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Data from: Detecting evolutionarily significant units above the species level using the Generalized Mixed Yule Coalescent method

Citation

Humphreys, Aelys M. et al. (2017), Data from: Detecting evolutionarily significant units above the species level using the Generalized Mixed Yule Coalescent method, Dryad, Dataset, https://doi.org/10.5061/dryad.3rt26

Abstract

1. There is renewed interest in inferring evolutionary history by modelling diversification rates using phylogenies. Understanding the performance of the methods used under different scenarios is essential for assessing empirical results. Recently we introduced a new approach for analysing broadscale diversity patterns, using the Generalized Mixed Yule Coalescent (GMYC) method to test for the existence of evolutionarily significant units above the species (higher ESUs). This approach focuses on identifying clades as well as estimating rates and we refer to it as clade-dependent. However, the ability of the GMYC to detect the phylogenetic signature of higher ESUs has not been fully explored, nor has it been placed in the context of other, clade-independent approaches. 2. We simulated >32,000 trees under two clade-independent models: constant-rate birth-death (CRBD) and variable-rate birth-death (VRBD), using parameter estimates from nine empirical trees and more general parameter values. The simulated trees were used to evaluate scenarios under which GMYC might incorrectly detect the presence of higher ESUs. 3. The GMYC null model was rejected at a high rate on CRBD-simulated trees. This would lead to spurious inference of higher ESUs. However, the support for the GMYC model was significantly greater in most of the empirical clades than expected under a CRBD process. Simulations with empirically derived parameter values could therefore be used to exclude CRBD as an explanation for diversification patterns. In contrast, a VRBD process could not be ruled out as an alternative explanation for the apparent signature of hESUs in the empirical clades, based on the GMYC method alone. Other metrics of tree shape, however, differed notably between the empirical and VRBD-simulated trees. These metrics could be used in future to distinguish clade-dependent and clade-independent models. 4. In conclusion, detection of higher ESUs using the GMYC is robust against some clade-independent models, as long as simulations are used to evaluate these alternatives, but not against others. The differences between clade-dependent and clade-independent processes are biologically interesting, but most current models focus on the latter. We advocate more research into clade-dependent models for broad diversity patterns.

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