Consistency in pest risk analysis – how can it be achieved and what are the benefits?

GND
105893614X
Zugehörigkeit
Julius Kühn-Institute (JKI), Institute for national and international plant health, Germany
Schrader, Gritta;
Zugehörigkeit
Food and Environment Research Agency, Sand Hutton, York (UK)
MacLeod, A.;
Zugehörigkeit
European and Mediterranean Plant Protection Organization, Paris (France)
Petter, F.;
Zugehörigkeit
Food and Environment Research Agency, Sand Hutton, York (UK)
Baker, R. H. A.;
Zugehörigkeit
European and Mediterranean Plant Protection Organization, Paris (France)
Brunel, S.;
Zugehörigkeit
Centre for Environmental Policy, Imperial College London, (UK)
Holt, J.;
Zugehörigkeit
Centre for Environmental Policy, Imperial College London, (UK)
Leach, A. W.;
Zugehörigkeit
Centre for Environmental Policy, Imperial College London, (UK)
Mumford, J. D.

This paper describes the efforts in the PRATIQUE EU project to increase consistency that were integrated into the revised EPPO Decision-support scheme (DSS) for Pest Risk Analysis (PRA). The establishment section is used here to illustrate the changes and improvements of the DSS, as it has undergone the most comprehensive changes with reformulation and restructuring of many questions and detailed rating guidance. When revising the establishment section of the EPPO DSS for PRA, there were three principal objectives that influenced the revision: (i) to focus the assessment on the most relevant factors influencing establishment; (ii) to identify the area where establishment is possible before assessing the suitability of that area, and (iii) to enhance the consistency of the establishment section by providing rating guidance with sub-questions and examples. To simplify the process, some questions were rephrased as closed questions (answer is either yes or no). Clearer notes were provided to explain what information is needed to answer the questions. Furthermore, consistency has been enhanced by developing tools to help assessors when deciding on an appropriate overall risk rating and uncertainty score by providing a visual summary of the risk ratings and uncertainty scores (‘Visualizer’) and a method for integrating all the responses to the questions to provide a summary score for each major section and an overall assessment of risk (‘Rule based matrix model’).

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