Arctic epishelf lakes as sentinel ecosystems: Past, present and future
Bibliographic record
Abstract
Ice shelves are a prominent but diminishing feature of the northern coastline of Ellesmere Island in the Canadian High Arctic (latitude 82–83°N). By blocking embayments and fiords, this thick coastal ice can create epishelf lakes, which are characterized by a perennially ice‐capped water column of freshwater overlying seawater. The goal of this study was to synthesize new, archived, and published data on Arctic epishelf lakes in the context of climate change. Long‐term changes along this coastline were evaluated using historical reports, cartographic analysis, RADARSAT imagery, and field measurements. These data, including salinity‐temperature profiling records from Disraeli Fiord spanning 54 years, show the rapid decline and near disappearance of this lake type in the Arctic. Salinity‐temperature profiling of Milne Fiord, currently blocked by the Milne Ice Shelf, confirmed that it contained an epishelf lake composed of a 16‐m thick freshwater layer overlying seawater. A profiling survey along the coast showed that there was a continuum of ice‐dammed lakes from shallow systems dammed by multiyear landfast sea ice to deep epishelf lakes behind ice shelves. The climate warming recently observed in this region likely contributed to the decline of epishelf lakes over the last century, and the air temperature trend predicted for the Arctic over the next several decades implies the imminent loss of this ecosystem type. Our results underscore the distinctive properties of coastal ice‐dammed lakes and their value as sentinel ecosystems for the monitoring of regional and global 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".