Fungal and Bacterial Abundance in Long‐Term No‐Till and Intensive‐Till Soils of the Northern Great Plains
Bibliographic record
Abstract
Abundance of fungi and bacteria in long‐term no‐till (NT) and intensively tilled (IT) soils in the Northern Great Plains were measured using phospholipid fatty acid analysis (PLFA) to determine if a shift in the relative abundance of fungi and bacteria occurs as the result of conversion to NT. Four tillage trials located in four different soil zones were sampled in spring of 2005 and 2006 before the crop was seeded to evaluate the long‐term effect of tillage on the microbial community. With the exception of one site‐year, total, bacterial, and fungal PLFA were greater in NT than IT soils at the soil surface (0‐ to 5‐cm depth) ( p < 0.05). Increases ranged from 8 to 202% for total biomass, 26 to 58% for bacterial biomass, and 0 to 120% for fungal biomass. At one site (Ellerslie) all biomass measurements were greater in IT than NT in 2005 and bacterial biomass was also greater under IT in 2006. The influence of tillage on microbial biomass was less pronounced with depth. Fungal dominance is commonly assumed under NT; however, our results demonstrate that although biomass of both fungi and bacteria increase in NT, the abundance of fungi vs. bacteria was not consistently greater under NT in the soils studied. Further research is needed to determine if fungi may be able to exert a more functionally dominant role in NT soils without an increase in relative abundance.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".