Experimental (Antiestrogen‐Mediated) Reduction in Egg Size Negatively Affects Offspring Growth and Survival
Bibliographic record
Abstract
The relationship between egg size and offspring phenotype is critical to our understanding of the selective pressures acting on the key reproductive life-history traits of egg size and number. Yet there is surprisingly little empirical evidence to support a strong, positive relationship between egg size and offspring quality (i.e., offspring growth, condition, and survival) in birds, in part because of confounding effects of parental quality and the lack of experimental techniques for directly manipulating avian egg size independently of maternal condition. Previously, we showed that treatment of laying female zebra finches (Taeniopygia guttata) with the antiestrogen tamoxifen can decrease egg size by ca. 8% but that this reduction in egg size had few effects on offspring mass and size at fledging. Here, we extend the use of this technique to induce larger decreases in egg size (up to 50% in individual females) and show that a reduction in egg size of ca. 18% is associated with decreased embryo viability, increased hatchling mortality, and lower posthatching offspring survival. Furthermore, we show that although hatchlings from eggs reduced in size by ca. 9% can survive to fledging, these chicks show slower initial growth during the linear growth phase (5-10 d of age), fledge at lower masses than chicks from control eggs, and show postfledging compensatory growth. Our results provide empirical support for significant effects of egg size on offspring quality and further suggest that among individual females there is a minimum egg size required to maintain embryo viability and offspring quality.
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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 | 0.001 |
| 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".