Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28784
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dc.contributor.authorChapman, Daniel Sen_UK
dc.contributor.authorWhite, Steven Men_UK
dc.contributor.authorHooftman, Danny A Pen_UK
dc.contributor.authorBullock, James Men_UK
dc.date.accessioned2019-02-13T16:49:51Z-
dc.date.available2019-02-13T16:49:51Z-
dc.date.issued2015-04en_UK
dc.identifier.other795Een_UK
dc.identifier.urihttp://hdl.handle.net/1893/28784-
dc.description.abstractThis report considers the prospects for increasing the use of quantitative models for plant pest spread and dispersal in EFSA Plant Health risk assessments. The agreed major aims were to provide an overview of current modelling approaches and their strengths and weaknesses for risk assessment, and to develop and test a system for risk assessors to select appropriate models for application. First, we conducted an extensive literature review, based on protocols developed for systematic reviews. The review located 468 models for plant pest spread and dispersal and these were entered into a searchable and secure Electronic Model Inventory database. A cluster analysis on how these models were formulated allowed us to identify eight distinct major modelling strategies that were differentiated by the types of pests they were used for and the ways in which they were parameterised and analysed. These strategies varied in their strengths and weaknesses, meaning that no single approach was the most useful for all elements of risk assessment. Therefore we developed a Decision Support Scheme (DSS) to guide model selection. The DSS identifies the most appropriate strategies by weighing up the goals of risk assessment and constraints imposed by lack of data or expertise. Searching and filtering the Electronic Model Inventory then allows the assessor to locate specific models within those strategies that can be applied. This DSS was tested in seven case studies covering a range of risk assessment scenarios, pest types and dispersal mechanisms. These demonstrate the effectiveness of the DSS for selecting models that can be applied to contribute to EFSA Plant Health risk assessments. Therefore, quantitative spread and dispersal modelling has potential to improve current risk assessment protocols and contribute to reducing the serious impacts of plant pests in Europe.en_UK
dc.language.isoenen_UK
dc.publisherJohn Wiley & Sons, Ltden_UK
dc.relationChapman DS, White SM, Hooftman DAP & Bullock JM (2015) Inventory and review of quantitative models for spread of plant pests for use in pest risk assessment for the EU territory. EFSA Supporting Publications, 12 (4), Art. No.: 795E. https://doi.org/10.2903/sp.efsa.2015.EN-795en_UK
dc.rightsThis article is published under the terms of the Creative Commons Attribution License (CC BY ND) (https://creativecommons.org/licenses/by-nd/4.0/) which allows users to copy, distribute and transmit an article, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author(s).en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/en_UK
dc.subjectPlant pesten_UK
dc.subjectdiseaseen_UK
dc.subjectinvasionen_UK
dc.subjectdispersalen_UK
dc.subjectspreaden_UK
dc.subjectmodelen_UK
dc.subjectsimulationen_UK
dc.titleInventory and review of quantitative models for spread of plant pests for use in pest risk assessment for the EU territoryen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.2903/sp.efsa.2015.EN-795en_UK
dc.citation.jtitleEuropean Food Safety Authority - Supporting Publicationsen_UK
dc.citation.issn2397-8325en_UK
dc.citation.volume12en_UK
dc.citation.issue4en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderCentre for Ecology & Hydrologyen_UK
dc.citation.date17/04/2015en_UK
dc.contributor.affiliationCentre for Ecology & Hydrologyen_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.identifier.wtid1100220en_UK
dc.contributor.orcid0000-0003-1836-4112en_UK
dcterms.dateAccepted2015-04-17en_UK
dc.date.filedepositdate2019-02-11en_UK
rioxxterms.apcnot chargeden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorChapman, Daniel S|0000-0003-1836-4112en_UK
local.rioxx.authorWhite, Steven M|en_UK
local.rioxx.authorHooftman, Danny A P|en_UK
local.rioxx.authorBullock, James M|en_UK
local.rioxx.projectProject ID unknown|Centre for Ecology & Hydrology|en_UK
local.rioxx.freetoreaddate2019-02-11en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nd/4.0/|2019-02-11|en_UK
local.rioxx.filenameChapman et al-EFSA-2015.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source2397-8325en_UK
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