Live fast and die young: walleye populations adapt their life cycle to degraded lakes of the Canadian clay belt
Bibliographic record
Abstract
Abstract Despite its widespread distribution in North America, many populations of walleye ( Sander vitreus ) declined to the point where restoration measures, including restocking, are necessary. In this study, we compared population structure and dietary composition of walleye populations in two degraded lakes and two non-degraded lakes in the Abitibi-Témiscamingue region of Quebec, Canada. Food resources were assessed for walleye larvae, young-of-the-year, juveniles, and adults. Growth and relative abundance were also quantified for young-of-the-year, juvenile, and adult walleye. Young-of-the-year were more abundant and grew faster in degraded lakes compared to non-degraded controls, benefiting from high populations of spring zooplankton, which are a critical larval resource. The simplified food webs in degraded lakes lacked pollution-sensitive macroinvertebrates, which resulted in walleye diets being even more dominated by fish. Although juveniles and adults were equally or more abundant in degraded lakes compared to control lakes, premature adult mortality compromised population stability. We recommend focusing on improving adult fish habitat, manage for prey species, and review fishing regulations to enhance the survival of mature walleye and ensure sustainable populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".