Characterization of <i>Pinus</i> ectomycorrhizas from mixed conifer and pygmy forests using morphotyping and molecular methods
Bibliographic record
Abstract
We used morphotyping and molecular methods to characterize ectomycorrhizas of bishop pine (Pinus muricata D. Don) and Bolander pine (Pinus contorta ssp. bolanderi (Parl.) Critchf.) from mixed conifer and hydric pygmy forests on the northern California coast. Sixteen ectomycorrhizal morphotypes were described, producing 15 internal transcribed spacer restriction fragment length polymorphism (ITS-RFLP) types, and 12 were identified via ITS sequencing. From a given site, all root tips of a specific morphotype produced identical ITS-RFLP patterns. However, sometimes two morphotypes produced the same ITS-RFLP type, and sometimes samples of the same morphotype from two different sites produced two different ITS-RFLP types. These results indicate that surveys of ectomycorrhizal fungi based on morphology alone are not sufficient, and that grouping morphotypes prior to molecular analysis can expedite the process. Ectomycorrhizas from mixed conifer included Russuloid sp., Tomentella sublilacina (Ellis & Holw.) Wakef., Tuber sp., and two Thelephoroid species. Ectomycorrhizas from hydric pygmy included two Dermocybe spp., a Cortinarius sp., two Thelephoroid spp., and Suillus tomentosus (Kauffman) Singer. Both plant communities contained Cenococcum geophilum Fr.:Fr. The hydric pygmy sites were more similar to each other than to the mixed conifer site (Jaccard similarity). The presence of ectomycorrhizal taxa in one plant community type may reflect biotic (host specificity) or abiotic (soil fertility or hydrology) adaptation.Key words: ectomycorrhiza, bishop pine, Pinus muricata, Bolander pine, Pinus contorta ssp. bolanderi, morphotyping, ITS-RFLP.
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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 | 0.000 | 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".