Impacts of freezing and thawing dynamics on foliar litter carbon release in alpine/subalpine forests along an altitudinal gradient in the eastern Tibetan Plateau
Bibliographic record
Abstract
Abstract. Carbon (C) release from foliar litter is a primary component in C exchange among the atmosphere, vegetation, soil and water from respiration and leaching, but little information is currently related to the effects of freezing and thawing dynamics on C release of foliar litter in cold regions. A 2-year field litter decomposition experiment was conducted along an altitudinal gradient (~ 2700 to ~ 3600 m) to mimic temperature increases in the eastern Tibetan Plateau. C release was investigated for fresh foliar litter of spruce, fir and birch. The onset of the frozen stage, deep frozen stage and thawing stage was partitioned according to changes in the freezing and thawing dynamics of each winter. More rapid 2-year C released from fresh foliar litter at upper elevations compared to lower elevations in the alpine/subalpine region. However, high C release was observed at low altitudes during winter stages, but high altitudes exhibited high C release during growing season stages. The deep frozen stage showed higher rates of C release than other stages in the second year of decomposition. Negative-degree days showing freezing degrees were correlated to C release rates for the deep frozen stages in both years, and this relationship continued for the duration of the experiment, indicating that changes in freezing can directly modify C release from foliar litter. The results suggested that the changed freezing and thawing dynamics could delay the onset of C release in fresh litter in this cold region in the scenario of climate 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 | 0.000 | 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".