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phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)

Revell, Liam J.·2024·PeerJ
DOI 10.7717/peerj.16505PMC PMC10773453

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Abstract

Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package has grown to become an important research tool for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools , while also illustrating several popular workflows of the phytools computational software.

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  • Previous RERconverge ancestral trait reconstruction functionality was only available for binary or continuous traits and used an approximate maximum parsimony approach for binary traits and estimation of maximum likelihood states for continuous traits.

    “Previous RERconverge ancestral trait reconstruction functionality was only available for binary or continuous traits and used an approximate maximum parsimony approach for binary traits and estimation of maximum likelihood states for continuous traits (Maddison 1989; Kowalczyk et al. 2019; Revell 2024).”

    From RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution (2024) · cites this paper as Revell 2024

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Research works printed but not linked: 137

  1. Amarasinghe, 2021, Evolution and biogeography of Mermecylon, American Journal of Botany, 108, 628, 10.1002/ajb2.1624 · DOI
  2. Atkinson, 2020, Evolutionary history drives aspects of stoichiometric niche variation and functional effects within a guild, Ecology, 101, e03100, 10.1002/ecy.3100 · DOI
  3. Baele, 2018, Recent advances in computational phylodynamics, Current Opinion in Virology, 31, 24, 10.1016/j.coviro.2018.08.009 · DOI
  4. Bartoszek, 2012, A phylogenetic comparative method for studying multivariate adaptation, Journal of Theoretical Biology, 314, 204, 10.1016/j.jtbi.2012.08.005 · DOI
  5. Bastide, 2018, Inference of adaptive shifts for multivariate correlated traits, Systematic Biology, 67, 662, 10.1093/sysbio/syy005 · DOI
  6. Beale, 2019, Genomic epidemiology of syphilis reveals independent emergence of macrolide resistance across multiple circulating lineages, Nature Communications, 10, 3255, 10.1038/s41467-019-11216-7 · DOI
  7. Beaulieu, 2016, Detecting hidden diversification shifts in models of trait-dependent speciation and extinction, Systematic Biology, 65, 583, 10.1093/sysbio/syw022 · DOI · Paper page
  8. Beaulieu, 2013, Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms, Systematic Biology, 62, 725, 10.1093/sysbio/syt034 · DOI · Paper page
  9. Bentz, 2018, The evolution of language families is shaped by the environment beyond neutral drift, Nature Human Behaviour, 2, 816, 10.1038/s41562-018-0457-6 · DOI
  10. Blinkhorn, 2021, Explanations of variability in middle stone age stone tool assemblage composition and raw material use in Eastern Africa, Archaeological and Anthropological Sciences, 13, 14, 10.1007/s12520-020-01250-8 · DOI
  11. Blomberg, 2003, Testing for phylogenetic signal in comparative data: behavioral traits are more labile, Evolution, 57, 717
  12. Bollback, 2006, SIMMAP: stochastic character mapping of discrete traits on phylogenies, BMC Bioinformatics, 7, 88, 10.1186/1471-2105-7-88 · DOI
  13. Broeckhoven, 2016, Enemy at the gates: rapid defensive trait diversification in an adaptive radiation of lizards, Evolution, 70, 2647, 10.1111/evo.13062 · DOI
  14. Bushman, 2019, Virus structures constrain transmission modes, Nature Microbiology, 4, 1778, 10.1038/s41564-019-0523-5 · DOI
  15. Butler, 2004, Phylogenetic comparative analysis: a modeling approach for adaptive evolution, The American Naturalist, 164, 683, 10.1086/426002 · DOI · Paper page
  16. Caetano, 2017, ratematrix: an R package for studying evolutionary integration among several traits on phylogenetic trees, Methods in Ecology and Evolution, 8, 1920, 10.1111/2041-210X.12826 · DOI
  17. Caraballo, 2022, Cross-species transmission of bat coronaviruses in the Americas: contrasting patterns between alphacoronavirus and betacoronavirus, Microbiology Spectrum, 10, e0141122, 10.1128/spectrum.01411-22 · DOI
  18. Chazot, 2021, Punctuational ecological changes rather than global factors drive species diversification and the evolution of wing phenotypes in morpho butterflies, Journal of Evolutionary Biology, 34, 1592, 10.1111/jeb.13921 · DOI
  19. Clavel, 2015, MvMORPH: an R package for fitting multivariate evolutionary models to morphometric data, Methods in Ecology and Evolution, 6, 1311, 10.1111/2041-210X.12420 · DOI
  20. Collar, 2014, Biting disrupts integration to spur skull evolution in eels, Nature, 5, 5505
  21. Compton, 2023, Cancer prevalence across vertebrates, bioRxiv, 10.1101/2023.02.15.527881 · DOI
  22. Csosz, 2016, Taxonomic revision of the Malagasy Nesomyrmex madecassus species-group using a quantitative morphometric approach, ZooKeys, 603, 105, 10.3897/zookeys.603.8271 · DOI
  23. Damian-Serrano, 2021, The evolution of siphonophore tentilla for specialized prey capture in the open ocean, Proceedings of the National Academy of Sciences, 118, e2005063118, 10.1073/pnas.2005063118 · DOI
  24. Endara, 2018, Tracking of host defenses and phylogeny during the radiation of neotropical Inga-feeding sawflies (Hymenoptera; Argidae), Frontiers in Plant Science, 9, 1237, 10.3389/fpls.2018.01237 · DOI
  25. Esquerré, 2019, How mountains shape biodiversity: the role of the Andes in biogeography, diversification, and reproductive biology in South America’s most species-rich lizard radiation (Squamata: Liolaemidae), Evolution, 73, 214, 10.1111/evo.13657 · DOI
  26. Etienne, 2012, A conceptual and statistical framework for adaptive radiations with a key role for diversity dependence, The American Naturalist, 180, E75, 10.1086/667574 · DOI · Paper page
  27. Evans, 2009, Climate, niche evolution, and diversification of the Bird-Cage evening primroses (Oenothera, sections Anogra and Kleinia), The American Naturalist, 173, 225, 10.1086/595757 · DOI
  28. Felsenstein, 2002, Quantitative characters, phylogenies, and morphometrics, 27, 10.1201/9780203165171.ch3 · DOI
  29. Felsenstein, 2004, Inferring phylogenies
  30. Felsenstein, 2005, Using the quantitative genetic threshold model for inferences between and within species, Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 1427, 10.1098/rstb.2005.1669 · DOI
  31. Felsenstein, 2012, A comparative method for both discrete and continuous characters using the threshold model, The American Naturalist, 179, 145, 10.1086/663681 · DOI
  32. FitzJohn, 2010, Quantitative traits and diversification, Systematic Biology, 59, 619, 10.1093/sysbio/syq053 · DOI
  33. FitzJohn, 2012, Diversitree: comparative phylogenetic analyses of diversification in R, Methods in Ecology and Evolution, 3, 1084, 10.1111/j.2041-210X.2012.00234.x · DOI
  34. Freitas, 2020, Comparative genomics of global optrA-carrying Enterococcus faecalis uncovers a common chromosomal hotspot for optrA acquisition within a diversity of core and accessory genomes, Microbial Genomics, 6, e000350, 10.1099/mgen.0.000350 · DOI
  35. Friedman, 2016, Ecomorphological convergence in planktivorous surgeonfishes, Journal of Evolutionary Biology, 29, 965, 10.1111/jeb.12837 · DOI
  36. Galtier, 2001, Maximum-likelihood phylogenetic analysis under a covarion-like model, Molecular Biology and Evolution, 18, 866, 10.1093/oxfordjournals.molbev.a003868 · DOI
  37. Garamszegi, 2014, Modern phylogenetic comparative methods and their application in evolutionary biology: concepts and practice, 10.1007/978-3-662-43550-2 · DOI · Paper page
  38. Gerber, 2019, optimParallel: an R package providing a parallel version of the L-BFGS-B optimization method, The R Journal, 11, 352, 10.32614/RJ-2019-030 · DOI
  39. Goelen, 2020, Bacterial phylogeny predicts volatile organic compound composition and olfactory response of an aphid parasitoid, Oikos, 129, 1415, 10.1111/oik.07301 · DOI
  40. Goldberg, 2012, Tempo and mode in plant breeding system evolution, Evolution, 66, 3701, 10.1111/j.1558-5646.2012.01730.x · DOI
  41. Halali, 2020, Seasonal environments drive convergent evolution of a faster pace-of-life in tropical butterflies, Ecology Letters, 24, 102, 10.1111/ele.13626 · DOI
  42. Harmon, 2019, Phylogenetic comparative methods: learning from trees, EvoEvoRxiv, 10.32942/osf.io/e3xnr · DOI
  43. Harmon, 2008, GEIGER: investigating evolutionary radiations, Bioinformatics, 24, 129, 10.1093/bioinformatics/btm538 · DOI
  44. Harvey, 1991, The comparative method in evolutionary biology, 10.1093/oso/9780198546412.001.0001 · DOI · Paper page
  45. Hedges, 2006, TimeTree: a public knowledge-base of divergence times among organisms, Bioinformatics, 22, 2971, 10.1093/bioinformatics/btl505 · DOI · Paper page
  46. Hermanson, 2020, A small podocnemidoid (Pleurodira, Pelomedusoides) from the Late Cretaceous of Brazil, and the innervation and carotid circulation of side-necked turtles, Papers in Palaeontology, 6, 329, 10.1002/spp2.1300 · DOI
  47. Higham, 2022, The evolution of mechanical properties of conifer and angiosperm woods, Integrative and Comparative Biology, 62, 668, 10.1093/icb/icac103 · DOI
  48. Hohenlohe, 2008, MIPoD: a hypothesis-testing framework for microevolutionary inference from patterns of divergence, The American Naturalist, 171, 366, 10.1086/527498 · DOI
  49. Huang, 2021, Evolution of adult male horn developmental phenotypes and character displacement in Xylotrupes beetles (Scarabaeidae), Ecology and Evolution, 11, 5503, 10.1002/ece3.7448 · DOI
  50. Huang, 2022, Assemblages of Plasmodium and related parasites in birds with different migration statuses, International Journal of Molecular Sciences, 23, 10277, 10.3390/ijms231810277 · DOI
  51. Huelsenbeck, 2003, Stochastic mapping of morphological characters, Systematic Biology, 52, 131, 10.1080/10635150390192780 · DOI
  52. Huey, 2019, Revisiting a key innovation in evolutionary biology: Felsenstein’s phylogenies and the comparative method, The American Naturalist, 193, 755, 10.1086/703055 · DOI
  53. Huie, 2021, Convergent patterns of adaptive radiation between island and mainland Anolis lizards, Biological Journal of the Linnean Society, 134, 85, 10.1093/biolinnean/blab072 · DOI
  54. Hultgren, 2021, Correlated evolution of larval development, egg size and genome size across two genera of snapping shrimp, Journal of Evolutionary Biology, 34, 1827, 10.1111/jeb.13945 · DOI
  55. Jezovit, 2020, Behavioral and environmental contributions to drosophilid social networks, Proceedings of the National Academy of Sciences of the United States of America, 117, 11573, 10.1073/pnas.1920642117 · DOI
  56. King, 2015, Ancestral state reconstruction, rate heterogeneity, and the evolution of reptile viviparity, Systematic Biology, 64, 532, 10.1093/sysbio/syv005 · DOI
  57. Kirk, 2004, The evolution of high visual acuity in the Anthropoidea, 539, 10.1007/978-1-4419-8873-7_20 · DOI
  58. Lee, 2016, Diversification rates and phenotypic evolution in venomous snakes (Elapidae), Royal Society Open Science, 3, 150277, 10.1098/rsos.150277 · DOI
  59. Lee, 1998, Reptilian viviparity and Dollo’s law, Evolution, 52, 1441, 10.2307/2411313 · DOI
  60. Lemon, 2006, Plotrix: a package in the red light district of R, R-News, 6, 8
  61. Lewis, 2001, A likelihood approach to estimating phylogeny from discrete morphological character data, Systematic Biology, 50, 913, 10.1080/106351501753462876 · DOI · Paper page
  62. Ligges, 2003, Scatterplot3d—an R package for visualizing multivariate data, Journal of Statistical Software, 8, 1, 10.18637/jss.v008.i11 · DOI
  63. Link, 2006, Model weights and the foundations of multimodel inference, Ecology, 87, 2626, 10.1890/0012-9658(2006)87[2626:MWATFO]2.0.CO;2 · DOI
  64. Losos, 2009, Lizards in an evolutionary tree: ecology and adaptive radiation of anoles
  65. MacPherson, 2022, Unifying phylogenetic birth—death models in epidemiology and macroevolution, Systematic Biology, 71, 172, 10.1093/sysbio/syab049 · DOI
  66. Maddison, 2007, Estimating a binary character’s effect on speciation and extinction, Systematic Biology, 56, 701, 10.1080/10635150701607033 · DOI
  67. Mahler, 2010, Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles, Evolution, 64, 2731, 10.1111/j.1558-5646.2010.01026.x · DOI
  68. Marazzi, 2012, Locating evolutionary precursors on a phylogenetic tree, Evolution, 66, 3918, 10.1111/j.1558-5646.2012.01720.x · DOI
  69. Martin, 2022, Modeling the evolution of rates of continuous trait evolution, Systematic Biology, 72, 590, 10.1093/sysbio/syac068 · DOI
  70. Martinez, 2020, Convergent evolution of olfactory and thermoregulatory capacities in small amphibious mammals, Proceedings of the National Academy of Sciences, 117, 8958, 10.1073/pnas.1917836117 · DOI
  71. Martins, 2021, The evolution of red blood cell shape in fishes, Journal of Evolutionary Biology, 34, 537, 10.1111/jeb.13757 · DOI
  72. McLaughlin, 2022, Genomic epidemiology of the first two waves of SARS-CoV-2 in Canada, Elife, 11, e73896, 10.7554/eLife.73896 · DOI
  73. Medina, 2016, The evolution of host specialisation in avian brood parasites, Ecology Letters, 19, 1110, 10.1111/ele.12649 · DOI
  74. Mifsud, 2023, Transcriptome mining extends the host range of the Flaviviridae to non-bilaterians, Virus Evolution, 9, veac124, 10.1093/ve/veac124 · DOI
  75. Mitov, 2019, Automatic generation of evolutionary hypotheses using mixed Gaussian phylogenetic models, Proceedings of the National Academy of Sciences, 116, 16921, 10.1073/pnas.1813823116 · DOI
  76. Molina-Mora, 2021, Genomic context of the two integrons of ST-111 Pseudomonas aeruginosa AG1: a VIM-2-carrying old-acquaintance and a novel IMP-18-carrying integron, Infection, Genetics and Evolution, 89, 104740, 10.1016/j.meegid.2021.104740 · DOI
  77. Morales-Poole, 2022, Sugar concentration, nitrogen availability, and phylogenetic factors determine the ability of Acinetobacter spp. and Rosenbergiella spp. to grow in floral nectar, Microbial Ecology, 86, 377, 10.1007/s00248-022-02088-4 · DOI
  78. Morlon, 2016, RPANDA: an R package for macroevolutionary analyses on phylogenetic trees, Methods in Ecology and Evolution, 7, 589, 10.1111/2041-210X.12526 · DOI
  79. Morlon, 2010, Inferring the dynamics of diversification: a coalescent approach, PLOS Biology, 8, e1000493, 10.1371/journal.pbio.1000493 · DOI
  80. Moura, 2016, Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes, Nature Microbiology, 2, 16185, 10.1038/nmicrobiol.2016.185 · DOI
  81. Near, 2005, Fossil calibrations and molecular divergence time estimates in centrarchid fishes (Teleostei: Centrarchidae), Evolution, 59, 1768
  82. Nee, 1994, The reconstructed evolutionary process, Philosophical Transactions of the Royal Society B: Biological Sciences, 344, 305, 10.1098/rstb.1994.0068 · DOI
  83. Nee, 1992, Tempo and mode of evolution revealed from molecular phylogenies, Proceedings of the National Academy of Sciences, 89, 8322, 10.1073/pnas.89.17.8322 · DOI
  84. Nielsen, 2002, Mapping mutations on phylogenies, Systematic Biology, 51, 729, 10.1080/10635150290102393 · DOI
  85. Nunn, 2011, The comparative approach in evolutionary anthropology and biology
  86. O’Meara, 2006, Testing for different rates of continuous trait evolution using likelihood, Evolution, 60, 922
  87. O’Meara, 2012, Evolutionary inferences from phylogenies: a review of methods, Annual Review of Ecology, Evolution, and Systematics, 43, 267, 10.1146/annurev-ecolsys-110411-160331 · DOI · Paper page
  88. Osuna-Mascaró, 2023, Fine-scale spatial genetic structure in a locally abundant native bunchgrass (Achnatherum therberianum) including distinct lineages revealed within seed transfer zones, Evolutionary Applications, 16, 979, 10.1111/eva.13547 · DOI
  89. Page, 1993, Parasites, phylogeny and cospeciation, International Journal for Parasitology, 23, 499, 10.1016/0020-7519(93)90039-2 · DOI
  90. Pagel, 1994, Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters, Proceedings of the Royal Society B: Biological Sciences, 255, 37, 10.1098/rspb.1994.0006 · DOI · Paper page
  91. Pagel, 1999, Inferring the historical patterns of biological evolution, Nature, 401, 877, 10.1038/44766 · DOI · Paper page
  92. Paradis, 2004, APE: analyses of phylogenetics and evolution in R language, Bioinformatics, 20, 289, 10.1093/bioinformatics/btg412 · DOI · Paper page
  93. Paradis, 2019, ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R, Bioinformatics, 35, 526, 10.1093/bioinformatics/bty633 · DOI
  94. Pennell, 2014, geiger v2.0: an expanded suite of methods for fitting macroevolutionary models to phylogenetic trees, Bioinformatics, 30, 2216, 10.1093/bioinformatics/btu181 · DOI
  95. Pepke, 2022, On the comparative biology of mammalian telomeres: telomere length co-evolves with body mass, lifespan and cancer risk, Molecular Ecology, 31, 6286, 10.1111/mec.15870 · DOI
  96. Pinheiro, 2000, Mixed-effects models in S and S-PLUS, 10.1007/978-1-4419-0318-1 · DOI · Paper page
  97. Plummer, 2006, CODA: convergence diagnosis and output analysis for MCMC, R News, 6, 7
  98. Popescu, 2012, ape 3.0: new tools for distance-based phylogenetics and evolutionary analysis in R, Bioinformatics, 28, 1536, 10.1093/bioinformatics/bts184 · DOI
  99. Poulakakis, 2020, Colonization history of Galapagos giant tortoises: insights from mitogenomes support the progression rule, Journal of Zoological Systematics and Evolutionary Research, 58, 1262, 10.1111/jzs.12387 · DOI
  100. Pozzi, 2022, The effects of body size, activity, and phylogeny on primate sleeping ecology, American Journal of Biological Anthropology, 179, 598, 10.1002/ajpa.24640 · DOI
  101. Pybus, 2000, Testing macro-evolutionary models using incomplete molecular phylogenies, Proceedings of the Royal Society B: Biological Sciences, 267, 2267, 10.1098/rspb.2000.1278 · DOI
  102. Quach, 2019, Historical allopatry and secondary contact or primary intergradation in the Puerto Rican crested anole, Anolis cristatellus, on Vieques Island in the Caribbean, Biological Journal of the Linnean Society, 129, 114
  103. Rabosky, 2014, Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees, PLOS ONE, 9, e89543, 10.1371/journal.pone.0089543 · DOI
  104. Revell, 2009, Size-correction and principal components for interspecific comparative studies, Evolution, 63, 3258, 10.1111/j.1558-5646.2009.00804.x · DOI
  105. Revell, 2012, phytools: an R package for phylogenetic comparative biology (and other things), Methods in Ecology and Evolution, 3, 217, 10.1111/j.2041-210X.2011.00169.x · DOI
  106. Revell, 2013, Two new graphical methods for mapping trait evolution on phylogenies, Methods in Ecology and Evolution, 4, 754, 10.1111/2041-210X.12066 · DOI
  107. Revell, 2014, Ancestral character estimation under the threshold model from quantitative genetics, Evolution, 68, 743, 10.1111/evo.12300 · DOI
  108. Revell, 2014, Graphical methods for visualizing comparative data on phylogenies, 77, 10.1007/978-3-662-43550-2_4 · DOI
  109. Revell, 2018, Comparing the rates of speciation and extinction between phylogenetic trees, Ecology and Evolution, 8, 5303, 10.1002/ece3.4030 · DOI
  110. Revell, 2021, A variable-rate quantitative trait evolution model using penalized-likelihood, PeerJ, 9, e11997, 10.7717/peerj.11997 · DOI
  111. Revell, 2009, Phylogenetic analysis of the evolutionary correlation using likelihood, Evolution, 63, 1090, 10.1111/j.1558-5646.2009.00616.x · DOI
  112. Revell, 2018, Comparing evolutionary rates between trees, clades and traits, Methods in Ecology and Evolution, 9, 994, 10.1111/2041-210X.12977 · DOI · Paper page
  113. Revell, 2022, Phylogenetic comparative methods in R
  114. Revell, 2008, Phylogenetic signal, evolutionary process, and rate, Systematic Biology, 57, 591, 10.1080/10635150802302427 · DOI · Paper page
  115. Revell, 2008, PCCA: a program for phylogenetic canonical correlation analysis, Bioinformatics, 24, 1018, 10.1093/bioinformatics/btn065 · DOI
  116. Revell, 2007, A phylogenetic test for adaptive convergence in rock-dwelling lizards, Evolution, 61, 2898, 10.1111/j.1558-5646.2007.00225.x · DOI
  117. Revell, 2012, A new phylogenetic method for identifying exceptional phenotypic diversification, Evolution, 66, 135, 10.1111/j.1558-5646.2011.01435.x · DOI
  118. Revell, 2015, Placing cryptic, recently extinct, or hypothesized taxa into an ultrametric phylogeny using continuous character data: a case study with the lizard Anolis roosevelti, Evolution, 69, 1027, 10.1111/evo.12628 · DOI
  119. Revell, 2022, A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree, PeerJ, 10, e13910, 10.7717/peerj.13910 · DOI
  120. Roy, 2020, Convergence diagnostics for Markov chain Monte Carlo, Annual Review of Statistics and its Application, 7, 387, 10.1146/annurev-statistics-031219-041300 · DOI
  121. Sánchez-Busó, 2019, The impact of antimicrobials on gonococcal evolution, Nature Microbiology, 4, 1941, 10.1038/s41564-019-0501-y · DOI
  122. Sander, 2021, Early giant reveals faster evolution of large body size in ichthyosaurs than in cetaceans, Science, 374, eabf5787, 10.1126/science.abf5787 · DOI
  123. Schliep, 2011, phangorn: phylogenetic analysis in R, Bioinformatics, 27, 592, 10.1093/bioinformatics/btq706 · DOI
  124. Schluter, 1997, Likelihood of ancestor states in adaptive radiation, Evolution, 51, 1699, 10.2307/2410994 · DOI
  125. Sidlauskas, 2008, Continuous and arrested morphological diversification in sister clades of characiform fishes: a phylomorphospace approach, Evolution, 62, 3135, 10.1111/j.1558-5646.2008.00519.x · DOI
  126. Stadler, 2011, Inferring speciation and extinction processes from extant species data, Proceedings of the National Academy of Sciences, 108, 16145, 10.1073/pnas.1113242108 · DOI
  127. Stadler, 2013, How can we improve accuracy of macroevolutionary rate estimates?, Systematic Biology, 62, 321, 10.1093/sysbio/sys073 · DOI
  128. Stull, 2020, Nuclear phylogenomic analyses of asterids conflict with plastome trees and support novel relationships among major lineages, American Journal of Botany, 107, 790, 10.1002/ajb2.1468 · DOI
  129. Uyeda, 2014, A novel Bayesian method for inferring and interpreting the dynamics of adaptive landscapes from phylogenetic comparative data, Systematic Biology, 63, 902, 10.1093/sysbio/syu057 · DOI
  130. Van Borm, 2023, Combined phylogeographic analyses and epidemiologic contact tracing to characterize atypically pathogenic avian influenza (H3N1) epidemic, Belgium, 2019, Emerging Infectious Diseases, 29, 351, 10.3201/eid2902.220765 · DOI
  131. Venables, 2002, Modern applied statistics with S, 10.1007/978-0-387-21706-2 · DOI
  132. Venditti, 2011, Multiple routes to mammalian diversity, Nature, 479, 393, 10.1038/nature10516 · DOI
  133. van der Walt, 2015, A better default colormap for Matplotlib, SciPy 2015
  134. Xie, 2016, bookdown: authoring books and technical documents with R markdown, 10.1201/9781315204963 · DOI
  135. Xie, 2018, R markdown: the definitive guide, 10.1201/9781138359444 · DOI
  136. Xie, 2020, R markdown cookbook, 10.1201/9781003097471 · DOI
  137. Yang, 2014, Molecular evolution: a statistical approach, 10.1093/acprof:oso/9780199602605.001.0001 · DOI

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Metadata

Authors
Revell, L. J.
Affiliations
Department of Biology, University of Massachusetts Boston, Boston, MA, USA
Venue
PeerJ
Publisher
PeerJ
Published
2024-01-05
Volume
12
Pages
e16505
ISSN
2167-8359
DOI
10.7717/peerj.16505
PMC
PMC10773453
Cited by
1,244
References
5
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (unspecified)
Funders
  • The National Science Foundation (DEB-1350474, DBI-1759940)
  • FONDECYT, Chile (1201869)

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