Associations between over‐winter survival and resting metabolic rate in juvenile North American red squirrels
Bibliographic record
Abstract
Summary 1. Resting metabolic rate (RMR) varies considerably among and within species. Two central questions in physiological ecology are whether values of RMR are repeatable and whether an association exists between RMR and fitness. 2. First, we investigated the repeatability of RMR in food hoarding, juvenile, North American red squirrels ( Tamiasciurus hudsonicus Erxleben). Second, we explored links between RMR and survival. A low RMR may enhance survival if it reduces winter expenditure costs and/or allows more energy to be allocated towards autumn food hoarding. Alternately, a high RMR may enhance survival if it enables juveniles to hoard more food by increasing the throughput of energy available for investment in hoarding activities. 3. Resting metabolic rate adjusted for body mass, was repeatable in both males and females ( r = 0·77) over a short‐term (mean 24·3 days) but only among females ( r = 0·72) over a long‐term interval (mean 192 days). 4. Heavier juveniles and those with a lower RMR relative to their body mass were more likely to survive over‐winter. Multiple selection models found significant selection for a decreased RMR (β′ = −0·56 ± 0·16) and increased mass (β′ = 0·69 ± 0·17). Survivors also tended to have more food stored within their hoard. 5. A low RMR relative to body mass and large body mass may have allowed individuals to minimize the expenditure costs related to a larger body mass, while maximizing thermal inertia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".