Age and diameter structure of a managed uneven-aged oak forest
Bibliographic record
Abstract
We studied the age and diameter structure on one section (259 ha) of a 63 000-ha privately owned forest in the Ozark Highlands of Missouri. The forest has been managed using a partial cutting strategy since 1954. Because a majority of the trees predate current management practices, the existing stand structure is a function of not only the current silvicultural system and the dynamics of this ecosystem but also the initial stand conditions. To determine age structure and evaluate the relationship of diameter and age, a random sample of 600 oaks [Formula: see text]4 cm DBH were collected from ten 0.4-ha plots. Based on the test of a binomial proportion, the oak populations on 7 of the 10 plots were deemed uneven aged, two were deemed two aged, and one was even aged. DBH accounted for 40 (red oaks) to 62% (white oaks) of the variation in tree age. Although the overall diameter frequency distribution of oaks formed a reverse-J shape, the age-frequency distribution approximated a normal (bell-shaped) distribution. We show how this apparent inconsistency between diameter and age distributions can be an artifact of a minimum sampling diameter. Such a truncation of the sampled population reduces the observed frequency of trees in the younger age-classes, which in turn results in a bell-shaped rather than a reverse-J-shaped age-frequency distribution. Thus, the lack of a reverse- J-shaped age distribution should not be interpreted as a failure to sustain regeneration in an uneven-aged stand.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".