Vessel anatomy of urban Celtis occidentalis trees varies to favour safety or efficiency depending on site conditions
Bibliographic record
Abstract
Abstract Key message Urban trees can acclimate to their growth environment through changes in vessel anatomy. Vessel lumen area and vessel frequency following a gradient from park trees to inner-city street trees. Abstract Urban trees stand in potentially stressful growth environments occurring along gradients of urban heat and impermeable surface cover and, to survive, can adjust their function and structure. The consequent tree-to-tree variations in hydraulic xylem traits can shed light on tree hydraulics and capacity to acclimate to diverse conditions, as well as identify limitations to tree growth and survival. Using microscopic analysis of increment cores, we compared early wood vessel traits of the ring-porous angiosperm Celtis occidentalis in three urban site types: central streets, residential streets and parks, within the city of Montreal. We explored differences in vessel traits (mean vessel lumen area, vessel frequency, vessel grouping index and derived variables) between site types, vessel trait intercorrelations and correlations with monthly temperature, precipitation and heat-moisture index over 10 years. The vessel traits significantly differed between site types. Park trees had the largest and central street trees had the smallest vessel lumen area and theoretical hydraulic conductivity; traits supporting efficient water transport. Central street trees had the largest vessel frequency and smallest theoretical vulnerability to cavitation; traits connected to hydraulic safety. Residential street tree traits were in between. Among central and residential street trees, water transport efficiency traits correlated positively with cool springs or arid summers, whereas among park trees, mainly vessel frequency and grouping index responded to climate variations. These results highlight the capacity of C. occidentalis to acclimate to urban environments and the potential of anatomical traits for quantifying the effects of urban environments on tree functioning. Graphical Abstract
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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 | 0.000 |
| 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".