Welcome to the repository accompanying the "Fire Adapted Forests" publication, which provides evidence for the role of forest treatments in stabilizing carbon storage, reducing wildfire severity, and enhancing resilience in mixed-conifer forests of the Central Sierras.
This repository contains code, data, and workflows for reproducing the analyses presented in the publication, leveraging dynamic performance baselines and natural experimental design techniques.
If you use this repository in your work, please cite:
Authors: Ethan Yackulic, Micah Elias, Joe Shannon, Sophie Gilbert, Michael Koontz, Spencer Plumb, Matthew Sloggy, Katharyn Duffy
Journal: Frontiers in Forests and Global Change
Pre-print DOI: 10.17605/OSF.IO/3UNGR
This repository includes:
- Code: Scripts for data processing, statistical analysis, and visualization.
- Data: Publicly available datasets, including pre-processed input files for modeling.
- Figures: Scripts to reproduce the publication figures and additional exploratory visualizations.
- Documentation: Detailed instructions for running the analyses and adapting them for other regions.
- Dynamic Performance Benchmarks: Methods for evaluating forest treatment effectiveness over time, using difference-in-differences and census-based reference regions.
- Wildfire Severity: Tools to analyze burn severity and its impact on carbon stability.
- Carbon Stability Assessment: Framework for quantifying carbon loss and recovery post-treatment and post-wildfire.
- Scalable Workflow: Methods adaptable to other forest types and disturbance regimes.
git clone https://github.com/Vibrant-Planet-Open-Science/Fire-Adapted-Forests.git
cd fire-adapted-forestsEnsure you have R (version 4.1 or later) and the following R packages: • data.table • tidyverse • bayestestR • ggplot2
Install them via CRAN:
install.packages(c("data.table", "tidyverse", "bayestestR", "ggplot2"))