Could Cryoturbic Diapirs Be Key for Understanding Ecological Feedbacks to Climate Change in High Arctic Polar Deserts?
Bibliographic record
Abstract
Abstract High Arctic polar deserts cover 26% of the Arctic. Increasing temperatures are predicted to significantly alter polar desert freeze‐thaw and biogeochemical cycles, with important implications for greenhouse gas emissions. However, the mechanisms underlying these changing cycles are still highly uncertain. Cryoturbic, carbon‐rich Bhy horizons (diapirs) in frost boils are key nutrient sources for Salix arctica. We hypothesized that diapirism leads to organic carbon characteristics that alter microbial pathways, which then control root foraging and greenhouse gas production. During July and August 2013, we characterized soil properties and examined gross nitrogen transformation rates in frost boils both with and without diapirs in two High Arctic polar deserts (dolomite and granite) near Alexandra Fjord (78°51′N 75°54′W), Ellesmere Island, Nunavut, Canada. Diapiric frost boils had 18% higher soil organic carbon in the dolomitic and 9% higher in the granitic deserts, and 29% higher total dissolved nitrogen in the dolomitic desert. However, diapirs decreased gross nitrogen mineralization rates by 30% in the dolomitic and by 48% in the granitic deserts. Attenuated total reflectance Fourier transformed mid‐infrared spectroscopy revealed greater concentrations of polysaccharides and recalcitrant carbon in diapiric versus nondiapiric frost boils. These increased polysaccharide concentrations likely facilitate diapirism as soil viscosity increases with polysaccharides. Lower microbial activity or ectomycorrhizae that are known to colonize S. arctica may accumulate total dissolved nitrogen in diapirs. Our results suggest geomorphologic‐plant‐microbe interactions may underlie important patterns of geochemical cycling in arctic systems. Thus, polar desert frost boils should represent a key focus of future investigations of climate change in arctic systems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".