Amaro A., Reed D., Soares P. (editors) Modelling Forest Systems
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32Amaro Forests - Chap 28 1/8/03 11:54 am Page 326
326 H.F. Carino and E.J. Biblis
Introduction
Loblolly pine (Pinus taeda L.) is the most important species of timber growing in the
southern region of the USA. It is considered an ideal tree for site restoration and for-
est management, largely because of its hardiness and versatility in terms of its abil-
ity to reproduce and grow rapidly on diverse sites (Schultz, 1997). More than half of
the southern yellow pine timber now available to sawmillers in the region comes
from plantations consisting mostly of loblolly pine. However, dimension lumber
producers are noticeably avoiding, whenever possible, the use of timber from
intensely managed loblolly pine plantations, apparently because of the fact that fast-
grown pine trees produce a high proportion of juvenile wood at young ages.
Juvenile wood, which in loblolly pine could occupy from 10 to 20 annual rings
(Zobel and Kirk, 1972), is generally unsuitable for solid wood product production. It
is known to be weaker and less stiff than mature wood, due to its lower specific
gravity, shorter tracheids, larger fibril angles, thinner cell walls, larger lumen diame-
ter, lower percentage of summerwood, more compression wood and larger longitu-
dinal shrinkage (Pearson and Gilmore, 1971; Zobel and Kirk, 1972; Zobel and Blair,
1976).
It has been determined that the structural quality of dimension lumber from
loblolly pine plantation sawtimber incr
eases with stand age and stand density
(Biblis et al., 1993, 1995, 1997; Biblis and Carino, 1999). This confirms the widespread
belief among wood industry people that quality, and not just volume, of loblolly
pine plantation timber increases with stand age. Therefore, the stumpage value also
increases with stand age, and a stratified stumpage pricing reflecting the quality dif-
ferences of sawlogs (Carino and Biblis, 2000) or sawtimber from loblolly plantation
stands of different age groups should be considered.
Also, a recently conducted study (Biblis et al.
, 1998) presents compelling evi-
dence that sawtimber regimes of loblolly pine plantations with longer rotations (e.g.
50 years) could provide competitive returns to landowners relative to pulpwood
regimes with shorter rotations (e.g. 20 years). The expected economic advantage
might even be greater if loblolly pine plantation stands were managed to produce
sawtimber purposely for structural-dimension lumber production, as shown in this
chapter. For instance, it was estimated, based on Summer 2000 prices quoted from
Alabama sawmillers, that a 25-year-old loblolly pine plantation on an average site
(e.g. stand top height or mean dominant height of 27.4 m at 50 years old) and with a
2.4 × 2.4 m initial spacing could yield about $10,006/ha of str
ess-graded dimension
lumber from the harvested sawtimber. In contrast, the same stand, if managed to
produce pulpwood, would yield only up to $2471/ha (based on a rather optimistic
timber harvest of 257 t/ha at $9.62/t).
There is no doubt that older stands of loblolly pine plantation timber will yield
higher expected income for the owners. However
, there is a dearth of information
about the volume and value of structural-dimension lumber yields from loblolly
pine plantation timber of various ages. More importantly, the economic harvest rota-
tion of loblolly pine plantations for structural-dimension lumber production is not
known. Not much is known, for instance, about whether it would be economically
advantageous and desirable for a sawmiller/landowner to defer for another 5, 10,
15 or 25 years the harvesting of a 25-year-old plantation stand of loblolly pine saw-
timber for structural-dimension lumber production. This chapter provides invalu-
able insights into this important issue.
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327 Expected Volume and Value of Lumber
Methods
Five loblolly pine plantation stands, representing 25-, 30-, 35-, 40- and 50-year age
classes, were used for this study. These were selected primarily due to their very
similar characteristics, including site indices, original spacing and thinning regimes
as listed in Table 28.1. The diameter at breast height (DBH) distribution was estab-
lished by measuring the DBH of all trees in four 0.10 ha sample plots. Fifty trees rep-
resenting the predetermined DBH distribution in each of the 25-, 30- and 35-year-old
stands were selected for sawing. Also selected in a similar fashion were 30 trees
from the 40-year-old stand and 12 trees from the 50-year-old stand. All selected sam-
ple trees were identified, harvested, measured and segregated prior to bucking them
into sawlogs. Each sawlog was measured, recorded and spray painted on each end
with different colours – one to indicate the stand age and the other the log location
within the tree.
For each batch of sawlogs of a given type (i.e. based on stand age and tree sec-
tion – butt, middle or top), the sawn pieces of lumber wer
e tallied and sorted by
width and length. About 12.9, 11.0 and 24.7 m
3
of lumber was recovered from each
group of 50 trees harvested and sawed, representing the 25-, 30- and 35-year-old
stands, respectively. Moreover, 14.3 and 9.5 m
3
of lumber was recovered from the 30
and 12 trees harvested from the 40- and 50-year-old stands, respectively. The lumber
was then kiln-dried to approximately 15% moisture content and subsequently
dressed to the mill’s specifications for dimension lumber.
The lumber produced from each plantation stand investigated was subsequently
tested mechanically using the destr
uctive method of determining flexural properties
(moduli of rupture (MOR) and elasticity (MOE)). For this purpose, 338, 374 and 474
lumber samples were randomly selected from the 25-, 30- and 35-year-old stands,
respectively. On the other hand, all the lumber pieces (468 and 356) produced from
sawlogs originating from the sample trees (30 and 12 trees, respectively) representing
the 40- and 50-year-old stands were tested. These were stored indoors at the Auburn
University Forest Products Laboratory for a minimum of 3 weeks prior to testing.
Every piece was tested edgewise in flexure to failure with two-point loading accord-
ing to ASTM D198-84 (American Society for Testing and Materials, 1999), using a
Tinius–Olsen hydraulic testing machine with a capacity of 54,545 kg. It should be
noted that only two length categories (2.4 and 3.7 m) of lumber were tested. The 5.08 ×
15.24 cm and 5.08 cm × 20.32
cm pieces were tested over a span of 3.35 m, and the
5.08 cm × 10.16
cm pieces were tested over a 2.3-m span. For flexure tests, the machine
was equipped with an extended base made from a steel double I-beam 6.25 m long
and a steel loading head 2.13 m long. Load and corresponding deflection-to-failure
data were obtained with a Hewlett-Packard (H-P) data acquisition system connected
Table 28.1. Characteristics of 25-, 30-, 35-, 40- and 50-year-old loblolly pine (Pinus taeda L.) stands
considered in this study. Site index at base age 50 years.
Average Average
Original Thinned No. of diameter at merchantable Basal
Stand age Site index spacing at age trees breast height length area
(years) (m) (m × m) (years) per ha (cm) (m) (m
2
/ha)
25 29 2.4 × 2.4 18 381 27.2 13.4 9.1
30 28 2.4 × 2.4 20 430 24.6 13.2 8.6
35 30 2.4 × 2.4 18 + 27 321 27.4 19.1 13.6
40 27 2.4 × 2.4 25 450 35.6 23.3 18.1
50 27 2.4 × 2.4 18 + 40 272 37.3 25.1 12.0
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 328
328 H.F. Carino and E.J. Biblis
to an H-P desk computer for processing. From the obtained data, the MOR and MOE
for each tested piece of lumber were calculated. To obtain the extreme fibre value in
bending ‘F
b
’ for every tested piece, its MOR value was divided by the 2.1 combine
safety factor recommended in ASTM D245 (American Society for Testing and
Materials, 1999). This ‘F
b
’ value in combination with the corresponding appropriate
value ‘E’ provides the stress grade for each lumber size listed in Tables 1a, 1b and 1c of
the SPIB standard grading rules (Southern Pine Inspection Bureau, 1994).
Analysis
The volume and value of the test sample boards for each combination of size and
stress-grade classes originating from a stand of a given age were then determined.
The valuation of lumber was based on lumber prices (in $/m
3
) quoted directly from
southern yellow pine lumber producers for the summer months of 2000. From the
test sample data, it was then possible to estimate the probability of occurrence (or
percentage distribution) of stress-graded dimension lumber coming from each sam-
ple stand of a given age based on volume (see Table 28.2). Also, it was possible to
estimate the weighted average unit value (in $/m) of the tested dimension lumber
from each sample stand of a given age, using the following relationship:
V
k
=
∑ ∑
P R
ij
(1)
ij
i j
where: V
k
is the weighted (by size and grade) average unit value ($/m
3
) of tested
(i.e. stress-graded) dimension lumber from a loblolly pine plantation of a given age
Table 28.2. Percentage distribution of stress-graded dimension lumber from 25-, 30-, 35-, 40- and 50-
year-old loblolly pine plantation stands considered in this study
a
.
Stand
Percent distribution based on volume yield
age Lumber size No. 1 and No. 3 and
(years) (cm × cm) better No. 2 below Total
25 5.08 × 10.16 12.0 9.4 49.9 71.3
5.08 × 15.24 4.0 3.5 21.2 28.7
16.0 12.9 71.1 100.0
30 5.08 × 10.16 28.6 12.3 42.2 83.1
5.08 × 15.24 7.6 2.4 6.9 16.9
36.2 14.7 49.1 100.0
35 5.08 × 10.16 17.0 10.1 16.0 43.1
5.08 × 15.24 24.4 10.4 11.9 46.7
5.08 × 20.32 5.3 0.7 4.2 10.2
46.7 21.2 32.1 100.0
40 5.08 × 10.16 29.6 12.8 14.1 56.5
5.08 × 15.24 9.6 6.2 12.6 28.4
5.08 × 20.32 10.1 2.0 3.0 15.1
49.3 21.0 29.7 100.0
50 5.08 × 10.16 12.8 1.0 0.6 14.4
5.08 × 15.24 62.2 6.3 8.3 76.8
5.08 × 20.32 8.0 0.4 0.4 8.8
Total 83.0 7.7 9.3 100.0
a
Stress grades are based on SPIB allowable design values of ‘F
b
’ and ‘E’ as listed in Tables 1a, 1b and
1c, pages A3, A4 and A5 of Standard Grading Rules for Southern Pine Lumber (Southern Pine
Inspection Bureau, 1994).
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 329
329 Expected Volume and Value of Lumber
k; P
ij
is the probability of occurrence of tested dimension lumber of a given size i and
grade j from a loblolly pine plantation of a given age; and R
ij
is the unit price ($/m
3
)
of tested dimension lumber of a given size i and grade j.
The estimated weighted average unit values (in $/m
3
) of the tested dimension
lumber from the 25-, 30-, 35-, 40 and 50-year-old stands are $100, $127, $150, $149
and $192/m
3
, respectively.
The total volume of dimension lumber per hectare of loblolly pine plantation of
a given age was estimated using the data on the number of sample tr
ees harvested
for the study, the volume of dimension lumber produced from such sample trees,
and number of trees at harvest time. For instance, in the case of the 25-year-old
stand, the total volume of dimension lumber is about 98 m
3/
ha (i.e. given the num-
ber of trees at harvest time = 380/ha; number of sample trees harvested = 50; vol-
ume yield of 50 trees = 12.9 m
3
). Calculated in a similar fashion, the estimated total
volume of dimension lumber from the 30-, 35-, 40- and 50-year-old stands was 94.4,
158.6, 215.1 and 215.7 m
3/
ha, respectively.
Given the data on weighted average unit value (in $/m
3
) and the estimated
total volume of dimension lumber per hectare, it was then possible to estimate the
total value of dimension lumber per hectare of loblolly pine plantation of a given
age. The estimated total value of dimension lumber of the 25-, 30-, 35-, 40- and 50-
year-old stands was $9808, $12,054, $23,836, $32,094 and $41,296/ha, respectively.
For the purposes of predicting expected values (see Table 28.3) as well as
observing tr
ends and rates of change of the unit value, total volume and value of
stress-graded dimension lumber produced per hectare of loblolly pine plantation of
various ages from 25 to 50 years, the following regression equations were devel-
oped:
Y
1
= 45.80 + 5.61X r
2
= 0.82 (2)
where: Y
1
is the expected total volume of stress-graded dimension lumber per unit
area (m
3/
ha) of loblolly pine plantation of a given age and X is the stand age (years).
Y
2
= 20.59 + 3.42X r
2
= 0.94 (3)
where: Y
2
is the expected unit value ($/m
3
) of stress-graded dimension lumber from
a loblolly pine plantation of a given age and X is the stand age (years).
The expected value of stress-graded dimension lumber produced per hectare of
loblolly pine plantation of a given age was estimated by multiplying the values
given by Equations 2 and 3. In this study
, a modified version of stumpage valuation
was used in the analysis. Stumpage was estimated by the value of structural-dimen-
Table 28.3. Expected volume and value yields of stress-graded dimension
lumber from 25-, 30-, 35-, 40- and 50-year-old loblolly pine plantation stands.
a
Expected total Expected unit Expected total
Stand age volume yield value value yield
(years) (m
3
/ha) ($/m
3
) ($/ha)
25 94.4 106 10,006
30 122.4 123 15,055
35 151.0 140 21,140
40 179.0 157 28,103
50 235.0 192 45,120
a
The expected unit value and total volume were calculated using Equations 2
and 3, respectively, and the expected value yield per hectare is the product of
the two.
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 330
330 H.F. Carino and E.J. Biblis
sion lumber yield based on actual volume recovery (instead of scaled volume as
conventionally done in practice). With such a modified valuation of stumpage
notwithstanding, the economic desirability of deferring the harvesting sawtimber
for structural-dimension lumber production from a loblolly pine plantation of a
given age was determined using incremental analysis in conjunction with dis-
counted-cash-flow techniques. For this analysis, the following relationship proved
to be very useful:
R = [(
F/P)
1/n
– 1] × 100 (4)
where: R is the expected incr
emental rate of return (%); P is the expected present
value ($) of stress-graded dimension lumber produced per hectare of loblolly pine
plantation of a given age; F is the expected future value ($) of stress-graded dimen-
sion lumber produced per hectare of loblolly pine plantation after n years from a
base age; and n is the stand age (years).
A decision to harvest the stand at a certain age (e.g. 25 years), and not later (e.g.
after 5 years or 30 years of age), would be implemented if
R is less than a specified
minimum acceptable rate of return on investment (MARR). Otherwise, it would be
more economically desirable to defer the harvesting of the stand until more
favourable economic conditions exist or whenever an R equal to or higher than the
MARR could be achieved (see Table 28.4).
Results and Discussion
From Table 28.3, it is apparent that the value of stumpage in loblolly pine planta-
tions increases with the age of the stand. The estimated total value yields of stress-
graded dimension lumber of the 25-, 30-, 35-, 40- and 50-year-old stands are $10,020,
Table 28.4. Estimated time value (or incremental rate of
return) of stumpage of loblolly pine plantations of various
ages managed for sawtimber production when harvesting
is deferred.
a
Stand age (years)
Current or
base Harvest time
Incremental rate
of return (%)
25
30
35
40
30
35
40
50
35
40
50
40
50
50
8.5
7.7
7.1
6.2
6.9
6.4
5.6
5.9
4.8
4.8
a
In this case, stumpage is based on the value of stress-
graded dimension lumber product yield. Stress grades
are based on SPIB allowable design values of ‘F
b
’ and ‘E’
as listed in Tables 1a, 1b and 1c, pages A3, A4 and A5 of
Standard Grading Rules for Southern Pine Lumber
(Southern Pine Inspection Bureau, 1994).
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 331
331 Expected Volume and Value of Lumber
$15,073, $21,081, $28,037 and $44,808/ha, respectively. These represent an annual
average increase of about $1399/ha, as determined by regression analysis. In terms
of the unit value of dimension lumber yield, the 25-, 30-, 35-, 40- and 50-year-old
stands yielded about $106, $123, $140, $157 and $192/m
3
, respectively. This repre-
sents an annual rate of increase in unit value yield of about $3.42/m
3
, as reflected by
the coefficient of X in Equation 3. Such age-related increases in value yield could be
attributed to increases or improvement in both the volume and quality of dimension
lumber yields.
Table 28.3 shows that for the 25-, 30-, 35-, 40- and 50-year-old stands, the esti-
mated volume of dimension lumber pr
oduced is about 94.4, 122.4, 151.0, 179.0 and
235.0 m
3/
ha, respectively, of which (see Table 28.2) approximately 16.0, 36.2, 46.7,
49.3 and 83.0% graded No. 1 and better, respectively. The annual rate of increase in
volume yield is about 5.61 m
3
, as reflected by the coefficient of X in Equation 2.
Using Equation 4 and the expected total value yields per hectare shown in Table
28.3, the time value (expressed in terms of percentage incremental rate of return or
R) of stumpage of loblolly pine plantations managed primarily for the production of
sawtimber converted into structural-dimension lumber was determined. For
instance, if the harvesting of the 25-year-old stand considered in this study was
deferred by 5, 10, 15 or 25 years, the R value could be about 8.5, 7.7, 7.1 or 6.2%,
respectively. Similarly, if the harvesting of the 30-year-old stand was deferred by 5,
10 or 20 years, the R value could be about 6.9, 6.4 or 5.6%, respectively. In the case of
the 35-year-old stand, if its harvesting was deferred by 5 or 10 years, the R value
could be about 5.9 or 4.8%, respectively. If the harvesting of the 40-year-old stand
was deferred by 10 years, the R value could be about 4.8%. All these estimated R
values are shown in Table 28.4. It should be noted that these are conservative esti-
mates because, as pointed out earlier, the value of structural-dimension lumber
derived from the sawtimber produced was the sole basis for the stumpage valua-
tion. The value of 1-inch boards and pulpwood from the top portion of the tree was
not included in estimating the stumpage value.
Evidently, the harvesting of a loblolly pine plantation stand of a given age
should be deferr
ed if the estimated R is equal to or higher than the minimum
acceptable rate of return on investment or MARR, whatever that may be. For exam-
ple, if the MARR is 7.5%, it would probably be prudent on the part of the owner of a
25-year-old loblolly pine plantation stand to defer harvesting it for another 10 years,
because the R value then or at 35 years of age would be about 7.7%. On the other
hand, it would seem more economically desirable for owners of 30-, 35-, 40- and 50-
year-old stands to do the harvesting now and not defer it to a later date, because the
estimated R values (see Table 28.4) are less than the 7.5% MARR. Certainly, harvest-
ing decisions have to be reviewed whenever a change in the hurdle rate or MARR
occurs. The bottom line is that harvesting of the stand should be implemented only
when favourable economic conditions exist, or deferred to a later date whenever the
expected R is equal to or higher than the MARR.
Summary and Conclusion
Stumpage values of 25-, 30-, 35-, 40- and 50-year-old plantation stands of loblolly
pine based solely on the volume and value (based on summer 2000 prices) of stress-
graded dimension lumber produced therefrom were determined. Regression equa-
tions for predicting the expected total volume and value of structural-dimension
lumber yield per hectare of loblolly pine plantation stands were developed. The
expected yield values were used in an incremental analysis in conjunction with dis-
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 332
332 H.F. Carino and E.J. Biblis
counted-cash-flow techniques to determine the economic desirability of deferring
the harvesting of a loblolly pine plantation stand of a given age for the purpose of
producing structural-dimension lumber. The following can be inferred from the
results of the analysis:
1. Structural-dimension lumber volume yield of loblolly pine timber from managed
plantations incr
eases with stand age. For 25-, 30-, 35-, 40- and 50-year-old stands like
those investigated, the expected total volume yield of stress-graded dimension lum-
ber could be as much as 94.4 , 122.4 , 151.0, 179.0 and 235.0 m
3
/ha, respectively. On
average, the expected annual increase in volume yield could be about 5.61 m
3
/ha.
2. The quality of loblolly pine plantation timber increases with stand age. This was
clearly r
eflected by the percentages (based on volume yield) of structural-dimension
lumber graded No. 1 and better, which are 16.0, 36.2, 46.7, 49.3 and 83.0%, respec-
tively, for 25-, 30-, 35-, 40- and 50-year-old stands. This was also reflected by the
expected unit value yield of structural-dimension lumber from the 25-, 30-, 35-, 40-
and 50-year-old stands, which are $106, $123, $140, $157 and $192/m
3
, respectively.
On average, the expected annual increase in unit value yield could be about
$3.42/m
3
.
3. Stumpage value of loblolly pine plantations based solely on the value of dimen-
sion lumber pr
oduced increases with stand age. For 25-, 30-, 35-, 40- and 50-year-old
stands like those investigated, the expected total value yield of stress-graded dimen-
sion lumber could be as much as $10,006, $15,055, $21,140, $28,103 and $45,120/ha,
respectively. On average, the expected annual increase in value yield could be about
$1399/ha.
4. It would be economically desirable to defer the harvesting of a 25-year-old plan-
tation stand of loblolly pine like the one investigated by 5, 10, 15 or 25 years if the
minimum acceptable rate of r
eturn on investment (MARR) is less than 8.5, 7.7, 7.1 or
6.2%, respectively. For a 30-year-old stand, it would be economically desirable to
defer harvesting it by 5, 10 or 20 years if the MARR is less than 6.9, 6.4 or 5.6%,
respectively. For a 35-year-old stand, it would be economically desirable to defer
harvesting it by 5 or 10 years if the MARR is less than 5.9 or 4.8%, respectively. And
for a 40-year-old stand, it would be economically desirable to defer harvesting it by
10 years if the MARR is less than 4.8%.
References
American Society for Testing and Materials (ASTM) (1999) Standard test methods of static tests
of lumber in structural sizes D 198–98. Standard Practice for Properties of Visually Graded
Lumber. D 245–99. Annual Book of ASTM Standards, Section 4, Vol. 04.10. West
Conshohocken, Pennsylvania.
Biblis, E.J. and Carino, H.F. (1999) Flexural properties of lumber from a 50-year-old loblolly
pine plantation. Wood and Fiber Science 31, 200–203.
Biblis, E.J., Carino, H.F. and Teeter, L. (1998) Comparative economic analysis of two manage-
ment options for loblolly pine timber plantations. Forest Products Journal 48(4), 29–33.
Biblis, E.J., Carino, H.F. and Brinker, R. (1997) Flexural properties of lumber from two 40-year-
old loblolly pine plantations with different stand densities. Wood and Fiber Science 29,
375–380.
Biblis, E.J., Carino, H.F., Brinker, R. and Mckee, C.W. (1995) Effect of stand density on flexural
properties of lumber from two 35-year-old loblolly pine plantations. Wood and Fiber
Science 27, 25–33.
Biblis, E.J., Brinker, R., Carino, H.F. and McKee, C.W. (1993) Effect of stand age on flexural
properties and grade compliance of lumber from loblolly pine plantation timber. Forest
Products Journal 43(2), 23–28.
32Amaro Forests - Chap 28 1/8/03 11:54 am Page 333
333 Expected Volume and Value of Lumber
Carino, H.F. and Biblis, E.J. (2000) Comparative analysis of the quality of sawlogs from 35-, 40-,
and 50-year
-old loblolly pine plantation stands. Forest Products Journal 50(11/12), 48–52.
Pearson, R.G. and Gilmore, R.C. (1971) Characterization of the strength of juvenile wood of
loblolly pine (Pinus taeda L.). Forest Products Journal 21(1), 23–30.
Southern Pine Inspection Bureau (1994) Grading Rules. SPIB, Pensacola, Florida, 134 pp.
Schultz, R.P. (1997) Loblolly Pine: the Ecology and Culture of Loblolly Pine (Pinus taeda L.).
Agriculture Handbook 713. USDA Forest Service, Washington, DC, 3 pp.
Zobel, B.J. and Blair, R. (1976) Wood and pulp properties of juvenile wood and topwood of the
southern pines. In: Proceedings of the 8th Cellulose Conference and Applied Polymer
Symposium, Vol. 28, pp. 421–433.
Zobel, B.J. and Kirk, D.G. (1972) Wood properties of young loblolly and slash pines. In:
Proceedings of a Symposium on the Effect of Growth Acceleration on the Properties of Wood.
USDA Forest Service, Forest Products Laboratory, Madison, Wisconsin.
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33Amaro Forests - Chap 29 25/7/03 11:09 am Page 335
29 Comparing Models for Growth
and Management of Forest Tracts
J.J. Colbert,
1
Michael Schuckers
2
and
Desta Fekedulegn
2
Abstract
The Stand Damage Model (SDM) is a PC-based model that is easily installed, calibrated and ini-
tialized for use in exploring the future growth and management of forest stands or small wood
lots. We compare the basic individual tree growth model incorporated in this model with alter-
native models that predict the basal area growth of trees. The SDM is a gap-type simulator. It is
a non-spatial, individual sample-tree diameter growth model, following the work of Botkin,
Shugart and others. Within SDM, the basic growth model is adjusted to account for shading,
competition and climate. Here we make those adjustments by calibrating the growth model to
historical data for individual sample trees. We fit alternative sigmoid growth models to the
same historical data and compare these models’ ability to predict short-term (5-year) and
longer term growth of trees. Accuracy and potential effects of bias are discussed relative to the
age and source locations of sample trees used in this study.
Introduction
The Stand Damage Model (SDM), a component of the Gypsy Moth Life System Model,
calculates tree diameter growth, current diameter and height, and tree mortality for
each year of a simulation. The model is a distance-independent, tree-growth simula-
tor, a gap model based on the work of Botkin (1993), Shugart (1984) and others. Each
year, the model calculates the diameter growth of trees as a function of relative
stocking (a measure of tree crowding), shading, heat and defoliation. The model can
be used to predict future growth of a forest stand or tract that the user wants to con-
sider as a homogeneous unit. The user can design tree removals to simulate various
kinds of silvicultural regimes at any year of a simulation. The user provides data for
management actions, including the year of entry, selection criteria for removals and
species-specific targets. The model has the ability to simulate predefined defoliation
scenarios over a 20-year period from the initial stand conditions or the user can
decide to have defoliation occur at any time and at intensities as input through the
1
USDA Forest Service, USA
Correspondence to: jcolbert@fs.fed.us
2
Department of Statistics, West Virginia University, USA
© CAB International 2003. Modelling Forest Systems (eds A. Amaro, D. Reed and P. Soares) 335