Changes in Denitrifier Abundance, Denitrification Gene mRNA Levels, Nitrous Oxide Emissions, and Denitrification in Anoxic Soil Microcosms Amended with Glucose and Plant Residues
Bibliographic record
Abstract
In agricultural cropping systems, crop residues are sources of organic carbon (C), an important factor influencing denitrification. The effects of red clover, soybean, and barley plant residues and of glucose on denitrifier abundance, denitrification gene mRNA levels, nitrous oxide (N(2)O) emissions, and denitrification rates were quantified in anoxic soil microcosms for 72 h. nosZ gene abundances and mRNA levels significantly increased in response to all organic carbon treatments over time. In contrast, the abundance and mRNA levels of Pseudomonas mandelii and closely related species (nirS(P)) increased only in glucose-amended soil: the nirS(P) guild abundance increased 5-fold over the 72-h incubation period (P < 0.001), while the mRNA level significantly increased more than 15-fold at 12 h (P < 0.001) and then subsequently decreased. The nosZ gene abundance was greater in plant residue-amended soil than in glucose-amended soil. Although plant residue carbon-to-nitrogen (C:N) ratios varied from 15:1 to 30:1, nosZ gene and mRNA levels were not significantly different among plant residue treatments, with an average of 3.5 x 10(7) gene copies and 6.9 x 10(7) transcripts g(-1) dry soil. Cumulative N(2)O emissions and denitrification rates increased over 72 h in both glucose- and plant-tissue-C-treated soil. The nirS(P) and nosZ communities responded differently to glucose and plant residue amendments. However, the targeted denitrifier communities responded similarly to the different plant residues under the conditions tested despite changes in the quality of organic C and different C:N ratios.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".