Climate, radial growth, and mortality associated with conifer regeneration infected by root disease (<i>Armillaria ostoyae)</i>
Bibliographic record
Abstract
Tree root disease caused by the pathogen Armillaria ostoyae (Romagn.) Herink has notable influence on bio-economic systems of southern British Columbia (BC) and the northwestern United States. Annual radial growth and mortality trends of regeneration associated with A. ostoyae during the first 21 years of a plantation were investigated. Our dendrochronological approach focused on a plantation established in 1991 with Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), western larch (Larix occidentalis Nutt.), and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm. ex S. Wats.). We examined tree rings for reduced growth onset (RGO) to estimate infection periods. Among trees studied, we found that the number of RGO events peaked in 2006 followed by a steady decline in frequency. A similar trend was seen in annual mortality rates which reached maximum values in 2007 followed by an uninterrupted decrease. The average number of years from RGO to death based on host species ranged from 2.3 to 3.6 years. According to on logistic regression modeling, values associated with drought codes and duff moisture codes were significant in determining the year of death for infected trees. The predicted increase in frequency of summer droughts may lead to elevated mortality associated with A. ostoyae in young plantations.
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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".