Soil carbon stabilization in jack pine stands along the Boreal Forest Transect Case Study
Bibliographic record
Abstract
Boreal forests, containing >20% of the total organic carbon (OC) present at the surface of the Earth, are expected to be highly vulnerable to global warming. The objective of this study was to compare soil OC stocks and chemistry in jack pine stands located along a latitudinal climatic transect in central Canada. Total OC stocks (0–1 m) increased with decreasing mean annual temperature (MAT). We used a combination of physical fractionation of soil OC pools, 13C isotopic determination and cross-polarization, magic-angle spinning 13C nuclear magnetic resonance (NMR) spectroscopy to further characterize OC composition at all sites. Soil OC was dominated by labile pools. As illustrated by the C/N ratios, δ13C data and results from the 13C NMR analysis, the light fraction showed little alteration within the soil profiles. Instead, this fraction reflected the importance of fresh litter inputs and showed an increase in root contribution with depth. As opposed to the light fraction, the clay- and silt-stabilized OC exhibited an increase in δ13C and a decrease in C/N with depth, indicating an increase in its degree of decomposition. These changes with depth were more marked at the southern than the northern sites. Results hence suggest that if the MAT were to increase in the northern boreal forest the overall jack pine soil OC stocks would decrease but the remaining OC would become more decomposed, and likely more stabilized than what is currently present within the soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".