Soil characteristics more strongly influence soil bacterial communities than land-use type
Why this work is in the frame
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Bibliographic record
Abstract
To gain insight into the factors driving the structure of bacterial communities in soil, we applied real-time PCR, PCR-denaturing gradient gel electrophoreses, and phylogenetic microarray approaches targeting the 16S rRNA gene across a range of different land usages in the Netherlands. We observed that the main differences in the bacterial communities were not related to land-use type, but rather to soil factors. An exception was the bacterial community of pine forest soils (PFS), which was clearly different from all other sites. PFS had lowest bacterial abundance, lowest numbers of operational taxonomic units (OTUs), lowest soil pH, and highest C : N ratios. C : N ratio strongly influenced bacterial community structure and was the main factor separating PFS from other fields. For the sites other than PFS, phosphate was the most important factor explaining the differences in bacterial communities across fields. Firmicutes were the most dominant group in almost all fields, except in PFS and deciduous forest soils (DFS). In PFS, Alphaproteobacteria was most represented, while in DFS, Firmicutes and Gammaproteobacteria were both highly represented. Interestingly, Bacillii and Clostridium OTUs correlated with pH and phosphate, which might explain their high abundance across many of the Dutch soils. Numerous bacterial groups were highly correlated with specific soil factors, suggesting that they might be useful as indicators of soil status.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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 it