May, Dennis M; LeDoux, Chris B.; Tansey, John B.; Widmann, Richard.
1994. Impact of in-woods product merchandizing on profitable logging
opportunities in southern upland hardwood forests. Res. Pap. SO-282.
New Orleans, LA: U.S. Department of Agriculture, Forest Service,
Southern Forest Experiment Station. 11 p.

Estimates profitable logging opportunities existing in upland hard-
wood forests in 14 Southern States and demonstrates the impact of
three alternative product-merchandizing options on profitable logging
opportunities and profit margins.

Keywords: Harvest, prices, profits, revenues, stumpage.



The growing-stock volume on each plot was har-
vested using three alternative product mixes:

Option 1—merchandize all growing-stock volume
into pulpwood.

Option 2—merchandize growing-stock volume
into pulpwood and sawlogs.

Option 3—merchandize growing-stock volume
into pulpwood, sawlogs, and veneer
logs.

For the two multiproduct harvesting options, the
growing-stock volume was allocated into product
groups based on the following:

Sawlog volume—the growing-stock volume in trees
of sawtimber size (9 inches in d.b.h. and larger for
softwoods and 11 inches in d.b.h. and larger for hard-
woods) from a 1-foot stump to a minimum sawlog top
(7 inches in d.o.b. for softwoods and 9 inches in d.o.b.
for hardwoods), or the point where the main stem
breaks into limbs.

Pulpwood volume—the growing-stock volume in
trees too small to be sawtimber plus the remainder of
the growing-stock volume that is not included in the
sawlog volume. a

Veneer volume —a proportion of sawlog volume based
on the latest harvest volumes of sawlogs and veneer
logs reported in each State.

Because the model assumes commercial clearcutting,
merchandizing options, such as selectively removing
only sawlogs or veneer logs, were not considered. Addi-
tionally, no adjustments were made to the product
bucking/sorting/decking costs for differences that
might exist between each option’s product mix and the
product mix inherent in the model (differences
assumed to be small) or for any marginal costs associ-
ated with added products between the options, which
Baumgras and LeDoux (1990) have shown to be smail
and to not adversely affect total harvesting cost. As a
consequence, the only differences in logging costs
between merchandizing options would be those associ-
ated with hauling each product to its respective mill.

Haul distances—represented by the mileage equiv-
alent of the straight-line distances between each FIA
sample plot and the nearest mill communities accept-
ing the wood products harvested, as determined by
differencing their respective geographic coordinates. To
accommodate the multiple products harvested from
each plot, mill communities were identified as pulp-
wood, sawlog, or veneer log markets, either singularly
or in some combination, based on the types of primary
wood-using mills associated with each community.
Communities with pulp, chip, chipboard, charcoal, or
shaving mills were classified as pulpwood markets;
those with mills producing sawn products, as sawlog
markets; and those with mills producing peeled, sliced,
or stamped veneers, as veneer log markets. It is realized

that this is a simplification of the wood-products mar-
ket within the region, and that wood products may not
always be delivered to the nearest market and almost
never are delivered via a straight delivery route. This
approach does, however, recognize the number and
Jocation of product markets relative to the resource and
should provide meaningful assessments of the relative
costs associated with hauling harvested wood products
from upland hardwood plots under each product-
merchandizing option.

Harvest tree size—represented by the average d.b.h.
of all growing-stock trees (5 inches in d.b.h. and larger)
on each selected FIA sample plot.

Logging system—the ECOST-version 2 model cur-
rently allows a choice of one of several ground- or cable-
based logging systems. The John Deere 540B rubber-
tired skidder system was the option considered most
representative of the logging systems commonly oper-
ating in the region’s upland hardwood forests.

Average skidding distance — set at 700 feet and based
on the average harvest tract size in the region, esti-
mated with FIA data to be about 75 acres and corrobo-
rated by State forestry departments.

Truck class—the ECOST-version 2 model currently
allows a choice of one of five truck classes. The 4-by-2,
single-axle truck tractor with tandem trailer was the
option considered most representative of the trucks
hauling wood in the region.

Road class—the ECOST-version 2 model currently
allows a choice of five road classes based on the design
speed of the roads. Haul distance for each product was
divided into two road classes. The slowest road class (4
miles per hour) was assigned to the distance from each
sample plot to the nearest all-weather road (one of the
plot description variables collected by FIA) as an esti-
mate of the “pull” road needed to access the timber.
The remaining haul distance, after subtracting pull-
road distance, was assigned a road class of 2 (35 miles
per hour) deemed representative of average truck
speeds on State roads.

Delay cost —an estimate, based on the user’s knowl-
edge of the logging system, of the unproductive time in
all aspects of harvesting and delivering wood to the
mill (set at 2 cents per cubic foot of harvest volume for
the demonstration). +

Move cost —an estimate, based on the user’s know]-
edge of the logging system, of the cost associated with
moving equipment into, out of, or within the harvest
tract (set at 1 cent per cubic foot of harvest volume for
the demonstration).

Stumpage cost—an average cost of procuring the
harvest volume under each product-merchandizing
option based on product stumpage costs reported by
Timber-Mart South (1984). The stumpage costs were
specific to the location (State) of each plot, product
distribution of each option, and species composition of
each product.


Table 4.—Optimal mix of merchandizing options for maximizing profits from profitable logging opportunities in

southern upland hardwood forests

Area profitable to log

Volume profitable to log

All All

State Option 1 Option 2 Option 3 options Option 1 Option 2 Option 3. options
— --- Thousand acres _— -- Million cubic feet --~ aon

Alabama 177.0 59.3 1,794.3 2,030.6 222.3 104.7 3,105.2 3,432.2
Arkansas 436.5 1,114.6 56.6 1,607.7 713.2 1,644.6 112.9 2,470.7
Florida 30.3 88.8 337.5, 456.6 6.5 108.7 509.1 624.3
Georgia 115.7 45.0 2,373.5 2,534.2 147.4 74.4 5,042.9 5,264.6
Kentucky 0.0 393.9 2,789.7 3,183.6 0.0 825.0 5,224.2 6,049.3
Louisiana 521.2 233.7 153.3 908.2 784.9 364.5 258.0 1,407.4
Mississippi 592.2 1,204.9 115.3 1,912.3 905.6 1,942.3 182.8 3030.7
North Carolina 86.4 6,005.3 14.2 5,105.9 81.2 11,800.6 35.0 11,916.7
Oklahoma 30.0 107.3 23.1 160.5 14.1 54.4 17.9 86.4
South Carolina 90.0 301.9 831.6 1,223.6 80.2 595.8 1,713.9 2,389.9
Tennessee 109.2 1,277.4 2,920.5 4,307.1 198.9 2,366.5 5,220.6 7,786.0
‘Texas 358.0 515 194.7 604.2 429.3 68.8 258.0 756.1
Virginia 46.3 1,289.4 3,980.8 5,316.6 65.0 2,580.2 8,521.3  11,166.5
West Virginia 0.0 372.8 3,823.1 4,195.9 0.0 820.9 8,920.1 9,741.0
Total 2,592.8 11,545.8 19,408.2 33,547.0 3,648.6 23,351.4 39,1219 66,1218

a
Sensitivity Analysis duction of veneer logs, and gains were concentrated in

As suggested by Baumgras and LeDoux (1991), the
harvesting revenues (delivered price minus harvesting
and hauling costs) generated by this logging prof-
itability model are sensitive to stand characteristics,
market locations, and logging-system productivity.
These revenue estimates set the maximum amount
available to pay for stumpage and profit. The actual
allocation of harvesting revenues between the land-
owner and logger depends on the monetary expecta-
tions of both parties and is difficult to assess for
individual harvest tracts. If it is assumed, however,
that the landowner shares the burden of excess costs
when logging takes place in less than ideal conditions
and demands a share of excess revenues when logging
takes place under ideal conditions, then the average
stumpage costs reported in published price reports pro-
vide a ready source of data to assist in partitioning
harvesting revenue between the landowner’s stumpage
and the logger’s profit. However, these stumpage costs
are still just averages of the monetary expectations of
landowners across a State. Because of this, and the
importance of stumpage costs in determining differen-
tial prices, a sensitivity analysis was conducted in
which stumpage costs were increased and decreased by
one-third to demonstrate the impact on logging prof-
itability and the optimal mix of merchandizing options.

Stumpage-cost increases shifted logging oppor-
tunities from the most to the least intensive merchan-
dizing option and reduced total profitable logging
opportunities (tables 4, 5, 6). Losses were concentrated
in States with price differentials disfavoring the pro-

8

States with highly competitive pulpwood markets.
Although the stumpage-cost variations were propor-
tionately equivalent, the impact on differential prices
was greater for products with high stumpage costs
than for those with low stumpage costs. As a result,
stumpage-cost increases created merchandizing advan-
tages for lower valued products causing profitable log-
ging opportunities to shift from option 3 to option 1.

CONCLUSIONS

Within the limits set by the model’s input variables
and assumptions, about two-fifths of the South’s
reported upland hardwood forests, which contain about.
three-fifths of the reported inventory volume, can be
profitably logged. At average prices, it would seem that
multiproduct merchandizing usually increases profit-
able logging opportunities and profit margins. How-
ever, because of the extreme sensitivity of in-woods
product merchandizing to shifts in price differentials,
as well as other determinants, multiproduct harvesting
should not always be assumed to return the greatest
benefit. Only a careful analysis of stand characteris-
tics, local markets, and product prices can determine
the optimal product mix for individual harvest tracts.
Fortunately, the procedure demonstrated is flexible
enough for users to tailor inputs and assumptions to
meet specific needs, whether the needs are regional
assessments of profitable logging opportunities or local
assessments of optimal product mixes to balance log-
ging profits with product yields.


‘Table 2.—Average characteristics of profitable logging opportunities in southern upland hardwood
farests for each alternative product-merchandizing option.

Haul Price
State Option Volume Diameter distance differential Profit
Ftijacre Inches Miles Dollars/Ft
Alabama 1 1,866.6 116 14.1 0.33 0.05
2 1,801.6 113 10.9 0.35 0.07
3 1,726.0 ul 13.4 0.38 0.08
Arkansas 1 1,632.7 116 16.9 0.37 0.06
2 1,569.8 118 1L7 0.36 0.07
3 1,570.4 17 12.0 0.36 0.07
Florida 1 1,402.4 15.4 29.0 0.35 0.05
2 1,431.9 41 171 0.40 0.12
3 1,425.9 13.9 22.4 0.44 0.13
Georgia 1 2,241.7 11.9 31.6 0.38 0.06
2 2,167.0 114 19.9 0.40 0.10
3 2,097.6 11.3 22.4 0.42 0.12
Kentucky 1 2,162.4 17 31.1 0.36 0.04
2 1,931.4 117 20.1 0.36 0.06
3 1,900.3 1L7 20.9 0.36 0.06
Louisiana ary 1,598.2 12.2 17.4 0.40 0.10
2 1,620.4 12.2 115 0.38 0.10
3 1,614.2 12.3 128 0.38 0.10
Mississippi 1 1,645.6 ua 18.1 0.39 0.08
2 1,643.1 11.3 118 0.38 0.08
3 1,658.8 11.3 12.7 0.38 0.08
North Carolina 1 2,648.4 11.6 28.2 0.39 0.09
2 2,343.5 111 15.2 0.48 0.20
3 2,359.9 la 16.9 0.47 0.19
Oklahoma 1 646.0 16.1 22.1 0.38 0.07
2 621.3 14.9 12.6 0.36 0.06
3 621.3 14.9 12.8 0.36 0.06
South Carolina 1 2,150.1 11.6 32.8 0.39 0.07
2 2,031.8 11.0 20.9 0.46 0.15
3 2,017.4 10.9 23.6 0.47 0.15
Tennessee 1 1,922.4 11.3 23.2 0.38 0.07
2 1,812.8 qL1 13.7 0.38 0.09
3 1,813.2 iLL 14.1 0.38 0.09
Texas 1 1,240.2 12.4 20.2 0.40 0.07
2 1,335.5, 12.5 15.0 0.36 + 0,05
3 1,344.1 12.5 16.6 0.37 0.05
Virginia 1 2,337.5, 12.0 24.9 0.35 0.06
2 2,114.0 114 11.7 0.41 0.12
3 2,103.0 11.4 18.6 0.42 0.13
West Virginia 1 2,484.3 114 30.3 0.35 0.04
2 2,349.5 112 211 0.35 0.07
3 2,327.2 112 21.5 0.36 0.07
Average 1 2,115.5 11.7 25.3 0.37 0.07
2 2,015.4 il4 16.8 0.40 0.11

3 2,000.0 114 18.0 0.40 0.11



Delivered price—an average price paid for the har-
vest volume under each product-merchandizing option
based on product-delivered prices reported by Timber-
Mart South (1984). The delivered prices were specific
to the location (State) of each mill community, product,
distribution of each option, and species composition of
each product.

For every sample plot, the profitability of each
product-merchandizing option was determined by com-
paring the revenues and costs associated with pro-
curing and harvesting the wood products and
delivering them to market (that is, financial return
equals delivered price minus procurement, harvesting,
and hauling costs). Options with break-even or positive
financial returns were classified as profitable to log.

PROFITABLE LOGGING OPPORTUNITIES

Individual Merchandizing Options

Under any one merchandizing option, only a fraction
of the South’s reported inventory of upland hardwood
forests can be profitably logged (table 1). However, as
in-woods product merchandizing intensifies from har-
vesting a single, lower valued product to harvesting
multiple, higher valued products, the proportion of the
reported inventory that is profitable to log increases.
Only the better quality stands in the inventory (plots
with higher volumes and larger trees) can “pay their
way out of the woods,” but multiproduct harvesting
allows stands of lower quality to be profitably logged
(table 2). Since logging costs increase as stand quality
decreases, the increase in profitable logging oppor-

tunities associated with multiproduct harvesting can
be attributed to compensating decreases in hauling
costs and favorable changes in product pricing.

With the addition of sawlogs to the product mix
between options 1 and 2, hauling distances decreased
(tables 2, 3), a consequence of the numerous and widely
distributed sawlog markets in the South (fig. 2). The
resulting drop in hauling costs explains some of the
increase in profitable logging opportunities under
option 2. In contrast, the increase in hauling distances
associated with the addition of veneer logs to the prod-
uct mix helped to suppress the increase in profitable
logging opportunities between options 2 and 3.

The importance of product pricing in determining
logging profitability is keyed to the difference between
delivered price and stumpage cost for a product. This
differential price is the amount available to pay for
harvesting costs, hauling costs, and profit. Products
with large differential prices can absorb higher har-
vesting and hauling costs and still be profitable. There-
fore, products with large differential prices relative to
those of other products have a merchandizing advan-
tage. So, even though Timber Mart South (1984)
reported delivered-price premiums for sawlogs over
pulpwood and veneer logs over sawlogs, after taking
into account the stumpage-cost premiums demanded
for these products by the landowners, higher valued
products did not necessarily have a merchandizing
advantage over lower valued products. The conse-
quences of this are evident in the differences between
the average differential prices for each merchandizing
option (table 2).

For the region as a whole, there is a price differential
favoring the merchandizing of sawlogs over pulpwood.

Table 1.—Profitable logging opportunities in southern upland hardwood forests for each alternative product-

merchandizing option

Area profitable to log

Volume profitable to log

Reported Reported
State area Option 1_ Option 2 Option 3 volume Option 1 Option 2. Option 3
Thousand acres —-—-—-~ a Million cubic feet

Alabama 7,661.4 1,217.4 1,674.9 1,949.4 6,786.8 2,272.4 3,017.5
Arkansas 7,264.6 1,208.4 1,494.0 1,499.4 6,054.9 1,972.9 2,345.3
Florida 1,890.4 243.6 413.4 431.8 919.9 341.6 592.0
Georgia 5,917.6 1,374.1 2,318.6 2,499.1 7,322.3 3,080.4 5,024.4
Kentucky 10,186.5 ~ 854.5 2,949.6 3,176.4 13,470.21 1,847.7 5,696.9
Louisiana 2,107.9 854.1 819.7 820.1 1,943.1 1,365.0 1,328.3
Mississippi 5,531.4 1,628.4 1,778.9 1,736.7 4,860.3 2,679.6 2,922.8
North Carolina 7,202.4 3,655.0, 5,075.1 5,009.2 13,092.5 9,679.6 11,893.5
Oklahoma 2,609.6 91.5 136.1 136.1 863.4 59.1 84.5
South Carolina 2,644.2 734.0 1,141.2 1,162.4 3,157.8 1,578.2 2,318.6
Tennessee 9,587.9 3,155.6 4,250.3 4,272.0 12,109.1 6,066.1 7,705.0
Texas 3,367.5 536.4 506.2 499.9 2,019.8 665.2 676.0
Virginia 9,772.5 3,075.0 5,222.6 5,303.6 14,906.2 7,187.7 11,040.6
West Virginia 10,860.2 1,657.9 4,018.0 4,137.0 18,031.5 4,118.8 9,440.4

Total 86,604.1 20,285.9 31,798.6 = 32,633.1 105,537.7 42,914.38 64,085.8 65,267.2



PULPWOOD MARKETS SAWLOG MARKETS

VENEER LOG MARKETS

Figure 2— Distribution of pulpwood, sawlog, and veneer log markets in the South (each dot represents a community with at least one primary mill
using the product indicated).


(G) Deparment of Impact of In-Woods Product Merchandizing

Agriculture on Profitable Logging Opportunities
Forest Service in Southern Upland Hardwood Forests
Eoverinent Seaton Dennis M. May, Chris B. LeDoux, John B. Tansey,

and Richard Widmann
New Orleans,
Louisiana

Research Paper
$0-282

April 1994


‘Table 5.—Optimal mix of merchandizing options for maximizing profits from profitable logging opportunities in
southern upland hardwood forests at low stumpage costs

‘Area profitable to log Volume profitable to log

All All
State Option 1 Option 2 Option 3 _ options Option 1 Option 2 Option 3 options

Million cubic feet ---

---- Thousand aeres -~

Alabama 54 104.7 3,446.1 3,556.2 28 971 4,864.2 4,964.1

Arkansas 0.0 1,115.5 1,519.0 2,634.5 0.0 1,507.9 2,035.0 3,542.9

Florida 0.0 175.2 549.6 724.8 0.0 37.9 7318 769.7,

Georgia 00 109.4 3,214.6 3,324.1 0.0 82.5, 6,050.6

Kentucky 0.0 13L7 4,785.3 49170 0.0 259.7 8,171.0

Louisiana 0.0 70.3 1,149.4 1,219.7 0.0 107.0 15774

Mississippi 0.0 141.1 2,578.5 2,719.5 0.0 183.0 3,581.4

North Carolina 47 3,260.3 2,350.0 5,615.1 71 7,244.7 5,187.5,

Oklahoma 0.0 10.2 300.1 310.3 0.0 0.5 184.9

South Carolina 5.2 87.3 1,425.9 1,518.5 1.6 153.2 2,539.0

Tennessee 12.5 910.1 5,167.1 6,089.7 20.3 1,698.5 8,040.6

Texas 0.0 182.5 958.5 1,141.0 0.0 196.2 984.3

Virginia 0.0 90.7 6,217.0 6,307.7 0.0 TIN — 12,364.8

West Virginia 0.0 608.5 5,407.3 6,015.8 0.0 1,219.1 11,5674 12,786.5
Total 27.8 6,997.5 39,068.4 46,093.9 31.8 12.964.3 67,879.9  80,876.1

Table 6.—Optimal mix of merchandizing options for maximizing profits from profitable logging opportunities in
southern upland hardwood forests at high stumpage costs

Area profitable to l Volume profitable to log
log p

All All
State Option 1 Option 2 Option 3 options Option 1 Option 2. Option 3 options

-- Thousand acres --. -- Million cubic feet —-- -
Alabama 437.8 175.4 108.5 721.7 908.9 356.9 221.1 1,486.9

Arkansas 859.0 68.0 116 938.7 1,490.9 108.9 219 1,621.7
Florida 10.8 143.7 125.3 279.8 25.0 223.6 193.8 442.4
Georgia 460.3 165.0 956.1 1,581.3 1,003.1 413.7 2,221.9 3,638.7
Kentucky 480.9 375.0 256.3 1,112.2 1,031.3 $24.4 562.6 2,418.3
Louisiana 699.4 28.3 0.0 727.7 1,187.7 46.0 0.0 1,233.7
Mississippi 1,129.5 95.3 22.3 1,247.1 1,953.6 183.8 42.3 2,179.6
North Carolina 522.5, 3,827.5 0.0 4,350.0 1,252.8 9,608.5. 0.0 10,861.3
Oklahoma 65.5 13.7 0.0 79.3 50.0 2.5 0.0 52.5
South Carolina 147.4 603.4 83.6 834.3 280.7 1,369.6 166.6 1,816.9
‘Tennessee 2,739.3 134.5 58 2,879.6 5,340.1 355.0 73 5,702.4
‘Texas 380.4 13.9 0.0 394.4 489.4 16.6 0.0 506.0
Virginia 338.7 2,841.1 866.5 4,046.2 N19 6,465.6 1,902.2 9,139.8
West Virginia 1,015.2 291.5 715.8 2,022.6 2,419.1 712.4 2,032.6 5,164.1

Total 9,286.7 8,776.3 3,151.8  21,214.9 18,204.5 20,687.5 7,372.3 46,264.3



OPTION 1 OPTION 2

OPTION 3

Figure 3.—Distribution of southern upland hardwood forests that return the greatest profit to the logger when harvested by the product-
merchandizing option indicated (each dot represents 5, 000 acres of timberland, option 1 is only pulpwood; option 2 is pulpwood and
sawlogs; option 3 is pulpwood, sawlogs, and veneer logs).


Table 3.—Average hauling distance for each delivered product

Product,
Veneer
State Pulpwood Sawlogs logs
--Miles —--

Alabama 14.1 19
Arkansas 16.9 65 42.0
Florida 29.0 10.8 34.6
Georgia 31.6 88 31.1
Kentucky 31.1 51 594
Louisiana 174 8.7 20.6
Mississippi 18.1 79 314
North Carolina 28.2 WW 25.0
Oklahoma 22.1 719 41.8
South Carolina 32.8 10.7 30.2
Tennessee 23.2 5.6 53.6
Texas 20.2 10.4 23.5,
Virginia 24.9 68 43.0
West Virginia 30.3 69 59.4

Average 25.3 cat 41.5

we

However, in States with numerous and highly competi-
tive pulpwood markets, such as Louisiana and Texas,
the opposite is true. As a result, profitable logging
opportunities are the highest in these two States under
option 1, despite the longer haul distance to pulpwood
markets.

For many States in the region, price differentials
provide little incentive for merchandizing veneer logs.
In Mississippi and North Carolina, for example, the
lack of merchandizing incentive and the longer hauling
distance to veneer markets result in profitable logging
opportunities being greatest under option 2. In con-
trast, Alabama and Georgia are examples of two States
where differential prices, market locations, and
resource characteristics favor the most intensive level
of product merchandizing as witnessed by the con-
centration of profitable logging opportunities in both
States under option 3.

Optimal Mix of Merchandizing Options

Table 1 depicts the profitable logging opportunities
for each option assuming the entire upland hardwood
forests of the South could be logged using only one
option to the exclusion of the other two. Logging
upland hardwood forests using a mixture of the options
would be more realistic. The optimal mix of merchan-
dizing options can be determined from a comparison of
the relative benefits derived from each option for each
harvest tract. If the assumption is made that the logger
is free to exploit all available markets and pursue max-
imum profits, then profit maximization can be used to
judge the relative merits of each option and derive the
optimal mix of merchandizing options.

Profit Maximization

The optimal mix of merchandizing options based on
profit maximization resulted in more profitable logging
opportunities than any one option did individually
(tables 1, 4). However, profit maximization shifted prof-
itable logging opportunities from the least to the most
intensive product-merchandizing option. The resulting
concentration of profitable logging opportunities in
option 3 is testimony to the advantages that can be
gained through multiproduct harvesting when the nec-
essary conditions of stand characteristics, market loca-
tions, and product prices are met.

In several States where price differentials and haul-
ing costs disfavor the merchandizing of veneer logs,
profit maximization concentrated profitable logging
opportunities under option 2 (table 4; fig. 3). This is not
to say that more of the upland hardwood forests in
these States could not be profitably harvested using
option 3, only that to do so would result in reduced
profits. The optimal product mix (table 4) maximizes
logging profits; each option in table 1 maximizes the
yield of an individual product. The option combinations
in tables 1 and 4 limit a range of option mixes that
could be used to profitably log the upland hardwood
forests in the South. Any shifting of the option mix
from one extreme toward the other would result in a
tradeoff between logging profits and product yields.
Such tradeoffs occur on a daily basis for loggers who
work under contracts, face product-production quotas,
or must meet the landowner’s financial expectations.

Despite the concentration of profitable logging oppor-
tunities in options harvesting multiple products, multi-
product harvesting options should not always be
assumed to be the most profitable. There are 2.5 mil-
lion acres where the exclusive merchandizing of pulp-
wood (option 1) returns the greatest profit to the logger
(table 4). Most of these logging opportunities are con-
centrated in States with numerous and highly competi-
tive pulpwood markets such as Louisiana and Texas.
This situation contrasts the situation in Kentucky and
West Virginia where the relative lack of pulpwood mar-
kets eliminates option 1 from the optimal mix of mer-
chandizing options (figs. 2, 3).

From figure 3, it is also evident that the reporting
structure of the price data used in this demonstration
affected the estimates of logging profitability. The use
of State-level price data created discrete transitions in
prices at State boundaries. Each State, in effect,
became an island of profitability advantage or disad-
vantage relative to other States and for products deliv-
ered across State lines. Despite this, State-level price
data were deemed suitable for this demonstration
because they were readily available and provided some
measure of price variation across the region. However,
users of this logging profitability model should be
aware of the impact that price-reporting structure can
have on the final estimates of logging profitability.


LS

Figure 1.—Distribution of upland hardwood forests in the South (each dot represents 10,000 acres of timberland).

MODEL INPUTS/ASSUMPTIONS

The ECOST-version 2 model inputs and assumptions
were derived either directly from sample-plot data or
selected to represent conditions within the 14-State
region and took the following form:

Harvest volume — represented by the entire growing-
stock volume on each selected upland hardwood sample
plot in the 14-State region. Growing-stock volume is
the cubic-foot volume from a 1-foot stump to a mini-

mum 4-inch top diameter outside bark (d.o.b.), or the
point where the main stem breaks into limbs, for live
trees 5 inches in d.b.h. and larger that are capable of
producing sawlogs, currently or prospectively. In real-
ity, some growing-stock volume remains after harvest,
and some nongrowing-stock volume, in trees or por-
tions of trees too rough, rotten, or small to be consid-
ered growing stock, is removed. However, growing-
stock volume is the volume routinely reported by FIA
against which most availability assessments are made
and is therefore the focus of the study.


Impact of In-Woods Product Merchandizing on Profitable Logging
Opportunities in Southern Upland Hardwood Forests

Dennis M. May, Chris B. LeDoux, John B. Tansey, and Richard Widmann

INTRODUCTION

Southern upland hardwood forests have traditionally
supplied a large portion of the wood requirements for
the hardwood lumber and other solid wood-product.
industries. More recently, these same forests have been
supplying an increasing share of the wood-fiber needs
of both domestic and foreign pulp and paper industries.
As harvesting pressure mounts, assessments of timber
supplies available from these once overlooked forests
will become increasingly more important.

Forest inventory statistics reported by the U.S.
Department of Agriculture, Forest Service, Forest
Inventory and Analysis (FIA) units, do provide esti-
mates of the wood volume existing in southern upland
hardwood forests. However, much of this reported vol-
ume is unavailable for harvest simply because it cannot
be profitably logged and delivered to market. Therefore,
determining the amount of the reported inventory that
is profitable to log is one key component in estimating
timber availability and is one objective of this report.
The other objective is to demonstrate how in-woods
product merchandizing can affect profitable logging
opportunities because it has been shown to offer oppor-
tunities for increasing logging profitability through
higher harvest revenues, increased logging system pro-
ductivity, improved wood utilization, and protection
against mill-imposed product quotas (Baumgras and
LeDoux 1988).

FOREST INVENTORY DATA

Each of the four eastern FIA units periodically
gathers forest inventory data from a series of sample
plots located across each State in its jurisdiction.
Reported inventory statistics for southern upland hard-
wood forests were compiled from the latest inventories
of sample plots occurring on upland hardwood forests

(FIA oak-hickory and maple-beech-birch forest type
groups) in 14 Southern States (fig. 1). This task was
greatly simplified by using the Eastwide Database
(Hansen and others 1992), which was designed to mini-
mize differences in sampling designs and inventory
data between the four eastern FIA units. Inherent in
the reported inventory is a discounting for upland
hardwood forests incapable of producing commercial
crops of timber due to legal restrictions or adverse
sites.

LOGGING PROFITABILITY MODEL

To determine the impact of in-woods product mer-
chandizing on profitable logging opportunities within
southern upland hardwood forests, an economic assess-
ment of the profitability of logging each selected sam-
ple plot was made for each of three alternative product-
merchandizing options using procedures similar to
those described by May and LeDoux (1992). The prof-
itability of logging each selected sample plot was based
on a comparison of the costs and revenues associated
with procuring, felling, limbing, bucking, skidding, and
loading the wood products from each upland hardwood
forest plot and delivering them to wood-using mills.
The costs and revenues were derived from wood-price
reports and ECOST-version 2 (LeDoux!, LeDoux 1985,
LeDoux and Baumgras 1990). The ECOST-version 2
model estimates logging costs in 1984 dollars-per-cubic-
foot-harvested based on the size and volume of wood
removed from each plot, the distance the wood was
hauled, and the production functions of conventional
logging systems working in conditions typically
encountered in upland hardwood forests.

1LeDoux, Chris B. 1988. ECOST-version 2—stump-to-mill produe-
tion cost equations and computer program, Unpublished report. On
file with: U.S. Department of Agriculture, Forest Service, North-
eastern Forest Experiment Station, Morgantown, WV. 9 p.

Dennis M. May is a research forester, U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, St. Paul, MN
55108, formerly with the U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, Starkville, MS 39759; Chris B.
LeDoux is a supervisory industrial engineer, U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station,
Morgantown, WV 26505; John B. Tansey (deceased) was a supervisory forester, U.S. Department of Agriculture, Southeastern Forest Experi-
ment Station, Asheville, NC 28802; and Richard Widmann is a research forester, U.S. Department of Agriculture, Northeastern Forest

Experiment Station, Radnor, PA 19087.


SUMMARY

Procedures developed to assess available timber supplies from upland hard-
wood forest statistics reported by the U.S. Department of Agriculture, Forest
Service, Forest Inventory and Analysis (FIA) units, were modified to demon-
strate the impact of three in-woods product-merchandizing options on profitable
logging opportunities in upland hardwood forests in 14 Southern States.
Product-merchandizing options ranged from harvesting a single, lower valued
product to harvesting multiple, higher valued products. Under the specific
assumptions and conditions of the demonstration, two-fifths of the South’s
reported upland hardwood forest, containing about three-fifths of the reported
inventory, was estimated to be profitable to log. Multiproduct harvesting was
generally shown to increase profitable logging opportunities and profit margins.
However, in specific situations defined by product prices, market locations,
and stand characteristics, merchandizing options harvesting fewer and lower
valued products were shown to be most profitable, demonstrating that multi-
product harvesting cannot always be assumed to be an optimal merchandizing
alternative.


LITERATURE CITED

Baumegras, John E.; LeDoux, Chris B. 1988. Impact of
stand diameter and product markets on revenue
gains from multiproduct harvesting. Forest Prod-
ucts Journal. 38(7/8): 57-63.

Baumgras, John E.; LeDoux, Chris B. 1990. Produc-
tion analysis of two tree-bucking and product-
sorting methods for hardwoods. In: Stokes, Bryce J.,
ed. Proceedings of the Southern Regional Council on
forest engineering; 1989 May 3-4; Auburn, AL. New
Orleans, LA: U.S. Department of Agriculture, Forest
Service, Southern Forest Experiment Station: 88-
96.

Baumgras, John E.; LeDoux, Chris B. 1991. Integrat-
ing forest growth and harvesting cost models to
improve forest management planning. In: McCor-
mick, Larry H.; Gottschalk, Kurt W., eds. Proceed-
ings of 8th Central hardwood forest conference.
1991 March 3-6; University Park, PA. Radnor, PA:
U.S. Department of Agriculture, Forest Service,
Northeastern Forest Experiment Station: 120-130.

of

Hansen, Mark H.; Frieswyk, Thomas; Glover, Joseph
F.; Kelly, John F. 1992. The eastwide forest
inventory data base: users manual. Gen. Tech. Rep.
NC-151. St. Paul, MN: U.S. Department of Agricul-
ture, Forest Service, North Central Forest Experi-
ment Station. 48 p.

LeDoux, Chris B. 1985. Stump-to-mill timber produc-
tion cost equations for cable logging eastern hard-
woods. Res. Pap. NE-566. Broomall, PA: U.S.
Department of Agriculture, Forest Service, North-
eastern Forest Experiment Station. 6 p.

LeDoux, Chris B.; Baumgras, John E. 1990. Develop-
ment of regional stump-to-mill logging cost estima-
tors. In: Stokes, Bryce J., ed. Proceedings of the
Southern Regional Council on forest engineering;
1989 May 3-4; Auburn, AL. New Orleans, LA: U.S.
Department of Agriculture, Forest Service, South-
ern Forest Experiment Station: 112-118.

May, Dennis M.; LeDoux, Chris B. 1992. Assessing
timber availability in upland hardwood forests.
Southern Journal of Applied Forestry. 16(2): 82-88.

Timber-Mart South. 1984. Summary of Mart. High-
lands, NC: Timber-Mart South: 1-12 Vol. 9.

*U.S.GPO: 1994-565-016/00007

li