Estimating site productivity in irregular stand structures by indexing the basal area or volume increment of the dominant species
Bibliographic record
Abstract
Estimating site productivity in irregular structures is complicated by variations in stand density, structure, composition in mixed stands, and suppression experienced by subordinate trees. Our objective was to develop an alternate to site index (SI) and demonstrate its application in models of individual-tree and stand growth. We analyzed coast redwood (Sequoia sempervirens (Lamb. ex D. Don) Endl.) tree and stand growth in a grid of 234 permanent sample plots covering a 110 ha study area in north coastal California. Partial harvesting created a mosaic of densities and openings throughout the 60-year-old redwood-dominated forest. Redwood SI was a poor predictor of volume increment (VI) per hectare among redwood in each plot over two decades after harvest. A new index of redwood basal area increment (BAI) productivity, calculated using inventory data for all stems in even-aged stands and the oldest cohort of multiaged stands, was a stronger predictor of VI. Diameter increment of individual redwood trees correlated strongly with stand density and the new BAI index. Forest managers should expect widely divergent responses following partial harvesting in crowded even-aged stands, with the greatest response coming from dominant redwoods with long crowns retained in areas with low residual stand density and high BAI index.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".