Deep sea cold seeps are a sink for mercury and source for methylmercury
Bibliographic record
Abstract
Abstract The effect of seafloor cold seeps on the biogeochemical cycling of mercury (Hg) remains enigmatic. Here we demonstrate substantial enrichments of mercury and methylmercury, along with the presence of microbes capable of metabolizing mercury in sediments of the Haima cold seep, South China Sea, by analyzing mercury and methylmercury concentrations, mercury isotopic composition analyses and metagenomic analyses of sediment cores. Compared to the reference area, the sediments in the upper sediment column of the active-seep area were 2.4 times enriched in Hg and 10.5 times in methylmercury. The slope of the capital delta ratio of mercury 199 to mercury 201 (Δ 199 Hg/Δ 201 Hg) with 1.23 ± 0.10 in the active-seep area indicate the occurrence of dark redox reactions. Genes related to mercury methylation ( hgcA ), demethylation ( merB ) and reduction ( merA ) were phylogenetically associated with several bacterial and archaeal linages. We roughly estimated an additional 2,835 Mg mercury and 9 Mg methylmercury are stored in cold seep globally. In summary, we propose that cold seeps globally function as a previously unrecognized sink for mercury and source for methylmercury in the deep ocean.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".