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Assessing vulnerability of selected farming communities in the Philippines based on a behavioural model of agent's adaptation to global environmental change
Authors:Lilibeth Acosta-Michlik  Victoria Espaldon
Institution:aUnité d’économie rurale, Faculté d’ingénierie biologique, agronomique et environnementale, Université catholique de Louvain, Belgium;bCentre for the Study of Environmental Change and Sustainability, School of Geosciences, University of Edinburgh, UK;cSchool of Environmental Science and Management, University of the Philippines at Los Baños, Philippines
Abstract:Behavioural models that allow simple representation of the complexity of human–environment links are important in vulnerability assessment because they allow the analysis of human adaptive processes in a changing environment. This paper applies an agent-based framework that considers the behavioural model of farmers in three villages in a municipality in the Philippines. Agent-based modelling is a useful policy tool for simulating the effects of different adaptation options on reducing vulnerability because it allows representation of not only the dynamic changes in climate and market but also the dynamic adaptive process of different groups of communities to the impacts of these changes. Model simulations of adaptation options under various global change scenarios showed that production support would significantly reduce future vulnerability only if complemented with appropriate market support. It is thus important for policy to provide a complementary bundle of adaptation measures. Lack of money and information are the most important reasons for not applying available technical adaptation measures, which currently hinder reduction of vulnerability in selected villages in the municipality. Social networks, which play an important role in adapting to environmental changes, are limited to relatives and neighbours, who are important sources of informal credit.
Keywords:Adaptation  Agent-based model  Climate change  Globalisation  Vulnerability
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