The implications of warmer winters for ice climbing: A case study of the Mount Washington Valley, New Hampshire, USA
Bibliographic record
Abstract
Ice climbing is important to the culture and economies of mountain communities worldwide. However, warming winters call into question the future of livelihoods associated with ice climbing. In response, this case study presents observed and simulated ice climbing conditions in the Mount Washington Valley, New Hampshire, USA, as well as local climbing guide's experiences of and responses to these changes. First, variability in ice conditions were evaluated by classifying and summarizing ice characteristics depicted in a 20-year collection of conditions reports (n = 372) including photos and written observations for a benchmark ice climb (Standard Route). Next, climate model ensembles were used to simulate probable changes in future ice season lengths according to intermediate and high climate forcing scenarios (i.e., RCP 4.5 & RCP 8.5). Finally, a survey and focus group were conducted with Mount Washington Valley ice climbing guides to examine observations and lived experiences of warming winters. This study, which is the first formal assessment of the implications of warming winters for ice climbing, reveals significant effects of climate change for current and projected ice climbing conditions as well as marked, and often differentiated, vulnerability and adaptability to these changes amongst climbing guides. The unique mixed-methods approach used is applicable in other locales where climate change is impacting ice climbing activities and associated livelihoods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".