readme for Braziunas et al. in review. Less fuel for the next fire

purpose

This readme gives an overview of directory structure, files, and steps for recreating outputs and analyses associated with Braziunas et al. in review.

Manuscript citation: Braziunas, K.H., N.G. Kiel, and M.G. Turner. In Review. Less fuel for the next fire? Short-interval fire delays forest recovery and interacting drivers amplify effects. Ecology.

platforms

• Operating systems and software used for development and implementation
  • OS: Windows 10
  • R version: 4.1.3
  • ArcGIS Desktop 10.6

directory overview

Directory structure and files:

• analysis/: Results from data analysis.
• data/: Raw data.
• processed_data/: Any data altered from raw form. Data derived during study design, plot selection, and spatial data processing. Includes summary tables and intermediate products created during data analysis.
• scripts/: R scripts.

scripts

Scripts are named in order (step01_, etc.). .Rmd scripts rely on external data inputs not included in this deposit (e.g., raw climate downloads, fire perimeters from MTBS). .R scripts can be rerun with data included in deposit.

Script descriptions:

• step01_fire_selection.Rmd: Identifies short- and long-interval fire perimeters from multiple data sources (MTBS, Yellowstone and Grand Teton National Parks). Creates shapefiles for final selected fires for 2021 field sampling. Outputs in processed_data/fire_selection/.
• step02_plot_selection.Rmd: Implements random selection of potential short-interval plots at pre-identified sampling sites where short- and long-interval severe fire occurred in close proximity. Identifies nearby long-interval plots that share similar topographic characteristics.
• step03_field_data_cleaning_prep.R: Cleans and organizes field data into plot-level totals prior to fuels calculations and data analysis. Inputs in data/raw_data/ and outputs in data/cleaned_data/ and processed_data/plot_selection/ (final coordinates of plots sampled in the field).
• step04_biomass_fuels_calcs.R: Calculates aboveground live and dead biomass and fuels prior to data analysis. Inputs in data/ and outputs in processed_data/biomass_fuels.csv.
• step05_climate_data_prep.Rmd: Prepares predictor climate variables relevant for tree regeneration. Outputs in processed_data/climate/.
• step06_data_analysis.R: Data analysis to answer questions in this study: (1) How do short-interval fire, climate, and other factors (topography, distance to live edge) interact to affect post-fire forest recovery? (2) How do forest biomass and fuels vary following short- versus long-interval severe fires? Inputs in data/ and processed_data/, outputs in analysis/.