The Evolutionary Loss of Paternal Care Is Associated With Shifts in Female Life‐History Traits
Bibliographic record
Abstract
ABSTRACT Parental care can increase the fitness of parents through increased offspring survival but can also reduce reproductive output by limiting time and energy allocated to additional mating opportunities. The evolutionary origin of parental care is often associated with shifts in life‐history traits (e.g., high investment in few, large offspring, slow offspring growth), but little is known about whether the evolutionary loss of care is associated with reciprocal shifts in the same life‐history traits. Here, we capitalize on the divergence of parental care between ecotypes of three‐spined stickleback (Gasterosteus aculeatus) to test for associations between parental care and life‐history traits. While males from most stickleback populations provide care, an unusual “white” ecotype has recently lost paternal care. We found support for the hypothesis that the evolutionary loss of paternal care is associated with shifts in female life‐history traits; relative to females of the ecotype with paternal care, females of the white ecotype that lack paternal care produced clutches with a similar overall mass and a greater number of smaller eggs, despite their smaller body size, suggesting lower per‐offspring investment. We did not detect an ecotypic difference in embryonic development rate, metabolic rate, or offspring age at hatching, contrary to the ‘safe harbor hypothesis’. These results support the theory that behavioral traits such as parental care co‐evolve with other life‐history traits and highlight opportunities for future study of the underlying causal mechanisms.
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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 | 0.001 | 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".