Individual variability of wild juvenile Atlantic salmon activity patterns: effect of flow stage, temperature, and habitat use
Bibliographic record
Abstract
The magnitude of variation of diel activity patterns and habitat use of wild Atlantic salmon (Salmo salar) parr was examined during the summer and autumn through a gradient of declining temperature. Fish were marked with passive integrated transponders and tracked using a large network of flatbed antennas. High interindividual variability was observed, as some individuals were predominantly nocturnal whereas others frequently changed their daily activity pattern. Overall fish activity decreased with decreasing temperature and increasing flow stage, but most of these changes in daily activity were observed in crepuscular periods. Parr used habitats with lower velocity at night than in the day during the summer, but not in the autumn. Furthermore, there was no difference between day and night habitats for fish that were cathemeral (active both day and night during a given day), so differences between day and night habitats were the result of individuals adopting different activity patterns. These results suggest that habitat interacts with activity pattern, as individuals using suboptimal habitats seem to increase daytime foraging to secure sufficient energy. Temporal and among-fish variability of activity patterns illustrate the dynamic nature of foraging decisions that may partly result from trade-offs experienced at the microhabitat scale.
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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".