Microbial Ecology of Methanotrophy in Streams Along a Gradient of CH4 Availability
Bibliographic record
Abstract
Despite the recognition of streams and rivers as sources of methane (CH4) to the atmosphere, the role of CH4 oxidation (MOX) in these ecosystems remains poorly understood to date. Here, we measured the kinetics of MOX in stream sediments of 14 sites to resolve the ecophysiology of methane oxidizing bacteria (MOB) communities. The streams cover a gradient of landcover and associated physico-chemical parameter and differed in stream- and porewater CH4 concentrations. Michealis-Menten kinetic parameter of MOX, Vmax (maximum rate) and KS (CH4 concentration at half Vmax) increased with CH4 supply. KS values in the micromolar range matched the CH4 concentrations measured in shallow stream sediments and indicate that MOX is mostly driven by low-affinity MOB. 16S rRNA gene sequencing identified MOB classified as Methylococcaceae and particularly Crenothrix. Their relative abundance correlated with pmoA gene counts and MOX rates, underscoring their pivotal role as CH4 oxidizers in stream sediments. Building on the concept of enterotypes, we identify two distinct groups of co-occurring MOB. While there was no taxonomic difference among the members of each cluster, one cluster contained abundant and common MOB, whereas the other cluster contained rare OTUs specific to a subset of streams. These integrated analyses of changes in MOB community structure, gene abundance and the corresponding ecosystem process contribute to a better understanding of the distal controls on methane oxidation in streams.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".