Consequences of fish stocking density in a recreational fishery
Bibliographic record
Abstract
Density-dependent processes resulting from fish stocking were demonstrated to have a significant impact on recreational fishery performance, and this case study will be of use to guide fish stocking decisions in other fisheries. We evaluated a put-grow-and-take lake fishery stocking program for Chinook salmon (Oncorhynchus tshawytscha) located in south-western Victoria, Australia. We hypothesised that recreational fishery performance would show significant density-dependent relationships with fish stocking. To test this hypothesis, we used Wald F tests in a general linear regression model to evaluate relationships between a long-term historical fish stocking program and fishery performance, including angler and net catch rates and weight, length, and condition of caught fish. Our results yielded (i) significant positive relationships between angler and net catch rate of Chinook salmon with the number of Chinook salmon stocked in the same year and (ii) significant negative relationships between the weight of angler-caught Chinook salmon with both the number of Chinook salmon stocked in the same year and total number of fish stocked (apart from Chinook salmon) over the previous three year period.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".