Mercury stocks in discontinuous permafrost and their mobilization by river migration in the Yukon River Basin
Bibliographic record
Abstract
Abstract Rapid warming in the Arctic threatens to destabilize mercury (Hg) deposits contained within soils in permafrost regions. Yet current estimates of the amount of Hg in permafrost vary by ∼4 times. Moreover, how Hg will be released to the environment as permafrost thaws remains poorly known, despite threats to water quality, human health, and the environment. Here we present new measurements of total mercury (THg) contents in discontinuous permafrost in the Yukon River Basin in Alaska. We collected riverbank and floodplain sediments from exposed banks and bars near the villages of Huslia and Beaver. Median THg contents were 49+13/−21 ng THg g sediment−1 and 39+16/−18 ng THg g sediment−1 for Huslia and Beaver, respectively (uncertainties as 15th and 85th percentiles). Corresponding THg:organic carbon ratios were 5.4+2.0/−2.4 Gg THg Pg C−1 and 4.2 +2.4/−2.9 Gg THg Pg C−1. To constrain floodplain THg stocks, we combined measured THg contents with floodplain stratigraphy. Trends of THg increasing with smaller sediment size and calculated stocks in the upper 1 m and 3 m are similar to those suggested for this region by prior pan-Arctic studies. We combined THg stocks and river migration rates derived from remote sensing to estimate particulate THg erosional and depositional fluxes as river channels migrate across the floodplain. Results show similar fluxes within uncertainty into the river from erosion at both sites (95+12/−47 kg THg yr−1 and 26+154/−13 kg THg yr−1 at Huslia and Beaver, respectively), but different fluxes out of the river via deposition in aggrading bars (60+40/−29 kg THg yr−1 and 10+5.3/−1.7 kg THg yr−1). Thus, a significant amount of THg is liberated from permafrost during bank erosion, while a variable but generally lesser portion is subsequently redeposited by migrating rivers.
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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 | 0.000 | 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 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".