Seasonal marine carbon system processes in an Arctic coastal landfast sea ice environment observed with an innovative underwater sensor platform
Bibliographic record
Abstract
Studying carbon dioxide in the ocean helps to understand how the ocean will be impacted by climate change and respond to increasing fossil fuel emissions. The marine carbonate system is not well characterized in the Arctic, where challenging logistics and extreme conditions limit observations of atmospheric CO2 flux and ocean acidification. Here, we present a high-resolution marine carbon system data set covering the complete cycle of sea-ice growth and melt in an Arctic estuary (Nunavut, Canada). This data set was collected through three consecutive yearlong deployments of sensors for pH and partial pressure of CO2 in seawater (pCO2sw) on a cabled underwater observatory. The sensors were remarkably stable compared to discrete samples: While corrections for offsets were required in some instances, we did not observe significant drift over the deployment periods. Our observations revealed a strong seasonality in this marine carbon system. Prior to sea-ice formation, air–sea gas exchange and respiration were the dominant processes, leading to increasing pCO2sw and reduced aragonite saturation state (ΩAr). During sea-ice growth, water column respiration and brine rejection (possibly enriched in dissolved inorganic carbon, relative to alkalinity, due to ikaite precipitation in sea ice) drove pCO2sw to supersaturation and lowered ΩAr to < 1. Shortly after polar sunrise, the ecosystem became net autotrophic, returning pCO2sw to undersaturation. The biological community responsible for this early switch to autotrophy (well before ice algae or phytoplankton blooms) requires further investigation. After sea-ice melt initiated, an under-ice phytoplankton bloom strongly reduced aqueous carbon (chlorophyll-a max of 2.4 µg L–1), returning ΩAr to > 1 after 4.5 months of undersaturation. Based on simple extrapolations of anthropogenic carbon inventories, we suspect that this seasonal undersaturation would not have occurred naturally. At ice breakup, the sensor platform recorded low pCO2sw (230 µatm), suggesting a strong CO2 sink during the open water season.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".