Biological effectiveness of an inexpensive nature‐like fishway for passage of warmwater fish in a small <scp>O</scp>ntario stream
Bibliographic record
Abstract
Abstract Few studies have been conducted to evaluate the effectiveness of nature‐like fishways, particularly in low gradient warmwater streams with diverse fish communities. We evaluated a nature‐like fishway that was installed to facilitate upstream passage at a low head dam on Indian Creek near Spencerville, Ontario, Canada. A passive integrated transponder (PIT) array was used to quantify attraction and passage efficiency for 391 PIT tagged warmwater fish, represented by seven species. Attraction efficiency for the three most common species, common shiner (Luxilus cornutus), creek chub (Semotilus atromaculatus) and white sucker (Catostomus commersonii), was 63.3%, 83.7% and 65.6%, respectively, and passage efficiencies were 5.1%, 38.4% and 25%, respectively. Creek chub were able to locate the fishway in less time than white sucker and common shiner; however, took longer to successfully pass. Manipulation of creek chub release locations was used to separate issues of attraction and passage and revealed that passage efficiency was highest (76.2%) for those released within the fishway and intermediate for those released at the entrance (42.1%). This multispecies fishway improved stream connectivity, but additional work is needed to fine tune its configuration. Similar projects that engage stakeholders in nature‐like fishway construction are a promising approach for the thousands of small dams that occur on low gradient streams around the globe, but those studies should incorporate a biological evaluation to ensure that attraction and passage efficiency are optimised.
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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".