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Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

dc.contributor.authorFresia, Pablo
dc.contributor.authorSilver, Micha
dc.contributor.authorMastrangelo, Thiago
dc.contributor.authorDe Azeredo-Espin, Ana Maria L.
dc.contributor.authorLyra, Mariana L. [UNESP]
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionArava Dev Co Ltd
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2015-03-18T15:53:15Z
dc.date.available2015-03-18T15:53:15Z
dc.date.issued2014-10-01
dc.description.abstractThe myiasis causing New World screwworm (NWS) fly is responsible for substantial losses to livestock breeders in the Americas. Due to the negative impact of the NWS fly in animal health, expansion of successful NWS fly eradication programmes is under discussion. However, the effects of geography and environmental diversity on NWS population structure and migration patterns need to be assessed before any political decision is made to implement such a programme. We present a GIS tool to construct potential connection corridors among sampling localities based on genetic and environmental data. We integrate, through a home-made python script, a friction raster based on a Maxent niche model and the pairwise Phi(ST) statistic. Among 38 NWS fly sampling localities from South America, we find a high population connectivity among the sampling localities from the south of the Amazon region. The region along the Atlantic Ocean was identified as the most probable migration corridor between the north (NAG) and the south (SAG) of the Amazon region. The approach highlighted previously undetected population structure within NAG showing low to medium connectivity through the Andes, correlating with current understanding of NWS fly migration in South America. Also, the approach is flexible, allowing future research to incorporate other niche simulations and genetic differentiation metrics. With this flexibility, the tool could become part of any AW-IPM by helping to target regions for control. (C) International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.en
dc.description.affiliationUniv Sao Paulo, Escola Super Agr Luiz De Queiroz, Dept Entomol & Acarol, BR-13400970 Piracicaba, SP, Brazil
dc.description.affiliationArava Dev Co Ltd, Arava, Israel
dc.description.affiliationUniv Estadual Campinas, Ctr Biol Mol & Engn Genet, BR-13083875 Campinas, SP, Brazil
dc.description.affiliationUniv Estadual Campinas, Inst Biol, BR-13083875 Campinas, SP, Brazil
dc.description.affiliationUniv Estadual Paulista, Inst Biociencias, Dept Zool, BR-13506970 Rio Claro, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Inst Biociencias, Dept Zool, BR-13506970 Rio Claro, SP, Brazil
dc.description.sponsorshipFAO/IAEA CRP: Applying Population Genetics
dc.description.sponsorshipGIS for Managing Livestock Insect Pests
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFAO/IAEA CRP: Applying Population GeneticsRE-14844-RO
dc.description.sponsorshipIdFAO/IAEA CRP: Applying Population Genetics14856-RO
dc.description.sponsorshipIdFAPESP: 12/11654-9
dc.format.extentS34-S41
dc.identifierhttp://dx.doi.org/10.1016/j.actatropica.2014.04.003
dc.identifier.citationActa Tropica. Amsterdam: Elsevier Science Bv, v. 138, p. S34-S41, 2014.
dc.identifier.doi10.1016/j.actatropica.2014.04.003
dc.identifier.issn0001-706X
dc.identifier.urihttp://hdl.handle.net/11449/116398
dc.identifier.wosWOS:000342529800006
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofActa Tropica
dc.relation.ispartofjcr2.509
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectCochliomyia hominivoraxen
dc.subjectMyiasisen
dc.subjectGISen
dc.subjectPhylogeographyen
dc.subjectEcological niche Modellingen
dc.subjectPest controlen
dc.titleApplying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South Americaen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências, Rio Claropt
unesp.departmentZoologia - IBpt

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