Wildfire is a dynamic natural process that continually shapes the structure and composition of landscapes. However, due to a combination of factors including climate change, management decisions and population growth, this natural process is having negative impacts on important ecosystem goods and services (EGS). It is critical to accurately measure and predict wildfire occurrence, its impacts to EGS and their post-fire response if effective adaptive management of landscapes is to take place. Vulnerability assessments have informed such adaptive management in response to other stressors. Yet our understanding of what makes landscapes and communities more or less vulnerable to wildfire specifically remains incomplete, which can undermine our ability to ensure that landscapes and communities are fire adapted.

Researchers conceptualized a framework for guiding landscape vulnerability assessments in the context of wildfire that include both retrospective and predictive components, as the combination of both is most powerful for informing adaptive management of landscapes.