Methanotroph Dynamics at Landfill Cover Soil Methane Emission Hotspots
Bibliographic record
Abstract
Abstract Landfills contribute significant emissions to the global methane cycle, where emission hotspots can account for the majority of methane released. Methanotrophs in landfill cover soils can mitigate these methane emissions, but are constrained by geochemical conditions in the soils and the climate at the landfill’s location. We sampled cover soils from four Ontario landfills with differing characteristics, including measurements of methane flux, soil methane concentration, and a suite of geochemical variables. Sampling sites were distinguished based on the levels of methane flux. Microbial community diversity and methanotroph dynamics were examined using 16S rRNA gene amplicon sequencing. Sites with high methane emissions showed strong enrichment of methanotrophs, dominated by the genus Methylomicrobium . The distribution of methanotrophs in samples across landfills and sites differed significantly when considering community evenness. Of the environmental factors examined, microbial community diversity correlated most strongly to nitrate and nitrite concentrations. Methanotroph dynamics across different methane exposures and geochemical conditions within landfill cover soils inform the use of designer cover soils and/or methanotroph amendments in efforts toward mitigating methane emissions from landfills.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".