Comparison of direct and indirect estimation of leaf area index in mature Norway spruce stands of eastern Germany
Bibliographic record
Abstract
IIn three mature Norway spruce (Picea abies (L.) Karst.) stands of the Erzgebirge (Ore Mountains) in eastern Germany, the performance of the LAI-2000 plant canopy analyzer (LI-COR instruments) was tested for indirect estimation of leaf area index (LAI). The LAI-2000 calculates effective leaf area index (LAIe, m2/m2) resulting from radiation measurements and subsequent model calculations. LAIe underestimated directly estimated half the total leaf area index (LAI0.5t, m2/m2) by 37-82% as determined from allometric relationships derived from subsample harvesting. The degree of underestimation was dependent upon stand density in two of three spruce stands examined; it was the highest in sparsely stocked plots. The relationship of LAIe to allometrically determined LAI0.5t for one of the three stands differed significantly from the other two spruce stands and the underestimation of LAI0.5t was less distinct. This was explained by stand structure, i.e., higher amounts of nonassimilating surfaces relative to LAI0.5t. These results indicate that the LAI-2000 is not generally applicable for estimation of LAI in mature spruce stands of the Erzgebirge because of effects of stand structure on LAIe-LAI0.5t relationships, which are stand specific.
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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 | 0.001 | 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".