MULTISPECIES FISH PASSAGE BEHAVIOUR IN A VERTICAL SLOT FISHWAY ON THE RICHELIEU RIVER, QUEBEC, CANADA
Bibliographic record
Abstract
ABSTRACT A shift from target species to ecosystem restoration has generated interest in developing fishways that are capable of passing entire fish communities. Although a number of multispecies fishways now exist in North America, evaluations of these fishways are lacking. We used a passive integrated transponder antenna array to quantify passage success and passage duration of fish using a vertical slot fishway (85 m in length, 2.65 m elevation rise, 12 regular pools and 2 turning basins) at a low head dam on the Richelieu River in Quebec, Canada. Fourteen of the 18 tagged species re‐ascended the fishway, and passage efficiency was highly variable among species (range 25%–100%); however, it was >50% for five of the species well represented in this study (n > 10) (Atlantic salmon, channel catfish, smallmouth bass, walleye and white sucker). Passage duration was likewise highly variable both among and within species (e.g. 1.0–452.9 h for smallmouth bass, 2.4–237.5 h for shorthead redhorse). Although this fishway design was not uniformly successful in passing fish of all species, this study does reveal the species that have problems with ascent and provides an estimate on the time spent in the fishway that is an important component of passage delay. Such information could be used to inform future design refinements to facilitate passage of the entire assemblage with minimal delay. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".