Effects of a decade of selenium emission reductions on mercury accumulation in aquatic biota in the Sudbury region of Ontario
Bibliographic record
Abstract
Control of smelting emissions in the Sudbury (Ontario, Canada) area has dramatically decreased the amount of selenium (Se) deposited onto the surrounding landscape. Historically, Se emissions in Sudbury correlated with lower total mercury (Hg) and methylmercury levels (MeHg) in tissues of zooplankton, amphipods (Hyalella azteca), mayflies (Stenonema femoratum), and young-of-the-year perch (Perca flavescens). In 2017, ten years following emission reductions, we evaluated whether changes in Se deposition affected total Hg and MeHg burden in lake biota. We show that total Se concentrations in the water of the majority of lakes have increased despite decreases in Se depositions, most likely due to the long residence time of Se in the watershed and the water column. As a result, Se in water continues to correlate with lower total Hg and MeHg accumulation in tissues of zooplankton, amphipods, mayflies, and perch. These results suggest that Se continues to exhibit a protective effect on Hg accumulation in biota, even years after emissions have greatly decreased. We expect this work to inform efforts aiming at long-term recovery of aquatic environments affected by smelter emissions and aid in designing remediation strategies involving Se additions.
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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 | 0.001 | 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".