Breeding timing and nest predation rate of sympatric scops owls with different dietary niche breadth
Bibliographic record
Abstract
Breeding timing is one of the key life-history traits considered to be under strong stabilizing selection, such that offspring should be born when food resources are most abundant. Predation, however, may also affect the breeding timing because nest predation is a leading mortality for many species, although this possibility has been less considered. Here, we examined the possible effects of nest predation on breeding timing by comparing sympatric scops owls in a subtropical forest where only reptilian predators are present. The Japanese Scops Owl (Otus semitorques Temminck and Schlegel, 1844), a dietary generalist, bred one month earlier than the specialist Ryukyu Scops Owl (Otus elegans (Cassin, 1852)). The breeding timing of the Ryukyu Scops Owl matched with the emergence of their main prey species, but also matched with predator activity. Accordingly, the predation rate on eggs or nestlings was 7.5 times higher in the Ryukyu Scops Owl (13.9%; 21 out of 150 nests) than in the Japanese Scops Owl (1.9%; 1 out of 52 nests). Clutch size, on the other hand, was significantly larger in the Ryukyu Scops Owl than in the Japanese Scops Owl, possibly compensating loss from predation. Although alternative explanations still remain, our results suggest that the food generalist might have adjusted its breeding timing to avoid nest predation, whereas the breeding timing of the specialist might have been constrained by the availability of its main prey items.
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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 | 0.001 | 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".