Surface soil organic carbon in temperate and subtropical oriental oak stands of East China
Bibliographic record
Abstract
Forest ecosystems contain large amounts of soil organic carbon (SOC), which is a major component of biogeochemical cycles that may be sensitive to environmental change. We used a combination of nuclear magnetic resonance (NMR) spectroscopy and elemental and isotopic composition to examine the influence of soil properties and climatic factors on the quantity and degree of decomposition of SOC for organic and surface mineral horizons in seven oriental oak (Quercus variabilis Blume) forest sites arranged across a 11o latitudinal gradient in East China. Lacking Oa horizons, the two southernmost sites contained lower amounts of SOC in the forest floor horizon, but otherwise, latitudinal trends were not consistent. The SOC stock in the 0–10 cm mineral horizon exhibited no clear trend along the gradient and had a negative association with clay + silt content. Based on a higher alkyl/O-alkyl (A/O) ratio and alkyl/methoxyl (A/M) ratio, the SOC at the 0–10 cm depth appeared to be relatively more decomposed in three of the four southern subtropical sites. However, the degree of SOC degradation also decreased strongly with increasing soil pH (R2 = 0.90, P = 0.001). Soil organic carbon exhibited increases in δ13C and δ15N and decreases in the C/N ratio with depth for all the seven sites, indicating an increase in its extent of decomposition. Our analysis indicated that the A/M ratio from NMR provided the best indication of the extent of SOC degradation along the latitudinal transect, whereas the elemental and isotopic composition better reflected patterns with soil depth.
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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 | 0.001 |
| 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".