Botanical composition of peat and degree of peat decomposition in three temperate peatlands
Bibliographic record
Abstract
Models of peat accumulation assume that peat decomposition occurs mostly above the water table, with little or no decomposition once peat enters the deeper, saturated, anoxic zone. However, few such measurements of peat decomposition exist. In this paper we quantified differences in degree of decomposition, botanical composition, and organic chemical composition of peat from three temperate peatlands with different water table levels. All sites had a thick layer of herbaceous peat, capped by a layer of Sphagnum peat. The lignin content and degree of decomposition, measured by the pyrophosphate index, generally increased with depth. Analysis of the lignin with cupric oxide (CuO) oxidation revealed most of the chemical differences between peat deposits occurred in the upper, aerated peat layer, as expected. The upper layer of Sphagnum peat was characterized by high p-hydroxyl phenolic yield, whereas Sphagnum peat below the water table exhibited a high degree of humification and high yield of vanillyl oxidation products despite being of similar botanical composition. Surprisingly, herbaceous peat below the water table was similar in terms of degree of decomposition to younger herbaceous peat. The results confirm that peat decomposition occurs mostly above the water table, although botanical source, climate, and local hydrology interact to create multiple trajectories in peat chemistry.
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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 | 0.000 | 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".