Intensity and duration of effects of impoundment on mercury levels in fishes of hydroelectric reservoirs in northern Québec (Canada)
Bibliographic record
Abstract
At the La Grande Hydroelectric Complex (Québec, Canada), total mercury (THg) levels in fish were monitored from 1978 to 2012 in more than 37 000 fish comprising 5 species: lake whitefish (Coregonus clupeaformis), longnose sucker (Catostomus catostomus), northern pike (Esox lucius), walleye (Sander vitreus), and lake trout (Salvelinus namaycush). In reservoirs, concentrations of all species increased rapidly after impoundment, peaking after 4–11 yr in nonpiscivorous species and after 9–14 yr in piscivorous species, at levels 2–8 times higher than those measured in surrounding natural lakes. In fish of standardized length, maximum levels reached 0.33–0.72 μg g−1 in nonpiscivorous species and 1.65–4.66 μg g−1 in piscivorous species. Depending on the reservoir, the return to levels equivalent (p < 0.05) to those found in fish in surrounding natural lakes was completed after 10–20 yr for all nonpiscivorous species and after 20– 31 yr in most piscivorous species, if no additional flooding occurred. These results tend to confirm the findings of other authors suggesting that the following reservoir characteristics play a major role in determining the intensity and duration of after-impoundment THg increases in fish: flooded area, annual volume of water flowing through the reservoir, filling period, water temperature, and percentage of flooded area located in the drawdown zone.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".