Potential for Mercury Reduction by Microbes in the High Arctic
Bibliographic record
Abstract
The contamination of polar regions due to the global distribution of anthropogenic pollutants is of great concern because it leads to the bioaccumulation of toxic substances, methylmercury among them, in Arctic food chains. Here we present the first evidence that microbes in the high Arctic possess and express diverse merA genes, which specify the reduction of ionic mercury [Hg(II)] to the volatile elemental form [Hg(0)]. The sampled microbial biomass, collected from microbial mats in a coastal lagoon and from the surface of marine macroalgae, was comprised of bacteria that were most closely related to psychrophiles that had previously been described in polar environments. We used a kinetic redox model, taking into consideration photoredox reactions as well as mer-mediated reduction, to assess if the potential for Hg(II) reduction by Arctic microbes can affect the toxicity and environmental mobility of mercury in the high Arctic. Results suggested that mer-mediated Hg(II) reduction could account for most of the Hg(0) that is produced in high Arctic waters. At the surface, with only 5% metabolically active cells, up to 68% of the mercury pool was resolved by the model as biogenic Hg(0). At a greater depth, because of incident light attenuation, the significance of photoredox transformations declined and merA-mediated activity could account for up to 90% of Hg(0) production. These findings highlight the importance of microbial redox transformations in the biogeochemical cycling, and thus the toxicity and mobility, of mercury in polar regions.
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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 | 0.000 | 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".