Migratory delay leads to reduced passage success of Atlantic salmon smolts at a hydroelectric dam
Bibliographic record
Abstract
Abstract Passage of fish through hydropower dams is associated with mortality, delay, increased energy expenditure and migratory failure for migrating fish and the need for remedial measures for both upstream and downstream migration is widely recognised. A functional fish passage must ensure safe and timely passage routes that a substantial portion of migrating fish will use. Passage solutions must address not only the number or percentage of fish that successfully pass a barrier, but also the time it takes to pass. Here, we used radiotelemetry to study the functionality of a fish bypass for downstream‐migrating wild‐caught and hatchery‐released Atlantic salmon smolts. We used time‐to‐event analysis to model the influence of fish characteristics and environmental variables on the rates of a series of events associated with dam passage. Among the modelled events were approach rate to the bypass entry zone, retention rates in both the forebay and the entry zone and passage rates. Despite repeated attempts, only 65% of the tagged fish present in the forebay passed the dam. Fish passed via the bypass (33%), via spill (18%) and via turbines (15%). Discharge was positively related to approach, passage and retention rates. We did not detect any differences between wild and hatchery fish. Even though individual fish visited the forebay and the entry zone on multiple occasions, most fish passed during the first exposures to these zones. This study underscores the importance of timeliness to passage success and the usefulness of time‐to‐event analysis for understanding factors governing passage performance.
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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) | 0.002 | 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".