ISBMqInOS 3!4!3l?d laded qsleasatl - US Forest ServiceThe Forest Service has responded by conducting several stu- dies analyzing the economic efficiency of its fire management program

6LL-MSd laded qsleasatl

uo!lelS luam!radx3 a6ueu pue lsaloj ISBMqInOS 3!4!3l?d

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 hc~ iv i s ion of 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

................................................ In Brief ii

............................................. Introduction 1

Methods ................................................ 1

............................ Calculating Net Value Change 1

ScopeofAnalysis ....................................... 2

SourcesofData ........................................ 2

Examples of Analysis Cases ................................ 4

Results ................................................. 7

T~mber Net Value ...................................... 7

Timber Volume ........................................ 8

Conclusions ............................................. 8

Appendix ............................................... 9

References ............................................... 25

1 IN BRIEF.. .

Florvers, Patrick J.; Shinkle, Patricia B.; Cain, Daria A.; Mills, Thomas J. ~ i m h e r net value and physical output changes following wildfire in the northern Rocky Moun- tains: estimates for specific fire situations. Res. Paper PSW-1719. Berkeley, CA: Pacific Southwest Forest and Range Experiment Station, Forest Service, U.S. Depart- ment 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 nonsite- specific 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 substan- tial 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 sim- ple 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 morecompleteformula- tioris 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 circum- stances. 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 Eval- uation 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 fire jaused change was necessary to avoid major errors in the estimate (Mills.and Flowers 1983).

The computational model used in the present study con- tains 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

PNV of infinite series PNV of infinite series PNV,,, = final harvests in - management costs in +

regenerated stand regenerated stand

PNV of harvests in - PNV of management existing stand 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 sal- PNV of management vaged following fire - cost in existing stand +

PNV of residual PNV of any single timber remaining - rotation difference in after fire 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 des- pite 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.

Timber output change is thedifference between thescheduled timber yield without fire and with fire.

Scope of Analysis

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 com- plexity 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.

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 without- fire harvest area. Sample data for fire situations in Douglas- fir 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 philo- sophy affects the regime. The rotation approximates or pre- ce'des the culmination of mean annual increment. There is a

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eo,ct,mbcr: ,-29 J0.39

, -1s -20

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28

L.29 3B.5, GO*

-1 ,511-80: S . . d l l n g / ~ p l l n 9 :

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64

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LO" ,50-80,: S*edlln9/..pLln9:

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s&"t,abec, 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 ..

ill.lh ,110.,1 II.Li'ns,n.silnp:

1-29 30.39 60.

Po,.LL.beLI 1-29 30.59 c *

s."t'mAo.: ,-a9 10-19 60.

w&cae< ,85-.,9,: Irrdllng/..Cln.i

1-29 30.59 6W

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1-19 ,0-53 60.

*s,ari.nrr: ,-*a ,%*,

6 a 8."t,rnb*C> 1-29 30.59 6-

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Ps*.t,nb*c: r 2 s 3a-59 GO*

3."e*mb.r, >-29 ,a-59 co*

d.il.m,.rir burned'

It, 5 I,' 1<1 x,, A I B ,I, 2.7 2,s '10 327 P I 0

111 ,?I 14, 122 as1 2 141 1 0 1 89s Ills $ # I 812

16 -19, -11(0 -111 260 12 I, ,I 16, 5.8 '81 469

0 0 0 ,110 1'11 16. *a0 100 is, 6 ' LOO

-3 -1 -I -1 -5 -6 -1 -I

,sll ,,D> ,I' 1.1)

7 - .I06 -102 1, -88 -72 -6s

111 216 260 111

0 @ 0 8 0 0

179 450 7 17s

I, I,< 7, I, n IS$ I_ 31

I * , 111 101 180

75 -2 1 2 1x3 36 48 ' 9 111 219 *I1 209

.. . . . . . . .. . . . . . . .. . . . . . .

.- . . . . - - .. . . . . . .

.. . . . - - -

.. . . . . . .

..

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12

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-32

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-2, >a

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"Od*C.<C ,81-L11,1 Ir~dl,"g/..#lns:

2-29 30.39 la

FoLet,.b*c. P

,->9 30-59

-,a 6a

-56 -,do

3.rl'vir.l 2-29 30.59 6a

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-6.

s."e*mb*c> 36

1-29 30.59 $0.

mcr 10" 110-491: S*~dllng/..pllnrj, 1-29 .. 30.59 .. GO. ..

s-leilvinl: >-29 .. 30.59 .. su ..

Table I-seleered DougIo5-Jir monosernen! regime ondyield cl~omelerisrics

Management emphasis, productivity Class, and rotation

Year of

Moderate public Low

Existing Regenerated

High Existing Regenerated

Intense public LOW Existing Regcnerated


Passive private LOW


Moderate Existing Regenerated

Intense private LOW



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. Pro- jected 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 1975 through 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

t W t , " - l i m l r a a ~ n l

S i ! L p ~ ~ " l i o n

L1d,YIM@"t mnzanionn and '"d pl'"li".mnl

~ I D l , / r n . , O , adl"nlm"nl

*ia,on criteria

& ID 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 regres- sion 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 man- ageable 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

net value change was then estimated using the SASSY financial return computer program (Goforth and Mills 1975).

EXAMPLES OF ANALYSIS CASES

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 behav- ior 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 the 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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191s doilacm/&ole bulnrd'

183 617 'Bii 786 611 7 611 4 783 ax7 488

1617 a,. I<# i5Gl i 160 4 7 9

2,. 226 221 -299 -28, -111 ' 3 7 'bl 10 *& 10

>ill i n 9 1 8 5 2 l O l D I B > i 1766

6 64 6 1 - > m i -110 -261 177 lii l b l -Its -116 -1,o ID08 116 716 848 611 618

0 0 0 0 0 0 0 0 0 - 0

4.1 129 1% 4 , 119 l l 9

119 101 8 9 x.9 0 , a9 0,s 525 118 692 'I), 239

,486 ,002 8 9 ,419 9.6 11'

I. I 3 I, -1,s -114 -112 B I 85 0, - 4 -4, .I,

675 48s 4 5 4 I B D 4 376

0 0 0 0 0 0 0 0 0 0 0 0

112 1 2 7 87 322 117 I,

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. . . . . . . . . . - - .. -- .. . . . . . . . . . - - . . . . . . .

.. -- -. . . . . . - . . . - - . . . . . . .

. . . . - . .. -. -- .. 5."t,Shr: . . . . . . . . . . . . . . . . . . . . . . . . - . . . . . . . s."k.u~~r: 1-23 1-29 . . . . . . . . . . . . . . . . . . . . . . . . . . ,s-s9 . . . . - . 30-59 . . . . . . . . . . . . . . . . . . . . . . . . . . 60. .- -- .. so+

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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

-x/ocre-- Without lire

1,510 -

Yean since fire

First commercial thin

Final harvest Site preparitian Fint commercial

thin Final harvest

. . . . . . . . . . . .

0 n 0 0 0 0 0 0 0 0 0 0

I'' l i b 10, 1.4 *I* 10,

i e i i 9 ,A 2 , 16

18 1 2 3 34 2, ,&

I,, 1 5 1 12, ,?I I J i 121

t* 3s I, -118 -,52 - 2 4 s 6. $2 &I - , I0 -116 -111

112 110 101 182 111 267

0 0 0 0 0 0 0 0 a * o n

I l l 31 80 121 92 811

0 0 0 0 B 0 0 0 @ 0 0 0

I*, >a 10 ,>, 28 ,o

-1 -, -1 -1 -1 -1 -2 -2 -2 -2 -2 -2

19, 7, , I In9 48 a

0 0 a B O O

0 0 n 3 0 0

0 0 0 0 0 0

0 0 0 0 0 122 22 8 ,%> % I 8 125 22 8 1 2 3 22 8

-1 -1 -1 -1 -1 -1 9, ' -23 29 -57 -8.

IS> GO 30 1,s a. ,a

Harvest

.... 6W ..

*OdSC.f* ,Bl- , ls, : I.rdil.p,s.pllnp;

1-29 ,e-39 60.

PO,Ot,rnb.', >-29 >0-<9 6W

22

sa"t,*bec: 36

L.29 10.59 60.

LO" I ~ D - l . , : .D

I..~iins,n.pllns; 1-*9 ,*-s9 60.

POiltljn~,: 1-29 30.39 60.

xa"c,mb*c: 1-29 ,o-ss

-1s

60. -28

YezY 101 ( 2 0 - . 9 / , 12

~ ~ . d , l n ~ / . . ~ , n p : 1-23 ,*-59 GO*

Pe,rtl*or: 1-29 30.39 6W

so"<,mb*c, L.29 -8 30-59 $0-

,2 1:

14,508 - With fire - 251 1,510 --

Price

Interplant Fint commercial

thin Final harvest Site preparation Fint commercial

thin Final harvest

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)

Benefit

,,,*h ,,20.?: 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.

" *<orat@ ,a5-,,9,: r.railn.i/.rpllns:

,-z9 39-59 6".

*o:ec,mb"z: . -29 ,0.5$ $ 0 .

,a"t.mb",, > - a * ,".9* 6D. """ (50 -84 , :

.nli"g,..Pll"g: 3-39 30.59 60.

D",er,mber: > - 2 g ,n-% 6". ......... ,-:* , * - 5 9 ....

) ill" ,2O-*l/: .~<a,,"q,oae,'"9:

-19

Cost

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

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)

ofsite preparation required wlth an assoc~ated cost 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

Repetition cycle

Years since fire

large fire size led to increases in the salvage price and reduc- tions 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.

Dcscriptian

Harvest Price

40 42 55

125

7 20

90

I00 cufflacre XI100 cuff -X/ocre-- Years Without lire

49 105 5,194 -- 0 Final harvest - -- -- 1.24 85 Plant -- -- -- 129 85 Precommereial

thin 57 134 7,638 -- 85 Final harvest

With lire -- -- - 88 85 Plant - -- -- 50 85 Precommercial

thin 57 134 7,638 -- 85 Final harvat

Benefit Cost Repetition

cycle Description

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

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

Description Repetition

cycle

Description

14 I5 93

I 2

83 2

Benefit Price

I00 ruf l laos %/I00 rufl -$/acre-- Yeors Without fire

44 41 1,804 -- 0 Final harvest -- -- -- 94 79 Site preparation 63 114 7:182 -- 79 Final harvest

With fire 33 4 132 -- 0 Salvage harvest -- -- 83 79 Site preparation -- 63 114 7,182 -- 79 Final harvest -- -- 70 -- 0 Site prepara-

tion eost adjustment

Years sincc fire

Benefit Price

14 15 17 32

57

77

I I2

I 2 3

18

43

63

98 2

3

Physical output

Years since lire

Cost

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)

Harvest

100 cuflloere $1 I00 cufl - S / o c r t Yeors Without fire

40 45 1,800 0 0 Final harvest -- -- 137 98 Site preparation -- -- -- 21 1 98 Plant -- -- -- 27 1 98 Preeommercial --

thin 3 79 237 98 Fint commercial

thin 12 129 1,548 98 Second commer-

cial thin 79 164 12,956 98 Final harvest

With fire 39 32 1.248 -- 0 Salvage harvest -- -- -- I21 98 Site preparation -- -- 184 98 Plant -- -- -- 236 98 Precommcrcial --

thin 3 66 198 -- 98 First commercial

thin 12 129 1.548 -- 98 Second commer-

cial thin 79 164 12.956 -- 98 Final harvest -- -- 90 0 -- Site preparation

eost adjustment -- -- 116 0 Planting cost --

adjustment

change: -78 (total for first 200 years 100 cu ft/acre)

Hamst Cost

Nct value change: -376 (1978 dallars/aere at 4 pct discount rate)

Repetition cycle

%*lo ,es..s,r ..il.l*d ohm*om I" nrr tlrber *urpur * LII-Si iruc~ rkmds ""dSC pernira pr,r.t* nm.iien*o*. n ~ i i h r c n il*<XY Na""la,"r, by I I C . S3.C ma i t r r p.l,.d

SL."d .irau.rlrirYi F,rc 0,zs: 1-33 acrus i." t i / a E i V Y i l . I

/ rile G ' Z > ; im. ofand r,/e. ."d I .OI I . l l IY <Ianm I

*.me p*r.-a ,y<-cs,

(Pet, , - 2 3 . 9 5 - 9 9 0 - 0 . 0 I 0 - P I 23.4) 50.99 1110.200 0.2110

RESULTS

Specific cases for which timber net value and output changes were calculated were described by the following parameter classes:

Parameter Classes Timber management emphasis Moderate public

Intense public Passive private Intense private

Cover type Douglas-fir Ponderosa pine Western white pine Fir-spruce eml lock Larch Lodgepole pine

Productivity class High (120t cu ftlacrelyr) Moderate (85-1 19 cu ft/acre/yr) Low (50-84 cu ftlacrelyr) Very low (2049 ccu ft/acre/yr)

Stand size Seedling-sapling Poletimber Sawtimber

Mortality 1-29 percent 30-59 percent 601 percent

Fire size 1-99 acres lOO+ acres

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

'Estir~ates for 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, Cali- fornia 92507.

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

.- - m a , c m m x Y)C - c O

m a , 0 = - $ g-E 'UE 2 - 0 0 m 0 .= - ", _I a a

m m a 5 m 0) n 2 c 3 . E 1 n or

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, volumeandstock- ing 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 deter- mined 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 salvage- able. 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 avail- asie 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 148 148 Poletimber 33 1 248 Sawtimber 237 27

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.

Timber Volume

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.

CONCLUSIONS

The estimates of net value changes and changes in timber output are sensitive to the fire situation and stand classifica- tion 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 situation- specific estimates presented in the reference tables also eliminates the cost of the repetitive calculations needed to produce site-specific estimates.

YL.b ,.no*,: "olalln~,..~.lns'

1-29 ,o -w eo*

Z O I ~ T l s b r i : 1-23 3a-$9 60.

S."t,rnb*C> ,-29 111-19 so*

*do.. ll 111-1,s,: Il.dl*nS/.aPL*nS.

1-29 30.59 60-

Pol*t,sbmr> 1-29 30-59 60.

S.Sll"blC/ 1-29 ,0-3* '0.

LO" ,5o-a,,: Ilrdl,ng,..illln9i

1-29 ,O.% 60.

*o,*L,vBcr> .-29 30.59 60.

S."timb*c: 1-13 30-59 60.

"SCY 10" ,ZO..$>& r~s~ i lns / -p i 'ns :

1-29 30.39 60+

P ~ > O t , r n B ~ . ~ 1-29 30.59 6s.

*a"t,-bor: L.29 ,o-sa so*

h t l w I-, mun - dm, a l r l r *", - I-, 0 - , a ar. -, - - mum 0 5 dm.

. . . . . . . . . . - - 30-59 . . . . . . 60. .. -- -- EQLntZmbeL: . . . . . . . . . . . . ..%9 .... . . . . . . 10-59 - . . . . . . . . . . . . 6% sm"e,mher, . . . . . . . . . . . . A-29 . . . . . . . . . - - - 3s-59 . . . . . . GO* .. -- --

I0dlrnre , IJ- l is , : s~eaL*ns ,~e , ins:

3-29 0 0 0 o n * lD-I9 0 0 0 0 0 0 60, 0 0 0 a 0 0

Pe,cs'nber: ,-z9 n 0 0 o a o ,0-59 1'3 111 11) 111 ,.is 1,s so* 46s 12, 1'1 a,, 184 L2D

sa"t,ebsc: 1-!9 192 185 isi -101 -289 -1111 30.39 ' 5 '2, .21 -150 -,a0 -,,I 60. 684 6 62.1 46 33 33

m , ~ l l - B l , i s*r~i,"9/n.Llnsi 1-29 B 0 0 O B O >0-,9 0 * 0 0 0 0 10. 350 IIa I* 150 11, I S

sol*ll.b*j: ,-a* 0 0 0 0 0 0 30-59 B O O a 0 9 60. a , 11, 12 6.7 7 11

S."<lib.,/ 1-29 26 i s -I,( -se -9' 30.59 0 118 l l b -33 -3s -35 GO. 8 , 211 25' 48 I, , I

very LO" ,10-,,,> 6..dll"9 ,... .*n.i

,-a9 0 0 0 0 0 0 3m-59 D 0 0 * 0 60. 0 0 0 0 0 s

PDI.LI.b.Li 1-29 0 0 0 0 0 0 20-re 0 0 0 0 0 0 m* 8x9 is9 88 8 199 P I

3a"e,-b.r, ,-a9 1 B 4, .1 -82 -11 -75 l l i . lS I,, 1.1 i t , -3. -1 -35 60. 3x3 269 264 33 I? 36

L.,S d.il.cn,.ri. b"l".di

237 209 ' 11 111 109 I j l 2* * .I> 2 1 3 20, 225 118 ' 0 8 225 1 9 8

.L -5 -7 -s -6 -9 - 9 - 9 -9 -9 I* .IS 3 , .,I, -232

22 11 -*9 -7, -77 282 i Q 9 -2611 - 3 -420 '0, 10, -16 ->ii -292

0 0 0 0 0 0 0 o a s

260 24, 1.7 160 2.3

'3 21 Ll, 'I I , ' 1 22 1 2 9 41 I2

278 151 899 ill 16

1 2 0 21 32 n 1 2 2 262 9, 4, -. 111 2 , 110 189 , l B

Ij 0 a 0 0 0 0 0 0 0 0 a 0 0 e

-1 -1 -1 -1 -1 -2 -2 -2 -2 -2 1011 116 111 6, 46

-2 -1 -2 -2 -2 10 -67 275 -111 -201

229 119 50' I 3 I

0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0

-1 -I -1 -1 -1 .I -1 -1 -1 -1

111 117 111 2.) I'

-2 -2 -2 -2 -2 -72 -,,0 200 -211 -275 1.6 10 161 -8 -6,

APPENDIX Cover type

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, 100-200 years) 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:

Douglas-fir Ponderasa pine Western white pine Firspruce Hemlock Larch Lodgepole pine

Management emphasis Moderate Intense Passive

public public private

(table number) I 8 15 2 9 16 3 10 i7 4 I I 18 5 I2 19 6 13 20 7 14 21

Intense private -

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.

r..l. 2C.PLrrc.Y..d m.n... tn r.iur or ponaeror. r lnr -rand= u . ~ ~ . mod.r... rYbilc ..n...lmr. n.rmrin aor*r nounrains. 4 LLI. .,)* &"* d'.rounl c.rr *.... p.....,,,,,y i *LZC s'ze: 2-39 .O,O" , r,,<T.z*: LOO* .GtCU

icu f".sr./Yrl. ip- .rand s,.., ..d s .IICDY.L I... lei, solT.,icy Si0.. i ,"=., I 4 . 7.875 10.0 I 4.0 1.811 '0.0

I 2 12 s 11 1 2 6 6 151 il7 i s 7 a1 70 ,111 L11) 1.9 2,. lli 69

1 -221 -218 - 4 - 0 -02. IS$ -11 - 7 -10. -686 -705 211 11 -11 -117 -53s -162

0 0 0 0 0 0 0 0 0 0 0 0

I l e 160 111 119 1611 111

,29 21 I 120 2 1 D Lie 2, B 11, 2 1 8 I S . io, 16% L', 92 77

-11 -21 -28 -232 -194 -lS6 Is3 2 la? ->l5 - 0 -101 4 , I t , 119 -101 -171 .lil

0 0 0 0 0 0 I1 L) 0 L 1 0 0 0 0 0 0 0

Ta*," ID.., YO.d .D."s.. I" ".k ti.*.. ."rPYL OL mYri.T-tl. =rand0 under Iled*r.tc i...Ol i."l, "..,.hli" IO.kY I.""t.l".. hY f l i . Zli. ."d Ti.. P l i O d

ILa"e PID.Y.k,V I<)., : - 9 , i PIC. .ti.: 10a. .CI(* ,em LVn.i./lrl. I .L."d . ,xe. and I Ili* i.i,.d IY.aI.1 Oorlu,ry class i (Par, I 0.24 2 5 - 4 1 IO.99 1110.200 0.200 , *.I. 25-49 50-99 L O l i - I n D 0-1oa

mb,* ,ln.- ,LI~ C.Ylld .D."(i.. L" ".E ".,"I .I Ilr- .PlYI. .Ln"eD ""d., ill."'. SY.,,C ..n.gm.nt. n.i.b.'n as<** munrazn.. 4 Llir

a,~c*""c r-te

.rind prod".r,V,il , r,,* o,z*, 1-39 8 r,re sxac: mo. *=tea I = " IV.Elt,l.l. i ll..d .,I.. and i Dln0.Y.L Z.L. ,we, , c . I ,PCLJ I &.~i ? . a i l 10.0 1 4 . 0 1.811 10.0

,978 d ~ , l a r G , ~ e c a h"c"~aL "X9h ,n20*,: sr.dllng,r.Piln~;

1-29 ($1 111 101 4 6 1 112 102 311.19 A , 2 10% '67 112 101 60. A60 11s 9 s ' 6 0 1 2 1 95

*o ,~c*sb* t : .-29 ,&, 62 1 8 1<1 6 1 i s 20-59 119 60 36 179 6 s I6 60. ~ 1 x 5 22% 8 1 1I.L Lls 6

sa"t,mbecx 1-23 204 1 s 99 ->S7 - 264 -27a 10.111 '98 103 262 1 6 1 -11 - 4 1 CO* 10) 7 111 lil 156 116

_dCj l** ,I5-.1S>: s..dlinS/r.LlnS:

1-29 O O * 0 0 0 30.99 09 126 sB 429 116 98 *a* 6 1 2 6 90 6 116 98

Po,st,aberm L.29 6 8 , I' 1 1 07 4. ,*-59 29, 8' '3 29, 4 42 60. llSS I , , 81 L119' 110 I

sa"t,sb*c: ,-m I , 4 -225 -209 -a *> > O - X 10 10 Ii -1011 -176 -L69 GO+ 01 101 111 -19 i 26

L*" < I O . I , J i sl.dling/roplln9:

1-29 O D 0 0 0 1)

,0-5* 0 0 0 0 0 0 60. 212 131 1x4 212 L11 I14

Fo,ct,mb~,: >->a 166 16' 127 6 6 . 1x7 ,O.% 6 , 2 , I*. 261 I l l 1x4 a o i 6,b 116 P I 502 I S 1

sa"txabcc: 1-29 212 97 1' 1, -6' -1,s 30-59 151) 111) 61 9, -1s .?5 60. 292 il, 77 IS. 41 -1

YIIS I." ,lO-'s,: s*c*,,"*,'.DlL"3:

1-23 D 0 0 0 0 0 30.59 0 0 0 0 0 0 60. 6 161 111 168 111 131

P*ir lMcr i 1-20 ' 5 IS5 L1, ,I, I.)* 111 10->? 43% 192 ,211 455 192 *a0 <>* 7,s 121 1, 4 IS -6s

I."r/.b~l: 3-29 -1 -1 -1 - 2 -1 -1 ,o-s* -2 -1 -2 -2 -2 -1 $0. 3 , 9' 18 111 6 -12

13C-p~.r..u..d ob8n9s. r .~u. OL D ~ X O C L sr-na. 1nr.n.. P"hl,. ..n..n.nr, no.rb.m xocrr wunr.Lns. 4 LLI. .'.. ."d *,.~~unt ..I.

p"dY.n",ty I r,.. .'... l.9, .-... I ,I.. .,..I .OD. ..I.. LC" tU....,l'l. I .%."a .IS., m.3 I o,.r.unr i.r. Is(', nols.l'tl ci... i ,Pot, 1 4.0 7 . 5 0 , 0 7.111 10.0

,911 4.,,...,.c.. ."lnrdl "Irjh .,110*,:

rroalins,..pilns~ L-23 610 238 135 GIs 118 191 ,0-59 622 3 1.7 GI2 0 181 So+ 7 3 1 154 61 610 1 2 -11

*a,*t,sbar: ..%* -8 -8 -0 -8 -0 -8 ,s-3* .,I -13 -14 - 5 -15 -*, 60. 862 -110 -112 72, -24s -406

s."t,mber, 1-29 1x9 & I . 1 2 2 -200 -181 -110 39-59 697 672 659 4 L II 12 60. 107s 925 I B a 111 P36 216

HOdCL.t* LB I -> IS , : Illd,lng/..pl*n9:

L-29 2 101 111 111 201 121 ,o-,* 765 1% LIB 1 L I 196 ill CO* 1126 181 77 ,056 121 20

S.llll.bl.: 1-29 21, 10, 6 2 10. L I 30.59 l , , 98 $3 P l i 98 (1 50. ,AS> ,.I -13, ,126 -11 -2%

s."t,aber- I.29 I, 8 , a0 -111 -111 -162 30.59 210 212 269 I S 62 50. $22 818 811 B l l 7Sl 1 4 1

La" ,Io-I. ,1 Ilrd,l.S,'PLL.S:

1-z9 0 0 0 O O D ,0-5, 2 o a I I) 0 GO+ 111 101 96 i s> 101 3 1

Po,ct,mb*c: 1-29 -1 -1 -1 -1 .I - 3 ,0.%3 1 -3 -1 I -1 -1 604 171 1, 10 101 I3 -2.

s."*,mba.: ,-Is I* s c 19 3 r 30.39 409 176 86 1 9 6 14 -11 60. 112 116 181 l a 9 111 1 2 9

very l o r ,20 - . * , : I.rdlL"g,n.pllnS:

1-23 0 0 0 0 0 0 ,*-59 0 0 0 e n 0 60. 30, 1%' 1111 19, I,, LIB

Po,at,mb*r: 1-29 ., .I -, -* -1 -1 >a-59 -1 -1 -2 -1 -1 -2 60. I . , 0 -1. 17, -11 - la

sa"c,.ba,: 1-23 -2 -2 -2 .I -2 -2 10-19 -3 -5 -5 -5 -5 -5 GO* 5x9 20, 101 4 , s .I6 46

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1-29 30.39 G*+

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229 119 50' I 3 I

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APPENDIX Cover type

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, 100-200 years) 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:

Douglas-fir Ponderasa pine Western white pine Firspruce Hemlock Larch Lodgepole pine

Management emphasis Moderate Intense Passive

public public private

(table number) I 8 15 2 9 16 3 10 i7 4 I I 18 5 I2 19 6 13 20 7 14 21

Intense private -

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 deter- mined 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 salvage- able. 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 avail- asie 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 148 148 Poletimber 33 1 248 Sawtimber 237 27

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.

Timber Volume

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.

CONCLUSIONS

The estimates of net value changes and changes in timber output are sensitive to the fire situation and stand classifica- tion 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 situation- specific estimates presented in the reference tables also eliminates the cost of the repetitive calculations needed to produce site-specific estimates.

YL.b ,.no*,: "olalln~,..~.lns'

1-29 ,o -w eo*

Z O I ~ T l s b r i : 1-23 3a-$9 60.

S."t,rnb*C> ,-29 111-19 so*

*do.. ll 111-1,s,: Il.dl*nS/.aPL*nS.

1-29 30.59 60-

Pol*t,sbmr> 1-29 30-59 60.

S.Sll"blC/ 1-29 ,0-3* '0.

LO" ,5o-a,,: Ilrdl,ng,..illln9i

1-29 ,O.% 60.

*o,*L,vBcr> .-29 30.59 60.

S."timb*c: 1-13 30-59 60.

"SCY 10" ,ZO..$>& r~s~ i lns / -p i 'ns :

1-29 30.39 60+

P ~ > O t , r n B ~ . ~ 1-29 30.59 6s.

*a"t,-bor: L.29 ,o-sa so*

h t l w I-, mun - dm, a l r l r *", - I-, 0 - , a ar. -, - - mum 0 5 dm.

. . . . . . . . . . - - 30-59 . . . . . . 60. .. -- -- EQLntZmbeL: . . . . . . . . . . . . ..%9 .... . . . . . . 10-59 - . . . . . . . . . . . . 6% sm"e,mher, . . . . . . . . . . . . A-29 . . . . . . . . . - - - 3s-59 . . . . . . GO* .. -- --

I0dlrnre , IJ- l is , : s~eaL*ns ,~e , ins:

3-29 0 0 0 o n * lD-I9 0 0 0 0 0 0 60, 0 0 0 a 0 0

Pe,cs'nber: ,-z9 n 0 0 o a o ,0-59 1'3 111 11) 111 ,.is 1,s so* 46s 12, 1'1 a,, 184 L2D

sa"t,ebsc: 1-!9 192 185 isi -101 -289 -1111 30.39 ' 5 '2, .21 -150 -,a0 -,,I 60. 684 6 62.1 46 33 33

m , ~ l l - B l , i s*r~i,"9/n.Llnsi 1-29 B 0 0 O B O >0-,9 0 * 0 0 0 0 10. 350 IIa I* 150 11, I S

sol*ll.b*j: ,-a* 0 0 0 0 0 0 30-59 B O O a 0 9 60. a , 11, 12 6.7 7 11

S."<lib.,/ 1-29 26 i s -I,( -se -9' 30.59 0 118 l l b -33 -3s -35 GO. 8 , 211 25' 48 I, , I

very LO" ,10-,,,> 6..dll"9 ,... .*n.i

,-a9 0 0 0 0 0 0 3m-59 D 0 0 * 0 60. 0 0 0 0 0 s

PDI.LI.b.Li 1-29 0 0 0 0 0 0 20-re 0 0 0 0 0 0 m* 8x9 is9 88 8 199 P I

3a"e,-b.r, ,-a9 1 B 4, .1 -82 -11 -75 l l i . lS I,, 1.1 i t , -3. -1 -35 60. 3x3 269 264 33 I? 36

%*lo ,es..s,r ..il.l*d ohm*om I" nrr tlrber *urpur * LII-Si iruc~ rkmds ""dSC pernira pr,r.t* nm.iien*o*. n ~ i i h r c n il*<XY Na""la,"r, by I I C . S3.C ma i t r r p.l,.d

SL."d .irau.rlrirYi F,rc 0,zs: 1-33 acrus i." t i / a E i V Y i l . I

/ rile G ' Z > ; im. ofand r,/e. ."d I .OI I . l l IY <Ianm I

*.me p*r.-a ,y<-cs,

(Pet, , - 2 3 . 9 5 - 9 9 0 - 0 . 0 I 0 - P I 23.4) 50.99 1110.200 0.2110

RESULTS

Specific cases for which timber net value and output changes were calculated were described by the following parameter classes:

Parameter Classes Timber management emphasis Moderate public

Intense public Passive private Intense private

Cover type Douglas-fir Ponderosa pine Western white pine Fir-spruce eml lock Larch Lodgepole pine

Productivity class High (120t cu ftlacrelyr) Moderate (85-1 19 cu ft/acre/yr) Low (50-84 cu ftlacrelyr) Very low (2049 ccu ft/acre/yr)

Stand size Seedling-sapling Poletimber Sawtimber

Mortality 1-29 percent 30-59 percent 601 percent

Fire size 1-99 acres lOO+ acres

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

'Estir~ates for 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, Cali- fornia 92507.

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

.- - m a , c m m x Y)C - c O

m a , 0 = - $ g-E 'UE 2 - 0 0 m 0 .= - ", _I a a

m m a 5 m 0) n 2 c 3 . E 1 n or

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, volumeandstock- ing per acre, treatment costs, and stumpage values.

0-B.): Illns/n.Pi'nsi .29 B 0 8.59 0 0 0 0 0 0

111 1 0 111 3 0

Po,et,mbsr> 1-29 5, 5, 50 Sl I 8 I , 3e-59 (10 95 93 11 14 1 3 60. 159 166 354 5'7 6 111

s."<,mbac: ,-29 81 s4 82 10 1 9 48 30.59 A , ,I, ,,I .I> '37 428 s** 86% s o am ara ssa s o

10" c20-49,, n * I) .a* o o a ,-59 0 0 Ll 0 0 0

110 1 0 130 1 I)

eo>ee,sber> L.29 '0 i s l a 38 I7 I6 30.11) S' 72 7, 6, 70 69 60- 169 138 11s 161 111 1211

8*"t,sb*c: 1-29 LO1 ID, 101 102 9s 96 so-53 268 161 >&I ibl 261 2 5 9 60. 0 830 808 i O l 5 129 OD?

'mt,w <-I a".. - 4, P L t L " e -"LO - 1-1 O - "0 "St ti.. -1 - nirvrlai mr luliynd.

.-a, . . . . . . 10-19 -. -. -- . . . . . . . . . . . . sw s."k,mb=r, . . . . . . . . . . . . 1-23 . . . . . . . . . . . . IO-IS . . . . . . . . . . . . 60.

Mdl..L* <Bl-,i9,; S..dll" .,.a .,,n.i

a-29 0 0 0 0 0 0 30.59 0 0 0 0 0 s 60. 117 2m 1.7 11, 201 1'1

. ~ > o ~ i ~ b c r > 1-%9 &I > I 29 61 39 1 9 30-%a 91 I 4 I0 S l I' 40 ro+ 7.1 (17 32s 101 AII 187

$owt,sbcr> 1-%a ,I 17 (1 -132 - 3 ->19 30.59 211 260 25' lli I I * Lao Gw 100 357 1.9 166 31 , lil

LO" ,so-a,,: s.rd,,"s,.~Llng:

, -I3 s s 0 0 0 0 30.59 0 0 n 0 0 0 60. ,a 1 0 IS L Ij

.o,s~,=b~r: 1-23 -1, -2, -11 -61 - 1 -3s ,0-59 -,, -6 -1 -6s -5, -,e &D+ 16. L16 i l l 16' 116 111

s ~ " ~ , m b n r : 1-29 1 0 1 2 I' .IS' -1.4 -1,s 30-59 111 111 111 i l 7 235 211 6- LO, I,, 326 3,. 30, ( 9 5

very 1s" ,20-,*,, reroilng,..pi,"ql 1-29 O O * a 0 0 ,o-s9 0 0 0 0 0 0 60. 18 1 0 18 I 0

eoL~<,mbnc> 1-29 .,, -1, .,I .,I - 4 - 4 4 ,*-59 -9 -1 -1 ->B -26 -35 60. 4 111 >I? lli 12) 1x7

s."t,~be,: ,-x* l, i s a0 9 -1111 -9s l o - l S 375 161 110 114 394 118 60. 6 , 60. 510 t l i 579 $65

lwnu. ,-, sl". - s"VD, salt,% mu. - 1-8 0 - m nar file -, - - *'Nltlai in Mu*.

"1.b l l i O . l i srodllns/..slms: . . . . . . . . . . . . . . . . .. *-29 -T - . . . . . . . . . .

30.59 .... - - - - . . . . . . . . . . . . . . . . . . . . 6- Fn,.%L.b.c: . . . . . . . . . . 1-%9 -. - - - -- . . . . . . . . . . . . . . . . . . ,o-59 - . . . . . . . . . . . . . . . . . . 8 - -

, . " n n A O l : . . . . . . . . . . . . . . . . . . ,-a9 - . . . . . . . . . . . . . . . . . . . . IO-IS . . . . . . . . . . . - - - .... ' w - VDdlr.fe Iml-llll,:

I..d,*ns/..L*nSi ,-29 O V I J O l l 0 0 0 0 ~ 30.59 B 0 0 0 0 0 0 0 0 0 6 w ~ 1 1 0 110 -160 46 1 -140 120 -Leo 46 I

eo.et,sb*r: 1-23 0 0 1 ) o o O O O L I O 30.59 O O O O D 0 0 0 0 0 6- 0 0 1) 0 0 1 1 0 0 1 1 1 )

s."<Lskac: 1-29 O O D D O 0 0 0 0 il ,0-39 0 0 0 0 0 0 0 0 0 0 6 w 0 0 0 0 0 0 0 0 0 0

Lo" 1111-8<11 I..a,ln./o.pllng:

.-,a 0 0 0 0 0 0 0 0 0 11

30.3, 0 0 0 0 0 o o o n o 6- 0 0 0 8 4 1 2 0 0 0 8 1 (2

s-,mt,iamr, I-2s 0 0 11 0 0 0 0 0 0 Ll ,lI->s o o o e D D ~ o ~ ~ 6- 0 0 111 2 1 4% O 0 , la i, ' I

8.WTl.b.l: L.29 0 0 0 11 0 0 0 0 0 0 30.53 0 0 ~ 0 0 l j D O L i 0 so. 0 0 ill 21 $2 0 I) 128 2, 0

*IS 101 (20-as,/ 5e.ailns/..*llnril

,-*9 o o l j o o D O O O * O O D O I I 0 0 0 11 0 ,*-59 so* Li D 0 I04 5% 0 0 s 10' 52

~oleflmh~r: I.*$ 0 ~ 0 0 0 0 0 11 0 0 30.59 0 0 11 11 0 0 0 0 0 0 60. 0 D 1 , 1 9 32 0 0 I,> IS 52

~a"timbc.> 1-29 0 I ) o o I I 0 11 0 0 0 ,O.% 0 0 0 1) 11 a - 0 0 0

60. I) 0 112 ,I/ I 2 0 0 111 39 11

lWir ,-, *nYIm .*hi p,llu. vax,eS - I-, O - "0 nal file -i - - .1tutLai "0+ luliypd.

.a. ........................ ..... 108--r*rrr.u.rd m.ns...m el*.. ....~....~.... ..n.gnmk. noieh-m wcxr ~ ~ ~ ~ . ~ . ~ ~ . w ..~..I.. m d 0.. mrloa

rrrna proavcrlvlqi T L r l d l i C i 1-93 osceo ) ).ire uLie: > o w ncc(a Ira Lr/acrUYr,. I ~ ~ . " d .**e. ."d I .... POZlOd I...... ............... ,PCI> , 0 - 4 5 - 9 9 - 0 0 - I 0.24 25-49 so-'l'l 100-100 0-100

C" te,acc*,ys.r' "Len I1I0.11

lo.allns,..Pllng: . . . . . . . . . . . . . . . . . . . . 1-29, . . . . . . . . . . . . . . . . . . . . 20.59 . . . . . . . . . . . . . . . . . . . . 6- S.LIT*.b.li . . . . . . . . . . . . . . . . . . . . 2-29

30.39 . . . . . . . . . . . . . . - - - - - sw . . . . . . . . . . . . . . . . . . . .

E."ll.bl., L.29 . . . . . . . . . . . . . . . . . . - . . . . . . . . . . . . . . . . . . . . 30-53 . . . . . . . . . . . . . . . . . . . . so*

"Dd.c.l* i l J - l l e , , I..ailns,..plm.l:

1-29 0 0 0 0 1 1 0 ~ 0 0 0 30.59 0 0 0 0 a D 0 0 0 0 6*+ s 1 0 , -101 D Q (I 10' -,a, 0 0

PoIIII.be.: L.23 -2s 0 0 0 -1 .?I 0 0 0 -1 30.59 .,I 0 0 0 -4 -16 11 0 0 -. 6% 4 4 I ) O I ' I O D I

S."LI.b.L, 1-29 0 0 0 0 0 0 0 0 a 0 30.59 0 0 0 0 ~ 0 0 0 0 0 6- O O O B O 0 0 0 I) 0

w ,I0.BOi I.ad,inq/..PilnS,

1-29 0 0 11 11 0 a 0 0 0 0 3s-59 0 0 0 0 0 O O O * O 6- 0 0 40 -23 -1 n I) .1/ -21 -1

sOl0rlmb~l: 1-29 0 D 0 0 a 0 0 D 0 0 ,0.%9 0 0 I1 L 1 0 0 0 9 1 1 0 c* 60 0 10 -11 I 6 0 10 -21 6

@."C,rnb*C> 1-29 1 ) 0 0 0 0 . 0 0 * 1 1 ,0->9 0 0 0 0 0 ~ L ) O l l l i & W 0 0 I D -2, -1 0 0 ' 0 -2, -1

VIIY ,el 110-as,: Ilcdllng/..Llnlli

1-x9 0 0 Ll 0 0 o o o o i l 30.5, 0 0 e 0 0 0 0 0 ~ 0 60. 0 0 i s -8 1 0 0 IS - I

s ~ i . a * i s i : 1-29 O O Y O O 0 D 0 0 L)

3B.W 0 0 0 0 0 ~ 0 0 0 0 6- 16 0 38 -I( >l 16 0 IS .B ,I

Q."njlb.r: 3 - 2 s 0 0 0 0 11 0 0 0 0 1)

$0.39 0 0 1 ) O O 0 0 0 ~ 0 60. 0 0 i s -a I 0 0 38 -e I

Iwt*. i-I - - -h, ei'ir "a- -I-, o - n. mr urn lsrtl - - .,urM d W .

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

-x/ocre-- Without lire

1,510 -

Yean since fire

First commercial thin

Final harvest Site preparitian Fint commercial

thin Final harvest

. . . . . . . . . . . .

0 n 0 0 0 0 0 0 0 0 0 0

I'' l i b 10, 1.4 *I* 10,

i e i i 9 ,A 2 , 16

18 1 2 3 34 2, ,&

I,, 1 5 1 12, ,?I I J i 121

t* 3s I, -118 -,52 - 2 4 s 6. $2 &I - , I0 -116 -111

112 110 101 182 111 267

0 0 0 0 0 0 0 0 a * o n

I l l 31 80 121 92 811

0 0 0 0 B 0 0 0 @ 0 0 0

I*, >a 10 ,>, 28 ,o

-1 -, -1 -1 -1 -1 -2 -2 -2 -2 -2 -2

19, 7, , I In9 48 a

0 0 a B O O

0 0 n 3 0 0

0 0 0 0 0 0

0 0 0 0 0 122 22 8 ,%> % I 8 125 22 8 1 2 3 22 8

-1 -1 -1 -1 -1 -1 9, ' -23 29 -57 -8.

IS> GO 30 1,s a. ,a

Harvest

.... 6W ..

*OdSC.f* ,Bl- , ls, : I.rdil.p,s.pllnp;

1-29 ,e-39 60.

PO,Ot,rnb.', >-29 >0-<9 6W

22

sa"t,*bec: 36

L.29 10.59 60.

LO" I ~ D - l . , : .D

I..~iins,n.pllns; 1-*9 ,*-s9 60.

POiltljn~,: 1-29 30.39 60.

xa"c,mb*c: 1-29 ,o-ss

-1s

60. -28

YezY 101 ( 2 0 - . 9 / , 12

~ ~ . d , l n ~ / . . ~ , n p : 1-23 ,*-59 GO*

Pe,rtl*or: 1-29 30.39 6W

so"<,mb*c, L.29 -8 30-59 $0-

,2 1:

14,508 - With fire - 251 1,510 --

Price

Interplant Fint commercial

thin Final harvest Site preparation Fint commercial

thin Final harvest

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)

Benefit

,,,*h ,,20.?: 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.

" *<orat@ ,a5-,,9,: r.railn.i/.rpllns:

,-z9 39-59 6".

*o:ec,mb"z: . -29 ,0.5$ $ 0 .

,a"t.mb",, > - a * ,".9* 6D. """ (50 -84 , :

.nli"g,..Pll"g: 3-39 30.59 60.

D",er,mber: > - 2 g ,n-% 6". ......... ,-:* , * - 5 9 ....

) ill" ,2O-*l/: .~<a,,"q,oae,'"9:

-19

Cost

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

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)

ofsite preparation required wlth an assoc~ated cost 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

Repetition cycle

Years since fire

large fire size led to increases in the salvage price and reduc- tions 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.

Dcscriptian

Harvest Price

40 42 55

125

7 20

90

I00 cufflacre XI100 cuff -X/ocre-- Years Without lire

49 105 5,194 -- 0 Final harvest - -- -- 1.24 85 Plant -- -- -- 129 85 Precommereial

thin 57 134 7,638 -- 85 Final harvest

With lire -- -- - 88 85 Plant - -- -- 50 85 Precommercial

thin 57 134 7,638 -- 85 Final harvat

Benefit Cost Repetition

cycle Description

t W t , " - l i m l r a a ~ n l

S i ! L p ~ ~ " l i o n

L1d,YIM@"t mnzanionn and '"d pl'"li".mnl

~ I D l , / r n . , O , adl"nlm"nl

*ia,on criteria

& ID 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 regres- sion 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 man- ageable 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

net value change was then estimated using the SASSY financial return computer program (Goforth and Mills 1975).

EXAMPLES OF ANALYSIS CASES

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 behav- ior 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 the 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

~oi;t,mae.: . . . . . . 1-29 . . . . . . . . . . .- .- .. . . . . . . . . . . .. -- L. . . . . - - eo. 30.59 . . . - . . . . . . . - 60. . . . . . . . . . . . . . . . . . . . . Fo,at,"b"r*

1-!9 . . . . . . . . . . Za"GimDmr, . . . . . . - - - - . . . - . . . . . . - - ,o-s* . . . . . . . . . . . . . . . . . . . . 1-29 . . . . . . . . . . . . 60. 30.59 . . . . . . Go+ .- -- .. . . . . . . . . . . . . . . . . . . . . S a W t i m b ~ r :

1-%9 . . . . . . . . . . . . . . . . . . . . >0-3* . . . . . . . . . . . . . . . . . . . . IMIat,* I., WOW - sYv, miti* d m - . I-, O - "0 Mf *LC. IDM, - - &o+

slurla ial -lad. at-rim h e , * n.r -lad. ,.I "",-. wh, p , * , V . v a - - 1-2 O .".ML *LC. -i --

Tab>. z,l--?,.rr."oed clmngc* I" ncr "0l"S .I r..r.m "hit. st". .*and. ........................................................... n b l c its--Plrr..u..d rh.ns.. L" n.r r,;ari ouepur at "..l.." ""'>o .t."d. n'ir and dl.ra"nt rat- Inrsnre *r<uilrm iianlgm."i. nril"rin l a c 9 *eunta,nn, by (Ir* .he a"d l.* pr.l.d ...". .rodu.r,*,~ .......................................................................... , ,,rs dZe: LOO* .er*n " " 0 , I 0 " , , , I .L..d .,XI. O l d I D%sco~,"e CF*, l i e . ."a I 7,ms m,*oa CY**CS,

t*i,e ..............I ... .....I <PCLJ I 4.0 7.875 ,010 I 4-11 1.875 i s . 0 (SCL) , 0 - 2 5 - 0 . 9 - 2 - 0 1 0-24 I%..') 50-99 LOO-IOO 0-IDD

191s doilacm/&ole bulnrd'

183 617 'Bii 786 611 7 611 4 783 ax7 488

1617 a,. I<# i5Gl i 160 4 7 9

2,. 226 221 -299 -28, -111 ' 3 7 'bl 10 *& 10

>ill i n 9 1 8 5 2 l O l D I B > i 1766

6 64 6 1 - > m i -110 -261 177 lii l b l -Its -116 -1,o ID08 116 716 848 611 618

0 0 0 0 0 0 0 0 0 - 0

4.1 129 1% 4 , 119 l l 9

119 101 8 9 x.9 0 , a9 0,s 525 118 692 'I), 239

,486 ,002 8 9 ,419 9.6 11'

I. I 3 I, -1,s -114 -112 B I 85 0, - 4 -4, .I,

675 48s 4 5 4 I B D 4 376

0 0 0 0 0 0 0 0 0 0 0 0

112 1 2 7 87 322 117 I,

I l l 5 2 , 590 isa 17, 528 231 , i s 6.1 402 281 l,, ,,a ><o

I 0 .B 4, -116 - u s -110 116 IS, is, 20 I0 I I I,' 61% I.), I S , 5 , $28

. . . . . . . . . . - - .. -- .. . . . . . . . . . - - . . . . . . .

.. -- -. . . . . . - . . . - - . . . . . . .

. . . . - . .. -. -- .. 5."t,Shr: . . . . . . . . . . . . . . . . . . . . . . . . - . . . . . . . s."k.u~~r: 1-23 1-29 . . . . . . . . . . . . . . . . . . . . . . . . . . ,s-s9 . . . . - . 30-59 . . . . . . . . . . . . . . . . . . . . . . . . . . 60. .- -- .. so+

I,+kiv. i-1 rnivn - sVn pi t , - durn - I-: O - n. "r( fir. IDM, - - 't*.~l- ,-, n(u- - sirn, Felt<* "03,- - i-, 0 - n. rrr Ell.. Ygrt! - - r,rwtlm n.+ -lira. 'lula s t -w.

ill.lh ,110.,1 II.Li'ns,n.silnp:

1-29 30.39 60.

Po,.LL.beLI 1-29 30.59 c *

s."t'mAo.: ,-a9 10-19 60.

w&cae< ,85-.,9,: Irrdllng/..Cln.i

1-29 30.59 6W

?s,*t*sb*c: I.29 10-11. so*

s."LL"b.LI 1-29 30.5, 60.

LO" IIO-S,,: s..dlln./..pLln.>

1-19 ,0-53 60.

*s,ari.nrr: ,-*a ,%*,

6 a 8."t,rnb*C> 1-29 30.59 6-

VSC)I LO" ,10-,s,, s.roLin./a.~lln.i 1->$ 3s-59 sa

Ps*.t,nb*c: r 2 s 3a-59 GO*

3."e*mb.r, >-29 ,a-59 co*

d.il.m,.rir burned'

It, 5 I,' 1<1 x,, A I B ,I, 2.7 2,s '10 327 P I 0

111 ,?I 14, 122 as1 2 141 1 0 1 89s Ills $ # I 812

16 -19, -11(0 -111 260 12 I, ,I 16, 5.8 '81 469

0 0 0 ,110 1'11 16. *a0 100 is, 6 ' LOO

-3 -1 -I -1 -5 -6 -1 -I

,sll ,,D> ,I' 1.1)

7 - .I06 -102 1, -88 -72 -6s

111 216 260 111

0 @ 0 8 0 0

179 450 7 17s

I, I,< 7, I, n IS$ I_ 31

I * , 111 101 180

75 -2 1 2 1x3 36 48 ' 9 111 219 *I1 209

.. . . . . . . .. . . . . . . .. . . . . . .

.- . . . . - - .. . . . . . .

.. . . . - - -

.. . . . . . .

..

.. .. -- -- . . . . . .

WlS" , 1 1 0 * , / sced,'"q,-P,,"q:

1-29 ,o-s*

12

6W no,*t,*b*ra

-32

3-29 -12 30.59 &W

-2, >a

sa"t'.b*c: ,-s 3s-59 6a

"Od*C.<C ,81-L11,1 Ir~dl,"g/..#lns:

2-29 30.39 la

FoLet,.b*c. P

,->9 30-59

-,a 6a

-56 -,do

3.rl'vir.l 2-29 30.59 6a

LO" ,~0.11,,> 81.dllns,s.p,ms:

2-29 ,a-39 so* -104

P*,st,ab*c> 1-29 -3s 3*-5% 6%

-6.

s."e*mb*c> 36

1-29 30.59 $0.

mcr 10" 110-491: S*~dllng/..pllnrj, 1-29 .. 30.59 .. GO. ..

s-leilvinl: >-29 .. 30.59 .. su ..

Table I-seleered DougIo5-Jir monosernen! regime ondyield cl~omelerisrics

Management emphasis, productivity Class, and rotation

Year of

Moderate public Low



Intense public LOW Existing Regcnerated


Passive private LOW


Moderate Existing Regenerated

Intense private LOW



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. Pro- jected 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 1975 through 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

PNV of infinite series PNV of infinite series PNV,,, = final harvests in - management costs in +

regenerated stand regenerated stand

PNV of harvests in - PNV of management existing stand 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 sal- PNV of management vaged following fire - cost in existing stand +

PNV of residual PNV of any single timber remaining - rotation difference in after fire 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 des- pite 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.

Timber output change is thedifference between thescheduled timber yield without fire and with fire.

Scope of Analysis

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 com- plexity 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.

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 without- fire harvest area. Sample data for fire situations in Douglas- fir 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 philo- sophy affects the regime. The rotation approximates or pre- ce'des the culmination of mean annual increment. There is a

1.m- 2,r-?,cr<~"lrd rh&"gon in *f ,arm ntan0. ""dl/ tncmnc prlr.Le ..nqc;m(, nolrhoin l D I k Y * .Y" l l *"T . bZ LLI. z,D--,I..-<."S.d tD."..s 3" ".f n*.. . Y L P Y I .I i l f t b . n o d . ""de. 'I*. and d<SOO""< 'at- inrmre Pilvnr* a.niino.*nr, "CC<h.rn n 0 . q n.untr*no, by Pi.. el.. and r,.r ..,,so

B19h 112a.1, r~~a,'n9,~api,n~, L.2, 30.59

52 -36

6% Po,rtlibrii

-92

,-29 20.59 6-

S & " t ' ~ b * ~ > 1-29 30.59 60.

nod*l* le Il l- , Is,: rr.dlmi/r.plmg:

k.29 30.53 co*

eo,ct,mbcr: ,-29 J0.39

, -1s -20

60. s . " t , ~ b ~ r ~

28

L.29 3B.5, GO*

-1 ,511-80: S . . d l l n g / ~ p l l n 9 :

1-23 30-$9 60.

D*,ekimber: ,-29 -2. 30.59 -32 60. 56

z8"k,mb*c: 1-29 30.59 60.

"IL7 I." ,ID..P,> s>n*,,n*,sap,,n9:

1-29 .. 10-$9 .. c o * ..

Po.*t%mber, 1-29 .. .".,O ..

"lsh , , lo . , : Irrdllng,.rpi'ng:

L.29 ,*-59 sv.

Fe,ct,mba.: 1-29 ..G I*-59 GO.

64

sa"t%mb"c: 6'

L.2, 30.59 6-

" 0 b ~ L . n I M I - i i P , : Seedi lng,~.*lng,

1-29 ,0-5, m.

>D,sri_",, ,-29 ,O.SP ->a 60.

sa"c,*b*c: 36

L.2, 30.59 60.

LO" ,50-80,: S*edlln9/..pLln9:

1-29 30.59 6-

e-Lcc,-ber: 1-29 20.59 84 ea

s&"t,abec, 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 ..

601 Sawtimber

1-29 30-59 601

'Table 29-Fuclomfor lezr-oohd e.~ri,~,orer. it,lzo,

M$magement empl,arir. sire, mortalityciass(pct)

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

Intense private Secdling/sapling

1-29 30-59 601

Poletimber 1-29

30-59 601

Sawtimber 1-29

30-59 60+

o~l l~ , .~ l i , z~ ruoclelcd ,,<>I ,rolcrr rhange esli,?~ore.s 10

root/<,</ ,,nlr,e is ,zexoli!,r

Sawtimbcr 1-29

Table 30-Faoorsfor adjuslmq roodcd ,,el ~ralur d,o,,fic c.s~i,r,ale.~ 10

~otroaded rsri,r,arm when rooded vol~re is posilive

Fire sire: 1-99 acres

Discount rate @ct)

30-59 601

Intense public Scedlingjsapling

1-29 30-59 601

Polctimbcr 1-29

30-59 6O+

Sawtimber 1-29

30-59 60+

- - - - - - - - - - .- - - - - - .. -

0 0 0 0 0 0 0 0.86 0.90 0.28 0.55 0.58 1.00 1.00 .99 1.00 1.00 1.00

.94 .95 .95 .77 .78 .79

.92 .84 .87 .49 .63 .67 - 1.00 1.00 .42 .62 .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 .94 .63 .79 .80 0 .88 .91 .24 .73 .77 - 1.00 1.00 - .SO .71

.95 .92 .94 .79 .85 .87 0 .63 .79 .51 .48 .54 - 1.00 1.00 1.00 .38 .50

0 0 0 0 0 0 - 0 0 .95 - -

1.00 - - 1.00 - -

Firc sire: lOO+ acres

Discount rate (PC[)

4.0

60, Sawtimbcr

Management stand si;re,

martvlity class (pct) 4.0

1-29 30-59 601

Intense private

Fire rirc: lOO+ acrcs-

Discount rate (pct)

7.875

30-59 601

Poletimber 1-29

30-59 601

Sawtimber

Modcratc public Scedlingjsapling

1-29 30-59 60,

Poletimbcr 1-29

7.875

Firc sire: 1-99 acres

Discount rate (pct)

4.0 10.0 INTRODUCTION

1.00 1.00 0 1.00 1.00 0 1.02 1.03 1.04 1.02 1.03 1.04 1.03 1.05 1.06 1.03 1.06 1.02

1.01 1.03 1.03 1.07 1.02 1.03

10.0 4.0

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 substan- tial 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 sim- ple 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 morecompleteformula- tioris 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 circum- stances. 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

7.875 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 Eval- uation 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.

7.875 10.0

METHODS

10.0

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 fire jaused change was necessary to avoid major errors in the estimate (Mills.and Flowers 1983).

The computational model used in the present study con- tains 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 IN BRIEF.. .

Florvers, Patrick J.; Shinkle, Patricia B.; Cain, Daria A.; Mills, Thomas J. ~ i m h e r net value and physical output changes following wildfire in the northern Rocky Moun- tains: estimates for specific fire situations. Res. Paper PSW-1719. Berkeley, CA: Pacific Southwest Forest and Range Experiment Station, Forest Service, U.S. Depart- ment 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 nonsite- specific 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.

REFERENCES

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 man- agcmcnt 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. Depart- ment 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 Metcorolagi- cal 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. Wush- ington. 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 Sta- tion, 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 Manage- ment Staffl. Washington. DC: 1980. 29 p.

U.S. Dcpartment of Agriculture, Forest Service. FSM 5 130.3-Firesuppres- sion policy. Washington. DC: 1981.

U.S. Department of Agriculture. Forest Service. FSH 5109.19-Fire msn- agement 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 and-~ange Experiment 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

................................................ In Brief ii

............................................. Introduction 1

Methods ................................................ 1

............................ Calculating Net Value Change 1

ScopeofAnalysis ....................................... 2

SourcesofData ........................................ 2

Examples of Analysis Cases ................................ 4

Results ................................................. 7

T~mber Net Value ...................................... 7

Timber Volume ........................................ 8

Conclusions ............................................. 8

............................................... Appendix 9

References ............................................... 25

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 Protection andmanagement of resources on 191 million acresof NationalForest System lands. 8 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. 0 Participation with other agencies in human resource and community assistance programs to

improve living conditions in mrai areas. 8 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~eei t ic tire 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 to calculating estimates for specific sites or to 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

Documents

ISBMqInOS 3!4!3l?d laded qsleasatl - US Forest ServiceThe Forest Service has responded by conducting several stu- dies analyzing the economic efficiency of its fire management program