Differing seasonal trends in water use and water status between park and street trees
Bibliographic record
Abstract
Understanding the drivers of variation in water use of urban trees is essential to estimate and predict tree survival, health, and provision of ecosystem services now and in the near future characterised by more frequent droughts. Urban tree water status and water use vary within the urban mosaic of diverse microclimates and growth conditions, distinguished for example by the proportion of impervious surfaces that increase temperature but decrease water availability. We compared tree water status and water use dynamics between two urban environments differing in terms of impervious surfaces and microclimate: parks and streets. To do this, we tracked mid-day leaf water potential (WPMD) and sap flow in five common broadleaf deciduous species in Montreal, Canada, over two growing seasons (2020 and 2021). In both years WPMD and in 2021 sap flow were higher in the park than in street trees during the early summer. Yet, towards late summer 2021 dry periods and a cumulative deficit of precipitation decreased WPMD and sap flow among park trees, whereas street trees maintained relatively stable WPMD and sap flow. In conclusion, park trees were more vulnerable to dry conditions, while street trees appeared to be protected against drought potentially by more stable access to water or by water-use acclimations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".