Temporal and Vertical Oxygen Gradients Modulate Nitrous Oxide Production in a Seasonally Anoxic Fjord: Saanich Inlet, British Columbia
Bibliographic record
Abstract
Abstract Nitrous oxide (N 2 O) is a strong greenhouse gas and an ozone depleting agent. In marine environments, N 2 O is produced biologically via ammonium oxidation, nitrite, and nitrate reduction. The relative importance of these principle production pathways is strongly influenced by oxygen availability. We conducted 15 N tracer experiments of N 2 O production in parallel with measurements of N 2 O concentration and natural abundance isotopes/isotopomers in Saanich Inlet, a seasonally anoxic fjord, to investigate how temporal and vertical oxygen gradients regulate N 2 O production pathways and rates. In April, June, and August 2018, the depth of the oxic‐anoxic interface (dissolved oxygen = 2.5 μmol L −1 isoline) progressively deepened from 110 to 160 m. Within the oxygenated and suboxic water column, N 2 O supersaturation coincided with peak ammonium oxidation activity. Conditions in the anoxic deep water were potentially favorable to N 2 O production from nitrate and nitrite reduction, but N 2 O undersaturation was observed indicating that N 2 O consumption exceeded rates of production. In October, tidal mixing introduced oxygenated water from outside the inlet, displacing the suboxic and anoxic deep water. This oxygenation event stimulated N 2 O production from ammonium oxidation and increased water column N 2 O supersaturation while inhibiting nitrate and nitrite reduction to N 2 O. Results from 15 N tracer incubation experiments and natural abundance isotopomer measurements both implicated ammonium oxidation as the dominant N 2 O production pathway in Saanich Inlet, fueled by high ammonium fluxes (0.6–3.5 nmol m −2 s −1 ) from the anoxic depths. Partial denitrification contributed little to water column N 2 O production because of low availability of nitrate and nitrite.
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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 | 0.002 | 0.001 |
| 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".