Uncovering the role of oxygen on organic carbon cycling: insights from a continuous culture study with a facultative anaerobic bacterioplankton species (Shewanella baltica)
Bibliographic record
Abstract
Deoxygenation is tied to organic carbon (Corg) supply and utilization in marine systems. Under oxygen-depletion, bacteria maintain Corg respiration using alternative electron acceptors such as nitrate. Since anaerobic respiration’s energy yield is lower, Corg remineralization may be reduced and its residence time increased. We investigated the influence of oxygen and alternative electron acceptors’ availability on Corg cycling by heterotrophic bacteria during a continuous culture experiment with Shewanella baltica, a facultative anaerobic γ-Proteobacteria in the Baltic Sea. We tested six different oxygen levels, from suboxic (<5 µmol L-1) to fully oxic conditions, using a brackish (salinity=14 g L-1) media supplied with high (HighN) or low (LowN) inorganic nitrogen concentrations relative to glucose as labile Corg source. Our results show that suboxia limited DOC (glucose) uptake and cell growth only under LowN, while higher availability of alternative electron acceptors seemingly compensated oxygen limitation under HighN. N-loss was observed under suboxia in both nitrogen treatments. Under HighN, N-loss was highest and a C:N loss ratio of ~2.0 indicated that Corg was remineralized via denitrification. Under LowN, the C:N loss ratio under suboxia was higher (~5.5), suggesting the dominance of other anaerobic respiration pathways, such as dissimilatory nitrate reduction to ammonium (DNRA). Bacterial growth efficiency was independent of oxygen concentration but higher under LowN (34 ± 3.0%) than HighN (26 ± 1.6%). Oxygen concentration also affected dissolved organic matter (DOM) cycling. Under oxic conditions, the release of dissolved combined carbohydrates was enhanced, and the amino acid-based degradation index (DI) pointed to more diagenetically altered DOM. Our results suggest bacterial Corg uptake in low-oxygen systems dominated by S. baltica can be limited by oxygen but compensated by high nitrate availability. Hence, suboxia diminishes Corg remineralisation only when alternative electron acceptors are lacking. Under high nitrate:Corg supply, denitrification leads to a higher N:C loss ratio, potentially counteracting eutrophication in the long run. Low nitrate:Corg supply may favour other anaerobic respiration pathways like DNRA, which sustains labile nitrogen in the system, potentially intensifying the cycle of eutrophication. Going forward, it will be crucial to establish the validity of our findings for S. baltica in natural systems with diverse organic substrates and microbial consortia.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".