Woodchip biochar with or without synthetic fertilizers affects soil properties and available phosphorus in two alkaline, chernozemic soils
Bibliographic record
Abstract
Fertility enhancement with biochar application is well documented for tropical acidic soils; however, benefits of biochar coapplied with synthetic fertilizers (SFs) on soil fertility are not well documented, particularly for alkaline chernozems. We examined the short-term interactive effects of woodchip biochar amendment with fertilizers on selected soil properties, available phosphorus (P), and P fractions of two alkaline Chernozems from Manitoba. Treatments were (1) urea and monoammonium phosphate fertilizers, (2) biochar at 10 g kg −1 , (3) biochar at 20 g kg −1 , (4) biochar at 10 g kg −1 with fertilizers, (5) biochar at 20 g kg −1 with fertilizers, and (6) a control. Treated soils were analysed for pH, electrical conductivity (EC), and Olsen P concentration biweekly, and for P fractions, cation exchange capacity (CEC), organic carbon (OC), and wet aggregate stability after 70 d of incubation. Biochar amendment without fertilizers significantly increased soil pH and CEC but had no effect on EC, while coapplication with fertilizers significantly increased Olsen P and labile P concentrations. When coapplied with fertilizers, biochar did not significantly increase soil pH relative to the control. Results suggest that biochar improved soil properties and available P in alkaline Chernozems, and the beneficial effects were enhanced when coapplied with SFs.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".