Taken as a classical issue in applied economics, the notion of ‘convergence’ is based on the concept of path dependence, i.e., from the previous trajectory undertaken by the system during its recent history. Going beyond social science, a ‘convergence’ perspective has been more recently adopted in environmental studies. Spatial convergence in non-linear processes, such as desertification risk, is a meaningful notion since desertification represents a (possibly unsustainable) development trajectory of socio-ecological systems towards land degradation on a regional or local scale. In this study, we test—in line with the classical convergence approach—long-term equilibrium conditions in the evolution of desertification processes in Italy, a European country with significant socioeconomic and environmental disparities. Assuming a path-dependent development of desertification risk in Italy, we provided a diachronic analysis of the Environmental Sensitive Area Index (ESAI), estimated at a disaggregated spatial resolution at three times (1960s, 1990s, and 2010s) in the recent history of Italy, using a spatially explicit approach based on geographically weighted regressions (GWRs). The results of local regressions show a significant path dependence in the first time interval (1960–1990). A less significant evidence for path-dependence was observed for the second period (1990–2010); in both cases, the models’ goodness-of-fit (global adjusted R2) was satisfactory. A strong polarization along the latitudinal gradient characterized the first observation period: Southern Italian land experienced worse conditions (e.g., climate aridity, urbanization) and the level of land vulnerability in Northern Italy remained quite stable, alimenting the traditional divergence in desertification risk characteristic of the country. The empirical analysis delineated a more complex picture for the second period. Convergence (leading to stability, or even improvement, of desertification risk) in some areas of Southern Italy, and a more evident divergence (leading to worse environmental conditions because of urban sprawl and crop intensification) in some of the land of Northern Italy, were observed, leading to an undesired spatial homogenization toward higher vulnerability levels. Finally, this work suggests the importance of spatially explicit approaches providing relevant information to design more effective policy strategies. In the case of land vulnerability to degradation in Italy, local regression models oriented toward a ‘convergence’ perspective, may be adopted to uncover the genesis of desertification hotspots at both the regional and local scale.

Modeling Spatio-Temporal Divergence in Land Vulnerability to Desertification with Local Regressions / Imbrenda, V.; Coluzzi, R.; Di Stefano, V.; Egidi, G.; Salvati, L.; Samela, C.; Simoniello, T.; Lanfredi, M.. - In: SUSTAINABILITY. - ISSN 2071-1050. - 14:17(2022). [10.3390/su141710906]

Modeling Spatio-Temporal Divergence in Land Vulnerability to Desertification with Local Regressions

Salvati L.;
2022

Abstract

Taken as a classical issue in applied economics, the notion of ‘convergence’ is based on the concept of path dependence, i.e., from the previous trajectory undertaken by the system during its recent history. Going beyond social science, a ‘convergence’ perspective has been more recently adopted in environmental studies. Spatial convergence in non-linear processes, such as desertification risk, is a meaningful notion since desertification represents a (possibly unsustainable) development trajectory of socio-ecological systems towards land degradation on a regional or local scale. In this study, we test—in line with the classical convergence approach—long-term equilibrium conditions in the evolution of desertification processes in Italy, a European country with significant socioeconomic and environmental disparities. Assuming a path-dependent development of desertification risk in Italy, we provided a diachronic analysis of the Environmental Sensitive Area Index (ESAI), estimated at a disaggregated spatial resolution at three times (1960s, 1990s, and 2010s) in the recent history of Italy, using a spatially explicit approach based on geographically weighted regressions (GWRs). The results of local regressions show a significant path dependence in the first time interval (1960–1990). A less significant evidence for path-dependence was observed for the second period (1990–2010); in both cases, the models’ goodness-of-fit (global adjusted R2) was satisfactory. A strong polarization along the latitudinal gradient characterized the first observation period: Southern Italian land experienced worse conditions (e.g., climate aridity, urbanization) and the level of land vulnerability in Northern Italy remained quite stable, alimenting the traditional divergence in desertification risk characteristic of the country. The empirical analysis delineated a more complex picture for the second period. Convergence (leading to stability, or even improvement, of desertification risk) in some areas of Southern Italy, and a more evident divergence (leading to worse environmental conditions because of urban sprawl and crop intensification) in some of the land of Northern Italy, were observed, leading to an undesired spatial homogenization toward higher vulnerability levels. Finally, this work suggests the importance of spatially explicit approaches providing relevant information to design more effective policy strategies. In the case of land vulnerability to degradation in Italy, local regression models oriented toward a ‘convergence’ perspective, may be adopted to uncover the genesis of desertification hotspots at both the regional and local scale.
2022
convergence; environmentally sensitive area index; geographically weighted regression; Mediterranean Europe; sustainable land management
01 Pubblicazione su rivista::01a Articolo in rivista
Modeling Spatio-Temporal Divergence in Land Vulnerability to Desertification with Local Regressions / Imbrenda, V.; Coluzzi, R.; Di Stefano, V.; Egidi, G.; Salvati, L.; Samela, C.; Simoniello, T.; Lanfredi, M.. - In: SUSTAINABILITY. - ISSN 2071-1050. - 14:17(2022). [10.3390/su141710906]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1675482
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