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      Triassic stem caecilian supports dissorophoid origin of living amphibians

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          Abstract

          Living amphibians (Lissamphibia) include frogs and salamanders (Batrachia) and the limbless worm-like caecilians (Gymnophiona). The estimated Palaeozoic era gymnophionan–batrachian molecular divergence 1 suggests a major gap in the record of crown lissamphibians prior to their earliest fossil occurrences in the Triassic period 26 . Recent studies find a monophyletic Batrachia within dissorophoid temnospondyls 710 , but the absence of pre-Jurassic period caecilian fossils 11, 12 has made their relationships to batrachians and affinities to Palaeozoic tetrapods controversial 1, 8, 13, 14 . Here we report the geologically oldest stem caecilian—a crown lissamphibian from the Late Triassic epoch of Arizona, USA—extending the caecilian record by around 35 million years. These fossils illuminate the tempo and mode of early caecilian morphological and functional evolution, demonstrating a delayed acquisition of musculoskeletal features associated with fossoriality in living caecilians, including the dual jaw closure mechanism 15, 16 , reduced orbits 17 and the tentacular organ 18 . The provenance of these fossils suggests a Pangaean equatorial origin for caecilians, implying that living caecilian biogeography reflects conserved aspects of caecilian function and physiology 19 , in combination with vicariance patterns driven by plate tectonics 20 . These fossils reveal a combination of features that is unique to caecilians alongside features that are shared with batrachian and dissorophoid temnospondyls, providing new and compelling evidence supporting a single origin of living amphibians within dissorophoid temnospondyls.

          Abstract

          Analysis of fossils of the oldest known caecilian provide insights into the origin and morphological and functional evolution of caecilians.

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          Most cited references77

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          MRBAYES: Bayesian inference of phylogenetic trees

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            TNT version 1.5, including a full implementation of phylogenetic morphometrics

            Version 1.5 of the computer program TNT completely integrates landmark data into phylogenetic analysis. Landmark data consist of coordinates (in two or three dimensions) for the terminal taxa; TNT reconstructs shapes for the internal nodes such that the difference between ancestor and descendant shapes for all tree branches sums up to a minimum; this sum is used as tree score. Landmark data can be analysed alone or in combination with standard characters; all the applicable commands and options in TNT can be used transparently after reading a landmark data set. The program continues implementing all the types of analyses in former versions, including discrete and continuous characters (which can now be read at any scale, and automatically rescaled by TNT). Using algorithms described in this paper, searches for landmark data can be made tens to hundreds of times faster than it was possible before (from T to 3T times faster, where T is the number of taxa), thus making phylogenetic analysis of landmarks feasible even on standard personal computers.
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              A Likelihood Approach to Estimating Phylogeny from Discrete Morphological Character Data

              Paul Lewis (2001)
              Evolutionary biologists have adopted simple likelihood models for purposes of estimating ancestral states and evaluating character independence on specified phylogenies; however, for purposes of estimating phylogenies by using discrete morphological data, maximum parsimony remains the only option. This paper explores the possibility of using standard, well-behaved Markov models for estimating morphological phylogenies (including branch lengths) under the likelihood criterion. An important modification of standard Markov models involves making the likelihood conditional on characters being variable, because constant characters are absent in morphological data sets. Without this modification, branch lengths are often overestimated, resulting in potentially serious biases in tree topology selection. Several new avenues of research are opened by an explicitly model-based approach to phylogenetic analysis of discrete morphological data, including combined-data likelihood analyses (morphology + sequence data), likelihood ratio tests, and Bayesian analyses.
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                Author and article information

                Contributors
                bkligman@vt.edu
                bmgee@uw.edu
                adam_marsh@nps.gov
                sjn2104@vt.edu
                matthew_e_smith@nps.gov
                william_parker@nps.gov
                stockerm@vt.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                25 January 2023
                25 January 2023
                2023
                : 614
                : 7946
                : 102-107
                Affiliations
                [1 ]Department of Resource Management and Science, Petrified Forest National Park, Petrified Forest, AZ USA
                [2 ]GRID grid.438526.e, ISNI 0000 0001 0694 4940, Department of Geosciences, , Virginia Tech, ; Blacksburg, VA USA
                [3 ]GRID grid.34477.33, ISNI 0000000122986657, Burke Museum and Department of Biology, , University of Washington, ; Seattle, WA USA
                Author information
                http://orcid.org/0000-0003-4400-8963
                http://orcid.org/0000-0003-4517-3290
                http://orcid.org/0000-0002-3223-8940
                http://orcid.org/0000-0002-7017-1652
                http://orcid.org/0000-0002-9790-502X
                http://orcid.org/0000-0002-6005-7098
                http://orcid.org/0000-0002-6473-8691
                Article
                5646
                10.1038/s41586-022-05646-5
                9892002
                36697827
                4b1da763-0f55-44fa-bf52-7bb03a5fc3e3
                © The Author(s) 2023

                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
                : 12 January 2022
                : 12 December 2022
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                © The Author(s), under exclusive licence to Springer Nature Limited 2023

                Uncategorized
                palaeontology,palaeoecology,herpetology,phylogenetics
                Uncategorized
                palaeontology, palaeoecology, herpetology, phylogenetics

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