On the interaction of turbulent flow and feeding behaviour of juvenile Atlantic Salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Anthropogenic activities can dramatically modify the riverine habitat of juvenile Atlantic salmon (Salmo salar). In the perspective of protecting and restoring the fluvial habitat, bioenergetic models are often used to estimate fish habitat quality. These models determine the habitat quality as the ratio between the energetic gains (food) and costs (growth, metabolism) of a fish. The energetic costs of swimming in a river are generally estimated using the average flow velocity without consideration of the effect of turbulence. Juvenile Atlantic salmon (JAS) live in rivers characterized by intense velocity fluctuations, which are often described as a succession of high‐ and low‐speed flow regions. These flow structures are likely to affect the JAS activity that consists of long periods of sit‐and‐wait at the top of a protuberant rock interrupted by short bursting motions to capture drifting food particles. To minimize the energetic costs, it is hypothesized that JAS use low‐speed flow regions to initiate and undertake their feeding motions. To improve bioenergetic modelling, this study aimed at analyzing the relation between turbulent flow structures and the feeding behaviour of JAS in a natural gravel‐bed river. We filmed eight JAS during 30 min with a submersible video camera while simultaneously measuring velocity fluctuations close to the fish in the St. Marguerite River, Quebec, Canada. Our results show that the proportion of time used for feeding motions decreases with increasing turbulent intensity and mean flow velocity; and that JAS do not seem to prefer low‐speed flow regions to initiate their feeding motions.
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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".