4.1 The most important drivers influencing vulnerability

Discussions with experts and the Multicriteria Analysis allowed us to establish the most important drivers influencing vulnerability. All of the people interviewed on the subject agreed in assigning the highest score to issues related to adaptive capacity (55/100), followed by sensitivity (29/100), and exposure (16/100). In the exposure category, snowpack reduction received the highest score (25/100), followed by glaciers melting (17/100), water scarcity – drought (15/100), changes in climate suitability, natural hazards and scenic beauty (all 12/100), and finally permafrost melting – rockfall (7/100). In the sensitivity group, the local environment (23/100) and institutions (20/100) obtained the highest scores, followed by tourism demand and supply (both 14/100). Afterwards these were local infrastructure (13/100), population (9/100), and economy (7/100). In the adaptive capacity category, acceptability clearly appears to play the most important role (79/100 against 21/100 for feasibility). Finally, in the feasibility sub-category, mainly the economic (30/100) and the technological (23/100) aspects appear to play the largest role. Two indicators, namely the past actions taken from the tourism sector in this direction (29/100) and the political framework (results of a 2008 vote related to the right of appeal of organisations) (14/100) (both in the adaptive capacity category), account for 43/100 of the total vulnerability score. Other indicators follow with a far smaller grade. After experts’ judgment, 24 indicators (over the 70) account for 80/100 of the score (See Table).Results given by experts were particularly homogenous in assessing the relative score of exposure, sensitivity and adaptive capacity and of the two components of adaptive capacity (feasibility and acceptability). They did, however, sometimes diverge in the other categories. The sensitivity analysis allows us to consider this point. Astonishingly, scores for adaptive capacity correspond extremely well with what was found in the ESPON Climate[1] project and in their Delphi analysis.

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