Response of the Arctic Marine Inorganic Carbon System to Ice Algae and Under‐Ice Phytoplankton Blooms: A Case Study Along the Fast‐Ice Edge of Baffin Bay
Bibliographic record
Abstract
Abstract Past research in seasonally ice‐covered Arctic seas has suggested that ice algae play a role in reducing dissolved inorganic carbon (DIC) during spring, preconditioning surface waters to low dissolved CO2 (pCO2sw), and uptake of atmospheric CO2 during the ice‐free season. The potential role of under‐ice phytoplankton blooms on DIC and pCO2sw has not often been considered. In this study we examined the inorganic carbon system beneath landfast sea ice starting midway through a bottom ice algae bloom and concluding in the early stages of an under‐ice phytoplankton bloom. During most of the ice algae bloom we observed a slight increase in DIC/pCO2sw in surface waters, as opposed to the expected reduction. Biomass calculations confirm that the role of ice algae on DIC/pCO2sw in the study region were minor and that this null result may be widely applicable. During snow melt, we observed an under‐ice phytoplankton bloom (to 10 mg/m3 Chl a) that did reduce DIC and pCO2sw. We conclude that under‐ice phytoplankton blooms are an important biological mechanism that may predispose some Arctic seas to act as a CO2 sink at the time of ice breakup. We also found that pCO2sw was undersaturated at the study location even at the beginning of our sampling period, consistent with several other studies that have measured under‐ice pCO2sw in late winter or early spring. Finally, we present the first measurements of carbonate saturation states for this region, which may be useful for assessing the vulnerability of a local soft‐shelled clam fishery to ocean acidification.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".