Air-Sea CO₂ Cycling in Arctic Coastal Seas: Case Studies in the Canadian Arctic Archipelago and Hudson Bay
Bibliographic record
Abstract
In contrast to the open ocean, the sources and sinks for atmospheric carbon dioxide (CO₂) in the coastal ocean are source of large uncertainties when budgeting the global ocean carbon sink. This is mainly because of the different characteristics of coastal seas, and strong spatial and temporal heterogeneity. Furthermore, the coastal ocean has been substantially impacted by human activities (e.g., hydroelectric damming, overfishing, shipping, etc.) and is now considered one of the most sensitive parts of the marine environment to climate change. As a result, it is vital to study the carbon cycle and quantify the air-sea CO₂ fluxes in these regions to predict and understand how they may change in response to future climate change. In this thesis, I address this knowledge gap in two Arctic coastal seas by studying the spatial and temporal variability of surface water CO₂ partial pressure (pCO₂) and by quantifying air-sea CO₂ fluxes. Using continuous underway ship measurements of pCO₂, salinity, sea surface temperature, and chlorophyll a (Chl a) concentrations, we quantified the multi-annual variability of air-sea CO₂ exchange in the Canadian Arctic Archipelago and provided a baseline estimate of CO₂ sources and sinks in Hudson Bay during the spring and early summer seasons. Both study regions acted as a net oceanic sink with an average air-sea CO₂ flux of -7.7 and -7.2 TgC yr⁻¹ in the Canadian Arctic Archipelago and Hudson Bay, respectively. In the Canadian Arctic Archipelago, we estimated an increase in the atmospheric CO₂ uptake in the last four decades due to an increase in sea ice loss and higher wind speeds. In Hudson Bay, we observed a distinct spatial pattern in pCO₂ related to proximity from freshwater sources, with supersaturated pCO₂ (relative to the atmosphere) measured near river mouths, and undersaturated pCO₂ in offshore and ice-melt influenced waters. This thesis budgeted the CO₂ sources and sinks in a third of the Arctic shelf seas area (about 36%) and shows the importance of accounting for the spatiotemporal variability of coastal shelves to get better estimates of the carbon budget in the Arctic Ocean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".