Two methods to assess vulnerability to climate change in the Mexican agricultural sector

Abstract

We applied two methods to assess vulnerability to climate change in Mexico’s agricultural sector. The first one was a principal component analysis (PCA) that weighted each variable separately. For the second one, we integrated the variables in a linear array in which all variables were weighted equally, and then, we used the arithmetic sum of the sub-indices of exposure and sensitivity minus the adaptive capacity to obtain the vulnerability index. We discuss the similarities and differences between two methods with respect to municipal-level maps as the outputs. The application of the method for the agricultural sector in Mexico gave us the spatial distribution of the high- and very-high vulnerability categories, which we propose as a tool for policy. The methods agreed that the very-high vulnerability category is present in 39 municipalities. Also we found that 16 % of the total population in the country is located in high-exposure areas. In addition, 41 % lives in municipalities identified as highly-sensitive. In terms of adaptive capacity, 20 % of the population lives in 1273 municipalities with low-adaptive capacity. Finally, we discuss the need for information regarding vulnerability at the national level to guide policies aimed at reducing exposure and sensitivity and increasing adaptive capacity.