Competition dynamics in pure- versus mixed-family stands of loblolly and slash pine in the southeastern United States
Bibliographic record
Abstract
Few studies within the native range of loblolly ( Pinus taeda L.) and slash pine ( Pinus elliottii Engelm. var. elliottii) have compared yield and stand dynamics in pure-family block versus mixed-family block plantings under a range of silvicultural treatments. Understanding intergenotypic competitive interactions is important for predicting phenotypic performance, defining growth strategies and ideotypes, and deploying the correct mix of families that possess complementary characteristics for enhanced yield and pest resistance. In 2000, replicated experimental trials were installed in the southeastern United States, controlling for genotype (pure- and mixed-family plantings; consisting of seven full-sibling loblolly and six full-sibling slash pine families), planting density (1334 vs. 2990 trees/ha), and levels of silvicultural treatment intensity (operational vs. intensive). We measured four installations of these trials. There were numerous examples of differential family performance in mixed versus pure plots manifested as significant deployment × family interactions for diameter at breast height, height, basal area, volume, survival, disease, and damage traits. Significant and consistent interactions of several families with mixed versus pure deployment led to the identification of putative crop and competition ideotypes in both loblolly and slash pine. Tree-level crown architectural traits and an index of growth efficiency for the identified families were consistent with the hypothesized ideotypes.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".