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Estimating the Impact of Socioeconomic Drivers on Land Degradation in Italy via Spatio‐Temporal Additive Expectile Regression

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  • Luca Merlo
  • Beatrice Foroni
  • Ioannis Konaxis
  • Lea Petrella
  • Luca Salvati

Abstract

Climate changes, soil degradation, and desertification increasingly threaten the entire territory of Italy due to the complex interplay between natural processes and anthropogenic forces. Motivated by this pressing issue, this paper investigates how land‐use and socioeconomic drivers have shaped desertification dynamics across Italian provinces between 1960 and 2020 using an additive expectile regression model for spatio‐temporal data. The effects of continuous covariates are modeled as the sum of a linear part and a nonlinear smooth function using penalized B‐splines, while tensor‐product B‐splines based on coordinate information are used to capture spatial dependencies. To promote sparsity in the model, estimation is carried out via component‐wise boosting combined with a stability selection approach, retaining only the most dominant factors. The results identify industrialization and tourism development activities as the primary amplifiers of desertification risk in vulnerable regions. Our analysis also uncovers strong spatial heterogeneity of desertification processes related to province characteristics, which is particularly acute in southern Italy and in the major islands.

Suggested Citation

  • Luca Merlo & Beatrice Foroni & Ioannis Konaxis & Lea Petrella & Luca Salvati, 2026. "Estimating the Impact of Socioeconomic Drivers on Land Degradation in Italy via Spatio‐Temporal Additive Expectile Regression," Environmetrics, John Wiley & Sons, Ltd., vol. 37(2), March.
    • Handle: RePEc:wly:envmet:v:37:y:2026:i:2:n:e70085
    DOI: 10.1002/env.70085
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    References listed on IDEAS

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