Rural Technology Initiative
College of Forest Resources
University of Washington
Box 352100
Seattle, WA 98195-2100
www.ruraltech.org

 

 

ACKNOWLEDGEMENTS

 

This work was made possible by a Community Assistance and Economic Action Program Grant WNFP-01-015 within the Multi-Agency National Fire Plan administered by USDA-Forest Service. The Freemont and Okanogan National Forests collaborated by providing forest inventory data and operational data on fires and management costs. Chelan County Public Utility District, the TurboSteam Corporation and Collins Pines collaborated on biomass production of energy information. Many local people from the USDA Forest Service, WA DNR, OR Department of Forestry, the Ecosystem Workforce Program, Sustainable Northwest, Lake County Resource Initiative, Okanogan Communities Development Council, Defenders of Wildlife, American Forest Resource Council, WA Contract Loggers Assoc., Oregon Associated Loggers, nineteen logging companies, nine sawmills and many other community representatives and interested individuals generously shared useful information relating to forest conditions, fuel reduction activities, the local infrastructure, contracting suggestions, harvest costs,and markets information. The carbon analysis benefited by supplemental funding provided by Columbia Pacific RC&EDD and EPA to demonstrate carbon tracking in response to forest management alternatives. The modeling capabilities also benefited by linking the findings of the Consortium for Research on Renewable Industrial Materials (www.CORRIM.org) with the Landscape Management System, a landscape planning system used extensively in the project and developed at the University of Washington (http://lms.cfr.washington.edu) Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the funding agencies or information providers.

 

EXECUTIVE SUMMARY

 

Abstract

Forest fuel reduction treatments are needed, as demonstrated by the increased number of devastating crown fires and annual increases in National Forest acres categorized as high risk. This report develops analysis components for effective fire risk reduction strategies to help professionals, publics, and policy-makers gain a better understanding of the current circumstances and alternatives. A range of thinning strategies were simulated and evaluated for the Okanogan and Freemont National Forests providing a set of results for comparative climatic and infrastructure conditions. Measures of fire risk reduction, economic cost, habitat protection, and carbon sequestration were evaluated, to develop the basis for characterizing both market and non-market values resulting from forest fires and fire risk reduction activities. The market cost of removing enough small diameter material to reduce fire risk sometimes exceeds the market value for the material removed. However, non-market benefits of reduced fire fighting and rehabilitation costs, facility losses and fatalities, protected habitats, sequestered carbon, saved water and other public values appear to more than offset treatment costs. Contracting alternatives and infrastructure needs are also evaluated. Treatment strategies can be customized to local forest and market conditions, providing the basis for management training as well as public education.

Management Strategies

The Okanogan and Fremont National Forests (ONF & FNF) were selected as case study areas to evaluate a range of management treatments that could reduce fire risk. They provide a north to south range in climate as well as substantially different market infrastructures. Forest inventory data were assembled from the Continuous Vegetation Survey (CVS) with 502 plots for FNF and 413 plots for ONF suitable for the analysis. Simulations of alternative treatments were produced using the Landscape Management System (LMS) developed at the Silviculture Laboratory of the College of Forest Resources, University of Washington in cooperation with the USDA Forest Service. For this investigation, LMS is used with the Forest Vegetation Simulator (FVS) as the growth model and the Fire and Fuels Extension (FFE), both developed by the USDA Forest Service. LMS also provides numerous habitat suitability and forest diversity measures, carbon sequestration measures and log production algorithms for economic analysis. This array of LMS outputs provides a consistent suite of metrics for measuring the critical influences of both fire and fire risk reduction management strategies.

Four thinning treatments were modeled: (1) removal of all trees with a DBH less than or equal to nine inches (9 and under); (2) thin from below (smaller trees first) removing 50% of the original basal area/acre (Half BA); (3) thin from below with a residual basal area target of 45 ft2/acre favoring ponderosa pine and western larch (BA 45); and (4) removal of all trees with a DBH greater than or equal to 12 inches to simulate a high revenue alternative (12 & over). In addition, (5) a no action alternative (with no disturbances) was developed (No action) and (6) a crown fire representative of each forest (Wildfire). All simulations were treated in 2000 and simulated growth of post-treatment inventories was modeled forward to 2030, without understory regeneration to mimic the impact of periodic controlled burns (or other fuel removals) and with understory regeneration to simulate natural ingrowth. Twelve total alternatives were simulated and analyzed for each of the 915 surveyed locations.

Fire Risk Assessment

Pre-treatment risk assessments indicated that 77.7% of the FNF plots and 76.8% of the ONF plots were at moderate to high risk of crown fire. This risk index is based upon the estimated wind speed in miles per hour (mph) at 20 feet off the ground needed to initiate an active crown fire from a surface fire. Wind speed estimates less than or equal to 25 mph were considered to be in a high fire risk category and from 25 through 50 mph in a moderate risk category. Estimates over 50 mph were considered low risk.

Treatment Results

The table below displays example risk reduction performance of treatment alternatives for the subset of FNF plots considered at high risk.

Treatment	High risk	Moderate Risk	Low risk
No action	100%	0%	0%
9 & under	37%	48%	15%
Half BA	7%	66%	27%
45 BA	2%	27%	71%
12 & over	80%	20%	0%
Wildfire	0%	0%	100%

Thinning 9 inch and under trees leaves 85% of the beginning high risk stands in a moderate or high risk category whereas retaining 45 BA almost eliminates the high risk with 29% in a moderate or high risk. Removing trees over 12 inches converts a few stands from high to moderate risk but none to low risk. Selection of best treatment alternatives can be customized to site conditions; however, removing some trees in the 9-12 inch diameter range is usually required for a substantive reduction in fire risk. With overstory trees retained and the understory re-established, fire risks return within 15-20 years.

Market Economics

Cost estimates for logging operations and treatment yield volumes are both site and equipment specific. As a result there is a significant range of variability in net revenue across all stands for the same treatment strategy. In addition, harvesters report that operations under federal contracts are uniquely costly indicating that refinements in federal contract requirements could reduce costs. Although the BA 45 treatment failed to generate the net economic returns of the 12 and over treatment, it produced the greatest risk reduction and, with low cost assumptions, provided a positive net return.

FNF average net revenue by treatment per acre

Treatment	High cost	Low cost
9 & under	($374)	($134)
Half BA	($319)	$139
45 BA	($168)	$529
12 & over	$1,244	$2,198

The range of net revenues per acre across all stands and treatments is quite large ($-2,015 to +11,414) indicating opportunities to customize treatments to specific conditions. Stands with positive revenues offset losses on other stands in this analysis of average impacts. A simple tradeoff between fire risk reduction and economics suggests treatment strategies can use positive revenue sites to compensate for revenue negative stand treatments. However, there may be other environmental considerations of importance as well. Habitat and carbon sequestration are both considered of high value by society. Additionally, there may be other economic values that are not reflected in treatment costs. Consideration of broader values of fire risk reduction provides a much more powerful motivator for fire risk reduction than looking only at net market revenue.

Wildlife Habitat

Treatments can substantially affect stand structure and, as a consequence, the habitat quality. Fires generally have a more extreme impact on habitat than any treatment. While the No action alternative might seem to benefit some species of wildlife, it assumes an unlikely eventuality of no fire and implicitly produces overstocked conditions different from pre- settlement forests with frequent fire return intervals. The impacts of the other treatments on habitat are mixed with some species benefiting at the expense of others. Habitat strategies associated with fire risk reduction are inherently local and need to be integrated into other objectives. Goshawks favor high-risk forests that are neither sustainable nor characteristic of pre-settlement conditions but their habitat can benefit from light thinnings and from avoidance of crown fires. The Lewis woodpecker can benefit from heavy thinnings if the largest trees and snags are retained. The Williamson's sapsucker needs soft snags making it very susceptible to fires. Pileated woodpeckers favor multi-story old forests, which are currently uncommon in the ONF or FNF. Retention of large trees and snags over time would eventually improve habitat for woodpeckers. The grizzly bear avoids stem exclusion structures and would favor a mix of treatments that reduces the dominance of overly dense stands. Analysis of the alternatives provides the opportunity to identify better habitat strategies in concert with other objectives and local conditions.

Carbon Analysis

Carbon is sequestered in the forest, and contributes undesirable emissions with fire, but is also stored in wood products for long periods. When biomass is converted to energy it displaces fossil fuels reducing carbon emissions. The 12 inch & over treatment produces the most flow of products and hence the most carbon sequestration but does not reduce the fire risk and is not sustainable. The BA 45 treatment produces the next highest level of carbon sequestration, reduces fire risk and is sustainable; in addition, much of the carbon is stored in products displacing energy-intensive substitute products like concrete and steel. As carbon credit markets are developed, they may contribute to treatment costs, paying for otherwise unprofitable treatments. Carbon is just one of the non-market benefits that result in positive values from fire risk reduction strategies.

Value Changes Associated with Fire Risk Reduction

While it is generally recognized that there are many non-market values that should be associated with fire risk reduction treatments, they are rarely articulated. With numerous outputs tabulated for each management strategy, it is possible to begin to put numbers on many non-market values. The tables below provide a conservative comparison of values and costs per acre for fire risk reduction in high and moderate risk forests. The benefits appear to far outweigh the costs, providing motivation for more aggressive fire risk reduction efforts than have been undertaken to date.

Market and Non-Market Values of Fire Risk Reduction/acre	Moderate	High
Reduced fire fighting cost	$231	$481
The value of reduced facilities losses	$72	$150
The value of reduced fatalities	$4	$8
The value of lost timber amenities	$371	$772
Habitat losses	?	?
The community value of fire risk reduction	$63	$63
Carbon credits	$20	$41
Green energy credits	?	?
Electrical transmission cost reductions	?	?
Regeneration and rehabilitation costs	$58	$120
Water quantity and quality	$86	$86
Regional economic benefits	$386	$386
Total Benefits	$1,291	$2,107

 

Costs of Fire Risk Reduction/acre	Moderate	High
Operational costs	$374	$374
Forest Service contract preparation costs	$206	$206
Soil compaction	?	?
Sedimentation	?	?
Impacts to wildlife habitats	?	?
Total Costs	$580	$580

While some non-market values have not been estimated, most appear to have lower order impacts and would probably not affect conclusions. While the value society places on habitat should be at least as high as the market revenue foregone, which can be roughly estimated from the 12 inch & over treatment revenue, habitats are more likely protected by treatments that avoid fire than by No action and should be significantly positive with more sustainable management.

Cogeneration Opportunity

Applying non-market values to motivate increased fire risk reduction treatments or selecting treatments that come close to breaking even does not by itself create a use for the lowest valued small diameter material harvested. Cogeneration in any number of forms adds value in the conversion of low-valued biomass to energy and can be considered a default use of material when higher-use markets are unavailable. Forest inventory analyses indicate that opportunities for cogeneration development exist on both forests. The primary limitation is assured access to sufficient biomass to warrant cogeneration investments. This raises the importance of contracting relationships and the sustainability of fire risk reduction planning.

Sustainability and Contracting

The Forest Service has generally been stymied in the process of completing environmental reviews and arranging contracting where costs and revenues are not directly related to positively valued timber markets. Stewardship End Result Contracts are being developed to allow negative revenue risk reduction operations that provide benefits such as contract longevity to support investments of risk capital in needed infrastructure.

Uses of the Report

This report provides parametric data on treatments that reduce fire risk, including their costs, market values, non-market values, and contracting issues. Specific examples can be used to customize strategies for a wide range of forest, infrastructure and market conditions. The information is also useful in training operators on how to design and layout fuel reduction treatments.

This report also demonstrates how an integrated forestry software package can assist federal agencies and other interested users in gaining greater efficiencies in planning fire risk reduction treatments to achieve multiple values with less conflict and less cost. The Landscape Management System (LMS) provides a sophisticated user-friendly software environment from which professional and public users with little training can participate in analysis of complex data to better understand the consequences of management alternatives. The results from case study analysis of two National Forests, presented in this report, demonstrate that fire risk can be effectively reduced while creating and protecting other positive environmental, economic, and social values.

 

TABLE OF CONTENTS

***(Read, save or print the PDF of this Report!)***

 

ACKNOWLEDGEMENTS
EXECUTIVE SUMMARY
LIST OF FIGURES
LIST OF TABLES

1. BACKGROUND

      1.1 The Forest
      1.2 The Risk
      1.3 The Imperative
      1.4 Better Information and Technology

2. METHODS

      2.1 Study Sites
      2.2 Technical Tools
            2.2.1 The Landscape Management System
            2.2.2 Forest Vegetation Simulator
            2.2.3 Fire and Fuels Extension to the Forest Vegetation Simulator
            2.2.4 Carbon Sequestration Model
            2.2.5 Wildlife Habitat Models
      2.3 The Data
            2.3.1 Current Vegetation Survey
            2.3.2 Literature and Reports
            2.3.3 Personal Interviews
      2.4 Assessments of Initial Forest Conditions
            2.4.1 Fire Risk Classification
            2.4.2 Forest Structure
            2.4.3 Forest Type
      2.5 Growth, Treatment, and Wildfire Simulation
      2.6 Analysis of Economics
            2.6.1 Conversions
            2.6.2 Logging and Hauling Costs
            2.6.3 Mill Log Values
            2.6.4 Net Revenue Calculation
            2.6.5 Market and non-market values of fire risk reduction

3. CASE STUDY SITE DESCRIPTIONS

      3.1 Fremont National Forest
      3.2 Okanogan National Forest

4. RESULTS

      4.1 Fire Risk Results
            4.1.1 Fremont National Forest
            4.1.2 Okanogan National Forest
      4.2 Economic Results
            4.2.1 Fremont National Forest
            4.2.2 Okanogan National Forest
      4.3 Cost to Fight Fire on the Fremont and Okanogan National Forests
      4.4 Wildlife Habitat
            4.4.1 Fremont habitat analysis results
                  4.4.1.1 No-action
                  4.4.1.2 Wildfire scenario (without regeneration)
                  4.4.1.3 Thinning treatments (without regeneration)
                  4.4.1.4 Wildfire scenario (with regeneration)
                  4.4.1.5 Thinning treatments (with regeneration)
                  4.4.1.6 Species summaries for FNF
            4.4.2 Okanogan habitat analysis results
                  4.4.2.1 No-action
                  4.4.2.2 Wildfire scenario (without regeneration)
                  4.4.2.3 Thinning treatments (without regeneration)
                  4.4.2.4 Wildfire scenario (with regeneration)
                  4.4.2.5 Thinning treatments (with regeneration)
                  4.4.2.6 Species summaries for ONF
      4.5 Carbon sequestration, displacement, and substitution
            4.5.1 Fremont
                  4.5.1.1 No-action
                  4.5.1.2 Wildfire
                  4.5.1.3 Treatments
                  4.5.1.4 Regeneration
            4.5.2 Okanogan
                  4.5.2.1 No-action
                  4.5.2.2 Wildfire
                  4.5.2.3 Treatments
                  4.5.2.4 Regeneration
      4.6 Market and Non-Market Values of Fire Risk Reduction
            4.6.1 Reduced fire fighting cost
            4.6.2 The value of reduced facilities losses and fatalities
            4.6.3 The value of lost timber amenities
            4.6.4 Habitat losses
            4.6.5 The community value of fire risk reduction
            4.6.6 Carbon credits
            4.6.7 Green energy credits
            4.6.8 Electrical transmission cost reductions
            4.6.9 Regeneration and rehabilitation costs
            4.6.10 Water quantity and quality
            4.6.11 Regional economic benefits
            4.6.12 Summary of Market and Non-Markets Values of Fires Risk Reduction
      4.7 Cogeneration Analysis
      4.8 Contracting and Public Outreach
            4.8.1 Excessive analysis
            4.8.2 Ineffective public involvement
            4.8.3 Management inefficiencies
            4.8.4 Stewardship Contracting

5. CONCLUSIONS AND DISCUSSION

WORKS CITED

APPENDICES- ( read , print or save the PDF version.)

      APPENDIX A. FIRE RISK CLASSIFICATION
      APPENDIX B. FREMONT NATIONAL FOREST
      APPENDIX C. OKANOGAN NATIONAL FOREST
      APPENDIX D. WILDLIFE MODELS
      APPENDIX E. EQUIPMENT INVESTMENT AND OPERATIONS COST E

LIST OF FIGURES

Figure 3.1	Fremont National Forest Boundaries
Figure 3.2	FNF Forest Type Distribution
Figure 3.3	FNF Elevation Class Distribution
Figure 3.4	FNF Canopy Structure Distribution
Figure 3.5	FNF Dominant Species Distribution
Figure 3.6	FNF TPA Class Distribution
Figure 3.7	FNF QMD Class Distribution
Figure 3.8	FNF BA Class Distribution
Figure 3.9	FNF Risk Distribution
Figure 3.10	Okanogan National Forest Boundaries
Figure 3.11	ONF Forest Type Distribution
Figure 3.12	ONF Elevation Distribution
Figure 3.13	ONF Canopy Structure Distribution
Figure 3.14	ONF Dominant Species Distribution
Figure 3.15	ONF TPA Class Distribution
Figure 3.16	ONF QMD Class Distributions
Figure 3.17	ONF BA Class Distribution
Figure 3.18	ONF Risk Distribution
Figure 4.1	FNF High Risk Species Distributions
Figure 4.2	FNF High Risk Structure Distributions
Figure 4.3	FNF Low Risk Species Distributions
Figure 4.4	FNF Low Risk Structure Distributions
Figure 4.5	FNF High Fire Risk Response to Six Simulations with Regeneration
Figure 4.6	FNF High Fire Risk Response with No Regeneration after Treatment
Figure 4.7	ONF High Risk Species Distributions
Figure 4.8	ONF High Risk Structure Distributions
Figure 4.9	ONF Low Risk Species Distributions
Figure 4.10	ONF Low Risk Structure Distributions
Figure 4.11	ONF High Fire Risk Response to Six Simulations with Regeneration
Figure 4.12	ONF High Fire Risk Response with No Regeneration after Treatment
Figures 4.13 and 4.14	FNF Net Revenue High and Moderate Risk Stands with Low Costs
Figures 4.15 and 4.16	FNF Net Revenue High and Moderate Risk Stands with High Cost
Figures 4.17 and 4.18	ONF Net Revenue for High and Moderate Risk Stands with Low Cost
Figures 4.19 and 4.20	ONF Net Revenue High and Moderate Risk Stands with High Cost
Figure 4.21	Fremont National Forest Fire Suppression Average Costs/Acre by Magnitude for 1992-2002
Figure 4.22	Okanogan-Wenatchee National Forest Fire Suppression Average Costs/Acre by Magnitude for 1990-2002
Figure 4.23	Source Habitat (ICBEMP; Wisdom et al. 2000a) Structural Stage Classifications Identify both of these Stands as Being Within the Same Stage - 'Stem exclusion (open canopy)'
Figure 4.24	Initial Habitat Distributions for Selected Species in Moderate to High Risk Areas in the FNF
Figure 4.25 a,b,c	Initial Habitat Distributions for Selected Species Displayed by Risk Class in the FNF
Figure 4.26	Initial Habitat Distributions for Selected Species in Moderate to High Risk Areas in the ONF
Figure 4.27 a,b,c	Initial Habitat Distributions for Selected Species Displayed by Risk Class in the ON
Figure 4.28	Present Value Estimations of Future Fire Fighting Costs
Figure 4.29	Present Value of a Perpetual Annual Series
Figure 4.30	The Landscape Management System Provides Visual, Tabular, and Graphical Capabilities

LIST OF TABLES

Table 2.1	Interviews
Table 2.2	Fire Risk Classifications
Table 2.3	Tons per Thousand Board Feet (MBF) for Eastern Washington and Oregon
Table 2.4	FNF and ONF Low and High Logging, Hauling/MBF and PCT Costs per Acre
Table 2.5	Regional Log Sort Values $/MBF Used for Economic Valuation
Table 3.1	Acres in Initial Fire Risk Class for Forests on FNF and ONF
Table 4.1 a,b,c	FNF Post-treatment Conditions for Stand Originally in High and Moderate Risk Classes
Table 4.2 a,b,c	ONF Post-treatment Conditions for High and Moderate Risk Classes
Table 4.3	FNF Mean Net Revenue for Thinning Treatments on High and Moderate risk forests with High and Low Logging Costs
Table 4.4	ONF Mean Net Revenue for Thinning Treatments on High and Moderate risk forests with High and Low Logging Costs
Table 4.5	Average Metric Tons per Acre of Carbon in the Forest by Treatment for the FNF
Table 4.6	Average Metric Tons per Acre of Carbon in Products by Treatment from the FNF
Table 4.7	Average Metric Tons per Acre of Carbon in the Forest, Products, and Displacement by Treatment in the FNF
Table 4.8	Average Metric Tons per Acre of Carbon in Forest, Products, Displacement, and Substitution by Treatment in the FNF
Table 4.9	Average Increase in Metric Tons per Acre of Carbon with Regeneration
Table 4.10	Average Metric Tons per Acre of Carbon in the Forest by Treatment for the ONF
Table 4.11	Average Metric Tons per Acre of Carbon in Products by Treatment from the ONF
Table 4.12	Average Metric Tons per Acre of Carbon in the Forest, Products, and Displacement by Treatment in the ONF
Table 4.13	Average Metric Tons per Acre of Carbon in Forest, Products, Displacement, and Substitution by Treatment in the ONF
Table 4.14	Average Increase in Metric Tons per Acre of Carbon by 2030 by Treatment with Regeneration
Table 4.15	Parametric Present Value Estimations of Fire Risk Costs with Assumptions of $1000/acre to Fight Fire and 5% as the Discount Rate
Table 4.16	Present Value (PV)/acre of Theoretical WTP Annual Contributions from Households for Protection from Wildfire on the FNF and ONF (Note that PV is Less for FNF because of Less Population and More Acres at Risk)
Table 4.17	Summary of Total Values/Acre Estimations of Benefits Associated with Fire Risk Reductions
Table 4.18	Summary of Estimated Costs that Might be Associated with Fire Risk Reduction Treatments

1. BACKGROUND

1.1 The Forest

Changes in forest composition and structure due to a century of fire suppression, grazing, and past harvest practices have been widely documented (Pyne 1997, Arno 2000). Where once frequent fire return intervals resulted in savanna-like forest conditions, now dense understories of shade-tolerant species have become established (Pfilf et al. 2002). Outbreaks of insects and of root disease have resulted in large areas of tree mortality (Stewart 1988). Dead trees and multiple layered canopies have become ladder fuels and increase risk of destructive wildfires. Concerns about large areas of National Forest lands in the inland west that are overstocked with small diameter suppressed trees are not new (Cooper 1960, Pyne 1982). However, increases in forest fire severity, extent, and costs in recent years have served to focus public attention on the widespread and urgent nature of this problem (Agee 1993, Western Governors Report 2001 and 2002). In 2002, Interior Secretary Norton estimated that 2/3 of public lands (more than 120 million acres) are at moderate to high risk of catastrophic fire (Norton 2002).

1.2 The Risk

While the average annual population growth over the last two decades in the United States has been about 1%, western states have experienced growth rates ranging from 2.5 to 13% (Riebsame 1997, Babbitt and Glickman 2000). As a result, development has occurred adjacent to federal lands in what has become known as the "wildland/urban interface". Consequently, risk from forest fires to private property and human life has increased making fire fighting more complicated, expensive, and dangerous (Babbitt and Gickman 2000).

In the period between 1990 and 1998, 133 individuals died while involved in fighting wild fires (Mangan 1999). Loss of life resulting from fire fighting activities is not the only health hazard associated with forest fires. Because of the fine particulate matter and other pollutants present in the smoke, forest fires can pose a significant health threat to people living in the "wildland-urban interface" (GAO/RCED-99-65 1999, Norton 2002). Smoke from forest fires increases atmospheric carbon associated with global warming (Buchanan and Keye 1997). Intense forest fires create other undesirable environmental consequences such as destruction of wildlife habitat and pollution of surface waters (Camp 1995, Laverty and Williams 2000, Hill 1998). Without intervention, these burned lands recover slowly and may be susceptible to vegetation changes that result in undesirable ecological consequences (Babbitt and Glickman, 2000).

Economic impacts from forest fires are considerable. Costs to fight forest fires reached record breaking proportions in 2000 when the federal government spent $1.5 billion on 8.3 million acres only to have the record broken again in 2002 when costs reached $2.2 billion on 7.2 million acres (The Office of the President 2002). However, these costs do not reflect other economic impacts at the federal level that result from losses of valuable timber resources or from post-fire expenditures such as forest regeneration. In addition to federal costs from fires are losses incurred by state and local governments or by the private sector. For example, after the 2000 fire season, Montana Governor Racicot estimated that businesses had lost about $3 million a day because of fire. Idaho Governor Kempthorne estimated losses in Idaho at $54.1 million overall, of which $15 million came from about 500 small businesses (Babbitt and Glickman 2000).

1.3 The Imperative

In 2000, the USDA Forest Service outlined a strategy to address forest health and wildfire in the forests of the inland west entitled Protecting People and Sustaining Resources in Fire-Adapted Ecosystems; a Cohesive Strategy (Laverty and Williams 2000). This report states that, "Without increased restoration treatments in these ecosystems, wildland fire suppression costs, natural resource losses, private property losses, and environmental damage are certain to escalate as fuels continue to accumulate and more acres become high-risk." The report goes on to identify the key components of a national strategy to deal with unprecedented wildfire risk:

Improve fire prevention and suppression
Reduce hazardous fuels
Restore fire-adapted ecosystems
Promote community assistance

1.4 Better Information and Technology

The challenge of developing long term strategies to reduce wildfire risks across tens of millions of acres of inland west forest is daunting. The body of information to be considered is huge and the planning process may be formidable. Infrastructure is limited, funding is scarce, costs high, and conflicts rampant (USDA Forest Service 2002). Strategies to help professionals, publics, and policy-makers gain better understanding of the present circumstances and the future possibilities of forest fire risk could be helpful. Areas of greatest risk will need to be prioritized for immediate attention. Predictive capabilities will be needed to assess future effectiveness of alternative treatment strategies for the achievement of risk reduction and other multiple-use management objectives. Development of efficient fuels reduction treatments at the least cost customized to local conditions will be necessary. Interested members of the lay public must be informed of present conditions and future possibilities such that choices for action are not confusing and subject to distrust.

This project will demonstrate how emerging modeling and data analysis technologies can assist the planning of fuel removal treatments for the achievement of multiple management goals. This project will also provide suggestions on how forest treatments to reduce fire risk might be customized to local conditions in order to lower costs and increase effectiveness. The project findings will provide the basis for developing technical tools, instructional materials, and training modules for creation of educational materials to assist the Forest Service and cooperating publics in the collaborative development of effective management strategies for the reduction of risk from catastrophic wildfire within dry site National Forests. The technologies useful for planning today will provide enduring benefit as the technologies used to assist monitoring and evaluation in the future.

 

2. METHODS

This project has developed a parametric sensitivity analysis to be used in tandem with existing modeling capabilities to assess the relative costs and benefits of alternative fuels reduction strategies. Additional information needed to gain better understanding of the opportunities and obstacles associated with fuel removal activities on federal lands has been gathered from the scientific literature, government publications, and personal interviews with forestry professionals and community representatives.

2.1 Study Sites

The Okanogan National Forest (ONF) in Washington and the Fremont National Forest (FNF) in Oregon were selected as case-study areas for this project. Both of these National Forests are located within the dry interior portion of the western United States. Both the Okanogan and the Fremont National Forests contain substantial acreages of overstocked forests that are considered to be at risk from wildfire. Both National Forests have experienced destructive wildfires in recent years. The rural communities surrounding these National Forests have double-digit unemployment and have experienced economic declines due to job losses associated with reductions in federal timber harvest volumes. Individuals, organizations, and businesses from both areas demonstrated interest in this investigation and contributed valuable reference information through personal interviews.

2.2 Technical Tools

2.2.1 The Landscape Management System

The effects of forest management alternatives on fire risk reductions, forest product outputs, economic metrics, wildlife habitat, and carbon sequestration were simulated using the Landscape Management System (LMS). LMS is an evolving computer-based, landscape-level forestry analysis software tool developed at the University of Washington College of Forest Resources (McCarter1997, McCarter et al. 1998, McCarter 2001). LMS offers a software platform for the integration of component capabilities that include growth and yield models, interactive stand treatment simulation programs, tabular and graphical analytical outputs, and stand and landscape visualization programs. Data sources necessary for LMS include stand inventory information (tree-based measurements), landscape data (slope, aspect, elevation, site quality), and Geographic Information System (GIS) spatial data (stand boundaries, streams, roads, etc.). LMS can be used to project stands and landscapes forward in time to predict potential future stand and landscape forest conditions, while virtually treating stands through harvesting, regeneration, and other activities to simulate potential management practices. The user interface within LMS is designed to provide a user-friendly "click and go" command format. The intended result is that this powerful forestry software is available for use by individuals with minimum computer skills and limited financial resources. Consequently, LMS has proven to be beneficial not only as a powerful analysis support tool for forestry professionals but also as a communication tool for use with stakeholder groups embarked on the often conflict-vulnerable process of consensus building (Courtmanche 2002). LMS is available for download and provided at no charge through a forestry research partnership between the University of Washington and Yale University. The web site address is http://lms.cfr.washington.edu/.

2.2.2 Forest Vegetation Simulator

The Forest Vegetation Simulator (FVS) is an individual-tree, distance-independent growth and yield model (Crookston 1990, Van Dyck 2000). FVS will simulate growth and yield for most major forest tree species, forest types, and stand conditions. FVS can simulate a wide range of silvicultural treatments. Variants of FVS provide growth and yield models for specific geographic areas of the United States. Prognosis (Stage 1973) is the original model that evolved into the Forest Vegetation Simulator. Stage developed Prognosis for use in the Inland Empire area of Idaho and Montana. In the early 1980s, the National Forest System's Timber Management Staff selected the individual-tree, distance-independent model form as the nationally supported framework for growth and yield modeling. Over the following years, the Forest Management Staff's Growth and Yield Unit incorporated much of the Prognosis modular structure and capabilities into the national model framework. This model framework is the Forest Vegetation Simulator, or FVS (Wykoff et al. 1982). There are 21 different FVS variants. Each is calibrated to a specific geographic area of the United States. Various extensions are available for some of the variants. These extensions provide the ability to estimate the influence of other agents upon tree growth (such as insects, disease, and fire), extend FVS modeling capabilities, and permit multiple stand simulation. For the simulations needed for this investigation the East Cascades Variant (EC) of FVS and the South Central Oregon and Northeastern California Variant (SORNEC) of FVS were selected for use within LMS to contribute growth-modeling capabilities for the Okanogan National Forest and the Fremont National Forest respectively. More information and a suite of FVS regional variants are available for download at no charge from the USFS web site at: http://www.fs.fed.us/fmsc/fvs/.

2.2.3 Fire and Fuels Extension to the Forest Vegetation Simulator

The Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS) links existing FVS models, that represent fire and fire-effects, with newly developed fuels dynamics and crowning submodels (Beukema et al. 1997, Scott and Reinhardt 2001). The Fire and Fuels Extension (FFE) has been developed to assess risk, behavior, and impact of fire in forest ecosystems (Beukema et al. 2002). FFE can produce reports of changes in various indices of potential fire severity as a result of alterations to stand characteristics resulting from simulated management alternatives. More information and downloadable FFE for use with selected variants of FVS are available for download at no charge from the USFS web site at: http://www.fs.fed.us/fmsc/fvs/.

2.2.4 Carbon Sequestration Model

A life cycle assessment process has been developed to serve as an accounting system for the carbon consequences of forest management alternatives (Manriquez, 2002). Estimates of changes in the amount of carbon stored over time in the standing forest are calculated using biomass to carbon conversion factors specific by species for tree bole, bark, foliage, limbs, and roots. Estimates of carbon stored in harvested wood products are also calculated. Estimates of carbon emitted to the atmosphere from harvesting and manufacturing operations are considered as reductions to carbon stored in wood products. Estimated as well is the amount of carbon not emitted due to displacement of fossil fuels in energy generation by wood used in a wood boiler, and substitution of wood for steel for construction materials. The model is implemented in Microsoft Excel and designed to work in tandem with LMS, allowing a comprehensive estimate of forest carbon storage, substitution, and displacement over time for different management alternatives. This carbon assessment process is based on studies of wood biomass (Gholz, 1979), carbon content (Birdsay, 1992), decomposition (Harmon, 1993), product utilization (Bowyer et al, 2002), harvesting and manufacturing emissions (Franklin Associates, 1998), fossil fuel displacement (Bowyer et al, 2002), and construction material substitution (Bowyer et al, 2002). Changes in forest biomass from growth (simulated with a growth model) and decomposition are simulated and converted to stored carbon estimates. Carbon amounts are moved from the forest to the products pool following a silvicultural operation, simulated in LMS. The model calculates log utilization to determine amounts of short-term and long-term products. These products are either decomposed through time or used in displacement (short-term) or substitution (long-term). Emissions from harvesting and manufacturing are determined from the types of silvicultural treatments done and the amount of harvest volume removed and processed.

2.2.5 Wildlife Habitat Models

Wildfires and forest management activities result in changes to wildlife habitat quality. When fuel removal treatment alternatives are compared to the potential impacts of wildfire, it is important, therefore, to consider the implications for wildlife habitats. Habitat suitability modeling provides an estimate of habitat quality (an index from 0.0-1.0) and quantity (i.e. area of the landscape) consolidated into a single metric known as a 'habitat unit' for each species of interest. Wildlife habitat models are analyzed to assess the tradeoffs in habitat units associated with various management alternatives. For some species, Habitat Suitability Index (HSI) models are available from the U.S. Fish and Wildlife Service (USFWS 2001); for others, habitat models developed by the U.S. Forest Service (Wisdom et al. 2000b) for the Interior Columbia Basin Ecosystem Management Project (ICBEMP) are used. Wildlife species analyzed differed between the two National Forests due to geographic ranges, model availability, and species of concern. Lists of species identified as important for consideration in this project were obtained from Kent Woodruff, Okanogan National Forest biologist, and Brent Frazier, Fremont National Forest biologist.

Changes to wildlife habitat conditions resulting from treatment simulations were analyzed for nine species on the Okanogan National Forest:

northern goshawk (Accipiter gentilis)
Lewis' woodpecker (Melanerpes lewis)
white-headed woodpecker (Picoides albolarvatus)
Williamson's sapsucker (Sphyrapicus thyroideus)
Canada lynx (Lynx canadensis)
grizzly bear (Ursus arctos)
pileated woodpecker (Dryocopus pileatus)
northern flying squirrel (Glaucomys sabrinus)
Townsend's big-eared bat (Corynorhinus townsendii)

Changes to wildlife habitat conditions resulting from treatment simulations were analyzed for seven species on the Fremont National Forest (all of above except lynx and grizzly bear):

pileated woodpecker (Dryocopus pileatus)
northern flying squirrel (Glaucomys sabrinus)
Townsend's big-eared bat (Corynorhinus townsendii)
northern goshawk (Accipiter gentilis)
Lewis' woodpecker (Melanerpes lewis)
white-headed woodpecker (Picoides albolarvatus)
Williamson's sapsucker (Sphyrapicus thyroideus)

Habitat Suitability Index (HSI) models were developed by the U.S. Fish and Wildlife Service for use in Habitat Evaluation Procedures (USFWS 1980a, 1980b). These predictive models estimate the habitat quality of particular patches or units (i.e. stands) for a given wildlife species based on a combination of variables (e.g. canopy closure, snag density, basal area). For species of concern for which HSI models are not available, a second category of habitat models is used. These species habitat models are referred to as forest structural stage models or "species source habitat matrix" models and were developed by the U.S. Forest Service (Wisdom et al. 2000b) for use with the Interior Columbia Basin Ecosystem Management Project (ICBEMP). These ICBEMP models are based upon matrix tables that provide the source habitat types (combination of cover type and structural stage) for 91 terrestrial vertebrate species within the interior Columbia River basin. Source habitats are defined as, "those characteristics of macrovegetation that contribute to stationary or positive population growth for a species in a specified area and time." A stand is categorized as either being a source habitat or not. There is no consideration of marginal habitat.

HSI models for four bird species were used on both Forests:

Northern Goshawk

Aspect (Fremont only) Basal area Quadratic mean diameter

Lewis' Woodpecker

Canopy cover Snags

White-headed Woodpecker

Aspect Canopy cover Snags Large ponderosa pine density Number of pine species

Williamson's Sapsucker

Canopy cover Snags

Documentation of these models, including variable thresholds and HSI equations, can be found in Appendix D. For the Lewis' woodpecker (Sousa 1982) and Williamson's sapsucker (Sousa 1983), models were available from the USFWS (2001). Modifications were made to both of these models to facilitate their use in this project. The changes are documented in Appendix D. The goshawk and white-headed woodpecker models were developed using available scientific literature and discussions with species experts throughout the region (Weber and Cannings 1976; Bull et al. 1986; Milne and Hejl 1989; Blair and Servheen 1993; Garrett et al. 1996).