Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28776
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dc.contributor.authorWhite, Steven Men_UK
dc.contributor.authorBullock, James Men_UK
dc.contributor.authorHooftman, Danny A Pen_UK
dc.contributor.authorChapman, Daniel Sen_UK
dc.date.accessioned2019-02-13T16:47:33Z-
dc.date.available2019-02-13T16:47:33Z-
dc.date.issued2017-06-30en_UK
dc.identifier.urihttp://hdl.handle.net/1893/28776-
dc.description.abstractXylella fastidiosa is an important plant pathogen that attacks several plants of economic importance. Once restricted to the Americas, the bacterium, which causes olive quick decline syndrome, was discovered near Lecce, Italy in 2013. Since the initial outbreak, it has invaded 23,000 ha of olives in the Apulian Region, southern Italy, and is of great concern throughout Mediterranean basin. Therefore, predicting its spread and estimating the efficacy of control are of utmost importance. As data on this invasive infectious disease are poor, we have developed a spatially-explicit simulation model for X. fastidiosa to provide guidance for predicting spread in the early stages of invasion and inform management strategies. The model qualitatively and quantitatively predicts the patterns of spread. We model control zones currently employed in Apulia, showing that increasing buffer widths decrease infection risk beyond the control zone, but this may not halt the spread completely due to stochastic long-distance jumps caused by vector dispersal. Therefore, management practices should aim to reduce vector long-distance dispersal. We find optimal control scenarios that minimise control effort while reducing X. fastidiosa spread maximally—suggesting that increasing buffer zone widths should be favoured over surveillance efforts as control budgets increase. Our model highlights the importance of non-olive hosts which increase the spread rate of the disease and may lead to an order of magnitude increase in risk. Many aspects of X. fastidiosa disease invasion remain uncertain and hinder forecasting; we recommend future studies investigating quantification of the infection growth rate, and short and long distance dispersal.en_UK
dc.language.isoenen_UK
dc.publisherBMCen_UK
dc.relationWhite SM, Bullock JM, Hooftman DAP & Chapman DS (2017) Modelling the spread and control of Xylella fastidiosa in the early stages of invasion in Apulia, Italy. Biological Invasions, 19 (6), pp. 1825-1837. https://doi.org/10.1007/s10530-017-1393-5en_UK
dc.rights© The Author(s) 2017 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectBuffer zoneen_UK
dc.subjectCoDiROen_UK
dc.subjectOlea europaeaen_UK
dc.subjectOlive quick decline syndromeen_UK
dc.subjectPierce’s diseaseen_UK
dc.subjectX. fastidiosaen_UK
dc.titleModelling the spread and control of Xylella fastidiosa in the early stages of invasion in Apulia, Italyen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1007/s10530-017-1393-5en_UK
dc.citation.jtitleBiological Invasionsen_UK
dc.citation.issn1573-1464en_UK
dc.citation.issn1387-3547en_UK
dc.citation.volume19en_UK
dc.citation.issue6en_UK
dc.citation.spage1825en_UK
dc.citation.epage1837en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderNatural Environment Research Councilen_UK
dc.citation.date21/02/2017en_UK
dc.contributor.affiliationCentre for Ecology & Hydrology (CEH)en_UK
dc.contributor.affiliationCentre for Ecology & Hydrology (CEH)en_UK
dc.contributor.affiliationCentre for Ecology & Hydrology (CEH)en_UK
dc.contributor.affiliationCentre for Ecology & Hydrologyen_UK
dc.identifier.isiWOS:000402143200012en_UK
dc.identifier.scopusid2-s2.0-85013482403en_UK
dc.identifier.wtid1100131en_UK
dc.contributor.orcid0000-0003-1836-4112en_UK
dc.date.accepted2017-02-16en_UK
dcterms.dateAccepted2017-02-16en_UK
dc.date.filedepositdate2019-02-12en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorWhite, Steven M|en_UK
local.rioxx.authorBullock, James M|en_UK
local.rioxx.authorHooftman, Danny A P|en_UK
local.rioxx.authorChapman, Daniel S|0000-0003-1836-4112en_UK
local.rioxx.projectProject ID unknown|Natural Environment Research Council|http://dx.doi.org/10.13039/501100000270en_UK
local.rioxx.freetoreaddate2019-02-12en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2019-02-12|en_UK
local.rioxx.filenameWhite2017_Article_ModellingTheSpreadAndControlOf.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1573-1464en_UK
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