Simulate Cladogenetic Trait Evolution
This function simulates trait evolution at each speciation/branching event
in a matrix output from
simFossilRecord, after transformation with
cladogeneticTraitCont(taxa, rate = 1, meanChange = 0, rootTrait = 0)
A five-column matrix of taxonomic data, as output by
rate of trait change; variance of evolutionary change distribution per speciation event
Mean change per speciation event. Default is 0; change to simulate 'active' speciational trends, where the expected change at each speciational event is non-zero.
The trait value of the first taxon in the dataset; set to 0 by default.
This function simulates continuous trait evolution where change occurs under
a Brownian model, but only at events that create new distinct morphotaxa
(i.e. species as recognized in the fossil record), either branching events
or anagenesis (pseudospeciation). These are the types of morphological
differentiation which can be simulated in the function
is sometimes referred to as cladogenetic or speciation trait evolution and
is related to Puncuated Equilibrium theory. Anagenestic shifts aren't
cladogenetic events per se (no branching!), so perhaps the best way to this
of this function is it allows traits to change anytime
a new 'morphotaxon' in a simulation.
Importantly, trait changes only occur at the base of 'new' species, thus allowing cladogenetic trait evolution to be asymmetrical at branching points: i.e. only one branch actually changes position in trait-space, as expected under a budding cladogenesis model. This distinction is important as converting the taxa matrix to a phylogeny and simulating the trait changes under a 'speciational' tree-transformation would assume that divergence occurred on both daughter lineages at each node. (This has been the standard approach for simulating cladogenetic trait change on trees).
Cryptic taxa generated with
simFossilRecord will not differ at
all in trait values. These species will all be identical.
See this link for additional details: http://nemagraptus.blogspot.com/2012/03/simulating-budding-cladogenetictrait.html
Retuns a vector of trait values for each taxon, with value names being the taxa IDs (column 1 of the input) with a 't' pasted (as with rtree in the ape library).
David W. Bapst
This function is similar to Brownian motion simulation functions such as
rTraitCont in ape,
sim.char in geiger and
unitLengthTree in this package and
speciationalTree in the package geiger. These are tree transformation
functions; together with BM simulation functions, they would be expected to
have a similar effect as this function (when cladogenesis is 'bifurcating'
and not 'budding'; see above).
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set.seed(444) record<-simFossilRecord(p=0.1, q=0.1, nruns=1, nTotalTaxa=c(30,1000), plot=TRUE) taxa<-fossilRecord2fossilTaxa(record) trait <- cladogeneticTraitCont(taxa) tree <- taxa2phylo(taxa) plotTraitgram(trait,tree,conf.int=FALSE) #with cryptic speciation record<-simFossilRecord(p=0.1, q=0.1, prop.cryptic=0.5, nruns=1, nTotalTaxa=c(30,1000), plot=TRUE) taxa<-fossilRecord2fossilTaxa(record) trait <- cladogeneticTraitCont(taxa) tree <- taxa2phylo(taxa) plotTraitgram(trait,tree,conf.int=FALSE)
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