Ringbarking to manage Armillaria root disease in the forests of central British Columbia
Bibliographic record
Abstract
Armillaria root disease, caused by the fungus Armillaria ostoyae (Romagn.) Herink, is an important agent of diversity in the forests of British Columbia. Forest operations can disrupt co-evolved host-pathogen balances, leaving behind a supply of carbohydrate-rich defenceless stumps, allowing for a post-harvest inoculum flush and disease spread. One management option is pre-harvest ringbarking, requiring the removal of a strip of bark, phloem, and cambium around a tree, in an attempt to limit carbohydrate transportation to the roots. In theory, ringbarking should deplete starch levels in roots prior to harvest, restricting A. ostoyae's energy base, directly limiting the pathogen, and indirectly increasing saprophytic competition and exclusion. I set out to determine if ringbarking Armillaria root disease centres in the forests of central BC prior to harvest would have a short-term influence on A. ostoyae's characteristic post-disturbance inoculum flush. My objectives were to quantify A. ostoyae colonization and starch content within the roots of ringbarked and untreated Douglas-fir (Pseudotsuga menziesii var. glauca (Mirb.) Franco (Beissn.) Franco). Thirty-six plots were established across three sites, with ringbarking randomly applied to eighteen plots. Sites were clearcut and sample stumps excavated. Armillaria ostoyae colonization was quantified by scoring disease severity of roots and by measuring percent colonized root lengths. Root samples were quantitatively analyzed for starch content. Logistic mixed models were used to assess incidence data, and linear mixed models to assess categorical measures of colonization severity, as well as intensive measures of colonization and starch content. No statistically significant differences were observed in post-harvest A. ostoyae colonization or starch content on roots from ringbarked trees versus untreated plots at any site or overall. My study was unable to confirm that ringbarking trees in Armillaria root disease centres prior to their felling influences starch content or colonization within root systems following harvest. My results combined with reviewed literature instead suggest that ringbarking may provide control through a host stress response mechanism. Additional long-term research is required to clarify the mechanisms of control and the effectiveness of treatment. Future work should address challenges surrounding initial disease assessment, treatment methods and timing, sampling, and the quantification of colonization and starch.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".