Species diversity of corticolous myxomycetes in Tianmu Mountain National Nature Reserve, China
Bibliographic record
Abstract
The species diversity of corticolous myxomycetes on 4 vegetation types in the Tianmu Mountain National Natural Reserve, eastern China, was examined from 2011 to 2012. A total of 1440 moist chamber cultures were prepared with bark samples, which yielded several hundred collections representing 42 species in 20 genera. It was found that 79% of cultures produced some evidence (either plasmodia or fruiting bodies) of myxomycetes. Eight species (Comatricha elegans, Cribraria confusa, Licea pusilla, Cribraria microcarpa, Collaria arcyrionema, Licea biforis, Arcyria cinerea, and Clastoderma debaryanum) were abundant (exceeding 3% of all records), but about a third of all species were classified as rare. Species richness (S = 33) and diversity (exp[H'] = 16.60, S/G = 1.74) of corticolous myxomycetes were the most diverse in the deciduous broadleaf forest. The species recorded from coniferous forest showed the lowest species richness (S = 21) but the highest evenness (J' = 0.91). The cluster analyses were based on the Bray-Curtis similarity matrix, and the results indicated that corticolous myxomycete assemblages were distributed by a seasonal and annual pattern. Canonical correspondence analysis showed that season and pH were key factors in determining species distribution.
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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 | 0.000 | 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".