Impact of Seabed Resuspension on Oxygen and Nitrogen Dynamics in the Northern Gulf of Mexico: A Numerical Modeling Study
Bibliographic record
Abstract
Abstract Resuspension affects water quality in coastal environments by entraining seabed organic matter into the water column, which can increase remineralization, alter seabed fluxes, decrease water clarity, and affect oxygen and nutrient dynamics. Nearly all numerical models of water column biogeochemistry, however, simplify seabed and bottom boundary layer processes and neglect resuspension. Here we implemented HydroBioSed, a coupled hydrodynamic‐sediment transport‐biogeochemical model to examine the role of resuspension in regulating oxygen and nitrogen dynamics on timescales of a day to a month. The model was implemented for the northern Gulf of Mexico, where the extent of summertime hypoxia is sensitive to seabed and bottom boundary layer processes. Results indicated that particulate organic matter remineralization in the bottom water column increased by an order of magnitude during resuspension events. This increased sediment oxygen consumption and ammonium production, which were defined as the sum of seabed fluxes of oxygen and ammonium, plus oxygen consumption and ammonium production in the water column due to resuspended organic matter. The increases in remineralization impacted biogeochemical dynamics to a greater extent than resuspension‐induced seabed fluxes and oxidation of reduced chemical species. The effect of resuspension on bottom water biogeochemistry increased with particulate organic matter availability, which was modulated by sediment transport patterns. Overall, when averaged over the shelf and on timescales of a month in the numerical model, cycles of erosion and deposition accounted for about two thirds of sediment oxygen consumption and almost all of the sediment ammonium production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 |
| 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 teacher head, 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".