Eco-epidemiological uncertainties of emerging plant diseases: the challenge of predicting Xylella fastidiosa dynamics in novel environments
2020
Occhibove, Flavia | Chapman, Daniel S | Mastin, Alexander J | Parnell, Stephen S R | Agstner, Barbara | Mato-Amboage, Rosa | Jones, Glyn | Dunn, Michael | Pollard, Chris R J | Robinson, James S | Marzano, Mariella | Davies, Althea L | White, Rehema M | Fearne, Andrew | White, Steven M | European Commission (Horizon 2020) | Biotechnology and Biological Sciences Research Council | Centre for Ecology & Hydrology (CEH) | Biological and Environmental Sciences | University of Salford | University of Salford | Fera Science Ltd | Fera Science Ltd | Fera Science Ltd | Forest Research | Forest Research | Forest Research | Forest Research | University of St Andrews | University of St Andrews | University of East Anglia | Centre for Ecology & Hydrology (CEH) | 0000-0003-1836-4112
In order to prevent and control the emergence of biosecurity threats such as vector-borne diseases of plants, it is vital to understand drivers of entry, establishment, and spatio-temporal spread, as well as the form, timing and effectiveness of disease management strategies. An inherent challenge for policy in combatting emerging disease is the uncertainty associated with intervention planning in areas not yet affected, based on models and data from current outbreaks. Following the recent high-profile emergence of the bacterium Xylella fastidiosa in several European countries, we review the most pertinent epidemiological uncertainties concerning this bacterium dynamics in novel environments. To reduce the considerable ecological and socio-economic impacts of these outbreaks, eco-epidemiological research in a broader range of environmental conditions needs to be conducted and used to inform policy to enhance disease risk assessment, and support successful policy-making decisions. By characterising infection pathways, we can highlight the uncertainties that surround our knowledge of this disease, drawing attention to how these are amplified when trying to predict and manage outbreaks in currently unaffected locations. To help guide future research and decision-making processes, we invited experts in different fields of plant pathology to identify data to prioritise when developing pest-risk assessments. Our analysis revealed that epidemiological uncertainty is mainly driven by the large variety of hosts, vectors, and bacterial strains, leading to a range of different epidemiological characteristics further magnified by novel environmental conditions. These results offer new insights on how eco-epidemiological analyses can enhance understanding of plant disease spread and support management recommendations.
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