Allometries of coarse tree, stem, and crown measures in Douglas-fir are altered by Armillaria root disease
Bibliographic record
Abstract
We used allometric relationships to quantify Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) stem and crown adaptation to Armillaria root disease (caused by Armillaria ostoyae (Romagn.) Herink). At four sites, we measured height, diameter, height to live crown, crown width and length, sapwood area at base of live crown, and infection duration for healthy and infected Douglas-fir trees. Diseased trees were on average smaller than healthy trees for all measured variables, but there were also proportional changes between tree parts suggesting allocation shifts to disease. Infected trees were shorter in relation to stem diameter compared with healthy trees by 4% on average. Crown diameter was positively related to stem diameter (0.24 m·cm–1) but not to disease or competition. Diseased tree crown lengths were on average 0.5 m shorter for a given crown diameter than healthy trees—akin to response to light competition except this also occurred in the upper canopy. Prolonged infection reduced crown length probably through shedding of lower branches and by reducing stem apical growth, possibly related to changed hydraulic architecture or light requirements. Crown surface area was related to stem sapwood area (0.81 m2·cm–2) but unaffected by disease or competition. We discuss how shifting allocation could reveal important implications for life strategies involving whole tree adaptations to disease and tree to tree interactions, and for wood quality and forest inventory.
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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) | 0.000 | 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".