From ice to ocean: Understanding the impacts of melting glaciers on marine biogeochemical cycles in the Canadian Arctic Archipelago
Bibliographic record
Abstract
When glaciers melt, they contribute significant quantities of water and ice, sediments and dissolved chemicals to the ocean. Recent efforts in Greenland and Antarctica show that both the delivery of materials to the marine environment, as well as local changes to ocean circulation induced by the input of freshwater, have the potential to profoundly impact key processes such as primary and secondary production, and by extension the biological carbon pump. Yet, extensive knowledge gaps remain about the chemical composition of glacial meltwater runoff at the ice-ocean interface, the spatial extent of its influence within coastal environs, and the mechanisms by which glaciers affect surface marine microbial communities. Nowhere are these knowledge gaps more prominent than in the Canadian Arctic Archipelago (CAA) – a region where the role of glacial meltwater in marine biogeochemical cycles is almost fully unexplored – despite the fact that it is a hotspot for glacial retreat and meltwater runoff to the ocean. Here, we conduct a regional comparative study of the nearshore coastal zone of glaciated and non-glaciated fjords and of multiple glaciers of varying type (land-terminating, tidewater) and size draining large ice caps. Our study site in Jones Sound, NU is home to the Inuit hamlet of Grise Fiord. Traditional knowledge from this community indicates that the termini of tidewater glaciers in this region are rich in wildlife, providing habitual hunting grounds for its citizens. Guided by this information, we combined shipboard measurements of temperature, salinity, turbidity, and chlorophyll a with bottle samples characterizing oxygen, sediment, carbon, nutrient, metal, and biological community composition to elucidate how these properties evolve with distance from the shore. Results from this study substantially further our understanding of glacier-ocean impacts in the CAA and beyond, while also providing data critical to accurate future projections of high-latitude marine ecosystem productivity and function in this era of climate change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".