Methane emissions may be driven by hydrogenotrophic methanogens inhabiting the stem tissues of poplar
Bibliographic record
Abstract
Summary Living trees in forests emit methane (CH4) from their stems. However, the magnitudes, patterns, drivers, origins, and biogeochemical pathways of these emissions remain poorly understood. We measured in situ CH4 fluxes in poplar stems and soils using static chambers and investigated the microbial communities of heartwood and sapwood by sequencing bacterial 16S, archaeal 16S, and fungal ITS rRNA genes. Methane emissions from poplar stems occurred throughout the sampling period. The mean CH4 emission rate was 2.7 mg m−2 stem d−1. Stem CH4 emission rate increased significantly with air temperature, humidity, soil water content, and soil CH4 fluxes, but decreased with increasing sampling height. The CO2 reduction and methylotrophic methanogenesis were the major methanogenic pathways in wood tissues. The dominant methanogen groups detected in stem tissues were Methanobacterium, Methanobrevibacter, Rice Cluster I, Methanosarcina, Methanomassiliicoccus, Methanoculleus, and Methanomethylophilaceae. In addition, three methanotrophic genera were identified in the heartwood and sapwood – Methylocystis, Methylobacterium, and Paracoccus. Overall, stem CH4 emissions can originate directly from the internal tissues or co‐occur from soils and stems. The co‐existence of methanogens and methanotrophs within heartwood and sapwood highlights a need for future research in the microbial mechanisms underlying stem CH4 exchange with the atmosphere.
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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) | 0.000 | 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 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".