Nitrifiers drive successions of particulate organic matter and microbial community composition in a starved macrocosm
Bibliographic record
Abstract
Organic carbon produced by nitrifiers plays an important role in maintaining the microbial metabolism in the aphotic ocean layer with carbon and energy scarcity. However, the contribution of nitrifiers to organic carbon processing remains unclear. To explore how nitrification impacts the material cycle in the starved ecosystem, we set up an ultra-large volume, long-term incubation experiment. Seawater collected from the Halifax coastal ocean was pumped into the Aquatron Tower Tank located at Dalhousie University, Canada, and was incubated under dark conditions for 73 days. The results indicated that the relative abundance of nitrifiers increased and nitrification was strengthened in the dark system where energy and organic carbon were scarce. The importance of nitrogenous compounds in particulate materials increased over the course of the incubation. Correlation analysis showed that the relative abundances of nitrifiers and particulate organic compounds containing nitrogen were significantly and positively correlated. Furthermore, network analysis suggested that metabolic processes related to nitrogenous and aromatic compounds are most important to particle associated bacteria. This study suggests that the nitrifiers could produce a series of organic compounds that result in the alteration of organic matter composition by promoting the degradation of recalcitrant aromatic compounds, which has important implications for organic matter processing in the starved dark ecosystem.
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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 | 0.000 | 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) | 0.036 | 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".