United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

Research Note

RMRS-RN-64

April 2014

A Comprehensive Guide to Fuel Treatment Management Practices 

for Dry Mixed Conifer Forests in the Northwestern United States

Inventory and Model-Based Economic Analysis of 

Mechanical Fuel Treatments

Implementing fuel treatments in every place where it could be beneficial to do so is 

impractical and not cost effective under any plausible specification of objectives. Only 

some of the many possible kinds of treatments will be effective in any particular stand 

and there are some stands that seem to defy effective treatment. In many more, effective treatment costs far more than the value of treatment benefits. Understanding the 

scope of the fuel management challenges in these forests is the first step towards identifying fuel treatment approaches that are likely to be both effective and economically 

feasible (e.g., self-supporting) in reducing fire hazard.

Jain and others (2012) have conducted a landscape-scale analysis to predict costs and 

effectiveness of fuel treatments from key stand attributes such as descriptors of stand 

structure, slope, distance from the nearest road, and distance from processing facilities. Using the Forest Inventory and Analysis (FIA) BioSum framework, they assessed 

the effectiveness, costs, and potential returns from generic multi-purpose mechanical 

fuel treatment approaches that are commonly implemented in this region. Treatment 

Figure 1—The BioSum framework integrates a suite of models to evaluate the economic feasibility 

of fuel treatments.
Citation

Jain, Theresa B.; Battaglia, Mike A.; Han, Han-Sup; Graham, Russell T.; 

Keyes, Christopher R.; Fried, Jeremy S.; Sandquist, Jonathan E. 2014. A 

comprehensive guide to fuel management practices for dry mixed conifer 

forests in the northwestern United States: Inventory and model-based 

economic analysis of mechanical fuel treatments. Res. Note RMRS-RN-64. 

Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 2 p. 

costs, yields, and gross revenues associated with merchantable and energy wood, costs of transporting wood to mills 

and bioenergy facilities, and net revenues (or costs) of 

treatment operations are all predicted and included in this 

modeling framework. BioSum was developed to combine 

several robust data sources and models to explore alternative 

landscape-scale treatment scenarios that achieve a variety of 

management objectives. Jain and others (2012) were able to 

model the entire dry mixed conifer forest using thousands 

of inventory plots that are statistically representative of this 

forested landscape. Supplemental information can be found 

in Appendix C of their report.

Fire Hazard Criteria and Evaluation

One product of the analysis is a massive knowledgebase of 

treatment outcomes. Product yields, costs, and revenues generated can be used to describe the “best” alternatives under 

a wide range of assumptions, objectives, and goals. In many 

cases, more than one hazard descriptor may be relevant. 

Treatments that lead to improvements in the crowning index, 

for example, often increase the hazard as indicated by torching index because the act of introducing greater separation 

among crowns also leads to greater surface wind speeds and 

fire intensity. Even with a single descriptor, one must decide 

on the threshold beyond which initial hazard is unacceptable 

and warrants some kind of treatment, assuming that some 

kind of treatment can be effective (for example, restoring the 

stand back to the safe side of the threshold).

Treatment Effectiveness and Economic 

Feasibility

According to the analysis, most dry mixed conifer forests 

currently have high fire hazard, but only a fraction of those 

forests can be effectively treated (at least by the fuel treatments currently relied upon in the dry mixed conifer region). 

While it might sound discouraging that prospects for effective treatment are limited to a relatively small subset of the 

forest, it does make the fuels management problem more 

tractable in that one can justifiably focus on treating the more 

limited area of the forest where success is attainable. It also 

suggests that on many other acres, there are few options for 

achieving significant hazard reduction.

Fuel treatments that are self-funding may ultimately be the 

most effective choices for mitigating fuel hazard, given the 

current and likely future Federal budget climate.

Selecting acres for treatment that are not genuinely hazardous, or that cannot be shown analytically to be economically 

viable for a fuel treatment program, may hinder gaining and 

maintaining public trust in fuels management. Using models 

such as BioSum and FFE-FVS provides managers with the 

decision support that can demonstrate treatment accomplishment (effectiveness and economics) objectively and provides 

a science basis for treatment choices.

Modeling Recommendations

Managers seeking the best choice for a particular stand may 

find it worthwhile to run models such as FFE-FVS and My 

Fuel Treatment Planner (www. fs.fed.us/pnw/data/myftp/

myftp.shtml) on sample data collected from that stand. Using their own assumptions they can then understand the potential impacts and costs of alternative prescriptions in terms 

that are relevant to the challenges they face. Managers seeking to analyze entire landscapes in support of a fuel treatment management program should consider learning and 

using the BioSum tool that is scheduled for general release 

in early 2014 (software, data, tutorials, and user guide will be 

available at www.BioSum.info).

The FIA BioSum framework produces statistically reliable 

summaries of the proportions of the forested landscape in 

the dry mixed conifer region that would respond positively 

to treatment. The system can also estimate the costs, revenues, and product flows that could be associated with a comprehensive fuel treatment program. Model output includes 

reports of the area for which each kind of treatment would 

be most effective. Trade-offs between area effectively treated 

and net treatment cost can also be summarized in order to 

understand the effects of policies such as requiring sales of 

derived products to cover treatment costs.

Source

Jain, Theresa B.; Battaglia, Mike A.; Han, Han-Sup; Graham, 

Russell T.; Keyes, Christopher R.; Fried, Jeremy S.; Sandquist, 

Jonathan E. 2012. A comprehensive guide to fuel management 

practices for dry mixed conifer forests in the northwestern 

United States: Chapter 11. Gen. Tech. Rep. RMRS-GTR-292. 

Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station. 331 p. Available 

online at www.treesearch.fs.fed.us/pubs/42150 [2012]. For a 

hard copy, contact Theresa Jain at tjain@fs.fed.us.