Food-supplementing parents reduces their sons' song repertoire size
Bibliographic record
Abstract
Food-supplemented parents typically produce more offspring, as numerous experiments on vertebrate populations have shown. 'Propagule' (egg or neonate) size and parental care may also be affected, with implications concerning the adult quality of offspring, although few experiments have addressed whether food-supplementing one generation affects adult quality in the next. We conducted a food supplementation experiment on song sparrows (Melospiza melodia) and tested whether song repertoire size, a demonstrated indicator of male quality, differed between the adult sons of fed (food-supplemented) and unfed (non-food-supplemented) parents. Counterintuitively, fed parents produced sons with smaller adult song repertoires, who may thus be expected to contribute fewer offspring, and fewer grand-offspring, to the population. Fed and unfed parents invested equally in the total biomass of their clutches and broods, and average nestling condition was comparable, but because fed parents produced more offspring, average egg and nestling sizes were reduced. Fed and unfed parents apportioned care differently within their broods, and we suggest compensatory growth of offspring emerging from light eggs, or egg size itself, may have affected adult repertoire size. Conceivably, the conservation benefits of food-supplementing populations could attenuate over time if fed parents produce offspring of poorer quality than themselves.
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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 | 0.000 |
| 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) | 0.002 | 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".