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      A Re-Evaluation of the Chasmosaurine Ceratopsid Genus Chasmosaurus (Dinosauria: Ornithischia) from the Upper Cretaceous (Campanian) Dinosaur Park Formation of Western Canada

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          Abstract

          Background

          The chasmosaurine ceratopsid Chasmosaurus is known from the Upper Cretaceous (Campanian) Dinosaur Park Formation of southern Alberta and Saskatchewan. Two valid species, Chasmosaurus belli and C. russelli, have been diagnosed by differences in cranial ornamentation. Their validity has been supported, in part, by the reported stratigraphic segregation of chasmosaurines in the Dinosaur Park Formation, with C. belli and C. russelli occurring in discrete, successive zones within the formation.

          Results/Conclusions

          An analysis of every potentially taxonomically informative chasmosaurine specimen from the Dinosaur Park Formation indicates that C. belli and C. russelli have indistinguishable ontogenetic histories and overlapping stratigraphic intervals. Neither taxon exhibits autapomorphies, nor a unique set of apomorphies, but they can be separated and diagnosed by a single phylogenetically informative character—the embayment angle formed by the posterior parietal bars relative to the parietal midline. Although relatively deeply embayed specimens ( C. russelli) generally have relatively longer postorbital horncores than specimens with more shallow embayments ( C. belli), neither this horncore character nor epiparietal morphology can be used to consistently distinguish every specimen of C. belli from C. russelli.

          Status of Kosmoceratops in the Dinosaur Park Formation

          Kosmoceratops is purportedly represented in the Dinosaur Park Formation by a specimen previously referred to Chasmosaurus. The reassignment of this specimen to Kosmoceratops is unsupported here, as it is based on features that are either influenced by taphonomy or within the realm of individual variation for Chasmosaurus. Therefore, we conclude that Kosmoceratops is not present in the Dinosaur Park Formation, but is instead restricted to southern Laramidia, as originally posited.

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          Most cited references6

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          A Bayesian missing value estimation method for gene expression profile data.

          Gene expression profile analyses have been used in numerous studies covering a broad range of areas in biology. When unreliable measurements are excluded, missing values are introduced in gene expression profiles. Although existing multivariate analysis methods have difficulty with the treatment of missing values, this problem has received little attention. There are many options for dealing with missing values, each of which reaches drastically different results. Ignoring missing values is the simplest method and is frequently applied. This approach, however, has its flaws. In this article, we propose an estimation method for missing values, which is based on Bayesian principal component analysis (BPCA). Although the methodology that a probabilistic model and latent variables are estimated simultaneously within the framework of Bayes inference is not new in principle, actual BPCA implementation that makes it possible to estimate arbitrary missing variables is new in terms of statistical methodology. When applied to DNA microarray data from various experimental conditions, the BPCA method exhibited markedly better estimation ability than other recently proposed methods, such as singular value decomposition and K-nearest neighbors. While the estimation performance of existing methods depends on model parameters whose determination is difficult, our BPCA method is free from this difficulty. Accordingly, the BPCA method provides accurate and convenient estimation for missing values. The software is available at http://hawaii.aist-nara.ac.jp/~shige-o/tools/.
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            Speciation in the fossil record.

            It is easy to claim that the fossil record says nothing about speciation because the biological species concept (which relies on interbreeding) cannot be applied to it and genetic studies cannot be carried out on it. However, fossilized organisms are often preserved in sufficient abundance for populations of intergrading morphs to be recognized, which, by analogy with modern populations, are probably biological species. Moreover, the fossil record is our only reliable documentation of the sequence of past events over long time intervals: the processes of speciation are generally too slow to be observed directly, and permanent reproductive isolation can only be verified with hindsight. Recent work has shown that some parts of the fossil record are astonishingly complete and well documented, and patterns of lineage splitting can be examined in detail. Marine plankton appear to show gradual speciation, with subsequent morphological differentiation of lineages taking up to 500000 years to occur. Marine invertebrates and vertebrates more commonly show punctuated patterns, with periods of rapid speciation followed by long-term stasis of species lineages.
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              Testing of the effect of missing data estimation and distribution in morphometric multivariate data analyses.

              Missing data are an unavoidable problem in biological data sets and the performance of missing data deletion and estimation techniques in morphometric data sets is poorly understood. Here, a novel method is used to measure the introduced error of multiple techniques on a representative sample. A large sample of extant crocodilian skulls was measured and analyzed with principal component analysis (PCA). Twenty-three different proportions of missing data were introduced into the data set, estimated, analyzed, and compared with the original result using Procrustes superimposition. Previous work investigating the effects of missing data input missing values randomly, a non-biological phenomenon. Here, missing data were introduced into the data set using three methodologies: purely at random, as a function of the Euclidean distance between respective measurements (simulating anatomical regions), and as a function of the portion of the sample occupied by each taxon (simulating unequal missing data in rare taxa). Gower's distance was found to be the best performing non-estimation method, and Bayesian PCA the best performing estimation method. Specimens of the taxa with small sample sizes and those most morphologically disparate had the highest estimation error. Distribution of missing data had a significant effect on the estimation error for almost all methods and proportions. Taxonomically biased missing data tended to show similar trends to random, but with higher error rates. Anatomically biased missing data showed a much greater deviation from random than the taxonomic bias, and with magnitudes dependent on the estimation method.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                4 January 2016
                2016
                : 11
                : 1
                : e0145805
                Affiliations
                [1 ]Department of Earth Sciences, Carleton University, Ottawa, Ontario, Canada
                [2 ]Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
                [3 ]Department of Vertebrate Paleontology, Cleveland Museum of Natural History, Cleveland, Ohio, United States of America
                [4 ]Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
                NYIT College of Osteopathic Medicine, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JAC MJR RBH CJSA. Performed the experiments: JAC. Analyzed the data: JAC MJR RBH CJSA. Contributed reagents/materials/analysis tools: JAC MJR CJSA. Wrote the paper: JAC MJR RBH CJSA.

                Article
                PONE-D-15-33022
                10.1371/journal.pone.0145805
                4699738
                26726769
                dde46661-a11b-4f88-ac96-6abf9d8fad66
                © 2016 Campbell et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 28 July 2015
                : 7 December 2015
                Page count
                Figures: 22, Tables: 0, Pages: 39
                Funding
                This research was supported by an Ontario Graduate Scholarship ( https://osap.gov.on.ca/OSAPPortal/en/A-ZListofAid/PRD19842319.html), Dr. George A. Jeletzky Memorial Scholarship ( http://earthsci.carleton.ca/future-students/graduate/funding), and National Geographic Society's Young Explorer's Grant (Grant Number 9160-12, http://www.nationalgeographic.com/explorers/grants-programs/young-explorers/) to JAC.
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                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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