Time-binning rates of continuous character evolution on a phylogeny: the origin of amniotes, not tetrapods, is characterised by increased rates
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Presentation at International Symposium on Early and Lower Vertebrates (Melbourne 2015).
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Time-binning rates of continuous character evolution on a phylogeny: the origin of amniotes, not tetrapods, is characterised by increased rates
- 1. Time-binning rates of continuous character evolution on a phylogeny: the origin of amniotes, not tetrapods, is characterised by increased rates @GraemeTLloyd Graeme T. Lloyd @Friedman_Lab Matt Friedman
- 2. Acknowledgements Chris Organ Graham Slater
- 3. Questions
- 4. Questions 1. How can we measure rates of evolution in a continuous character over multiple time bins?
- 5. Questions 2. How did the tempo of tetrapod mandible evolution change over their early evolution? 1. How can we measure rates of evolution in a continuous character over multiple time bins?
- 6. Questions 2. How did the tempo of tetrapod mandible evolution change over their early evolution? 3. How does phylogenetic time-scale choice affect patterns of tempo? 1. How can we measure rates of evolution in a continuous character over multiple time bins?
- 7. How fast?
- 8. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 9. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 10. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 11. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 12. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 13. Rate categories Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
- 14. Rate data types Simpson 1944,1953; Westoll 1949
- 15. Rate data types Simpson 1944,1953; Westoll 1949
- 16. Rate data types Simpson 1944,1953; Westoll 1949
- 17. Rate data types Simpson 1944,1953; Westoll 1949
- 18. Discrete data: disparity and tempo Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
- 19. Discrete data: disparity and tempo Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
- 20. Discrete data: disparity and tempo Claddis Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
- 21. Continuous data: mode dominates
- 22. Continuous data: mode dominates Trait value Time
- 23. Early Burst Late Burst Trait Time Continuous data: mode dominates
- 26. Raia et al. 2013 Continuous rates
- 27. Harmon et al. 2008 New method: guts
- 32. S1 S2 S31 New method: description
- 33. Anderson et al. 2013 Data
- 34. Anderson et al. 2013 Data
- 36. Lee et al 2014 Time-scaling trees: simultaneous
- 37. Time-scaling trees: a posteriori paleotree strap
- 38. Time-scaling trees: a posteriori + paleotree strap
- 39. Time-scaling trees: a posteriori + = paleotree strap
- 40. Time-scaling trees: a posteriori Arbitrary Branch-sharing Ruta et al 2006; Brusatte et al 2008 Arbitrary addition(s) Derstler 1982 Minimum branch-length Laurin 2004
- 41. Time-scaling trees: a posteriori cal3 Bapst 2013 Hedman method Lloyd and Friedman in prep Nowak Nowak et al 2013 Arbitrary Probabilistic Branch-sharing Ruta et al 2006; Brusatte et al 2008 Arbitrary addition(s) Derstler 1982 Minimum branch-length Laurin 2004
- 42. Time-scaling trees: a posteriori Hedman method Lloyd and Friedman in prep Arbitrary Probabilistic Branch-sharing Ruta et al 2006; Brusatte et al 2008
- 43. τ7 τ8 τ6 τ5 Traditional approach first Ruta et al. 2006; Brusatte et al. 2008 Branch-sharing (“equal”)
- 44. τ7 τ8 τ6 τ5 root age τ7 τ6 τ5 Traditional approach first Share time with preceding (non-zero length) branch Ruta et al. 2006; Brusatte et al. 2008 τ8 Branch-sharing (“equal”)
- 45. τ6 τ5 τ4 τ2 τ1 τ3 Hedman 2010; Lloyd and Friedman in prep τ0 Probabilistic time-scaling
- 46. τ0 τ6 τ5 τ4 τ2 τ1 τ3 Age (Ma) τ0 Probabilistic time-scaling Hedman 2010; Lloyd and Friedman in prep
- 56. Conclusions
- 57. Conclusions
- 58. Conclusions
- 59. Conclusions
- 60. Conclusions