DOI: 10.5061/dryad.31227
title: Data from: Age-dependent speciation can explain the shape of empirical phylogenies

description: Tens of thousands of phylogenetic trees, describing the evolutionary
 relationships between hundreds of thousands of taxa, are readily
 obtainable from various databases. From such trees inferences can be made
 about the underlying macroevolutionary processes, yet remarkably these
 processes are still poorly understood. Simple and widely used evolutionary
 null models are problematic: empirical trees show very different imbalance
 between the sizes of the daughter clades of ancestral taxa compared to
 what models predict. Obtaining a simple evolutionary model that is both
 biologically plausible and produces the imbalance seen in empirical trees
 is a challenging problem, to which none of the existing models provide a
 satisfying answer. Here we propose a simple, biologically-plausible
 macroevolutionary model in which the rate of speciation decreases with
 species age, while extinction rates can vary quite generally. We show that
 this model provides a remarkable fit to the thousands of trees stored in
 the online database TreeBase. The biological motivation for the identified
 age-dependent speciation process may be that recently evolved taxa often
 colonise new regions or niches and may initially experience little
 competition. These new taxa are thus more likely to give rise to further
 new taxa than a taxon that has remained largely unchanged and is therefore
 well-adapted to its niche. We show that age-dependent speciation may also
 be the result of different within-species populations following the same
 laws of lineage splitting to produce new species. As the fit of our model
 to the tree database shows, this simple biological motivation provides an
 explanation for a long standing problem in macroevolution.
description: Data-set empirical
 treesThe input file”
 treebase_input.rda” has the trees cached from TreeBase by the R-package
 treebase (Sanderson, M.J., Donoghue, M.J., et al. 1994). The file was
 later treated for specific statistics and compared with simulated trees,
 as described in out methodology. For that the “processing_treebase.R”
 R-script was used, being the file “treebaselist_output.RData” the final
 output. We would like to stress that this is not a complete catalogue of
 all R-scripts used in our study, especially regarding plotting and
 investigation of model behavior, once much was simulated with a cluster
 computer involving multiple outputs, code files and csv parameter tables
 that changed over time. If you plan to run similar experiments, we
 strongly encourage the reading of our TreeSimGM R-package help
 material.data-set_empirical_trees.zipEmpirical trees parameter estimation based on simulated trees“SBFUSED_input.RData” is the main input data that was generated from simulations using the central high-performance computer cluster of ETH Zurich (Brutus) and the R-package TreeSimGM (Hagen, O., Stadler, T. 2013). Inputs from “treebase_output.RData” (that can be found at “data-set_empirical_trees.zip”) are also used, once we use here empirical trees for the fitting. For more details please consult the respective R-package tutorials. All other files are the sub products of the “procedure_rscript.R” script. More details can be found at the methodology section. Figure 3 originates mainly from “SBep_output.RData”, “SBleast.square_output.RData” and “plot_script.R”. We would like to stress that this is not a complete catalogue of all R-scripts used in our study, especially regarding plotting and investigation of model behavior, once much was simulated with a cluster computer involving multiple outputs, code files and csv parameter tables that changed over time. If you plan to run similar experiments, we strongly encourage the reading of our TreeSimGM R-package help material.empirical_trees_parameter_estimation_based_on_simulated_trees.zipReliable estimates of shape on simulated phylogeniesData and scripts used to test our procedure for parameter estimation over the three sets of simulated phylogenies (SI_Fig 6, 7, and 8). We would like to stress that this is not a complete catalogue of all R-scripts used in our study, especially regarding plotting and investigation of model behavior, once much was simulated with a cluster computer involving multiple outputs, code files and csv parameter tables that changed over time. If you plan to run similar experiments, we strongly encourage the reading of our TreeSimGM R-package help material.reliable_estimates_of_shape_on_simulated_phylogenies.zipSupplementary Figures 1-10SupplementaryFigures1-10.pdfSupplementary Analytic ResultsSupplementaryAnalyticResults.pdf