Inoculum and pH effects on ammonium removal and microbial community dynamics in aquaponics systems
Bibliographic record
Abstract
Understanding the ecology of microorganisms is essential for optimizing aquaponics systems. Effects of pH and inoculum on ammonium removal and dynamics of microbial community composition from all compartments of lab-scale aquaponics systems were examined. Initial ammonium accumulation in systems with comammox-enriched inocula were 47% and 69% that of systems enriched with ammonia-oxidizing bacteria (AOB), with higher rates of ammonium removal and transient nitrite accumulation measured in the latter systems. By the end of operation, Nitrosomonas and Nitrosospira AOB were dominant nitrifiers in systems at pH 7.6–7.8, whereas comammox ( Nitrospira ) nitrifiers and plant growth-promoting microbes were abundant in systems operating at pH 5.8–6.0. Lower pH systems supported more robust plant growth with no significant effects on fish health. This study demonstrated functional redundancy of aquaponics microbiota, with selectivity of nitrifying taxa as a function of pH. The results suggest that inoculum and pH are important considerations for aquaponics system initiation and optimization.
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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 | 0.001 |
| 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 | 0.001 | 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".