Winter survival of a small predator is determined by the amount of food in hoards
Bibliographic record
Abstract
The hoarding behaviour of animals has evolved to reduce starvation risk when food resources are scarce, but effects of food limitation on survival of hoarding animals is poorly understood. Eurasian pygmy owls (Glaucidium passerinum) hoard small mammals and birds in natural cavities and nest boxes in late autumn for later use in the following winter. We studied the relative influence of the food biomass in hoards of pygmy owls on their over-winter and over-summer apparent survival. We also tested whether this influence is modulated by intrinsic (age, sex) traits or extrinsic factors (winter temperature, snow depth). We measured biomass of prey items in pygmy owl food-hoards during autumns 2003-2023 in west-central Finland. We individually marked and recaptured pygmy owls both at nests in the breeding season and at food-hoards. Our dataset included a total of 407 pygmy owls, which were all captured from a food-hoard at least once during their capture history. The mean biomass of the annual food-hoards associated with one individual was 443 g (SD = 523 g, range from 3.5 to 4505 g) and was markedly higher in autumns of vole abundance than in those of vole scarcity. Hoard size had a positive effect on apparent survival of owls over consecutive winter, whereas it did not affect apparent survival over next summer. Hoard size was a better predictor of apparent survival than vole abundance (main food of pygmy owls) in the field. Male owls had higher overall apparent survival rates than female owls, particularly when food-hoards were small. That hoard size was a better predictor of apparent survival than vole abundance indicates that the hoards are critical for pygmy owls during winter, likely because they are unable to hunt voles below deep snow cover. The positive relationship between apparent survival of owl individuals and their hoard size during winter (when the hoard is being consumed), but not summer, indicates that the hoard size has a true positive effect on survival, and does not only reflect latent inter-individual differences and/or dissimilarities in their environments. We conclude that food limitation during hoarding essentially regulates apparent over-winter survival of pygmy owl individuals.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".