Root-associated fungi of <i>Pinus wallichiana</i> in Kashmir Himalaya
Bibliographic record
Abstract
An important factor in the performance of out-planted conifers is the association of plant roots with ectomycorrhizal (EcM) fungi. However, limited information is available about the diversity of root-associated EcM fungi of Pinus wallichiana A.B. Jackson, a coniferous species endemic to Himalayan forests that has hampered the reforestation programs in the area. The study was carried at three major forest areas of the Kashmir Himalaya believed to be pure stands of P. wallichiana. Fine root tips harbouring EcM fungi were collected and processed for extraction of fungal DNA, which was subsequently subjected to ITS rDNA targeted PCR–RFLP profiling. DNA sequencing analysis of the overlapping ITS amplifications followed by global nucleotide BLAST analyses of the assembled nuclear ribosomal DNA (rDNA) revealed a total of 33 fungal taxa associated with P. wallichiana of which 23 species were EcM fungi. Of the 10 non-EcM fungi, we found a peculiar saprophytic wood decaying fungus, Chalara microchona, associated with P. wallichiana for the first time. The study not only reveals the species richness of fungi associated with this conifer but also documents new fungal associations with it, which have not been reported so far. The results in the study set a baseline for the broad association of ectomycorrhizal fungi with P. wallichiana, which may serve as guiding cue to design reforestation programs in the Kashmir Himalaya.
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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) | 0.000 | 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".