Insights for planning an effective stocking program in anadromous brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Brown trout (Salmo trutta) is a salmonid species with a high socio-economic value related with recreational fishing. Because of that, stocking programs have been developed in many populations, although they have focused on resident populations. To explore which factors promote migratory behaviour when implementing stocking actions, 28 brown trout artificial crosses were carried out in a noncommercial hatchery, and the returning success of their offspring was further evaluated. Return rate was examined according to male phenotype (anadromous versus resident), mean egg size, parents’ similarity at major histocompatibility complex (MHC) class II β-gene, and stocking procedure. At the end of the experiment, 35 of the captured returning adults (9.4%) belonged to 14 of those crosses. Return success shows a significant effect (p = 0.0016) by parental MHC similarities, stocking procedure, and male phenotype. Our results indicate that planting fertilized eggs in nursery areas of the river, together with the selection of anadromous males as brood stock and mate pairs with higher similarity at the MHC locus, can be an appropriate option to increase the migratory part of trout populations. In addition, nursery areas can allow an important decrease in the cost per stocked individual, being 32 times less expensive than the cost per hatchery-reared individual.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".