A suite of models to support the quantitative assessment of spread in pest risk analysis

Pest Risk Analyses (PRAs) are conducted worldwide to decide whether and how exotic plant pests should be regulated to prevent invasion. There is an increasing demand for science-based risk mapping in PRA. Spread plays a key role in determining the potential distribution of pests, but there is no sui...

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Veröffentlicht in:PloS one 2012-10, Vol.7 (10), p.e43366-e43366
Hauptverfasser: Robinet, Christelle, Kehlenbeck, Hella, Kriticos, Darren J, Baker, Richard H A, Battisti, Andrea, Brunel, Sarah, Dupin, Maxime, Eyre, Dominic, Faccoli, Massimo, Ilieva, Zhenya, Kenis, Marc, Knight, Jon, Reynaud, Philippe, Yart, Annie, van der Werf, Wopke
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container_issue 10
container_start_page e43366
container_title PloS one
container_volume 7
creator Robinet, Christelle
Kehlenbeck, Hella
Kriticos, Darren J
Baker, Richard H A
Battisti, Andrea
Brunel, Sarah
Dupin, Maxime
Eyre, Dominic
Faccoli, Massimo
Ilieva, Zhenya
Kenis, Marc
Knight, Jon
Reynaud, Philippe
Yart, Annie
van der Werf, Wopke
description Pest Risk Analyses (PRAs) are conducted worldwide to decide whether and how exotic plant pests should be regulated to prevent invasion. There is an increasing demand for science-based risk mapping in PRA. Spread plays a key role in determining the potential distribution of pests, but there is no suitable spread modelling tool available for pest risk analysts. Existing models are species specific, biologically and technically complex, and data hungry. Here we present a set of four simple and generic spread models that can be parameterised with limited data. Simulations with these models generate maps of the potential expansion of an invasive species at continental scale. The models have one to three biological parameters. They differ in whether they treat spatial processes implicitly or explicitly, and in whether they consider pest density or pest presence/absence only. The four models represent four complementary perspectives on the process of invasion and, because they have different initial conditions, they can be considered as alternative scenarios. All models take into account habitat distribution and climate. We present an application of each of the four models to the western corn rootworm, Diabrotica virgifera virgifera, using historic data on its spread in Europe. Further tests as proof of concept were conducted with a broad range of taxa (insects, nematodes, plants, and plant pathogens). Pest risk analysts, the intended model users, found the model outputs to be generally credible and useful. The estimation of parameters from data requires insights into population dynamics theory, and this requires guidance. If used appropriately, these generic spread models provide a transparent and objective tool for evaluating the potential spread of pests in PRAs. Further work is needed to validate models, build familiarity in the user community and create a database of species parameters to help realize their potential in PRA practice.
doi_str_mv 10.1371/journal.pone.0043366
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Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>NARCIS:Publications</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Robinet, Christelle</au><au>Kehlenbeck, Hella</au><au>Kriticos, Darren J</au><au>Baker, Richard H A</au><au>Battisti, Andrea</au><au>Brunel, Sarah</au><au>Dupin, Maxime</au><au>Eyre, Dominic</au><au>Faccoli, Massimo</au><au>Ilieva, Zhenya</au><au>Kenis, Marc</au><au>Knight, Jon</au><au>Reynaud, Philippe</au><au>Yart, Annie</au><au>van der Werf, Wopke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A suite of models to support the quantitative assessment of spread in pest risk analysis</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2012-10-09</date><risdate>2012</risdate><volume>7</volume><issue>10</issue><spage>e43366</spage><epage>e43366</epage><pages>e43366-e43366</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Pest Risk Analyses (PRAs) are conducted worldwide to decide whether and how exotic plant pests should be regulated to prevent invasion. There is an increasing demand for science-based risk mapping in PRA. Spread plays a key role in determining the potential distribution of pests, but there is no suitable spread modelling tool available for pest risk analysts. Existing models are species specific, biologically and technically complex, and data hungry. Here we present a set of four simple and generic spread models that can be parameterised with limited data. Simulations with these models generate maps of the potential expansion of an invasive species at continental scale. The models have one to three biological parameters. They differ in whether they treat spatial processes implicitly or explicitly, and in whether they consider pest density or pest presence/absence only. The four models represent four complementary perspectives on the process of invasion and, because they have different initial conditions, they can be considered as alternative scenarios. All models take into account habitat distribution and climate. We present an application of each of the four models to the western corn rootworm, Diabrotica virgifera virgifera, using historic data on its spread in Europe. Further tests as proof of concept were conducted with a broad range of taxa (insects, nematodes, plants, and plant pathogens). Pest risk analysts, the intended model users, found the model outputs to be generally credible and useful. The estimation of parameters from data requires insights into population dynamics theory, and this requires guidance. If used appropriately, these generic spread models provide a transparent and objective tool for evaluating the potential spread of pests in PRAs. Further work is needed to validate models, build familiarity in the user community and create a database of species parameters to help realize their potential in PRA practice.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23056174</pmid><doi>10.1371/journal.pone.0043366</doi><tpages>e43366</tpages><orcidid>https://orcid.org/0000-0002-9355-0516</orcidid><orcidid>https://orcid.org/0000-0002-4933-4656</orcidid><orcidid>https://orcid.org/0000-0002-0602-8595</orcidid><orcidid>https://orcid.org/0000-0002-5506-4699</orcidid><oa>free_for_read</oa></addata></record>
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1932-6203
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source Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry
subjects Agriculture
Algorithms
Animal behavior
Animal biology
Animals
asterisk
Biology
Climate
Climate models
Coleoptera - physiology
Computer Science
Computer Simulation
Corn
Data processing
Diabrotica
Diabrotica virgifera virgifera
economic-impact
Ecosystem
Eichhornia crassipes
Europe
Familiarity
Food
Geography
Habitat
Health risks
Host-Parasite Interactions
Initial conditions
Insect Control - methods
Insect Control - statistics & numerical data
Insects
Introduced species
invasions
Invasive species
Life Sciences
long-distance dispersal
Mapping
Models, Biological
Natural resources
Nematoda
Nematodes
Parameter estimation
Pathogens
Pests
pitch canker
Plants (botany)
Plants - parasitology
Population biology
Population Dynamics
population expansion
Risk analysis
Risk Assessment
Spatial distribution
Taxa
Vegetal Biology
western corn-rootworm
Zea mays - parasitology
title A suite of models to support the quantitative assessment of spread in pest risk analysis
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