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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
@GraemeTLloyd Graeme T. Lloyd
@Friedman_LabMatt Friedman
Acknowledgements
Chris Organ Graham Slater
Questions
Questions
1. How can we measure rates of evolution in acontinuous character over multiple time bins?
Questions
2. How did the tempo of tetrapod mandibleevolution change over their early evolution?
1. How can we measure rates of evolution in acontinuous character over multiple time bins?
Questions
2. How did the tempo of tetrapod mandibleevolution change over their early evolution?
3. How does phylogenetic time-scalechoice affect patterns of tempo?
1. How can we measure rates of evolution in acontinuous character over multiple time bins?
How fast?
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate categories
Cloutier 1991; Lloyd et al. 2012; Lloyd submitted
Rate data types
Simpson 1944,1953; Westoll 1949
Rate data types
Simpson 1944,1953; Westoll 1949
Rate data types
Simpson 1944,1953; Westoll 1949
Rate data types
Simpson 1944,1953; Westoll 1949
Discrete data: disparity and tempo
Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
Discrete data: disparity and tempo
Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
Discrete data: disparity and tempo
Claddis
Davis et al. 2012; Lloyd et al. 2012; Lloyd submitted
Continuous data: mode dominates
Continuous data: mode dominates
Traitvalue
Time
Early Burst
Late BurstTrai
t
Time
Continuous data: mode dominates
Rate
Time
Continuous rates
Rate
Time
Continuous rates
Raia et al. 2013
Continuous rates
Harmon et al. 2008
New method: guts
New method: description
New method: description
New method: description
New method: description
S1 S2 S31
New method: description
Anderson et al. 2013
Data
Anderson et al. 2013
Data
Time-scaling trees
Lee et al 2014
Time-scaling trees: simultaneous
Time-scaling trees: a posteriori
paleotree
strap
Time-scaling trees: a posteriori
+
paleotree
strap
Time-scaling trees: a posteriori
+ =
paleotreestrap
Time-scaling trees: a posteriori
Arbitrary
Branch-sharingRuta et al 2006; Brusatte et al 2008
Arbitrary addition(s)Derstler 1982
Minimum branch-lengthLaurin 2004
Time-scaling trees: a posteriori
cal3Bapst 2013
Hedman methodLloyd and Friedman in prep
NowakNowak et al 2013
Arbitrary Probabilistic
Branch-sharingRuta et al 2006; Brusatte et al 2008
Arbitrary addition(s)Derstler 1982
Minimum branch-lengthLaurin 2004
Time-scaling trees: a posteriori
Hedman methodLloyd and Friedman in prep
Arbitrary Probabilistic
Branch-sharingRuta et al 2006; Brusatte et al 2008
τ7
τ8
τ6
τ5
Traditional approach first
Ruta et al. 2006; Brusatte et al. 2008
Branch-sharing (“equal”)
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”)
τ6
τ5
τ4
τ2
τ1
τ3
Hedman 2010; Lloyd and Friedman in prep
τ0
Probabilistic time-scaling
τ0
τ6
τ5
τ4
τ2
τ1
τ3
Age (Ma)
τ0
Probabilistic time-scaling
Hedman 2010; Lloyd and Friedman in prep
“Equal” time-tree
Probabilistic time-tree
“Equal”timetree
Results
“Equal”timetree
Results
“Equal” timetreeProbablistic timetree
Results
Results with error
Results with error
S1 S2
Two-tempo evolution
Slater 2013
BrownianOrnstein-Uhlenbeck
Two-mode evolution
Conclusions
Conclusions
Conclusions
Conclusions
Conclusions
