Effects of mutual shading of tree crowns on prediction of photosynthetic light-use efficiency in a coastal Douglas-fir forest
Why this work is in the frame
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Bibliographic record
Abstract
Gross primary production (GPP) is often expressed as the product of absorbed photosynthetically active radiation and the efficiency (epsilon) with which a plant community uses absorbed radiation in biomass production. Light-use efficiency is affected by environmental stresses, and varies diurnally and seasonally. Uncertainty about epsilon can be a serious limitation when modeling GPP. An important determinant of epsilon is the amount and type of solar radiation incident on a canopy, because an abundance of light can trigger a photo-protective reaction, diminishing GPP. The radiation regime in a forest canopy is determined by the predominant sky conditions and by mutual shading of tree crowns. Shading effects, producing shifts in the amount of incident direct and diffuse solar radiation, have been largely ignored, however, because they depend on forest structure and are difficult to measure. We describe a new approach for estimating changes in mutual canopy shading throughout the day and year based on a canopy structure model derived from light detection and ranging (LiDAR). Proportions of canopy shading were then combined with eddy covariance data to assess the explanatory power for variance in epsilon by regression tree analysis over half-hourly, daily and weekly time scales. The approach explained between 75 and 97% of variance in epsilon, representing an increase of between 5 and 16% compared with models driven solely by meteorological variables.
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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 it