Marine depth use of sea trout <scp><i>Salmo trutta</i></scp> in fjord areas of central Norway
Bibliographic record
Abstract
The vertical behaviour of 44 veteran sea trout Salmo trutta (275-580 mm) in different marine fjord habitats (estuary, pelagic, near shore with and without steep cliffs) was documented during May-February by acoustic telemetry. The swimming depth of S. trutta was influenced by habitat, time of day (day v. night), season, seawater temperature and the body length at the time of tagging. Mean swimming depth during May-September was 1·7 m (individual means ranged from 0·4 to 6·4 m). Hence, S. trutta were generally surface oriented, but performed dives down to 24 m. Mean swimming depth in May-September was deeper in the near-shore habitats with or without steep cliffs (2·0 m and 2·5 m, respectively) than in the pelagic areas (1·2 m). May-September mean swimming depth in all habitats was slightly deeper during day (1·9 m) than at night (1·2 m), confirming that S. trutta conducted small-scale diel vertical movements. During summer, S. trutta residing in near-shore habitat progressively moved deeper over the period May (mean 1·1 m) to August (mean 4·0 m) and then reoccupied shallower areas (mean 2·3 m) during September. In winter (November and February), individuals residing in the innermost part of the fjords were found at similar average depths as they occupied during the summer (mean 1·3 m). The swimming depths of S. trutta coincide with the previously known surface orientation of salmon lice Lepeophtheirus salmonis. Combined with previous studies on horizontal use of S. trutta, this study illustrates how S. trutta utilize marine water bodies commonly influenced by anthropogenic factors such as aquaculture, harbours and marine constructions, marine renewable energy production or other human activity. This suggests that the marine behaviour of S. trutta and its susceptibility to coastal anthropogenic factors should be considered in marine planning processes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".