Structure of soil microbial communities in sugi plantations and seminatural broad-leaved forests with different land-use historyThis article is one of a selection of papers published in the Special Forum on Towards Sustainable Forestry — The Living Soil: Soil Biodiversity and Ecosystem Function.
Bibliographic record
Abstract
Phospholipid fatty acid profiles were used to evaluate microbial community composition in different soil layers of sugi ( Cryptomeria japonica (L.f.) D. Don) plantations and seminatural secondary forests in southeastern Kyushu, Japan. These forests had previously been utilized as meadows or coppices. Principal components analysis and canonical correspondence analysis of the phospholipid fatty acid data demonstrated differences in microbial community structure between current vegetation (sugi plantations or seminatural forests) in the FH layer. In contrast, differences between the previous land-use types (meadows or coppices) were detected through variation in the soil microbial community structure in the upper part of the A layer (0–5 cm). However, in the deeper part of the A layer (5–10 cm), the influence of the previous land-use history on soil microbial community structure was weak and the influence of the current vegetation could be detected. In the 0–5 cm part of the A layer, the organic matter was correlated with the microbial community structure. However, it cannot be assumed that these soil chemical characteristics were the principal factors responsible for separation of the microbial communities based on previous land-use history because the difference in chemical characteristics between the sites was small.
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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 | 0.001 |
| 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".