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SSRN Electronic Journal

DOI: 10.2139/ssrn.1566861

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A Spatial Agent-Based Model to Explore Scenarios of Adaptation to Climate Change in an Alpine Tourism Destination

Journal article published in 1970 by Stefano Balbi ORCID, Carlo Giupponi, Pascal Perez
This paper is available in a repository.
This paper is available in a repository.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

A vast body of literature suggests that the European Alpine region may be one of the most sensitive to climate change impacts. Adaptation to climate change of Alpine socio-ecosystems is increasingly becoming an issue of interest for the scientific community while the people of the Alps are often unaware of or simply ignore the problem. ClimAlpTour is a European research project of the Alpine Space Programme, bringing together institutions and scholars from all countries of the Alpine arch, in view of dealing with the expected decrease in snow and ice cover, which may lead to a rethinking of tourism development beyond the traditional vision of winter sports. The research reported herein analyses the municipality of Auronzo di Cadore (22,000 ha) in the Dolomites under the famous peaks of the “Tre Cime di Lavaredo”. The local economy depends on tourism which is currently focused on the summer season, while the winter season is weak. As a whole, the destination receives approximately 65,000 guests per year with a resident population of 3,600 inhabitants. Since recently the Community Council is considering options on how to stimulate a further development of the winter tourism. This paper refers to a prototype agent-based model, called AuronzoWinSim, for the assessment of alternative scenarios of future local development strategies, taking into account complex spatial and social dynamics and interactions. Different typologies of winter tourists compose the set of human agents. Climate change scenarios are used to produce temperature and snow cover projections. The model is mainly informed by secondary sources, including demographic and economic time series, and biophysical data which feed-in its spatial dimension. Primary data from field surveys are used to calibrate the main parameters. AuronzoWinSim is planned for use in a participatory context with groups of local stakeholders.