Methylmercury production in a Chesapeake Bay salt marsh
Why this work is in the frame
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Bibliographic record
Abstract
In a detailed study of the biogeochemical factors affecting the methylation of mercury in a Chesapeake Bay salt marsh, we examined relationships between mercury methylation and numerous variables, including sulfate reduction rates, organic carbon mineralization rates, iron and sulfur chemistry, and the character of dissolved organic matter (DOM). Our data show that salt marshes are important sites of de novo methylmercury (MeHg) production in coastal ecosystems. Some of the controls on MeHg production that have been well‐described in other ecosystems also impacted MeHg production in this salt marsh, specifically the effect of sulfide accumulation on mercury bioavailability. We observed some novel biogeochemical relationships with Hg(II)‐methylation and MeHg accumulation, particularly the positive association of Hg(II)‐methylation with zones of microbial iron reduction. On the basis of this relationship, we suggest caution in wetland and groundwater remediation approaches involving iron additions. Aqueous phase Hg complexation appeared to be the dominant control on Hg bioavailability across the marsh sites examined, rather than Hg partitioning behavior. A detailed examination of DOM character in the marsh suggested a strong positive association between Hg(II)‐methylation rate constants and increasing DOM molecular weight. Overall, our results indicate that net MeHg production is controlled by a balance between microbial activity and geochemical effects on mercury bioavailability, but that a significant zone of MeHg production can persist in near surface salt marsh soils. Production of MeHg in coastal marshes may negatively impact ecosystems via export to adjacent estuaries or through direct bioaccumulation in birds, fish and amphibians that feed in these highly productive ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 it