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      Early Arrival and Climatically-Linked Geographic Expansion of New World Monkeys from Tiny African Ancestors

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          Abstract

          New World Monkeys (NWM) (platyrrhines) are one of the most diverse groups of primates, occupying today a wide range of ecosystems in the American tropics and exhibiting large variations in ecology, morphology, and behavior. Although the relationships among the almost 200 living species are relatively well understood, we lack robust estimates of the timing of origin, ancestral morphology, and geographic range evolution of the clade. Herein, we integrate paleontological and molecular evidence to assess the evolutionary dynamics of extinct and extant platyrrhines. We develop novel analytical frameworks to infer the evolution of body mass, changes in latitudinal ranges through time, and species diversification rates using a phylogenetic tree of living and fossil taxa. Our results show that platyrrhines originated 5–10 million years earlier than previously assumed, dating back to the Middle Eocene. The estimated ancestral platyrrhine was small—weighing 0.4 kg—and matched the size of their presumed African ancestors. As the three platyrrhine families diverged, we recover a rapid change in body mass range. During the Miocene Climatic Optimum, fossil diversity peaked and platyrrhines reached their widest latitudinal range, expanding as far South as Patagonia, favored by warm and humid climate and the lower elevation of the Andes. Finally, global cooling and aridification after the middle Miocene triggered a geographic contraction of NWM and increased their extinction rates. These results unveil the full evolutionary trajectory of an iconic and ecologically important radiation of monkeys and showcase the necessity of integrating fossil and molecular data for reliably estimating evolutionary rates and trends.

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          PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals

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

            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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              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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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Syst Biol
                Syst. Biol
                sysbio
                Systematic Biology
                Oxford University Press
                1063-5157
                1076-836X
                January 2019
                20 June 2018
                20 June 2018
                : 68
                : 1
                : 78-92
                Affiliations
                [1 ]Department of Biological and Environmental Sciences, University of Gothenburg, Carl Skottsbergs gata 22B, Gothenburg 41319, Sweden
                [2 ]Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland
                [3 ]Gothenburg Global Biodiversity Center, Carl Skottsbergs gata 22B, Gothenburg 41319, Sweden
                [4 ]Swiss Institute of Bioinformatics, Quartier Sorge, 1015 Lausanne, Switzerland
                [5 ]Instituto Patagónico de Geología y Paleontología (CCT CONICET-CENPAT), Boulevard Almirante Brown 2915, 9120 Puerto Madryn, Chubut, Argentina
                [6 ]Facultad de Ciencias Naturales, Sede Trelew, Universidad Nacional de la Patagonia ‘San Juan Bosco’, 9100 Trelew, Chubut, Argentina
                [7 ]Department of Zoology, University of British Columbia, 2212 Main Mall, Vancouver, BC Canada
                [8 ]Division of Evolutionary Biology, Ludwig-Maximilians-Universität München, Großhaderner Straße 2, 82152 Munich, Germany
                [9 ]Gothenburg Botanical Garden, Carl Skottsbergs gata 22A, 413 19 Gothenburg, Sweden
                [10 ]Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford St., Cambridge, MA 02138, USA
                [11 ]These authors contributed equally to this work
                [12 ]These authors are severs as a co-last authorship
                Author notes
                Correspondence to be sent to: Department of Biological and Environmental Sciences, University of Gothenburg, 413 19 Gothenburg, Sweden; E-mail: daniele.silvestro@ 123456unil.ch .
                Article
                syy046
                10.1093/sysbio/syy046
                6292484
                29931325
                7f198819-b1ad-44a0-8934-cb6c45c2f41e
                © The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For Permissions, please email: journals.permissions@ 123456oup.com

                History
                : 22 January 2018
                : 25 April 2018
                : 6 June 2018
                Page count
                Pages: 15
                Funding
                Funded by: Swedish Research Council 10.13039/501100004359
                Award ID: 2015-04748
                Funded by: Argentine Fund for Science and Technology
                Award ID: PICT 2014-1818
                Funded by: Swedish Research Council 10.13039/501100004359
                Award ID: B0569601
                Funded by: Swedish Foundation for Strategic Research 10.13039/501100001729
                Funded by: Faculty of Sciences at the University of Gothenburg
                Funded by: David Rockefeller Center for Latin American Studies
                Funded by: Wenner-Gren Foundations
                Funded by: Wallenberg Academy
                Funded by: Swiss National Science Foundation 10.13039/501100001711
                Award ID: CR32I3-143768
                Award ID: 31003A-163428
                Funded by: University of Lausanne 10.13039/501100006390
                Categories
                Regular Articles

                Animal science & Zoology
                trait evolution,primates,birth-death models,bayesian methods,fossils
                Animal science & Zoology
                trait evolution, primates, birth-death models, bayesian methods, fossils

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