The impact of soil, altitude, and climate on tree form and wood properties of plantation grown <i>Pinus patula</i> in Mpumalanga, South Africa
Bibliographic record
Abstract
Abstract Plantation forests were originally established in South Africa to meet an increasing demand for solid wood products as there was a limited supply from native forests. The majority of the commercial softwood plantations were established with Mexican Pinus patula . Since growing conditions are known to impact tree growth, tree form, and wood quality of P. patula , sample plots were established over a cross-section of plantations in the Lowveld Escarpment and Highveld forestry regions of South Africa that covered an array of geologies and altitudes. Each sample plot was classified according to soil properties, rainfall, and temperature, and trees within the plots were measured for growth, form, and wood properties. Soil, growing days, and temperature were found to have little impact on tree form and wood properties. However, rainfall and specifically, spring rainfall, was found to have a highly significant impact on late wood formation, proportion of juvenile core, and wood density. In addition, tree height was found to be strongly correlated with maximum annual temperature.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".