Effects of river flow on walleye (<i>Sander vitreus</i>) recruitment in the Saskatchewan River Delta
Bibliographic record
Abstract
Alteration of natural flow regimes is affecting freshwater fish populations. For example, the walleye ( Sander vitreus) fishery in the Saskatchewan River Delta has declined since the mid-1990s, which may be related to changes to flow regimes due to upstream dams. To test this hypothesis, walleye age data obtained from otoliths collected through sustenance and commercial fishing were used in a generalized linear mixed model catch-curve analysis to test the relationship between discharge during predefined biologically significant periods and walleye recruitment. The best fit model identified that the fry growth period (weeks 30–42) had a positive relationship between river discharge and future recruits. Based on the estimated Bayesian posterior distribution, there was a very high probability ( p > 0.99) that the effect was different from zero. This effect had an estimated 69% increase (28%–105% credible interval) in recruitment with every 100 m3·s−1 increase in discharge over the fry growth period. These findings support previous work on walleye recruitment in another northern freshwater delta and will inform water resource management in these systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".