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      Long‐term urbanization impacts the eastern golden frog ( Pelophylax plancyi) in Shanghai City: Demographic history, genetic structure, and implications for amphibian conservation in intensively urbanizing environments

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          Abstract

          Understanding the mechanisms of how urbanization influences the evolution of native species is vital for urban wildlife ecology and conservation in the Anthropocene. With thousands of years of agriculture‐dominated historical urbanization followed by 40 years of intensive and rapid urbanization, Shanghai provides an ideal environment to study how the two‐stage urbanization process influences the evolution of indigenous wildlife, especially of anuran species. Therefore, in this study, we used mitochondrial Cyt‐b gene, microsatellite (SSR), and single nucleotide polymorphism (SNP) data to evaluate the demographic history and genetic structure of the eastern golden frog ( Pelophylax plancyi), by sampling 407 individuals from 15 local populations across Shanghai, China. All local populations experienced bottlenecks during historical urbanization, while the local populations in urban areas maintained comparable contemporary effective population sizes ( N e) and genetic diversity with suburban and rural populations. Nevertheless, the rapid modern urbanization has already imposed significant negative effects to the integrity of populations. The 15 local populations were differentiated into eight genetic clusters, showing a spatial distribution pattern consistent with the current urbanization gradient and island–mainland geography. Although moderate gene flow still occurred from the rural peripheral cluster to urban and suburban clusters, population fragmentation was more serious in the urban and suburban populations, where higher urbanization levels within 2‐km radius areas showed significant negative relationships to the N e and genetic diversity of local populations. Therefore, to protect urban wildlife with limited dispersal ability, improving conditions in fragmented habitat remnants might be most essential for local populations living in more urbanized areas. Meanwhile, we highlight the need to preserve large unfragmented rural habitats and to construct corridor networks to connect discrete urban habitat remnants for the long‐term wildlife conservation in intensively urbanizing environments.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            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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              Inference from Iterative Simulation Using Multiple Sequences

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                Author and article information

                Contributors
                pyhua@bio.ecnu.edu.cn
                zhwang@bio.ecnu.edu.cn
                Journal
                Evol Appl
                Evol Appl
                10.1111/(ISSN)1752-4571
                EVA
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                1752-4571
                07 November 2020
                January 2021
                : 14
                : 1 , Evolution in Urban Environments ( doiID: 10.1111/eva.v14.1 )
                : 117-135
                Affiliations
                [ 1 ] School of Life Sciences East China Normal University Shanghai China
                [ 2 ] Shanghai Landscaping & City Appearance Administrative Bureau Shanghai Forestry Bureau Shanghai China
                [ 3 ] Natural History Research Centre of Shanghai Natural History Museum Shanghai Science and Technology Museum Shanghai China
                [ 4 ] Shanghai Science and Technology Museum Shanghai China
                [ 5 ] Institute of Eco‐Chongming Shanghai China
                [ 6 ] School of Ecological and Environmental Sciences East China Normal University Shanghai China
                [ 7 ] Joint Translational Science and Technology Research Institute East China Normal University Shanghai China
                [ 8 ] Yangtze Delta Estuarine Wetland Ecosystem Observation and Research Station Ministry of Education & Shanghai Science and Technology Committee Shanghai China
                Author notes
                [*] [* ] Correspondence

                Zhenghuan Wang, School of Life Sciences, East China Normal University, Shanghai 200241, China.

                Email: zhwang@ 123456bio.ecnu.edu.cn

                Panyu Hua, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China.

                Email: pyhua@ 123456bio.ecnu.edu.cn

                Author information
                https://orcid.org/0000-0002-7074-0878
                https://orcid.org/0000-0002-3493-136X
                Article
                EVA13156
                10.1111/eva.13156
                7819575
                33519960
                e5c9c2da-d361-4aa7-b859-458c5e60ed57
                © 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 April 2020
                : 11 October 2020
                : 20 October 2020
                Page count
                Figures: 5, Tables: 1, Pages: 19, Words: 14160
                Funding
                Funded by: Shanghai Landscaping & City Appearance Administrative Bureau
                Funded by: the Ministry Science and Technology of China
                Award ID: 2015FY110200
                Award ID: 2016YFC0503200
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 31470488
                Award ID: 32071529
                Categories
                Special Issue Orignal Article
                Special Issue Original Articles
                Custom metadata
                2.0
                January 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.6 mode:remove_FC converted:21.01.2021

                Evolutionary Biology
                amphibian,conservation biology,pelophylax plancyi,population genetics,shanghai,urbanization

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