Effects of genetic origin on phenotypic divergence in Brook Trout populations stocked with domestic fish
Bibliographic record
Abstract
Abstract Phenotypic changes due to human activities are occurring at a far greater speed than those originating from natural causes in animal populations. For instance, phenotypic divergence among individuals may arise in populations supplemented with farm‐reared fish that are known to display different phenotypes from those of wild individuals because of domestication. Little is known about how these phenotypic differences are maintained when domestic and wild individuals face the same environment and hybridize, as it is the case after supplementation. In this study, we assessed the effect of genetic origin of individuals on phenotypic trait divergence (morphology, growth, and size‐at‐age) in stocked populations of Brook Trout (Salvelinus fontinalis). We also evaluated whether genetic origin influences habitat use by documenting trophic niche and/or level using stable isotope analyses. We found significant effects of genetic origin on phenotypic variables with domestic fish generally being more fusiform and larger than wild and hybrid individuals. Lake identity also explained most of the variation in phenotypic variables, meaning that population‐specific attributes were important drivers of morphology and size. Our results also showed that domestic fish were feeding in more littoral niches and at a higher trophic level than wild and hybrid individuals, suggesting that differences in feeding habits could partially explain phenotypic differences. These results highlight the importance of accounting for the genetic composition of populations when assessing the causes of phenotypic divergence in the wild.
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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 | 0.001 |
| 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".