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      Commonly used Bayesian diversification methods lead to biologically meaningful differences in branch-specific rates on empirical phylogenies

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          Abstract

          Identifying along which lineages shifts in diversification rates occur is a central goal of comparative phylogenetics; these shifts may coincide with key evolutionary events such as the development of novel morphological characters, the acquisition of adaptive traits, polyploidization or other structural genomic changes, or dispersal to a new habitat and subsequent increase in environmental niche space. However, while multiple methods now exist to estimate diversification rates and identify shifts using phylogenetic topologies, the appropriate use and accuracy of these methods are hotly debated. Here we test whether five Bayesian methods—Bayesian Analysis of Macroevolutionary Mixtures ( BAMM), two implementations of the Lineage-Specific Birth–Death–Shift model (LSBDS and PESTO), the approximate Multi-Type Birth–Death model ( MTBD; implemented in BEAST2), and the Cladogenetic Diversification Rate Shift model (ClaDS2)—produce comparable results. We apply each of these methods to a set of 65 empirical time-calibrated phylogenies and compare inferences of speciation rate, extinction rate, and net diversification rate. We find that the five methods often infer different speciation, extinction, and net-diversification rates. Consequently, these different estimates may lead to different interpretations of the macroevolutionary dynamics. The different estimates can be attributed to fundamental differences among the compared models. Therefore, the inference of shifts in diversification rates is strongly method dependent. We advise biologists to apply multiple methods to test the robustness of the conclusions or to carefully select the method based on the validity of the underlying model assumptions to their particular empirical system.

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          phytools: an R package for phylogenetic comparative biology (and other things)

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            BEAST 2: A Software Platform for Bayesian Evolutionary Analysis

            We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.
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              ggplot2

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                Author and article information

                Contributors
                Journal
                Evol Lett
                Evol Lett
                evlett
                Evolution Letters
                Oxford University Press (US )
                2056-3744
                April 2024
                31 October 2023
                31 October 2023
                : 8
                : 2
                : 189-199
                Affiliations
                Department of Integrative Biology and the University Herbarium, University of California , Berkeley, CA, United States
                School of Integrative Plant Science, Section of Plant Biology and the L.H. Bailey Hortorium, Cornell University , Ithaca, NY, United States
                Department of Plant and Microbial Biology, University of California , Berkeley, CA, United States
                Department of Integrative Biology and the University Herbarium, University of California , Berkeley, CA, United States
                Department of Biology, Skyline College , San Bruno, CA, United States
                Department of Integrative Biology and the University Herbarium, University of California , Berkeley, CA, United States
                School of Life Sciences, University of Hawai’i at Manoa , HI, United States
                GeoBio-Center, Ludwig-Maximilians-Universitat München , Munich, Germany
                Department of Earth and Environmental Sciences, Paleontology and Geobiology, Ludwig-Maximilians-Universität München , Munich, Germany
                23andMe, Sunnyvale , CA, United States
                GeoBio-Center, Ludwig-Maximilians-Universitat München , Munich, Germany
                Department of Earth and Environmental Sciences, Paleontology and Geobiology, Ludwig-Maximilians-Universität München , Munich, Germany
                School of Integrative Plant Science, Section of Plant Biology and the L.H. Bailey Hortorium, Cornell University , Ithaca, NY, United States
                Department of Integrative Biology and the University Herbarium, University of California , Berkeley, CA, United States
                Department of Biology, Utah State University , Logan, UT, United States
                Author notes
                Corresponding author: Jesús Martínez-Gómez, Department of Integrative Biology and the University Herbarium, University of California, Berkeley, CA 94720, United States. Email: jmartinezg@ 123456berkeley.edu

                J.M.-G., M.J.S., and C.M.T. contributed equally to this study.

                Article
                qrad044
                10.1093/evlett/qrad044
                11275465
                39070288
                94848ce5-ae9f-4276-83d6-5c096236dd60
                © The Author(s) 2023. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEN).

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 17 May 2023
                : 05 September 2023
                : 08 September 2023
                Page count
                Pages: 11
                Funding
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Categories
                Letters
                AcademicSubjects/SCI00010
                AcademicSubjects/SCI00960
                AcademicSubjects/SCI01130

                diversification-rate analyses,phylogeny,bamm,revbayes,beast,clads2,macroevolution

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