Biodiversity of foliar fungal endophytes in white spruce (<i>Picea glauca</i>) from southern Québec
Bibliographic record
Abstract
The objective of this study was to investigate the foliar endophyte biodiversity of white spruce ( Picea glauca (Moench) Voss to establish a baseline for future comparative studies examining the impact of forestry practices. It identifies for the first time endophytic fungi living inside the needles of white spruce from 280 needles collected in seven natural stands in southern Québec. The endophyte colonization rate on surface sterilized needles was 53.2%. We performed a PCR-RFLP and sequence analysis on the ITS region of the nuclear ribosomal DNA to achieve molecular identification. Isolate ITS sequences were compared with data from GenBank presenting the best similarity and were analyzed by a maximum of parsimony and Bayesian inference. Relationships between morphological groups, digestion groups, and sequence groups were investigated. In all, 23 morphotypes were found to belong to 14 sequence groups and we demonstrated that morphological groups are poor indicators for estimating species diversity. This study is the first to establish species richness values for foliar endophytes. Among the 141 isolates in this study, 75.15% have a high sequence similarity with Lophodermium piceae , 10.95% with an unknown species of Mycosphaerella , and 5.5% with two species of the genus Hypoxylon . Distribution, incidence and biological significance of all the endophytes found in this study are discussed.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".