Costs of reproduction can explain the correlated evolution of semelparity and egg size: theory and a test with salmon
Bibliographic record
Abstract
Species' life history traits, including maturation age, number of reproductive bouts, offspring size and number, reflect adaptations to diverse biotic and abiotic selection pressures. A striking example of divergent life histories is the evolution of either iteroparity (breeding multiple times) or semelparity (breed once and die). We analysed published data on salmonid fishes and found that semelparous species produce larger eggs, that egg size and number increase with salmonid body size among populations and species and that migratory behaviour and parity interact. We developed three hypotheses that might explain the patterns in our data and evaluated them in a stage-structured modelling framework accounting for different growth and survival scenarios. Our models predict the observation of small eggs in iteroparous species when egg size is costly to maternal survival or egg number is constrained. By exploring trait co-variation in salmonids, we generate new hypotheses for the evolution of trade-offs among life history traits.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".