Demographic Buffering Across Taxa

This repository contains the analytical pipeline and data associated with the manuscript "Plant population responses to environmental variability are primarily driven by survival-reproduction trade-offs and mediated by aridity" published in Nature Communications. The study explores the demographic buffering continuum across diverse taxa, analyzing how population responses to environmental stochasticity are driven by life-history trade-offs and mediated by aridity.

Workflow & Reproducibility

The entire workflow—from data integration to MCMCglmm inference—is documented in a reproducible format.

• Main Framework: All primary analysis steps, logic, and figure generation are contained in 0 - Script Framework.rmd.
• Output: A rendered version of the complete analysis is available in 0 - Script Framework.html.

Repository Structure

File	Description
0 - Script Framework.rmd	The central RMarkdown document that coordinates the full analysis.
0 - Script Framework.html	The compiled report showing results, visualizations, and statistical outputs.
1 - Data cleaning and selection.R	Script for filtering matrix singularity and selecting individual matrices.
2 - Life history traits calculation.R	Script for calculating demographic traits (Entropy, Age at maturity, etc.).
MainFunction - Stochastic elasticities of variance lower level.R	Core functions for calculating stochastic elasticities of variance ($
3 - Climatic variables calculation.R	Extraction and processing of environmental metrics and stochastic noise.
ChelsaData Download and extraction.ipynb	Jupyter Notebook for high-resolution climate data extraction (CHELSA).
5a - MCMCglmm - Model selection.R/.ipynb	Preliminary model selection and comparison scripts.
5b- MCMCglmm run.R/.ipynb	Final Bayesian phylogenetic mixed models execution.
references.bib	BibTeX file with all citations (MOSAIC, COMPADRE, CHELSA, etc.).

Data Files (/Data)

• CleanData.RDS: Filtered population matrices and associated metadata.
• supertree.RDS: Phylogenetic information extracted from the MOSAIC database.
• LHtraits.RDS: Calculated life-history traits including reproductive window and mortality risk.
• climate_df.RDS: Cleaned environmental variables and PCA coordinates.
• buffcalc.RData: Pre-calculated demographic buffering metrics to ensure reproducibility.
• MCMCglmm_output.rds: Stored posterior distributions from the final statistical models.

Data Sources

The analysis integrates data from:

• COMPADRE & COMADRE (v.6.23.5.0): Matrix Population Models.
• MOSAIC: Unified trait database for life-history complements.
• CHELSA: High-resolution climatologies for environmental stochasticity.

Requirements

This project requires R and the following key packages:

• Rcompadre & Rage: Demographic calculations.
• MCMCglmm: Bayesian inference.
• tidyverse: Data wrangling and visualization.
• ape & phytools: Phylogenetic analysis.

Citation

Please cite the associated paper in Nature Communications: Santos et al. 2026. Plant population responses to environmental variability are primarily driven by survival-reproduction trade-offs and mediated by aridity.

License

Individual dataset licenses (COMPADRE, MOSAIC, CHELSA) apply. Code is provided for reproducibility.

Disclaimer

This README was drafted with Google Gemini.