Competition among juvenile brown trout, grayling, and landlocked Atlantic salmon in flumes — predicting effects of interspecific interactions on salmon reintroduction success
Bibliographic record
Abstract
Worldwide declines in salmonid populations have generated major interest in conservation and restoration of wild populations and riverine habitats. Species reintroductions to previous habitats raise questions about their potential impact on these systems. In River Klarälven, landlocked Atlantic salmon (Salmo salar) have been extinct from upper reaches for over 50 years due to hydropower dams. Here we study competitive interactions among juvenile salmon, grayling (Thymallus thymallus), and brown trout (Salmo trutta) that occur in the upper reaches of the river. We examine foraging rates, aggression, and activity of juvenile fish in allopatry at three different densities and in sympatry with one or both potential competitors in laboratory flumes. Salmon captured prey less frequently in the presence of brown trout and grayling, whereas grayling and brown trout were unaffected by salmon, but affected each other. Grayling was the most aggressive and active species, whereas salmon the least. Consequently, reintroduction of salmon probably will have little impact on grayling and brown trout, whereas grayling and brown trout could affect the success of reintroducing salmon.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".