modelling speciation with incipient species
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README.md

#protractedbirthdeath

Travis-CI Build Status

##modelling speciation with incipient species

This library uses a modification of the PBD package by Etienne and Rosindell (2014) allowing for 0s as parameters, and extinction. It also treats "orphaned" incipient species in a more intelligent way. There are also new function for analysis of the outputs.

Output from this work published as:

Cutter AD, Gray JC. Ephemeral ecological speciation and the latitudinal biodiversity gradient. Evolution 2016;70(10):2171–2185. doi: 10.1111/evo.13030.

The main core of the project is now a package. To install, run:

# install.packages("devtools")
devtools::install_github("jeremycg/protractedbirthdeath/protractedbirthdeath")

##Examples

The main part of the package lies in the pbdsim2 function. Output is a list, parse it (and run multiple repeats) using repsim2

library(protractedbirthdeath)
run<-pbdsim2(c(0.7,0.7,0.7,0.1,0.1),15)
runs<-repsim2(c(0.7,0.7,0.7,0.1,0.1),5,15)

pars[1] is good speciation rate

pars[2] is speciation completion rate

pars[3] is incipient speciation rate

pars[4] is good extinction rate

pars[5] is incipient extinction rate

the following numbers are repeats and time (defaulted to 15 million years)

pbdsim2 has a limit on numbers of species at 100000. this can be altered in the code.

summaryrepsim will take means and sem of repeats. Plotsim will make a plot of these summaries.

summary1<-summaryrepsim(c(0.7,0.7,0.7,0.1,0.1),5,15)
plotsim(summary1)

##Shiny

A cut down shiny app is in the package as a function:

#library(protractectedbirthdeath)
pbdshiny()

This should popup a shiny app which will run the simulations. Large numbers of species can take a long time! The first two tabs are responsive to the sliders on the side.

  1. on the fly:giving an output of means and sds of taxa numbers based on 15 repeats
  2. phylograms:a tree based on the evolutionary history
  3. Tau - the tau parameter based on the given parameters

The package began life as a shiny app, and this is still extant. This has functions built in to view batch run data for summary stats that the function misses. You will need to have the (large!) simulation output files.

To run, simply download the exampledata folder, install and load shiny

#install.packages(shiny)
library(shiny)
runGitHub("protractedbirthdeath","jeremycg",subdir="shiny")

The r function choose.dir() is currently windows only - you can manually modify the source to your directory.

Output is in multiple tabs - first tab reads from the example data and plots previous data, second does the same but on the fly - some parameter choices might take a long time. Third tab gives boxplots of number of species at t=0 for differing single parameters. Fourth draws two trees based on the inputs from the sliders Fifth gives contour plots of number of species, based on three fixed variables, and two to plot. This won't work with example data Sixth is tau - mean time to speciation again based on contour plots.