Variation in large‐bodied fish‐community structure and abundance in relation to water‐management regime in a large regulated river
Bibliographic record
Abstract
Variation in life-history traits (growth, condition, mortality and recruitment) and relative abundance of 11 large-bodied fish species was investigated among three water-management regimes (unimpounded, run-of-the-river and winter reservoirs) in the large regulated Ottawa River, Canada. If waterpower management had an effect on fishes, then (1) would be expected community structuring among water-management regimes and (2) species with similar life-history traits should be affected in a similar manner. Large-bodied fish communities were assessed using two different standard index-netting techniques, one using trap nets and the other gillnets. Community structure could be discriminated based on species caught in nets using holographic neural networks (78.8% correct overall classification rate using trap nets and 76.0% using gillnets); therefore, water-management regimes affected community structure in the Ottawa River. Littoral zone benthivores were significantly lower in abundance (P < 0.001) or absent in winter reservoirs, whereas the abundance of planktivores or species that were planktivorous at young ages were significantly greater than in unimpounded river reaches. Growth, condition and mortality did not vary among reach types except smallmouth bass Micropterus dolomieu were in better condition in winter reservoirs than unimpounded reaches. Lake sturgeon Acipenser fulvescens recruitment was impaired in run-of-the-river reaches, whereas recruitment for other species that spawn in fast water was not affected.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".