Climate change and mercury in the Arctic: Abiotic interactions
Bibliographic record
Abstract
Dramatic environmental shifts are occuring throughout the Arctic from climate change, with consequences for the cycling of mercury (Hg). This review summarizes the latest science on how climate change is influencing Hg transport and biogeochemical cycling in Arctic terrestrial, freshwater and marine ecosystems. As environmental changes in the Arctic continue to accelerate, a clearer picture is emerging of the profound shifts in the climate and cryosphere, and their connections to Hg cycling. Modeling results suggest climate influences seasonal and interannual variability of atmospheric Hg deposition. The clearest evidence of current climate change effects is for Hg transport from terrestrial catchments, where widespread permafrost thaw, glacier melt and coastal erosion are increasing the export of Hg to downstream environments. Recent estimates suggest Arctic permafrost is a large global reservoir of Hg, which is vulnerable to degradation with climate warming, although the fate of permafrost soil Hg is unclear. The increasing development of thermokarst features, the formation and expansion of thaw lakes, and increased soil erosion in terrestrial landscapes are increasing river transport of particulate-bound Hg and altering conditions for aquatic Hg transformations. Greater organic matter transport may also be influencing the downstream transport and fate of Hg. More severe and frequent wildfires within the Arctic and across boreal regions may be contributing to the atmospheric pool of Hg. Climate change influences on Hg biogeochemical cycling remain poorly understood. Seasonal evasion and retention of inorganic Hg may be altered by reduced sea-ice cover and higher chloride content in snow. Experimental evidence indicates warmer temperatures enhance methylmercury production in ocean and lake sediments as well as in tundra soils. Improved geographic coverage of measurements and modeling approaches are needed to better evaluate net effects of climate change and long-term implications for Hg contamination in the Arctic.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".