Glacial meltwater and primary production are drivers of strong CO <sub>2</sub> uptake in fjord and coastal waters adjacent to the Greenland Ice Sheet
Bibliographic record
Abstract
Abstract. The Greenland Ice Sheet releases large amounts of freshwater, which strongly influences the physical and chemical properties of the adjacent fjord systems and continental shelves. Glacial meltwater input is predicted to strongly increase in the future, but the impact of meltwater on the carbonate dynamics of these productive coastal systems remains largely unquantified. Here we present seasonal observations of the carbonate system over the year 2013 in the surface waters of a west Greenland fjord (Godthåbsfjord) influenced by tidewater outlet glaciers. Our data reveal that the surface layer of the entire fjord and adjacent continental shelf are undersaturated in CO2 throughout the year. The average annual CO2 uptake within the fjord is estimated to be 65 g C m−2 yr−1, indicating that the fjord system is a strong sink for CO2. The largest CO2 uptake occurs in the inner fjord near to the Greenland Ice Sheet and high glacial meltwater input during the summer months correlates strongly with low pCO2 values. This strong CO2 uptake can be explained by the thermodynamic effect on the surface water pCO2 resulting from the mixing of fresh glacial meltwater and ambient saline fjord water, which results in a CO2 uptake of 1.8 mg C kg−1 of glacial ice melted. We estimated that 28% of the CO2 uptake can be attributed to the input of glacial meltwater, while the remaining part is due to high primary production. Our findings imply that glacial melt\\-water is an important driver for undersaturation in CO2 in fjord and coastal waters adjacent to large ice sheets.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".