Interacting effects of age, density, and weather on survival and current reproduction for a large mammal
Bibliographic record
Abstract
Individual-based study of natural populations allows for accurate and precise estimation of fitness components and the extent to which they might vary with ecological conditions. By tracking the fates of all 701 horses known to have lived on Sable Island, Canada, from 2009 to 2013 (where there is no predation, human interference, or interspecific competition for food), we present a detailed analysis of structured population dynamics with focus on interacting effects of intraspecific competition and weather on reproduction and survival. Annual survival of adult females (0.866 ± 0.107 [[Formula: see text] ± SE]) was lower than that of 3-year-olds (0.955 ± 0.051), although annual fecundity (producing a foal in a year that was observed during our census) was higher in adults (0.616 ± 0.023) compared to 3-year-olds (0.402 ± 0.054). Milder winters and lower densities during gestation increased fecundity. Density negatively impacted survival for all age and sex categories; however, highest adult female survival was observed during high-density years coupled with a harsh winter, the result expected if pregnancy loss during winter or loss of foals in spring improved survival. Three-year-old females, which reproduced at lower rates, experienced higher survival than adults. Our results contrast with a previous study of feral horses that suggested recently feral ungulates might be artificially selected to reproduce even when costs to survival are high. In part, this may be because of the comparably long history of feralization (250 years; at least 25 generations) for Sable Island horses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".