Migratory contingents of brown trout reveal variable exposure to anthropogenic threats along a fjord‐river continuum
Bibliographic record
Abstract
Abstract Brown trout is a partially migratory salmonid that makes use of diverse habitats to maximise growth and fitness. One of the most substantial threats to brown trout is infection with pathogens from open net‐pen fish farming, which creates hotspots for pathogen reproduction and transmission. Western Norway is a global hotspot for both fish farming and wild salmonids, which generates conflicts due to the impacts of the farms on the behaviour, survival, and fitness of salmonids that overlap with farming activities. In this study, we tagged adult brown trout (>35 cm) at two spatiotemporal intervals that corresponded to two different life history stages: springtime in the river when trout were completing overwintering and summer in the fjord when trout were in their marine feeding phase. The tagging revealed three different behaviours, fish that remained in freshwater, fish that migrated between freshwater and the fjord, and fish that remained in the estuary. Although some trout moved >100 km to the outer fjord areas, most trout remained relatively close to the river. Depth sensor transmitters in a subset of trout also revealed that the trout remained in the upper water column. Most of the horizontal and vertical movements therefore resulted in spatial overlap with fish farming for the migratory trout, but not for resident trout that remained in the estuary or in freshwater. Findings reveal the challenges of managing a fish with such behavioural plasticity but the urgency of recognising how important inner fjord habitats are for migratory brown trout.
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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 | 0.001 | 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".