Climate‐driven carry‐over effects negatively influence population growth rate in a food‐caching boreal passerine
Bibliographic record
Abstract
Understanding how events throughout the annual cycle are linked is important for predicting variation in individual fitness, but whether and how carry-over effects scale up to influence population dynamics is poorly understood. Using 38 years of demographic data from Algonquin Provincial Park, Ontario, and a full annual cycle integrated population model, we examined the influence of environmental conditions and density on the population growth rate of Canada jays (Perisoreus canadensis), a resident boreal passerine that relies on perishable cached food for over-winter survival and late-winter breeding. Our results demonstrate that fall environmental variables, most notably the number of freeze-thaw events, carried over to influence late-winter fecundity, which, in turn, was the main vital rate driving population growth. These results are consistent with the hypothesis that warmer and more variable fall conditions accelerate the degradation of perishable stored food that is relied upon for successful reproduction. Future warming during the fall and winter may compromise the viability of cached food that requires consistent subzero temperatures for effective preservation, potentially exacerbating climate-driven carry-over effects that impact long-term population dynamics.
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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 | 0.000 | 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".