Linking the availability of cached food to climate change: an experimental test of the hoard-rot hypothesis
Bibliographic record
Abstract
Understanding how long-term changes in climate influence populations requires knowledge of the mechanisms by which climate influences individual success and population abundance. We explored the implications of warmer falls and winters on a nonmigratory, food-caching bird, the Gray Jay (Perisoreus canadensis (L., 1766)), in Algonquin Park, Ontario, by experimentally examining the influence of temperature on the caloric content and mass of simulated cached food. Using three sites in, north of, and south of Algonquin, we examined the hypothesis that warmer temperatures would negatively influence the preservation of cached food by accelerating decay. Food cached at the highest latitude site retained the greatest mass and caloric content over 180 days of exposure, but there was no difference between the intermediate and the low latitude sites. We also show that Algonquin experienced a winter climate similar to our northernmost site as recently as 1990, and our results suggest that food availability in Algonquin has likely decreased since then, due to a warming climate. Interestingly, this coincides with a decline in territory occupancy by Gray Jays in Algonquin. Our results point to a unique mechanism by which climate warming may influence the persistence of a boreal species through its influence on winter food availability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".