Synergistic Effects of Biochar and Bacillus thuringiensis NL-11 on Ophiopogon japonicus Growth and Soil Microbial Diversity in Trampled Urban Forest Soils
Bibliographic record
Abstract
Bare soil expansion in urban forests, driven by persistent high-intensity trampling, degrades both macro-scale natural resources and micro ecological conditions. Targeted interventions are therefore essential. In this study, trampled bare ground in forest parks and artificially cultivated Ophiopogon japonicus were used as experimental models We employed trampled bare ground in forest parks as well as artificially cultivated O. japonicus as experimental models. Five treatments were implemented: enclosure control (CK), ploughing (F), Bacillus thuringiensis NL-11 application (J), biochar addition (C), and co-application of B. thuringiensis NL-11 with biochar (JC). Our results indicate that, compared with CK, biochar treatments reduced soil bulk density by 30%, increased soil porosity by 89%, and improved water-holding capacity. The soil nitrate nitrogen content in the NL-11 treatment was increased by 113.8% compared with CK, while the co-application of NL-11 with biochar exhibited the highest sucrase and urease activities. Notably, the co-application of B. thuringiensis NL-11 with biochar exhibited the most pronounced effects on aboveground biomass, plant height, and root development, followed by the B. thuringiensis NL-11 treatment. Microbial β-diversity shifts under co-application of B. thuringiensis NL-11 with biochar treatment strongly correlated with soil enzyme activation and plant growth enhancement (Mantel test, p < 0.05). Correlation analysis confirmed that exogenous nutrient inputs significantly influenced enzyme activities, thereby promoting plant development. These results highlight the effectiveness of integrating microbial inoculation with biochar to restore trampled urban forest soils.
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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 | 0.000 |
| 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".