Impact of Climate Change on Wheat Production for Ethanol in Southern Saskatchewan, Canada
Bibliographic record
Abstract
This study assessed the impact of climate change on wheat production for ethanol in southern Saskatchewan, Canada.The DSSAT-CSM model was used to simulate biomass and grain yield under three climate change scenarios (IPCC SRES A1B, A2 and B1) in the 2050s.Synthetic 300-yr weather data were generated by the AAFC stochastic weather generator for the baseline period and scenarios.Compared to the baseline, all three scenarios increase precipitation every month except July and August and June (A2 only), when less rains are projected.Annual air temperature is increased by 3.2, 3.6 and 2.7 o C for A1B, A2 and B1, respectively.The model predicted increases in biomass by 28, 12 and 16% without the direct effect of CO 2 and 74, 55 and 41% with combined effect (climate and CO 2 ) for A1B, A2 and B1, respectively.Similar increases were found for yield.However, the occurrence of heat shock (>32 o C) will increase during grain filling under climate change conditions and could cause severe yield reduction, which is not simulated by DSSAT-CSM; therefore, the yield could be overestimated.Several measures such as early seeding must be taken to avoid heat damage and take the advantage of projected increase in precipitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".