‘Old’ Territorial Disparities and ‘New’ Spatial Patterns: Unraveling the Latent Nexus between Sustainable Development and Desertification Risk in Italy

Abstract

Although sustainable development and desertification risk are hegemonic concepts in environmental economics, their intimate relationship was occasionally studied and made spatially explicit. The present study contributes to fill this knowledge gap by delineating a statistical procedure that investigates, at the municipal scale in Italy, the association between two composite indexes of sustainable development (SDI) and desertification risk (ESAI). Based on a refined knowledge of the local context, results of a geographically weighted regression delineate two distinctive territorial models reflecting the mutual interplay of sustainable development and desertification risk in Italy. The level of sustainable development was negatively associated with desertification risk in Southern Italy, a region classified as ‘affected’ based on the Italian National Action Plan (NAP) to combat desertification. These findings document a traditional ‘downward spiral’ between local development and early desertification processes, suggesting that a high desertification risk is associated with local contexts having structural conditions that lead to unsustainable development, e.g., population growth, industrial development, tourism pressure, crop intensification, agricultural mechanization, and land abandonment. In non-affected regions such as Northern and Central Italy, the level of sustainable development was positively associated with desertification risk, indicating that sustainability conditions can be unable, at least in some local contexts, to assure a significant containment of environmental degradation. Policy strategies reconnecting local development with more specific environmental conservation targets in development countries are increasingly required to adapt to (and differentiate on the base of) heterogeneous local contexts.

Keywords

• composite indexes
• geographically weighted regression
• sustainability
• agricultural intensification
• Italy