Projected Climate Change Impacts on Grape Growing in the Okanagan Valley, British Columbia, Canada
Bibliographic record
Abstract
Abstract A statistical analysis was conducted on long-term climate records in the Okanagan Valley wine grape growing region of British Columbia, Canada. No observable trends for average annual temperatures were found in the region. Analyses of monthly mean and extreme temperatures show wide spatial and temporal heterogeneity, indicating that future studies using downscaling of global climate models for this region will require resolutions on the order of several kilometers. Mean winter temperatures are increasing throughout the valley, and extreme minimum temperatures are also increasing during the winter at the central and northern sites which have historically presented the most risk of winter damage to grapevines. Only the most southern and northern sub-regions are expected to see significant changes in their heat unit accumulations during the growing season. Over the coming century, the southern end of the valley will likely move from Winkler heat unit region 1 to 2. All regions of the Okanagan will continue to have latitude-temperature indices among the lowest of the world's fine table wine producing regions over the coming century. Growing season and dormant season average temperatures are expected to change by only a modest amount by 2100. Current climate maturity groupings for ripening grape varieties will likely stay constant at cool (central and southern areas) and intermediate (south-central) for all sites except Osoyoos (south). The climate trendings at Osoyoos suggest it will transition from an intermediate to a warm grouping by about 2050. The early to mid-season ripening capacity of the region may improve due to climate changes, but there is a risk of the asymmetric late season increases in minimum daily temperatures lowering the daily temperature range at some sites, possibly leading to difficulties in maintaining a balanced between sugar and sensory profiles as wine grapes approach maturity. The projected warming at the southern end of the valley should favor improved and increased Merlot production, will require Chardonnay production to shift northwards, and will allow growing of warmer climate wine grape varieties currently inaccessible because of low winter temperatures and a lack of growing season heat units. Increasing winter temperatures throughout the region are expected to result in increased risk of pests such as Pierce’s disease.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".