Variance in within-pair reproductive success influences the opportunity for selection annually and over the lifetimes of males in a multi-brooded songbird
Bibliographic record
Abstract
Abstract In socially monogamous species, male reproductive success consists of ‘within-pair’ offspring produced with their socially-paired mate(s), and ‘extra-pair’ offspring produced with additional females throughout the population. Both reproductive pathways offer distinct opportunities for selection in wild populations, as each is composed of separate components of mate attraction, female fecundity, and paternity allocation. Identifying key sources of variance and covariance among these components is a crucial step towards understanding the reproductive strategies that males use to maximize fitness both annually and over their lifetimes. We use 16 years of complete reproductive data from a population of black-throated blue warblers ( Setophaga caerulescens ) to partition variance in male annual and lifetime reproductive success, and thereby identify if the opportunity for selection varies over the lifetimes of individual males and what reproductive strategies likely favor maximum lifetime fitness. The majority of variance in male reproduction was attributable to within-pair success, but the specific effects of individual components of variance differed between total annual and total lifetime reproductive success. Positive overall lifetime covariance between within-pair and extra-pair components indicates that males able to maximize within-pair success, particularly with double-brooding females, likely achieve higher overall lifetime fitness via both within-pair and extra-pair reproductive pathways.
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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".