Geochemical controls on anaerobic organic matter decomposition in a northern peatland
Bibliographic record
Abstract
The decomposition of deep peat deposits controls the long‐term carbon balance of peatlands but is poorly understood with respect to rates and controls. To rectify this deficiency, we estimated in situ dissolved inorganic carbon (DIC) and methane (CH4) production rates from a beaver pond to a central bog dome and related them to organic matter properties, Gibbs free energies of respiration, and δ13C values of DIC and CH4. DIC and CH4 production decreased from maxima of ~10 nmol cm‐3 d‐1 near the water table to values <0.1 nmol cm‐3 d‐1 at depths >1 m, and there was little differentiation among sites. Deeper into the peat, we measured an accumulation of DIC, CH4, and dissolved organic matter (DOM) enriched in aromatic and phenolic moieties, which resulted from the slowness of diffusive vertical pore‐water movement. Lack of transport may have slowed decomposition in two ways: (1) Aromatic and phenolic DOM moieties accumulated, while the release of carbohydrate‐rich DOM from peat was apparently impeded. (2) The accumulation of DIC and CH4 reduced Gibbs free energy of acetoclastic methanogenesis toward a critical threshold value of ‐25 to ‐20 kJ mol‐1 CH4. Hydrogenotrophic methanogenesis was energetically more favorable and generally dominated according to an isotopic fractionation between CO2 and CH4 of 1.053 to 1.076, but it was apparently impeded by some other factor. We conclude that lateral homogeneity and slowness of decomposition in geologically sealed deep peat deposits are assisted by a lack of solute transport, which facilitates the formation of deep peat deposits over millennia.
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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".