Linking soil carbon availability, microbial community composition and enzyme activities to organic carbon mineralization of a bamboo forest soil amended with pyrogenic and fresh organic matter
Bibliographic record
Abstract
Despite fresh and pyrogenic organic matter have been widely used as amendments to improve soil organic carbon (SOC) storage, mineralization that links to C quality and soil temperature, microbial community composition and enzyme activity remain poorly understood. This study aims to explore the effects of amendments (bamboo leaves and its biochar) and incubation temperature on mineralization, and disentangle the relationships of SOC mineralization with chemical composition of SOC, labile organic C, microbial community composition, and activities of enzymes in a subtropical bamboo forest soil. Results showed that cumulative soil CO2 emissions ranked as bamboo leaf (Leaf) > bamboo leaf biochar (Biochar) > Control, regardless of the incubation temperature. Compared to the control, the Leaf treatment markedly increased, whereas the Biochar treatment decreased, the temperature sensitivity of SOC mineralization (P < 0.05). The cumulative soil CO2 emission was positively correlated (P < 0.05) with water-soluble organic C (WSOC), microbial biomass C (MBC), O-alkyl C and alkyl C contents, and activities of β-glucosidase and dehydrogenase, but negatively correlated (P < 0.01) with aromatic C content, regardless of the incubation temperature. This indicated that the lower SOC mineralization rate and lower temperature sensitivity in the Biochar (cf. Leaf) treatment were intimately associated with the lower WSOC, MBC, O-alkyl C content, and β-glucosidase and dehydrogenase activities, and higher aromatic C content in the Biochar. The high relative abundance of bacteria relating SOC mineralization included Rhizobiales, Sphingobacteriales and JG30-KF-AS9, whereas that of fungi included Eurotiales, Sordariales, Agaricales and Helotiales. Our results revealed that the application of pyrogenic organic matter, as compared to the application of fresh organic matter, can reduce SOC mineralization and its temperature sensitivity in a subtropical forest soil by limiting the availability of C and microbial activity, and thus has a great potential for maintaining soil carbon stock in subtropical forest ecosystems.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".