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This repository contains the data and code for our paper:

Magneville et al. Echoes of the Past: Long-Term Climate Stability Shapes Functional and Phylogenetic Diversity in Euro-Mediterranean Forests
Accepted for publication in Global Ecology and Biogeography on December 2025

How to cite

Though not required, a recommended citation for this compendium:

(2025). Compendium of R code and data for Past Climate Stability Shapes Diversity. Accessed [...] Online at
https://doi.org/10.5061/dryad.w0vt4b94h

Long-Term Climate Stability Shapes FD and PD In Euro-Mediterranean Forests

The goal of this R project is to reproduce all analyses, figures, and
tables of drivers of FD and PD of Mediterranean forests (multidiversity
and muti taxon approach)🌳 Past climate stability, Present habitat
characteristics, Disturbances and Past and Present human impact.

Content

This repository contains all the R scripts used to run the analyses from the manuscript cited above. It contains data from the null models, and not the raw data used for the analyses, as the authors do not hold distribution rights for all the data. The user is then able to look at all the R scripts used for the analyses, and run all the analyses from the step of the null models onward. R packages which are needed to run the analyses are named in the DESCRIPTION file.
Users who wish to access the raw species and trait data underlying the null-model outputs may request them from the INTEGRADIV project’s principal investigator, Agathe Leriche (agathe.leriche@imbe.fr), as these datasets are not publicly distributed by the authors.

To run the make.R file and analyses easily, the files are organised as follows

• 📁 R: ⚙ Folder containing all functions
  created for the analyses. These functions can be loaded using
  devtools::load_all(). They are called in the scripts coded in
  the analysis folder. This folder gathers all the files with a name ending with "_fcts"
• 📁 analysis: 🍳 Folder containing all script to
  prepare data and analyse it. It uses the functions coded in the R
  folder. This folder contains all the files named with numbers"
• 📁 env_db: 📦 Folder containing a file with the names of the drivers (used for graphic purposes), 50*50km grid cells and land masks for plotting maps.
• 📁 transformed_data: 📦 Folder containing the dataframe gathering the drivers data (restricted or not to the final number of cells studied in the paper), and another folder "div_values_null_models", containing:
• rds files containing functional and phylogenetic indices values per studied grid cells. Named "FacetName_IndicesNames_ScaleStudtied_TAXA.rds".
• rds files containing outputs from the null models run.
  Named "FacetName_IndexNames_null_models_ScaleStudtied_TAXA.rds".
• rds containing values computed out of the null models and observed diversity values. Named "FacetName_IndexNames_null_models_metrics_ScaleStudtied_TAXA.rds"
• make.R File: Script to run the whole project. The steps 1 to 7 can't be run with raw data (as the authors don't do not hold distribution rights for raw data), but associated R scripts can still be looked at. These steps are related to cleaning the data and computing observed diversity indices and null models. Steps from 8-16 can be run with provided data (as they rely on the outputs of the null models which are provided). These steps are related to: random forests analyses, plotting the main Figures/Appendices, associated statistical tests and model checks.