Thermo-erosion gullies boost the transition from wet to mesic tundra vegetation
Bibliographic record
Abstract
Abstract. Continuous permafrost zones with well-developed polygonal ice-wedge networks are particularly vulnerable to climate change. Thermo-mechanical erosion can initiate the development of gullies that lead to substantial drainage of adjacent wet habitats. How vegetation responds to this particular disturbance is currently unknown but has the potential to significantly disrupt function and structure of Arctic ecosystems. Focusing on three major gullies of Bylot Island, Nunavut, we estimated the impacts of thermo-erosion processes on plant community changes. We explored over 2 years the influence of environmental factors on plant species richness, abundance and biomass in 62 low-centered wet polygons, 87 low-centered disturbed polygons and 48 mesic environment sites. Gullying decreased soil moisture by 40 % and thaw-front depth by 10 cm in the center of breached polygons within less than 5 years after the inception of ice wedge degradation, entailing a gradual yet marked vegetation shift from wet to mesic plant communities within 5 to 10 years. This transition was accompanied by a five times decrease in graminoid above-ground biomass. Soil moisture and thaw-front depth changed almost immediately following gullying initiation as they were of similar magnitude between older (> 5 years) and recently (< 5 years) disturbed polygons. In contrast, there was a lag-time in vegetation response to the altered physical environment with plant species richness and biomass differing between the two types of disturbed polygons. To date (10 years after disturbance), the stable state of the mesic environment cover has not been fully reached yet. Our results illustrate that wetlands are highly vulnerable to thermo-erosion processes, which drive landscape transformation on a relative short period of time for High Arctic perennial plant communities (5 to 10 years). Such succession towards mesic plant communities can have substantial consequences on the food availability for herbivores and carbon emissions of Arctic ecosystems.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".