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      The Phylogeographic History of the New World Screwworm Fly, Inferred by Approximate Bayesian Computation Analysis

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      PLoS ONE
      Public Library of Science

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          Abstract

          Insect pest phylogeography might be shaped both by biogeographic events and by human influence. Here, we conducted an approximate Bayesian computation (ABC) analysis to investigate the phylogeography of the New World screwworm fly, Cochliomyia hominivorax, with the aim of understanding its population history and its order and time of divergence. Our ABC analysis supports that populations spread from North to South in the Americas, in at least two different moments. The first split occurred between the North/Central American and South American populations in the end of the Last Glacial Maximum (15,300-19,000 YBP). The second split occurred between the North and South Amazonian populations in the transition between the Pleistocene and the Holocene eras (9,100-11,000 YBP). The species also experienced population expansion. Phylogenetic analysis likewise suggests this north to south colonization and Maxent models suggest an increase in the number of suitable areas in South America from the past to present. We found that the phylogeographic patterns observed in C. hominivorax cannot be explained only by climatic oscillations and can be connected to host population histories. Interestingly we found these patterns are very coincident with general patterns of ancient human movements in the Americas, suggesting that humans might have played a crucial role in shaping the distribution and population structure of this insect pest. This work presents the first hypothesis test regarding the processes that shaped the current phylogeographic structure of C. hominivorax and represents an alternate perspective on investigating the problem of insect pests.

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          Most cited references45

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          Arlequin (version 3.0): An integrated software package for population genetics data analysis

          Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.
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            Measuring the accuracy of diagnostic systems.

            J Swets (1988)
            Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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              Speciation in amazonian forest birds.

              J Haffer (1969)
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                2 October 2013
                : 8
                : 10
                : e76168
                Affiliations
                [1 ]Departamento de Entomologia e Acarologia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, São Paulo, Brasil
                [2 ]Centro de Biologia Molecular e Engenharia Genética and Instituto de Biologia, Universidade Estadual de Campinas, São Paulo, Brasil
                [3 ]Departamento de Zoologia, Instituto de Biociências, Universidade Estadual Paulista, São Paulo, Brasil
                George Washington University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PF AMLA MLL. Performed the experiments: PF MLL. Analyzed the data: PF MLL. Contributed reagents/materials/analysis tools: AMLA. Wrote the manuscript: PF AMLA MLL.

                Article
                PONE-D-13-10915
                10.1371/journal.pone.0076168
                3788763
                5b86f39a-26e1-4376-ab3a-08b37f516b5a
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 March 2013
                : 21 August 2013
                Funding
                Pablo Fresia was supported by a fellowship from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-CAPES. Mariana Lúcio Lyra was supported by a fellowship from the Fundação de Amparo à Pesquisa do Estado de São Paulo-FAPESP (grant nº 03/13598-0). This work was supported by grants from FAO/IAEA (11822/RO) and FAPESP. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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