Decomposition of <i>Abies faxoniana</i> litter varies with freeze–thaw stages and altitudes in subalpine/alpine forests of southwest China
Bibliographic record
Abstract
Freeze–thaw events in winter may affect litter decomposition in cold biomes but few reports are available. We characterized the fir (Abies faxoniana) litter decomposition over a whole winter (November 2008 to April 2009) during the late autumn, deep winter, and early spring stages. The mass loss, nutrient release, and quality change of fir litter were determined using the litterbag method at 2700, 3000, 3300, and 3600 m altitude in southwest China. Over the winter an average of 18% mass, 27% C, 50% N, 40% P, 36% K, 30% cellulose, and 14% lignin were lost. Of these total losses, a majority loss of mass (70%), C (65%), N (50%), P (58%), K (42%), cellulose (70%), and lignin (68%) occurred during the deep winter stage. The highest loss rate of mass (19.2%) and lignin (16.4%) but the lowest N loss (47.9%) was at the highest 3600 m altitude. Soil freeze–thaw cycle resulted in significant losses of mass, while mass loss rate did not increase under the higher mean soil temperature during each stage. Our results confirmed that the physical process seemed to be the most important process for cold season decomposition in the cold biome.
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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".