Data and Code: Aridification and habitat shifts drove diversification in Australian diplodactylid geckos

Data and Code for: Aridification and habitat shifts drove diversification in Australian diplodactylid geckos Authors: Sarin Tiatragul1; Ian G. Brennan1; Alexander Skeels1; Damien Esquerré2; Stephen M. Zozaya1; J. Scott Keogh1; Mitzy Pepper1 Affiliation: Authors: Sarin Tiatragul1; Ian G. Brennan1,2; Alexander Skeels1; Damien Esquerré3; Stephen M. Zozaya1; J. Scott Keogh1; Mitzy Pepper1 1Division of Ecology & Evolution, Research School of Biology, The Australian National University, Canberra, ACT, 2601 Australia 2Biodiversity and Geosciences; Queensland Museum; PO Box 3300; South Brisbane BC; Queensland 4101; Australia 3Environmental Futures Research Centre, School of Science, University of Wollongong, Wollongong, NSW 2500, Australia Overview This repository contains data and analysis scripts associated with a phylogenomic and macroevolutionary study of Australian diplodactylid geckos (family Diplodactylidae). Using ~5,000 nuclear loci from 276 taxa, we reconstructed the evolutionary history of the group, estimated ancestral biome occupancy, modeled state-dependent diversification, and examined morphological evolution across habitat types. Raw genomic data: Sequence reads are available from the Bioplatforms Australia Data Portal (https://data.bioplatforms.com/organization/ausarg). Alignments and gene trees are included in this archive (alignments.zip and gene_trees.zip). Analysis scripts are archived on Zenodo. Setup Download all archive files from Dryad into a single folder. Rename the folder to diplo-phylo (e.g., ~/diplo-phylo/). All scripts use setwd("~/diplo-phylo/") as the working directory root. Extract all zip archives into the project root: unzip code.zip # → code/ (all analysis scripts + helper functions) unzip data.zip # → data/ (analysis inputs) unzip v4_out.zip # → v4_out/ (wASTRAL tree + gene trees) unzip alignments.zip -d alignments/ # → alignments/ (5,375 .fas files) unzip gene_trees.zip -d gene_trees/ # → gene_trees/ (5,375 .contree files) unzip dating.zip # → dating/ (README only; see note inside) unzip phylogeny.zip # → phylogeny/ (README only; see note inside) The ExtendedData/ folder is included as-is (no zip) and contains supplementary result files cited in the manuscript. It does not need to be extracted. Install required R packages (see Software Requirements below). Run scripts in numbered order from the code/ directory. Note: Scripts prefixed 00_ are data-preparation scripts that may require external inputs (raw genomic data, ALA downloads, AusARG metadata). They are included for transparency. The core analysis scripts (01_ through 05_) can be run directly from the provided data files. The dating/ and phylogeny/ directories contain only a README_placeholder.txt explaining what external genomic data belongs there and how to obtain it. The v4_out/ directory contains the wASTRAL species tree and concatenated gene trees; its README_placeholder.txt lists which additional IQ-TREE 2 outputs are still required. Contents Extended Data (ExtendedData/) These files are supplementary results cited in the manuscript and supplement as Extended Data figures and tables. They are not used as inputs to any analysis script — they are final outputs provided for transparency and citation. File Description ExtendedData/ED01_sampling_summary.csv Taxon sampling list — all 276 taxa, locus counts, geographic origin, MCMCTree inclusion (Extended Data 01) ExtendedData/ED02_occurrence_data.csv Curated occurrence records for Australian diplodactylids (Extended Data 02) ExtendedData/ED03_diplo_morpho_traits.csv Raw morphological measurements for 19 traits across all specimens (Extended Data 03) ExtendedData/ED04_gcf_scf_qcf_5k_annotated.nex gCF/sCF/qCF concordance-annotated species tree in NEXUS format (Extended Data 04) ExtendedData/ED05_concordance_vectors.csv Branch-specific concordance vectors for all nodes (Extended Data 05) ExtendedData/ED05_concordance_vectors_5k_subset.csv Concordance vectors for the 5k-locus subset (Extended Data 05) ExtendedData/ED06_node_state_probabilities_3state.csv BioGeoBEARS DEC node state probabilities — 3-state biome classification (Extended Data 06) ExtendedData/ED06_node_state_probabilities_allstates.csv BioGeoBEARS DEC node state probabilities — 11-state Köppen-Geiger classification (Extended Data 06) Data files (data/) All files required to run analysis scripts 01_ through 05_ are in the data/ subdirectory. Extract from data.zip. File Description data/Diplo_mcmctree_v4.tre Time-calibrated species-level phylogeny from MCMCTree (AHE + UCE combined) data/diplo_mcmctree_genera.tre Time-calibrated genus-level phylogeny from MCMCTree (6 fossil calibrations) data/diplo_mcmctree_genera_FigTree.tre Genus-level MCMCTree output with node annotations (HPD bars; FigTree format) data/gcf_scf_qcf_5K.nex Full concordance vector annotated tree (Newick + annotations) data/gcf_scf_qcf_5k_rerooted.nex wASTRAL species tree rerooted on outgroup for concordance factor plotting data/diplo_aus_habitats_v3.csv Ecological state assignments (open terrestrial / arboreal / saxicolous) for all species data/diplo_morpho_traits.csv Processed morphological trait data (species means, log shape ratios) used by analysis scripts data/diplo_metadata_v4.csv Sample metadata (v4): specimen IDs, easy labels, MCMCTree labels, subset flags data/interpolated_Li_etal_2022_Scotese_DEM_climate_curves_highres.csv Paleoclimate curves at high resolution (MAT, MAP, AI, WMMT; 0–50 Ma) data/interpolated_Li_etal_2022_Scotese_DEM_climate_curves_lowres.csv Paleoclimate curves at low resolution (same variables; used for RPANDA models) data/diplodactylidae_biogeographic_simmaps_time_stratified_DECxn_3state.rds 50 BioGeoBEARS stochastic biogeographic maps (3-state: tropical/arid/temperate) data/diplodactylidae_biogeographic_simmaps_time_stratified_DECxn_allstates.rds 50 BioGeoBEARS stochastic biogeographic maps (11-state Köppen-Geiger) data/allstates_cols.rds Named colour vector for 3-state biogeographic plotting data/allstates_cols_allstates.rds Named colour vector for 11-state biogeographic plotting data/diplo_Data.Rdata Processed R data object: time-calibrated tree, morphological traits, and ecological data combined data/MuHiSSE_results.Rdata All fitted MuHiSSE/MuSSE/CID model objects from state-dependent diversification analysis data/sp_AHE_UCE_combined_mcmc.txt Species-level MCMC posterior samples from MCMCTree (138 MB; used for divergence time density plots) data/mcmc_GC_combine.txt Genus-level combined MCMC chains (21 MB; used for Skew-T calibration fitting) code.zip All analysis scripts (code/) and helper functions (code/func/). Extract with unzip code.zip. data.zip All files in the data/ directory including data/script_generated/. Extract with unzip data.zip to restore the full data/ structure. v4_out.zip wASTRAL species tree (aster/Dip_wASTRAL_v4.tre) and concatenated gene trees (merge/AllLoci.trees); plus README_placeholder.txt listing additional IQ-TREE 2 outputs required for 00_concordance_vector.R. Extract with unzip v4_out.zip. alignments.zip TAPER-processed AHE + UCE locus alignments (5,375 loci; FASTA format). Extract with unzip alignments.zip -d alignments/. gene_trees.zip Per-locus maximum likelihood consensus trees from IQ-TREE 2 v2.2.6 (5,375 .contree files; Newick format). Extract with unzip gene_trees.zip -d gene_trees/. dating.zip Placeholder directory with README_placeholder.txt describing MCMCTree input files not included (raw genomic data). Extract with unzip dating.zip. phylogeny.zip Placeholder directory with README_placeholder.txt describing phylogenomic pipeline outputs not included (raw genomic data). Extract with unzip phylogeny.zip. Not included (require external sources): - data/koppen_Beck/ — Köppen-Geiger raster (Beck et al. 2018); download from https://doi.org/10.1038/sdata.2018.214 - v4_out/cf/ — IQ-TREE 2 concordance factor stat files; generated by running IQ-TREE 2 v2.3.6 against v4_out/aster/Dip_wASTRAL_v4.tre and v4_out/merge/AllLoci.trees (see v4_out/README_placeholder.txt) Data File Descriptions Extended Data files (ExtendedData/) ED01_sampling_summary.csv Sample-level metadata for all 276 taxa including Australian diplodactylids (n=190 individuals, 108 spp.), New Caledonian (n=31 spp.), and Aotearoa New Zealand (n=18 spp.) taxa. Columns: specimen ID, genus, species, geographic region, locus count, subset used for divergence time estimation (yes/no). Generated by code/04_sampling_summary.R. ED02_occurrence_data.csv Curated occurrence records for Australian diplodactylids downloaded from the Atlas of Living Australia (ALA) using the galah R package (v.2.1.2), supplemented with data from the primary literature. Records were visually inspected and corrected to reflect current taxonomy. Only specimen-based records (no human observations) with valid coordinates were retained. Columns include: recordID, scientificName, decimalLatitude, decimalLongitude, catalogNumber, institutionCode. ED03_diplo_morpho_traits.csv Raw linear morphological measurements (mm) for 19 traits across all Diplodactylidae specimens with original (non-regenerated) tails. Traits measured with digital calipers to the nearest 0.5 mm following Brennan et al. (2024). Includes: snout-vent length, head length/width/depth, neck length, body width, limb segment lengths (upper/lower arm and leg), interlimb length, tail length, tail width, geometric mean of size. Also includes log shape ratios (each trait divided by geometric mean and log-transformed) and specimen/species metadata. ED04_gcf_scf_qcf_5k_annotated.nex wASTRAL species tree with concordance factors annotated as node labels. Gene concordance factors (gCF), site concordance factors (sCF using -scfl option), and quartet concordance factors (qCF) were computed using IQ-TREE 2 v2.3.6. NEXUS format compatible with FigTree and phytools. ED05_concordance_vectors.csv / ED05_concordance_vectors_5k_subset.csv Branch-specific concordance vectors for all nodes in the species tree. Each row gives the gCF, sCF, and qCF values for one branch, along with the number of decisive gene trees. The 5k_subset file covers the subset of loci used in the parsimony-informative site analysis. Generated by code/00_concordance_vector.R. ED06_node_state_probabilities_3state.csv / ED06_node_state_probabilities_allstates.csv BioGeoBEARS DEC model marginal state probabilities at all internal nodes. The 3state file uses the simplified tropical/arid/temperate biome classification; allstates uses the full 11-state Köppen-Geiger system. Each row is a node; columns give the probability of each geographic state. Analysis input files (data/) Diplo_mcmctree_v4.tre Time-calibrated species-level phylogeny estimated in MCMCTree (PAML v4.9) using four partitioned AHE datasets (GeneClumps 1–4, codon positions 1+2) and one unpartitioned UCE dataset. Topology fixed to the wASTRAL tree. Calibrated with 5 fossil constraints and 13 Skew-T secondary calibrations derived from the genus-level analysis. 4 independent MCMC runs combined with LogCombiner; tree represents the combined posterior. FigTree format with HPD node bars. diplo_metadata_v4.csv Sample metadata table (version 4) used to match specimen file names to display labels across analysis scripts. Columns: file.name, easy_label, mcmctree_labels, genus, species, region, subset (y/n for MCMCTree inclusion), and additional metadata fields. diplo_morpho_traits.csv Processed morphological data table with species-level mean trait values and log shape ratios, derived from the raw measurements in ExtendedData/ED03_diplo_morpho_traits.csv. Used as direct input for 01_morpho_trait.R and 02_morpho_trait_viz.R. sp_AHE_UCE_combined_mcmc.txt Combined MCMC posterior samples (4 chains) from the species-level MCMCTree analysis (138 MB). Tab-delimited with columns for generation number and per-node divergence times. Used to compute and visualize node age uncertainty (HPD intervals) in 01_mcmctree_results.R and 01_concordance_factor_plot.R. mcmc_GC_combine.txt Combined MCMC posterior samples from the genus-level MCMCTree analysis (21 MB). Used in 00_Fit_skewT_priors.R to fit Skew-T secondary calibrations for the species-level analysis. allstates_cols.rds / allstates_cols_allstates.rds Named R vectors mapping biogeographic state labels to colours for plot consistency across 02_bgb_results.R, 02_physig_morphospace.R, and 03_anc_state.R. The allstates version covers all 11 Köppen-Geiger states; the base version covers the 3-state classification. diplo_aus_habitats_v3.csv Ecological state assignments for all diplodactylid species. Primary ecological states: ground (open terrestrial), rock (saxicolous), tree (arboreal), spinifex. These were consolidated into three broad states for diversification analyses: open (ground + spinifex), arboreal (tree), saxicolous (rock). Based on literature review, museum records, and field observations. interpolated_Li_etal_2022_Scotese_DEM_climate_curves_highres.csv Paleoclimate curves for Australia and globally from 0–50 Ma at high temporal resolution. Variables: mean annual temperature (MAT), warmest mean monthly temperature (WMMT), mean annual precipitation (MAP), aridity index (AI). Derived from general circulation model (GCM) climatology downscaled to high resolution using CHELSA; based on Scotese DEM paleogeographic reconstructions. Used to define BioGeoBEARS time-stratification dispersal weights. Original data: Li et al. (2022); interpolation: A. Skeels. diplodactylidae_biogeographic_simmaps_*.rds {#diplodactylidae_biogeographic_simmaps_rds } R list objects (50 elements each) containing stochastic biogeographic maps generated from 50 draws of the BioGeoBEARS DEC model posterior. Each element is a phytools-format simmap object. The 3state version uses a simplified tropical/arid/temperate classification; allstates uses the full 11-state Köppen-Geiger system. diplo_Data.Rdata Primary processed data object loaded by all downstream analysis scripts. Contains: the time-calibrated MCMCTree phylogeny (full_mcmc_dip_tree), a species-level morphological trait matrix with log shape ratios, ecological state assignments, and associated metadata. Created by code/01_morpho_trait.R. MuHiSSE_results.Rdata List of all fitted diversification model objects from 05_MuHiSSE_Oz.R, including MuSSE (null and full), MuHiSSE, and CID models with 2–8 hidden states. Each object includes log-likelihood, AIC, and fitted parameters. alignments.zip TAPER-processed and ClipKit-trimmed locus alignments for all 5,375 AHE + UCE loci in FASTA format. Files are named [locus]_ct.fas (suffix _ct = clipped and TAPER-processed). Alignments were processed via the ausarg/pipesnake Nextflow pipeline v1.2 using MAFFT v7.520 for alignment, TAPER for outlier sequence removal, and ClipKit v2.3.0 for trimming. gene_trees.zip Per-locus maximum likelihood consensus trees (5,375 .contree files) estimated by IQ-TREE 2 v2.2.6 (via ausarg/pipesnake). Files are named [locus]_ct.fas.contree (Newick format with bootstrap support values). These gene trees were used as input to wASTRAL v1.20.3.7 for species tree inference and to IQ-TREE 2 v2.3.6 for concordance factor computation. Analysis Scripts Scripts are in the code/ directory and are numbered in execution order. All scripts use setwd("~/diplo-phylo/") — rename this folder to diplo-phylo before running. Outputs (PDFs, CSV tables) are written to output/. Intermediate objects shared between scripts are written to data/script_generated/. Where to start: If you have downloaded this archive, begin with the scripts numbered 01_ through 05_ — these run entirely from the provided data files. Scripts prefixed 00_ are included for transparency and reproducibility documentation; most require external genomic data, ALA downloads, or external software pipelines not included in this archive. Execution order Script Stage Description Runnable from archive 00_occurrence_data.R Data prep Download and curate ALA occurrence records Requires ALA download 00_concordance_vector.R Data prep Compute concordance vectors (gCF, sCF, qCF) from IQ-TREE output Requires v4_out/ 00_Fit_skewT_priors.R Dating prep Fit Skew-T distributions to genus-level MCMCTree posteriors for secondary calibrations Yes 00_assign_species_to_biomes_V2.R Biogeography prep Assign species to Köppen-Geiger biomes from occurrence records Requires Koppen raster 00_mcmctree_prep.R Dating prep Prepare alignment partitions and tree inputs for MCMCTree Requires dating/ 01_mcmctree_results.R Phylogenetics Process and visualize MCMCTree divergence time results Yes 01_concordance_factor_plot.R Phylogenetics Visualize concordance factors on the phylogeny Yes (partial: CF stat requires v4_out/) 01_morpho_trait.R Morphology Compile morphological trait data; compute log shape ratios; saves diplo_Data.Rdata Yes 01_bgb_prep.R Biogeography Prepare BioGeoBEARS input tree and geographic state matrix Yes 02_bgb_results.R Biogeography Process and visualize ancestral biome estimates Yes 02_morpho_trait_viz.R Morphology PCA of log shape ratios; saves PCA results to data/script_generated/diplo_morpho_trait_pca_results.rda Yes 02_physig_morphospace.R Morphology Multivariate phylogenetic signal analysis (K_A, K_G) and phylomorphospace (Fig. S6) Yes 02_trait_simmap.R Ecology Fit extended Mk models for habitat type and substrate use; ancestral state reconstruction Yes 03_anc_state.R Ecology Discrete character ancestral state reconstruction — visualization (Fig. 2, Fig. S5) Yes 03_fit_trait_mvgls.R Morphology Multivariate and univariate phylogenetic GLS; produces Table S11 Yes 03_morpho_vis.R Morphology Morphospace and pairwise ecological morphology heatmap (Fig. 4); run after 02_morpho_trait_viz.R and 03_fit_trait_mvgls.R Yes 04_sampling_summary.R Sampling Compile taxon sampling summary table Yes 05_MuHiSSE_Oz.R Diversification State-dependent diversification modeling (MuHiSSE, Australia-only) Yes colour_schemes.R Utility Project-wide colour palettes (sourced by visualization scripts) Yes Helper functions (code/func/) File Description RunMultiStartMuHiSSE.R Multi-start optimization for MuHiSSE model fitting colour_by_cf_mcmctree.R Colour phylogeny branches by concordance factor on MCMCTree colour_by_cf.r Colour branches by concordance factor (gradient ramp) color_by_CF_Ian.R Alternative concordance factor branch colouring plot_simmap_patterned.R Plot patterned pie charts at ancestral nodes on stochastic maps Software Requirements R packages Package Version used Purpose ape 5.8 Phylogenetic data structures and tree manipulation phytools 2.x Ancestral state reconstruction, stochastic mapping, phylomorphospace MCMCtreeR 1.1.2 Read and plot MCMCTree output hisse 2.1.6 State-dependent diversification models (MuSSE, MuHiSSE, CID) mvMORPH 1.2.1 Multivariate phylogenetic GLS (mvgls) FactoMineR 2.11 Principal component analysis (PCA) BioGeoBEARS 1.1.3 Biogeographic model fitting (DEC) galah 2.1.2 Atlas of Living Australia data download terra 1.7+ Spatial data manipulation (Köppen rasters) deeptime 1.1.0 Geological time scale axis for phylogenies sn 2.1.1 Skew-T distribution fitting for MCMCTree calibrations dplyr 1.1+ Data manipulation tidyverse 2.0+ Data manipulation and visualization patchwork 1.2+ Multi-panel figure composition kableExtra 1.4+ Supplementary table rendering (PDF) External software Software Version Purpose IQ-TREE 2 2.2.6 Maximum likelihood gene tree estimation (via ausarg/pipesnake Nextflow pipeline) IQ-TREE 2 2.3.6 Concordance factor computation (gCF, sCF, qCF; run locally) wASTRAL 1.20.3.7 Weighted summary coalescent species tree inference BPP 4.7.0 Full Bayesian multispecies coalescent (MSC) analysis MCMCTree (PAML) 4.9j Bayesian divergence time estimation MAFFT 7.520 Multiple sequence alignment ClipKit 2.3.0 Alignment trimming (paired with TAPER in ausarg/pipesnake) AMAS — Alignment concatenation and partitioning SEGUL 0.22.1 Alignment subsetting and format conversion LogCombiner (BEAST 2) Combining independent MCMC chains BioGeoBEARS 1.1.3 Time-stratified DEC biogeographic model fitting ausarg/pipesnake (Nextflow) 1.2 (Nextflow 24.10.0) Gene tree construction pipeline (alignment → trimming → IQ-TREE) Data Provenance Occurrence data: Atlas of Living Australia (ALA; ala.org.au); downloaded 2025-07 using galah R package. Supplemented with locality data from Conrad Hoskin (pers. comm., corresponding to Hoskin & Couper 2023) and primary literature. Morphological measurements: Original measurements from museum specimens held at the Australian Museum (AM), Queensland Museum (QM), Western Australian Museum (WAM), South Australian Museum (SAMA), Museum Victoria (NMV), and the Australian National Wildlife Collection (ANWC). Published comparative data from other sources are listed in ExtendedData/ED03_diplo_morpho_traits.csv. Paleoclimate curves: Li et al. (2022) climate reconstructions interpolated by A. Skeels at the temporal resolution of the BioGeoBEARS time slices (0–50 Ma at 10 Ma intervals). Based on Scotese DEM paleogeographic reconstructions and CHELSA downscaling. Köppen-Geiger climate classification: Beck et al. (2018); 1991–2020 climatology at 0.1° resolution. Not included in this archive — download from: https://doi.org/10.1038/sdata.2018.214 Published sequence data integrated: New Caledonian taxa from Skipwith et al. (2019); Aotearoa New Zealand taxa from Title et al. (2024). Sequences matched to Squamate Conserved Loci (SqCL) targets (Singhal et al. 2017). Key References Beck HE et al. (2018) Present and future Köppen-Geiger climate classification maps at 1-km resolution. Scientific Data 5: 180214. doi:10.1038/sdata.2018.214 Brennan IG et al. (2024) Pipesnake: Generalized software for the assembly and analysis of phylogenomic datasets from conserved genomic loci. Bioinformatics 40(5): btae195. doi:10.1093/bioinformatics/btae195 Green AL et al. (2024) Adaptive tails? Parallel evolution of expanded tails in monsoonal tropics lineages of an Australian gecko radiation (Oedura). Zoological Journal of the Linnean Society 202(2): zlad186. doi:10.1093/zoolinnean/zlad186 Hoskin CJ and Couper PJ (2023) Revision of zigzag geckos (Diplodactylidae: Amalosia) in eastern Australia, with description of five new species. Zootaxa 5343(4): 301–337. doi:10.11646/zootaxa.5343.4.1 Karger DN et al. (2017) Climatologies at high resolution for the Earth’s land surface areas. Scientific Data 4: 170122. doi:10.1038/sdata.2017.122 Lanfear R and Hahn MW (2024) The meaning and measure of concordance factors in phylogenomics. Molecular Biology and Evolution 41(11): msae214. doi:10.1093/molbev/msae214 Li X et al. (2022) A high-resolution climate simulation dataset for the past 540 million years. Scientific Data 9: 371. doi:10.1038/s41597-022-01490-4 Matzke NJ (2013) BioGeoBEARS: BioGeography with Bayesian (and likelihood) evolutionary analysis in R Scripts. R package v1.1.1. doi:10.5281/zenodo.1478250 McDonald PJ et al. (2024) Vicars in the desert: Substrate specialisation and paleo-erosion underpin cryptic speciation in an Australian arid-zone lizard lineage (Diplodactylidae: Diplodactylus). Vertebrate Zoology 74: 577–594. doi:10.3897/vz.74.e128775 Mo YK et al. (2023) Updated site concordance factors minimize effects of homoplasy and taxon sampling. Bioinformatics 39(1): btac741. doi:10.1093/bioinformatics/btac741 Singhal S et al. (2017) Squamate conserved loci (SqCL): A unified set of conserved loci for phylogenomics and population genetics of squamate reptiles. Molecular Ecology Resources 17(6): e12–e24. doi:10.1111/1755-0998.12681 Skipwith PL et al. (2019) Relicts and radiations: Phylogenomics of an Australasian lizard clade with East Gondwanan origins (Gekkota: Diplodactyloidea). Molecular Phylogenetics and Evolution 140: 106589. doi:10.1016/j.ympev.2019.106589 Title PO et al. (2024) [New Zealand gecko macroevolution paper — please verify citation details]. Yang Z (2015) The BPP program for species tree estimation and species delimitation. Current Zoology 61(5): 854–865. doi:10.1093/czoolo/61.5.854 Zhang C and Mirarab S (2022) Weighting by gene tree uncertainty improves accuracy of quartet-based species trees. Molecular Biology and Evolution 39(12): msac215. doi:10.1093/molbev/msac215