Role of sea surface temperature variability on the risk of Canadian wheat, barley, and oat yields
Bibliographic record
Abstract
Surface air temperature (SAT) and precipitation in Prairie (Western) and Maritime (Eastern) Canada are influenced by the El Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO), respectively. However effects of ENSO and AMO on major crop yield in Canada is yet to be understood. Here we investigate the longest record (1908–2017) of wheat, barley, and oat yield as well as its associated risk with summer (May-September) ENSO and AMO interannual and multidecadal variability in Prairie and Maritime, respectively. We used generalized linear models with autocorrelative residuals to assess region- and crop-specific associations between ENSO, AMO, surface air temperatures, and precipitation on crop yield. After adjusting for covariates our models show that a positive phase of the AMO (in comparison to negative phase) significantly reduces the risk of Maritime crop yields by ~3–12%, with both extreme heat and wet precipitation found to be significant risk factors for reducing yields. Summer El Niño or La Niña was found to have a small, insignificant effect on yield in the Prairie region, with no effects found on crops in Maritimes. Therefore, analysis of Atlantic oceanic variability can offer insight into major crop yield variability in Maritime Canada.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".