Tree traits and meteorological factors influencing the initiation and rate of stemflow from isolated deciduous trees
Bibliographic record
Abstract
Abstract Tree canopy processes affect the volume and biogeochemistry of inputs to the hydrological cycle in cities. From June 2012 to November 2013, we studied stemflow production from 37 isolated deciduous park trees in a semi‐arid climate dominated by small precipitation events. To clarify the effects of canopy traits on stemflow metrics, we analysed branch angles, bark relief (one component of roughness), tree size, canopy and wood cover fraction, median leaf size, and branch and leader counts. High branch angles contributed to stemflow production in both single‐leader and multi‐leader trees. While bark relief was negatively correlated with stemflow rates in multi‐leader trees, it was positively correlated with rates for single‐leader trees, possibly reflecting the conducive role of linear furrows once bark of single‐leader trees is saturated. The association between numerous leaders, low stemflow initiation thresholds, and high rates deserves further study. Among meteorological variables, rain depth was strongly correlated with stemflow yields; rainfall inclination angle and wind speed were positively correlated with yields, while total intra‐storm break duration and vapour pressure deficit were inversely related. For rain depths <3 mm, greater stemflow was generally associated with leafless canopies. In support of integrated stormwater management, our results can inform climate‐sensitive selection and siting of urban trees with traits that tend to either promote or minimize stemflow, depending on infiltration potential. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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".