Forest Floor Composition in Aspen‐ and Spruce‐Dominated Stands of the Boreal Mixedwood Forest
Bibliographic record
Abstract
The ability of high‐resolution cross‐polarization magic‐angle spinning 13 C nuclear magnetic resonance spectroscopy (CPMAS 13 C NMR) to characterize soil organic matter (SOM) has been previously demonstrated, but rarely has this information been directly related to local environmental conditions that affect SOM formation. In this study, CPMAS 13 C NMR was used to characterize the forest floor (Oe + Oa horizon) of stands dominated by trembling aspen ( Populus tremuloides Michx.) or white spruce [ Picea glauca (Moench) Voss] in the boreal mixedwood forest of Alberta, Canada. Aromatic C content was higher and carbonyl C content was lower in the forest floor of spruce stands than in aspen stands. Within stand types, correlation analyses indicated significant relationships between the composition of the forest floor and soil temperature, mass of the Oi horizon, and mass of the moss layer. However, these relationships could not explain observed differences in the chemical composition of the forest floor between stand types. Although forest floor from spruce stands was largely composed of moss, which is low in aromatic C, it had a greater aromatic C content than forest floor from aspen stands, where moss was rare. Furthermore, a lack of significant correlations across stand types suggests that there are different relationships between the chemical and environmental characteristics of forest floor from spruce and aspen stands.
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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".