Factors contributing to elevated levels of methyl and total mercury related to alteration in wetland conditions and agricultural activity (the Raisin River watershed)
Bibliographic record
Abstract
Seasonal and spatial patterns of methyl and total mercury and nutrient concentrations were measured during 2005--2007 in the Raisin River, North-west of Cornwall, Ontario, Canada (75°44' W, 45°08' S) to determine if inputs from farming activities or altered wetlands (Newington Bog and Monkland Drain) are contributing to the contamination of the River. Water samples were analyzed using atomic fluorescence gas chromatography for methyl mercury; a Tekran 2600 mercury analyzer for total mercury; and a Lachat Nutrient Analyzer 8000 QuikChem for nitrate, ammonia, sulphate, and total phosphorus. Land features from the Ontario Ministry of Natural Resources and local precipitation data from the City of Cornwall were used. Kruskal-Wallis and Spearman statistical analyses were applied. MeHg and THg concentrations in the 5 Divisions of the Raisin River ranged from 0.03--1.02 ng L -1 and 0--7.57 ng L-1 respectively. MeHg concentrations in the peatlands were in the range of ∼0.10 to 2.29 ng L-1, with the highest observed at the Newington Bog in May 2007. Nutrient concentrations in the Raisin River were high with ammonia ranging to 263 mug L-1, nitrate to 2575 mug L -1, and total phosphorus to 162 mug L-1. The statistical analyses support a seasonal variation of MeHg and THg in the Raisin River, but not a spatial trend for MeHg, for % of THg as MeHg, THg and for the Peatland sites. Significantly positive correlations of MeHg and THg with nutrients exist. Yield data identifies the drained peatland in the headwater regions as the major source of mercury to the river with little, if any, influence of the elevated nutrient levels found along the river. Considerations of the yield data and land features suggest that agricultural activities, including runoffs and inputs from residential/community activities in upstream towns can influence nutrients and mercury levels in water systems.
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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 | 0.001 |
| 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".