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Forecasting future range shifts of Xylella fastidiosa under climate change
Author(s) -
Godefroid Martin,
Cruaud Astrid,
Streito JeanClaude,
Rasplus JeanYves,
Rossi JeanPierre
Publication year - 2022
Publication title -
plant pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.928
H-Index - 85
eISSN - 1365-3059
pISSN - 0032-0862
DOI - 10.1111/ppa.13637
Subject(s) - xylella fastidiosa , outbreak , climate change , range (aeronautics) , distribution (mathematics) , biology , geography , ecology , agroforestry , bacteria , mathematical analysis , genetics , materials science , mathematics , virology , composite material
Abstract Xylella fastidiosa (Xf) is a vector‐borne plant bacterium native to the Americas, which causes severe diseases to agricultural crops, ornamental plants and forest trees. The bacterium is becoming a source of worldwide health plant concern and disease outbreaks associated with Xf have occurred outside of its native range (in Europe, Asia and the Middle East). Several studies have estimated risks associated with Xf outbreaks in invaded regions under current climate conditions, but future climate change has been seldom addressed. In the present study, we calibrated correlative models of bioclimatic species distribution to forecast the potential range and severity of two economically important Xf‐related diseases (Pierce's disease and the bacterial leaf scorch of shade trees) by the period 2040–2060. Models predict that conditions could become highly favourable for Pierce's disease in economically important wine‐producing regions of the world, highlighting the need to design control strategies. Similarly, models suggest that risk of bacterial leaf scorch of shade trees might increase in temperate regions where it is still apparently absent. However, we note that substantial uncertainty in predictions arises from high levels of correlation among climatic variables in the calibration data set. The inherent lack of knowledge concerning whether the distribution of Xf‐related diseases is at climatic equilibrium or not in Europe may also influence our predictions. The models provide valuable information to identify regions where increased surveillance efforts should be made and where control strategies are required.