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 (WP MD ) and sap flow in five common broadleaf deciduous species in Montreal, Canada, over two growing seasons (2020 and 2021). In both years WP MD 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 WP MD and sap flow among park trees, whereas street trees maintained relatively stable WP MD 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. • We compared sap flow and leaf water potential between urban park and street trees. • In early summer, sap flow and water potential were higher in park than street trees. • By late summer, dry conditions affected water dynamics of park trees in particular. • In most species, park trees seemed more vulnerable to drought.
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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".