Tree size and relative clade age influence estimation of speciation rate shifts
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology, Evolutionary Studies
- Keywords
- diversification, BiSSE, BAMM, MEDUSA, rate shift, phylogenetics, key innovation, macroevolution, simulation
- Copyright
- © 2017 Kodandaramaiah et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Tree size and relative clade age influence estimation of speciation rate shifts. PeerJ Preprints 5:e3206v1 https://doi.org/10.7287/peerj.preprints.3206v1
Abstract
The development of methods to estimate rates of speciation and extinction from time-calibrated phylogenies has revolutionized evolutionary biology by allowing researchers to correlate diversification rate shifts with causal ecological factors. We use rigorous simulations to evaluate the statistical performance of three widely used modelling approaches - BiSSE, BAMM and MEDUSA - in relation to detection of speciation rates shifts. We simulated sets of trees with each tree having a single increase in speciation rate. We varied the location of shifts, the degree of increase in speciation rate and the total age of the tree. We then used BiSSE, BAMM and MEDUSA to estimate rate shifts. For BiSSE, we assigned different character states for the lineages with different simulated speciation rates. We show that all methods are better at detecting rate shifts when the change in speciation rate is higher, but had high Type II errors (non-detection of rate shifts). While the algorithms more accurately identified rate shifts close to the root of the tree, both perform poorly when the rate shift occurred more recently. All methods performed better with increase in the overall number of tips and the number of tips in the clade with rate shift, both of which are correlated with tree age and speciation rate asymmetry. We discuss the implications of this study for the use and development of methods for hypothesis testing based on diversification rate shifts.
Author Comment
This is a submission to PeerJ for review.
Supplemental Information
Proportion of shifts detected for different basetree ages and λ1 values using the backward simulation method estimated using BiSSE
Power, measured as the proportion of shifts detected, for BiSSE analysis using backward simulation method from Treesim package (Stadler 2010). X axes values are the simulated speciation rate asymmetry values. The first panel (A) represents simulated scenarios of λ0 0.22 and basetree age 25 units, the second panel (B) represents λ0 0.27 and basetree age 25 units, while the third column (C) represents λ0 0.27 and basetree age 15 units.
BiSSE estimated speciation rates
Speciation rate estimates by BiSSE under different simulated conditions. The title of each panel indicates speciation rate asymmetry values. The point of intersection between the red-dotted lines represents known values used in the simulations. The simulation conditions (subtree age Sage, basetree age Bage and basetree speciation rate λ0) are given as captions for each sub-figure.
BAMM estimated speciation rates
Speciation rate estimates by BAMM under different simulated conditions. The title of each panel indicates speciation rate asymmetry values. The point of intersection between the red-dotted lines represents known values used in the simulations. The simulation conditions (subtree age Sage, basetree age Bage and basetree speciation rate λ0) are given as captions for each sub-figure.
BiSSE estimated extinction rates
Extinction rate estimates by BiSSE under different simulated conditions: (A) λ0=0.22; Bage=25 (B) λ0=0.27; Bage=15 (C) λ0=0.27; Bage=25
BAMM estimated extinction rates
Extinction rate estimates by BAMM under different simulated conditions: (A) λ0=0.22; Bage=25 (B) λ0=0.27; Bage=15 (C) λ0=0.27; Bage=25