Effects of arbuscular mycorrhizal fungi on organic carbon allocation, sequestration, and decomposition in black soils
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) play important roles in the dynamics of soil organic carbon (SOC), as they can promote its accumulation and the formation of soil aggregates, thereby increasing soil carbon storage. However, the impact of carbon input through AMF inoculation on SOC sequestration is still unclear. In this study, the effects of AMF on photosynthetic carbon transport and SOC accumulation in two types of black soils with either high or low SOC soils were analyzed by an outdoor pot experiment using isotope 13C labeling, thus, revealing the mechanism of action of AMF in stabilizing SOC fixation. The results showed that AMF symbiosis increased the allocation of photosynthetic carbon to the roots of the maize plant and soils. Inoculation with AMF also increased the proportions of soil macro-aggregates and the soil microbial biomass carbon content in low SOC soil, promoted the accumulation of soil aggregates, and enhanced the chemical composition of SOC. After returning the harvested labeled straw to the original pots the following year after planting, inoculation with AMF was found to increase the contents of hemicellulose and lignin at the time when maize kernels attained a plump appearance. AMF significantly increased glomalin-related soil protein in high SOC soil. In addition, AMF had a promoting effect on the decomposition of cellulose, hemicellulose, and lignin in the straw, which could subsequently increase the accumulation of carbon. We provide evidence for the promotion of soil aggregates, soil C accumulation, and SOC sequestration with AMF inoculation.
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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) | 0.001 | 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".