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      Two new species of green treefrogs (Pelodryadidae: Litoria) from the northern slopes of Papua New Guinea’s Central Cordillera

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      Zootaxa
      Magnolia Press

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          Abstract

          We describe two new species of moderate-sized (male body length 26.5–29.8 mm and 41.0 mm), predominantly green treefrogs in the genus Litoria from hill forest on the northern slopes of Papua New Guinea’s Central Cordillera. Phylogenetic analysis of mitochondrial ND4 nucleotide sequences shows that the first species is related to Litoria iris (Tyler) and its allies. It is morphologically most similar to Litoria mystax, a small green treefrog known only from the holotype that was described more than 100 years ago from the north coast of western New Guinea but differs from that species in having longer legs and a broader head. The second species is closest to Litoria gasconi, a species known only from the foothills of the Foja Mountains in Papua Province, Indonesian New Guinea, and the Prince Alexander Mountains in northern Papua New Guinea. It has a net average sequence divergence of 10% from L. gasconi and can be distinguished morphologically from it and from other pelodryadids by the presence of a striking pattern of spots and blotches on the ventral surfaces and on the hidden surfaces of the limbs. These descriptions add to the rapidly increasing known diversity of frogs in hill and lower montane forest, habitats that support the most diverse frog communities on mainland New Guinea.  

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          Most cited references36

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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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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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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
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Zootaxa
                Zootaxa
                Magnolia Press
                1175-5334
                1175-5326
                April 27 2023
                April 27 2023
                : 5271
                : 3
                : 477-502
                Article
                10.11646/zootaxa.5271.3.3
                a54b530c-17ab-483b-bb83-1533df632b6a
                © 2023
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