Increasing nest predation will be insufficient to maintain polar bear body condition in the face of sea ice loss
Bibliographic record
Abstract
Climate change can influence interspecific interactions by differentially affecting species-specific phenology. In seasonal ice environments, there is evidence that polar bear predation of Arctic bird eggs is increasing because of earlier sea ice breakup, which forces polar bears into nearshore terrestrial environments where Arctic birds are nesting. Because polar bears can consume a large number of nests before becoming satiated, and because they can swim between island colonies, they could have dramatic influences on seabird and sea duck reproductive success. However, it is unclear whether nest foraging can provide an energetic benefit to polar bear populations, especially given the capacity of bird populations to redistribute in response to increasing predation pressure. In this study, we develop a spatially explicit agent-based model of the predator-prey relationship between polar bears and common eiders, a common and culturally important bird species for northern peoples. Our model is composed of two types of agents (polar bear agents and common eider hen agents) whose movements and decision heuristics are based on species-specific bioenergetic and behavioral ecological principles, and are influenced by historical and extrapolated sea ice conditions. Our model reproduces empirical findings that polar bear predation of bird nests is increasing and predicts an accelerating relationship between advancing ice breakup dates and the number of nests depredated. Despite increases in nest predation, our model predicts that polar bear body condition during the ice-free period will continue to decline. Finally, our model predicts that common eider nests will become more dispersed and will move closer to the mainland in response to increasing predation, possibly increasing their exposure to land-based predators and influencing the livelihood of local people that collect eider eggs and down. These results show that predator-prey interactions can have nonlinear responses to changes in climate and provides important predictions of ecological change in Arctic ecosystems.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".