Environmental enrichment in steelhead (<i>Oncorhynchus mykiss</i>) hatcheries: field evaluation of aggression, foraging, and territoriality in natural and hatchery fry
Bibliographic record
Abstract
Reforms for salmonid hatcheries include production of hatchery fish with behavioral characteristics similar to wild conspecifics. Enrichment of the hatchery environment has been proposed to achieve this goal. Field experiments of steelhead (i.e., sea-run rainbow trout, Oncorhynchus mykiss) fry from a common stock reared under natural (i.e., stream), enriched hatchery, and conventional hatchery conditions indicated no significant differences in the rates of foraging or aggression between rearing treatments. However, the rates of foraging and aggression of natural fry were significantly affected by the type of hatchery fry stocked with them. Natural steelhead fry fed at lower rates and exhibited higher rates of aggression when stocked with steelhead fry raised in enriched hatchery environments. Territory sizes of steelhead fry ranged from 0.015 to 0.801 m2; were significantly, positively related to body length; and were not significantly different between rearing treatments. We conclude that hatchery steelhead fry released into streams establish territories that are proportional to their body length and similar in size to territories of natural steelhead fry. Our results indicate that both conventional and enriched hatchery environments produce natural social behaviors in steelhead released as fry and that fry from enriched hatchery environments may alter the foraging and aggressive behavior of natural, resident steelhead fry.
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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 | 0.000 |
| 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".