What is the Optimal Rate and N2O Mitigation Policy for Nitrogen Application in Saskatchewan Canola?
Bibliographic record
Abstract
This thesis examines privately and socially optimal nitrogen (N) fertilizer rates for Canola production in Saskatchewan. In 2018 nitrous oxide (N2O) emissions from agricultural soils accounted for approximately 42% (in CO2eq) of all Canadian agricultural greenhouse gas emissions. In 2020 the Government of Canada set a national target of reducing absolute levels of GHG emissions from fertilizer application by 30% from 2020 levels by the year 2030. Canola is the largest N using crop in Canada and therefore optimizing N fertilizer use in this crop is of great importance. A canola production function is estimated using a large (n = 47,059) producer-reported data set from Saskatchewan Crop Insurance Corporation on field-level canola management over the years 2011-2019 and a wide variety of spatial and climatic conditions. The estimated implied canola N response curve was combined with price information and previous estimates for direct N2O emissions to estimate the marginal abatement cost curves and compare the observed applied N fertilizer rates to the estimated privately optimal rates and socially optimal rates. The results of this study support the previous findings of a nearly flat pay-off function for N fertilizer in crop production. On average, Saskatchewan canola producers do not appear to be overapplying nitrogen relative to the estimated privately optimal N rate. Regulation to reduce nitrogen fertilizer application rates by 30% from the privately optimal rate were found to result in net social welfare losses for canola cropping systems in Saskatchewan. When applying a N2O tax using the highest carbon price in the Canadian governments’ schedule of $170/t CO2eq for 2030, N rates are estimated to be reduced from the privately optimal rate by only 12.3% – 14.6% in the black soil zone and 6.12% – 6.92% in the brown soil zone. Given the heterogeneity in emissions factors across ecoregions and nitrogen management practices, focusing on the 4R’s of Nutrient Stewardship, agronomic research, and extension to improve N management and optimize fertilizer use are better opportunities to reduce emissions as opposed to a uniform mandatory reduction in N rates.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".