Multiyear Total and Methyl Mercury Exports from Two Major Sub-Arctic Rivers Draining into Hudson Bay, Canada
Bibliographic record
Abstract
From 2003 to 2007, concentrations of total mercury and methylmercury (THg and MeHg) were continuously measured in two Canadian sub-Arctic rivers (the Nelson and the Churchill) that drain into western Hudson Bay. THg and MeHg concentrations were low in the Nelson River (mean i standard deviation, 0.88 +/- 0.33 and 0.05 +/- 0.03 ng L(-1), respectively). The Churchill River, however, had high concentrations of Hg, particularly MeHg (1.96 +/- 0.8 and 0.18 +/- 0.09 ng L(-1), respectively) and hence may be an important source of MeHg to organisms feeding in the Churchill River estuary. A large portion of THg in the Nelson River was particulate-bound (39 +/- 23%), while in the Churchill River, most was in the dissolved form (78 +/- 15%) and is likely dissolved organic carbon (DC)-bound Hg originating in the surrounding wetlands. In fact, both the Nelson and Churchill Rivers had high DOC concentrations and were therefore large exporters of DOC to Hudson Bay (1480 +/- 723 and 392 +/- 309 x 10(3) t year(-1), respectively) compared to rivers to the south and east Despite high Churchill River Hg concentrations, due to large Nelson River flows, average THg and MeHg exports to Hudson Bay from the Churchill River (37 +/- 28 and 4 +/- 4 kg year(-1), respectively) were about one-third and half the Nelson River exports (113 +/- 52 and 9 +/- 4 kg year(-1)). Interestingly, combined Hg exports to Hudson Bay from Nelson and Churchill River discharge are comparable to THg inputs from Hudson Bay springtime snowmelt (177 +/-140 kg year(-1)) but are approximately 13 times greater than MeHg snowmelt inputs (1 +/- 1 kg year(-1)). Although Hg inputs from rivers and snowmelt together may account for a large portion of the THg pool in Hudson Bay, these inputs account for a lesser portion of the MeHg pool, thus highlighting the importance of water column Hg(ll) methylation as a source of MeHg to Hudson Bay marine food webs.
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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 | 0.000 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".