Basal thermal regime affects the biogeochemistry of subglacial systems
Bibliographic record
Abstract
Abstract. Ice formed in the subglacial environment can contain some of the highest concentrations of solutes, nutrients, and microbes found in glacier systems. Upon glacial melt, these materials are released to downstream freshwater and marine ecosystems and glacier forefields. Despite the potential ecological importance of basal ice, our understanding of its biogeochemical characteristics, and their spatial and temporal variability, remains limited. We hypothesize that the basal thermal regime of glaciers is a dominant control on subglacial biogeochemistry because it influences the degree to which glaciers mobilize material from the underlying substrate and controls the nature and extent of biogeochemical activity that occurs at glacier beds. Here, we characterize the solutes, nutrients, and microbes found in the basal regions of a cold-based glacier and three polythermal glaciers and compare them to those found in overlying glacier ice. Compared to its parent glacier ice, basal ice from polythermal glaciers was consistently enriched in major ions, dissolved organic matter (including a specific fraction of humic-like fluorescent material), and microbes, and occasionally enriched in dissolved phosphorus and reduced nitrogen (NH4+) and in a second dissolved component of humic-like fluorescent material. In contrast, the biogeochemistry of basal ice from the cold-based glacier was remarkably similar to that of its parent glacier ice. Although basal ice from the cold-based glacier may have acquired some inorganic and organic nutrients from the underlying substrate, it did not appear to contain significant amounts of either solutes or microbes derived from the glacier bed. These findings suggest that a glacier's basal thermal regime can play an important role in determining the mix of solutes, nutrients, and microbes that are acquired from subglacial substrates and/or produced in situ.
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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".