Impact of protozoan grazing on nitrification and the ammonia- and nitrite-oxidizing bacterial communities in activated sludge
Bibliographic record
Abstract
In activated sludge, protozoa feed on free-swimming bacteria and suspended particles, inducing flocculation and increasing the turnover rate of nutrients. In this study, the effect of protozoan grazing on nitrification rates under various conditions in municipal activated sludge batch reactors was examined, as was the spatial distribution of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) within the activated sludge. The reactors were monitored for ammonia, nitrite, nitrate, and total nitrogen concentrations, and bacterial numbers in the presence and absence of cycloheximide (a protozoan inhibitor), allylthiourea (an inhibitor of ammonia oxidation), and EDTA (a deflocculating agent). The accumulations of nitrate, nitrite, and ammonia were lower in batches without than with protozoa grazing. Inhibition of ammonia oxidation also decreased the amount of nitrite and nitrate accumulation. Inhibiting protozoan grazing along with ammonia oxidation further decreased the amounts of nitrite and nitrate accumulated. Induction of deflocculation led to high nitrate accumulation, indicating high levels of nitrification; this effect was lessened in the absence of protozoan grazing. Using fluorescent in situ hybridization and confocal laser scanning microscopy, AOB and NOB were found clustered within the floc, and inhibiting the protozoa, inhibiting ammonia oxidation, or inducing flocculation did not appear to lower the number of AOB and NOB present or affect their position within the floc. These results suggest that the AOB and NOB are present but less active in the absence of protozoa.
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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 | 0.001 | 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 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".