Xylella Fastidiosa Active Containment Through a multidisciplinary-Oriented Research Strategy

Researchers studied the effects of climatic and spatial factors on the geographic distribution of Xylella fastidiosa in Apulia and Alicante, two regions in Europe severely affected by this pathogen.

Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)The aim is to support plant health authorities in building risk maps for the implementation of surveillance and control strategies.
From the climate point of view, results reinforce previous studies’ findings indicating that Xylella fastidiosa subsp. multiplex, the one detected in Alicante, may be more tolerant to cold temperatures. However, the models show no direct relationships between the distribution and temperature or precipitation in the study area.

In Apulia, areas with more precipitation in winter and higher temperatures during the vegetative growth period of the olive trees were associated with a lower probability of Xylella fastidiosa subsp. pauca presence. These results might indicate that wet winters and hot summers would be detrimental to vector activity and/or bacterial multiplication in the host plants. Nevertheless, the outcomes of the models are somehow affected by the heterogeneous distribution of the samples in this region.

In both the study areas, the spatial factor had the strongest effect on the models. This substantial contribution might indicate that the current extent of Xylella fastidiosa in the study regions had arisen from a single outbreak in each zone or several nearby outbreaks that coalesced. These results also indicated that climatic factors are not likely to prevent the colonization of the neighboring areas by Xylella fastidiosa. Therefore, control measures should be enforced to limit further disease spread.
The spatial models developed in the study may assist risk managers in designing more efficient surveillance strategies, enabling authorities to adjust inspection and sampling efforts according to the probability of Xylella fastidiosa presence.

Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
https://doi.org/10.3389/fpls.2020.01204 | via Frontiers in Plant Science