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dc.contributor.authorLázaro, Elena
dc.contributor.authorSesé, M.
dc.contributor.authorLópez-Quílez, Antonio
dc.contributor.authorConesa, David
dc.contributor.authorDalmau, Vicente
dc.contributor.authorFerrer, Amparo
dc.contributor.authorVicent, Antonio
dc.date.accessioned2021-06-01T12:52:05Z
dc.date.available2021-06-01T12:52:05Z
dc.date.issued2021es
dc.identifier.citationLázaro, E., Sesé, M., López-Quílez, A., Conesa, D., Dalmau, V., Ferrer, A., & Vicent, A. (2021). Tracking the outbreak. An optimized delimiting survey strategy for Xylella fastidiosa. Biological invasions, 2021, 1-19.es
dc.identifier.issn1387-3547 (print)
dc.identifier.issn1573-1464 (electronic)
dc.identifier.urihttp://hdl.handle.net/20.500.11939/7397
dc.description.abstractThe EU plant health legislation enforces the implementation of intensive surveillance programs for quarantine pests. After an outbreak, surveys are implemented to delimit the extent of the infested zone and to manage disease control. Surveillance in agricultural and natural environments can be enhanced by increasing the survey efforts. Budget constraints often limit inspection and sampling intensities, thus making it necessary to adapt and optimize surveillance strategies. A sequential adaptive delimiting survey involving a three-phase and a two-phase design with increasing spatial resolution was developed and implemented for the Xylella fastidiosa demarcated area in Alicante, Spain. Inspection and sampling intensities were optimized using simulation-based methods. Sampling intensity thresholds were evaluated by quantifying their effect on the estimation of X. fastidiosa incidence. This strategy made it possible to sequence inspection and sampling taking into account increasing spatial resolutions, and to adapt the inspection and sampling intensities according to the information obtained in the previous, coarser, spatial resolution. The proposed strategy was able to efficiently delimit the extent of Xylella fastidiosa, while improving on the efficiency and maintaining the efficacy of the official survey campaign. From a methodological perspective, our approach provides new insights into alternative delimiting designs and new reference sampling intensity valueses
dc.language.isoenes
dc.publisherSpringeres
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectAdaptive samplinges
dc.subjectAlmond leaf scorches
dc.subjectBayesian spatial statisticses
dc.subjectSequential samplinges
dc.subjectSimulation-based optimization methodses
dc.subjectSurvey designes
dc.titleTracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveyses
dc.typearticlees
dc.authorAddresslazaro_ele@gva.eses
dc.entidadIVIACentro de Protección Vegetal y Biotecnologíaes
dc.identifier.doi10.1007/s10530-021-02572-xes
dc.identifier.urlhttps://link.springer.com/article/10.1007%2Fs10530-021-02572-xes
dc.journal.issueNumber2021es
dc.journal.titleBiological Invasionses
dc.page.final19es
dc.page.initial1es
dc.relation.projectIDThe present work has been funded by Horizon 2020 Project No. 727987 XF-ACTORS (Xylella Fastidiosa Active Containment Through a Multidisciplinary-Oriented Research Strategy) and the Projects E-RTA 2017-00004-C06-01 FEDER INIA-AEI Ministerio de Economía y Competitividad and Organización Interprofesional del Aceite de Oliva Español, Spain.es
dc.relation.projectIDThe work of ALQ and DC has also been supported by Grants MTM2016-77501-P and TEC2016-81900-REDT from the Spanish Ministry of Science, Innovation and Universities State Research Agency (jointly financed by the European Regional Development Fund, FEDER).es
dc.rights.accessRightsopenAccesses
dc.source.typeelectronicoes
dc.subject.agrisH20 Plant diseaseses
dc.type.hasVersionpublishedVersiones


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Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España