Variation in soil microbial communities across a boreal spruce forest landscape
Bibliographic record
Abstract
We investigated soil microbial community structure by phospholipid fatty acid (PLFA) analysis in a mature boreal spruce forest landscape in southern Norway, with low diversity of vascular plants. We investigated the spatial variation in PLFAs and the importance of environmental variables in 10 plots (each 13 samples) in a study area of 1 km × 1 km. The scales investigated were 15 cm to 10 m within study plots and 100 m to 1 km between study plots. Soil microbial biomass varied 10-fold and we found a large variation in microbial community structure, even at distances of 15 cm. Samples aggregated into plots when PLFAs were subjected to a principal components analysis. Plot identity explained 36.3% of the variation in the PLFAs and geostatistical analysis showed that the microbial community structure displayed spatial dependence at within-plot distances. Environmental variables differed significantly between all plots but explained only minor parts of the variation in the overall PLFA pattern. The vegetation variables were, however, the best at explaining the PLFA pattern, and up to 60% of within-plot variation in individual plots, respectively, could be explained by vegetation variables, pH, and soil depth.
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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".