Is climate change responsible for changing landslide activity in high mountains?
Bibliographic record
Abstract
ABSTRACT Climate change, manifested by an increase in mean, minimum, and maximum temperatures and by more intense rainstorms, is becoming more evident in many regions. An important consequence of these changes may be an increase in landslides in high mountains. More research, however, is necessary to detect changes in landslide magnitude and frequency related to contemporary climate, particularly in alpine regions hosting glaciers, permafrost, and snow. These regions not only are sensitive to changes in both temperature and precipitation, but are also areas in which landslides are ubiquitous even under a stable climate. We analyze a series of catastrophic slope failures that occurred in the mountains of Europe, the Americas, and the Caucasus since the end of the 1990s. We distinguish between rock and ice avalanches, debris flows from de‐glaciated areas, and landslides that involve dynamic interactions with glacial and river processes. Analysis of these events indicates several important controls on slope stability in high mountains, including: the non‐linear response of firn and ice to warming; three‐dimensional warming of subsurface bedrock and its relation to site geology; de‐glaciation accompanied by exposure of new sediment; and combined short‐term effects of precipitation and temperature. Based on several case studies, we propose that the following mechanisms can significantly alter landslide magnitude and frequency, and thus hazard, under warming conditions: (1) positive feedbacks acting on mass movement processes that after an initial climatic stimulus may evolve independently of climate change; (2) threshold behavior and tipping points in geomorphic systems; (3) storage of sediment and ice involving important lag‐time effects. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".