Ikaite crystals in melting sea ice – implications for <i>p</i> CO <sub>2</sub> and pH levels in Arctic surface waters
Bibliographic record
Abstract
Abstract. A major issue of Arctic marine science is to understand whether the Arctic Ocean is, or will be, a source or sink for air–sea CO2 exchange. This has been complicated by the recent discoveries of ikaite (a polymorph of CaCO3·6H2O) in Arctic and Antarctic sea ice, which indicate that multiple chemical transformations occur in sea ice with a possible effect on CO2 and pH conditions in surface waters. Here, we report on biogeochemical conditions, microscopic examinations and x-ray diffraction analysis of single crystals from a melting 1.7 km2 (0.5–1 m thick) drifting ice floe in the Fram Strait during summer. Our findings show that ikaite crystals are present throughout the sea ice but with larger crystals appearing in the upper ice layers. Ikaite crystals placed at elevated temperatures disintegrated into smaller crystallites and dissolved. During our field campaign in late June, melt reduced the ice floe thickness by 0.2 m per week and resulted in an estimated 3.8 ppm decrease of pCO2 in the ocean surface mixed layer. This corresponds to an air–sea CO2 uptake of 10.6 mmol m−2 sea ice d−1 or to 3.3 ton km−2 ice floe week−1. This is markedly higher than the estimated primary production within the ice floe of 0.3–1.3 mmol m−2 sea ice d−1. Finally, the presence of ikaite in sea ice and the dissolution of the mineral during melting of the sea ice and mixing of the melt water into the surface oceanic mixed layer accounted for half of the estimated pCO2 uptake.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".