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      Integrative taxonomy uncovers a new stygobiotic Caridina species (Decapoda, Caridea, Atyidae) from Guizhou Province, China

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          Collecting much-needed information on the taxonomy, distribution, and ecology of cave-dwelling shrimp is vital for addressing the urgent challenges in conservation biodiversity in fragile cave ecosystems. Caridina incolor sp. nov., a new atyid shrimp from an underground stream of Yaoshui Cave, Daqikong scenic area, Libo County, Guizhou Province, southwestern China is described based on morphology and DNA analysis (mitochondrial COI). Caridina incolor sp. nov. differs from epigean congeners by its smaller eyes which range from reduced to completely blind; colorless body and appendages; long stylocerite and sixth abdominal segment; and relatively large eggs. In comparison to other cave species, Caridina incolor sp. nov. presents a long rostrum and stylocerite; slender sixth abdominal segment; and unique shape of the appendix masculina. Data on the habitat, ecology, and levels of threat are provided and suggest that it should be categorized as Critically Endangered (CR) under the current IUCN criteria.

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          Most cited references 43

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.

                Author and article information

                Pensoft Publishers
                05 April 2021
                : 1028
                : 29-47
                [1 ] Department of Animal Science, School of Life Science and Engineering, Foshan University, Nanhai 528231, Guangdong Province, China Foshan University Nanhai China
                [2 ] South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510520, Guangdong Province, China South China Institute of Environmental Sciences, Ministry of Ecology and Environment Guangzhou China
                Author notes
                Corresponding author: Zhao-Liang Guo ( zlguo@ 123456fosu.edu.cn )

                Academic editor: C. Magalhães

                Shuo Feng, Qing-Hua Chen, Zhao-Liang Guo

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Research Article
                Biodiversity & Conservation
                Conservation Biology


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