Spatial patterns in the adaptive capacity of dryland agricultural households in South Punjab, Pakistan

Abstract

Climate change and desertification continue to threaten livelihoods in drylands across the globe. This study explores the relative importance of Sustainable Livelihoods Framework components in explaining variation in the adaptive capacity of agricultural households in three districts in the drylands of south Punjab, Pakistan, and to identify spatial patterns in adaptive capacity distribution. Questionnaire generated data were analyzed using Non-Linear Principal Component Analysis and spatial cluster mapping using the Global Moran's I and Anselin Local Moran's I. Natural assets were found to describe most variation among households, followed by physical, financial, human and social assets. Most households with high adaptive capacity were spatially clustered in Rahim Yar Khan, a district offering more employment opportunities and multiple income sources. Low adaptive capacity clusters were abundant in Rajanpur where respondents had negative loadings on all the principal components. Bahawalpur district lacked any significant adaptive capacity clusters. Spatial analyses can serve as a useful tool for policy makers in identifying the areas requiring government intervention to enhance adaptive capacity. The approach used here could usefully be applied to dryland regions in other parts of the world, and could help guide more targeted efforts to build adaptive capacity.