Feasibility of estimating stem size distribution from measurement on the largest trees in even-aged pure stands
Bibliographic record
Abstract
Reconstruction of the size distribution of trees in stands provides critical information for assessing the effects of environmental changes on forests and for forest management. For furthering a method of such reconstruction, feasibility of estimating size distribution in stem volume from measurement of the largest trees was examined for even-aged pure stands of Pinus banksiana Lamb.and Larix gmelinii (Rupr.) Rupr. We tested what percentage of the largest trees should be included in obtaining a frequency distribution in stem volume that is not statistically different from the observed size distribution patterns. The 3/2 power, beta-type, and adjusted beta-type distribution functions were applied. Comparison of the observed stem frequencies and those estimated from measurement of the largest trees in a stand suggested that (i) the 3/2 power distribution, beta-type distribution, or adjusted beta-type distribution may be used for reconstruction of stem size variation in pure stands, if the overall size variation could be approximated by one of these functions; (ii) we can be at least 95% sure that the tree size pattern be expressed successfully with the 3/2 power distribution with tree samples of only the largest 20% in the stand, or with the beta-type distribution with the largest 30% in the stand; and (iii) the reliability decreases somewhat for the adjusted beta-type distribution. The second observation implies that reconstruction of the temporal changes in stand structure may be reliable up to the time when the stand density was about five times that of the trees used for fitting the 3/2 power distribution curve. Reliability may be warranted up to the stand density of about three times as the number of trees used for fitting the beta-type distribution. Other considerations and limitations are also discussed.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".