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The Authors:
at the time oflhis study were with the Station's unit studying fire management planning
and economics, with lheadquarters at Riverside, Calif. PATRICK J. FLOWERS is now
forest economist with t h c ~ i v i s i o nof Forestrv. Dcaartment of Lands. Montana. Hc
~~~
computer science graduate (1983) of the University of California, Riverside. She has been
with the Station since 1976. DARlA A. CAIN, research forester, earned a bachelor's
degree in biolagicalscicnces(1973) at theUniversity ofMaryland and a mastcr'sdegreein
forest management (1975) at Colorado State Unirersitj! THOMAS J. MILLS js now
leader of the Renewable Resources Economics Group of the Forest Service's Resources
Economics Rcscarch Staff, Washington, D.C. He carncd degrees at Michigan State
University: bacheloi'sin forestry (1968),and muster's(1969)and doctorate(1972) in forest
economics.
Publisher:
Pacific Southwest Forest and Range Experiment Station
P.O. Box 245, Berkeley, California 94701
December 1985
Timber Net Value and Physical
Output Changes Following Wildfire
in the Northern Rocky Mountains:
estimates for specific fire situations
Patrick J. Flowers
Patricia B.Shinkle
Daria A . Gain
Thomas J. Mills
CONTENTS
................................................ ii
Introduction ............................................. 1
Methods ................................................ 1
Calculating Net Value Change ............................ 1
ScopeofAnalysis ....................................... 2
SourcesofData ........................................ 2
Examples of Analysis Cases ................................ 4
Results ................................................. 7
T~mberNet Value ...................................... 7
Timber Volume ........................................ 8
Conclusions ............................................. 8
Appendix ............................................... 9
References ............................................... 25
In Brief
1
IN BRIEF..
.
Florvers, Patrick J.; Shinkle, Patricia B.; Cain, Daria A.;
Mills, Thomas J. ~ i m h e rnet value and physical output
changes following wildfire in the northern Rocky Mountains: estimates for specific fire situations. Res. Paper
PSW-1719. Berkeley, CA: Pacific Southwest Forest and
Range Experiment Station, Forest Service, U.S. Department of Agriculture; 1985. 25 p.
Retrieval Terrns: fire effects, economies-to-scale, fire size,
timber management regime
Estimates of timber net value change due to wildfire are
sensitive to characteristics ofthe firesite, fireseverity, and the
timber management regime. Reflecting this sensitivity in
value change estimates requires detailed data collection and
computations. For this reason, the variability of the timber
resource must be considered in detail when fire management
programs are analyzed. The extensive data collection and
computation efforts necessary to incorporate this required
detail are generally not possible under the constraints of
escaped fire situation analysis and may not b.e possible under
long-term fire management planning situations if analytical
resources are limited.
An efficient alternative to estimating site-specific net value
change is calculating changes in timber net value and timber
output at a centralized location for a variety of nonsitespecific fire and management situations. The resulting estimates can then be consolidated and used in the form of
reference tables representing the likely range of fireand management situations. This approach eliminates the inefficiency
of duplicating site-specific calculations, and the detailed data
are preferable to highly aggregative potential loss averages
that are applied to broad heterogeneous areas. These highly
aggregative estimates d o not adequately reflect variability in
the resource base and management regimes, which materially
affect the net value changes.
Estimates ofthe timber net valuechangeand timber output
change resulting from wildfire were calculated for 9828
situation-specific fire and management conditions in the
northern Rocky Mountains. After slight aggregation across
the less sensitive situation parameters, reference tables with
estimates of net value change and timber output change were
prepared for 1764 roaded situations. They are defined by
timber management emphasis, cover type, productivity class,
stand size, mortality class, and fire size, with adjustments for
access status.
INTRODUCTION
I
n the last decade, the fire management program of the
Forest Service, U.S. Department of Agriculture, has come
under closer scrutiny because of ever-rising program costs.
The Forest Service has responded by conducting several studies analyzing the economic efficiency of its fire management
program. Some components of the analytical models have
been difficult to develop, particularly changes in the net value
and output of timber caused by wildfire.
The timber net value change calculation can be complex
because of the long timber production time and the substantial impact of the management context on the timing of
management costs and harvests. The timber computation is
critical, because the change in the timber resource accounts
for a large share of the total net value change due to fire:
nationwide, 60 percent on National Forest land and 75 percent on State protected lands (U.S. Dep. Agric., Forest Sew.
1980, 1982).
Numerous approaches have been proposed for estimating
timber net value change (Flint 1924, Lindenmuth and others
1951, Mactavish 1966, Marty and Barney 1981, Van Wagner
1983). The computations vary substantially in how they
reflect fire-caused changes in both the magnitude and timing
of the management costs and harvests, and in how certain
conceptual issues, such as the substitution of unburned for
burned timber, are addressed. For example, a relatively simple formulation of the timber net value change calculation
ignores price differentials between green and salvaged timber,
and the possibility for retention and future harvest of partially
destroyed immature timber stands (Schweitzer and others
1982). On the other hand, one of the morecompleteformulatioris includes harvest timing differentials in immaturestands,
salvage and green price differentials, and adjustments in the
management costs required if the fire removes a natural seed
source (Mactavish 1966).
Although these past studies include ample discussion of
methodology, the estimates of timber net value change they
contain are only illustrative and too few to demonstrate how
the net value change behaves under a wide range of circumstances. Therefore, we calculated change in timber net value
and in timber output due to wildfire for a broad range of
specific fire and management situations.
This paper summarizes trends in estimates of timber net
value changes and timber output changes due to wildfire for
1764 roaded situations in the northern Kocky Mountains.
Actual values are listed in extensive reference tables and have
four potential uses (Mills 1983): (I) analyses of long-term fire
management program options, such as those in the National
Fire Management Analysis and Planning Handbook (U.S.
Dep. Agric., Forest Serv. 1982) or the Fire Economics Evaluation System (Mills and Bratten 1982); (2) establishment of
fire dispatching priorities; (3) analysis of escaped fire situations where extensive calculations are often difficult to
accomplish because of the real-time demands of the decision
process ( U S . Dep. Agric., Forest Serv. 1981; Seaver and
others 1983); and (4) analysis of long-term harvest schedules
when fire-caused changes in timber yields are required.
METHODS
Calculating Net Value Change
Net value change is the difference between the present net
value of resource outputs and management costs "without
fire" and the present net value "with fire":
NVC = PNVw1,- PNV,
in which
NVC = net value change
PNVWI,= present net value without fire
PNV, = present net value with fire
According to this definition, a fire that produces a net gain in
present value has a negative NVC and one that produces a
loss of value has a positive NVC.
Because the NVC is a present value calculation, any change
in the magnitude or timing of the management costs, the
harvests, or the stumpage prices affects the NYC. Analysis of
the sensitivity of NVC to the completeness with which the
fire-caused impacts on these quantities were represented in
computations for 24 timber cases in the northern Rocky
Mountains, showed that a fairly complete representation of
the firejaused change was necessary to avoid major errors in
the estimate (Mills.and Flowers 1983).
The computational model used in the present study contains three,types of terms: (I) the existing rotation costs and
harvest values, (2) the regenerated rotation costs and harvest
values, and (3) one-time costs or revenues created by fire, such
as salvage values. The generalized form of the computation
was
1.m-
PNV of infinite series
PNV,,, = final harvests in
regenerated stand
PNV of harvests in
existing stand
-
PNV of infinite series
management costs in
regenerated stand
PNV of residual
timber remaining
after fire
-
Scope of Analysis
PNV of management
costs in existing stand
PNV of infinite series PNV of infinite series
PNV,, = final harvests in
- management costs in
regenerated stands
regenerated stands
following fire
following fire
PNV of timber salvaged following fire
+
PNV of management
cost in existing stand
Timber output change is thedifference between thescheduled
timber yield without fire and with fire.
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PNV of any single
rotation difference in
management costs
following fire
Not all terms are included in every fire case. For example, the
one-time change in regenerated rotation management costs.
(such as the removal of a scheduled site preparation because
the fire essentially accomplished the site preparation, or the
inclusion of a planting rather than a natural regeneration
because the fire removed the seed source) only enter the
computation. if the stand size, stocking, fire size, and tree
mortality are of certain levels. Similarly, the salvage transaction enters the computation only under certain conditions of
stand size, volume per acre, and fire size. The first two terms
make the with- and without-fire cash flows cdmparable despite dissimilar rotation lengths or unmatched sequencing of
without- and with-fire rotations.
A major assumption imbedded in our net value change
computation concerns the geographic area from which the
fire-induced change in the resource output is measured. Two
options exist: measuring the effect on only the fire site plus
direct physical and biological effects offsite (Althaus and
Mills 1982); or measuring the effects on the entire management area or market area in which the fire occurs (Van
Wagner 1983). Our analysis measured the fire-induced
changes on the fire site only because the firesite analysis most
closely reflects the impact of fire on the basic productivity of
the timber growing site, relatively unencumbered by management constraints.
Timber net value change was estimated at three discount
rates: 4.0,7.875, and 10.0 percent. The4.0 percent rate was an
approximation ofthe real return on investments in the private
sector (Row and others l98I), and is being used by the Forest
Service in land management planning; 7.875 percent was the
1983 discount rate for Federal water project evaluations (U.S.
Dep. Agric., Soil Conservation Serv. 1982); and 10 percent
was the rate recommended by the U.S. Officeof Management
and Budget (1972) as the real rate of return on investments in
the private sector.
In addition to the timber net value change, we calculated
the timber output change for the first 200 years following.fire.
52
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The analysis was structured to evaluate situation-specific
cases defined by a combination of values for the following
parameters that characterize the fire site, the timber management context in which the fire occurs, and the fire severity:
access, slope, management emphasis, cover type, productivity, stand size, fire size, and mortality. After removing
parameter combinations not generelly found in the northern
Rocky Mountains, such as passive private management on
high productivity sites, we estimated net value change for
9828 separate situations.
This situation-specific approach, rather than a site-specific
analysis, was followed because of the required model complexity and its associated datademands. Errors that will result
from extrapolation of these situation-specific estimates to
particular sites is expected to be far less than the errors that
would result from incomplete model specification or poor
data input that would likely occur if the computations were
for site-specific conditions with limited analysis resources.
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Sources of Data
Four categories of data were required: timber management
regimes, timber yields, silviculture treatment costs, and stumpage prices. Most of the data were derived from National
Forest sources in the Forest Service's Northern Region
(northern Idaho and Montana). The data were developed to
follow as closely as possible the input used in land management planning, thereby increasing the applicability of the
results to long-term planning on National Forest lands.
Four sets of timber management regimes were developed
from selected land management plans in the Northern Region
and on recommendation from the Regional silvicultural staff
(Wulf 1982): one each for "moderate intensity public,"
"intense public," "passive private," and "intense private"
timber management. The regimes differ in the form of stand
estab1ishment;the numberofcommercialand precommercial
thinning entries, rotation age, and the acreage of the withoutfire harvest area. Sample data for fire situations in Douglasfir are in table I.
The moderate intensity public regime reflects a generally
nontimber resource objective but where limited commercial
timber harvesting still occurs. Rotations are generally extended beyond the culmination of mean annual increment.
There are no precommercial thinnings and only one commercial thinning, if one is commercially viable. In the intense
public regime, commercial timber,harvesting is the primary
objective, but here too, the multiple-use management philosophy affects the regime. The rotation approximates or prece'des the culmination of mean annual increment. There is a
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Management emphasis,
productivity Class,
and rotation
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INumber of precommercial and commercial thinnings in existing rotation regimes. The
actual number in each analysis case was a function of existing stand age artime of fire, i.e.,
stand age for the cover typc and stand size class. and scheduled thinning age.
'Mean aonual increment was calculated from the sum of the harvest volumes divided by
rotation agc. First rotation harvest ageand mean annual increment are for sawtimber stands
only.
precommercial thinning and one or two commercial thinning~,depending on commercial viability.
The passive private regime assumed a final harvest will be
the only management activity after stand establishment. The
rotation age approximated the financially optimum age and
was estimated using the CHEAP0 supplement (Medema and
Hatch 1982) of the Prognosis timber growth model (Wykoff
and others 1982). For the intensive private regime, the rotation age is also set to approximate the maximization of
present net worth but in the presence of precommercial thinning and up to two commercial thinnings.
Timber yield estimates for the regenerated or second rotation were developed from a Prognosis projection of 212
samplestands from selected National Forests in the Northern
Region, a subset of the sample stands that were used to
develop yield estimates for land management planning. Projected yields for individual stands were aggregated into 96
yield sets by cover type, productivity class, and management
emphasis. The existing or first rotation yields for existing
seedling/saplingand poletimber stands were derived through
a percentage reduction of the second rotation yields. This
percentage reduction reflects the less intensive management
of the existing seedling/sapling and poletimber stands. The
first rotation yields for existing sawtimber stands were
derived empirically from inventory data on existing sawtimber stands. This derivation implicitly assumes that current
seedling/sapling and poletimber stands will, at maturity,
more closely resemble the Prognosis projection than the existing sawtimber stands. Viable commercial thinnings were
identified using the Northern Region's thinning default
option in the Prognosis model.
The cost of silvicultural treatments, such as site preparation, planting, and precommercial thinning, were derived
from equations developed from silvicultural service contracts
let in the Northern Region from 1975through 1978 (Mills and
others 1985). The only variable retained in the equations was
acres treated. The other variables were collapsed into the
intercept by setting them equal to their mean sample values.
This simplified equation form still permitted a reflection of
the economies-of-scale found in larger treatment areas. Real
net value change was then estimated using the SASSY financial return computer program (Goforth and Mills 1975).
EXAMPLES OF ANALYSIS CASES
t
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Figure I-Generalized data were adjusted for individual cases according to decision rules.
increase in treatment cost was assumed to be 1 percent per
year through 2030. Costs were held constant thereafter.
Green stumpage price estimates were drawn from regression equations developed from transaction data for 790
Northern Region timber sales on National Forest land
(Merzenich 1982), from September 1977 th<ough December
1982. Size of harvest area also influences the green stumpage
price through a variable for the total volume of the sale, thus
interjecting another scale economy influence. Real stumpage
prices increased over time to the year 2030, as a function of
lumber price and production cost projections (Adams and
Haynes 1980). Real prices were assumed constant after 2030.
The decision to salvage and the subsequent price of the
salvage sale were derived from equations based on salvage
sale transaction data in the Northern Region (Loveless and
Jackson 1983). The salvage sales database extended from
1970 through 1980. The decision to salvage was strongly
affected by accessibility and the total fire size. The price of
advertised salvage sales was set at 53 percent of the comparable green timber price. Unadvertised salvage sales were sold at
the "green slip" price of $1 per 1,000 board feet.
Management regimes, timber yields, treatment costs, and
stumpage prices were adjusted usinga number of internalized
decision rules that considered characteristics of individual
analysis cases flg.1). For example, the decision to retain a
partially destroyed stand was based on a comparison of the
postfire stocking with minimum stocking standards for manageable stands. This methodology permitted a fairly efficient
analysis while still addressing appropriate adjustment for
individual case differences. The individual transactions in the
regime were developed using the regime, yield, cost, and price
information, adjusted by the internalized decision rules. The
The net result of combiningthevaried and numerous types
of data used in this analysis can most easily be seen through
several illustrative cases. Although not a statistical sample,
these cases represent some of theimportant patterns of behavior in the timber NVC calculations. Four illustrativecases are
presented in detail.
The first case represents a seedling/sapling stand that was
retained after fire and then interplanted to raise stocking to an
acceptable level (table 2). The stand was retained because the
minimum stocking standard was met. The number of trees
per acre was low enough, however, to require an interplanting. Because of interplanting, the timing of future harvests
was delayed by 14 years. When combined with the cost of
interplanting, this extension of the rotation caused a net loss
due to fire. Net timber output did not change due to fire in this
situation. It is the change in timing oftransactions along with
cost differences, not the magnitude of the loss in yield, that
causes a net value change when fire occurs.
The second case illustrates nonretention and no salvage
after a high-mortality fire of moderate size in a poletimber
stand (table 3). This stand did not have sufficient stocking
after the fire to be retained. Based on stand conditions for
average diameter at breast height (d.b.h.) and dead volume
per acre, no salvage harvest occurred. Establishment of the
new postfire stand was delayed by 5 years. This same 5-year
delay affected all subsequent with-fire transactions as well.
This situation showed a net loss resulting from the foregone
without-firefinal harvest benefit that would haveoccurred 40
years hence, and because the loss was not offset by a with-fire
salvage harvest.
The third example case also shows nonretention for a
moderate size fire of high mortality in apoletimber stand, but
volume and d.b.h. were sufficient to support a salvage harvest
(lable4). The stand was not retained after fire due to failure of
the postfire stand to meet the minimum stocking standards.
The determination of whether to sell the salvage harvest as an
advertised or unadvertised sale was affected by the average
d.b.h. of the stand and the size of the fire. In this case, dead
volume was sold as an unadvertised saleat $I per 1,000 board
feet. The final price of the salvage was a weighted average of
the live volume at a comparable green timber bid price and
the dead volume a t t h e unadvertised "green slip" price. The
with-fire stand was salvaged at a weighted bid price ($4 per
100 ftl of timber), which was much lower than the full final
harvest price ($41 per l00ft3) of the without-firestand just 14
years in the future. The fire causes a reduction in the amount
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.he a"d l
.
* pr.l.d
rh.ns..
its--Plrr..u..d
Inrsnre *r<uilrm
rat-
iianlgm."i.
nril"rin
.rodu.r,*,~
"
0
.,XI.
,
Old
t*i,e .....I
<PCLJ
I
I
I
7.875
4.0
,010
I
4-11
191s doilacm/&ole
183
7
1617
2,.
' 3
>ill
a,.
4
783
I<# i 5 G l i
226
221
i n 9
1852
lOlD
64
61
->mi
-Its
116
lbl
716
0
0
0
0
119
0,s
,486
848
0
0
129
ax7
479
-111
10
-110
-116
611
0
0 ,
x.9
692
,419
I3
85
I,
-1,s
0,
48s
454
239
9.6
11'
- 4
-114
-4,
-112
.I,
IBD
4
0
0
0
0
0
322
0
117
I,
I
l
isa
l
5
17,
,
528
2
231
402
281
l,,
0
4,
is,
I.),
..
,s-s9
-
.-
sVn p i t , -
--
-116
20
IS,
durn
..
-
I-:
,a
0-24
I%..')
50-99
LOO-IOO 0-IDD
,is
><o
-us
-110
I0
5 ,
$28
II
......
O
1
0
0
. . .--. . ...
. .. .. .. .-..
.. . .
- - . .
......
.. . .-- - -.
.
..
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.
.
. . . . - .
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-. . --.
.
. .. .. .-.. . . . . . .
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. . . . - .
5."t,Shr:
1-23
2 -
376
87
.B
-
a9
'I),
0
61%
0 . 9
0
127
IS,
-
618
0
I 0
116
I,'
5
-261
112
590
6.1
0-2
dZe:
LOO* .er*n
-1,o
ll9
89
0
,
,,rs
CY**CS,
1766
119
8 9
0
7,ms m,*oa
I
488
160
-28,
*&
IB>i
4 ,
0
1%
(SCL)
I
611
0
118
101
525
,002
I.
BI
675
I,+kiv.
i-1 rnivn
r,rwtlm n.+ -lira.
10
lii
4.1
60.
-299
177
ID08
6
is.0
."a
bulnrd'
'Bii
'bl
lie.
I..
1.875
786
617
611
7
0 "
CF*,
D%sco~,"e
--
i-
-
n. "r( fir. IDM, -
-
..........
.
..
. .. .. .. .. .. .. .. .. ..................
..
s."k.u~~r:
1-29
30-59
..........
so+
't*.~l-
'lula s t
,-, n(u-
-w.
sirn, Felt<* "03,-
-
i-,
0
-
n. rrr Ell..
Ygrt!
--
Table 2-Exan7ple of a Do~rglos-firseedling/sr?pIings~an~Ilhar
was reroinedqflerfire ond i,,terplonred
Description: <'I0 percent slope, very low productivity, moderate interrsity public management, 10-99
acres, 60+ percent mortality, roaded
Decisions: retained, interplantcd
Yean since
fire
. . . . . .
......
....
6W
*OdSC.f*
n
0
0
0
0
lib
10,
,A
I,,
t*
6.
112
ii
0
0
0
0
1.4
0
0
10,
*I*
18
34
12
12,
,?I
IJi
3s
I,
-118
-,52
-116
$2
110
9
16
&I
101
-,I0
182
0
0
a
0
0
31
80
121
0
0
0
0
@
10
I*,
>a
-1
-2
19,
-2
7,
-,
0
3
0
0
a
O
0
0
0
0
122
22
22
8
'
-1
GO
0
In9
O
IS>
,>,
,I
0
-1
0
-1
-2
B
-1
9,
*
-1
-2
0
125
Cost
Repetition
cycle
-x/ocre-Without lire
1,510
-
..
2,
111
3
&
,
121
>-29
>0-<9
22
6W
sa"t,*bec:
36
-24s
L.29
-111
10.59
60.
LO" I ~ D - l . , :
267
14,508
With fire
- 251
1,510
--
.D
8
-23
30
0
o
92
B
0
0
n
811
0
0
28
,o
-1
-2
48
-1
-2
a
0
n
0
0
0
0
0
0
0
,%>
123
%I
8
8
-1
29
1,s
-1
22
-57
a.
-1
-8.
,a
1-*9
,*-s9
60.
POiltljn~,:
1-29
Interplant
Fint commercial
thin
Final harvest
Site preparation
Fint commercial
thin
Final harvest
30.39
60.
xa"c,mb*c:
1-29
,o-ss
60.
YezY 101 ( 2 0 - . 9 / ,
~~.d,ln~/..~,np:
Dcscriptian
First commercial
thin
Final harvest
Site preparitian
Fint commercial
thin
Final harvest
1-29
,e-39
60.
I..~iins,n.pllns;
0
0
Ill
0
Benefit
PO,Ot,rnb.',
151
2,
Price
I.rdil.p,s.pllnp;
0
''I
ie
,Bl-,ls,:
Harvest
-1s
-28
12
1-23
,*-59
GO*
Pe,rtl*or:
1-29
30.39
6W
so"<,mb*c,
L.29
-8
30-59
,2
1:
$0-
Physical output change: 0 (total for first 204 years in 100 cu ftlaere)
Net value change: 307 (1978 dallars/acre at 4 pct discount rate)
Table 3-Example of apolefimber srond rhor was nor retained offerfire and was nor solvaged
Description: <do percent slope, low productivity, intense private management, 10-99 acres, 60+
percent mortality, roaded
Decisions: not retained, not salvaged
Years since
fire
,,,*h
,,20.?:
Harvest
Price
I00 cufflacre
XI100 cuff
49
40
42
55
--
105
---
125
57
134
7
20
--
---
90
57
134
Benefit
Cost
Repetition
cycle
-X/ocre-Without lire
5,194
--1.24
-129
Years
-7,638
With lire
88
-50
85
85
85
--
85
0
85
85
r.ediln9,r~ilmp:
1-23
30.59
60.
Pa,ct."b"c:
1-23
,o-59
60.
sa"tLSbec:
1-29
30.59
60.
" * < o r a t @ ,a5-,,9,:
r.railn.i/.rpllns:
,-z9
39-59
6".
*o:ec,mb"z:
.-29
,0.5$
$0.
,a"t.mb",,
7,638
Description
Final harvest
Plant
Precommereial
thin
Final harvest
Plant
Precommercial
thin
Final harvat
Physical output change: -9 (total for first 200 yean in 100 cu ftlacte)
Net value change: 964 (1978 dallars/acre at 4 pct discount rate)
>-a*
,".9*
6D.
""" ( 5 0 - 8 4 , :
.nli"g,..Pll"g:
3-39
30.59
60.
D",er,mber:
>-2g
.........
,n-%
6".
,-:*
....
,*-59
)
ill"
,2O-*l/:
.~<a,,"q,oae,'"9:
-19
ofsite preparation required wlth an assoc~atedcost reduction
of $70 per acre. This site preparation cost adjustment is a
benefit due to fire. The net impact of these forces was a loss of
value.
The fourth case represents a sawtimber stand with moderate mortality after a large fire (table 5). In this situation, the
net gain results from economies-of-scale and the truncation of
an otherwise uneconomical without-fire regime. The postfire
stand was not retained after the fire due to insufficient stocking, but stand conditions were adequate to support a postfire
salvage harvest. The economies-of-scale associated with a
large fire size led to increases in the salvage price and reductions in the stand establishment costs. The per acre costs of
site preparation and planting were less with the large burned
area (2088 acres) than they would be with the smaller management area (35 acres). The intense public regime in this case
had a rotation age that extended beyond the financially optimum age with respect to timber values. The fire reduced the
final harvest age to a point nearer the financial optimum.
While fire may have had a detrimental effect on nontimber
outputs, it had a positive financial impact on the timber
output.
Table 4-'Exo,nple oj o polerintbrr srand rhar ivos nor reruined oflerflre bur tvos salvosed
Description: < 40 percent slope, modcrate productivity, passive private management, 10-99 acres, 60+
percent mortality, roaded
Decisions: not retained, salvaged, site preparation cost adjusted
Years sincc
fire
Harvest
Price
I00 r u f l l a o s
%/I00rufl
14
I5
93
44
-63
41
-114
I
2
83
2
33
-63
4
-114
--
--
Benefit
Cost
Repetition
cycle
Description
Yeors
-$/acre--
Without fire
1,804
--94
7:182
--
0
79
79
Final harvest
Site preparation
Final harvest
With fire
132
--83
7,182
-70
--
0
79
79
0
Salvage harvest
Site preparation
Final harvest
Site preparation eost
adjustment
Physical output change: I I (total for first 200 years in lW$u ftlacre)
Net value change: 794 (1978 dollan/acre at 4 pct discount rate)
Table 5-Exan7ple ofa sowrinzber srond rlzor was solvosed oflerfire
Description: <40 percent slope, high productivity, intense public management, lOO+ acres, 30-59
percent mortality, roaded
Decisions: not retained, salvaged, site preparation and planting costs adjusted
Years since
lire
Hamst
Price
100 cuflloere
$1 I00 cufl
40
--
45
--
Benefit
Cost
-S/ocrt
Without fire
1,800
0
-137
-21 1
-27 1
Repetition
cycle
0
14
15
17
32
---
--
57
3
79
237
98
77
12
129
1,548
98
I I2
79
164
12,956
98
With fire
1.248
--I21
-184
-236
0
98
98
98
--
32
98
98
98
I
2
3
18
39
----
43
3
66
198
--
98
63
12
129
1.548
--
98
98
2
79
--
164
--
12.956
--
-90
98
0
3
--
--
--
116
0
---
--
Physical output change: -78 (total for first 200 years 100 cu ft/acre)
Nct value change: -376 (1978 dallars/aere at 4 pct discount rate)
Description
Yeors
Final harvest
Site preparation
Plant
Preeommercial
thin
Fint commercial
thin
Second commercial thin
Final harvest
Salvage harvest
Site preparation
Plant
Precommcrcial
thin
First commercial
thin
Second commercial thin
Final harvest
Site preparation
eost adjustment
Planting cost
adjustment
RESULTS
Specific cases for which timber net value and output
changes were calculated were described by the following
parameter classes:
Parameter
Timber management emphasis
Cover type
Classes
Moderate public
Intense public
Passive private
Intense private
Douglas-fir
Ponderosa pine
Western white pine
Fir-spruce
eml lock
Stand size
Larch
Lodgepole pine
High (120t cu ftlacrelyr)
Moderate (85-1 19 cu ft/acre/yr)
Low (50-84 cu ftlacrelyr)
Very low (2049 ccu ft/acre/yr)
Seedling-sapling
Mortality
Poletimber
Sawtimber
1-29 percent
Productivity class
30-59 percent
601 percent
Fire size
%*lo
,es.s,r
p e r n i r a pr,r.t*
i."
..il.l*d
ohm*om I" nrr tlrber *urpur
nm.iien*o*.
n ~ i i h r c nil*<XY Na""la,"r,
F,rc
.irau.rlrirYi
SL."d
ti/aEiVYil.
ofand r,/e.
.OII.llIY
(Pet,
."d
0,zs:
1-33
acrus
I
I
,
<Ianm
I
- 2
*.me
3 . 9
5-99
0
-
0 . 0
*by LIIIIC- S. i i r u c ~ rma
k m d s ""dSC
S3.C
/
p*r.-a
rile
itrr
G'Z>;
p.l,.d
im.
,y<-cs,
I 0-PI
23.4)
50.99
1110.200
0.2110
1-99 acres
lOO+ acres
timber net value changes averaged $190 per acre burned, but
they ranged from a net loss of $2132 per acre to a net benefit of
$-I545 per acre. The majority of the net value changes were
net losses, i.e., positive net value changes. Net losses occurred
in 82 percent of the situations discounted at 4 percent, and I8
percent of the situations showed net gains. Most situations
having a net gain were large fires in sawtimber stands. These
net benefits are due to economies-of-scale in stand establishment costs, salvage harvest revenues, and sometimes the truncation of uneconomically long rotations.
The various situation parameters had different impacts on
net value change. Management emphasis, stand size, firesize,
and mortality rate had major effects. The effect of cover type
and productivity class on the estimates was not well defined.
Ultimately, it is the combination of the effects or interactions
among these parameters that explains the variability among
cases.
Management emphasis affected net value change through
the sequence and timing of transactions. The timing and
sequence of transactions are defined by management emphasis but can be altered by fire. The moderate public management emphasis had the lowest average net value change, $101
per acre burned. The average net change given intense public
management was almost twice as large on average, $196 per
acre. The passive private and the intense private had average
net changes of $173 and $318 per acre, respectively.
Timber net value changes varied by cover type; lodgepole
pinedisplayed the least average net value changeand hemlock
the greatest (jig. 2). Cover type affected net value change
Slope and access parameters were originally included in the
computations. To reduce the volume of the results, the original 9828 estimates were aggregated by calculating the mean of
the two original estimates for slope class. The resolution lost
by this aggregation had little impact on the results. Theaccess
parameter was handled in a similar way. This aggregation led
to estimates for 1764 "roaded" situations and adjustment
factors that can he used to estimate the corresponding 1764
"unroadeh" situations. The appendixlists estimates oftimber
net value change and timber output change due to fire forthe
aggregated set of 1764 fire situations under roaded conditions.1 It also lists the adjustment factors.
The following is a discussion of the aggregated set of 1764
"roaded" situations. General trends within the full set of9828
situations (Mills and Flowers 1984) and detailed results of a
small set of the ponderosa pine and lodgepole pine situations
(Mills and Flowers, in press) are discussed elsewhere.
Timber Net Value
Patterns exist in the net value change results but estimates
vary significantly among the specific fire situations. The
-$
.-
-
0)
2
'Estir~atesfor the original 9828 situations are available on magnetic
computer tapeon request from: Patricia 8. Shinkle, PacificSouthwest Forest
and Range Experiment Station, 4955 Canyon Crcsl Drive, Riverside, California 92507.
ma,
c m
m
g-E
'UE
2
n
c
"
,
m m
3.
Y)C
- c
O
x
0
=
a
5
_I
E
0
1
m
0
ma,
-
0 .=
a
a
m
or
n
g
2
3
ii
3
Figure 2-Timber net value changes varied by cover type due to
differences in diameter at breast helght,stand age,volumeandstocking per acre, treatment costs, and stumpage values.
becauqe of differences in d.b.h., stand age, volume per acre,
stocking pcs acre, costs, arid stumpage values. Existing stand
conditions varied by cover type and productivity class with
slight adjustments for management emphasis. This existing
stand information came from existing National Forest inventory data.
Site quality affected net value change. Higher quality sites
had greater timber volumes at risk which led to greater losses
when fires occurred. Overall, high quality sites showed greatest average net value change ($264 per acre), followed by
moderate sites ($241), low sites ($1471, and very low sites
($106).
Stand size also significantly affected net value change.
Poletimber stands had the highest average net change at $290
per acre burned. Seedling/sapling stands had an average net
value change of $148, and sawtimber stands had a similar
change of $133. Losses in the seedling/sapling stands were
generally associated with interplanting costs and delay in
harvests. Losses in poletimber stands occurred when the fire
removed previously scheduled commercial thinnings or the
fire led to nonretention with no salvage harvest. The foiegone
final harvest in the sawtimber stands was much nearer in the
future than in the other two stand sizes, so the foregone
present value of the without-fire regime was greater. Part of
the loss in sawtimber stands was offset by salvage revenues.
The impact of mortality rate on net value change varied by
stand size. Mortality rate had a major impact on thenet value
change in the seedlinglsapling stands because the decision to
retain a stand after fire and whether to interplant was determined by postfire stocking. This interplantingcost or delay in
harvests caused a net loss when fire occurred. Poletimber
stands showed an even greater sensitivity to mortality rate.
Poletimber stands were usually retained in low mortality
situations, but net losses may still have occurred due to
elimination of a previously scheduled commercial thin. At
higher mortality rates, the postfire poletimber stand was
generally not retained and often the stand was not salvageable. Net losses increased with mortality rate in sawtimber
stands too. At moderate and high mortality rates sawtimber
stands were usually not retained due to insufficient stocking,
but stand conditions were often sufficient for a salvage harvest. The potential for salvage existed at all mortality rates in
sawtimber stands, but the proportion of green timber availasie decreased as the mortality rate increased. At lower mortality rates a salvage harvest may take place, as well as a final
harvest of reduced volume.
The impact of the fire size on net value change differed by
stand size:
Average loss per acre
when lire sire was . . .
Stand size
1-99 acres
100+ aercs
Dollars
Seedling/sapling
Poletimber
Sawtimber
148
33 1
237
148
248
27
YL.b
,.no*,:
"olalln~,..~.lns'
1-29
,o-w
eo*
ZOI~Tlsbri:
1-23
Losses in the.large fire situations were generally less than
those in small fire situations due to the economies-of-scale in
salvage prices and stand establishment costs.
3a-$9
60.
S."t,rnb*C>
,-29
111-19
*do..
so*
ll 111-1,s,:
Il.dl*nS/.aPL*nS.
1-29
30.59
60-
Pol*t,sbmr>
1-29
Timber Volume
30-59
60.
S.Sll"blC/
1-29
,0-3*
'0.
,5o-a,,:
Ilrdl,ng,..illln9i
1-29
,O.%
60.
LO"
The change in the timber output was the net change in
yields between the without-fire and the with-fire situations.
The results for the change in yields in the first 200-year time
period showed much of the same variability across the
parameters as did the net value change. The timber output'
changes ranged from a gain of 49 cu ftlacrel year to a loss of
75 cu ft/acre/ year during the first 200 years after the fire. The
overall average across all the situations analyzed was 0.97 cu
ft/acre/ year.
The effect ofthe situation parameters on the timber output
changes varied greatly, with mortality rate showing a strong
impact, and cover type and management emphasis having less
impact. Timber output changes were the same for all productivity classes except the highest site, and thesame for all stand
sizes except sawtimber. Fire size had no impact on the physical changes.
*o,*L,vBcr>
.-29
30.59
60.
S."timb*c:
1-13
30-59
60.
"SCY
10" ,ZO..$>&
r~s~ilns/-pi'ns:
1-29
30.39
60+
P~>Ot,rnB~.~
1-29
30.59
6s.
*a"t,-bor:
L.29
,o-sa
so*
h t l w I-,mun
mum 0 5
CONCLUSIONS
30-59
60.
EQLntZmbeL:
The estimates of net value changes and changes in timber
output are sensitive to the fire situation and stand classification parameters in various ways. It is the interaction of these
parameters that causes the great variability among the cases.
Because of this variability situation-specific estimates should
be used when describing net value changes, instead of estimates for highly aggregated situations. Use of the situationspecific estimates presented in the reference tables also eliminates the cost of the repetitive calculations needed to produce
site-specific estimates.
..%9
10-59
6%
sm"e,mher,
A-29
3s-59
GO*
I0dlrnre
.
. .--. . .-.
.
..
...
...
.
. ..
. . ....
.
..
..
.
.
..
..
..
..
..
.
......
. . . . . -.
....
......
.
. --. - --- .
.
,IJ-lis,:
s~eaL*ns,~e,ins:
3-29
0
lD-I9
0
60,
Pe,cs'nber:
0
n
,-z9
,0-59
sa"t,ebsc:
1-!9
30.39
60.
0
0
0
0
111
0
0
0
o
n
*
0
0
0
a
o
0
0
a
o
1,s
L2D
11)
1'1
111
,.is
192
' 5
684
185
isi
'2,
6
.21
-101
-150
46
-289
-,a0
B
0
0
O
*
0
I*
150
B
0
62.1
a,,
0
184
12,
1'3
46s
so*
m
.
. .. .. ...-.-
33
-1111
-,,I
33
,~ll-Bl,i
s*r~i,"9/n.Llnsi
1-29
0
>0-,9
350
10.
IIa
0
11,
sol*ll.b*j:
,-a*
0
B
30-59
60.
1-29
30.59
GO.
0
O
11,
O
12
6.7
26
0
8 ,
118
211
llb
-I,(
-33
25'
48
,...
0
0
is
very LO" ,10-,,,>
6..dll"9
.*ni
,-a9
3m-59
60.
,I
s
88
8
0
0
PI
.1
-82
-11
-3.
33
-1
I?
-75
-35
264
0
0
m*
0
8x9
0
0
is9
,-a9
1B
4,
1.1
269
3x3
-9'
-35
0
0
199
0
I,
-3s
I,
0
0
0
lli.lS
60.
-se
0
9
11
0
0
0
3a"e,-b.r,
0
0
7
*0
0
PDI.LI.b.Li
a
0
0
D
0
1-29
20-re
0
0
a ,
S."<lib.,/
O
0
IS
it,
0
0
0
36
dm.
-
dm,a l r l r
*",- I-,
0
-,
a ar.
-, -
-
APPENDIX
L.,S
d.il.cn,.ri.
b"l".di
237
Ijl
225
209
'11
2**
.I>
118
'08
.L
-5
-7
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Net value change estimates are listed for three discount
rates (4.0, 7.875, and 10 percent) (tables IA-28A). Timber
output changes are given (tables 15-288) for the same fire
situations for which net value change was estimated. These
output changes are measured in ftl/acre/year for four different time periods (0-24,25-49,50-99, 100-200years) and a total
for the first 200 years of the analysis. Positive values in the
tables represent net losses due to fire. Negative values represent net benefits due to fire.
The net value change estimates are presented in 1978 dollars because that was the base year for National Forest planning at the time the study was started. Implicit GNP deflators
can be used to convert the net value change estimates from
I978 dollars to estimates for other years from 1972 to 1984:
Year
-
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Given a timher net value change of $150 per acre hurned in
1978 dollars, to determine the net value change in 1980 dollars, set up a ratio between the 1980 deflator of 178.6 and the
1978 deflator of 150.4. Multiply this ratio, 178.6/150.4 or
1.19, by the $150 per acre hurned in 1978 dollars for a timher
net value change of $178.5 dollars per acre burned in 1980
dollars.
To locate a particular fire situation in the tables, identify the
management emphasis and cover type, then use the following
index to locate the appropriate table:
Cover type
Douglas-fir
Ponderasa pine
Western white pine
Firspruce
Hemlock
Larch
Lodgepole pine
Moderate
public
I
2
3
4
5
6
7
Management emphasis
Intense Passive
public
private
Intense
private
-
(table number)
8
15
16
9
10
i7
II
18
I2
19
13
20
14
21
22
23
24
25
26
27
28
The following example shows how to locate the net value
change at the 4 percent discount rate for a fire situation
described as follows:
Management emphasis-"moderate puhlic"
Cover type-ponderosa pine
Productivity-low
Stand size-poletimber
Mortality-60 percent plus
Fire size-100 acres or more
Access-roaded
The index shows that the fire situation is in table 2. In table
2A, locate the appropriate productivity, stand size, and mortality class in the left hand column, and then the appropriate
fire size and discount rate. The net value change is a loss of
$143 per acre burned.
To estimate the net value change for unroaded situations,
use the factors givenin tables29and 30 to adjust the estimates
for roaded situations. Unique sets of adjustment factors are
used when the net value change of the roaded situation is
negative (iable 29) and when it is positiye (!able 30). The
adjustment factors are stratified by management emphasis,
stand size, mortality class, and fire size.
The roaded, ponderosa pine fire situation given as an
example above had a positive net value change of $143 per
acre hurned. To Bdjust this value to an unroaded estimate,
turn to table 30. The adjustment factor for the moderate
public management, poletimber stands with 60+ percent mortality, and fire size 100+acres, at the4 percent discount rate is
1.18. Multiply the roaded net value change times the adjustment factor-$143 per acre x 1.18 = net valuechange of $169
per acre hurned in the unroaded situation.
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APPENDIX
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Net value change estimates are listed for three discount
rates (4.0, 7.875, and 10 percent) (tables IA-28A). Timber
output changes are given (tables 15-288) for the same fire
situations for which net value change was estimated. These
output changes are measured in ftl/acre/year for four different time periods (0-24,25-49,50-99, 100-200years) and a total
for the first 200 years of the analysis. Positive values in the
tables represent net losses due to fire. Negative values represent net benefits due to fire.
The net value change estimates are presented in 1978 dollars because that was the base year for National Forest planning at the time the study was started. Implicit GNP deflators
can be used to convert the net value change estimates from
I978 dollars to estimates for other years from 1972 to 1984:
Year
-
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
Given a timher net value change of $150 per acre hurned in
1978 dollars, to determine the net value change in 1980 dollars, set up a ratio between the 1980 deflator of 178.6 and the
1978 deflator of 150.4. Multiply this ratio, 178.6/150.4 or
1.19, by the $150 per acre hurned in 1978 dollars for a timher
net value change of $178.5 dollars per acre burned in 1980
dollars.
To locate a particular fire situation in the tables, identify the
management emphasis and cover type, then use the following
index to locate the appropriate table:
Cover type
Douglas-fir
Ponderasa pine
Western white pine
Firspruce
Hemlock
Larch
Lodgepole pine
Moderate
public
I
2
3
4
5
6
7
Management emphasis
Intense Passive
public
private
Intense
private
-
(table number)
8
15
16
9
10
i7
II
18
I2
19
13
20
14
21
22
23
24
25
26
27
28
The following example shows how to locate the net value
change at the 4 percent discount rate for a fire situation
described as follows:
Management emphasis-"moderate puhlic"
Cover type-ponderosa pine
Productivity-low
Stand size-poletimber
Mortality-60 percent plus
Fire size-100 acres or more
Access-roaded
The index shows that the fire situation is in table 2. In table
2A, locate the appropriate productivity, stand size, and mortality class in the left hand column, and then the appropriate
fire size and discount rate. The net value change is a loss of
$143 per acre burned.
To estimate the net value change for unroaded situations,
use the factors givenin tables29and 30 to adjust the estimates
for roaded situations. Unique sets of adjustment factors are
used when the net value change of the roaded situation is
negative (iable 29) and when it is positiye (!able 30). The
adjustment factors are stratified by management emphasis,
stand size, mortality class, and fire size.
The roaded, ponderosa pine fire situation given as an
example above had a positive net value change of $143 per
acre hurned. To Bdjust this value to an unroaded estimate,
turn to table 30. The adjustment factor for the moderate
public management, poletimber stands with 60+ percent mortality, and fire size 100+acres, at the4 percent discount rate is
1.18. Multiply the roaded net value change times the adjustment factor-$143 per acre x 1.18 = net valuechange of $169
per acre hurned in the unroaded situation.
becauqe of differences in d.b.h., stand age, volume per acre,
stocking pcs acre, costs, arid stumpage values. Existing stand
conditions varied by cover type and productivity class with
slight adjustments for management emphasis. This existing
stand information came from existing National Forest inventory data.
Site quality affected net value change. Higher quality sites
had greater timber volumes at risk which led to greater losses
when fires occurred. Overall, high quality sites showed greatest average net value change ($264 per acre), followed by
moderate sites ($241), low sites ($1471, and very low sites
($106).
Stand size also significantly affected net value change.
Poletimber stands had the highest average net change at $290
per acre burned. Seedling/sapling stands had an average net
value change of $148, and sawtimber stands had a similar
change of $133. Losses in the seedling/sapling stands were
generally associated with interplanting costs and delay in
harvests. Losses in poletimber stands occurred when the fire
removed previously scheduled commercial thinnings or the
fire led to nonretention with no salvage harvest. The foiegone
final harvest in the sawtimber stands was much nearer in the
future than in the other two stand sizes, so the foregone
present value of the without-fire regime was greater. Part of
the loss in sawtimber stands was offset by salvage revenues.
The impact of mortality rate on net value change varied by
stand size. Mortality rate had a major impact on thenet value
change in the seedlinglsapling stands because the decision to
retain a stand after fire and whether to interplant was determined by postfire stocking. This interplantingcost or delay in
harvests caused a net loss when fire occurred. Poletimber
stands showed an even greater sensitivity to mortality rate.
Poletimber stands were usually retained in low mortality
situations, but net losses may still have occurred due to
elimination of a previously scheduled commercial thin. At
higher mortality rates, the postfire poletimber stand was
generally not retained and often the stand was not salvageable. Net losses increased with mortality rate in sawtimber
stands too. At moderate and high mortality rates sawtimber
stands were usually not retained due to insufficient stocking,
but stand conditions were often sufficient for a salvage harvest. The potential for salvage existed at all mortality rates in
sawtimber stands, but the proportion of green timber availasie decreased as the mortality rate increased. At lower mortality rates a salvage harvest may take place, as well as a final
harvest of reduced volume.
The impact of the fire size on net value change differed by
stand size:
Average loss per acre
when lire sire was . . .
Stand size
1-99 acres
100+ aercs
Dollars
Seedling/sapling
Poletimber
Sawtimber
148
33 1
237
148
248
27
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Losses in the.large fire situations were generally less than
those in small fire situations due to the economies-of-scale in
salvage prices and stand establishment costs.
3a-$9
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The change in the timber output was the net change in
yields between the without-fire and the with-fire situations.
The results for the change in yields in the first 200-year time
period showed much of the same variability across the
parameters as did the net value change. The timber output'
changes ranged from a gain of 49 cu ftlacrel year to a loss of
75 cu ft/acre/ year during the first 200 years after the fire. The
overall average across all the situations analyzed was 0.97 cu
ft/acre/ year.
The effect ofthe situation parameters on the timber output
changes varied greatly, with mortality rate showing a strong
impact, and cover type and management emphasis having less
impact. Timber output changes were the same for all productivity classes except the highest site, and thesame for all stand
sizes except sawtimber. Fire size had no impact on the physical changes.
*o,*L,vBcr>
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CONCLUSIONS
30-59
60.
EQLntZmbeL:
The estimates of net value changes and changes in timber
output are sensitive to the fire situation and stand classification parameters in various ways. It is the interaction of these
parameters that causes the great variability among the cases.
Because of this variability situation-specific estimates should
be used when describing net value changes, instead of estimates for highly aggregated situations. Use of the situationspecific estimates presented in the reference tables also eliminates the cost of the repetitive calculations needed to produce
site-specific estimates.
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-
RESULTS
Specific cases for which timber net value and output
changes were calculated were described by the following
parameter classes:
Parameter
Timber management emphasis
Cover type
Classes
Moderate public
Intense public
Passive private
Intense private
Douglas-fir
Ponderosa pine
Western white pine
Fir-spruce
eml lock
Stand size
Larch
Lodgepole pine
High (120t cu ftlacrelyr)
Moderate (85-1 19 cu ft/acre/yr)
Low (50-84 cu ftlacrelyr)
Very low (2049 ccu ft/acre/yr)
Seedling-sapling
Mortality
Poletimber
Sawtimber
1-29 percent
Productivity class
30-59 percent
601 percent
Fire size
%*lo
,es.s,r
p e r n i r a pr,r.t*
i."
..il.l*d
ohm*om I" nrr tlrber *urpur
nm.iien*o*.
n ~ i i h r c nil*<XY Na""la,"r,
F,rc
.irau.rlrirYi
SL."d
ti/aEiVYil.
ofand r,/e.
.OII.llIY
(Pet,
."d
0,zs:
1-33
acrus
I
I
,
<Ianm
I
- 2
*.me
3 . 9
5-99
0
-
0 . 0
*by LIIIIC- S. i i r u c ~ rma
k m d s ""dSC
S3.C
/
p*r.-a
rile
itrr
G'Z>;
p.l,.d
im.
,y<-cs,
I 0-PI
23.4)
50.99
1110.200
0.2110
1-99 acres
lOO+ acres
timber net value changes averaged $190 per acre burned, but
they ranged from a net loss of $2132 per acre to a net benefit of
$-I545 per acre. The majority of the net value changes were
net losses, i.e., positive net value changes. Net losses occurred
in 82 percent of the situations discounted at 4 percent, and I8
percent of the situations showed net gains. Most situations
having a net gain were large fires in sawtimber stands. These
net benefits are due to economies-of-scale in stand establishment costs, salvage harvest revenues, and sometimes the truncation of uneconomically long rotations.
The various situation parameters had different impacts on
net value change. Management emphasis, stand size, firesize,
and mortality rate had major effects. The effect of cover type
and productivity class on the estimates was not well defined.
Ultimately, it is the combination of the effects or interactions
among these parameters that explains the variability among
cases.
Management emphasis affected net value change through
the sequence and timing of transactions. The timing and
sequence of transactions are defined by management emphasis but can be altered by fire. The moderate public management emphasis had the lowest average net value change, $101
per acre burned. The average net change given intense public
management was almost twice as large on average, $196 per
acre. The passive private and the intense private had average
net changes of $173 and $318 per acre, respectively.
Timber net value changes varied by cover type; lodgepole
pinedisplayed the least average net value changeand hemlock
the greatest (jig. 2). Cover type affected net value change
Slope and access parameters were originally included in the
computations. To reduce the volume of the results, the original 9828 estimates were aggregated by calculating the mean of
the two original estimates for slope class. The resolution lost
by this aggregation had little impact on the results. Theaccess
parameter was handled in a similar way. This aggregation led
to estimates for 1764 "roaded" situations and adjustment
factors that can he used to estimate the corresponding 1764
"unroadeh" situations. The appendixlists estimates oftimber
net value change and timber output change due to fire forthe
aggregated set of 1764 fire situations under roaded conditions.1 It also lists the adjustment factors.
The following is a discussion of the aggregated set of 1764
"roaded" situations. General trends within the full set of9828
situations (Mills and Flowers 1984) and detailed results of a
small set of the ponderosa pine and lodgepole pine situations
(Mills and Flowers, in press) are discussed elsewhere.
Timber Net Value
Patterns exist in the net value change results but estimates
vary significantly among the specific fire situations. The
-$
.-
-
0)
2
'Estir~atesfor the original 9828 situations are available on magnetic
computer tapeon request from: Patricia 8. Shinkle, PacificSouthwest Forest
and Range Experiment Station, 4955 Canyon Crcsl Drive, Riverside, California 92507.
ma,
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ma,
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or
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2
3
ii
3
Figure 2-Timber net value changes varied by cover type due to
differences in diameter at breast helght,stand age,volumeandstocking per acre, treatment costs, and stumpage values.
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Description: <'I0 percent slope, very low productivity, moderate interrsity public management, 10-99
acres, 60+ percent mortality, roaded
Decisions: retained, interplantcd
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-8.
,a
1-*9
,*-s9
60.
POiltljn~,:
1-29
Interplant
Fint commercial
thin
Final harvest
Site preparation
Fint commercial
thin
Final harvest
30.39
60.
xa"c,mb*c:
1-29
,o-ss
60.
YezY 101 ( 2 0 - . 9 / ,
~~.d,ln~/..~,np:
Dcscriptian
First commercial
thin
Final harvest
Site preparitian
Fint commercial
thin
Final harvest
1-29
,e-39
60.
I..~iins,n.pllns;
0
0
Ill
0
Benefit
PO,Ot,rnb.',
151
2,
Price
I.rdil.p,s.pllnp;
0
''I
ie
,Bl-,ls,:
Harvest
-1s
-28
12
1-23
,*-59
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Pe,rtl*or:
1-29
30.39
6W
so"<,mb*c,
L.29
-8
30-59
,2
1:
$0-
Physical output change: 0 (total for first 204 years in 100 cu ftlaere)
Net value change: 307 (1978 dallars/acre at 4 pct discount rate)
Table 3-Example of apolefimber srond rhor was nor retained offerfire and was nor solvaged
Description: <do percent slope, low productivity, intense private management, 10-99 acres, 60+
percent mortality, roaded
Decisions: not retained, not salvaged
Years since
fire
,,,*h
,,20.?:
Harvest
Price
I00 cufflacre
XI100 cuff
49
40
42
55
--
105
---
125
57
134
7
20
--
---
90
57
134
Benefit
Cost
Repetition
cycle
-X/ocre-Without lire
5,194
--1.24
-129
Years
-7,638
With lire
88
-50
85
85
85
--
85
0
85
85
r.ediln9,r~ilmp:
1-23
30.59
60.
Pa,ct."b"c:
1-23
,o-59
60.
sa"tLSbec:
1-29
30.59
60.
" * < o r a t @ ,a5-,,9,:
r.railn.i/.rpllns:
,-z9
39-59
6".
*o:ec,mb"z:
.-29
,0.5$
$0.
,a"t.mb",,
7,638
Description
Final harvest
Plant
Precommereial
thin
Final harvest
Plant
Precommercial
thin
Final harvat
Physical output change: -9 (total for first 200 yean in 100 cu ftlacte)
Net value change: 964 (1978 dallars/acre at 4 pct discount rate)
>-a*
,".9*
6D.
""" ( 5 0 - 8 4 , :
.nli"g,..Pll"g:
3-39
30.59
60.
D",er,mber:
>-2g
.........
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6".
,-:*
....
,*-59
)
ill"
,2O-*l/:
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-19
ofsite preparation required wlth an assoc~atedcost reduction
of $70 per acre. This site preparation cost adjustment is a
benefit due to fire. The net impact of these forces was a loss of
value.
The fourth case represents a sawtimber stand with moderate mortality after a large fire (table 5). In this situation, the
net gain results from economies-of-scale and the truncation of
an otherwise uneconomical without-fire regime. The postfire
stand was not retained after the fire due to insufficient stocking, but stand conditions were adequate to support a postfire
salvage harvest. The economies-of-scale associated with a
large fire size led to increases in the salvage price and reductions in the stand establishment costs. The per acre costs of
site preparation and planting were less with the large burned
area (2088 acres) than they would be with the smaller management area (35 acres). The intense public regime in this case
had a rotation age that extended beyond the financially optimum age with respect to timber values. The fire reduced the
final harvest age to a point nearer the financial optimum.
While fire may have had a detrimental effect on nontimber
outputs, it had a positive financial impact on the timber
output.
net value change was then estimated using the SASSY financial return computer program (Goforth and Mills 1975).
EXAMPLES OF ANALYSIS CASES
t
Wt,"-limlraa~nl
L1d,YIM@"t mnzanionnand
~IDl,/rn.,O,
&
I
D
Si!Lp~~"lion
'"d pl'"li".mnl
adl"nlm"nl
*ia,on criteria
Figure I-Generalized data were adjusted for individual cases according to decision rules.
increase in treatment cost was assumed to be 1 percent per
year through 2030. Costs were held constant thereafter.
Green stumpage price estimates were drawn from regression equations developed from transaction data for 790
Northern Region timber sales on National Forest land
(Merzenich 1982), from September 1977 th<ough December
1982. Size of harvest area also influences the green stumpage
price through a variable for the total volume of the sale, thus
interjecting another scale economy influence. Real stumpage
prices increased over time to the year 2030, as a function of
lumber price and production cost projections (Adams and
Haynes 1980). Real prices were assumed constant after 2030.
The decision to salvage and the subsequent price of the
salvage sale were derived from equations based on salvage
sale transaction data in the Northern Region (Loveless and
Jackson 1983). The salvage sales database extended from
1970 through 1980. The decision to salvage was strongly
affected by accessibility and the total fire size. The price of
advertised salvage sales was set at 53 percent of the comparable green timber price. Unadvertised salvage sales were sold at
the "green slip" price of $1 per 1,000 board feet.
Management regimes, timber yields, treatment costs, and
stumpage prices were adjusted usinga number of internalized
decision rules that considered characteristics of individual
analysis cases flg.1). For example, the decision to retain a
partially destroyed stand was based on a comparison of the
postfire stocking with minimum stocking standards for manageable stands. This methodology permitted a fairly efficient
analysis while still addressing appropriate adjustment for
individual case differences. The individual transactions in the
regime were developed using the regime, yield, cost, and price
information, adjusted by the internalized decision rules. The
The net result of combiningthevaried and numerous types
of data used in this analysis can most easily be seen through
several illustrative cases. Although not a statistical sample,
these cases represent some of theimportant patterns of behavior in the timber NVC calculations. Four illustrativecases are
presented in detail.
The first case represents a seedling/sapling stand that was
retained after fire and then interplanted to raise stocking to an
acceptable level (table 2). The stand was retained because the
minimum stocking standard was met. The number of trees
per acre was low enough, however, to require an interplanting. Because of interplanting, the timing of future harvests
was delayed by 14 years. When combined with the cost of
interplanting, this extension of the rotation caused a net loss
due to fire. Net timber output did not change due to fire in this
situation. It is the change in timing oftransactions along with
cost differences, not the magnitude of the loss in yield, that
causes a net value change when fire occurs.
The second case illustrates nonretention and no salvage
after a high-mortality fire of moderate size in a poletimber
stand (table 3). This stand did not have sufficient stocking
after the fire to be retained. Based on stand conditions for
average diameter at breast height (d.b.h.) and dead volume
per acre, no salvage harvest occurred. Establishment of the
new postfire stand was delayed by 5 years. This same 5-year
delay affected all subsequent with-fire transactions as well.
This situation showed a net loss resulting from the foregone
without-firefinal harvest benefit that would haveoccurred 40
years hence, and because the loss was not offset by a with-fire
salvage harvest.
The third example case also shows nonretention for a
moderate size fire of high mortality in apoletimber stand, but
volume and d.b.h. were sufficient to support a salvage harvest
(lable4). The stand was not retained after fire due to failure of
the postfire stand to meet the minimum stocking standards.
The determination of whether to sell the salvage harvest as an
advertised or unadvertised sale was affected by the average
d.b.h. of the stand and the size of the fire. In this case, dead
volume was sold as an unadvertised saleat $I per 1,000 board
feet. The final price of the salvage was a weighted average of
the live volume at a comparable green timber bid price and
the dead volume a t t h e unadvertised "green slip" price. The
with-fire stand was salvaged at a weighted bid price ($4 per
100 ftl of timber), which was much lower than the full final
harvest price ($41 per l00ft3) of the without-firestand just 14
years in the future. The fire causes a reduction in the amount
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Management emphasis,
productivity Class,
and rotation
x,,
It,
DougIo5-Jir monosernen! regime ondyield cl~omelerisrics
..
.
.
.
.
..
.
.
.
.
Moderate public
Low
Existing
Regenerated
High
Existing
Regenerated
Intense public
LOW
Existing
Regcnerated
High
Existing
Regenerated
Passive private
LOW
Existing
Regenerated
Moderate
Existing
Regenerated
Intense private
LOW
Existing
Regenerated
High
Existing
Regenerated
INumber of precommercial and commercial thinnings in existing rotation regimes. The
actual number in each analysis case was a function of existing stand age artime of fire, i.e.,
stand age for the cover typc and stand size class. and scheduled thinning age.
'Mean aonual increment was calculated from the sum of the harvest volumes divided by
rotation agc. First rotation harvest ageand mean annual increment are for sawtimber stands
only.
precommercial thinning and one or two commercial thinning~,depending on commercial viability.
The passive private regime assumed a final harvest will be
the only management activity after stand establishment. The
rotation age approximated the financially optimum age and
was estimated using the CHEAP0 supplement (Medema and
Hatch 1982) of the Prognosis timber growth model (Wykoff
and others 1982). For the intensive private regime, the rotation age is also set to approximate the maximization of
present net worth but in the presence of precommercial thinning and up to two commercial thinnings.
Timber yield estimates for the regenerated or second rotation were developed from a Prognosis projection of 212
samplestands from selected National Forests in the Northern
Region, a subset of the sample stands that were used to
develop yield estimates for land management planning. Projected yields for individual stands were aggregated into 96
yield sets by cover type, productivity class, and management
emphasis. The existing or first rotation yields for existing
seedling/saplingand poletimber stands were derived through
a percentage reduction of the second rotation yields. This
percentage reduction reflects the less intensive management
of the existing seedling/sapling and poletimber stands. The
first rotation yields for existing sawtimber stands were
derived empirically from inventory data on existing sawtimber stands. This derivation implicitly assumes that current
seedling/sapling and poletimber stands will, at maturity,
more closely resemble the Prognosis projection than the existing sawtimber stands. Viable commercial thinnings were
identified using the Northern Region's thinning default
option in the Prognosis model.
The cost of silvicultural treatments, such as site preparation, planting, and precommercial thinning, were derived
from equations developed from silvicultural service contracts
let in the Northern Region from 1975through 1978 (Mills and
others 1985). The only variable retained in the equations was
acres treated. The other variables were collapsed into the
intercept by setting them equal to their mean sample values.
This simplified equation form still permitted a reflection of
the economies-of-scale found in larger treatment areas. Real
1.m-
PNV of infinite series
PNV,,, = final harvests in
regenerated stand
PNV of harvests in
existing stand
-
PNV of infinite series
management costs in
regenerated stand
PNV of residual
timber remaining
after fire
-
Scope of Analysis
PNV of management
costs in existing stand
PNV of infinite series PNV of infinite series
PNV,, = final harvests in
- management costs in
regenerated stands
regenerated stands
following fire
following fire
PNV of timber salvaged following fire
+
PNV of management
cost in existing stand
Timber output change is thedifference between thescheduled
timber yield without fire and with fire.
""dl/
'I*.
2,r-?,cr<~"lrd
rh&"gon in
*f ,arm ntan0.
tncmnc prlr.Le
..nqc;m(,
nolrhoin l D I k Y * . Y " l l * " T .
bZ LLI.
and d<SOO""< 'at-
B19h 112a.1,
r~~a,'n9,~api,n~,
,2.L
+
+
PNV of any single
rotation difference in
management costs
following fire
Not all terms are included in every fire case. For example, the
one-time change in regenerated rotation management costs.
(such as the removal of a scheduled site preparation because
the fire essentially accomplished the site preparation, or the
inclusion of a planting rather than a natural regeneration
because the fire removed the seed source) only enter the
computation. if the stand size, stocking, fire size, and tree
mortality are of certain levels. Similarly, the salvage transaction enters the computation only under certain conditions of
stand size, volume per acre, and fire size. The first two terms
make the with- and without-fire cash flows cdmparable despite dissimilar rotation lengths or unmatched sequencing of
without- and with-fire rotations.
A major assumption imbedded in our net value change
computation concerns the geographic area from which the
fire-induced change in the resource output is measured. Two
options exist: measuring the effect on only the fire site plus
direct physical and biological effects offsite (Althaus and
Mills 1982); or measuring the effects on the entire management area or market area in which the fire occurs (Van
Wagner 1983). Our analysis measured the fire-induced
changes on the fire site only because the firesite analysis most
closely reflects the impact of fire on the basic productivity of
the timber growing site, relatively unencumbered by management constraints.
Timber net value change was estimated at three discount
rates: 4.0,7.875, and 10.0 percent. The4.0 percent rate was an
approximation ofthe real return on investments in the private
sector (Row and others l98I), and is being used by the Forest
Service in land management planning; 7.875 percent was the
1983 discount rate for Federal water project evaluations (U.S.
Dep. Agric., Soil Conservation Serv. 1982); and 10 percent
was the rate recommended by the U.S. Officeof Management
and Budget (1972) as the real rate of return on investments in
the private sector.
In addition to the timber net value change, we calculated
the timber output change for the first 200 years following.fire.
52
-36
30.59
6%
The analysis was structured to evaluate situation-specific
cases defined by a combination of values for the following
parameters that characterize the fire site, the timber management context in which the fire occurs, and the fire severity:
access, slope, management emphasis, cover type, productivity, stand size, fire size, and mortality. After removing
parameter combinations not generelly found in the northern
Rocky Mountains, such as passive private management on
high productivity sites, we estimated net value change for
9828 separate situations.
This situation-specific approach, rather than a site-specific
analysis, was followed because of the required model complexity and its associated datademands. Errors that will result
from extrapolation of these situation-specific estimates to
particular sites is expected to be far less than the errors that
would result from incomplete model specification or poor
data input that would likely occur if the computations were
for site-specific conditions with limited analysis resources.
tD."..s
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,.
Sources of Data
Four categories of data were required: timber management
regimes, timber yields, silviculture treatment costs, and stumpage prices. Most of the data were derived from National
Forest sources in the Forest Service's Northern Region
(northern Idaho and Montana). The data were developed to
follow as closely as possible the input used in land management planning, thereby increasing the applicability of the
results to long-term planning on National Forest lands.
Four sets of timber management regimes were developed
from selected land management plans in the Northern Region
and on recommendation from the Regional silvicultural staff
(Wulf 1982): one each for "moderate intensity public,"
"intense public," "passive private," and "intense private"
timber management. The regimes differ in the form of stand
estab1ishment;the numberofcommercialand precommercial
thinning entries, rotation age, and the acreage of the withoutfire harvest area. Sample data for fire situations in Douglasfir are in table I.
The moderate intensity public regime reflects a generally
nontimber resource objective but where limited commercial
timber harvesting still occurs. Rotations are generally extended beyond the culmination of mean annual increment.
There are no precommercial thinnings and only one commercial thinning, if one is commercially viable. In the intense
public regime, commercial timber,harvesting is the primary
objective, but here too, the multiple-use management philosophy affects the regime. The rotation approximates or prece'des the culmination of mean annual increment. There is a
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I*-59
64
6'
GO.
sa"t%mb"c:
L.2,
30.59
6"0b~L.n
IMI-iiP,:
Seedilng,~.*lng,
1-29
,0-5,
m.
>D,sri_",,
,-29
,O.SP
60.
sa"c,*b*c:
->a
36
L.2,
30.59
60.
LO"
,50-80,:
S*edlln9/..pLln9:
1-29
30.59
6-
e-Lcc,-ber:
1-29
20.59
ea
s&"t,abec,
84
8,
1-29
30.59
&W
"SLY 1.1 1201.91,
s.rdl*ng/..pllnll.
1-29
3s-59
6a
*o,*t,nbez:
1-29
>D.,9
..
.
.
.
.
..
..
3" ".f n*.. . Y L P Y I
"CC<h.rn
n 0 . q n.untr*no,
.I
ilftb
by Pi.
.nod.
e.l
""de.
and r,.r
..,,so
'Table 29-Fuclomfor o ~ l l ~ , . ~ lruoclelcd
i , z ~ ,,<>I ,rolcrr rhange esli,?~ore.s
10
lezr-oohd e.~ri,~,orer.
it,lzo,root/<,</,,nlr,e is ,zexoli!,r
Fire sire: 1-99 acres
Firc sire: lOO+ acres
M$magement
Discount rate @ct)
Discount rate (PC[)
empl,arir.
sire,
mortalityciass(pct)
4.0
7.875
10.0
4.0
10.0
7.875
Table 30-Faoorsfor
adjuslmq roodcd ,,el ~ralurd,o,,fic c.s~i,r,ale.~
10
~otroadedrsri,r,arm when rooded vol~reis posilive
Fire rirc: lOO+ acrcsFirc sire: 1-99 acres
Management
Discount rate (pct)
Discount rate (pct)
stand si;re,
martvlity class (pct)
4.0
7.875
10.0
4.0
7.875
10.0
Moderate public
Seedlingjrapling
1-29
30-59
60*
Poletimbcr
1-29
30-59
601
Sawtimbcr
1-29
30-59
60,
Intense public
Scedling/sapling
1-29
30-59
601
Poletimbcr
1-29
30-59
601
Sawtimber
1-29
30-59
60+
Passivc private
Seedlingjsapling
1-29
30-59
601
Poletimber
Modcratc public
Scedlingjsapling
1-29
30-59
60,
Poletimbcr
1-29
1.00
1.02
1.03
1.00
1.03
1.05
0
1.04
1.06
1.00
1.02
1.03
1.00
1.03
1.06
0
1.04
1.02
1.01
1.03
1.03
1.07
1.02
1.03
601
Sawtimber
1-29
30-59
601
Intense private
Secdling/sapling
1-29
30-59
601
Poletimber
1-29
30-59
601
Sawtimber
1-29
30-59
60+
-
-
-
-
..
.
-
0
0.86
1.00
0
0.90
.99
0
0.28
1.00
0
0.55
1.00
0
0.58
1.00
-
.95
.84
1.00
.95
.87
1.00
.77
.49
.42
.78
.63
.62
.79
.67
.67
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
.30
.94
.88
1.00
.94
.91
1.00
.63
.24
-
.79
.73
.SO
.80
.77
.71
-
.92
.63
1.00
.94
.79
1.00
.79
.51
1.00
.85
.48
.38
.87
.54
.50
0
0
0
0
0
0
1.00
-
.95
1.00
-
-
-
-
-
0
0
1.00
.94
.92
0
.95
0
0
-
-
Sawtimbcr
1-29
30-59
601
Intense public
Scedlingjsapling
1-29
30-59
601
Polctimbcr
1-29
30-59
6O+
Sawtimber
1-29
30-59
60+
0
-
60,
Sawtimbcr
1-29
30-59
601
Intense private
30-59
601
Poletimber
1-29
30-59
601
Sawtimber
INTRODUCTION
I
n the last decade, the fire management program of the
Forest Service, U.S. Department of Agriculture, has come
under closer scrutiny because of ever-rising program costs.
The Forest Service has responded by conducting several studies analyzing the economic efficiency of its fire management
program. Some components of the analytical models have
been difficult to develop, particularly changes in the net value
and output of timber caused by wildfire.
The timber net value change calculation can be complex
because of the long timber production time and the substantial impact of the management context on the timing of
management costs and harvests. The timber computation is
critical, because the change in the timber resource accounts
for a large share of the total net value change due to fire:
nationwide, 60 percent on National Forest land and 75 percent on State protected lands (U.S. Dep. Agric., Forest Sew.
1980, 1982).
Numerous approaches have been proposed for estimating
timber net value change (Flint 1924, Lindenmuth and others
1951, Mactavish 1966, Marty and Barney 1981, Van Wagner
1983). The computations vary substantially in how they
reflect fire-caused changes in both the magnitude and timing
of the management costs and harvests, and in how certain
conceptual issues, such as the substitution of unburned for
burned timber, are addressed. For example, a relatively simple formulation of the timber net value change calculation
ignores price differentials between green and salvaged timber,
and the possibility for retention and future harvest of partially
destroyed immature timber stands (Schweitzer and others
1982). On the other hand, one of the morecompleteformulatioris includes harvest timing differentials in immaturestands,
salvage and green price differentials, and adjustments in the
management costs required if the fire removes a natural seed
source (Mactavish 1966).
Although these past studies include ample discussion of
methodology, the estimates of timber net value change they
contain are only illustrative and too few to demonstrate how
the net value change behaves under a wide range of circumstances. Therefore, we calculated change in timber net value
and in timber output due to wildfire for a broad range of
specific fire and management situations.
This paper summarizes trends in estimates of timber net
value changes and timber output changes due to wildfire for
1764 roaded situations in the northern Kocky Mountains.
Actual values are listed in extensive reference tables and have
four potential uses (Mills 1983): (I) analyses of long-term fire
management program options, such as those in the National
Fire Management Analysis and Planning Handbook (U.S.
Dep. Agric., Forest Serv. 1982) or the Fire Economics Evaluation System (Mills and Bratten 1982); (2) establishment of
fire dispatching priorities; (3) analysis of escaped fire situations where extensive calculations are often difficult to
accomplish because of the real-time demands of the decision
process ( U S . Dep. Agric., Forest Serv. 1981; Seaver and
others 1983); and (4) analysis of long-term harvest schedules
when fire-caused changes in timber yields are required.
METHODS
Calculating Net Value Change
Net value change is the difference between the present net
value of resource outputs and management costs "without
fire" and the present net value "with fire":
NVC = PNVWi,- PNV,
in which
NVC = net value change
PNVWI,= present net value without fire
PNV, = present net value with fire
According to this definition, a fire that produces a net gain in
present value has a negative NVC and one that produces a
loss of value has a positive NVC.
Because the NVC is a present value calculation, any change
in the magnitude or timing of the management costs, the
harvests, or the stumpage prices affects the NYC. Analysis of
the sensitivity of NVC to the completeness with which the
fire-caused impacts on these quantities were represented in
computations for 24 timber cases in the northern Rocky
Mountains, showed that a fairly complete representation of
the firejaused change was necessary to avoid major errors in
the estimate (Mills.and Flowers 1983).
The computational model used in the present study contains three,types of terms: (I) the existing rotation costs and
harvest values, (2) the regenerated rotation costs and harvest
values, and (3) one-time costs or revenues created by fire, such
as salvage values. The generalized form of the computation
was
REFERENCES
1
IN BRIEF..
.
Florvers, Patrick J.; Shinkle, Patricia B.; Cain, Daria A.;
Mills, Thomas J. ~ i m h e rnet value and physical output
changes following wildfire in the northern Rocky Mountains: estimates for specific fire situations. Res. Paper
PSW-1719. Berkeley, CA: Pacific Southwest Forest and
Range Experiment Station, Forest Service, U.S. Department of Agriculture; 1985. 25 p.
Retrieval Terrns: fire effects, economies-to-scale, fire size,
timber management regime
Estimates of timber net value change due to wildfire are
sensitive to characteristics ofthe firesite, fireseverity, and the
timber management regime. Reflecting this sensitivity in
value change estimates requires detailed data collection and
computations. For this reason, the variability of the timber
resource must be considered in detail when fire management
programs are analyzed. The extensive data collection and
computation efforts necessary to incorporate this required
detail are generally not possible under the constraints of
escaped fire situation analysis and may not b.e possible under
long-term fire management planning situations if analytical
resources are limited.
An efficient alternative to estimating site-specific net value
change is calculating changes in timber net value and timber
output at a centralized location for a variety of nonsitespecific fire and management situations. The resulting estimates can then be consolidated and used in the form of
reference tables representing the likely range of fireand management situations. This approach eliminates the inefficiency
of duplicating site-specific calculations, and the detailed data
are preferable to highly aggregative potential loss averages
that are applied to broad heterogeneous areas. These highly
aggregative estimates d o not adequately reflect variability in
the resource base and management regimes, which materially
affect the net value changes.
Estimates ofthe timber net valuechangeand timber output
change resulting from wildfire were calculated for 9828
situation-specific fire and management conditions in the
northern Rocky Mountains. After slight aggregation across
the less sensitive situation parameters, reference tables with
estimates of net value change and timber output change were
prepared for 1764 roaded situations. They are defined by
timber management emphasis, cover type, productivity class,
stand size, mortality class, and fire size, with adjustments for
access status.
Adams, D. M.; Hayncs. Richard W. The 1980softwood timber assessment
market model: structure, projections, and policy simulations. Forcst Sci.
Monagr. 22: 1980. 64 p.
Althaus, Irene A.; Mills. Thomas J. Resource values in analyzing fire managcmcnt programs far economic efficicney. Gen. Tccli. Rcp. PSW-57.
Berkeley, CA: Pacilic Southwcst Forest and Range Experiment Station.
Forest Service. U.S. Department of Agriculture; 1982. 9 p.
Flint, Howard R. Appraisal of forest fire damages. J . For. 22(2): 154-161;
1924.
Goforth. Marcus H.: Mills, Thomas J . A financial return program for
forestry investments. Agric. Handb. 488. Washington, DC: U.S. Department of Agriculture; 1975. 18 p.
Lindcnmuth, A. W.. Jr.; Keetch, J. J.: Ncleon, Ralph M. Forcst lire damagc
appraisal procedures and tables for the northeast. Station Paper No. I I .
Asheville. NC: Southcastern Forest Experiment Station, Forest Scrvicc,
U.S. Department of Agriculture; 1951. 28 p.
Lovelcss, Robert S.: Jackson. David H. Volume and value changes in
fire-damaged timbcr sales. 1983. Unpublished draft supplied by authors.
Mactavish. J. S. Appraising fire damage to mature forest stands. Dep. Pub.
1162. Ottawa, Canada: Forestry Branch, Canada Department of Forestry
and Rural Developmcnt; 1966. 31 p.
Marty. Robert J.; Barncy. Richard J. Fire cost, losses, and benefits: an
economic evaluation procedure. Gen.Tech. Rep. INT-108. Ogden, UT:
lntermountain Forcst and Range Experiment Station. Forest Scrviec
U.S. Departmcnt of Agriculture; 1981. 1 1 p.
Medemu, Lee E.; Hatch, Charles R. Computerized help for the economic
analysis af Prognosis-model outputs: a user's manual. Contribution 227.
Moscow. ID: Forest, Wildlife, and Range Enperimcnt Station. University
of Idaho; 1982. 72 p.
Merzenich, Jim, Operations Rcsearch Analyst, Planning Program and
Budgeting Staff, Northern Region, Forest Service, U.S. Departmcnt of
Agriculture. Missoula, Montana. Personal communications. 1982.
Mills, Thomas J. Integrating fire management analysis into land management planning. Gen. Tech. Rep. PSW-74. Berkeley. CA: Pacific Southwest
Forest and Range Experiment Station. Forest Service. U.S. Departmcnt
of Agriculture; 1983. 8 p.
Mills. Thomas J.; Bratten, Frederick W. FEES: design of a FireEeonomies
Evaluation System. Gcn. Tech. Rep. PSW-65. Berkeley, CA. Pacific
Southwcst Torest and Range Experiment Station, Forest Service, U.S.
Department of Agriculture; 1982. 26 p.
Mills. Thomas J.: Flowers, Patrick J . Completeness of model rpeelficatian:
an illustration with fire-induced timbcr net value change. In: Praeecdingr
aftheScventhconfercncc on fiicand forest meteorology. Pieprint volume;
1983 April 25-28: Fort Collins. CO. Boston. MA: American Metcorolagical Society: 1983: 153.157.
Mills, Thomas J.; Flowers, Patrick J. Fire-induced change in the value of
timber outputs: a sensitivity analysis. Can. J. For. [In $ress].
Miils,Thamas J.: Flowers, Patrick J. Wildfireindueedehangein the present
net value of timber stands in the northern Rocky Mountains. 1984.
Unpublished draft.
Miils. Thomas J.; Shinkle, Patricia 6.; Cox, Gregory L. Direct costs of silvicultural treatmentson National Forests, 197578. Res. Paper WOd0. Wushington. DC: U.S. Department of Agriculture, Forcst Service; 1985. 16 p.
Office of Management and Budget. Circular A-94. Washingion, DC. 1972:
4 P.
Row, Clsrk F.: Kaiser. F H.; Sessions. J. Discount rate for long-term Forest
Serviec investments. J . Far. 79(6): 367-369; 1981.
Scha,eilzer, Dennis L.; Anderson. Ernest %; Mills. Thomas J. Economic
efficiency of fire managemfnt programs at sir National Forests. Res.
Papcr PSW-157. Berkeley, CA: Pacific Southwest Foxst and Range
Experiment Station, Forest Service. U.S. Dcpartment of Agriculture;
1982. 29 p.
Seavcr. David A,; Roussopaulos, Peter J.; Freeling, Anthony N. S. The
escaped fircsituation: a decision analysis approach. Res. Paper RM-244.
Fort Collins, CO: Rocky Mountain Forest and Range Experiment Station, Forcst Service. U.S. Department of Agriculture; 1983. 12 p.
U.S. Department of Agricuiture, Forest Service. U.S. National Forest S ~ S tem fire management budget analysis, I980 [Aviation and Fire Management Staffl. Washington. DC: 1980. 29 p.
U.S. Dcpartment of Agriculture, Forest Service. FSM 5 130.3-Firesuppression policy. Washington. DC: 1981.
U.S. Department of Agriculture. Forest Service. FSH 5109.19-Fire msnagement analysis and planning handbook. Washington. DC; 1982.
U.S. Oepanment of Agriculture, Soil Conservation Service. Interestratesfor
water and related land resource prajcets. Nat. Bull. 200-3-1. Washington,
DC; 1982. 3 p.
Van Wagner, C. E. Simulating the effect of fortst fire on long-term annual
timber supply. Can. J. Forest Res. 13: 451.457: 1983.
Wulf, Norman W.. Silviculturist, Clearwater Forest, Forest Service, U.S.
Department of Agriculture, Orofioo, Idaho. Personal communications.
1982.
Wykoff, W. R., Crookston, N. L., Stage, A. P. User's guide to the tta*
prognosis model. Gen. Tech. Rep. INT-133. Ogden, UT: Intermountain
Forest a n d - ~ a n g eExperiment Station, Forest Service, U.S. Department
of Agriculture; 1982. 112 p.
Timber Net Value and Physical
Output Changes Following Wildfire
in the Northern Rocky Mountains:
estimates for specific fire situations
Patrick J. Flowers
Patricia B.Shinkle
Daria A . Gain
Thomas J. Mills
CONTENTS
................................................ ii
Introduction ............................................. 1
Methods ................................................ 1
Calculating Net Value Change ............................ 1
ScopeofAnalysis ....................................... 2
SourcesofData ........................................ 2
Examples of Analysis Cases ................................ 4
Results ................................................. 7
T~mberNet Value ...................................... 7
Timber Volume ........................................ 8
Conclusions ............................................. 8
Appendix ............................................... 9
References ............................................... 25
In Brief
The Forest Service, U.S. Department of Agriculture, is responsible for Federal leadership in
forestry. It canies out this role through four main activities:
0
8
0
8
Protection andmanagement of resources on 191million acresof NationalForest System lands.
Cooperation with State and local governments, forest induslTies, and private landowners to
help protect and manage non-Federal forest and associated range and watershed lands.
Participation with other agencies in human resource and community assistance programs to
improve living conditions in mrai areas.
Research on all aspects of forestry, rangeland management, and forest resources utilization.
The Pacific Southwest Forest and Range Experiment Station
0 Represents the research branch of the Forest Service in California, Hawaii, and the western
Pacific.
Flowers. Patrick J.; Shinkle. Patricia €3.: Cain, Daria A,: Mills, Thomas I. Timber net
valueand physical output changesfallowing wildtirein thenorthern Rocky Mountains:
estimates for s~eeitictire situations. Res. Paper PSW-179. Berkeley. CA: Pacific
Southwest Forest and Range Experiment Station. Forest Service, U.S. Department of
Agriculture: 1985. 25 p.
Onc of the major economic effects of wildfire is the change in the net value of timber
Estimates o f these changes were calculated lor a wide range of fire situations in the
northern Rocky Mountains of the United States. The results are presented in reference
tables. They are intcndcd as an nlteinntive t o calculating estimates for specific sites or t o
using broad averages. Spccific fire situations are identificd by management emphasis.
cover type, productivity clnss. stand sire. mortality clnss. fire sire, and access puramctcrs.
The reference tables have potential uses in plurlninglong-term fire management programs.
establishing dispatching priorities. analyzing escaped fire situations, and an.llyring
wildfire's impact an long-term harvest schedules.
Rerrievol Tertns: fire eifects, economies-to-scale, fire sire. timber management regime