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      Strong phylogenetic signals and phylogenetic niche conservatism in ecophysiological traits across divergent lineages of Magnoliaceae

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          Abstract

          The early diverged Magnoliaceae shows a historical temperate-tropical distribution among lineages indicating divergent evolution, yet which ecophysiological traits are phylogenetically conserved, and whether these traits are involved in correlated evolution remain unclear. Integrating phylogeny and 20 ecophysiological traits of 27 species, from the four largest sections of Magnoliaceae, we tested the phylogenetic signals of these traits and the correlated evolution between trait pairs. Phylogenetic niche conservatism (PNC) in water-conducting and nutrient-use related traits was identified, and correlated evolution of several key functional traits was demonstrated. Among the three evergreen sections of tropical origin, Gwillimia had the lowest hydraulic-photosynthetic capacity and the highest drought tolerance compared with Manglietia and Michelia. Contrastingly, the temperate centred deciduous section, Yulania, showed high rates of hydraulic conductivity and photosynthesis at the cost of drought tolerance. This study elucidated the regulation of hydraulic and photosynthetic processes in the temperate-tropical adaptations for Magnoliaceae species, which led to strong phylogenetic signals and PNC in ecophysiological traits across divergent lineages of Magnoliaceae.

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          MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

          Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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            jModelTest 2: more models, new heuristics and parallel computing.

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              R: A language and environment for statistical computing

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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                16 July 2015
                2015
                : 5
                : 12246
                Affiliations
                [1 ]Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences , Xingke Road 723, Guangzhou 510650, China
                [2 ]University of Chinese Academy of Sciences , Yuquan road 19A, Beijing 100049, China
                [3 ]Botany & Plant Sciences, University of California , 2150 Batchelor Hall, Riverside, CA 92521-0124, USA
                [4 ]Smithsonian Tropical Research Institute , P.O. Box 0843-03092, Balboa, Ancon, Panama, Republic of Panama
                [5 ]Horticulture Center, South China Botanical Garden, Chinese Academy of Sciences , Tianyuan Road 1190, Guangzhou 510520, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep12246
                10.1038/srep12246
                4503962
                26179320
                25ac44b4-c545-4584-b288-96015cb2fe80
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 03 September 2014
                : 19 June 2015
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