Forest composition following overstory mortality from southern pine beetle and associated treatmentsExperiment Station Project 06-08-109 of the Kentucky Agricultural Experiment Station, Lexington, Kentucky.
Bibliographic record
Abstract
Bark beetle caused mortality continues to play a critical role in determining the composition and structure of forests in North America, and revegetation dynamics following these disturbances are poorly understood. We assessed forest composition following southern pine beetle, Dendroctonus frontalis Zimmermann, mortality and associated cut and leave suppression, and compared them with undisturbed loblolly pine, Pinus taeda L., stands in Texas. Abundant hardwood regeneration dominated the understory, with little loblolly pine regeneration following either mortality event. Disturbances eliminated loblolly pine dominance in these even-aged stands, thus stratifying forest structure and apparently increasing stem density (stems·ha –1 ), richness (species·ha –1 ), and diversity (ha) in the lower strata. Aspect and elevation, presumably through influences on site moisture, were the primary gradients associated with vegetation variation in the canonical correspondence analyses for new regeneration. Mortality from Dendroctonus and cut and leave practices shifted loblolly pine communities to mixed upland hardwoods in model predictions generated by the southern variant of the Forest Vegetation Simulator. In addition to being an effective bark beetle control, cut and leave suppression did not alter predicted forest composition 50 years hence when compared with unsuppressed bark beetle-caused mortality. Because of the predicted shift to hardwood domination and a low pine basal area, it is expected that mortality from D. frontalis and cut and leave will substantially reduce future hazards from D. frontalis outbreaks.
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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 | 0.001 | 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) | 0.000 | 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".