Radial variations in xylem sap flux in a temperate red pine plantation forest
Bibliographic record
Abstract
BACKGROUND: Scaling sap flux measurements to whole-tree water use or stand-level transpiration is often done using measurements conducted at a single point in the sapwood of the tree and has the potential to cause significant errors. Previous studies have shown that much of this uncertainty is related to (i) measurement of sapwood area and (ii) variations in sap flow at different depths within the tree sapwood. RESULTS: ) trees to more accurately estimate water-use at the tree- and stand-level in a plantation forest near Lake Erie in Southern Ontario, Canada. Results showed that most of the water transport (65%) occurred in the outermost sapwood, while only 26% and 9% of water was transported in the middle and innermost depths of sapwood, respectively. CONCLUSIONS: These results suggest that failing to consider radial variations in sap flux density within trees can lead to an overestimation of transpiration by as much as 81%, which may cause large uncertainties in water budgets at the ecosystem and catchment scale. This study will help to improve our understanding of water use dynamics and reduce uncertainties in sap flow measurements in the temperate pine forest ecosystems in the Great Lakes region and help in protecting these forests in the face of climate change.
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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) | 0.000 | 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 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".