Surveillance of airborne plant disease dissemination at continental scale using air mass trajectory analysis and network theory

Sustainable management of plant disease outbreaks in agriculture is one of the main challenges of the next years to restore economic and environmental viability of farming practices. Improving early-detection capabilities and disease surveillance is increasingly seen as an obligate step to design appropriate and effective prophylactic measures. In this context, plant diseases caused by wind-dispersed pathogens represent an interesting case of study, since they are particularly complex and hard to observe directly, especially if compared to other dissemination means, and demand for a multidisciplinary approach to be dealt with. Wind dispersal could imply a geographic differentiation in pathogens spreading potential, due to the emerging of local meteorological features. In this work we analyze the spatio-temporal patterns of wind connectivity in Europe and the Mediterranean basin in order to identify possible pathways of Puccinia graminis spores, the causal agent of stem rust of wheat. By running backwards Lagrangian simulations merging a biological layer coupled with a pathogen viability model, we investigate possible long-distance connections between regions in the study area across different seasons. We characterized these regions in terms of network centrality indicators to identify possible spreaders of stem rust of wheat, founding that Central and Western European regions appears to provide highest connectivity for the spread of P. graminis.