Movement of Walleyes in Lakes Erie and St. Clair Inferred from Tag Return and Fisheries Data
Bibliographic record
Abstract
Abstract Lake Erie walleyes Sander vitreus support important fisheries and have been managed as one stock, although preliminary tag return and genetic analyses suggest the presence of multiple stocks that migrate among basins within Lake Erie and into other portions of the Great Lakes. We examined temporal and spatial movement and abundance patterns of walleye stocks in the three basins of Lake Erie and in Lake St. Clair with the use of tag return and sport and commercial catch‐per‐unit effort (CPUE) data from 1990 to 2001. Based on summer tag returns, western basin walleyes migrated to the central and eastern basins of Lake Erie and to Lake St. Clair and southern Lake Huron, while fish in the central and eastern basins of Lake Erie and in Lake St. Clair were primarily caught within the basins where they were tagged. Seasonal changes in sport and commercial effort and CPUE in Lake Erie confirmed the walleye movements suggested by tag return data. Walleyes tagged in the western basin but recaptured in the central or eastern basin of Lake Erie were generally larger (or older) than those recaptured in the western basin of Lake Erie or in Lake St. Clair. Within spawning stocks, female walleyes had wider ranges of movement than males and there was considerable variation in movement direction, minimum distance moved (mean distance between tagging sites and recapture locations), and mean length among individual spawning stocks. Summer temperatures in the western basin often exceeded the optimal temperature (20–23°C) for growth of large walleyes, and the migration of western basin walleyes might represent a size‐dependent response to warm summer temperatures. Cooler temperatures and abundant soft‐rayed fish probably contributed to an energetically favorable foraging habitat in the central and eastern basins that attracted large walleyes during summer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".