Name
Title | ||
|---|---|---|
A georeferenced agent-based model to analyze the climate change impacts on ski tourism at a regional scale |
Abstract | ||
|---|---|---|
One main argument for modeling socio-ecological systems is to advance the understanding of dynamic correlations between various human and environmental factors, including impacts and responses to environmental change. We explore the shift in skier distribution among ski resorts taking into account the behavioral adaptation of individuals due to the impact of climate change on snow conditions. This analysis is performed at a regional scale by means of a coupled gravity and georeferenced agent-based model. Four different scenarios are considered. Two scenarios assume an increase of winter mean temperature of +2 degrees C and +4 degrees C, respectively, taking into account only natural snow conditions. Two additional scenarios add the effect of snowmaking to enhance the natural snow depth and extend the skiing season in the +2 degrees C and +4 degrees C base scenarios. Results show differing vulnerability levels, allowing the classification of ski resorts into three distinct groups: (1) highly vulnerable ski resorts with a strong reduction in visitors attendance for all climate change scenarios, characterized by unfavorable geographical and attractiveness conditions, making it difficult to ensure snow availability in the future; (2) low vulnerability ski resorts, with moderate reduction in season length during a high climate change scenario but no reduction (or even an increase) in a low one, characterized by ski resorts with a medium capacity and attractiveness to ensure enough snow conditions and capture skiers from other ski resorts; and (3) resilient ski resorts, with good conditions to ensure future snow-reliable seasons and outstanding attractiveness, allowing them to offer longer ski seasons than their competitors and potentially attracting skiers from other closed or marginal resorts. Ski resorts included in this last group increase their skier attendance in all climate change scenarios. Although similar studies in the literature foretell a significant reduction of the ski market in the near future, another probable effect outlined in this study is a redefinition of this market due to a redistribution of skiers, from vulnerable ski resorts to more resilient ones. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1080/13658816.2014.933481 | International Journal of Geographical Information Science |
Keywords | Field | DocType |
gis,winter tourism,agent-based model,adaptation,climate change,snow | Climate change,Environmental resource management,Tourism,Environmental change,Attractiveness,Artificial intelligence,Snowmaking,Geography,Snow,Vulnerability,Climate change scenario,Simulation,Machine learning | Journal |
Volume | Issue | ISSN |
28 | 12 | 1365-8816 |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Pons | 1 | 1 | 1.71 |
| Peter A. Johnson | 2 | 6 | 2.46 |
| Martí Rosas-casals | 3 | 77 | 14.43 |
| Eric Jover | 4 | 1 | 0.69 |