Seasonal stage differences overwhelm environmental and individual factors as determinants of energy expenditure in free-ranging red squirrels
Bibliographic record
Abstract
1. Despite the central importance of the rate of energy expenditure in the lives of animals, the major drivers of within-species variation in energy expenditure remain uncertain, largely because most intraspecific studies focus on one or only a few potential determinants of expenditure. 2. Here, we examine the determinants of daily energy expenditure (DEE) in free-ranging female North American red squirrels (Tamiasciurus hudsonicus Erxleben) occupying a highly seasonal environment. By relating variation in 260 measurements of DEE from 176 individuals to key sources of seasonal (reproductive and foraging stages), environmental (resources and air temperature) and individual (body mass and individual identity) variation, our comprehensive analysis examines the relative importance of DEE predictors that have been more commonly examined in isolation. 3. Red squirrels demonstrated extensive variation in DEE with 5th (177 kJ per day) and 95th (660 kJ per day) percentile DEE levels that would correspond to mammals on an interspecific scale ranging in mass from 148 to 1120 g. 4. Seasonal stage differences accounted for most variation in DEE, with high expenditure during lactation and autumn hoarding, and very low expenditure during winter. Contrary to interspecific studies, energy expenditure increased with increasing ambient temperature and it was weakly related to body mass in all seasons except for winter. High resource availability was associated with reduced energy expenditure in winter, but elevated expenditure during lactation and hoarding. 5. Collectively, these results highlight substantial intraspecific variation in energy expenditure, most of which can be explained by a combination of seasonal stages and environmental conditions, and fundamental differences in the importance and direction of determinants of energy expenditure when examined at the intra- versus the interspecific level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.011 | 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 teacher head, 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".