Ice Darkening on Turner Glacier in Auyuittuq National Park, Nunavut: A Characterization of Surface Algal Blooms and the Associated Implications for Glacier Albedo and Melt
Bibliographic record
Abstract
The Arctic is the largest regional source of land ice to global sea-level rise, composing 31% of the global eustatic sea-level contributions since 1992. Within the Arctic, the glaciers of the Canadian Arctic are the third largest contributor. The presence of light absorbing particles (LAPs) on glaciers, such as mineral dust, ash, and algae, have been shown to lower the albedo of ice, leading to an increase in the absorption of incoming solar radiation, promoting melt. While surface algal blooms and their albedo-reducing effect has been quantified on glaciers in western Canada, Alaska, the European Alps, and southwestern Greenland, it is currently unknown if, or to what extent, either of these phenomena are occurring in the Canadian Arctic. This study employs light microscopy and field spectroscopy to characterize surface algal blooms found on Turner Glacier in Auyuittuq National Park, Nunavut, and to evaluate the associated effect on albedo. From ice samples, an average algal cell abundance of 6.1 x 104 cells/mL was found, with Mesotaenium berggrenii as the dominant species, followed by Ancylonema nordenskioeldii, among the six identified species. Additionally, a significant negative relationship between broadband albedo and algal cell abundance (R2 = 0.67, p = 0.0001) was observed, confirming, for the first time, that the algal-albedo effect is occurring in the Canadian Arctic. The relationship between cell abundance and spectral reflectance was quantified by integrating cell counts with in-situ spectroradiometer measurements (320nm-1100nm), to develop a field-calibrated, remote sensing index. When combined with satellite imagery from the MultiSpectral Instrument (MSI) aboard Sentinel-2, this index will support the future large-scale mapping of glacier algae. Together, these findings fill an important geographical knowledge gap that will inform and improve the characterization, remote detection, and monitoring of surface algal blooms on glaciers in the Canadian Arctic, and their implications for albedo and melt.
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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 | 0.001 |
| 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) | 0.000 | 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 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".