A comparison of methods of determining the allowable cut on the University of British Columbia research forest, Haney, B.C.
Bibliographic record
Abstract
Generally it is not adequate to calculate an allowable cut for a property by only one formula or method. Usually it is preferable to utilize all the information available with as many suitable formulae or methods as possible to obtain reasonable estimates of the yearly utilization rates by several approaches. For the University Research Forest fifteen different formulae and methods were selected for comparison, because their basic assumptions appeared applicable to this forest. The methods and formulae tested were: Methods: Area regulation, Area-volume check, Area-volume allotment, Barnes’ and H. A. Meyer's. Formulae: Austrian, Black Hills, Grosenbaugh, Hanzlik, Hundeshagen, Kemp, W. H. Meyer, S. Petrini (compound and simple interest) and Von Mantel. Appropriate inventory techniques were developed in order to collect the necessary information regarding rates of growth, mortality and numbers of trees per acre by diameter classes. Present and future decadal growing stocks were estimated. Simple and compound growth rates, including and excluding ingrowth, for all types were calculated separately for stands over eighty years of age and for stands under eighty years. The inventory was based on the areas and estimates taken from 1961 aerial photographs supplemented by both temporary and permanent sample plots, employing primarily the principles of the point sampling techniques as described by L. R. Grosenbaugh. After substituting the actual data into the formulae and various methods, allowable cut estimates for 3.1, 9.1, 11.1, and 13.1 inches minimum diameter limits were calculated. Allowances were made for an intermediate standard of utilization and for waste, breakage and decay. Considering the inventory and the allowable cut calculations it was found that: 1. Simple area regulation will lead to undesirably large fluctuations in allowable cut. 2. Volume formulae are useful means of determining the yearly harvest volume, though the distribution of the cut on the ground requires definition in terms of area as well. 3. Neither area nor volume control can be used exclusively. Some combination and integration is usually necessary in actual practice. In the case of the Research Forest this can be applied most conveniently by following the area-volume computation basis.
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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 | 0.025 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".