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      Geological and Pleistocene glaciations explain the demography and disjunct distribution of red panda ( A. fulgens) in eastern Himalayas

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          Abstract

          Pleistocene glaciations facilitated climatic oscillations that caused for enormous heterogeneity in landscapes, and consequently affected demography and distribution patterns of the mountain endemic species. In this context, we investigated demographic history and population genetic structure of red panda, distributed along the geographical proximity in the southern edge of the Qinghai-Tibetan Plateau. Bayesian based phylogeny demonstrated that red panda diverged about 0.30 million years ago (CI 0.23–0.39) into two phylogenetic (sub) species, that correspond to the middle-late Pleistocene transition. The observed intraspecific clades with respect to Himalayan and Chinese red panda indicated restricted gene flow resulting from the Pleistocene glaciations in the eastern and southern Tibetan Plateau. We found Himalayan red panda population at least in KL-India declined abruptly in last 5–10 thousand years after being under demographic equilibrium. We suggest revisiting the ongoing conservation activities through cross border collaboration by developing multi-nationals, and multi-lateral species-oriented conservation action plans to support the red panda populations in transboundary landscapes.

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          Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

          We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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            DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets.

            We present version 6 of the DNA Sequence Polymorphism (DnaSP) software, a new version of the popular tool for performing exhaustive population genetic analyses on multiple sequence alignments. This major upgrade incorporates novel functionalities to analyze large data sets, such as those generated by high-throughput sequencing technologies. Among other features, DnaSP 6 implements: 1) modules for reading and analyzing data from genomic partitioning methods, such as RADseq or hybrid enrichment approaches, 2) faster methods scalable for high-throughput sequencing data, and 3) summary statistics for the analysis of multi-locus population genetics data. Furthermore, DnaSP 6 includes novel modules to perform single- and multi-locus coalescent simulations under a wide range of demographic scenarios. The DnaSP 6 program, with extensive documentation, is freely available at http://www.ub.edu/dnasp.
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              BEAST 2: A Software Platform for Bayesian Evolutionary Analysis

              We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.
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                Author and article information

                Contributors
                thamukesh@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 January 2021
                8 January 2021
                2021
                : 11
                : 65
                Affiliations
                [1 ]GRID grid.473833.8, ISNI 0000 0001 2291 2164, Zoological Survey of India, New Alipore, ; Kolkata, West Bengal 700053 India
                [2 ]GRID grid.59056.3f, ISNI 0000 0001 0664 9773, Department of Zoology, , University of Calcutta, ; Kolkata, West Bengal 700019 India
                Article
                80586
                10.1038/s41598-020-80586-6
                7794540
                33420314
                3bedaff2-a370-4be5-a9d8-341e4ad031a5
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 October 2020
                : 23 December 2020
                Funding
                Funded by: Department of Science and Technology, New Delhi
                Award ID: DST/INSPIRE/04/2016/002246
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                evolution,genetics,zoology,ecology,animal migration,biodiversity,conservation biology,ecological genetics,molecular ecology

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