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    Rights statement: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Economic Entomology following peer review. The definitive publisher-authenticated versionPhilip Donkersley, Justine M Blanford, Renan Batista Queiroz, Farley W S Silva, Claudine M Carvalho, Abdullah Mohammed Al-Sadi, Simon L Elliot, Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping, Journal of Economic Entomology, Volume 111, Issue 6, December 2018, Pages 2553–2561, https://doi.org/10.1093/jee/toy248 is available online at: https://academic.oup.com/jee/article/111/6/2553/5076923

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Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping

Research output: Contribution to journalJournal article

Published
  • Philip William Donkersley
  • Justine M. Blanford
  • Renan Batista Queiroz
  • Farley W. S. Silva
  • Claudine Márcia Carvalho
  • Abdullah Mohammed Al-Sadi
  • Simon L. Elliot
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<mark>Journal publication date</mark>1/12/2018
<mark>Journal</mark>Journal of Economic Entomology
Issue number6
Volume111
Number of pages9
Pages (from-to)2553-2561
Publication statusPublished
Early online date20/08/18
Original languageEnglish

Abstract

Biological invasions of vectorborne diseases can be devastating. Bioclimatic modeling provides an opportunity to assess and predict areas at risk from complex multitrophic interactions of pathogens, highlighting areas in need of increased monitoring effort. Here, we model the distribution of an economically critical vectorborne plant pathogen ‘Candidatus Phytoplasma aurantifolia’, the etiological agent of Witches’ Broom Disease of Lime. This disease is a significant limiting factor on acid lime production (Citrus aurantifolia, Swingle) in the Middle East and threatens its production globally. We found that temperature, humidity, and the vector populations significantly determine disease distribution. Following this, we used bioclimatic modeling to predict potential novel sites of infections. The model outputs identified potential novel sites of infection in the citrus producing regions of Brazil and China. We also used our model to explore sites in Oman where the pathogen may not be infectious, and suggest nurseries be established there. Recent major turbulence in the citrus agricultural economy has highlighted the importance of this work and the need for appropriate and targeted monitoring programs to safeguard lime production.

Bibliographic note

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Economic Entomology following peer review. The definitive publisher-authenticated versionPhilip Donkersley, Justine M Blanford, Renan Batista Queiroz, Farley W S Silva, Claudine M Carvalho, Abdullah Mohammed Al-Sadi, Simon L Elliot, Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping, Journal of Economic Entomology, Volume 111, Issue 6, December 2018, Pages 2553–2561, https://doi.org/10.1093/jee/toy248 is available online at: https://academic.oup.com/jee/article/111/6/2553/5076923