Repeated fuel treatments fall short of fire-adapted regeneration objectives in a Sierra Nevada mixed conifer forest, USA

Fire exclusion over the last two centuries has driven a significant fire deficit in the forests of western North America, leading to widespread changes in the composition and structure of these historically fire-adapted ecosystems. Fuel treatments have been increasingly applied over the last few decades to mitigate fire hazard, yet it is unclear if these fuels-focused treatments restore the fire-adapted conditions and species that will allow forests to persist into the future. A vital pre-requisite of restoring fire-adaptedness is ongoing establishment of fire-tolerant tree species, and both the type and reoccurrence of fuel treatments are likely to strongly influence stand trajectories. Here, we leveraged a long-term study of repeated fuel treatments in a Sierra Nevada mixed-conifer forest to examine the regeneration response of six native tree species to repeated application of common fuel treatments: prescribed fire, mechanical, mechanical plus fire, and untreated controls. Our objec..., Seedling data were collected in .004 hectare and 1m2 plots. Overstory tree data (used for calculating basal area) were collected in 0.04 hectare plots. Weather data was collected from an on-site weather station. Data were processed using the R statistical software. , , # Fire & Fire Surrogate Seedling Study

Code and data for Nagelson et. al. 2024

All data (.rdata files) and code are available to replicate the analyses and generate figures and tables. All intermediary data products are also provided (e.g. JAGS outputs), which means that one can jump straight to figure and table generation by using \"FFSseedling_Figures_and_Tables.Rmd\".

# Scripts

**FFSseedling_Figures_and_Tables.Rmd** - R markdown document used to generate all tables and figures in manuscript. This is the only script necessary if the user is only interested in reproducing figures/tables or the statistical results defined under research objective 1.

## Bayesian models and post-processing scripts

**postprocessing_functions.R** - post-processing code for abundance and occupancy models.

**abundancemod.R** - pre-processing and run abundance model.

**occmod.R** - pre-processing and run occupancy model.

**FFS_all_scripts.R** - model scripts written in JAGS syntax. These are called ...