Modelling the biogeochemical effects of heterotrophic and autotrophic N <sub>2</sub> fixation in the Gulf of Aqaba (Israel), Red Sea
Bibliographic record
Abstract
Recent studies demonstrate that marine N 2 fixation can be carried out without light by heterotrophic N 2 fixers (diazotrophs). However, direct measurements of N 2 fixation in aphotic environments are relatively scarce. Heterotrophic as well as unicellular and colonial photoautotrophic diazotrophs are present in the oligotrophic Gulf of Aqaba (northern Red Sea). This study evaluates the relative importance of these different diazotrophs by combining biogeochemical models with time series measurements at a 700 m deep monitoring station in the Gulf of Aqaba. At this location, an excess of nitrate, relative to phosphate, is present throughout most of the water column and especially in deep waters during stratified conditions. A relative excess of phosphate occurs only at the water surface during nutrient-starved conditions in summer. We show that a model without N 2 fixation can replicate the observed surface chlorophyll but fails to accurately simulate inorganic nutrient concentrations throughout the water column. Models with N 2 fixation improve simulated deep nitrate by enriching sinking organic matter in nitrogen, suggesting that N 2 fixation is necessary to explain the observations. The observed vertical structure of nutrient ratios and oxygen is reproduced best with a model that includes heterotrophic as well as colonial and unicellular autotrophic diazotrophs. These results suggest that heterotrophic N 2 fixation contributes to the observed excess nitrogen in deep water at this location. If heterotrophic diazotrophs are generally present in oligotrophic ocean regions, their consideration would increase current estimates of global N 2 fixation and may require explicit representation in large-scale models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".