Organic matter remineralization in marine sediments: A Pan‐Arctic synthesis
Bibliographic record
Abstract
Abstract Climate change in the Arctic is ongoing and causes drastic modification on the ecosystem functioning. In soft‐bottom environments, organic matter remineralization is considered an important ecosystem function. Here we provide a large‐scale assessment of the current knowledge on the benthic organic matter remineralization and its potential response to climate change. Sediment oxygen demand (SOD) values (n = 1154), measured throughout the Arctic, were gathered from 30 publications and 16 databases, and nutrient flux values, available in a far lesser extent (n < 80), were also compiled. Generalized additive models were used to estimate the influence of explanatory variables on benthic oxygen fluxes and for interpolating SOD to the whole Arctic region. This first Pan‐Arctic review of the distributions of SOD showed that oxygen fluxes strongly depended on water depth, i.e., followed the general trend observed for other regions, and also on the availability of labile organic matter. The continental shelves (representing ~50% of Arctic Ocean's total area) were characterized by the highest SOD values (10.5 ± 7.9 mmol O2 m−2 d−1), and differences among shelves were observed; SOD values in inflow, interior, and outflow shelves were 11.8 ± 8.0, 6.2 ± 5.6, and 3.9 ± 3.5 mmol O2 m−2 d−1, respectively. Moreover, seasonal variation in SOD changed significantly among areas. The interpolation based on the best fitted model showed high respiration in the inflow and interior shelves. In the inflow shelves, characterized by productive waters, benthic activities replenish bottom water with nutrients which may augment primary productivity, whereas sediments from the interior shelves, e.g., under the direct influence of the Mackenzie River, consume nutrients.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".