Concentrations and Yields of Mercury, Methylmercury, and Dissolved Organic Carbon From Contrasting Catchments in the Discontinuous Permafrost Region, Western Canada
Bibliographic record
Abstract
Abstract Climate change and permafrost thaw may impact the mobilization of terrestrial dissolved organic carbon (DOC), mercury (Hg), and neurotoxic methylmercury (MeHg) into aquatic ecosystems; thus, understanding processes that control analyte export in northern catchments is needed. We monitored water chemistry for 3 years (2019–2021) at a peatland catchment (Scotty Creek) and a mixed catchment (Smith Creek) in the Dehcho (Northwest Territories), within the discontinuous permafrost zone of boreal western Canada. The peatland catchment had higher DOC and dissolved MeHg, but lower total Hg concentrations (mean ± standard deviation; 19 ± 2.6 mg DOC L −1 ; 0.08 ± 0.04 ng DMeHg L −1 ; 1.1 ± 0.3 ng THg L −1 ) than the mixed catchment (12 ± 4.4 mg DOC L −1 ; 0.05 ± 0.01 ng DMeHg L −1 ; 3.1 ± 2.2 ng THg L −1 ). Analyte concentrations increased with discharge at the mixed catchment, suggesting transport limitation and the flushing of near‐surface, organic‐rich flow paths during wet periods. In contrast, analyte concentrations in the peatland catchment were not primarily associated with discharge. MeHg concentrations, MeHg:THg, and MeHg:DOC increased with water temperature, suggesting enhanced Hg methylation during warmer periods. Mean open water season DOC and total MeHg yields were greater and more variable from the peatland than the mixed catchment (1.1–6.6 vs. 1.4–2.4 g DOC m −2 ; 5.2–36 vs. 6.1–10 ng MeHg m −2 ). Crucial storage thresholds controlling runoff generation likely drove greater inter‐annual variability in analyte yields from the peatland catchment. Our results suggest climate change may influence the production and transport of MeHg from boreal‐Arctic catchments as temperatures increase, peatlands thaw, and runoff generation is altered.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".