Distribution and diversity of zoosporic fungi from soils of four vegetation types in New South Wales, Australia
Bibliographic record
Abstract
Chytrids are common microfungi in soils, but their distribution and diversity in Australian soils is poorly described. In this study we analyzed chytrid distribution and diversity in soils from four collection sites representing a subtropical rain forest, wet sclerophyll forest, dry sclerophyll forest, and open heath, using a defined and reproducible sampling protocol. The greatest number of chytrid species was observed from dry sclerophyll forest soils, while the least number of species occurred in the open heath soils, although each soil sample of the open heath harbored more species per sample. Differences in patterns of distribution of chytrid species were statistically significant between subtropical rain forest and open heath. Patterns in other habitats differed but could not be verified statistically to be significant at the 5% level. Observed differences in chytrid distribution, diversity, and freqency indicate that their ecological strategies may be in response to environmental cues such as specific edaphic conditions and substrate availability, and their capacity to respond to the environment.Key words: Chytridiomycota, frequency, habitat, sampling.
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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 | 0.001 |
| 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 | 0.001 |
| 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".