Fire research over the last four decades has identified surface fuel loadings as important variables for determining the behavior and effects of wildland fires.

Fuel loading is defined as the mass of a fuel component per unit area, expressed in this study as kg m-2. Fire research has categorized or stratified fuels into several unique components specifically for predicting fire behavior and effects. Downed dead woody fuels are separated into five size classes based on the diameter of the woody fuel particle. Other important fuel components include live and dead shrubs and herbaceous, litter, and duff. Fuel loading is one of the few fuel characteristics that fire managers can alter to change fire behavior and influence fire effects. Loadings of fuel components provide important inputs into fire behavior models, including BEHAVE and FARSITE, and fire effects models, including FOFEM and CONSUME. These models can then be used to plan, prioritize, design, and implement important fuel treatments for restoring historical fire regimes and reducing hazardous fuels to save lives and property. Yet, recent research has found that surface and canopy fuels are inherently variable and this variability precludes the use of an average or mean value to describe their distribution. The research presented here is a comprehensive effort to describe the spatial variability these surface and canopy fuel characteristics across major forest ecosystem types in the northern Rocky Mountains and then summarizing and synthesizing these characteristics into a model that can be used to produce fuelbeds of similar spatial characteristics at any scale and resolution.

PRINCIPAL INVESTIGATOR

Robert E. Keane, Deputy Program Manager, Fire, Fuel, and Smoke Science (FFS); Research Ecologist; Director, Fire Modeling Institute (FMI)

Staff

Jhen Rawling, Greg Cohn, Violet Holley, Signe Leirfallom, Laurie Dickinson, Curtis Johnson

GOALS AND OBJECTIVES

The project has one primary objectives and a number of specific objectives:

• Develop methods for creating the next generation of fuel models that can be used to generate accurate maps of fuels for fire effects and behavior prediction models at any scale and resolution

This objective can be achieved using the following steps described as sub-objectives;

• Measure the fuel properties of major fuel components across major forest types in the northern Rocky Mountains
• Describe the variability of the characteristics of these fuelbeds using geostatistical techniques
• Develop a process to create fuel models that incorporate measures of variability and other fuel characteristics to map fuels for fire behavior and effects prediction
• Test and evaluate developed fuel models model by comparing results with sampled fuelbeds

The audience for this effort is managers and researchers interested in describing and sampling fuels for fire behavior and effects prediction. This research may lead to new methods of simplifying fuels characteristics to aid fuel mapping efforts. Moreover, it should provide important parameters and values for fuel sampling efforts.

METHODS AND RESULTS

This project will consist of four phases that will successfully and eventually accomplish the stated objectives. The first phase will involve the sampling of biophysical and fuel characteristics across space in the field in several heterogeneous stands. The second phase will be to analyze and summarize samples collected from the field sampling effort using standard statistical and geostatistical techniques. The third phase is the complex analysis of the data using spatial statistical techniques to develop fuel models that are used as input to fire effects and behavior models. The last phase is the testing of these models using independent data sets and the sampled data to determine its accuracy and evaluate and improve its performance.

PROJECT STATUS

This is a 5 year study started in 2007. Currently, only three of six sites have been measured.

FUNDING ORGANIZATIONS

This work is currently being funded by RMRS and Missoula Fire Fuels and Smoke Program.