Temporal and Spatial Stability of Ammonia-Oxidizing Archaea and Bacteria in Aquarium Biofilters
Bibliographic record
Abstract
Nitrifying biofilters are used in aquaria and aquaculture systems to prevent accumulation of ammonia by promoting rapid conversion to nitrate via nitrite. Ammonia-oxidizing archaea (AOA), as opposed to ammonia-oxidizing bacteria (AOB), were recently identified as the dominant ammonia oxidizers in most freshwater aquaria. This study investigated biofilms from fixed-bed aquarium biofilters to assess the temporal and spatial dynamics of AOA and AOB abundance and diversity. Over a period of four months, ammonia-oxidizing microorganisms from six freshwater and one marine aquarium were investigated at 4-5 time points. Nitrogen balances for three freshwater aquaria showed that active nitrification by aquarium biofilters accounted for ≥ 81-86% of total nitrogen conversion in the aquaria. Quantitative PCR (qPCR) for bacterial and thaumarchaeal ammonia monooxygenase (amoA) genes demonstrated that AOA were numerically dominant over AOB in all six freshwater aquaria tested, and contributed all detectable amoA genes in three aquarium biofilters. In the marine aquarium, however, AOB outnumbered AOA by three to five orders of magnitude based on amoA gene abundances. A comparison of AOA abundance in three carrier materials (fine sponge, rough sponge and sintered glass or ceramic rings) of two three-media freshwater biofilters revealed preferential growth of AOA on fine sponge. Denaturing gel gradient electrophoresis (DGGE) of thaumarchaeal 16S rRNA genes indicated that community composition within a given biofilter was stable across media types. In addition, DGGE of all aquarium biofilters revealed low AOA diversity, with few bands, which were stable over time. Nonmetric multidimensional scaling (NMDS) based on denaturing gradient gel electrophoresis (DGGE) fingerprints of thaumarchaeal 16S rRNA genes placed freshwater and marine aquaria communities in separate clusters. These results indicate that AOA are the dominant ammonia-oxidizing microorganisms in freshwater aquarium biofilters, and that AOA community composition within a given aquarium is stable over time and across biofilter support material types.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".