Bottom RedOx Model (BROM, v.1.0): a coupled benthic-pelagic model for simulation of seasonal anoxia and its impact
Bibliographic record
Abstract
Abstract. Interaction between seawater and benthic sediments plays an important role in global biogeochemical cycling. Benthic fluxes of chemical elements (C, N, P, O, Si, Fe, Mn, S) directly affect redox state and acidification (i.e. pH and carbonate saturation), which in turn determine the functioning of the benthic and pelagic ecosystems. The redox state of the near bottom layer can change and oscillate in many regions responding to the supply of organic matter, physical regime and coastal discharge. The goal of this work was to develop a model that captures key biogeochemical processes occurring at the bottom boundary layer and sediment–water interface and analyze the changes that result from seasonal variability in redox conditions in the water column. We used a modular approach allowing the model to be coupled to existing hydrophysical models in 1-D, 2-D or 3-D. The model is capable to simulate seasonality in production and respiration of organic matter as well as in mixing, that leads to variation of redox conditions in the bottom boundary layer. Production and reduction of organic matter and varying redox conditions in the bottom boundary layer affect the carbonate system and lead to changes in pH and alkalinity. Bacteria play a significant role in the fate of organic matter due to chemosynthesis (autotrophs) and consumption of organic matter (heterotrophs). Changes in the bottom boundary layer redox conditions modify the distribution of nutrients (N and P) and redox metals (Mn and Fe). The model can be used for analyzing and interpreting data on sediment-water exchange, and estimating the consequences of forcing such as climate change, external nutrient loading, ocean acidification, carbon storage leakages, and point-source metal pollution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".