Heritability estimation via molecular pedigree reconstruction in a wild fish population reveals substantial evolutionary potential for sea age at maturity, but not size within age classes
Bibliographic record
Abstract
While evolutionary responses require heritable variation, estimates of heritability (h 2 ) from wild fish populations remain rare. A 20-year molecular pedigree for a wild Scottish population of Atlantic salmon (Salmo salar) was used to investigate genetic contributions to (co)variation in two important, correlated, phenotypic traits: “sea age” (number of winters spent at sea prior to spawning) and size-at-maturity (body length just prior to spawning). Sea age was strongly heritable (h 2 = 0.51) and size exhibited moderate heritability (h 2 = 0.27). A very strong genetic correlation (r G = 0.96) between these traits implied the same functional loci must underpin variation in each. Indeed, body size within sea ages had much lower heritability that did not differ significantly from zero. Thus, within wild S. salar populations, temporal changes in sea age composition could reflect evolutionary responses, whereas rapid changes of body size within sea ages are more likely due to phenotypic plasticity. These inheritance patterns will influence the scope of evolutionary responses to factors such as harvest or climate change and, hence, have management implications for salmonid populations comprising a mix of sea ages.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".