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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.
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              Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds.

              We implement a Bayesian Markov chain Monte Carlo algorithm for estimating species divergence times that uses heterogeneous data from multiple gene loci and accommodates multiple fossil calibration nodes. A birth-death process with species sampling is used to specify a prior for divergence times, which allows easy assessment of the effects of that prior on posterior time estimates. We propose a new approach for specifying calibration points on the phylogeny, which allows the use of arbitrary and flexible statistical distributions to describe uncertainties in fossil dates. In particular, we use soft bounds, so that the probability that the true divergence time is outside the bounds is small but nonzero. A strict molecular clock is assumed in the current implementation, although this assumption may be relaxed. We apply our new algorithm to two data sets concerning divergences of several primate species, to examine the effects of the substitution model and of the prior for divergence times on Bayesian time estimation. We also conduct computer simulation to examine the differences between soft and hard bounds. We demonstrate that divergence time estimation is intrinsically hampered by uncertainties in fossil calibrations, and the error in Bayesian time estimates will not go to zero with increased amounts of sequence data. Our analyses of both real and simulated data demonstrate potentially large differences between divergence time estimates obtained using soft versus hard bounds and a general superiority of soft bounds. Our main findings are as follows. (1) When the fossils are consistent with each other and with the molecular data, and the posterior time estimates are well within the prior bounds, soft and hard bounds produce similar results. (2) When the fossils are in conflict with each other or with the molecules, soft and hard bounds behave very differently; soft bounds allow sequence data to correct poor calibrations, while poor hard bounds are impossible to overcome by any amount of data. (3) Soft bounds eliminate the need for "safe" but unrealistically high upper bounds, which may bias posterior time estimates. (4) Soft bounds allow more reliable assessment of estimation errors, while hard bounds generate misleadingly high precisions when fossils and molecules are in conflict.

                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@ 123456nrm.se . 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 ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 1 September 2011
                : 19 October 2011
                : 7 June 2012
                Page count
                Pages: 27
                Regular Articles

                Animal science & Zoology
                Animal science & Zoology


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