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Ecological constraints from incumbent clades drive trait evolution across the tree-of-life of freshwater macroinvertebrates

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      Most cited references 53

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      BEAST: Bayesian evolutionary analysis by sampling trees

      Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
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        APE: Analyses of Phylogenetics and Evolution in R language.

        Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes. The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.
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          jModelTest: phylogenetic model averaging.

          jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" (Guindon and Gascuel 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 52:696-704.). It implements 5 different selection strategies, including "hierarchical and dynamical likelihood ratio tests," the "Akaike information criterion," the "Bayesian information criterion," and a "decision-theoretic performance-based" approach. This program also calculates the relative importance and model-averaged estimates of substitution parameters, including a model-averaged estimate of the phylogeny. jModelTest is written in Java and runs under Mac OSX, Windows, and Unix systems with a Java Runtime Environment installed. The program, including documentation, can be freely downloaded from the software section at http://darwin.uvigo.es.
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            Author and article information

            Affiliations
            [1 ]Grup de Recerca Freshwater Ecology and Management (FEM), Dept Biologia Evolutiva, Ecologia i Ciències Ambientals Facultat de Biologia, Univ. de Barcelona, Barcelona, Catalonia, Spain and Inst. de Recerca de la Biodiversitat (IRBio), Univ. de Barcelona, Barcelona; Catalonia Spain
            [2 ]Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés, Univ. Lyon 1; Villeurbanne Cedex France
            [3 ]Dept of Integrative Ecology; Estación Biológica de Doñana (CSIC); Seville Spain
            [4 ]Dept of Life Sciences; Natural History Museum; London UK
            [5 ]Dept of Life Sciences; Imperial College London, Silwood Park Campus; Ascot UK
            Journal
            Ecography
            Ecography
            Wiley
            09067590
            July 2018
            July 2018
            December 04 2017
            : 41
            : 7
            : 1049-1063
            10.1111/ecog.02886
            © 2017

            http://doi.wiley.com/10.1002/tdm_license_1.1

            http://onlinelibrary.wiley.com/termsAndConditions#vor

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