Measuring Canopy Structure and the Kinematics of Subcanopy Flows in Two Forests
Bibliographic record
Abstract
Abstract A better understanding of forest subcanopy flows is needed to evaluate their role in the horizontal movement of scalars, particularly in complex terrain. This paper describes detailed measurements of the canopy structure and its variability in both the horizontal and vertical directions at a deciduous forest in complex terrain (the Harvard Forest, Petersham, Massachusetts). The effects of the trunks and subcanopy shrubs on the flow field at each of six subcanopy array locations are quantified. The dynamics of the subcanopy flow are examined with pragmatic methods that can be implemented on a small scale with limited resources to estimate the stress divergence, buoyancy, and pressure gradient forces that drive the flow. The subcanopy flow at the Harvard Forest was driven by mechanisms other than vertical stress divergence 75% of the time. Nocturnal flows were driven predominantly by the negative buoyancy of a relatively cool layer near the forest floor. The direction of the resulting drainage flows followed the azimuth of the longest forest-floor slope. Similar results were found at a much flatter site at Borden, Ontario, Canada. There was no clear evidence of flow reversals in the subcanopy in the lee of ridges or hills at the Harvard Forest even in high wind conditions, contrary to some model predictions.
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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".