Understanding Prescribed Fire Management in the Context of Climate Change and Landscape Transformation
Principal Investigator: John Kupfer, University of South Carolina
Proposed Project Completion: December 2022
Implements Science Plan Theme: Impacts
Co-Investigators: Kirstin Dow (University of South Carolina), Kevin Hiers (Tall Timbers Research Station), Kirsten Lackstrom (University of South Carolina), Peng Gao (University of North Carolina – Greensboro), Adam J Terando (Southeast Climate Adaptation Science Center)
Prescribed burning is a primary tool used to reduce wildfire risk and manage ecosystems to achieve a range of ecological, economic and societal goals. The ability of fire managers to use prescribed fire as a management tool is complicated in regions such as the Southeast because of rapid population growth, extensive suburban development, and a changing climate. Such change restricts prescribed burning while also highlighting the necessity of an active prescribed fire management regime to reduce wildfire risk in these communities. To help managers make decisions in light of these factors, there is a need to document: 1) the current conditions under which practitioners are willing to burn and restrictions to active fire management, and 2) how such restrictions are likely to change in the future given potential scenarios of urbanization and climate change.
This project will collect and analyze data from prescribed fire managers across the full historic range of longleaf pine in the Southeast. Data collection will focus on the criteria used for prioritizing burn sites within a management unit, current burning practices and restrictions, and expectations for future changes in burning restrictions. This project will document the overlap (or disconnection) between perceptions of how urbanization and climate change will affect prescribed burning opportunities vs. projected changes in fire, climate and landscape development. Results from this project will provide crucial data on prescribed fire management that will help natural resource managers make science-based decisions about management priorities and adapt to future changes.