Estimates of direct nitrous oxide emissions from Canadian agroecosystems and their uncertainties
Bibliographic record
Abstract
Using a revised Intergovernmental Panel on Climate Change (IPCC) methodology and the process-based model DeNitrification and DeComposition (DNDC), we estimated N 2 O emissions from agroecosystems in Canada for each census year from 1981 to 2001. Based on the IPCC methodology, direct emissions of N 2 O ranged from 12.9 to 17.3 with an average of 15.1 Tg CO 2 equivalents, while the DNDC model predicted values from 16.0 to 24.3 with an average of 20.8 Tg CO 2 equivalents over the same period, and showed a large interannual variation reflecting weather variability. On a provincial basis, emissions estimated by IPCC and DNDC methods were highest in Alberta, Saskatchewan and Ontario, intermediate for Manitoba and Quebec and lowest in British Columbia and the Atlantic provinces. The greatest source of emissions estimated by the IPCC method was from N fertilizer (avg. 6.32 Tg CO 2 equiv. in Canada), followed by crop residues (4.24), pasture range and paddocks (PRP) (2.77), and manure (1.65). All sources of emissions, but especially those from fertilizers, increased moderately over time. Monte Carlo Simulation was used to determine the uncertainty associated with the 2001 emission estimates for both IPCC and DNDC methodologies. The simulation generated most likely values of 19.2 and 16.0 Tg CO 2 equivalents for IPCC and DNDC, respectively, with uncertainties of 37 and 41%, respectively. Values for the IPCC estimates varied between 28% for PRP and manure and 50% for N fertilizer and crop residues. At the provincial level, uncertainty ranged between 15 and 47% with higher values on the prairies. Sensitivity analyses for IPCC estimates showed crop residues as the most important source of uncertainty followed by synthetic N-fertilizers. Our analysis demonstrated that N 2 O emissions can be effectively estimated by both the DNDC and IPCC methods and that their uncertainties can be effectively estimated by Monte Carlo Simulation. Key words: Nitrous oxide, IPCC, DNDC model, Uncertainty analysis, Monte Carlo Simulation
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".