Forest-floor chemical properties are altered by clear-cutting in boreal mixedwood forest stands dominated by trembling aspen and white spruce
Bibliographic record
Abstract
Alterations in the chemical properties of the forest floor following clear-cut harvesting may have implications for forest productivity in boreal stands. We used proximate analysis, carbon-13 (13C) isotopic determination, and cross-polarization, magic-angle spinning (CPMAS) 13C nuclear magnetic resonance (NMR) spectroscopy to examine differences in the characteristics of the forest floors from uncut stands and clear-cut stands dominated by white spruce (Picea glauca (Moench) Voss; SPRUCE) and trembling aspen (Populus tremuloides Michx.; ASPEN) in northern Alberta. Proximate analysis revealed no difference in the chemical properties of forest floors from clear-cut and uncut stands in either stand type, but the acid-insoluble residue of forest floors from clear-cut ASPEN stands was enriched in 13C compared with those from uncut ASPEN stands. CPMAS 13C NMR spectroscopy revealed that forest floors from clearcuts were enriched in total aromatic C, particularly in ASPEN stands, and depleted in phenolic C, particularly in SPRUCE stands. These patterns indicate that forest floors from the clearcuts have become more humified, which may reflect stand-type differences in the amount of labile C available to the forest-floor microbial community and reductions in above- and below-ground inputs to the forest floor following clear-cutting in both stand types. Changes in the chemical properties of forest floors from clear-cut SPRUCE and ASPEN stands could exacerbate C limitation in these soils and alter patterns of nutrient cycling.
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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".