Height growth and vertical development of an old-growth<i>Pseudotsuga</i>-<i>Tsuga</i>forest in southwestern Washington State, U.S.A.
Bibliographic record
Abstract
A detailed analysis of diameter-height relationships was applied to an old-growth Pseudotsuga menziesii (Mirb.) Franco var. menziesii - Tsuga heterophylla (Raf.) Sarg. forest in southwestern Washington State, U.S.A., to predict future development of vertical stratification among tree species. Differences among species in relative abundance and size structure resulted in diameter-height regressions of varying certainty and stability. Damage and shading had negative impacts on predicted heights and estimates of maximum attainable height (Hmax) in all species. However, species varied as to the main causes and size dependency of damage in relation to tree height. Current height-growth rates of the upper canopy species declined with increasing tree height, reaching minimum values near the predicted Hmax. The future development of the forest canopy would involve a slow invasion of the upper canopy by Tsuga heterophylla and Thuja plicata Donn ex D. Don, as P. menziesii are near their maximum attainable height, and Abies amabilis Dougl. ex Forbes and Taxus brevifolia Nutt. are restricted to the middle to lower canopy. However, if current height-growth rates continue, P. menziesii should maintain its dominant status in the upper canopy for at least another century.
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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".