Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California.
Identifieur interne : 000B77 ( Main/Exploration ); précédent : 000B76; suivant : 000B78Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California.
Auteurs : Nik J. Cunniffe [Royaume-Uni] ; Richard C. Cobb [États-Unis] ; Ross K. Meentemeyer [États-Unis] ; David M. Rizzo [États-Unis] ; Christopher A. Gilligan [Royaume-Uni]Source :
- Proceedings of the National Academy of Sciences of the United States of America [ 1091-6490 ] ; 2016.
Descripteurs français
- KwdFr :
- MESH :
- parasitologie : Quercus.
- prévention et contrôle : Maladies des plantes.
- thérapie : Maladies des plantes.
- Californie, Facteurs temps, Forêts, Phytophthora, Risque, Épidémies.
English descriptors
- KwdEn :
- MESH :
- parasitology : Quercus.
- prevention & control : Plant Diseases.
- therapy : Plant Diseases.
- California, Epidemics, Forests, Phytophthora, Risk, Time Factors.
Abstract
Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that "front loading" the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.
DOI: 10.1073/pnas.1602153113
PubMed: 27140631
PubMed Central: PMC4878485
Affiliations:
- Royaume-Uni, États-Unis
- Angleterre, Angleterre de l'Est, Californie, Caroline du Nord
- Cambridge
- Université de Cambridge
Links toward previous steps (curation, corpus...)
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Cunniffe</name><affiliation wicri:level="4"><nlm:affiliation>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom; njc1001@cam.ac.uk.</nlm:affiliation><country wicri:rule="url">Royaume-Uni</country><wicri:regionArea>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA</wicri:regionArea><orgName type="university">Université de Cambridge</orgName><placeName><settlement type="city">Cambridge</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Angleterre de l'Est</region></placeName></affiliation></author><author><name sortKey="Cobb, Richard C" sort="Cobb, Richard C" uniqKey="Cobb R" first="Richard C" last="Cobb">Richard C. Cobb</name><affiliation wicri:level="2"><nlm:affiliation>Department of Plant Pathology, University of California, Davis, CA 95616-8751;</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Californie</region></placeName><wicri:cityArea>Department of Plant Pathology, University of California, Davis</wicri:cityArea></affiliation></author><author><name sortKey="Meentemeyer, Ross K" sort="Meentemeyer, Ross K" uniqKey="Meentemeyer R" first="Ross K" last="Meentemeyer">Ross K. 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Rizzo</name><affiliation wicri:level="2"><nlm:affiliation>Department of Plant Pathology, University of California, Davis, CA 95616-8751;</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Californie</region></placeName><wicri:cityArea>Department of Plant Pathology, University of California, Davis</wicri:cityArea></affiliation></author><author><name sortKey="Gilligan, Christopher A" sort="Gilligan, Christopher A" uniqKey="Gilligan C" first="Christopher A" last="Gilligan">Christopher A. Gilligan</name><affiliation wicri:level="4"><nlm:affiliation>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom;</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA</wicri:regionArea><orgName type="university">Université de Cambridge</orgName><placeName><settlement type="city">Cambridge</settlement><region type="country">Angleterre</region><region type="région" nuts="1">Angleterre de l'Est</region></placeName></affiliation></author></analytic><series><title level="j">Proceedings of the National Academy of Sciences of the United States of America</title><idno type="eISSN">1091-6490</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>California (MeSH)</term><term>Epidemics (MeSH)</term><term>Forests (MeSH)</term><term>Phytophthora (MeSH)</term><term>Plant Diseases (prevention & control)</term><term>Plant Diseases (therapy)</term><term>Quercus (parasitology)</term><term>Risk (MeSH)</term><term>Time Factors (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Californie (MeSH)</term><term>Facteurs temps (MeSH)</term><term>Forêts (MeSH)</term><term>Maladies des plantes (prévention et contrôle)</term><term>Maladies des plantes (thérapie)</term><term>Phytophthora (MeSH)</term><term>Quercus (parasitologie)</term><term>Risque (MeSH)</term><term>Épidémies (MeSH)</term></keywords><keywords scheme="MESH" qualifier="parasitologie" xml:lang="fr"><term>Quercus</term></keywords><keywords scheme="MESH" qualifier="parasitology" xml:lang="en"><term>Quercus</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Plant Diseases</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Maladies des plantes</term></keywords><keywords scheme="MESH" qualifier="therapy" xml:lang="en"><term>Plant Diseases</term></keywords><keywords scheme="MESH" qualifier="thérapie" xml:lang="fr"><term>Maladies des plantes</term></keywords><keywords scheme="MESH" xml:lang="en"><term>California</term><term>Epidemics</term><term>Forests</term><term>Phytophthora</term><term>Risk</term><term>Time Factors</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Californie</term><term>Facteurs temps</term><term>Forêts</term><term>Phytophthora</term><term>Risque</term><term>Épidémies</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that "front loading" the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">27140631</PMID><DateCompleted><Year>2016</Year><Month>12</Month><Day>13</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1091-6490</ISSN><JournalIssue CitedMedium="Internet"><Volume>113</Volume><Issue>20</Issue><PubDate><Year>2016</Year><Month>May</Month><Day>17</Day></PubDate></JournalIssue><Title>Proceedings of the National Academy of Sciences of the United States of America</Title><ISOAbbreviation>Proc Natl Acad Sci U S A</ISOAbbreviation></Journal><ArticleTitle>Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California.</ArticleTitle><Pagination><MedlinePgn>5640-5</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1073/pnas.1602153113</ELocationID><Abstract><AbstractText>Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that "front loading" the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Cunniffe</LastName><ForeName>Nik J</ForeName><Initials>NJ</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom; njc1001@cam.ac.uk.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cobb</LastName><ForeName>Richard C</ForeName><Initials>RC</Initials><AffiliationInfo><Affiliation>Department of Plant Pathology, University of California, Davis, CA 95616-8751;</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Meentemeyer</LastName><ForeName>Ross K</ForeName><Initials>RK</Initials><AffiliationInfo><Affiliation>Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27607-8002.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rizzo</LastName><ForeName>David M</ForeName><Initials>DM</Initials><AffiliationInfo><Affiliation>Department of Plant Pathology, University of California, Davis, CA 95616-8751;</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gilligan</LastName><ForeName>Christopher A</ForeName><Initials>CA</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom;</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>05</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Proc Natl Acad Sci U S A</MedlineTA><NlmUniqueID>7505876</NlmUniqueID><ISSNLinking>0027-8424</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002140" MajorTopicYN="N">California</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058872" MajorTopicYN="N">Epidemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D065928" MajorTopicYN="Y">Forests</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010838" MajorTopicYN="Y">Phytophthora</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010935" MajorTopicYN="N">Plant Diseases</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName><QualifierName UI="Q000628" MajorTopicYN="Y">therapy</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D029963" MajorTopicYN="N">Quercus</DescriptorName><QualifierName UI="Q000469" MajorTopicYN="Y">parasitology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012306" MajorTopicYN="N">Risk</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013997" MajorTopicYN="N">Time Factors</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Phytophthora ramorum</Keyword><Keyword MajorTopicYN="N">constrained budget</Keyword><Keyword MajorTopicYN="N">landscape-scale stochastic epidemiological model</Keyword><Keyword MajorTopicYN="N">optimizing disease control</Keyword><Keyword MajorTopicYN="N">risk aversion</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>5</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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Cambridge</li></orgName></list><tree><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Cunniffe, Nik J" sort="Cunniffe, Nik J" uniqKey="Cunniffe N" first="Nik J" last="Cunniffe">Nik J. Cunniffe</name></region><name sortKey="Gilligan, Christopher A" sort="Gilligan, Christopher A" uniqKey="Gilligan C" first="Christopher A" last="Gilligan">Christopher A. Gilligan</name></country><country name="États-Unis"><region name="Californie"><name sortKey="Cobb, Richard C" sort="Cobb, Richard C" uniqKey="Cobb R" first="Richard C" last="Cobb">Richard C. Cobb</name></region><name sortKey="Meentemeyer, Ross K" sort="Meentemeyer, Ross K" uniqKey="Meentemeyer R" first="Ross K" last="Meentemeyer">Ross K. Meentemeyer</name><name sortKey="Rizzo, David M" sort="Rizzo, David M" uniqKey="Rizzo D" first="David M" last="Rizzo">David M. Rizzo</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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