Assessing the Adaptive Capacity of an Arctic Seabird to Increasing Frequency in Predation Risk from Polar Bears Using Behavioural and Physiological Metrics
Bibliographic record
Abstract
Predator-prey dynamics in the Arctic are being altered with changing sea-ice phenology. The increasing frequency of predation on colonial nesting seabird eggs by a rare predator - the polar bear (Ursus maritimus), is a consequence of bears shifting to terrestrial food resources through a shortened seal-hunting season. I study a colony of nesting common eiders (Somateria mollissima) on Mitivik (East Bay) Island, Nunavut, Canada, that is exposed to established nest predators such as arctic fox (Vulpes lagopus), but has recently experienced an increase in polar bear nest predation due to the bears’ lost on-ice hunting opportunities. Given eiders’ limited eco-evolutionary experience with polar bears, my thesis aimed to determine the capacity of incubating eider hens to perceive and respond to this increasing frequency in predation risk from bears. I used eider heart rate and flight initiation distance (FID) as physiological and behavioural metrics, respectively, to characterize the perceived risk of imminent threat posed by simulated predators that differ in evolved familiarity. I then quantified eider heart rate to examine the capacity of incubating hens to dynamically update their perception of risk across variation in real predation risk by polar bears. My results indicate that eiders were less responsive in terms of heart rate to impending visual cues of polar bears in comparison to that of an evolved egg predator (arctic fox), but responded to all simulated threats with similar FIDs. Eiders exhibited mild tachycardia to bears present closer to their nests, but were insensitive to variation in exposure duration to bears. Taken together, these results suggest eiders do not perceive the full risk that bears pose as egg- and adult predators. This thesis provides insight into the mechanisms governing the ability of eiders to cope with polar bears and subsequent fitness consequences due to indirect effects of anthropogenic climate change.
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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) | 0.000 | 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 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".