2-inch diameter classes. Projections are made by simulating 
annual changes in timberland and numbers of trees. In 
contrast, the Timber Resource Inventory Model is an area- 
based, yield-table system that projects acres by detailed 
strata for periods consistent with inventory stand-age classes. 
In this study, 5-year age classes were used. In the Timber 
Resource Inventory Model, the inventory is represented by 
an array of acreage cells classified by region, ownership, 
management type, site productivity class, stocking class, 
management intensity, and age class (table 3.1). Acreage 
is shifted among the cells, and volume and growth estimates 
are derived from acreage movements through assumed yield 
tables. The Timber Resource Inventory Model easily simu- 
lates shifts in management intensity and consequent changes 
in yields based upon alternative assumptions about the 
future, a major advantage of the model. The Timber Re- 
source Inventory Model is not, in principle, an even-age 
model since it can model growth and removal processes 
across all age classes. However, its treatment of harvest 
does introduce a bias toward even-aged stands. The Timber 
Resource Inventory Model currently does not recognize par- 
tial harvests; it does recognize thinning. All volume is as- 
sumed to be removed at harvest from either the oldest age 
class or spread across several age classes. Depending on the 
Table 3.1—Acreage cell categories used in the Timber Resource 
Inventory Model (TRIM) 
Region Southeast 
South Central 
Ownership National forest 
Other public 
Forest industry (including leased lands) 
Other private: 
Farmer 
Corporate 
Other individual 
Management type Pine plantations 
Natural pine 
Mixed pine—hardwoods 
Upland hardwoods 
Bottomland hardwoods 
Site productivity class High (85 or more cubic ft/acre/yr) 
Medium (50-84 cubic ft/acre/yr) 
Low (20-49 cubic ft/acre/yr) 
Full (100% or more) 
Medium (60%-99%) 
Poor (0-59%) 
(Categories vary by owner, site class, 
and management type. Maximum is 5.) 
Stocking class 
Management intensity 
Age class 0 to 90 in 5-year increments: 18 classes 
rate of harvests, this results in all older timber being har- 
vested and, consequently, stand structures with fairly com- 
pact age distributions. Harvested acres may enter any 
acreage cell or leave the timberland base entirely. 
The Southern Area Model system represents a significant 
advance for area projections over approaches used in the 
past. The system uses econometric equations to project area 
change for each State and ownership. Transition probabili- 
ties based on Forest Survey data are used to project area 
changes for management type on ownerships. Interaction 
with the Timber Assessment Market Model allows acreage 
trends to respond to economic changes. The acreage projec- 
tions are linked with the Timber Resource Inventory Model 
to establish the acreage within each cell at each projection 
period. 
Equilibrium Conditions 
This analysis differs from past assessments of the timber 
situation in that all projections are made at equilibrium 
levels. In prior assessments, projections were also pre- 
sented that had no direct interaction between the base-level 
projections of timber demands and supplies. Timber de- 
mands could rise more rapidly than base-level supplies to 
create an imbalance or gap. Under equilibrium conditions, 
prices and production factors are allowed to change until the 
quantities supplied and demanded are equal. 
Equilibrium conditions are achieved by running the three 
models interactively through an iterative process. Long-term 
production factors such as management intensity and tim- 
berland area are allowed to change in response to projected 
prices, which in turn are affected by the supply and de- 
mand relationships. 
Data Base 
The data base is critical for determining the starting point 
for timber resource projections and for developing the rela- 
tionships and trends that guide the projections. A major part 
of this study has been to assemble a consistent historical 
data base for the Southern States spanning the period 1952— 
85. An exhaustive effort was made to adjust past data to cur- 
rent standards and to extract data for detailed ownership 
and management categories as far back as possible. 
Area estimates were cross-tabulated by ownership and man- 
agement type for the entire historical period; however, the 
‘‘other private’’ category could only be subdivided into 
‘‘farmer,’’ ‘‘corporate,’’ and ‘‘other individual’’ for 1977 
and 1985. Softwood and hardwood inventory, growth, re- 
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