Assessing the global potential distribution of Xylella fastidiosa using species distribution models

Species distribution models (SDMs) determine the relationships between sample location for a species and associated environmental variables, and are used to estimate the ecological requirements for a particular species. SDMs provide realistic scenarios to explain the influence of bioclimatic variables on the epidemiology of plant pathogens, particularly in the context of emerging plant diseases. Different modeling techniques, including regression, classification and machine learning approaches were used within an ensemble forecasting framework (Naimi & Araujo, 2016) to quantify and map the global patterns of the potential geographic distribution of Xylella fastidiosa. The global distribution of X. fastidiosa was obtained from EFSA (EFSA, 2016). To cope with the equilibrium assumption, pseudo-absence data were generated outside the organism’s ecological domain (Barbet- Massin et al., 2012). Overall, projected potential distribution from estimated models conformed well to the current known distribution of X. fastidiosa. The application of SDMs to the most prevalent X. fastidiosa subspecies (i.e. fastidiosa, pauca and multiplex) will be discussed.This study was financially supported by funding from the European Union’s Horizon 2020 research and innovation program under grants agreement No 635646 POnTE (Pest Organisms Threatening Europe) and No 727987 XF-ACTORS (Xylella fastidiosa Active Containment Through a multidisciplinary-Oriented Research Strategy).N