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      Dasyophthalma (Lepidoptera: Nymphalidae: Satyrinae): systematics, distribution, and conservation perspectives of a butterfly genus endemic from the Brazilian Atlantic Forest

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          Abstract

          Dasyophthalma includes five species of medium-sized butterflies, all endemic from the Atlantic Forest of Brazil. All known species are univoltine and are dayflying, differently from other Brassolini that are mostly crepuscular. In despite of recent advances little is known about their natural history. Three out of the five species are included in the Brazilian Red List of threatened fauna and are of conservation concern. The present study provides for the first time a phylogenetic assessment of all Dasyophthalma species based on a molecular approach based on three loci. Also, the taxonomic status of D. rusina delanira was revised based on molecular data. In addition, up-to-date distributional data and conservation aspects of the threatened species from the genus are presented and discussed. The molecular phylogenetic analysis supports the monophyly of Dasyophthalma, with Dynastor darius as its sister-group, and, combined with a genetic divergence analysis, supported Dasyophthalma delanira stat. rest. as a valid name to species-level, sister-group to D. geraensis (and not a subspecies of D. rusina). The geographical range (extent of occurrence and area of occupancy) for all five species are presented, showing that these are very restricted for D. delanira stat. rest. and D. geraensis, following the distributions of the high-altitude forests. As much biological information about the genus is lacking, the present study can serve as a starting point for future studies on Dasyophthalma, adding information that can be crucial for future conservation actions and essential to assure the future of the threatened species in this genus.

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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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            ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

            Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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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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                Journal
                Arthropod Systematics & Phylogeny
                ASP
                Pensoft Publishers
                1864-8312
                1863-7221
                May 23 2023
                May 23 2023
                : 81
                : 455-473
                Article
                10.3897/asp.81.e96397
                3d698797-eca6-45ed-ba50-d3e0ff10668d
                © 2023

                https://creativecommons.org/share-your-work/public-domain/cc0/

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