Collaborative Research: FIRE-NET: Grass Fires: A Convergent Network for Understanding Fuels and Fire Risk in Grasslands

Grassland wildfires increasingly threaten human life and property in regions of the USA and worldwide. Managing fuels is a key way to reduce grassland fire risk. However, risk management strategies developed for forests do not translate to grassland systems, which are not as well studied. Grassland fuels vary across the year, vary from year to year, and change dramatically across the landscape. The critical knowledge gaps around how grassland fuel structures vary across space and through time make it difficult to evaluate methods for effectively reducing wildfire risk. In addition, approaches that allow scaling on-the-ground fuel measurements to characterize landscape-scale parcels are needed to assess risk and prioritize mitigation. In this project, a collaborative network of researchers, land managers, and fire practitioners work to fill these knowledge gaps and build the capacity to coordinate across organizations and regions in the Southern Great Plains of the United States. This project aims to fill several critical gaps in understanding grassland wildfire risk. The project forms and coordinates a collaborative network of partners interested in grassland wildfire that range from researchers to land managers and fire practitioners across regions of the Southern Great Plains. In addition, this project organizes coordinated data collection on grassland fuel variation and how the attributes of fuel influence fire behavior. This dataset enables effective scaling from on-the-ground fuel characteristic measurements to landscape scales important for land management planning and risk assessment. This network of field sites provides the ability to test patterns in grassland fuel characteristics across different climates, plant communities, and cultural fire contexts. Together, these advances enable better representation of grassland fuels in large scale fuel models and ultimately improve fire behavior modeling and risk assessments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.