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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

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Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping. / Donkersley, Philip William; Blanford, Justine M.; Queiroz, Renan Batista et al.
In: Journal of Economic Entomology, Vol. 111, No. 6, 01.12.2018, p. 2553-2561.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Donkersley, PW, Blanford, JM, Queiroz, RB, Silva, FWS, Carvalho, CM, Al-Sadi, AM & Elliot, SL 2018, 'Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping', Journal of Economic Entomology, vol. 111, no. 6, pp. 2553-2561. https://doi.org/10.1093/jee/toy248

APA

Donkersley, P. W., Blanford, J. M., Queiroz, R. B., Silva, F. W. S., Carvalho, C. M., Al-Sadi, A. M., & Elliot, S. L. (2018). Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping. Journal of Economic Entomology, 111(6), 2553-2561. https://doi.org/10.1093/jee/toy248

Vancouver

Donkersley PW, Blanford JM, Queiroz RB, Silva FWS, Carvalho CM, Al-Sadi AM et al. Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping. Journal of Economic Entomology. 2018 Dec 1;111(6):2553-2561. Epub 2018 Aug 20. doi: 10.1093/jee/toy248

Author

Donkersley, Philip William ; Blanford, Justine M. ; Queiroz, Renan Batista et al. / Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia) : Identifying High-Risk Areas by Climatic Mapping. In: Journal of Economic Entomology. 2018 ; Vol. 111, No. 6. pp. 2553-2561.

Bibtex

@article{051c2207cd3b4dbab66fedc542c6a1a3,
title = "Witch{\textquoteright}s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia): Identifying High-Risk Areas by Climatic Mapping",
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 {\textquoteleft}Candidatus Phytoplasma aurantifolia{\textquoteright}, the etiological agent of Witches{\textquoteright} 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.",
keywords = "bioclimatic modeling, witches{\textquoteright} broom disease of lime, acid citrus lime, Middle East, Brazil",
author = "Donkersley, {Philip William} and Blanford, {Justine M.} and Queiroz, {Renan Batista} and Silva, {Farley W. S.} and Carvalho, {Claudine M{\'a}rcia} and Al-Sadi, {Abdullah Mohammed} and Elliot, {Simon L.}",
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{\textquoteright}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",
year = "2018",
month = dec,
day = "1",
doi = "10.1093/jee/toy248",
language = "English",
volume = "111",
pages = "2553--2561",
journal = "Journal of Economic Entomology",
issn = "0022-0493",
publisher = "Entomological Society of America",
number = "6",

}

RIS

TY - JOUR

T1 - Witch’s Broom Disease of Lime (Candidatus Phytoplasma aurantifolia)

T2 - Identifying High-Risk Areas by Climatic Mapping

AU - Donkersley, Philip William

AU - Blanford, Justine M.

AU - Queiroz, Renan Batista

AU - Silva, Farley W. S.

AU - Carvalho, Claudine Márcia

AU - Al-Sadi, Abdullah Mohammed

AU - Elliot, Simon L.

N1 - 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

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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.

AB - 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.

KW - bioclimatic modeling

KW - witches’ broom disease of lime

KW - acid citrus lime

KW - Middle East

KW - Brazil

U2 - 10.1093/jee/toy248

DO - 10.1093/jee/toy248

M3 - Journal article

VL - 111

SP - 2553

EP - 2561

JO - Journal of Economic Entomology

JF - Journal of Economic Entomology

SN - 0022-0493

IS - 6

ER -