Phenotypic plasticity in mass loss during chick-rearing in the European starling (Sturnus vulgaris)
Bibliographic record
Abstract
It has long been recognized that mass loss during breeding could be adaptive (e.g., by ameliorating the costs of increased parental activity). However, many studies still commonly interpret mass loss as evidence of “stress” or a cost of reproduction (a negative effect of high workload during chick provisioning). Despite several studies reporting evidence in support of both hypotheses, the ecological and/or life-history contexts under which mass loss may be viewed as a “cost” or an adaptive strategy are still unclear. Here, we used a long-term dataset from a breeding population of European starlings to investigate the natural annual and individual variation in body mass and mass loss and to test whether mass loss during chick-rearing represents a phenotypically plastic trait that varies predictably in relation to ecological context and individual quality. While there was significant annual variation in incubation mass, chick-rearing mass, and mass change, there were no systematic relationships between mass loss and (1) current breeding success or (2) future fecundity and survival. In addition, we found moderate repeatability of mass loss (R = 0.59) suggesting there might be additive genetic variation for this trait, though with considerable residual environmental variation. However, we found no covariation between this residual, intra-individual variation and other reproductive or life-history traits. We therefore found no support for the idea that mass loss reflects “reproductive stress” in our system: there were no negative relationships between mass loss and either current or future reproduction and survival (local return rate). Our results are consistent with mass loss being an individually plastic trait, potentially with moderate additive genetic variance, with individuals using mass loss to “level the playing field” and individually optimize reproductive effort and fitness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.029 |
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 teacher head, 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".