Climate Change and Winter Survival of Perennial Forage Crops in Eastern Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Severe winter climatic conditions cause recurrent damage to perennial forage crops in eastern Canada. Predicted increases of 2 to 6°C in minimum temperature during winter months due to global warming will likely affect survival of forage crops. Potential impacts of climate change on overwintering of perennial forage crops in eastern Canada were assessed using climatic indices reflecting risks of winter injuries related to cold intensity and duration, lack of snow cover, inadequate cold hardiness, soil heaving, and ice encasement. Climatic indices were calculated for 22 agricultural regions in eastern Canada for the current climate (1961–1990) and future climate scenarios (2010–2039 and 2040–2069). Climate scenario data were extracted from the first‐generation Canadian Global Coupled General Circulation Model. Compared with current conditions, the hardening period in 2040 to 2069 would be shorter by 4.0 d, with a lower accumulation of hardiness‐inducing cool temperatures. The period during which a temperature ≤−15°C can occur (cold period) would be reduced by 23.8 d, and the number of days with snow cover of at least 0.1 m would be reduced by 39.4 d. Consequently, the number of days with a protective snow cover during the cold period would be reduced by 15.6 d. Under predicted future climate, risks of winter injury to perennial forage crops in eastern Canada will likely increase because of less cold hardening during fall and reduced protective snow cover during the cold period, which will increase exposure of plants to killing frosts, soil heaving, and ice encasement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it