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      Ignoring stratigraphic age uncertainty leads to erroneous estimates of species divergence times under the fossilized birth–death process

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          Abstract

          Fossil information is essential for estimating species divergence times, and can be integrated into Bayesian phylogenetic inference using the fossilized birth–death (FBD) process. An important aspect of palaeontological data is the uncertainty surrounding specimen ages, which can be handled in different ways during inference. The most common approach is to fix fossil ages to a point estimate within the known age interval. Alternatively, age uncertainty can be incorporated by using priors, and fossil ages are then directly sampled as part of the inference. This study presents a comparison of alternative approaches for handling fossil age uncertainty in analysis using the FBD process. Based on simulations, we find that fixing fossil ages to the midpoint or a random point drawn from within the stratigraphic age range leads to biases in divergence time estimates, while sampling fossil ages leads to estimates that are similar to inferences that employ the correct ages of fossils. Second, we show a comparison using an empirical dataset of extant and fossil cetaceans, which confirms that different methods of handling fossil age uncertainty lead to large differences in estimated node ages. Stratigraphic age uncertainty should thus not be ignored in divergence time estimation and instead should be incorporated explicitly.

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          The delayed rise of present-day mammals.

          Did the end-Cretaceous mass extinction event, by eliminating non-avian dinosaurs and most of the existing fauna, trigger the evolutionary radiation of present-day mammals? Here we construct, date and analyse a species-level phylogeny of nearly all extant Mammalia to bring a new perspective to this question. Our analyses of how extant lineages accumulated through time show that net per-lineage diversification rates barely changed across the Cretaceous/Tertiary boundary. Instead, these rates spiked significantly with the origins of the currently recognized placental superorders and orders approximately 93 million years ago, before falling and remaining low until accelerating again throughout the Eocene and Oligocene epochs. Our results show that the phylogenetic 'fuses' leading to the explosion of extant placental orders are not only very much longer than suspected previously, but also challenge the hypothesis that the end-Cretaceous mass extinction event had a major, direct influence on the diversification of today's mammals.
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            Paleontological evidence to date the tree of life.

            The role of fossils in dating the tree of life has been misunderstood. Fossils can provide good "minimum" age estimates for branches in the tree, but "maximum" constraints on those ages are poorer. Current debates about which are the "best" fossil dates for calibration move to consideration of the most appropriate constraints on the ages of tree nodes. Because fossil-based dates are constraints, and because molecular evolution is not perfectly clock-like, analysts should use more rather than fewer dates, but there has to be a balance between many genes and few dates versus many dates and few genes. We provide "hard" minimum and "soft" maximum age constraints for 30 divergences among key genome model organisms; these should contribute to better understanding of the dating of the animal tree of life.
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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.
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                Author and article information

                Journal
                Proc Biol Sci
                Proc. Biol. Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                15 May 2019
                8 May 2019
                8 May 2019
                : 286
                : 1902
                : 20190685
                Affiliations
                [1 ]Department of Biosystems Science and Engineering, ETH Zurich , Basel, Switzerland
                [2 ]Swiss Institute of Bioinformatics (SIB) , Lausanne, Switzerland
                [3 ]Department of Ecology, Evolution and Organismal Biology, Iowa State University , Ames, IA, USA
                [4 ]Palaeontological Institute and Museum, University of Zurich , Zurich, Switzerland
                [5 ]Division of Paleontology, American Museum of Natural History , New York, NY, USA
                Author notes
                Author information
                http://orcid.org/0000-0002-5220-5468
                http://orcid.org/0000-0002-9964-1646
                http://orcid.org/0000-0001-6431-535X
                Article
                rspb20190685
                10.1098/rspb.2019.0685
                6532507
                31064306
                9a326124-838e-430f-9bd7-079c8e5bfd8d
                © 2019 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 22 March 2019
                : 12 April 2019
                Funding
                Funded by: FP7 People: Marie-Curie Actions, http://dx.doi.org/10.13039/100011264;
                Award ID: COFUND programme
                Funded by: FP7 Ideas: European Research Council, http://dx.doi.org/10.13039/100011199;
                Award ID: PhyPD 335529
                Funded by: Eidgenössische Technische Hochschule Zürich, http://dx.doi.org/10.13039/501100003006;
                Award ID: Postdoctoral Fellowship
                Categories
                1001
                44
                144
                Palaeobiology
                Research Article
                Custom metadata
                May 15, 2019

                Life sciences
                fossilized birth–death,stratigraphic age uncertainty,fossil data,bayesian phylogenetics,divergence times estimation

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