Testing relationships between multiple regional features and biogeographic processes of speciation, extinction, and dispersal

This dataset is associated with Swiston & Landis 2023 (https://doi.org/10.1101/2023.06.19.545613). It contains two major elements. First is a simulation study performed using R and RevBayes associated with the validation of the MultiFIG model. Here, we provide simulated regional feature values, simulated phylogenetic trees and present-day species ranges, and output from analyses with the MultiFIG model. Second is an empirical analysis of the Liolaemus genus under the MultiFIG model. We also provide figures and supplemental figures associated with the manuscript.

Description of the data and file structure

Overview: The code .zip file contains all of the scripts necessary for generating and analyzing simulations for the simulation study (sim), running the empirical analysis of Liolaemus (emp), and plotting the results of both analyses (plotting). The data .zip file contains all of the simulated datasets for the simulation study in sim and empirical dataset for the analysis of Liolaemus in emp. The output .zip file contains all of the unprocessed and processed output from the simulation analyses (sim) and empirical analysis (emp), as well as all plots and supplemental figures from the associated manuscript (plots).

• code Contains R and RevBayes code for MultiFIG simulation study and empirical analysis of Liolaemus, as well as plotting scripts.
  • sim Contains scripts for generating and analyzing simulated datasets under the MultiFIG model
  • batchsim.sh Shell script for submitting simulations using an LSF job scheduler (not required if simulating locally)
  • sim.sh Shell script that calls separate scripts for simulating geographies and trees under the MultiFIG model
  • geosim.R R Script for simulating "geographies", generating .csv data files in data/sim/geo representing simulated regional features and feature summaries
  • sim.Rev RevBayes script for generating phylogenetic trees, tip states, and model parameters in data/sim/history according to the MultiFIG model (based on simulated geographies)
  • batchinf.sh Shell script for submitting inference jobs on simulated datasets using an LSF job schedule (not required if performing inference locally)
  • inf.sh Shell script that calls inf.Rev on simulated datasets
  • inf.Rev RevBayes script for performing inference on simulated datasets under the MultiFIG model
  • emp Contains RevBayes scripts for performing an analysis of Liolaemus under the MultiFIG model
  • batchinf.sh Shell script for submitting inference jobs on Liolaemus dataset using an LSF job scheduler (not required if performing analysis locally)
  • inf.sh Shell script that calls inf.Rev on Liolaemus dataset
  • inf.Rev RevBayes script for performing inference on Liolaemus dataset under the MultiFIG model
  • plotting Contains R scripts for plotting results of simulation study and empirical analysis of Liolaemus
  • cov_plots.R R script for generating coverage plots and coverage table associated with the simulation study
  • joint_plots.R R script for generating joint posterior plots associated with the analysis of Liolaemus
  • posterior_plots.R R script for generating plots of Bayesian posteriors associated with the analysis of Liolaemus
  • rj_sim_plots.R R script for plotting reversible jump results associated with the simulation study
  • state_plots.R R script for plotting the ancestral state reconstruction for Liolaemus
  • variance_plots.R R script for plotting the variance of the empirical features against the variances of the simulated features
• data Contains data for simulation study and empirical analysis of Liolaemus
  • sim Contains data associated with the simulation study
  • geo Contains data files for regional features over a set of simulated geographies, as well as summary files which describe the features used in each analysis (some analyses use different features in simulation versus inference)
    • The first element of the filename represents whether the analysis will be performed using reversible-jump (RJ) or without (NONRJ)
    • The second element of the filename represents the number of regions
    • The third element represents the experimental condition of the analysis (all 12 features are generated, but some are not used)
    • LESS: area & distance during simulation; area, distance, & altitude during inference
    • FULL: area, distance, & altitude during simulation; area, distance, & altitude during inference
    • MORE: area, distance, altitude, & temperature during simulation; area, distance, & altitude during inference
    • NOISY: area, distance, & taltitude (true altitude) during simulation; area, distance, & altitude during inference
    • The fourth element represents the tree size category: 25-49 = XSMALL, 50-99 = SMALL, 100-199 = MEDIUM, 200-349 LARGE (this information is not used in simulating geographies, but will be used in simulating trees)
    • The fifth element represents the index of the simulated geography (randomly assigned)
    • SIM_feature_summary.csv files contain a list of features to be used in the associated simulation
    • INF_feature_summary.csv files contain a list of features to be used in the associated inference
    • For all feature files:
    • The fifth element represents the type of data (c=categorical, q=quantitative, w=within-region, b=between-regions)
    • The sixth element is the geographical feature that the data represents: area, distance, altitude, true altitude, or temperature
    • Eg. 3.FULL.MEDIUM.1.cb_distance.csv uses 3 regions, will use the feature set "FULL" when simulating a "MEDIUM" tree, is the simulated geography indexed 1, and contains a matrix of categorical distances between regions -- adjacency matrix
  • history Contains data files for simulated trees, tip states, and model parameters
    • Eg. RJ.3.FULL.MEDIUM.1.tree.tre Contains a Newick-string representation of a dated phylogeny, simulated based on the 3-region geography indexed 1 using the feature set "FULL", and targeting a medium tree size, to be analyzed using reversible jump
    • Eg. RJ.3.FULL.MEDIUM.1.data.tsv Contains tip states corresponding to the RJ.3.FULL.MEDIUM.1 simulation
    • Eg. RJ.3.FULL.MEDIUM.1.param.txt Contains MultiFIG model parameters that produced the RJ.3.FULL.MEDIUM.1 simulation
  • emp Contains empirical dataset associated with Liolaemus and 6 South American regions (AA = Altiplanic Andes, CA = Central Andes, PA = Patagonia, CC = Central Chile, AD = Atacama Desert, EL = Eastern Lowland)
  • history Contains the empirical dataset relating to Liolaemus
    • liolaemidae.data.full.csv Contains information about each species in the family Liolaemidae (including the genus Liolaemus), such as presence/absence in different regions, as well as other species traits that are not used for the MultiFIG analysis -- data from Esquerré et al. 2019
    • make_dat.py A Python script for translating the data from liolaemidae.data.full.csv into data that is usable for the MultiFIG model (liolaemidae.data.table.tsv and ranges.data.tsv)
    • state_labels_n6.txt Relates binary presence/absence data to integer state numbers used by RevBayes for the MultiFIG analysis, used by the make_dat.py script
    • liolaemidae.data.table.tsv Contains present-day ranges of Liolaemus, representing presence in a region with (1) and absence with (0)
    • ranges.data.tsv Contains state numbers for present-day Liolaemus species
    • tree.mcc.tre Time-calibrated phylogeny of Liolaemus
  • geo Contains the empirical dataset relating to South America
    • shapefiles Contains shapefiles associated with the 6 regions used in the Liolaemus analysis, are not required for running the analysis
    • RJ.6.HL.LIOLAEMUS.feature_summary.csv Contains information about which features to use for the empirical analysis using highland/lowland classification
    • altitudes Contains regional features associated with altitude
    • andean_classification.csv Classifying regions as Andean or non-Andean
    • andean_sameness.csv Matrix describing whether regions share (1) or do not share (0) Andean classification
    • classification.csv Altitude classification of regions (1=high, 0=low)
    • mean.csv Mean altitudes of regions (m)
    • mean_diff.csv Differences in mean altitude between regions (m)
    • sameness.csv Matrix describing whether regions share (1) or do not share (0) altitude classification
    • sd.csv Standard deviation of altitudes of regions
    • areas Contains regional features associated with area
    • areas.csv Sizes of regions (km^2)
    • classification.csv Size classification of regions (1=large, 0=small)
    • distances Contains regional features associated with distance
    • mean.csv Mean distances between regions (km)
    • adjacency.csv Matrix of region adjacency
    • equal Contains vectors/matrices of equal features values for simplified analyses (removing feature effects)
    • Eg. q_equal_vector.csv A vector of equal feature values for simplified analysis -- in this case, a quantitative one-dimensional vector
• output Contains output of simulated and empirical analyses
  • sim Contians output of simulation study
  • output Output of simulation analyses (logfiles for model parameters)
  • data Summaries of output for each analysis (estimates and HPD intervals)
  • processed_data Contains large output file of the coverage analysis, coverages.csv
  • emp Contains output of empirical analysis of Liolaemus, including 6 file types: .ase.tre (ancestral state tree), .states.log (ancestral state trace), .stoch.log (stochastic mapping), .events.tsv (list of state transitions and cladogenetic events), .model_extras.log (by-region rates of biogeographic processes), and .model.log (logfile of model parameters)
  • concatenated.model.log Logfile of model parameters used for results in the manuscript; created by concatenating the output of analyses 8 and 9 (numbering was arbitrary), after removing burnin -- done to ensure sufficient number of generations
  • output Contains other output files associated with analyses 8 and 9, including the ancestral state reconstruction generated from analysis 9
• plots Contains plots associated with Swiston & Landis 2023 (https://doi.org/10.1101/2023.06.19.545613)

Sharing/Access information

Links to other publicly accessible locations of the data:

• https://bitbucket.org/sswiston/multifig/src/master/

Data was derived from the following sources:

• Esquerré, D., Brennan, I. G., Catullo, R. A., Torres-Pérez, F., & Keogh, J. S. (2019). How mountains shape biodiversity: The role of the Andes in biogeography, diversification, and reproductive biology in South America’s most species-rich lizard radiation (Squamata: Liolaemidae). Evolution; International Journal of Organic Evolution, 73(2), 214–230.
• NASA. (2013). Shuttle Radar Topography Mission (SRTM) Global [Data set]. https://doi.org/10.5069/G9445JDF
• Swiston, S. K., & Landis, M. J. (2023). Testing relationships between multiple regional features and biogeographic processes of speciation, extinction, and dispersal. BioRxiv. https://doi.org/10.1101/2023.06.19.545613

Code/Software

• The dataset contains .R files for generating simulated geographies and plotting output. These files were designed to be run using R version 4.4.0.
• The dataset also contains .Rev files for performing analyses in RevBayes. Correct versions of RevBayes and TensorPhylo can be found in Docker image sswiston/rb_tp:7 https://hub.docker.com/r/sswiston/rb_tp.

For a tutorial explaining the details of the MultiFIG analysis, visit https://revbayes.github.io/tutorials/multifig/.

Version Changes:

• 2024/07/22: Due to changes in RevBayes and TensorPhylo software, all scripts were overhauled, all analyses re-run, and all figures re-generated. New .zip files have been uploaded.