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      The Pristimantis trachyblepharis species group, a clade of miniaturized frogs: description of four new species and insights into the evolution of body size in the genus

      1 , 2 , 3 , 4 , 1
      Zoological Journal of the Linnean Society
      Oxford University Press (OUP)

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          Abstract

          Species richness in the genus Pristimantis is underestimated due to the existence of morphologically cryptic species. This is worsened by the low sampling effort and the lack of studies using genetic markers. Here, we use molecular and morphological data to determine the phylogenetic relationships of a clade of Pristimantis distributed throughout montane tropical forests in the eastern Andes, from central Ecuador to northern Perú. We name this clade the Pristimantis trachyblepharis species group. Our results show that it comprises nine species, of which four are formally described and five are new. Four of these undescribed species are formally described here. The group is composed of miniaturized species, such as Pristimantis nanus sp. nov., currently the smallest known species of the genus and the smallest vertebrate in Ecuador. As a first approach to understanding the evolutionary origin and implications of body-size reduction in Pristimantis, we here study the phylogenetic signal and evolutionary trends of body size within the genus. We also provide the first record of P. aquilonaris in Ecuador and we show, for the first time, the phylogenetic position of P. albujai, P. aquilonaris, P. minimus and P. trachyblepharis, which are also members of the P. trachyblepharis species group.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            Is Open Access

            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

              Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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                Author and article information

                Contributors
                Journal
                Zoological Journal of the Linnean Society
                Oxford University Press (OUP)
                0024-4082
                1096-3642
                May 01 2022
                May 07 2022
                August 30 2021
                May 01 2022
                May 07 2022
                August 30 2021
                : 195
                : 1
                : 315-354
                Affiliations
                [1 ]Museo de Zoología, Escuela de Biología, Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Católica del Ecuador, Av. 12 de Octubre y Roca, Aptdo. 17-01-2184, Quito, Ecuador
                [2 ]Real Jardín Botánico (RJB-CSIC). Plaza de Murillo, 2. 28014 Madrid, Spain
                [3 ]Departamento de Biología (Genética). Facultad de Ciencias (Ed. Biología), Universidad Autónoma de Madrid (UAM)., c/ Darwin 2, 28049, Madrid, Spain
                [4 ]Centro de Investigaciones en Biodiversidad y Cambio Global (CIBC-UAM). Edificio de Biología, Universidad Autónoma de Madrid., c/ Darwin 2, 28049, Madrid, Spain
                Article
                10.1093/zoolinnean/zlab044
                c8c560f7-c172-4b4a-a60d-8d4df0e838af
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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