DOI: 10.5281/zenodo.14642074
title: Replication Data and Code for Forest Product Market Conditions Mediate the Scale and Benefits of Sustainable Forest Management in the Tahoe-Central Sierra Region

description: Replication Data and Code for Forest Product Market Conditions Mediate the Scale and Benefits of Sustainable Forest Management in the Tahoe-Central Sierra Region. This includes full BioSum run data, FVS .kcp files specifying fuel treatment keywords, and R files for data management and figure creation. 

BioSum requires a whole multi-layer cake of coding and modeling. This doc is an attempt to walk you through the additional processes/analyses performed for this analysis. Users hoping to replicate the analysis from start to finish should familiarize themselves with USFS's BioSum and FVS tools. This replication code and documentation builds on the basic BioSum workflow to customize FVS variables and create visualizations of BioSum outputs across various modeled scenarios. Please see BioSum User Guide http://biosum.info/UsersGuide/ for information on the BioSum workflow. 

The entire BioSum runs, with all data and results, are found in tcsi_full_run.zip. These data are needed to recreate the figures and extract final treatments. 

Initial FIA data to be loaded into BioSum was downloaded from the FIA DataMart (https://apps.fs.usda.gov/fia/datamart/datamart.html). The 2021 update of the California FIADB was used for this study. Biosum_Plots_TCSI.txt is a list of plots in the TCSI region that the CAFIADB is filtered to within the 'Database' step of BioSum. 

When BioSum has generated the FVSIn.db files that are ready to load into FVS, run the 1_Add_Max_SDI_OWN_FVSIN.R script. This overwrites the default maxSDI calculations with custom-calculated maxSDI values by forest type, and pulls in the OWNCD to FVS so that treatments can be specified based on land ownership. 

At the same time (before loading data into FVS) run the 2_get_tpa_spp_size_classes.R script. This calculates species specific mortality based on inventory data, which is then included in the treeSzCp keywords in the FVS runs. 

FVS runs are defined by the .kcp files in tcsi_kcps_11-6-24.zip. These build upon the CEC .kcp runs (found here: https://github.com/USFS-PNW/Fia_Biosum_Scripts/tree/master/CEC%20Master%20KCPs) but with some additional customization such as the treeSzCp keywords. 

After all treatments are modeled in FVS and the data is loaded back into BioSum, run the 3_calc_hazard_mvp.R. This calculates the composite fire hazard score, which is used to determine whether treatments are effective. 

Finally, once all optimization scenarios are run in BioSum, run the 4_biosum_results_extract.R script to extract .csv tables of the resulting optimal treatments. These are shown compiled in treatments_final.zip. Note: separate BioSum scenarios were run with all operational facilities and all existing facilities (including those no longer operational) in TCSI and surrounding areas. However, the differences between these runs was minimal, so final results were displayed only for operational facilities. 

Replication Code for FiguresFigure 1 and SI Figure 4 - see python notebook Figure 2 - see corresponding R scriptFigure 3 - see corresponding R script SI Figure 1 - see corresponding R script 

Reach out to corresponding author Evan Patrick (epatrick@ucsb.edu) for any questions