2026-10-07T23:11:42Z https://api.figshare.com/v2/oai

oai:figshare.com:article/31450903 2026-10-01T12:46:39Z category_24235 item_type_14 month_year_10_2026

Code and Data for "Thermal baselines and climate-space geometry mediate systematic terrestrial biodiversity responses to warming" anonymity anonymity (6419120) Terrestrial ecology Climate change # README: Reproducibility Code & Data > **Title:** *Thermal baselines and climate-space geometry mediate systematic terrestrial biodiversity responses to warming*> **Date:** March 2026 *** ## 1. OverviewThis repository contains the full analytical pipeline for investigating how **climate-space geometry** (area and isolation) and **thermal baselines** modulate the response of terrestrial biodiversity to warming. The study utilizes 1,161 assemblage time series from the BioTIME 2.0 database. --- ## 2. Directory Structure ### 📁 `Code/`All R scripts are prefixed with numbers to indicate the execution order. * **`01_Preprocess and rarefy data.R`**Processes raw BioTIME data, including: site screening, spatial gridding (hexagonal cells), sample-based rarefaction, and calculation of community metrics (Richness, Abundance, Evenness).* **`02_brmModel.R`**Constructs Bayesian hierarchical models using the `brms` package to model diversity slopes against temperature change.* **`03_Plotting_Figures.R`**A collection of scripts to generate all Main Text and Supplementary Figures.* **`FUNCTION calculate metrics.R`**A core utility script containing custom functions for community analysis, climatic data matching (CHELSA/CRU TS), and temperature change estimation. ### 📁 `Data/`* **Input:** Raw BioTIME 2.0 records and climatic layers (CHELSA/CRU TS).* **Output:** Processed dataframes from Script 01 and fitted `.Rdata` model objects from Script 02. ### 📁 `Figure/`* Output destination for all high-resolution plots generated by Script 03. --- ## 3. Data Availability 🌐 **Biodiversity Data:**The raw records used in this study are available from the **BioTIME 2.0 database** at:👉 [https://doi.org/10.1111/geb.70003](https://doi.org/10.1111/geb.70003) **Climate Data:*** **CHELSA:** [https://chelsa-climate.org/](https://chelsa-climate.org/)* **CRU TS:** [https://crudata.uea.ac.uk/cru/data/hrg/](https://crudata.uea.ac.uk/cru/data/hrg/) **Analytical Code:**All processed datasets and custom R code are archived at **Figshare** (DOI: Pending). --- ## 4. Workflow (How to Reproduce) To fully reproduce the findings, run the scripts in the following order: 1. **Step 1:** Run `01_Preprocess and rarefy data.R`. It automatically sources `FUNCTION calculate metrics.R`.2. **Step 2:** Run `02_brmModel.R`. (Note: Fitting Bayesian models is computationally intensive; pre-fitted objects are provided in `/Data`).3. **Step 3:** Run the `03_...` series to output all figures directly to the `/Figure` folder. --- ## 5. Software Requirements 🛠️ The analysis was performed in **R (version 4.2.2)**. The following libraries are required: ```r# Data Manipulation & Statslibrary(tidyverse) # dplyr, ggplot2, tidyrlibrary(data.table) # Fast data loadinglibrary(brms) # Bayesian modelinglibrary(vegan) # Ecological metrics # Spatial & Visualizationlibrary(dggridR) # Hexagonal griddinglibrary(wesanderson) # Color paletteslibrary(patchwork) # Multi-panel plotslibrary(ggdist) # Visualizing distributions 2026-10-01T12:46:39Z Text Conference contribution 10.6084/m9.figshare.31450903.v1 https://figshare.com/articles/conference_contribution/Code_and_Data_for_Thermal_baselines_and_climate-space_geometry_mediate_systematic_terrestrial_biodiversity_responses_to_warming_/31450903 CC BY 4.0