<i>Armillaria</i> species distribution and site relationships in <i>Pinus</i>- and <i>Tsuga</i>-dominated forests in Massachusetts
Bibliographic record
Abstract
The primary objective of this study was to determine the composition of Armillaria species in northeastern North American Pinus - and Tsuga -dominated forests. This was accomplished by sampling 32 plots at eight sites within pitch pine ( Pinus rigida Mill.), eastern white pine ( Pinus strobus L.), eastern white pine – mixed oak, and eastern hemlock ( Tsuga canadensis (L.) Carr.) forests. In total, 320 isolates were collected from 19 host tree species, with 207 of 320 (65%) of all isolations coming from Pinus and Tsuga. Armillaria solidipes Peck was the most abundant species, making up 188 of 320 (59%) of all isolations, which included 39 isolations from hardwoods. Meanwhile, Armillaria mellea (Vahl) P. Kumm. was collected a total of 27 times from eastern white and pitch pine. These two Armillaria species co-occurred at five of the eight sites sampled. Chi-square analyses showed that incidence of Armillaria species were significantly different by forest type. Pitch pine forests had a higher incidence of A. solidipes (p < 0.001), eastern white pine forests had a higher incidence of A. mellea (p = 0.001), and eastern hemlock forests had a higher incidence of Armillaria gallica Marxm. & Romagn. (p = 0.002) compared with expected values. The distribution of A. solidipes varied significantly by soil drainage and soil type, with a higher incidence on excessively drained (p < 0.001) and loamy sand (p < 0.001) soils.
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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 | 0.001 |
| 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".