The ecology and dynamics of ice wedge degradation in high-centre polygonal terrain in the uplands of the Mackenzie Delta region, Northwest Territories
Bibliographic record
Abstract
Climate warming has the potential to alter the structure and function of Arctic ecosystems in ways that are not fully understood. Polygonal terrain is a widespread permafrost feature of Arctic landscapes that is likely to be impacted by warming ground temperatures. This is of particular relevance in the uplands in the Mackenzie Delta region, where high-centre ice wedge polygon fields comprise 10% of the terrestrial landscape, and mean annual ground temperatures have increased between 1 and 2°C over the last 40 years (Burn and Kokelj 2009). I used broad-scale airphoto analysis and fine-scale field studies to investigate the impacts and possible trajectories of ice wedge degradation in the upland tundra north of Inuvik, NWT. Field investigations were undertaken to characterize biotic and abiotic conditions and feedbacks in stable and degrading high-centre polygons. Field surveys were conducted along transects which crossed three polygon micropositions (centres, edges and troughs) and targeted a degradation sequence from stable troughs to ice wedge melt ponds. I measured surface microtopography, active layer depth, water depth, plant community composition, soil gravimetric moisture, late winter snow depth, and shallow annual ground temperatures. Field data showed that ice wedge degradation drove increases in soil moisture, standing water depth, ground surface collapse, ground temperature, and active layer thaw and snow pack compared to stable troughs. These changing abiotic conditions drove the shift from mesic upland tundra plant communities to unvegetated melt ponds. Interactions between abiotic and biotic factors in degrading troughs increase ground temperature and contribute to positive feedbacks for ice wedge degradation. Analysis of broad-scale factors affecting ice wedge degradation involved the mapping of high-centre polygon distribution across the study area and the distribution of ice wedge melt ponds using high-resolution aerial photographs from 2004. Recent changes in melt pond area were also mapped using imagery dating from 1972. Thermokarst activity in polygonal terrain adjacent to anthropogenic disturbances was also assessed. Polygon fields were more abundant and larger in the northern part of the study area, where ground temperature conditions were most favourable for ice wedge formation. Spatial variation in polygonal terrain density was also related to topography, drainage, and the distribution of lacustrine sediments. Melt pond mapping and assessment of thermokarst at anthropogenic disturbances showed that ice wedges at higher latitudes are more susceptible to degradation primarily because these areas are underlain by larger and more abundant ice wedges. Melt pond mapping confirmed that the polygonal fields north of 69.4°N have shown both large increases and decreases in area, and that polygons in the south have been relatively stable in recent decades. The increased thaw sensitivity of polygonal terrain at higher latitudes has implications for soil carbon dynamics, terrestrial ecosystems, and the planning and maintenance of infrastructure as air and ground temperatures continue to increase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".