Lake characteristics influence how methanogens in littoral sediments respond to terrestrial litter inputs
Bibliographic record
Abstract
Abstract Shallow lake sediments harbor methanogen communities that are responsible for large amounts of CH4 flux to the atmosphere. These communities play a major role in degrading in-fluxed terrestrial organic matter (t-OM)—much of which settles in shallow near-shore sediments. Little work has examined how sediment methanogens are affected by the quantity and quality of t-OM, and the physicochemical factors that shape their community. Here, we filled mesocosms with artificial lake sediments amended with different ratios and concentrations of coniferous and deciduous tree litter. We installed them in three boreal lakes near Sudbury, Canada that varied in trophic status and water clarity. We found that higher endogenous nutrient concentrations led to greater CH4 production when sediment solar irradiance was similar, but high irradiance of sediments also led to higher CH4 concentrations regardless of nutrient concentrations, possibly due to photooxidation of t-OM. Sediments with t-OM had overall higher CH4 concentrations than controls that had no t-OM, but there were no significant differences in CH4 concentrations with different t-OM compositions or increasing concentrations over 25%. Differences among lakes also explained variation in methanogen community structure, whereas t-OM treatments did not. Therefore, lake characteristics are important modulators of methanogen communities fueled by t-OM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".