The arbuscular mycorrhizal fungal communities associated with Taxus brevifolia (western yew) are sensitive to soil pH and neighborhood forest composition
Bibliographic record
Abstract
Temperate rainforest systems are being radically altered by commercial timber harvest and climate change, imposing unprecedented stress on the trees and their mycorrhizal fungal communities. We used marker gene sequencing to describe the arbuscular mycorrhizal fungal (AMF; phylum Mucoromycota) communities associated with in-situ, mature Taxus brevifolia Nutt. (western yew) and co-occurring Acer glabrum var. douglasii (Douglas maple) and Thuja plicata Donn ex. D. Don (western redcedar) in the inland temperate rainforests of southern interior British Columbia. We identified a total of 48 phylogroups (virtual taxa; VT) in the Mucoromycota, and observed a high degree of overlap in AMF composition within mixed-species groups at the same location. We additionally observed an unusually linear relationship between rhizosphere soil pH and the AMF richness of T. brevifolia. Rhizosphere soil pH was further related to the tree canopy composition (i.e., dominant and codominant tree species) immediately adjacent to the host trees. These results confirm that this community of late-seral temperate tree species shares a common guild of AMF and suggest that T. brevifolia and its associated AMF may be particularly sensitive to environmental changes, such as shifts in neighborhood forest composition.
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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 | 0.001 | 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".