The primary theme of our study is the cost-effectiveness of fuel treatment at multiple scales, addressing the question of whether fuel treatments can be justified on the basis of saved suppression costs. Our study was designed to track the influence of a dollar invested in fuel treatments on final fire outcomes, and to quantify this influence in terms of both financial and risk-based metrics. We focused on the nexus of fuels management and suppression response planning, designing spatial fuel treatment strategies to incorporate landscape features that provide control opportunities that are relevant to fire operations. We also aimed to demonstrate a proof-of-concept modeling approach for approximating alternative fire suppression strategies. We used the concept of leverage, quantified frequency-magnitude distributions for fire-treatment and fire-fire encounters, and demonstrated how they vary with alternative fuels management and suppression response policies. As a first step, we performed a synthesis of the relevant literature on fuel treatments impacts on suppression costs, and aimed to include these insights into our model framework development. Two key conclusions were: 1) to account for the inherent uncertainty of when and where wildfires will occur, evaluations of return on fuel treatment investments must use a spatial, risk-based framework; and 2) the relative rarity of large wildfire on any given point on the landscape and the commensurate low likelihood of any given area burning in any given year suggest a need for large-scale fuel treatments if they are to have an impact on risk. We chose the Sierra National Forest as our study site, due to previous work providing relevant data and analytical products, and because it reflects a microcosm of many of the challenges surrounding contemporary fire and fuels management in the western U.S., including potential for large, long-duration fires and corresponding potential for high suppression expenditures. We designed two separate modeling frameworks, one to address alternative fire suppression responses and the other to optimize fuel treatments. Both made use of the Large Fire Simulator (FSim), a stochastic fire simulation program that generates maps of annual burn probability and conditional flame length probability, a list of fires with their corresponding sizes, dates, locations, and durations, and a set of fire perimeters. These outputs were utilized to ascertain the impact of alternative fire suppression response and fuel treatments on fire size and burn probability. Modeling results generally confirmed that fire-treatment encounters are rare (such that median suppression cost savings are zero), that treatment effects are most pronounced within their boundaries and decay rapidly with distance, that treatment strategies can reduce risk and possibly expand opportunities for moderated suppression response, and that such changes in suppression response lead to feedbacks that limit burned area over time. Here we found that under most years the benefits of a fuel treatment investment may be negligible (from the perspective of changing fire outcomes), although under extreme (1/10,000) years the investment could yield a large return in avoided costs and damages. Over time, mean annual savings can accumulate such that return on investment approaches breakeven in terms of financial metrics alone. On top of this, high leverage rates for risk reduction suggest the possibility for positive return, but with the caveat that treatment benefits are highly uncertain and dependent on the vagaries of fire-treatment encounters. There exists ample opportunities to improve the integration of fuels management and suppression response planning.