Assessing the driving role of the anthropogenic landscape on the distribution of the Xylella fastidiosa-driven "olive quick decline syndrome" in Apulia (Italy).

The plant pathogen Xylella fastidiosa (Xf) is a significant threat to various economically important tree cash crops. Although previously found only in the Americas, the bacterium responsible for olive quick decline syndrome was detected in Apulia, Italy, in 2013. Since then, it has spread to approximately 54,000 ha of olive trees in the region, causing dramatic concern throughout the Mediterranean basin. As a result, it is crucial to comprehend its distribution and forecast its potential diffusion. The effect of the anthropogenic component of the landscape on the distribution of Xf remains little explored. The present study used an ecological niche model to identify how different land uses, used as proxies of different levels of human pressure across the Apulia territory, impacted the distribution of the Xf-infected olive trees in 2015-2021. Results demonstrated that the anthropogenic component significantly contributed to the epidemic, with the road system representing the main driver of diffusion and natural/seminatural areas hampering Xf spread at the landscape scale. This evidence highlighted the importance of explicitly considering the effects of the anthropogenic landscape when modelling Xf distribution and support the design of landscape-informed monitoring strategies to prevent Xf spread in Apulia and other Mediterranean countries.

Exploring the role of land degradation on agricultural land use change dynamics.

The role that land-use and socioeconomic factors exert on consolidating land degradation (LD) processes is a major research issue. However, intensity and type of the impact played by LD on such land use factors is still underexplored. The present study investigates the role of LD on land-use change (LUC) trajectories of land abandonment (LA) and urban expansion (URB) in the three geographical repartitions (North, Centre, South) of Italy between 1990 and 2012, by means of the Environmental Niche Factor Analysis (ENFA). ENFA is a multivariate approach originally introduced in the analysis of animal ecology allowing to compute habitat suitability (HS) models without requiring presence/absence data. Four environmental quality indices about climate (CQI), soil (SQI), vegetation (VQI) and land management (MQI) have been analyzed for the years 1990 and 2000 and related to the trajectories of LA and URB, respectively, for the time periods 1990-2000 and 2000-2012. Empirical results have indicated that different driving forces are linked to LA and URB, and that for each trajectory, the role of some forces may change over time. Evidence shows that soil quality and low human pressure represent the main drivers of LA. By contrast, as for URB, high human pressure represented the main driving factor throughout the country, both during 1990-2000 and 2000-2012. The HS maps show the probability arrangement of LA and URB in the three geographical repartitions. Starting from this work, further research is increasingly required to implement prediction models of future LA and URB trajectories according to the current land quality status.