Multi-Year (2007-2017) Mercury (Hg) Concentration and Fluxes From Small High Arctic Rivers Impacted by Landscape Disturbance
Bibliographic record
Abstract
Arctic mercury (Hg) contamination is an ongoing threat to human populations and ecosystems alike. Compared to preindustrial levels, elevated concentrations of Hg in air and water samples have been observed across the high latitudes with recent estimates demonstrating substantial Hg storage in Arctic soils. Climate change is expected to have a strong impact on the stability of permafrost landscapes potentially releasing large quantities of Hg from thawed soils to surface waters. This study investigates multi-year, seasonal, and diel dynamics of total mercury (THg) and methyl mercury (MeHg) concentrations, particulate partitioning, and flux from two small High Arctic rivers, subject to permafrost disturbance, at the Cape Bounty Arctic Watershed Observatory, Nunavut, Canada. Water samples were collected from the outlet of the rivers during the melt season (2007-2017; excluding 2011, 2013-2015), and from several small hillslope tributaries with various levels of permafrost disturbance (2009, 2016, 2017). Results indicate that there are large diel and inter-annual variations in THg concentration and flux, in part due to climate-driven changes in discharge and the physical disturbance of active layer and permafrost soils. A large proportion of THg (30.5-72.5%) was particulate bound, and significant positive relationships were observed between THg, suspended sediment, discharge, and organic carbon concentrations in both rivers. MeHg concentrations were low for both rivers (0.05 ng L-1) and were poorly correlated with discharge, suspended sediment concentration or organic carbon. The timing and intensity of runoff was a dominant driver of THg flux in all years with the majority of discharge and peak THg concentrations occurring during either the brief nival freshet or uncommon late season rainfall events. These results provide a critical link between Hg stored in Arctic soils, permafrost disturbance and fluvial Hg export, with important implications for Hg cycling in a changing Arctic.
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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 | 0.001 | 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".