The Tree-Ring Record of Drought on the Canadian Prairiesa,b
Bibliographic record
Abstract
Abstract Ring-width data from 138 sites in the Canadian Prairie Provinces and adjacent regions are used to estimate summer drought severity during the past several hundred years. The network was divided into five regional groups based on geography, tree species, and length of record: the eastern Rockies, northern Saskatchewan, central Manitoba, southern Manitoba, and northwestern Ontario. Regional tree-ring records are primarily related to summer moisture and drought conditions, and are less responsive to droughts caused by deficits in winter precipitation. These summer-sensitive data are not linearly related to major modes of climate variability, including ENSO and the Pacific decadal oscillation (PDO), which primarily affect the climate of western Canada during winter. Extended drought records inferred from tree rings indicate that drought on the Canadian Prairies has exhibited considerable spatial heterogeneity over the last several centuries. For northern Saskatchewan and northwestern Ontario, intervals of persistently low tree growth during the twentieth century were just as long as or longer than low-growth intervals in the eighteenth or nineteenth centuries. Longer records from southern Alberta suggest that the most intense dry spell in that area during the last 500 yr occurred during the 1720s. At the eastern side of the prairies, the longest dry event is centered around 1700 and may coincide with low lake stands in Manitoba, Minnesota, and North Dakota. Although the Canadian Prairies were dry at times during the 1500s, there is no regional analog to the sixteenth-century “megadroughts” that affected much of the western United States and northern Mexico.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".