Assessment of mercury methylation and methylmercury demethylation potentials in water and sediments along the Wabigoon River system
Bibliographic record
Abstract
Monomethylmercury (MMHg) plays a crucial role in the accumulation of mercury (Hg) within aquatic food chains. Since ambient levels of methylmercury are governed by the balance of simultaneous methylation and demethylation processes, determining in situ methylation and demethylation rates is critically important to understand the dynamics of methylmercury in the environment. This is especially important in the Wabigoon River system in Ontario, Canada, which is severely contaminated with Hg by a chlor-alkali facility operating in the 1960s, and still exhibits some of the highest recorded fish mercury concentrations in Canada. This work used a simultaneous addition of isotope enriched Hg and MMHg tracers to ascertain Hg methylation and MMHg demethylation potentials. At the locations investigated for this study, the most favourable conditions for Hg methylation were found at the Hydroelectric dam, being able to transform 4.2 % and 4.4 % of added Hg in water and sediments per day, respectively, to MMHg. This could correspond to 1.9 ng/L and 29 ng/g of new MMHg being produced from current ambient Hg. Clay Lake, which is considered a sink for mercury and exhibiting a seasonal anoxic environment at its bottom waters, also demonstrated significant MMHg generation, being able to produce 2.7 ng/L and 13 ng/g of MMHg per day, respectively. Demethylation rates in sediments of riverbed and wetland locations showed an average half-life for methylmercury of 2.1 days, indicating a rapid turnover of MMHg in the Wabigoon River. However, significantly lower demethylation rates were also measured near the inflow of Clay Lake, where it took up to 144 days for MMHg to decrease by 50 %. Generally, most of the investigated locations downstream of the pollution source displayed the potential to generate methylmercury, which could be distributed throughout the Wabigoon River system and therefore require attention with respect to future remediation activities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".