Microbial habitat dynamics and ablation control on the Ward Hunt Ice Shelf
Bibliographic record
Abstract
Abstract The Ward Hunt Ice Shelf (83°02′N, 74°00′W) is an ∼40 m thick ice feature that occupies a large embayment along Canada's northernmost coast. Sediments cover 10% of its surface and provide a habitat for diverse microbial communities. These assemblages form an organo‐sedimentary matrix (microbial mat) composed of cold‐tolerant cyanobacteria and several other types of organisms. We investigated the environmental properties (temperature, irradiance, conductivity and nutrient concentration) of the microbial mat habitat and the effect of the microbial mats on the surface topography of the ice shelf. The low albedo of microbial mats relative to the surrounding snow and ice encouraged meltwater production, thereby extending the growth season to 61 days despite only 52 days with mean temperatures above 0 °C. We found large excursions in salinity near the microbial mat during freeze‐up and melt, and 54% of all ponds sampled had conductivity profiles indicating stratification. Nutrient concentrations within the microbial mats were up to two orders of magnitude higher than those found in the water column, which underscores the differences between the microbial mat microenvironment and the overall bulk properties of the cryo‐ecosystem. The average ice surface ablation in the microbial mat‐rich study site was 1·22 m year−1, two times higher than values measured in areas of the ice shelf where mats were less prevalent. We demonstrate with topographic surveys that the microbial mats promote differential ablation and conclude that the cohesive microbial aggregates trap and stabilize sediment, reduce albedo, and thereby influence the surface morphology of the ice shelf. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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".