A species- and site-specific stand density index based on growth and mortality
Bibliographic record
Abstract
A stand density index (SDI) was derived from three hypotheses, of which two concern mortality and growth up to the age at which there is an inflection point in growth, and the third relates mean tree volume and dbh (quadratic mean diameter at breast height) up to that age. The equations are [Formula: see text] or [Formula: see text], reference dbh = 25.4 cm or 10 inches. The parameters λ and β relate mean tree volume to dbh and stand volume to number of trees. Either equation provides a simple alternative to determining the self-thinning line and finding its slope, and also provides a direct comparison to the Reineke equation. Comparison of SDI values and exponents from the above equations to others’ results indicates the equations tend to produce smaller exponents, and larger SDI values, for dbh less than 25.4 cm. Values of [Formula: see text] varied with species and site quality, generally with smaller values than 1.605 for conifers, and larger values for angiosperms, when these were determined from yield tables, while values from experimental plots were always smaller than those from yield tables. Parameters must be estimated from data that are not significantly beyond the inflection age, and β and the ratio of growth to mortality parameters must be comparable.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".