Estimating social-ecological resilience: fire management futures in the Sonoran Desert

Resilience quantifies the ability of a system to remain in or return to its current state following disturbance. Due to inconsistent terminology and usage of resilience frameworks, quantitative resilience studies are challenging, and resilience is often treated as an abstract concept rather than a measurable system characteristic. We used a novel, spatially explicit stakeholder engagement process to quantify social-ecological resilience to fire, in light of modeled social-ecological fire risk, across the non-fire-adapted Sonoran Desert Ecosystem in Arizona, USA. Depending on its severity and the characteristics of the ecosystem, fire as a disturbance has the potential to drive ecological state change. As a result, fire regime change is of increasing concern as global change and management legacies alter the distribution and flammability of fuels. Because management and use decisions impact resources and ecological processes, social and ecological factors must be evaluated together to predict resilience to fire. We found highest fire risk in the central and eastern portions of the study area, where flammable fuels occur with greater density and frequency and managers reported fewer management resources than in other locations. We found lowest fire resilience in the southeastern portion of the study area, where combined ecological and social factors, including abundant fuels, few management resources, and little evidence of past institutional adaptability, indicated that sites were least likely to retain their current characteristics and permit achievement of current management objectives. Analyzing ecological and social characteristics together permits regional managers to predict the effects of changing fire regimes across large, multi-jurisdictional landscapes and to consider where to direct resources. This study brought social and ecological factors together into a common spatial framework to produce vulnerability maps; our methods may inform researchers and managers in other systems facing novel disturbance and spatially variable resilience.