Simulation of effects of wood microstructure on water transport
Bibliographic record
Abstract
A tracheid-level model was used to quantify the effects of differences in wood microstructure between coastal and interior Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii and var. glauca) wood on larger scale properties like hydraulic conductivity. The model showed that tracheid length, the ease of flow through a bordered pit and effective tracheid diameter can all limit maximum hydraulic conductivity. Among the model parameters tested, increasing bordered pit conductivity and tracheid length resulted in the greatest increase in maximum conductivity in both the inland and coastal ecotypes. A sensitivity analysis of the uncertainty between parameters governing flow through the bordered pit and air-seeding potential showed that, although decreased pit flow resistance increased maximum hydraulic conductivity, increased cavitation led to lower conductivity over time. The benefits of increasing the number of bordered pits depended on the intensity of the meteorological driving function: in drier environmental conditions, wood with fewer pits was more conductive over time than wood with more pits. Switching the bordered pit characteristics between coastal and interior wood indicated that the conductivity time course of coastal and interior wood was primarily governed by differences in the number of bordered pits and not differences in tracheid dimensions. The rate at which tracheids refilled had little effect on the conductivity time course of either coastal or interior wood during the first two summers when the wood was highly saturated, but had a marked influence in subsequent years once the cavitation profile stabilized. Our work highlights the need for more empirical work on bordered pits to determine whether variation in their number and properties is related to changing environmental conditions. In addition, a detailed simulation model of a bordered pit is needed to understand how variation in pit properties affects the relationship between ease of flow through a bordered pit and its potential for facilitating air-seeding.
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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".