The rates and players of denitrification, dissimilatory nitrate reduction to ammonia (DNRA) and anaerobic ammonia oxidation (anammox) in mangrove soils
Bibliographic record
Abstract
Mangroves are ecosystems located in the transition zone between land and sea, characterized by periodic flooding that confer to its unique characteristics. Little is known about the transformation of nutrients that occur during the organic matter degradation in this system. In this study, we monitor the nitrogen transformations in soils from three mangroves with distinct levels of contamination using labeled 15NO3-. We also screened the mangroves metagenomes for the presence of genes that encode enzymes involved in denitrification (nirS, nirK, nosZ, norB and narG), anaerobic oxidation of ammonia (anammox) (hh, hao and hzo) and dissimilatory nitrate reduction to ammonium (DNRA) (nrfA). The transformations of 15NO3- indicated the balance of denitrification over anammox and DNRA in all three mangroves, with lower rates of processes in the mangrove affected by oil contamination. The metagenomic analysis detected 56 sequences related to denitrification, 19 with anammox and 6 with DNRA. Genes related with denitrification were phylogenetically distributed among several groups of bacteria (mainly Gammaproteobacteria). Anammox and DNRA related sequences were affiliated with Planctomycetes and Gammaproteobacteria, respectively. Thus, metagenomic and functional approaches supported the description of denitrification, anammox and DNRA rates in mangrove soils, and identified the major bacterial groups involved in these processes.
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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".