Nitrogen loss processes in response to upwelling in a Peruviancoastal setting dominated by denitrification
Bibliographic record
Abstract
Abstract. Upwelling of nutrient-rich deep waters make Eastern Boundary upwelling systems (EBUS), such as the Humboldt Current System, hotspots of marine productivity. Associated settling of organic matter to depth and consecutive aerobic de composition results in large sub-surface water volumes being oxygen-depleted. Under these circumstances organic matter remineralisation can continue via denitrification which represents a major loss pathway of bioavailable nitrogen. Another process removing significant amounts of nitrogen in these areas is anaerobic ammonium oxidation. Here we assess the interplay of suboxic water upwelling and nitrogen cycling in a manipulative off-shore mesocosm experiment. Measured denitrification rates in the oxygen-depleted bottom layer of the mesocosms mostly ranged between 5.5–20 (interquartile range), reaching up to 80 nmol N2 L−1 h−1. However, realised in-situ rates did most likely not exceed 0.6–1.6 nmol N2 L−1 h−1 (interquartile range), due to substrate limitation in the mesocosms. This was in contrast to realised rates in the surrounding Pacific. Both in the mesocosms and the Pacific Ocean anammox made only a minor contribution to overall nitrogen loss when encountered. Over the first 38 days of the experiment, total nitrogen loss calculated from denitrification and anammox rates was comparable to estimates from a full nitrogen budget in the mesocosms and ranged between ∼ 2–6 μmol N L−1. This represents up to ∼ 20 % of the initially bioavailable inorganic and organic nitrogen standing stocks. Interestingly, this loss is comparable to the total amount of particulate organic nitrogen that was exported into the sediment traps at the bottom of the mesocosms in about 20 metres depth. Altogether, this suggests that a significant portion, if not the majority of nitrogen that could be exported to depth, is already lost, i.e. converted to N2 in a relatively shallow layer of the surface ocean, provided oxygen-deficient conditions like during coastal upwelling in our study.
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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 | 0.000 | 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".