Search

Climate warming, agricultural intensity, and urban growth are main forces triggering land degradation in advanced economies. Being active over different spatial and temporal scales, they usually reflect—at least indirectly—the impact of additional factors, such as wellbeing, demographic dynamics, and social development, on land quality. Using descriptive statistics and a multiple regression analysis, we analyzed the impact of these three processes comparatively over a decadal scale from 1960 to 2020 at the provincial level (Nuts-3 sensu Eurostat) in Italy. We enriched the investigation with a short-term forecast for 2030, based on four simplified assumptions grounded on a purely deterministic approach. Land degradation was estimated adopting the Environmental Sensitive Area Index (ESAI) measured at the spatio-temporal scale mentioned above. Computing on multiple observations at nearly 300,000 locations all over Italy, provinces were regarded as representative spatial units of the territorial pattern of land degradation. Between 1960 and 1990, the three predictors (climate, agriculture, and urbanization) explained a relatively high proportion of variance, suggesting a modest role for any other (unobserved) factor. All of these factors were found to be highly significant predictors of land degradation intensity across provinces, the most impactful being farming intensity. The highest adjusted-R2 coefficient was observed in both 1990 and 2000, and suggests that the three predictors still reflect the most powerful drivers of land degradation in Italy at those times, with a marginal role for additional (unobserved) factors. The impact of farming intensity remained high, with the role of urbanization increasing moderately, and the role of climate aridity declining weakly between 2000 and 2010. In more recent times (2010 and 2020), and in future (2030) scenarios, the adjusted R2 diminished moderately, suggesting a non-negligible importance of external (unobserved) factors and the rising role of spatial heterogeneity. The climate factor became progressively insignificant over time, while increasing the role of urbanization systematically. The impact of farming intensity remained high and significant. These results underlie a latent shift in the spatial distribution of the level of land vulnerability in Italy toward a spatially polarized model, influenced primarily by human pressure and socioeconomic drivers and less intensively shaped by biophysical factors. Climate aridity was revealed to be more effective in the explanation of land degradation patterns in the 1960s rather than in recent observation times. [ABSTRACT FROM AUTHOR]

This article presents empirical results of a multivariate analysis run with the aim to identify (apparent and latent) socioeconomic transformations that shape the distribution pattern of cropland in a metropolitan region of southern Europe (Athens, Greece) over a sufficiently long time interval spanning from 1960 to 2010. The study area is representative of monocentric cities expanding in an unregulated fashion and experiencing sequential cycles of economic growth and recession. Percent share of cropland in total municipal area increased moderately over time. A non-linear relationship with the distance from downtown Athens was also observed, indicating that the highest rates of cropland were observed at a distance ranging between 20 and 30 km from the inner city. A multivariate regression was run by decade at each municipality of the study area using 11 predictors with the aim to identify the factors most associated with cropland decline along urban fringes. Distance from downtown Athens, soil and climate quality, population growth rate, and competing land use were the most relevant factors correlated with cropland expansion (or decline) in the study area. Competing land use was particularly important for cropland decline in a first urbanization phase (1960–1980), while population growth rate—and hence an increased human pressure—was positively associated with agricultural areas in a subsequent phase (1990–2010). In these regards, per capita urban land had a non-linear spatial behavior, being correlated negatively with cropland in 1960 and 1970 and positively in 2010, possibly indicating a moderate change from a monocentric model towards a more dispersed metropolitan configuration impacting distribution of agricultural areas. Empirical findings of this study suggest that effective strategies supporting peri-urban agriculture require a comprehensive knowledge of the local socioeconomic context and relevant biophysical conditions—specifically focusing on the dominant soil and climate attributes. [ABSTRACT FROM AUTHOR]