20
views
0
recommends
+1 Recommend
0 collections
    2
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Range expansion of the Bluetongue vector, Culicoides imicola, in continental France likely due to rare wind-transport events

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The role of the northward expansion of Culicoides imicola Kieffer in recent and unprecedented outbreaks of Culicoides-borne arboviruses in southern Europe has been a significant point of contention. We combined entomological surveys, movement simulations of air-borne particles, and population genetics to reconstruct the chain of events that led to a newly colonized French area nestled at the northern foot of the Pyrenees. Simulating the movement of air-borne particles evidenced frequent wind-transport events allowing, within at most 36 hours, the immigration of midges from north-eastern Spain and Balearic Islands, and, as rare events, their immigration from Corsica. Completing the puzzle, population genetic analyses discriminated Corsica as the origin of the new population and identified two successive colonization events within west-Mediterranean basin. Our findings are of considerable importance when trying to understand the invasion of new territories by expanding species.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: found
          • Article: not found

          MRBAYES: Bayesian inference of phylogenetic trees.

          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Detection of reduction in population size using data from microsatellite loci.

            We demonstrate that the mean ratio of the number of alleles to the range in allele size, which we term M, calculated from a population sample of microsatellite loci, can be used to detect reductions in population size. Using simulations, we show that, for a general class of mutation models, the value of M decreases when a population is reduced in size. The magnitude of the decrease is positively correlated with the severity and duration of the reduction in size. We also find that the rate of recovery of M following a reduction in size is positively correlated with post-reduction population size, but that recovery occurs in both small and large populations. This indicates that M can distinguish between populations that have been recently reduced in size and those which have been small for a long time. We employ M to develop a statistical test for recent reductions in population size that can detect such changes for more than 100 generations with the post-reduction demographic scenarios we examine. We also compute M for a variety of populations and species using microsatellite data collected from the literature. We find that the value of M consistently predicts the reported demographic history for these populations. This method, and others like it, promises to be an important tool for the conservation and management of populations that are in need of intervention or recovery.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

              Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                06 June 2016
                2016
                : 6
                : 27247
                Affiliations
                [1 ]Cirad, UMR15 CMAEE, 34398; INRA, UMR1309 CMAEE , 34398 Montpellier, France
                [2 ]CNRS, Université de Montpellier, UMR 5290 Maladies Infectieuses & Vecteurs-Ecologie, Génétique, Ecologie, Contrôle (MIVEGEC) , Montpellier, France
                [3 ]IRD, UR 224 MIVEGEC, BP 64501, Agropolis , 34 394 Montpellier cedex 5, France
                [4 ]INRA, UMR1309 CMAEE,34398; Cirad, UMR15 CMAEE , 34398 Montpellier, France
                [5 ]Cirad, UMR15 CMAEE, 97170 Petit-Bourg, France; INRA, UMR1309 CMAEE 34398 Montpellier, France
                [6 ]Centre de Recerca en Sanitat Animal (CReSA), UAB-IRTA, Campus de la Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès) , Spain
                [7 ]Met Office , Exeter, UK
                [8 ]Vector-borne Viral Diseases Programme, The Pirbright Institute , Pirbright, UK
                [9 ]West African Science Service on Climate Change and Adapted Land Use, Climate Change Economics Research Program, Cheikh Anta Diop University , Sénégal
                [10 ]Institut National de la Médecine Vétérinaire (IMV), Laboratoire vétérinaire régional , Tizi Ouzou, Algeria
                [11 ]Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise ‘G. Caporale’ , 64100 Teramo, Italy
                [12 ]Office National de Sécurité Sanitaire des produits Alimentaires (ONSSA) , Rabat, Morocco
                [13 ]Faculdad de Veterinaria, University of Zaragoza (UZ) , Zaragoza, Spain
                [14 ]Laboratory of Zoology, University of Balearics (UIB) , Palma de Mallorca, Spain
                [15 ]CIISA, Faculdade de Medecina Veterinaria, Universidade de Lisboa (FMV-ULisboa) , Lisboa, Portugal
                [16 ]Entente interdépartementale pour la démoustication-Méditerranée (EID-Méd), Montpellier , France
                [17 ]Institut Sénégalais de Recherches Agricoles (ISRA), Laboratoire National de l’Elevage et de Recherches Vétérinaires, Dakar, Sénégal
                Author notes
                Article
                srep27247
                10.1038/srep27247
                4893744
                27263862
                a62aaf70-0f7c-4cbc-bebc-2c60d6954f29
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 24 September 2015
                : 13 May 2016
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article