Environmental, anthropogenic, and dietary influences on fine-scale movement patterns of Atlantic salmon through challenging waters
Bibliographic record
Abstract
Partial barriers to migration can affect migratory fish population dynamics and be influenced by many biotic, abiotic, and anthropogenic factors, including nutritional deficiencies. We investigated how such variables (including a thiamine deficiency) impact fine-scale movement of landlocked Atlantic salmon (Salmo salar) by treating returning spawners with thiamine and observing their attempts to climb a human-altered, high velocity stretch of river using fine-scale radio telemetry. Multiple re-entries into a river section, along with water temperature, strongly influenced movement rates. High or increasing discharge encouraged downstream movement; males abandoned migratory attempts at a higher rate than females. Although thiamine-injected salmon exhibited greater migratory duration, this did not produce a measurable improvement in passage performance, possibly due to the difficulty associated with this section of river — among 24 tagged salmon staging 10.9 attempts each and lasting 1.5 days per attempt on average, only three traversed the entire reach. This study provides new insights into how biotic and abiotic variables affect fish movement, while suggesting limits to the potential for human intervention (thiamine injections) to assist passage through partial migratory barriers.
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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".