The impacts of broadcast burning after clear-cutting on the diversity of ectomycorrhizal fungi associated with hybrid spruce seedlings in central British Columbia
Bibliographic record
Abstract
Morphological and molecular (polymerase chain reaction restriction fragment length polymorphism) methods were used to assess ectomycorrhiza (ECM) diversity in naturally regenerating and planted Picea engelmannii Parry ex Engelm. × Picea glauca (Moench) Voss seedlings in two recently clear-cut sites, two clear-cut and broadcast burned sites, and two mature forests (>100 years) in central British Columbia. Based on 24 characterized ECM, burning did not affect overall diversity (Shannon, Simpson, Shannon evenness, and Margalef indices). However, the occurrence and relative abundance of some ECM morphotypes varied significantly. Hebeloma and a Russulaceae type 1 were more abundant and Cenococcum was less abundant in planted seedlings from cut-burned sites compared with those from clear-cut sites. E-strain, MRA, and Amphinema were more abundant in planted seedlings from both cut-burned and clear-cut sites compared with naturally regenerating seedlings from mature sites. ECM diversity of regenerating seedlings was significantly greater in mature forests compared with clear-cut sites and was greater in planted seedlings than naturally regenerating seedlings in clear-cut sites. Molecular analysis of the internal transcribed spacer region of the nuclear-encoded ribosomal RNA gene repeat showed no significant differences among treatments or seedling type. Twenty-two genotypes were identified from eight common morphotypes: Cenococcum (one), Thelephora (two), E-strain, Tuber, Hebeloma, and Russulaceae type 1 (three each), MRA (four), and Amphinema (six). Hebeloma genotypes matched three for Amphinema; genotypes from unidentified lightly colonized tips matched those for E-strain, MRA, and Amphinema-Hebeloma.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".