Activity and abundance of denitrifying bacteria in the subsurface biosphere of diffuse hydrothermal vents of the Juan de Fuca Ridge
Bibliographic record
Abstract
Abstract. Little is known about fixed nitrogen (N) transformation and elimination at diffuse hydrothermal vents where anoxic fluids are mixed with oxygenated crustal seawater prior to discharge. Oceanic N sinks that remove bio-available N ultimately affect chemosynthetic primary productivity in these ecosystems. Using 15N paired isotope techniques, we determined potential rates of fixed N loss pathways (denitrification, anammox) and dissimilatory nitrate reduction to ammonium (DNRA) in sulfidic hydrothermal vent fluids discharging from the subsurface at several sites at Axial Volcano and the Endeavour Segment on the Juan de Fuca Ridge. We also measured physico-chemical parameters (i.e., temperature, pH, nutrients, H2S and N2O concentrations) as well as the biodiversity and abundance of chemolithoautotrophic nitrate-reducing, sulfur-oxidizing γ-proteobacteria (SUP05 cluster) using sequence analysis of amplified small subunit ribosomal RNA (16S rRNA) genes in combination with taxon-specific quantitative polymerase chain reaction (qPCR) assays. Denitrification was the dominant N loss pathway in the subsurface biosphere of the Juan de Fuca Ridge, with rates of up to ~1000 nmol N l−1 day−1. In comparison, anammox rates were always < 5 nmol N l−1 day−1 and below the detection limit at most of the sites. DNRA rates were up to ~150 nmol N l−1 day−1. These results suggest that bacterial denitrification out-competes anammox in sulfidic hydrothermal vent waters. Taxon-specific qPCR revealed that γ-proteobacteria of the SUP05 cluster sometimes dominated the microbial community (SUP05/total bacteria up to 38%). Significant correlations were found between fixed N loss (i.e., denitrification, anammox) rates and in situ nitrate and dissolved inorganic nitrogen (DIN) deficits in the fluids, indicating that DIN availability may ultimately regulate N loss in the subsurface. Based on our rate measurements, and on published data on hydrothermal fluid fluxes and residence times, we estimated that up to ~10 Tg N yr−1 could globally be removed in the subsurface biosphere of hydrothermal vents systems, thus, representing a small fraction of the total marine N loss (~275 to > 400 Tg N yr−1).
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".