Ammonia-oxidizing archaea and complete ammonia-oxidizing Nitrospira in water treatment systems
Bibliographic record
Abstract
Nitrification, the oxidation of ammonia to nitrate via nitrite, is important for many engineered water treatment systems. The sequential steps of this respiratory process are carried out by distinct microbial guilds, including ammonia-oxidizing bacteria (AOB) and archaea (AOA), nitrite-oxidizing bacteria (NOB), and newly discovered members of the genus Nitrospira that conduct complete ammonia oxidation (comammox). Even though all of these nitrifiers have been identified within water treatment systems, their relative contributions to nitrogen cycling are poorly understood. Although AOA contribute to nitrification in many wastewater treatment plants, they are generally outnumbered by AOB. In contrast, AOA and comammox Nitrospira typically dominate relatively low ammonia environments such as drinking water treatment, tertiary wastewater treatment systems, and aquaculture/aquarium filtration. Studies that focus on the abundance of ammonia oxidizers may misconstrue the actual role that distinct nitrifying guilds play in a system. Understanding which ammonia oxidizers are active is useful for further optimization of engineered systems that rely on nitrifiers for ammonia removal. This review highlights known distributions of AOA and comammox Nitrospira in engineered water treatment systems and suggests future research directions that will help assess their contributions to nitrification and identify factors that influence their distributions and activity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".