BAMM at the court of false equivalency: A response to Meyer and Wiens

The software program BAMM has been widely used to study rates of speciation, extinction, and phenotypic evolution on phylogenetic trees. The program implements a model‐based clustering algorithm to identify clades that share common macroevolutionary rate dynamics and to estimate parameters. A recent simulation study by Meyer and Wiens (M&W) argued that (1) a simple inference framework (MS) performs much better than BAMM, and (2) evolutionary rates inferred with BAMM are poorly correlated with true rates. I address two statistical concerns with their assessment that affect the generality of their conclusions. These considerations are not specific to BAMM and apply to other methods for estimating parameters from empirical data where the true grouping structure of the data is unknown. M&W constrain roughly half of the parameters in their MS analyses to their true values, but BAMM is given no such information and must estimate all parameters from the data. This information disparity results in a substantial degrees of freedom advantage for the MS estimators. When both methods are given equivalent information, BAMM outperforms the MS estimators.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146370/1/evo13566.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146370/2/evo13566_am.pd

Unlinked Mendelian inheritance of red and black pigmentation in snakes: Implications for Batesian mimicry

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135324/1/evo12902_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135324/2/evo12902.pd

Ecological and biogeographic drivers of biodiversity cannot be resolved using clade age-richness data

Estimates of evolutionary diversification rates – speciation and extinction – have been used extensively to explain global biodiversity patterns. Many studies have analyzed diversification rates derived from just two pieces of information: a clade’s age and its extant species richness. This “age-richness rate” (ARR) estimator provides a convenient shortcut for comparative studies, but makes strong assumptions about the dynamics of species richness through time. Here we demonstrate that use of the ARR estimator in comparative studies is problematic on both theoretical and empirical grounds. We prove mathematically that ARR estimates are non-identifiable: there is no information in the data for a single clade that can distinguish a process with positive net diversification from one where net diversification is zero. Using paleontological time series, we demonstrate that the ARR estimator has no predictive ability for real datasets. These pathologies arise because the ARR inference procedure yields “point estimates” that have been computed under a saturated statistical model with zero degrees of freedom. Although ARR estimates remain useful in some contexts, they should be avoided for comparative studies of diversification and species richness

Speciation dynamics during the global radiation of extant bats

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/1/evo12681-sup-0008-FIGURE7.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/2/evo12681-sup-0003-FIGURE2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/3/evo12681.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/4/evo12681-sup-0002-FIGURE1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/5/evo12681-sup-0009-FIGURE8.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/6/evo12681-sup-0007-FIGURE6.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/7/evo12681-sup-0006-FIGURE5.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/8/evo12681-sup-0004-FIGURE3.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111917/9/evo12681-sup-0005-FIGURE4.pd

FiSSE: A simple nonparametric test for the effects of a binary character on lineage diversification rates

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137596/1/evo13227.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137596/2/evo13227_am.pd

Tip rates, phylogenies and diversification: What are we estimating, and how good are the estimates?

Species‐specific diversification rates, or ‘tip rates’, can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait‐dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios.We compared the statistical performance of three model‐free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model‐based approach (Bayesian analysis of macroevolutionary mixtures [BAMM]). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates.We show decisively that model‐free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non‐model‐based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes.We found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait‐dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149536/1/mee313153-sup-0001-FigS1-S10.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149536/2/mee313153.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149536/3/mee313153_am.pd