Nutrient Uptake in the Supraglacial Stream Network of an Antarctic Glacier
Bibliographic record
Abstract
Abstract In polar regions, where many glaciers are cold based (frozen to their beds), biological communities on the glacier surface can modulate and transform nutrients, controlling downstream delivery. However, it remains unclear whether supraglacial streams are nutrient sinks or sources and the rates of nutrient processing. In order to test this, we conducted tracer injections in three supraglacial streams (62 to 123 m long) on Canada Glacier in the Taylor Valley, of the McMurdo Dry Valleys, Antarctica. We conducted a series of additions including nitrate (N), N + phosphate (P), N + P + glucose (C), and N + C. In two reaches, N‐only additions resulted in N uptake. The third reach showed net N release during the N‐only addition, but high N uptake in the N + P addition, indicating P‐limitation or N + P colimitation. Coinjecting C did not increase N‐uptake. Additionally, in these systems at low N concentrations the streams can be a net source of nitrogen. We confirmed these findings using laboratory‐based nutrient incubation experiments on sediment collected from stream channels on Canada Glacier and two other glaciers in the Taylor Valley. Together, these results suggest there is active biological processing of nutrients occurring in these supraglacial streams despite low sediment cover, high flow velocities, and cold temperatures, modifying the input signals to proglacial streams. As glaciers worldwide undergo rapid change, these findings further our understanding of how melt generated on glacier surfaces set the initial nutrient signature for subglacial and downstream environments.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".