paleobuddy is an R package to simulate species
diversification, fossil records, and phylogenetic trees. While the
literature on species birth-death simulators is extensive, including
important software like paleotree and APE, we concluded there were
interesting gaps to be filled regarding possible diversification
scenarios. Differently from most simulators in the field, we strove for
flexibility over focus, implementing a large array of regimens for users
to experiment with and combine, and structuring the package on a general
framework to allow for straightforward expansion of available scenarios.
In this way, paleobuddy can be used as a complement to
other simulators or, in the case of scenarios implemented only here, can
allow for robust and easy simulations for novel scenarios.
You can install the released version of paleobuddy from CRAN with:
install.packages("paleobuddy")And the development version from GitHub with:
library(devtools)
devtools::install_github("brpetrucci/paleobuddy")We run a simple birth-death simulation as follows
set.seed(1)
n0 <- 1 # initial number of species
lambda <- 0.1 # speciation rate
mu <- 0.05 # extinction rate
tMax <- 30 # maximum simulation time
# run simulation
sim <- bd.sim(n0, lambda, mu, tMax)We can then generate fossil records, and visualize the results
set.seed(1)
rho <- 1 # sampling rate
bins <- seq(tMax, 0, -1) # something to simulate geologic intervals
# get a data frame with fossil occurrence times
fossils <- sample.clade(sim = sim, rho = rho, tMax = tMax, bins = bins)
# visualize simulation and fossil occurrences
draw.sim(sim, fossils = fossils)
And generate phylogenies as well
phy <- make.phylo(sim) # make a phylogenetic tree with the simulated group
ape::plot.phylo(phy, root.edge = TRUE) # plot it with a stem (requires APE)
ape::axisPhylo() # add axis
bd.sim is the birth-death simulation function, allowing
for multiple arguments to build a large number of possible scenarios.
One can supply constant or time-dependent speciation rate
lambda and extinction rate mu. On top of the
base rates, we allow for a shape parameter for each, if one
chooses to interpret lambda and mu as scales
of a Weibull distribution for age-dependent diversification. We take the
novel step allowing for time-dependent scale and shape as well. One can
also supply an env parameter to make rates dependent on a
time-series, such as temperature. These can all be combined as the user
wishes, creating a myriad of possible scenarios.
sample.clade generates fossil records, returning an
organized data frame with occurrence times - or occurrence time ranges,
provided the user supplies the respective interval vector. It allows for
a sampling rate rho that can be as flexible as
lambda and mu above, with the exception of a
shape parameter, since we omitted that option given the
absence of the use of Weibull distributions to model age-dependent
fossil sampling in the literature. Instead, we allow for the user to
supply a function they wish to use as age-dependent sampling,
adFun, such as the PERT distribution used in PyRate.
bd.sim.traits and sample.clade.traits work
similarly to bd.sim and sample.clade, but on
the context of state-dependent diversification, in particular using the
MuSSE model.
make.phylo closes the trio of most important functions
of the package, taking a paleobuddy simulation and
returning a phylo object from the APE package (see
above).
draw.sim allows for easy visualization of birth-death
simulation objects, drawing species’ durations and kinship, besides
allowing for the addition of fossil occurrences as well.
Besides its main simulating and visualization functions,
paleobuddy also supplies the user with a few interesting
statistical tools, such as rexp.var, a generalization of
the rexp function in base R that allows for time-varying
exponential rates and a shape parameter, in which case it
generalizes the rweibull function.
Given the possibility of functions in paleobuddy to use
environmentally-dependent rates, we have included with the package data
frames containing environmental data, namely temperature
(temp) and co2 (co2). These have been modified
from data on RPANDA (RPANDA: Morlon H. et al (2016) RPANDA: an R package
for macroevolutionary analyses on phylogenetic trees. Methods in Ecology
and Evolution 7: 589-597). To see more about the origin of the data, see
?data, where data is the data frame’s
name.
paleobuddy was idealized by Bruno do Rosario Petrucci
and Tiago Bosisio Quental. The birth-death, statistical, and part of the
sampling functions were written by Bruno. The phylogeny and most of the
sampling functions were written by Matheus Januário.