The role of weather and topography in the development of Dothistroma septosporum.
Bibliographic record
Abstract
Dothistroma septosporum (Dorog.) Morelet is recognized worldwide as a foliar disease of pine trees, infecting needles and causing premature defoliation. This results in reduced growth of the tree and, in severe cases, death. Red banding, caused by the mycotoxin dothistromin, along needles where infection has been successful characterizes this fungal pathogen. Symptoms develop sooner with higher temperatures and longer wetness periods. In a severe outbreak of Dothistroma needle blight in the Skeena Stikine Forest District in northwestern British Columbia (BC), damage has ranged from low levels of infection to nearly 100% mortality. A high concentration of young susceptible hosts and warm, moist summers and cool, wet falls in this area are thought to be contributing to the outbreak. Heavy fogs that persist in plantations close to rivers, lakes, or streams may also facilitate D. septosporum development. The purpose of this research is to identify climatic and site conditions contributing to the development of Dothistroma needle blight with respect to the severe outbreak happening in northwestern BC. The main objectives are to monitor the variation in disease expression, identify the ranges of temperature and humidity conducive to disease development, and identify site factors associated with disease. In the Skeena Stikine Forest District four sites were selected according to signs of Dothistroma infection, accessibility, and the presence of trees within 10-25 years of age. Within each site, three plots were established for weekly monitoring. In each of the twelve plots, weather stations were set up and six trees were selected. Six plots also had leaf wetness sensors. On each tree, four cohorts of ten needles were marked. These needles were examined weekly for the development of red bands, fruiting bodies, and spore production. When fruiting bodies were detected, needles were extracted from the tree for dissection to determine their reproductive state. Survey data of lodgepole pine plantations in the Skeena Stikine
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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 | 0.000 | 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) | 0.001 | 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".