Nutrient and Silicon Isotope Dynamics in the Laptev Sea and Implications for Nutrient Availability in the Transpolar Drift
Bibliographic record
Abstract
Abstract Realistic prediction of the near‐future response of Arctic Ocean primary productivity to ongoing warming and sea ice loss requires a mechanistic understanding of the processes controlling nutrient bioavailability. To evaluate continental nutrient inputs, biological utilization, and the influence of mixing and winter processes in the Laptev Sea, the major source region of the Transpolar Drift (TPD), we compare observed with preformed concentrations of dissolved inorganic nitrogen (DIN) and phosphorus (DIP), silicic acid (DSi), and silicon isotope compositions of DSi (δ 30 Si DSi ) obtained for two summers (2013 and 2014) and one winter (2012). In summer, preformed nutrient concentrations persisted in the surface layer of the southeastern Laptev Sea, while diatom‐dominated utilization caused intense northward drawdown and a pronounced shift in δ 30 Si DSi from +0.91 to +3.82‰. The modeled Si isotope fractionation suggests that DSi in the northern Laptev Sea originated from the Lena River and was supplied during the spring freshet, while riverine DSi in the southeastern Laptev Sea was continuously supplied during the summer. Primary productivity fueled by river‐borne nutrients was enhanced by admixture of DIN‐ and DIP‐rich Atlantic‐sourced waters to the surface, either by convective mixing during the previous winter or by occasional storm‐induced stratification breakdowns in late summer. Substantial enrichments of DSi (+240%) and DIP (+90%) beneath the Lena River plume were caused by sea ice‐driven redistribution and remineralization. Predicted weaker stratification on the outer Laptev Shelf will enhance DSi utilization and removal through greater vertical DIN supply, which will limit DSi export and reduce diatom‐dominated primary productivity in the TPD.
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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 | 0.001 | 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".