Elevated atmospheric CO2 decreases methylmercury production in freshwater lakes
Bibliographic record
Abstract
Abstract Elevated atmospheric carbon dioxide (CO 2 ) level reshapes microbial communities in nature, yet its consequences for neurotoxic methylmercury (MeHg) production in waters remain unclear. Here, we show that elevated CO 2 levels (650 and 1000 ppm) consistently reduced net MeHg production across 45 freshwater lakes spanning 1200 longitudinal kilometers, particularly in eutrophic conditions (54–96%). Elevated CO 2 -driven shifts in carbon substrates favored hydrogenotrophic methanogens (e.g., Methanobacterium ) lacking the hgcA methylation gene over hgcA -harboring acetoclastic strains (e.g., Methanosarcina ), decreasing methanogen abundance (18–98% in hgcA copies) and activity (13–53% in net CH 4 production) and suppressing Hg methylation. Model simulations predict a 33%–74% global decline in lake MeHg production under future CO 2 scenarios, partially counteract MeHg increases associated with intensified algal blooms under warming. This overlooked pathway highlights the need to integrate interacting climate drivers to improve predictions of MeHg risks in a climate-changing future.
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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 | 0.000 | 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) | 0.001 | 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".