Gasply : a computer model for Georgia's future forest

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GEORGIA FOREST RESEARCH COUNCIL REPORT NO. 36 A APRIL 1978

"
The Authors

Vernon L. Robinson, Ph. D.
Principal Economist, USDA Forest service, Southeastern Forest Experiment Station, Forestry SCiences Laboratory. Athens, Ga.

Albert A. Montgomery, Ph.D.
senior Research Associate, Contract Research Division, College of Business Administration, Georgia State University, Atlanta.

James D. Strange, B.5c.
Consulting Forester. USDA Forest service (Ret.). Atlanta, Ga.

ACKNOWLEDGMENTS: The authors gratefully acknowledge the Georgia Forest Research Council and an economic advisory committee chaired by H. E. Ruark. Director of the Council. that encouraged the development of the Georgia Long-Run Timber Economic Model and subsequent published reports of which this computer model is the basis. The assistance of RicKard K. Hokans is also appreciated for incorporating subroutine REPLY into the computer program.

Q1SP~
A COMPllrER
MODEL FOR GEORGIA'S FllrURE FORES-
by Vernon L. Robinson, Albert A. Montgomery, and James D. Strange

Abstract

Introduction -

GASPLY (Georgia Supply) is a computer program, written in FORTRAN IV, for estimating the long-run timber supply from even-aged forests in Georgia, although it is appl icable to other states or reg ions. The model uses existing data on timberland area by aggregating Forest Survey plots into acreage cells, each of which is analyzed according to three management plans - custodial. natural stand, and plantation. Maximization of present net worth is the criterion for choosing among the mutually exclusive man-

agement plans for a given cell. Insertion of a long-run demand equation allows the user to estimate an economic growth goal which balances the future demand and supply of forest products. The program prints out the long-run timber supply function and the management prescription that will ach ieve a balance in future demand and supply.
KEYWORDS: Timber supply and demand. forest management.

Computer program GASPLY is a timber supply and demand model developed as an aid in evaluating the management for Georgia's future forest resource. The model focuses on the long-run economic problem of how much capital to invest in forestry in the near future in order to efficiently supply timber demands, which are projected to double by the end of this century and beyond (1, 2).

1

Overview of Model

The basic premise of the model is that in the long run all factors of production are variable. Hence, the potential timber supply from an area is not a function of what exists there today, but rather of what could be grown on that land if it were managed with proven methods of sound silviculture. This premise requires the long run to be defined not as a definite time period but as a state or condition in which the disparity between trees growing and trees harvested is bridged by the assumption of sustained yield. The potential supply of timber is therefore defined as a function of the amount of land available for growing timber, the management plan used, and the per-acre yields and costs associated with that plan.
GASPLY is designed to utilize existing data on timberland area by aggregating Forest Survey plots into acreage cells each homogeneous with respect to region, subregions, called Area Planning and Development Commissions (APDC's), forest type, owner, site quality, and physiographic class. Depending upon the definitions assigned to the region and subregions, the model can be applied to forest land management on individual tracts or a state or region, Each acreage cell is assigned three management plans - custodial. natural stand, and plantation, The custodial option implies no management and minimal costs; property taxes are the only cost outlay, The natural stand and plantation options, as their names imply, reflect currently accepted methods of regeneration and management.
GASPLY assembles the acreage cells with their accompanying management routines, costs, and yields into a long-run timber supply curve that reflects the average unit costs of producing various amounts of timber. Maximization of present net worth is the criterion for choosing

among the mutually exclusive management plans tor a given cell. An iterative procedure is required since the long-run timber supply curve is an envelope curve composed of a series of management prescriptions computed at various stumpage prices. Those cells whose unit costs of producing timber lie above the price level are assigned to custodial management. This assignment is based upon the assumption that if average costs cannot be covered in the long run, the land will revert to a custodial state in which timber will continue to grow without encouragement and owners will continue to pay taxes on these unmanaged lands.
One of the principal advantages of the model is its ability to demonstrate the impact of changes in the various factors underlying the supply curve. The program will yield a longrun timber supply curve for any situation that can be cast in terms of changes in acreages, management plans, costs, or yields, Hence, the model can serve as a versatile management guide for identifying policies and action programs that are likely to have the greatest impact upon the future supply of timber within a state.
It is important to recognize that the results of any economic analysis depend upon the price level chosen as well as the costs, interest rates, and physical characteristics used to describe the supply situation, In rateof-retum and cost-benefit analyses, the emphasis is typically upon the costs and the physical characteristics, while the price level is arbitrarily chosen by the investigator. Nonetheless, this choice implies a demand equation, without specifying the conditions to which it applies. Here, a demand equation is explicitly incorporated into the program because the model is intended to evaluate the collective forest management of a broad gao-

graphic area (such as a state) that can appreciably affect timber supply and stumpage prices,
The advantage of using a demand equation is that it also allows the program to identify the equilibrium point at which the amount demanded by processors at the indicated price will just equal the amount which would be supplied at that price by the timberland owners. Although no such forecast can hope to be precise, the model is logically complete, Furthermore, there is a strong economic incentive, in the long run, for forest investors to develop the forest resource toward this equilibrium level of output because the marginal acreage included in it will yield a retum at the equilibrium price, which is just equal to the capital cost of the marginal acreage cell.I Hence, this long-run equilibrium output provides an estimate of an economic growth goal which balances the future demand and supply of forest products, In addition, the model simultaneouslyyieldsestimates of the total investment cost of producing this level of output. as well as describing type of management needed, and the location, site quality, owners, and number of acres involved.
'The intemal rate-of-retum below the equilibrium price will be higher than the capital cost on the marginal acreage cell. while that above will be lower.

2

Description of Program GASPLY

Program GASPLY is written in standard FORTRAN IV language for the IBM 3CJJ/65 computer located at the University of Georgia.2 It consists of a main program and five subroutines. Operations performed by each routine are described below and identified by comment statements in the source program (APPENDIX 1). Input variables and structure of the data deck are described in the section entitled User-Supplied Information.
Main Program
The main program performs the following operations:
1. Controls the user-supplied input section consisting of keyword and data cards which identify and initialize the various arrays.
2. Adjusts the forest cell area for urban encroachment and other losses in land use.
3. Assigns the management costs and yields to each cell.
4. Computes the future costs of each management option for each cell.
5. Calls subroutines REPLY, PNW, ADJUST, SORT, and ACCUM.
6. Tests for both the long-run and equilibrium solutions from a series of price levels and a demand equation, respectively.
7. Writes out in tabular form the long-run timber supply curve, the management prescription for the equilibrium forest in which future demand and supply are balanced, and a summary of the acreages under management for the state by APDC, ownership, forest type, physiographic class, and site class.
Subroutine REPLY
Subroutine REPLY is used in conjunction with the MAIN program to control the data input. It reads and writes the user-supplied data which initialize the data arrays. This subroutine uses keywords to identify the different data sets and blank spaces within the sets to identify any datum in free format.
2The program was found to be fully compatible with the UNIVAC 70/7 computer located at Georgia state University. requiring only the addition of system commands unique to this computer..

Subroutine PNW
Subroutine PNW is called by the main program to compute the present net worth (perpetualrotation basis) of each management option and to select that option which maximizes the present net worth for each acreage cell. It is assumed that an even-aged forest is established upon bare land to yield a crop at periodic intervals. Since the present net worth is affected by the stumpage price or demand equation, this subroutine, along with subroutines ADJUST and SORT, is called in an iterative manner as the stumpage price undergoes incremental increases. An option to restrict the private, nonindustrial landowners to custodial management is incorporated into this subroutine. This option is activated by
setting ICUS = 1 on the PARAMETERS
keyword card.
Subroutine ADJUST
Agricultural activities are a major competitor with forestry for large areas of land. How much land forestry gains from or loses to agriculture depends in the long run upon the economic returns that can be earned by land in each of these uses. If future stumpage prices are high relative to agricultural prices and rents, forestry stands to gain land from agriculture, as it has in the past. Conversely, if future stumpage prices are relatively low, farmers will have incentive to clear timberland for use as cropland and improved pasture.
This economic reasoning is incorporated into the program in subroutine ADJUST by setting limits upon the amount of land that the model can shift between forestry and agriculture. In the instance of forestry, only the most productive timberland found in farm ownerships is considered feasible for conversion to agriculture. This land is identified by the program from among the Forest Survey data cells. On the other hand, the amount of farmland potentially available to forestry must be supplied by the user; it might include idle farmland or unim-
3

proved pasture. This acreage must be incorporated into acreage cells and appended to the Forest Survey data cells. Since the program treats these acreages differently than those currently forested, they must be given an APDC number that is 20 greater than the APDC number within which they lie. For example, if there are 3,000 acres of idle farmland in APDC number 6, the data cell for idle farmland within this subregion would be given an APDC number of 26.
By using data from arrays FARM RENT, and CLEAR, subroutine ADJUST yields estimates of the acreage that might shift between agriculture and forestry. The acreage shifting from forestry to agriculture is determined by comparing, for each farm woodland cellon sites of high quality, the present net worth of the forestry option plus a land clearing cost, adjusted to an annual basis, with an agricultural land rent. Shifts in the opposite direction are determined by comparing only the annualized present net worth with the land rent. The presence of land clearing costs within the program makes it more difficult for land to shift from forestry to agriculture than vice versa. To obtain a sustained volume of yield, subroutine ADJUST also divides the yield of the management option by the rotation age; the cell acreage is then divided by the rotation age to provide estimates, on an annual basis, of the area needing the chosen management prescription.
Subroutine SORT
For each acreage cell, subroutine SORT arranges the unit cost of the chosen management option in ascending order of magnitude. This arrangement facilitates accumulation of the total yield, from which the main program can locate the equilibrium level of output.
Subroutine ACCUM
Subroutine ACCUM summarizes the equilibrium forest area in each management option by APDC, owner, forest type, physiographic class, and site class. The main program then writes out this summary.

User-Supplied Information

Values for 16 variables and 17 arrays which describe treatment opportunities or control program execution are read from data cards supplied by the program user. These entries are identified under 16 keyword data cards and are briefly described in the tabulation entitled Order and Contents of the Data Deck at the end of this section. The keyword cards are an essential part of the data deck because they identify the data input. Most of the entries are in free format, requiring only a blank space between entries and in column 80. A detailed description of the entries is given in this section.
JOB
The JOB keyword card controls the number of tables printed, the type of supply curve computed, and whether the Forest Survey data cells are written out. The program allows the user a choice between a public and private supply curve. The public curve is based upon the real economic costs of forestry which concern the public in terms of economic efficiency; the private curve is based upon the financial costs of forestry which concern the individual forestry investor. The assumptions underlying the construction of the public supply curve are identical with those of the private supply curve in every respect, except that (1) private as well as public land is charged the real economic cost of the overhead to public forestry activities in lieu of the ad valorem property tax that applies to private lands under the private supply curve, and (2) investment in forestry on private as well as public lands is charged at the real economic cost of capital rather than at the real rate that applies to the individual investor, as would be the case under the private point of view. The program automatically develops the public timber supply curve when the user sets IPOV = 1 on the JOB keyword card, provided he also initializes PUBLIC and RATES (1) on the INIT keyword card.

PARAMETERS
The demand equation utilized in this program is one of the exponential form
P = EXP (-PARAM1* (InQ-PARAM2
where:
P = stumpage price (dollars per thousand cubic feet or S/MCF),
Q = amount of stumpage demanded in goal year (MCF),
PARAM1 = the inverse of the elasticity of demand, and
PARAM2 =the natural logarithm
of the constant term and the demand shifters. The program sums the annualized yield over the acreage cells for the estimate of Q and from the equation, computes the demand price at this level of harvest. An iterative procedure is utilized to locate the equilibrium point. The values of PARAM1 and PARAM2 are supplied by the user. They may be obtained in several ways. One possibility is to regress P and other demand shifters on Q from timeseries data,. then substitute into this equation the values of the demand shifters in the goal year to estimate PARAM2. Since the model is concerned with the basic forces underlying the market for stumpage, the potential consequences of inflation should be factored out of demand. Thus, demand should be denominated in dollars having purchasing power that is constant or equivalent with that of the base period used in the formulation of supply. This constant-dollar assumption has the effect of focusing the results of the model upon the real economic benefits and costs flowing from forestry investments. For example, if the model indicates a higher future market price than actually prevailed in the base period, the proper interpretation is that stumpage prices are expected to rise more rapidly than prices generally in the economy.

INIT
The INIT keyword card initializes the size of the computing matrix, the stumpage price level, the public and private overhead costs, the cost of capital, the number of APDC's, and the number of regions. The annual public overhead costs are entered as variable PUBLIC, while the private overhead costs are assigned to variable PRIVAT.
The array RATES requires a cost of capital for public, industry, and other private woodland owners. In assigning these rates, it is important to recognize that most of the recent increases in the nominal interest rates commonly used in financial analysis reflect the inflation which has been plaguing the nation. If this prospective impact of inflation is ignored, the future costs of supplying timber at the stump will be seriously exaggerated relative to demand unless the cost of capital is deflated also. Furthermore, it should be recognized that among the three types of investors there exists a rate differential which reflects the risk associated with their costs of capital. Finally, it is often the practice to include an additional charge for the risk associated with the timber-growing operation itself, either as an increment in the rate of retum or as an annual cost. The authors believe, however, that this type of risk should be treated as an adjustment to either the yield or management cost data rather than to the real cost of capital. This adjustment frees the interest charge from undue risk aversion while making the resulting intemal rate of return comparable with the retums from any other long-term investment. The problems arising from uncertainty can be handled by incorporating their certainty equivalents into the real rates of return.

4

SCHEDULES and
IDMATRIX
The program provides for 15 treatment schedules, each composed of 10 activities. The purpose of these schedules is to reflect treatment differences with respect to type of management. region, owner objectives, and forest type. To accomplish this differentiation, specific rows of the treatment schedule arrays are assigned to each of the three management plans, The rows within a plan are further assigned on the basis of region, owner, and forest type to reflect treatment differences appropriate to these characteristics. The row numbers are then identified in IDMATRIX to reflect these assignments to plantation, natural stand, and custodial management.3 As an acreage cell flows through the program, these identification matrices ensure that the appropriate treatment schedule is assigned to that cell.
One silvicultural restriction has been built into the program. Idle farmland cannot come into forestry by means of natural stand management. It must receive either plantation or custodial management, This restriction appears in the main program at step 200,
The ten activities within each treatment schedules are for entering the treatment costs in TSC (matrix of treatment schedule cost) and the age of the stand to which the costs apply in TSA (matrix of treatment schedule age). In plantation management. the first activity is reseNed for site preparation in year zero. Normally, this would be followed by a slash burn in the same year, The third activity is reseNed for planting. The tenth activity is reseNed for the rotation age. The remaining activities may be used for thinning or any other stand treatment desired by the user, In natural stand and custodial management. only the tenth activity is reseNed for the rotation age. By definition, no activities will be carried on under custodial management. but a rotation age must be specified.
'Zero or entries greater than the number of schedules in IDTSP. IDTSN, IDTSC should be avoided as they may cause the computer to reach outside the range of the TSC and TSA arrays.

In computing the total future cost of the stand, the activity age is subtracted from the rotation age to determine the length of time needed to carry the cost of the activity, Thus, if planting takes place in the year after site preparation and the stand is to be haNested at age 25, then the rotation age should be set at 26 and the planting activity at age one, This arrangement will allow the site preparation, slash burn, and ad valorem property taxes to be carried for 26 years and the planting costs to be carried for 25 years,
snEP and PLANT
To reduce the number of treatment schedules needed to describe the various planting conditions within a state, the site preparation and planting costs have been incorporated into separate arrays, Experience in Georgia suggests that site preparation costs be adequately defined as a function of region, physiographic class, and forest type, while planting costs were found to vary by region. The program Inserts these costs into columns one and three of TSC.
TAX, RENT, FARM,
and URBAN
The data for these keywords are a function of the APDC's and therefore make the model sensitive to localized conditions existing within a state, The program is designed to handle property taxes paid on an annual basis under the keyword TAX; they are assigned by the program to the tenth activity cell in TSC. Other forms of taxation will necessitate changes in the computational procedure, Under a fair-market-value tax system, one might expect ad valorem property taxes to rise in anticipation of expected urban sprawl. The lands affected by this anticipation are likely to exceed the property use changes that actually take place; therefore, the user might wish to adjust the ad valorem property tax for a given base year by some factor which is tied to the anticipated acreages lost to urbanization,

The model makes two adjustments to the commercial forest land area as recorded from Forest SUNey on the data cells. First, the URBAN data converts the current forest land area to a future basis by accounting for the anticipated urban sprawl and highway construction,4 This adjustment is limited to the acreage owned by nonindustrial private landowners, on the assumption that such land losses to public and industry holdings will be replaced through land acquisition, The program multiplies this factor by all the other private lands in that APDC, as reported on the Forest SUNey data cells. Secondly, certain types of nonforested land, such as idle farmland, might be expected to revert to forestry, while certain agricultural activities might impinge upon the more productive commercial forest area, Subroutine ADJUST uses the RENT and FARM keyword data to compare the relative profitability of these activities in order to determine the amount of disputed land that will move into or out of forestry,
The dollar amount of the agricultural rent which applies to the contested acreage will vary among APOC's but will center around a predetermined statewide average rent, The level chosen should be realistic in light of agricultural opportunities prevailing in the base period so as to be consistent with the stumpage price level and land-use pattern prevailing at that time,
The FARM keyword data represent the proportion of nonindustrial private forestland in farm ownership, Subroutine ADJUST assumes that potential agricultural opportunities are available only to farmers,
CLEAR
The land clearing costs under this keyword are similar to those of SITEP, but the intent here is to reflect the costs of clearing land for agriculture purposes rather than for forestry, Hence, these costs are likely to be higher than those for site preparation, Subroutine ADJUST adds these costs to the present net worth of forestry on the appropriate Forest
4The urban sprawl can be expected to impinge upon the total non-urban area of an APDC. Hence, In computing the URBAN adjustment factors, care must be taken to assign only that portion that Is likely to Impinge upon the forested area.

5

Survey data cells to determine whether the land will remain in forestry or not. Thus, if the present net worth (in annual terms) of forestry plus clearing cost is greater than the agricultural rent, the disputed land remains in forestry.
YIELDS
The user assigns plantation yields to YIELD2 and those from natural stands to YIELD3. These arrays are a function of region, forest type, owner, and site quality. The species to be employed will be indicated by the region and forest type in question. Rotation age is determined outside the program. These characteristics, coupled with the type of owner, will tie the yields to the treatment schedules and hence to harvest age. The yields may be obtained from yield tables according to the species, treatment schedule, and silvicultural restrictions that the user wishes to impose upon the program.
NAMES
The NAME keyword card is followed by the names assigned to the APDC's, owners, forest types, physiographic classes, site qualities, and state. These names are used for column headings in the printed tables.
DATA
The DATA keyword card signals the computer to rewind the tape or disk which is being used for a scratch file to store the Forest Survey and contested acreage cells. A maximum of 812 such cells is allowed. These cells may be obtained from Forest Survey

in a special computer run designed to aggregate the commercial forest land area from individual Forest Survey plots by the desired breakdown of the area. The program is designed for an area breakdown consisting of 18 APDC's, 3 owners, 5 forest types, 3 physiographic classes, 3 site qualities, and 3 regions. The number of APDC's and regions can be enlarged by changing the appropriate common and dimension statements at the beginning of the program. The other data cell identifications are fixed at the number indicated. In addition, specific statements within the program require owner number one to be public and owner number three to be private nonindustrial. Similarly, site quality number one needs to be the best site.
The regional breakdown utilized by this program is intended to conform with Forst Survey units within a state. These brood physiographic units provide a relatively homogeneous basis for determining species composition yields and operating conditions from which treatment activity costs can be ascertained. The APDC designations provide a finer breakdown of these units, in recognition of local impacts on land use and ad valorem property taxes.
The commercial forest area in acres obtained from the latest Forest Survey, is entered in columns 8-15 of the data cell cards, and an estimate of the growth for custodial management is entered in columns 55-60. The latter is intended to reflect a growth rate representing the lack of forest management. The program muItiples the growth estimate by the rotation age to obtain the custodial yield. The last data cell must be followed by a trailer card with a 9 punched in column one.

END
The END keyword card signals the program to a normal stop. If tandem runs are desired, the keyword cards and the data changes followed by another DATA card should be inserted between the trailer card and the END card. After completing the first run, the program will make the desired changes, rewind the scratch tape when the DATA card is encountered, and proceed to make the calculations for the second run. These tandem runs may be used to determine the sensitivity of the longrun timber supply curve to any of the factors (yields, costs, etc.) underlying its construction. As previously mentioned, the option to restrict the private nonindustrial landowners to custodial management is incorporated into the model. Activation of this option would demonstrate the timber supply shortfall that might develop if these owners fail to practice more intensive management (3).
The above keyword cards are identified by their first two letters. If an error is made in punching these letters, the program will stop and an error message will be written. Other abnormal stops will be encountered if the values of certain arrays are exceeded. If TPRICE on the INIT card is lower than the lowest unit cost encountered, a computer error will probably also cause an error message to be written. This problem can be eliminated by raising TPRICE above the lower unit cost.

6

Order and Contents of Data Deck

Keyword JOB PARAMETERS INIT
SCHEDULES

Number of Variable or
Cords Matrix Name

Columns

1 IJOB

IPOV ECHO 1 PARAM1 PARAM2 ICUS
1 II JJ TPRICE
PUBLIC PRIVAT RATES NAPDC NREGS 1
NSKED

Format

Description

Job control keyword.

I'

Control for number of tables printed:

long-run, equilibrium, and summary (1 );

long-run and summary (2); long-run

,.

only (3). Control for point of view: public (1),

private (2).

I'

Control for Forest Survey data write:

no write (0), write (1).

Demand parameters keyword.

R' Inverse of elasticity of demand without sign in log-log equation.

R' Constant term, including all shifters in log-log equation.

I'

Control for custodial management

restriction on private nonindustrial

owners: no restriction (0), restriction (1).

Initialization control keyword.

I'

Number of rows in the computing matrix

(C), the number of Forest Survey data cells.

I'

Number of columns in the computing

matrix (C), fixed at 24.

R' Initial stumpage price level (SjMCF) for long-run supply curve must be greater than the lowest unit cost (SjMCF).

R' Annual public overhead cost per acre.

R' Annual private overhead cost per acre, except taxes.

R' Cost of capital as a function of owner. Enter as a decimal.

I'

Number of APDC's.

I'

Number of regions.

Treatment schedule keyword followed by 2'NSKED schedule cards in pairs representing rows in matrices TSC and TSA.

I'

Number of treatment schedules.

7

Order and Contents of Data Deck (continued)

Keyword SCHEDULES
(con't.) IDMATRIX
SITEP
PLANT TAX RENT FARM

Number of Variable or
Cards Matrix Name

Columns

Format

Description

NSKED TSC NSKED TSA
1 NREGS IDTSP
NREGS IDTSN NREGS IDTSC
1 3*NREGS SITEP
1 PLANT
NAPDC/9 TAX
NAPDC/9 RENT
NAPDC/9 FARM

6-50 6-50 6-50 6-40

R* R* 1513 1513 1513 5F7.2
R*
R* R* R*
a

Treatment schedule cost matrix composed of 10 treatment activities, costs per acre.
Treatment schedule age matrix composed of 10 treatment activity ages.
Keyword for treatment schedule row control followed by 3*NREGS identification cards.
Treatment schedule identification for plantation management. The cells within this matrix identify the rows in TSC and TSA as function of region, owner, and forest type, with three owners within five forest types per card.
Treatment schedule identification for natural stand management.
Treatment schedule identification for custodial management.
Site preparation keyword followed by 3*NREGS site preparation cards.
Site preparation costs per acre as a function of region, physiographic class, and forest type with five forest types per card. These costs are placed by the program in the first activity cell in that portion of TSC assigned to plantation management.
Plantation cost keyword.
Planting cost per acre as a function of region on the keyword card. These costs are placed by the program in the third activity cell in that portion of TSC assigned to plantation management.
Property tax keyword.
Annual ad valorem property tax per acre as a function of NAPDC with nine entries per card beginning on the keyword card.
Agricultural rent keyword.
Annual agricultural rent per acre as a function of NAPDc, with nine entries per card beginning on the keyword card.
Farm ownership keyword
Proportion of other private forestland in farm ownership as a function of NAPDC, with nine entries per card beginning on the keyword card.

Order and Contents of Data Deck (continued)

Keyword URBAN CLEAR YIELDS
NAMES DATA

Number of Variable or
Cards Matrix Name

Columns

Format

Description

NAPDC/9 URBAN

1 NREGS CLEAR
1 5-NREGS YIELD2

5-NREGS YIELD3

1 NAPDC+14 R

1

STATE

1

10(1) ID(2)
ID(3) ID(4) ID(5) ID(6) AREA

6-45
6-26
6-26
1-20 1-20
1 2 3 4 5 6-7 8-15

R-
5F8.3
3F7.0 3F7.0
5M 5M
11 11 11 11 11 12 F8.0

Urban land loss keyword.
Proportion of other private forestland remaining in forestry in goal year, as a function of NAPDC, with nine entries per card beginning on the keyword card.
Land clearing keyword followed by NREGS clearing cost cards.
Land clearing costs per acre for agricultural purposes as a function of region and forest type, with five forest types per card.
Yield keyword followed by 10-NREGS yield cards.
Plantation management yields (cubic feet/ acre) as a function of region, forest type, owner, and site quality, with three sites within each of three owners types per card.
Natural stand management yields (cubic feet/acre) as a function of region, forest type, owner, and site quality, with three sites within each of three owners types per card.
Table names keyword followed by NAPDC + 14 name cards.
Table row names including NAPDC, owners, forest types, physiographic classes. and site classes.
Name of state.
Acreage cell keyword followed by a variable number of Forest SUNey and contested acreage data cards followed by a trailer card with 9 in column 1.
Region; Maximum of three.
ONner: Public (1), Industry-owned and leased (2), other private (3).
Forest type; Maximum of five.
Physiographic class; Maximum of three.
Site quality: High (1), Medium (2), Low (3).
APDC; Maximum of 18.
Commercial forest area in acres from the latest Forest SUNey.

9

Order and Contents of Data Deck (continued)

Keyword

Number of Variable or
Cards Matrix Name

Columns

Format

Description

DATA (con't.)

GADJ

55-60

F6.1 Mean annual growth on the Forest Survey plots which have been combined into the given acreage cell adjusted for rotation age.

1

1

11 Trailer card with 9 punched in column 1.

(Insert tandem runs here)

END

1

Keyword for end of run.

Integer or real variables in free-format form with each entry separated by at least one blank space, and column 80 blank.

10

An Application of GASPLV

The sample problems that follow have been documented and described elsewhere (1, 2, 3). The purpose here is to demonstrate the configuration of the data deck and the table output of the program. The first problem is concerned with estimating the optimal long-run level of management for the Geor-
gia forest. The data deck for this problem consists of the 135 cards shown in figure 1.
The numbers on the JOB card indicate that three tables will be printed: the long-run timber supply function, the long-run timber management prescription for the equilibrium forest, and a summary of the long-run timber management prescription. The timber supply CUNe will be based upon the private costs of forestry and the Forest SUNey input data cells will not be printed.
For the PARAMETERS card, the elasticity of demand was estimated to be -0.14. The inverse of this number is substituted for PARAM1; but. the negative sign is accounted for intemally in the program. The natural logarithm of the constant term is 14.892487, which is substituted for PARAM2. The value of this term corresponds to a doubling of demand at current price levels. No restrictions are placed on the private nonindustrial landowners in this run.
The INIT keyboard card calls for 812 data cells, and the computing matrix will have 24 columns. The initial stumpage price level is set at $25/MCF. The program will automatically raise this level in 20 steps of $10 each. The annual public overhead costs are set at SO. 73/acre and the private overhead costs, excluding taxes, are SO.13/acre. The cost of capital for public, industrial. and private nonindustrial owners is set at 0.03, 0.04, and 0.05, respectively. The impact of inflation has been removed from these rates. The model will utilize 18 subregions and three regions.
A total of 15 treatment schedules will be used, as indicated on the SCHEDULES card. Each treatment
schedule is composed of two cards. The first card contains the treatment costs per acre, and the second card

contains the age at which these costs are encountered. Here, treatment schedules 1, 2, 11, and 12 are set up for plantation management. Schedules 3 through 8 are for natural stand management, and the remaining schedules are for custodial management.
The IDMATRIX cards identify where the treatment schedules will be applied. The rows of this matrix identify regions within type of management while the columns identify owners within forest type. For example, the first three rows represent plantation management in north, central. and south Georgia. The first three columns represent public, industrial. and private nonindustrial owners within the longleaf-slash pine forest type. This sequence of columns is repeated for each of the five forest types utilized as shown under the NAMES card.
The SITEP matrix contains the site preparation costs per acre. The rows identify physiographic classes within region, while the columns identify forest types. Here, the first three rows identify the site preparation costs for xeric, mesic, and hydric physiographic classes within north Georgia.
The PLANT card contains the planting costs per acre for north, central. and south Georgia. These costs and the other costs in this problem are averages of cost data supplied the authors by woodland managers in Georgia. They reflect the costs incurred by them in 1973.
The TAX, RENT, FARM and URBAN keyword cards contain data by subregions which are identified under the NAMES card. The type of data contained on these cards has been previously described. The CLEAR card is followed by the land clearing costs per acre. The rows represent the three regions while the columns represent the five forest types.
The model assumes that the rotation age decision is predetermined. This age, coupled with the management prescription set up under SCHEDULES and a species decision, leads to the anticipated yields contained in the YIELDS matrix. This matrix contains both the plantation

and natural stand management yields. The first five rows give the anticipated yields by forest type within north Georgia for plantation management yields by forest type within central and south Georgia follow.s The plantation yield format is then repeated for the natural stand yields. The first three columns con-
tain the yields for public, industrial and private nonindustrial owners on high quality sites. This pattem is repeated for sites of medium and low quality.
Following the NAMES keyword card are the names which identify the 18 subregions, the 3 owners, the 5 forest types, the 3 physiographic classes, the 3 site classes, and the name of the state.
The DATA card is followed by the 783 Forest SUNey data cells and the 29 contested acreage cells, for a total of 812 acreage cells - each identified by region, owner, forest type, physiographic class, site quality, and subregion. Each of these cells also contains the commercial forest area in acres from the latest Forest SUNey and the mean annual growth on the Forest SUNey plots, which have been combined into the given acreage cell. adjusted for rotation age. This means annual growth will be multiplied by the rotation age to obtain the custodial yields for the cell.
The trailer card with 9 punched in column one is used to signal the computer to initiate the next logical step in the program. If only one run is desired, the trailer card would be followed by an END keyword card. In this sample problem, however, a second run will be made restricting the private nonindustrial landowners to custodial management. This run requires only the insertion of another PARAMETERS keyword card
a with a 1 instead of the for ICUS and
the addition of another DATA card between the trailer card and the END card.
'The reader will note that certain of these cells contain a zero yield. This value reflects the assumption that softwoods would not be planted on the bottomland hardwood forest types. It also reflects the assumption that while some hardwood plantations are being established. they are not being established on an extensive scale.

11

Figure 1. Data Deck Configuration For Sample Problems

1

2

3

4

5

6

1

B

1234561B901234561B9CI234561B901234561B90123~561B901234561B901234561B901234561B90

JaR 1 2 0
APa"'~TC:DS
IN IT 8\2 24

1

.142B 25.0

51 .13

1

4

.89 13

2.4n81

.

a
04

C5

1B

3

C;CH~nlllES 15

O. 00

1.50

0.00

3.15

2.5e

3.00

O.JO

0.00

0.00

0.00

1. 0.00 1. 2.50 5.

1. 1.50 1. 3.00 10.

o1..no
1. 11.60 10.

\6. 2.50
II. 3.15
25.

1L 3.15
H.
~ .. 15 45.

26. 2.50
19. 3.00
65.

1. 3.00 26. 0.00 5.

I. o.<'lO
, .I.
0.00

1. 0.00 I. 0.00 5.

26. 0.00
26. 0.00
65.

2.50

3.00 11.60

~. 15

3.1!

3.15

3.00

0.00

0.00

0.00

5.

10.

10.

25.

45.

65.

15.

5.

5.

15.

25. 00

3.15

3.15

3.15

3.0C

0.00

0.00

0.00

0.00

0.00

15. 2.50

25. 3.00

45. 11.60

65. , .15

85. 2.50

5. 3.15

5. 2.50

5. 3.00

5.

85.

0.00

0.00

5
o?'

..so

10. 3.00

10. 11.60

20. 2.50

2 O. 3.15

30. 2.50

30. 3.15

40. 2.50

5.

40.

3.00

0.00

5.

\ O.

10.

15.

20.

23.

30.

31 ..

40.

40.

25.00

3.15

3.15

~. 00

C.OC

0.00

0.00

0.00

0.00

0.00

15.

25.

40.

55.

5.

5.

5.

5.

5.

55.

0.00

0.00

0.00

0.00

C.00

0.00

0.00

0.00

0.00

0.00

9o..on

9. 0.00

Q.
0.00

Q.
0.00

9. 0.00

9. 0.00

9. 0.00

9. 0.00

9.

44.

0.00

0.00

o5..on

5. 1.50

5n..oo

5. ~ .. 15

5. 3.1!

5. 3.15

5. 3.00

5. 0.00

5. 0.00

5o5..oa

I.

I.

1.

21.

41.

61.

11.

1.

1.

11.

0.00

1.50

0.00

3.15

3.75

3.00

0.00

0.00

0.00

0.00

1.

1.

1.

?I.

41.

61.

I.

I.

1.

61.

0.00 9.

0.00 9.

0.00 9.

0.00
q.

0.00 q.

0.00 9.

0.00 9.

0.00 9.

0.00

0.00

9.

69.

0.00

0.00

0.00

0.00

O.OC

0.00

0.00

0.00

0.00

0.00

g9. :00

9. 0.00 5.

9. 0.00 5.

9. 0.00 5.

9. C.O C 5.

9. 0.00 5.

9. 0.00 5.

9. 0.00 5.

9. 0.00 5.

19. 0.00
85.

IDMATQTX

11 1 I 11 I I II I I 11 I 1 11 I 1

12 1 I 12 I I 12 I I 12 I 1 12 1 1

12 4 3

2 6 6

2 12 64 63

2 6 6

2 12

6 6

~

2 6 6

2 6 6

I~
5

2e
f

2 12 85 85

22 88 B8

3 14 13

1 9 9

13 9 14 9 13

~
oj

13 9 14 9 13

1 9 9

1 5 885 88 9 15 10 10 15 10 10 9 15 10 10 15 10 10

13 9 9 13 9 9 13 9 9 15 10 10 15 10 10

SITFP

53.55 53.55 ~"3.55 53.5 ~ 53.55

3 B.55 38.55 53.55 53.5 ~ 53.55

U:1a ~~: t6 ii:16 ~1:H n:~6

32.10 32.10 41.10 41.1 C 41.10

41.10 41.10 41.10 41.1C 41.10

47.25 41.25 41.25 47.2 ! 41.25

32.25 32.25 41.25 47.2 S 41.25

41.25 41.25 41.25 41.25 41.25

PLUff 16.45 15.20 13.50

TAX

1.300 1.100

1.910 0.680

3.350 14.810 1.350 0.920

1.610 1.040

1.330 1.430

~:~?8

1.020 1.110

1.450 2.800

RENT

2.350 2.900 2.600 2.260 3.230 1.820 2.120 4.500 6.800

5.510 1.12 C 1.290 1.HO 8.010 1.610 1.990 1.530 5.060

FAq"

0.319 0.320 0.At49 0.114 0.428 0.273 0.464 0.402' 0.555

0.343 0.530 0.399 0.511 0.534 0.620 0.599 0.401 0.158

tlp.ea.~

0.863 0.844 0.832 C.111 0.846 0.B58 0.195 0.932 0.946

0.921 11.946 0.942 0.H9 0.952 0.995 0.958 0.969 0.964

r:lFAq;

56.050 56.050 11.050 11.C50 11.050

50.200 50.200 65.200 65.200 65.20C

49.150 49.15 C f:4.750 64.150 64.150

y I FLO~

6165. 4320. 2800. 4918. 2620. 1364. 4918. 2620. 1364.

6065. 4320. 28CO. 4918. 2620. 1364. 4978 .. 2620. 1364.

6ry65. O. O.

4320. 4'320 ..
O.

2AOO. 2800.
O.

4918.
o.
O.

2620. 2620.
O.

1364. 1364.
O.

4918.
oO..

2620. 2620.
O.

1364. 1364.
O.

6960. 5620. "'H!. 4'1e. 2620. 13M. 4918. 262 O. 1364

&"&0. 5620.

436'i .. 491B. 2620.

1364.

491~.

262 O.

1364.

6960. 5620. 4365. 4918. 2620. 1364. 4918. 2620. 1364.

O. O.

5620. O.

436o5..

O. O.

262o0..

1364. O.

oO..

2620. O.

1364. O.

6480. 4660. 2805. 4 ?18. 2340. 1285. 4318. 2340. 1285.

6e:J60 .. 5620. "'~ll5 .. 4918.

2620.

1364.

4918. 262 O.

1364.

64AO. 64AO.
O.

4660. 4660.
O.

2805. 28C5.
O.

4.. 3311e8..
O.

2340. 2340.
O.

12B5. 12A5.
O.

4318. 4318.
O.

2340
234o0..

1285. 1285.
O.

6065. 4l10. ~AOO. 3555. 2540. 1640. 3555. 2540. 1640.

(1)6S. 4320. 28CO. 3555. 2540. 1640. 3555. 2540. 1640.

6'n0i6ta5..

4320 .. 2A85.

2800. 2030.

3555. 2415.

2540. 1110.

1640. 1120.

3555. 2415.

2540. 1110.

1640. 1120.

B935. 5360. 4195. 4100. 2900. 2315. 4100. 2900. 2315.

6960. 562". 436'5 .. 5015. 3925. 2950. 5015. 3925. 2950.

6960. 5620. l.H~. 'iCl!. 3925. 2950. 5015. 3925. 2950.

6~6 O. 5620.

1t~65.

5015.

3925.

2950.

5015.

3925.

2950.

3140. A935.

2B85. 53'0.

2030. "1 C!.

2415. 410C.

1110. 2900.

1120. 2315.

2415. 410n ..

1710. 2900.

1120. 2315.

64AO. 4660 2805. H2O. 3280. 1955. 4620. 3280. 1955.

6960. '620. 4~f.5. 5015. 3925. 2950. 5015. 3925. 2950.

t-.4~O.

4660.

2P.C5. H2C.

3280.

1955.

4620.

3280. 1955.

3140. 8935.

2BA5. 5360.

2030. 41 q-;:.

2415. 4100.

1110. 2900.

1120. 2315.

2415. 4100.

1710. 2900.

1120. 2315.

12

The output of the sample problems is composed of three tables for each run, (Appendices 2 and 3). The first table is the estimated long-run timber supply function. It shows the average long-run cost of producing various quantities of annual sustained-yield harvests. For example, at a unit cost of $95/MCF. the model suggests that 977 million cubic feet of timber could be harvested annually. This harvest compares favorably with the 813 million cubic feet of roundwood harvested from the Georgia forests in 1971. Higher unit costs would have to be encountered in order to increase the sustained yield harvest. The total investment in forest management represented by any point along this function may be obtained by multiplying the average cost per unit by the equilibrium quantity produced at this cost level.
The table also shows a breakdown of the commercial forest area by the management prescription which is optimal for any given level of cost. At very low stumpage prices (unit costs), little forest management is feasible, as indicated by the vast area under the unmanaged custodial option. At successively higher stumpage prices, progressively higher intensities of management become feasible. But even at very high stumpage prices, the custodial management option is optimal for very large areas of the total commercial forest. Finally, this table also shows the number of acres lost to and gained from agriculture at the indicated stumpage prices.

The second table is the long-run timber management prescription for the equilibrium forest. While the previous table is based upon the stumpage prices shown, this table and the succeeding one are based upon the demand equation specified on the PARAMETERS keyword card. The table consists of a printout of each data cell indicating the optimal management plan for the equilibrium stumpage price shown at the top of each page. Plans 1, 2, and 3 correspond to plantation, natural stand, and custodial management. respectively. The 812 data cells required 17 pages of computer printout. For brevity, only that page containing the data cell at the equilibrium price and quantity is reproduced here. As mentioned previously, this equilibrium quantity provides an estimate of an economic growth goal which balances the future demand and supply of forest products.
The third table summarizes the acreages under long-run management prescription by type of management. SUbregion, ownership, forest type, physiographic class, and site class.
The second sample problem run reproduces the same three tables under the constraint of limiting the private nonindustrial owners to custodial management, (Appendix 3). By plotting the two long-run timber supply functions in the pricequantity plane, the reader will

observe that this latter supply curve is shifted upward and to the left, indicating that the unit costs of producing a given level of sustained yield harvest have risen substantially as a result of this constraint. A comparison of the second table from each run shows that the equilibrium stumpage price has risen from $95 to $204 per MCF, while the equilibrium quantity has fallen
from 1,551 to 1,394 million cubic feet. The implications of this restriction are discussed elsewhere (2,3).
Each of the sample problems produced 20 pages of output. The CPU time utilized in the FORT and GO steps on the IBM 360/65 was 0.0419 hours. Memory accounting called for 15.5576 kilo-bite hours from a region size of 250 K. The total machine charge was $11.57. The program and data deck were read into the computer on a card reader. Data Set 5. The program output was on a printer, Data Set 6, and Data Set 9 was a scratch file which can be either tape or disk.

Literature Cited

1. Montgomery, AA. VL. Robinson, and J. D. Strange 1975. AA economic model of Georgia's long-run timber market. Ga. For. Res. Counc. Rep. 34. 21 p.

2.

_

1976. Impacts of land-use competition and other constraints on Georgia's future timber supply. Ga. For. Res. Counc. Rep. 36, 25 p.

3. Robinson, V L., A A Montgomery. and J. D. Strange 1976. Georgia's future timber supply depends on landuse policies. South. Lumberman 233(2895): 101103.

13

Appendix 1 Program GASPLV

Main Program

rrC..

PQfJGRA.N GASPlY

C

I ~DfIM=r<N~~SIIOiNi~Y8I~F~LR0m3'~h:3585n??Wr~~1IO~TmSPiIf3~.~3~lM5:t~~JIlOITlS5NI310.3E51

gl=~~m~ Um::ioI61:~lelil:~Ma.11.m~ml~Rmml

W8t' DlfIIIJ=NSION YfflI:'213,5,3,3'. IDTSCt3,3,S',TC(lOI,UR8ANI18l

n~~~~: n~pfH~~~~c~~:

X21201.L 1ST 1531 ,STATF 141.N I) 161

tNtTlAt.T1E C!TA

nlrQ POYfl.l'.POVct.z"'PUel','IC 'I nATA PClVf2,1),P("JI2,1)/'PRIY','ATE '/
g~t~ ~1~t~~~i~~~~SoFALSF.1

:

:~:l~~:l~

*

,7 ,2

.,11HHS!

,ll-lC ,tHO



,7,lH$,IHI

*

.2 .1HP, IHL ,2, lHr, IHA



,2,lHP.IHE

...

,..,r, .2 tlHF ,lHA

.2. lHU t IHR

,2,

IH...



,2,lHY,lHt



,2.IHN,tHA



,4,1"'(, lHA,LH,l~A



,3,lHE,lHN,lf"'O


*

OAT

Ao~:

A,P0O1r.

t' :

.'g~~f:: :~qP~:::~~~~::

: Sll~:



I'

'tip ','VPF ','APHI','SS t



,

I,

"'

" I C Cl','



OATA n~~.t:::(H~}~7 F~l;E.1 ','4SS','

'I

NKEYS=16

C

E

CONTROL INPUT SfCTWN

ra,ll REPlYflISltlh('lRQ ,X,tGCTI

IF! IW~RO.LT.l.0'.IwnRo.GT.HfYSIGOTO 2

GO Tn (lOt1'),~O,25,30t35,40,45,50t5S,60,6'),70,75t80,6),

IIWORO

2 WPITEI6,:3t

'} FnR~AT(t rNC('~RfrT I<.FYW('lPO, RJN STOPS.'.

STnp

~ ~~~~~ltt~INrcpp~rT VALUE R~NGE, PUN STOPS.')

6 STnp

C C

Jna

r

10 npT(t1=.TQU~.

IJnR=IFIXIXllll

IPOV=IFI X(XI?lt

l~nJ~~~eU:~~~IJOB.LT.l1 QJ TO 4

IFflP~V.GT.2.nR.IJnR.I.T.1I GO TO 4

Gn TO I

PARAMETERS (Fer: r)E~A~C FOJATION)

1

5

0PPATR~ll2l\1l==.xT

RU H)

F

.

P"'M2=XI21 IrU5=IFIX!X!?11 Gn l") 1

Er.

TNT T r \1 T1. 1=

70 OPTI~I=.TPUC.

1l=!FIXIX!11I

JJ=IFIXIX(711

= TP~TrF

X(~l

PURLlC=X 141 PPIYAT=)( 151

-'TFSIII=XlbI
~~~~~H: ~:~J I

Flfl.T~S = FlrWNER)
N~PDt:=Xlqt+(l.S

N2=(N6P['l(+l )/2

TFO.!I\POr:.f,T.IB.nP.II.r.T.AI2.0R.JJ.GT.241 GO TO 4

NQ17G$=X(IO) +O.S r;n Tn 1

<;r.YFOlll c S = I:(MGT.PlAN,lREATMENTSI

~S nPH4)=.TQllE.

N~ K1:0= TF T X (X (t , I

nn 76 T=l ,'J'l.;lCFr

r.6Ll p,:P( Yfl {C::T t TWf1RO,X,IGCT)

(At I ?FPl V(l '5T. T~npn,X2t TGnT I

nTnc::r.

76
( T.

J J

=,=l),(l

Cl IJ

I

?:6 T<;A(I,JI'=X7 lJI

r-n r" 1

= 'f)"l~T~n: Fno ("(HF.f'lllE~

FIPFGN,r""~lfP,FTVPEI

Vl npT["iI-=. nlI e

QFAf) '5.~I.FpP=2)f( IrCT~PI t,J,KI,J=l,31,I<-=l,5)tl

0fhn ll:i,11.r"oO "'? I (( (I nTS~( T ,J,KJ ,J=I,31 ,1<.=1 ,5), I

Q,FA"'l (S, '1t.l: Qo -=?)( (IOTsr( I,J t KI,J=l t 1)tK=l,S) ,T

wOT Tt= 1~,311

III tr;TSPI T,J, K I,J= 1, 3 ),K= 1, .'51, r

~~~J~1~:in

ii ~l~t~n J:j:~::j~1:51:~:1:~::1

c," Tr') 1

"1 l=:npl,l.\T(5'1(.l~T~)

r. rC.

= q ; c PQl:PfOj\T{CN r(<;Ts

FIPl=:(,N. PHvStr, FTYPFI

'f.. 1"i 'lD T I61=.TQUI:.

nn

!=l,t-'f)I:r-S

pr. ... IlI'5.371({~r .. l:DIT,J.t<'),I<=I,51,J=1.11

3~ IoI 0 TTl:(6,'RH (~lTCP' T,J,I("K-=l,SI,J=l.~1

"1 ~~Q~~d6X.q F."

~q ~i'O"'lr.T(1X,Sf!.71

PI ~NTT~lr (rST~

FIR Fr.N)

40 nP T I7)=.T P I1::.
nr 41 T-= 1.f'ICI r.r.~
!, 1 PI a"lT ( f 1 -='( f T I r.r Fl 1

T!\X:::<; '" l={tonr(1

CAll REPLYfl 1ST, IWOtlD,X2,JGIJTJ

IFI IWO~O.NE.OI GC TO 2

nn 46 t"'l,N2

HXIII=XIII

46 HXfNHII=X2111

GO TO I

C

rC.

lGRICULTURAL ~FNTS - FIHOCI

5J OPT (q t=. TPUF.

CALL REPlYfltST,TWORD,X2,IGCT)

IFIIW~RO.~F.OI GC TC 2

00 51 I'" I,Ni'

RFNTIII-XIII

51 RENTlN2>1I=X21It

rr..

G~ TO I FARM PROPORTTrN nF OT~EP PRIVbTE LAND

C SS OPTlIOI.TRUf.

FIAPOCI

CALL RfPLY1LlSToIWnRO.X2.IGCTI IFIIW~RD.NF.OI r.C TO 2

~~R~?d :~1~~

56 FARMIN2+11=X?1I1

r.

Gn Tn I

rC.

UReAN LANC AOJU5TMFNT FACT)~S FIAPDCI

60 OPTllll=.TRUf. r.~ll REPlYll 1ST, TWORD,X2, I<:OT I

IFflWOqO.Nf.CI GC Tr. 2 00 61 1"'1,N2

u~eANII1=X(11

61 UIRANIN2+II=X2111 r.O Tn I
C

E

CLEARING ((1$15'= F(RFGN,FTVPE)

65 nPTfl21.TRUE.

~~A~~ 5~ bJ,:~:~~}) (el E. rq I ,J) ,J=l ,SI

H WRITE(6,6BI fClE_PfI,J 'tJ:::l,5)
r.o Tn I 61 Fn ~ "'1.6, T I 7 x, 5 F P :3 )

68 F('lR,.,AT IBX,5F8.31

C

C

YIFLO~ FOR PLANHTION MGT. FIPEGN,I=TVPF.,OWNER,SITE.

rC.

YI':lOS FOP NAT. ~TANr MGT.

, FI~EGN,FTYPE,('WNEP SI TE)

10 nPTl13I=.TRU<. no 11 1=I,NRfGS

71 :~~~~76?~~~~~(~~~I~~1~~~~~~Lt:~;t~3~:~;i:3~:~~f:~t=t,sJ
12 F(1R,..4 T I4X,9F8.01 00 7~ 1=I,NREG5 RFAn(5,71,ER.~=211ICYI!=:lO~(1,J,<tlJ,L=I,:3.,K=1,3. ,J:::l,5J

73 ~ I TE 16, 7~ I II IY' ElO 3 ( I, J, I<. ,l) ,l -.:: 1,3 J t K-.:: 1,:3 J, J-.:: 1, 5 J Gn TO I

14 FClRwATI5X,QF8.01

C

C

NAMES (FnR TAeLESI

C

15 OPTI141-. TRU<.

n('l 16 T=I,NA,PDC

PFAOI'5,77HRII,J )tJ=lt5J

16 ~~~ii~~~78. f Rrt, J), J ... t, 51

11 FnR"l/lTC '5.&.4)

1R Fnp"'ATft I,S~4t

~~AA75!7~jl~~ t tJ 'tJ""l,51

19 WPTTFf6,18t IPI f t J',J:r:.l,SI

RFAOI5,71') SlATf

WPTTEf6,781 ~TATr:

GO TO I

C

[

DATa, fFPO~ I=CRFST ~UPVFY)

C eo TF(npTfll:;l) en Tr QO

f'}PT(t';) -= .T~UF.

nr 82 1=1 .14

TFIOPTlT)I (;( TI1 A2

"' ~~J~~~~,AAITI t:;Qrllp'.!3,' ""SSING'/) n"T (16' ., TCltJF.

R7 f~~~bfYftl) r-n l( '1

NN -= 1

B Q F A0 f I), 84, F PR= 2 I 10, AD E ~ , G.A OJ

e4 crQ:l,laTf"1.T?FFl.r,'9)l,F6.11

r

C T"E aF'o,wr:: STUr::MFt-.'T ~."'Y BE rt-'A"GED B'JT THI: PRIlGRAM ~Fcnf.NIZES:
r. rr;llJlIoIIN 1 = :;>F(;Ii'N r. crlUM~I? ::: f'J\o""FR

~

= r.ntu"1p..'?; -= F(DFST TVPF

~0ltJ"'N 4

PHYSlrGRAPH!( CLASS

C"LUMN'; -= rOlllMN h ,7~

SqI:T:nEc

OUAlTTV

a'in THFTQ~"TMF'JT <'ir;t-lp)lJtFS, rr<;TS, FTC. ,..PI=" TIF(') Tn THiS TO.

NT 0 III = I NInI21=? NI013I=3
~\gl~\~~
NI0161=6
NI 0161 =6

"'m -= n t "II"'~ TO, ::: '1
pl:'Tr~ -= TDC!rcpC,\r) r: .... "~5T c::.ucyty CIITA C':LLS

14

Appendix 1 (cont.)

UR8A~ A~O CTH~P lA~O lOSS AOJUSTMENT,INClUOING TPACT SIH

IFII0(61.GT.201 CC TC 95
i~~iO!7l.~1.J~p~~ll~li~1

95 vrOSTI : O. TCOSTI : O. G("l Tn (ICO.2CO,3CO. ,N

PLANTATION ... .aNAGfMENT

10~ m~o~ ir.m~7m7~nl~~:Hlm2I,101511
on 102 1:1,1( TUIl - TSCIISCH,Il I n TAllI - TSAIISC~oll TCIII - SITEP!l01II,IDI4Iol01311 Trnl: PlANTlIrll .. Gn TO 400

NATURAL STAN~ MANAGEMENT

200 IFIIOI61.GT.201 GO Tn 300
imo~ iommll7~nl!~~ni~WI"01511

mll : on 202 1-1,10

202

mlm~:11

r.n TO 40n

C C C
lOO

CUSTQntAl MA"".aGf"'F~1' VIElOI - r.AOJ ISCH - InTSCflCfll,10121.IC1311
~2d~2:I ~h l~m, 1I

302 HIli - TSAllSCH,I1

= ROT - TAIIOI

vtFlOl

Yt~Lrl.pnT

ASSIGN PROPFRTY TAXES

400 i~lIg\6j.8t~20, GO TO 402

M s ID(6)

GO Tn 404

402 M - 10161-20

404 IF CHHZ t -2' ... ('6,408.It 10

406 ~fn81 500 Pl'8l1 C

408 TCIIOI : pp nAT

410 Tr 1101 Tr I 101'TAXIMI

C

C

COMPUTE FtJTUPf ((I$T5

C

5)0 IF!lPDV.EO,1I GO TO 502

~AT~ .. PATc::snC(2)

GO To 50a

5)7 RATF = R.ATF~ (11

504 RC'T - TAllO)

00 506 1-1,9

~~~STI R~TE~~IH Sow OGII"PATE III

506 ~'f~m ~ ~m~IRh~1~~6HI:JiHlllIl-l.1

508 ~Po~91 I ;03f~IV\ 'lPrrCCNST7IRATE I 0 PUPlICI

1';11 TO 5\ 2

510 TrO~Tl = vrf)<:Tl + IfcrNST2/ Q ATEI TeUOt)

512 Jf=(~Z) !14,'"lt.'.:18

514 YPI : VI ElOI

TrPl -= r':1"'511

Q.flTP = Q.f'T

r;n T'1 520

516 YNI = VI C::lOt

TrNI .... TrO$TI

qnT"J = prT

for" Tr"1 520

5\ 8 Y(" 1 : VI., 01

fRrncTtr

=:
=

Tr"C;TI
tun

II)~O~=fI.J+t
1'::("-1.",T.'::l) r:r 'Tn 522 r.n Tn 95

= '5" NN ''IN+t

= I"')(; -:74 1:= 1. t:

"~4 (lNN,1'

rr.n I

t(:(P,l.,t'1... l,q~)1

YrrPDI t

rlflm,lOI

O(T~

r,pol"'dLJ

V~l

(fNa.:.l11

T(Nt

r:fNN,lll

f. = r.

f

N~. NN.

\41 1 "i I

O(T~
yr. T ((" 1

fINN,U.) := RrTr

e(N'I) ,.. Ar::F1I./lt:'{lC.

C

r.r Tn qt

r

")~ nr '52'"1 I=1.7~

1"("'1 C:ZR J=l. e

"i7A $1 0P,JI := C.

b11') 61)

N~'N '" 1

1"\ .... 602 t= I. I'

Oft hO' rll.7I

J==q1 7! 1. J J

( " l I d ) = f'I ..

rn"'OIlT- I"C'F<r::f\T ~cT "rent-' (IF fACH rPT I"N 'HIO ~clcrl rPTlO~' "PH T"'tF IotAX P';W

rllli 1l"'WPI .tDPJ.PPtr~I~,HfSd(,UC;)

r" II .' I)J lIS'" ItT. !J t TF C; t rAP"'. 0 D"j T , elF A') 1

fALL 5":>T(!l)

'":::-:T Fn c Fl'etll RD fl!M, u~rNC PPICf Lfvn S

1. ot;, 1 =: O.
O~7 := ((.Jf1111.71)-rfj.ll(lI. 1"1(\ 704 1=,1.' T

= 0" "1: 1-0\ "1 + (rfJ~IJ(1.701"':(JA(I(), 11)
Q!'7" ()<;? + IrlJfJ(1 1,701"'CIJAIII, 7) pr ~ f)q, r c

= Pq := fIJ\fKI,t'1'

0","
,r(!

)

,

,

r(J!'lT :,.,".pr

1 l

.1'1
(I"'

)

Tn

7(14

= r,r l~fQ"".'lF.C<;I1

Tfl 700

ror- 0<;1

OE : OSI

GO Tn 106

100

pIFe

CP ~

S2.G PO

T

.

P

S

I

I

GC

TO 102

Of - OS2 GO TO 106

102 ALPHA - AUN21IPE2-PSII,cOS2-0SIII

PE - PO OF OSI+ClPO-PSIIOICCSIAlPHAIISINlAlPHAlII Gf\ TO 106 104 CONT! NUl;
106 {t~\~~~:}\ = ~~

1~8 S~l~RdfIN3NANI,i3I1 :-H'S-l2R.I,NNN10,e311+1C0I,J1~1I2I, 11 110 ~rRl~N~~~1 - SlRINNN,41+<:IJAIII, 11
Gn Tn 116 112 IFICIJAlII.t91.Gl.PRlcel Gf TO 114
SlRINNN,51 - SlRINNN,51+<:IJAIII, 11 GO TO 116
: 114 SlRINNN,61 - SlRINN~,61+CIJAl1l, 11
116 ~l=I~~~~~1 ~t~I~~~:~I:tli~I\I:~:1

118 CONT!~UE

WRITF OUT lCNG-PUN SUPPlV CURVE

IFINNN.GT.II GO TO 126
120 ~~I t~l ~~~~4FHA~~~lP(v lIPCV,I) ,I-I ,2I,'ATESIII, PAres 111, I PAT ES 111
17.2 ~~lf~I~~~241 STATE,IPDVIIPCV,II,I-I,2I,.AreSlIl,PATfSI2I, 1241~~UHHHI,a?X"lCNG PUN TI~ER SUPPlV FUNfTlON FOP ...411
}~i~2~z~~~I~~jgj~~9~~v~~Er~Nr,;~~~.AXl~~[7~~~Q~PT'T~S~ _'_,

355H - - - MANAGED APEA - - - - - - -

UN-MGO

,

;~~~OSTpr~NTATICNGAIN ~:~~'~fl~b23HCOSluSTOOIAlQUANTlljSTO:

tU~OI~lCU. FT. AGRIC M ACPES AGRIC "~Xl~~~~ER M CU'M"lCRE:

846HS

Ar HS

ACRES

M ACRESoI I

126 WPIT'=16,7281 fSlRfNNN,Jl,J-l,8t

128 FOA,.ITtlH ,8X,F8.2,5X,Fll.l,6f5X,F10.lI1

PlllrE - PRICF+IO.OO NNN ~ NN~'+l ~~\~~16~~2~?1 GC' TO 600

129 FC'RM6TIIHII

IFIIJ08.~0.31 GO TO 880

~

CQMPUTF lr~G-.llN MGT. PR ESC.IPTION FOR EOUIllBRllJO' FOREST

C

800 ~rR V?~91-~' Hp (-PAR \M I.IAl OGISlRI I, 211-PAR AM211

IFISlRll.lI.1l.SlPII,9 .. GC TO 802

PP~JCC' ~ ~lR.CJ,l)

GO TO 804

802 fC'NT!~UF

80~ N('I 1

806 PRICE: PPPICF

o0n0

808 808

,- I,ll J211,JJ

ClI,1I: FIll ('(I,Jl "" O. C t:AllONW(Ir,IP(V.PRICF,PHfS,ICUS. C r./tU .\r')JtJST( IT,QATf~,fAPI'l,P~NT,ClEAP)

rAt.lSOQl(ltl

TEST FOP '01l1l18PIlJO', USING DEMAND EOUA110N

OS I : O.

052: CIJ AlII.20I oCIJAIII, 11

on ~16 1=?,It

I( ""
O~ 1

I-I :: O~ 1 +

((, J IJ (K , 20 I.C ( JA (K ,

7 J

"11 mAI1~:~1 ~ ~r ~~~1!.~1$~~1~1 ~WOSn!.PARAM211
~~lC!J~Ull~\',21j.C(JAIIl,\qll GO TO 816

gRf ~ F.1~:l~l~fJI

~~?A::r.l~UHlm-P07l. IOS2-0SII1

IFIO'2.GT.CSll GC TC 812 PF = 002 OF : 057

"12

7rl~~,~H.o'll "0
pc = 0C;2

TO

Pia

OF : OS7-IIP'2-oCnoICOSIPfTA"SINIBFTAlII r,n Tt1 AlII
= 814 ~~TAP = eTAN2ftP~1-PSJ),(OS2-~SlI'
61 PHflO 1.1Ii707Q6326-RF TIJP

TH!=Tft, = RFTA+FlcT.AP

AlPHA = 1."1r7q6~23-BfTj

~~ ~ ~~~::~7~\~t~:~\:ll~~~:g8~l:~~~::~:~~~~~l~:t~:1:::: r.r Tf"'t 818
816 r:"~TI"lJc

8'0

r" ...,,, = ""0+ 1
I!=( .... n.r.T.7l

Tr 82?

f'JFlTA = PRtCf-PF

r.n cr 'F(A~C;COfl T"'I.l~.O.IIiO)

P=f""Of:lTIJ.r.T.'J1

Tn. A2e

(F rOE l T A.l T ~ 0 ~. en T0 820

DpqIr c :: PQICF-f.6*~~lTIJ

r,r Tn An6

= ~~~lTft.

~nFlTA.'

= op~,C~ PPlrr.-f.l*nFlTIJI

for' Tr') A()f.

'F(lJ""~~O.}1 r,r T('I A46

Ifl 922

WPfTC: lr,.'C:-QIJN MGT~ PPC:~CR(PTIO"" HlP rOllllIPPIUM F'1PFST

iQ\ f1 ':P4 ~~ T ~~:;=~ P~~~Y ~ pny, J, J=l, 2 RA Tf S It, PATF S( 1) ,PA TF fll r.f'" 1 ,P~Tr:C.O~.r.c; T1 8J<'

A'\ WPTTCI6.A"~1 (r"lrYllpOV,JI,J=I,lt,(RATfS(l(t,l'=l,",I,PPICc,PF,

lOF

RJIt H''1Q ... z\T(\ .... 1.1 Xdc;Hl:Nr.-QI~ TIM8EP MANAGH<lFNT PPFS(RtPTIOt.J,

~~;~1 ~~~.. ;~~J \p~ JV~ C; ~np :~r F'~~;l~l ~ '~i~~~i 4~~k Yt ~w~ FV l:{A't~,

1'H ,.c~~2, ~ .?3Hf:Olltl IBPIU'" PRt:~

.. ,F8~2,lX ,7HFCtlll fB,

416Hl)l'IJol CI''''I 'TV: ,CII.I./I

8?q W01TCI~'P'(,1

15

Appendix 1 (cont.)

8)0 FnRMATflH .14X.l~P,lqJ,lHO

H,lbX,lbHA W T Y S P,t

16X.52HP N Y S t l

AVG. LONG-RUN

CFlL

AVG. A.

ho 2~~HNN.

TCT. '~N.

CU"JlAT IVE

l~~~VE ~~~~IA T! VE. ~r~l62HO E PVI

'VG. 'NN. CUN\A.A T!.

TA

Yl ~~T

~~~~N AR~tR N cu~~: 'R~'ACRES ARg:/H:m'liE R /cu~ F~.

1~OH

N cu. FT.

0 ACRES

NACRES

N ACRES.II

K 0 SUNI O.

= SUN2 O.
SUN3 O. 00 844 tal, t I

YlO CIJUII.201*CIJ'III. 11

SUNI' SUNI YlO SUNZ SUNZ (IJAlII.ZZI

SUN3 SUN3 CIJAIII. 11 K K+l

IF IK.NE.501 (0 TC 838

832 ~~ 11~1 ~~U8~3g0~~Y~OV.JI. J-I. 21.RATE S 111. RATE Sill .UTESllI

1,PAtCE,PE,OE

.

GO TO 836

8." WRITE(6.828t fPnVfrPOV,JI,J-l,Z (R.ATESfll ,l-1,3t,PRICE,PE,

1 836 SSITE16.830'

838 0K0 - 83I 9 J-Z.5

iBm 1:1" 839 IOlJI - CIJAII,. JI
18IU :

UJ, 840
842

I~mm' ~~f' vHO
FORNAnlH .h.I!.5

1 1IX~c.'jZ~Il.l5~~X.~F~8I.IL!~. I~~9'1.~iFj1~.~A1lII.15.X1.1F.I

O.

I.

H.

844 1~~~fIN~~F9.? Zl!X.FlO. 3Il

C

f

IIRlTe roT ACRfAGE SUNNARV FOR EOUllI~RIUN FOREST

C

846 CAll ACCUNIII.PRICEI

C

GO TO 1850.85ZI,IPOV

8~0 lIP I TH6~854' I POVII POV.Jl. J-I.21.RATES Ill. RATESllI.RATES III

IcbRlo 85~' CE

852 "RITE(6te~. (POVUPOV,J.,J.t.21,fR. ... TES(KI ,K-l,31,Pfi[C:,PE,

8541~RNATllHI .3ZX,4CHSlJ'''ARV I()jG-RUN NANAGENENT PP ESCRI PT ION.

I23H FOR EOlJIlI. Z4X.11HINTEREST

RRIAUTNESF: Ol8lE3S1Tf,4I.II~HlXIXIFI6.H1P1O1I1NXT.~O~FPRVIICEEIIl:EVE.LZA4-.

.

mHR',j~8c3~~fimFO~HU~~~38X~~311--.; !._ 8:2:3~'m~w~:

555HREA - - - - - - -

UN-NGO

LOST TO

GA.

t~~N FROlll~H~o1:PLANTATI~~11C NAT. STA~8RIC'/4ij~~ll:ll:~:

855HRES

~ .CRES

NACRES

NACRES

9Z3H NACRES

" ACRES,/II

C

856 1-0

DOa6~Jl.ll!l

IFIt.EO.1I GC TO 860

858 ~~mtl~5~lz~:~h~L(~i~~H:mRII.KI.K-l.6l

GO TO 864

860 l l+l

WRITEC6. 862 Oll.Jll., .... l. 5.

862 FnR~AT(lHO.l0X,5A4./1 W'l:1 TE (6,8~8t fRC I,Jt.J-l,5' ,ISSRC I,KI,Kz l,6)

864 C ONTT ~U'= Crt TO (866,8681" IPOV
866 WIll Telb. 8541 IPCVII PO'V,JI,J-l,2 ),RATFS Ill. RATESt 1I,RATESIll

1~~~6~E:,pr:OF

GO TO nc
868 VR I TE (6,854' (POVe t POV,J I" Jat" 2), (RATES'K) ,Kz 1,31 ,PRICE" PE"

861

870

818 119.?Z

IFlI.F.O.19.0R.I.EO.22.0R.I.EO.27.0R.I.EO.30' G(l TO 814

872 ~~~~i l~ i~7~: 21~ ~l4~ ~l~; ~I~ ~:l~JR( t" KI" K-1, 6'

C,o TO 8T8 814 l l+l

.s9J 816 ~W~'llmTaE l16~T~lIc~(C~(Ut~,~JI},rJ-"t,5511. ISSRr ItK J. K'" 1, 6)
878 CONTI NUE

IIR ITE 16. 7291 880 GO TO I

END

EOUI VAle NCE 181U'K. SVI'll Cll." .1 CO NNA.S VN8011511 OAT A I FNGTH/801



.,OAIlGletli"OlH/2O01,lHl,lH2 .tH]. lH' ,I H5 ,lH6.IH1, tH8, 1H9 ,5 *0/



SYJllfla./l~ IH-. HI+.IH ,tH,1

C

C

INITI'LTlE SOR. PAPAIlETERS

C

C IF vIOnuTI-II5I SH TO READ FRC" A DEVICE OTHER THAN 5. CHANGf lOT I

W!"'RO=O

GOTTFNO

POI ~T-O

DC 5 t-t,ILlC'W[

ANSlIERlll =0.

C

C

HAD IN T~E STRING OF CHARACTERS

C

10 RFAO II0Tl.I~I ISTRINGIIETTERI.IETTfRI.LENGTHI

I~ fORNATl80Al'

.... 1~~6d8vElml~:W~fMlH!T~~EI~~~G~~~EACH CONNANO

16 fOOATllH .80A\I

C

C

OETER~INF. THE FIRST NCN-BlANK CHARACTER AFTER A 8lANK

C

OR COON'

C

ZO fIRST-.TRUF.

30 PC'HT~POtNT+l

IFIPOINT.GT.IE~G'HI RETURN

IFISTRINGIPOINTI.EO.8tANK.CR.STRINGIPOINTI.EO.CO .... AI GO TO

IlO

IFI.NOT.FlRSTI GO TO 30

FIA:ST-.FAlSC:

C

l

CHECK Fnp A ~U"BER

O(l 35 INOEX-I.5 01 GI TIl ~OEX+10 I-SVN8011 INa EX' 35 CONTlNUf OIGITS-O E.PO NUN8E.-O
50 ~l,GroIINOEX=1.15

14b~ ~b:~S~~~~~~~lo~i o~ \~A~i ~m; '~bE~ 0 TO (q O. 90 ,90. 90. 90.90.

60 CONTI NUF

IFI GO

OTOIGzIoToS.

GT.

O'

RETURN

18 all'iilNOEXI.OIGITI II

GO TO 110

90 mmm~l;EH (-0 TO 100

.. 0IGITI121-0IGITIII
100 ~~~mM mlibHNoEx-,

IFIOIGITllll.NE.!VOPCllllI EXPEXP.I ItO pntNT=pnlNT+l
Gr TO ~O lZ0 GOTTEN-GOTT",'.I
tFlr~TTfN.l~.AllOWO' ANS~EPIGOTT=~'zSIGN*NUMe~R/IO EXP G~ TO 20

CHECk Fn o a I(fY'WORO GIVEN THAT I S NOT A NUM8':P

on 200

110 wr~n=1.20

Zl" 215

210

7}0
2~0

GJ TQ 2~0

Subroutine REPLY

........................................................ .. SU8ROUTINE REPIVIIIST.1I0RO.aHSIIE,.GOTTENI

r.

C

VA'IA8IE OEFI~ITION

rC.

AllOI/O

THE ~UR8ER CF NUR8ERS THAT RAY 8E READ

_

C C
~

ANSWE"
~b~:
DIGIT

: um:t AN ARRAV OF THE NUN~ERS REAO ~~~~~
AN 'RRAV (IF CHARACTERS lEGAL IN NUN8ERS

~
t

DIGITS ~~trH

THE 'l\)IlHR OF OIGITS I~ , NUIl8E' ~H~lIm~T~OJN~~A!hmTR~A~Or2 IS NOT A HYWORO

C

XP

T~E EXPrJ<F.lH fOR RlACTIONAl "RTS OF NUN8ERS

........................................................... ~

"IRST
Gt!TIF.~

A SIIITCH TO INDICAIF. A NEll IIORO OR NUN8ER T~E NUNtlER OF NURseRS FOUND

t ~~~J

~~~TKH.Arolln~, NUN8ER RETURNEO

C

C

tNTFC-:R l~NG TH



III CWO .~l.N'



trfrllfrllA



.OIGtTI151

*

.01G ITS



,(

~n' ;l1TTfN



,t 15TU'


:

,.:PS~O'~IGN~~IT lW?1



WOQO

REAl 'NSIIEPI201

lOGICAL OONE



,FIRST



,KFYf20J

Subroutine PNW

SURR1tlT'~t: P'-W(I f .IPr".p~,rC:.RATt:S. JrlJS

l3 ~~~~~~ 1h~ 8 ~ ~ t ~~ I. PP fl.W n) Te2 ( 3. 1 Dt ~ 1

n"
Q AT

40 1= ~= D.aT

1.' I=S t

rI

(

1.7.

II

1~(lpnv.~c., I oAT~=I:lATfC;lll

(

('

rnloU'IuT:: pf'lCC;c .... T ""C:T W~PTH

r.

r')~ 1 C 1 T= 1. "\

N)'T=,( P-ll

O('T=r:(T.II)+~XTI
(:rN S T= (F XD t 0 ( T.... ( At nr. ( I. + P ~ T Fl I J -l

OPJ.i;r( IT 1=( (p~Yrc.((( t.8+~JX1"1000.))-rt! ,9+NX111/C["lt\lST

TT T I " " (

l=oCl~().qQ

Ie 1~ I r IT. q +NX T I .l T 011 G(, TO 10
Tr 211 TI = (( ( I .9+fI. )Crt I T .A +tl:XT I ) *1 Of) o

In I"'(INT!'HJC:

P= Ie I J,,., I.(.r .l~. 1 PONW 121 =-Q999. Q 9

<:cU:I"'1' r'PTtN' WITH ~AX''''UM PPfSfN1' N!=T ~C'cH..j

I"'tr 20 ! 1':1."

20If'llfT)=(fl.ITI.C.":

~

I~ (U<:1rOHl HSTo'rllr~---> rUST('{)1Al

tFflr.tJC;.EO.l.t,,'r.IC(;::I.FO.~1r.P 1Q ':liS
XIo4AX=a.ftI1AXlff'ON"111.PP~W(2) ,PR~",n))
nr 30 IT=l.:'

IT = 1 = PI H .. HTIC" "'~r\IGf"'fNT TT = ;: = No\TUPAl --U"-O "6N&r.E"'~NT

16

Appendix 1 (cont.)

C

IT 3 CUSTODIAL ~ANAGE~!NT

C C

I' PNwaOl ~U~ OP COST> PAICE ---> NEXT ~GT LEVEL

C

IF IPA"" lIT I.L T .X~O .CA TC 21 ITI.GT .PA ICE I. AND. IT .NE. 31 I TO 30

GO

CII,\71- FlOArllTl

ClI.18'- PANWllTl

ClI.l91- TOIITI

IF I PA~WlITI. GE .X~AX .AND. TC 2IlTl.LE. PPICEI GO TO 'to

10 CONTINUE

GO 10 40

15 ClI,\7I 3.

ClI.181 PA~W131

CII.19' 10131

40 CONTINU'

AFT~N

FiNO

Subroutine ADJUST

suaROUTINE 4rJUST( t "RA lFS ,FAIU4,RENT ,e LEAR'
gf=~2~15~8l~,~~I!r~~lt~lt:l~l~~TI18,.CLEAAI3.51
Ol~ENS ION 10161

00 45 I-I.ll

r6J~ ~-~lL,

I ra CONTI NUl'
Inl8lij :~~: i

i8 ~8

IFII014 .NE. 2 GO TO 20

IFI lOI61.GT.201 GO 10 10

C

E

POTENTIAL ACHAGF LOST TC AGAICULTUAE
: m~r ~mfln~HI!A~~~Q~mm\Al~\~1 3111

I< I AOJUS.LE.O., GO 10 20

IFIAOJUS.GT.I.I '[JUS - 1.0

EI\;2~1, : m~Un~~~~!~1611'ClI,7I1

GO TO 20

;:

POTENTIAL ACPEAGE GAINEr FAO~ AGAICUlTUAE

C-
10 ANHEQV RATE5IJJ*CII,18.

AOJUS IAFNTlIOI61-201-ANNEQV'/AENTlIOI6'-20'

1~I:g}~~:rt:~i!ofOA6Su~5.-1.0

Cl I, 71 = A8SIAOiUS"CI I, 71

7' iiolf~4~0= CI T. 7

15

c( nn

,
,

191

ClI,20'

= o.

:z=
=

qqqq.qq
o.

glt~2lo' O.

20 25

~o'Tbl 12~?!0 ClI,20' = cd

,35181~/C

l

I,I

01

CIT,22' ::t (I It lJ/Cft.lO'

GO TO 40

30 CII.201 (11,\IIIC(I,I3'

ClI,22' = CII, 1I/ClI.l31

G" TO 40

11 ~5 C( 1,20' ... CIl,l<ttI/C ((,16'

~O

\12~lcil~\~1 711CII,HI

JA t 1 J :c ,

45 (ONTJ-"Ut:

qFTUR~

F~O

Subroutine SORT

SlIRttOUTI PIIt: C"'''''"I)N C (R

5C" 12.'

10,)
4., Af

e12

J

JA

t

812

J

r I

l O t :: 2 1f t

IFfY .lC:. ~. r,fl Tn LO

flit = , - I

lO III = ""/2

= IFf" .~O. n) 0E"TlJPN
l N - ...

nn 40 J= 1, L

OC3nJl=1.J,!IIl

1 1/114

""

=

J

+ 1+

1M

Jl

1Ft A(l W ' .('.E. AI til Gn Tc 40

Tl:"'P = "111

A~ (llI""I = AT(F':"~PI

JTE:loilP = Jf.(ll

J"l tI = JA( '''''I

30

rJrf""(rT"!'

)= rvUF

JTF"P

ftn (f"NTr",,"F

r,r TI') ~l1

~"ln

Subroutine ACCUM

$1l8pnUTINt= AC(U .. t Jl.PflIC~1
((' ....or..; r. (RI2.''''t,1J181?I.JAI81Zt,SSO 13l,6)

nn e; 1:: 1. ':lit'

nr ') J=l. 6

rr r; != ')D

J) :: f'.

t, r)r'l f.l 1= I.

~r 61 J=l. , r.r rr"l (1l1.1tS.?C,7'5,30I,J

1 0 1 Fir I J AI! ) f, I. r; T .20) (,fl T'1 11

CIJ6(!I.61

Gf"I Tn ~C)

11

Ir(on

::

CIJAI Tf'l 3!i

l)

.

tl-

20

Ie; I( = CtJ.&,(l) .;'+!'E

f;r> T'1 31)

20 K CIJAIJ1,31+21

GO TO 35

25 K CIJAIIl,41+2f

GO TO 35

30 35

'Ficiltfll: lil~I~,

40,45,5C

PLANT All ON ACAEAH

40 SSP IK.II :& ~5R(IC,I).C(J.6II'.71

GO TO 60

NATUA'L ~TANC ACPE.GE 45 SSA IK .21 :& 5~PIJ(,21.CIJ.6111,1.
GO TO 60

50 IFICIJAIII,l91.GT.PAICE' GC TO 55
SSA ~~~~~O! A~Sm ;~~~ ~~m I ;~VI LI,8AIU" PAl CF

GO TO 60

CUSTOOIAL ~C'E'GE A8CVE EQUI1I8AIU~ PAl CE
55 SSA1~~UGE HHKt~I~~~muUn

60 SS'~~nGE ~~mr5H6~JW\~l}UAE

SSR (K ,61 == SSRII<,61.CIJ.6II 1.2ftl 61 CONTINUE

AETUAN END

17

Appendix 2 Output of Sample Problem One

AVG. lONG-RUN COST
PFct JlII CU. FT.
25.00 35.00 "5.00 55.00 65.00 75.00 85.00 95.00 I O~.OO 115.00 125.00 135.00 '''5.00 155.00 165.00 175.00 185.00 195.00 205.00 215.00

ICNG RUN TIMe~p SUP PI Y FU NCT ION FOR GEORGIA

FOINT OF VI EW: PRIVATE

INTEREST RATES: 0.03 0.0" 0.05

FQUIIIBRIUN

NANAGED AREA

-----

UPr-MGD

QUrA:VN.TITFYT.

PIANTATIN N AC RES

NAT. STANO N AC RES

CUSTOOIAl N AC RE S

CUSTODIAL N ACRES

916B.B 52621.7 209123.3 522617." 911891.3 1239009.0 1389105.0 15"8521.0 '674'191.0 1808"9".0 2023355.0 21182"0.0 2215979.0 22"7206.0 2322HI.O 233870".0 2H8702.0 2376867.0 2393719.0 2"OH23.0

0.0 O. C 277. I 1"68.6 2592.4 330".9 38"7.8 "5"02874..5~ 5761.3
mn:1 9300.6
1"358. ~ 1"911.1 155369082..6E 17123.7 17212.8 17272.6

0.0 26.5
8" 17 0" .. 82 2903.5 4248.0 5250.1 5999.8 6732.5 7227.1 6509.6
~m:2
3758.2 3821.9
3H5720"..3" 2109.5 2257.5 Zlt2".5

53.6 517 .5 129".6 2007.8 2281.4 3668.1 3319.6 3713.1 3668.9 "029.6 2927.9 2831.9 2620.7 2911.9 3Z1t6.6 3182.9 311". I 3068.8 3025.7 2905.7

220"1.9 21608.6
m~u
1"692.4 11404." 10"07.8
8883.1 7699.B 6317 .6 "708.2 3651.0 3039.5 2551.7 16"5.8 1560.1 1519.5
1"52." 1290.4 120".2

lOST TO AGRIC
~ ACRES
1135.7 1078.7 1021.9
925.6 762.0 611.4 "58.5 327.5 ZIt 6. 2 182.6 15".0 1"7." 1"1.2 IH.9 128.6 122.2 116.5
99.1 88.3 81.9

GAIN FRO" AGRIC
N A: RE S
0.0 0.0 0.0 0.0 0.0 4.9 51.9 119." 200.0 286.3 368." 1tl3.2 ""8"35..5" 521.9 556.5 591.0 621.5 6"2.9 656.9

ICNG-RUN TI ~SER NANAGE"ENT PR ES CR I PT ION FOR EQUILIBRIUN FOR ES T

F[J H OF V lEw: PRIVATE

PRICt: l EVC:l

95.35

EQUIIIB~ IUN PRICE

P

0

H

A WT Y S P

0
0

~

Y P

S I

rI

I A

C

E0 E N

1 3 2 2 10 12

I 1 1 3 2 3

1 I
"I "2 I "2 "3 2

2
,2
2
3

3 3
~
3 1 2

, 5 7 1 2 2 I

~ 2222 I

9 353

3

I 7213 3

A352 I 3

IZ 1 4 2 ? I

" 9 I

22 I

8 I 422 1

I~
15 1< 18 17

" I

2

7 53

252

72Z

152

2
,22
2

I 3
,3
7

9 7~323

, 0 Z 5 2 2 3
Il 2 4 2 2 I

6

223 3

15 11 16
8

,2 1

35

3

5 5

2 2 3 2

~ ~
I 2

~ ~
3 3

I17'
n15

2
~
3 3

5 I I 3

3 3 3 2

~
,~
3

~ ~
3 3

17 3 1 2 3 3

nI
14 I
IR
q
6
,?
10
,l ' 5

7 l 2 I 3 3 3 2 2 3 I 2 3 I

4l
"2
53 2I I3 42 43 43 72 53 31 42 33 3I

I 2
,l
3
I 1 I 3 2
,J
I
,'\

3
,3
3
3 3
,3
3
,J
3 3 3

, 13 2 5 2

3

'4 3 5 2 I J

5 333

3

"Vr.. clf1rNqG-PUN oE R "" cu. FT.
89.B9
8q9o..A~99
90.49 9 I. 01
(1l.1i)
91.59 91. ~q 91.c;4 92.16 92.116 '013.31 93.37 93. ~1 93. '!7 93.4B q3. itA 93.63 94.61 94.68 94.68 95.1' 91.41 OS.36
q~.!7
98.84 100.15 tl')O. '.:9 100.72
too. E~
lOt .94 107.00 107. ~o 103. Co 103.21 104. I3 104.66 104.71 104.11 105.06 lOCi. ~~ 105.90 106.05 11)6.51')
10'.74 tr!7.24 107.'5 107.65 107. PO

CHI
AR fA Arl:lES
18." 181.7
58.2 59.6 37.1
3.2 H"..3B "2.3
8.2 lit. 5 "'.9 15.0
8.3 0.2 2.6 10.0 37.4 3.0 8.6 42.0 . 31.3 29.7 2.3 3.3 30.2 38.2 4.7 8.5 J.4 1 ~.9 29.5 ~. 3 20.1 39.3 4" 5.5 97.0 7.9 3.4 2.9 7.6 5.4 ~. 8 3.J 9.1 7 5. 7 10.3 3.7

AVG. ANN.

cu.

YI [10 FT./

ACRE

36. , 36.1 35.9 72.5 100.B 73. B 100.8 100.8 7 8. 2 "0.7 54.7 9Z.\ 92.1 92.1 92.1 5 B.O 58.0 98.1 34.3 58.0
1500B..Oe
4t.9 41.6 46.3 60.7
50.~
4369.. 9" 48.7 3 I. 0 39.4 "8.3 3 ~.4 39.4 27.6 91.9 48.3 48.3 48.3 5 O. 8 51.5 27.1 48.3 "7.8 26.8 33.9 47.9 5 1.3

INTERFST RATES: 0.03 0.0" 0.05 S 95.06 EQUILlBPII" QUANTITY:

TOT. ANN. YIELD
" CU. FT. 662.5
6558.5 2090.9 432".5 3735.9
238.0 "81.1 7"82.3 3309.0 333.3 1887.6 1371t.9 1382.6 760.6
19.3 I"B.2 579.9 3t69.6 103.8 501.2 2"36.7 3158.4 1390.8 95.6 154.3 1831.6 1927.A 219.3 ~40. 7 163.4 "30.7 1162.7 256.3 710.3 1548.6 112.8 502.2 4686.6 3AI.9 163.1 146.7 389.8 146.8 230.4 143.1 243.1 869.8 495.4 187.4

CUNUIA T IV E YIElO
N CU. FT.
1508122 .0 151"680.0 1516770.0 152109".0 15Z1t829.0 1525067.0 15255" 8.0 1533030.0 153633 8.0 1536671.0 1538558.0 1539932 .0 1541314.0 15"2074.0 1542093.0 15"2241.0 15"2820.0 15"M89.0
tm6~!:g
1549529.0 1552687.0 1554077 .0 1554172.0 1554326.0 1556157.0 1558084.0 1558303.0 155861t3.0 1558806.0 1559236.0 1560398.0 1560651t .0 1561364.0 1562912.0 156302lt .0 1563526.0 1568212.0 1568593.0 1568756.0 1568902.0 1569291.0 1569437.0 156C?6b7.0 1569810.0 1570053.0 1570922.0 1571417.0 1571604.0

AVG. A'i~. AREA
N ACRE S

0.216

2.137

0.685

1.35~

o1

.426 .OB I

0.184

Z.856

0.769

0.186

0.627

0.2.5

O. Zlt6

0.135

0.003

0.0"6

0.182

0.935

0.036

0.157

0.764

1.205

0.674

0.052

0.061

0.549

o0..O69B46

0.19"

0.076

0.316

0.671

0.096

0.H5

0.115

0.052

~:m

0.144

0.061

0.066

O.13B

0.069

0.087

0.076

0.115

0.466

0.188

0.083

1551695.0
CUMUlATIVE ANN. AREA M A: RE S 373.2H 375.381 376.066
377.~21
378. B47 378.92B 379.\11 381.967 382.136 382.922 383.550 383.194 38".040 384.175 384,\79 384.225 38".407 385. H2 385. 377 385.B4 386.298 387.503 388.177 388.?29 388.289 388.83B 389.532 389.618 389.812 389.888 390.203 390.8H 390.970 391.335 392.050
m:m 392.101
39".133 394.194 39".260 39".397 394.466 39".552 394.628 39".743 395.209 395.397 395.480

CUNUIA TI VE AREA
NACRES
13500.898 13682.5H 137"0.813 13800."61 13837.531 I 381tO. 758 138"5.531 13919.781 13962.094 13970.281 "'00".789 14019.711 "'OH.715
t~m:m 1~g;~:m
14093.121 14096.1"5 1410".785 14146.797 "'178.137 14207.789 14210.086 14213."'8 I 421t3.590 "'281.762 1"Z86. "96 "'295.031 "'298.383 14312.273 14Hl.781 1"3"7.086 14367.lIt8 14"06. "53 14410.539 lH16.004 1"513.031 I1t520.938 14524.313 14527.199 lIt531t.766
14540.18~
I 4541t. 949 14548.293 1"557.363 14583.020
14593.35~
14597.012

18

Appendix 2 (cont.)

p~tCf lfVEl

SUM"APY LDlG-llUN "NAGEMENT p'eSC'IPTION FOR EQUILIBRIUM FOPEST

P~INT OF VI Ell: PR IVAn

INTfREST RAlfS: 0.03 0.04 0.05

~5.35 EQUILIBRIUM PPICE

S ~5.06 EQUILIBRIUM OJ.NTITY:

L55L695.0

PL~Num~

MAN.GEO ARF' - - - - - - -

N'~'Am~o

c~smgl

UI+-IOGO CUSTODIAL
M 'CRES

LOS T TO 'GRI C
M 'CRES

G'I N FROII AGRIC
M 'CRES

,POC

COOSA V.llEY NORT H GEOPG IA GEORGIA M(lJNT'INS '71ANTA METRO NORTHE.ST GEORGIA CH' TT'HOCHEE-F!I NT ~~=~SH TR'IL

C,NTRAt .. IODlE

S'V'NN'H GEORGIA

R.

"IOOLE FLINT

LOWER :H'TT'HOOCHEE

HEART OF GEORGIA .LT ....H.-<;EORGIA

so.

~~~Y~[S~~~2RGIA

SL'SH PINE COA STat

OIlNl'RSHI P

PUllllC IIlUSTRY OTHER PR IV. TE

F ORES T TV PE

LONGLEAF-SL.SH L08LI1.L V-SHORTt E AF OU-PINE
~~~~L~~~~~~OOCS

PHYSIOGRAPHIC Cl'SS XER rc lIES IC H'toR IC

SITE CL'SS HIGH "EorU'" LOW

L67.9 76.0
227.5 0.0
419.8 291. ~
72.0 384.' 501.3 218. 1
1~8.2
213.4 360.3 311.1
3~~:i
e !40.0
I ~~. '2.9
1200.0 3222. 7 1192.8 2061.9 870.7
340.2 0.0
113.4 4097.4
254. ~ 4170. t
295.0 0.0

36.6 41.5 100.2
2.0 0.8 35.0 0.4 586.5 813.5 420.3 315.5 447.4 377.L 552.0
m:\
1268.4 203.5
653.3 1920.5 3426.1 247B.6 1839.2 1649.0
0.0 B.O
173.9 5300.0
525.9 260.7 5611.4 127.7

362 .3 230.6 355.3
L.3 349.0 64701
0.1 75.7 114.6 L47.2 189.0 28.8 236.3 445.6
3H:~
105.5 71.0
755.4 653.5 2304.3
941.6 1549.7
47.8 540.3 6B.8
512.2 2673.1
527.8
560.1 3094.4
5B: 7

762.0 6L8.9 729.6 520.3 4'01.1 608.L 279.3 287.5 675.3 207.6 222.L 246.0 324.e 440.6
m:~
509.9 920.6 120.0 1465.1 7266.9 525.B 981.9 1231.0 3792.2 2321.4 939.2 6295.2 1617.7 971.7 6611.1 1269.4

0.0 0.6 9.4 22.8 1.2 0.0 8.3 17.3 32.5 11' ..59 13.6 33.5 28. B 68.1
t~:~
4.B 0.0 0.0 323.6 86.9 22.8 37.3 104.2 72.4 0.0 323.6 0.0 323.6 0.0 0.0

40.9 5.9 0.0 0.0
15.1 58.5
0.0 1.8 0.0
8:8
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 122.1 0.2 121.9 0.0 0.0 0.0 0.0 122.1 0.0 122.1 0.0 0.0

19

Appendix 3 Output of Sample Problem Two

~Vr.. l rNG-OU~ r."5T
PEP ~ CU. H.
25.00 35.00 45.01"'l 55.00 65.00 75.00 85.00 95.00 105.00 1 15.00 125.00 135.00 145.00
155.0~
165.00 175.00 185.00 195.00
?O5.~O
215.00

l[NG RUN TI Mq,:p SUPPLY FII"CTION Fr;R GEORGIA

D"]',l OF \IH:

.FOIl Tl I ~p Ill"" OtlA.'ln lY (IJ <T.

"lANH- TIP'" H AC RFS

P~tVA.TJ=

UH ~ P FS T PAT fS: 0.03

pr.lA.NA G~O APF A ~'tT .. STH!D H he- RC S

---- -
CUS TPOI'l ~ 6cof S

0.04 0.05 UN-MGO
[US TOOl AL ACRES

n e ~R.
57621.7 207673.7
3q6taf,.~
6172".4 772776.9 841R03.1 Q71401.E': 1030480. q 1111016.0 1173714.0 12075"'.0 1247077.0 12'19520.0

C.O C.C 277.1 7155.3 841.5 943.4
9U.3 1211. ~ 1505.7 171f:.2 3047.2 3686.4 ~71lt. 1 3718.7

0.0 26.5 391.4 549.7 1835.8 2161.3 2253.1 2573.8 2662.5 2896.6 1876.8 14Sj4.Z 1656.6 1707.2

53.6 517.5 1317.2
248~.4
Hon.4 6011.0 7069.3 8744. I 9114.3 9969.6 10591.3 11107.0 11546.4 12230.3

22041.9 21608.5 20223.6 18HO.7 15542.8 13261.1 12143.9
9958.2 9259.3 8014.7 7137.1 6457.8 5833.5 5140.2

1328126.0 1340655.0 1357301.0 1375715.0 1395967.0 1401138.0

:!71 8.7 4112.2 4281.4 42ET.3 4315.7 4320. I

1719.6 1415.2 1307.9 1354.5 1393.7 1393.7

13169.1 13236.3 13459.9 13927.3 14401.2 14492.3

4234.2 4121.8 3873.0 3391.2 2880.7 2824.1

lPST TO AGRI[
H ACPfS
1135.7 1078.7 1022.2
966.4 910 .6 854.9 799.1 71t4.1 690.0 636.1 589.8 545.8 508.9 472.6 436.5 401.5 368.2 335.2 302.4 270.3

(,A IN FPO" AG' I C
~ A(DES

o. a

0.0

0. O.

0a

0.0

0.0

0.0

0.0

0.0

1.4

10.3

19.3

28.2

37.1

46.0

55.0

58.5

58.5

61.8

68.7

lONG-no. TI.BER MANACEMFNT PoFSCFIPTION FOR ~OUILl8PIU" F ORES T

PPI NT OF VIEW: PRI VAn

'>ICc LEVfl

204.43 ECUI1I8RIU. polCf

P

" 0
A WT Y

P

P NYS

I

0
~

Pf

P E

I J

A
~

5 3532 3

6 35323

15
15
9 9 1 18 2 16
,13 7
7 14
9 15 9
9 15 IR

3 3
,3
3 3 3 3 3
,3
2
,3
3 3
,3
3 2

4 4 1 4 4 4 1 4 5 4
,2
3
1 1 4
,2
5
5

3
,1
2 3 1 2 1 3 2 2 1 2 1 3
,2
2 1 3

2 2 3 2 2 2 3
,1
3 3 1 3
~
3 2 3
,1
3

,3
,3 ,,1
3
3
,1, ,,3
3
,,33

15 8 5 8 2
,17
17

3 3 3 3 3 3 3 3

3 5
,4
4 4 1 3

1 3 7 2 2 7 2 1

,~
1
,3
I
'\
3

1 3
,3
3
1,
3

10 \e
,3
15
18 q 7 b
,2
16
1,h
18 18 11
I 14

3 2 3
,1
,2
3 3 3
,3
3
,3 ,3
3 3

4
,5
3 4 5 3 3 4 4 1 2 3 3 3 5 5 4 4

,2
3
,2
1
,,1
2 2 1 7
,2
7
3 2 7

3
,,2
I
1
2 7
,1
,;> ,,'\
,,,i

,3,3 ,3
3
,,33
1
,,33 ,3
3

AVG. , (HoIG-RUN

pc.

CO'f fill rUe

FT.

196. ~2
l'l;'I7.~.
700.29 200.29 701. f5 ZO~ .. 09 203.00 20'.98 ~04. 20 .04.54 704.76 2"5.41 208.17 710.15 212.97 213.51 114.68 216. e3 ]17 .. ~O 217. Rh 119.28 ]19 .~5
221. '6 227.79 77'5. '::0 725.77 127. C2 212.04 233.66 24('1. ?7 243.48 244. PO
74~.R~
248. f')R
lc;O .4i7. 751.':0 2')4. l7 759.C8 267. 7 ' 2"'7. ':2 268.15 il6f1 .Bb 769. PQ
277.~8
273.23 777.66 278.14 281.47 2A'3. ?3

CFIl
""p fA
" HFFS
19.0 34.4 12.2
7.9 32.7 208.7 26.5 95.1 10.1
4.1 35.5 10.4
2.3 24.3
4.9 7.9 ~ .15 180.4 7.2 3.4 4.1 4.3 ~ .6 7.8 101 .. 9 @.4 1 C. 2 38.7 10.2 le.5 11.0 45.9 "'9.0 30.5 e.7 66.9 7.7 61.4 4.0 75.0 30.1 17.7 ~. e 87.0 40.0 24.6 :3 .7 68.1 ~.'"

AVG. AN"'!. YI ElO
CU. FT./ACPf
40.6 33.4 35.4 35.4 24.7 35.4 35.4 31.6 4701 46.3 29.3 22.2 40.7 54.6 50.0 16.7 23.2 32.7 22.9 33.0 22.4 46.3 22.1 22.7 35.4 22.4 28.9 25.0 17.2 27.3 22.4 "1.6 46.8 19.8 ,. B.? 55.2 19.6 41.1 25.1 3 5.4 15.5 42.8 15. 1 41.2 35.7 50.0 16.4 22.9 1 8.7

INTEIl:EST lUTES: 0.03 0.04 J.05

". 204.10

EOUILl8RIUI' ~UANTITY:

TOT .. ANN.
YIElD CU. fT.
770.1 1148.4
432.3 279.9 807.6 7389.7 938.3 3098.5 475.1 191.6 1040.3 231.2
93.1 1329.2
242.8 132.2
80.7 5900.1
164.6 112.7 92.0 198.0
79.7 177.7 3605.6 188.0 295.5 967.6 174.9 504.6 246.5 1910.3 2794.2 604.1 395.1 3695.4 150.8 ;>522 .0 100. ,. 2 654.5 476.5 757.7 104.5 ? 6 71. fI 140R .0 1227 .8
52.4 1559.6
65.1

CUHUIAT IVE YIElD
" CU. FT.
1379915.0 1381063.0 1381495.0 1381714.0 1382581.0 1389970.0 1390908.0 1394006.0 1394481.0 1394672 .0 \395712.0 1395943.0 1396036.0 1397365.0 1397601.0 1397739.0 1357819.0 1403719.0 1403883.0 1403995.0 1404086.0 1404284.0 1404363.0 1404540.0 1408145.0 1408332.0 .1408627.0 1409594.0 1409768.0 1410272.0 1410518.0 1412428.0 1414722 .0 1415326.0 1415721.0 1419416.0 1419566.0 1422088.0 1422188.0 1424842.0 1425318.0 1426075.0 1426179.0 1429850.0 1431258.0 1432485.0 1432537.0 1434096.0 1434161.0

AVG. ANN. AREA
" AC RE S
0.3~5
0.625 0.222 0.144 0.143 3.795 0.482 1.733 0.229 0.075 0.646 00189 0.052 0.553 0.110 0.180 0.079 3.281 0.163 0.062 0.093 0.078 0.082 0.142 1.852 0.153 0.232 0.704 0.231 0.42J 0.200 0.835 1.114 0.693 0.149 1.217 0.175 1.395 0.073 1.363 0.699 0.401 0.154 1.976 0.909 0.446 0.058 1.238 0.065

1394268. a
(J.UlA! IVE INN. lREA H l:US 480.321 480.946 481.168 481.31Z 482.055
485.~50
1t86.. 33? 488.115 488 .. 344 488. 419 489.065 489 .. ?:ljlt 489.306
489.~59
489.969 490.149 490.228 493.508 493.672 493.734 493.827 493.905 493.986 494.128 495.980 496. 133 496.365 497.069 497.300 497.719 497.919 498. 754 499.368 500.562 500.710 501.927 502.102 503.497 503.569 504.932 505.631 506.033 506.187 508.165 509.073 509.520 509. >78 510.816 510.881

CU.UIAT IVE UEl
" lCRE S
19637 .809 19672.191 19684.398 19692.305 19725.000 19933.746 19960.25J 20058.301 20068.387
~8m:m
20118.441 20120.727 20145.070 20149.922
m~l:J~
20341.738 20348.926 20352.340 20356.441 20360.715 20364.32' 20372.145 20473.996 20482.387 20492.609 20531.309 20541.473 20559.957 20570.957 20616.875 20665.895 20696.402 20704.582 20771.527 20779.219 20840.578 20844.574 20919.559 20950.297 20968.00' 20974.781 21061.789 21101.789 21126.344 21129.535 21197.637 21201.215

20

Appendix 3 (cont.)

SU""''''' lOiC-RUN 'UN' CEMENT PR ESCR [PTJON FOR EOJlllBR[UM FOREST

PRICE LfYEl

POINT OF YIEW. PR [YAH

[NTERE ST RATES: 0.03 O. O~ 0.05

s 20~.~3 EOU[lI BRI UM PRICE

20~. [0 EOU[lIBRIUM QUANTITY:

13H2b6.0

PlANTATJO~
" ACOES

MANA CEO AR E A NAT. STANO
" ACRES

CUSTOOI Al " ACRES

UN-MGO CUSTOo[AL
" ACRE S

lOST TJ 'GRIC
" ACRES

:;AJ N FR.OM 'GUC
" 'CRES

APoC r.DOSA VAllEY NllIlTH GEORGIA GEORG[ A "IlUNTA[NS ATlI,..T" METRn NORTHEAST GEORG[A CHA nA HOC HEf-F 1I ~T "C[HJSH TOlIL OCONEE CENTRn SAYANNAH R. MIDDLE GFORGIA "loOlE FlI'lT lOWFR CHI,TTAHeOCHEe HEART OF GEORGIA alTANAHA-GEoRG[A so. ~~m":[SkmRG[A SLASH PINF cna STH
'lWNf;A ~H' p PUllllC I '10 UST' Y OTHeR PRIVATE
FORI;ST TYPF
g;~~~~:~h~~~lEAF
nU-PI'lE UPlAND HAROWOOOS e~TTn~lA~O HAAOW(COS
PHYSIOGHPHIC CLASS XlR IC "1-::S1C HlfODJC
S,~ rUSS H[GH "EO 1U"l lm.

156.~
ICC. q
~B.7
13.0 186.6 276
2C.1 210.!
397.~
201.3
m:~
23~.6 ~25.0
m:~
773.0 ~78
~1.!i ~258.2
O. C 1763.C 1209.0
709.1 63~. 7
0.0
1~.2
3859.5 316.0 957. q
?318.2 39.6

5'.2 50.6 170.1
2.3 19.6 '1.6
1.6 101.3
76.7 64.0 40.9 117.6 35.3 81.1
~~:i
2'1.5 212.9
888.1 505.6
0.0
2~.5
'23.5 262.2
~6. 4 'IS .1
196.' 867.7 329.6
383.8 824.3 185.6

972.1 S05. B 660.9
1.0 877.7 1220.9 168 .~ 958.7 152a.0 722.4 734.8 568.5 1028.0 1205.6
li~U
1011.2 308.3
625.9 344.0 13389.5
3107, 0 4370. , 2222.6 2491.1 2162.7
8'2.5 11513.6
1998.5
0218.5 9605.7
535.'

107.9
30~.3
537.9 507.3 112.9
'8.9 167.1
16.2 97 .~ II .J 30.5
11.~
17.9 '0.6
m:i 99.' 396.9
0.2 131.1 2788.9
41.3 339.0 59'.0 1512.0 433.9
559.6 2078.5
282.2
361.5 1863.6
695.2

0.0 0.2
~.,
22.8 0.0 0.0 2.2 2.7
45.7
266..6'
2503 16.3 25.9 68.7 38.4 15.6
3.1
0.0 0.0 304.3
67.8 53.0 48.0 86.7 48.8
0.0 304.3
0.0
304.3 0.0 0.0

2.8 0.0 0.0 0.0 0.0 58.5 0.0 0.2
g0..o0 .0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 61.4 0.0 61.4 0.0 0.0 0.0 0.0
6A:~
61.4 0.0 0.0

21