Trace metals and Mo isotopic fractionation in Skagerrak sediments–effects of different oxygen conditions
Bibliographic record
Abstract
Abstract The Skagerrak is the main depot center for organic matter and anthropogenic pollutants from the entire North Sea. Changes in ocean circulation or suspended matter supply might impact the sediment redox conditions. Indeed, little is known about the response of Skagerrak sediment and associated pollutants to different oxygen levels. We investigated sediments from three stations within the Skagerrak and incubated them for up to twelve months under aerobic and anaerobic conditions. Furthermore, we present the first δ 98/95Mo data for Skagerrak sediment profiles and the incubations to be utilized as a redox tracer. The sediment profiles of metals reflected anthropogenic pollution (Cu, Ni, Pb) but differed regionally with redox conditions. We differentiated redox conditions mainly by sediment and porewater Fe, Mn, Mo and δ 98/95Mo. In aerobic incubations, no Mn or Fe reduction was detected, while under anaerobic conditions, initial Mn and Fe reduction decreased after approximately three months. Under anaerobic conditions, a strong isotopic fractionation of Mo in the dissolved phase was found, reaching up to 5.03 ± 0.10‰, probably caused by incomplete thiolation of molybdate under low hydrogen sulfide levels. During the incubations, Cd, Cu, Ni, Pb were mobilized. While Cu and Cd were mobilized under aerobic conditions, Ni and Pb mobilization depended mainly on remineralization and redox conditions. Our results show that changes in oxygen conditions in the Skagerrak can have significant effects on the (legacy) metals stored in the sediment over the past decades. Graphical Abstract
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".