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      Diversity and Disparity of Therocephalia: Macroevolutionary Patterns through Two Mass Extinctions

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          Abstract

          Mass extinctions have the potential to substantially alter the evolutionary trends in a clade. If new regions of ecospace are made available, the clade may radiate. If, on the other hand, the clade passes through an evolutionary “bottleneck” by substantially reducing its species richness, then subsequent radiations may be restricted in the disparity they attain. Here we compare the patterns of diversity and disparity in the Therocephalia, a diverse lineage of amniotes that survived two mass extinction events. We use time calibrated phylogeny and discrete character data to assess macroevolutionary patterns. The two are coupled through the early history of therocephalians, including a radiation following the late Guadalupian extinction. Diversity becomes decoupled from disparity across the end-Permian mass extinction. The number of species decreases throughout the Early Triassic and never recovers. However, while disparity briefly decreases across the extinction boundary, it recovers and remains high until the Middle Triassic.

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          The fossilized birth-death process for coherent calibration of divergence-time estimates.

          Time-calibrated species phylogenies are critical for addressing a wide range of questions in evolutionary biology, such as those that elucidate historical biogeography or uncover patterns of coevolution and diversification. Because molecular sequence data are not informative on absolute time, external data--most commonly, fossil age estimates--are required to calibrate estimates of species divergence dates. For Bayesian divergence time methods, the common practice for calibration using fossil information involves placing arbitrarily chosen parametric distributions on internal nodes, often disregarding most of the information in the fossil record. We introduce the "fossilized birth-death" (FBD) process--a model for calibrating divergence time estimates in a Bayesian framework, explicitly acknowledging that extant species and fossils are part of the same macroevolutionary process. Under this model, absolute node age estimates are calibrated by a single diversification model and arbitrary calibration densities are not necessary. Moreover, the FBD model allows for inclusion of all available fossils. We performed analyses of simulated data and show that node age estimation under the FBD model results in robust and accurate estimates of species divergence times with realistic measures of statistical uncertainty, overcoming major limitations of standard divergence time estimation methods. We used this model to estimate the speciation times for a dataset composed of all living bears, indicating that the genus Ursus diversified in the Late Miocene to Middle Pliocene.
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            paleotree: an R package for paleontological and phylogenetic analyses of evolution

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              Sampling-through-time in birth-death trees.

              I consider the constant rate birth-death process with incomplete sampling. I calculate the density of a given tree with sampled extant and extinct individuals. This density is essential for analyzing datasets which are sampled through time. Such datasets are common in virus epidemiology as viruses in infected individuals are sampled through time. Further, such datasets appear in phylogenetics when extant and extinct species data is available. I show how the derived tree density can be used (i) as a tree prior in a Bayesian method to reconstruct the evolutionary past of the sequence data on a calender-timescale, (ii) to infer the birth- and death-rates for a reconstructed evolutionary tree, and (iii) for simulating trees with a given number of sampled extant and extinct individuals which is essential for testing evolutionary hypotheses for the considered datasets. Copyright © 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                neil.brockehurst@earth.ox.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 March 2019
                25 March 2019
                2019
                : 9
                : 5063
                Affiliations
                [1 ]ISNI 0000 0001 2248 7639, GRID grid.7468.d, Institut für Biologie, , Humboldt-Universität zu Berlin, ; Invalidenstraße 42, Berlin, D-10115 Germany
                [2 ]ISNI 0000 0001 2293 9957, GRID grid.422371.1, Museum für Naturkunde, , Leibniz-Institut für Evolutions- und Biodiversitätsforschung, ; Invalidenstraße 43, D-10115 Berlin, Germany
                [3 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Earth Sciences, , University of Oxford, ; South Parks Road, Oxford, OX1 3AN UK
                Article
                41628
                10.1038/s41598-019-41628-w
                6433905
                30911058
                d134a90a-c935-4125-a39f-2ded6ceeb01a
                © The Author(s) 2019

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 August 2018
                : 7 March 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: BR 5724/1-1
                Award Recipient :
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