Indirect effects of prey fluctuation on survival of juvenile arctic fox (<i>Vulpes lagopus</i>): a matter of maternal experience and litter attendance
Bibliographic record
Abstract
Reproductive experience affects juvenile survival in a wide range of species with possible links to differences in foraging capacity and predation. Using supplementary feeding, we aimed to limit direct effect of prey abundance to investigate indirect effects of small-rodent availability and maternal experience on juvenile summer survival rates in an endangered population of arctic fox (Vulpes lagopus (L., 1758)). We used data spanning 7 years, included a complete small-rodent cycle, comprising 49 litters and 394 cubs. The effect of small-rodent abundance on juvenile survival depended on maternal breeding experience. Cubs born by first-time-breeding females had lower survival rate when small-rodent abundance was low compared with juveniles born to experienced mothers who remained unaffected. It was unlikely due to starvation, as physical condition was unrelated to survival. Instead, we favour the explanation that intraguild predation was an important cause of mortality. There was a negative relationship between survival and amount of time cubs were left unattended, suggesting that parental behaviour affected predation. We propose that a prey switch related to small-rodent abundance caused fluctuations in intraguild predation pressure and that inexperienced females were less able to cope with predation when small rodents were scarce.
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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".