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      A Total-Evidence Approach to Dating with Fossils, Applied to the Early Radiation of the Hymenoptera

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          Phylogenies are usually dated by calibrating interior nodes against the fossil record. This relies on indirect methods that, in the worst case, misrepresent the fossil information. Here, we contrast such node dating with an approach that includes fossils along with the extant taxa in a Bayesian total-evidence analysis. As a test case, we focus on the early radiation of the Hymenoptera, mostly documented by poorly preserved impression fossils that are difficult to place phylogenetically. Specifically, we compare node dating using nine calibration points derived from the fossil record with total-evidence dating based on 343 morphological characters scored for 45 fossil (4--20 complete) and 68 extant taxa. In both cases we use molecular data from seven markers (∼5 kb) for the extant taxa. Because it is difficult to model speciation, extinction, sampling, and fossil preservation realistically, we develop a simple uniform prior for clock trees with fossils, and we use relaxed clock models to accommodate rate variation across the tree. Despite considerable uncertainty in the placement of most fossils, we find that they contribute significantly to the estimation of divergence times in the total-evidence analysis. In particular, the posterior distributions on divergence times are less sensitive to prior assumptions and tend to be more precise than in node dating. The total-evidence analysis also shows that four of the seven Hymenoptera calibration points used in node dating are likely to be based on erroneous or doubtful assumptions about the fossil placement. With respect to the early radiation of Hymenoptera, our results suggest that the crown group dates back to the Carboniferous, ∼309 Ma (95% interval: 291--347 Ma), and diversified into major extant lineages much earlier than previously thought, well before the Triassic. [Bayesian inference; fossil dating; morphological evolution; relaxed clock; statistical phylogenetics.]

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            R: A language and environment for statistical computing

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              Estimating the rate of evolution of the rate of molecular evolution.

              A simple model for the evolution of the rate of molecular evolution is presented. With a Bayesian approach, this model can serve as the basis for estimating dates of important evolutionary events even in the absence of the assumption of constant rates among evolutionary lineages. The method can be used in conjunction with any of the widely used models for nucleotide substitution or amino acid replacement. It is illustrated by analyzing a data set of rbcL protein sequences.

                Author and article information

                Syst Biol
                Syst. Biol
                Systematic Biology
                Oxford University Press
                December 2012
                26 July 2012
                26 July 2012
                : 61
                : 6
                : 973-999
                1Department of Biodiversity Informatics, Swedish Museum of Natural History, Box 50007, SE-104 05 Stockholm, Sweden
                2Department of Entomology, Natural History Museum of Denmark, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark
                3Faculty of Biology, Department II, Ludwig-Maximilians-University, Groβhaderner Straβe 2–4, DE-82152 Martinsried, Germany
                4Department of Biology, Duke University, Box 90338, Durham, NC, 27708, USA
                5Paleontological Institute, Russian Academy of Sciences, Profsoyuznaya Ulitsa 123, Moscow 117647, Russia
                Author notes
                * Correspondence to be sent to: Department of Biodiversity Informatics, Swedish Museum of Natural History, Box 50007, SE-10405 Stockholm, Sweden; E-mail: fredrik.ronquist@ . Fredrik Ronquist and Seraina Klopfstein contributed equally to this article.
                © The Author(s) 2012. Published by Oxford University Press

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Pages: 27
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                Animal science & Zoology


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