United States 

Depart rnent of 

Agriculture 

Forest Service 

ma1 Level o 

Expenditure to Control the 

Southern Pine Beetle 

Southeastern Forest 

Experiment Station J.E. de Steiguer 

Research Paper Roy L. Hedden 

SE-263 John M. Pye 
Optimal Level of Expenditure 

to Control the Southern Pine Beetle 

J. E. de Steiguer 

Project Leader 

Southeastern Forest Experiment Station 

Research Triangle Park, North Carolina 

Roy L. Hedden 

Professor of Entomology 

Clemson University 

Clemson, South Carolina 

John M. Pye 

Ecologist 

Southeastern Forest Experiment Station 

Research Triangle Park, North Carolina 
ABSTRACT 

The optimal level of expenditure to control 

damage to commercial timber stands by the southern 

pine beetle (SPB) was determined by models that sirnulated and analyzed SPE attacks during a typical season 

for It Southern States, The optimal level was defined 

as that which maximized the dollar value sf timber 

saved mf nus the cost of control (4 ,e,, maximized net 

benefits), Real discount rates of 4 and I@ percent were used, At 4 percent, maximized net benefits for 

the entire Southern region are estimated at about $50 

million, or a benefid/cosl ratio of 6,22; at 10 percent, more than $30 million, or a benefid/cost ratio 

of 5-93, Alabama, North Carolina, and Texas warrant 

the largest control programs; Georgia, Louisiana, 

South Carolina, and Mississippi, moderate programs, 

Virginia, Tennessee, Arkansas, and Oklahoma justify 

small control programs, Methods and costs for betecLJon, evaluation, and suppression of SPB Znfeslations are di scusseb, 

Keywords: Dendroctsnus frontalis, CLEMBEETLE, 

OVERFLIGHT, BEAM, cut and leave, cut and salvage, 

This study was conducted to assist 

State & Private Forestry and various 

State forestry agencies in the planning 

and implementation of more efficient 

southern pine beetle (SPB) control activities, The purpose was to deternine the 

most econsmi cal ly efficient (optimum) 

level of expenditure to control SPB 

ddmaye to commercial timber stands in 

Alabama, Arkansas, Geory i a, Loui si and, 

Mi ssi ssi ppi , North Card i na, Okl ahorna, 

South Cars1 i na, Tennessee, Texas, and 

Virginia. The basic geographic units of 

analysis were %6,141 Forest Inventow 

and Analysis (FIA) survey plots Icacated 

within the study area, Each plot represented about 4,500 acres of a particular 

forest standlsite condition, These survey data were obtained from both the 

Southeastern and the Southern Forest 

Experiment Stations, The Pi nat results 

of the economic analysis were summarized 

and reported by State and by the 

following land ownership classes: 

Federal , State, forest industry, and 

nonindustrial private (NIPF) . The three major components of the 

analytical system used were the 

CLEMBEETLE stochastic simul atisn model , the Beetle Economic Aaalysi s Mode7 

(BEAM), and the OVERFLIGHT simul at ion 

model, CLEMBEETLE is written in IBMFORTRAN 77 and was developed by Roy 

Hedden, BEAM is programmed within the 

Stdtistical Analysis System (SAS) to run 

on dn XBM computer; OVERFLIGHT is written in BASIC to run on an Apple IIe 

microco~nputer. The latter two programs 

were developed by 3,E, de Steiguer, 

Using FIA survey plot data, 

CLEMBEETLE simulated SPB infestdtions 

and the volume oh timber lost to SPB for 

a single day of infestation growth, The 

OVERFLIGHT model cal cul ated the total 

number sf days that SPB infestations 

would yrcw during the course of' a single 

SPB season if (I) no betecdion takes 

place (i .em, without control) and (2) 

various levels sf detection are undertaken (Lee, with control), Within 

BEAH, the sirnul ations generated by 

CLEMBEETLE and OVERFLIGHT were combined 

with data from the State forestry pest 

control officers and other sources cancerning control pkactices and costs, 

salvage rates, and stumpage prices to 

obtain estimates of the benefits and 

costs at the various levels sf control, 

REAM selected the optimum level of 

control for each survey plot, and these 

optima were summed and classified 

according Lo %ate and ownership class, 

The o~timum level of control was defined 

as that lr~hich maximized "che value of 

timber saved less the cost of saving the 

timber, 

Procedures 

Economi c Model 

TDe optimal level of SPB mntrul 

was defined as that which maximized net 

benefits, Net benefits were defined as 

the present value of timber losses 

averted due to control minus the cost of 

control. The analysis simulated SPB 

darnaye that could be expected with and 

without control duriny a single year, 

given a typical level of SPB population. 

This typical level of SPB population was 

based on average beetle populations over 

the past 10 years, 
The basic geographic units of analysis were 16,141 FZA survey plots, each 

of which represented about 4,500 acres 

of a particular forest standfsite condition, Each plot was treated as an 

i ndependent forest management unit , 

Plots could he aggregated to mu1 ticounty 

areas called Survey Units, and Survey 

Units could be aggregated ts State 

levels, The forest owners were assumed 

to be prof i t-maximi zi ng producers of 

pulpwood and sawtimber who did not consider the amenity values of the forest 

when making pest management decjsions, 

Atonistie competition was assumed so 

that the actions of any single producer 

woul d not infl uence market output or 

prices, Al so, forest managers were 

assumed to have perfect knowledge 

regarding future timber markets, prices, 

and the consequences of theiP pest management strategies, 

Tirtlber losses due to SPB were 

treated as small, isolated openings in 

the existing forest stand which had no 

effect on future stand rotation schedule or on annual management costs associated with the current stand, Furthermore, timber losses were not compensated 

by increased growth in the residual 

stand, All pest management costs were 

treated as vari ahle, 

With these qualificalions and 

assumptions, it is now possihle ta 

derive a general sol~ltion for the optimal level of SPR control expenditure. 

The general solution wi 11 then serve as 

a hasi s for presenting the REAP1 model, 

First, consider a forest stand (FIA slrrvey plot) which is ctrrrently "nu years 

of age and is attacked by SPB, If no 

action is taken to control davage, the 

okdQer expects to lose a volune of tinher 

equal to Q,. This volume (0,) represents the total amount of timber which 

will be lost to SPB, and consists of the 

currently standing volume plus the 

growth %ha& would have been added by the 

anticipated year of harvest (Tf, The 

present value of losses without control 

(Lo) is: 

where: 

P = stumpage price at harvest 

i = discount rate 

If, instead, same type of SPB 

contra1 is elected, the owner will lose 

some lesser volume of wood (Ow), hut 

will also incur a control cost (C), The 

value of losses with control (L,) may he 

written as follows: 

The net benefits (NR) of control 

are fo~ind by dedllctirlg equation (2) from 

eqi~ation (1) with the following result: 

The forest owner will undertake SPB 

control as long as the net benefits of 

control are positive, 10 other words, 

control is desirable if the present 

valve of timber losses averted (benefits) 

exceed the cost of control, However, 

the problem facing the landowner may be 

more complex than simply deciding between the options of control VS, no 

control. Instead, the owner may have to 

choose the most appropriate level of 

control. If we assume that by expending 

more control dollars more timber can be 

saved, and that C = f(O,), then it is 

possible to derive a theoretical solution for the optimal level of SPB 

control. If equation (3) is continuous 

and differentiable, and its shape is 

concave, fi rst increasing with oi~tput 

and then decreasing, the maxinc~m 

(optimal) level of net benefits is fotrnd 

where the first derivative of NR with 

respect to 0, is eqt~al to zero. Thus, 

from eqtration (3) the optimal sollltion 

i s: 

Equation (4) can be rearranged to 

demonstrate that at optimum, marginal 

benefits will equal marginal costs: 

The foregoing general solution to 

the problc.13 of optimal SPB contrd 
served as the kasis for the WE414 model, 

However, for REAF?, the bass"& modemwas 

substantial ly expanded to include factors such as salvage valtjes and the 

various components of control cost, 

Also, the optimal solutions were derived 

through iterative simulations because 

the damage and control production f~rncLions could nod be expessed in conti nuous Forq, 

"T understand REAFG it fs necessary 

to understand the steps involved in the 

control of SPR outbreaks, SPR control 

consists of three steps: (1) dPtectioo, 

(2) evaluation, and (3) suppression. 

Detection is typically conducted from 

aircraft, In the jargon of SPB control, 

such detection activities are referred 

to as "pres~lppression fl i ghts ." Once 

infestations have keen detected they 

must then be evaluated, Evaluation is 

the on--themground inspect.ion of each 

infestation to deternine its exd~nt. and 

csndi t i on, Eva1 rjati on may be fol 1 ~wsd 

by stappression, which is the step where 

action is taken to halt the spread of 

the infestation, The most common 

current methods of suppression, 

according to State forest pest control 

officers, are cut and salvage, and cut 

and leave, Both techniques involve 

cutting a buffer strip aroi~nd the 

advancing head of the infestation, With 

the former method, the cut timher is 

salvage for sale, whereas with the 

latter, the timher is simply left on the 

ground, Detect ion and eval uat ion 

requir2 cash outlays, hence are referred 

to as direct costs in this stlrdy, Suppression involves both di rect and indirect costs, Direct costs are those 

for tree felling in the case of the cutand4 eave method, hdi rect costs result 

from harvesting the Financially immature 

timher that OCCIJ~~ PS the hilffer strip, 

The intensity of control was determi ned by the frequency of pr~st~ppressi nn 

flights. tdith increasing nrrmbers of 

detect ion fl ighls, timher losser were 

rarlirced because infestation5 had fewer 

days to spread before eval l~at i n~ and 

suppression Look pl ace, This concept 

will be discussed later in gre8ter 

detail, Here, however, it is important 

do realize that the intensity of control 

or the lack of condro1 was ref1ec"cerl in 

the number of days an infestation w6s 

allowed to spread, Trs REAIPI, it was 

assumed that a7 7 infestations, oncedetected, were evaluated and suppressed, 

and that all suppression activiTies were 

conpetely effective in stopping the 

spread of infestations, 

From CLEPBBEETLE , REAP4 ohtai necf 

sinul ated estimates of the vol ume of 

timber that woultd be lost to SPR per day 

of infestdion growth, per acre of 

forest type, These CLEMBEETLE estimates 

may be expressed as V+G, where V is the 

volume of currently sda~ding timber last 

and G 7's the growth "cad wo~nld have 

occurred had the stand reached some 

assumed rotation age, For the withoutcontrol sf tuation (Lo) , the present 

val ue of timber l ost , 1 ess salvage 

value, was calculated as follows: 

where: 

Do = days of infestation growth 

without control 

P = current timber stumpage prices 

r = annual real rate of stumpage 

price increase 

i = real discount rate 

T = assumed rotation age 

n = current stand age 

a = fraction of dead timber 

sal vaged 

b = dead timber price as a fraction of green timber price 

A = total acres of forest type 

W = fraction of Survey Unit in SPR 

outbreak condition 

For the with-control si trrations 

(L,) , the present val ue of timher lost, 

less salvage value plus control costs, 

was calculated as follows: 
where : 

Dk = days of infestation growth 

with various 1 eve1 s of control 

F = direct cost of presuppressi~n 

fl l"gkts 

E = direct cost sf evaluation 

fn - direct cost of suppression 

SH = indirect cost of suppression 

The values of the various control 

cost el ements were cal cut ated as 

f ol 1 ows : 

F = number of flights 

x cost per acre of Plying 

x total (8) 

E = number of infestations 

x fraction of infestations 

control led 

x cost of visiting an 

i nfestation (9) 

SD = buffer strip size (acres) 

x fraction of acres subject 

to cut-and-l eave tree 

fell ing 

x cost per acre of tree 

fell ing (10) 

SE = buffer strip size (acres) 

x present val uelacre of buffer 

strip timber 

- current salvage value of 

buffer strip timber (11) 

The net benefits (MB) of control 

were c a l c u l ated by subtraeLi ng equation 

(7) from equation (6). The result, 

which represents the present value of 

losses averted minus the change in 

salvage value minus the cost of control , .is: 

In the analysis, eight presuppression flights were simulated for 

each FZA survey plot, This, in turn, 

generated eight values for the variahl e 

Ow. The value of equation (12) was 

cal cu9 ated ei ght separate times, once 

for each value of Ow. From these eight 

optional level s of control , the one that 

yielded the maximum net benefits was 

selected as the optimum, provided that 

this maximum value was positive. Figure 

1 illustrates the benefits and costs for 

a typical FIA survey plot, The optimal 

solutions for %he individual plots wre 

sumaed for the States by Forest ownership classes, 

VOLUME OF TIMBER LOSSES AVERTED 

Figure 1,--Benefits and costs of SPB 

control, Optimal volume of timber saved 

from the hede (Qf is Found where net 

benefits are maximized (MR), This is 

the point of greatest distance between 

total benefits (8) and total costs (C). 

Following is a description of the 

data used in the study, Real discount 

rates of 4 and 10 percent were used do 

provide a sensitivity analysis, The 

real annual rates of stumpage price 

increase for pulpwood and sawtimber 

were, respect ivei y , 1 and 2,5 percent, 

The casts per acre sf detection flights 
and cut-and-1 eave land cf ear3 ng were, 

respectively, 2 cents and $500, provided 

by State & Private Forestry (S&PF) personnel, The stand rotation ages, 

obtained from State forestry pest 

control officers, were 60 years for 

Federal forest lands, 45 for State-owned 

1 ands, 35 For forest industry Sands, and 

45 for NIPF lands, The current stand 

ages and the total acres of forest type 

were obtained from FIX data, The Fraction of the Survey Units in an SPB 

outbreak condition (fig. 2) represents 

the portion of the area, based on data 

for the past 10 years, which has had SPB 

The remaining data used in the 

study are shown in table 1. These 

i ncl ude stumpage prices, salvage rates, 

dead timber price fractions, fraction of 

buffer strip to which cut and leave was 

applied, and the cost of evaf uating 

infestations, Stumpaqe prices were 

obtain@d from Timber Mart--5out4, fnc,, 

and represented average prices far the 

past 10 years stated in constant 1984 

do1 lars. Salvage rates were assirmed to 

be 50 percent Psr the without-control 

situation based on the advice of S&PF 

personnel, 

Survey 

Unit 

Figure 2.--Yap of Survey Units in the States surveyed, and the fractions 

of these Si~rvey Units in outhreak condition during the last 10 years. 
Table 1.--Stumpage prices, timber salvage rates, and control costs, by State 

Sawtimber Pulpwood Fraction of Fraction of Fraction Fraction Cost of 

priies prices dead timber green price of infes- of infes- evaluating 

per fbm, per cord, salvaged for dead tation cut tation cut infesStaW 11984 I r3R4 timber Rsalvaged R left tations 

. . . Dollars . . . 

Table 2,--New SPR infestation occurrence 

as a percentage of total annual new 

infestations, by month and region Days of Infestation Growth --- -- 

Piedmont I& 

Month Gul fa ~ountai n" 

. . . Percent . . . January 0 0 

February 2 0 

March 3 1 

Apri l 13 1 

Hay 14 10 

June 17 17 

July 25 20 

August 13 25 

September 7 17 

October 3 6 

November 3 3 

December 0 0 

Annual tstal 100 100 - 

aAl abama , Arkansas, Loui si ana, 

Mississippi, Oklahoma, Texas, 

'6eorgia, North Carol ina, South 

Carol i na , Tennessee, Vi rgi ni a, 

Within the BEAM model, the intensity of SPB control or lack of control 

was determined by the frequency of presuppression fl ights, which were simulated during the SPB season, The total 

number of days that an infestation was 

allowed to grow, and thus the volume of 

timber lost, decreased as the number of 

detection flights increased. The number 

of days of infestation growth was calcu1 ated by the OVERFLIGHT model , 

The OVERFLIGHT model used data 

obtained from State forestry pest 

control personnel concerning the ref ative Frequency of,new infestation 

occurrence, by region and month, during 

a typical SPR* seqson (table 2). The 

average number of days of infestation 

growth for the without-control situation 

was calculated by multiplying the monthly 

relative Prequen~y of new infestation 

occurrence by the number of days remaining in the SPB season, These products 

were summed $0 obtain the weighted 

average number OF days of growth for an 

infestation, Far each of the eight 

1 eve1 s of p~esuppression fl ights, the 
flights were placed within the season to 

minimize the number of days of infesdae 

tjon growth, The monthly relative frequencies were multiplied by the number 

of days before the next presuppression 

PI ight would oecrir, and summed for the 

season, Also, an additional 30 days was 

allowed in the calculations to account 

for a lag between detection and 

suppression, The resulting average 

nrrmher of days of infestation growth for 

the without-contml and the eight withcontrol situat i ans are presented , by 

region, in table 3, 

Table 3.--Average days of growth for SPB 

infestations assuming various numbers of 

presuppression flights per season and 

allowing 30 days between detection and 

suppression implementation, by region 

No, of' Pfednrond R 

f'I ights Gulf a ~ountm in" 

"A1 abama, Arkansas, Esui siana, 

Mississippi, Oklahoma, Texas, 

b~eorgia, North Carol ina, South 

Carolina, Tennessee, Virginia, 

Simulation sf Volume Loss 

Voluine loss due do SPB attack was 

generated by using a modification of the 

CLEMBEETLE program. 1 92 Vol ume loss consifted of trees aetually killed by SPB 

as well as growth loss due to premature 

death of the tree, Rased on average 

beetle populations from 1971 to 1980, 

losses were generated for three population Ievek by the number of spots per 

1,000 acres of pi ne and pi ne-hardwood : 

low--0,s spots, moderate--2,O spots, 

high--5,O spots, For each population 

level, the s-r"rnulation of loss consisted 

of the following steps: 

I, Cal crrl ate the probahi 1 i ty of an 

infestation occurring per acre 

(PR09), 

2, Generate the number sf active 

trees (AT')* 

3, Calculate the probability of a 

spot being inactive at detection (PROBI), 

4, Test to see if the spot is 

inactive, 

5, if the spot is inactive at 

y round check, cal cul ate the 

number of dead trees (DEBDU, 

6, If the spot is active, calculate the number sf trees killed 

per day (TKD), 

7, Calculate the number of trees 

killed in an active spot: 

DEADA = (PKD x DAYS) + A%, 

8, Calculdte the expected number 

of trees killed (ELOSS): 

a, Inactive spots: 

ELOSS = PROB x DEAnI, and 

h, Active spots: 

ELOSS = PROR x DEADA, 

These steps were repeated 15Q times 

for each FIA survey plot that contained 

forest types susceptible to SPR attack, 

The sum of the ELOSSk was divided by 

150 to obtain the average expected 

number sf trees killed, 

'~edden, R,L, Impact sub-models far a southern plne 

beetle pest management program--Phase I, Unpublished 

progress report do the USOA Forest Service, IPM 

Program For Bark Beetles of Southern Pfnes, New 

Orleans, LA, 1982, 40 pp, 

'~edden, R-1, Impact sub-models far a southern pine 

beetle pest management program--Phase I, Unpublished 

final report to the USDA Forest Service, IPM Program 

for Bark Beetles of Southern Pines, New Orleans, LA, 

1983, 31 pp, 
Separate model s for probabi l ity of 

infestation were used for the Mountain, 

Piedmont , and Coastal Pl ai n regions, 

Models compatible with HA survey data 

were developed for each region from site 

and stand data eol lected during the 

expanded Southern Pi ng Research and 

Appl ications Program. In each region 

the probability of infestation varies by 

forest type and the SPB population 

level, Other variables used were: 

Mountai n Piedmont Coastal Plain 

1) Proportion 1) Slope 1) Land form 

of pine (slope) 

2) Site 2) Basa7 area 

i ndex per acre 

3) Stand 3) Proportion 

origin of pine 

4) Age 

The number of active trees was a 

function of the number sf trees per acre 

(IPA), with dense stands having a 

greater number of active trees than did 

less dense stands, Active trees were 

generated from an exponent i al di st ri bution with an expected value of 0,15 x 

TPA. In addition, not al l spots wi ll be 

active (contain &tacking adult beetles 

or developing broods) at the time of 

detection, In these spots, the average 

number of dead trees was generated from 

an exponential distribution with an 

expected value of 1 tree. In active 

spots, the number of trees killed was a 

function of the number of active trees, 

SPB population level, total basal area 

per acre, mean stand diameter, and 

number of days a spot remains active, 

The expected number of trees killed per 

acre was the product of the probability 

of infestation and the number of dead 

trees, 

The expected vol ume per acre ki 1 l ed 

by SPB is obtal"ned by mu1tiplys"ng ELOSS 

by the average pine volume per tree for 

each survey plat, The average pine 

volume per tree is derived From the 

total pine volume per plot and the 

number of pine growing-stock trees per 

plot. For the area covered by the 

Southeastern Forest Experiment Station, 

the number oP growing-stock trees per 

acre was derived from the total number 

of 1 ive stems per acre, age, and basal 

area per acre, Survey data for the 

Southern Farest Experiment Station did 

not include the number of l ive stems per 

acre; therefore, trees per acre were 

estimated by forest type, age, and 

observed basal area per acre, 

Po determine the ref iability of the 

results of the simul ation procedure, 

actual publisted data on the volume 

killed by SPB were compared for the 

Southern region. Data for the decade 

1971 to 1380 were used in the analysis, 

For each Survey Unit, predicted l bsses 

for the moderate SPB paputation level 

(2.0 spots per 1,000 acres) were 

multiplied by the proportion of the unit 

area in an outbreak condition in each 

year. These adjusted loss estimates 

were summed to obtain total decade 

losses by Survey Unit. The unitwide 

losses were then aggregabd to obtain 

State and region totals, 

In order to obtain the loss projections, an estimate of the average number 

of days a spot is allowed to grow is 

needed. During outbreak periods, most 

States make three to four detection 

flights per year. Assuming the flights 

were optimally timed and that the spots 

were either controlled or inactive 

within 30 days of detection, the average 

interval sf spot growth is: 

Number of 

 aster, 3,E, ; Searcy , J,L,, eds, Site, stand and 

host characteristics of southern pine beetle Infestation, Tech, Bull, 1612, New Orleans, LA: USDA 

Combined forest Pest and Development Program; 1981, 

115 pp, 

4~rice, e,; Dsggett, 6, A At story sf southern plne 

beetle outbreaks in the southeastern United States, 

Macon, GA: &osgia Forestry CsmZssian, 1982, 32 pp, 
Table 4,--Predicted average annual cubic-foot volume of timber ki 11 ed 

by SPR in 10 Southern States 

Oays of spot Predicted volume D.i fference Percent 

g rowt h killeda between predicted errorG 

(ft3 x 106) and observed" 

Data for Oklahoma not included because of neyl igible SPB activity, 

aPredicted volume killed includes an average buffer strip volume of 30 

percent for a71 salvaged spots, 

bobserved average annual volume ki l led, including buffer strip trees, 

for 1971 and 1980 (see footnote 4) is 12,788 x 106 ft3; cords and fhm 

were converted to cubic feet by using factors of 70 ft3 per cord and 

210 ft3 per fbm, 

CPercent error = (predicted - observed)/predicted. 

When these periods of spot growth were 

used to generate expected losses, the 

results in table 4 were obtained, 

The results indicate a positive 

bias in the predictions, An average 

period of 65 days between spot occurrence and control is probably opti - 

mistic, Reported periods between 

detection and control in east Texas for 

1974 and 19755were 53 and 35 days, 

respectively. nuring this period, the 

Texas Forest Service was Plying seven or 

more presuppression flights per year, 

which means that the average period of 

spot growth was between 66 and 84 days, 

If it is assumed that the average period 

a spot grows is 75 days, then the 

results in table 5 are obtained for each 

of the States, 

On a statewide basis, the poorest 

predictions were for Arkansas and 

Tennessee, which are on the extreme 

"fexas Forest Service, Texas forest pest activity 

northern ranges of the SPB. Even 

i ncl udi ng these States, the rank correlation between the observed and predicted volumes killed is 3,8 (Spearman8s 

rank correlation, statistically significant at the 99,5 percent level), 

There are many potentidl sources of 

error in this comparison of predicted 

and observed volume ki l led by SPB, The 

data for observed volume killed are 

reported by each State, The degree of 

emphasis given to pest con&rol activities, the level of the personnel 

involved, and the methods of ohtaininq 

reported vol ume ki 1 led vary great1 ye 

The data are adequate for internal use 

by the States, hut they may be less t3an 

satisfactory for model val idation purposes, This situation is especially 

true for the volume ki l led but not 

sal vaged. Furthermore, the conversi nq 

factors used to obtain cubic-foot vol ume 

from cords and board-foot measure (fbm) 

can also be a source of bias, 

1974-1975 and forest pest control sectfon biennial 

report, TFS circa 226, GOI lege StatSon, TX; 1976, There is also potential error ~SSO19 PP, ciated with the method sf determining 
the buffer strip volume from the sirnula- since SPB populations are cyclic, 

tion results, The State pest control whereas forest conditions are d-ynamiworkers reported that sf the total 

volume salvaged, an average of 30 percent consisted of buffer strip trees, 

This value, expressed as a proportion, 

was mu%-l;ipH ied by the reported average 

proportion of the total voldme killed 

that was salvaged and by %he total 

volume killed in each State to obtain 

the predicted volume of buffer strdp 

trees, This volume was added to the 

predicted vol ume ki 11 ed to obtai a the 

combined volume lost due to SPB attack, 

The FIA survey is a1 so a source of 

potential error, The data were eolIecLed at a single point in time and 

were used to generate predicted losses, 

which were compared with averaye observed 

losses over a decade, Aggregate multiyear loss comparisons are necessary 

cal ly changing; thus, the overai l 

susceptibi l ily and vul nekabi 1 ity sf the 

forest to SPB attack changes from year 

to year, Furthermore, some modification 

of the simulation program was nece5sary 

to accommodate FIA survey data, These 

modifications resulted in the use of 

some submodel s with reduced predictive 

abi li-ty, 

Lastly, the survey data obtained 

from the Southern Forest Experiment 

Station ind uded age, expressed in 10- 

yedr increments, but did not include 

inforination on the number 0%: trees per 

awe, Therefore, the number of yrowinystock trees had to be generated from 

other survey plot variables, one of 

which was age, This procedure was less 

Table 5,--Predicted and observed annual cubic-foal volume of timber 

killed by SPB if the average infestation grows for 75 days 

Predicted vol ume Observed vsl ume Percent 

Statea killed" kl" l l edc errord 

aOkl ahoma omitted because of negligible SPB activity. 

'predicted volume killed includes an average buffer strip volume of 30 

percent of sal vaged spots, 

'Observed average annual volume ki 11 ed, including buffer strip trees, 

for 1971 to 1980 (see footnote 4); cords and fbm were converted to 

cubic feet by using factors sf 70 ft3 per cord and 290 ft4 per fbm, 

"~ercent error = (predicted - observed) /predicted. 
than satisfactory, as is reflected in 

the simulation results shown in Gable 6. 

where: 

These resul ts are a1 so ref1 ected in 

the range of prediction errors for the 

States within each FPA survey region, 

For the Southern Station, the range was 

-181,66 to 82,44 percent, with five of 

the six States having errors greater 

than 240 percent ftabl e 51, For the 

Southeastern Station, the range was 

-16,63 to 37.56 percent, with three 05 

four States having prediction errors 

less than +21 percent (table 5), Furthermore, the relative rank of States in the 

Southeastern Station region is the sane 

with regard to observed and predicted 

volumes kil led, Based on these results, 

the projections for the States in the 

Southeastern Stat ion survey region must 

be considered more re1 i abf e, 

In addition to simulation of actual 

volume killed by SPB, estimates of 

growth loss due ts premature harvest 

(salvaged) were also made, The first 

step in this process was the development 

of total cubic-foot volume equations for 

each State Prom FIB survey data, The 

form of equation was: 

v = total cubic-food volume per 

acre 

A = age in years 

SC = site class 

D = square feet of basal area per 

acre 

To obtain the volume at the end of 

the projected rotation, harvest ages 

appropriate do the ownership and projected basal area at rotation were 

entered in the equation, The typical 

harvest or rotation ages provided by 

State forestry pest control officers for 

various ownership classes were SO years 

for Federal Ian&, 45 years For State 

1 ands, 35 years for industry, and 45 

years far NIPF lands, The difference 

between the volume ad the time of attack 

by SPB and the proje@ted volume at the 

end of the rotation was the estimated 

growth toss, No growth loss occurred if 

a stand was older than the appropriate 

rata%ion age for the ownership, 

The process is dependent upsn a 

method sf prsjecting the basal area per 

acre at the rotation age, In this 

study, equations for predicting basal 

area were developed for different forest 

types From FIB survey data, 

Table 6.--Comparison of predicted and observed volume of timber killed 

by SPB, based on an average period of spot growth of 75 days 

Forest Experiment Predicted vol ume Observed vol ume Percent 

Statl" on killed killed error" 

a~ercent error = (predicted - observed)/predicted. 

abama, Arkansas, Louisiana, Mississippi , Tennessee, Texas. 

(Oklahoma omitted because of negligible SPB activity .) 

'Georgia, North Carol ina, South Carol ina, Vi rginia. 
where : 

B = basal area per acre 

SC = site class 

4 = age in years 

( 14) levels of net benefits, Table 7 qives the benefit/csst ratios for the States, 

These ratios, at the 4 percent discount 

rate, range from a high sf 92% for 

Alabama to a Isw of 1,12 for Oklahoma, 

This equa&isn was used to calculate the 

di fference (DRA) between the basal area 

per acre for the survey plot and the 

predicted basal area of the plot given 

the same site class and age, The 

equation was then used to predict the 

expected basal area at the end of the 

rotation given the same site class and 

age, This value was added to DBA Lo 

obtain the predicted basal area per acre 

at the end sf the rotation, This 

approach seems to overpredict basal area 

at the end of the rotation if the initial basal area per acre is high. It 

also %ends to underpredict for low initial basal areas. This method of projection is less than satisfactory; 

however, due to lack of suitable basal 

area growth equations, it was the best 

of the many alternatfve ppediction 

-nethods tested, Csnsequenfly, there is 

a source sf potential error of unknown 

magnitude associated with the grnwt h 

loss projections, Furthermore, the 

error dssocdated with the growth loss 

estimated for States in the Southern 

Forest Experiment Station will be 

greater than For States Prow the 

Southeastern Station area due to the 

deficiencies in the survey mentioned 

previously, 

Figure 3 illustrates a ranking of 

the States by the optimal net benefits 

of SPB control for both the 4 and 10 

percent discount rates, The States can 

be separated into three categories 

according to their level of net benefits 

for SPB control, Alabama, North 

Carolina, and Texas fall into the eategory of highest net benefits, Georgia, 

Louisiana, South Carolina, and 

Mississippi display a moderate level sf 

qet benefits, Virginia, Tennessee, 

Arkansas, and Okl ahorna exhi bit very low 

4 PERCENT DISCOUNT RATE 

I0 

-=-' 

10 PERCENT DiSCWNT RATE @ a0 

& 

Q 

Figure 3,--Optimal net benefits of SPB 

control , at two di scsunt rates, by State, 
Table 7,--Summary sf optimal total benefits and total costs for SPB 

cant roi at two di senunt rates, assirm-i" ng a moderate beeat l e gopul at fan, 

in thousands of 1984 do1 lass, by State 

Total Total Net BeneFi d/ 

State henefi ts costs benefjts cost rat i s 

Regional 

total 

Regional 

total 

4 PERCENT DISCOUNT RATE 

$0 PEQCENT DISCOtJfdT RATE 

'Less than $500, 

Tab1 e 7 summasi zes the optimal 

total costs (both direct and indirect) 

and benefits for SPB control at both the 

4 and 10 percent real discount rates. 

These results represent the optimal 

solutions obtained for the individual 

FIA survey plots summed for each State. 

The results indicate that the calculations of benefits and costs were very 

sensitive do the different discount 

rates, At the 4 percent discount rate, 

the total benefits were about $59,% 

million for the entire region, and the 

total costs were about $9,5 million, 

yielding net benefits of $49.6 million. 

The regional benefitJcost ratio was 

6,22, At the $0 percent discount rate, 

the regional benefits were approximately 

$372 million with tstal costs of 362 

million, Net benefits were $30,9 

mil 1 ion, and the benefitfcssd ratio was 

533, 
fable 8,--Summary of optimal total benefits and direct costs For SPR 

control, assuming a moderate beetle population, in thousands of 1984 

do1 1 ars, by State 

Total Di rec t Benef i ds , net Benefi t/di rzct 

State beneft" t s costs of direct costs cost ratio 

4 PERCENT DBSGOIJNT RATE 

Reg1 onal 

total 59,097 7,051 52,046 

10 PERCENT DISCOUNT RAPE 

Regional 

total 37,160 5,244 31,916 

aLess than 6500, 

Table 8 carrtar'ns study resnf ts 

sjmilar to those in table 7 except that 

the direct costs of SPR control are 

given instead of the total control 

costs, These direct costs represent the 

actual cash out1 agss for presljppre5sfon 

fligh%s, evaiuation, and suppression, 

and exclude the opportunity cmts 

involved fn the harvesting of financially immature timber to control SPB, 

The regional benefits net of di rect 

costs were $52 mil l inn at the 4 percent 

discarrnt rate, wiith a henefl"t/cost ratio 

of 8,38, Ad the I0 percent discount 

rate, the benefits net of direct costs 

were about $32 mil 1 ion, yielding a 

benefitlcost ratio of 7,08, 
Table 9,--Summary of optinal regional benefits and costs for SPB 

control at two di scount rates, assuni ng a moderate beet1 e popul adion, 

in thousands sf 1984 do1 lars, by ownership class 

Ownershr" p Total Total Net Werrefi t/' 

class benefi t s costs benef i ts cost ratio 

Federal 

State 

Forest industry 

NrPF 

Regional 

total 

Federal 

State 

Forest industry 

N I PI"" 

Regional 

total 

4 PERCENT DISCOUNT RATE 

20 PERCENT DISCOUNT RATE 

Table 9 contains the regional henefits and costs by land ownership class, 

At the 4 percent discount rate, NIPF 

lands accounted for 64 percent of dhe 

total net benefits; forest industry 

l ands, 20 percent; Federal lands, 12 

percent; and State lands, 4 percent, 

NIPF lands represented 65 percent of the 

total costs; forest industry lands , 23 

percent; Federal lands, 10 percent; and 

State lands, 2 percent. At the 10 percent discount rate, the general pattern 

of benefit and cost distribution remains 

the same, with NIPF lands accounting for 

the majority of benefits and costs. The 

benefitlcost ratios, at the 4 percent 

discount rate, range from 7,93 on State 

lands to 5,66 on forest industry lands, 
4 ERCENT DISCWNT RAE 

10 PERCENT DISCOUNT RATE 

CUT AND a EVALUATION 

INDIRECT a DETECTION 

Figure 4.--Components of SPB control 

cssts, a% two discount rales, by State, 

Figure 4 displays the breakdown of 

total control cost into the various 

direct and indirect cost components, by 

State, Far most of the Sta$es, the eost 

of presuppression flights was the 

l argest component of cant rol cost, 

averaging about 40 peg~enk of total 

costs, The indirect cost of premature 

timber harvest was the next largest eost 

csmgonent, averaging about 28 percent sf 

total costs, Eva1 uation costs averaged 

27 percent of total costs, bud the 

direct cost of cut-and-leave suppression 

constituted only 5 percent, The direct 

cut-and-leave cost is a larger share of 

total cost in Georgia and, parlicularly, 

Texas because the practice is more cornm8n there, 

The csmple%e, detailed study 

results are in the appendix, Table 18 

contains the analysis results far the 

enti re Southern region; tables 11-21 

contain the results for the separate 

States, Each table contains the results 

for both the 4 and 90 percent discount 

rates, Optimal total benefits, changes 

in %a1 vage value, direct and indirect 

cssts, and benefitlcost ratios are given 

by Sand ownership class, Row and column 

total s may contai n some sl i ght rounding 

errors, 

Csncl usion and Discussion 

The results of this study indicated 

that, in a year of typical SPB activity, 

substantial benefits could be realized 

from optimal economic control of SPB 

damage to commercial timber stands, Ad 

a 4 percent real rate to discount the 

value of timber losses, the optimal net 

benefits of control for the entire 

Southern region are estimated at about 

$50 mi 1 l ion, yielding a benefitlcost 

ratio of 6,22, Even at a 10 percent 

real discount rate, the regional net 

benefits are estimated to be more than 

$38 mil 1 ion with a benefiticost satis of 

5e93, 

Seven States--Alabama, North 

Carolina, Texas, Georgia, Louisiana, 

South Carolina, and I"lisss"ssippl"-.- 

unquestionably warrant large SPB control 

efforts, Of those, Alabama, North 

Carolina, and Texas are the three 

largest in terms of net benefits, 

averaging about $9 m?lI ion per State, 

The remaining four States could generate 

optimal net benefits of about $5 million 

each, Vi rgi ni a, Tennessee, Arkansas, 
and Bkl ahsna, under optimal SPB control 

conditions, would yield net benefits per 

State of less than $1 million, 

From the study results, the total 

regional optimal annual direct cost for 

SPB control is estimated to be about $7 

to $5 mi57ion, depending upon the 

assumed discount rate of 4 or 10 percent, 

respectively. The majority of this 

control expenditure should be appl ied to 

presuppression flights and to the evaluation sf SPB infestations, The direct 

cost associated with suppression, i ,e, , cut and leave and cut and salvage, is a 

minor component of control activities, 

The optimal direct control costs for 

Al abama , North Carol i na, Texas, Geergi a, 

Loui si ana, South Carol i na, and 

Mississippi range from about $1.2 

mil lion to $700,000 annually, per State, 

depending upon the assumed discount rate 

of 4 or 10 percent, respectively. 

This study was an attempt to pi-$-- 

vide an economic basis for the planning 

of SPB control programs. As such, it 

represents a conceptually complex 

research activity. The simulation 

program seems to slightly overpredict 

volume ki 11 ed by SPB on a regional 

basis. Overpredicti on appears to be 

greater for the States in the FIA survey 

region of the Southern Forest Experiment 

Station. The predictions for States 

covered by the Southeastern Station survey (Georgia, North Carol ina, South 

Carol ina, Vi rginia) are very close to 

the observed volume ki4 led when a7 1 the 

sources of pdenlial error are considered, The estimates of future growth 

loss due to premature death of the trees 

are subject to an unknown degree of 

error given the methods used to make the 

psojec$isns, 

In spite of these caveats, the use 

of projected volume killed for the 

moderate popul ati on l eve1 weighted by 

the proportion of the region in an 

outbreak condition during an average 

year provides a realistic estimate of 

the direct mortality due to SPB attack. 

Because sf these sesul t%, only the 

moderate SPB population projections were 

used in the economic analysis conducted 

with BEAM. Use of either the low or 

high popul atisn values would result in 

extreme underestimates or overestimates 

of loss, Losses calculated from volume 

killed combined with growth loss due to 

premature death of trees caused by SPB 

attack provide the only estimates of the 

total regional impact sf tRis pest 

avai l abl e today. There shoul d furni sh 

suitable initial estimates for eva7- 

ua$ing the economics of cooperative 

control programs, 

Further investigations and refinement of the models and data are, 

perhaps, warranted; however, the authors 

express confidence in the results that 

have been generated, Al so, sensitivity 

analyses were conducted to determine the 

effect of varying assumptions regarding 

salvage rates, timber prices, etc, , on 

the study results, We determined that 

the results were not very sensitive to 

small changes in the data, Indeed, 

changes in the discount rate had far 

greater hpack on the study results than 

did changes in the other variables, 

Thus, data inaccuracies should not be a 

matter of great concern, 

Acknowledgment 

The study was funded by the USDA 

Forest Service, Forest Pest Management, 

State & Private Forestry, The research 

was conducted by the Southeastern Forest 

Experiment Station with J,E, de Steiguer 

serving as principal investigator, Portions of the study were contracted to 

Roy Hedden, entomologist, Clemson University; Hugh Devine, data process1 ng special ist, Nsrtk Carolina State University; and Gary Kmnrad, economist, North 

Carol i na State University, Assistance 

in computer programming was provided by 

John M, Pye, Southeastern Forest 

Experiment Stati an, Kim McBonough, North 

Carolina State University, and Mike 

Marshal 1 , Clemson Uni versi ty, lechnieal 

advice concerning various aspects of the 

study were provided by Ken Swain, entomol ogi st, Forest Pest Management, State 

& Private Forestry, Region 8, 
APPENDIX 

Table 10.--Optimal level for SPR control in thousands of dollars, by 

ownership class, for the Southern region 

Category 

parest 

Federal State industry WPF Total 

4 PERCENT DISCOIlNT RATE 

Beneffts 

Timber saved $7,142 $1,430 $12,954 939,523 $61,059 

Change in salvage -239 -466 -1,498 -1,962 - 

Total benefits 6,903 1,331 %2,498 38,325 59,097 

Di rect casts 

Psesuppressl" on f% ights 352 73 905 2,544 3,875 

Eva1 aradion 237 45 523 1,842 2,645 

Cut and leave 56 7 - % 76 292 539 

Total direct costs 644 125 1,604 4,677 7,051 

Indirect costs (buffer timber) 244 -- 604 1,530 - 2,446 

Total casts 908 173 2,208 6,208 9,497 

Net benefits 85,995 $1,198 %10,2Qfl 632,117 $49,600 

Renefl"d/cost ratio 7,60 7,93 5 66 6,47 6,22 

"I PERCENT DISCPIIINI RATE 

ReneFt" ts 

Timber saved 

Change in salvage 

Total henefi ts 2,942 997 10,204 23,017 37,161 

Di rect costs 

Presuppres%ion fl igkts 175 54 732 1,512 2,474 

Eva1 uadi on 200 40 490 1,576 2,305 

Cut and leave 51 6 165 242 464 

Total direct costs 42 7 100 1,386 3,330 5,243 

Indirect costs (buffer timber) 61 23 418 520 1,022 

Total costs 488 124 1,804 3,850 6,266 

Net benefits $7,455 5874 $8,400 $19,167 $30,895 

Benef i t/cost ratio 6,03 8,07 5,66 5,98 5,93 
Table 12,--Optimal level for SPB control, in thousands of dallars, by 

ownership class, for Wl abama 

Forest 

Federal State industry MIQF Total 

Berlefi ts 

Timher saved 

Change in salvage 

4 PERCENT DISCOUNT RATE 

Total benefits 579 206 2,587 7,214 10,586 

Direct costs 

Presuppression flights 33 9 174 426 642 

Eva1 uati on 15 5 82 214 316 

Cud and leave Y 1 - 0 7 3 - 9 P 13 

Total direct costs 48 14 260 649 970 

Indirect casts (buffer timber) - 12 - 1 50 - 98 162 

Total costs 61 14 31 0 747 1,132 

Net benefits $519 $192 $2,277 $6,467 $9,454 

Benefit /cost ratio 9,54 14,44 8,35 9,66 9,35 

10 PERCENT DISCOUNT RATE 

Renef t'ts 

Timber saved 

Change in salvage 

Total benefits 159 153 1,901 3,699 5,912 

Direct costs 

Presuppression flights 9 6 119 183 316 

Eva7 eaation I1 4 75 180 270 

Cut and leave 1 - 0 3 8 12 

Total direct casts 20 10 198 371 599 

Indirect costs (buffer timber) I 17 5 23 

Total costs 21 10 214 376 622 

Net benefits 

Benef i LJcost ratio 7,5I 15,26 8,87 9,84 9,53 
Table 12.--Optimal level for SPB control, in thousands of dollars, by 

ownership cl ass, for Arkansas 

Forest 

Federal State industry NIPF Total 

4 PERCENT DISCOUNT RATE 

Benefl'ts 

Timber saved 

Change in salvage 

Total benefits 

Direct costs 

Presuppressi on fl igkts 0 1 22 22 45 

Eval uat i on 0 0 2 2 4 

Cud and leave 0 0 5 5 I0 

Total direct costs 

Indirect costs (buffer timber) 

ToUI costs 

Net benefits $0 $4 $60 $69 $1 33 

Benef i Llcost ratio 

10 PERCENT DISCOUNT RAPE 

Benef ids 

Timber saved 

Change in salvage 

Total benefits 

Direct costs 

Presuppression flights 0 1 20 16 37 

Eval uation 0 0 2 2 4 

Cut and leave 0 0 5 5 -- 9 

Total direct costs 0 2 26 23 511 

Indirect costs (buffer timber) 

"Todal costs 

Ned benefits 

Renef-i"t/cost ratio 
Table 13.--Optimal level for SPB control, in thousands of dollars, by 

ownership class, for Georgia 

Category 

Forest 

Federal State industffy NIPF Total 

Benefits 

Timber saved 

Change in salvage 

4 PERCENT DISCOUNT RATE 

Total benefits 682 50 B ,071 5,599 7,402 

Direct costs 

Presuppresston flfghts 43 5 97 440 586 

Eva1 uatlon 31 3 53 345 432 

Cut and leave 7 - 1 4 7 P 78 103 

Total direct costs 631, 9 168 863 1,121 

Indi rect costs (buffer timber) 76 324 

Total costs 12 1 13 244 1,187 1,565 

Net benefits $561 $37 $828 $4,412 $5,837 

Benef i tlcost ratio 5,62 3,77 4,40 4,92 4,73 

10 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 403 27 847 3,172 4,450 

D-i rect costs 

Presuppression flights 25 3 72 251 351 

Eva7 uatton 26 2 510 289 367 

Cud and leave 6 1 17 71. 95 

Total direct costs 57 6 139 61 f 813 

Indirect costs (buffer timber) 15 37 90 - 143 

Total costs 72 7 176 701. 956 

Net benefits $332 $20 $671 $2,472 $3,493 

Benef i %/cost ratio 5,62 3,65 4,81 4,53 4,65 
Table 14.--Optimal level for SPB control, in thousands of do1 lars, by 

ownership class, for Louisiana 

Category 

Forest 

Federal State industry NlPF Total 

4 PERCENT DISCOUNT RATE 

Beileftts 

limber saved $1.038 $322 $2,175 83,254 $6,789 

Change in salvage -4 1 -- 1 3 -66 -97 -21 8 

Total benefits 

Di rect costs 

Presuppression flights 52 14 163 258 487 

Eva1 uatian 21 6 64 102 194 

Cud and leave - 1 0 P 3 4 -- 8 

Total direct costs 

Indirect costs (buffer timber) 34 10 - 106 - 164 - 315 

Totall costs 108 30 336 528 1,003 

Met benefits 

Benefi tlcost ratio 9,25 10,20 6,27 5,98 6,55 

10 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 

Di rect costs 

Presuppression fl lghts 17 9 137 139 302 

Eva1 uat i on 17 6 61 88 172 

Cut and leave 1 0 - 3 4 7 

Total direct costs 35 15 201 231 482 

Indirect costs (buffer timber) 3 I 73 30 106 

S"o"t1 costs 37 16 273 261 587 

Net benefits 

BenePi t/eosG ratio 5,87 9,46 6,13 5,67 5,99 
Table 15,--Optimal level for SPB control, in thousands of do1 l ars, by 

ownershi g class, for Mississippi 

Category 

Farest 

Federal State industry Nf Pf Total 

Benefits 

Timber saved 

Change in salvage 

Total benefits 

Direct costs 

Presuppression ffights 

Evaluation 

Cud and leave 

Total direct costs 

Indirect costs (buffer timber) 

Total costs 

Net benefits 

Benef i tlcost ratio 

RenePi ts 

limber saved 

Change in salvage 

Total benefits 

Di rect costs 

Presuppression flights 

Eval uadisn 

Cut and leave 

Total direct costs 

Indirect costs (buffer timber) 

Total costs 

Net benefits 

Benef it/cost rat i s 

4 PERCENT DISCOUNT RATE 

I0 PERCENT DISCOUNT RATE 
Table 16.--Optimal level for SPB control, in thousands of dollars, by 

ownership cl ass, for North Carol ina 

Forest 

Category Federal State indrrslry NlPF Tota 1 

4 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 332 284 506 9,195 10,317 

Di rect costs 

Presuppression flights 24 12 43 449 528 

Eval uation 16 9 21 454 500 

Cut and leave - 1 - 0 - I - I 1 - 13 

Total direct costs 

Indirect costs (buffer timber) 

Total costs 

Net benefits 

Benef it/cost rat is 

10 PERCENT DISCOIJNT RATE 

~enefi ts 

Timber saved 

Change in salvage 

Total benefits 205 230 450 6,586 7,477 

Oi rect costs 

Presuppression fl ights 14 9 36 31 7 378 

Eval uation 15 9 20 404 449 

Cut and leave 1 - 0 - 1 - 10 -- 12 

Total direct costs 

Indirect costs (buffer timber) 

Total costs 

Net henefi ts 

Benef i %/cost ratio 
Table 17.--Optimal level for SPB control, in thousands of dollars, by 

ownership class, for Oklahoma 

Forest 

Category Federal State industry NIQF Total 

4 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits ,51 0 0 0 

Direct costs 

Presuppressi~n fl ights .22 0 0 If 

Evahdion .01 0 0 0 

Cud and leave .03 0 0 0 

Total direct costs .26 0 0 0 

lndise~t eests (buffer timber) Q 

Total costs .45 0 0 8 

Net benefits $. 05 $0 $0 $6 

Benef it/cost rat is 1,12 --. -- - - 

10 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits .32 0 0 0 

Di rect costs 

Presuppression fl ights .I1 0 0 0 

Eval uation .[I1 0 0 0 

Cut and leave F .04 - 0 0 - r) 

Total direct costs @I6 0 0 0 

Indirect costs (buffer timber) - .I2 - If - 0 

Total costs .27 0 0 0 

Net benefits s.05 $0 $0 $0 

Benef i tlcost ratio 1,17 -- -- -- 
Table 18,--Optimal level for SPB control, in thousands of dollars, by 

ownership class, for South Carol ina 

Category 

Forest 

Federal State industry NIPF Total 

Benefl" ds 

Bl"n,ber saved 

Change in salvage 

4 PERCENT DISCOUNT RATE 

Total benefits 586 156 563 4,718 6,024 

Direct costs 

Presupgression flights 38 7 48 279 379, 

Eval uadion 26 6 26 267 324 

Cut and leave 1 0 1 7 9 

Total direct costs 64 41 3 75 552 705 

Indirect costs (buffer timber) 25 - 5 - 36 245 

Total costs 90 18 I10 732 950 

Net benefits 

Benefi tlcost ratio 6,54 8,5R 5,410 6,45 6,34 

10 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 383 138 444 2,953 3,917 

Direct costs 

Presuppression fl lights 21 6 39 185 251 

Eva1 uati on 23 5 24 246 298 

Cud and leave - 1 - 0 1 - 7 9 

Total direct costs 

Indirect costs (buffer timber) - 8 - 3 19 56 86 

Total costs 53 15 83 493 544 

Net benefits 

Benefitleost ratio 
Table 19.--Optimal level for SPB control, in thousands of dollars, by 

ownershi p cl ass, for Tennessee 

Farest 

Federal State industsy MIPF Totdl 

Renef i t r 

Timber saved 

Ghange in salvage 

Total benefits 

Di sect costs 

Presuppression fl ight% 

Eva1 ua-tion 

Cut and leave 

Total direct costs 

Indi rect costs (buffer timber) 

Totakcests 

Met benef i t s 

BenePit/csst ratio 

Benefr" ts 

Timber saved 

Change in salvage 

Total benefits 

Direct costs 

Presuppression flights 

Evaluation 

Cut and leave 

Patal direct costs 

Indl" rect costs (buffer timber) 

Total costs 

Net benefits 

Benefitlcost ratio 

4 PERCENT DISCOUNT RATE 

10 PEWGENT IPISCOajNT RATE 
Table 20,--Optimal level for SPB can"irof, in thousands of do1 lars, isy 

o~nership class, for Texas 

Category 

Forest 

Federal State industry NIPF loda '"r 

4 PERCENT DISCOUNT RATE 

BeneFi ts 

Timber saved $2,671 $190 $4,020 $3,964 $10,845 

Change in salvage -118 -6 -126 -1 35 -377 

Total benefits 2,561. 183 3,894 3,829 10,468 

Di rect costs 

Presuppression flights 7 1 6 228 2 38 543 

Eva1 uati on 70 6 164 259 399 

Cut and leave - 43 - 4 - 140 P 

157 P 

344 

Tatal direct costs 185 16 532 553 1,286 

Indirect costs (buffer timber) - 80 - 8 197 - 193 -- 478 

Total costs 265 24 729 746 1,764 

NeL benefits $2,297 $160 $3,165 $3,083 $8,704 

Benef itlcost ratio 9,68 7,76 5,34 5,13 5,94 

10 PERCENT DISCOUNT RATE 

Benefi ts 

Timber saved 

Change in salvage 

Total benefits 1,099 153 3,541 2,448 7,242 

Di rect costs 

Presuppression flights 42 5 204 147 398 

Eva1 uati on 53 5 156 126 350 

Cut and leave - 40 4 P 131 P 

119 P 

293 

Total direct costs 145 13 491 391 1,041 

Indirect costs (buffer timber) 21 6 172 93 292 

Total costs 166 19 663 485 1,333 

Ned benefits 9933 $134 $2,818 $9,964 $5,909 

Henef i tlcost ratio 6,6f 8,fO 5,34 5,05 5,43 
Table 21,--8ptimal 1 eve1 for SPB conlrol , in thousands of dollars, by 

ownership class, For Virginia 

Category 

Forest 

Federal State industry MIPF Total 

4 PERCENT DISCOUNT KATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 53 49 201) 935 1,237 

Di rect costs 

Presuppression flights 1'1 4 26 123 163 

Evaluation 4 2 10 48 63 

Cut and leave 1 -- 1 -- - 3 16 --- - 21 

Total direct costs 16 6 39 186 247 

Indi rect costs (buffer timber) --- 7 - 3 22 -- - 99 P 

132 

Net benefits $30 $39 $139 $650 $858 

Benefi t/cost ratio 2,31 4.93 327 3,28 3,26 

10 PERCENT DISCOUNT RATE 

Benefits 

Timber saved 

Change in salvage 

Total benefits 32 45 171 673 920 

Di rect costs 

Presuppression flights 7 4 22 87 119 

Evaluation 3 2 9 41 55 

Cut and leave - 1 - 0 - 3 14 -- 19 -- 

Total direct costs 11 6 34 142 192 

Indirect costs (buffer timber) - 3 -.- 3 - 17 P 57 P 

80 

Total costs 14 9 51 198 272 

Met benefits $19 $36 $120 $474 $649 

Benef i t / cost ratio 2,34 522 3.34 339 339 
i 

I de Steigwer, J.E.; Hedden, Roy L.; Pye, John M. 

I 

! de Steiguer, J.E.; Hedden, Roy L.; Pye, John M. 

I Optimal level of expenditure to control the southern pine beetle. 

1 

I Optimal level of expenditure to control the southern pine beetle. I 

I Res. Pap. SE-263. Ashevi 1 lev NC: U.S. Department of Agriculture, Res. Pap. SE-263. Ashevi 1 le, NC: U.S. Department of Agriculture, 1 Forest Service, Southeastern Forest Experiment Station; 1987. 30 pp. I 

I Forest Service, Southeastern Forest Experiment Station; 1987. 30 pp. I 

I 

I 

I Optimal level of expenditure to control damage to commercial timber 

stands by the southern pine beetle was determined by models that simu- 1 

I lated and analyzed beetle attacks during a typical season for 11 1 

1 Southern States. At a real discount rate of 4 percent, maximized net 1 

I benefits for the Southern region are estimated at about $50 mi 11 ion; at I 10 percent, more than $30 million. Methods and costs for detection, 

I evaluation, and suppression of beetle infestation are discussed. Tables I 

I of optimal level for the 11 States are included. 1 

Optimal level of expenditure to control damage to commercial timber 

stands by the southern pine beetle was determined by models that simuI 

lated and analyzed beetle attacks during a typical season for 11 I 

Southern States. At a real discount rate of 4 percent, maximized net 

benefits for the Southern region are estimated at about $50 million; at 

I 

10 percent, more than $30 mil 1 ion. Methods and costs for detection, I 

evaluation, and suppression of beetle infestation are discussed. Tables 1 

of optimal level for the 11 States are included. I 

I KEYWORDS: Dendroctonus frontal i s, CLEMBEETLE, OVERFLIGHT, BEAM, cut and I KEYWORDS: kndroctonus frontal is, CLEMBEETLE, OVERFLIGHT, BEAM, cut and i 

I leave, cut and salvage, presuppression flights. 1 1 eave, cut and sal vage, presuppress i on f 1 i ght s. 

t I