Compatible diameter and height increment models for lodgepole pine, trembling aspen, and white spruce
Bibliographic record
Abstract
In this study, compatible height and diameter increment models were fitted for lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.), trembling aspen ( Populus tremuloides Michx.), and white spruce ( Picea glauca (Moench) Voss), using the relationship between diameter and height growth. It was assumed that tree diameter increment is directly proportional to height increment, and the proportionality constant is a function of competition and site productivity. The results showed that the fit statistics are comparable with results of other studies, with adjusted R2ranging from 30% to 50%. A validation test of the models, using independent permanent sample plots data, showed that the short-term predictions of the models for both pure and mixedwood stands are fairly unbiased. The models also gave reasonable average height growth and diameter growth trajectories for pure stands of the three species and also projected long-term mixedwood (aspen – white spruce mixture) volume growth dynamics reasonably well. The models also projected reasonably well (i) the effect of increasing initial stem density on average diameter and height, and (ii) the stand volume compared with an older version the Mixedwood Growth Model (ver. 2000A). It was concluded that explicitly linking tree height and diameter increment models does not only have a solid ecological basis, but it also results in a compatible prediction of tree growth and stand dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".