Finding novel ways to plan and implement landscape-level forest treatments that protect sensitive wildlife and other key ecosystem components, while also reducing the risk of large-scale, high-severity fires, can prove to be difficult. We examined alternative approaches to landscape-scale fuel-treatment design for the same landscape. These approaches included two different treatment scenarios generated from an optimization algorithm that reduces modeled fire spread across the landscape, one with resource-protection constrains and one without the same. We also included a treatment scenario that was the actual fuel-treatment network implemented, as well as a no-treatment scenario. For all the four scenarios, we modeled hazardous fire potential based on conditional burn probabilities, and projected fire emissions. Results demonstrate that in all the three active treatment scenarios, hazardous fire potential, fire area, and emissions were reduced by approximately 50% relative to the untreated condition. Results depict that incorporation of constraints is more effective at reducing modeled fire outputs, possibly due to the greater aggregation of treatments, creating greater continuity of fuel-treatment blocks across the landscape. The implementation of fuel-treatment networks using different planning techniques that incorporate real-world constraints can reduce the risk of large problematic fires, allow for landscape-level heterogeneity that can provide necessary ecosystem services, create mixed forest stand structures on a landscape, and promote resilience in the uncertain future of climate change.