Cohort effects in red squirrels: the influence of density, food abundance and temperature on future survival and reproductive success
Bibliographic record
Abstract
1. Environmental conditions experienced early in life may have long-lasting effects on individual performance, thereby creating 'silver-spoon effects'. 2. We used 15 years of data from a North American red squirrel (Tamiasciurus hudsonicus Erxleben) population to investigate influences of food availability, density and spring temperature experienced early in life on reproduction and survival of female squirrels during adulthood. 3. We found that spring temperature and food availability did not affect female survival after 1 year of age, whereas higher squirrel densities led to lower survival, thereby affecting longevity and lifetime fitness. 4. In addition, both food availability experienced between birth and weaning, and spring temperature in the year of birth, had long-lasting positive effects on female reproductive success. These results emphasize the critical effect environmental conditions during the early life stages can have on the lifetime performance of small mammals. 5. These long-term effects of early food and temperature were apparent only once we controlled for conditions experienced during adulthood. This suggests that silver-spoon effects can be masked when conditions experienced early in life are correlated to some environmental conditions experienced later in life. 6. The general importance of silver-spoon effects for adult demographic performance might therefore be underestimated, and taking adult environment into account appears to be necessary when studying long-term cohort effects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".