Degradation of <sup>13</sup> C–U–Glucose in <i>Sphagnum majus</i> Litter Responses to Redox, pH, and Temperature
Bibliographic record
Abstract
We studied the utilization of 13 C–U–glucose by the microbial community in shallow Sphagnum majus (Russ.) C. Jens. ssp. norvegicum Flatb. litter and its regulation by pH, temperature, and redox conditions. The transformation of 13 C–glucose was monitored by solution‐ and solid‐state 13 C–nuclear magnetic resonance (NMR) spectroscopy. The aerobic microbial community used the glucose C for respiration and, to a lesser degree, for storage as mannitol, triglycerides, and polysaccharides. Under both aerobic and anaerobic conditions, the allocation of glucose C for storage was greater at pH 6.8 than at 4.3; however, the amount of C used for building new biomass was the same at both pH settings. At 15°C, 15 to 18% of the utilized C under aerobic conditions was found in new microbial biomass: less than the previously reported values of 40 to 72%. This indicates that peat soils may promote significantly different microbial growth patterns from other minerogenic and moor humus soils. The production of mannitol and triglycerides suggests that fungi dominated the microbial community and utilized the glucose under aerobic conditions. Using a combination of solid and liquid NMR techniques we were able, for the first time, to follow the anaerobic pathways of glucose degradation in a natural soil sample. The anaerobic microbial community produced mainly volatile fatty acids (VFA), ethanol, and CO 2 from the added glucose, and only minor amounts were converted to methane, storage C, and new microbial biomass. Nuclear magnetic resonance spectroscopy allows nondestructive assays of metabolic events and, therefore, was shown to be an excellent tool for studying the microbial utilization of 13 C–glucose in peat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".