Parental allocation of additional food to own health and offspring growth in a variable environment
Bibliographic record
Abstract
Life-history theory predicts increased investment in current reproduction when future reproduction is uncertain and a more balanced investment in current and future reproduction when prospects for both are good. The outcome of the balance in parental allocation depends on which life-history component maximizes the fitness benefits. In our study system, a 3-year vole cycle generates good prospects of current and future reproduction for Ural owls ( Strix uralensis Pallas, 1771) in increase vole phases and uncertain prospects in decrease vole phases. We supplementary-fed Ural owls during the nestling period in 2002 (an increase phase) and 2003 (a decrease phase), and measured offspring growth, parental effort, and physiological health by monitoring haematocrit, leucocyte profiles, intra- and inter-celluar blood parasites, and (in 2003) humoral antibody responsiveness. Food supplementation reduced parental feeding rate in both years, but improved a female parent’s health only in 2002 (an increase phase) and had no effects on males in either year. Nevertheless, supplementary-fed offspring reached higher asymptotic mass and fledged earlier in both years. Furthermore, early fledging reduced offspring exposure to blood-sucking black flies (Diptera, Simuliidae) in the nest. We discuss how parental allocation of resources to current and future reproduction may vary under variable food conditions.
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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".