United States

Department of

Agriculture

Forest Service

Northeastern

Research Station

General Technical

Report NE-298

Forest Volume-to-Biomass Models

and Estimates of Mass for Live and

Standing Dead Trees of U.S. Forests

James E. Smith

Linda S. Heath

Jennifer C. Jenkins
Published by: For additional copies:

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Abstract

We present methods and equations for nationally consistent estimates of tree-mass

density at the stand level (Mg/ha) as predicted by growing-stock volumes reported

in USDA Forest Service surveys for forests of the conterminous United States.

Developed for use in FORCARB, a carbon budget model for U.S. forests, the

equations also are useful for converting stand-, plot-, and regional-level forest

merchantable volumes to estimates of total mass. Tree biomass is about 50 percent

carbon, so carbon estimates can be derived from estimates of biomass by

multiplying by 0.5. We include separate equations for live and standing dead trees.

Similarly, separate equations predict the components of aboveground only vs. full

trees (including coarse roots) and hardwood vs. softwood species. Equations are

developed for broad forest types by region and are applicable to large-scale forestinventory data. Example estimates are provided for regional tree-mass totals using

summary forest statistics for the United States.

The Authors

JAMES E. SMITH, jsmith11@fs.fed.us, and LINDA S. HEATH, lheath@fs.fed.us,

are research plant physiologist and research forester/project leader, respectively,

with the Northeastern Research Station at Durham, New Hampshire; JENNIFER C.

JENKINS, jjenkins@fs.fed.us, is a research forester with the Northeastern

Research Station at Burlington, Vermont.

Manuscript received for publication 19 April 2002
Forest Volume-to-Biomass Models and Estimates of Mass

for Live and Standing Dead Trees of U.S. Forests

James E. Smith, Linda S. Heath, and Jennifer C. Jenkins

Acknowledgments

We thank Richard Birdsey, Paul Van Deusen, Sarah Duke, Steve Prisley, and Harry Valentine

for helpful comments on drafts of this manuscript. Eric Fiegenbaum provided the cover artwork.

This work was partly supported by the USDA Forest Service’s Northern Global Change Program

and the RPA Assessment Management Group.

1 megagram (Mg) or metric tonne = 1,000 kg or 1 x 106 g

1 metric tonne = 1.102 U.S. ton, or 2,205 lb

1 megatonne (Mt) = 1 x 106

 tonne, or teragram (Tg) or 1 x 1012 g

1 gigatonne (Gt) = 1 x 109

 tonne, or petagram (Pg) or 1 x 1015 g

1 hectare (ha) = 2.471 acres, or 10,000 m2

1 cubic meter (m3) = 35.31 ft3

100 m3/ha = 1429 ft3/acre

100 Mg/ha = 44.6 U.S. tons/acre, or 89,200 lb/acre
1

Introduction

The potential for U.S. forests to sequester carbon dioxide

from the troposphere is well established. A large portion

of assimilated carbon accumulates as tree biomass. The

effect of this accumulation on atmospheric levels of

greenhouse gasses and the role of forests in this process

remain the subjects of national1

 and international research

discussions (Watson and others 2000). Thus, the need for

a nationwide carbon budget of U.S. forests extends

beyond the current year’s carbon gains, losses, and net

inventory. Information needed for policy development

includes estimates of past trends and projected future

scenarios. The mass estimators presented in this report are

part of an effort to improve carbon budget estimates for

U.S. forests. The value of biomass equations for this effort

is based on the link between individual-tree and wholestand biomass estimates (Clutter and others 1983;

Parresol 1999), coupled with the assumption that mass of

wood is about 50 percent carbon (Birdsey 1992).

The few regional- to national-scale budgets of biomass or

carbon mass developed for the United States are based

largely on forest structure as described by previous

versions of the USDA Forest Service’s Forest Inventory

and Analysis Database (FIADB; Miles and others 2001)

developed by the Forest Inventory and Analysis (FIA)

program. Currently, the database contains only recent

data (within about the last 10 years), though extensive

statistically based continuous forest surveys date back to

about 1950. These surveys are designed to estimate the

amount of volume of growing stock, which is a phrase

describing merchantable trees. Data from the surveys also

have been used to estimate biomass or carbon. Cost and

others (1990) summarized FIA data into national

estimates of growing-stock biomass. Birdsey (1992)

derived volume-to-biomass ratios by comparing the

estimates of growing-stock biomass in Cost and others

(1990) to equivalent growing-stock volumes in Powell

and others (1993). Birdsey used these ratios to calculate

forest carbon budgets that later served as the basis for

FORCARB, a carbon budget model for U.S. forests

(Plantinga and Birdsey 1993; Heath and Birdsey 1993;

Birdsey and Heath 1995). Turner and others (1995)

published carbon estimates largely based on FIA data and

Birdsey’s (1992) values for carbon density. Schroeder and

others (1997) and Brown and others (1999) improved on

the volume-to-biomass relationship by recognizing that

volume-to-biomass ratios vary by tree size or, on an

aggregated scale, forest structure. They developed largescale biomass estimates for the Eastern United States

based on FIA data and generalized biomass expansion

factors for select eastern forest types. None of these

previous studies provided estimates of biomass of

standing dead trees, nor were the biomass estimates based

on equations that reflect the species composition of U.S.

forests.

Our objective was to develop equations for estimating the

mass (Mg/ha) of live and standing dead trees as predicted

by FIA growing-stock volume (m3

/ha) for forests of the

48 conterminous States. Thus, values calculated by the

FIA can readily serve as inputs to the regression-based

estimates. Although these equations were developed for

use with FIA volumes as applied in the Aggregated

TimberLand Assessment System (ATLAS) model (Mills

and Kincaid 1992), they also can be applied to statistics

for large regions and broad classifications of forest types

as presented in periodic national inventory compilations

(see Smith and others 2001, Powell and others 1993, and

Waddell and others 1989). Because the equations are

based on current FIA datasets at a vegetation-type scale,

they might be less precise for specific sites or for

inventories with growing-stock definitions that differ

from those of FIA. Similar cautions extend to applying

regional-scale historical data or long-term projections. We

used the equations to develop national-level estimates of

tree mass and compare them with those produced

following the methods of Birdsey (1992) and Brown and

others (1999).

These equations are part of a larger project to develop

estimates of forest carbon using FORCARB, which also

accounts for carbon in forest products (Heath and others

1996; Skog and Nicholson 1998). An understanding of

how the carbon budget numbers were obtained and how

alternate scenarios or interpretations of data affect results

is useful for policy development or negotiations.

FORCARB was used to produce projections for the 2001

U.S. Submission to the United Nations Framework

Convention on Climate Change on Land Use, Land Use

Change, and Forestry (U.S. State Dep. 2000), and most

recently to examine uncertainty in U.S. forest carbon

budgets (Smith and Heath 2000, 2001; Heath and Smith

2000). With such intended applications, our models are

fundamental, tractable, and transparent—with few

inputs, widely applicable, and obvious relationships

among the parts.

1

See U.S. Global Change Research Information Office

Internet site: http://www.gcrio.org/index.shtml (accessed

March 28, 2002).
2

Methods

The estimates of tree-mass density presented here and

incorporated in FORCARB are based on tree- and plotlevel data in the FIADB (Miles and others 2001) and the

individual-tree biomass equations of Jenkins and others

(in press). Estimates are formed in two steps: (1)

summaries of tree mass are developed at the FIA plot

level, and (2) regressions are developed to estimate plotlevel tree mass as functions of growing-stock volume. The

individual-tree biomass equations are applied to

determine mass for each tree recorded on an FIA

inventory plot. Tree mass and merchantable volume of

growing stock are summed for each plot and expressed as

densities (Mg/ha and m3

/ha for mass and volume,

respectively). The paired mass and volume densities are

then incorporated in regressions with growing-stock

volume as the independent variable.

Plot summary pairs and corresponding regression

equations are classified and sorted by various categories, a

requirement for their subsequent inclusion in

FORCARB. Region and forest type are the highest levels

of classification. The 48 conterminous states are divided

into 10 regions (Fig. 1), each of which includes six to

eight forest types. Relationships between classifications

used in ATLAS and FORCARB and those of the FIADB

are described in Table 1. Additional classifications include

live or standing dead trees; aboveground only or whole

trees (including coarse roots); and live softwood or

hardwood tree species.

A consequence of these classification schemes is a

proliferation in the number of estimators of tree-mass

density in FORCARB simulations. Use of the regression

estimates was an important consideration in developing

the procedures described in this report. We standardized

inputs (independent variable) to a single summary value

available for all FIADB plots, and limited the form of the

regression models to one for live trees and another for

standing dead trees.

Forest-Inventory Design and Data Description

Unlike the U.S. census, which uses complete enumeration

(every individual is counted), the FIA inventory design

relies on a sampling scheme to estimate growing-stock

volumes at a designated level of precision. Sampling is

conducted in different phases, allowing cost-efficient data

collection. In the past, these surveys were conducted

periodically by state, usually every 5 to 7 years in the

South and every 10 to 15 years in other regions. The data

used in this study are from the most recent summary for

each state (Table 2). Although FIA has adopted an

annualized inventory with three sampling phases, the

current data are from inventories of two phases based on

double-sampling for stratification (Schreuder and others

1993). In the first phase, sample points on aerial

photographs are interpreted and classified by land use and

type of vegetation or land cover on an area of known size.

These areas are taken from U.S. Bureau of Census reports

and other sources. Depending on the individual state,

additional classifications might include productivity,

estimated volume, or stand age. In the second phase, a

sample of points from the first phase is chosen for crews

to visit in the field. Until FIA recently adopted a national

plot design, many designs were used in the second phase

of past inventories. Detailed observations are made on

forest plots, particularly those that meet a productivity

standard and are labeled as timberland. The data from

Southeast (SE)

South Central (SC)

Northeast (NE)

Northern Lakes 

States (NLS) Northern Prairie

States (NPS)

Rocky Mountains, 

South (RMS)

Rocky Mountains, 

North (RMN)

Pacific 

Southwest (PSW)

Pacific Northwest, 

Westside (PWW)

Pacific Northwest, 

Eastside (PWE)

Figure 1.—Regions of the United States used in classifying forest types.
3

Table 1.—Forest types classified for mass estimates of trees in this report (based on the FIADB

forest-type groups)

Regiona Forest type FIADB forest-type group

NE Aspen-Birch Aspen-Birch

MBB/Other HW Oak-Gum-Cypress, Elm-Ash-Cottonwood, and

Maple-Beech-Birch

Oak-Hickory Oak-Hickory

Oak-Pine Oak-Pine

Other Pine Longleaf-Slash Pine, Loblolly-Shortleaf Pine, and

pines other than White-Red-Jack

Spruce-Fir Spruce-Fir and other non-pine conifers

WRJ-Pine White-Red-Jack Pine

Nonstocked Nonstocked

NLS Aspen-Birch Aspen-Birch

Lowland HW Oak-Gum-Cypress and Elm-Ash-Cottonwood

MBB Maple-Beech-Birch

Oak-Hickory Oak-Hickory

Pine All pine groups and Oak-Pine

Spruce-Fir Spruce-Fir

Nonstocked Nonstocked

NPS Conifer All conifer groups

Lowland HW Oak-Gum-Cypress, Elm-Ash-Cottonwood, and

Aspen-Birch

MBB Maple-Beech-Birch

Oak-Hickory Oak-Hickory

Oak-Pine Oak-Pine

Nonstocked Nonstocked

SC, SE Bottomland HW Oak-Gum-Cypress, Elm-Ash-Cottonwood, and

Aspen-Birch

Natural Pine Longleaf-Slash Pine and Loblolly-Shortleaf Pine,

naturally occurring

Oak-Pine Oak-Pine

Other Conifer Other conifer groups

Planted Pine Longleaf-Slash Pine and Loblolly-Shortleaf Pine, planted

Upland HW Oak-Hickory and Maple-Beech-Birch

Nonstocked Nonstocked

PSW Douglas-fir Douglas-fir and Hemlock-Sitka Spruce

Fir-Spruce Fir-Spruce-Mountain Hemlock

Hardwoods Hardwoods

Other Conifer Ponderosa Pine, Lodgepole Pine, and other conifer groups

Pinyon-Juniper Pinyon-Juniper

Redwood Redwood

Nonstocked Nonstocked

PWE Douglas-fir Douglas-fir, Western Larch, and Redwood

Fir-Spruce Fir-Spruce-Mountain Hemlock and Hemlock-Sitka Spruce

Hardwoods Hardwoods

Lodgepole Pine Lodgepole Pine

Ponderosa Pine Ponderosa Pine and Western White Pine

Pinyon-Juniper Pinyon-Juniper

Continued
4

2

U.S. Department of Agriculture, Forest Service. 2001.

Forest inventory and analysis national core field guide,

volume 1: field data collection procedures for phase 2

plots, version 1.5. Internal report on file at: U.S.

Department of Agriculture, Forest Service, Forest Inventory

and Analysis, 201 14th St., Washington, DC.

Nonstocked Nonstocked

PWW Douglas-fir Douglas-fir and Redwood

Fir-Spruce Fir-Spruce-Mountain Hemlock

Other Conifer Ponderosa Pine, Western White Pine, Lodgepole

Pine, and other conifer groups

Other Hardwoods Other hardwoods

Red Alder Alder-Maple

Western Hemlock Hemlock-Sitka Spruce

Nonstocked Nonstocked

RMN, RMS Douglas-fir Douglas-fir, Western White Pine, Hemlock-Sitka

Spruce, Western Larch, and Redwood

Fir-Spruce Fir-Spruce-Mountain Hemlock

Hardwoods Hardwoods

Lodgepole Pine Lodgepole Pine

Other Conifer Other conifer groups

Ponderosa Pine Ponderosa Pine

Pinyon-Juniper Pinyon-Juniper

Nonstocked Nonstocked

a

NE=Northeast; NLS=Northern Lake States; NPS=Northern Prairie States; SC=South Central; SE=Southeast;

PSW=Pacific Southwest; PWE=Pacific Northwest Eastside; PWW=Pacific Northwest Westside; RMN=Rocky

Mountains North; RMS=Rocky Mountains South.

Regiona Forest type FIADB forest-type group

Table 1.—continued.

both phases are used to determine the area that each

ground plot represents. Allowable tolerances are specified

for the measurements; for example, diameters are

measured to the nearest 0.1 inch. The designated

maximum allowable sample error for area is 3 percent per

1 million acres of timberland. For more information, see

the documentation accompanying the FIADB (Miles and

others 2001) and the “Forest Inventory and Analysis

National Core Field Guide.”2

In this section we describe how we used the FIADB to

estimate plot-level tree-mass density based on generalized

individual-tree biomass equations, and subsequently to

develop regression-based estimates of mean tree-mass

density. We first describe our interest in selected variables

and our rationale for organizing the data into separate

forest groups. Where useful, we provide specific variable

names as found in the FIADB as of March 2002, for

example, STDAGE (stand age). FIA data are collected in

English units; we converted them to metric units.

For our purposes, the FIADB includes data at two levels

of organization: FIA inventory plot and individual tree.

Plot information includes location (state and county),

landowner classification, current forest type, stand origin

(plantation or natural regeneration), site productivity

classification, estimated stand age, current and past landuse classification, area (in acres) that each plot represents,

and years between remeasurements. Individual-tree

information — for all trees larger than 1 inch in diameter

at breast height (d.b.h.) — includes species, diameter,

status (live or dead), whether growing stock or cull,

growing-stock volume if applicable, and number per acre

represented by each individual. Plot volumes are

calculated by summing individual-tree growing-stock

volumes on the plot and expressed as volume per unit area

(m3

/ha).

We classify forests according to region and forest type

with a goal to gain added flexibility in applying results.

We wanted forest groupings consistent with: (1)

classifications used in the FIADB, (2) timber units used

in ATLAS (Mills and Kincaid 1992; Haynes and others
5

1995), (3) forest-type groups listed in Forest Service

statistical reports, for example, Smith and others (2001),

and (4) other components of FORCARB. The variables

for state (STATECD) and FIA inventory unit (UNITCD) are

used to define the 10 regions (Fig. 1). Forest types

(FORTYPCD) are grouped to reflect species composition and

other aspects of stand structure that influence overall

biomass. The principal goals in grouping forest types for

this analysis were to maintain a small set of types to

represent each region and conform to types used in

ATLAS’ timber projections.

We considered additional forest groupings by ownership

(OWNCD or OWNGRPCD) and productivity (SITECLCD).

Decisions about whether to include such additional

classifications were based on preliminary analyses of the

data rather than required links to other models as with

region and forest type. Preliminary analysis of covariance

identified some forest types as showing an effect of

ownership on the relationship between volume of

growing stock and tree-mass density. These ownerships

are classified as “public” or “private” lands and included

in the classification scheme described in Table 1. Analyses

also revealed slight interactions between productivity and

the initial slope of this same biomass-to-volume

relationship. However, this effect was inconsistent across

forest types of the two areas where productivity is an

important variable in simulation models—the South and

the Pacific Northwest. Thus, no estimates in this report

are classified by productivity.

Some older inventories identified and measured only live

or merchantable dead (salvageable) trees on new plots;

that is, all standing dead trees were not necessarily

included in the initial survey for a plot. To avoid plots

where standing dead trees might be underrepresented, we

used only remeasured plots (KINDCD=2) or recently

completed surveys, which were more likely to include

standing dead trees. Current surveys include the

identification and measurement of all trees. We used all

measured plots (KINDCD=1 through 3) on surveys since

1999.

Estimating Mass for Individual Trees

Mass estimates are provided for individual trees (DRYBIOT)

in the FIADB. However, we applied the nationally

consistent set of individual-tree biomass estimates of

Jenkins and others (in press) because FIA biomass

estimates may differ considerably by FIA unit. We also

wanted to extend mass estimates to standing dead trees

and coarse tree roots. The 10 equations are designed to

estimate all tree species in U.S. forests: five softwood

species groups, four hardwood species groups, and one

group for woodland species. These equations estimate

Table 2.—Most recent statewide forest inventories

included in FIADB and used in this analysis

State Date of inventory

Alabama 2000

Arizona 1999

Arkansas 1995

California 1994

Colorado 1983

Connecticut 1998

Delaware 1999

Florida 1995

Georgia 1997

Idaho 1991

Illinois 1998

Indiana 1998

Iowa 1999

Kansas 1994

Kentucky 1988

Louisiana 1991

Maine 1995

Maryland 1999

Massachusetts 1998

Michigan 1993

Minnesota 1990

Mississippi 1994

Missouri 1999

Montana 1989

Nebraska 1994

Nevada 1989

New Hampshire 1997

New Jersey 1999

New Mexico 1999

New York 1993

North Carolina 1990

North Dakota 1995

Ohio 1993

Oklahoma 1993

Oregon 1995

Pennsylvania 1989

Rhode Island 1998

South Carolina 1999

South Dakota 1995

Tennessee 1999

Texas 1992

Utah 1995

Vermont 1997

Virginia 1992

Washington 1991

West Virginia 1989

Wisconsin 1996

Wyoming 1984
6

total aboveground (that is, above the root collar) biomass

for trees of 1 inch or larger in d.b.h. Additional equations

are provided for estimating the ratio of components to

total aboveground biomass. The component equations are

for foliage, coarse roots, stem bark, and stem wood.

Live trees

Live trees are identified as STATUSCD=1. Once identified as

a live tree larger than 1 inch d.b.h. in an FIA plot, the

only variables needed to estimate individual-tree mass are

diameter (DIA) and species (SPCD). The value of DIA usually

is measured at breast height except for woodland species,

which generally are measured at the root collar. The

individual-tree biomass equations provide estimates of the

mass (kg) of individual live trees.

Mass per unit area is then determined by multiplying by the

number of trees per acre (TPACURR). Mass is summed across

all trees per plot and the sum is converted to metric units.

The mass density of live trees at the plot level is expressed as

Mg/ha. Growing-stock volume as estimated per tree by FIA

(VOLCFNET where TREECLCD=2) also is summed for each

plot and expressed as m3

/ha. The paired values (volume,

mass density) from each FIA plot were the source of the

observations used in the regressions we developed. The same

process of estimating volume-density and mass-density pairs

per FIA plot can be repeated for both aboveground and

total-tree estimates. Similarly, hardwood-only or softwoodonly estimates are developed with mass and volume pairs

representing only the hardwood or softwood portion of

the live trees on a plot.

Standing dead trees

Trees identified in the FIADB as STATUSCD=2 are standing

dead trees. For the same diameter, these are likely to have

less mass than live trees, which were the basis for the

individual-tree biomass equations. We adjust tree mass to

reflect an expected difference between live and dead trees

of the same d.b.h. by reducing the mass of some parts of

dead trees. We do not have specific information on mass

of standing dead trees, which can encompass a wide range

of structural damage and decay, so we use the component

equations of Jenkins and others (in press) to reduce the

mass of standing dead relative to live by the following

amounts: 10 percent of stem wood and bark; 100 percent

of leaves; 33 percent of branches; and 20 percent of coarse

roots. Separate component equations are for hardwood

and softwood species and are based on d.b.h. The net

effect of the component reductions is illustrated in Figure

2 by the ratios of standing dead to live mass according to

d.b.h. and species group (softwood or hardwood).

Adjusting for cull trees

The biomass of cull trees (TREECLCD=3 or 4) is likely to

differ from that of trees of similar diameter classified as

growing stock (TREECLCD=2). The biomass of live cull

trees represents more than 10 percent of live-tree biomass

in the East (estimated from FIADB). Cull status is

assigned to a tree if it is a nonmerchantable species or if a

significant portion of the bole of a merchantable species is

unusable as timber. Cull status suggests that diameter-tobiomass relationships likely differ from those of the

individual-tree biomass equations. We did not have

specific estimates of biomass for cull trees, so we

developed generalized adjustments to the individual-tree

biomass equations by examining the apparent effect of

cull classification on volume; that is, we developed ratios

for estimating the woody mass of cull trees that were

proportional to ratios of cull volumes to growing-stock

volumes.

Biomass correction factors for cull trees are based on

analysis of the Eastwide and Westwide inventory

D.b.h. (cm)

0 50 100 150 200

Standing Dead :

Live Tree Mass

0.76

0.78

0.80

0.82

0.84

0.86

0.88

0.90

Hardwood Species

Softwood Species

Figure 2.—Ratios of standing dead mass to live tree mass for individual

trees, by d.b.h. and classification as softwood or hardwood.
7

databases (Hansen and others 1992; Woudenberg and

Farrenkopf 1995), which provided the format for FIA

inventory data prior to the FIADB. Cull trees are

distributed across similar diameter ranges as growingstock trees with proportionally more rough cull at smaller

diameters. We focused on trees less than 40 cm d.b.h.

because most trees are in this size range. The ratio of

volume for cull to volume for growing stock changed

slightly with diameter, but we used average ratios over the

range of 25 to 40 cm. We plotted values for the net

volume of wood in the central stem (the variable NETCFVL

in the Eastwide and Westwide databases) as functions of

d.b.h. for growing stock, rough cull, and rotten cull for

the broad classifications of hardwood vs. softwood, and

for the Eastern vs. Western United States. Volumes of cull

trees are consistently less than those for growing stock.

The tree classification rough cull (TREECLCD=3) can be

based on form defect or identity as a noncommercial

species. No adjustments were made in applying the

individual-tree biomass equations to rough cull of

noncommercial species. We did adjust mass for such trees

where the classification was based on form defect. The

adjustment was based on the assumption that defect may

reduce the volume of rough cull proportionally more than

biomass. The ratio of volume for rough cull to volume for

growing stock obtained from FIA tree data was 0.74 and

0.64 for hardwoods and softwoods in the East,

respectively. The ratio of volume for rough-cull trees to

volume for growing stock was 0.64 and 0.42 for

hardwoods and softwoods in the West. We assumed that

25 percent of the volume reduction of cull trees (that is,

compared to volume for regular growing stock) reduced

the biomass of the tree, and adjusted the estimated

biomass for the cull trees by this factor. For example, in

the East, volume was 26 percent lower for rough-cull

hardwoods relative to growing-stock volume. We apply

25 percent of this reduction (0.26 x 0.25 = 0.06) to the

mass of a cull tree by reducing the estimated mass of a

noncull live tree by 6 percent. The net effect of these

assumptions was reductions in bole mass of 6 and 9

percent for hardwoods and softwoods in the East,

respectively, and of 9 and 14 percent for hardwoods and

softwoods in the West.

The tree classification of rotten cull (TREECLCD=4) is based

on threshold levels of rot in bole wood. We adjusted mass

for rotten cull by applying assumptions about the extent

of rot to ratios of volume in rotten culls to volume in

growing stock. This was similar to the way in which we

adjusted mass for rough cull. The ratio of volume for

rotten-cull trees to volume for growing stock obtained

from FIA tree data was 0.42 and 0.30 for hardwoods and

softwoods in the East, respectively, and 0.40 and 0.22 for

hardwoods and softwoods in the West. We assumed that

more than 50 percent of the volume reduction had some

degree of rot. Of this volume reduction, we assumed 75

percent was rotten wood that was assumed to have lost 45

percent of its mass, or specific gravity, depending on the

state of decay (Heath and Chojnacky 2001). Multiplying

these factors produced an adjustment factor for the

estimated biomass for rotten-cull trees. For example,

volume was 58 percent lower for rotten-cull hardwoods in

the East (relative to volume of growing stock). If 75

percent of this volume was missing 45 percent of its intact

mass, overall bole-wood mass was reduced by 20 percent

(0.58 x 0.75 x 0.45 = 0.20). Total-tree mass was adjusted

by reducing wood mass by 20 percent. The net effect of

these assumptions was reductions in bole-wood mass of

20 and 24 percent for hardwoods and softwoods in the

East, respectively, and 20 and 26 percent for hardwoods

and softwoods in the West.

To summarize, adjusting the tree mass estimates from the

individual-tree biomass equations to account for cull-tree

mass depends on our assumptions. The assumptions that

likely had the greatest effect were that: 1) cull trees have a

lower bole mass than a tree of the same diameter, and 2)

differences in volume between rotten cull and growing

stock were represented by woody mass that was 75

percent rotten. The low precision in values subtracted

from bole mass reflects the level of information available.

However, these differences in individual-tree mass have

little impact on total-tree biomass at regional and national

level summaries because they represent only several

percent of density of the mass of all trees.

Equations for Estimating Density of

Forest-Tree Mass

Applying the individual-tree biomass equations to FIA

trees and summarizing to the plot produces paired values

of growing-stock volume density (m3

/ha) and tree-mass

density (Mg/ha) on each plot. After sorting the plot-level

summary data according to region and forest

classification, we developed regression-based estimates of

mass density as predicted by growing-stock volume. Stand

age was considered as a candidate predictor variable for

regression. However, the poor relationship shown in

Figure 3 for some northeastern hardwoods is typical of

many forest types. Thus, stand age was dropped from

consideration.

As mentioned earlier, preliminary regression analyses were

performed to help establish a classification scheme for

forest types. Second-order polynomial regressions were

useful in classifying forest types, particularly in

identifying effects of ownership and productivity. The

polynomial model worked initially because we were

interested only in the initial slope of the relationship. We
8

restricted analyses to points below the 75th percentile of

growing-stock volumes. Analyses of covariance with the

second-order polynomial model and ownership or

productivity as the class variable identified the

importance of ownership for some forest types (Table 1).

However, the sign and the magnitude of the quadratic

effect coefficient often produced unrealistic estimates

relative to other important assumptions about the volume

and biomass relationship. Thus, this regression form was

not useful for further development of stand-level

estimates, so we adopted a different equation form for the

analyses.

Live trees

Several candidate linear and nonlinear models were

considered for the regression estimates of live-tree mass

density. A form of the Chapman-Richards growth

equation (Clutter and others 1983) was selected primarily

because of its flexibility in the shape of the initial portion

of the curve and the continuous decrease in slope at

greater volumes. Although this relationship usually

describes net growth (for example, of populations), it was

suitable for our purpose. We added an intercept term

because the usual form of the Chapman-Richards

equation is forced through the origin, but tree biomass is

expected to remain greater than zero as growing-stock

volume approaches zero. The addition of the intercept

meant that four coefficients were estimated. Nonlinear

regression (Proc NLIN in SAS) was used to determine

values for these coefficients. Estimates of regression

coefficients showed that the coefficient determining the

shape of the initial portion of the curve was unimportant.

Thus, the regression was changed to essentially an

exponential model with a non-zero intercept, and mean

mass density of live trees is estimated by:

Live-tree mass density = F · (G + (1-e(-volume/H)))

where volume is in m3

/ha and coefficients F, G, and H are

estimated using nonlinear regression. Because some fixedradius FIA plots are assigned to more than one condition

class (CONDID), the number of trees per area represented

by each tree can vary within a plot. Thus, the proportion

of plot in each condition (CONDPROP) is used as a

weighting variable in the regressions.

In addition to estimates of total (hardwood plus

softwood) tree mass, we develop separate estimates for

live-tree mass of hardwood and softwood species within

each forest type based on their respective growing stock.

We estimate absolute mass density of hardwoods and

NE, MBB/Other HW

Stand Age (years)

0 50 100 150

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

500

Growing Stock Volume (m3/ha)

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

500

Mixed age

or unknown

Figure 3.—Mean live-tree mass density per FIA plot as function of stand age

(upper graph) and growing-stock volume (lower graph) for NE MBB/Other HW

forests. The same set of FIA inventory plots contributed to each graph. However,

23 percent of points were classified as mixed or unknown age in the upper graph.
9

softwoods rather than model hardwoods and softwoods as

a percentage of total mass. We chose this method over

modeling percentages to avoid regressions with skewed

data, as would be expected with high or low percentages.

A disadvantage of estimating components with separate

independent and dependent variables is that individual

predictions of hardwood and softwood mass may not sum

to total mass, which is estimated separately.

Standing dead trees

Mean mass density of standing dead trees is estimated by

fitting nonlinear regressions to the FIA plot-level ratio of

the mass of standing dead to predicted live-tree mass (Fig.

4). A three-parameter Weibull function is used to model

this ratio, which generally decreases with increasing live

growing stock-volume. Regression procedures and

weighting are the same as for estimating live mass. The

basic form of the equation is:

Dead-tree mass density =

(Estimated live-tree mass density) · A · e(-((volume/B)^C))

where live-tree mass density is in Mg/ha, volume is in m3/

ha, and coefficients A, B, and C are estimated using

nonlinear regression.

Applying the estimates

Interest in biomass and carbon mass often focuses on

specific subsets of the entire forest system (Birdsey 1992;

Watson and others 2000). Hence, we developed estimates

of specific subsets of total-tree mass. This approach was

extended to provide estimates for both the entire tree —

including coarse roots — and the aboveground portion

only. Similarly, hardwood or softwood live-tree mass

density can be estimated separately from hardwood or

softwood growing-stock volume. Carbon mass or carbon

dioxide equivalents often are the quantities of interest

where tree-mass estimates extend beyond converting from

merchantable-wood volumes. Carbon mass is about 50

percent of wood dry weight; more precise values for

carbon content depend on the identity of the species and

tissue or part of the tree.

Several units are used in reporting estimates of forest

carbon, so the results can be confusing. The use of metric

units internationally but English units in the United

States has resulted in hybrid measures, for example,

metric tons/acre. For clarity, values taken from the

FIADB are in the original units, for example, inches for

d.b.h. Our analysis was conducted in metric units so our

results generally are expressed in those units. International

discussions of greenhouse gas inventories (Watson and

others 2000) in which the United States has participated

for many years report carbon mass in tonnes (t) and

megagrams (Mg), which are identical values (also defined

as 103

 kg and 106 g, respectively). Larger aggregate values

of mass are reported as teragrams (1012 g) and petagrams

(1015 g). Area is in hectares (10,000 m2

).

Results and Discussion

Model Parameters

Coefficients for estimating mean tree-mass densities are

provided in Tables 3 through 10 (pages 12-31) by stand

component, region, and forest type. In the Appendix,

examples from Tables 3 and 4 are illustrated in Figures 5

through 62. The mass of live and dead trees can be

estimated for the full tree (including coarse roots) or

aboveground only. All the forest types listed in Table 1 are

represented in Tables 3-10. However, some sets of

coefficients are not based on type-specific regressions.

Estimates for the Nonstocked and Pinyon/Juniper forest

types are simply means from the FIA plots. Pinyon/

Juniper averages are based on all FIA plots of that type

across the West. Type-specific regression estimates were

not possible for several forest types. For example,

nonlinear procedures failed to fit coefficients for

hardwood tree mass in a publicly owned lodgepole pine

forest in the Pacific Northwest Eastside (PWE) region.

We substituted regression-based estimates of hardwood

components in all softwood forests of PWE. See table

footnotes for cases in which regional summary values

were substituted for type-specific regression equations.

Estimates of some components of forest-tree mass are

based on regressing over data points that tend to be

grouped near the origin. For example, this occurs in

hardwood species of western pine forests or softwoods in

northern hardwood forests. In such cases, the regressions

are applicable over a limited range of growing-stock

volumes. For this reason, the tables of coefficients also

provide an indication of the upper end of the range of

growing stock volume that contributed to the coefficient

estimates. We also provide the mean square error of the

regression models and the number of FIA plot summaries

that contributed to each regression.

The use of remeasured FIA plots and the substitution of

estimates from other forest types when necessary can

affect estimates of mass density. This effect is most likely

for mass density of standing dead trees because fewer

regressions for standing dead trees successfully estimated

parameters without pooling forest types within a region.

The effect of these assumptions in our model will be a

major part of any difference between our estimates and

the direct application of the individual-tree biomass

equations of Jenkins and others (in press) to FIADB tree

data. However, dead mass is a small part of overall tree
10

mass, as illustrated in Figure 4 and Appendix Figures 5

through 62.

Comparing Alternate Estimates

of Total-Tree Biomass

We maintained many separate and distinct forest types

when developing our estimates. This is possible largely

because of the set of individual-tree biomass equations.

Both species composition and other characteristics of

stand structure, such as tree size and stem density, can

affect tree-mass density. The equations in Tables 3-10 are

based on linked datasets and regression models, so they

can be updated easily as the FIADB is updated. We

structured our classifications to conform to commonly

used forest types and regions such as are used in timber

projection models. A key point was maintaining

flexibility for application back to historical data and

forward to forest projections.

We compared estimates of average biomass density among

four relatively separate sets of estimates (Table 11, page

32). All forest types were classified as hardwood or

softwood to facilitate comparison; Nonstocked and

Pinyon/Juniper types were excluded from this summary.

These values are described as average tree-mass density

because total biomass was estimated for large areas by

forest type and then divided by the total area. Estimates

were developed from: 1) our analysis, 2) the biomass

information included as part of the FIADB, 3) summaries

developed by Birdsey (1992), and 4) the biomass

expansion factors developed by Brown and others (1997,

1999).

Consistent sets of results were developed for making the

comparisons in Table 11. All sets were based on the same

dataset of plot and tree information extracted from the

FIADB in March 2002. Estimates were for live trees,

aboveground only; all live trees at least 1 inch d.b.h. were

included. Estimates taken directly from the FIADB were

based on the variable DRYBIOT. The estimates from Birdsey

(1992) were derived by applying information in Tables

1.1 and 1.2 to plot-level summaries of hardwood and

softwood growing-stock volume by forest type and

region. Similarly, the estimates of Brown and others

(1999) were by applying the three biomass expansion

factors to plot-level summaries of growing-stock volume

by forest type. Estimates of Birdsey (1992) and Brown

and others (1999) were calibrated with some reference to

Eastwide or Westwide data at different times. The same is

true of preliminary analysis of our estimates.

There were similarities between our method and that of

Schroeder and others (1997) and Brown and others

(1999). Both included constraints on the regression line

at greater volumes; that is, both featured asymptotic limits

to increasing biomass at large growing-stock volumes.

Additionally, both were based on a regression of estimated

biomass on growing stock-volume. However, the

regression models were slightly different. We estimate

0 100 200 300 400 500 600

Standing Dead :

Live Tree Mass

0

1

2

3

4

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500 600

Mass (Mg/ha)

0

100

200

300

Figure 4.—Estimates of the ratio of the mass of standing dead tree to predicted

live-tree mass (upper graph) and estimate of standing dead tree mass (lower

graph) for RMS Fir-Spruce forests (individual points are plot-level density

summaries).
11

mass density directly from growing-stock volume.

Schroeder and others (1997) and Brown and others

(1999) included an additional step of calculating a

biomass expansion factor; we believe that step is useful

only when comparing ratios. The biomass expansion

factors also were undefined at zero volume, while the

direct relationship of volume to mass density provided an

estimate of mass at zero volume. Finally, we developed

equations for mass of live and dead trees for a number of

forest types in the United States; previous literature

focused on the live biomass of several eastern forest types.

Suitability of Equations and Spatial Scale

The estimates developed here are likely to be applied at a

range of spatial scales that sometimes differ greatly from

those of the FIA plots used as the bases for regressions.

For example, biomass predictions based on the full set of

FIA forest plots or plot-level RPA data (a component of

the 1997 RPA forest dataset; Smith and others 2001) are

at the same scale as the original regressions, so scaling is

not a likely source of systematic error. By contrast,

biomass predictions associated with the linked forest

models ATLAS and FORCARB are applied to volume of

growing stock aggregated over areas of tens to hundreds

of thousand hectares—one to two orders of magnitude

larger than the FIA plots used in developing the

regressions.

Applying these equations at a different scale might result

in systematic error (Rastetter and others 1992). Although

both independent and dependent variables are expressed

per unit area, the predictions are scale-dependent because

volume and biomass densities can be averaged over

different areas from one prediction to the next. For

example, aggregating FIA plot summary values to county,

unit, or state levels and then applying the equations may

produce average volume-mass density paired values on the

concave side of a regression fit to the FIA plot-scale

values. This could result in lower estimates of biomass for

many forest types. This form of bias is unlikely when

these predictors are applied to ATLAS/FORCARB

summary values because such aggregation in ATLAS is

systematic rather than random. Forest volumes and areas

are classified by age class prior to aggregation; thus,

samples are effectively stratified. Specific information on

aggregation of forest areas, for example, by ATLAS/

FORCARB, can offset this potential bias through: 1)

quantification of possible systematic error, and 2)

modification of regression to reflect specific levels of

aggregation. In fact, preliminary analyses indicate that

applying our equations at scales greater than plot level, for

example, UNIT or COUNTY, produces estimates that are

within 5 percent of the actual value. This effect is from

essentially random aggregation—any bias associated with

stratified aggregation is likely to be considerably less.

Thus, for most purposes, these equations can be applied

at more aggregated spatial scales with only negligible

error.

Continuing Research

The most immediate application of the estimates of treemass density is shown in Table 12 (page 33), which

includes mass totals obtained from applying estimates to

1997 RPA forest data (Smith and others 2001). Current

research is focused on extending these for more general

applicability and links to other models or forest

assessments. Carbon estimators based on alternate forest

classification schemes as well as estimates of uncertainty

in these values will be available in subsequent

publications. We also are considering alternate approaches

to modeling mass for standing dead trees. Specifically,

gaps in recording or expanding tree data for dead trees

need to be addressed – this likely would reduce bias for

under representing dead stems.
12

Table 3.—Coefficients for estimating mass density of live trees (above- and belowground, Mg/ha) by

type, region, and owner (as appropriate); F, G, and H are coefficients; n = number of FIA plots; mse =

mean squared error of the prediction relative to individual plots; volume limit (m3

/ha) = 99th percentile

of growing-stock volumes within each set of FIA plots (upper limit of independent variables in the

regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 508.5 0.0361 397.4 264 510 250

MBB/Other HW (Priv.) 425.3 0.0476 254.7 2302 936 273

MBB/Other HW (Publ.) 558.4 0.0276 374.7 362 1140 342

Oak-Hickory 488.2 0.0509 312.8 3314 1262 306

Oak-Pine 369.0 0.0490 245.5 304 656 268

Other Pine 715.5 0.0348 697.2 295 595 304

Spruce-Fir 306.4 0.0419 156.3 236 524 237

WRJ-Pine 415.6 0.0349 276.1 398 1056 354

Nonstocked 5.8 0.0000 0.0 14 19 10

NLS

Aspen-Birch 362.5 0.0524 270.1 8072 568 239

Lowland HW (Priv.) 505.2 0.0419 359.1 1322 858 223

Lowland HW (Publ.) 744.5 0.0229 555.0 662 570 281

MBB 350.0 0.0496 187.0 5871 1077 259

Oak-Hickory 364.8 0.0755 186.1 2049 1136 238

Pine 432.1 0.0346 373.2 2056 548 280

Spruce-Fir 391.9 0.0582 278.8 4926 647 217

Nonstocked 8.5 0.0000 0.0 83 466 119

NPS

Conifer 583.1 0.0482 577.4 256 569 236

Lowland HW 1192.0 0.0284 988.5 1030 1378 303

MBB 465.9 0.0725 321.6 1682 1223 252

Oak-Hickory 1012.1 0.0393 727.6 2516 1437 243

Oak-Pine 255.9 0.1240 157.6 172 1011 200

Nonstocked 22.9 0.0000 0.0 41 903 71

SC

Bottomland HW (Priv.) 314.5 0.1091 174.9 2092 1528 309

Bottomland HW (Publ.) 313.5 0.1022 147.9 295 1379 329

Natural Pine (Priv.) 358.3 0.0935 421.9 1620 811 321

Natural Pine (Publ.) 363.1 0.1133 480.0 448 838 373

Oak-Pine 282.3 0.0904 197.4 2000 922 265

Other Conifer 162.6 0.1869 85.5 72 792 208

Planted Pine 161.8 0.1398 116.1 1477 578 265

Upland HW (Priv.) 229.7 0.1533 112.2 3934 1399 204

Upland HW (Publ.) 285.9 0.0977 140.7 481 1094 252

Nonstocked 56.5 0.0000 0.0 19 2679 8

SE

Bottomland HW (Priv.) 963.2 0.0261 800.4 2516 2176 453

Bottomland HW (Publ.) 429.2 0.0573 291.6 334 2268 427

Natural Pine (Priv.) 356.4 0.0429 340.9 2892 541 382

Natural Pine (Publ.) 1213.0 0.0140 1610.1 662 689 357

Oak-Pine 420.1 0.0353 309.8 2307 660 347

Continued
13

Other Conifer 324.8 0.0233 201.1 145 1000 397

Planted Pine 226.4 0.0670 183.7 3865 413 267

Upland HW (Priv.) 417.4 0.0618 283.8 5071 1156 334

Upland HW (Publ.) 405.2 0.0915 260.0 779 1890 336

Nonstocked 56.5 0.0000 0.0 74 4515 214

PSW

Douglas-fir 2094.3 0.0164 2177.5 93 3605 1090

Fir-Spruce 897.3 0.0108 773.5 51 1445 1020

Hardwoods 1463.7 0.0000 1119.4 695 6812 639

Other Conifer 1323.8 0.0372 1480.6 795 2864 687

Pinyon-Juniper 58.0 0.0000 0.0 6335 2165 48

Redwood 4409.2 0.0124 6562.8 108 3639 1691

Nonstocked 35.7 0.0000 0.0 18 601 119

PWE

Douglas-fir (Priv.) 653.6 0.0168 572.1 226 719 488

Douglas-fir (Publ.) 3234.5 0.0000 3884.9 972 1564 636

Fir-Spruce (Priv.) 615.3 0.0129 561.6 95 870 496

Fir-Spruce (Publ.) 4480.5 0.0000 5880.2 1213 2512 761

Hardwoods 614.0 0.0534 660.4 46 2856 292

Lodgepole Pine (Priv.) 368.2 0.0195 390.1 65 289 325

Lodgepole Pine (Publ.) 692.3 0.0111 975.0 835 699 389

Ponderosa Pine (Priv.) 378.5 0.0178 330.0 262 425 336

Ponderosa Pine (Publ.) 1504.1 0.0058 2042.9 1939 331 402

Pinyon-Juniper 58.0 0.0000 0.0 6335 2165 48

Nonstocked 13.6 0.0000 0.0 49 357 293

PWW

Douglas-fir (Priv.) 1191.2 0.0187 1251.2 1032 1781 913

Douglas-fir (Publ.) 5062.8 0.0052 6830.2 2106 3510 1626

Fir-Spruce (Priv.) 793.9 0.0165 754.4 123 1305 835

Fir-Spruce (Publ.) 1837.9 0.0122 2418.7 776 3399 1517

Other Conifer 6695.1 0.0043 10108.6 158 748 616

Other Hardwoods 16854.7 0.0021 20533.0 512 2867 858

Red Alder 3100.3 0.0101 4587.8 557 1208 719

Western Hemlock 2017.5 0.0196 2967.6 963 3894 1556

Nonstocked 27.1 0.0000 0.0 49 2025 304

RMN

Douglas-fir 592.8 0.0415 503.8 3122 2389 526

Fir-Spruce 913.3 0.0225 960.9 1820 1684 578

Hardwoods 427.8 0.0526 374.6 243 642 243

Lodgepole Pine 422.1 0.0488 519.3 1381 967 491

Other Conifer 671.2 0.0314 544.4 273 1166 360

Ponderosa Pine 481.7 0.0263 484.2 889 483 401

Pinyon-Juniper 58.0 0.0000 0.0 6335 2165 48

Nonstocked 41.0 0.0000 0.0 78 1381 79

RMS

Douglas-fir 835.8 0.0461 703.2 833 1658 491

Fir-Spruce 764.4 0.0342 658.6 1371 1656 574

Table 3.—continued.

Forest type F G H n mse Volume

limit

Continued
14

Hardwoods 669.7 0.0538 621.4 1712 1127 337

Lodgepole Pine 452.7 0.0581 567.6 533 907 422

Other Conifer 378.1 0.0326 234.1 263 1409 500

Ponderosa Pine (Priv.) 436.7 0.0556 399.8 585 658 289

Ponderosa Pine (Publ.) 353.0 0.0673 350.5 1192 624 321

Pinyon-Juniper 58.0 0.0000 0.0 6335 2165 48

Nonstocked 26.2 0.0000 0.0 620 1929 39

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-exp(-

volume/H))). If coefficient H equals 0, then F is the predicted value, which is the mean for that forest type (units for

F are then Mg/ha).

Table 3.—continued.

Forest type F G H n mse Volume

limit

Continued

Table 4.—Coefficients for estimating mass density of standing dead trees (above- and belowground,

Mg/ha) by type, region, and owner (as appropriate); A, B, and C are coefficients; n = number of FIA

plots; mse = mean squared error of the prediction relative to individual plots; volume limit (m3

/ha) =

99th percentile of growing-stock volumes within each set of FIA plots (upper limit of independent

variables in the regressions)a

Forest type A B C n mse Volume

limit

NE

Aspen-Birch b 0.0436 704.78 3.506 264 12 250

MBB/Other HW (Priv.) c 0.1189 240.36 2.391 2302 143 273

MBB/Other HW (Publ.) c 0.1189 240.36 2.391 362 151 342

Oak-Hickory 0.0610 459.83 1.617 3314 137 306

Oak-Pine 0.0605 342.95 2.044 304 83 268

Other Pine d 0.1334 228.25 1.368 295 73 304

Spruce-Fir d 0.1334 228.25 1.368 236 47 237

WRJ-Pine d 0.1334 228.25 1.368 398 94 354

Nonstocked 9.9137 0.00 0.000 14 98 10

NLS

Aspen-Birch 0.4176 127.05 0.426 8072 342 239

Lowland HW (Priv.) 0.5147 97.24 0.642 1322 1894 223

Lowland HW (Publ.) 1.8111 1.00 0.149 662 3291 281

MBBc 0.1189 240.36 2.391 5871 524 259

Oak-Hickory 0.1888 329.05 0.432 2049 269 238

Pine 0.3818 7.48 0.156 2056 132 280

Spruce-Fir 0.1517 415.08 1.088 4926 221 217

Nonstocked 9.9137 0.00 0.000 83 418 119

NPS

Conifer 0.0396 287.04 11.740 256 79 236

Lowland HW 0.1178 220.67 1.409 1030 276 303

MBB 0.1006 164.17 1.145 1682 151 252

Oak-Hickory 0.0589 339.57 1.892 2516 151 243
15

Oak-Pine 0.0594 127.97 1.382 172 83 200

Nonstocked 14.7956 0.00 0.000 41 464 71

SC

Bottomland HW (Priv.) 0.1493 145.42 0.484 2092 147 309

Bottomland HW (Publ.) 0.3291 30.12 0.305 295 242 329

Natural Pine (Priv.) 0.0550 424.29 1.901 1620 55 321

Natural Pine (Publ.) 0.0467 974.52 1.355 448 61 373

Oak-Pine 0.0622 835.98 0.892 2000 67 265

Other Conifer 0.0457 116.64 4.311 72 30 208

Planted Pine 0.0631 5137.75 0.136 1477 29 265

Upland HW (Priv.) 0.0666 315.70 1.314 3934 82 204

Upland HW (Publ.) 0.0616 313.09 2.438 481 91 252

Nonstocked 3.6926 0.00 0.000 19 29 8

SE

Bottomland HW (Priv.) e 0.0774 347.43 1.104 2516 112 453

Bottomland HW (Publ.) e 0.0774 347.43 1.104 334 204 427

Natural Pine (Priv.) e 0.0510 826.84 1.353 2892 42 382

Natural Pine (Publ.) e 0.0510 826.84 1.353 662 31 357

Oak-Pine e 0.0510 826.84 1.353 2307 42 347

Other Conifer e 0.0510 826.84 1.353 145 44 397

Planted Pine e 0.0510 826.84 1.353 3865 18 267

Upland HW (Priv.) e 0.0774 347.43 1.104 5071 80 334

Upland HW (Publ.) e 0.0774 347.43 1.104 779 128 336

Nonstocked 3.6926 0.00 0.000 74 136 214

PSW

Douglas-fir f 0.2840 848.73 0.379 93 1737 1090

Fir-Spruce f 0.2840 848.73 0.379 51 1106 1020

Hardwoods f 1.0478 2.67 0.230 695 287 639

Other Conifer f 0.2840 848.73 0.379 795 937 687

Pinyon-Juniper 5.1131 0.00 0.000 6335 134 48

Redwood f 0.2840 848.73 0.379 108 2273 1691

Nonstocked 2.4773 0.00 0.000 18 99 119

PWE

Douglas-fir (Priv.) 0.1005 401.57 1.175 226 491 488

Douglas-fir (Publ.) 8.4407 1.00 0.313 972 1074 636

Fir-Spruce (Priv.) g 4.7263 1.00 0.205 95 3905 496

Fir-Spruce (Publ.)g 4.7263 1.00 0.205 1213 1904 761

Hardwoods 0.9233 1.00 0.585 46 362 292

Lodgepole Pine (Priv.) g 0.3081 422.52 0.868 65 912 325

Lodgepole Pine (Publ.) g 0.3081 422.52 0.868 835 655 389

Ponderosa Pine (Priv.) g 0.8898 3.11 0.178 262 2050 336

Ponderosa Pine (Publ.) g 0.8898 3.11 0.178 1939 365 402

Pinyon-Juniper 5.1131 0.00 0.000 6335 134 48

Nonstocked 27.1975 0.00 0.000 49 2162 293

PWW

Douglas-fir (Priv.) f 0.2840 848.73 0.379 1032 1440 913

Douglas-fir (Publ.) f 0.2840 848.73 0.379 2106 4218 1626

Table 4.—continued.

Forest type A B C n mse Volume

limit

Continued
16

Fir-Spruce (Priv.) f 0.2840 848.73 0.379 123 1825 835

Fir-Spruce (Publ.) f 0.2840 848.73 0.379 776 3413 1517

Other Conifer 0.6505 1.76 0.132 158 244 616

Other Hardwoods f 1.0478 2.67 0.230 512 1078 858

Red Alder 0.3107 1.00 0.128 557 1485 719

Western Hemlock f 0.2840 848.73 0.379 963 5392 1556

Nonstocked 2.4773 0.00 0.000 49 1768 304

RMN

Douglas-fir h 1.9177 1.00 0.197 3122 1054 526

Fir-Spruce 2.1076 1.00 0.155 1820 2118 578

Hardwoods 0.1906 284.53 1.030 243 250 243

Lodgepole Pine 3.6764 1.00 0.235 1381 946 491

Other Conifer 0.7495 111.08 0.927 273 1742 360

Ponderosa Pine h 1.9177 1.00 0.197 889 388 401

Pinyon-Juniper 5.1131 0.00 0.000 6335 134 48

Nonstocked 15.8190 0.00 0.000 78 1622 79

RMS

Douglas-fir 0.6134 1.00 0.100 833 813 491

Fir-Spruce 1.7428 2.70 0.166 1371 2464 574

Hardwoods 0.1441 811.36 1.448 1712 316 337

Lodgepole Pine h 1.9177 1.00 0.197 533 1004 422

Other Conifer 0.4705 128.54 0.324 263 1183 500

Ponderosa Pine (Priv.) 0.5260 1.00 0.186 585 144 289

Ponderosa Pine (Publ.) 0.1986 238.44 0.415 1192 328 321

Pinyon-Juniper 5.1131 0.00 0.000 6335 134 48

Nonstocked 10.0360 0.00 0.000 620 1327 39

a

Prediction of mass density of standing dead trees based on the following equation: Standing dead mass density (Mg/ha)

= (predicted live-tree mass density)*A*exp(-((volume/B)C)). If coefficient C equals 0, then A is the predicted value,

which is the mean for that forest type (units for A are then Mg/ha).

b

From pooled hardwood forests in NE.

c

From pooled MBB/Other HW forests in NE and MBB forests in NLS.

d

From pooled softwood forests in North (NE, NLS, and NPS).

e

From pooled softwood or hardwood forests in South (SC and SE).

f

From pooled softwood or hardwood forests in Pacific Northwest (PWW and PWE).

g

From pooled private and public ownerships.

h

From pooled softwood forests in Rocky Mountains (RMN and RMS).

Table 4.—continued.

Forest type A B C n mse Volume

limit
17

Table 5.—Coefficients for estimating mass density of live trees (aboveground only, Mg/ha) by type,

region, and owner (as appropriate); F, G, and H are coefficients; n = number of FIA plots; mse = mean

squared error of the prediction relative to individual plots; volume limit (m3

/ha) = 99th percentile of

growing-stock volumes within each set of FIA plots (upper limit of independent variables in the

regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 438.5 0.0347 410.7 264 351 250

MBB/Other HW (Priv.) 357.4 0.0470 255.1 2302 658 273

MBB/Other HW (Publ.) 473.3 0.0272 379.5 362 806 342

Oak-Hickory 412.5 0.0502 314.8 3314 890 306

Oak-Pine 310.1 0.0482 247.8 304 457 268

Other Pine 594.5 0.0342 699.3 295 408 304

Spruce-Fir 252.5 0.0413 155.6 236 354 237

WRJ-Pine 344.1 0.0345 274.9 398 736 354

Nonstocked 4.8 0.0000 0.0 14 13 10

NLS

Aspen-Birch 304.5 0.0516 270.8 8072 397 239

Lowland HW (Priv.) 430.9 0.0411 366.8 1322 603 223

Lowland HW (Publ.) 645.4 0.0220 577.2 662 399 281

MBB 293.8 0.0491 187.2 5871 759 259

Oak-Hickory 307.5 0.0748 186.9 2049 806 238

Pine 358.7 0.0343 375.4 2056 381 280

Spruce-Fir 325.8 0.0569 280.8 4926 435 217

Nonstocked 7.1 0.0000 0.0 83 329 119

NPS

Conifer 501.1 0.0463 601.4 256 395 236

Lowland HW 1016.1 0.0279 1002.5 1030 973 303

MBB 394.7 0.0715 324.5 1682 862 252

Oak-Hickory 864.5 0.0384 740.0 2516 1014 243

Oak-Pine 213.3 0.1234 157.6 172 707 200

Nonstocked 19.1 0.0000 0.0 41 635 71

SC

Bottomland HW (Priv.) 263.0 0.1085 173.3 2092 1083 309

Bottomland HW (Publ.) 263.8 0.1011 147.9 295 977 329

Natural Pine (Priv.) 297.4 0.0926 422.4 1620 561 321

Natural Pine (Publ.) 301.3 0.1121 479.3 448 586 373

Oak-Pine 236.8 0.0893 198.8 2000 646 265

Other Conifer 136.8 0.1843 87.5 72 545 208

Planted Pine 134.4 0.1380 117.5 1477 393 265

Upland HW (Priv.) 193.5 0.1521 112.8 3934 988 204

Upland HW (Publ.) 241.0 0.0968 141.4 481 773 252

Nonstocked 47.4 0.0000 0.0 19 1887 8

SE

Bottomland HW (Priv.) 808.6 0.0258 801.6 2516 1553 453

Bottomland HW (Publ.) 359.9 0.0567 291.6 334 1618 427

Natural Pine (Priv.) 296.9 0.0423 344.1 2892 374 382

Natural Pine (Publ.) 1044.8 0.0133 1680.6 662 480 357

Oak-Pine 352.9 0.0347 312.4 2307 462 347

Continued
18

Other Conifer 268.5 0.0223 199.6 145 699 397

Planted Pine 187.3 0.0662 184.9 3865 281 267

Upland HW (Priv.) 352.6 0.0609 285.8 5071 816 334

Upland HW (Publ.) 342.3 0.0904 261.8 779 1337 336

Nonstocked 47.4 0.0000 0.0 74 3195 214

PSW

Douglas-fir 1719.4 0.0164 2155.5 93 5861 1090

Fir-Spruce 741.8 0.0107 776.3 51 4177 1020

Hardwoods 1244.6 0.0000 1142.2 695 4813 639

Other Conifer 1127.0 0.0368 1536.5 795 3054 687

Pinyon-Juniper 47.9 0.0000 0.0 6335 1470 48

Redwood 3738.2 0.0122 6752.8 108 8123 1691

Nonstocked 34.7 0.0000 0.0 18 557 119

PWE

Douglas-fir (Priv.) 540.6 0.0167 575.1 226 1603 488

Douglas-fir (Publ.) 2757.3 0.0000 4024.8 972 2556 636

Fir-Spruce (Priv.) 507.7 0.0127 562.3 95 1731 496

Fir-Spruce (Publ.) 3839.5 0.0000 6123.8 1213 4281 761

Hardwoods 557.1 0.0497 729.3 46 2015 292

Lodgepole Pine (Priv.) 303.4 0.0192 390.5 65 561 325

Lodgepole Pine (Publ.) 577.3 0.0108 989.6 835 1009 389

Ponderosa Pine (Priv.) 312.8 0.0176 331.2 262 727 336

Ponderosa Pine (Publ.) 1256.7 0.0057 2072.9 1939 729 402

Pinyon-Juniper 47.9 0.0000 0.0 6335 1470 48

Nonstocked 13.3 0.0000 0.0 49 332 293

PWW

Douglas-fir (Priv.) 984.2 0.0185 1251.5 1032 3659 913

Douglas-fir (Publ.) 4190.5 0.0052 6848.0 2106 9529 1626

Fir-Spruce (Priv.) 658.8 0.0162 757.6 123 2811 835

Fir-Spruce (Publ.) 1523.8 0.0121 2432.5 776 8683 1517

Other Conifer 6139.8 0.0039 11258.9 158 1375 616

Other Hardwoods 10429.2 0.0028 15217.0 512 3891 858

Red Alder 2318.0 0.0111 4085.2 557 1643 719

Western Hemlock 1670.1 0.0194 2977.1 963 8663 1556

Nonstocked 26.3 0.0000 0.0 49 1895 304

RMN

Douglas-fir 489.6 0.0413 505.6 3122 1622 526

Fir-Spruce 756.9 0.0223 967.6 1820 1142 578

Hardwoods 351.8 0.0530 366.2 243 450 243

Lodgepole Pine 348.2 0.0483 521.1 1381 649 491

Other Conifer 553.3 0.0313 545.5 273 789 360

Ponderosa Pine 398.4 0.0260 486.1 889 326 401

Pinyon-Juniper 47.9 0.0000 0.0 6335 1470 48

Nonstocked 34.2 0.0000 0.0 78 965 79

RMS

Douglas-fir 694.2 0.0457 709.7 833 1128 491

Fir-Spruce 630.6 0.0341 659.0 1371 1125 574

Continued

Forest type F G H n mse Volume

limit

Table 5.—continued.
19

Hardwoods 556.1 0.0539 616.3 1712 783 337

Lodgepole Pine 373.1 0.0577 568.1 533 610 422

Other Conifer 311.6 0.0325 234.3 263 958 500

Ponderosa Pine (Priv.) 363.6 0.0552 405.0 585 450 289

Ponderosa Pine (Publ.) 291.4 0.0671 351.4 1192 424 321

Pinyon-Juniper 47.9 0.0000 0.0 6335 1470 48

Nonstocked 21.9 0.0000 0.0 620 1356 39

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-

exp(-volume/H))). If coefficient H equals 0, then F is the predicted value, which is the mean for that forest type

(units for F are then Mg/ha).

Forest type F G H n mse Volume

limit

Table 5.—continued.

Table 6.—Coefficients for estimating mass density of standing dead trees (aboveground only, Mg/ha)

by type, region, and owner (as appropriate); A, B, and C are coefficients; n = number of FIA plots;

mse = mean squared error of the prediction relative to individual plots; volume limit (m3

/ha) = 99th

percentile of growing-stock volumes within each set of FIA plots (upper limit of independent

variables in the regressions)a

Forest type A B C n mse Volume

limit

NE

Aspen-Birchb 0.0439 697.18 3.478 264 9 250

MBB/Other HW (Priv.) c 0.1194 240.22 2.383 2302 101 273

MBB/Other HW (Publ.) c 0.1194 240.22 2.383 362 106 342

Oak-Hickory 0.0615 459.11 1.609 3314 98 306

Oak-Pine 0.0610 340.62 2.023 304 59 268

Other Pine d 0.1340 228.56 1.348 295 50 304

Spruce-Fir d 0.1340 228.56 1.348 236 32 237

WRJ-Pine d 0.1340 228.56 1.348 398 65 354

Nonstocked 8.2496 0.00 0.000 14 68 10

NLS

Aspen-Birch 0.4211 124.38 0.424 8072 240 239

Lowland HW (Priv.) 0.5168 97.30 0.641 1322 1362 223

Lowland HW (Publ.) 1.8157 1.00 0.149 662 2373 281

MBB c 0.1194 240.22 2.383 5871 373 259

Oak-Hickory 0.1879 329.99 0.441 2049 191 238

Pine 0.3847 7.12 0.155 2056 90 280

Spruce-Fir 0.1524 416.99 1.069 4926 151 217

Nonstocked 8.2496 0.00 0.000 83 291 119

NPS

Conifer 0.0400 286.14 11.668 256 56 236

Lowland HW 0.1189 220.02 1.401 1030 198 303

MBB 0.1015 163.51 1.144 1682 109 252

Oak-Hickory 0.0593 338.68 1.887 2516 109 243

Oak-Pine 0.0605 125.62 1.387 172 60 200

Continued
20

Nonstocked 12.4386 0.00 0.000 41 328 71

SC

Bottomland HW (Priv.) 0.1501 144.76 0.483 2092 105 309

Bottomland HW (Publ.) 0.3253 31.65 0.309 295 172 329

Natural Pine (Priv.) 0.0549 425.16 1.880 1620 38 321

Natural Pine (Publ.) 0.0465 1003.34 1.337 448 42 373

Oak-Pine 0.0623 845.84 0.874 2000 46 265

Other Conifer 0.0460 114.35 4.398 72 21 208

Planted Pine 0.0632 3207.56 0.150 1477 19 265

Upland HW (Priv.) 0.0666 315.78 1.313 3934 58 204

Upland HW (Publ.) 0.0615 313.20 2.451 481 65 252

Nonstocked 3.1095 0.00 0.000 19 21 8

SE

Bottomland HW (Priv.) e 0.0775 348.79 1.102 2516 80 453

Bottomland HW (Publ.) e 0.0775 348.79 1.102 334 146 427

Natural Pine (Priv.) e 0.0512 868.32 1.265 2892 29 382

Natural Pine (Publ.) e 0.0512 868.32 1.265 662 21 357

Oak-Pine e 0.0512 868.32 1.265 2307 30 347

Other Conifer e 0.0512 868.32 1.265 145 30 397

Planted Pine e 0.0512 868.32 1.265 3865 12 267

Upland HW (Priv.) e 0.0775 348.79 1.102 5071 57 334

Upland HW (Publ.) e 0.0775 348.79 1.102 779 91 336

Nonstocked 3.1095 0.00 0.000 74 97 214

PSW

Douglas-fir f 0.2794 448.29 0.344 93 1040 1090

Fir-Spruce f 0.2794 448.29 0.344 51 792 1020

Hardwoods f 1.0857 1.90 0.224 695 172 639

Other Conifer f 0.2794 448.29 0.344 795 608 687

Pinyon-Juniper 4.2241 0.00 0.000 6335 92 48

Redwood f 0.2794 448.29 0.344 108 1264 1691

Nonstocked 2.0326 0.00 0.000 18 4 119

PWE

Douglas-fir (Priv.) 0.0815 402.37 1.171 226 285 488

Douglas-fir (Publ.) 6.8161 1.00 0.312 972 719 636

Fir-Spruce (Priv.) g 3.8137 1.00 0.204 95 2585 496

Fir-Spruce (Publ.) g 3.8137 1.00 0.204 1213 1276 761

Hardwoods 0.9233 1.00 0.670 46 240 292

Lodgepole Pine (Priv.) g 0.2500 430.81 0.872 65 596 325

Lodgepole Pine (Publ.) g 0.2500 430.81 0.872 835 440 389

Ponderosa Pine (Priv.) g 0.6972 3.79 0.182 262 1340 336

Ponderosa Pine (Publ.) g 0.6972 3.79 0.182 1939 246 402

Pinyon-Juniper 4.2241 0.00 0.000 6335 92 48

Nonstocked 22.3113 0.00 0.000 49 1494 293

PWW

Douglas-fir (Priv.) f 0.2794 448.29 0.344 1032 749 913

Douglas-fir (Publ.) f 0.2794 448.29 0.344 2106 2907 1626

Fir-Spruce (Priv.) f 0.2794 448.29 0.344 123 683 835

Continued

Table 6.—continued.

Forest type A B C n mse Volume

limit
21

Fir-Spruce (Publ.) f 0.2794 448.29 0.344 776 2428 1517

Other Conifer 0.5689 1.15 0.127 158 164 616

Other Hardwoods f 1.0857 1.90 0.224 512 697 858

Red Alder 0.1675 1.00 0.059 557 911 719

Western Hemlock f 0.2794 448.29 0.344 963 3703 1556

Nonstocked 2.0326 0.00 0.000 49 75 304

RMN

Douglas-fir h 1.9239 1.00 0.197 3122 719 526

Fir-Spruce 2.1217 1.00 0.155 1820 1447 578

Hardwoods 0.1911 284.22 1.025 243 173 243

Lodgepole Pine 3.7059 1.00 0.235 1381 643 491

Other Conifer 0.7522 110.91 0.929 273 1186 360

Ponderosa Pine h 1.9239 1.00 0.197 889 265 401

Pinyon-Juniper 4.2241 0.00 0.000 6335 92 48

Nonstocked 13.0819 0.00 0.000 78 1106 79

RMS

Douglas-fir 0.6141 1.00 0.100 833 554 491

Fir-Spruce 1.7483 2.68 0.166 1371 1682 574

Hardwoods 0.1439 817.86 1.456 1712 219 337

Lodgepole Pine h 1.9239 1.00 0.197 533 681 422

Other Conifer 0.4729 126.66 0.325 263 807 500

Ponderosa Pine (Priv.) 0.5251 1.00 0.186 585 99 289

Ponderosa Pine (Publ.) 0.1996 235.82 0.414 1192 225 321

Pinyon-Juniper 4.2241 0.00 0.000 6335 92 48

Nonstocked 8.3065 0.00 0.000 620 904 39

a

Prediction of mass density of standing dead trees based on the following equation: Standing dead mass density

(Mg/ha) = (predicted live-tree mass density)*A*exp(-((volume/B)C)). If coefficient C equals 0, then A is the

predicted value, which is the mean for that forest type (units for A are then Mg/ha).

b

From pooled hardwood forests in NE.

c

From pooled MBB/Other HW forests in NE and MBB forests in NLS.

d

From pooled softwood forests in North (NE, NLS, and NPS).

e

From pooled softwood or hardwood forests in South (SC and SE).

f

From pooled softwood or hardwood forests in Pacific Northwest (PWW and PWE).

g

From pooled private and public ownerships.

h

From pooled softwood forests in Rocky Mountains (RMN and RMS).

Table 6.—continued.

Forest type A B C n mse Volume

limit
22

Table 7.—Coefficients for estimating mass density of live softwood tree species (above- and

belowground, Mg/ha) by type, region, and owner (as appropriate); F, G, and H are coefficients; n =

number of FIA plots; mse = mean squared error of the prediction relative to individual plots; volume

limit (m3

/ha) = 99th percentile of growing-stock volumes within each set of FIA plots (upper limit of

independent variables in the regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 73.3 0.0183 38.3 264 58 41

MBB/Other HW (Priv.) 471.3 0.0020 386.6 2302 29 74

MBB/Other HW (Publ.) 175.9 0.0020 135.4 362 49 111

Oak-Hickory 405.3 0.0008 372.8 3314 13 47

Oak-Pine 460.0 0.0149 538.3 304 92 132

Other Pine 1209.8 0.0170 1517.9 295 344 256

Spruce-Fir 334.7 0.0351 220.6 236 356 227

WRJ-Pine 322.1 0.0259 261.2 398 476 279

Nonstocked 0.8 0.0000 0.0 14 7 2

NLS

Aspen-Birch 181.8 0.0047 141.4 8072 44 84

Lowland HW (Priv.) 241.7 0.0018 169.8 1322 43 83

Lowland HW (Publ.) 193.5 0.0072 148.0 662 65 85

MBB 318.4 0.0009 230.8 5871 80 121

Oak-Hickory 118.8 0.0034 91.6 2049 18 60

Pine 428.7 0.0281 429.4 2056 341 268

Spruce-Fir 405.6 0.0517 320.0 4926 600 188

Nonstocked 2.5 0.0000 0.0 83 17 18

NPS

Conifer 291.9 0.0674 313.1 256 276 182

Lowland HW 109.8 0.0011 96.7 1030 2 12

MBB 36.9 0.0047 22.5 1682 2 15

Oak-Hickory b 1438.0 0.0002 1420.2 2516 5 26

Oak-Pine 382.2 0.0321 459.7 172 92 145

Nonstocked 3.0 0.0000 0.0 41 84 56

SC

Bottomland HW (Priv.) 342.8 0.0007 383.6 2092 75 184

Bottomland HW (Publ.) b 612.6 0.0012 793.0 295 56 85

Natural Pine (Priv.) 403.8 0.0561 655.7 1620 346 302

Natural Pine (Publ.) 396.0 0.0714 746.2 448 250 340

Oak-Pine 127.4 0.0748 177.4 2000 92 168

Other Conifer 105.4 0.1621 74.5 72 298 123

Planted Pine 132.6 0.1393 107.6 1477 404 253

Upland HW (Priv.) 84.4 0.0114 104.6 3934 13 59

Upland HW (Publ.) 57.7 0.0055 65.4 481 14 69

Nonstocked 5.0 0.0000 0.0 19 25 8

SE

Bottomland HW (Priv.) 813.1 0.0006 973.8 2516 100 276

Bottomland HW (Publ.) 477.5 0.0036 556.1 334 276 268

Natural Pine (Priv.) 289.6 0.0397 354.2 2892 268 337

Natural Pine (Publ.) 617.7 0.0207 947.1 662 219 303

Oak-Pine 337.1 0.0146 456.4 2307 77 167

Continued
23

Other Conifer 403.5 0.0254 423.4 145 487 386

Planted Pine 213.8 0.0621 200.2 3865 279 261

Upland HW (Priv.) 132.2 0.0042 160.9 5071 10 59

Upland HW (Publ.) 191.7 0.0035 224.6 779 16 71

Nonstocked 5.0 0.0000 0.0 74 121 79

PSW

Douglas-fir 3537.8 0.0081 4159.6 93 2610 1008

Fir-Spruce 903.2 0.0110 784.0 51 1480 1020

Hardwoods 726.9 0.0075 735.0 695 356 383

Other Conifer 791.4 0.0115 736.1 795 1063 617

Pinyon-Juniper 56.6 0.0000 0.0 6335 2135 47

Redwood 1974.9 0.0115 2634.0 108 3183 1691

Nonstocked 29.4 0.0000 0.0 18 482 96

PWE

Douglas-fir (Priv.) 645.3 0.0156 560.7 226 714 479

Douglas-fir (Publ.) 3364.5 0.0000 4050.1 972 1547 636

Fir-Spruce (Priv.) 709.1 0.0137 686.7 95 867 496

Fir-Spruce (Publ.) 4600.0 0.0000 6045.5 1213 2502 758

Hardwoods 237.4 0.0013 229.2 46 120 194

Lodgepole Pine (Priv.) 373.3 0.0199 405.4 65 318 305

Lodgepole Pine (Publ.) 689.2 0.0111 970.6 835 697 389

Ponderosa Pine (Priv.) 366.7 0.0194 325.7 262 330 327

Ponderosa Pine (Publ.) 1501.5 0.0057 2038.9 1939 312 402

Pinyon-Juniper 56.6 0.0000 0.0 6335 2135 47

Nonstocked 11.6 0.0000 0.0 49 262 291

PWW

Douglas-fir (Priv.) 1244.6 0.0155 1319.9 1032 1434 913

Douglas-fir (Publ.) 5215.8 0.0046 7046.3 2106 3251 1626

Fir-Spruce (Priv.) 686.1 0.0164 657.5 123 1200 768

Fir-Spruce (Publ.) 1846.0 0.0120 2424.4 776 3312 1517

Other Conifer 5934.2 0.0045 9074.3 158 586 616

Other Hardwoods 7750.0 0.0000 8874.0 512 918 754

Red Alder 2253.7 0.0035 2922.4 557 414 475

Western Hemlock 2084.8 0.0176 3074.5 963 3835 1549

Nonstocked 22.4 0.0000 0.0 49 1324 191

RMN

Douglas-fir 599.8 0.0397 510.9 3122 2374 526

Fir-Spruce 908.7 0.0221 954.4 1820 1681 578

Hardwoods 227.9 0.0045 169.1 243 65 118

Lodgepole Pine 422.1 0.0471 517.1 1381 966 491

Other Conifer 676.5 0.0306 549.0 273 1157 360

Ponderosa Pine 480.8 0.0261 483.5 889 463 401

Pinyon-Juniper 56.6 0.0000 0.0 6335 2135 47

Nonstocked 6.5 0.0000 0.0 78 189 79

RMS

Douglas-fir 723.0 0.0441 581.5 833 1517 468

Fir-Spruce 810.5 0.0265 707.0 1371 1519 574

Continued

Forest type F G H n mse Volume

limit

Table 7.—continued.
24

Hardwoods 932.5 0.0038 844.5 1712 169 156

Lodgepole Pine 498.3 0.0476 640.5 533 874 422

Other Conifer 383.5 0.0295 240.1 263 1409 500

Ponderosa Pine (Priv.) 310.6 0.0453 251.7 585 431 280

Ponderosa Pine (Publ.) 350.8 0.0643 359.3 1192 538 312

Pinyon-Juniper 56.6 0.0000 0.0 6335 2135 47

Nonstocked 5.4 0.0000 0.0 620 206 39

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-

exp(-volume/H))). Note that for this table, volume is growing-stock volume of softwood species only. If coefficient

H equals 0, then F is the predicted value, which is the mean for that forest type (units for F are then Mg/ha).

b

Coefficients from softwood tree mass in all hardwood forests across the region.

Forest type F G H n mse Volume

limit

Table 7.—continued.

Table 8.—Coefficients for estimating mass density of live hardwood tree species (above- and

belowground, Mg/ha) by type, region, and owner (as appropriate); F, G, and H are coefficients; n =

number of FIA plots; mse = mean squared error of the prediction relative to individual plots; volume

limit (m3

/ha) = 99th percentile of growing-stock volumes within each set of FIA plots (upper limit of

independent variables in the regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 683.6 0.0245 566.9 264 395 250

MBB/Other HW (Priv.) 426.4 0.0479 261.0 2302 889 259

MBB/Other HW (Publ.) 737.5 0.0240 534.2 362 993 335

Oak-Hickory 456.3 0.0527 285.2 3314 1230 299

Oak-Pine 243.6 0.0695 139.3 304 511 166

Other Pine 160.5 0.0356 78.4 295 184 92

Spruce-Fir 261.1 0.0138 117.1 236 123 59

WRJ-Pine 235.4 0.0317 127.6 398 286 140

Nonstocked 4.9 0.0000 0.0 14 19 9

NLS

Aspen-Birch 341.9 0.0534 258.2 8072 542 216

Lowland HW (Priv.) 504.1 0.0397 358.5 1322 795 213

Lowland HW (Publ.) 760.0 0.0204 561.8 662 479 257

MBB 328.1 0.0532 173.1 5871 990 244

Oak-Hickory 356.5 0.0760 176.8 2049 1088 236

Pine 5558.9 0.0000 3378.2 2056 177 87

Spruce-Fir 304.3 0.0084 182.0 4926 103 77

Nonstocked 6.0 0.0000 0.0 83 458 119

NPS

Conifer 495.4 0.0156 321.2 256 186 159

Lowland HW 1170.7 0.0285 962.3 1030 1370 303

MBB 469.3 0.0711 323.5 1682 1213 252

Oak-Hickory 1038.5 0.0381 747.0 2516 1420 240

Continued
25

Oak-Pine 289.3 0.0954 188.1 172 808 150

Nonstocked 19.8 0.0000 0.0 41 857 71

SC

Bottomland HW (Priv.) 312.9 0.1041 166.5 2092 1387 256

Bottomland HW (Publ.) 302.3 0.1038 136.2 295 1271 329

Natural Pine (Priv.) 129.1 0.0908 54.0 1620 287 70

Natural Pine (Publ.) 149.2 0.0985 70.4 448 343 112

Oak-Pine 185.1 0.1132 82.0 2000 599 124

Other Conifer 177.2 0.0991 84.8 72 386 140

Planted Pine 98.6 0.0667 36.6 1477 133 40

Upland HW (Priv.) 218.9 0.1519 97.0 3934 1311 190

Upland HW (Publ.) 290.5 0.1068 145.3 481 1031 230

Nonstocked 51.4 0.0000 0.0 19 2264 5

SE

Bottomland HW (Priv.) 1138.6 0.0204 893.0 2516 1776 370

Bottomland HW (Publ.) 470.7 0.0485 312.9 334 1910 359

Natural Pine (Priv.) 184.8 0.0430 97.0 2892 213 115

Natural Pine (Publ.) 238.0 0.0296 124.1 662 223 104

Oak-Pine 269.0 0.0582 154.5 2307 534 210

Other Conifer 306.0 0.0190 173.2 145 317 127

Planted Pine 156.2 0.0276 68.5 3865 116 40

Upland HW (Priv.) 413.4 0.0649 280.7 5071 1135 326

Upland HW (Publ.) 420.0 0.0926 277.3 779 1835 331

Nonstocked 51.4 0.0000 0.0 74 4420 214

PSW

Douglas-fir 257.6 0.0224 166.1 93 849 247

Fir-Spruce 26.0 0.0134 6.9 51 6 28

Hardwoods 2851.0 0.0000 2199.2 695 5801 421

Other Conifer 1064.4 0.0126 681.3 795 1653 194

Pinyon-Juniper 1.4 0.0000 0.0 6335 35 0

Redwood b 1173.8 0.0102 832.7 108 832 141

Nonstocked 6.3 0.0000 0.0 18 190 41

PWE

Douglas-fir (Priv.) 91.4 0.0023 66.8 226 9 36

Douglas-fir (Publ.) 134.7 0.0007 136.9 972 4 28

Fir-Spruce (Priv.) 153.0 0.0055 132.8 95 18 97

Fir-Spruce (Publ.) 555.4 0.0001 633.9 1213 3 14

Hardwoods 1883.5 0.0148 2026.8 46 2484 288

Lodgepole Pine (Priv.) 27.0 0.0088 1.4 65 3 57

Lodgepole Pine (Publ.) b 100.3 0.0006 67.3 835 1 3

Ponderosa Pine (Priv.) 81.3 0.0033 16.8 262 18 28

Ponderosa Pine (Publ.) b 100.3 0.0006 67.3 1939 9 3

Pinyon-Juniper 1.4 0.0000 0.0 6335 35 0

Nonstocked 2.0 0.0000 0.0 49 74 21

PWW

Douglas-fir (Priv.) 174.9 0.0114 179.0 1032 131 178

Douglas-fir (Publ.) 253.1 0.0055 299.9 2106 81 134

Continued

Forest type F G H n mse Volume

limit

Table 8.—continued.
26

Fir-Spruce (Priv.) 825.2 0.0023 922.4 123 153 198

Fir-Spruce (Publ.) b 264.5 0.0039 309.2 776 39 73

Other Conifer 506.5 0.0052 573.2 158 113 90

Other Hardwoods 526.3 0.0506 548.3 512 1454 487

Red Alder 551.3 0.0306 755.8 557 594 488

Western Hemlock 362.8 0.0011 469.2 963 30 134

Nonstocked 4.7 0.0000 0.0 49 141 114

RMN

Douglas-fir 147.8 0.0032 125.3 3122 15 35

Fir-Spruce 283.4 0.0007 252.6 1820 5 16

Hardwoods 309.1 0.0578 254.3 243 594 201

Lodgepole Pine 107.8 0.0011 71.4 1381 3 13

Other Conifer b 165.3 0.0018 139.9 273 9 0

Ponderosa Pine 27.2 0.0003 6.4 889 2 6

Pinyon-Juniper 1.4 0.0000 0.0 6335 35 0

Nonstocked 34.5 0.0000 0.0 78 1441 4

RMS

Douglas-fir 238.8 0.0134 172.6 833 91 78

Fir-Spruce 273.6 0.0120 241.4 1371 121 106

Hardwoods 424.6 0.0737 379.2 1712 909 268

Lodgepole Pine 79.3 0.0253 42.5 533 41 23

Other Conifer 246.6 0.0047 154.8 263 26 28

Ponderosa Pine (Priv.) 132.3 0.0480 80.8 585 300 26

Ponderosa Pine (Publ.) 57.5 0.0409 23.9 1192 67 19

Pinyon-Juniper 1.4 0.0000 0.0 6335 35 0

Nonstocked 20.8 0.0000 0.0 620 1701 0

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-

exp(-volume/H))). Note that for this table, volume is growing-stock volume of hardwood species only. If

coefficient H equals 0, then F is the predicted value, which is the mean for that forest type (units for F are then

Mg/ha).

b

Coefficients from hardwood tree mass in all softwood forests across the region.

Forest type F G H n mse Volume

limit

Table 8.—continued.
27

Table 9.—Coefficients for estimating mass density of live softwood tree species (aboveground only,

Mg/ha) by type, region, and owner (as appropriate); F, G, and H are coefficients; n = number of FIA

plots; mse = mean squared error of the prediction relative to individual plots; volume limit (m3

/ha) =

99th percentile of growing-stock volumes within each set of FIA plots (upper limit of independent

variables in the regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 60.3 0.0180 38.4 264 39 41

MBB/Other HW (Priv.) 387.3 0.0020 386.1 2302 20 74

MBB/Other HW (Publ.) 144.8 0.0020 135.5 362 33 111

Oak-Hickory 335.1 0.0008 374.6 3314 9 47

Oak-Pine 380.5 0.0147 540.6 304 62 132

Other Pine 1011.3 0.0167 1541.0 295 231 256

Spruce-Fir 276.7 0.0345 222.3 236 237 227

WRJ-Pine 265.1 0.0258 261.0 398 323 279

Nonstocked 0.7 0.0000 0.0 14 5 2

NLS

Aspen-Birch 150.3 0.0046 142.5 8072 29 84

Lowland HW (Priv.) 199.6 0.0018 170.8 1322 29 83

Lowland HW (Publ.) 159.8 0.0071 148.8 662 44 85

MBB 262.7 0.0009 231.4 5871 54 121

Oak-Hickory 98.2 0.0033 92.2 2049 12 60

Pine 354.8 0.0278 432.4 2056 229 268

Spruce-Fir 336.0 0.0508 322.9 4926 400 188

Nonstocked 2.1 0.0000 0.0 83 12 18

NPS

Conifer 238.8 0.0673 310.4 256 186 182

Lowland HW 90.8 0.0011 97.4 1030 1 12

MBB 30.4 0.0047 22.6 1682 2 15

Oak-Hickory b 1225.1 0.0002 1472.0 2516 3 26

Oak-Pine 317.6 0.0316 464.2 172 62 145

Nonstocked 2.5 0.0000 0.0 41 57 56

SC

Bottomland HW (Priv.) 282.5 0.0007 383.7 2092 51 184

Bottomland HW (Publ.) b 505.0 0.0012 793.6 295 38 85

Natural Pine (Priv.) 333.0 0.0555 655.2 1620 232 302

Natural Pine (Publ.) 325.0 0.0709 740.6 448 168 340

Oak-Pine 105.6 0.0736 178.6 2000 62 168

Other Conifer 87.4 0.1597 75.5 72 199 123

Planted Pine 109.6 0.1376 108.4 1477 271 253

Upland HW (Priv.) 70.1 0.0112 105.6 3934 9 59

Upland HW (Publ.) 47.8 0.0054 66.0 481 9 69

Nonstocked 4.2 0.0000 0.0 19 17 8

SE

Bottomland HW (Priv.) 670.4 0.0006 976.0 2516 67 276

Bottomland HW (Publ.) 390.1 0.0036 551.5 334 185 268

Natural Pine (Priv.) 239.3 0.0392 355.9 2892 179 337

Natural Pine (Publ.) 510.2 0.0205 949.6 662 147 303

Oak-Pine 279.4 0.0143 459.3 2307 52 167

Continued
28

Other Conifer 332.8 0.0250 423.8 145 328 386

Planted Pine 176.6 0.0613 201.5 3865 186 261

Upland HW (Priv.) 109.6 0.0041 162.2 5071 6 59

Upland HW (Publ.) 160.1 0.0035 228.2 779 11 71

Nonstocked 4.2 0.0000 0.0 74 82 79

PSW

Douglas-fir 2949.5 0.0080 4203.5 93 5302 1008

Fir-Spruce 746.9 0.0109 787.2 51 4198 1020

Hardwoods 602.8 0.0074 739.9 695 547 383

Other Conifer 654.6 0.0114 739.4 795 2055 617

Pinyon-Juniper 46.7 0.0000 0.0 6335 1449 47

Redwood 1631.3 0.0114 2637.1 108 7886 1691

Nonstocked 29.4 0.0000 0.0 18 482 96

PWE

Douglas-fir (Priv.) 533.7 0.0155 563.8 226 1591 479

Douglas-fir (Publ.) 2860.8 0.0000 4185.0 972 2541 636

Fir-Spruce (Priv.) 586.7 0.0136 690.5 95 1723 496

Fir-Spruce (Publ.) 3939.7 0.0000 6292.4 1213 4274 758

Hardwoods 194.8 0.0013 228.1 46 183 194

Lodgepole Pine (Priv.) 307.0 0.0197 405.2 65 584 305

Lodgepole Pine (Publ.) 574.4 0.0109 984.8 835 1007 389

Ponderosa Pine (Priv.) 303.1 0.0192 327.2 262 662 327

Ponderosa Pine (Publ.) 1254.6 0.0056 2069.0 1939 716 402

Pinyon-Juniper 46.7 0.0000 0.0 6335 1449 47

Nonstocked 11.6 0.0000 0.0 49 262 291

PWW

Douglas-fir (Priv.) 1031.2 0.0153 1327.3 1032 3353 913

Douglas-fir (Publ.) 4350.7 0.0045 7126.1 2106 9334 1626

Fir-Spruce (Priv.) 567.4 0.0162 660.1 123 2746 768

Fir-Spruce (Publ.) 1531.1 0.0118 2439.7 776 8598 1517

Other Conifer 5423.1 0.0040 10083.7 158 1276 616

Other Hardwoods 6636.5 0.0000 9217.1 512 2232 754

Red Alder 1877.9 0.0035 2953.7 557 911 475

Western Hemlock 1733.6 0.0173 3101.5 963 8611 1549

Nonstocked 22.4 0.0000 0.0 49 1324 191

RMN

Douglas-fir 495.5 0.0395 512.9 3122 1612 526

Fir-Spruce 753.4 0.0219 961.4 1820 1141 578

Hardwoods 187.5 0.0045 169.0 243 44 118

Lodgepole Pine 348.3 0.0466 519.1 1381 649 491

Other Conifer 557.8 0.0305 550.1 273 783 360

Ponderosa Pine 397.6 0.0259 485.4 889 312 401

Pinyon-Juniper 46.7 0.0000 0.0 6335 1449 47

Nonstocked 5.3 0.0000 0.0 78 128 79

RMS

Douglas-fir 597.7 0.0438 584.2 833 1029 468

Fir-Spruce 669.9 0.0263 710.1 1371 1030 574

Continued

Forest type F G H n mse Volume

limit

Table 9.—continued.
29

Hardwoods 778.3 0.0037 857.2 1712 114 156

Lodgepole Pine 411.2 0.0471 642.3 533 587 422

Other Conifer 316.2 0.0294 240.5 263 959 500

Ponderosa Pine (Priv.) 256.3 0.0451 252.4 585 291 280

Ponderosa Pine (Publ.) 289.5 0.0641 360.3 1192 364 312

Pinyon-Juniper 46.7 0.0000 0.0 6335 1449 47

Nonstocked 4.4 0.0000 0.0 620 140 39

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-

exp(-volume/H))). Note that for this table, volume is growing-stock volume of softwood species only. If coefficient

H equals 0, then F is the predicted value, which is the mean for that forest type (units for F are then Mg/ha).

b

Coefficients from softwood tree mass in all hardwood forests across the region.

Forest type F G H n mse Volume

limit

Table 9.—continued.

Table 10.—Coefficients for estimating mass density of live hardwood tree species (aboveground only,

Mg/ha) by type, region, and owner (as appropriate); F, G, and H are coefficients; n = number of FIA

plots; mse = mean squared error of the prediction relative to individual plots; volume limit (m3

/ha) =

99th percentile of growing-stock volumes within each set of FIA plots (upper limit of independent

variables in the regressions)a

Forest type F G H n mse Volume

limit

NE

Aspen-Birch 581.3 0.0239 574.9 264 275 250

MBB/Other HW (Priv.) 360.4 0.0473 262.8 2302 626 259

MBB/Other HW (Publ.) 627.6 0.0236 541.8 362 702 335

Oak-Hickory 385.6 0.0519 286.9 3314 867 299

Oak-Pine 205.9 0.0685 140.5 304 359 166

Other Pine 135.3 0.0351 78.9 295 128 92

Spruce-Fir 221.1 0.0135 118.6 236 86 59

WRJ-Pine 198.9 0.0312 128.6 398 201 140

Nonstocked 4.1 0.0000 0.0 14 14 9

NLS

Aspen-Birch 287.7 0.0525 258.3 8072 379 216

Lowland HW (Priv.) 428.2 0.0391 363.1 1322 562 213

Lowland HW (Publ.) 646.4 0.0199 569.3 662 338 257

MBB 276.4 0.0526 173.7 5871 699 244

Oak-Hickory 300.0 0.0756 177.2 2049 770 236

Pine 5420.6 0.0000 3931.4 2056 124 87

Spruce-Fir 258.4 0.0083 184.6 4926 72 77

Nonstocked 5.0 0.0000 0.0 83 324 119

NPS

Conifer 427.2 0.0152 331.2 256 130 159

Lowland HW 996.9 0.0279 974.7 1030 967 303

MBB 397.4 0.0702 326.3 1682 855 252

Oak-Hickory 885.2 0.0374 757.8 2516 1002 240

Continued
30

Oak-Pine 244.7 0.0943 189.7 172 568 150

Nonstocked 16.6 0.0000 0.0 41 604 71

SC

Bottomland HW (Priv.) 263.9 0.1033 167.1 2092 980 256

Bottomland HW (Publ.) 254.7 0.1031 136.3 295 899 329

Natural Pine (Priv.) 108.8 0.0897 54.3 1620 201 70

Natural Pine (Publ.) 125.7 0.0975 70.7 448 241 112

Oak-Pine 156.1 0.1119 82.4 2000 421 124

Other Conifer 150.4 0.0979 86.0 72 272 140

Planted Pine 83.1 0.0655 36.9 1477 93 40

Upland HW (Priv.) 184.7 0.1508 97.6 3934 924 190

Upland HW (Publ.) 245.2 0.1058 146.2 481 727 230

Nonstocked 43.2 0.0000 0.0 19 1600 5

SE

Bottomland HW (Priv.) 968.3 0.0200 904.5 2516 1254 370

Bottomland HW (Publ.) 397.5 0.0480 314.8 334 1350 359

Natural Pine (Priv.) 156.1 0.0423 97.9 2892 149 115

Natural Pine (Publ.) 200.6 0.0292 124.9 662 156 104

Oak-Pine 227.2 0.0574 155.7 2307 375 210

Other Conifer 260.0 0.0187 175.7 145 223 127

Planted Pine 132.6 0.0269 69.9 3865 81 40

Upland HW (Priv.) 349.1 0.0641 282.2 5071 801 326

Upland HW (Publ.) 355.3 0.0915 279.5 779 1297 331

Nonstocked 43.2 0.0000 0.0 74 3131 214

PSW

Douglas-fir 217.2 0.0222 166.9 93 1006 247

Fir-Spruce 21.9 0.0134 7.0 51 7 28

Hardwoods 2431.0 0.0000 2232.3 695 6560 421

Other Conifer 897.1 0.0125 683.1 795 1811 194

Pinyon-Juniper 1.2 0.0000 0.0 6335 25 0

Redwood b 990.1 0.0101 835.7 108 624 141

Nonstocked 6.3 0.0000 0.0 18 190 41

PWE

Douglas-fir (Priv.) 77.1 0.0023 67.2 226 11 36

Douglas-fir (Publ.) 114.1 0.0007 138.5 972 5 28

Fir-Spruce (Priv.) 127.6 0.0055 131.3 95 23 97

Fir-Spruce (Publ.) 482.1 0.0001 655.1 1213 4 14

Hardwoods 1620.9 0.0144 2079.2 46 2719 288

Lodgepole Pine (Priv.) 22.7 0.0087 1.6 65 4 57

Lodgepole Pine (Publ.) b 84.6 0.0006 67.7 835 1 3

Ponderosa Pine (Priv.) 68.5 0.0033 17.0 262 21 28

Ponderosa Pine (Publ.) b 84.6 0.0006 67.7 1939 10 3

Pinyon-Juniper 1.2 0.0000 0.0 6335 25 0

Nonstocked 2.0 0.0000 0.0 49 74 21

PWW

Douglas-fir (Priv.) 147.4 0.0113 179.6 1032 159 178

Douglas-fir (Publ.) 214.5 0.0054 302.6 2106 96 134

Continued

Forest type F G H n mse Volume

limit

Table 10.—continued.
31

Fir-Spruce (Priv.) 703.3 0.0022 935.2 123 213 198

Fir-Spruce (Publ.) b 223.7 0.0039 311.4 776 30 73

Other Conifer 431.9 0.0051 582.8 158 121 90

Other Hardwoods 444.4 0.0501 550.7 512 1901 487

Red Alder 463.4 0.0303 754.3 557 1069 488

Western Hemlock 308.2 0.0011 474.5 963 43 134

Nonstocked 4.7 0.0000 0.0 49 141 114

RMN

Douglas-fir 124.6 0.0032 125.9 3122 10 35

Fir-Spruce 241.9 0.0006 257.4 1820 3 16

Hardwoods 260.6 0.0571 255.1 243 418 201

Lodgepole Pine 90.9 0.0011 72.0 1381 2 13

Other Conifer b 139.7 0.0017 141.3 273 6 0

Ponderosa Pine 22.8 0.0003 6.4 889 1 6

Pinyon-Juniper 1.2 0.0000 0.0 6335 25 0

Nonstocked 28.8 0.0000 0.0 78 1007 4

RMS

Douglas-fir 201.6 0.0132 173.9 833 63 78

Fir-Spruce 231.2 0.0119 243.1 1371 85 106

Hardwoods 357.3 0.0731 379.8 1712 636 268

Lodgepole Pine 66.8 0.0250 42.9 533 29 23

Other Conifer 208.9 0.0046 156.4 263 18 28

Ponderosa Pine (Priv.) 111.3 0.0475 81.0 585 210 26

Ponderosa Pine (Publ.) 48.5 0.0404 24.1 1192 47 19

Pinyon-Juniper 1.2 0.0000 0.0 6335 25 0

Nonstocked 17.5 0.0000 0.0 620 1201 0

a

Prediction of mass density of live trees based on the following equation: Live mass density (Mg/ha) = F*(G+(1-

exp(-volume/H))). Note that for this table, volume is growing-stock volume of hardwood species only. If coefficient

H equals 0, then F is the predicted value, which is the mean for that forest type (units for F are then Mg/ha).

b

Coefficients from hardwood tree mass in all softwood forests across the region.

Forest type F G H n mse Volume

limit

Table 10.—continued.
32

Table 11.—Estimated mass density of live trees (aboveground only, Mg/ha) by region and hardwood/

softwood types; to ensure consistent comparisons among estimates, all were applied to the same set

of plot and tree records from the FIADB (nonstocked and woodland forest types were excluded)

Region Forest Estimates based FIADB Birdsey Brown and

type on Table 3 (DRYBIOT) (1992) others (1999)

Mg/ha

NE Hardwood 116.7 110.6 102.4 128.2

Softwood 84.0 79.3 60.2 82.8

NLS Hardwood 103.7 94.0 89.8 121.4

Softwood 81.1 67.0 58.3 87.8

NPS Hardwood 100.7 80.8 91.1 102.1

Softwood 69.1 51.5 54.0 62.8

SC Hardwood 104.6 112.1 90.5 104.0

Softwood 78.5 97.3 71.1 89.8

SE Hardwood 120.8 105.7 114.2 144.8

Softwood 67.0 66.0 59.8 89.8

PSW Hardwood 140.7 159.1 101.0

Softwood 178.3 174.1 133.1

PWE Hardwood 84.3 67.4 56.2

Softwood 108.3 98.4 96.4

PWW Hardwood 191.1 201.8 181.04

Softwood 264.0 264.5 268.5

RMN Hardwood 71.6 49.7 47.2

Softwood 122.3 111.7 119.8

RMS Hardwood 72.0 53.2 39.4

Softwood 113.0 92.7 91.0
33

Table 12.—Estimated total mass (Mt) of live and standing dead trees larger than 1 inch d.b.h.

(aboveground and coarse roots) and area, by region and forest classification; values obtained by applying

biomass estimates from Tables 3 and 4 to data from 1997 RPA database (Smith and others 2001)

Timberlanda Reserved Other

Region Live Dead Area Live Dead Area Live Dead Area

Thousand Thousand Thousand

ha ha ha

NE 4846 349 31940 315 20 2009 79 6 647

NLS 2470 311 19906 19 6 775 11 3 402

NPS 1735 100 13937 27 2 408 17 3 340

North 9051 760 65783 362 28 3191 108 11 1388

SC 5722 311 47024 58 3 486 183 11 3254

SE 4230 206 34320 87 5 1092 22 1 469

South 9953 517 81344 146 8 1579 205 13 3723

PSW 1664 223 7265 714 82 2415 464 57 5920

PWE 1097 125 7989 185 28 1151 100 14 1559

PWW 2251 257 8671 275 33 1268 18 2 249

RMN 2104 201 14685 280 87 2893 57 11 701

RMS 1625 228 12796 232 126 4440 1335 140 21025

West 8740 1033 51407 1686 355 12167 1974 223 29454

All regions 27744 2311 198534 2193 391 16937 2286 248 34565

a

Timberland is forest land classified as having a growth capacity of at least 20 cubic feet industrial wood per acre per

year. Reserved forests are withdrawn by law from the production of wood products.
34

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36

Index to Figures

Figure 5. .................................................................. 42

Estimated mass density of live and standing dead trees

in NE Aspen-Birch forests (individual points are plotlevel density summaries).

Figure 6. ................................................................... 42

Estimated mass density of live and standing dead trees

in NE MBB/Other HW forests on privately owned

land.

Figure 7. ................................................................... 42

Estimated mass density of live and standing dead trees

in NE Oak-Hickory forests.

Figure 8. ................................................................... 43

Estimated mass density of live and standing dead trees

in NE Oak-Pine forests.

Figure 9. ................................................................... 43

Estimated mass density of live and standing dead trees

in NE Other Pine forests.

Figure 10. ................................................................. 43

Estimated mass density of live and standing dead trees

in NE Spruce-Fir forests.

Figure 11. ................................................................. 44

Estimated mass density of live and standing dead trees

in NE WRJ-Pine forests.

Figure 12. ................................................................. 44

Estimated mass density of live and standing dead trees

in NLS Aspen-Birch forests.

Figure 13. ................................................................. 44

Estimated mass density of live and standing dead trees

in NLS Lowland HW forests on privately owned land.

Figure 14. ................................................................. 45

Estimated mass density of live and standing dead trees

in NLS MBB forests.

Figure 15. ................................................................. 45

Estimated mass density of live and standing dead trees

in NLS Oak-Hickory forests.

Figure 16. ................................................................. 45

Estimated mass density of live and standing dead trees

in NLS Pine forests.

Figure 17. ................................................................. 46

Estimated mass density of live and standing dead trees

in NLS Spruce-Fir forests.

Figure 18. ................................................................. 46

Estimated mass density of live and standing dead trees

in NPS Conifer forests.

Figure 19. ................................................................. 46

Estimated mass density of live and standing dead trees

in NPS Lowland HW forests.

Figure 20. ................................................................. 47

Estimated mass density of live and standing dead trees

in NPS MBB forests.

Figure 21. ................................................................. 47

Estimated mass density of live and standing dead trees

in NPS Oak-Hickory forests.

Figure 22. ................................................................. 47

Estimated mass density of live and standing dead trees

in NPS Oak-Pine forests.

Figure 23. ................................................................. 48

Estimated mass density of live and standing dead trees

in SC Bottomland HW forests on privately owned land.

Figure 24. ................................................................. 48

Estimated mass density of live and standing dead trees

in SC Natural Pine forests on privately owned land.

Figure 25. ................................................................. 48

Estimated mass density of live and standing dead trees

in SC Oak-Pine forests.

Figure 26. ................................................................. 49

Estimated mass density of live and standing dead trees

in SC Other Conifer forests.

Figure 27. ................................................................. 49

Estimated mass density of live and standing dead trees

in SC Planted Pine forests.

Figure 28. ................................................................. 49

Estimated mass density of live and standing dead trees

in SC Upland HW forests on privately owned land.

Figure 29. ................................................................. 50

Estimated mass density of live and standing dead trees

in SE Bottomland HW forests on privately owned land.

Figure 30. ................................................................. 50

Estimated mass density of live and standing dead trees

in SE Natural Pine forests on privately owned land.

Figure 31. ................................................................. 50

Estimated mass density of live and standing dead trees

in SE Oak-Pine forests.

Figure 32. ................................................................. 51

Estimated mass density of live and standing dead trees

in SE Other Conifer forests.

Figure 33. ................................................................. 51

Estimated mass density of live and standing dead trees

in SE Planted Pine forests.

Apendix
37

Figure 34. ................................................................. 51

Estimated mass density of live and standing dead trees

in SE Upland HW forests on privately owned land.

Figure 35. ................................................................. 52

Estimated mass density of live and standing dead trees

in PSW Douglas-fir forests (estimates of standing dead

tree mass for PSW were based on Pacific Northwest

data, individual plot-level summaries are not available).

Figure 36. ................................................................. 52

Estimated mass density of live and standing dead trees

in PSW Fir-Spruce forests.

Figure 37. ................................................................. 52

Estimated mass density of live and standing dead trees

in PSW Hardwoods forests.

Figure 38. ................................................................. 53

Estimated mass density of live and standing dead trees

in PSW Other Conifer forests.

Figure 39. ................................................................. 53

Estimated mass density of live and standing dead trees

in PSW Redwood forests.

Figure 40. ................................................................. 53

Estimated mass density of live and standing dead trees

in PWE Douglas-fir forests on publicly owned land.

Figure 41. ................................................................. 54

Estimated mass density of live and standing dead trees

in PWE Fir-Spruce forests on publicly owned land.

Figure 42. ................................................................. 54

Estimated mass density of live and standing dead trees

in PWE Hardwoods forests.

Figure 43. ................................................................. 54

Estimated mass density of live and standing dead trees

in PWE Lodgepole Pine forests on publicly owned land.

Figure 44. ................................................................. 55

Estimated mass density of live and standing dead trees

in PWE Ponderosa Pine forests on publicly owned land.

Figure 45. ................................................................. 55

Estimated mass density of live and standing dead trees

in PWW Douglas-fir forests on publicly owned land.

Figure 46. ................................................................. 55

Estimated mass density of live and standing dead trees

in PWW Fir-Spruce forests on publicly owned land.

Figure 47. ................................................................. 56

Estimated mass density of live and standing dead trees

in PWW Other Conifer forests.

Figure 48. ................................................................. 56

Estimated mass density of live and standing dead trees

in PWW Other Hardwoods forests.

Figure 49. ................................................................. 56

Estimated mass density of live and standing dead trees

in PWW Red Alder forests.

Figure 50. ................................................................. 57

Estimated mass density of live and standing dead trees

in PWW Western Hemlock forests.

Figure 51. ................................................................. 57

Estimated mass density of live and standing dead trees

in RMN Douglas-fir forests.

Figure 52. ................................................................. 57

Estimated mass density of live and standing dead trees

in RMN Fir-Spruce forests.

Figure 53. ................................................................. 58

Estimated mass density of live and standing dead trees

in RMN Hardwoods forests.

Figure 54. ................................................................. 58

Estimated mass density of live and standing dead trees

in RMN Lodgepole Pine forests.

Figure 55. ................................................................. 58

Estimated mass density of live and standing dead trees

in RMN Other Conifer forests.

Figure 56. ................................................................. 59

Estimated mass density of live and standing dead trees

in RMN Ponderosa Pine forests.

Figure 57. ................................................................. 59

Estimated mass density of live and standing dead trees

in RMS Douglas-fir forests.

Figure 58. ................................................................. 59

Estimated mass density of live and standing dead trees

in RMS Fir-Spruce forests.

Figure 59. ................................................................. 60

Estimated mass density of live and standing dead trees

in RMS Hardwoods forests.

Figure 60. ................................................................. 60

Estimated mass density of live and standing dead trees

in RMS Lodgepole Pine forests.

Figure 61. ................................................................. 60

Estimated mass density of live and standing dead trees

in RMS Other Conifer forests.

Figure 62. ................................................................. 61

Estimated mass density of live and standing dead trees

in RMS Ponderosa Pine forests on publicly owned land.
38

0 100 200 300

Live 

Tree 

Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

20

40

Figure 5.—Estimated mass density

of live and standing dead trees in

NE Aspen-Birch forests (individual points are plot-level density

summaries).

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 6.—Estimated mass density

of live and standing dead trees in

NE MBB/Other HW forests on

privately owned land.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 7.—Estimated mass density

of live and standing dead trees in

NE Oak-Hickory forests.
39

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

25

50

75

Figure 8.—Estimated mass density

of live and standing dead trees in

NE Oak-Pine forests.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

Figure 9.—Estimated mass density

of live and standing dead trees in

NE Other Pine forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

20

40

Figure 10.—Estimated mass

density of live and standing dead

trees in NE Spruce-Fir forests.
40

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing dead tree 

0 100 200 300 400

mass (Mg/ha)

0

25

50

75

Figure 11.—Estimated mass

density of live and standing dead

trees in NE WRJ-Pine forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

50

100

150

Figure 12.—Estimated mass

density of live and standing dead

trees in NLS Aspen-Birch forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

50

100

150

Figure 13.—Estimated mass

density of live and standing dead

trees in NLS Lowland HW forests

on privately owned land.
41

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 14.—Estimated mass

density of live and standing dead

trees in NLS MBB forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

50

100

150

Figure 15.—Estimated mass

density of live and standing dead

trees in NLS Oak-Hickory forests.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

100

Figure 16.—Estimated mass

density of live and standing dead

trees in NLS Pine forests.
42

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

25

50

75

100

Figure 17.—Estimated mass

density of live and standing dead

trees in NLS Spruce-Fir forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

20

40

Figure 18.—Estimated mass

density of live and standing dead

trees in NPS Conifer forests.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 19.—Estimated mass

density of live and standing dead

trees in NPS Lowland HW forests.
43

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 20.—Estimated mass

density of live and standing dead

trees in NPS MBB forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

50

100

150

Figure 21.—Estimated mass

density of live and standing dead

trees in NPS Oak-Hickory forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

20

40

Figure 22.—Estimated mass

density of live and standing dead

trees in NPS Oak-Pine forests.
44

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 23.—Estimated mass

density of live and standing dead

trees in SC Bottomland HW

forests on privately owned land.

0 100 200 300 400 500

Live 

Tree 

Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

75

Figure 24.—Estimated mass

density of live and standing dead

trees in SC Natural Pine forests on

privately owned land.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

100

Figure 25.—Estimated mass

density of live and standing dead

trees in SC Oak-Pine forests.
45

0 100 200 300

Live 

Tree 

Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

20

40

Figure 26.—Estimated mass

density of live and standing dead

trees in SC Other Conifer forests.

0 100 200 300 400

Live 

Tree 

Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

Figure 27.—Estimated mass

density of live and standing dead

trees in SC Planted Pine forests.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

25

50

75

100

Figure 28.—Estimated mass

density of live and standing dead

trees in SC Upland HW forests on

privately owned land.
46

0 200 400 600

Live Tree Mass 

(Mg/ha)

0

200

400

600

800

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600

Mass (Mg/ha)

0

50

100

150

Figure 29.—Estimated mass

density of live and standing dead

trees in SE Bottomland HW

forests on privately owned land.

0 200 400 600

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600

Mass (Mg/ha)

0

25

50

75

100

Figure 30.—Estimated mass

density of live and standing dead

trees in SE Natural Pine forests on

privately owned land.

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

75

100

Figure 31.—Estimated mass

density of live and standing dead

trees in SE Oak-Pine forests.
47

0 100 200 300 400

Live 

Tree 

Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

20

40

Figure 32.—Estimated mass

density of live and standing dead

trees in SE Other Conifer forests.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

100

Figure 33.—Estimated mass

density of live and standing dead

trees in SE Planted Pine forests.

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

75

100

Figure 34.—Estimated mass

density of live and standing dead

trees in SE Upland HW forests on

privately owned land.
48

0 300 600 900 1200

Live Tree Mass 

(Mg/ha)

0

250

500

750

1000

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 300 600 900 1200

Mass (Mg/ha)

0

25

50

75

100 Figure 35.—Estimated mass

density of live and standing dead

trees in PSW Douglas-fir forests

(estimates of standing dead tree

mass for PSW were based on

Pacific Northwest data, individual

plot-level summaries are not

available).

0 200 400 600

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600

Mass (Mg/ha)

0

25

50

75

100

Figure 36.—Estimated mass

density of live and standing dead

trees in PSW Fir-Spruce forests.

0 100 200 300 400 500

Live 

Tree 

Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

Figure 37.—Estimated mass

density of live and standing dead

trees in PSW Hardwoods forests.
49

0 100 200 300 400 500

Live 

Tree 

Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

Figure 38.—Estimated mass

density of live and standing dead

trees in PSW Other Conifer

forests.

0 300 600 900 1200

Live Tree Mass 

(Mg/ha)

0

250

500

750

1000

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 300 600 900 1200

Mass (Mg/ha)

0

50

100

150

Figure 39.—Estimated mass

density of live and standing dead

trees in PSW Redwood forests.

0 200 400 600 800 1000

Live Tree Mass 

(Mg/ha)

0

250

500

750

1000

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800 1000

Mass (Mg/ha)

0

50

100

150

200

Figure 40.—Estimated mass

density of live and standing dead

trees in PWE Douglas-fir forests

on publicly owned land.
50

0 200 400 600 800 1000

Live Tree Mass 

(Mg/ha)

0

200

400

600

800

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800 1000

Mass (Mg/ha)

0

100

200

Figure 41.—Estimated mass

density of live and standing dead

trees in PWE Fir-Spruce forests on

publicly owned land.

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

250

500

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

25

50

75

100

Figure 42.—Estimated mass

density of live and standing dead

trees in PWE Hardwoods forests.

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

100

200

Figure 43.—Estimated mass

density of live and standing dead

trees in PWE Lodgepole Pine

forests on publicly owned land.
51

0 200 400 600

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600

Mass (Mg/ha)

0

100

200

Figure 44.—Estimated mass

density of live and standing dead

trees in PWE Ponderosa Pine

forests on publicly owned land.

0 500 1000 1500 2000

Live Tree Mass 

(Mg/ha)

0

400

800

1200

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 500 1000 1500 2000

Mass (Mg/ha)

0

100

200

300

Figure 45.—Estimated mass

density of live and standing dead

trees in PWW Douglas-fir forests

on publicly owned land.

0 500 1000 1500 2000

Live Tree Mass 

(Mg/ha)

0

300

600

900

1200

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 500 1000 1500 2000

Mass (Mg/ha)

0

100

200

300

Figure 46.—Estimated mass

density of live and standing dead

trees in PWW Fir-Spruce forests

on publicly owned land.
52

0 200 400 600 800

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800

Mass (Mg/ha)

0

50

100

150

Figure 47.—Estimated mass

density of live and standing dead

trees in PWW Other Conifer

forests.

0 200 400 600 800 1000

Live Tree Mass 

(Mg/ha)

0

250

500

750

1000

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800 1000

Mass (Mg/ha)

0

50

100

150

200

Figure 48.—Estimated mass

density of live and standing dead

trees in PWW Other Hardwoods

forests.

0 200 400 600 800

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800

Mass (Mg/ha)

0

50

100

150

200

Figure 49.—Estimated mass

density of live and standing dead

trees in PWW Red Alder forests.
53

0 500 1000 1500 2000

Live Tree Mass 

(Mg/ha)

0

300

600

900

1200

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 500 1000 1500 2000

Mass (Mg/ha)

0

100

200

300

Figure 50.—Estimated mass

density of live and standing dead

trees in PWW Western Hemlock

forests.

0 200 400 600 800

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800

Mass (Mg/ha)

0

100

200

Figure 51.—Estimated mass

density of live and standing dead

trees in RMN Douglas-fir forests.

0 200 400 600 800

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 200 400 600 800

Mass (Mg/ha)

0

100

200

Figure 52.—Estimated mass

density of live and standing dead

trees in RMN Fir-Spruce forests.
54

0 100 200 300

Live Tree Mass 

(Mg/ha)

0

100

200

300

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300

Mass (Mg/ha)

0

25

50

75

100

Figure 53.—Estimated mass

density of live and standing dead

trees in RMN Hardwoods forests.

0 100 200 300 400 500 600

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500 600

Mass (Mg/ha)

0

50

100

150

Figure 54.—Estimated mass

density of live and standing dead

trees in RMN Lodgepole Pine

forests.

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

50

100

150

Figure 55.—Estimated mass

density of live and standing dead

trees in RMN Other Conifer

forests.
55

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

75

100

Figure 56.—Estimated mass

density of live and standing dead

trees in RMN Ponderosa Pine

forests.

0 100 200 300 400 500 600

Live Tree Mass 

(Mg/ha)

0

200

400

600

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500 600

Mass (Mg/ha)

0

50

100

150

200

Figure 57.—Estimated mass

density of live and standing dead

trees in RMS Douglas-fir forests.

0 100 200 300 400 500 600

Live Tree Mass 

(Mg/ha)

0

200

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500 600

Mass (Mg/ha)

0

100

200

300

Figure 58.—Estimated mass

density of live and standing dead

trees in RMS Fir-Spruce forests.
56

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

25

50

75

100

Figure 59.—Estimated mass

density of live and standing dead

trees in RMS Hardwoods forests.

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

50

100

150

200

Figure 60.—Estimated mass

density of live and standing dead

trees in RMS Lodgepole Pine

forests.

0 100 200 300 400 500

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400 500

Mass (Mg/ha)

0

50

100

150

Figure 61.—Estimated mass

density of live and standing dead

trees in RMS Other Conifer

forests.
57

0 100 200 300 400

Live Tree Mass 

(Mg/ha)

0

100

200

300

400

Growing Stock Volume (m3/ha)

Standing Dead Tree 

0 100 200 300 400

Mass (Mg/ha)

0

25

50

75

100

Figure 62.—Estimated mass

density of live and standing dead

trees in RMS Ponderosa Pine

forests on publicly owned land.
Printed on Recycled Paper

Smith, James E.; Heath, Linda S.; Jenkins, Jennifer C. 2003. Forest volume-tobiomass models and estimates of mass for live and standing dead trees of

U.S. forests. Gen. Tech. Rep. NE-298. Newtown Square, PA: U.S. Department

of Agriculture, Forest Service, Northeastern Research Station. 57 p.

Includes methods and equations for nationally consistent estimates of tree-mass

density at the stand level (Mg/ha) as predicted by growing-stock volumes reported

by the USDA Forest Service for forests of the conterminous United States.

Developed for use in FORCARB, a carbon budget model for U.S. forests, the

equations also are useful for converting plot-, stand- and regional-level forest

merchantable volumes to estimates of total mass. Also includes separate

equations for live, standing dead, aboveground only and full trees (including coarse

roots), and for hardwood and softwood species. Example estimates are provided for

regional tree-mass totals using summary forest statistics for the United States.

Keywords: biomass, carbon, carbon sequestration, forest, live and standing dead

trees
Headquarters of the Northeastern Research Station is in Newtown Square,

Pennsylvania. Field laboratories are maintained at:

Amherst, Massachusetts, in cooperation with the University of Massachusetts

Burlington, Vermont, in cooperation with the University of Vermont

Delaware, Ohio

Durham, New Hampshire, in cooperation with the University of New Hampshire

Hamden, Connecticut, in cooperation with Yale University

Morgantown, West Virginia, in cooperation with West Virginia University

Parsons, West Virginia

Princeton, West Virginia

Syracuse, New York, in cooperation with the State University of New York,

College of Environmental Sciences and Forestry at Syracuse University

Warren, Pennsylvania

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