Spring barley yield and potential northward expansion under climate change in Canada
Bibliographic record
Abstract
Abstract Spring barley (Hordeum vulgare L.), being a cold‐tolerant crop, may not benefit as much from a warmer climate and a lengthening of the growing season due to climate change though its suitable production area could expand further north. The objectives of this study were to assess the impact of climate change on barley yields across Canada for both current production regions and potential northern crop expansion regions in the future. Three crop models (DeNitrification and DeComposition, Decision Support System for Agrotechnology Transfer, and Simulateur mulTIdisciplinaire pour les Cultures Standard) and 18 climate scenarios (1981–2100) were used to simulate the effect of climate change on potential (non‐water and non‐nitrogen limited) and rainfed (non‐nitrogen limited) spring barley yields for 32 locations across Canada. For the currently planted spring barley regions characterized by a humid summer in Eastern Canada (growing season precipitation >500 mm), potential and rainfed yields were projected to slightly increase in the future (<+0.2 t ha−1). In western regions where precipitation amount is lower (growing season precipitation <500 mm), changes in the potential yield varied slightly (−0.1 to +0.2 t ha−1), while the rainfed yield was projected to increase (0.2–1.0 t ha−1) mainly due to a reduction in water stress under elevated CO2. Finally, in northern regions where future expansion may occur, projected yield increases were generally large (up to 2.8 t ha−1 for potential yield), but the risk of crop failure usually remained high. Our findings suggest that future climate change will present both opportunities and regionalized risks for spring barley producers with the potential to further expand barley production northward.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".