Unexplained Variation in Movement by Walleye and Sauger after Catch-and-Release Angling Tournaments
Bibliographic record
Abstract
Abstract Walleye Sander vitreus is a popular species for catch-and-release angling tournaments in North America, but we currently know little about the postrelease behavior of this species and the congeneric Sauger S. canadensis. We used radiotelemetry and acoustic telemetry to track Walleyes (n = 101) and Saugers (n = 19) for 7 d after release at tournaments in Saskatchewan. Our objectives were to provide a description of postrelease movements, and examine the influence of handling variables and stress scores on movement. Walleyes made highly variable movements over 7 d, and total dispersal ranged from less than 100 m to over 28 km from the release point. Path lengths—the cumulative distance between start and end points—were considerably longer than straight-line dispersal. Walleyes made larger movements than Saugers, with average total dispersal values of 6.1 ± 6.9 km (mean ± SD) and 1.3 ± 1.8 km, respectively. Multivariate modeling revealed that species and tournament were the only important factors affecting movement. Fish size (TL), capture depth, distance transported, and time spent in a live well were not consistently important predictors of postrelease movement. Walleyes and Saugers moved much smaller distances when they had poor outcomes for the reflex action mortality predictor (RAMP) test, but RAMP scores in general did not explain a significant proportion of the variance in any fish movement metric. Swim scores at the time of release, an alternative metric of stress, also did not explain a significant proportion of variance in fish movement. Our results show intriguing variance in the behavioral response of individual Walleyes and Saugers to catch and release at tournaments, but do not identify causal factors.
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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 | 0.001 |
| 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".