This is the first release of paleobuddy
, an R package dedicated to
flexible simulations of diversification, fossil records, and
phylogenetic trees. Below we list current features, and above sections
will be filled as new features and fixes are implemented.
rexp.var
generalizesrexp
to take any function of time as a rate. Also allows for ashape
parameter, in which case it similarly generalizesrweibull
.bd.sim
simulates species diversification with high flexibility in allowed speciation and extinction rate scenarios. Produces asim
object.sample.clade
simulates fossil sampling. Similar flexibility tobd.sim
, though even more so in the case of age-dependent rates.make.phylo
creates a bifurcating phylogenetic tree as aphylo
object (see APE) from asim
object. Can take fossils to be added as length0
branches.draw.sim
plots asim
by drawing species durations and relationships, and optionally adding fossils as time points or ranges.
find.lineages
creates subsets of asim
defined as the clades descended from one or more species present in the simulation. Needed to e.g. generate phylogenetic trees from simulations with more than one starting species.make.rate
creates a purely time-dependent (or constant) rate based on optional inputs. Used internally to allow for users to define rate scenarios easily inbd.sim
.phylo.to.sim
creates asim
object from aphylo
object, provided the user makes choices to solve ambiguities on bifurcating phylogenetic trees.var.rate.div
calculates expected diversity for a given diversification rate and set of times. Useful for testingbd.sim
and planning rate scenarios.
sim
a class returned bybd.sim
and used as an input for many functions in the package. Formally, it is a named list of vectors recording speciation time, extinction time, status (extant or extinct), and parent information for each lineage in the simulation. It contains the following methods: **print
gives some quick details about number of extant and total species, and the first few members of each vector. **head
andtail
return thesim
object containing only a given number of species from the beginning and end of its vectors, respectively. **summary
gives quantitative details, e.g. quantiles of durations and speciation waiting times. **plot
plots lineages through time (LTT) plots for births, deaths, and diversity. **sim.counts
counts numbers of births, deaths, and diversity for some given timet
. **is.sim
checks the object is a validsim
object. Used internally for error checking.
temp
temperature data during the Cenozoic. Modified from RPANDA.co2
CO2 data during the Jurassic. Modified from RPANDA.
overview
gives a reasonably in depth look at the main features of the package, including examples of workflows using most available rate scenarios, and examples of applications.
The question of how to structure time came up a lot during development
of the package. Most of the literature in macroevolution and
paleontology considers absolute geological time, i.e. t = 0
at the
present and t = 5
five million years ago. It becomes challenging,
however, to visualize and program complex rates going backwards. As
such, the code is structured such that all functions are considered to
go from 0
to the maximum simulation time tMax
—i.e. the inverse of
absolute geological time. There is only one exception to this rule, the
adFun
parameter describing age-dependent distribution of fossil
occurrences in sample.clade
. In any case, all returned objects in the
package are set to follow absolute geological time, so as to conform to
the literature.
-
The
integrate
function occasionally fails when given functions that vary suddenly and rashly, usually happening in the case of environmentally-dependent rates. I have tracked this error down to numerical problems inintegrate
, and testing seems to indicate the error does not preventintegrate
from finding the correct result. As such this is not currently something I intend to fix, though if issues are found that indicate this could be apaleobuddy
problem, not anintegrate
problem, that could change. -
paleobuddy
is the first package to implement time-dependent parameters for Weibull-distributed waiting times. Since the authors currently are not aware of an analytical solution to important quantities in the BD process in this case, it is challenging to test exactly. Simulation tests indicate pretty strongly that the algorithm works, however, with one exception—in cases where shape is time-dependent and varies dramatically, especially when close to0
,rexp.var
seems to have a hard time finding the correct waiting time distribution. When maintained within levels generally accepted as sensible throughout the literature—around 0.8 to 3, say—, and even a reasonable amount outside of that range, tests indicate the algorithm functions as it should. Atestthat
routine will be implemented in the future to formalize these claims, and this issue is one I plan to work on soon, especially if users report it as more prevalent than I thought.