Soil organic carbon dynamics along a climatic gradient in a southern Appalachian spruce–fir forest
Bibliographic record
Abstract
A field study was conducted in a high-elevation spruce–fir ( Picea rubens Sarg. – Abies fraseri (Pursh.) Poir) forest in the Great Smoky Mountains National Park to assess the effect of temperature on soil C storage and dynamics. In eight plots along an elevation gradient (1500–1900 m), we measured soil temperature, forest floor and mineral soil C, litter decomposition, soil respiration, and forest floor mean residence time. Mean annual soil temperature and annual degree-days above 5 °C were inversely correlated with elevation. Total soil C (166–241 Mg·ha–1) showed no trend with elevation, while forest floor C accumulation (16.3–35.9 Mg·ha–1) decreased significantly with elevation. Carbon dynamics did not follow a consistent elevation pattern; however, the cooler upper elevations showed the lowest C turnover as indicated by the lowest needle decomposition rate (k = 0.0231·year–1) and the longest mean residence time of forest floor C (22 years). Mean annual CO2efflux from the soil (1020–1830 kg C·ha–1·year–1) was negatively correlated with mean annual soil temperatures and annual degree-days above 5 °C. This gradient study offers useful insights into C release patterns under future warming scenarios, and suggests that the highest elevation may be most susceptible to global warming.
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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 | 0.001 | 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".