Supplementary code and data for the submitted manuscript

Code and Data Availability (Zenodo Repository Description) Repository Overview This repository contains all the code and data required to reproduce the analyses and figures presented in the associated manuscript. The material is organized into three main R scripts and two structured data directories. All scripts are fully annotated to ensure transparency and reproducibility. Folder Structure / clim_space_statistics.R geo_clim_path_analysis.R geo_clim_spaces_maps.R combined_spaces_df/ geo_clim_space_amphibians.rds geo_clim_space_birds.rds geo_clim_space_mammals.rds geo_clim_space_reptiles.rds other_files/ geographic_gridcells/(gridcell shapefiles) world_continents/(continent shapefile) R Scripts 1. clim_space_statistics.R Purpose:Runs all main statistical analyses evaluating how climate and the geography of climate influence speciation rates. The script uses mammals as an example but is fully generalizable to any tetrapod group. Analyses included: Effects of mean temperature and precipitation on speciation Effects of climate geography (climate area and climate isolation) Summary statistics and visualizations Additional analyses using climate niche evolution rates (replace mean_temp / mean_prec with temp_bamm / prec_bamm) Reproducing analyses for other taxa:Load the respective .rds dataset from combined_spaces_df/. 2. geo_clim_path_analysis.R Purpose:Performs path analyses testing: Direct effects of climatic tropicality and geographic tropicality on speciation rates Indirect effects mediated by climate niche evolution rates The script uses mammals as an example. Replace the input data to run analyses for amphibians, birds, or reptiles. Outputs include: Standardized path coefficients Model fit indices Path diagrams Summary tables for main figures and supplementary material 3. geo_clim_spaces_maps.R Purpose:Generates all climate-space and geography-space visualizations used in the manuscript. Features: Maps speciation rate estimates (BAMM, ClaDS, DR, MiSSE) in geographic and climate space Maps the climate area and climate isolation in climate space Creates the combined figure panels used in the study To reproduce the maps for a different tetrapod class, change the input dataset. Data Files 1. combined_spaces_df/ This folder contains the processed climate–geography–spaces datasets for each tetrapod class. Each .rds file contains one record per species × climate bin (or species × gridcell). Variables included: geoID: Unique gridcell identifier long, lat: Gridcell centroid coordinates species: Species name grid_presence: Species presence in the gridcell BAMM_spec: Speciation rate from BAMM DR: Diversification rate using the DR metric misse_spec: Speciation rate from MiSSE claDS: Speciation rate from ClaDS2 temp_bamm, prec_bamm: Climate niche evolution rates (BAMM) temp_bayesT, prec_bayesT: Climate niche evolution rates (Bayesian models) climateID: Climate bin ID tropicality: Climatic tropicality index mean_temp, mean_prec: Mean temperature and precipitation clim_area: Total area of the climate bin clim_isolation: Mean geographic isolation of the climate bin clim_fragment_n: Number of climate fragments clim_fragment_dist: Mean distance among fragments num_geo_cells: Number of geographic gridcells in the bin temp_mid_bin, prec_mid_bin: Midpoints of climate bins for plotting 2. other_files/ A. geographic_gridcells/Contains the spatial grid used to map species occurrences and environmental variables. These data correspond directly to the geoID values in the main datasets. B. world_continents/Contains the continent shapefile used for spatial visualizations and geographic analyses. How to Reproduce the Full Workflow Open any R script (e.g., clim_space_statistics.R). Load the required R packages (listed at the top of each script). Select the tetrapod group by loading the appropriate .rds file from combined_spaces_df/. Run the script from start to finish. Figures and tables will be generated in your working directory. Software Requirements R version ≥ 4.2 Commonly required packages include:tidyverse, sf, terra, raster, phytools, lavaan, phylolm, geosphere, ggplot2, viridis, cowplot, dplyr(See script headers for exact versions.)