Probability of fusiform rust in southern pines varies with pine species, management, stand age, and oak species
Bibliographic record
Abstract
Fusiform rust disease has been one of the most damaging diseases in the southeastern United States pine forests. Tree improvement programs and other silvicultural techniques have been applied to control the disease. Recent evidence suggests a potential species-specific decline in disease prevalence in some geographical regions. Previous studies had mostly focused on plantations and selected regions of the species ranges. In this study, we tried to understand the relationship between fusiform rust disease incidences and key tree and forest variables for both natural and planted stands of the three dominant southeastern pine species across the southern region using Forest Inventory and Analysis data. We applied generalized linear mixed models to describe the relations between the disease and the characteristics of pine trees and forest stands. We found pine species, management, stand age, and presence of certain oak species are related to the disease. While slash pine plantations had a higher incidence of disease, loblolly pines were less infected in plantations than in natural stands, likely due to the positive impact of disease-resistant plantation stocks. We suggest further efforts are necessary to control fusiform rust in slash pine plantations and management actions could focus on controlling specific oak species.
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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 | 0.000 |
| 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".