Two-generation common-garden experiment reveals a strong genetic contribution to migration tendency in brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Many salmonids, including brown trout ( Salmo trutta), demonstrate alternative migration strategies under different environmental conditions, and as such, they are assumed to be predominantly facultative. Through experimental breeding for two generations, we produced purebred, crossed, and backcrossed groups of phenotypically resident, migratory, and hybrid strains of brown trout originating from a single watershed, and raised them in common-garden conditions. We examined the spring smolt migration tendency of the crosses in outdoor circular channels using passive integrated transponder telemetry at ages 2 and 3 years and found consistent and individually repeatable interstrain differences in migration distance and migration activity. The crossbred fish displayed intermediate behaviour, while later release to the migration channels with food augmentation affected the temporal dynamics of migration but not the total distances migrated. Migration tendency was positively associated with physiological smoltification and fish growth metrics. These results show that some earlier results interpreted as phenotypic plasticity may instead reflect genetic differences within and among populations. The intrinsic differences in reaction norms for both growth and migration tendency require novel management attention for effective conservation strategies.
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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 | 0.000 |
| 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 | 0.001 |
| 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".