Soil Properties and Trace Gas Fluxes in a Chronosequence of Permafrost Disturbances, Cape Bounty, Melville Island, Nunavut
Bibliographic record
Abstract
Permafrost thaw is accelerating in the Arctic, likely leading to the widespread formation of active layer detachments (ALDs), a disturbance event that takes the form of a shallow landslide in areas underlain by permafrost. Despite a growing body of literature concerning thermokarst effects on ecosystem function, there remains a considerable knowledge gap regarding the long-term effects that ALDs exert on tundra ecosystems. Without an understanding of how these features affect tundra nutrient distribution and availability over time, projections of carbon feedback loops in the Arctic cannot be made. This research addresses how ALDs affect soil nutrient distribution (carbon, nitrogen, and trace elements) and greenhouse gas fluxes across a chronosequence of ALDs. In summer 2022, we characterized nine ALDs of varying ages (0-2 years, 15-16 years, and 60+ years) since disturbance at the Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut. Each age was replicated three times, and an undisturbed site was established close to each age ALD. At each of the plots, we measured surface trace gas emissions, bulk soil element depth distribution to 50 cm, and soil physical factors. For most properties, control sites differed across the landscape. We therefore assessed the impact of age by subtracting the disturbance values from control values. ALDs elevated soil total carbon and nitrogen values for at least 15 years, while soil physical properties remained largely unaffected. Gas fluxes were highly variable across the landscape and not ultimately linked to ALD age. Surprisingly, no trends with soil depth were noted. This research will provide landscape and temporal scale information on soil element distribution and gas flux in disturbed tundra environments, assisting in efforts to characterize how the Arctic will respond to a changing climate.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".