Genetic control over survival in Pacific salmon (<i>Oncorhynchus</i> spp.): experimental evidence between and within populations of New Zealand chinook salmon (<i>O. tshawytscha</i>)
Bibliographic record
Abstract
The ability to survive to adulthood and return to natal sites is a fundamental characteristic of anadromous salmonids, and low survival is likely to have prevented establishment of new populations within and outside their native range. We hypothesised that there is family-level genetic variation in traits contributing to survival and that populations evolve to maximise survival in response to prevailing local conditions. To test these predictions, we compared postrelease survival for chinook salmon families from two populations established in New Zealand in the 1900s. Both populations, Glenariffe Stream and Hakataramea River, had similar survival when released after translocation to a drainage familiar to neither population. However, Glenariffe families had higher survival than Hakataramea families when both populations were released from Glenariffe Stream, indicating a survival advantage for the local fish. In addition, there were significant correlations between survival rates for paternal half-sib families of Glenariffe fish and between survival rates for families released from the two locations. Family-specific survival was positively correlated with weight at release, but there were underlying genetic correlations unexplained by size. Taken together, these results suggest considerable genetic influence over survival and return of salmon and that population-specific adaptation can occur within 30 generations of establishment.
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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 | 0.001 | 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 | 0.001 |
| 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".