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Global biogeography and invasion risk of the plant pathogen genus Phytophthora

By P. Scott, M.K-F. Bader, T. Burgess, G. Hardy and N. Williams


A global database of the pathogen genus Phytophthora, comprising ca. 12,500 disease reports over 142 years, was collated to benchmark and examine the genus-wide distribution and invasiveness. Rarefaction was used to estimate global Phytophthora species richness. We applied a framework, leveraging geographically and economically biased pathogen data against environmental and socioeconomic metrics to model their distribution. Hierarchical clustering of host and country range allowed characterisation of invasion potential. Phytophthora descriptions rose to 86 by the year 2000, surging to over 180 species to date driven primarily by novel molecular techniques, resulting in a species richness estimate of 326 (95% CI: 274–378). Countries with diverse ecosystems and entrenched agricultural and forestry industries supported by intensive research programmes reported the highest diversity. Constructing principal components from enviro-socioeconomic factors highlighted national data deficits, showing that two-thirds of trading nations have reported lower-than-predicted species numbers. Phytophthora species clustered into two main invasiveness groups as either cosmopolitan generalists or specialists, historically tied to agriculture. Further spread and detection of Phytophthora pathogens are inevitable with increasing global trade, especially in developing and emerging economies. Adoption of best practice diagnostics and enhanced resource and data sharing are crucial for coordinated global pathogen surveillance and biosecurity. This research aimed to test the following hypotheses: • The global distribution of Phytophthora species is associated with environmental, social and economic traits of different country’s. • Models for Phytophthora diversity, incorporating environmental, social and economic characteristics, can be used to predict a countries trade risk. • Phytophthora species biogeography and host range can be used to predict invasiveness and a country’s conduciveness to infection

Publisher: 'Elsevier BV'
Year: 2019
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Provided by: Research Repository
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