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      Description of a New Species of the Pareas hamptoni Complex from Yunnan, China, with Confirmation of P. hamptoni Sensu Stricto in China (Squamata, Pareidae)

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      Animals
      MDPI AG

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          Abstract

          We describe a new species of the genus Pareas, based on three specimens collected from Guanyinshan Provincial Nature Reserve in Yuanyang County, Honghe Prefecture, Yunnan Province, China. The new species is distinguished from its congeners by one preocular, one postocular or postocular fused with subocular, loreal not bordering the orbit, one row enlarged vertebral scales, five rows keeled mid-dorsal scales at the middle of the body, 189–192 ventral scales and 72–89 subcaudal scales. The dorsal surfaces of the head and body are yellowish red or yellowish brown, and the belly and ventral surfaces of the head and tail are pinkish yellow or yellow with more or less small black spots. Phylogenetic analyses of mitochondrial DNA recovered the new species being the sister taxon to P. hamptoni sensu stricto. The genetic divergences between the new species and P. hamptoni sensu stricto were 4.2% in the Cyt b sequences and 5.0% in the ND4 sequences. In addition, based on specimens collected from Honghe and Wenshan prefectures, we confirmed that P. hamptoni sensu stricto is distributed in China.

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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%.
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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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              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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                Author and article information

                Contributors
                Journal
                ANIMG5
                Animals
                Animals
                MDPI AG
                2076-2615
                February 2024
                January 27 2024
                : 14
                : 3
                : 421
                Article
                10.3390/ani14030421
                846885d2-2117-4dc9-96f3-b18d1667d998
                © 2024

                https://creativecommons.org/licenses/by/4.0/

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