The role of methanotrophy in the microbial carbon metabolism of temperate lakes
Bibliographic record
Abstract
Previous stable isotope and biomarker evidence has indicated that methanotrophy is an important pathway in the microbial loop of freshwater ecosystems, despite the low cell abundance of methane-oxidizing bacteria (MOB) and the low methane concentrations relative to the more abundant dissolved organic carbon (DOC). However, quantitative estimations of the relative contribution of methanotrophy to the microbial carbon metabolism of lakes are scarce, and the mechanism allowing methanotrophy to be of comparable importance to DOC-consuming heterotrophy remained elusive. Using incubation experiments, microscopy, and multiple water column profiles in six temperate lakes, we show that MOB play a much larger role than their abundances alone suggest because of their larger cell size and higher specific activity. MOB activity is tightly constrained by the local methane:oxygen ratio, with DOC-rich lakes with large hypolimnetic volume fraction showing a higher carbon consumption through methanotrophy than heterotrophy at the whole water column level. Our findings suggest that methanotrophy could be a critical microbial carbon consumption pathway in many temperate lakes, challenging the prevailing view of a DOC-centric microbial metabolism in these ecosystems.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".