Diversity of <i>nirK</i> Denitrifying Genes and Transcripts in an Agricultural Soil
Bibliographic record
Abstract
Environmental conditions can change dramatically over a crop season and among locations in an agricultural field and can increase denitrification and emissions of the potent greenhouse gas nitrous oxide. In a previous study, changes in the overall size of the denitrifier community in a potato crop field were relatively small and did not correlate with variations in environmental conditions or denitrification rates. However, denitrifying bacteria are taxonomically diverse, and different members of the community may respond differently to environmental changes. The objective of this research was to understand which portion of the nirK denitrifying community is active and contributes to denitrification under conditions in a potato crop field. Denaturing gradient gel electrophoresis (DGGE) of nirK genes in soil-extracted DNA showed changes in the composition of the nirK denitrifier community over the growing season and among spatial locations in the field. By contrast, the composition of the active nirK denitrifier community, as determined by DGGE analysis of nirK transcripts derived from soil-extracted mRNA, changed very little over time, although differences in the relative abundance of some specific transcripts were observed between locations. Our results indicate that the soil denitrifier populations bearing nirK genes are not all contributing to denitrification and that the denitrifying populations that are active are among the most abundant and ubiquitous nirK-bearing denitrifiers. Changes in the community composition of the total and active nirK denitrifiers were not strongly correlated with changes in environmental factors and denitrification activity.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".