Landscape influence on permafrost ground ice geochemistry in a polar desert environment, Resolute Bay, Nunavut
Bibliographic record
Abstract
Arctic permafrost is degrading and is thus releasing nutrients, solutes, sediment and water into soils and freshwater ecosystems. The impacts of this degradation depends on the geochemical characteristics and in large part on the spatial distribution of ground ice and solutes, which is not well-known in the High Arctic polar desert ecosystems. This research links ground ice and solute concentrations, to establish a framework for identifying locations vulnerable to permafrost degradation. It builds on landscape classifications and cryostratigraphic interpretations of permafrost history. Well-vegetated wetland sites with syngenetic permafrost aggradation show a different geochemical signature from polar desert and epigenetic sites. In wetlands, where ground ice contents were high (<97% volume), total dissolved solute concentrations were relatively low (mean 283.0 ± 327.8 ppm), reflecting a carbonate terrestrial/freshwater setting. In drier sites with epigenetic origin, such as polar deserts, ice contents are low (<47% volume), solute concentrations were high (mean 3248.5 ± 1907.0 ppm, max 12055 ppm) and dominated by Na + and Cl − ions, reflecting a post-glacial marine inundation during permafrost formation. Dissolved organic carbon and total dissolved nitrogen concentrations usually increased at the top of permafrost and could not be as clearly associated with permafrost history. The research shows that the geochemistry of polar desert permafrost is highly dependent on permafrost history, and it can be estimated using hydrogeomorphological terrain classifications. The lower ice content of polar desert sites indicates that these areas are more vulnerable to thaw relative to the ice-rich wetland sites, and the elevated solute concentrations indicate that these areas could mobilise substantial solutes to downstream environments, should they become hydrologically connected with future warming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".