Victoriaâs street trees : planning for climate change through species selection and arboricultural maintenance practices
Bibliographic record
Abstract
Street tree health in the City of Victoria, British Columbia has declined in the last decade. Using the health condition of six tree genera representing 72 % of the total 17,601 COV street trees inventory in 2005 this trend is likely in large part due to lack of moisture from June to October. Declining health is evident in branch die back and early leaf drop especially on species with a medium to high water requirement. The Prunus genus (cherries and plums) in particular, which comprises 29% of all COV street trees, \nwas rated at 54% fair to dead condition which is 20% higher than all COV street trees. Current summer precipitation from June to early October totals 105 mm and evapotranspiration for the same period totals -382 mm leaving a moisture deficit of 277 mm. This deficit is projected to increase (based on extreme models) to 362 mm by 2050 and 420 mm by 2080 which will have a devastating impact on street trees which will not able to withstand the intense moisture deficit interval. Recommendations on species selection and maintenance alternatives include: regular monitoring with site specific information, changing the list of trees used for selection and planting, increase watering, and increased maintenance. The results and recommendations of this study may be of value to other jurisdictions that will be affected by the impacts of moisture deficit related to climate change.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".