Nitrification and nitrous oxide production in the offshore waters of the Eastern Tropical South Pacific
Bibliographic record
Abstract
Marine oxygen deficient zones (ODZs) are dynamic areas of microbial nitrogen cycling. Nitrification, the microbial oxidation of ammonia to nitrate, plays multiple roles in the biogeochemistry of these regions, including production of the greenhouse gas nitrous oxide (N2O). We present here the results of two oceanographic cruises investigating nitrification, nitrifying microorganisms, and N2O production and distribution from the offshore waters of the Eastern Tropical South Pacific (ETSP). On each cruise, high-resolution measurements of ammonium ([NH4+]), nitrite ([NO2-]), and N2O were combined with 15N tracer-based determination of ammonia oxidation, nitrite oxidation, nitrate reduction and N2O production rates. Depth-integrated inventories of NH4+ and NO2- were positively correlated with one another, and with depth-integrated primary production. Depth-integrated ammonia oxidation rates were correlated with sinking particulate organic nitrogen flux but not with primary production; ammonia oxidation rates were undetectable in trap-collected sinking particulate material. Nitrite oxidation rates exceeded ammonia oxidation rates at most mesopelagic depths. We found positive correlations between archaeal genes and ammonia oxidation rates and between -like 16S rRNA genes and nitrite oxidation rates. N2O concentrations in the upper oxycline reached values of greater than 140 nM, even at the western extent of the cruise track, supporting air-sea fluxes of up to 1.71 umol m-2 d-1. Our results suggest that a source of N2O other than ammonia oxidation may fuel high rates of nitrite oxidation in the offshore ETSP and that air-sea fluxes of N2O from this region may be higher than previously estimated.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".