Greenland Ice Sheet exports labile organic carbon to the Arctic oceans
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Runoff from small glacier systems contains dissolved organic carbon (DOC) rich in protein-like, low molecular weight (LMW) compounds, designating glaciers as an important source of bioavailable carbon for downstream heterotrophic activity. Fluxes of DOC and particulate organic carbon (POC) exported from large Greenland catchments, however, remain unquantified, despite the Greenland Ice Sheet (GrIS) being the largest source of global glacial runoff (ca. 400 km3 yr−1). We report high and episodic fluxes of POC and DOC from a large (>600 km2) GrIS catchment during contrasting melt seasons. POC dominates organic carbon (OC) export (70–89% on average), is sourced from the ice sheet bed, and contains a significant bioreactive component (9% carbohydrates). A major source of the "bioavailable" (free carbohydrate) LMW–DOC fraction is microbial activity on the ice sheet surface, with some further addition of LMW–DOC to meltwaters by biogeochemical processes at the ice sheet bed. The bioavailability of the exported DOC (26–53%) to downstream marine microorganisms is similar to that reported from other glacial watersheds. Annual fluxes of DOC and free carbohydrates during two melt seasons were similar, despite the approximately two-fold difference in runoff fluxes, suggesting production-limited DOC sources. POC fluxes were also insensitive to an increase in seasonal runoff volumes, indicating a supply limitation in suspended sediment in runoff. Scaled to the GrIS, the combined DOC (0.13–0.17 Tg C yr−1 (±13%)) and POC fluxes (mean = 0.36–1.52 Tg C yr−1 (±14%)) are of a similar order of magnitude to a large Arctic river system, and hence may represent an important OC source to the near-coastal North Atlantic, Greenland and Labrador seas.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it