Vulnerability to harvest by anglers differs across climate, productivity, and diversity clines
Bibliographic record
Abstract
We contrast catchability of walleye (Sander vitreus) and northern pike (Esox lucius) populations with angling fisheries across regions that differ twofold in growing-degree-days and productivity and sixfold in fish diversity. Populations of both species in Alberta, Wisconsin, Minnesota, and Oneida Lake, New York, had density-dependent catchability with approximately tenfold higher catchability in Alberta than in the other regions when density was controlled for. There is no evidence that the higher catchability estimates for Alberta walleye and northern pike are due to differential spatial distributions, enhanced hook avoidance due to catch and release or to differential size structure of the populations, or to differences in harvest regulations. We argue that the most likely explanation for the tenfold higher catchability is increased hunger resulting in enhanced foraging activity in the region with a substantially shorter growing season, lower prey productivity, and lower prey community diversity. Regardless of the proximate causes, higher catchability of fish harvested in recreational fisheries in Alberta substantially increases their vulnerability to overharvest and collapse if angling effort is unabated.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".