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. The primary vector of Xf in Italy is the spittlebug Philaenus spumarius. Several studies suggested that vector mobility has been a critical factor influencing the epidemic, along with the insect population density and the pathogen transmission rate. 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. While a large contribution to the “olive quick decline syndrome” (OQSD) study has been focused on the insect-bacterium characteristics as well as on the climate, phenological and epidemiological Xf-driving factors, to date, the effect of the anthropogenic pressure on the distribution of OQDS has been neglected, notwithstanding some authors hinted to the importance of human mobility and settlements on the vector dissemination, and on the actual spread of insect pests over short and medium distances. To fill this research gap, we analyzed the spatiotemporal patterns of the OQDS epidemic in Apulia using 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.