Unraveling the Biogeochemical Drivers of Aragonite Saturation State in Baffin Bay: Insights From the West Greenland Continental Shelf
Bibliographic record
Abstract
Abstract This study investigates the biogeochemical drivers of aragonite saturation state (ΩAr) in Baffin Bay, with a focus on the relatively undersampled west Greenland shelf. Our findings reveal two main depth‐dependant processes controlling the spatial distribution of ΩAr in Baffin Bay; within the upper 200 m, lower ΩAr coincides with increasing fractions of Arctic‐outflow waters, while below 200 m organic matter respiration decreases ΩAr. A temporal analysis comparing historical measurements from 1997 and 2004 with our 2019 data set reveals a significant decrease in the ΩAr of Arctic‐outflow waters, coinciding with reduced total alkalinity (TA). However, no discernible anthropogenic ocean acidification signal is identified. Significant Arctic water fractions (20%–40%) are found to be present on the west Greenland shelf, associated with reduced TA and ΩAr. A numerical modeling simulation incorporating a passive tracer demonstrates that periodic changes in wind direction lead to a switch from onshore to offshore Ekman transport along the Baffin Island current, transporting Arctic waters toward the west Greenland shelf. This challenges the conventional understanding of Baffin Bay's circulation and underscores the need for further research on the region's physical oceanography. Based on salinity‐TA relationships, surface waters on the west Greenland shelf have a significantly lower meteoric TA end‐member compared to waters of the Baffin Island Current in western Baffin Bay. The low eastern TA freshwater end‐member agrees well with recent glacial meltwater TA measurements, suggesting that glacial meltwater is the main freshwater source to surface waters on the west Greenland shelf.
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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 | 0.001 | 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".