Quantifying the Effects of Climate on the Radial Growth Rates of Urban Trees in Toronto
Bibliographic record
Abstract
Despite the importance of trees to urban ecosystem services and citizens’ well-being, they are an understudied aspect of modern ecology. Although some studies have been conducted in other countries, no urban dendroclimatological work has been conducted in Canada. I investigated the impact of climate on urban tree growth, focusing on Toronto. I collected cores from five tree species: red oak, European linden, sugar maple, Norway maple, and Austrian pine, from street and park locations. I found a difference in environmental stress by location and by species, with street trees exhibiting negative correlations between summer temperature and growth. Norway maple and sugar maple were found to be particularly stressed by summer temperatures, with increases in negative growth-climate correlations in recent years, while red oak and linden were found to be less stressed by climate. An analysis of growth figures found high annual growth rates for both red oak and linden, and low annual growth for Norway maple and Austrian pine. This suggests that certain species may experience decreased growth rates in the coming decades due to climate change. The findings emphasize the need for attention to urban tree management in the face of changing climates, providing insights for urban forestry planning and conservation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".