Climate‐Modulated Nutrient Conditions Along the Labrador Shelf: Evidence From Nitrogen Isotopes in a Six‐Hundred‐Year‐Old Crustose Coralline Alga
Bibliographic record
Abstract
Abstract The impacts of climate change on north Atlantic nutrient chemistry remain poorly understood, as there exist a multitude of rapidly changing biological and physical drivers of nutrient conditions throughout the region. Here, we present nitrogen isotope measurements derived from a six‐hundred‐year‐old crustose coralline alga (δ 15 N algal ) to elucidate historical and contemporary trends in nitrate utilization and circulation patterns along the Labrador Shelf. Prior to the early 1900s, we argue that intervals during which utilization approached completion were controlled by reduced nitrate advection linked to an increased proportion of nitrate‐poor polar waters and subdued Atlantic influence, as expected from concurrent negative modes of the Atlantic multidecadal oscillation. While nitrate conditions should have recovered in recent years, our record suggests that high utilization persisted since ∼1870, which we also attribute to reduced Atlantic advection, likely associated with the twentieth‐century anthropogenic weakening of the Atlantic meridional overturning circulation. These results highlight the role of ongoing climate‐induced circulation changes in modulating nutrient distributions throughout the subpolar north Atlantic, which may have implications for other environmental phenomena such as fisheries and oceanic carbon storage.
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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 | 0.000 |
| 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".