Effects of leaching on fungal growth and decay of western redcedar
Bibliographic record
Abstract
We tested the effect of leaching on the concentration of western red cedar (WRC; Thuja plicata Donn ex D. Don) heartwood extractives that are known to exhibit antimicrobial activity and correlated this with fungal growth and decay. We assessed the extractive tolerance of the following fungal species: Acanthophysium lividocaeruleum, Coniophora puteana, Heterobasidion annosum, Pachnocybe ferruginea, Phellinus sulphurascens, and Phellinus weirii by measuring their growth rate (mm/day) on media with or without WRC leachate. These data were correlated with the ability of the fungal species to grow on and decay leached versus nonleached WRC. We used an ergosterol assay to estimate growth and a standard soil-block test to assess decay. We estimated that leaching reduced the concentration of 5 major extractives: (-)-plicatic acid, beta-thujaplicin, gamma-thujaplicin, beta-thujaplicinol, and thujic acid by approximately 80%. Phellinus sulphurascens exhibited the lowest extractive-tolerance in vitro, grew poorly on and caused minimal decay in nonleached WRC, but it grew well on and decayed pine and leached WRC. Coniophora puteana, H. annosum, and P. weirii displayed moderate to high tolerance to leachate, grew on and caused decay in nonleached as well as leached WRC, but their growth and decay were always greatest on leached WRC and pine, suggesting that leaching enhances decay by these fungi. Acanthophysium lividocaeruleum and Pachnocybe ferruginea exhibited high extractive-tolerance. Whereas A. lividocaeruleum clearly caused decay on all types of wood, no decay was observed with Pachnocybe ferruginea, which grew very slowly in the different wood species, and it may or may not be able to decay wood.
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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) | 0.001 | 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 | 0.001 |
| 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".