Land-use, landform, and seasonal-dependent changes in microbial communities and their impact on nitrous oxide emission activities
Bibliographic record
Abstract
The greenhouse gas nitrous oxide (N2O) is produced mainly by the microbial processes of nitrification and denitrification. I hypothesized that microbial community structure (composition and abundance) is linked to differences in soil N2O emissions from these two processes. Microbial community composition (type and number of nitrifier and denitrifier genotypes), abundance and N2O emission activity were determined and compared for soils from two landscapes characteristic of the North American “prairie pothole region” (cultivated vs. uncultivated wetlands). The landscape difference in composition of individual microbial communities was not predictive of soil N2O emissions, indicating that there is redundancy in each microbial community in relation to N2O emission activities. However, community factors influenced the pattern and distribution of N2O emission from the soils of the study site. For example, nitrification was the dominant N2O emitting process for soils of all landforms. However, neither nitrifier amoA abundance nor community composition had predictive relationships with nitrification associated N2O emissions. This lack of relationship may be a consequence of using amoA as the gene target to characterize nitrifiers. For denitrifying bacteria, there was a temporal relationship between community composition and N2O emissions. However, this may be related to the change in water-filled pore space over time. Alternatively, the presence of fungi can be linked directly to N2O emissions from water accumulating landform elements. Under hypoxic conditions, there may be two fungal pathways contributing to N2O release: fungal denitrification via P450nor and fungal heterotrophic nitrification. Results suggest that the relative importance of these two processes is linked to root exudates such as formate. It is the interaction between the seasonal fluctuations of the microbial and environmental factors that determine the level of N2O emissions from soils.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".