napc 2014 constraint and convergence on a graptoloid supertree
TRANSCRIPT
NAPC 2014
David W. Bapst (SDSMT, UC Davis) & Charles E. Mitchell (SUNY Buffalo)
Functional Constraint in Graptoloid Morphology?
Figures from Bulman, 1970; Mitchell, 1990; Maletz et al., 2009; etc.
Using Phylogeny to Test for Constraints
Convergent traits give opportunity to study biotic and abiotic drivers of trait acquisition across clades
Convergence alone indicates potential
…but isn’t evidence of ecomorph.function or other constraints
Randomly evolving traits will converge
Simulate characters on the phylogeny
Test how often some aspect of the observed data occurs in simulationsWagner and
Erwin, 2006
Major Features Primary Stipe Number
Many, 4, 2, 1.5, 1
Scandency Not Scandent, Partly, Scandent
Reduced Periderm
Extrathecal Threads
Determinant Growth
Cladia
Figures from Bulman, 1970; Mitchell, 1990; Maletz et al., 2009; etc.
GraptoloidPhylogenetics
3D preservation provides detailed characters for cladistics
…but only some taxa: ~49% of genera are on published cladograms
Missing lots of unique colony morphologies
Informal Supertreeof 117 Genera
Trees from:Maletz et al., 2009 Mitchell et al., 2007 Storch et al., 2011Melchin et al., 2011Bates et al., 2005
Adding extra taxa to cladistic ‘skeleton’
Summarize our current knowledge of relationships using all types of evidence
Hierarchical placing of unanalyzed taxa
First, synapomorphies in cladistic analyses
If not, most recent taxonomic placement
Inclusive Summary of Relationships among 245 Graptoloid Genera
The under-analyzed Monograptidae: one single polytomy
Poorly preserved early graptoloids: mostly unresolved
Use soft polytomies (multifurcating nodes) for uncertainty in morphology or taxonomy
Character Analyses Minimum number of gains and losses: How much convergence?
Parsimony ancestral trait reconstruction
Resolve polytomies to minimize character gains under parsimony
Simulation Analyses of constraint
Simulate character evolution on observed phylogeny (randomly-resolved)
Use estimated transition matrices for each trait (assuming indep evolving)
…but no time-scaling?
Character Analyses Minimum number of gains and losses: How much convergence?
Parsimony ancestral trait reconstruction
Resolve polytomies to minimize character gains under parsimony
Simulation Analyses of constraint
Simulate character evolution on observed phylogeny (randomly-resolved)
Use estimated transition matrices for each trait (assuming indep evolving)
…but no time-scaling? Really?
Character Analyses Minimum number of gains and losses: How much convergence?
Parsimony ancestral trait reconstruction
Resolve polytomies to minimize character gains under parsimony
Simulation Analyses of constraint
Simulate character evolution on observed phylogeny (randomly-resolved)
Use estimated transition matrices for each trait (assuming indep evolving)
Analyzing Not Time-scaled Trees
# of character changes / evolutionary ‘length’ per branch: minimal reversals
Are we willing to assume relatively uniform sampling of taxa, nodes
Minimum Number of Transitions Polytomies resolved to minimize
number of character transitions
Minimally, many indep ‘gains’ to derived states with few reversals
High evolvability?
Lack of reversals an indicator of species sorting for some traits?
‘Gains’ Reversals
# of Primary Stipes 15 0
Scandency 6 4
Reduced Periderm 6 0
Extrathecal Threads 3 0
Determinant Growth 6 0
Cladia 3 0 (Sort of a reversal for stipe #)
Relative to Primitive State:
Nonrandom Associations Between Characters Imbalance of by-genus
contingency table for pairs of discrete traits (Cramer’s V)
Proportion of simulations with imbalance as high or higher than observed value
Some traits aren’t evolving independent of each other
# of stipes and scandency
Extrathecal threads with red. periderm and det. growth
Constraints on trait change?
ScandencyReduced Periderm
Extrathecal Threads
Determinant Growth
Cladia
# of Primary Stipes 0.03 0.23 0.14 0.55 0.19
Scandency - 0.32 0.09 0.39 0.81Reduced Periderm - - < 0.01 0.15 0.25
ExtrathecalThreads - - - 0.03 0.34
Determinant Growth - - - - 0.4
But are these ecomorphological constraints?
W&E ‘06: Paleozoic gastropod taxa distributed among fewer morphotypesthan in simulations
Even when the number of potential char combos in simulation limited to the
observed # of combos
Implies ecomorpologicalconstraints, not ‘biotic’ architectural constraints
Observed
Wagner and Erwin (2006)
Ecomorphological Constraint on Graptoloids?
Using same traits except treating cladia as a return to many-stipes…
Observed frequencies are slightly higher than simulations without constraining the number of character combinations
95% Quantile
Ecomorphological Constraint on Graptoloids But when we constrain simulations to
observed number of combinations…
Simulations match observed frequency distribution almost perfectly
I.e., the distribution of taxa among combinations of these traits is closely predicted by a null model where some morphologies are simply unavailable …But not rejecting null ≠ accepting null
95% Quantile
Conclusions Large scale summaries of what we think we know about
relationships in a group can be useful, if we adequately explore phylogenetic uncertainty in our analyses
Derived states of these major morph innovations in graptoloids were repeatedly ‘gained’ independently, implying evolvability
Rarely reverse back… may reflect species sorting (for some)
We can reject these characters evolve independently
But based on the obs frequency of morphotypes, we can’t reject that convergence are due to intrinsic biotic constraints such as construnctional or developmental factors
Thanks to M. Foote, P. Smits, M. Pennell, E. King for useful discussions.
Characters Tied Across Branches…? Sets of traits ( ) seem to repeat in
certain clades … but not always in the same taxon in those clades
Some invisible ‘predictor’ trait?
Use mean patristic distance of taxon with one character to closest relative with other trait
Only works for binary traits
Proportion of simulations with low or lower mean pairwise patristic distance than observed
Extrathecal Threads
Determinant Growth
Cladia
Reduced Periderm < 0.01 0.09 0.31
Extrathecal Threads - 0.16 0.33
Determinant Growth - - 0.32
GlossograptidsCorynoides
Cryptograptus
RetiolitidsSpinograptus
Hard to reject null?
Informing Our Functional Morphology Analyses
Use physics to test a supposed function for morphology
Can test that X could do function Y
Cannot test whether X had any function
Need to start with a carefully chosen specific hypothesis of a specific function
Larger patterns of evolution can be useful for informing what we should investigate
Cladia-like abnormal Amplexograptus latus