F-OREST MANAGEMENT NOTE Note 58 Northwest Region PREDICTING DENSITY-RELATED LODGEPOLE PINE HEIGHT GROWTH IN ALBERTA
Bibliographic record
Abstract
For most tree species, height growth of domi nant and codominant trees is unaffected by stand density over a fairly wide range. Lodgepole pine (Pinus contorta Doug!. var. latifolia Engelm.) is an exception because even moderate density reduces its height growth and associated timber production, thus. diminishing the value of traditional site index (S1) as a productivity measure for this species. The approach used in this note recognizes that reduction of density-related lodgepole pine height growth is a dynamic process that changes during the life of a stand; it may not occur in a stand at the juvenile stage but become a very strong factor in the young and intermediate-age stand, and then lessen in the old stand. Models using cumulative functions and/or the traditional fixed-age SI models (e.g., Johnstone 1976) are unsuitable for describing this phenomenon. Cieszewski and Bella (1993) developed a new height-growth model based on annual height increments as a function of density. This model can represent changing conditions caused by thinning or natural mortality, and at the same time it could be used with minimum input requirements for thin ning prescriptions across a range of stand densities. This note describes the application of the new density-related height-growth model for lodgepole pine (Cieszewski and Bella 1993) that allows stand density changes to be examined and results predicted in terms of height growth, and provides the basis for spacing and thinning prescriptions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".