Seasonal influences on fungal community structure in unimproved and improved upland grassland soils
Bibliographic record
Abstract
Seasonal and management influences on the fungal community structure of two upland grassland soils were investigated. An upland site containing both unimproved floristically diverse (U4a) and improved mesotrophic (MG7b) grassland types was selected. Samples from both grassland types were taken at five times in one year. Soil fungal community structure was assessed using fungal automated ribosomal intergenic spacer analysis (ARISA), a DNA-profiling approach. A grassland management regime was found to strongly affect fungal community structure, with fungal ARISA profiles from unimproved and improved grassland soils differing significantly. The number of fungal ribotypes found was higher in unimproved than improved grassland soils, providing evidence that improvement may reduce the suitability of upland soil as a habitat for specific groups of fungi. Seasonal influences on fungal community structure were also noted, with samples taken in autumn (October) more correlated with change in ribotype profiles than samples from other seasons. However, seasonal variation did not obscure the measurement of differences in the fungal community structure that were due to agricultural improvement, with canonical correspondence analysis indicating grassland type had a stronger influence on fungal profiles than did season.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".