Sedimentary phosphorus dynamics and the evolution of bottom‐water hypoxia: A coupled benthic–pelagic model of a coastal system
Bibliographic record
Abstract
The present study examines oxygen and phosphorus dynamics at a seasonally hypoxic site in the Arkona basin of the Baltic Sea. A coupled benthic–pelagic reactive‐transport model is used to describe the evolution of bottom‐water solute concentrations, as well as pore‐water and sediment profiles. Aerobic respiration dominates remineralization, with iron reduction, denitrification, and sulphate reduction playing secondary roles, while other pathways are negligible. Sediments represent a significant oxygen sink chiefly due to the aerobic degradation of organic matter, as well as nitrification and iron oxyhydroxide precipitation. Most phosphorus deposited in sediments is in organic matter, yet cycling is dominated by iron‐bound phosphorus due to rapid dissimilatory iron reduction coupled with aerobic iron oxyhydroxide formation. Sustained hypoxia results in an initial decrease in sediment phosphorus content due to dissolution of phosphorus‐bearing iron oxyhydroxides, resulting in a pulse of phosphate to overlying waters. Although an organic‐rich layer is formed under low‐oxygen conditions, enhanced remineralization of organic phosphorus relative to organic carbon tempers sedimentary phosphorus accumulation. Upon reoxygenation of bottom waters after a decade of sustained hypoxia, oxygen concentrations do not immediately achieve values observed prior to hypoxia because the organic‐rich layer creates a higher benthic oxygen demand. Artificial reoxygenation of bottom waters leads to a substantial increase in the iron‐bound phosphorus pool; the total phosphorus content of the sediment, however, is unaffected. A relapse into hypoxia would consequently produce a large pulse of phosphate to the overlying waters potentially exacerbating the situation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".