Autumn electrofishing reduces harm to Ontario (Canada) stream fishes collected during watershed health monitoring
Bibliographic record
Abstract
Electrofishing surveys provide important information on watershed health, and the status of imperiled and recreationally important stream fishes. Concerns about the harmful effects of electrofishing on the endangered redside dace Clinostomus elongatus have resulted in restrictions on its use in sampling activities in the province of Ontario, Canada. However, the effectiveness of these restrictions is unproven. We undertook a paired sampling gear study in 2018-2019 to test whether an alternate gear (seine nets) or a change in electrofishing timing (autumn rather than summer) reduced harm to stream fishes. The study took place in streams located in the Greater Toronto Area. We found large differences in the frequency and magnitude of sampling-related mortalities between sampling gear and seasons. During individual surveys, electrofishing mortality never exceeded 9% in the summer or 4% in the autumn, while seining-related mortality reached 60% at two stream sites. Overall, autumn electrofishing resulted in mortality rates that were 5.6 and 15 times lower than summer electrofishing and summer seining. These results indicate that survival of Ontario stream fishes can be improved by delaying electrofishing until early autumn.
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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 | 0.001 | 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".