Phytolith-occluded organic carbon in intensively managed Lei bamboo (<i>Phyllostachys praecox</i>) stands and implications for carbon sequestration
Bibliographic record
Abstract
Phytolith-occluded organic carbon (PhytOC) is an important long-term (up to several thousand years) terrestrial carbon (C) fraction in forest ecosystems. The objectives of this study were to (i) investigate the spatial distribution of PhytOC in Lei bamboo (Phyllostachys praecox C.D. Chu & C.S. Chao.) forests under intensive management (mulching and fertilization) and (ii) assess the role of PhytOC in C sequestration in a Lei bamboo stand and across subtropical China. Phytolith concentrations in Lei bamboo plant components were (P < 0.05) in the following order: rhizome ≈ stump > leaf ≈ branch > culm. The distribution of PhytOC in bamboo leaves, branches, culms, rhizomes, and stumps was 22.2%, 12.1%, 16.1%, 15.9%, and 33.7%, respectively. The PhytOC stock was in the following order (P < 0.05): soil (9361 kg C·ha −1 ) > mulching materials (197.5 kg C·ha −1 ) > belowground plant parts (13.0 kg C·ha −1 ) ≈ aboveground plant parts (12.8 kg C·ha −1 ) ≈ litterfall (11.3 kg C·ha −1 ). The PhytOC accretion rate in the vegetation in the Lei bamboo stand was 19.4 kg C·ha −1 ·year −1 , equivalent to 71 kg CO 2 -eq·ha −1 ·year −1 . The soil PhytOC stock decreased markedly with depth and had an accretion rate of 325 kg C·ha −1 ·year −1 for the 0–60 cm soil layer. Based on a PhytOC accretion rate of 0.795 Mg CO 2 -eq·ha −1 ·year −1 , PhytOC accretion rate in the 2.62 × 10 6 ha of Lei bamboo stands in southern China is estimated to be 2.08 × 10 6 Mg CO 2 -eq·year −1 . In conclusion, intensively managed Lei bamboo stands have a large potential in long-term C sequestration in the form of PhytOC, and the PhytOC stock belowground should not be ignored due to its contribution to the ecosystem level PhytOC stock.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".