Live fast and die young: accelerated life histories of walleye populations in degraded boreal lakes
Bibliographic record
Abstract
Despite their widespread distribution in North America, many walleye ( Sander vitreus) populations have declined, primarily due to anthropogenic activities (e.g., mining, agriculture, municipal wastewater, aquatic invasive species, and overfishing) that degrade lakes. We compared population structure and dietary composition of walleye in two historically stocked degraded lakes and two naturally recruiting non-degraded lakes in the Abitibi-Témiscamingue region, Québec, Canada. Food resources were assessed for larvae, young-of-the-year (YOY), juveniles, and adults by sampling zooplankton, macroinvertebrates, and prey fish. Growth and relative abundance were quantified via electrofishing for YOY, gillnets for older fish, and otolith age reading. YOY were more abundant and grew faster in degraded lakes, benefiting from high spring zooplankton availability. Simplified food webs in degraded lakes lacked pollution-sensitive macroinvertebrates, making walleye diets more fish-dominated. Although juveniles and adults were equally or more abundant in degraded lakes, premature adult mortality compromised population stability. We recommend improving adult habitat, managing prey species, and reviewing fishing regulations to enhance survival of mature walleye and support 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 | 0.001 |
| 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".