All Lands Approaches to Fire Management in the Pacific West: A Typology

Abstract

Since 2009, the US Department of Agriculture Forest Service has promoted an “all lands approach” to forest restoration, particularly relevant in the context of managing wildfire. To characterize its implementation, we undertook an inventory of what we refer to as fire-focused all lands management (ALM) projects, defined as projects in which fuels reduction treatments are planned or implemented across more than one landownership to reduce wildfire risk or increase forest resilience to wildfire. We focused on regions of Washington, Oregon, and California dominated by dry, fire-prone forests and documented 41 projects. From this sample we developed a typology with five project categories. We found that ALM takes many forms and occurs in diverse contexts, federal lands and land managers are frequently involved in them, and all projects foster relationship and capacity building for future ALM. Our typology provides a framework for better understanding of all lands approaches and suggests areas for further investigation. Management and Policy Implications: Many scientists, land management agencies, and policies in the United States promote an “all lands approach” to forest restoration, but the concept remains somewhat abstract. We provide a typology of “all lands management” (ALM) projects that aim to mitigate wildfire risk or increase forest resilience to wildfire using all lands approaches and examples of projects in the five typology categories. Through the typology, we demonstrate the diversity of ALM projects and project participants and offer a framework that allows for comparisons across projects. By characterizing different all lands approaches, we provide a common language that may help managers and policymakers communicate and share ideas about ALM and improve policy tools to support it. The typology may also help managers interested in fire-focused ALM pursue the approach most appropriate for them and learn from strategies used by other projects. It also offers a starting point for developing hypotheses about how different types of ALM may be more or less effective in achieving desired outcomes, highlighting areas for future research.