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Título

Global risk predictions for Pierce's disease of grapevines

AutorGiménez-Romero, Alex CSIC ORCID
Fecha de publicación12-dic-2022
EditorGitHub
CitaciónGiménez-Romero, Alex; 2022; Global risk predictions for Pierce's disease of grapevines [Software]; GitHub; https://github.com/agimenezromero/PierceDisease-GlobalRisk-Predictions
ResumenThe clonal lineage of the bacterium Xylella fastidiosa (Xf) responsible for Pierce’s disease (PD) poses a threat to viticulture worldwide. Although this vector-transmitted disease has remained mainly restricted to the United States, recent introductions on the islands of Majorca (Spain) and Taiwan have raised concerns about the risk of spreading worldwide. To assess this risk, here we build a climate-driven epidemiological model that simulates PD progression. The model considers the temperature-dependent infection process based on a 3-year inoculation assay and assume local disease propagation when climatic conditions are favourable. The model was successfully validated with spatiotemporal data of the PD distribution in the United States yielding a remarkable ~90% accuracy. Thereafter the model was applied to the main winegrowing regions worldwide, specially focusing in Europe as a case study based on the distribution of the main vector, Philaenus spumarius. Our model simulation reveals that most wine-quality producing areas in China, Europe, Argentina, Chile, South Africa, and Australia currently thrive in non-risk or transient-risk zones. To a lesser extent, epidemic-risk zones with low to moderate risk indices appear in coastal zones such as Mallorca and Apulia, where Xf outbreaks have been already detected. The European case shows how models assuming a vector heterogeneous distribution yield lesser extended epidemic-risk zones than previous risk maps. Overall, a global expansion of PD epidemic-risk zones is projected for 2050, although with low increase in risk indices. Our study highlights the importance of considering climate variability and an invasive criterion to obtain precise risk maps for plant health decision-making.
DescripciónThis repository contains an example of the simulation code used to assess global risk of Pierce's Disease of grapevines.-- In the presented example we make use of GRIB files to compute the climatic variables (indeed this is the tricky part, the simulation itself is pretty easy). However, for other usages, temperature data could be in different formats, such as .csv or excel. As previously mentioned, the algorithms to compute MGDD and CDD are described in this repository, athough they are written to be used with GRIB files using Julia. To compute the climatic variables with other data formats the details of the implementation could change for major efficiency. Anyone interested to use the approach presented here but having troubles in the implementation (e.g. because she/he is using other data formats) can contact us at alex@ifisc.uib-csic.es.
Versión del editorhttps://github.com/agimenezromero/PierceDisease-GlobalRisk-Predictions
URIhttp://hdl.handle.net/10261/330243
ReferenciasGiménez-Romero, Alex; Galván Fraile, Javier; Montesinos, Marina; Bauzà, Joan; Godefroid, Martin; Fereres, Alberto; Ramasco, José J.; Matías, Manuel A.; Moralejo, Eduardo. Global predictions for the risk of establishment of Pierce's disease of grapevines. https://doi.org/10.1038/s42003-022-04358-w . http://hdl.handle.net/10261/305247
Aparece en las colecciones: (IFISC) Software de investigación

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