High Abundances and Expression Levels of Atypical, Non‐Denitrifier N<sub>2</sub>O Reductases Drive Strong Microbial N<sub>2</sub>O Consumption Rates in a Minimally Impacted Mangrove Stand
Bibliographic record
Abstract
Abstract Knowledge of the ecological mechanisms governing N2O cycling in marine sediments lags that of water columns and terrestrial soils, leaving much to be learned about how microbial community dynamics relate to variability in sediment N2O fluxes. The present study assesses these relationships across two distinct environments by focusing on the community structure and activity of N2O reducing microorganisms. The N2O sink capacity of minimally impacted Bermudian mangrove sediments was first estimated using trace‐level microsensors and profile interpretation modeling. Molecular data obtained from these sediments were then compared with those from the Northeast Subarctic Pacific (NESAP) outer continental margin, where previous measurements suggest considerable N2O effluxes. Net N2O uptake was observed for mangrove sediments under ambient and elevated dissolved inorganic nitrogen concentrations (−0.22 ± 0.15 to −0.30 ± 0.26 μmol N2O m−2 d−1), suggesting the microbial potential for N2O consumption exceeded the potential for production via combined nitrification and denitrification. Targeting of bacterial nosZI and nosII gene clusters for quantification using qPCR indicated higher abundance and expression of non‐denitrifier nosZII genes in mangrove sediments demonstrating net N2O uptake. Net N2O production in NESAP sediments was associated with higher abundance and expression of nosZI genes associated with canonical denitrifiers. These results suggest that organisms possessing atypical nosZII genes may act as important N2O scavengers in low‐nitrogen coastal sediments.
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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 | 0.000 | 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 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".