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Chapter 4: Alternative Views of the Future

Introduction

The base case discussed in detail in chapter 3 provides one view of the possible 

future of the U.S. forest products sector. Projections are dependent on the many 

parameters and behavioral rules incorporated in the projection models. They are 

also dependent on the assumptions made about the economic and resource conditions that lie outside the model (e.g., population, national income, and land use 

trends as presented in chapter 2). The external assumptions used in the base case 

were drawn from an array of creditable sources to provide a consistent and “likely” 

outlook, but they still represent only one set of possible future conditions. By 

varying background assumptions and recasting the projection, it is possible to learn 

more about the sensitivity of outcomes to external conditions and to build some 

qualitative notions of the key uncertainties in the outlook.1

This chapter examines an array of alternative futures that explore variations 

in some of the major background assumptions of the base case. Scenario planning 

has been a formal part of the timber assessments since the 1983 update (Haynes 

and Adams 1985). Timber assessments in the past two decades have included 46 

alternative futures. Here we examine six that reflect both contemporary issues as 

well as several reflecting longstanding concerns such as the extent of reforestation 

and climate change. The scenarios and their rationales are tabulated below. Detailed 

results are summarized in app. 1, table 41.

1

These alternative futures provide users of the RPA timber assessment with a basis for 

“scenario planning” by using classical sensitivity analysis, where a limited number of 

key exogenous and endogenous elements are varied in a projection, and key results are 

examined for differences. These differences allow the identification of emerging problems 

and provide a way to measure the effectiveness of possible solutions to those problems 

(Schwartz 1991).
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GENERAL TECHNICAL REPORT PNW-GTR-699

Scenario name Rationale for examination What gets changed?

Reduction in other 

private timberland 

area

Other private ownerships are rapidly 

losing timberland area. What is the 

impact of this loss on future timber 

supplies?

Accelerate land loss from other private 

ownerships in all regions relative to the 

base case.

Climate change What would differential shifts in 

timber growth rates across regions 

do to the U.S. forest sector outlook 

and regional positions?

(1) Adjust prospective timber growth rates in 

the ATLAS model for effects of both climate 

and elevated carbon dioxide. 

(2) Adjust prospective timber growth rates in 

the ATLAS model for effects of climate change 

only.

Restoration 

thinning on 

public lands 

in the West

A side effect of a program to restore 

the health of public forest lands in the 

West would be larger volumes of timber 

harvest. What would be the market

effects of this expanded public harvest?

Raise public harvest in interior West regions 

consistent with one possible restoration 

thinning program.

Sequestration 

of carbon in 

plantations

What would be the impacts of a large 

program to expand U.S. forest carbon 

sequestration through afforestation of 

marginal agricultural lands? This case 

is the opposite of the other private land 

loss scenario.

Add plantations from hypothetical carbon 

sequestration program to timberland base.

Southern pine 

plantation 

establishment

How important is management 

intensification on private timberlands 

to the timber supply outlook of the 

South and the United States?

Reduce the rate of pine plantation 

establishment on private lands in the 

South to 10 percent below the base 

by 2020.

Reduction in Nonindustrial Private Timberland Area

In the base case, nonindustrial private forest (NIPF) timberland area was projected 

to decline by nearly 1 percent per decade in the Southeast (SE) and by 0.4 percent 

per decade in the Pacific Northwest West (PNWW) (largely as a result of losses to 

development) but to rise at about 0.2 percent per decade in the South Central (SC) 

(owing to agricultural land reversion to forest). These changes are consistent with 

historical multidecade trends in these regions. In the present scenario, we examine 

a case of NIPF timberland loss in all regions at rates substantially higher than the 

base. For the SE and PNWW, NIPF area declines by 5 percent each decade and for 

the SC region by 2 percent each decade from the year 2000 base level (see table 

18). Accelerated area reductions for the SE and PNWW regions assume regionwide 

application of findings from recent Forest Inventory and Analysis (FIA) surveys for 

North Carolina (Brown 2004) and western Washington (Gray et al. 2005) that show 

5-percent decadal reductions in the most recent remeasurements in those regions. 
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The SC region has a slight increase projected in the base case because of opportunities to afforest agricultural lands. Under the present scenario, these opportunities 

are assumed to be less extensively promoted by the next national farm bill and any 

regional environmental restoration efforts (e.g., bottomland hardwood ecosystem 

restoration). As a result, conversions to other uses dominate reversions to timberland over the projection period in the region. 

In the simulation process, timberland area was reduced in proportion to current 

area by forest type. For the miscellaneous corporate portion of the NIPF class 

(which contains timber investment management organizations [TIMOs] and real 

estate investment trusts [REITs]), there has been a general increase in timberland 

area since 1990, while the “farmer and miscellaneous” component has declined. To 

reflect this ownership difference, we held the timberland area of the miscellaneous 

corporate component constant in the scenario. 

As NIPF timberland area drops gradually below the base case in the South 

and PNWW, NIPF inventories in these regions fall, harvests decline, and stumpage prices rise. By the last decade of the projection (2041–2050), Southern NIPF 

softwood inventory is 12 percent below the base level and hardwood inventory is 

10 percent smaller (see figs. 49 and 50). In the face of declining inventories, annual 

Southern NIPF softwood and hardwood removals fall in the area reduction alternative on average 2 percent over the 2020–2050 period (see fig. 51 for softwood 

removals). In the PNWW, NIPF softwood inventory falls by 11 percent from the 

base level in the final decade (see fig. 49) and average softwood removals drop by 

5 percent in the 2020–2050 period. 

Table 18–Timberland area in nonindustrial private forest (NIPF) ownership by 

region, base case, and reduced NIPF timberland scenario

Scenario and area 2000 2010 2020 2030 2040 2050

Base—

Southeast 60.739 60.116 59.470 59.097 58.385 57.614

South Central 82.285 82.525 82.752 82.909 83.037 83.130

Pacific Northwest West 4.751 4.725 4.705 4.687 4.671 4.658

Reduced NIPF area—

Southeast 60.739 57.702 54.819 52.078 49.474 47.000

South Central 82.285 80.639 79.027 77.446 75.897 74.380

Pacific Northwest West 4.752 4.514 4.288 4.073 3.870 3.677

Note: Lands held by firms with commercial timber production objectives but no processing facilities (e.g., 

timberland investment organizations [TIMOs] and real estate investment trusts [REITs] are included in both 

forest industry and nonindustrial private forest categories, depending on their classification in the starting 

(approximately 1995) inventory data. See text in chapter 2 “Projected Area Changes for Land Uses and Forest 

Management Cover Types” section for further discussion.
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GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 49—Softwood growing-stock inventory for base and reduced-NIPF-timberland-area scenario, for 

Pacific Northwest West and Southern nonindustrial private (NIPF) land.

Figure 50—Hardwood growing-stock inventories for base and reduced-NIPF-timberland-area scenario, 

for Southern nonindustrial private (NIPF) land.

1990 2000 2010 2020 2030 2040 2050 2060

Year

0

10

20

30

40

50

Softwood growing-stock inventory 

(billion cubic feet)

Southeast base

Southeast reduced area

South Central base

South Central reduced area

Pacific Northwest West base

Pacific Northwest West reduced area

1990 2000 2010 2020 2030 2040 2050 2060

Year

40

45

50

55

60

65

Hardwood growing-stock inventory (billion cubic feet)

South Central base

South Central reduced area

Southeast base

Southeast reduced area
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The 2005 RPA Timber Assessment Update

Figure 51—Softwood growing-stock removals for base and reduced-NIPF-timberland-area scenario, 

for Southern nonindustrial private (NIPF) land.

Although these inventory changes are sizable, the associated harvest shifts 

are smaller and have limited impacts on markets at the regional and national 

levels. Southern and PNWW softwood stumpage prices rise by 2 percent and 3 

percent, respectively. Both Southern and PNWW lumber output decline by less 

than 1⁄2 percent, national lumber prices rise by less than 1⁄4 percent, and total U.S. 

lumber output falls by about 0.1 percent. The damping of regional and national 

impacts reflects, in part, substitution between owner groups within regions and 

across producing regions. In the South and PNWW, forest industry owners expand 

annual harvest by 1 and 2 percent, respectively, in the period from 2020 to 2050 in 

response to higher stumpage prices, offsetting the reductions on NIPF ownerships. 

Expanded output in other U.S. regions and in imports also counters the small reductions in PNWW and Southern softwood lumber output. Thus, despite the loss of 

more than 7 percent of the U.S. NIPF timberland base by 2050, the price and output 

impacts are heavily moderated.

1990 2000 2010 2020 2030 2040 2050 2060

Year

5.0

4.5

4.0

3.5

3.0

2.5

Softwood growing-stock removals 

(billion cubic feet)

South base

South area reduction
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GENERAL TECHNICAL REPORT PNW-GTR-699

Effects of Climate Change on U.S. Forests and 

Forest Products Markets 

Global climate change may modify the growth rates and geographic distribution 

of forests in North America (National Assessment Synthesis Team 2000, Neilson 

et al. 1998). Forests are affected by changes in atmospheric carbon dioxide (CO2) 

levels, annual and seasonal temperature patterns, and precipitation regimes (Norby 

et al. 2005). These changes influence physiological processes in trees, such as 

tree growth and, ultimately, the ability of trees to survive in various regions. The 

extent and geographic distribution of specific climatic and vegetation shifts remain 

uncertain. Research with climate models and ecological process models2 presently 

yields fairly broad ranges of possible impacts, even for large regions. One contribution to this variation is the assumption about the influence of elevated atmospheric 

CO2 on plant growth, the “fertilization” effect. Recent field research has suggested 

that this influence of the elevated atmospheric CO2 on plant growth may be less 

than originally reported (Oren et al. 2001). For this report, we examine the potential 

impact of climate change with and without this assumption about fertilization on 

the productivity response in forests and the consequent changes in the forest sector.

Changes in forest growth and location will affect human use of forests. Accelerated growth and forest expansion in some regions would raise timber inventories 

and provide a basis for expanded harvest and wood products production. Reduced 

growth and the decline of forests in other regions would lead to a contraction in 

commercial use. Noncommodity services of forests would be affected as well, 

including recreation and amenity uses as described by Irland et al. (2001). Several 

past studies have examined the impacts of climate change on commodity output 

in the forest sector (Alig et al. 2002, 2004a; Joyce et al. 1995; McCarl et al. 2000; 

Perez-Garcia et al. 2002; Sohngen and Mendelsohn 1998). 

In the present study, we use one projection of climate from the Hadley Centre 

in the United Kingdom that has been used in a number of recent ecological studies (National Assessment Synthesis Team 2000). The projected warming over the 

21st century in the United States is approximately 5 °F. Regionally, the Hadley 

model scenario projects Eastern U.S. temperature increases of 3 to 5 °F by 2100 

and greater increases in temperature (up to 7 °F) in the Western United States. 

The entire United States is projected to have increases in precipitation, except 

for the gulf coast and the Pacific Northwest. These increases vary regionally and 

2

So-called GCMs or global circulation models describe climate patterns as the chemistry 

of the atmosphere is projected to change with economic and population growth globally. 

Using these potential future climates, ecological models, in turn, estimate climate impacts 

on forest productivity and location.
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seasonally. Under this climate scenario, atmospheric CO2 continues to increase 

and influence plant growth. This scenario will be referred to as the “climate + 

CO2” scenario. We examine a second scenario with the same climate scenario, but 

here we assume that the elevated carbon dioxide does not enhance plant growth, a 

“climate only” future.

In the “climate + CO2” scenario, climate and elevated CO2 act to augment 

growth in all regions. Both softwood and hardwood growth on private lands expand 

steadily (relative to the base), with particularly large percentage changes in the 

Western regions. In the “climate only” scenario, some regions continue to realize 

increases in timber growth (e.g., SE), while growth in other regions declines (e.g., 

SC). For the United States as a whole, however, both scenarios lead to overall 

increases in both softwood and hardwood inventories on private lands. Projections 

are shown in figure 52. Relative to the base, average private softwood inventory 

over the 2010–2050 period rises by 9.3 percent and hardwood inventory by 5.6 

percent in the “climate + CO2” scenario but by only 2.3 percent and 1.2 percent, 

respectively, in the “climate only” scenario. The “climate + CO2” scenario influences tree growth and, consequently, softwood and hardwood inventories more 

positively than the “climate only” scenario. As in previous climate impact analyses, 

the regional impacts differ and can be quite different from the national average 

results, reflecting regional climate changes. The greatest relative increases in 

softwood inventories for both climate scenarios is in the South. And in contrast to 

the base, where Southern hardwood inventories declined, the volume of hardwood 

growing stock rises steadily throughout the “climate + CO2” projection. 

Because the inventory changes are gradual, their impacts on private timber harvest, timber prices, and ultimately on product markets and prices in both scenarios 

are relatively small and expand over the projection. For example, total U.S. softwood sawtimber harvest in 2050 increases by 0.9 percent in the “climate + CO2” 

scenario and by only 0.3 percent in the “climate only” scenario. For the “climate 

only” scenario, the small aggregate increase reflects the mix of harvest expansion 

in some regions (PNWW, Pacific Southwest [PSW], and SE) and decline in others 

(Pacific Northwest East [PNWE], Southern Rockies [SR], North Central [NC], and 

SC). Regional stumpage prices are somewhat more sensitive, with 2050 softwood 

sawtimber prices falling by 18 percent in the PNWW and 11 percent in the South 

under the “climate + CO2” scenario. In the “climate only” scenario, 2050 PNWW 

prices fall by 6 percent and by just 1 percent in the South.

Impacts in national product markets are further muted given extensive interregional and international substitution. By 2050 annual softwood lumber production 

in the United States rises by about 1.1 percent in “climate + CO2” scenario, imports 

The effects of climate 

change are gradual.
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GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 52—Total U.S. softwood and hardwood growing-stock inventory on private lands under the 

base, global change No. 1 (climate + CO2 ) and global change No. 2 (climate only) scenarios.

180

200

220

240

260

280

300

320

340

400

380

360

340

320

300

280

1960 1980 2000 2020 2040 2060

Growing-stock inventory (billlion cubic feet) Growing-stock inventory (billlion cubic feet)

Softwood

1960 1980 2000 2020 2040 2060

Year

Year

Hardwood

Global Change No. 1

Global Change No. 2

Base

Global Change No. 1

Global Change No. 2

Base
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The 2005 RPA Timber Assessment Update

fall by 1.1 percent, and consumption rises by about 0.2 percent. National market 

changes for the “climate only” scenario are half or less of the “climate + CO2” case. 

Further details of changes are shown in app. 1, table 41.

Restoration Thinning on Public Lands in the West

Large areas of public forest land in the Western States support overly dense stands 

and abnormally high accumulations of fuels, partly as a result of decades of fire 

protection and cutting practices that emphasized ponderosa pine. As a result, forests 

in these areas have reduced growth rates, higher mortality, increased susceptibility 

to insect and disease outbreaks, and higher risk of catastrophic wildfires. Thinning 

in these stands to reduce fuels and mortality has been proposed as one approach to 

ecosystem restoration and improving forest health. The Healthy Forests Restoration 

Act of 2003 (PL 108-148) was enacted in part to facilitate stand treatments on federal lands with these objectives, but its provisions have yet to be made operational.

Implementation of a restoration thinning program would entail balancing an 

array of political, ecological, and economic considerations. Some of the major 

issues include, first, identifying stands and areas in need of treatment. Criteria 

might include the extent of fuel accumulation, departures from potential growth 

(e.g., as measured by an index of stand density), extent of species imbalance (e.g., 

unnaturally large numbers of fire-sensitive species), or some combined criterion 

such as the Fire Regime Current Condition Class (FRCCC) proposed by Schmidt 

et al. (2002), which estimates how far a stand has departed from natural wildfire 

conditions by integrating all these components.

The second issue is determining areas to be reserved from treatment. Portions 

of the public lands have been set aside for a wide array of purposes, including 

wilderness areas, natural areas, recreation areas, and habitat conservation or 

rehabilitation areas. It may be desirable to exclude some of these areas from thinning treatment to allow natural or other vegetation change processes to continue 

undisturbed.

The third issue is prescribing the form of the thinning treatment. The trees to 

be removed must be identified. Options generally involve the range of diameters 

that can be removed, starting with the smallest and moving up to some maximum. 

How many (and what sizes of) trees or how much basal area to remove depends on 

the objectives used in identifying the stands (in the first issue above) and relate to 

desired conditions in the postthinning stands.
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GENERAL TECHNICAL REPORT PNW-GTR-699

The fourth issue is providing access to thinning areas. Large areas of forest in 

need of thinning (by a number of different criteria) lie far from road access. These 

areas may be eliminated from consideration unless decisions are made to construct 

roads.

The fifth issue is administering a treatment program and auditing costs. Even 

small-scale thinning programs could entail large numbers of treatment areas, requiring an expanded administrative structure within public forestry agencies to manage 

the thinning process, identify actual work areas on the ground, secure contractors 

or others to conduct the thinnings, and audit accomplishments and the costs of the 

program. Decisions are also required on the form and extent of any payments to be 

made by contractors for merchantable material removed, requirements for treatment 

of nonmerchantable material (small and dead wood), and whether subsidies will 

be offered to contractors for the treatment of areas with little or no merchantable 

material.

The areas to be thinned and the extent and quality of potential harvest volumes 

will be determined by the conditions noted above. At present, only small-scale 

projects (unrelated to the Healthy Forests Act) have been implemented in local areas 

under highly diverse circumstances, so no definitive guidelines on removal volumes 

are available. As a result, studies that have attempted to estimate potential thinning 

removals have done so under an array of assumptions about possible constraints. But 

even with fairly restrictive conditions on areas to be treated, limitations on access 

and maximum size of stems to be harvested, it is likely that a Westwide restoration 

thinning program would generate very large volumes of both merchantable sawtimber and biomass.3

 Rummer et al. (2003), for example, attempted a broad-scale 

assessment of potential thinning harvest volumes in the Western States. In a case 

where they assumed that only material from the readily accessible and highest risk 

stands could be removed (FRCCC class 3) to reach lower stand-density targets, they 

found sufficient volume to provide wood for 25 percent of the current conventional 

wood products processing capacity in the Western States for the next 30 years.

The scenario examined here was based on this latter example. Rummer et al. 

(2003) estimated that 576.1 million bone dry tons of wood fiber could be removed 

from the highest-risk land class (FRCCC class 3) on all ownerships.4 Assuming that 

3

See, for example, Fried et al. (2003) for a case that focuses on biomass generation in 

Oregon and California, and Adams and Latta (2005), which looks at sawtimber volumes 

that could be removed in thinning operations in eastern Oregon.

4

The silvicultural objective of this thinning is to reduce stand stocking, as measured by the 

stand density index, to a lower level allowing higher growth and reducing mortality. See 

Rummer et al. (2003).
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The 2005 RPA Timber Assessment Update

roughly 60 percent of this aggregate estimate would come from public land, that 

only 60 percent of this public land is actually accessible with existing roads, and 

that about 70 percent of the removals would represent merchantable material, the 

total sawlog volume would amount to about 148 million bone dry tons or roughly 

11.6 billion cubic feet. We assume that this volume is removed in a 30-year initial 

program (2006–2035) at 387 million cubic feet per year.5 If, as seems likely, a 

natural fire regime is not instituted in the region after the first thinning, continued 

thinnings would be required to maintain stand conditions. To emulate this process, 

we set removals at one-third their initial level for the remainder of the projection 

(2036–2050).

Thinning volumes enter the timber assessment projection model as a fixed 

expansion in Interior West public sawlog supply. This should reduce softwood 

stumpage prices in the region, stimulating expanded lumber output and expansion 

in processing capacity as the thinning program continues. This expansion takes 

place in those areas with an established industry (eastern Oregon, eastern Washington, and the northern Rockies). Higher lumber output at lower costs in the West will 

substitute for some production in Eastern regions and for imports. Softwood lumber 

prices would be expected to fall and U.S. consumption to rise. The speed and extent 

of these changes depend heavily on the rate at which softwood lumber and plywood 

processing capacity can be expected to expand in the Interior West region as a 

thinning program is initiated. Prior to 1990, public lands were the largest source of 

timber in the region. With the redirection of public lands management after 1990 

and the associated reduction in public timber harvest, processing capacity has 

declined. We estimate that softwood lumber capacity fell by 40 to 50 percent for 

the region as a whole between 1989 and 2002, whereas for the SR region alone, the 

decline was closer to 75 percent. With low current capacity levels, large increments 

in public timber supply are likely to sharply depress stumpage prices at the outset 

of the program. This will provide some inducement to expand capacity, which in 

turn will act to move stumpage prices back toward base levels. Capacity changes 

in the assessment projection model are based largely on profitability measures, 

and this leads to fairly rapid capacity growth in the scenario results. Many other 

considerations are known to influence real-world capacity investment decisions, 

however, including perceived risk and stability of input supply—issues which could 

act to alter the capacity change projected by our model. Rates of capacity expansion 

5

This is the total for all public lands in the Interior West region, which comprises the 

PNWE, Pacific Southwest, Northern Rockies, and Southern Rockies RPA assessment 

regions.

Falling lumber 

production in 

the Interior West 

complicates efforts to 

increase thinning.
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GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 53—Softwood lumber market effects of a restoration thinning program in the Interior West region and United States 

projected to 2050.

slower than those projected in the scenario would increase the regional stumpage 

price effect but reduce all of the production, consumption, and trade adjustments.

As illustrated in figure 53, annual softwood lumber production in the Interior 

West rises rapidly (under our capacity-expansion assumptions) to about 2.0 billion 

feet above the base case. As supply expands, U.S. softwood lumber price falls, on 

average about 4.0 percent over the 2010–2050 period. In response, annual softwood 

lumber production in other regions falls by 560 million board feet, yielding an 

increase in aggregate U.S. softwood lumber output of roughly 3.8 percent or about 

1.4 billion board feet on an annual basis. Annual softwood lumber imports are also 

highly sensitive to price and fall by about 890 million board feet. As a result, the 

net increase in annual U.S. softwood lumber consumption is only some 560 million 

board feet, a bit more than one-quarter of the original production increment in the 

Interior West region.

20

25

30

35

40

45

50

Softwood lumber production 

(billion board feet)

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

Softwood lumber producer 

price index (1982 = 1.0)

5

10

15

20

25

30

Softwood lumber imports 

(billion board feet)

United States 

1970

1980

1990

2000

2010

2020

2030

2040

2050

2060

1970

1980

1990

2000

2010

2020

2030

2040

2050

2060

5

6

7

8

9

10

11

12

13

14

Softwood lumber production 

(billion board feet)

Interior West 

Thin

Base

Thin

Base

United States 

1970

1980

1990

2000

2010

2020

2030

2040

2050

2060

1970

1980

1990

2000

2010

2020

2030

2040

2050

2060

United States

Thin

Base

Thin

Base

Year Year
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The 2005 RPA Timber Assessment Update

Figure 54—Interior West softwood sawtimber harvest by owner and private softwood growing 

stock for base and restoration thinning projected to 2050.

Expanded public timber harvest reduces Interior West stumpage prices and the 

incentive to harvest timber on private lands in the region as shown in figure 54. 

This public-for-private harvest substitution yields a gradually accumulating “inventory savings” on private lands (see the lower graph in fig. 54). When public timber 

harvest drops back to lower levels and stumpage prices rise after 2035, private 

harvest expands above the base level to exploit this potential.

1990 2000 2010 2020 2030 2040 2050 2060

Year

1990 2000 2010 2020 2030 2040 2050 2060

Year

1.2

1.0

0.8

0.6

0.4

0.2

0

Softwood sawtimber harvest 

(billion cubic feet)

45

50

55

60

65

70

Private softwood growing-stock inventory 

(billion cubic feet)

Private base

Private thin

Public base

Public thin

Thin

Base
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GENERAL TECHNICAL REPORT PNW-GTR-699

Sequestration of Atmospheric Carbon in 

Forest Plantations

Human activities have played a significant role in raising the atmospheric concentrations of greenhouse gases (including CO2) through the combustion of fossil fuels, 

use of certain agricultural practices, and land-use changes (IPCC 2001). In the global 

carbon cycle, terrestrial ecosystems are important sources and sinks of atmospheric 

carbon. Roughly half of all carbon in terrestrial systems is stored in forest vegetation 

as biomass and as organic carbon in the soil and is subject to decrease or increase 

as a result of disturbance (including harvest), regrowth, or conversion to other uses 

(Watson et al. 2000, [table 1, pg. 4, in Policymaker Summary]). Historically, changes 

in land use have been major factors affecting terrestrial carbon sinks. During the 

period 1850–1998, cumulative CO2 emissions from land-use change are estimated to 

have contributed 33 percent of total global emissions (Bolin and Sukumar 2000). In 

the United States, Houghton et al. (1999) estimated that changes in land use released 

about 25 Pg (25 billion metric tonnes) of carbon to the atmosphere over the period 

1700–1990, largely from the conversion of forests to agricultural lands and from 

cultivation of prairie soils.

Expanding forest area through afforestation of economically marginal agricultural lands has been proposed as one approach to reduce net emissions of CO2 in the 

United States and other countries. Several studies in the United States over the past 

decade have attempted to assess the extent of the area that might be suitable for such 

afforestation and the costs of the additional carbon sequestered. Results have shown 

a fairly broad range of cost and area estimates. Moulton and Richards (1990), for 

example, found that nearly 120 million acres of land might be afforested at carbon 

costs of $20 per (short) ton or less, increasing carbon flux by roughly 250 million 

(short) tons per year. In contrast, Parks and Hardie (1995), using a different approach 

to cost estimation, found that almost no land could be afforested for carbon sequestration if forest carbon was worth only $20 per ton. A recent survey by Stavins and 

Richards (2005) summarized a wide array of carbon cost studies, virtually all of 

which examined only afforestation as a means to increase forest carbon flux. Using 

what might be called the trend results from this set of studies, they found that at a 

carbon value of $20 per ton, perhaps as much 80 million tons per year of additional 

carbon might be sequestered through afforestation. Based on afforestation area and 

carbon flux estimates from Stavins and Richards, an 80-million-ton annual program 

could require as much as 42 million acres of agricultural land.6

6

Based on simple proportioning from area and sequestration rate estimates presented by 

Stavins and Richards (2005: p 33).
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The 2005 RPA Timber Assessment Update

7

The land area estimate was derived by using the same proportioning approach as in 

footnote 4, and the approximate carbon value was derived from figure 6 in Stavins and 

Richards (2005).

In this scenario, we examine the market and resource impacts of a relatively 

modest 6-million-acre expansion in U.S. forested area through afforestation of 

agricultural land. Such a program could yield roughly a 7-million-short-ton annual 

increment in U.S. forest carbon flux and would be roughly consistent with a carbon 

value of just less than $10 per ton.7 Following patterns observed in previous programs of agricultural land diversion (e.g., the Soil Bank and Conservation Reserve 

Programs), 90 percent of the afforestation was assumed to occur in the South, 

roughly 7 percent in the West, and 3 percent in the North. These lands would be 

part of existing farming/ranching operations and hence were classed with the NIPF 

owner group. For the South, the area change amounts to a 2.7 percent increase in 

total regional timberland. For the United States as a whole, 6 million acres represents about a 1.7-percent increase in the private timberland base. 

In the South and West, all plantations were assumed to be in softwood types 

(again similar to experience in earlier programs), whereas in the North, a small 

fraction (20 percent) was planted to the oak-hickory type. The land was classed 

as medium-site forest land. The plantations were assumed to be given low to 

medium management treatment beyond initial stand establishment and were 

treated as available for commercial timber harvest once they passed minimum 

merchantability thresholds.

Given the relatively modest size of the timberland area increment, the aggregate 

resource and market impacts of this scenario are limited. As the afforested areas 

mature, NIPF softwood inventories rise above the base as shown in figure 55. 

Because the largest portion of the new timberland is in the South and given the 

rapid early growth rates of Southern planted pine, the inventory increments are 

observable relatively early in this region. Inventory differences have roughly 

stabilized by 2040, when Southern NIPF softwood inventories are about 11 percent 

above the base. Changes are smaller in the West and North and discernable in 

figure 55 only near the end of the projection. Increased inventory stimulates some 

additional timber removals in the South, as shown in figure 56, but the change is 

significant only after 2035 and averages less than 0.5 percent in the last 15 years 

of the projection. Changes in the North and West are too small to be visible in 

the figure. As a result, impacts on regional stumpage prices and national product 

markets and prices are also small. 
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GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 55—Softwood growing-stock inventory for nonindustrial private owners in selected regions under base and increased 

afforestation cases projected to 2050.

Figure 56—Softwood growing-stock removals (all owners) by major region under base and increased afforestation cases 

projected to 2050.

1990 2000 2010 2020 2030 2040 2050 2060

Year

0

10

20

30

40

50

60

Softwwod growing-stock inventory 

(billion cubic feet)

Southeast base

Southeast afforest

North base

North afforest

South Central base

South Central afforest

Pacific Northwest West base

Pacific Northwest West afforest

1990 2000 2010 2020 2030 2040 2050 2060

Year

0

1

2

3

4

5

6

7

8

9

10

Softwood growing stock removals 

(billion cubic feet)

South base

South afforest

West base

West afforest

North base

North afforest
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The 2005 RPA Timber Assessment Update

Reduced Southern Pine Plantation Establishment

In the base case, the area of planted pine on private lands in the South grows steadily 

through the projection, rising by 12.4 million acres between 2000 and 2050. Southern planted pine area rises from 16 percent of the private timberland base in 2000 to 

24 percent by 2050. How important is this increase in plantation area to the softwood 

(and hardwood) supply potential of the South and the United States? This scenario 

examines a gradual reduction in Southern planted pine area, falling to 10 percent 

below the base case by 2020 (see table 19), a total reduction of some 4.2 million 

acres by 2050. Planted pine area was reduced in the projection on all private ownerships and all sites and was redistributed proportionally across the other forest cover 

types, both softwood and hardwood. As a result, the total projected timberland area 

(summed across all forest cover types) remains the same as the base.

Table 19—Southern private timberland area by cover type for base and 

reduced planted pine area scenarios

Base Reduced planted pine area

Year Planted pine Other types Planted pine Other types

Million acres Percent change from base

2000 29.257 149.457 0 0

2005 32.401 146.212 -2.50 0.55

2010 34.487 143.813 -5.00 1.18

2015 36.289 141.616 -7.50 1.90

2020 37.881 139.701 -10.00 2.67

2025 39.363 137.983 -10.00 2.81

2030 40.496 136.631 -10.00 2.92

2035 41.122 135.674 -10.00 2.98

2040 41.445 134.936 -10.00 3.02

2045 41.521 134.469 -10.00 3.04

2050 41.608 134.010 -10.00 3.05

Pine plantations have more rapid growth and higher yields than other cover 

types. Less plantation area would be expected to lower future timber inventories, 

reduce timber harvests, raise stumpage prices relative to the base, and lower product 

output. As illustrated in figure 57, the private inventory reduction is substantial, and 

aggregate Southern private inventory expansion after 2020 is sharply curtailed. By 

the last decade of the projection, Southern private softwood inventory is 11 percent 

below the base. Transmission of inventory changes to timber harvest and product 

output, however, is strongly attenuated. Average annual (2010–2050) Southern 

softwood growing-stock removals fall by only 1.1 percent relative to the base (fig. 

58). Private owners continue harvesting at just below base rates despite the large difference in inventory. This is due in part to increases in Southern softwood sawtimber 

stumpage prices that reach nearly 10 percent above the base by 2050 (fig. 59).
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GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 57—Private softwood growing-stock inventory in Southern regions for base and reduced-planted-pine scenarios 

projected to 2050.

Figure 58—Softwood growing-stock removals for Southern regions for base and reduced-planted-pine scenarios projected 

to 2050.

1990 2000 2010 2020 2030 2040 2050 2060

Year

40

45

50

55

60

65

70

Softwood growing-stock inventory 

(billion cubic feet)

Southeast base

Southeast reduced planted pine

South Central base

South Central reduced planted pine

1990 2000 2010 2020 2030 2040 2050 2060

Year

5.5

5.0

4.5

4.0

3.5

3.0

2.5

2.0

Softwood growing-stock removals 

(billion cubic feet)

South Central base

South Central planted pine

Southeast base

Southeast planted pine
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The 2005 RPA Timber Assessment Update

Figure 59—Softwood sawtimber stumpage price for Southern region, base and reduced-planted-pine scenarios 

projected to 2050.

Outside of the SC region, impacts in product markets are still smaller as a result 

of substitution between suppliers. Average (2010–2050) annual softwood lumber 

production outside of the South rises by about 1 percent while southern production falls by about 0.4 percent. At the national level, average annual U.S. softwood 

lumber production falls by 0.1 percent, imports rise by 0.1 percent, and U.S. consumption declines by less than 0.05 percent. Changes for other solid wood products 

are even smaller. Thus, as seen in several preceding scenarios, price response 

and substitution—in this case between regions—act to dilute the impacts of large 

regional changes in broader market areas.

These alternative views of the future illustrate the sensitivity of outcomes to 

external conditions and provide some qualitative notions of the key uncertainties in 

the outlook. Alternative futures have been a formal part of the past six RPA timber 

assessments. These past analyses, and the new scenarios examined here (such as 

restoration thinning on public lands and the possible climate change impacts on forest growth), focus on a range of contemporary resource issues and, in some cases, 

the effectiveness of various programs to mitigate possible impacts. Results from the 

scenarios may also be useful in drawing inferences about trends in other resources, 

such as wildlife habitat, environmental services, or amenity values, in that changes 

2000 2010 2020 2030 2040 2050 2060

Year

100

150

200

250

300

Stumpage price (1982 dollars/thousand 

board feet, log scale, Scribner)

South base

South reduced planted pine
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GENERAL TECHNICAL REPORT PNW-GTR-699

in major timberland attributes (e.g., timber inventory and structure) can broadly 

affect prospective conditions for a number of forest-based goods and services.8

Examining differences and similarities across the alternative futures can help 

to identify some general characteristics of responses as projected by the models 

used in the assessment. One general observation is that land, timber, capital, and 

wood product markets will likely adjust and adapt to external conditions in ways 

that act to limit economic effects. Many changes are possible across the large timberland base, including shifts among owners and regions in timber production and 

harvests and in timber processing technology. However, adjustments across regions, 

including international responses, may at times involve lags, depending on resource 

conditions (e.g., age class distributions) or processing capacity. Several forms of 

adaptation may be used in the forest sector, including changes in (a) land use and 

forest cover types, (b) timber management intensity, (c) hardwood/softwood species 

mix of timber harvest, (d) timber harvesting patterns within and between regions, 

(e) timber rotation ages, and (f) use of wood versus other products (i.e., substitution 

of nonwood products in consumption based on relative price). 

The scenarios also illustrate the temporal differences between types of activities or actions and their associated economic effects. In our climate change scenarios, timber inventories respond gradually to climate change, and their impacts 

on private harvest, prices, and ultimately on product markets and prices are relatively small. Timber harvest rises because of increased timber inventories, as both 

softwood and hardwood growth on private timberlands expands steadily relative 

to the base. The directions of change are consistent with earlier studies, including 

the regional variation, e.g., growth increases in Western regions but reductions in 

parts of the South. The timing of impacts in the restoration thinning case is much 

more immediate, with most of the shifts in solid wood markets evident by 2010. 

In addition, even though the timber supply changes from the restoration thinning 

scenario are concentrated in the West and involve primarily sawtimber, the marketrelated impacts are felt nationally and affect both the solid wood and pulp and paper 

portions of the forest sector. 

The temporal scale for adjustments or responses is often related to whether 

the activity or issue acts initially on the market for forest products (and hence on 

existing timber stocks) or on forest management options for new or existing forests. 

8

Treatment of other resource conditions is outside the scope of this timber assessment, but 

for example, see Adams et al. (1992) projection of wildlife habitat indices as part of a forest 

resource assessment or Nalle et al.’s (2004) modeling of joint production of wildlife and 

timber. There is a growing interest in environmental markets and payments for ecosystem 

services to promote forest management that “results in better biodiversity and sustains 

local economies” (see Clarren 2006 for more details). 
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The 2005 RPA Timber Assessment Update

The public lands restoration thinning scenario, for example, has major effects on 

near-term markets for forest products and influences private timber management 

decisions only indirectly through changes in expected future prices. The carbon 

sequestration or pine plantation scenarios, in contrast, relate primarily to future 

forests and, hence, the impacts occur gradually in the future. 

Consideration of broader geographic scales acts to mitigate how some changes 

play out in local, regional, national, and international markets. For example, 

although the South may face reductions in forest growth relative to the base under 

the second climate change scenario, the region has potential to add timberland, 

especially high-yielding pine plantations. However, as with the expanded carbon 

sequestration scenario, timber and product price response and substitution act to 

reduce the impacts of large regional changes in broader market areas. 

The scenario of using forest-based activities in climate change mitigation indicates how timber markets may react to activities designed for nontimber purposes. 

Expanding afforestation on 6 million acres of marginal agricultural lands in the 

SC region could result in a 7-million-short-ton annual increment in U.S. forest 

carbon flux, or about 0.5 percent of annual U.S. emissions. Given the relatively 

modest size of the timberland area increment and the several decades required for 

maturation of the plantations, aggregate market impacts are limited. However, the 

other scenario of a reduction in NIPF timberland area indicates that deforestation 

could potentially more than offset the gain in inventory from the climate change 

mitigation scenario, in that both private softwood and hardwood growing-stock 

inventories are projected to be 13 percent lower than the base in the South by 2050 

if that deforestation occurs. Consideration of deforestation owing to changes in 

land demand manifested through land markets raises the possibility of leakage for 

climate change mitigation programs; the net impact on timberland area can be less 

than the original area increment because of countervailing timberland transfers to 

agriculture or developed uses as land markets adjust (see Alig et al. 1997 for a more 

complete discussion). 

Another market-based adjustment that can affect both timber supplies and 

climate change mitigation costs is the possibility of a reduced rate of establishment 

of a key ingredient in future timber supplies, pine plantations in the South. For 

both regions, establishment rates of pine plantations may fall below base projections if landowners perceive lower financial returns relative to the base. As with 

the expanded carbon sequestration scenario, timber and product price response and 

substitution would act to reduce the impacts of large regional changes in broader 

market areas. 
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GENERAL TECHNICAL REPORT PNW-GTR-699

Information gleaned from the bioeconomic modeling systems applied in examining different scenarios in large-scale assessments, even though some scenarios 

are not directly designed or intended as climate change scenarios, can aid policymakers in identifying implications for possible policy options in view of the joint 

production of timber and standing forest carbon. For example, the reduced NIPF 

timberland area scenario with the reduction in private softwood growing-stock 

inventory by 2050, owing to reduced pine plantation establishment would roughly 

offset the projected increase in the carbon sequestration scenario.

Key in this last point is how the base run can be interpreted as a baseline for 

expected environmental services such as carbon storage. Interpreting the base 

as a baseline illustrates several critical issues where there is not consensus in the 

scientific community such as defining a baseline that combines both biophysical 

and economic components. Here the base includes expected market impacts including increased harvests to meet future expected timber consumption and future 

timberland area losses. It includes assumptions about changes in the mix, location, 

and efficiency of processing facilities. It includes increases in forest resource conditions reflecting changes in timberland extent and improved forest management. The 

comparisons of the base with scenarios can be used to measure the incremental 

effects (referred to as additionality) of various changes, a key component in many 

of the discussions of environmental services.

Results from the restoration thinning scenario point to the importance of capacity adjustments and investment capital flows. New capacity will be located in areas 

with the ability to compete cost-effectively in domestic commodity lumber markets. 

This reflects expanding opportunities for adjustment as the projection advances and 

demand shifts resulting from substitution. For example, in the restoration thinning 

case, lumber price differences decline relative to the base as demand expands. During the early periods of this scenario, lower stumpage prices encourage expansion 

of domestic lumber production and capacity in the Interior West. This new capacity 

absorbs the additional timber made available near processing facilities; as a result, 

stumpage prices stabilize and then gradually approach prices in the base. In a 

similar fashion, initial reductions in lumber prices increase the quantities of lumber 

demanded. As prices remain lower than the base, consumers continue to shift away 

from substitutes, and lumber consumption rises further above the base. 

Similar processes of substitution by consumers and lagged adjustments in 

production take place in other sawtimber/solid wood supply scenarios, producing 

a characteristic pattern of prices and volumes. This is similar to the adjustments 

described by Haynes (2003) for an expanded national forest timber harvest scenario 
127

The 2005 RPA Timber Assessment Update

in the 2000 timber assessment. In the present update, the lumber orientation of the 

Western U.S. restoration thinning scenario means that sawlog markets are primarily 

affected. 

The Western U.S. restoration thinning scenario reveals the importance of 

lumber imports from Canada for the aggregate timber supply outlook. With Canada 

as the United States’s largest trading partner for forest products, lumber imports 

from Canada are affected both by changes in Canadian timber harvest levels and 

U.S. harvest levels. In the scenario, U.S. lumber production rises while Canadian 

imports drop, and there are ripple effects in other regions. Producers in Canada and 

the U.S. South are the most cost-effective suppliers of softwood lumber, and when 

the design of a scenario reduces or alters softwood lumber consumption or production, the various adjustments are borne by producers in less cost-effective regions, 

mostly in the Western United States. 

Finally, the climate change scenarios have higher domestic timber harvests than 

the base. However, because timber inventory changes are gradual as climate change 

alters stand growth, their impacts on private timber harvest, stumpage prices, 

and ultimately on product markets and prices are relatively small. Timber harvest 

increases are due to increased timber inventories as both softwood and hardwood 

growth on private timberlands expands steadily relative to the base. The directions 

of change are consistent with some earlier studies, including regional impacts that 

differ geographically, e.g., growth increases in Western regions, growth reduction 

in the SC region. 

In general, results across the scenarios suggest that changes in supply and 

demand interact, both regionally and nationally, and associated adjustments will 

result in national impacts that are relatively small by 2050 compared to some 

regional or short-term impacts. This insensitivity results from a large timberland 

base, flexible capital flows, numerous possibilities for substitution in resource 

and product markets, technological changes, investments in timber growing and 

processing, and other adaptation options. The ability of the forest sector to continue 

to adapt to both market and resource changes depends on deliberate policy deliberations that attempt to anticipate emerging issues and to evaluate the effectiveness of 

various means to seek solutions. 

Differences in scenario 

outcomes demonstrate 

the adaptibility of the 

forest sector.
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GENERAL TECHNICAL REPORT PNW-GTR-699
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The 2005 RPA Timber Assessment Update

Chapter 5: Summary and Discussion

Findings in the eight1 timber assessments from 1953 to 2000 trace a gradual evolution in the number and complexity of forestry issues in the United States. A persistent concern in all these studies, however, has been how to expand timber production 

and utilization from a contracting forest land base to meet growing and evolving public needs and expectations for a variety of forest goods and services. Past assessments 

provide evidence of a substantial expansion in the productive capability of America’s 

forests. Since 1953, U.S. timberland area has fallen by about 1 percent while softwood inventories have risen by 14 percent and hardwood stocks have nearly doubled. 

Softwood growth rose by more than 75 percent and hardwood growth expanded by 

nearly two-thirds. At the same time, softwood harvest has increased by a third until 

recently and hardwood use has nearly doubled. The result is that in America’s forests 

today, growth is 21⁄2 times removals and the density of stocking (timber volume) per 

acre is 40 percent higher than it was 50 years ago. Of course there are regional and 

ownership variations in these trends, but in the aggregate the improvement in timber 

productivity potential has been dramatic.

In this last chapter, we summarize the main themes that emerge from the 2005 

update and offer some observations about developments that may influence the future 

of American forest management. 

Future Trends and Conditions

Expected Market Changes

The 2005 update base projection envisions continued strong growth in total U.S. 

forest products requirements (domestic consumption plus exports) to 2050. Although 

imports will rise, they will actually provide a smaller portion of the growth in total 

wood requirements between 2002 and 2050 (and domestic sources a correspondingly 

larger share) than was the case during the last five decades. Future harvests from 

domestic forests alone2 are expected to grow each year by 0.13 billion cubic feet 

(bcf), slightly greater than the trend over the past 50 years of 0.12 bcf/year (fig. 8). At 

the same time, real product price growth will fall below long-term historical rates for 

nearly all products. 

Over the 50 years from 1952 to 2002, U.S. consumption plus exports of all forest 

products (our total need for wood) rose by some 9.5 bcf. The U.S. timber harvest 

increased by 6.0 bcf, and imports rose by 3.5 bcf over this same period (fig. 8). Real 

prices of softwood lumber, hardwood lumber, and paper rose (compound rates of 

1

Prior to the five RPA timber assessments there were assessments published in 1958, 

1965, and 1974 (USDA FS 1958, 1965, 1974).

2

Excluding agricultural short-rotation woody crops (SRWC).

The essential question 

is how to expand 

timber production 

from a contracting 

forest land base.
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GENERAL TECHNICAL REPORT PNW-GTR-699

0.8, 0.4, and 0.3 percent, respectively), while prices of softwood plywood, oriented 

strand board (OSB) (since 1976), and paperboard fell. In the 2005 update base 

projection, U.S. consumption plus exports increase over the 2002–2050 period 

by 8.0 bcf. Imports grow by 2.6 bcf, while harvest from both forests and SRWC 

plantations rises by 5.4 bcf.3 Prices of softwood lumber, hardwood lumber, and 

OSB rise slowly (0.2, 0.3, and 0.1 percent, respectively); in contrast, prices of 

softwood plywood, paper, and paperboard remain stable or fall. 

Timberland Area and Forest Management Types

Between 1953 and 2002, U.S. timberland area declined by 5 million acres, or about 

1 percent, to 503.5 million acres. The 2005 update base case projects a further 

decline of about 3 percent by 2050. The major cause of deforestation will be 

conversion to developed uses (e.g., residential and commercial building sites) with 

population growth as a major factor, rather than conversion to agriculture, which 

was the dominant competing use in earlier decades.

 Several significant recent trends in private timberland ownership are expected 

to continue. The result will be a smaller private timberland base and a more numerous and diverse set of owners with smaller parcels closer to urban areas. 

• Land held by the forest industry group (firms integrated to processing) will 

continue to decline through sales to institutional and other financial investors (timberland investment organization [TIMOs] and real estate investment trusts [REITs]). These groups manage for appreciation in the value of 

the forest land asset but do not operate timber processing facilities. 

• The land base of nonindustrial ownerships is also projected to decline by 

more than 12 million acres or about 4 percent by 2050, continuing the trend 

of the past 50 years. At the same time, the number of nonindustrial landowners is expected to continue to grow and the average parcel size fall. 

• Between 1997 and 2002, the forest area in major metropolitan regions 

increased by 5 percent. Future urban development will bring still more 

urban forests and more people living closer to the remaining forest lands. 

• The area of planted pine in the South will continue to expand as U.S. 

timber production is concentrated on fewer acres. Even so, hardwood types 

will continue to dominate the forest land base in the South and throughout 

the Eastern United States. 

3

Domestic forest harvest rises by 5.3 billion cubic feet and SRWC by 0.1 billion cubic feet.
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The 2005 RPA Timber Assessment Update

Softwood Harvest

The U.S. softwood growing-stock removals rise slowly over the projection at about 

0.7 percent per year (2002–2050), driven entirely by expansion of pulpwood consumption (for OSB and wood pulp). Sawtimber cut for lumber, plywood, and other 

solid wood products declines slightly for the first decade of the projection (to 2015) 

then recovers to near current levels by 2050 (fig. 24). The decline to 2015 reflects a 

modest reduction in U.S. softwood lumber production and a steady fall in plywood 

output. Housing starts are projected to move back to levels of the late 1990s, and 

the recent rapid growth in housing unit size will come to an end. This slowing in 

end-use activity is reflected in reduced softwood lumber consumption. At the same 

time, softwood lumber imports, both from Canada in response to the interior British Columbia (BC) mountain pine beetle (Dendroctonus ponderosae) epidemic and 

from off-shore sources, continue to out-compete domestic products. Thus, in the 

period to 2015, imports grow while U.S. output slowly declines. After 2015, driven 

by expansion in residential upkeep and alteration (and by a resurgence in new housing after 2030), growth in softwood lumber consumption and overall sawtimber 

harvest resumes. Softwood plywood consumption and output fall steadily through 

2030, as substitution by OSB in all major markets continues.

In contrast, U.S. paper and paperboard output and OSB production continue 

to expand throughout the projection, driving up pulpwood consumption and total 

softwood nonsawtimber harvest (fig. 24). Between 2006 and 2050, total U.S. 

pulpwood consumption (at OSB and wood pulp mills) is projected to grow at 

an average annual rate of 0.8 percent, while roundwood pulpwood consumption 

(including export) is projected to grow annually at about 1.1 percent and wood 

residue pulpwood consumption declines by 0.7 percent per year. Over the projection 

period, wood use in OSB production expands at 1.2 percent per year and U.S. wood 

pulp production expands at 0.7 percent. Consumption of OSB rises steadily, both 

because it continues to capture market share from softwood plywood and because 

it accounts for essentially all of the future growth in structural panel consumption. 

The projected growth in U.S. wood pulp production is less than half the historical 

growth rate from 1970 to 1999 (1.5 percent).

The U.S. paper and paperboard production and consumption both experienced 

a significant downturn after 1999, associated with economic globalization and a 

decline in overall U.S. industrial production. Downsizing and import competition resulted in structural changes in U.S. manufacturing, and also in paper and 

paperboard production, with substantial labor productivity gains achieved by U.S. 

producers through consolidation and automation. 
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GENERAL TECHNICAL REPORT PNW-GTR-699

In 2004, U.S. output of paper and paperboard increased by 4 percent, reflecting the general recovery in U.S. industrial production, but paper and paperboard 

production dropped by 1 percent in 2005. In the decades ahead, production and 

consumption are projected to gradually increase along with projected increases in 

U.S. population and overall economic growth. However, U.S. per-capita consumption of paper and paperboard is projected to remain essentially flat in the decades 

ahead (at around 700 pounds per capita) while consumption per unit of gross 

domestic product (GDP) is projected to decline (fig. 19). Thus, the current growth 

outlook for U.S. production and consumption of paper, paperboard, and wood pulp 

is much lower than historical growth rates of the late 20th century (fig. 20). Whereas 

U.S. paper and paperboard output increased at an average annual rate of 2.3 percent 

from 1970 to 1999, the projections from 2001 to 2050 represent an average annual 

rate of only 0.8 percent, with very modest projected expansion in production capacity (future capacity expansion is likely to be met entirely by incremental expansions 

or upgrades at existing mills rather than construction of new mills).

The U.S. wood pulp production is projected to increase at an average annual 

rate of just 0.7 percent (from 2001 to 2050), which is less than half the historical 

growth rate from 1970 to 1999 (1.5 percent, fig. 60). Projected growth in wood pulp 

output derives from modest projected growth in paper and paperboard output and 

limited projected growth in domestic recycled fiber use. Paper recovery for recycling is projected to continue increasing in the United States, and the recovery rate 

Figure 60—U.S. paper, paperboard, and pulp production projected to 2050. Paper and paperboard = 

paper + paperboard + building paper. Wood pulp includes estimated dissolving pulp production. 

0

20

40

60

80

100

120

140

1970

1980

1990

2000

2010

2020

2030

2040

2050

Year

Paper and paperboard 

(million short tons) 

140

120

100

80

60

40

20

0

Wood pulp (million short tons) 

U.S. paper and paperboard production

U.S. wood pulp production

2.3%

0.7%

0.8%
133

The 2005 RPA Timber Assessment Update

is projected to remain above 50 percent, but growth in exports (mainly to China) 

accounts for the largest share of projected expansion in paper recovery. United 

States municipalities are shifting toward single-stream recycling (commingled 

curbside collection) to reduce collection costs, resulting in higher downstream 

costs for recovered paper sorting and separation. This favors shipment of recovered 

paper to countries such as China, where labor for hand sorting is cheap and paperrecycling capacity is rapidly expanding. United States recovered paper exports 

doubled in the past decade, with China the leading export destination, and exports 

are projected to increase from 16 million tons in 2005 to 25 million tons by 2050. 

This analysis also took into account projected shifts in product output by 

principal grade of paper, paperboard, and wood pulp, and their effects on pulpwood 

use, both hardwood and softwood. For example, U.S. newsprint production and 

consumption is projected to continue declining in the future, while kraft linerboard 

(for corrugated containers) is projected to continue increasing. Both newsprint and 

kraft linerboard are heavy consumers of softwood pulpwood, and thus the decline 

in softwood consumption in newsprint is offset by projected gains in linerboard. 

Printing and writing paper grades are heavy consumers of hardwood fiber, but little 

growth is projected in U.S. printing and writing paper output. 

The net effect of projected trends in fiber use and production is a relatively 

stable distribution of hardwood and softwood in projected U.S. pulpwood consumption (pulpwood receipts at wood pulp mills), with a gradually increasing share for 

softwood and gradually declining share for hardwood (fig. 21). The projections 

contrast with trends of preceding decades when the hardwood share was increasing. 

Overall pulpwood receipts at pulp mills are projected to gradually increase (at 0.7 

percent per year between 2006 and 2050), following the projected growth in wood 

pulp production, but the projected trend in hardwood pulpwood receipts is relatively flat, at just 0.4 percent per year (fig. 21). Projected growth in U.S. softwood 

pulpwood receipts, at 0.9 percent per year, is well below the 1960-2003 trend rate 

of 1.4 percent. However, softwood accounts for the largest share of projected gains 

in pulpwood receipts. The projected gains in U.S. softwood pulpwood receipts are 

supplied primarily by southern pine plantations. 

Hardwood Harvest

Projected hardwood harvest on timberland rises steadily over the projection. On 

average, hardwood harvest is projected to increase at 0.7 percent per year from 2005 

to 2050. As in the case of softwoods, the increase is due in large part to expansion 

of the pulpwood component of nonsawtimber harvest (fig. 24). 
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GENERAL TECHNICAL REPORT PNW-GTR-699

In contrast, hardwood harvests for sawtimber products are relatively stable over 

the projection (fig. 24). This pattern is dictated by end-use consumption trends in 

hardwood lumber, where declining use for pallets and furniture offset growth in use 

for millwork and miscellaneous products.

Private Inventories

For the United States as a whole, and for all regions and private owner groups, 

projected softwood inventory in 2050 is higher than estimated levels in 2000 (major 

regions are illustrated in fig. 61). Growth exceeds harvest in all cases despite rising 

removals over the projection. Aggregate U.S. private hardwood inventories also rise 

sharply by 2050, with continued expansion in the North offsetting modest reductions in the South. 

One of the key determinants of long-term forest growth is private investment in 

silvicultural activities. For the South, the 2005 update base case projects continued 

shifts of private timberland in softwood types toward the more intensive forms of 

Figure 61—U.S. private growing-stock inventory by region and species group projected to 2050.

1990 2000 2010 2020 2030 2040 2050 2060

0

50

100

150

200

250

300

350

Growing-stock inventory (billion cubic feet)

Hardwood East

Softwood East

Softwood West

Hardwood West

Year
135

The 2005 RPA Timber Assessment Update

management for both industrial and nonindustrial ownerships.4 This is illustrated 

in figure 35 for the two largest groups of Southern softwood timberland, industrial 

planted pine and other private “other softwoods” (natural pine, and oak-pine). In 

the Pacific Northwest West (PNWW), industrial ownerships continue to shift lands 

toward more intensive silvicultural regimes until the 2010 decade (2010–2019), but 

by the end of the projection, the structure of management intensities has returned to 

the mix observed in the 1990s.

Prices

The 2005 update projects a very moderate future for growth in real forest products 

prices. Solid wood products prices are expected to rise, but at rates that are small 

in absolute terms (0.3 percent per year or less) and well below those of the past 

five decades (fig. 22). Prices for the large aggregates of paper and paperboard are 

expected to decline in real terms (fig. 23).

Limited product price growth derives from continued improvements in input 

use efficiency in domestic production, competition from substitute products, and 

continued pressure from lower cost imports across the whole array of product 

classes.

Slow product price growth is reflected in many categories of stumpage prices 

(figs. 31, 32, 33). Sawtimber stumpage prices in the South and Interior West decline 

slowly after 2010, while those in the PNWW and North rise at about 0.2 percent 

and 0.6 percent per year. Southern hardwood pulpwood prices rise steadily in the 

projection as hardwood inventories contract. Southern softwood pulpwood prices 

oscillate in response to the changing fiber mix, ending the projection near recent 

levels.

Main Results From the Projections

• Growing consumption. Total U.S. forest products consumption is projected to continue to rise, reaching 27.0 bcf annually by 2050, a 38-percent 

increase relative to 2002 levels (see tables 8 and 9). Both softwoods and 

hardwoods share in this growth. Per capita wood use, which has shown 

wide variation over the past 50 years, will trend slightly downward below 

the average level of the past five decades (see fig. 62). Solid wood products 

consumption per capita will continue to fall and pulp products use will rise.

4

Management intensity shifts occur at time of regeneration in the update model. They are 

based, in part, on the anticipated soil expectation values of the several investment options.

The decisions of 

numerous private 

landowners have 

changed available 

forest resources.
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GENERAL TECHNICAL REPORT PNW-GTR-699

• Rising imports and import dependency. The United States’ relative 

import dependence5 nearly doubled between 1952 and 2002, rising from 12 

to 23 percent, while the absolute level of imports more than tripled (fig. 8). 

Over the period to 2050, U.S. imports will continue to rise (by 53 percent 

2002–2050) and at a somewhat faster rate than domestic wood supply. As a 

result, import dependence is projected to rise to about 27 percent in 2010, 

then decline slowly to just below 26 percent by 2050. Growth of imports’ 

share results from continued expansion in off-shore (non-Canadian) 

imports of all product types and rapid near-term growth in Canadian softwood lumber imports arising from timber salvaged in the interior BC pine 

beetle epidemic. As a result, the United States will have reason for continued interest in the forest resource and forest industry policies of trading 

partners and all nations.

Figure 62—U.S. forest products consumption per capita by type of product (dashed lines are 

historical trend from regression), projected to 2050.

1940 1960 1980 2000 2020 2040 2060

Year

0

10

20

30

40

50

60

70

80

90

Forest products consumption 

(cubic feet per capita)

Total

Solidwood

Pulp products

Fuelwood

5

Import dependence is computed here as the ratio of imports to the sum of domestic 

consumption plus exports.

The United States 

is increasing its 

dependency on 

imports of forest 

products.
137

The 2005 RPA Timber Assessment Update

• Slow changes in domestic resource conditions. Large or dramatic changes 

in U.S. forest conditions are not expected over the next 50 years, even as 

harvest rises. Adjustments will continue in the extent of certain forest types 

(expanding in some regions and contracting in others), shifts in age-class 

structures (some continuous and some transitory), an accumulation of older 

stands on public lands in the West, and an array of other variations, but most 

are expected to be gradual and not large relative to historical experience 

over the past 50 years. This does not suggest that debates on issues of forest 

protection, stewardship, and the adequacy of forest-based environmental services are moot, only that these deliberations need not proceed in an atmosphere of impending crisis based on concerns for fiber scarcity or large-scale 

ecological change.

• Growing role of South in wood supply. The South is the largest single 

wood-supplying region in the United States, and its importance is expected 

to rise over the next 5 decades. The South’s share of total U.S. harvest rose 

from 46 percent in the early 1950s to nearly 56 percent in 2002. The region’s 

share is projected to rise to 61 percent of total harvest by 2050. The absolute levels of both softwood and hardwood harvest are projected to rise. The 

South’s share of U.S. softwood harvest increases from 63 percent to 68 percent between 2002 and 2050, and its hardwood share rises from 51 percent 

to 52 percent.

• Hardwood inventories decline in the South, rise in the North. The base 

projection shows a markedly different picture of future hardwood inventory 

development in the North and South. Across all forest types in the South, 

hardwoods have the lowest rates of timber growth, the least intensive forms 

of management, and the greatest expected future reductions in the area 

available for timber production. Knowledge of intensive Southern hardwood 

culture is limited, and silvicultural activities in hardwood stands are complex owing to the diversity of species. To date, silvicultural research has 

emphasized softwood stand management. In addition, many of the Southern 

hardwood forests are in small parcels held by nonindustrial private owners 

with diverse objectives. Finally, the area of hardwood types is expected to 

decline 7 percent (15.4 million acres) over the projection through conversion 

to other types (predominantly softwoods), losses to urban and developed 

uses, and reservations for nontimber purposes. Reflecting these conditions, and continued growth in harvest, Southern hardwood inventories are 

expected to decline by about 6 percent between 2002 and 2050.
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GENERAL TECHNICAL REPORT PNW-GTR-699

Northern hardwood forests are characterized by low growth rates compared 

to the hardwoods in the South, they are managed under similar limitations 

on silvicultural research, they have a roughly similar parcelization structure, and they contained nearly equivalent volumes of growing-stock inventory in 2002 (168 bcf in the North versus 160 bcf in the South). They face a 

lower rate of harvest, however, given the limited and historically declining 

nature of the forest industry in the Northern States. Further, despite a projected decline in the aggregate area of timberland in the North (5 percent 

over all owners between 2002 and 2050), the area of hardwood types is 

expected to increase (by 2 percent) as softwood types are allowed to revert 

to hardwoods on nonindustrial private forest (NIPF) ownerships. The 

result is a projected increase of nearly 50 percent in the Northern hardwood 

inventory by 2050.

• Intensification of management on a portion of private timberlands. The 

update base projection assumes a continuation of current policies on public 

timberlands. As a consequence, private lands supply virtually all future 

increases in harvest in the United States, and public lands make a relatively 

limited contribution. It is expected that a larger portion of private timberland will be shifted into more intensive management as a result. Even so, 

more than three-fourths of the private land base will remain in natural 

forest types with little or no active management. Our projection envisions 

the development of a mixed pattern of management on private lands. Some 

areas are projected to be used intensively for wood production, while most 

of the land base is used at a lower level of intensity for timber production or 

for provision of nonwood outputs and services.6

6

This concentration of intensive management on a portion of the private land base has been 

advocated by some as a goal for domestic forest policy (see, for example, Binkley 1999, 

Sample 2001, and Victor and Ausubel 2000).
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The 2005 RPA Timber Assessment Update

Observations

This section highlights some of the broader outcomes of the base and scenario 

projections that may have implications for forest management decisions and forest 

policy development in the 21st century. 

The Importance of Rising Prices to Forest Management 

and Retention of Forest Cover

Many private, and a few public, timberland owners give some consideration to 

potential financial returns in determining how intensively they will manage their 

timber and the ages at which stands will be cut. Upward trends in prices over long 

periods effectively augment any reductions in costs of timber production and the 

financial rates of return from a timber investment (see fig. 63 for example). Rising 

timber prices make more intensive, and more expensive, forms of management 

Figure 63—Stumpage prices for Douglas-fir and southern pine sawtimber.

0

50

100

150

200

250

300

350

400

450

1910

1915

1920

1925

1930

1935

1940

1945

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

Year

Sawtim

b

er stumap

g

e

price

(1982 d

ollars/thousand

b

oard feet, Scribner)

Douglas-fir

Southern pine
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GENERAL TECHNICAL REPORT PNW-GTR-699

look more attractive (net returns are higher).7 In older assessment reports (see, for 

example, Haynes 1990, Haynes et al. 1995, USDA FS 1982) timber prices were 

projected to rise over most of the projection period. In the 2000 assessment (Haynes 

2003) and this 2005 update, however, product substitution, competition from 

imported sources of products, and rising domestic timber output potential in the 

South combine to largely eliminate timber price growth in the projections.

Many types of silvicultural investments in many regions promise reasonable 

rates of return without timber price growth.8 However, there is wide variation in 

acceptable rates of return and attitudes toward risk among private forest owners 

and potential forestry investors. As a consequence, the absence of prospective 

timber price inflation (and hence lower potential returns) may adversely influence 

the attractiveness of timber investments to some owners, reducing the intensity of 

management on private lands, and lowering long-term timber output potential. The 

methods used in the 2005 update to simulate owner decisions about the management intensity classes (MICs) adopted at regeneration include consideration of 

prospective rates of return (see app. 2). Thus, management intensity in the base and 

other projections are, in part, sensitive to future price trends. These methods are 

only approximations, however, and cannot include the full array of considerations 

influencing private investment decisions.

Intensification of forest management is sometimes viewed as the adoption of a 

complex regime of practices such as site preparation, planting, competition control, 

precommercial thinning, and so on. In practice, however, intensive management 

may involve nothing more than insuring prompt and adequate regeneration after 

harvest or adjusting the form of partial removals to favor more rapid growth of 

residual trees. The effect of more intensive management, whatever its specific form, 

is to raise rates of forest growth and expand inventories on the available timberland 

base. Other ecosystem services that are related to the rate of growth and extent of 

inventory (e.g., carbon dioxide uptake, certain types of wildlife habitat, or visual 

amenities) may be enhanced as well. Absent the inducement of rising prices, both 

the direct and indirect effects of intensification may be reduced in U.S. forests.

7

In this discussion, we are concerned with prices that rise over multiple rotations or cutting 

cycles. Prices of timber may also rise over the life a timber stand owing to quality improvements in the timber as it gets older and larger, but we do not consider these so-called 

quality-premium issues here. See McConnell et al. (1983) for an analysis of the rotation-age 

effects of continually changing prices in a general context. Continually rising prices do not 

necessarily lead to longer even-age rotations as is generally the case with quality-premium 

effects.

8

For an example in the U.S. South, see Siry et al. 2001.

Market incentives for 

forest management 

are declining.
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The 2005 RPA Timber Assessment Update

Continually rising timber prices act to increase the value of land in forest uses, 

making forest use relatively more attractive for some lands than alternatives such 

as agriculture or development. A stable timber price outlook affects the balance 

between returns from alternative uses and, in the update projections, leads to higher 

rates of forest land loss than would be the case under rising prices (see Alig and 

Butler 2004, for discussion of the modeling methods). These land area shifts augment the long-term timber supply reductions resulting from less intensive management.

Urbanization and Rural Development Affecting America’s Forests

Concerns about reduction in the area of U.S. forest lands are of long standing. Some 

of the earliest efforts in forest conservation were inspired by rapid loss of forests to 

agriculture and logging, the desire to protect timber and water resources, and the 

desire to preserve lands of extraordinary beauty and uniqueness. In earlier sections of this study, we saw that land base changes can affect the South’s ability to 

continue its growing role in softwood timber supply and constitute one of the key 

reasons for the projected decline in southern hardwood timber inventory. Recent 

forest inventory and analysis (FIA) surveys (e.g., Brown 2004, Gray et al. 2005) and 

the USDA NRCS national resource inventory (2001) suggest that loss of timberland 

to urbanization is accelerating in key timber supply regions. For example, expansion of developed area and urban sprawl in the South has been described as a major 

issue for future natural resource management, especially for the region’s forests 

(Seelye 2001, Wear and Greis 2002). The national net loss of timberland over the 

past five decades was about 1 percent on all ownerships and about 2 percent on 

private lands alone. The base projection anticipates nearly a 3-percent loss in the 

next 50 years from all ownerships and 3.7 percent from private holdings. Shifts to 

urban and other developed uses promise to be the largest causes of these reductions 

(Alig et al. 2004b). 

Urbanization and developments in rural areas can result not only in direct 

conversion of forest land but can also involve fragmentation, parcelization, ownership changes, and land value changes.9

 Development pressures can also add to 

uncertainty about how forest land will be managed and its ultimate environmental 

conditions if owners anticipate higher economic returns in an alternative use. Forest 

9

Forest fragmentation is the creation of smaller forested blocks owing to conversion of 

forest to nonforest use. Forest parcelization is the creation of smaller forest ownership 

tracts owing to an increase in the number of owners, although the original amount of forest 

area may remain the same, in contrast to forest fragmentation. See Alig 2000, Alig and 

Plantinga 2004, Alig et al. 2005, Butler and Leatherberry 2004, and Butler et al. 2004 for 

further discussion of these issues.
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GENERAL TECHNICAL REPORT PNW-GTR-699

landowners face increasing pressures (through existing and proposed public regulations) to produce multiple forest-based goods and services from their forest lands. 

This often occurs in circumstances where the economic incentives to shift land uses 

to urban and other developed uses are rising as well, with increased demand due to 

projected increases in population and personal incomes (Alig et al. 2004b). Forest 

land prices capture information regarding current as well as potential uses of land. 

As a result, they anticipate future development of forest land near urbanizing areas, 

casting what Wear and Newman (2004) call a “speculative shadow” over timberland values and owners’ decisions. 

Increased housing development in America’s private forests also has implications for the condition and management of the forests and the watersheds in which 

they occur, including reduced fish and wildlife habitat, altered water flows and 

water quality, and increased area of forest-residential interface that affects forest 

fire suppression costs and risks (Stein et al. 2005, Stewart et al. 2003). Some 44 million acres or 11 percent of private forests—particularly in the East—are projected 

to undergo increased housing development over the next three decades. About half 

of this development would involve shifts from rural (16 or fewer housing units per 

square mile) or exurban (forests with 16 to 64 housing units per square mile) use 

to urban use by 2030, with the remainder being forest land experiencing a higher 

density of houses than at present (Stein et al. 2005). The number of forested acres 

per capita in the United States has been shrinking, and conditions of the remaining 

forested acres have been altered over time. A shared desire to protect open spaces 

and the associated goods and services (that many consider to be public goods) as 

populations increase and the remaining forest land is shared among more people 

has motivated an emerging alliance between forest owners and conservation advocates (Kline et al. 2004).10 With increased public demand for open space preservation, a frequently cited strategy is to increase the economic attractiveness of current 

land uses by compensating private landowners for their contributions to broad-scale 

conservation goals (e.g., Best 2002, Best and Wayburn 2001). 

10An example in 2001 was the New England Forestry Foundation purchasing a conservation easement on more than 760,000 acres of privately owned forest land in northern 

Maine. An example of a working forest conservation easement is the Pacific Forest Trust’s 

alliance with the Bascom Pacific’s Pondosa Tree Farm Project (near Mount Shasta, California) to conserve habitat for multiple fish species and protect wet meadows and aspen groves 

(Web site for the 2005 California Forest Futures conference at http://nature.berkeley.edu).
143

The 2005 RPA Timber Assessment Update

Substitution Regulates Impacts of Market and Resource Changes

The economic process of substitution, stimulated by changes in the relative prices 

of competing goods or of comparable goods from different suppliers, is a dominant 

characteristic of the markets for forest products. Consumers of forest products, such 

as homebuilders that use lumber or merchants that use paper-based packaging, can 

substitute nonwood products such as steel studs or plastic wrapping if wood-based 

products become relatively more costly. They can also shift to different types of 

wood-based products, for example, wooden I-joists rather than solid lumber, or purchase the same products from lower priced sellers in different regions or countries. 

The availability of many types of substitutable products and many sources of supply for any given forest product act to reduce the price impacts of supply shifts in 

forest products markets. In effect, the demand faced by any single supplier is made 

very sensitive to price as a result of having many competitors. A small increase in 

a single supplier’s price will quickly send buyers to other sources, reducing output 

and costs. A small price reduction quickly attracts more buyers, pushing the single 

supplier’s output toward capacity and raising costs. In both cases, the overall impact 

on market price is reduced.

The effects of supply-side substitution are reflected in the results of the scenario 

analyses in chapter 4. All the scenarios can be interpreted as some form of supply 

shift: restoration thinning on public lands in the Western United States increases 

that region’s lumber output, reductions in pine plantation or NIPF timberland area 

in the South reduces that region’s timber supply, and so on. The timing of the 

impacts differs from case to case, e.g., the restoration thinning effects are immediate, whereas the impacts of the Southern land area reductions take many decades, 

but they all lead to some form of supply change. The effects of substitution in 

moderating price impacts can be seen at several levels. For example, increased 

public harvest in the West under a restoration thinning program raises western 

softwood lumber output but reduces production in the South and lowers the volume 

of lumber imports. Thus, despite increases in output of interior West softwood 

lumber approaching 30 percent (2 billion board feet), national product prices fall 

by 3 to 5 percent and consumption rises by about 0.5 billion board feet (1.1 percent 

at the peak year). Fully 75 percent of the Western lumber increment is offset by 

substitution across regional suppliers (domestic and foreign).

Substitution (and the lack of it) also regulates adjustment to supply shifts within 

a region. For example, in the case of reduced timberland areas in NIPF ownership 
144

GENERAL TECHNICAL REPORT PNW-GTR-699

Figure 64—Composite index and total harvest index, 1952–2002 and projections to 2050. 

in the South, stumpage prices rise. In the context of the timber assessment projection model, only forest industry lands provide an alternative price-sensitive timber 

source. The stumpage price shift is not large but would be far larger if there were no 

price responsive substitutes at all.

The State of Overall Forest Conditions 

Society’s concerns for environmental health and forest-land conditions have raised 

interest in understanding the overall state of forest conditions. A variety of issues 

motivate these concerns. In the international arena, debates about forest management often deal with different suggestions for how to supplement market-determined actions with processes that endeavor to find an equilibrium among interests 

advocating environmental protection, employment that contributes to economic 

prosperity, public access, and social justice (see Andersson et al. 2004 for a variety 

of perspectives on these issues). In the United States, there is a growing awareness 

of the threats that land use changes pose to the ability of forests to produce a broad 

array of ecosystem goods and services. Finally, there is the longstanding concern 

about the nature and extent of the tradeoff in forest conditions between timber 

harvests as an economic activity and environmental conditions. 

Some of these concerns can be examined in the context of overall forest conditions by using a timberland integrity index such as the one discussed in chapter 3. 

This composite index provides a description of timberland conditions and can be 

used to illustrate how the relation between environmental and commodity outputs 

0

50

100

150

200

250

102 104 106 108 110 112 114 116 118 120

Composite index

Harv

est ind

e

x

1952 1962

1970 1976

1986

1991

1997 2010

2020

2030

2050

2040

2002
145

The 2005 RPA Timber Assessment Update

of the forest changes over time. This latter use might provide a means for assessing 

the state of overall resource conditions or progress toward forest planning goals 

such as sustainable forest management. 

The relation between the biophysical/environmental and commodity dimensions of forest production have framed much of the contemporary forest management debate (see Monserud et al. 2003 for discussion). Figure 64 shows the 

relationship between composite forest conditions (as described by the timberland 

integrity index) and timber harvests for roughly a 50-year historical period and the 

update projection to 2050. The direction and slope of changes over time suggest 

the extent and nature of tradeoffs or compatibility among these two broad-scale 

measures. For example, movements between consecutive years upward and to the 

left indicate that harvest increased at the expense of ecological conditions. This 

happened between 1962 and 1970, 1976 and 1986, and it is expected to happen 

through this decade. Movements to the right and downward suggest gains in the 

composite index while harvest levels have been stable or falling (such as between 

1991 and 2002). Otherwise the movements have been mostly upward and to the 

right, where there has been an expansion in both timber harvest and timberland 

integrity, suggesting compatible changes between commodity output uses and 

ecological conditions.

The general upward (to the right) trend after 1986 has resulted in part from 

the use of forest management methods that enabled improvements in both timber 

harvest levels and timberland conditions. Figure 64 could be viewed as evidence 

that the United States is making progress toward the goals, embedded in sustainable 

forest management, of simultaneously improving economic prosperity and environmental conditions. But much of the rhetoric of the current debate about sustainability suggests that it is less about the physical notions of sustainability (given that the 

United States will sustain increases in timber inventories, gross forest conditions, 

and timber harvest levels) than about competing goals for public and private land 

management that involve other societal values (e.g., conservation of biodiversity) 

for forests [for examples of analyses informing these types of discussions see Heinz 

Center (2002) and USDA FS (2004)]. 

Although the United States has no formal mechanism for strategic forest policy 

discussions, a de facto policy has evolved from the decisions made for the management of public lands, state and local forest practice regulations, and the collective 

decisions of private timberland owners. For federal timberlands, this forest policy 

includes goals that assign forests to some type of reserved status or management in 

a passive fashion with limited timber harvest. For private timberlands, the result has 

been management of the majority of the forest area in a custodial fashion at a very 

The U.S. forest 

conditions are 

expected to 

improve while 

harvest levels 

increase.
146

GENERAL TECHNICAL REPORT PNW-GTR-699

low intensity (but available for wood production) with only a small fraction 

managed more intensively. The trends in figure 64 suggest that this policy has 

allowed improvements in both timber harvest and forest conditions.

Acknowledgments

Many people in the Forest Service, other federal agencies, state forestry agencies, 

universities, environmental groups, and forest industry associations and companies 

have contributed in significant ways to this study. Their help is gratefully acknowledged. 

We acknowledge the assistance of James Howard, Dave Mckeever, and Ken 

Skog who provided historical data or helped with interpretations of recent trends in 

estimates of timber use. Jean Daniels provided extensive revisions to the trade data. 

We are grateful to our formal technical reviewers: John Perez-Garcia (University of 

Washington), Don Flora, and Mary Coulombe (American Forest & Paper Association).

We are grateful for Judy Mikowski’s assistance in compiling many of the 

data summaries and tables, reconciling different versions of the text, and seeing it 

through the editing process. David Darr provided a number of insightful comments 

on early drafts. Adrienne Van Nalts (Oregon State University) provided excellent 

programming assistance. 

Equivalents

When you know	 Multiply by:	 To find:

Inches 2.54 Centimeters

Feet .305 Meters

Square feet .09 Square meters

Cubic feet (hardwood)a 40 Pounds

Cubic feet (softwood)a 35 Pounds

Cubic feetb .2 Board feet

Cubic feet .028 Cubic meters

Acres 0.41 Hectares 

Cubic feet per acre .07 Cubic meters per hectare

Pounds .454 Kilograms

Tons .907 Metric tonnes 

Degrees Fahrenheit (°F) .556(F - 32) Degrees Celsius

Dollars (1982) 1.602 Dollars (2005)

a Timber weights are air dry.

b For the purposes of this report, we use five board feet per cubic foot (log scale) for 

harvested timber but the actual value differs by region, depending on the type of log scale 

used and the physical characteristics of the timber (diameter, length, taper, defect).
147

The 2005 RPA Timber Assessment Update

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Glossary

The terms in this glossary were taken from several sources including the Forest 

Ecosystem Management Assessment Team Report (1993), The Dictionary of 

Forestry (Helms 1998), the Forest Resources of the United States, 1992 (Powell 

et al. 1993), and the Forest Resources of the United States, 1997 (Smith et al. 2001).

afforestation—The establishment of a forest or stand in an area where the 

preceding vegetation or land use was not forest.

age class—An interval into which the age range of trees is divided for classification or use. Ten-year intervals are used most commonly except in the South where 

5-year intervals are used.

chain weighted—A form of adjusting gross domestic product (GDP) for inflation 

that accounts for both changes in quantities and prices from year to year. The GDP 

series not adjusted for inflation are referred to as being in unchained dollars.

chemical wood—Trees used as a source of various chemicals such as acetic acid, 

methanol, and wood alcohol. Usually, timber that is not of sufficient size and/or 

quality to make lumber or plywood. 

cord—A traditional measure of wood volume defined as the amount of round wood 

that can be stacked in a 4- by 4- by 8-foot space, equivalent to roughly 75 to 80 

cubic feet of solid wood volume inside the bark for pulpwood, or about 500 board 

feet, log scale. 

cropland—Land used for the production of adapted crops for harvest, including 

row crops, small grain crops, hay crops, nursery crops, orchard crops, and other 

specialty crops. The land may be used continuously for these crops, or they may be 

grown in rotation with grasses and legumes. 

cull tree—A live tree, 5.0-inches in diameter at breast height (d.b.h.) or larger, that 

is unmerchantable for sawlogs now or prospectively because of rot, roughness, or 

species. (See definitions for rotten and rough trees).

diameter class—A classification of trees based on diameter outside bark measured 

at breast height (4 1/2 feet above ground). The common abbreviation for “diameter 

at breast height” is d.b.h. For 2-inch diameter classes, the 6-inch class, for example, 

includes trees 5.0 through 6.9 inches d.b.h.

Douglas-fir subregion—The area in the states of Oregon and Washington that is 

west of the crest of the Cascade Range (also called Pacific Northwest West).
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Doyle rule—A log rule or formula for estimating the board-foot volume of logs. 

The formula is:

V = [(D-4)2/4]L

where D is diameter inside bark at the small end in inches and L is length in feet.

dry weight—The weight of wood and bark, oven-dry basis (excluding all moisture).

engineered wood products—Composite wood products designed to substitute 

directly for dimension lumber in many building and structural applications. 

Includes prefabricated wood I-joists, glued laminated timber, and structural composite lumber (laminated veneer lumber, parallel strand lumber, and oriented strand 

lumber).

prefabricated wood I-joists (wood I-joists)—Structural, load-carrying 

members designed for roof and floor joist applications, offering long lengths 

with low material weights. The I-joist flange is typically dimension lumber or 

structural composite lumber; the web material is oriented strand board.

glued laminated timber (glulam)—Engineered, stress-rated product created 

by adhesively bonding individual pieces of lumber having a thickness of 2 

inches or less. It is versatile and can be shaped into forms ranging from straight 

to complex curved beams. Uses include headers, girders, purlins, beams, and 

arches.

structural composite lumber (SCL)—Composite products designed to be 

dimension lumber substitutes. Includes laminated veneer lumber, parallel 

strand lumber, and oriented strand lumber.

laminated veneer lumber (LVL)—A structural composite lumber product 

made by adhesively bonding thin sheets of wood veneer into a large billet. The 

grain of the veneers are all parallel in the “long” direction. The billet is then 

sawn to desired dimensions. Uses include headers, beams, rafters, scaffold 

planking, and flanges for prefabricated wood I-joists.

parallel strand lumber (PSL)—A structural composite lumber product 

made by adhesively bonding veneer that has been chopped into strands to 

take out knots and other imperfections. A billet is formed with the grain of 

the strands in the long direction and then sawn. Uses include beams and 

garage door headers.
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oriented strand lumber (OSL)—A structural composite lumber product 

made from flaked wood strands that have a high length-to-thickness ratio. The 

strands are oriented with the grain in the long direction into a billet and then 

sawn to desired dimension. Uses include millwork parts, studs, and flanges for 

prefabricated wood I-joists.

farmer-owned lands—Lands owned by a person who operates a farm, either doing 

the work themselves or directly supervising the work.

fiber products—Products made with largely intact plant fibers (or wood fibers) 

derived primarily from pulpwood, pulpwood chips, and recovered paper, such as 

wood pulp, paper or paperboard products, and also (in this publication) products 

made primarily from pulpwood roundwood, such as oriented strand board, but not 

including other panel products made primarily from fine wood residues, sawdust, or 

bark. 

fine materials—Wood residues not well suited for chipping or for use in fiber 

products because of small particle size and a large proportion of fibers that are cut 

or broken, such as planer shavings and sawdust (used in panel board products such 

as particleboard, but not in oriented strand board, and seldom used for pulpwood 

because of poor fiber quality).

forest industry (FI)—A diverse group of manufacturers that harvest, process, and 

use timber products in their final products. Activities include the harvesting of the 

timber resource; conversion of logs to primary timber products, such as lumber, 

plywood, and wood pulp; and the conversion of primary timber products to secondary or final products, such as pallets, furniture, and paper products. 

forest land—Land at least 10 percent stocked by forest trees of any size, including land that formerly had such tree cover and that will be naturally or artificially 

regenerated. Forest land includes transition zones, such as areas between heavily 

forested and nonforested lands that are at least 10 percent stocked with forest trees, 

and forest areas adjacent to urban and built-up lands. Also included are pinyonjuniper and chaparral areas in the West, and afforested areas. The minimum area 

for classification of forest land is 1 acre. Roadside, streamside, and shelterbelt 

strips of timber must have a minimum crown width of 120 feet to qualify as 

forest land. Unimproved roads and trails, streams, and clearings in forest areas 

are classified as forest if less than 120 feet in width.

forest management type— A classification of timberland based on the species and 

source of trees forming a plurality of live trees present. 
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forest inventory types—A classification of forest land based on the species forming a plurality of the live-tree stocking. Major forest type groups recognized in the 

timber assessment include:

white-red-jack pine—Forests in which eastern white pine, red pine, or jack 

pine, singly or in combination compose a plurality of the stocking. Common 

associates include hemlock, aspen, birch, and maple. 

spruce-fir—Forests in which spruce or true firs, singly or in combination 

compose a plurality of the stocking. Common associates include white cedar, 

tamarack, maple, birch, and hemlock. 

natural pine—A Southern management type representing stands that (a) have 

not been artificially regenerated, (b) are classed as a pine or other softwood 

forest type, and in which 50 percent or more of the naturally established stand 

is loblolly pine, slash pine, shortleaf pine, longleaf pine, or other southern pines 

singly or in combination. Common associates include oak, hickory, and gum. 

planted pine—A Southern management type representing forests in which 50 

percent or more of the stand is loblolly pine, slash pine, shortleaf pine, longleaf 

pine, or other southern pines that have been established by planting or direct 

seeding. 

lowland hardwood—A Southern management type composed of forests in 

which 50 percent or more of the stand is tupelo, blackgum, sweetgum, oak, and 

southern cypress, singly or in combination, and southern pine makes up less 

than 25 percent. Common associates include cottonwood, willow, oak, elm, 

hackberry, and maple. This type is found on the alluvial flood plains of the 

Mississippi and other southern rivers. May also be called bottomland hardwood. 

oak-pine—A Southern management type composed of forests in which 50 percent or more of the stand is hardwood, usually upland oaks, and southern pines 

make up 25 to 49 percent of the stocking. Common associates include upland 

oak-shortleaf pine in the foothills and plateaus; mixed hardwood-loblolly pine 

on moist sites; and scrub oak-longleaf pine in the sand hills of the Carolinas, 

Georgia, and Florida. Other associates include gum, hickory, and yellow-poplar. 

May also be called mixed pine-hardwood.
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oak-gum-cypress—Bottomland forests in which tupelo, blackgum, sweetgum, 

oaks, or southern cypress, singly or in combination compose a plurality of the 

stocking except where pines make up 25 to 50 percent, in which case the stand 

would be classified as oak-pine. Common associates include cottonwood, willow, ash, elm, hackberry, and maple.

elm-ash-cottonwood—Forests in which elm, ash, or cottonwood, singly or in 

combination compose a plurality of the stocking. Common associates include 

willow, sycamore, beech, and maple.

maple-beech-birch—Forests in which maple, beech, or yellow birch, singly or 

in combination compose a plurality of the stocking. Common associates include 

hemlock, elm, basswood, and white pine.

aspen-birch—Forests in which aspen, balsam poplar, paper birch, or gray 

birch, singly or in combination compose a plurality of the stocking. Common 

associates include maple and balsam fir.

Douglas-fir—Forests in which Douglas-fir composes a plurality of the stocking. Common associates include western hemlock, western redcedar, the true 

firs, redwood, ponderosa pine, and larch.

hemlock-Sitka spruce—Forests in which western hemlock, Sitka spruce, or 

both compose a plurality of the stocking. Common associates include Douglasfir, silver fir, and western redcedar. 

redwood—Forests in which redwood composes a plurality of the stocking. 

Common associates include Douglas-fir, grand fir, and tanoak.

ponderosa pine—Forests in which ponderosa pine composes a plurality of 

the stocking. Common associates include Jeffrey pine, sugar pine, limber pine, 

Arizona pine, Apache pine, Chihuahua pine, Douglas-fir, incense cedar, and 

white fir.

western white pine—Forests in which western white pine composes a plurality 

of the stocking. Common associates include western redcedar, larch, white fir, 

Douglas-fir, lodgepole pine, and Engelmann spruce.

lodgepole pine—Forests in which lodgepole pine composes a plurality of the 

stocking. Common associates include alpine fir, western white pine, Engelmann 

spruce, aspen, and larch.
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larch—Forests in which western larch composes a plurality of the stocking. 

Common associates include Douglas-fir, grand fir, western redcedar, and 

western white pine.

fir-spruce—Forests in which true firs, Engelmann spruce, or Colorado blue 

spruce, singly or in combination compose a plurality of the stocking. Common 

associates include mountain hemlock and lodgepole pine.

western hardwoods—Forests in which aspen, red alder, or other western 

hardwoods, singly or in combination compose a plurality of the stocking.

pinyon-juniper—Forests in which pinyon pine and juniper singly or in combination compose a plurality of the stocking.

upland hardwoods—A Southern management type composed of stands that 

have at least 10 percent stocking and classed as an oak-hickory or maple-beechbirch forest type. Common associates include yellow-poplar, elm, maple, and 

black walnut.

fuelwood—Wood used by conversion to some form of energy, primarily residential 

use.

green ton—Weight measure for pulpwood roundwood or pulpwood chips that are 

freshly cut and have not had enough time to age or lose free moisture, generally 

assumed to be the weight of wood at 50-percent moisture content on a total weight 

basis (2.0 green tons = 1 bone dry ton). 

growing stock—A classification of timber inventory that includes live trees of 

commercial species meeting specified standards of quality or vigor. Cull trees are 

excluded. When associated with volume, includes only trees 5.0 inches d.b.h. and 

larger.

hardwood—A dicotyledonous (nonconiferous) tree, usually broad leaved and 

deciduous.

harvest—(a) An intermediate or final cutting that extracts salable trees. (b) The 

volume of roundwood harvested from both growing-stock and non-growing-stock 

sources that is extracted from harvest sites. 

highly erodible cropland—All cropland in land capability classes (classifications 

used by the Soil Conservation Service to rate the suitability of soils for agricultural 

production) 3e, 4e, 6e, and 7e.

industrial wood—All commercial roundwood products except fuelwood.
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international 1/4-inch rule—A log rule, or formula, for estimating the board-foot 

volume of logs. The mathematical formula is:

V = (0.22D2 - 0.17D)(0.904762),

for 4-foot sections, where D = diameter inside bark at the small end of the section.

land area—(a) Bureau of the Census: the area of dry land and land temporarily or 

partly covered by water, such as marshes, swamps, and river food plains; streams, 

sloughs, estuaries, and canals less than 1/8 statute mile wide; and lakes, reservoirs, 

and ponds less than 40 acres in area. (b) Forest Inventory and Analysis: same as (a) 

except that the minimum width of streams, etc., is 120 feet, and the minimum size 

of lakes, etc., is 1 acre. This latter definition is the one used in this publication.

live cull—A classification that includes live, cull trees. When associated with 

volume, it is the net volume in live, cull trees that are 5.0 inches d.b.h. and larger.

log scale—The volume contents of individual trees or logs prior to processing. In 

the United States the most common rules for measuring board-foot volumes for 

sawtimber are the Scribner log rule, international 1/4-inch log rule, and the Doyle 

log scale.

logging residues—The unused portions of growing-stock trees cut or killed by 

logging and left in the woods.

managed plantations—Stands of trees established by artificial means (e.g., planting or direct seeding) composed primarily of single or related species, treated to 

have uniform structure and age class, and projected to receive at least minimal 

treatment for growth enhancement. 

management intensities—Growth and yield catagories developed for the aggregate timberland assessment system (ATLAS) to represent the development of stands 

under various improved management practices (i.e., genetic improvement, stocking 

control, fertilization, commercial thins, etc.). 

marginal cropland and pasture—Cropland and pasture that would yield higher 

rates of return to the owner if planted to pine.

market pulp—Mostly bleached kraft or sulfite pulp produced for sale to pulp 

customers.
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net annual growth—The average annual net increase in the volume of trees during 

the period between inventories. Components include the increment in net volume of 

trees at the beginning of the specific year surviving to its end, plus the net volume 

of trees reaching the minimum size class during the year, minus the volume of trees 

that died during the year, and minus the net volume of trees that became cull trees 

during the year.

net volume in cubic feet—The gross volume in cubic feet less deductions for rot, 

roughness, and poor form. Volume is computed for the central stem from a 1-foot 

tall stump to a minimum 4.0-inch top diameter outside bark, or to the point where 

the central stem breaks into limbs.

nonforest land—Land that has never supported forests and lands formerly forested 

where use of timber management is precluded by development for other uses. 

(Note: Includes area used for crops, improved pasture, residential areas, city parks, 

improved roads of any width and adjoining clearings, powerline clearings of any 

width, and 1- to 40-acre areas of water classified by the Bureau of the Census as 

land. If intermingled in forest areas, unimproved roads and nonforest strips must be 

more than 120 feet wide, and clearings, etc., more than 1 acre in size, to qualify as 

nonforest land).

non-growing-stock—A classification of inventory that includes all trees not meeting the standards for growing stock.

nonindustrial private forest (NIPF)—An ownership class of private forest lands 

whose owner does not primarily operate wood-using plants (distinguished from 

land owned by forest industry).

nonsawtimber—Timber that is not used by sawmills or veneer mills, but is used in 

the manufacture of pulp, paper, oriented strand board (OSB), various nonstructural 

panels, or used for fuelwood. 

nonstocked areas—Timberland less than 10 percent stocked with growing-stock 

trees.

oriented strand board (OSB)—An engineered structural-use panel made from 

wood strands that are cut longitudinally from small-diameter logs or pulpwood 

roundwood. The strands have a high length-to-thickness ratio and are bonded 

together with waterproof resin under heat and pressure. The strands are oriented 

along the length or width of the panel in alternating layers to take advantage of the 

inherent longitudinal fiber strength of wood. The panels are used in construction for 

roof, wall, and floor sheathing and for the web for prefabricated wood I-joists.
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other forest land—Forest land other than timberland and productive reserved 

forest land. It includes reserved forest land, and available land that is incapable of 

producing annually 20 cubic feet per acre of industrial wood under natural conditions because of adverse site conditions such as sterile soils, dry climate, poor 

drainage, high elevation, steepness, or rockiness. Urban forest land is also included 

that, owing to its location, is considered unavailable for sustained timber harvesting. 

other industrial timber products—Also called a miscellaneous products category 

of roundwood products that includes such items as poles; piling; posts; round mine 

timbers; hewn ties; bolts used for shingles; handles, and woodturnings; cooperage 

logs; chemical wood; and miscellaneous items.

other land—Nonforest land less the area in streams, sloughs, estuaries, and canals 

between 120 and 660 feet and lakes, reservoirs, and ponds between 1 and 40 acres 

in area (i.e., nonforest land less non-census water area).

other removals—Unutilized wood volume from cut or otherwise killed growing 

stock, from cultural operations such as precommercial thinnings, or from timberland clearing. Does not include volume removed from inventory through reclassification of timberland to productive reserved timberland.

other sources—Sources of roundwood products that are non-growing-stock. These 

include salvable dead trees, rough and rotten trees, trees of noncommercial species, 

trees less than 5.0 inches d.b.h., tops, and roundwood harvested from nonforest land 

(e.g., fence rows).

other white oaks—A group of species in the oak genus that includes overcup, 

chestnut, and post.

overrun—The difference between the greater volume actually sawn over the lessor 

estimated log scale volume. 

ownership—Categories of property owners: a combination of persons; a legal 

entity such as a corporation, partnership, club, or trust; or a public agency. All parcels of land in the United States are assigned to one of the categories of ownership.

plantation—See managed plantation.

plant byproducts—Wood material (such as slabs, edgings, trimmings, miscuts, 

sawdust shavings, veneer cores and clippings, and pulp screenings) from primary 

manufacturing plants used for pulp, particleboard, fuelwood, and other products. 
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poletimber—Live trees at least 5.0 inches in diameter, but smaller than sawtimber 

trees (9.0 inches or greater).

ponderosa pine subregion—The area in the states of Oregon and Washington that 

is east of the crest of the Cascade Range, (also called Pacific Northwest East).

primary wood-using mill—A mill that converts roundwood products into other 

wood products. Common examples are sawmills that convert sawlogs into lumber 

and pulp mills that convert pulpwood roundwood into wood pulp.

private ownerships:

forest industry (FI)—An ownership class of private lands owned by companies that grow timber for industrial use and own wood processing facilities.

nonindustrial private forest (NIPF)—An ownership class of private lands 

where the owner does not operate wood-use plants. This includes lands owned 

by operators of farms, lands owned by private individuals, and lands owned by 

private corporations. 

Native American-(a) Lands held in trust by the United States or states for 

Native American tribes or individual Native Americans. (b) Lands owned in 

fee by Native American tribes whether subject to federal or state restrictions 

against alienation or not. Since 1990, these lands are grouped with other private 

lands in the NIPF ownership group.

productivity class—A classification of forest land in terms of potential annual 

cubic-foot volume growth per acre at culmination of mean annual increment in 

fully stocked natural stands.

public ownerships:

federal—An ownership class of public lands owned by the U.S. Government.

national forest—An ownership class of federal lands, designated by Executive 

order or statute as national forests or purchase units, and other lands under the 

administration of the Forest Service including experimental areas and Bankhead-Jones Title III lands.

Bureau of Land Management (BLM)—An ownership class of federal lands 

administered by the Bureau of Land Management, U.S. Department of the 

Interior.

county and municipal—An ownership class of public lands owned by counties 

or local public agencies, or lands leased by these governmental units for more 

than 50 years.
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other public—An ownership class that includes all public lands except national 

forest. This category generally includes federal, state, county, and municipal 

ownerships.

state—An ownership classification of public lands owned by states or lands 

leased by states for more than 50 years.

pulpwood—Roundwood, wood chips, or wood residues that are the wood raw 

materials used for the production of wood pulp or (in this publication) the roundwood inputs for reconstituted panels (such as oriented strand board). In this publication, pulpwood does not include wood residues used for reconstituted panels.

reconstituted panels—The entire family of wood panel products that are reconstituted from small wood particles, fibers, or strands, including oriented strand board, 

insulating board, hardboard, particleboard, and medium density fiberboard (MDF), 

but excluding plywood 

recovered paper—Paper that is recovered after commercial or consumer use for 

recycling back into products, primarily into recycled paper or paperboard products.

reserved timberland—Forest land withdrawn from timber use through statute, 

administrative regulation, or designation without regard to protective status.

residues—Bark and woody materials that are generated in primary wood-using 

mills when roundwood products are converted to other products. Examples are 

slabs, edgings, trimmings, miscuts, sawdust, shavings, veneer cores and clippings, 

and pulp screenings. Includes bark residues and wood residues (both coarse and 

fine materials) but excludes logging residues.

removals—The net volume of growing-stock trees removed from the inventory by 

harvesting; cultural operations, such as timber stand improvement or land clearing; 

or changes in land use. 

rotten tree—A live tree of commercial species that does not contain a sawlog now 

or prospectively, primarily because of rot (i.e., when rot accounts for more than 50 

percent of the total cull volume).

rough tree—(a) A live tree of commercial species that does not contain a sawlog 

now or prospectively, primarily because of roughness (i.e., a sound tree that is 

culled because of such factors as poor form, splits, or cracks affecting more than 50 

percent of its total cull volume); or (b) a live tree of noncommercial species.
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roundwood—Logs, bolts, or other round sections cut from growing-stock and nongrowing-stock sources such as trees smaller than 5.0 inches d.b.h.; stumps, tops, 

and limbs of growing-stock trees; rough and rotten trees; dead trees; and trees that 

grow on land other than timberland.

roundwood equivalent—The volume of logs or other round products required to 

produce given quantities of lumber, plywood, wood pulp, paper, or other similar 

products, after deducting the proportion of wood raw material input that is obtained 

not from logs or roundwood but from plant byproducts or recycled wood fiber (from 

recovered paper). 

salvable dead tree—A standing or down dead tree that is considered currently or 

potentially merchantable by regional standards.

sawlog—A log meeting minimum standards of diameter, length, and defect, including logs at least 8 feet long, sound and straight, and with a minimum diameter 

inside bark of 6 inches for softwoods and 8 inches for hardwoods, or meeting other 

combinations of size and defect specified by regional standards. A log usually used 

in the manufacture of lumber and plywood.

sawtimber—Stands at least 10 percent occupied with growing-stock trees, with 

half or more of total stocking in sawtimber or poletimber trees, and with sawtimber 

stocking at least equal to poletimber stocking.

sawtimber trees—Live trees containing at least one 12-foot saw log or two 

noncontiguous 8-foot logs, and meeting regional specifications for freedom from 

defect. Softwood trees must be at least 9.0 inches d.b.h., and hardwood trees must 

be at least 11.0 inches d.b.h.

seral stage—A stage or recognizable condition of a plant community that occurs 

during its development from bare ground to climax. Forests are assumed to progress through five recognized stages: seedling; poles and saplings; young; mature; 

and old mature. These stages are represented by grouping age classes. The ageclass groupings differ by broad regions reflecting successional differences among 

various timber types.

seedling stage—The stand establishment stage. Includes the first age class 

(average age of 5 years) in all regions for both hardwood and softwood types, 

except for softwood types in the North where it includes the first two (5 and 15) 

age classes. Grass, herbs, or brush are plentiful.
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poles and sapling stage—Young stands. Crown closure occurs early in 

this stage; as stand density increases, grass, herbs, or brush rapidly decrease. 

Usually considered not to be merchantable, although both precommercial 

and commercial thinning can occur depending on market conditions. 

Age classes

Hardwood Softwood

North 15 to 35 25 to 35

South 10 to 20 10 to 15

West 15 to 35 15 to 35

young stage—Young stands where the crown differentiation is starting to 

occur. These stands contain a mix of sawtimber and nonsawtimber size trees 

and little understory vegetation. For many private landowners, these stands 

are often considered to reflect typical rotation lengths. 

Age classes

Hardwood Softwood

North 45 to 65 45 to 65

South 25 to 55 20 to 35

West 45 to 55 45 to 75

mature stage—Stands composed mostly of sawtimber. For softwoods, often 

thought to be at or just over the age where net annual growth has peaked. For 

hardwoods, these stands are often considered merchantable. In some types 

there is gradually increasing stand diversity, hiding cover, and forage. 

Age classes

Hardwood Softwood

North 75 to 135 75 to 135

South 60 to 75 40 to 75

West 65 to 135 85 to 135

old mature—Stands considered to be overmature. Stand ages are past the point 

where net annual growth has peaked. For some types, stands represent the 

potential plant community capable of existing on a site given the frequency of 

natural disturbance events. 

Age classes

Hardwood Softwood

North ≥$145 ≥$145

South ≥$80 ≥$80

West ≥$145 ≥$145
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Scribner rule—A diagram log rule that assumes 1-inch boards, is based on diameter at the small end of the log, disregards taper, and does not provide for overrun.

site productivity class—A classification of forest lands in terms of inherent 

capacity to grow crops of industrial wood. The class identifies the average potential 

growth in cubic feet per acre per year and is based on the culmination of mean 

annual increment of fully stocked natural stands. 

high sites—Land capable of growing at least 85 cubic feet of wood per 

acre per year. 

medium sites—Land capable of growing 50 to 85 cubic feet of wood 

per acre per year. 

low sites—Land capable of growing 20 to 49 cubic feet of wood per 

acre per year.

softwood—A coniferous tree, usually evergreen, having needles or scalelike leaves.

southern pine—This is not a forest type but a common name for stands that are 

composed of loblolly, slash, shortleaf, longleaf pine, or other pines grown in the 

South; also called southern yellow pine. 

sound dead—The net volume in salable dead trees.

stocking—The degree of occupancy of land by trees, measured by basal area or 

number of trees by size and spacing, or both, compared to a stocking standard; i.e., 

the basal area or number of trees, or both, required to fully use the growth potential 

of the land.

stumpage—Standing timber (trees) in the forest.

stumpage price—The price paid for standing timber (trees) in the forest. Usually 

expressed as dollars per thousand board feet, log scale.

succession—A series of dynamic changes by which one community succeeds 

another through stages leading to potential natural community or climax. The 

sequence of communities is called a sere, or seral stage.

timber supplies—The volumes of roundwood actually harvested, range of volume 

available for harvest at varying price levels, or future volumes estimated to be 

harvested at market equilibrium. Includes roundwood from growing-stock and 

non-growing-stock sources. 
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timberland—Forest land that is producing or is capable of producing crops of 

industrial wood and not withdrawn from timber use by statute or administrative 

regulation. Areas qualifying as timberland have the capability of producing in 

excess of 20 cubic feet per acre per year of industrial wood in natural stands. 

Currently inaccessible and inoperable areas are included.

tops—The wood of a tree above the merchantable height (or above the point on the 

stem 4.0-inches diameter outside bark [dob]). It includes the usable material in the 

uppermost stem and branches.

unreserved forest land—Forest land (timberland and woodland) that is not withdrawn from use by statute or administrative regulation. Includes forest lands that 

are not capable of producing in excess of 20 cubic feet per year of industrial wood 

in natural stands.

urban and other areas—Areas within the legal boundaries of cities and towns; 

suburban areas developed for residential, industrial, or recreational purposes; 

school yards; cemeteries; roads and railroads; airports; beaches, power lines, and 

other rights-of-way; or other nonforest land not included in any other specified land 

use class. 

veneer logs—The logs used in the manufacture of veneer. A roundwood product 

from which veneer is sliced or sawn and that usually meets certain standards of 

minimum diameter and length and maximum defect.

wood pulp—A fibrous raw material made from plant fiber (chiefly wood fiber in 

the United States) and used primarily to make paper and paperboard products.
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Species List

Common name	 Scientific name

Alpine fir (subalpine fir) Abies lasiocarpa (Hook.) Nutt.

Apache pine Pinus engelmannii Carr.

Arizona pine Pinus ponderosa var. arizonica (Engelm.) Shaw

Ash Fraxinus spp.

Aspen Populus spp.

Balsam fir Abies balsamea (L.) Mill.

Balsam poplar Populus balsamifera L.

Basswood Tilia spp.

Beech Fagus spp.

Birch Betula spp.

Blackgum (Black tupelo) Nyssa sylvatica Marsh. var. sylvatica

Black walnut Juglans nigra L.

Chestnut oak Quercus prinus L.

Chihuahua pine Pinus (associates with Apache pine)

Colorado blue spruce Picea pungens Engelm.

Cottonwood Populus spp.

Cypress Taxodium spp.

Douglas-fir Pseudotsuga menziesii (Mirb.) Franco

Eastern white pine Pinus strobus L.

Elm Ulmus spp.

Engelmann spruce Picea engelmannii Parry ex Engelm.

Eucalyptus Eucalyptus spp.

Grand fir Abies grandis (Dougl. ex D. Don) Lindl.

Gray birch (yellow birch) Betula alleghaniensis Britton

Gum Liquidambar spp.

Hackberry Celtis occidentalis L.

Hemlock Tsuga spp.

Hickory Carya spp.

Incense-cedar Libocedrus decurrens Torr.

Jack pine Pinus banksiana Lamb.

Jeffrey pine Pinus jeffreyi Grev. & Balf.

Juniper Juniperus spp.

Larch Larix spp.

Limber pine Pinus flexilis James

Loblolly pine Pinus taeda L.

Lodgepole pine Pinus contorta Dougl. ex Loud.

Longleaf pine Pinus palustris Mill.

Maple Acer spp.

Mountain hemlock Tsuga mertensiana (Bong.) Carr.

Oak Quercus spp.

Overcup oak Quercus lyrata Walt.

Paper birch Betula papyrifera Marsh.

Pinyon Pinus edulis Engelm.

Ponderosa pine Pinus ponderosa Dougl. ex Laws 

Post oak Quercus stellata Wangenh.

Red alder Alnus rubra Bong.

Red pine Pinus resinosa Ait.

Redwood Sequoia sempervirens (D. Don) Endl.
177

The 2005 RPA Timber Assessment Update

Common name	 Scientific name

Scrub oak Quercus berberidifolia Liebm.

Shortleaf pine Pinus echinata Mill.

Silver fir (Pacific silver fir) Abies amabilis Dougl. ex Forbes

Sitka spruce Picea sitchensis (Bong.) Carr.

Slash pine Pinus elliottii Engelm.

Sugar pine Pinus lambertiana Dougl.

Sweetgum Liquidambar styraciflua L.

Sycamore Platanus occidentalis L.

Tamarack Larix laricina (Du Roi) K. Koch

Tanoak Lithocarpus densiflorus (Hook. & Arn.) Rehd.

True firs Abies spp.

Tupelo Nyssa spp.

Western hemlock Tsuga heterophylla (Raf.) Sarg. 

Western redcedar Thuja plicata Donn ex D. Don

Western white pine Pinus monticola Dougl. ex D. Don

White-cedar Chamaecyparis thyoides (L.) B.S.P.

White fir Abies concolor (Gord. & Glend.) Lindl. ex Hildebr.

White pine See western white pine

Willow Salix spp.

Yellow-poplar Liriodendron tulipifera L.

Source: Burns and Honkala 1990a, 1990b.
178

GENERAL TECHNICAL REPORT PNW-GTR-699

Appendix 1: Background Tables

Table 20—Softwood removals, harvest, growth, and inventory for the national forest timberlands, 

1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 3 3 3 3 6 5 1 3 4 4 4 4

Harvest 3 3 3 2 6 6 4 4 6 6 6 6

Net annual growth 13 15 16 18 19 14 15 14 12 11 10 9

Inventory 459 532 637 636 678 782 838 953 1,041 1,112 1,174 1,226

North Central:

Removals 22 30 28 34 26 25 14 18 24 24 24 24

Harvest 24 28 34 32 29 28 19 20 26 26 26 26

Net annual growth 57 73 75 98 118 94 94 64 67 64 61 59

Inventory 1,336 1,988 2,170 2,542 3,270 3,578 3,499 3,958 4,400 4,808 5,191 5,548

Southeast:

Removals 15 28 35 67 74 47 10 19 27 27 27 27

Harvest 14 27 33 61 59 45 15 18 26 26 26 26

Net annual growth 80 90 129 137 94 57 79 110 73 62 60 56

Inventory 2,074 2,243 2,705 2,946 2,848 2,991 2,971 3,968 4,701 5,098 5,440 5,757

South Central:

Removals 145 94 156 181 174 139 37 63 76 76 76 76

Harvest 141 90 147 174 163 132 35 46 72 72 72 72

Net annual growth 211 336 314 245 231 192 205 192 144 117 116 117

Inventory 3,123 4,874 4,952 5,670 6,466 6,396 6,498 6,660 7,718 8,283 8,675 9,087

Rocky Mountains:a

Removals 229 412 524 463 468 130 79 104 133 133 133 133

Harvest 218 387 480 426 465 186 102 116 148 148 148 148

Net annual growth 689 776 905 1,044 1,296 1,274 1,160 893 832 746 675 618

Inventory 58,013 62,979 63,825 65,081 70,832 84,993 90,815 98,791 106,262 112,778 118,511 123,621

Pacific Southwest:b

Removals 117 263 378 306 334 96 42 75 104 104 104 104

Harvest 89 216 346 286 347 117 64 79 108 108 108 108

Net annual growth 162 186 338 364 422 616 658 431 406 384 363 343

Inventory 29,590 29,391 28,694 28,073 27,213 29,539 28,723 32,427 35,568 38,477 41,171 43,659

Pacific Northwest West:c

Removals 364 567 530 525 538 66 24 22 38 40 40 40

Harvest 361 586 489 511 659 73 19 22 39 41 41 41

Net annual growth 180 197 240 227 320 778 768 801 754 694 640 597

Inventory 47,584 47,704 45,478 44,088 33,607 51,399 50,718 58,711 66,139 73,014 79,216 85,002

Pacific Northwest East:c

Removals 121 256 314 313 387 72 29 51 71 73 73 73

Harvest 100 232 286 292 378 83 45 52 74 76 76 76

Net annual growth 261 310 329 312 269 320 317 294 280 258 240 225

Inventory 23,408 25,757 25,911 23,649 17,331 23,915 24,222 26,692 28,891 30,837 32,582 34,173
179

The 2005 RPA Timber Assessment Update

Table 20—Softwood removals, harvest, growth, and inventory for the national forest timberlands, 

1952–2002, with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Alaska:

Removals 13 75 114 95 54 51 14 29 29 29 29 29

Harvest 11 66 100 83 47 43 12 20 20 20 20 20

Net annual growth 10 16 20 23 15 85 53 53 53 53 53 53

Inventory 38,850 38,228 37,555 35,414 24,068 18,733 19,757 19,290 19,847 20,404 20,961 21,518

United States:

Removals 1,028 1,728 2,082 1,986 2,061 630 250 384 506 510 510 510

Harvest 961 1,635 1,918 1,867 2,153 712 315 377 519 523 523 523

Net annual growth 1,664 1,999 2,367 2,468 2,783 3,431 3,349 2,852 2,621 2,389 2,218 2,077

Inventory 204,437 213,696 211,927 208,099 186,313 222,326 228,041 251,450 274,567 294,847 312,921 329,591

a Rocky Mountains region historical data include the Great Plains States. For projections, western South Dakota 

is in Rocky Mountains; eastern South Dakota and other Great Plains States are in the North Central region.

b Pacific Southwest excludes Hawaii.

c

Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and 

Pacific Northwest East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, 

growth, inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment 

projections; projections from Mills and Zhou 2003.
180

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 21—Hardwood removals, harvest, growth, and inventory for the national forest timberlands, 

1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 10 11 19 29 13 16 7 5 6 6 6 6

Harvest 9 9 15 21 26 19 10 8 9 9 9 9

Net annual growth 69 88 105 117 131 68 68 75 67 59 53 47

Inventory 1,983 2,580 3,007 3,749 4,074 3,696 3,959 4,700 5,356 5,917 6,416 6,848

North Central:

Removals 28 35 47 49 53 64 49 39 43 44 45 46

Harvest 32 34 40 43 76 68 52 53 57 59 60 61

Net annual growth 112 141 140 159 154 139 145 118 121 116 112 109

Inventory 2,482 3,491 3,994 4,483 5,470 6,281 6,249 6,991 7,796 8,538 9,223 9,875

Southeast:

Removals 12 18 26 21 14 51 14 9 11 11 11 10

Harvest 9 11 17 15 14 47 10 8 10 10 10 10

Net annual growth 73 86 122 141 139 105 108 87 79 71 56 42

Inventory 2,784 3,335 3,511 4,679 5,503 5,773 5,776 6,415 7,172 7,842 8,414 8,831

South Central:

Removals 61 52 36 26 34 56 17 11 13 13 13 13

Harvest 41 29 32 18 35 52 12 11 12 12 12 12

Net annual growth 67 111 122 144 135 144 155 127 115 98 82 67

Inventory 1,785 2,793 3,947 3,576 4,502 5,249 5,699 6,251 7,419 8,390 9,201 9,855

West:a

Removals 6 11 19 5 45 11 4 7 8 9 10 10

Harvest 9 14 19 4 16 32 25 23 27 28 29 30

Net annual growth 74 82 85 97 58 218 160 161 158 146 137 134

Inventory 4,522 5,008 5,262 5,080 5,558 8,790 10,173 11,568 13,123 14,554 15,853 17,111

United States:

Removals 117 126 146 130 160 198 91 70 81 83 85 85

Harvest 100 97 123 101 166 217 109 103 115 118 120 122

Net annual growth 396 508 573 658 617 674 637 568 540 490 440 399

Inventory 13,556 17,207 19,721 21,567 25,107 29,789 31,856 35,925 40,866 45,241 49,107 52,520

a

West excludes Hawaii and Alaska. The 1997 increase in inventory data is due to changes in inventory procedures in the Rocky Mountains.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, inventory from 

Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections; projections from Mills and Zhou 2003.
181

The 2005 RPA Timber Assessment Update

Table 22—Softwood removals, harvest, growth, and inventory for other public timberlands, 1952–2002, 

with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 7 6 9 14 16 13 14 12 12 11 10 10

Harvest 7 5 7 13 18 20 18 17 18 17 16 16

Net annual growth 27 32 37 49 54 61 63 47 50 49 47 45

Inventory 885 1,044 1,275 1,555 2,496 2,797 3,111 3,414 3,798 4,185 4,564 4,923

North Central:

Removals 35 39 43 48 33 71 59 59 57 57 56 56

Harvest 33 35 38 41 43 74 65 64 61 61 61 61

Net annual growth 92 120 126 142 168 141 141 164 165 164 161 158

Inventory 2,162 2,943 3,237 3,728 4,840 5,272 5,275 6,320 7,415 8,488 9,560 10,586

Southeast:

Removals 52 45 71 80 120 114 112 101 108 115 123 128

Harvest 51 43 69 88 100 109 95 97 104 110 117 122

Net annual growth 70 84 126 149 148 145 155 174 124 127 137 138

Inventory 1,584 2,089 2,278 2,770 3,639 4,452 4,577 5,677 6,154 6,217 6,291 6,385

South Central:

Removals 43 32 38 51 74 61 63 60 67 70 75 78

Harvest 30 30 32 51 64 57 55 58 63 67 72 74

Net annual growth 56 58 78 71 55 66 81 92 81 78 80 83

Inventory 780 824 1,225 1,340 1,458 1,951 2,179 2,210 2,431 2,517 2,550 2,579

Rocky Mountains:a

Removals 79 86 86 93 76 49 51 92 112 125 139 145

Harvest 72 78 78 85 79 54 90 97 118 131 144 150

Net annual growth 119 141 162 162 220 168 169 211 190 174 164 157

Inventory 9,923 10,147 10,399 10,429 11,094 8,427 8,503 9,777 10,661 11,208 11,503 11,646

Pacific Southwest:b

Removals 5 18 27 24 15 23 23 9 11 11 11 11

Harvest 3 16 26 22 12 24 9 9 11 12 12 11

Net annual growth 14 14 14 14 25 29 29 20 22 21 21 20

Inventory 1,892 1,435 1,150 1,108 1,245 1,320 1,320 1,412 1,517 1,622 1,719 1,811

Pacific Northwest West:c

Removals 155 274 359 439 419 159 159 210 222 222 221 221

Harvest 158 290 343 428 418 163 213 215 226 226 226 226

Net annual growth 193 316 356 371 495 491 459 545 556 550 551 542

Inventory 20,085 19,787 19,610 19,161 19,576 19,243 19,243 22,495 25,835 29,172 32,505 35,766

Pacific Northwest East:c

Removals 52 64 103 96 102 67 67 49 48 44 40 37

Harvest 48 61 97 89 77 73 52 51 50 46 41 38

Net annual growth 66 88 91 96 139 67 27 42 42 42 42 43

Inventory 7,792 6,536 6,483 6,748 7,027 2,537 2,539 2,458 2,401 2,371 2,392 2,449

Alaska:

Removals 1 4 14 6 3 5 5 5 5 5 5 5

Harvest 1 4 12 5 3 3 4 4 4 4 4 4

Net annual growth 93 108 123 137 67 40 54 54 54 54 54 54

Inventory 10,081 10,915 11,864 12,200 5,880 5,090 5,090 5,637 6,129 6,621 7,112 7,604
182

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 22—Softwood removals, harvest, growth, and inventory for other public timberlands, 1952–2002, 

with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

United States:

Removals 429 568 750 851 858 562 553 597 642 660 680 691

Harvest 403 562 702 822 814 577 600 612 655 674 693 702

Net annual growth 730 961 1,113 1,191 1,371 1,208 1,178 1,349 1,284 1,259 1,257 1,240

Inventory 55,184 55,720 57,521 59,039 57,255 51,089 51,837 59,400 66,341 72,401 78,196 83,749

Note: Data for 1952–1986 contain Indian lands; in 1991 Indian lands were transferred to nonindustrial private forest.

Note: Historical harvest data are estimates of harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as of 

January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year. 1997 data updated since 

2000 report.

a Rocky Mountains region historical data (excluding harvest) includes the Great Plains States. For projections, western South Dakota 

is in the Rocky Mountains region; eastern South Dakota and other Great Plains States are in North Central region.

b Pacific Southwest excludes Hawaii.

c

Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and Pacific Northwest 

East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, 

inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections; 

projections from Zhou et al. (in press).

Table 23—Hardwood removals, harvest, growth, and inventory for other public timberlands, 1952–2002, 

with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 24 30 37 30 28 45 51 50 54 54 55 55

Harvest 23 26 28 23 23 92 76 78 83 82 81 81

Net annual growth 142 182 210 238 265 151 194 138 150 154 151 150

Inventory 3,803 4,838 5,697 6,478 9,110 10,158 11,018 11,838 12,747 13,761 14,735 15,693

North Central:

Removals 44 55 77 87 74 231 189 172 180 181 180 179

Harvest 45 51 70 72 81 249 229 232 240 240 240 240

Net annual growth 213 270 278 304 341 237 305 369 375 369 370 371

Inventory 4,583 6,619 7,649 8,343 10,112 11,430 11,538 13,561 15,546 17,446 19,326 21,255

Southeast:

Removals 15 16 29 34 36 39 54 52 58 67 76 81

Harvest 12 10 20 31 62 34 46 48 53 61 70 76

Net annual growth 27 32 55 71 86 100 106 75 76 77 78 78

Inventory 845 1,155 1,547 1,992 3,006 4,062 4,262 4,418 4,595 4,680 4,695 4,664

South Central:

Removals 50 40 35 52 62 53 51 54 67 79 92 101

Harvest 33 36 36 53 66 49 47 57 63 73 85 95

Net annual growth 55 71 90 109 101 181 146 165 161 153 141 133

Inventory 1,365 1,750 2,106 2,401 3,307 4,956 5,728 6,095 7,110 7,909 8,499 8,859
183

The 2005 RPA Timber Assessment Update

Table 23—Hardwood removals, harvest, growth, and inventory for other public timberlands, 1952–2002, 

with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Rocky Mountains:a

Removals 2 4 3 2 2 2 1 3 3 3 3 3

Harvest 2 2 1 1 1 4 7 8 9 8 7 7

Net annual growth 8 9 10 11 27 45 18 13 15 15 15 14

Inventory 566 624 670 682 974 823 827 746 866 985 1,099 1,222

Pacific Southwest:b

Removals 1 2 2 2 1 1 1 1 1 1 1 1

Harvest 1 1 1 2 1 1 1 11 11 11 10 10

Net annual growth 6 5 7 7 16 5 5 4 5 5 4 4

Inventory 218 190 263 283 554 319 319 332 384 433 478 512

Pacific Northwest

Removals 5 3 13 15 15 13 33 27 29 31 32 34

Harvest 6 4 10 13 36 14 42 43 46 47 49 50

Net annual growth 34 58 92 93 88 74 64 77 82 85 84 82

Inventory 1,135 1,584 2,089 2,322 2,442 2,846 2,846 3,331 3,828 4,377 4,894 5,389

Alaska:

Removals — — 3 3 5 1 1 1 1 1 1 1

Harvest — — 4 4 6 2 1 2 2 2 2 2

Net annual growth 7 7 7 7 55 49 72 72 72 72 72 72

Inventory 3,902 3,861 3,873 3,864 1,751 1,930 2,260 2,696 3,400 4,105 4,810 5,514

United States:

Removals 141 150 199 225 223 386 381 361 394 418 441 456

Harvest 122 130 170 199 276 445 451 479 507 524 544 561

Net annual growth 492 634 749 840 978 841 910 913 936 930 915 904

Inventory 16,417 20,621 23,894 26,365 31,256 36,524 38,798 43,017 48,476 53,696 58,536 63,108

Note: Data for 1952–86 contain Indian lands; in 1991 Indian lands were transferred to nonindustrial private forest.

Note: Historical harvest data are estimates of harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as 

of January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year.

— = less than 0.5 million cubic feet. a Rocky Mountains region historical data (excluding harvest) includes the Great Plains States. For projections, western 

South Dakota is in the Rocky Mountains; eastern South Dakota and other Great Plains States are in the North Central 

region. The 1997 increase in growth data is due to changes in inventory procedures.

b Pacific Southwest excludes Hawaii.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, 

growth, inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment 

projections; projections from Zhou et al. (in press).
184

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 24—Population and lumber consumption in the United States, per capita and by end use, 1962–2002, 

with projections to 2050

End use

Per Residential New Packaging

capita New upkeep and nonresidential and All Total

Year Population use housing improvements construction Manufacturing shipping other use

Millions Board feet - - - - - - - - - - - - - - - - - - - - - - - - - - - - Billion board feet - - - - - - - - - - - - - - - - - - - - - - - - - - - -

1962a 186.5 209 14.1 4.3 4.2 4.5 4.5 7.3 39.1

1970 205.1 199 14.0 5.0 4.7 4.7 5.7 6.7 40.7

1976 218.0 202 18.3 6.3 4.5 4.9 5.9 4.3 44.1

1986 240.7 238 20.8 15.4 5.3 6.1 5.9 3.8 54.7

1996 265.5 231 19.8 15.3 4.9 7.9 6.4 7.0 61.3

1998 270.3 238 22.2 14.1 5.4 8.4 7.2 7.1 64.4

2002 287.5 235 23.3 17.3 4.5 8.0 7.1 7.6 67.7

2010 298.0 236 20.2 20.4 6.0 7.8 7.3 8.7 70.4

2020 323.0 217 18.6 21.4 6.2 7.9 7.3 8.7 70.1

2030 347.2 210 18.4 22.6 6.6 8.1 7.4 9.6 72.8

2040 370.3 211 20.3 24.3 7.0 8.2 7.5 10.7 78.0

2050 394.2 213 22.4 26.1 7.3 8.5 7.6 12.0 83.9

Note: Data may not add to totals because of rounding.

a

Historical data 1962–86 updated to reflect revisions in new housing and residential repair and alterations.

Source: Historical data McKeever 2002.

Table 25—Lumber consumption, imports, exports, and production in the United States, 1962–2002, with 

projections to 2050

Consumption Imports Exports Production

Softwood Hardwood Softwood Hardwood Softwood Hardwood Softwood Hardwood

Year lumber lumber Total lumbera lumber Total lumbera lumber Total lumber lumber Total

Billion board feet

1962b 30.8 8.3 39.1 4.6 0.3 4.9 0.6 0.1 0.8 26.8 8.1 34.9

1970 32.2 8.5 40.7 5.8 .3 6.1 1.1 .1 1.2 27.5 8.3 35.9

1976 36.0 8.0 44.1 8.0 .3 8.2 1.6 .2 1.8 29.7 8.0 37.7

1986 47.1 10.2 57.4 13.8 .3 14.0 1.9 .5 2.4 35.3 10.5 45.7

1996 49.5 11.8 61.3 18.0 .4 18.4 1.8 1.1 2.9 33.3 12.5 45.8

1998 52.0 12.2 64.2 18.5 .5 19.0 1.1 1.1 2.2 34.7 12.7 47.4

2002 56.0 11.1 67.7 21.0 .7 21.7 .8 1.2 2.0 35.8 11.5 47.4

2010 59.0 11.4 70.4 26.3 .7 27.0 1.0 1.5 2.5 33.7 12.2 45.9

2020 58.5 11.6 70.1 24.2 .7 24.9 1.1 1.5 2.6 35.4 12.4 47.8

2030 60.9 11.9 72.8 25.0 .7 25.7 1.3 1.5 2.8 37.2 12.7 49.8

2040 65.8 12.2 78.0 26.8 .7 27.5 1.4 1.5 2.9 40.4 13.0 53.4

2050 71.4 12.5 83.9 28.9 .7 29.6 1.5 1.5 3.0 44.0 13.3 57.3

Note: Data may not add to totals because of rounding.

a Includes small volumes of mixed species not classified as softwood or hardwood.

b Historical data 1962–86 updated to reflect revisions in new housing and residential repair and alterations.

Source: Historical data McKeever 2002.
185

The 2005 RPA Timber Assessment Update

Table 26—Lumber production in the contiguous United States, by softwoods and hardwoods and region, 

1952–2002, with projections to 2050

Historical Projections

Species group and region 1952 1962 1970 1976 1986 1996 2002 2010 2020 2030 2040 2050

Billion board feet, lumber tally

Softwoods:

Northeast 1.3 0.8 0.6 0.8 1.4 1.4 1.5 1.4 1.3 1.3 1.4 1.4

North Centrala .4 .3 .3 .4 .3 .5 .8 .6 .7 .7 .7 .7

Southeast 5.2 2.7 2.9 3.4 5.3 6.7 7.3 5.9 6.4 6.5 6.7 7.0

South Central 3.6 3.2 4.3 4.6 6.2 8.7 9.4 8.8 9.6 10.7 11.9 13.1

Rocky Mountains— 2.5 3.6 4.3 4.5 4.6 3.6 3.4 3.2 3.3 3.4 3.7 3.8

Northern Rockies 1.6 2.8 3.0 3.1 3.4 3.1 3.0 2.7 2.7 2.8 3.0 3.1

Southern Rockies .9 1.0 1.2 1.2 1.3 .5 .4 .4 .5 .6 .7 .8

Pacific Northwestb

—

 Westc 10.3 8.6 7.6 8.5 9.3 7.4 9.2 10.7 11.0 11.2 12.4 14.0

Eastc 2.3 2.4 2.4 2.7 2.8 1.5 1.6 1.4 1.6 1.9 2.2 2.5

Pacific Southwestd 4.6 5.0 5.2 4.8 5.2 3.4 2.6 1.8 1.6 1.5 1.4 1.4

Total U.S. softwoods 30.2 26.8 27.5 29.7 35.3 33.3 35.8 33.7 35.4 37.2 40.4 44.0

Hardwoods:

Northeast .9 1.3 1.6 1.9 2.3 3.1 3.0 3.3 3.4 3.6 3.8 4.0

North Centrala 2.4 1.5 1.7 2.6 3.2 3.1 2.6 2.9 3.0 3.1 3.1 3.2

Southeast 1.6 1.9 2.0 1.4 2.0 2.2 2.1 2.2 2.3 2.3 2.4 2.4

South Central 2.3 3.3 2.9 1.8 2.7 3.5 3.3 3.3 3.1 3.1 3.1 3.1

West 0 .1 .1 .2 .2 .5 .5 .5 .5 .5 .4 .5

Total U.S. hardwoods 7.2 8.1 8.3 8.0 10.5 12.5 11.5 12.2 12.4 12.6 13.0 13.3

Note: Data may not add to totals because of rounding.

a Includes Great Plains. 

b Excludes Alaska.

c Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and Pacific 

Northwest East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

d Excludes Hawaii. 

Source: Historical data for softwoods WWPA (annual issues), AF&PA (annual issues); USDC (annual issues); for 

hardwoods USDC (annual issues), Luppold and Dempsey 1989. 
186

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 27—Population and structural panel consumption in the United States, per capita and by end use, 

1962–2002, with projections to 2050

Panel type End use

Per OSB/ Residential New Packaging

capita Softwood wafer- New upkeep and nonresidential Manu- and All

Year Population use plywood board housing improvements construction facturing shipping other Total

 Square

Millions feet - - - - - - - - - - - - - - - - - - - - - - - - Billion square feet (3/8-inch basis) - - - - - - - - - - - - - - - - - - - - - - - -

1962 186.5 51 9.5 — 3.9 1.7 1.7 0.7 0.2 1.3 9.5

1970 205.1 69 14.3 — 5.9 2.3 1.9 .9 .3 3.0 14.3

1976 218.0 82 17.7 — 8.7 3.2 1.9 1.1 .3 2.6 17.8

1986 240.7 107 21.6 4.2 11.8 7.0 3.1 1.8 .4 1.7 25.7

1996 265.5 119 18.0 13.6 17.0 7.5 2.5 3.2 .5 .8 31.6

1998 270.3 129 17.2 17.6 19.4 7.3 2.9 3.7 .6 .9 34.8

2002 287.5 130 15.7 21.7 20.8 6.0 3.0 3.8 .7 3.2 37.4

2010 298.0 134 11.8 28.2 22.2 8.0 3.0 3.6 1.3 1.8 40.0

2020 323.0 123 10.7 29.2 20.3 8.4 3.3 4.0 1.9 1.9 39.9

2030 347.2 119 10.4 30.9 19.5 8.9 3.8 4.5 2.7 1.9 41.3

2040 370.3 122 10.5 34.6 20.7 9.7 4.2 5.0 3.7 1.9 45.1

2050 394.2 128 10.5 40.0 22.0 10.5 4.5 5.7 4.9 2.7 50.5

Note: Data may not add to totals because of rounding.

— = Less than 50 million square feet.

Source: Historical data Howard 2003.

Table 28—Structural panel consumption, imports, exports, and production in the United States, 1962–2002, 

with projections to 2050

Consumption Imports Exports Production

 OSB/ OSB/ OSB/ OSB/

Softwood wafer- Softwood wafer- Softwood wafer- Softwood waferYear plywood board Total plywood board Total plywood board Total plywooda board Total

Billion square feet (3/8-inch basis)

1962 9.5 — 9.5 — — — — — — 9.5 — 9.5

1970 14.2 — 14.2 — — — 0.1 — 0.1 14.3 — 14.3

1976 17.7 0.1 17.8 — — — .7 — .7 18.4 0.1 18.5

1986 21.6 4.2 25.7 0.1 0.7 0.8 .6 — .6 22.0 3.5 25.6

1996 18.0 13.6 31.6 .1 4.4 4.5 1.2 .2 1.4 19.2 9.3 28.5

1998 17.2 17.6 34.8 .2 6.5 6.7 .8 .1 .9 17.8 11.2 29.0

2002 15.7 21.7 37.4 .9 8.5 9.4 .4 .2 .6 15.2 13.4 28.6

2010 11.8 28.2 40.0 3.0 12.2 15.2 .5 — .5 9.3 16.0 25.3

2020 10.7 29.2 39.9 4.4 12.5 17.0 .5 — .5 6.7 16.7 23.4

2030 10.4 30.9 41.3 4.4 12.2 16.7 .5 — .5 6.5 18.6 25.1

2040 10.5 34.7 45.1 4.4 12.8 17.2 .5 — .5 6.5 21.9 28.4

2050 10.5 40.0 50.5 4.4 14.3 18.7 .3 — .3 6.4 25.6 32.0

Note: Data may not add to totals because of rounding.

— = Less than 50 million square feet.

OSB = oriented strand board. a

Includes production from both domestic and imported species. 

Source: Historical data Howard 2003. 
187

The 2005 RPA Timber Assessment Update

Table 29—Structural panel production in the contiguous United States, by region, 1962–2002, with 

projections to 2050

Species group Historical Projections

and region 1962 1970 1976 1986 1996 2002 2010 2020 2030 2040 2050

Billion square feet (3/8-inch basis)

Softwoods:

Northeast 0 0 0.1 0.6 1.3 1.6 2.6 3.0 3.8 5.0 6.4

North Centrala 0 0 .1 1.7 3.0 3.5 4.2 4.4 4.9 5.7 6.6

Southeast 0 .9 1.7 3.5 6.2 6.6 6.6 5.5 5.8 6.5 7.2

South Central 0 2.4 5.1 8.7 11.9 12.1 9.2 9.2 9.3 10.0 10.7

Rocky Mountains .2 .9 1.2 1.4 1.3 .9 .6 .5 .4 .4 .4

Pacific Northwest

b c

West 8.0 8.7 8.8 8.6 3.8 3.5 1.5 .4 .4 .4 .2

East .1 .6 .9 .9 1.0 .5 .5 .5 .4 .4 .5

Pacific Southwest

d 1.2 .8 .6 .1 0 0 0 0 0 0 0

United States 9.5 14.3 18.5 25.6 28.5 28.6 25.3 23.4 25.1 28.4 32.0

Note: Data may not add to totals because of rounding. a The Great Plains are included in the North Central region. 

b Excludes Alaska. 

c

Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and 

Pacific Northwest East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

d Excludes Hawaii.

Source: Historical data: Adams et al. 1988, American Plywood Association 1996–2002. 
188

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 30—Nonstructural panel consumption, imports, exports, and production in the United States by type, 

1962–2002, with projections to 2050

Consumption Imports

Hardwood Insulating Particle Hardwood Insulating Particle

Year plywood board Hardboard boarda Total plywood board Hardboard boarda Total

Billion square feet (3/8 inch basis)

1962 2.0 1.0 1.0 4.0 7.9 1.0 0 0 0 1.0

1970 3.8 3.2 4.8 3.7 13.6 2.0 0.1 0.4 0 2.5

1976 3.4 3.4 7.1 6.9 17.3 2.4 0 .5 0.1 3.0

1986 4.5 2.4 6.5 11.4 21.5 3.2 .3 .8 2.8 7.1

1990 3.0 2.5 5.2 9.5 17.8 1.6 .3 .7 .7 3.3

1997 3.6 2.5 4.5 13.4 22.5 2.0 .3 1.3 1.9 5.5

2002 4.9 2.5 4.9 19.8 31.4 2.9 .3 2.7 8.2 14.1

2010 3.5 3.5 2.1 16.7 25.8 1.7 .4 .6 3.1 5.8

2020 3.2 3.3 2.2 18.1 26.8 1.7 .4 .6 3.5 6.2

2030 3.0 3.0 2.3 19.6 27.8 1.7 .5 .7 3.8 6.6

2040 2.7 2.7 2.4 21.6 29.4 1.7 .5 .7 4.2 7.1

2050 2.4 2.4 2.5 23.6 30.9 1.7 .5 .7 4.5 7.5

Exports Production

Hardwood Insulating Particle Hardwood Insulating Particle

Year plywood board Hardboard boarda Total plywood board Hardboard boarda Total

Billion square feet (3/8 inch basis)

1962 0 0 0 0 0 1.5 0.8 0.8 3.8 6.9

1970 .1 .1 0 0 .2 1.8 4.3 1.5 3.7 11.4

1976 .1 .1 .1 .2 .5 1.1 4.5 2.3 6.9 14.8

1986 .1 .2 .1 .2 .6 1.4 2.9 1.9 8.8 15.0

1990 .2 .2 .2 .7 1.3 1.5 3.1 1.7 9.5 15.8

1997 .3 .2 .4 .4 1.3 1.9 3.1 1.5 11.8 18.3

2002 .2 .2 .2 .4 1.0 2.1 3.1 1.0 12.1 18.3

2010 .3 .3 .3 .8 1.7 2.1 3.4 1.8 14.4 21.7

2020 .3 .3 .3 .8 1.7 1.9 3.1 1.9 15.5 22.3

2030 .3 .3 .3 .8 1.8 1.6 2.8 1.9 16.6 22.9

2040 .4 .3 .3 .9 1.8 1.4 2.5 2.0 18.3 24.2

2050 .4 .3 .3 .9 1.9 1.1 2.2 2.1 20.0 25.3

Note: Data may not add to totals because of rounding.

a

Includes medium-density fiberboard.

Source: Historical data Howard 2003.
189

The 2005 RPA Timber Assessment Update

Table 31—Softwood removals, harvest, growth, and inventory on forest industrya timberlands in the 

contiguous United States, 1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 105 92 138 182 273 118 118 156 113 95 86 83

Harvest 99 87 128 168 356 144 247 222 167 142 130 125

Net annual growth 179 236 339 377 188 65 66 140 140 140 140 137

Inventory 5,246 6,427 9,753 10,824 9,191 5,803 5,722 4,858 4,870 5,195 5,655 6,150

North Central:b

Removals 34 23 28 33 37 32 25 9 11 10 9 8

Harvest 30 22 25 28 41 34 13 9 11 9 8 8

Net annual growth 43 44 63 55 50 35 35 45 48 50 49 50

Inventory 917 1,314 1,521 1,690 1,653 1,426 1,426 1,831 2,141 2,518 2,888 3,285

Southeast:

Removals 325 262 458 518 821 961 928 1,059 1,451 1,600 1,584 1,668

Harvest 318 252 430 473 740 923 1,014 1,035 1,426 1,571 1,550 1,630

Net annual growth 375 411 558 688 725 890 966 1,435 1,670 1,759 1,828 1,796

Inventory 6,803 7,809 8,670 9,142 10,717 10,231 10,295 12,001 15,649 18,170 20,014 21,864

South Central:

Removals 494 341 564 898 1,088 1,259 1,301 1,597 1,924 2,146 2,355 2,471

Harvest 484 328 530 893 1,045 1,196 1,297 1,522 1,830 2,039 2,238 2,347

Net annual growth 707 971 889 894 829 1,135 1,207 1,632 2,117 2,346 2,495 2,515

Inventory 9,738 13,087 13,501 14,430 13,515 14,231 13,844 14,501 17,546 20,399 22,597 23,505

Rocky Mountains:

Removals 99 130 186 177 158 154 150 100 74 75 75 77

Harvest 128 145 138 115 178 152 180 121 82 83 84 85

Net annual growth 79 92 103 105 125 126 126 103 105 124 151 173

Inventory 6,767 6,447 5,939 5,156 5,343 4,773 4,773 3,481 3,716 4,176 4,902 5,849

Pacific Southwest:

Removals 456 449 318 344 435 357 357 193 198 191 180 160

Harvest 393 385 294 321 452 371 338 223 232 226 214 193

Net annual growth 90 108 135 139 205 247 247 205 190 200 220 215

Inventory 11,268 9,639 8,244 7,457 7,918 8,592 8,592 6,673 3,716 6,603 6,869 7,284

Pacific Northwest West:c

Removals 1,150 909 1,272 1,302 1,222 657 657 974 950 929 971 1,046

Harvest 1,244 976 1,234 1,268 1,244 643 1,000 1,013 976 954 993 1,068

Net annual growth 337 393 455 606 915 799 734 963 985 1,057 1,105 1,089

Inventory 32,725 27,399 23,767 21,978 20,137 17,648 17,648 17,730 17,862 18,988 20,573 21,404

Pacific Northwest East:c

Removals 103 95 120 162 179 144 144 79 72 77 82 88

Harvest 100 94 117 151 166 160 118 90 82 86 91 97

Net annual growth 62 71 84 85 115 85 70 118 123 135 147 154

Inventory 3,975 3,972 4,038 3,849 4,279 3,557 3,557 3,897 4,381 4,922 5,583 6,266
190

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 31—Softwood removals, harvest, growth, and inventory on forest industrya timberlands in the 

contiguous United States, 1952–2002, with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

United States: 

Removals 2,765 2,301 3,084 3,616 4,213 3,683 3,680 4,166 4,794 5,122 5,342 5,601

Harvest 2,796 2,289 2,896 3,417 4,222 3,623 4,207 4,234 4,806 5,110 5,308 5,553

Net annual growth 1,872 2,326 2,626 2,949 3,152 3,382 3,453 4,641 5,377 5,811 6,135 6,129

Inventory 77,439 76,094 75,433 74,526 72,753 66,261 65,857 64,972 69,881 80,970 89,080 95,607

Note: Historical harvest data are estimates of the harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as of 

January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year.

a

Lands held by firms with commercial timber production objectives but no processing facilities (e.g., timberland investment 

organizations [TIMOs] and real estate investment trusts [REITs]) are included in forest industry and nonindustrial private forest 

categories, depending on their classification in the starting (approximately 1995) inventory data. See text in chapter 2 “Projected 

Area Changes for Land Uses and Forest Management Cover Types” section for further discussion.

b

Data for the Great Plains are included in the Rocky Mountains region for the historical period. For projections, western South 

Dakota is in the Rocky Mountains region, eastern South Dakota and other Great Plains States are in the North Central region.

c

Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and Pacific Northwest 

East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, 

inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections.

Table 32—Hardwood removals, harvest, growth, and inventory on forest industrya timberlands in the 

contiguous United States, 1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast: 

Removals 47 51 91 121 110 158 158 160 158 157 156 157

Harvest 44 45 69 89 216 199 163 169 165 163 161 163

Net annual growth 129 156 193 226 230 196 191 217 216 213 210 205

Inventory 4,742 5,554 6,819 7,636 8,835 8,700 8,531 9,592 10,094 10,565 11,017 11,416

North Central:b

Removals 74 45 64 69 142 105 93 56 41 27 13 6

Harvest 73 41 57 55 201 113 62 58 43 29 16 10

Net annual growth 99 100 118 118 105 86 86 80 77 69 61 58

Inventory 2,048 2,673 3,129 3,376 3,430 3,274 3,277 3,533 3,738 4,005 4,310 4,698

Southeast:

Removals 169 158 161 147 185 285 217 142 107 98 122 130

Harvest 127 96 108 107 176 257 160 126 98 93 119 129

Net annual growth 171 174 230 259 246 191 199 167 159 146 138 129

Inventory 5,588 6,220 7,248 7,542 8,157 6,857 6,566 5,323 5,356 5,326 5,576 5,580

South Central:

Removals 211 375 202 213 322 454 406 319 301 352 364 360

Harvest 157 227 213 184 323 430 376 304 286 339 353 351

Net annual growth 203 285 379 453 348 358 349 362 317 304 305 308

Inventory 5,656 7,753 8,086 9,661 9,594 9,488 9,633 8,446 8,601 8,376 7,746 7,141
191

The 2005 RPA Timber Assessment Update

Table 32—Hardwood removals, harvest, growth, and inventory on forest industrya timberlands in the 

contiguous United States, 1952–2002, with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Rocky Mountains:c

Removals 3 6 3 3 11 3 3 30 33 36 40 40

Harvest 0 0 1 1 27 3 60 66 70 76 82 85

Net annual growth 2 2 2 2 1 8 1 1 1 1 1 1

Inventory 103 101 100 64 33 31 31 24 23 26 30 36

Pacific Southwest:

Removals 3 4 5 4 4 5 5 15 15 15 14 14

Harvest 2 3 3 3 24 25 38 41 42 43 45 47

Net annual growth 11 15 24 19 46 45 46 52 53 55 56 55

Inventory 336 449 717 679 1,374 1,701 1,701 2,099 2,462 2,831 3,103 3,380

Pacific Northwest:

Removals 18 24 44 44 44 40 40 96 93 90 87 84

Harvest 18 22 37 34 57 42 136 136 130 123 117 114

Net annual growth 75 98 124 145 154 101 73 120 120 126 125 119

Inventory 1,900 2,675 3,282 3,355 3,888 3,475 3,475 3,234 3,406 3,708 4,034 4,342

United States:

 Removals 525 663 570 600 818 1,050 927 817 749 775 796 792

 Harvest 421 434 488 473 1,025 1,069 996 901 834 867 893 900

 Net annual growth 690 830 1,070 1,222 1,130 986 945 998 943 914 897 874

 Inventory 20,373 25,425 29,381 32,313 35,311 33,526 33,214 32,251 33,680 34,838 35,816 36,594

Note: Historical harvest data are estimates of the harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as of 

January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year.

a

Lands held by firms with commercial timber production objectives but no processing facilities (e.g., timberland investment 

organizations [TIMOs] and real estate investment trusts [REITs]) are included in forest industry and nonindustrial private forest 

categories, depending on their classification in the starting (approximately 1995) inventory data. See text in chapter 2 “Projected 

Area Changes for Land Uses and Forest Management Cover Types” section for further discussion.

b

Data for the Great Plains are included in the Rocky Mountains region for the historical period. For projections, western South 

Dakota is in the Rocky Mountains region, eastern South Dakota and other Great Plains States are in the North Central region.

c

1997 increase in growth data is due to changes in inventory procedures.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, 

inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections. 
192

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 33—Softwood removals, harvest, growth, and inventory on nonindustrial private forest (NIPF)a

timberlands, 1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 358 274 263 300 226 278 282 251 247 238 236 245

Harvest 338 258 244 278 296 375 324 340 345 342 346 364

Net annual growth 433 539 510 623 441 508 513 444 410 384 355 324

Inventory 13,438 16,031 16,214 17,976 19,244 21,563 21,809 23,608 24,635 25,273 25,598 25,776

North Central:b

Removals 59 61 72 79 109 132 130 183 191 194 193 193

Harvest 62 63 70 74 119 144 194 194 204 207 208 208

Net annual growth 128 152 170 196 250 257 255 274 266 252 236 228

Inventory 2,610 3,382 4,010 4,899 6,246 8,155 8,198 9,919 10,516 10,878 11,071 11,216

Southeast:

Removals 1,444 1,234 1,235 1,365 1,821 1,826 1,667 1,554 1,630 1,785 2,052 2,237

Harvest 1,414 1,189 1,157 1,247 1,640 1,741 1,312 1,505 1,583 1,723 2,014 2,203

Net annual growth 1,349 1,567 1,882 2,130 1,656 1,688 1,897 1,938 1,835 1,861 1,843 1,830

Inventory 25,087 28,033 32,179 36,150 35,415 34,187 34,915 42,728 45,560 46,851 46,527 43,163

South Central:

Removals 606 787 1,117 1,278 1,569 2,072 2,200 1,605 1,712 1,851 2,043 2,312

Harvest 584 748 1,129 1,264 1,507 1,995 1,877 1,557 1,672 1,811 2,000 2,264

Net annual growth 792 1,182 1,668 2,000 1,762 1,719 1,876 1,929 2,070 2,259 2,392 2,372

Inventory 11,273 16,128 23,646 28,760 31,555 30,408 32,741 28,086 32,270 36,473 40,799 42,705

Rocky Mountains:

Removals 127 111 93 109 137 184 231 236 265 278 302 309

Harvest 79 74 118 147 154 221 390 346 408 439 480 499

Net annual growth 213 247 276 283 315 458 446 372 348 352 373 396

Inventory 12,842 13,649 14,112 14,445 13,029 16,489 16,749 17,115 17,968 18,573 19,223 20,015

Pacific Southwest:

Removals 542 271 178 145 34 145 203 94 96 110 132 152

Harvest 468 230 163 136 35 164 168 109 112 129 157 183

Net annual growth 178 192 211 197 238 270 262 227 211 209 213 208

Inventory 15,256 12,900 9,608 9,337 9,931 9,716 9,716 10,986 12,180 13,136 13,969 14,589

Pacific Northwest West:c

Removals 302 201 259 200 203 304 364 365 333 351 390 435

Harvest 317 207 245 195 232 298 462 381 342 360 399 444

Net annual growth 265 308 358 340 409 404 354 377 410 502 550 512

Inventory 9,510 9,520 10,304 8,458 10,171 10,336 10,335 8,959 9,729 11,263 13,025 14,004

Pacific Northwest East:c

Removals 103 68 49 65 70 153 179 59 67 97 118 136

Harvest 100 67 48 60 65 198 99 64 74 106 129 148

Net annual growth 109 136 148 121 122 217 111 190 192 203 209 207

Inventory 4,495 4,319 4,725 4,604 3,896 7,321 7,324 9,338 10,656 11,936 13,090 13,970

Alaska:d

Removals — — 4 2 61 123 120 60 30 15 15 15

Harvest — — 5 2 54 93 124 62 31 16 16 16

Net annual growth 1 2 2 3 21 11 15 15 15 15 15 15

Inventory 218 283 323 663 7,103 5,987 4,177 3,502 3,202 3,127 3,127 3,127
193

The 2005 RPA Timber Assessment Update

Table 33—Softwood removals, harvest, growth, and inventory on nonindustrial private forest (NIPF)a

timberlands, 1952–2002, with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

United States:

Removals 3,541 3,007 3,270 3,543 4,230 5,217 5,572 4,408 4,572 4,899 5,482 6,033

Harvest 3,362 2,836 3,179 3,403 4,102 5,189 4,950 4,558 4,772 5,134 5,749 6,330

Net annual growth 3,468 4,325 5,225 5,893 5,214 5,532 5,730 5,767 5,757 6,037 6,184 6,093

Inventory 94,729 104,245 115,121 125,292 136,590 144,162 145,964 154,242 166,718 177,511 186,428 188,566

Note: Historical harvest data are estimates of the harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as of 

January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year. Historical data updated 

since 2000 report.

— = less than 0.5 million cubic feet. a

Lands held by firms with commercial timber production objectives but no processing facilities (e.g., timberland investment 

organizations [TIMOs] and real estate investment trusts [REITs]) are included in forest industry and nonindustrial private 

forest categories, depending on their classification in the starting (approximately 1995) inventory data. See text in chapter 2 

“Projected Area Changes for Land Uses and Forest Management Cover Types” section for further discussion.

b

Data for the Great Plains are included in the Rocky Mountains region for the historical period. For projections, western South 

Dakota is in the Rocky Mountains region, eastern South Dakota and other Great Plains States are in the North Central region.

c

Pacific Northwest West (western Oregon and western Washington) is also called the Douglas-fir subregion, and Pacific 

Northwest East (eastern Oregon and eastern Washington) is also called the ponderosa pine subregion.

d

The increase in NIPF removals, harvest, growth, and inventory data in Alaska after 1986 was the result of the Alaska Native 

Claims Settlement Act that enabled Native corporations to select about 500,000 acres of land from the Tongass National Forest.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, 

inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections. 

Table 34—Hardwood removals, harvest, growth, and inventory on nonindustrial private forest (NIPF)a

timberlands, 1952–2002, with projections to 2050

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

Northeast:

Removals 424 503 591 623 630 643 647 851 873 905 980 1,099

Harvest 404 438 448 462 1,241 999 1,150 1,247 1,286 1,338 1,446 1,603

Net annual growth 1,018 1,296 1,465 1,491 1,620 1,767 1,722 1,488 1,489 1,481 1,447 1,400

Inventory 32,669 39,863 44,751 49,457 58,505 67,680 68,686 79,050 84,704 89,396 92,922 95,411

North Central:b

Removals 629 661 797 793 932 857 857 848 883 926 969 1,022

Harvest 751 685 738 737 1,326 1,079 1,017 1,074 1,124 1,183 1,248 1,327

Net annual growth 961 980 1,084 1,137 1,377 1,525 1,524 1,648 1,631 1,575 1,512 1,442

Inventory 24,385 29,009 31,821 35,636 42,884 53,655 54,492 66,507 73,277 79,106 83,668 89,936

Southeast:

Removals 817 861 843 801 1,096 1,138 1,105 1,494 1,605 1,666 1,593 1,540

Harvest 617 523 566 586 1,043 1,035 988 1,370 1,468 1,522 1,466 1,430

Net annual growth 1,020 1,175 1,439 1,715 1,633 1,559 1,646 1,536 1,439 1,425 1,438 1,454

Inventory 32,316 36,288 40,583 46,478 51,487 54,432 54,640 56,314 54,915 52,390 50,223 48,894
194

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 34—Hardwood removals, harvest, growth, and inventory on nonindustrial private forest (NIPF)a

timberlands, 1952–2002, with projections to 2050 (continued)

Historical Projections

Region and item 1952 1962 1970 1976 1986 1997 2002 2010 2020 2030 2040 2050

Million cubic feet

South Central:

Removals 1,396 1,313 1,012 948 1,208 1,633 1,688 2,000 2,190 2,260 2,373 2,518

Harvest 937 730 848 713 1,212 1,535 1,945 1,900 2,077 2,140 2,249 2,389

Net annual growth 1,424 1,459 1,845 2,117 1,800 2,239 2,345 2,197 2,134 2,098 2,130 2,152

Inventory 37,669 39,691 42,243 45,836 53,471 60,699 67,646 62,719 63,175 61,631 59,687 56,718

Rocky Mountains:c

Removals 27 18 18 17 7 20 18 31 34 38 41 41

Harvest 1 1 1 1 17 29 60 66 70 76 82 85

Net annual growth 46 51 57 60 84 284 96 49 43 42 42 41

Inventory 2,251 2,412 2,600 2,720 3,462 4,971 4,905 2,998 3,038 3,044 3,028 2,991

Pacific Southwest:

Removals 4 7 10 8 1 2 2 26 25 23 21 20

Harvest 2 4 7 7 8 14 47 51 51 51 51 52

Net annual growth 29 30 40 36 95 80 78 94 89 85 80 74

Inventory 998 1,050 1,562 1,598 3,352 4,054 4,054 5,037 5,661 6,279 6,878 7,457

Pacific Northwest:

Removals 8 29 22 47 7 46 54 141 134 127 120 115

Harvest 6 24 16 37 9 51 181 184 173 161 151 145

Net annual growth 99 131 156 148 189 150 109 164 169 175 168 169

Inventory 3,197 3,972 4,711 3,807 5,201 5,185 5,185 5,519 5,782 6,212 6,653 7,163

Alaska:d

Removals — — — — — 3 3 6 12 12 12 12

Harvest — — — — — 3 3 3 3 3 3 3

Net annual growth — — — — 38 21 11 11 11 11 11 11

Inventory 39 82 102 121 2,312 1,040 515 574 594 584 574 564

United States:

Removals 3,305 3,392 3,293 3,237 3,881 4,342 4,374 5,397 5,756 5,956 6,109 6,366

Harvest 2,718 2,405 2,624 2,543 4,856 4,745 5,658 5,895 6,252 6,474 6,696 7,033

Net annual growth 4,597 5,122 6,086 6,704 6,836 7,625 7,530 7,189 7,005 6,892 6,827 6,743

Inventory 133,524 152,367 168,373 185,653 220,674 251,716 260,123 278,717 291,145 298,642 303,634 306,136

Note: Historical harvest data are estimates of the harvest trends and differ somewhat from the estimates of actual consumption 

shown in some tables. For the projection years, the data show the average volume that would be harvested given the assumptions 

of the study. Inventory data for 1952 and 1962 are as of December 31. Inventory data for 1970 and the projection years are as of 

January 1. Inventory data shown under 1976, 1986, 1997, and 2002 are as of January 1 of following year. 1997 data updated since 

2000 report.

— = less than 0.5 million cubic feet. a

Lands held by firms with commercial timber production objectives but no processing facilities (e.g., timberland investment 

organizations [TIMOs] and real estate investment trusts [REITs]) are included in forest industry and nonindustrial private 

forest categories, depending on their classification in the starting (approximately 1995) inventory data. See text in chapter 2 

“Projected Area Changes for Land Uses and Forest Management Cover Types” section for further discussion.

b

Data for the Great Plains are included in the Rocky Mountains region for the historical period. For projections, western South 

Dakota is in the Rocky Mountains region, eastern South Dakota and other Great Plains States are in the North Central region.

c

1997 increase in growth data is due to changes in Rocky Mountain inventory procedures.

d

The increase in NIPF removals, harvest, growth, and inventory data in Alaska after 1986 was the result of the Alaska Native 

Claims Settlement Act that enabled Native corporations to select about 500,000 acres of land from the Tongass National Forest.

Source: For historical data, Powell et al. 1993; 1997 removals, growth, inventory data Smith et al. 2001; 2002 removals, growth, 

inventory from Smith et al. 2004; harvest data from Haynes 2003; 2002 harvest estimated from the assessment projections.
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The 2005 RPA Timber Assessment Update

Table 35—Average diametera of timber harvested on private timberlands in the timber assessment regions

Pacific Coastb Rocky Mountainsb North South

Year Hardwood Softwood Hardwood Softwood Hardwood Softwood Hardwood Softwood

Inches

1976 — 27.5 — 16.9 13.3 11.3 13.7 13.1

1986 16.6 18.7 18.9 9.6 14.2 12.0 12.4 9.9

1990 16.5 17.4 17.5 9.5 13.6 12.0 12.1 10.7

1997 16.1 16.1 9.7 10.3 14.2 11.3 11.0 9.6

2002 16.2 15.8 9.9 10.0 13.1 11.2 11.3 9.2

2010 16.5 15.5 10.4 10.1 13.2 11.3 11.5 8.7

2030 16.8 15.2 11.9 11.0 13.8 10.7 11.6 8.5

2050 16.8 14.6 10.8 11.4 14.3 11.1 11.2 9.0

a

Diameter measured at breast height. Data do not include commercial thinning or area loss volume.

b

For this table, Pacific Coast = Pacific Northwest West and Pacific Southwest regions, Rocky Mountains = 

Pacific Northwest East and Rocky Mountain North and South regions. 

Table 36—Projections of Canadian softwood harvest 

Year Total harvest Sawtimber Pulpwood Annual allowable cut

Million cubic feet

1970 3,816 2,225 1,591 NA

1980 4,927 3,331 1,596 NA

1986 5,577 3,861 1,716 5,862

1990 4,946 3,586 1,360 6,639

1997 5,371 4,462 909 6,251

2002 5,641 4,903 738 6,251

2010 6,322 5,248 1,075 NA

2020 5,423 4,383 1,040 NA

2030 5,423 4,431 992 NA

2040 5,389 4,462 927 NA

2050 5,371 4,477 894 NA

NA = not available.

Source: Historical data: National Forestry Database Program, 

Canadian Forest Service (1999).
196

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 37—National forest timberland by seral stage

Seral stage

Species and area Seedlinga Poles-saplingsb Youngc Matured Old maturee Total 

Thousand acres

Softwood:

North—

2002 345 559 1,115 600 158 2,777

 2010 231 501 1,103 821 121 2,777

2020 232 341 990 1,086 128 2,777

 2030 197 263 889 1,372 139 2,777

2040 208 228 622 1,550 169 2,777

2050 192 228 447 1,715 194 2,777

South—

 2002 1,075 1,150 3,028 596 59 5,908

2010 166 1,174 2,784 1,732 52 5,908

2020 191 345 2,294 3,004 74 5,908

2030 180 363 1,498 3,738 130 5,908

2040 180 351 694 4,239 443 5,908

2050 173 343 700 3,412 1,280 5,908

West—

2002 4,335 4,485 13,104 28,023 16,190 66,137

2010 2,752 6,983 8,698 29,034 18,671 66,137

2020 2,724 7,651 6,324 28,246 21,193 66,137

2030 2,650 7,891 5,603 25,139 24,854 66,137

2040 2,578 6,343 7,607 21,654 27,956 66,137

 2050 2,516 6,181 8,520 16,916 32,005 66,137

Hardwood:

North—

2002 434 1,195 2,668 2,136 690 7,123

2010 255 1,313 1,725 3,140 691 7,123

2020 238 1,130 1,387 3,649 719 7,123

2030 224 895 1,191 4,061 753 7,123

2040 211 692 1,308 3,881 1,032 7,123

2050 200 649 1,126 3,979 1,169 7,123

South—

 2002 303 660 3,967 216 191 5,337

 2010 91 576 3,806 653 211 5,337

 2020 92 266 3,002 1,607 370 5,337

2030 88 263 1,724 2,463 800 5,337

2040 85 252 966 2,193 1,842 5,337

2050 82 243 757 1,198 3,058 5,337

West—

2002 232 614 522 3,472 748 5,588

2010 45 680 329 3,670 864 5,588

2020 34 565 300 3,673 1,015 5,588

2030 33 279 466 3,600 1,208 5,588

2040 34 93 527 3,370 1,563 5,588

2050 32 82 251 3,142 2,080 5,588

a

Seedlings seral stage = age 5 all regions and fiber except North softwood, which includes 5 to 15.

b

Poles and saplings seral stage = age 25 to 35 North softwood; 15 to 35 North hardwood; 10 to 15 South 

softwood; 10 to 20 South hardwood; 15 to 35 West hardwood and softwood.

c

Young sawtimber seral stage = age 45 to 65 North; 20 to 35 South softwood; 25 to 55 South hardwood; 

45 to 75 West softwood; 45 to 55 West hardwood.

d

Mature sawtimber seral stage = age 75 to 135 North; 40 to 75 South softwood; 60 to 75 South hardwood; 

85 to 135 West softwood; 65 to 135 West hardwood.

e

Old mature sawtimber seral stage = age 145+ North; 80+ South; 145+ West.
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The 2005 RPA Timber Assessment Update

Table 38—Other public timberland by seral stage

Seral stage

Species and area Seedlinga Poles-saplingsb Youngc Matured Old maturee Total 

Thousand acres

Softwood:

North—

2002 657 1,221 2,404 1,627 362 6,270

 2010 688 1,058 2,001 2,288 235 6,270

 2020 682 657 2,099 2,605 228 6,270

2030 514 688 1,590 3,267 210 6,270

2040 442 682 1,345 3,505 296 6,270

2050 399 514 1,058 3,925 374 6,270

South—

2002 523 1,191 2,336 381 5 4,436

2010 293 822 2,547 773 1 4,436

2020 294 578 2,013 1,544 8 4,436

2030 277 586 1,400 2,160 12 4,436

2040 296 565 1,164 2,327 84 4,436

2050 303 597 1,151 2,107 278 4,436

West—

2002 1,109 1,469 3,262 3,643 979 10,463

2010 706 1,996 2,930 3,602 1,228 10,463

2020 677 2,335 2,426 3,870 1,156 10,463

2030 626 2,493 2,152 3,644 1,549 10,463

2040 583 2,010 2,578 3,772 1,521 10,463

2050 550 1,885 2,703 3,451 1,874 10,463

Hardwood:

North—

2002 810 3,287 6,654 4,619 1,260 16,630

2010 1,104 3,300 4,178 6,936 1,112 16,630

2020 924 3,057 4,050 7,452 1,147 16,630

 2030 817 2,838 3,287 8,577 1,112 16,630

2040 726 2,845 3,300 8,335 1,425 16,630

2050 671 2,467 3,057 8,942 1,492 16,630

South—

2000 463 1,156 3,691 95 140 5,545

2010 175 915 4,128 210 117 5,545

2020 201 540 3,812 862 129 5,545

2030 220 620 2,576 1,947 182 5,545

2040 242 671 1,721 2,396 516 5,545

2050 244 717 1,538 1,582 1,465 5,545

West—

2002 142 346 286 744 111 1,629

2010 74 336 297 807 114 1,629

 2020 63 286 276 886 118 1,629

2030 55 279 194 971 130 1,629

2040 48 192 212 1,047 131 1,629

2050 43 165 216 1,005 199 1,629

a

Seedlings seral stage = age 5 all regions and fiber except North softwood, which includes 5 to 15.

b

Poles and saplings seral stage = age 25 to 35 North softwood; 15 to 35 North hardwood; 10 to 15 South 

softwood; 10 to 20 South hardwood; 15 to 35 West hardwood and softwood.

c

Young sawtimber seral stage = age 45 to 65 North; 20 to 35 South softwood; 25 to 55 South hardwood; 

45 to 75 West softwood; 45 to 55 West hardwood.

d

Mature sawtimber seral stage = age 75 to 135 North; 40 to 75 South softwood; 60 to 75 South hardwood; 

85 to 135 West softwood; 65 to 135 West hardwood.

e

Old mature sawtimber seral stage = age 145+ North; 80+ South; 145+ West.
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GENERAL TECHNICAL REPORT PNW-GTR-699

Table 39—Private timberland area by seral stage

Seral stage

Species and area Seedlinga Poles-saplingsb Youngc Matured Old maturee Total 

Thousand acres

Softwood:

North—

2002 3,196 5,394 8,026 6,686 206 23,508

2010 4,175 2,692 9,146 6,098 260 22,371

2020 3,204 3,254 6,751 7,863 301 21,373

2030 2,483 4,216 5,589 7,529 383 20,200

2040 1,782 3,235 4,894 8,716 426 19,052

2050 1,660 2,502 4,865 8,464 731 18,222

South—

2002 12,675 25,587 30,262 14,942 1,020 84,487

2010 13,290 27,480 36,211 10,914 1,169 89,064

2020 11,957 26,727 41,438 10,174 1,541 91,837

2030 12,253 24,792 40,147 14,584 1,933 93,708

2040 11,486 24,176 39,612 16,177 2,265 93,717

2050 11,611 23,069 39,527 16,307 2,548 93,062

West—

2002 6,477 9,299 10,683 12,089 2,576 41,124

2010 4,392 14,053 7,526 12,654 2,368 40,994

2020 2,779 15,941 6,631 11,914 3,591 40,856

2030 2,796 13,828 8,397 11,870 3,705 40,596

2040 2,974 10,126 12,348 9,719 5,394 40,559

2050 3,237 8,678 14,099 7,770 6,638 40,422

Hardwood:

North—

2002 11,175 29,946 36,459 28,693 618 106,891

2010 9,450 27,569 41,171 28,692 1,254 108,140

2020 7,618 28,376 32,794 37,097 1,561 107,445

2030 7,054 28,970 29,391 38,131 2,786 106,333

2040 6,577 24,456 27,212 43,008 3,475 104,728

2050 6,832 21,494 27,994 41,154 5,893 103,367

South—

2002 6,042 18,891 42,449 19,228 8,912 95,521

2010 4,073 19,397 36,017 18,486 12,406 90,379

2020 4,842 13,848 40,202 13,812 14,269 86,973

2030 5,457 16,436 39,062 9,020 14,751 84,726

2040 5,226 19,009 39,331 7,646 12,813 84,025

2050 5,116 20,292 39,824 7,945 10,805 83,983

West—

2002 480 1,571 1,828 3,285 94 7,259

2010 606 1,427 1,509 3,454 70 7,067

 2020 587 1,517 1,092 3,617 153 6,966

2030 491 1,688 890 3,642 203 6,915

2040 511 1,718 791 3,468 406 6,893

2050 543 1,625 874 3,238 620 6,900

a

Seedlings seral stage = age 5 all regions and fiber except North softwood, which includes 5 to 15.

b

Poles and saplings seral stage = age 25 to 35 North softwood; 15 to 35 North hardwood; 10 to 15 South 

softwood; 10 to 20 South hardwood; 15 to 35 West hardwood and softwood.

c

Young sawtimber seral stage = age 45 to 65 North; 20 to 35 South softwood; 25 to 55 South hardwood; 

45 to 75 West softwood; 45 to 55 West hardwood.

d

Mature sawtimber seral stage = age 75 to 135 North; 40 to 75 South softwood; 60 to 75 South hardwood; 

85 to 135 West softwood; 65 to 135 West hardwood.

e

Old mature sawtimber seral stage = age 145+ North; 80+ South; 145+ West.
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The 2005 RPA Timber Assessment Update

Table 40—Indices of change for selected indicators for the North, South, and West regions

Area of Total growing- Softwood Composite

Area Old stands Fragmentation timberland stock inventory inventory Growth/harvest index

- - - - - - - - - - - - - - - - - - - - - - - 1952 = 100 - - - - - - - - - - - - - - - - - - - - - - - Percent

North:

1952 100 100 100 100 100 188 115

1962 95 76 101 124 101 242 132

1970 93 73 100 140 102 245 136

1976 91 68 99 157 103 250 140

1986 106 113 100 183 96 134 119

1991 115 120 102 200 94 116 120

1997 121 92 103 207 88 147 133

2002 121 86 103 210 88 156 137

2010 128 82 103 242 84 141 142

2020 136 76 103 262 83 137 148

2030 161 71 101 281 82 132 156

2040 189 69 99 296 82 122 162

2050 249 69 98 309 82 111 172

South:

1952 100 100 100 100 100 134 106

1962 95 77 102 117 106 185 121

1970 96 80 99 134 110 185 122

1976 98 78 98 150 111 190 126

1986 102 97 96 165 106 121 114

1991 110 95 97 169 101 120 117

1997 117 110 98 173 100 112 115

2002 117 95 99 180 99 134 123

2010 145 104 98 183 105 126 124

2020 160 109 98 196 112 116 125

2030 166 113 98 202 118 111 125

2040 164 118 97 207 122 107 124

2050 178 125 97 206 125 100 123

West:

1952 100 100 100 100 100 89 98

1962 96 106 100 100 99 100 99

1970 94 119 98 98 98 105 97

1976 92 117 93 95 98 111 96

1986 88 132 90 91 96 124 96

1991 87 127 88 90 95 126 96

1997 87 81 95 100 95 225 123

2002 83 78 95 102 95 206 120

2010 88 82 95 109 95 182 117

2020 90 77 95 118 95 175 119

2030 94 72 95 128 95 172 122

2040 99 70 94 137 95 164 124

2050 104 68 94 146 94 153 125

Source: The data for all columns except old stands are given in tables 4 and 12. The indices were computed by dividing each value by 

the 1952 value for that series except the ratio of growth to harvest, which is used directly. See Haynes (2007) for computation details.
200

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 41—Summary of base case and alternative scenarios

Reduction in Sequestered Restoration

nonindustrial Climate carbon Reduced southern thinning

Year Base private forest area plus CO2 Climate only in plantations pine plantation public land

Million board feet

Softwood lumber production:

2002 35,831 35,831 35,831 35,831 35,831 35,831 35,831

2010 33,690 33,684 33,711 33,692 33,690 33,689 34,886

2020 35,400 35,379 35,453 35,383 35,412 35,379 36,615

2030 37,165 37,131 37,346 37,202 37,194 37,125 38,676

2040 40,387 40,335 40,706 40,465 40,424 40,300 41,784

2050 43,968 43,807 44,456 44,137 44,035 43,792 45,507

Softwood lumber consumption:

2002 55,981 55,981 55,981 55,981 55,981 55,981 55,981

2010 58,964 58,963 58,969 58,965 58,964 58,964 59,302

2020 58,522 58,517 58,535 58,515 58,525 58,516 58,967

2030 60,906 60,893 60,941 60,905 60,916 60,884 61,537

2040 65,801 65,789 65,879 65,824 65,813 65,758 66,483

2050 71,324 71,274 71,497 71,386 71,352 71,259 72,129

Softwood lumber imports:

2002 20,980 20,980 20,980 20,980 20,980 20,980 20,980

2010 26,273 26,279 26,258 26,273 26,273 26,275 25,416

2020 24,248 24,263 24,207 24,258 24,238 24,262 23,477

2030 24,991 25,012 24,845 24,953 24,973 25,008 24,111

2040 26,788 26,830 26,549 26,734 26,764 26,833 26,074

2050 28,857 28,968 28,541 28,749 28,818 28,967 28,122

1982 = 100

Softwood lumber price index:

2002 1.303 1.303 1.303 1.303 1.303 1.303 1.303

2010 1.198 1.199 1.197 1.198 1.198 1.199 1.161

2020 1.388 1.390 1.384 1.389 1.387 1.390 1.332

2030 1.354 1.358 1.345 1.354 1.353 1.360 1.286

2040 1.402 1.406 1.386 1.395 1.400 1.408 1.345

2050 1.462 1.474 1.436 1.451 1.458 1.474 1.400

Hardwood lumber price index:

2002 1.360 1.360 1.360 1.360 1.360 1.360 1.360

2010 1.455 1.455 1.453 1.454 1.455 1.455 1.452

2020 1.557 1.558 1.554 1.557 1.557 1.557 1.552

2030 1.603 1.606 1.598 1.603 1.603 1.603 1.599

2040 1.642 1.646 1.635 1.642 1.642 1.642 1.639

2050 1.664 1.671 1.654 1.663 1.664 1.663 1.662

1982 dollars/thousand board feet

South softwood sawtimber harvest price:

2002 209 209 209 209 209 209 209

2010 248 248 245 246 248 248 243

2020 246 247 241 248 245 249 242

2030 232 234 221 233 228 240 227

2040 226 230 207 225 219 240 222

2050 227 235 201 225 217 249 222
201

The 2005 RPA Timber Assessment Update

Table 41—Summary of base case and alternative scenarios (continued)

Reduction in Sequestered Restoration

nonindustrial Climate carbon Reduced southern thinning

Year Base private forest area plus CO2 Climate only in plantations pine plantation public land

1982 dollars/thousand board feet

Pacific Northwest West softwood sawtimber harvest price:

2002 208 208 208 208 208 208 208

2010 169 170 167 169 169 169 162

2020 229 231 225 230 229 229 218

2030 217 222 205 215 216 218 216

2040 217 225 190 206 214 218 220

2050 231 246 189 212 226 232 235

North hardwood sawtimber harvest price:

2002 186 186 186 186 186 186 186

2010 172 172 170 171 172 172 172

2020 170 170 169 170 170 170 170

2030 181 181 179 180 181 181 181

2040 193 193 193 193 193 193 193

2050 208 208 210 208 207 208 208

South hardwood sawtimber harvest price:

2002 99 99 99 99 99 99 99

2010 83 83 82 82 83 82 83

2020 91 92 88 90 91 90 90

2030 99 103 93 98 98 98 98

2040 108 116 98 106 108 107 108

2050 118 132 101 115 117 116 118

Million cubic feet

North softwood growing-stock removals:

2002 643 643 643 643 643 643 643

2010 690 690 690 690 690 690 687

2020 656 656 658 658 656 656 654

2030 626 626 629 628 626 626 624

2040 614 619 617 617 615 619 614

2050 620 624 623 623 621 623 621

South softwood growing-stock removals:

2002 6,514 6,514 6,514 6,514 6,514 6,514 6,514

2010 6,082 6,082 6,115 6,120 6,082 6,083 6,027

2020 7,031 7,012 7,025 6,974 7,032 7,013 6,982

2030 7,646 7,614 7,729 7,601 7,660 7,576 7,537

2040 8,335 8,398 8,393 8,302 8,327 8,195 8,363

2050 9,117 8,952 9,128 9,130 9,108 8,836 8,918

West softwood growing-stock removals:

2002 2,759 2,759 2,759 2,759 2,759 2,759 2,759

2010 2,769 2,769 2,769 2,768 2,769 2,769 2,968

2020 2,749 2,748 2,752 2,749 2,749 2,750 2,936

2030 2,788 2,785 2,800 2,792 2,788 2,791 3,029

2040 2,944 2,938 2,971 2,955 2,946 2,948 3,158

2050 3,101 3,084 3,145 3,124 3,106 3,108 3,340

North hardwood growing-stock removals:

2002 2,068 2,068 2,068 2,068 2,068 2,068 2,068

2010 2,182 2,182 2,181 2,182 2,182 2,182 2,181

2020 2,224 2,223 2,214 2,226 2,224 2,224 2,223

2030 2,270 2,273 2,246 2,269 2,260 2,272 2,259

2040 2,373 2,397 2,336 2,396 2,341 2,388 2,370

2050 2,563 2,598 2,454 2,622 2,475 2,549 2,556
202

GENERAL TECHNICAL REPORT PNW-GTR-699

Table 41—Summary of base case and alternative scenarios (continued)

Reduction in Sequestered Restoration

nonindustrial Climate carbon Reduced southern thinning

Year Base private forest area plus CO2 Climate only in plantations pine plantation public land

Million cubic feet

South hardwood growing-stock removals:

2002 3,557 3,557 3,557 3,557 3,557 3,557 3,557

2010 4,097 4,096 4,060 4,065 4,097 4,098 4,099

2020 4,350 4,328 4,324 4,354 4,350 4,340 4,340

2030 4,576 4,539 4,567 4,553 4,579 4,547 4,560

2040 4,644 4,585 4,705 4,637 4,644 4,655 4,659

2050 4,767 4,576 4,799 4,785 4,736 4,797 4,750

U.S. sawtimber softwood harvest:

2002 5,887 5,888 5,887 5,887 5,887 5,887 5,887

2010 5,075 5,074 5,078 5,075 5,075 5,074 5,227

2020 5,071 5,069 5,078 5,069 5,073 5,068 5,211

2030 5,170 5,167 5,192 5,174 5,175 5,163 5,335

2040 5,445 5,440 5,481 5,452 5,449 5,431 5,593

2050 5,697 5,681 5,749 5,712 5,705 5,670 5,861

U.S. nonsawtimber softwood harvest:

2002 3,911 3,911 3,911 3,911 3,911 3,911 3,911

2010 4,695 4,695 4,724 4,732 4,695 4,697 4,704

2020 5,600 5,582 5,592 5,548 5,598 5,587 5,600

2030 6,138 6,107 6,213 6,097 6,148 6,081 6,110

2040 6,704 6,770 6,755 6,681 6,694 6,591 6,802

2050 7,414 7,255 7,418 7,442 7,403 7,178 7,298

U.S. sawtimber hardwood harvest:

2002 2,509 2,509 2,509 2,509 2,509 2,509 2,509

2010 2,466 2,466 2,468 2,467 2,466 2,466 2,464

2020 2,470 2,469 2,473 2,471 2,471 2,471 2,467

2030 2,498 2,495 2,502 2,498 2,498 2,498 2,492

2040 2,546 2,541 2,552 2,546 2,545 2,547 2,540

2050 2,583 2,576 2,592 2,584 2,584 2,585 2,577

U.S. nonsawtimber hardwood harvest:

2002 4,770 4,770 4,770 4,770 4,770 4,770 4,770

2010 4,937 4,936 4,901 4,908 4,937 4,937 4,939

2020 5,231 5,211 5,195 5,236 5,231 5,222 5,225

2030 5,495 5,470 5,457 5,471 5,488 5,472 5,476

2040 5,698 5,677 5,699 5,713 5,665 5,719 5,712

2050 6,062 5,947 5,963 6,138 5,943 6,069 6,048

North private softwood growing-stock inventory:

2002 37,155 37,155 37,155 37,155 37,155 37,155 37,155

2010 39,710 39,710 40,033 39,931 39,710 39,710 39,716

2020 41,645 41,644 42,401 42,021 41,680 41,646 41,665

2030 43,337 43,335 44,722 43,972 43,448 43,339 43,378

2040 44,676 44,656 46,787 45,642 44,863 44,659 44,728

2050 45,884 45,833 48,738 47,271 46,160 45,835 45,931

South private softwood-growing stock inventory:

2002 91,795 91,795 91,795 91,795 91,795 91,795 91,795

2010 97,261 96,640 100,592 99,214 97,261 97,106 97,364

2020 110,970 108,387 119,726 113,178 113,809 108,475 111,420

2030 121,837 115,489 139,937 126,104 131,182 113,679 123,021

2040 129,881 119,042 158,855 135,788 143,414 116,915 131,785

2050 131,182 115,222 172,254 139,387 147,268 114,656 133,414
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The 2005 RPA Timber Assessment Update

Table 41—Summary of base case and alternative scenarios (continued)

Reduction in Sequestered Restoration

nonindustrial Climate carbon Reduced southern thinning

Year Base private forest area plus CO2 Climate only in plantations pine plantation public land

Million cubic feet

West private softwood growing-stock inventory:

2002 69,735 69,739 69,735 69,735 69,735 69,735 69,737

2010 70,419 70,275 70,655 70,254 70,419 70,419 70,783

2020 74,732 74,315 75,883 74,424 74,793 74,726 76,664

2030 80,472 79,600 84,623 81,430 80,789 80,455 84,447

2040 87,319 85,709 96,539 90,704 88,112 87,268 92,812

2050 92,664 90,067 109,057 99,671 94,100 92,564 97,375

North private hardwood growing-stock inventory:

2002 145,696 145,696 145,696 145,696 145,696 145,696 145,696

2010 157,492 157,491 159,232 158,522 157,492 157,492 157,493

2020 170,482 170,474 174,160 171,781 170,502 170,480 170,473

2030 181,607 181,614 188,480 183,798 181,695 181,616 181,650

2040 190,323 190,216 201,016 193,650 190,527 190,220 190,359

2050 196,747 196,477 211,511 201,689 197,496 196,580 196,893

South private hardwood growing-stock inventory:

2002 131,468 131,468 131,468 131,468 131,468 131,468 131,468

2010 132,752 131,648 135,067 133,679 132,752 133,914 132,753

2020 131,983 128,732 137,570 132,547 132,207 133,984 132,013

2030 127,645 121,379 138,934 129,186 128,256 130,226 127,783

2040 123,139 112,987 141,741 125,315 123,990 126,522 123,458

2050 118,225 103,604 147,226 122,408 119,597 121,955 118,669

1982 = 100

Price index for paperboard:

2002 110.374 110.374 110.374 110.374 110.374 110.374 110.374

2010 102.188 102.199 102.127 102.138 102.188 102.392 102.408

2020 101.303 101.713 101.293 101.827 101.296 101.548 101.525

2030 98.926 98.829 98.898 98.952 99.027 99.006 99.080

2040 99.267 99.294 97.963 98.591 98.285 99.517 99.530

2050 101.776 103.855 102.843 102.024 104.275 103.888 103.725

Price index for paper:

2002 125.324 125.324 125.324 125.324 125.324 125.324 125.324

2010 131.257 131.258 130.793 130.806 131.257 131.284 131.282

2020 124.411 124.946 124.462 124.299 124.411 124.921 125.674

2030 118.109 117.827 117.697 117.871 117.648 118.690 119.222

2040 118.522 118.869 116.396 117.783 117.074 118.551 117.634

2050 118.855 119.952 117.202 118.911 117.107 120.299 118.731

1982 dollars/cord

Southern softwood pulpwood price:

2002 12 12 12 12 12 12 12

2010 18 18 17 17 18 18 19

2020 15 15 13 15 15 16 16

2030 10 11 8 10 9 12 11

2040 12 15 7 11 9 15 13

2050 13 18 6 12 9 17 13
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GENERAL TECHNICAL REPORT PNW-GTR-699

Table 41—Summary of base case and alternative scenarios (continued)

Reduction in Sequestered Restoration

nonindustrial Climate carbon Reduced southern thinning

Year Base private forest area plus CO2 Climate only in plantations pine plantation public land

1982 dollars/cord

Southern hardwood pulpwood price:

2002 11 11 11 11 11 11 11

2010 7 7 6 6 7 6 7

2020 5 5 5 5 5 5 5

2030 10 11 9 10 9 9 10

2040 17 20 12 16 15 17 18

2050 20 22 13 20 19 21 20

Million short tons

U.S. paper production:

2002 45.1 45.1 45.1 45.1 45.1 45.1 45.1

2010 41.9 41.9 41.8 42.0 41.9 41.9 41.9

2020 42.3 42.2 41.8 43.0 42.3 42.3 42.3

2030 44.4 43.8 43.6 44.6 44.2 43.7 43.6

2040 46.0 46.0 45.6 46.0 46.0 45.5 45.6

2050 46.7 45.9 46.7 47.7 47.2 46.0 45.9

U.S. paperboard production:

2002 51.5 51.5 51.5 51.5 51.5 51.5 51.5

2010 52.9 52.9 52.9 52.9 52.9 53.0 53.0

2020 61.3 61.0 61.0 59.9 61.3 61.0 61.5

2030 68.9 69.5 69.4 67.6 69.1 69.3 69.1

2040 76.4 77.2 76.6 74.8 74.9 75.3 78.0

2050 83.5 84.3 80.6 80.9 81.1 82.0 82.7

Million cubic feet

U.S. softwood pulpwood harvest:

2002 3,188 3,188 3,188 3,188 3,188 3,188 3,188

2010 3,987 3,987 4,016 4,024 3,987 3,989 3,999

2020 4,900 4,883 4,893 4,849 4,898 4,887 4,927

2030 5,370 5,337 5,438 5,324 5,375 5,309 5,359

2040 5,881 5,944 5,928 5,860 5,876 5,766 5,993

2050 6,527 6,368 6,532 6,553 6,509 6,290 6,413

U.S. hardwood pulpwood harvest:

2002 2,843 2,843 2,843 2,843 2,843 2,843 2,843

2010 2,846 2,845 2,810 2,817 2,846 2,846 2,848

2020 3,026 3,006 2,990 3,031 3,026 3,017 3,020

2030 3,189 3,156 3,152 3,164 3,181 3,158 3,169

2040 3,232 3,218 3,233 3,250 3,199 3,260 3,256

2050 3,424 3,298 3,332 3,492 3,305 3,433 3,403

Percent

U.S. wastepaper recovery rate:

2002 48.20 48.20 48.20 48.20 48.20 48.20 48.20

2010 52.45 52.45 52.58 52.52 52.45 52.46 52.45

2020 51.03 51.21 51.54 51.26 51.07 51.17 51.46

2030 50.46 50.83 50.63 50.52 50.61 50.65 50.75

2040 50.41 50.34 50.41 50.35 50.63 50.49 50.14

2050 49.92 50.43 50.14 49.45 50.35 50.31 50.07
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The 2005 RPA Timber Assessment Update

Appendix 2: A Price-and-Yield-Sensitive Mechanism 

for Allocation of Regeneration Area to Management 

Intensity Classes in ATLAS

Within the Aggregate Timberland Assessment (ATLAS) timber inventory projection model, private timberland area shifts between management intensity classes 

(MICs) only at the time of regeneration (after harvest). For a given region, ownership, forest type, and site class (called a “stratum”), harvested areas from all MICs 

are pooled and assigned to new MICs in the subsequent rotation. In past assessments this assignment has been based on exogenously determined patterns or percentages developed to emulate the expected behavior in the stratum. These patterns 

were generally not sensitive to changes in prices, costs, or yields save to the extent 

that they were modified in some cases, based on judgment, to reflect variation in 

these factors. In the 2005 update, an alternative mechanism was developed to allocate regeneration areas to MICs in a way that is sensitive to both the financial and 

yield characteristics of alternative MICs and, in the South only, reflects the results 

of past surveys on owner intentions to undertake various MIC regimes.

As in the development of the private timber supply relations used in Timber 

Assessment Market Model (TAMM) and North America Pulp and Paper (NAPAP), 

we assume that private owners manage their lands so as to maximize their intertemporal utility. For industrial owners this may be largely a function of the present 

value of future net returns from timber sales, whereas for nonindustrial private 

(NIPF) owners, utility may depend on both net returns and other factors including 

satisfaction derived directly from the ownership of some area or volume of timber. 

To illustrate the derivation, consider a simple case in which only net returns matter. We examine only three periods and use a highly simplified form for the utility 

function. Following Ovaskainen (1992), the owner’s problem can be written as:

Maximize U = u(c1) + βu(c2) + β2u(c3)

subject to:

 c1 = p1H1 - w1E1

 c2 = p2H2 - w2E2

 c3 = p3H3

 I

1 = I0 - H1

 I

2 = I1 - H2 + F(I1,E1)

 I

3 = I2 - H3 + F(I2,E2) = 0 ,
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GENERAL TECHNICAL REPORT PNW-GTR-699

where

U is the owner’s overall intertemporal utility,

u is the utility contribution from a single period (assumed to be separable),

β is the owner’s rate of time preference or “discount” rate,

ct is net return in period t,

Ht is harvest,

pt is the price of timber,

Et is the management investment or management “effort,”

wt is the unit cost of management input,

I

t

 is the inventory of timber after harvest (I

0 is the initial inventory), and

F(I

t

, Et) is the growth of the forest in period t that depends on the starting inventory and the extent of management investment.

We assume that F rises with I and with E—more intensive management 

produces higher yields.

Ovaskainen (1992) shows that the owner’s solution to this problem leads to 

rules for harvest and management investment that can be summarized as:

H*

 = H* ( pt, pt+1, β, w, I

0)

E* = E* ( pt, pt+1, β, w, I

0 )

Both harvest and management input depend on current and expected future 

timber prices, the “discount” rate, the cost of management inputs and the initial 

inventory. The harvesting expression motivates the form of the timber supply 

relations used elsewhere in TAMM and NAPAP. The management input or management “effort” expression provides the basis for our alternative model of MIC 

allocation. Note that the specific form of E* will depend on an array of unobservable conditions, including the specific forms of the u’s and F.

In the ATLAS context, management intensity/investment is set at the start of 

a rotation by selecting the allocations of regeneration lands to different MICs. By 

analogy with the E* equation above, we assume that owners wish to allocate portions of their regeneration land to various MICs within a given stratum depending 

on the anticipated soil expectation value (SEV) of the MIC and an array of other 

concerns linked to specific owner, region, type, and site conditions. The SEV incorporates current and anticipated prices, costs, and discount rates. We ignore I

0, as it 

is fixed. The desired fractional allocation to MIC j in stratum i can be written as:
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The 2005 RPA Timber Assessment Update

A*

i, j,t

 = ƒSEVi, j,t, Di for all i, j [A 1] 

where

A*

i,j,t is the desired fractional allocation of regeneration lands to MIC j in stratum i

in period t,

SEVi,j,t is the estimated soil expectation value of land allocated to MIC j in stratum 

i in period t, and 

Di is a set of measures of the characteristics of the stratum that relate to the form 

and nature of the u’s and F as noted above.

Since the A*

i, j,t

 are fractions of the total regeneration area ∑jA*

i, j,t = 1.

It seems likely, however, that an array of limitations on owners will preclude their 

immediate achievement of the desired A* allocation, including lack of knowledge 

or expertise in some aspects of silviculture, restrictions on equipment or planting 

stock, and uncertainties about departing from past forms of management. As a 

consequence, we assume that in any given period owners adjust only partially from 

their MIC allocations of the previous period. That is:

∆ Ai, j,t = ρi A*

i, j,t - Ai, j,t-1 = ρi ƒSEVi, j,t

, Di - ρi Ai, j,t-1 [A 2]

where

∆ Ai, j,t is the observed or actual adjustment of the proportion of regeneration land 

allocated to MIC j between t-1 and t,

ρi is a partial adjustment coefficient (0 < ρi < 1), and

Ai, j,t is last period’s allocation.

Because the sum of the Ai, j,t and Ai, j,t-1 over the MICs (j’s) is 1, the ∑jAi, j,t = 0.

In the application of this model to the South, we were able to develop estimates 

of the parameters ρi by means of data on intended allocations of regeneration area 

from past studies and subsequent surveys of Southern private owners. Conducted 

to provide estimates for the fixed allocation approach used in previous assessments, 

the surveys (weighted by area to give regionwide averages) indicate the intended 

allocation of new regeneration land to each of the MICs used in ATLAS. The first 

regionwide study was conducted for the South in the early 1980s (USDA FS 1988). 

Those results were later modified for use in ATLAS in the late 1980s and early 

1990s (Haynes 1990; Haynes et al. 1995; Mills 1988, 1993). They are used here to 

represent management intentions in about 1995. Surveys targeting managers and 

Southern state foresters were conducted in the late 1990s and used to represent 

intentions in 2000 (AF&PA 1999; Moffat et al. 1998a; Siry 1998, 2002). 
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GENERAL TECHNICAL REPORT PNW-GTR-699

These surveys give data for the Ai, j,tand Ai, j,t-1, where t = 2000 and t-1 = 1995 

and comprise a panel with two time observations across a large number of strata 

(regions, owners, sites, and forest types). We computed SEVs for each MIC by stratum as of 2000 by using costs as estimated for that year and prices as projected in 

the 2000 RPA timber assessment (Haynes 2003). As there is a wide range of SEVs 

depending on site and type, we replaced the raw SEV values with the SEV rankings (1, 2, 3, etc.). And as most of the attributes that would compose the set Di

 are 

unobservable, we use a set of region, owner, site, and type dummies as surrogates. 

The function ƒ(.) in [A 2] was assumed to be linear. The equation to be estimated 

thus becomes:

∆ Ai, j,t = ρi φ0 + φ1 SEVRANKi, j,t + φ2 Di - ρi Ai, j,t-1 [A 3]

Regression results for the Southern model used in this 2005 update are given 

in the following table. Because both timber prices and costs are largely out of the 

control of individual owners, we take them as exogenous. Ordinary least squares 

(OLS) was the estimation method. Standard errors are in parentheses below the 

coefficients. After some experimentation with specification, the model was modified to allow separate SEVRANK coefficients for both owner (FI = forest industry, 

OP = NIPF) and forest type (PP = planted pine, OT = all other types) and separate 

coefficients for the lagged allocation term for industry and NIPF owners.

Estimates of coefficients for equation [A 3] in linear form

SEVRANK Lagged

Intercept ( ρi φ1) allocation (-ρi

) Region Type Site

0.5402 -0.0416 FI_PP -0.4504 FI -0.0304 -0.0052 0.0057

(.1804) (.0052) (.0871) (.0206) (.0137) (.0119)

-.0775 FI_OT -.8093 OP

(.0145) (.0716)

-.0444

OP_PP

 (.0082)

 -.0503 

OP_OT

 (.0182)

Adjusted R2 = 0.482; observations = 264.

Estimates of the ρi are the negatives of the lagged allocation coefficients. Both 

are within the expected range and both are highly significant. Based on the relative 

sizes of the adjustment coefficients, NIPF owners appear to adjust more rapidly 

to SEV changes than does industry. The SEVRANK coefficients are also highly 
209

The 2005 RPA Timber Assessment Update

significant with a large difference only for the “industry-other types” case. These 

coefficients have negative signs because the SEVRANK variable starts at 1 for 

the highest SEV and increases for lower rankings. None of the region, type, or 

site dummies are significantly different from zero.

For the Pacific Northwest West (PNWW) region, comparable historical data 

on owner allocation intentions were not available, so empirical estimation of the 

adjustment coefficients in [A 3] was not possible. In this case, we continued to 

employ the partial adjustment model form but set the adjustment coefficients 

based on judgment. Because we can not estimate the φ1, the desired allocation was 

assumed to be 100 percent to the MIC with highest SEV (i.e., one of the A*

i, j,t is 1 

and all others are 0). In the final base case projections, ρi was set at 0.5 for all 

owners, types, and sites.

In both the South and PNWW forms, the MIC allocations are based on an 

initial set of timber price expectations. Each period in the projection the SEVs 

and SEVRANKs are recomputed by using these price expectations, costs, and the 

previous period’s allocations. At the end of the simulation, the projected prices will 

very likely differ from the expectations used in the SEV computations. We believe 

that it is reasonable to assume, however, that owners know at least as much about 

future timber markets as the projection model (their expectations are rational). Thus 

we use the new price projections as the price expectations in a second iteration of 

the simulation. We continue this iteration process until the prices used as expectations in the last iteration differ by only a small amount from those projected in the 

current iteration. In this way, choices of MIC allocations in the simulations are 

sensitive to both current and projected prices.

Projecting the Unavailable Class of Timberland

Surveys of land managers and state foresters in the South (AF&PA 1999; Moffat 

et al. 1998a, 1998b; Siry 1998, 2002) indicated the fifth RPA timber assessment 

should recognize some timberland to be explicitly set aside from harvest. This class 

of timberland would represent more recent trends in the attitudes and behavior of 

landowners; the land would remain in the timberland inventory but not be harvested 

or actively managed. This was named the “unavailable class.” The timber resource 

itself was accounted for and growth was projected, but no further active management or harvest occurred on timberland in this class. 

There has been confusion surrounding this representation of timberland. Part 

of it stems from how timberland is defined, and part from the way availability is 

expressed in the TAMM and land AREACHANGE models. The formal definition 
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GENERAL TECHNICAL REPORT PNW-GTR-699

of timberland states it meets a minimum forest productivity requirement and is land 

not withdrawn or reserved from timber production by administrative statute, such 

as formally declared wilderness or national park lands. These reserved lands are 

not formally considered timberland and not included in our projections. Our use of 

the term “unavailable” is for land that meets timberland classification but is simply 

withheld from harvest owing to a variety of factors. Working groups indicated the 

reasons for this class include local rules and regulations that are perhaps tied to 

environmental or ecological considerations, operability constraints making harvest 

too expensive, or simply owner preferences.

 In TAMM there is a built-in assumption that at any given time there is a 

proportion of mature timber not available for harvest. Based on historical data of 

inventory and harvest, a set of cut-to-inventory ratios is incorporated into timber 

supply functions for forest industry and nonindustrial private owners, and this links 

the availability of timber to the behavior of market forces, namely prices. 

The land AREACHANGE models are also developed around historical data. 

These models project the movement of timberland to other uses while simultaneously projecting the movement of land (mostly from agriculture) to timberland. 

Data from successive forest inventory and analysis (FIA) inventories is most often 

used to predict the behavior of forest owners over time as they face various markets 

for wood and agricultural products. These land movements are typically between 

forests and agriculture, although a certain amount of forest is permanently lost to 

development. Another movement of forest is between cover types. These movements occur owing to changing species composition from natural succession or 

owner management activities (e.g., hardwood forest types to pine plantations). 

The survey responses indicated that historical information might not reflect 

what owners see as the coming trends. Forest industry owners thought that in 

addition to operational constraints, a portion of their lands would be set aside in the 

future for habitat conservation or other environmental reasons. State foresters were 

seeing a trend where nonindustrial private owners were purchasing and managing 

timberland with objectives that did not include timber harvest, and this was happening at higher rates than in the past. Timber harvest might not be permanently 

eliminated from these lands, but urban encroachment and population pressure 

would add weight to wildlife, ecological, and aesthetic objectives that may exclude 

or minimize harvesting. 

Because of the way the surveys were designed, industrial land managers and 

state foresters responded differently in their assessment of the amount of land that 
211

The 2005 RPA Timber Assessment Update

would be available for timber production, both now and in the future. The industry 

response was specific in terms of the number of acres by forest type and site for 

successive rotations, whereas the state foresters responded in terms of percentage of 

area by forest type by decadal points in time (2000, 2010, and 2020). 

To allocate area to the unavailable class, timberland was pooled by ownership, forest type, site class, and age from which all acres were equally likely to 

be assigned to any of the associated management classes. This approach was 

used because the FIA forest inventory does not classify timberland plots by using 

variables that might be directly associated with actual timber availability. One 

might try examining plot variables to help make the availability classification; 

for example, one could make the case that it would be unlikely for a 15-year-old 

recently thinned planted pine plot to be assigned to the unavailable class. But the 

thinning data does not tell us if the action was for timber production or other goals 

such as habitat enhancement. Although surveys did indicate that some planted pine 

would be unavailable for future harvest, it never made up more than a few percent 

of all the unavailable acres. But neither the surveys nor the data could tell us which 

stands those would be. 

The unavailable class was managed by using a custodial approach; the growth 

and yield parameters from the owner’s lowest management class. Stands were 

grown forward with no harvesting allowed, and none of the inventory was recognized by TAMM as part of the “available” fiber supply. The growth and standing 

volume were added back to the rest of the timberland inventory for reporting 

purposes. 

When considering the South as a whole, the initial unavailable area and volume 

on private land was significant. In 1995, 12.3 million acres and 17 billion cubic 

feet of inventory were classified as unavailable. This is just about 8 percent of the 

private timberland area and 9 percent of the associated volume. About 71 percent of 

both the unavailable area and volume were in forest types predominated by hardwood tree species. Additions to the unavailable class were made as the projection 

progressed, by 2020 the area and volume reached 11 and 14 percent of the total, and 

by 2050 additions of area had slowed while the volume increased at a faster rate 

owing to normal growth. The totals amounted to 16 and 23 percent, or 27.7 million 

acres supporting 59 billion cubic feet. Throughout the projection, roughly twothirds of the volume in the unavailable class was composed of hardwood species. 
212

GENERAL TECHNICAL REPORT PNW-GTR-699

Demand Regions

Pacific

Northwest

Pacific

Southwest

Canada

Rocky

Mountains

North

Central

Northeast

South

Southern

Rocky

Mountains

Northern

Rocky

Mountains

 Pacific

 Southwest

North

Central

Interior

Provinces Eastern

Provinces

South

Central

Southeast

Pacific Northwest East Northeast

Pacific Northwest West

British Columbia Coast

Supply Regions
Pacific Northwest Research Station

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Pacific Northwest Research Station

General Technical Report

PNW-GTR-699

March 2007

DEPAR TMENT OF AGRICULT URE