Release and turn-over of carbon, nitrogen and metals under oxic and suboxic conditions in long-term incubations of Skagerrak sediments 
Bibliographic record
Abstract
Suspended particulate matter and associated pollutants from the entire North Sea are deposited in the Skagerrak, located between Norway and Denmark. Consequently, the sediments of the Skagerrak play a key role for long-term carbon storage within the North Sea. Due to its location and bathymetry, the bottom sediment redox conditions within the Skagerrak are heterogeneous and cover a wide range from oxic to suboxic conditions. We investigated nitrogen sequestration processes and the mobility of pollutants in these sediments during incubation experiments that simulated oxic and suboxic conditions. Analysis of isotopic fractionation was used as a tool to better understand the nitrogen sequestration pathways (δ15NO3-) and redox conditions (δ98/95Mo).Typically, incubation experiments last days to weeks but do not cover long-term effects. In contrast, we incubated different zones of three sediment cores with North Sea water for up to twelve months. The sediments originated from locations with (a) mainly iron reduction, (b) mainly manganese reduction and (c) both iron and manganese reduction. After one, three, six and twelve months, we sampled water and sediments from the incubations for various parameters (e.g., trace elements, carbon and nitrogen content, nutrients, δ15NO3-, δ98/95Mo). Under aerobic conditions, the sediments with high organic carbon content (2.78 ± 0.05 %) released up to 33 ± 6 µmol g‑1 NO3- during remineralization, while in anaerobic incubations, these sediments released only up to 4.8 ± 0.8 µmol g-1 NH4+. However, sediments with lower organic carbon contents (1.89 ± 0.05 %) released only 4.8 ± 1.2 µmol g‑1 NO3- and 1.18 ± 0.19 µmol g-1 NH4+, respectively. In combination with trace element concentrations, δ98/95Mo ratios allowed to distinct between different organic matter oxidation pathways. The aerobic incubations released mainly copper, lead and nickel while under anaerobic conditions, also cobalt but significantly less copper has been released. Hence, the prevailing oxygen conditions also have a strong impact on the remobilization of e.g., legacy pollutants stored in the sediments. The results of our long-term incubations reveal important biogeochemical processes and indicate that some processes are only traceable at larger timescales applied in this study, but not by incubation durations that are usually applied for biogeochemical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".