Evidence of Handling Mortality of Adult Chum Salmon Caused by Fish Wheel Capture in the Yukon River, Alaska
Bibliographic record
Abstract
Abstract From 1996 to 1998, marked fish from a mark–recapture experiment were used to examine potential effects of fish wheel capture, handling, and tagging on adult chum salmon Oncorhynchus keta in the Yukon River, Alaska. Four fish wheels equipped with live holding boxes were used to capture fish, two at the marking site and two at the recapture site. During the 3 years of the study we annually marked 8,513–18,632 fish with individually numbered spaghetti tags; annual tag returns external to the mark–recapture experiment (not by project fish wheels) ranged from 594 to 1,007. Individual salmon were captured from one to four times in the four project fish wheels used in the mark–recapture experiment. Tag returns, interviews, carcass surveys, and data from other management projects indicated that the proportion of fish with marks decreased as distance from the marking site increased. Nine possible explanations for these observations were considered, but fish mortality associated with capture and handling appeared to be the most likely cause. Tags returned outside of the mark–recapture experiment were used to investigate the relationship between the capture history within the experiment and upriver recapture. Recapture probabilities declined significantly as the number of times a fish was captured increased. Our results raise concern over the relatively common use of fish wheels for gathering in-season management data and for other research purposes. We recommend more definitive investigation of these phenomena, a review of fish wheel construction and operation to minimize potential effects to salmon populations, reexamination of the efficacy of live box capture as a management tool, and development of alternatives to current live box capture practices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".