Predicting the mortality of <i>Pinus sylvestris</i> attacked by <i>Gremmeniella abietina</i> and occurrence of <i>Tomicus piniperda</i> colonization
Bibliographic record
Abstract
The fungus Gremmeniella abietina (Lagerb.) Morelet is widely distributed in the northern hemisphere and causes scleroderris canker in several coniferous species. In Sweden, large areas, mainly with 30- to 40-year-old Scots pine (Pinus sylvestris L.) forests, were attacked by the fungus in 2000. The main aim of this study was to investigate the relationship between tree crown transparency (CT) induced by G. abietina and P. sylvestris tree mortality. Furthermore, regenerationcolonization by Tomicus piniperda (L.) was monitored in the investigated stands. Thirty-five permanent sample plots were established in five P. sylvestris stands (3846 years old) infected by G. abietina and located in the central part of Sweden. During the 2 years following the attack, the total tree mortality accounted for 380 trees·ha1 and 6.2 m2·ha1 on average in the five stands, corresponding to 35% of the trees and 27% of the basal area at the time of the attack. Galleries with broods of T. piniperda occurred in trees with a CT value higher than 97%. A model was derived for predicting the probability of P. sylvestris tree mortality. The mortality of individual trees was found to be related to CT, position of needle loss within the crown (CTPOS), and tree diameter at breast height. Furthermore, there was an interaction between CT and CTPOS and a tendency for CT and site to interact. For a P. sylvestris tree with a 0.16-m diameter at breast height and a CT value of 90% spread throughout the crown, the model indicated a mortality probability of 0.03. Above this CT value, the probability of mortality increased substantially. For coniferous species, irrespective of the cause of damage, a CT value of 90%95% appears to be a critical range; any values greater than this indicate a high probability of mortality.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".