The effects of hydrologic fluctuation and sulfate regeneration on mercury cycling in an experimental peatland
Bibliographic record
Abstract
Abstract A series of severe droughts during the course of a long‐term, atmospheric sulfate‐deposition experiment in a boreal peatland in northern Minnesota created a unique opportunity to study how methylmercury (MeHg) production responds to drying and rewetting events in peatlands under variable levels of sulfate loading. Peat oxidation during extended dry periods mobilized sulfate, MeHg, and total mercury (HgT) to peatland pore waters during rewetting events. Pore water sulfate concentrations were inversely related to antecedent moisture conditions and proportional to past and current levels of atmospheric sulfate deposition. Severe drying events caused oxidative release of MeHg to pore waters and resulted in increased net MeHg production likely because available sulfate stimulated the activity of sulfate‐reducing bacteria, an important group of Hg‐methylating bacteria in peatlands. Rewetting events led to increased MeHg concentrations across the peatland, but concentrations were highest in peat receiving elevated atmospheric sulfate deposition. Dissolved HgT concentrations also increased in peatland pore waters following drought but were not affected by sulfate loading and did not appear to be directly controlled by dissolved organic carbon mobilization to peatland pore waters. Peatlands are often considered to be sinks for sulfate and HgT in the landscape and sources of MeHg. Hydrologic fluctuations not only serve to release previously sequestered sulfate and HgT from peatlands but may also increase the strength of peatlands as sources of MeHg to downstream aquatic systems, particularly in regions that have experienced elevated levels of atmospheric sulfate deposition.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".