economics
The Irrationality of Continued Fire
Suppression: An Avoided Cost
Analysis of Fire Hazard Reduction
Treatments Versus No Treatment
ABSTRACT
Gary Snider, P.J. Daugherty, and D. Wood
Without large-scale implementation of fire hazard reduction treatments, the costs of uncharacteristic
crown fires in southwest forests will continue to increase. Federal policy continues to allocate vastly more
funds to suppression than to prefire hazard reduction. We examined the economic rationality of
continuing this policy of emphasizing fire suppression activities over restoration-based fire hazard
reduction treatments. We compared treatment plus fire suppression costs to the cost of fire suppression
without treatments over 40 years for southwestern forests. This avoided-cost analysis estimates the
amount one could invest in treatments to avoid the future cost of fire suppression. Using conservative
economic values, we found that avoided future costs justifies spending $238 – 601/ac for hazard
reduction treatments in the southwest. We conclude that the policy of underfunding hazard reduction
treatments does not represent rational economic behavior, because funding hazard reduction would pay
for itself by lowering future fire suppression costs.
Keywords: economics, restoration, avoided cost, fire, fire hazard reduction
T
he history and culture of forest
fires in the United States has been
chronicled and described by Pyne
(1982), Pyne et al. (1996), and Arno and
Allison-Bunnell (2002). In 1905, the Bureau of Forestry became the USDA Forest
Service with the responsibility of protecting newly designated forest reserves. A
critical part of its charge was the prevention and control of fires. In 1908, Congress set up a system, “like an open checkbook,” that essentially authorizes deficit,
unlimited expenditures for fire suppression (Pyne et al. 1996, Arno and AllisonBunnell 2002). Subsequent to the fires of
1910 the Forest Service embarked on a
campaign to “battle fire to death” (Pyne
2004). Since that time the fire suppression
checkbook has never run out of blank
checks and remains open to this day.
Although it has become increasingly
apparent that an ounce of presuppression activity is worth a pound of suppression funds
(Pyne et al. 1996, Daugherty and Snider
2003) federal land-management agencies
continue to allocate vastly more funds to
suppression activities than to prefire hazard
reduction. To a large degree, the history and
institutional culture of management agencies and a long-conditioned public have perpetuated this policy of investing in the further disruption of fire cycles and the
continued depreciation of forest values. In
this article we examine the economic rationality of continuing this policy.
Historical practices starting with Euro-
pean settlers (e.g., overgrazing in the late
1800s, selective harvesting of large trees, and
fire exclusion) have created vast areas of unhealthy forest ecosystems in the southwestern United States (Covington and Moore
1994). These practices have caused significant structural and functional changes in
southwestern ponderosa pine (PP) and dry
mixed-conifer (DMC) forests that include
unprecedented tree densities and fuel loadings and anomalous fire regimes that are inconsistent with the region’s evolutionary
history (Covington and Moore 1994,
Dahms and Geils 1997). The overly dense
conditions, exacerbated by drought, have increased bark beetle mortality and the size
and frequency of stand-replacing crown
fires. These interconnected symptoms warn
society of the jeopardy of losing these forest
ecosystems. To avoid this loss, we must implement large-scale restoration-based thinning treatments designed to significantly reduce tree densities, improve the cover,
composition and production of the herbaceous understory, and reintroduce fire to its
normal disturbance regime (Fule et al.
2002), sooner rather than later.
Rieman et al. (2003) argued that we
need additional study as to the effects of restoration-based thinning treatments and the
use of fire in management on organisms,
habitats, watersheds, and ecosystem processes. Continued study and research is necessary if we are to truly implement adaptive
Journal of Forestry • December 2006
431
management (AM); however, the tired
“more research is needed” mantra should
not be used as an excuse to forego large-scale
restoration-based fuel treatments. Hardy
(2005) notes that there is no possible single
metric capable of integrating all that must be
considered with respect to fire hazard, and
Finney (2005) states that the calculations required to determine burn probabilities and
fire behavior are computationally and practically impossible because of the nearly infinite sequences of weather and ignition timing and location.
The significant gaps in our understanding of probabilities and effects are not limited to fire ecology and management. An
analogous situation exists in fire economics.
Fairbrother and Turnley (2005) have argued
that without an understanding of the type,
likelihood, and magnitude of changes that
will result from fire (uncharacteristic or controlled burns) or conversely from the lack of
fire, one can not quantify the risks, costs,
and benefits associated with fire management activities. Kline (2004) describes the
typical steps in determining the expected
value of present net benefits and the information that would be required to make these
calculations. First, one must know the probability of an uncharacteristic wildfire occurring at any given point in space and time
with and without treatment. This information is not going to be available any time
soon. He further states that any attempt to
evaluate the net benefits of fuel treatments
via cost-benefit analysis would require such
information on everything from potential
changes in fire severity and suppression costs
to effects on forest conditions and ecological
functions. This information must be sufficient to meet prevailing demands for scientific quality in forest management and policymaking. He concludes that currently there
is insufficient information and analysis to
determine whether or not investment in hazardous fuel treatments represents a rational
economic choice. Conversely, the same lack
of information and analysis could have been
used to argue that we can not determine that
continuing the current policy represents a
rational choice, implying that a change in
policy requires rationality, while continuation does not.
Although empirical precision and theoretical rigor improve the accuracy of costbenefit analysis, obviously unattainable precision is unnecessary for policymaking.
Given the current conditions of PP and
DMC forests of the arid southwest and the
432
Journal of Forestry • December 2006
inevitability of future uncharacteristic largescale crown fires, simple and relevant is preferable to elegant and inexpedient. Although
we understand that the issue is not a simple
dichotomy between fire suppression and
treatment, we argue that waiting for a complete understanding of the social and ecological complexities before taking significant
action is folly.
A number of recent studies have asked
the question, How much are fire hazard reduction treatments going to cost and can society afford to pay for restoration-based
treatments? These studies examined the financial feasibility of implementing these
types of treatments (Lynch et al. 2000, Fiedler et al. 2002, Larson and Mirth 2004). In
general, these studies found it difficult to
justify treatment expenditures based on the
value of the wood fiber removed by the treatments. This conclusion suggests that restoration-based fuel treatments must be considered an investment and would need to be
justified by the marginal benefits/value provided by a healthy ecosystem. However, it is
possible we have been asking the wrong
question. Perhaps the question we should be
asking is, Can we afford not to implement restoration-based hazardous fuel reduction/thinning treatment? In other words, will continuing the current policy of emphasizing fire
suppression cost society more than the alternative of investing in hazard reduction.
The ever-increasing cost of not doing
restoration-based hazard reduction treatments suggests an approach for determining
the level of investment that avoids the aforementioned described difficulties with costbenefit analysis. One can set a conservative
lower bound on the amount to be invested
by setting hazard reduction funding at least
equal to the direct costs, such as fire suppression, that would be avoided by investing—in other words, each dollar invested in
restoration-based hazard reduction would
save at least a dollar in suppression. This
study presents results of an economic analysis comparing the cost of implementing restoration-based hazard reduction treatments
to no treatment for areas identified at high
risk for crown fire. The with- and withouttreatment comparison focuses on PP and
DMC forest ecosystems in Arizona and New
Mexico (Forest Service Region 3). The analysis provides a conservative estimate of the
potential economic losses due to a continuation of policies that emphasize suppression
over proactive restoration-based hazard reduction treatments.
Methods
We developed a relatively simple economic analysis that compares the costs of
restoration-based hazard reduction treatments to the costs of fire suppression and
rehabilitation expected without treatment.
This avoided-cost approach answers the
question of how much can we invest in prevention to avoid the continued cost of fire
suppression and rehabilitation. The approach assumes that the cost avoided (fire
suppression) by investment is otherwise unavoidable, which is clearly the case with
wildfire in the wildland-urban interface.
We used a 40-year time horizon for analyzing costs and a 4% discount rate for converting costs to PV. Annual suppression and
rehabilitation costs were discounted to the
present and summed to yield the present
value (PV) of costs without treatments. Hazard reduction treatments were assumed to
have an initial cost (e.g., restoration thinning and burning) plus maintenance costs
(e.g., prescribed fire) that occurred every 10
years after the initial treatment. The withtreatment PV was calculated as the sum of
the discounted costs of initial and maintenance treatments and the discounted costs
of reduced fire suppression and rehabilitation. The net PV (NPV) of treatment was
determined using a “with” minus “without”
procedure: the PV without restorationbased treatments was subtracted from the
PV with treatment to calculate the net value
of the treatment. This difference (NPV) between projected with- and without-treatment costs represents a partial measure of
the economic value of these treatments, i.e.,
the net avoided cost due to treatment. We
determined break-even values by raising or
lowering the initial treatment cost per acre
until the NPV equaled zero. The break-even
value indicates the dollar per acre that could
be spent on treatment such that the PV of
the treatment costs is just covered by the PV
of avoided fire suppression and rehabilitation costs.
Study Area. The PP and DMC forests
of Arizona and New Mexico provide a good
application area for the analysis. These forests have undergone important changes,
with two of the most important being simplification in structure and unprecedented
increased tree densities (from about 50
trees/ac to upward of a 1,000 trees/ac).
These conditions have resulted in increased
fuel and the existence of a continuous fuel
ladder. In 2002, there were 9,887,181 ac of
Table 1. Acres and percentage of Ponderosa pine (PP) and dry mixed-conifer (DMC) by
fire regime condition class for Arizona and New Mexico combined.
PP
DMC
Total
Class percent
Class 1
Class 2
Class 3
Total
475,184
246,858
722,042
7.3
5,805,000
6,425
5,811,424
58.8
3,190,625
163,090
3,353,714
33.9
9,470,808
416,373
9,887,181
100.0
Source: Based on data from Schmidt et al. (2002).
PP and DMC forests in Arizona and New
Mexico (Table 1). Over 90% of these forests
are at high (condition 3) or moderate (condition class 2) risk of losing key ecosystem
components (Schmidt et al. 2002). It is not
possible to know exactly when, where, or the
size of a future fire. We do know that given
the current condition of the PP and DMC
forests of the arid southwest, those areas at
high risk are going to burn.
Data and Model Assumptions. We set
the initial expected acres burned per year
without treatment at 443,307 ac. This figure
was based on the average annual fire acreage
for fires greater than 100 ac on state and
federal lands in Arizona and New Mexico
during the period 1993–2002 (National Interagency Fire Center [NIFC] 2003). The
443,307 ac represent approximately 4.5% of
the total acreage of PP and DMC forests in
Arizona and New Mexico. We assumed that
future fire occurrence will be similar to that
experienced during that decade.
We computed the costs for suppression and rehabilitation as the average per
acre expenditure for large fires (greater
than 100 ac) on public lands for which the
Forest Service provided suppression support during the period 1993–2002 (Gebert 2003). All costs were converted into
2002 dollars. We only included variable
costs directly associated with large fires.
We did not include fixed costs of preparedness. During this period Forest Service Region 3 spent an average of $377/ac
per year on suppression for large fires. The
$377/ac fire suppression cost is slightly
less than the $387/ac figure reported by
Donovan and Noordijk (2005). They
spent an additional $22/ac per year on
emergency rehabilitation, which only covers emergency measures to control erosion/sedimentation and only occurs on a
limited number of acres. Rehabilitation
does not include reforestation activities.
This approach assumes that Forest Service
costs are adequate estimators of costs on
all public lands.
We assumed that restoration-based
fire hazard reduction treatments can eventually eliminate large-scale, uncharacteristic crown fires and associated variable costs
of large-fire suppression and rehabilitation
incurred in the recent past. We assumed
that a given amount of acres required
treatment and that the number of largefire acres would diminish in proportion to
the amount of required acreage shifted
from high or moderate risk to low risk. We
assumed that the restoration-based hazard
reduction treatment would shift forestland to low risk. We also assumed that
large fires also shifted forestland to low
risk. The reduction in large-fire acreage
was assumed to occur for both causes of
shifts to low risk. In other words, both the
with- and without-treatment scenarios results in reduction of large fires, with the
difference being that treatment can accelerate the reduction in large fires. As largescale, uncharacteristic crown fires are diminished, the associated variable costs of
fire suppression and rehabilitation will diminish also.
We kept the model simple by only including direct costs in the comparison of
treatment versus no treatment. We did not
account for losses and damages to structures,
private land value, and other infrastructure
associated with the wildland-urban interface. We also did not include nonmarket values associated with ecological goods and services. These nonmarket values include
recreation, wildlife habitat, watershed condition, and water quality. These values generally are considered to be improved by restoration-based fuel treatments (Mason et al.
2006). Finally, we did not include lost timber harvest values. These values could be
substantial, or not, depending on the resolution of such issues as the imposition of diameter caps and the successful development
of a private sector smallwood utilization industry. Given that the only benefits accounted for in this analysis are the fire suppression and rehabilitation costs avoided,
the total economic value of the restorationbased fuel treatments are significantly underestimated.
Analytical Scenarios. We developed
analytical scenarios by varying the required
number of acres to be treated and the rate at
which they are treated (Table 2). We initially set the required number of acres to be
treated at either 33 or 50% of the total acreage of PP and DMC forests in Arizona and
New Mexico (3,262,770 or 4,943,590 ac).
We used three treatment rates: treating 5,
10, and 15% of the required acres per year.
We set the initial treatment cost to $200/ac,
and used $50/ac for the maintenance treatments that occur every 10 years after initial
treatment. We then varied the initial treatment costs to determine the break-even values. For these scenarios, we applied the assumption that reduction in large-fire
occurrence would be proportional to the
amount of required acres treated.
To test the sensitivity of results to the
amount of acres requiring treatment, we
conducted a series of sensitivity analyses
(SEN) that varied the required amount from
30 to 65% of the forest (2,966,154 to
6,426,667 ac). For these scenarios we used
annual treatment rates of 5 and 15% of required acres.
To test the sensitivity of the analysis to
the proportional reduction assumption, we
developed an additional scenario that incorporates a time lag before reductions in fire
suppression and rehabilitation costs occur.
This lag scenario (LAG) addresses the concept that a certain amount of strategically
located treatment must occur before gaining
any significant reduction in large-fire occurrence and associated fire suppression costs.
The LAG scenario assumed no reductions in
fire suppression and rehabilitation costs until treatment had occurred on 35% of the
required acreage. We conducted the LAG
scenario using 33% required treatment acreage and a 5% annual treatment rate.
Results
With an initial treatment cost of $200/
ac, all treatment scenarios had positive
NPVs and break-even values (Table 3). The
no-treatment scenario’s (A) costs for largefire suppression and rehabilitation resulted
in a PV of negative $2.0 billion. Treatment
scenario costs resulted in PVs from ⫺$1.1
billion to ⫺$1.9 billion. The NPV of treatment scenarios ranged from $128 to 894
million. Break-even values for treatment scenarios ranged from $238 to 601/ac.
Journal of Forestry • December 2006
433
Table 2. Scenario variables—area requiring treatment and rate of treatment.
Scenario variables
Area requiring treatment
Scenario
(code)
A
B
C
D
E
F
G
SEN
LAG
Rate of treatment
(% total ac)
(ac)
(%/yr)
(ac/yr)
N/A
33
33
33
50
50
50
30–65
33
N/A
3,262,770
3,262,770
3,262,770
4,943,590
4,943,590
4,943,590
2,966,154–6,426,667
3,262,770
N/A
5
10
15
5
10
15
5, 15
5
N/A
163,138
326,277
489,416
247,180
494,359
741,539
148,305–964,000
163,138
Table 3. Results of analytical scenarios—NPVs, with minus without values and break-even values.
Scenario
A
B
C
D
E
F
G
SEN
LAG
Required
(% ac)
Treatment variables
Rate
(%/yr)
Rate
(ac/yr)
PV costs
($billion)
Results
NPV*
($million)
Break-even
($/ac)
N/A
33
33
33
50
50
50
30–65
33
N/A
5
10
15
5
10
15
5, 15
5
N/A
163,138
326,277
489,416
247,180
494,359
741,539
Variable
163,138
⫺2.0
⫺1.4
⫺1.2
⫺1.1
⫺1.7
⫺1.6
⫺1.5
⫺1.4 to ⫺1.9
⫺1.7
N/A
604
797
894
351
464
524
649–128
344
N/A
530
535
538
326
329
331
601–238
388
*NPV calculated as difference between PV of with-treatment scenarios (B through LAG) minus PV of without-treatment scenarios (A).
With-treatment NPV increased with
increases in the annual rate of treatment and
decreased with increases in the required
amount of treatment. The increase in NPV
with faster treatment rates occurs because
the faster treatment rate results in a faster
decrease in acres of large fires and associated
costs. The earlier decreases in these costs offset the higher up-front treatment cost associated with faster rates. Although the NPVs
increase with treatment rate, the break-even
values show virtually no change. The faster
treatment rate restores more acres and the
increase in treated acres keeps the per-acre
break-even values constant even though
NPV increases. With the required treatment
level at 33%, the 10% treatment rate (scenario C) treats 16% more acres than the 5%
rate (scenario B). The 5% increase in treatment rate results in a larger percent increase
in treatment acres, because the faster treatment rate also reduces the number of acres
burned, making these acres available for
treatment. The faster treatment rate also significantly decreases the annual amount of
acres burned. Figure 1 illustrates this effect
using scenarios B and C. The greater the
number of acres treated per year, the fewer
the number of acres burned by wildfire.
434
Journal of Forestry • December 2006
Figure 1. The effect of annual treatment rates on the amount of acres burned over time.
Increasing the number of acres requiring treatment significantly lowers the NPVs
and break-even values. Increasing the required acres from 33 to 50% decreased the
NPVs by 40% and break-even values by
38%. Figure 2 illustrates the result of the
sensitivity analysis (scenarios SEN) on the
effect of increasing acres requiring treatment
on break-even values. Break-even values
range from $601/ac if 30% of acres require
Figure 2. Effect of amount of acres requiring treatment on break-even values.
treatment to $238/ac if 65% of acres need
treatment. The rate of decrease in breakeven values slows as the acres requiring treatment increases. Even if 100% of the forest
needs treatment (not shown), the breakeven value remains positive at $93/ac.
The LAG scenario tested the effect of a
delay in large-fire reduction and suppression
costs, using a 33% required treatment and a
5% treatment rate. The LAG assumption of
no reduction in fire suppression or rehabilitation costs until 35% of required treatment
has been accomplished significantly lowers
the NPV and break-even value. When compared with its no LAG equivalent (scenario
B), the LAG scenario’s NPV drops by 43%
to $344 million, and the break-even value
drops by 27% to $388/ac.
Discussion
The results of all scenarios suggest that
continuing the current policy of favoring fire
suppression over prevention does not represent a rational economic choice. All withtreatment scenarios had lower PV of costs
than the no-treatment alternative. The
amount that could be invested in restoration-based hazard reduction treatments
ranged from $238 to 601/ac.
We believe these scenario results are
very conservative for several reasons. Our estimates of future fire occurrence use the average acres burned from 1992 to 2002.
Given the worsening forest conditions, the
assumption of no increase in large fires over
the average of 10-year period is conservative.
Our estimates of per-acre fire suppression
cost did not include all charges for national
contracts, such as many aviation or catering
services. These costs averaged $96/ac for the
period of 1993–2002 (Gebert 2003). The
analysis only included variable fire suppression costs. Presuppression and other fixed
costs are likely to decline as the occurrence of
large fires declines. We assumed that treatment costs are net of any value recovered
from the fuel treatment. If the treatment
generated $200/ac in wood products, the total break-even investment value increases by
this amount. We did not include losses and
damages associated with structures, private
land value, and other infrastructure associated with the wildland-urban interface in
the avoided costs. We did not include
changes in ecological and social values associated with restoration-based treatments. Although not market valued, the changes generally are considered to be positive and
significant in magnitude. We essentially assumed that there is no difference between
the value of a burned and restored forest.
The analysis supports the idea that the
current pace and scale of implementation of
restoration-based treatments that would begin healing degraded forests and reduce the
threat of unnatural wildfire remains woefully inadequate. Inadequate federal funding
for restoration-based fuel treatments and the
reprogramming of treatment dollars to suppression activities perpetuates the problem.
Although society demands suppression of
fires, it is extremely expensive and fails to
solve the underlying problem leading to
fires. By underfunding restoration-based
hazard reduction treatments, we ensure the
continued need for suppression by undermining the rational approach to solving the
wildfire problem.
The results indicate that the amount of
acres requiring treatment significantly decreases NPVs and break-even values. This
finding points out the importance of efficient spatial strategies and fuel treatment design that produce genuine reductions in the
probability of uncharacteristic crown fire.
Random or arbitrary fuel treatment patterns
will likely be ineffective and increase the total number of acres requiring treatment thus
reducing the economically rational expenditure level.
There are several forces that prevent implementation of large-scale restorationbased fuel treatments in the forests of the
arid southwest. Given current forest conditions we can not simply cease fire suppression efforts, especially in the wildland-urban
interface. Thus, in the short run, costs will
increase as we will be paying for both suppression and restoration. Elections are always just around the corner and the federal
and private wildland fire industrial complex
is heavily vested, politically and financially,
in perpetuating the annual war on wildfire.
Revenues are increasingly scarce and restoration of the health and resilience of the forested ecosystems of the arid southwest does
not appear to be very high on the priority
list. This situation is analogous to other
funding paradoxes, e.g., funding emergency
over preventative health care, funding flood
disaster relief over levee maintenance.
Clearly, it will be challenging to generate the
long-term financial and managerial commitment for an activity for which ecological and
economic benefits may not be evident for a
number of years into the future— beyond
the next election, budget crisis, or tenure of a
forest supervisor.
Another significant force limiting implementation has been the near demise of
the region’s wood harvesting and utilization
infrastructure over the past 10 –15 years.
This loss stands as a critical impediment to
the implementation of restoration-based
fuel reduction treatments. Although there
are initial signs of emerging small-scale operations, the development of a competitive
Journal of Forestry • December 2006
435
market for the wood fiber removed by restoration-based treatment remains elusive.
Commercial use of the wood fiber removed,
especially small-diameter logs, could reduce
treatment costs that will otherwise be borne
by taxpayers; but the current limited scale of
fire hazard reduction work in the Southwest
presents a barrier to market development.
Manufacturing firms want a reasonable expectation of a raw material supply throughout their planning horizon. Currently, the
reasonable expectation is that the supply of
wood fiber from southwestern restoration
projects will remain intermittent and variable, because of litigation or the threat of
litigation by groups skeptical of the influence that a profit-driven economic system
can have on ecological systems. This concern that for-profit enterprises will corrupt
or distort restoration-based treatment activities is perhaps the most vexing socioeconomic issue in the restoration of southwestern ponderosa pine forests. Although
genuine, this concern prevents innovation
by local entrepreneurs, who could create
new uses for the raw materials (Daugherty
and Snider 2003).
The latest management paradigm promoted by federal land-management agencies
was ecosystem management, which has since
evolved into AM, or learning by doing. We
suspect that all the ecological and economic
arguments for the implementation of landscape-scale restoration-based fuel treatments
will avail us little for many of the same reasons given for our failure to implement AM.
These include strong opposition to experimental policies and management strategies
by persons protecting various self-interests;
management agencies trapped by cumbersome, inflexible, formalized processes and
narrow interpretations of legal mandates;
and demands by various organizations and
interest groups for spurious certitude
(Walters 1997, Gunderson 1999). The fact
that we will continue to learn is a given. The
fact that we will do so intentionally and in
time to avoid the odious and in some cases
irreversible (Savage and Mast 2005) consequences of anomalous stand-replacing
crown fires is not.
Conclusions
There are no risk-free management actions. Indeed, under present forest conditions, the no-action or go-slow alternative
may very well be the most risky of all. As
pointed out by Dombeck et al. (2004), to
avoid risk in wildfire management today is
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Journal of Forestry • December 2006
to advocate even larger uncharacteristic
wildfires and destruction of property and
ecosystems. Our results indicate that the ever-increasing ecological and economic costs
resulting from high-severity, ecosystemscale fires in the ponderosa pine and dry
mixed-conifer forests of the southwest far
exceed the cost to society of proactive restoration-based thinning treatments. The current sociopolitical condition of continuing
to spend dollars on fire suppression while
implementing limited treatment of highrisk forest areas represents an irrational ecological and economic decision.
We no longer face the question of
whether society will spend the money or not.
We are going to pay, one way or another,
unless we make the unlikely choice to no
longer spend money trying to fight and contain unnatural crown fires. We now face the
choice of how we are going to spend the
money and what are we likely to obtain from
that expenditure. If we invest in restorationbased hazardous fuel treatments, we invest
in the future; we invest in healthy, sustainable ecosystems for our children and grandchildren. By not investing in restorationbased fuel treatments, we continue the
depreciation of our forests, increasing the
risk of radical shifts in their structure and
function because of uncharacteristic crown
fire. Given these choices, it makes a great
deal of economic sense to conduct forest restoration on a large scale today to retain future ecological and economic values. Our
analysis shows that the fire suppression costs
that can be avoided in the future are sufficiently large by themselves to justify restoration-based fuel treatment expenditures today.
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Gary Snider (Gary.Snider@nau.edu) is doctoral candidate, P.J. Daugherty (P.J.
Daugherty@nau.edu) is associate professor,
and D.B. Wood (Brent.Wood@nau.edu) is
professor emeritus (retired), Northern Arizona University, School of Forestry, Box
15018, Flagstaff, AZ 86011. This research
was supported by the Ecological Restoration
Institute at Northern Arizona University.
The authors are grateful to the Journal of
Forestry editor and three anonymous reviewers for their thoughtful and helpful suggestions on earlier versions of this article.
Journal of Forestry • December 2006
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