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Climate-driven vulnerability and risk perception: implications for climate change adaptation in rural Mexico

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Abstract

Climate change is a major issue for rural communities in developing countries; thus, a better understanding of climate-related vulnerability and risk beliefs to unlock adaptation actions is necessary. By focusing on the rural communities located in the Mexican lagoon system of El Carmen, El Pajonal and La Machona, we first investigate different sources of vulnerability (exposure, sensitivity and adaptive capacity) and derive an aggregated vulnerability index integrating all the information. Hence, we link the different vulnerability sources—on top of additional cognitive and experiential elements—with climate-related individual risk perceptions. On the one hand, results identify the municipalities and communities most endangered and reveal the existence of levels of vulnerability along the lagoon deserving prioritization and action. On the other hand, a relationship between greater vulnerability and higher perception of risk applies. While exposure, sensitivity and cognitive components are found to shape climate-related risk perception, adaptive capacity and experiential factors appear to have no statistically significant influence.

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Funding

This research is related to the project “Diseño de Medidas de Adaptación para Reducir la Vulnerabilidad del sitio piloto del Sistema lagunar Carmen-Pajonal-Machona, Tabasco, a los Impactos Generados por el Cambio Climático y por Actividades Humanas”, funded by the World Bank and developed by the Instituto Nacional de Ecología y Cambio Climático (INECC) and the Instituto Mexicano de Tecnología del Agua (IMTA). We are greatful to Emiliano Ramieri for his excelent project coordination and Elisa Calliari and Laura Esmeralda Vidal Fernández for their support in data production. 

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Correspondence to Melania Michetti.

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Michetti, M., Ghinoi, S. Climate-driven vulnerability and risk perception: implications for climate change adaptation in rural Mexico. J Environ Stud Sci 10, 290–302 (2020). https://doi.org/10.1007/s13412-020-00607-8

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