Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys

The 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...

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Autores principales: Lázaro, Elena, Sesé, M., López-Quílez, Antonio, Conesa, David, Dalmau, Vicente, Ferrer, Amparo, Vicent, Antonio
Formato: article
Lenguaje:Inglés
Publicado: Springer 2021
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Acceso en línea:http://hdl.handle.net/20.500.11939/7397
https://link.springer.com/article/10.1007%2Fs10530-021-02572-x
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author Lázaro, Elena
Sesé, M.
López-Quílez, Antonio
Conesa, David
Dalmau, Vicente
Ferrer, Amparo
Vicent, Antonio
author_browse Conesa, David
Dalmau, Vicente
Ferrer, Amparo
Lázaro, Elena
López-Quílez, Antonio
Sesé, M.
Vicent, Antonio
author_facet Lázaro, Elena
Sesé, M.
López-Quílez, Antonio
Conesa, David
Dalmau, Vicente
Ferrer, Amparo
Vicent, Antonio
author_sort Lázaro, Elena
collection ReDivia
description The 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 values
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institution Instituto Valenciano de Investigaciones Agrarias (IVIA)
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spelling ReDivia73972025-04-25T14:48:19Z Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys Lázaro, Elena Sesé, M. López-Quílez, Antonio Conesa, David Dalmau, Vicente Ferrer, Amparo Vicent, Antonio Adaptive sampling Almond leaf scorch Bayesian spatial statistics Sequential sampling Simulation-based optimization methods Survey design H20 Plant diseases The 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 values 2021-06-01T12:52:05Z 2021-06-01T12:52:05Z 2021 article publishedVersion Lázaro, 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. 1387-3547 (print) 1573-1464 (electronic) http://hdl.handle.net/20.500.11939/7397 10.1007/s10530-021-02572-x https://link.springer.com/article/10.1007%2Fs10530-021-02572-x en info:eu-repo/grantAgreement/EC/H2020/727987/EU//XF-ACTORS info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTA2017-00004-C06-01 The 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. The 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). Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ openAccess Springer electronico
spellingShingle Adaptive sampling
Almond leaf scorch
Bayesian spatial statistics
Sequential sampling
Simulation-based optimization methods
Survey design
H20 Plant diseases
Lázaro, Elena
Sesé, M.
López-Quílez, Antonio
Conesa, David
Dalmau, Vicente
Ferrer, Amparo
Vicent, Antonio
Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title_full Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title_fullStr Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title_full_unstemmed Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title_short Tracking the outbreak: an optimized sequential adaptive strategy for Xylella fastidiosa delimiting surveys
title_sort tracking the outbreak an optimized sequential adaptive strategy for xylella fastidiosa delimiting surveys
topic Adaptive sampling
Almond leaf scorch
Bayesian spatial statistics
Sequential sampling
Simulation-based optimization methods
Survey design
H20 Plant diseases
url http://hdl.handle.net/20.500.11939/7397
https://link.springer.com/article/10.1007%2Fs10530-021-02572-x
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