PERFORMANCE OF FISH PASSAGE STRUCTURES AT UPSTREAM BARRIERS TO MIGRATION
Bibliographic record
Abstract
ABSTRACT Attraction and passage efficiency were reviewed and compared from 19 monitoring studies that produced data for evaluations of pool‐and‐weir, Denil, vertical‐slot and nature‐like fishways. Data from 26 species of anadromous and potamodromous fishes from six countries were separated by year and taxonomic family into a matrix with 101 records. Attraction performance was highly variable for the following fishway structures: pool‐and‐weir (attraction range = 29–100%, mean = 77%, median = 81%), vertical‐slot (attraction range = 0–100%, mean = 63%, median = 80%), Denil (attraction range = 21–100%, mean = 61%, median = 57%) and nature‐like (attraction range = 0–100%, mean = 48%, median = 50%). Mean passage efficiency was inversely related to mean attraction efficiency by fishway structure type, with the highest passage for nature‐like fishways (range = 0–100%, mean = 70%, median = 86%), followed by Denil (range = 0–97%, mean = 51%, median = 38%), vertical‐slot (range = 0–100%, mean = 45%, median = 43%) and pool‐and‐weir (range = 0–100%, mean = 40%, median = 34%). Principal components analysis and logistic regression modelling indicated that variation in fish attraction was driven by biological characteristics of the fish that were studied, whereas variation in fish passage was related to fishway type, slope and elevation change. This meta‐analysis revealed that the species of fish monitored and structural design of the fishways have strong implications for both attraction and passage performance, and in most cases, existing data are not sufficient to support design recommendations. Many more fishway evaluations are needed over a range of species, fishway types and configurations to characterize, to optimize and to design new fishways. Furthermore, these studies must be performed in a consistent manner to identify the relative contributions of fish attraction and passage to overall fishway performance at each site. Copyright © 2011 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".