Early-life fitness trait variation among divergent European and North American farmed and Newfoundland wild Atlantic salmon populations
Bibliographic record
Abstract
It has long been clear that interbreeding between domesticated and wild Atlantic salmon can lead to negative fitness consequences for native populations. Few studies, however, have examined these consequences at critical early life stages, particularly in the context of distinct geographical and ancestral relationships among populations as well domestication selection. In Newfoundland (NF), Canada, while the majority of aquaculture sites use the North American (NA) Saint John River strain, site-specific permission has been granted to farm a strain of European origin (EO). We designed a common-garden experiment to compare fitness-related traits (e.g. development time, survival, size and growth) at different early-life stages (eye development, hatch and yolk absorption) among EO and NA farmed, 2 NF wild and F1hybrid groups. Significant differences (p < 0.001) were observed in development time, survival, growth and energy conversion among farmed, F1hybrid and wild populations. While pure populations (farmed and wild) differed amongst one another, we found few differences in fitness-related traits between F1hybrids and their maternal wild/farmed strains. This suggests that the early-life fitness consequences of F1hybridization will be largely manifested through the action of maternal effects. Additionally, significant associations between the maternal effects of egg size and alevin development time, size, survival, growth, condition and energy conversion efficiency were found. These findings suggest that early-life fitness-related trait differences among farmed, wild and their related F1hybrids are generated by the geographic and ancestral relationship and maternal effects of egg size and less so by domestication selection.
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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 | 0.001 | 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".