Natural Variations in Dissolved Silicon Isotopes Across the Arctic Ocean From the Pacific to the Atlantic
Bibliographic record
Abstract
Abstract We present measurements of the silicon isotopic composition of silicic acid (δ 30 Si‐Si(OH) 4 ) from seawater collected along a transect following one of the main flow paths of Pacific‐origin waters through the Arctic Ocean during the Canadian Arctic GEOTRACES and Distributed Biological Observatory expeditions in the summer of 2015. The δ 30 Si‐Si(OH) 4 signals track the modification of Pacific‐origin waters as they transit from west to east, and reflect the distribution of water masses, the dissolution of biogenic silica (bSiO 2 ), and the biological utilization of Si in surface waters. Pacific‐origin waters have lower δ 30 Si‐Si(OH) 4 values than the surrounding water masses and are closely linked with a tongue of nutrient‐rich cold water that can be traced back to the Bering Strait. The δ 30 Si‐Si(OH) 4 measurements indicate that the high [Si(OH) 4 ] in the deep waters of Baffin Bay are driven entirely by dissolution of exported bSiO 2 . Using an open‐system model, we estimate the biogenic Si isotope effect ( 30 ε) for the Bering and Chukchi Seas, and the Canadian Arctic Archipelago to be 30 ε = −1.18 ± 0.02‰ (1SE), which agrees very well with laboratory and field estimates. In contrast, the isotope systematics in the Canada Basin and Baffin Bay are better represented by a closed‐system model. We also present an approach to estimate production by sea‐ice algae using δ 30 Si‐Si(OH) 4 signals, though a better understanding of the sea‐ice/water column Si systematics in the Arctic is needed to confirm the viability of this approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".