Climate change and winter damage to fruit trees in eastern Canada
Bibliographic record
Abstract
Climatic conditions during the cold season represent a serious constraint to fruit production in eastern Canada. Meteorological models predict that temperatures of winter months will increase by 2 to 6°C by 2050. The possible impact of climate change on fruit trees in eastern Canada was assessed using agroclimatic indices expressing the risks associated with known causes of damage during fall, winter, and spring. Indices were calculated for 15 agricultural regions in eastern Canada for recent (1961–1990) and future periods (2010–2039 and 2040–2069) using temperature and precipitation data predicted by the Canadian Global General Circulation Model (CGCMI). Averaged across all agricultural regions, the first fall frost in 2040–2069 would be delayed by 16 d while the last spring frost (≤-2°C) would be advanced by 15 d. By 2040 to 2069, the risks of damage to fruit trees by early winter frosts in eastern Canada are likely to decrease because the shorter photoperiod at the time of the first fall frost would result in a longer hardening period. Milder winter temperatures will also reduce the cold stress as the accumulation of cold degree-days (<-15°C) would be reduced and the annual minimum temperature would be increased in all regions of eastern Canada. More frequent winter thaw events, however, would result in a loss of hardiness and in a thinner snow cover that would increase the plant vulnerability to subsequent extreme sub-freezing temperatures. The risk of damage to flower buds by a late frost would increase in southern Ontario, remain almost unchanged in the Maritimes and Ottawa Valley-southern Québec regions, and decrease in the Continental North. The projected climate change should allow for the introduction of new varieties and species where fruit trees are currently grown and for an extension further north of the commercial production in eastern Canada. Key words: Overwintering, fruit production, climatic indices, winter injury, spring frost
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".