine predator, the polar bear (Ursus maritimus). Polar bear movement patterns were quantified using satellite-linked telemetry data collected from collars deployed between 1991-1997 and 2004-2009. We showed that specific sea ice characteristics can predict the timing of seasonal polar bear migration on and off terrestrial refugia. In addition, fidelity to specific onshore regions during the ice-free period was predicted by the spatial pattern of sea ice break-up but not by the timing of break-up. The timing of migration showed a trend towards earlier arrival of polar bears on shore and later departure from land, which has been driven by climate-induced declines in the availability of sea ice. Changes to the timing of migration have resulted in polar bears spending progressively longer periods of time on land without access to sea ice and their marine mammal prey. The links between increased atmospheric temperatures, sea ice dynamics, and the migratory behaviour of an ice-dependent species emphasizes the importance of quantifying and monitoring relationships between migratory wildlife and environmental cues that may be altered by climate change.
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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) | 0.002 | 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 it