Organic carbon and nitrogen stocks in a clay loam soil 10 years after a single compost application
Bibliographic record
Abstract
Yang, X., Reynolds, W. D., Drury, C. F., Fleming, R., Tan, C. S., Denholm, K. and Yang, J. 2014. Organic carbon and nitrogen stocks in a clay loam soil 10 years after a single compost application. Can. J. Soil Sci. 94: 357-363. Household food waste compost (FWC), yard waste compost (YWC) and pig manure plus wheat straw compost (PMC) were applied once in the fall of 1998 to a Brookston clay loam soil in southwestern Ontario to determine immediate and long-term effects of organic amendments on soil quality and productivity. In this report, we describe the residual effects of these single compost applications on soil organic carbon (SOC) and total soil nitrogen (TN) stocks 10 yr after compost addition (2009). FWC was applied at 75 Mg ha-1, 150 Mg ha-1 and 300 Mg ha-1, while YWC and PMC were applied at the single rate of 75 Mg ha-1. The 75 Mg ha-1 additions of YWC, PMC and FWC increased SOC in the top 30 cm relative to a control (no compost additions) by 12.3% (9.0 Mg ha-1), 16.6% (12.2 Mg ha-1) and 0%, respectively; and they increased TN relative to the control by 8.0% (0.53 Mg ha-1), 11.7% (0.77 Mg ha-1), and 0%, respectively. The 150 and 300 Mg ha-1 additions of FWC increased SOC in the top 30 cm by 13.0 and 24.7 Mg ha-1, respectively, and they increased TN by 0.93 and 1.70 Mg ha-1, respectively. These results indicate that increases in SOC and TN stocks accruing from a single compost addition can persist for at least a decade, but the degree of increase depends strongly on compost type and addition rate. It was concluded that high compost addition rates of FWC and/or addition of composts derived from recalcitrant organic materials may be a good strategy for achieving long-term carbon and nitrogen sequestration in the cool, humid fine-textured soils of southwestern Ontario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".