Interspecific competition among juvenile salmonids: social behaviour and HORMONE LEVELS OF ATLANTIC SALMON AND TWO NON-NATIVE TROUT SPECIES
Bibliographic record
Abstract
Competition with ecologically similar non-native salmonids may hinder efforts to restore Atlantic salmon (Salmo salar) in Lake Ontario. I examined the competitive effects of juvenile brown trout (S. truttci) and rainbow trout (Oncorhynchus mykiss), two non-native competitors, on aggression, dominance, growth, and hormone concentrations of three candidate strains of juvenile Atlantic salmon selected for réintroduction into Lake Ontario. Interspecific competition in semi-natural streams reduced aggression, dominance, and growth of Atlantic salmon, coincident with increasing concentrations of cortisol, a hormone that functions in part in the stress response. An aggression-associated hormone, 11-ketotestosterone, was largely unaffected. Interestingly, the most ecologically similar competitor, rainbow trout, had less impact on Atlantic salmon behaviour and growth, relative to brown trout. Atlantic salmon from Lac Saint-Jean were least affected, implicating genetic differences among strains and specific management recommendations. This study highlights the necessity of competition experiments to understand how competition may influence restoration of extirpated populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".