Evaluating short-term effects of fuel treatments on fuel loading in western US dry conifer forests: A meta-analysis

Fuel treatments are crucial for reducing wildfire hazard, especially as severe wildfires increase across western United States (US) dry conifer forests. While many studies have documented the effectiveness of fuel treatments in reducing future wildfire severity, few have synthesized data to predict post-treatment fuel loads for major classes of fuels. We conducted a Bayesian meta-analysis using 1932 observations from 65 published papers in western US dry conifer forests to (1) evaluate the short-term effects of different fuel treatments on fuel loading and overstory structure and (2) characterize patterns of post-treatment fuel loading and overstory structure across multiple fuel components. Treatments included thinning followed by prescribed burning (THIN+BURN), thinning only (THIN), and first-entry prescribed fire only (BURN). Our results show that treatments effectively reduce fuel loads, but outcomes vary based on treatment type, forest type, and initial stand conditions. THIN+BURN treatments were most effective in reducing overstory fuel loads while preventing surface fuel buildup, whereas BURN treatments were the most effective at reducing surface fuel loads, even after a single entry. Our findings underscore the importance of treatment type and pre-treatment stand conditions in influencing fuel reduction outcomes. Fuel treatments, especially in landscapes with heavy fuel loads, offer a valuable tool for moderating wildfire severity, reducing fire risk, and promoting forest restoration. Our synthesis of post-treatment fuel loads provides important insights for assessing forest vulnerability, improving fire behavior model estimates, and informing wildfire management strategies in a changing climate.