Conversion of total to projected leaf area index in conifers
Bibliographic record
Abstract
Several definitions of leaf area index (LAI) presently exist in the literature but the relationships among them are not clear. To compare the results of various studies, there is a need to convert from one definition to another. Factors for converting among four definitions of LAI are presented for six conifer species: Abies grandis (Dougl. ex D. Don) Lindl., Thuja plicata Donn ex D. Don., Tsuga heterophylla (Raf.) Sarg., Picea sitchensis (Bong.) Carr.), Pinus contorta Dougl., and Pseudotsuga menziesii (Mirb) Franco). Among the four definitions of LAI, the two extremes involve (i) the total area of the leaf and (ii) the projected area of nonhorizontal leaves, as they occur on the tree. If leaves are randomly oriented in space, then the conversion factor between definitions i and ii should be 0.25. Four of the six species have conversion factors very close to this value, and three of these four are relatively shade-intolerant,. The remaining two species, A. grandis and Thuja plicata, have conversion factors of approximately 0.35, owing to the approximately horizontal orientation of their leaves. These two species are both relatively shade-tolerant, and the trend toward horizontal leaves might be an adaptation to assist in shade tolerance. A sensitivity analysis indicated that the foliage of most of the species maximized the amount of light gathered when the light was coming from almost straight overhead, as is the case with many shaded forest trees.Key words: leaf area index, conifers, leaf area index conversion.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".