Freeze-Tolerance of Cacti (Cactaceae) In Ottawa, Ontario, Canada
Bibliographic record
Abstract
Many fewer species of cacti are native to and thought to be able to survive winters in eastern Ontario than in the similarly cold winters of central Colorado. We collected 12 yr of data on 107 specimens representing 50 cactus species that have been tested outdoors in gardens in the City of Ottawa (Canada) and report which have successfully weathered six or more consecutive winters and which have not. Some species that we expected to be more successful were not, while a small number of species native to considerably warmer environments survived surprisingly well. We review general mechanisms for freeze-tolerance in plants, focusing on what is known about cacti in particular. Phylogeny does not appear to be important in determining success or failure in cold climates, so we explore other possible explanatory factors for differences in survival between Ontario and Colorado. Our data indicate that freeze tolerance of cacti in eastern Ontario may be a function of snow cover, rather than polyploidy. Colorado's greater cactus richness may also be a function of its location closer to the southwestern deserts' center of diversity, which would provide a larger pool of potential species that could expand to colder regions. More thorough studies of freeze-tolerance over a larger geographic range – albeit controlling for growing conditions, using identical clones at multiple sites, and determining precise cause of death – will be necessary to reach more definitive conclusions.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".