Microbial methane cycling in a landfill on a decadal time scale
Bibliographic record
Abstract
Abstract Landfills generate outsized environmental footprints due to microbial degradation of organic matter in municipal solid waste, which produces the potent greenhouse gas methane. With global solid waste production predicted to increase 69% by the year 2050, there is a pressing need to better understand the biogeochemical processes that control microbial methane cycling in landfills. In this study, we had the rare opportunity to characterize the microbial community responsible for methane cycling in landfill waste covering a 39-year timeframe. We coupled long term geochemical analyses to whole-community DNA (i.e., metagenomic) sequencing and identified key features that shape methane cycling communities over the course of a landfill’s lifecycle. Anaerobic methanogenic microbes are more abundant, diverse, and metabolically versatile in newer waste, fueling rapid methane production early in a landfill’s lifecycle. Aerobic methanotrophs were repeatedly found in leachate where low levels of oxygen were present and exhibited adaptations that aid survival under steep redox gradients in landfills. The potential for anaerobic methane oxidation, which has historically been overlooked despite anoxic habitats dominating landfills, was prevalent in a 26-year-old landfill cell which was in a state of slow methanogenesis. Finally, we identified the metabolic potential for methane oxidation in lineages that are widespread in aquatic and terrestrial habitats, whose capacity to metabolize methane remains poorly characterized. Ultimately, this work expands the diversity of methane cycling guilds in landfills and outlines how these communities can curb methane emissions from municipal solid waste. Significance Microbes are major contributors to methane emissions from solid waste however the temporal dynamics of methane cycling communities in landfills remain poorly understood. We addressed this gap by using whole-community DNA (i.e., metagenomic) approaches to characterize microbial methane cycling in waste covering a 39-year timeframe. We show that methane-producing microbes are more abundant, diverse, and metabolically versatile in new waste compared to old waste. We highlight that methane oxidation in the absence of oxygen is overlooked in landfill biogeochemical models and that novel lineages can potentially contribute to methane sinks across a broad range of habitats. These findings can strengthen predictive models for methane cycling in landfills and inform sustainable waste management strategies to curb methane emissions from solid waste.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".