Montana’s Forest Resources, 

2003–2009

Jim Menlove, John D. Shaw, Michael T. Thompson, Chris 

Witt, Michael C. Amacher, Todd A. Morgan, Colin Sorenson, 

Chelsea P. McIver, Chuck Werstak

United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

Resource Bulletin

RMRS-RB-15

July 2012
Menlove, Jim; Shaw, John D.; Thompson, Michael T.; Witt, Chris; Amacher, Michael C.; Morgan, Todd A.; Sorenson, Colin; 

McIver, Chelsea; Werstak, Charles. 2012. Montana’s forest resources, 2003–2009. Resour. Bull. RMRS-RB-15. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 140 p.

Abstract

This report presents a summary of the most recent inventory information for Montana’s forest lands. The report includes 

descriptive highlights and tables of area, number of trees, biomass, volume, growth, mortality, and removals. Most of the 

tables are organized by forest type group, species group, diameter class, or owner group. The report also describes inventory design, inventory terminology, and data reliability. Results show that Montana’s forest land totals 25.6 million acres. 

Sixty percent (15.4 million acres) of this forest land is administered by the USDA Forest Service. Douglas-fir forests cover 

7.5 million acres or roughly 29 percent of Montana’s forested lands, making it the most abundant forest type in the State. 

The lodgepole pine type is the second-most common individual forest type comprising 17 percent of Montana’s forest land. 

Lodgepole pine is the most abundant tree species in Montana by number of trees, and Douglas-fir is the most abundant 

species by volume or biomass. Net annual growth of all live trees 5.0 inches diameter and greater on Montana forest land 

totaled 289.8 million cubic feet. Average annual mortality totaled nearly 746.3 million cubic feet. 

Keywords: Montana, forest resources, inventory methods, forest inventory, forest type

Authors

Jim Menlove is an Ecologist and a member of the Analysis Team with the Interior West Inventory and Analysis 

Program at the USFS Rocky Mountain Research Station in Ogden, Utah. He holds a B.S. degree in Biology 

from the University of Utah and an M.S. degree in Zoology and Physiology from the University of Wyoming, both 

with an emphasis in ecology (contact: jmenlove@fs.fed.us, 801-625-5426).

John D. Shaw is a Biological Scientist and Analysis Team Leader with the Interior West Inventory and Analysis 

Program at the USFS Rocky Mountain Research Station in Ogden, Utah. He holds B.S. and M.S. degrees in 

Natural Resources Management from the University of Alaska Fairbanks and a Ph.D. in Forest Ecology from 

Utah State University.

Michael T. Thompson is a Forester and a member of the Analysis Team with the Interior West Inventory and 

Analysis Program at the USFS Rocky Mountain Research Station in Ogden, Utah. He holds a B.S. degree in 

Forestry from North Carolina State University.

Chris Witt is an Ecologist and a member of the Analysis Team with the Interior West Inventory and Analysis 

Program at the USFS Rocky Mountain Research Station in Ogden, UT. He holds B.S. and M.S. degrees in 

Ecology from Idaho State University.

Michael C. Amacher is a Research Soil Scientist in the Forest and Woodland Ecosystems Research Program 

at the USFS Rocky Mountain Research Station in Logan, Utah. He also serves as the western soils Indicator 

Advisor in the Indicators of Forest Health program. He has B.S. and M.S. degrees in Chemistry and a PhD in 

Soil Chemistry, all from The Pennsylvania State University.

Todd A. Morgan is the director of the Forest Industry Research Program at The University of Montana’s Bureau 

of Business and Economic Research in Missoula, Montana. He received a B.A. degree in Philosophy and a 

B.S. degree in Forest Science from Pennsylvania State and an M.S. degree in Forestry from The University of 

Montana.

Colin Sorenson is a Research Economist with the Forest Industry Research Program at The University 

of Montana Bureau of Business and Economic Research in Missoula, Montana. He holds a B.S. degree in 

Social Science with a secondary degree in Natural Resources and Environmental Sciences from Kansas State 

University and an M.A. degree in Economics from The University of Montana. 

Chelsea P. McIver is a Research Assistant with the Forest Industry Research Program at The University of 

Montana’s Bureau of Business and Economic Research in Missoula, Montana. She received her B.A. degree 

in Rural & Environmental Sociology and is currently working towards her M.S. degree in Forestry, both at The 

University of Montana. 

Chuck Werstak is a Biological Scientist and a member of the Analysis Team with the Interior West Inventory 

and Analysis Program at the USFS Rocky Mountain Research Station in Ogden, Utah. He holds a B.S. degree 

in Geography from Western Illinois University and an M.S. degree in Geography from Utah State University.

Cover photo: Looking toward Glacier NP from the west side (photo by Renate 

Bush, Regional Inventory Specialist, USDA Forest Service, Northern Region).
Acknowledgments

The Rocky Mountain Research Station gratefully acknowledges the cooperation and assistance of the Northern Region, 

Forest Service, U.S. Department of Agriculture; the Montana State Forester and other Montana Department of Natural 

Resources and Conservation personnel; the Bureaus of Land Management and Indian Affairs; and the National Park 

Service, U.S. Department of the Interior. The authors extend a special note of thanks to the field staff who collected the 

inventory data and to private landowners who provided information and access to field sample plots.

Table of Contents

I. Introduction........................................................................................................................................ 1

II. Inventory Methods............................................................................................................................ 2

Plot Configuration ................................................................................................................................................ 2

Sample Design ................................................................................................................................................... 2

Three-Phase Inventory ........................................................................................................................................ 2

Sources of Error................................................................................................................................................... 4

III. Overview of Tables.......................................................................................................................... 5

IV. Overview of Montana’s Forest Resources.................................................................................... 6

Ecoregion Provinces of Montana......................................................................................................................... 6

Forest Land Classification ................................................................................................................................... 7

Forest Land Ownership ....................................................................................................................................... 8

Forest Type.......................................................................................................................................................... 8

Numbers of Trees .............................................................................................................................................. 13

Volume and Biomass......................................................................................................................................... 15

Forest Growth and Mortality .............................................................................................................................. 18

Stand Density Index (SDI)................................................................................................................................. 22

Quality Assurance Analysis................................................................................................................................ 24

V. Current Issues ................................................................................................................................ 28

Mountain Pine Beetle......................................................................................................................................... 28

Aspen Mortality.................................................................................................................................................. 28

Whitebark Pine Status ....................................................................................................................................... 32

Fire in Montana Forests..................................................................................................................................... 34

Old Growth Forests ........................................................................................................................................... 38

Noxious Weeds.................................................................................................................................................. 42

Snags as Wildlife Habitat................................................................................................................................... 43

VI. FIA Indicators ................................................................................................................................ 47

Forest Soil Resources ....................................................................................................................................... 47

Down Woody Material ....................................................................................................................................... 49

Damage to Live Trees........................................................................................................................................ 56

VII. Montana Timber Harvest and Forest Products Summary........................................................ 60

VIII. Conclusion................................................................................................................................... 63
IX. Standard Forest Inventory and Analysis Terminology.............................................................. 64

X. References...................................................................................................................................... 72

Tables in Body of this Report

Table 1: Total area (acres) by ownership class, land status, and forest land classification, 

Montana, cycle 2, 2003-2009.......................................................................................................................... 9

Table 2: Net volume (cubic-feet) and biomass (tons) per acre of live trees by common forest 

types on forest land, Montana, cycle 2, 2003-2009. ..................................................................................... 17

Table 3: Maximum SDI by forest type, Montana, cycle 2, 2003-2009................................................................ 23

Table 4: QA results for condition-level variables from 169 conditions in Montana, cycle 2, 2003-2009. ........... 26

Table 5: QA results for tree variables from 3471 trees in Montana, cycle 2, 2003-2009. .................................. 27

Table 6: Average elevation and DWM loadings by FIA survey unit with number of plots. Montana, 

cycle 2, subcycles 4-7, 2006-2009................................................................................................................ 51

Table 7: Average elevation and DWM loadings by forest type group and forest type with number 

of plots. Montana, cycle 2, subcycles 4-7, 2006-2009.................................................................................. 52

Table 8: Distribution of primary damage agents by agent group, Montana periodic (1988-2001) 

and annual (2003-2009) inventories. ............................................................................................................ 58

Appendix A: Inventory History.......................................................................................................... 77

Appendix B: Species Groups, Common Names, Scientific Names, and Timber (T) or 

Woodland (W) Designation for Trees ........................................................................................... 84

Appendix C: Forest Type Groups, Forest Type Names, and Timber (T) or Woodland (W) 

Designation for Forest Types........................................................................................................ 85

Appendix D: Volume, Biomass, and Site Index Equation Sources................................................ 86

Appendix E: Forest Resource Tables .............................................................................................. 87

Table 1: Percentage of area by land status. ...................................................................................................... 89

Table 2: Area of accessible forest land by owner class and forest land status.................................................. 90

Table 3: Area of accessible forest land by forest type group and productivity class.......................................... 91

Table 4: Area of accessible forest land by forest type group, ownership group, and land status. ..................... 92

Table 5: Area of accessible forest land by forest type group and stand-size class............................................ 93

Table 6: Area of accessible forest land by forest type group and stand-age class. ........................................... 94

Table 7: Area of accessible forest land by forest type group and stand origin................................................... 95

Table 8: Area of forest land by forest type group and primary disturbance class. ............................................. 96

Table 9: Area of timberland by forest type group and stand-size class.............................................................. 97

Table 10: Number of live trees on forest land by species group and diameter class......................................... 98

Table 11: Number of growing stock trees on timberland by species group and 

diameter class............................................................................................................................................... 99

Table 12: Net volume of all live trees by owner class and forest land status................................................... 100

Table 13: Net volume of all live trees on forest land by forest type group and stand-size class...................... 101

Table 14: Net volume of all live trees on forest land by species group and ownership group. ........................ 102

Table 15: Net volume of all live trees on forest land by species group and diameter class............................. 103

Table 16: Net volume of all live trees on forest land by forest type group and stand origin............................. 104

Table 17: Net volume of growing stock trees on timberland by species group and diameter class................. 105

Table 18: Net volume of growing stock trees on timberland by species group and ownership group. ............ 106

Table 19: Net volume of sawtimber trees (International 1/4 inch rule) on timberland by species 

group and diameter class............................................................................................................................ 107

Table 20: Net volume of sawtimber trees on timberland by species group and ownership group................... 108

Table 21: Average annual net growth of all live trees by owner class and forest land status. ......................... 109

ii
Table 22: Average annual net growth of all live trees on forest land by forest type group and 

stand-size class. ..........................................................................................................................................110

Table 23: Average annual net growth of all live trees on forest land by species group and 

ownership group. .........................................................................................................................................111

Table 24: Average annual net growth of growing stock trees on timberland by species group and 

ownership group. .........................................................................................................................................112

Table 25: Average annual mortality of all live trees by owner class and forest land status. .............................113

Table 26: Average annual mortality of all live trees on forest land by forest type group and 

stand-size class. ..........................................................................................................................................114

Table 27: Average annual mortality of all live trees on forest land by species group and 

ownership group. .........................................................................................................................................115

Table 28: Average annual mortality of growing stock trees on timberland by species group and 

ownership group. .........................................................................................................................................116

Table 29a: Aboveground dry weight (regional equation method) of all live trees by owner class 

and forest land status...................................................................................................................................117

Table 29b: Aboveground dry weight (component ratio method) of all live trees by owner class 

and forest land status...................................................................................................................................117

Table 30a: Aboveground dry weight (regional equation method) of all live trees on forest land 

by species group and diameter class...........................................................................................................118

Table 30b: Aboveground dry weight (component ratio method) of all live trees on forest land by 

species group and diameter class. ..............................................................................................................119

Table 31: Area of accessible forest land by Forest Survey Unit, county and forest land status. ..................... 120

Table 32: Area of accessible forest land by Forest Survey Unit, county, ownership group and 

forest land status......................................................................................................................................... 122

Table 33: Area of timberland by Forest Survey Unit, county and stand-size class. ......................................... 125

Table 34: Area of timberland by Forest Survey Unit, county and stocking class. ............................................ 127

Table 35: Net volume of growing stock and sawtimber (International 1/4 inch rule) on timberland 

by Forest Survey Unit, county, and major species group............................................................................ 129

Table 36: Average annual net growth of growing stock and sawtimber (International 1/4 inch rule) 

on timberland by Forest Survey Unit, county, and major species group..................................................... 131

Table 37: Sampling errors by Forest Survey Unit and county for area of timberland, volume, 

average annual net growth, average annual removals, and average annual mortality on timberland........ 133

Appendix F: Tables of Mean Soil Properties.................................................................................. 135

Appendix F Table 1a: Mean water, carbon, and nitrogen contents of forest floor and soil cores 

by forest type, Montana, soil visit 1, 2003-2007.......................................................................................... 136

Appendix F Table 1b: Mean water, carbon, and nitrogen contents of forest floor and soil cores 

by forest type, Montana, soil visit 2, 2008-2009.......................................................................................... 137

Appendix F Table 2a: Mean physical and chemical properties of soil cores by forest type, 

Montana, soil visit 1, 2003-2007. ................................................................................................................ 138

Appendix F Table 2b: Mean physical and chemical properties of soil cores by forest type, 

Montana, soil visit 2, 2008-2009. ................................................................................................................ 138

Appendix F Table 3a: Mean exchangeable cation concentrations in soil cores by forest type, 

Montana, soil visit 1, 2003-2007. ................................................................................................................ 139

Appendix F Table 3b: Mean exchangeable cation concentrations in soil cores by forest type, 

Montana, soil visit 2, 2008-2009. ................................................................................................................ 139

Appendix F Table 4a: Mean extractable trace element concentrations in soil cores by forest 

type, Montana, soil visit 1, 2003-2007. ....................................................................................................... 140

Appendix F Table 4b: Mean extractable trace element concentrations in soil cores by forest 

type, Montana, soil visit 2, 2008-2009. ....................................................................................................... 140

iii

USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 1

I. Introduction

This report contains highlights of the status of Montana’s forest resources, with 

discussions of pertinent issues based on the first 7 years of inventory under the 

new Forest Inventory and Analysis (FIA) annual system (Gillespie 1999). In 1998, 

the Agricultural Research Extension and Education Reform Act (also known as 

the Farm Bill) mandated that inventories would be conducted throughout United 

States’ forests on an annual basis. This annual system integrates FIA and Forest 

Health Monitoring (FHM) sampling designs resulting in the mapped-plot design, 

which includes a nationally consistent plot configuration with 4-fixed-radius subplots; a systematic national sampling design consisting of one plot in each approximately 6,000-acre hexagon; annual measurement of a proportion of permanent 

plots; data or data summaries within 6 months after yearly sampling is completed; 

and a State summary report after 5 years.

Interior West Forest Inventory and Analysis (IWFIA) implemented the new annual inventory strategy starting in Montana in 2003. The strategy for the Western 

United States involves measurement of 10 systematic samples (or subpanels) each 

of which represents approximately 10 percent of all plots in the State. Because the 

initial 5-year Montana report was delayed, the decision was made to use the most 

current available data.

The most recent periodic report for Montana (Conner and O’Brien 1993) was 

based on inventory data from 1989, and from other data sources for National Forest 

lands. Reserved areas were not inventoried. Because of differences in plot design, 

sampling intensity, and measurement and data compilation strategies, comparisons 

with past inventories are somewhat tenuous. Appendix A discusses in more detail 

the differences between the current inventory, the 1993 report, and the 1989 data 

available in the national FIA database.

Although nearly two-thirds of Montana is on the Great Plains, the western portion of the State contains the backbone of the Rocky Mountains, including a portion of the Continental Divide. West of the Continental Divide, Montana has a 

maritime-influenced climate, with higher precipitation and relatively warmer winters than the rest of the State. As a result, 80 percent or more of the land area is 

forested, with the highest tree diversity in the State. Species requiring moister site 

conditions—such as western larch, grand fir, western hemlock, western white pine, 

and western redcedar—are found here. The climate east of the Continental Divide 

is increasingly influenced by continental weather patterns, with a slightly lower 

proportion of forest land and less tree diversity in the mountains. Moving east, out 

of the mountains onto the Great Plains, forests and tree diversity decrease. On the 

eastern plains of the State, in areas with varied topography—such as the hills of the 

Powder River basin and the Missouri Breaks region—forests dominated by ponderosa pine and Rocky Mountain juniper occur. The distribution and composition 

of forests are determined by many factors such as elevation, aspect, soils, climate, 

and past fire history, and their influences are discussed in this report.

Annual inventory summaries are updated each spring to include the most recent 

subpanels of data available to the public. Data may be downloaded in table form 

or queried using a variety of online tools (http://fia.fs.fed.us/tools-data/default.

asp). After 2013, a full assessment of 10 subpanels of data will be included in the 

upcoming 10-year (full cycle) report. In 2013, the re-measurement phase of the 

inventory will begin by re-measuring the first subpanel of plot data collected in 

2003.
2 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

II. Inventory Methods

Plot Configuration

The national FIA plot design consists of four 24-foot radius subplots configured as a central subplot and three peripheral subplots. Centers of the peripheral subplots are located at distances of 120 feet and at azimuths of 360 degrees, 

120 degrees, and 240 degrees from the center of the central subplot (USDA Forest 

Service 2003-2009a). Each standing tree with a diameter at breast height (d.b.h.) 

for timber trees, or a diameter at root collar (d.r.c.) for woodland trees, 5 inches or 

larger is measured on these subplots. Each subplot contains a 6.8-foot radius microplot with its center located 12 feet east of the subplot center on which each tree 

with a d.b.h./d.r.c. from 1.0 -inch to 4.9 inches is measured.

In addition to the trees measured on FIA plots, data are also gathered about 

the stand or area in which the trees are located. Area classifications are useful for 

partitioning the forest into meaningful categories for analysis. Some of these area 

attributes are measured (e.g., percent slope), some are assigned by definition (e.g., 

ownership group), and some are computed from tree data (e.g., percent stocking).

To enable division of the forest into various domains of interest for analysis, it 

is important that the tree data recorded on these plots are properly associated with 

the area classifications. To accomplish this, plots are mapped by condition class. 

Field crews assign a number to the first condition class encountered on a plot. This 

condition is then defined by a series of discrete variables attached to it (i.e., land 

use, stand size, regeneration status, tree density, stand origin, ownership group, 

and disturbance history). Additional conditions are identified if there is a distinct 

change in any of the condition-class variables on the plot.

Sample Design

Based on historic national standards, a sampling intensity of approximately one 

plot per 6,000 acres is necessary to satisfy national FIA precision guidelines for 

area and volume. Therefore, FIA divided the area of the United States into nonoverlapping, 5,937-acre hexagons and established a plot in each hexagon using 

procedures designed to preserve existing plot locations from previous inventories. 

This base sample, designated as the Federal base sample, was systematically divided into a number of non-overlapping panels, each of which provides systematic 

coverage of the State. Each year the plots in a single subpanel are measured, and 

subpanels are selected on either a 5-year (eastern regions) or 10-year (western 

regions) rotating basis (Gillespie 1999). For estimation purposes, the measurement of each subpanel of plots can be considered an independent, equal probability 

sample of all lands in a State, or all plots can be combined to represent the State.

Three-Phase Inventory

FIA conducts inventories in three phases. Phase 1 uses remotely sensed data 

to obtain initial plot land cover observations (prefield) and to stratify land area in 

the population of interest to increase the precision of estimates. In Phase 2, field 

crews visit the physical locations of permanent field plots to measure traditional 

inventory variables such as tree species, diameter, and height. In Phase 3, field 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 3

crews visit a subset of Phase 2 plots to obtain measurements for an additional suite 

of variables associated with forest and ecosystem health. The three phases of the 

enhanced FIA program are discussed in the following sections.

Phase 1: Remotely sensed data in the form of aerial photographs, digital orthoquads, and satellite imagery are used for initial plot establishment. Each plot 

is assigned a digitized geographic location, and a human interpreter determines 

whether a plot has the potential to sample forest or other wooded land. Plot locations that are accessible to field crews and have the potential to sample forest or 

other wooded land are selected for further measurement via field crew visits in 

Phase 2.

The only remote sensing medium used for stratification in Montana was 2004 

MODIS satellite imagery. The spatial resolution of the MODIS imagery used was 

250 meters. Three strata were recognized: forest/other wooded land, nonforest 

land, and census water. Depending on geography and sampling intensity, geographic divisions are identified within a State for area computation and are referred 

to as estimation units. In Montana, individual counties served as the estimation 

units. The area of each estimation unit is divided into strata of known size using the 

satellite imagery and computer-aided classification. The classified imagery divides 

the total area of the estimation unit into pixels of equal size and assigns each pixel 

to one of H strata. Each stratum, h, then contains nh ground plots where the Phase 

2 attributes of interest are observed.

To illustrate, the area estimator for forest land for an estimation unit in Montana 

is defined as:

A A

n

n

n

y

g

hg

hg

ihg

h

H

i

hg

g Tg

n

1

1 = c

=

=

l

l /

/

where:

Ag ˆ = total forest area (acres) for estimation unit g

ATg = total land area (acres) in estimation unit g

H = number of strata (3)

n ́hg = number of Phase 1 points in stratum h in estimation unit g

n ́g = total number of Phase 1 points in estimation unit g

ythg = forest land condition proportion on Phase 2 plot i in stratum h in estimation 

unit g

nhg = number of Phase 2 plots in stratum h in estimation unit g

Phase 2: In Phase 2, field crews record a variety of data for plot locations sent 

to the field by Phase 1 (USDA Forest Service 2003-2009a). Before visiting privately owned plot locations, field crews consult county land records to determine 

the ownership of plots and then seek permission from private landowners to measure plots on their lands. The field crews determine the location of the geographic 

center of the center subplot using geographic positioning system (GPS) receivers. They record condition-level variables that include land use, forest type, stand 

origin, stand-size class, site productivity class, forest disturbance history, slope, 

aspect, and physiographic class. For each tree, field crews record a variety of 
4 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

variables including species, live/dead status, diameter, height, crown ratio, crown 

class, damage, and decay status. Office staff personnel apply statistical models 

using field crew measurements to calculate values for additional variables such 

as individual tree volume and per unit area estimates of number of trees, volume, 

biomass, growth, and mortality. The standard set of Phase 2 variables is collected 

by all FIA regions in a consistent manner. In addition to these national “core” 

variables, IWFIA collects data on additional forest attributes that regional stakeholders find informative and useful. These include understory vegetation cover 

and species dominance, noxious weeds, and down woody material. These data are 

collected through documented protocols on all accessible Phase 2 forested plots in 

the Interior West. These regional attributes are used in the “Noxious Weeds” and 

“Down Woody Material” sections of this report.

Phase 3: The third phase of the enhanced FIA program focuses on forest health. 

Phase 3 is administered cooperatively by the FIA program, other Forest Service 

programs, other Federal agencies, State natural resource agencies, universities, 

and the Forest Health Monitoring (FHM) program. Phase 3 is the ground survey 

portion of the Forest Health Monitoring (FHM) program and was integrated into 

the FIA program in 1999. The Phase 3 sample consists of a 1/16 subset of the 

Phase 2 plots, which equates to one Phase 3 plot for approximately every 95,000 

acres. Phase 3 measurements are obtained by field crews during the growing season and include an extended suite of ecological data (USDA Forest Service 2003-

2009b). Because each Phase 3 plot is also a Phase 2 plot, the entire suite of Phase 

2 measurements is collected on each Phase 3 plot at the same time as the Phase 3 

measurements. Phase 3 measurements include detailed assessments of tree crown 

condition, more detailed down woody material measurements, lichen diversity, 

and soil structure and chemistry. Phase 3 soil data are used in the “Forest Soil 

Resources” section of this report.

Sources of Error

Sampling error: The process of sampling (selecting a random subset of a population and calculating estimates from this subset) causes estimates to contain error 

they would not have if every member of the population had been observed and 

included in the estimate. The 2003-2009 FIA inventory of Montana is based on a 

sample of 10,711 plots systematically located across the State (a total area of 94.1 

million acres); a sampling rate of approximately one plot for every 8,785 acres.

The statistical estimation procedures used to provide the estimates of the population totals presented in this report are described in detail in Bechtold and Patterson 

(2005). Included with every estimate is an associated sampling error that is typically expressed as a percentage of the estimated value but that can also be expressed 

in the same units as the estimate or as a confidence interval (the estimated value 

plus or minus the sampling error). This sampling error is the primary measure of 

the reliability of an estimate. An approximate 67 percent confidence interval constructed from the sampling error can be interpreted to mean that under hypothetical 

repeated sampling, approximately 67 percent of the confidence intervals calculated 

from the individual repeat samples would include the true population parameter if 

it were computed from a 100-percent inventory. The sampling errors for State- and 

county-level estimates are presented in Appendix E table 37.

Users may compute statistical confidence for subdivisions of the reported data 

using the formula below. Because sampling error increases as the area or volume 

considered decreases, users should aggregate data categories as much as possible. 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 5

Sampling errors obtained from this method are only approximations of reliability 

because homogeneity of variances is assumed. The formula is:

SEs = SEt X

X

s

t

SEs = sampling error for subdivision of State total.

SEt

 = sampling error for State total.

Xs

 = sum of values for the variable of interest (area, volume, biomass, etc.) for 

subdivision of State total.

Xt

= sum of values (area, volume, biomass, etc.) for State total.

Measurement error: Errors associated with the methods and instruments used 

to observe and record the sample attributes are called measurement errors. On FIA 

plots, attributes such as the diameter and height of a tree are measured with different instruments, and other attributes such as species and crown class are observed 

without the aid of an instrument. On a typical FIA plot, 30 to 70 trees are observed 

with 15 to 20 attributes recorded on each tree. In addition, many attributes that 

describe the plot and conditions on the plot are observed. Errors in any of these 

observations affect the quality of the estimates. If a measurement is biased—such 

as tree diameter consistently taken at an incorrect place on the tree—then the estimates that use this observation (e.g. calculated volume) will reflect this bias. Even 

if measurements are unbiased, high levels of random error in the measurements 

will add to the total random error of the estimation process. A Quality Assurance 

Program is an integral part of all FIA data collection efforts to ensure that all FIA 

observations are made to the highest standards possible (see “Quality Assurance 

Analysis” in Section IV for more details).

Prediction error: Errors associated with using mathematical models (such as 

volume models) to provide information about attributes of interest based on sample attributes are referred to as prediction errors. Area, number of trees, volume, 

biomass, growth, removals, and mortality are the primary attributes of interest 

presented in this report. Area and number of trees estimates are based on direct 

observation and do not involve the use of prediction models; however, FIA estimates of volume, biomass, growth, and mortality use model-based predictions in 

the estimation process.

III. Overview of Tables

FIA is currently working on a revised National Core Table set that will expand 

the suite of tabled information to incorporate more of the core FIA Program, using 

both Phase 2 and 3 data (“core” refers to elements of data collection, compilation, and reporting that are consistent and required in all State’s FIA programs). 

Appendix E contains an interim set of tables supporting this report, using Montana 

annual data for the years 2003 through 2009. There are a total of 37 tables with 

statistics for land area, number of trees, wood volume, biomass (weight), growth, 

mortality, and sampling errors. Table 1 is the only table that includes all land types 

or land status; the rest are for accessible forest land or timberland. Table 37 shows 

sampling errors for area, volume, net growth, and mortality at the 67 percent confidence level. A complete listing of mean soil properties in Montana, organized by 
6 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

forest type, is in the Soil Indicator core tables in Appendix F. Additional tables in 

the text of this report that supplement specific sections are numbered consecutively 

as they appear, starting with table 1.

To avoid confusion with tables found in the body of this report and tables found 

in the appendices, appendix tables will be referred to beginning with the appendix 

letter (for example, Appendix E) followed by the table number. A list of all report 

tables and appendix tables with headings appears in the “Table of Contents.”

IV. Overview of Montana’s Forest Resources

Ecoregion Provinces of Montana

Issues and events that influence forest conditions often occur across forest types, 

ownerships, and political boundaries. As a result, scientists, researchers, and land 

managers must also find a way to assess and treat these issues in a boundary-less 

way. Ecoregions are often used as a non-political land division to help researchers 

study forest conditions. An ecoregion is a large landscape area that has relatively 

consistent patterns of physical and biological components that interact to form environments of similar productive capabilities, response to disturbances, and potentials for resource management (McNab and others 2007). Ecoregions are classed 

in a descending hierarchy of provinces, sections, and subsections.

Montana encompasses parts of five ecoregion provinces (Bailey 1995): 

(1) the Northern Rocky Mountain Forest-Steppe Province, (2) the Middle Rocky 

Mountain Steppe Province, (3) the Southern Rocky Mountain Steppe Province, 

(4) the Great Plains-Palouse Dry Steppe Province, and (5) a very small portion of 

the Intermountain Semi-Desert Province. All of these provinces contain forest land 

in Montana, differing in composition and extent. FIA uses the modifications to 

Bailey (1995) of McNab and others (2007) to assign plots to ecological provinces, 

sections, and subsections (fig. 1).

The Northern Rocky Mountain Forest-Steppe Province has a maritime-influenced 

climate, and has the lowest elevations of the three Rocky Mountain provinces. As 

a result of these and other influences, it has the highest proportion of forest area 

(83 percent forested) of Montana’s provinces. It is also the most diverse in respect 

to forest trees: moist site species like grand fir, western larch, mountain hemlock, 

western hemlock, and western redcedar are concentrated here, and nearly all of the 

conifer species found elsewhere in Montana are found here as well.

From the Northern Rockies through the Middle Rocky Mountain Steppe and 

to the Southern Rocky Mountain Steppe Provinces, climatic influences shift from 

maritime to continental, and elevation increases. Some of the tree species found 

predominantly in the Northern Rockies are present with a limited distribution in 

the Middle Rockies, and are absent in the Southern Rockies. Douglas-fir, lodgepole pine, Engelmann spruce, subalpine fir, and whitebark pine are common in 

these provinces.

Although the Great Plains-Palouse Dry Steppe Province is the most sparsely 

forested (6 percent forested) of Montana’s provinces, due to its large area it contains 13 percent of the State’s forest land. The forests are dominated by ponderosa 

pine and Rocky Mountain juniper.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 7

Forest Land Classification

Historically, FIA has used a nationally consistent standard for defining different categories of forest land. These categories were originally developed for the 

purpose of separating forest land deemed suitable for timber production from forest land that was either not suitable or unavailable for timber harvesting activity. 

The first division of forest land is unreserved forest land and reserved forest land. 

Unreserved forest land is considered available for harvesting activity where wood 

volume can be removed for timber products. Reserved forest land is considered 

unavailable for any type of wood utilization management practice through administrative legislation.

Unreserved forest land is further divided into timberland and unproductive forests. Timberland is forest land capable of producing 20 cubic feet of wood per acre 

per year of trees designated as a timber species and not withdrawn from timber 

production. Unproductive forests, because of species characteristics and site conditions, are not capable of producing 20 cubic feet of wood per acre per year of 

trees designated as a timber species and not withdrawn from timber production 

(see Section IX, “Standard Forest Inventory and Analysis Terminology”).

Reserved forest land can also be divided by productivity. Some characteristics that contribute to productivity can be visibly obvious, such as the presence or 

absence of non-commercial species, rocky substrates, and high elevation. While 

these distinctions may be important to reserved area management concerns, for example, their effect on visitor experience, wood production capability on reserved 

forest land is probably not the best way to discuss these issues.

Figure 1—Ecoregion provinces of Montana.
8 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

The State of Montana covers over 94 million acres (Appendix E table 1). 

Twenty-seven percent, or 25.6 million acres, of the area meets the definition of 

forest land. The remaining 64 percent or 68.5 million acres are classified as nonforest or water. Unreserved forest land accounts for 84 percent (21.5 million acres) 

of Montana’s forest land, with 92 percent of unreserved forest land classified as 

timberland, and only 8 percent classified as unproductive. Sixteen percent (4.1 million acres) of the forest land is reserved, with similar proportions of productive and 

unproductive forest land as in the unreserved portion.

Forest Land Ownership

Table 1 shows that although only 36 percent of Montana’s total land area is in 

the public domain (34.2 million acres: all Forest Service, other Federal, and State 

and local), this area includes 73 percent of the total forest land area (18.7 million 

acres). The National Forest Systems (NFS) contains the majority of forest land, at 

60 percent, or 15.4 million acres. Over 82 percent of NFS forest land is unreserved, 

with 79 percent (12.2 million acres) classified as timberland. Seventeen percent, or 

2.7 million acres, of NFS forest land is reserved.

Other public agencies managing large portions of Montana’s forest land are the 

Bureau of Land Management (BLM), with 1.2 million acres (69 percent timberland, 10 percent reserved), the State of Montana with 0.9 million acres (89 percent 

timberland, none reserved), and the National Park Service (NPS) with 0.9 million 

acres (no timberland, 100 percent reserved). The U.S. Fish and Wildlife Service 

(USFWS), local (county and municipal) governments, and other Federal agencies 

combined manage just less than 1 percent of Montana’s forest land. The proportion 

of total managed area that is forested is highest on NFS lands (87 percent) and NPS 

lands (82 percent).

Privately owned forest land totals 6.9 million acres, or 27 percent of the forest 

land. Montana’s private forest land owners consist of private individuals/families, corporations, and tribes, along with a few unincorporated groups or associations, and non-governmental conservation organizations. All private forest land is 

considered unreserved, with the exception of some tribal timber reserves. Half of 

the unreserved, unproductive forest land in Montana is privately owned. Figure 2 

shows the spatial distribution of FIA plots by ownership.

Forest Type

Forest type is a classification of forest land based on the species forming a plurality of living trees growing in a particular forest (Arner and others 2001). Forest 

types are aggregated into forest type groups, which may contain one or several forest types in a particular state. The distribution of forest types across the landscape 

is determined by factors such as climate, soil, elevation, aspect, and disturbance 

history. Many of these factors are captured in Montana’s ecoregion provinces. 

Forest type names may be based on a single species or groups of species. Forest 

types are an important measure of diversity, structure, and successional stage. Loss 

or gain of a particular forest type over time can be used to assess the impact of 

major disturbances such as fire, weather, insects, disease, and man-caused disturbances such as timber harvesting activity.

The most abundant forest type group in Montana is the Douglas-fir group, 

consisting of only one forest type in Montana. The Douglas-fir forest type covers 7.5 million acres and accounts for 29 percent of the forest land in the State, 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 

9

Table 1—Total area (acres) by ownership class, land status, and forest land classification, Montana, cycle 2, 2003-2009.

Owner class Forest land Total forest land Nonforest Water Total area

Not reserved Total not reserved Reserved

Timberland Unproductive

Forest Service

National Forest 12,239,635 471,423 12,711,058 2,688,863 15,399,921 2,211,138 101,080 17,712,139

Total Forest Service 12,239,635 471,423 12,711,058 2,688,863 15,399,921 2,211,138 101,080 17,712,139Other Federal

National Park Service -- -- -- 908,085 908,085 194,034 11,135 1,113,254Bureau of Land Management 851,623 256,111 1,107,734 123,882 1,231,616 6,483,645 -- 7,715,261Fish & Wildlife Service -- -- -- 186,915 186,915 764,273 239,722 1,190,909Other Federal -- -- -- 8,241 8,241 175,041 58,776 242,058

Total other Federal 851,623 256,111 1,107,734 1,227,122 2,334,856 7,616,992 309,633 10,261,481State and local government

State 825,472 103,140 928,612 -- 928,612 5,067,304 174,408 6,170,324Local 10,227 -- 10,227 -- 10,227 33,751 -- 43,979

Total State and local 835,700 103,140 938,839 -- 938,839 5,101,056 174,408 6,214,303Private

Undifferentiated private 5,947,519 803,984 6,751,503 165,672 6,917,176 52,648,592 353,113 59,918,881

Total private 5,947,519 803,984 6,751,503 165,672 6,917,176 52,648,592 353,113 59,918,881All owners 19,874,476 1,634,659 21,509,135 4,081,657 25,590,792 67,577,778 938,234 94,106,804
10 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

mostly in the Rocky Mountain ecoregion provinces. Second in abundance is the 

fir-spruce-mountain hemlock forest type group with 20 percent (5.0 million acres) 

of the forest land area. This group includes the Engelmann spruce, Engelmann 

spruce-subalpine fir, subalpine fir, grand fir, and mountain hemlock forest types. 

The subalpine fir forest type is the most abundant of these, with 45 percent of 

the area in the forest type group. The fir-spruce-mountain hemlock group occurs 

only in the Rocky Mountain ecoregion provinces, with the grand fir and mountain 

hemlock forest types concentrated in the Northern Rocky Mountain province. The 

lodgepole pine forest type/forest type group includes 17 percent (4.4 million acres) 

of forest land, primarily in the Rocky Mountain provinces. Ponderosa pine forest 

type/forest type group makes up 12 percent (3.0 million acres) of Montana’s forest land, but 53 percent of ponderosa pine forest is in the Great Plains province, 

although it occurs in the Rocky Mountain provinces as well. Figure 3A-D shows 

the spatial distributions of these four most abundant forest type groups.

The other western softwoods group, consisting of the whitebark pine, limber pine, 

and miscellaneous western softwoods (subalpine larch in Montana) forest types; and 

the western larch forest type/forest type group each cover 0.9 million acres.

Other forest type groups occurring in the inventory are the pinyon-juniper group 

(primarily Rocky Mountain juniper), the aspen-birch group, the hemlock-Sitka 

spruce group, the elm-ash-cottonwood group, the oak-hickory group, the woodland hardwoods group, and the alder-maple group.

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®0 25 50 100 150 200Miles

Plot ownership Federal ownership

NFS

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BLM

Counties

Water

!( NFS

!( NPS

!( BLM

!( USFWS

!( Other Federal

!( State

USFWS

Other Federal

!( Local

!( Private

Figure 2—Distribution of inventory plots by ownership, showing Federal land management, Montana, cycle 2, 2003-2009. Note: plot locations 

are approximate and some on private land are randomly swapped.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 11

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0 25 50

®100 150 200Miles

A - Douglas-fir forest type group

Forest types

!( Douglas-fir

Elevation

Under 2,000 feet

2,000 - 4,000 feet

4,000 - 6,000 feet

6,000 - 8,000 feet

8,000 - 10,000 feet

Over 10,000 feet

Ecoregion Province

Great Plains

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Middle Rocky Mountains

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0 25 50

®100 150 200Miles

B - Fir - Spruce - Mountain Hemlock forest type group

Forest types

!( Subalpine fir

!( Engelmann spruce-subalpine fir

!( Engelmann spruce

!( Grand fir

!( Mountain hemlock

Elevation

Under 2,000 feet

2,000 - 4,000 feet

4,000 - 6,000 feet

6,000 - 8,000 feet

8,000 - 10,000 feet

Over 10,000 feet

Ecoregion Province

Great Plains

Intermountain Semi-desert

Southern Rocky Mountains

Middle Rocky Mountains

Northern Rocky Mountains

Figure 3—Distribution of inventory plots for four major forest type groups by forest type, ecoregion province, and elevation, Montana, cycle 2, 

2003-2009. Note: plot locations are approximate and some on private land are randomly swapped.
12 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Figure 3—Continued.

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USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 13

Numbers of Trees

A measure of the numbers of live trees is needed in a variety of silvicultural, 

forest health, and habitat management applications. To be meaningful, numbers of 

trees are usually combined with information about the size of the trees. Younger 

forest stands are usually comprised of large numbers of small-diameter trees 

whereas older forest stands contain small numbers of large-diameter trees.

There are an estimated 12.0 billion live trees in Montana (Appendix E table 

10). Softwood species total 11.7 billion trees or 97 percent of the total (fig. 4). 

Nearly 66 percent of softwood trees are under 5.0-inches in diameter and over 

2 percent are 15.0-inches and larger in diameter. The true fir species group, consisting of subalpine fir and grand fir, is the most abundant species group accounting 

for 23 percent, or 2.8 billion trees, of the live trees. Next in abundance is lodgepole 

pine, comprising its own species group, at 2.7 billion trees. Third in abundance 

is another single- species group, Douglas-fir, with 2.6 billion trees. At 0.9 billion trees, Engelmann spruce (which entirely comprises the Engelmann and other 

spruces group) is the fourth most abundant species, followed by ponderosa pine 

(comprising the ponderosa and Jeffrey pine group) with 0.8 billion trees.

Figure 4—Number of live trees 1.0 inch diameter and greater by species group on forest land, Montana, cycle 2, 2003-2009.
14 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Next in abundance is the other western softwood species group at 0.7 billion 

trees. The other western softwoods group is a combination of whitebark pine, limber pine, mountain hemlock, pacific yew, and subalpine larch.

Following three other softwood species groups (western woodland softwoods, 

western larch, and western redcedar), the cottonwood and aspen group is the most 

abundant hardwood group with 0.25 billion trees. The group consists primarily 

of quaking aspen, but also includes black cottonwood, plains cottonwood, and 

narrowleaf cottonwood; and accounts for 2 percent of all trees, but 78 percent of 

hardwood trees. Seventy-six percent of hardwood trees are under 5.0-inches in 

diameter and 1.5 percent are 15.0-inches and larger in diameter.

Figure 5 shows numbers of live trees by diameter class for the three most 

abundant species groups in Montana. It shows the expected distribution of many 

smaller trees compared to larger trees, and also illustrates the differences in this 

distribution between species groups that are due to differing ecologies and life histories. For trees less than 5 inches diameter, the true firs are most dominant, with 

80 percent of the trees in those size classes compared to 61 percent of Douglasfirs and 56 percent of lodgepole pines. Lodgepole pines are dominant in the 5- to 

10.9-inch diameter classes, with 39 percent of the trees, compared to 27 percent of 

Figure 5—Number of live trees on forest land by three major species groups and diameter class, Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 15

Douglas-firs and 17 percent of true firs. Twelve percent of all live Douglas-firs are 

11 inches diameter and larger, while only 5 percent of lodgepole pines and 3 percent of true firs are that large.

On timberland (nonreserved and productive) in Montana, there are 3.2 billion 

live growing-stock trees 5.0-inches diameter and greater, of which lodgepole pine 

is the most common with 31 percent (Appendix E table 11). The next most abundant growing-stock species on timberland are Douglas-fir with over 28 percent, 

subalpine fir (in the true fir species group) with 11 percent, ponderosa pine with 

8 percent, Engelmann spruce with 7 percent, western larch with 4 percent, and 

whitebark pine (in the other western softwoods group) with over 3 percent.

There are an estimated one billion standing dead trees, or snags, at least 5.0-inches diameter on forest land in Montana, or an average of 39.7 snags per acre (this 

compares to 159.3 live trees per acre of these diameters). As with live trees, larger 

snags are less common than smaller snags, and often contribute more significantly 

to important forest landscape components such as wildlife habitat, nutrient cycles (including carbon), fire fuel loading, and soil formation. Considering snags 

11.0-inches diameter and larger, the average density is 8.3 per acre (compared to 

33.3 live trees per acre of this size). Very large snags, 19.0-inches diameter and 

larger, occur on Montana forests at about 1.1 per acre (3.8 live trees per acre of this 

size). Overall, the most common species for snags is lodgepole pine, which is also 

the most common in the 11.0-inches and over snag class. In the 19.0-inches and 

over class, the most abundant species for snags is Douglas-fir. Snag densities are 

calculated over all forest land in the State, and do not take into account irregular 

distributions of dead trees caused by localized mortality events like fires, insect 

outbreaks, and diseases. Densities may vary considerably when looked at by sublevels of forest land like ownerships, counties, or forest types.

Volume and Biomass

The amount of cubic-foot volume of wood in a forest is important for determining the sustainability of current and future wood utilization. The forest products 

industry is interested in knowing where available timber volume is located, who 

owns it, the species composition, and the size distribution. Estimates of gross and 

net volume include only the merchantable portion or saw-log portion (e.g., cubicfoot or board-foot) of trees, while biomass describes aboveground tree weight 

(oven-dry) by various components (merchantable bole and bark, tops and limbs, 

saplings). Net volumes are computed by deducting rotten, missing, or form defect 

from gross volume. Biomass estimates for this report are those obtained using 

IWFIA regional equations (Appendix E tables 29a and 30a), which are based on 

gross volumes and exclude foliage. These volume and biomass equation sources 

are documented in Appendix D. For comparison, biomass estimates using the FIA 

national component ratio method are presented in tables 29b and 30b. For explanation of the component ratio method, see Appendix J in Woudenberg and others 

(2010).

Appendix E tables 12 through 16 show net volume of live trees 5.0-inches diameter and greater on Montana forest land by various categories. The total net 

volume of wood in live and standing dead trees 5.0-inches diameter and greater on 

Montana forest land is 44.6 and 9.2 billion cubic-feet, respectively. Over 75 percent, or 33.7 billion cubic feet, is located on lands administered by National Forest 

System. Fifteen percent, or 6.5 billion cubic feet, is under private ownership. 

Seven percent, or 3.1 billion cubic feet is on lands administered by various Federal 
16 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

agencies other than the National Forest System. The remainder, about 1.3 billion 

cubic feet, is on lands administered by State and local governments.

The predominant species are Douglas-fir, which comprises 28 percent of 

the total live net cubic-foot volume, followed by lodgepole pine at 24 percent, 

Engelmann spruce at 14 percent, subalpine fir at 10 percent, and ponderosa pine at 

7 percent. Lodgepole pine comprises 35 percent of the total standing dead volume, 

followed by 16 percent for Dougas-fir, 15 percent for subalpine fir, 12 percent for 

whitebark pine, and 11 percent for Engelmann spruce (fig. 6). The total weight of 

oven-dry biomass in live (1.0 inches diameter and greater) and standing dead trees 

(5.0 inches diameter and greater) on Montana forest land is 870 and 200 million 

tons, respectively (fig. 7).

Another way to look at volume and biomass is by forest type, for which net volume and biomass per acre can be computed (table 2). These estimates include the 

different species that occur within each forest type. Because estimates for forest 

types with small samples may not be representative, only forest types sampled on 

at least 20 plots are included in this discussion. Western redcedar has the highest 

per-acre net volume of live trees 5.0 inches diameter and greater at 4,226 cubicfeet per acre, and the highest biomass of live trees 1.0 inches diameter and greater 

0.0 2.5 5.0 7.5 10.0 12.5 15.0

Douglas-fir

Lodgepole pine

Engelmann and other spruces

True fir

Ponderosa and Jeffrey pines

Western larch

Other western softwoods

Western redcedar

Western woodland softwoods

Western hemlock

Western white pine

Cottonwood and aspen

Other western hardwoods

Red alder

Western woodland hardwoods

Softwoods Hardwoods

Billion cubic feet

Species group

Live

Standing dead

Figure 6—Net cubic-foot volume of all live and standing dead trees 5.0 inches diameter and greater by species group on forest land, 

Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 17

0 50 100 150 200 250 300

Douglas-fir

Lodgepole pine

True fir

Engelmann and other spruces

Ponderosa and Jeffrey pines

Western larch

Other western softwoods

Western redcedar

Western woodland softwoods

Western hemlock

Western white pine

Cottonwood and aspen

Other western hardwoods

Western woodland hardwoods

Red alder

Softwoods Hardwoods

Million tons

Species group

Live (1" + dia)

Standing dead (5" + dia)

Figure 7—Oven-dry weight biomass of live and standing dead trees by species group on forest land, Montana, cycle 2, 2003-2009.

Table 2—Net volume (cubic-feet) and biomass (tons) per acre of live trees by common 

forest types on forest land, Montana, cycle 2, 2003-2009.

Forest type Net volume Biomass

Western redcedar 4,226 74.6

Engelmann spruce 3,038 48.2

Engelmann spruce-subalpine fir 2,998 52.6

Western larch 2,723 53.8

Grand fir 2,486 44.1

Lodgepole pine 2,211 41.9

Whitebark pine 1,906 36.9

Douglas-fir 1,836 38.9

Subalpine fir 1,669 32.2

Cottonwood 1,325 22.1

Ponderosa pine 964 20.9

Aspen 571 12.2

Limber pine 517 13.0

Rocky Mountain juniper 329 7.5

Nonstocked 59 1.3

 All types 1,742 34.0
18 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

at 74.6 tons per acre. Douglas-fir, the most common forest type in Montana, has 

about 1,836 cubic-feet per acre of volume and 38.9 tons per acre of biomass.

The net volume of growing stock trees on nonreserved productive timberland 

in Montana is 36 billion cubic feet (Appendix E table 17). Douglas-fir makes 

up 31 percent of the total growing stock volume, followed by lodgepole pine 

at 24 percent, Engelmann spruce at 12 percent, and subalpine fir and lodgepole 

pine, each with 9 percent. Appendix E table 19 shows the volume of sawtimber 

trees (International 1⁄4-inch rule) on nonreserved productive timberland at about 

149.5 billion board feet. Douglas-fir accounts for the majority of sawtimber at 

30 percent, followed by lodgepole pine at 18 percent, Engelmann spruce at 15 percent, and ponderosa pine at 10 percent. The total weight of oven-dry biomass in 

live trees 1.0 inches diameter and greater on nonreserved productive timberland 

land is 715 million tons (Appendix E table 29a). Although biomass is usually sold 

by green weight, the water content of wood is highly variable geographically, seasonally, and even across portions of a single tree. This makes live-tree inventory 

estimates of green biomass unreliable and potentially misleading.

Forest Growth and Mortality

Two common measures of forest vigor and sustainability are tree growth and 

mortality. Growth, as reported here, is the average annual growth volume calculated from a sample of tree increment core measurements based on the previous 

10 years of radial growth. Mortality, as reported here, is the average annual net 

volume of trees that have died in the 5 years prior to the year of measurement. The 

reason behind this growth and mortality estimation procedure in Montana is that 

the inventory data are limited to initial plot measurements. Complete remeasurement data for the State—where the status of the plot and all trees on the plot are 

known at two points in time—will not be available until all ten panels of data are 

completed and remeasurement begins in the eleventh year.

The relationship between growth and mortality quantifies the change in inventory volume over time. Net growth is gross, or total, growth minus mortality, which 

approximates the average annual change in inventory volume, but does not include 

the average annual volume removed through timber harvesting.

Net annual growth of all live trees 5.0 inches diameter and greater on Montana 

forest land totaled 289.8 million cubic feet while mortality totaled nearly 746.3 million cubic feet (Appendix E tables 22 and 25). Figure 8 illustrates the relationship 

between net growth and mortality by ownership group in Montana. Mortality of all 

trees on forest land administered by the National Forest System totaled 578 million 

cubic feet and exceeded net growth on this owner group by more than threefold. 

In contrast, net growth exceeded mortality on privately owned forests. Net growth 

totaled 126.9 million cubic feet on private forest land compared to 58.8 million 

cubic feet of mortality.

Figure 9 illustrates the relationship between net growth and mortality for the 

major species and species groups in Montana. Of the nine species and one species group listed, mortality exceeded net growth for five. A striking relationship 

between net growth and mortality occurred in lodgepole pine. The 252.6 million 

cubic feet of lodgepole pine mortality was over 25 times higher than the 10 million cubic feet of net growth. Whitebark pine—an important producer of food for 

wildlife in Montana and other States—actually recorded a negative net growth of 

–30.4 million cubic feet compared to 53.8 million cubic feet of mortality. Mortality 

of the true fir species group, consisting of grand fir and subalpine fir, totaled 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 19

Figure 8—Net annual growth and mortality of live trees on 

forest land by ownership group, Montana, cycle 2, 2003-2009.

138.5 million cubic feet compared to only 34.4 million cubic feet of net growth. 

Ponderosa pine, western larch, western redcedar, western hemlock, and aspen indicated positive relationships between net growth and mortality.

As mentioned in the “Introduction” and further explained in Appendix A, comparisons of current inventory estimates with previous inventories are tenuous. In 

previous inventories, reserved lands were not inventoried, sampling intensities varied, and data compilation strategies were different. However, general comparisons 

between current estimates of net growth and mortality and previous estimates do 

provide some historical perspective. For the current inventory, net annual growth 

of growing-stock trees averaged 361.5 million cubic feet and growing stock mortality averaged 492.1 million cubic feet on forest land defined as timberland. In the 

1989 inventory, net annual growth averaged 658.0 million cubic feet and mortality 

averaged 199.4 million cubic feet on forest land classified as timberland at that 

time (Conner and O’Brien 1993). Net growth also exceeded mortality in the 1979 

inventory (Green and others 1985) as well as in the inventory that occurred during 

the period between 1943 and 1949 on land defined as timberland (Hutchison and 

Kemp 1952). Despite the differences in inventory procedures over time, the 2003-

2009 inventory of Montana undoubtedly marks the first period since the State began inventories where mortality exceeded net growth.

Since high mortality is the driving force behind the large reductions in gross 

growth, further examination of this change component by other resource attributes 

can help explain the factors behind the high level of tree volume estimated to 

have died in the previous 5 years. Significant differences were observed in peracre estimates of mortality between major ownership groups and reserved status. 

Converting the State-level estimates of mortality into per-acre estimates removes Million cubic feet 300
20 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

the effect of differences in the amount of forest land administered by different 

ownership groups. Across all ownerships, the per-acre estimate of annual mortality 

volume averages 29.2 cubic feet per year on forest land. Mortality on reserved forest land was significantly higher than unreserved land. Average annual mortality 

on reserved land averaged 58.4 cubic feet per acre compared to 23.6 cubic feet per 

acre on unreserved forest land. Figure 10 illustrates per-acre estimates of mortality 

by two major owner categories and reserved status. Reserved forest land administered by private landowners, other Federal agencies, and State agencies recorded 

the highest average level of per-acre mortality at 59.3 cubic feet per acre followed 

by National Forest System’s lands classified as reserved at 58 cubic feet per acre.

Figure 11 illustrates per-acre estimates of mortality by reserved status and 

cause of death. All trees classified as mortality are assigned a cause of death in the 

field. Drawing conclusions from mortality estimates by cause of death should be 

done with caution. The actual agent that caused a tree’s death may be difficult, if 

not impossible, to determine. The cause of death category of other includes trees 

that have died due to reasons the field crews are unable to determine. Interactions 

between insects and diseases are complex and make identification of damaging 

agents difficult. Mortality due to fire accounted for the majority (46.9 percent) of 

total mortality. Insects were the second leading contributor to mortality, accounting for 34.5 percent of the total. Disease accounted for 13 percent. There was a 

very significant difference in the level of fire-caused per-acre mortality recorded 

on reserved forest land (fig. 11).

Figure 9—Net annual growth and mortality of live trees on forest land by species or species group, Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 21

Figure 10—Average annual per-acre mortality on forest land 

by two major owner categories and reserved status, Montana, 

2003-2009.

Figure 11—Average annual per-acre mortality 

on forest land by reserved status and cause of 

death, Montana, 2003-2009.
22 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

The high mortality resulted in a very significant reduction in gross growth for 

several species and species groups. Mortality is highest on forest land classified as 

reserved. Mountain pine beetle infestations are likely contributing to much of the 

lodgepole pine mortality. Lodgepole pine accounted for 57 percent of the mortality volume determined to be caused by insects. Trends in lodgepole pine mortality 

believed to have been caused by mountain pine beetle are examined in “Mountain 

Pine Beetle” in Section V.

Stand Density Index (SDI)

Stand density index (SDI; Reineke 1933) is a relative measure of stand density, 

based on quadratic mean diameter of the stand and the number of live trees per 

acre. In the western States, silviculturists often use SDI as one measure of stand 

structure to meet diverse objectives such as ecological restoration and wildlife 

habitat (e.g., Smith and Long 1987; Lilieholm and others 1994; Long and Shaw 

2005).

SDI is usually presented as a percentage of a maximum SDI for each forest type. 

Maximum SDI is rarely, if ever, observed in nature at the stand scale because the 

onset of competition-induced (self-thinning) mortality begins to occur at about 60 

percent of the maximum SDI. Average maximum density, which is used in normal 

yield tables and is equivalent to the A-line in Gingrich-type stocking diagrams 

(Gingrich 1967), is equal to approximately 80 percent of maximum SDI. There are 

several reasons why stands may have low SDI. Stands typically have low SDI following major disturbances, such as fire, insect attack, or harvesting. These stands 

remain in a low-density condition until regeneration fills available growing space. 

Stands that are over-mature can also have low SDI, because growing space may 

not be re-occupied as fast as it is released by the mortality of large, old trees. 

Finally, stands that occur on very thin soils or rocky sites may remain at low density indefinitely, because limitations on physical growing space do not permit full 

site occupancy. A site is considered to be fully occupied at 35 percent of maximum 

SDI. At lower densities, individual tree growth is maximized but stand growth is 

below potential, while at higher densities, individual tree growth is below potential 

but stand growth is maximized (Long 1985).

Originally developed for even-aged stands, SDI can also be applied to unevenaged stands (Long and Daniel 1990; Shaw 2000). Stand structure can influence 

the computation of SDI, so the definition of maximum SDI must be compatible 

with the computation method. Because FIA data include stands covering the full 

range of structure, the maximum SDIs are currently being revised for FIA forest 

types (Shaw and Long, in prep.). The provisional revised maximum SDIs, which 

are compatible with FIA computation methods, are shown in table 3. SDI was 

computed for each condition that sampled forest land using the summation method 

(Shaw 2000), and the SDI percentage was calculated using the maximum SDI for 

the forest type found on the condition.

The distribution of SDI values in Montana is relatively balanced. Figure 12 

shows that stands appear to be well-stocked, with over 52 percent of forest acres 

at least fully occupied (SDI equal to 35 percent or greater). The other 48 percent 

is relatively evenly distributed over the lower range of stocking. Over 19 percent 

of Montana’s forests are in the range where competition-induced mortality is expected (SDI equal to 60 percent or greater).

Stands with SDI between 35 and 60 percent of maximum SDI (full stocking 

zone) are desirable from a forest management perspective because that density 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 23

range maximizes stand growth and minimizes competition-induced mortality; 

other objectives, such as fuel reduction or maintenance of wildlife habitat characteristics, may warrant lower relative densities. The proportion of Montana’s forests 

in the full stocking zone (32.5 percent) is comparable to the proportions found 

in other interior Western States (Arizona, 25.2 percent; Colorado, 34.9 percent; 

Idaho, 32.7 percent; Utah, 32.0 percent). At 19.6 percent, the proportion of area 

in the competition mortality zone is about in the middle of the range found in other interior Western States (Arizona, 15.8 percent; Colorado, 25.3 percent; Idaho, 

14.4 percent; Utah, 20.0 percent). The proportion of acreage in this density range 

is likely to decrease over time because excessive density is considered a risk factor for many damaging agents. Several damaging agents, such as mountain pine 

beetle and spruce budworm, are currently active in Montana and are expected to 

disproportionately affect high-density stands. Management activities designed to 

reduce risks, such as thinnings and fuel reduction treatments, will also reduce the 

proportion of stands in high-density condition. At the same time, many lower-density stands should increase in relative density. Depending on the severity of insect 

infestations, the combined effects of growth, mortality, and management activities 

may lead to an eventual increase in the area of well-stocked forest land, or possibly 

an increase in the area of lower-stocked stands.

Table 3—Maximum SDI by forest type, Montana, cycle 2, 2003-2009.

Forest type Maximum SDI

182 Rocky Mountain juniper 425

184 Juniper woodland 385

201 Douglas-fir 485

221 Ponderosa pine 375

265 Engelmann spruce 500

266 Engelmann spruce / subalpine fir 485

267 Grand fir 475

268 Subalpine fir 470

270 Mountain hemlock 560

281 Lodgepole pine 530

301 Western hemlock 600

304 Western redcedar 630

321 Western larch 430

366 Limber pine 410

367 Whitebark pine 500

368 Misc. western softwoods 450

517 Elm / ash / black locust 458

703 Cottonwood 360

706 Sugarberry / hackberry / elm / green ash 504

709 Cottonwood / willow 420

901 Aspen 490

902 Paper birch 440

911 Red alder 445

974 Cercocarpus woodland 415

999 Unknown / nonstocked 475
24 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Quality Assurance Analysis

FIA employs a Quality Assurance (QA) Program to ensure the quality of all 

collected data. The goal of the QA program is to provide a framework to assure 

the production of complete, accurate, and unbiased forest information of known 

quality. Specific Measurement Quality Objectives (MQO) for precision are designed to provide a performance objective that FIA strives to achieve for every 

field measurement. These data quality objectives were developed from knowledge 

of measurement processes in forestry and forest ecology, as well as the program 

needs of FIA.

The practicality of these MQO, as well as the measurement uncertainty associated with a given field measurement can be tested by comparing data from blind 

check plots. Blind check data are paired observations where, in addition to the field 

measurements of the standard FIA crew, a second QA measurement of the plot is 

taken by a crew without knowledge of the first crew’s results (Pollard and others 

2006). The QA data for this analysis were collected between 2003 and 2009, in the 

same year as the standard field measurements, and then compared for measurement precision between two independent FIA crews’ observations. Therefore, for 

0 

500

1,000

1,500

2,000

2,500

Thousand acres

Percent of Maximum SDI

Free to grow zone

Canopy closure zone

Full stocking zone

Competition mortality zone

Figure 12—Distribution of stand density on Montana forest land, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 25

many FIA variables the data quality is measured by the repeatability of two independent measurements.

The results of the QA analysis for this reporting period are presented in tables 

4 and 5. Table 4 describes tolerances for condition-level variables, and table 5 describes tree-level variables. Tolerances are the “accepted” range of variability between two independent observations, for checking or comparison purposes. Each 

variable and its associated tolerance are followed by the percentage of total paired 

records that fell within one, two, three, and four times the tolerance. The last four 

columns show the number of times out of the total records the data fell outside the 

tolerance.

For example, table 5 shows that there were 3,358 paired records for the variable 

“d.b.h.” (diameter at breast height). At the 1X tolerance level, over 91 percent of 

those records fell within plus or minus one-tenth inch of each other, for each 20.0 

inches of d.b.h. observed. This percentage is referred to as the observed compliance rate. MQO for each variable consists of two parts: a compliance standard and 

a measurement tolerance, and can be compared to the observed compliance rate to 

determine that variable’s performance.

The information in tables 4 and 5 shows variables with varying degrees of repeatability. For example, one condition-level regional variable that appears fairly 

repeatable is “percent bare ground.” At the 1X tolerance level, its observed compliance rate was 94 percent for 146 paired observations that were within plus or 

minus 10 percent of each other. In contrast, the compliance rate for “habitat type 

1,” which has no tolerance variability, was only 62 percent for the same observations. Habitat types, often grouped in various ways, are an important variable for 

forest management. Accurate determination could provide an insight to successional status when combined with existing vegetation, such as tree numbers, size 

class, and species by habitat types or series, thus warranting further investigations 

into the potential repeatability issues associated with evaluating habitat types and/

or groups.

The tree-level variable “d.b.h.,” as mentioned above, is more repeatable when 

compared to the regional variable “tree age,” which has a 1X tolerance compliance 

rate of 18 percent. This is probably due to the difficulty of obtaining accurate tree 

ages. Several factors might affect inconsistent tree ages: (1) tree too large to reach 

the center, (2) rings too close or faded to read accurately, or (3) variation in age estimation when not hitting tree center (pith). Although not much can be done about 

the first two situations, QA data can be used to develop better field procedures for 

the last, especially for critical variables such as tree age.

As more blind check information becomes available, it might become apparent 

that a variable’s MQO needs to be adjusted accordingly to better reflect the realistic expectation of quality for that variable. As a result, MQO should be used not 

only to assess the reliability of FIA measurements and whether current standards 

are being met, but also to provide data collection experts with the information 

necessary to improve the current data collection system. This process can improve 

repeatability, or lead to elimination of variables that prove to be unrepeatable.
26 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Table 4—QA results for condition-level variables from 169 conditions in Montana, cycle 2, 2003-2009. Percentage of data within tolerance Number of times data exceeded tolerance Variable Tolerance @1x @2x @3x @4x @1x @2x @3x @4x Records Condition status No tolerance 99.4 1 169 Reserve status No tolerance 98.8 2 169 Owner group No tolerance 98.8 2 169 Forest type (Type) No tolerance 91.1 13 146 Stand size No tolerance 87.0 19 146 Regeneration status No tolerance 99.3 1 146 Tree density No tolerance 100.0 0 146 Owner class No tolerance 95.9 7 169 Owner status No tolerance 92.5 3 40 Stand age ±10 % 99.3 99.3 99.3 99.3 1 1 1 1 145 Disturbance 1 No tolerance 79.5 30 146 Disturbance year 1 ±1 yr 63.6 72.7 72.7 72.7 4 3 3 3 11 Disturbance 2 No tolerance 98.6 2 146 Disturbance year 2 ±1 yr Disturbance 3 No tolerance 100.0 0 146 Disturbance year 3 ±1 yr Treatment 1 No tolerance 95.9 6 146 Treatment year 1 ±1 yr 50.0 100.0 1 0 2 Treatment 2 No tolerance 99.3 1 146 Treatment year 2 ±1 yr Treatment 3 No tolerance 100.0 0 146 Treatment year 3 ±1 yr Physiographic class No tolerance 61.0 57 146 Present nonforest use No tolerance 95.0 1 20 Regional variables Percent crown cover ±10 % 83.6 99.3 99.3 99.3 24 1 1 1 146 Percent bare ground ±10 % 94.5 97.3 98.6 99.3 8 4 2 1 146 Habitat type 1 No tolerance 61.6 56 146 Habitat type 2 No tolerance 54.8 66 146
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 27 Table 5—QA results for tree variables from 3471 trees in Montana, cycle 2, 2003-2009. Percentage of data within tolerance Number of times data exceeded tolerance Variable Tolerance @1x @2x @3x @4x @1x @2x @3x @4x Records DBH ±0.1 /20 in. 91.5 96.8 98.2 98.7 285 107 61 44 3358 DRC ±0.1 /20 in. 52.2 59.3 64.6 70.8 54 46 40 33 113 Azimuth ±10 o 97.5 99.2 99.5 99.5 86 29 19 17 3471 Horizontal distance ±0.2 /1.0 ft 93.7 97.4 98.3 98.8 218 89 58 43 3471 Species No tolerance 98.8 41 3471 Tree status No tolerance 99.6 15 3471 Rotten/Missing cull ±10 % 95.3 98.2 99.1 99.6 146 56 28 11 3118 Total length ±10 % 80.9 94.2 97.7 99.0 662 200 80 33 3471 Actual length ±10 % 81.8 94.9 98.3 99.5 633 176 59 19 3471 Compacted crown ratio ±10 % 72.7 93.9 98.4 99.5 800 180 47 14 2932 Uncompacted crown ratio (P3) ±10 % 87.2 96.1 98.4 99.5 334 102 41 12 2611 Crown class No tolerance 81.9 530 2932 Decay class 100.0 0 524 Cause of death No tolerance 83.7 23 141 Mortality year No tolerance 61 141 Condition class No tolerance 99.1 30 3471 New tree Regional variables Mistletoe ±1 class 98.4 98.9 99.4 99.8 48 33 19 5 2932 Number of stems No tolerance 54.9 51 113 Percent missing top ±10 % 97.4 98.1 98.7 99.0 81 59 41 32 3118 Sound dead ±10 % 90.1 94.4 96.4 97.3 310 176 112 84 3118 Form defect ±10 % 93.6 97.1 98.0 98.3 159 73 50 43 2499 Current tree class No tolerance 151 3471 Tree Age ±5 % 18.0 23.4 35.1 48.6 91 85 72 57 111 DRC using IW MQO ±0.2 in/stem 90.3 92.0 96.5 97.3 11 9 4 3 113 Horiz Dist-timberland ±0.2 /1.0 ft 95.4 98.3 99.0 99.2 154 58 35 27 3358 Horiz Dist-woodland ±0.2 /1.0 ft 43.4 72.6 79.6 85.8 64 31 23 16 113
28 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

V. Current Issues

Mountain Pine Beetle

High tree mortality rates associated with mountain pine beetle infestations have 

become a serious issue in many western forests. Since the primary host of mountain pine beetle is lodgepole pine, and lodgepole pine comprises a significant component of many western North American forests, recent epidemics of this insect 

have raised significant concerns about the health, stand structure, and composition 

of lodgepole pine stands.

The mountain pine beetle is a native insect to western pine forests in North 

America and innocuous populations are almost always present in forests. Transition 

to epidemic populations is a function of the beetle’s capacity to locate, colonize, 

and reproduce within suitable host trees in a weather pattern conducive to overwintering survival, emergence, and dispersal (Caroll and others 2004). The reasons behind the recent outbreaks have received considerable discussion. Most bark 

beetles prefer to invade trees that are in poor physiological condition (Rudinsky 

1962). Temperature is known to influence insect outbreaks, especially species such 

as the mountain pine beetle (Amman 1973). Because of the recent interest in climate change, the effect of global warming is believed by some researchers to be a 

contributing factor in the severity of mountain pine beetle infestations (Logan and 

others 2003). Another significant factor is the presence of large areas of lodgepole 

pine stands comprised of ideal host trees homogeneous in age, composition, and 

structure.

Figure 13 illustrates the average annual volume of lodgepole trees killed by insects by measurement year in Montana. The estimates in figure 13 illustrate a moving average trend that accumulates information from successive annual inventory 

measurements. The assumption is that most of the lodgepole classified as mortality 

and assigned a cause of death of insects is due to the mountain pine beetle. It is 

clearly evident that a pronounced upward trend has occurred during the 7 years of 

annual inventories in Montana. As of 2009, the average annual volume of insectkilled lodgepole pines is 121 million cubic feet, which is nearly five times higher 

than the average of 25 million cubic feet recorded in 2003.

Aspen Mortality

Aspen is the widest-ranging species in North America. It is present in all States 

in the Interior West and occupies a wide elevational range from 2,000 ft in northern 

Idaho to 11,700 ft in Colorado. It is also found on a wide range of sites, and occurs 

in 26 of the forest types that occur in the Interior West. The species is intolerant of 

shade and relatively short-lived, which makes it prone to replacement by conifers 

through successional change. In the Interior West, it also reproduces infrequently 

by seeding, relying mostly on root sprouting for reproduction. However, aspen 

responds well to fire and cutting, and it is able to dominate heavily disturbed sites 

for many years following severe disturbance. In addition, there is some evidence 

that aspen is able to persist in conifer-dominated forests by exploiting gaps in the 

conifer canopy that are caused by insects, disease, windthrow, and other smallerscale disturbances.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 29

0

20

40

60

80

100

120

140

2003 2003-04 2003-05 2003-06 2003-07 2003-08 2003-09

Million cubic feet

Measurement years

Figure 13—Moving average estimate of average annual volume of lodgepole pine killed by insects by measurement years, Montana, 

cycle 2, 2003-2009.

In recent years there has been concern about the future of aspen on the landscape, primarily due to the characteristics of aspen and how they relate to changes 

in disturbance regimes. The earliest concerns were related to successional change 

in the Interior West, where fire suppression has decreased disturbance rates and, as 

a result, aspen regeneration rates. In addition, it has been shown that large populations of herbivores can inhibit aspen regeneration where it occurs spontaneously or 

after disturbance (e.g., Hessl and Graumlich 2002). The lack of disturbance allows 

conifers to gain dominance where they are present, and in pure aspen stands, consumption of regeneration by ungulates could lead to loss of senescing overstory 

trees without replacement. More recent concerns are related to a period of drought 

that has an impact on aspen and other forest types (e.g., Shaw and others 2005; 

Thompson 2009). Drought appears to have contributed to mortality in many lowelevation stands (Worrall and others 2008); in some of these stands, regeneration 

is either lacking or suppressed by herbivores.

Johnson (1994) suggested that the acreage of aspen-dominated stands had 

declined as much as 46 percent in Arizona since the 1960s, with most of these 

acres becoming dominated by mixed conifer forest types. Bartos (2001) suggested that similar changes—aspen acres decreasing by 64 percent—had occurred in 

Montana. These assessments of “lost” aspen acres were based on the assumption 

that forested acres with a minority aspen component were, at one time in the recent 

past, dominated by aspen in pure, or nearly pure, stands. This assumption may not 

be reasonable because there are many situations where aspen may persist normally 

as a minor stand component.
30 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

It is not possible to estimate trends in the aspen forests of Montana with great 

certainty because of differences between the coverage of periodic and annual inventories (see Appendix A: Inventory History). However, it is possible to make a 

limited set of comparisons when looking at certain characteristics that are indicative of aspen status, such as the proportion of aspen acreage to total forest acreage, 

number of acres with only dead aspen present, and number of acres with aspen 

reproduction present.

Current inventory data show that there are just nearly 450,000 acres of the aspen 

forest type in Montana, as compared to over 263,000 acres found during the previous inventory. When considering all acres where aspen is present, the current inventory data show that at least one live aspen stem is present on over 791,000 acres, 

while the previous inventory showed live aspen present on just over 671,000 acres.

Statistics on live trees may overlook “relict” aspen stands, and both inventories show that some stands had only dead aspen present at the time of inventory. 

The 1990s periodic inventory showed that only dead aspen 1.0 inch diameter and 

greater were found on approximately 34,000 acres, or about 4.6 percent of all 

acres with aspen present. The current inventory shows an apparent increase to over 

65,000 acres, or about 7.6 percent of all acres with aspen present. However, when 

seedling-sized trees are taken into account the area with only dead aspen decreases 

substantially, and there are many more acres where only aspen seedlings (or suckers) are recorded. Of the plots where aspen is only found as seedlings or suckers, 

disturbances such as fire are frequently recorded (see “Fire in Montana’s Forests” 

in Section V).

Another way to compare the previous and current inventories is to normalize 

data on a common basis, for example, basal area per acre. During the 1990s periodic inventory in aspen-dominated stands (aspen forest type), the average basal 

area per acre of all aspen (live and standing dead) was just over 68 square feet per 

acre, with nearly 62 square feet per acre in live aspen. In the current annual inventory, aspen-dominated stands averaged just over 42 square feet of live and dead 

aspen basal area, with just under 37 square feet per acre of live aspen. The results 

are similar for all stands with an aspen component of trees at least 1 inch diameter. 

Total aspen basal area in these stands averaged just over 34 square feet of basal 

area in the periodic inventory, with about 31 square feet of basal area in live aspen. 

As with the aspen-dominated acres, the numbers were lower in the annual inventory: nearly 29 square feet per acre of live and dead aspen, and slightly more than 

24 square feet of live aspen. These figures suggest that live aspen basal area has 

fallen approximately 40 percent on a per-acre basis since the periodic inventory. 

However, it is not yet possible to tell if this is a real decrease possibly caused by 

successional changes and disturbances or an apparent increase that may have been 

caused by capturing a high proportion of regenerating aspen acres in the annual 

inventory that were not captured in the periodic inventory.

In contrast with apparent trends in live aspen stocking, mortality rates do not 

appear to be increasing in recent years, at least in comparison to the mortality 

rates observed during the periodic inventory. Mortality is expressed here as the 

proportion of basal area estimated to have died in the 5 years prior to the plot visit. 

During the 1990s periodic inventory, mortality was estimated at almost 7 percent 

in aspen-dominated stands and over 6 percent in stands with an aspen component. 

This equates to an average annual mortality of about 1.3 percent. During the annual inventory, mortality was estimated at 4 percent in aspen-dominated stands and 

less than 4 percent in stands with an aspen component. This equates to an average 

annual mortality of about 0.8 percent. Because the annual inventory is spatially 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 31

unbiased over time, it is possible to look at year-by-year mortality estimates for 

possible trends. Figure 14 shows the mortality estimates for annual inventory 

years 2003-2009. Although the annual trend data might be somewhat noisy due to 

small sample size within any given year, it does not appear that there has been any 

substantial change in mortality rates since 2003. Individual annual estimates vary 

about the 7-year average.

Comparisons between the mid-1990s periodic inventory results and the current annual inventory data in Montana give somewhat conflicting results, so aspen 

trends are difficult to interpret at this point in the inventory. Total acreage with 

aspen present appears to be somewhat higher than in the 1990s, but the aspen component appears to have decreased when considered on a basal area per acre basis. 

Several disturbance agents, including fire and drought, have apparently reduced 

aspen basal area. However, there are a substantial number of plots with aspen reproduction present. On many of these plots there are no large, standing live or dead 

aspen, so it is difficult to ascertain whether these plots are capturing re-occupation 

of the sites by aspen or expansion of aspen into other forest types. However, continued monitoring of these plots in the future will tell whether or not the young 

aspen reproduction is able to persist.

Figure 14—Estimated 5-year mortality rates for individual measurement years and average 5-year mortality for all annual inventory years 

(2003-2009) of aspen in Montana, cycle 2, 2003-2009.

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

2002 2003 2004 2005 2006 2007 2008 2009 2010

Aspen mortality

Inventory year

Mort Pct

Avg Mort Pct

Mortality percent

Average mortality percent
32 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

There have been many studies that have shown aspen to be in decline at local 

scales (e.g., Bartos and Campbell 1998; Di Orio and others 2005; Worrall and others 2008), while other analyses have shown increased dominance of aspen in some 

landscapes (Kulakowski and others 2004). It is not surprising that studies documenting loss are more numerous, because unexplained or unexpectedly high mortality events tend to attract the attention of managers, researchers, and the public. 

Because these changes are evident to a wide range of observers, there is a tendency 

to extrapolate local conditions to larger areas. Aspen is found in many forest types 

with a wide variety of associate tree species, so the characteristics of aspen-dominated stands and stands with aspen as a minor component vary considerably over 

the range of the species. This makes generalization difficult. In addition, local or 

regional trends may differ from those of the population as a whole, because agents 

like drought and fire are not regularly distributed over the landscape. However, 

with continued monitoring under the annual inventory system, FIA will be able to 

assess regional- and population-scale trends in aspen.

Whitebark Pine Status

Whitebark pine has become recognized as an important component of highelevation ecosystems in western North America. Its periodic crops of large wingless seeds provide a major food source for several species of birds and mammals 

including the black bear and grizzly bear (Schmidt and McDonald 1990). Wildlife 

biologists have noted that for several months after production of a large whitebark 

pine cone crop, bears concentrate their feeding on cone caches made by squirrels 

and tend to stay away from lower elevation encounters with humans and their habituations (Kendall 1980). Whitebark pine aids in the protection of watersheds by 

stabilizing soil and rock on the harshest sites and by catching and retaining snowpack (Arno and Hoff 1989).

Compared to other conifer species in Montana, whitebark pine is relatively 

uncommon. Whitebark pine forest types comprise about 679 thousand acres in 

Montana or about 2.7 percent of total forest area in the State. The number of all 

live whitebark pine trees 1.0-inches d.b.h. and larger totals 491 million trees in 

Montana or about 4 percent of all live trees in the State.

In many areas in the West, whitebark pine stands have experienced heavy mortality (Arno 1986). The principal agents named in the decline are white pine blister 

rust (Cronartium ribicola), mountain pine beetle (Dendroctonus ponderosae), and 

successional replacement by shade-tolerant trees in the absence of fire.

To address the decline issue in whitebark pine in Montana, an analysis of longterm trends was performed using remeasurement data from permanently established FIA plots. In the previous 1988 to 1998 periodic inventories of Montana, 

field plots used a variable-radius tree sampling design. When the annual inventory 

began in 2003, IWFIA changed the sampling design to the fixed-radius national 

mapped-plot design. In addition to the initial establishment of the mapped plot, 

field crews were instructed to relocate and remeasure trees tallied on the previously 

established variable-radius plot. All trees measured in the previous inventory (time 

1) were accounted for and current status recorded (live, dead, cut) in the current 

inventory (time 2). This remeasurement and accounting for trees on previously 

established plots provides an accurate measure of growth, removal, and mortality 

rates since the status of trees are known at both points in time. The procedures used 

to remeasure the previous variable-radius plot and a description of the plot layout 

is described in USDA Forest Service 2011.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 33

Remeasurement of permanent FIA plots can produce estimates of change that 

quantify the net change in inventory between two points in time. For this analysis, 

mean basal area per acre of whitebark pines 5.0-inches d.b.h. and larger was the 

attribute of interest. The following components were generated for the analysis:

• Initial Inventory—Basal area/acre of live whitebark pines 5.0 inches d.b.h. and 

larger measured at the previous visit.

• Survivor growth—Change in basal area/acre of live whitebark pine trees 

5.0 inches d.b.h. and larger measured at the previous visit and the basal area/

acre of live whitebark pine trees 5.0 inches d.b.h. and larger measured at the 

second visit.

• Ingrowth—Basal area/acre of live whitebark pine trees 5.0 inches d.b.h. and 

larger at time of second visit but were less than 5.0 inches d.b.h. at time of previous visit (trees that grew on to the inventory during the remeasurement period).

• Mortality—Basal area/acre of live whitebark pine trees 5.0 inches d.b.h. and 

larger measured at the previous visit that was dead due to natural causes at time 

of second visit.

• Removals—Basal area/acre of live whitebark pine trees 5.0 inches d.b.h. and 

larger measured at the previous visit that was cut at time of second visit.

• Terminal Inventory—Basal area/acre of live whitebark pines 5.0 inches d.b.h. 

and larger measured at the second or current visit.

For this analysis, only remeasured plots where at least one live whitebark pine 

5.0 inches d.b.h. and larger was measured in the initial inventory were selected. 

A total of 199 remeasured plots in Montana met the criteria. The initial inventory 

measurement years ranged from 1988 to 1998. The terminal inventory measurement years ranged from 2003 to 2009. Plots measured prior to 1991 were on nonNational Forest Systems (NFS) land and those measured after 1990 were on NFS 

land. The average interval between plot measurements was 10.4 years. The procedure used to estimate the basal area per acre for the six components is described in 

Beers and Miller 1964.

Mean basal area per acre of whitebark pine for the six change components are 

illustrated in figure 15. Mean basal area per acre of whitebark pine in Montana 

decreased 22 percent or by about 2.2 percent per year. Mortality reduced the estimate of initial inventory by 27 percent. Mortality rate of whitebark pine averaged 

2.6 percent per year. The leading cause of death of the whitebark pines classified as 

mortality was disease, which accounted for 38 percent of the trees that died during 

the remeasurement interval. The second leading cause of death was attributed to 

insects at 29 percent. Fire accounted for 23 percent of the whitebark pine mortality.

These results indicate a very significant decline in live basal area of whitebark 

pine. The annual level of mortality is currently outpacing the combined annual 

basal area growth of survivor trees and ingrowth trees. Similar studies conducted 

in the early 1970s in western Montana also indicated significant basal area reductions in whitebark pine due to heavy mortality (Keane and Arno 1993). Figure 16 

illustrates the numbers of live whitebark pine trees by diameter class. Numbers of 

2- and 4-inch whitebark pines comprise 62 percent of all live whitebark pines in 

Montana. The high proportion of sapling-size trees might suggest enough regeneration is occurring to offset losses due to mortality in the larger diameter classes. 

However, blister rust can cause mortality and top kill in whitebark pine seedlings 

and saplings resulting in fewer saplings reaching maturity. Blister rust incidence is 

particularly high in southwestern Montana (Kegley and others 2011). Whitebark 
34 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

pine is a slow-growing tree. Depending on site conditions, the tree can attain small 

to moderately large size after 250 or more years, but may start producing cones as 

early as 70 years old.

This analysis underscores the need to use broad-scale inventory data for monitoring trends in whitebark pine. The power to detect significant effects related to 

whitebark pine mortality and other parameters of interest will increase substantially with estimates derived from the remeasurement (paired) plots that will be 

available as the IWFIA region begins to accumulate data from remeasured plots.

Fire in Montana Forests

Fire is an important disturbance in Montana forests. In some forest types, like 

ponderosa pine, fire can maintain open stands and promote grasses and forbs 

growth in the understory. For other forest types, such as aspen and lodgepole pine, 

fire plays an important role in stand regeneration. In some areas, a century of fire 

suppression has led to a buildup of fuels and stand densification. In these areas 

there can be uncharacteristically intense fires. Some areas that are intensely burned 

may experience slow regeneration, but others may recover relatively quickly. 

0 

10

20

30

40

50

60

Initial 

Inventory

Survivor 

Growth

Ingrowth Mortality Removals Terminal 

Inventory

Basal Area/acre (sq. ft.)

Figure 15—Periodic estimates of initial 

inventory, terminal inventory, and change 

components for whitebark pine in Montana 

expressed as mean basal area per acre for 

remeasured plots.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 35

0	
  

50	
  

100	
  

150	
  

200	
  

250	
  

1.0-­‐2.9	
   3.0-­‐4.9	
   5.0-­‐6.9	
   7.0-­‐8.9	
  9.0-­‐10.9	
  	
   11.0-­‐12.9	
  	
   13.0-­‐14.9	
  	
   15.0-­‐16.9	
  	
   17.0-­‐18.9	
  19.0+	
  

Million	
  trees	
  

Diameter	
  class	
  (inches)	
  

Figure 16—Numbers of live whitebark pines by diameter class in Montana, cycle 2, 2003-2009.

For example, the area inside the boundary of the large 1910 fires in Idaho and 

Montana (Cohen and Miller 1978; Pyne 2008; Egan 2009) now carries about the 

same amount of live tree volume per acre as areas outside the fires, although the 

mean stand age is somewhat lower and the volume is generally distributed among 

smaller trees (Wilson and others 2010).

Assessment of fire effects without a complete cycle of FIA data is not straightforward. During the period covered by this report there were many fires in Montana. 

Some FIA plots within fire boundaries were measured before the fire occurred in 

that area and some were measured after. As a result, within the perimeter of a large 

fire there may be pre- and post-fire data, or a plot within the perimeter of a small 

fire may represent only pre-fire conditions. This means that normal data compilation methods cannot be used without introducing some element of temporal bias—

that is, plots measured earlier in the inventory will tend to underestimate the effect 

of fire because they might have been affected by fire after they were measured. 

These limitations on analysis will be reduced as the current inventory cycle is 

completed and remeasurement data are acquired during the next cycle. However, 

there are some general analyses that can be conducted with the current data. These 

results should be considered preliminary.

We used data from the Monitoring Trends in Burn Severity (MTBS) project, 

which is an interagency effort being conducted and maintained by the USDA 

Forest Service Remote Sensing Applications Center and the U.S. Geological 

Survey National Center for Earth Resources Observation and Science (EROS). 
36 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

The purpose of the MTBS project is to consistently map the burn perimeters and 

severity of fires across all lands of the United States. The multi-year project was 

designed to “assesses the frequency, extent, and magnitude (size and severity) of 

all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in 

the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for 

the period of 1984 through 2010 (Eidenshenk and others 2007). The analysis presented here is based on burned area perimeters of wildland fires identified by the 

MTBS program between 2003 and 2009 and FIA plot data for the corresponding 

period in Montana.

MTBS data showed 238 fires and fire complexes (hereafter, fires) burned 

2.48 million acres in Montana between 2003 and 2009. The size of these fires 

ranged from just a few acres to over 200,000 acres, with an average of 10,403 acres. 

Forested plots measured during the same period occurred within the boundaries 

of 74 of the fires. The remaining 164 fires encompassed only non-forested plots, 

encompassed plots that have not yet been measured on the current cycle, or did 

not encompass an FIA plot location. The largest fire—the Derby Fire, at 201,000 

acres—encompassed 12 forested conditions. The area expansion estimated by 

these conditions is just over 108,000 acres, which indicates that just over half of 

the Derby Fire burned forested areas. The other four fires that were over 100,000 

acres only encompassed two to six forested conditions each, which translates to 

about 20 to 30 percent of these fires burning forested land. The sixth largest fire 

(Chippy Creek) covered almost 96,000 acres according to the MTBS fire perimeter, but it encompassed the highest number (13) of forested conditions. The plotbased area estimate for these 13 conditions is slightly higher (103,000 acres) than 

the MTBS area estimate, illustrating the sampling noise that is inherent in small 

area estimation. However, the fact that there is less than 10 percent difference suggests that all or most of the Chippy Creek fire involved forested land. The average 

number of forested plots within a sampled fire boundary was just over 2.5, and 

about half of the fires that were sampled by FIA plots encompassed only one plot. 

Although the plot-based and MTBS-based acreage estimates for smaller fires can 

be similar, it is not appropriate to draw inference about the mixture of forest and 

nonforest for small, individual fires. At this point in the inventory, the scaling factor for a single plot is approximately 10,000 acres, which is larger than most of the 

fires in the MTBS database. As a result, the proportion of burned area in forest vs. 

nonforest must be done by aggregating a large number of plots and burned area.

Given that population-scale estimates are difficult to produce with a partial inventory, another way to look at the data is to examine per-acre estimates. There 

were 2482 forested conditions measured in Montana between 2003 and 2009. Of 

these, 2262 were located outside the MTBS fire boundaries and 220 were located 

inside (fig. 17). Of the 220 located inside, 117 were measured prior to the fire in 

which they were located and 103 were measured after the fire. Conditions located 

outside the burned areas had an average of 119 square feet of basal area per acre 

in live and dead trees, with 97 square feet of that in live trees. Conditions within 

the burned areas that were measured before the fires occurred averaged 116 square 

feet of total basal area per acre and 89 square feet per acre of live trees. While 

the unburned conditions within the fires appear to have slightly less basal area 

than conditions outside the burned areas, the ratio of live basal area to total basal 

area (live + dead) was similar for both groups (81 percent and 77 percent respectively). This would suggest that the burned areas did not have extraordinarily large 

amounts of standing dead trees prior to the fires, but the lower standing basal area 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 37

might indicate that the stands were more open or that there was more down wood 

in these stands.

When comparing within-fire pre-burn conditions to within-fire post-burn conditions, it is possible to estimate the proportion of trees killed within burned areas. 

Conditions located within fire boundaries and measured after the fires averaged 

104 total square feet of basal area per acre, with only 40 square feet of basal area 

remaining in live trees. The lower average total basal area found in within-fire 

post-burn conditions as compared to within-fire pre-burn conditions (104 vs. 116 

sq. ft. per acre) is consistent with the expectation that fire would result in some 

basal area being consumed and/or falling down. Likewise, the lower ratio of live 

to total basal area (39 percent) is consistent with the expectation that only partial 

mortality of trees located within the fire boundaries would occur. If it is assumed 

that the pre-burn conditions are representative of the post-burn conditions, then it 

would appear that the average fire-caused mortality was about 50 square feet per 

acre, or about 55 percent of the pre-fire live basal area.

One of the potential beneficial effects of fire is the stimulation of aspen regeneration. Although there are only about 708,000 acres of the aspen forest type 

in Montana, approximately 1.5 million acres have some aspen component (see 

“Aspen Mortality” in Section V). Of the 191 conditions measured with some 

Figure 17—FIA plot locations and MTBS fire perimeters, showing plot status and measurement relative to the time of fires for plots inside fire 

perimeters, Montana, cycle 2, 2003-2009. Note: plot locations are approximate and some on private land are randomly swapped. Forested 

plots may include multiple forest conditions or nonforest conditions.
38 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

aspen component, only six were located within MTBS fire boundaries and only 

one was measured after the fire had burned. Although this sample is very small, it 

suggests that the number of potentially fire-disturbed acres with aspen present is 

around 51,000 acres, or about 3.3 percent of all acres with an aspen component. 

Converting this figure to an annual rate and assuming that fire will be evenly distributed over time and area, it implies that it would take approximately 210 years 

for all acres with aspen present to be disturbed by fire. This rate may be lower than 

would be necessary to maintain aspen across the Montana landscape, but it will 

only be possible to establish long-term trend with continued monitoring.

The analysis in this section should be considered only a first approximation 

of fire effects on Montana forests. Although the results are generally consistent 

with expectations, the magnitude of fire-related mortality cannot be stated with 

precision at this point in the inventory. However, the data confirm that within fire 

boundaries there has been only partial mortality. Additional data and analysis will 

be required to determine whether, for example, mortality is more-or-less evenly 

distributed among plots within the burned areas or mortality tends to be all-or-none 

at the plot scale. Remeasurement data will be necessary to confirm the portions of 

standing live and dead trees that are consumed by fire and converted to the down 

woody material pool. Also, given the short time period over which the estimate of 

aspen stand disturbance has been made, it should be considered with a great deal 

of caution. However, future measurements will not only enable analysis of fires 

effects on aspen, they will also provide important information on the amount and 

rate of recovery in all burned areas over time.

Old Growth Forests

An important aspect in managing for ecologically sustainable and diverse ecosystems is the maintenance of forest stands representing the full range of forest 

succession. The oldest stages of this range are of particular interest to forest managers. Historically, these last stages of forest growth have been difficult to define 

or describe. The terminology has included late seral, climax, mature, overmature, 

and old growth, among others. Generally, at issue is that stand structure changes 

in ways that are important to ecological and habitat function as forests mature. 

Standardized definitions are difficult because the final structure and age of a given 

forest stand depends on many biological and physical components: climate and geology, dominant tree species, fire regimes, and others (Kaufman and others 2007; 

Vosick and others 2007). In addition, the characteristics of old growth can change 

with the scale of observation, from patches to stands and landscapes (Kaufman and 

others 2007).

Responding to the Chief’s Directive of 1984, all USDA Forest Service Regions 

developed old growth definitions. The Northern Region has defined old growth for 

twenty different forest regimes, or potential old growth types, in Montana (Green 

and others 1992). Potential old growth types are determined based on whether the 

forest is east or west of the continental divide (12 types on the east side and 8 on 

the west), on large-tree species dominance, and on habitat type groupings. Each 

type has minimum old growth screening criteria, including trees per acre with a 

minimum age and diameter, and minimum live basal area per acre. Depending on 

the biophysical environment, trees per acre minima range from 4 to 30 trees per 

acre, ages range from 120 to 200 years, diameters are from 9 to 21 inches, and 

basal areas range from 40 to 80 square feet per acre; all depend on the potential old 

growth type. For instance, a stand west of the Continental Divide, with ponderosa 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 39

pines as the predominant large trees, and a ponderosa pine/Idaho fescue habitat 

type would require eight trees per acre at least 170 years old and 21 inches diameter, and at least 60 square feet per acre of basal area in order to be considered 

old growth. A stand east of the Continental Divide, with Engelmann spruce and 

subalpine firs as the predominant large trees, and a whitebark pine/subalpine fir 

habitat type would require eight trees per acre at least 135 years old and 13 inches 

diameter, and at least 40 square feet per acre of basal area.

The old growth types in Green and others (1992) are all based on timber type 

conifers, so woodland types and hardwoods do not have defined types. This analysis applies the Forest Service Northern Region old growth minimum criteria to all 

ownerships of forest land in Montana. Although the analysis is based on criteria 

used by the Northern Region, it was not conducted using the same database structure or specific programming algorithms used internally by the Northern Region, 

so result may vary.

Fourteen percent, or 3.6 million acres, of Montana’s forest land meet the old 

growth criteria. Nearly 3.0 million acres of that occur on National Forests, accounting for over 19 percent of the National Forest’s forest land (fig. 18). Privately 

owned forests contain over 0.2 million acres of old growth, while just less than 

0.2 million acres of old growth are on National Park Service land. The proportion 

of private forest land that meets old growth criteria is less than 4 percent, while the 

0 

2 

4 

6 

8 

10

12

14

16

National Forest 

Service

Private BLM State of Montana National Park 

Service

US Fish & Wildlife 

Service

Local 

Governments

Other Federal

Million acres

Ownership

Total acres

Meets old growth criteria

Figure 18—Total area of forest land and area meeting old growth criteria by ownership, Montana, cycle 2, 2003-2009.
40 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

National Park Service proportion is 19 percent, similar to National Forests. The 

proportion of old growth that is reserved is over 20 percent, compared to 13 percent for non-reserved forests.

Of the forest land meeting old growth criteria, one third (1.2 million acres) 

occurred west of the Continental Divide, while two thirds (2.4 million acres) is 

located on the east side. Old growth is most common in Montana’s southwestern 

forest survey unit, where 32 percent of the forest land met old growth criteria. 

Other survey units’ proportions of old growth were: west central, 15 percent; western, 10 percent; northwestern, 9 percent; and eastern, 8 percent. See Appendix E, 

tables 31-37 for counties included in forest survey units, and figure 28 in “Down 

Woody Material” in Section VI for a map of forest survey units.

The forest types with the most acres meeting the old growth criteria are lodgepole pine and Douglas-fir, each with over 0.8 million acres (fig. 19). These are 

also the two most common forest types. The forest types with the highest percentage of their area meeting old growth criteria are whitebark pine, at 45 percent, 

and Engelmann spruce-subalpine fir, at 38 percent. Common forest types with 

relatively low percentages of area meeting old growth criteria are ponderosa pine 

(7 percent), western larch (10 percent), grand fir (4 percent), and western redcedar 

(6 percent). Although the old growth criteria are based on timber type conifers, a 

few acres designated by FIA as woodland (Rocky Mountain juniper) or hardwoods 

(Cottonwood) met the old growth criteria, based on the presence of large old timber type conifers in the overstory.

In addition to area, the amount and proportions of aboveground biomass in old 

growth can also be assessed. Biomass in this analysis uses IWFIA regional equations (see “Volume and Biomass” in Section IV). As might be expected from criteria based on large-diameter trees and with minimum basal area requirements, proportions of live biomass occurring in forests that meet the old growth criteria are 

larger than proportions for acres. Over 25 percent of Montana’s aboveground live 

biomass, 221 million tons, occurs in forests meeting old growth criteria. Similar 

to area, the Douglas-fir and lodgepole pine forest types have the most biomass 

in stands meeting old growth criteria with 52 million tons and 48 million tons, 

respectively. Forest types with high proportions of their total biomass occurring 

in old growth stands are whitebark pine (59 percent) and Engelmann spruce-subalpine fir (50 percent). Common forest types with low proportions of their total 

biomass occurring in old growth stands are ponderosa pine (16 percent), grand fir 

(13 percent) and western redcedar (8 percent).

Another measure to evaluate the old growth stands selected in this analysis could 

be the number of snags per acre. Higher than average densities of snags larger than 

about 9 inches is used as a secondary characteristic of old growth by Green and 

others (1992), and as a structural feature or indicator of old growth by both Fiedler 

and others (2007) and Kaufmann and others (2007). Density of standing dead trees 

at least 9 inches diameter is 14.1 snags per acre for all forest land in Montana, 13.0 

snags per acre for conditions not meeting old growth criteria, and 23.4 snags per 

acre for old growth conditions. Figure 20 shows the number of snags per acre for 

the eight forest types with the most acres meeting old growth criteria along with 

estimates for all forest types combined, for both old growth and non-old growth 

conditions. In all cases, snags per acre are approximately 20 to 80 percent higher 

in old growth than in non-old growth.

As discussed in Section IV (“Quality Assurance Analysis”) tree age and habitat 

type are two of the FIA variables that are most difficult to collect accurately and 

consistently. This analysis depends heavily on those variables, so some caution 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 41

0 

1 

2 

3 

4 

5 

6 

7 

8 

Million acres

Forest type

Total acres

Meets old growth criteria

Figure 19—Total area of forest land and area meeting old growth criteria by forest type (showing only forest types with acreage meeting old 

growth criteria), Montana, cycle 2, 2003-2009.

must be taken with these results due to the increased possibility of measurement 

error. The use of habitat type groups in this analysis to assess site potential presents 

the possibility that the compliance rate for habitat type could be improved. That 

is, although two FIA field crews may disagree on the specific habitat type for a 

site, the two preferred types may be similar enough that they would both be in the 

same group. However, many plot conditions either met or did not meet old growth 

criteria based on tree ages within a few tolerance levels of the minimum tree age. 

While the old growth criteria presented by Green and others (1992) were developed to be compatible with inventory data, future research could focus on methods 

to improve the utility of FIA data for assessing old growth criteria. Options include 

improving data collection methods to increase repeatability, identifying possible 

surrogate measurements, and collection of additional field attributes to increase 

the reliability of habitat type assignment. Also, for areas of the country and for 

forest types where old growth characteristics are not as well defined as they are in 

Montana, the FIA database could be used to help quantify potential tree and stand 

characteristics to be used for defining the minimum criteria of old growth.
42 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

0 

5 

10

15

20

25

30

35

40

45

Lodgepole pine Douglas-fir Engelmann 

spruce / 

subalpine fir

Subalpine fir Engelmann 

spruce

Whitebark pine Ponderosa pine Western larch All types

Snags per acre

Forest type

Old growth

Not old growth

Noxious Weeds

Noxious plant species can have many negative effects on forest communities. 

Noxious species can displace native flora, alter fire regimes, reduce diversity in the 

plant and pollinator communities, and generally reduce the diversity and resiliency 

of forest ecosystems. FIA field crews record any instance where a noxious weed 

is found on a plot that contains a forested condition. This allows the spatial and 

temporal extent of these species to be documented as plots are revisited. A total 

of 3,382 sampled conditions were used to assess the occurrence of noxious plants 

in Montana. These samples represent plots that had a forested condition recorded 

somewhere within the boundaries of the four subplots.

Twenty-four different species were documented on forested plots in Montana, 

with one or more found on 555 (16 percent) of the sampled plots. Spotted knapweed (Centaurea diffusa), Canada thistle (Cirsium arvence), and gypsyflower 

(Cynoglossum officinale) were the most common species by a large margin. These 

three species accounted for 77 percent of the weed occurrences (fig. 21). It appears 

that Montana’s hardwood forest types are most prone to noxious plant infestation. 

This may be due to one or more factors, including soil conditions, accessibility 

Figure 20—Snags per acre by old growth and non-old growth for the eight forest types with the most area meeting old growth criteria, and for 

all forest types combined, Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 43

Figure 21—Number of forested conditions infested by each State-listed noxious plant, Montana, cycle 2, 2003-2009.

to livestock grazing, road and foot traffic, and/or high frequency of both natural 

and man-induced disturbance. Of the forest types having more than one condition 

sampled, the sugarberry-hackberry-elm-green ash forest type has the highest percentage of its area infested with at least one noxious species (fig. 22). However, 

a low sample size (n = 5) needs to be considered in this instance. Conversely, the 

Limber pine type had the smallest proportion of infested locations (2.0 percent). 

Nineteen percent of all sampled plots in Montana had multiple conditions.

Multiple conditions on a plot indicate transition zones between forest types and 

between forest and non-forest conditions. These “edge” areas are often dynamic 

in terms of site occupation, utilization, and species composition. This makes them 

more susceptible to occupation by noxious plants than the more stable interior of 

the stands. Locations that had more than one condition (more than one forest type 

or a portion of the plot was non-forest) had almost twice the occurrence of noxious 

species than did those locations where only a single forested condition represented 

the entire plot (24 percent and 13 percent respectively).

Snags as Wildlife Habitat

Standing dead trees (snags) provide important habitat in the forested ecosystems of Montana. There are many organisms that utilize snags at some point in 

their life history. These include, but are not limited to, bacteria, fungi, insects, rodents, cavity-nesting birds, bats, raptors, mustelids, and black bears. The diameters 

of standing dead trees are important variables to species that consider the utility 
44 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

of snags as a nesting, roosting, or den site. Individual tree data collected by FIA 

field crews allow for population level analysis of the availability and quality of 

individual snags that meet criteria important to wildlife.

Cavity-nesting birds in Montana are especially dependent on snags for both 

nesting and foraging activities. There are a handful of bird species that act as primary excavators of nest sites. These birds create a cavity during one breeding 

season, but often abandon it and create a new cavity the following year. The old 

cavities are then occupied by secondary cavity-nesting birds. Secondary cavitynesters do not excavate their own nest sites and are dependent on primary excavators for their cavities. The suitability of an old cavity for a secondary nester often 

depends on the species of primary excavator that created it. Here we present data 

reflecting the number of snags in Montana that are suitable for three important primary excavators that provide the bulk of cavities for secondary nesters. The hairy 

woodpecker (Picoides villosus), red-naped sapsucker (Sphyrapicus nuchalis), and 

northern flicker (Colaptes auratus) create different sized openings and cavities 

and are also relatively abundant and widespread throughout the different forest 

types of Montana; therefore, they provide suitable nest sites for a wide variety of 

secondary nesting species. The distribution of suitable snags by stand age is also 

presented. Suitability is based on mean diameters found to be used by these birds 

(Flack 1976; McClelland and others 1979; Dobkin and others 1995; Martin and 

others 2004).

Figure 22—Percentage of area infested with noxious plant species by forest type, Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 45

There are more than 297 million snags in Montana that meet the size preferences of the hairy woodpecker (≥25cm (9.8 inches) d.b.h.). The most abundant 

tree species contributing to these bird’s nesting sites are lodgepole pine (78.4 million snags), Douglas-fir (54.5 million), and whitebark pine (49.6 million) (fig. 23). 

These snags are predominately found in the Douglas-fir, lodgepole pine, and subalpine fir forest types. Nearly 155 million snags meet the diameter preferences of 

the red-naped sapsucker (≥31cm (12.2 inches) d.b.h.). Douglas-fir, whitebark pine, 

and lodgepole pine species again contribute the majority of these snags at 37.2, 

27.7, and 27.3 million snags respectively. The forest types where most of these 

snags can be found are Douglas-fir, subalpine fir, and nonstocked. Most potential 

northern flicker snags (≥35cm (13.8 inches) d.b.h.) are also found in the Douglasfir, subalpine fir, and nonstocked forest types. The tree species that comprise most 

of the suitable snag population for northern flickers are Douglas-fir (28.6 million), 

whitebark pine (18.3 million), and Engelmann spruce (14.0 million). The nonstocked forest type often includes areas disturbed by wildfire, disease, and insect 

infestations. These types of stands account for the high number of snags in this 

forest type.

Figure 23—Number of snags meeting the preferences of three important cavity-excavating birds by tree species, Montana, cycle 2, 

2003-2009.
46 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Figure 24 shows the distribution of snags ≥35cm d.b.h by stand-age. These 

snags are large enough to accommodate all three species of cavity excavators discussed here. The largest percentage of suitable snags for all three birds is found in 

the 101-150 (26 percent) and the 151-200 (22 percent) age-classes. The zero ageclass holds a large amount of suitable snags due to the large amount of disturbed 

forests in the nonstocked forest type. Another notable forest group is aspen-birch. 

Aspen forests are particularly important for some primary and secondary nesting 

birds because of the relationship of diseased aspen, primary excavators, and secondary nesters (Hart and Hart 2001). Diseased trees provide a relatively soft substrate for primary excavators to build their nest cavities in. The secondary nesters 

then occupy many of these cavities in subsequent years. Because few aspen trees 

live past 100 years in Montana and aspen snag retention time is short, the majority 

(83 percent) of snags in aspen forests are found in the 1- to 50-year age-class.

Variables other than snag dimensions and numbers need to be considered when 

predicting suitable wildlife habitat for forest-dwelling species. Proximity to forest 

edge and stand density of live trees is important to many cavity-nesting birds. The 

state of decay of a tree and its distance to foraging also plays a role in nest site suitability. FIA data can address many of these factors and there are current efforts to 

build predictive models for these species using data collected by our crews. These 

models can be valuable tools for Federal and State land managers, as most of the 

forests containing suitable snags occur on public lands.

Figure 24—Number of snags meeting the preferences of three important cavity-excavating birds by stand-age class and forest type group, 

Montana, cycle 2, 2003-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 47

VI. FIA Indicators

Forest Soil Resources

Soils on the landscape are the product of five interacting soil forming factors. 

These are parent material, climate, landscape position (topography), organisms 

(vegetation, microbes, other soil organisms), and time (Jenny 1994). Many external forces can have a profound influence on forest soil condition and hence forest 

health. These include agents of change or disturbances to apparent steady-state 

conditions such as shifts in climate, fire, insect and disease activities, land use 

activities, and land management actions.

The Soil Indicator of forest health was developed to assess the status and trend 

of forest soil resources in the United States across all ecoregions, forest types, 

and land ownership categories. For this report, data were analyzed and are being 

reported by forest type groups. This forest type stratification not only reflects the 

influence of forest vegetation on soil properties, but also the interaction of parent material, climate, landscape position, and time with forest vegetation and soil 

organisms. A complete listing of mean soil properties in Montana, organized by 

forest type, is in the Soil Indicator core tables in Appendix F (“Tables of Mean 

Soil Properties”). Some plots had a repeat visit so the data are summarized by 

visit number (1 or 2) and by forest type. Plots visited for the first Soil Indicator 

measurements were sampled in 2003 through 2007. Only a small subset of plots 

have been re-visited thus far in 2008 and 2009 so there is not yet enough data to 

run a valid repeated measures analysis. Nevertheless, we report the data for the 

re-visited plots summarized by forest type in the Soil Indicator core tables. Some 

of the key soil properties were graphed by forest type group in Montana and are 

highlighted in the discussion below.

Generally, soil moisture increases with elevation and latitude (associated with 

cooler temperatures) and forest types tend to reflect this climatic gradient. When 

expressed in terms of megagrams of C per hectare of forest area, C stocks generally increase with elevation and/or soil moisture storage (fig. 25). In Montana, 

spruce-fir forests tend to store the most C in terms of forest floor mass and belowground in mineral soil compared to other forest types. Soil N stocks in spruce-fir 

forests in Montana also tend to be higher than those in other forest types. This is in 

contrast to States such as Utah and Colorado where higher amounts of N are stored 

in aspen-dominated landscapes (DeBlander and others 2010; Thompson and others 2010). However, the cottonwood-aspen-birch group in Montana is represented 

by only seven plots and only three of those are dominated by aspen. This is far 

too small a sampling to generalize findings for this forest type across the State as 

a whole.

Soils in drier areas such as soils under Rocky Mountain juniper and ponderosa 

pine tend to be less weathered and have higher amounts of exchangeable base cations such as sodium, potassium, magnesium, and calcium (fig. 26). Acidic soils, 

many of which are found in wetter, higher elevation environments (e.g., sprucefir), tend to have lower levels of exchangeable base cations and have measureable 

levels of exchangeable aluminum. In none of the plots sampled are soil exchangeable aluminum levels high enough to pose a toxicity risk to tree roots given the 

ample supply of exchangeable calcium.
48 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Soil pH in drier calcareous soils tends to be near-neutral to alkaline (fig. 27 top) 

and such soils are found under Rocky Mountain juniper and ponderosa pine in 

Montana. The lowest pH soils are found under lodgepole pine and spruce-fir forests and these tend to be only moderately acid as a whole in Montana. Moderately 

acid soils often have elevated levels of extractable manganese (fig. 27 middle). 

Although elevated levels of manganese present some toxicity risk to sensitive species, potentially toxic levels of extractable manganese have yet to be established 

for most forest plant species. In general, only about 3.4 percent of the 0-10 cm 

forest soil layers in the Interior West contain extractable Mn levels greater than 

100 mg/kg (Amacher and Perry 2011). In Montana, most of the forest soils with 

elevated levels of extractable Mn are found under lodgepole pine (mean extractable Mn = 40 mg/kg in 0-10 cm layer).

The lowest levels of extractable phosphorus by the Olsen method were found in 

soils under Rocky Mountain juniper and Ponderosa pine forests, whereas the highest were found under Douglas-fir (fig. 27 bottom). The lower levels of extractable 

Figure 25—Soil organic carbon (top) and total nitrogen 

(bottom) stocks (Mg/ha) in the forest floor and 0-10 and 

10-20 cm soil layers arranged by forest type groups in 

Montana. The forest type groups are arranged left to right in 

order of increasing latitude, elevation, and precipitation with 

some overlap among forest types. The spruce/fir group in 

MT includes grand fir, Engelmann spruce, subalpine fir, and 

mixed Engelmann spruce/subalpine fir.

Figure 26—Exchangeable cations (sodium, potassium, 

magnesium, calcium, and aluminum) in the 0-10 cm and 10-20 

cm soil layers arranged by forest type groups in Montana.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 49

Figure 27—Averages, with standard errors, 

of soil pH, 1 M NH4Cl-extractable manganese, 

and Olsen (pH 8.5 0.5 M NaHCO3)-extractable 

phosphorus in the 0-10 cm soil layer arranged 

by forest type groups in Montana.

P in the calcareous soils reflects strong attenuation of plant-available P by the 

abundant calcium minerals in these soils.

Overall, soils under lodgepole pine in Montana tended to have the least nitrogen 

stocks, the lowest levels of exchangeable bases, and the lowest pH. This probably 

reflects the ability of the widely distributed lodgepole species to occupy lower 

fertility soils, whereas many other species prefer richer deeper soils. Throughout 

the Interior West as a whole, aspen, for example, tends to occupy deeper, richer, 

wetter soils and is associated with sites with higher nitrogen and potassium reserves, near-neutral pH levels, and a general absence of exchangeable aluminum 

(DeBlander and others 2010).

Down Woody Material

Down woody material (DWM) is an important component of forests that greatly impacts fire behavior, wildlife habitat, soil stabilization, and carbon sources. 

Some examples of DWM are fallen trees, branches, and leaf litter commonly found 

within forests in various stages of decay. The main components of DWM include 

fine woody debris (FWD), coarse woody debris (CWD), litter, and duff. FWD 

comprises the small diameter (1- to 3-inch) fire-related fuel classes (1-hr, 10-hr, 

100-hr), and CWD comprises the large diameter (3-inch +) 1000-hr fuels.
50 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Nationally, DWM is measured on Phase 3 (P3) plots. In 2006, due to the increasing need for more intensive DWM information, IWFIA initiated a Phase 2 

(P2) DWM inventory in all its annual States. This DWM analysis used regional 

P2 protocols (USDA 2006-2009) for data collected from 2006 to 2009. Due to the 

presence of snow or other hazardous conditions, not all DWM components were 

able to be sampled on all plots. Only plots that sampled all six DWM components 

were included.

The random distribution of four annual subcycles of P2 DWM plots is displayed 

in figure 28. This shows the total DWM biomass (tons per acre) by FIA survey unit 

for 1,860 plot/conditions in Montana. In general, DWM biomass is highest in the 

northwestern and southwestern parts of the State; this distribution reflects the distribution of forest types. Moist, northwestern forest types, such as western larch, 

have high DWM biomass estimates, as do high-elevation types common in the 

southwest, like Engelmann spruce-subalpine fir; while Rocky Mountain juniper, 

a dryer forest type common in the eastern survey unit, has relatively low DWM 

biomass estimates.

Table 6 shows the mean biomass (tons per acre) by DWM component, number 

of plot/conditions sampled, and average elevation, for FIA survey units. The northwestern survey unit has the highest mean DWM, at 28.2 tons/acre, followed by 

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Total DWM biomass (tons/acre)

!( <10.0

!( 10.0 - 19.9

!( 20.0 - 29.9

!( 30.0 - 39.9

!( 40.0+

Survey units

Northwestern

Western

West Central

Southwestern

Eastern

Counties

Water

®

0 25 50 100 150 200

Miles

Figure 28—Plot distribution of total DWM biomass (tons per acre) by FIA survey unit, Montana, cycle 2, subcycles 4-7, 2006-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 51

the southwestern at 23.7 tons/acre. The eastern survey unit has the lowest, at 14.2 

tons/acre. The mean DWM for the entire State is 21.8 tons/acre. Specific DWM 

components mostly show a similar pattern. The exception is the litter component, 

where the eastern survey unit has the highest mean tons/acre. Table 7 shows the 

mean biomass (tons per acre) by DWM component, number of plot/conditions 

sampled, and average elevation for forest type groups and forest types. Western 

larch has the highest mean DWM, at least for forest types with more than a few 

plot/conditions, at 40.5 tons/acre; and the lowest is 6.8 tons/acre for juniper types 

in the pinyon-juniper group. Some of the forest types in this analysis may not be 

representative due to small sample sizes.

Fuel loadings by DWM component are essential for predicting fire behavior. 

Table 7 also shows that the duff DWM component has the highest mean fuel loadings over all, followed by the CWD component and then the litter component. 

Several forest types show some variation from this general trend. Also, fuel loading variation among forest types in the three FWD classes is not as great as in the 

CWD, duff, and litter classes.

Surface fuel classifications of duff, litter, FWD, and CWD for estimating fire 

effects were compiled from a wide variety of recent fuel sampling projects conducted across the contiguous United States (Lutes and others 2009). For each FIA 

plot/condition, fuel loading ranges from these four classes were used to identify one of 21 potential fuel loading models (FLM) described by Lutes and others 

(2009). Figure 29 displays the number of plot/conditions identified by FLM class 

for the five survey units in Montana. This shows that for this DWM dataset all of 

the 21 possible FLM’s were identified, and the largest proportion of all the plot/

conditions (249) occurred in the class 31 FLM, followed by classes 21 (171 plot/

conditions) and 11 (170 plot/conditions). Class 31 was the most common FLM for 

all of the survey units except the eastern unit, where class 11 was the most common. Although these plot classifications are currently under review, once they are 

objectively classified they can be used as inputs to fire effects models to compute 

smoke emissions, fuel consumption, and carbon released to the atmosphere.

Structural diversity in terms of CWD diameters and decay classes are important 

criteria for wildlife habitat. IWFIA field crews identify one of five large-end diameter 

classes for each P2 CWD piece tallied. This information may be critical for wildlife 

species that use large-diameter logs for habitat. Figure 30 displays the percentage of 

CWD pieces for decay classes 1 through 4 in each large-end diameter class by forest type. Although they contribute to biomass and carbon pools, large-end diameter 

class is not recorded for decay class 5 pieces due to their degree of decomposition. At 

over 3 percent, the fir-spruce-mountain hemlock group (consisting of the Engelmann 

spruce, Engelmann spruce-subalpine fire, subalpine fir, grand fir and mountain 

hemlock forest types) has the highest percentage of CWD pieces in the 21.0-inch 

and greater class. Three other groups also have close to 3 percent in the 21.0-inch 

and greater class: the other western softwoods forest type group (consisting of the 

Table 6—Average elevation and DWM loadings by FIA survey unit with number of plots. Montana, cycle 2, subcycles 4-7, 2006-2009.

FIA survey unit Number of plots Elevation CWD FWD large FWD medium FWD small Duff Litter Total DWM

Northwestern 512 4,686 9.4 2.0 0.5 0.2 12.5 3.6 28.2

Western 305 5,626 6.1 1.5 0.5 0.2 9.2 2.7 20.0

West Central 318 6,084 4.9 1.4 0.4 0.2 10.3 2.8 20.1

Southwestern 340 7,441 7.9 1.4 0.4 0.1 10.7 3.1 23.7

Eastern 385 4,369 2.1 0.9 0.3 0.1 7.1 3.7 14.2

All types 1,860 5,517 6.3 1.5 0.4 0.2 10.2 3.3 21.8
52 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Table 7—Average elevation and DWM loadings by forest type group and forest type with number of plots. Montana, cycle 2, subcycles 4-7, 2006-2009. Forest type group and forest type Number of plots Elevation CWD FWD large FWD medium FWD small Duff Litter Total DWM Pinyon-juniper group Rocky Mountain juniper 70 3,887 0.4 0.5 0.2 0.1 3.3 2.7 7.2 Juniper woodland 5 5,283 0.1 0.1 0.1 0.0 0.3 1.0 1.6 Total 75 3,980 0.4 0.4 0.2 0.1 3.1 2.6 6.8 Douglas-fir group Douglas-fir 525 5,341 4.3 1.8 0.5 0.2 7.6 2.4 16.9 Total 525 5,341 4.3 1.8 0.5 0.2 7.6 2.4 16.9 Ponderosa pine group Ponderosa pine 203 3,883 1.7 0.8 0.3 0.1 6.4 4.3 13.5 Total 203 3,883 1.7 0.8 0.3 0.1 6.4 4.3 13.5 Fir-spruce-mountain hemlock group Engelmann spruce 93 6,423 11.8 1.5 0.4 0.2 12.1 2.3 28.4 Engelmann spruce / subalpine fir 84 6,538 12.8 1.5 0.5 0.2 13.6 2.8 31.4 Grand fir 13 3,765 10.6 1.9 0.7 0.2 14.7 4.0 32.2 Subalpine fir 171 6,712 10.8 1.3 0.4 0.2 10.9 2.1 25.7 Mountain hemlock 4 5,667 5.2 1.2 0.1 0.1 4.2 2.5 13.2 Total 365 6,482 11.4 1.4 0.4 0.2 11.9 2.4 27.8 Lodgepole pine group Lodgepole pine 298 6,464 9.0 1.6 0.3 0.1 14.4 4.2 29.7 Total 298 6,464 9.0 1.6 0.3 0.1 14.4 4.2 29.7 Hemlock-Sitka spruce group Western hemlock 2 4,173 14.9 2.2 0.5 0.2 13.5 2.5 33.8 Western redcedar 12 3,840 15.2 2.3 0.5 0.3 11.5 3.0 32.7 Total 14 3,887 15.1 2.3 0.5 0.3 11.8 2.9 32.9 Western larch group Western larch 74 4,488 12.6 2.8 0.6 0.2 18.2 6.1 40.5 Total 74 4,488 12.6 2.8 0.6 0.2 18.2 6.1 40.5 Other western softwoods group Limber pine 19 6,468 1.5 0.8 0.2 0.1 7.8 3.7 14.1 Whitebark pine 45 8,504 4.7 0.8 0.3 0.1 13.5 3.3 22.7 Miscellaneous western softwoods 4 7,784 0.5 0.5 0.2 0.1 5.4 2.0 8.5

 Total 68 7,893 3.6 0.8 0.3 0.1 11.4 3.4 19.5
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 53 Oak-hickory group Elm / ash / black locust 1 2,667 0.2 1.2 0.6 0.1 24.5 17.1 43.7 Total 1 2,667 0.2 1.2 0.6 0.1 24.5 17.1 43.7 Elm-ash-cottonwood group Cottonwood 16 3,418 2.3 2.9 0.8 0.2 19.9 4.4 30.4 Sugarberry / hackberry / elm / green ash 1 3,093 5.9 0.0 0.0 0.1 15.7 7.8 29.5 Cottonwood / willow 2 3,512 5.0 7.5 0.4 0.1 10.5 8.6 32.1 Total 19 3,411 2.7 3.2 0.7 0.2 18.7 5.0 30.5 Aspen-birch group Aspen 36 5,431 4.6 1.7 0.3 0.1 20.2 5.6 32.5 Paper birch 2 3,732 4.1 3.2 0.5 0.2 37.5 11.5 57.0 Total 38 5,342 4.6 1.8 0.3 0.1 21.1 5.9 33.8 Alder-maple group Red alder 1 3,338 5.5 1.4 0.7 0.3 44.9 2.4 55.2 Total 1 3,338 5.5 1.4 0.7 0.3 44.9 2.4 55.2 Woodland hardwoods group Cercocarpus (mountain brush) woodland 1 5,975 0.8 0.0 0.2 0.0 8.4 1.6 11.1 Total 1 5,975 0.8 0.0 0.2 0.0 8.4 1.6 11.1 Nonstocked Nonstocked 178 4,920 3.5 1.1 0.2 0.1 6.7 3.0 14.6 Total 178 4,920 3.5 1.1 0.2 0.1 6.7 3.0 14.6 All types 1,860 5,517 6.3 1.5 0.4 0.2 10.2 3.3 21.8
54 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

whitebark pine, limber pine, and miscellaneous western softwoods forest types), the 

aspen-birch group (aspen and paper birch forest types), and the western larch type/

group. At 15.0 to 20.9 inches large-end diameter, the hemlock-Sitka spruce forest 

type group (consisting of the western redcedar and western hemlock forest types) has 

the most at 12 percent, followed by the fir-spruce-mountain hemlock group (consisting of Engelmann spruce, subalpine fir, Engelmann spruce-subalpine fir, grand fir, 

and mountain hemlock forest types) and the pinyon-juniper group (Rocky Mountain 

juniper and juniper woodland forest types), each with 10 percent.

Another consideration other than size is the degree of decay of individual logs. 

Decay classes can range from class 1, which are newly fallen trees with no decay, 

to class 5, which still resemble a log but often blend into the duff and litter layers. 

Figure 31 shows the percentage of CWD pieces by forest type and decay class. In 

general, the wetter types have a higher percentage of CWD pieces in the advanced 

decomposition classes, while drier types have a lower percentage.

The annual FIA system supports live and standing dead tree inventories but does 

not include down dead trees as did some past periodic inventories. The current P3 

DWM protocols and estimation procedures (Woodall and Monleon 2008) include 

improvements such as population estimation, and are designed to capture some 

important aspects that serve as a better surrogate for answering relevant questions 

about the various components of down woody materials in forests. However, as 

Figure 29—Number of plot/conditions by fuel loading model (FLM) class and FIA survey unit, Montana, cycle 2, subcycles 4-7, 2006-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 55

Figure 30—Percentage distribution of CWD pieces by large-end diameter class and forest type group, Montana, cycle 2, subcycles 4-7, 

2006-2009.

discussed in Section II, P3 is a 1/16th sample of P2, and although it may be adequate at the regional or national level, it is often inadequate for many DWM applications at the State level.

Although this analysis included only plot-level per acre estimates and analysis, 

soon IWFIA will have population estimate capabilities for its regional P2 DWM 

database. This will allow analyses of the impacts and implications of expanding 

plot level information to the State.

For example, table 7 showed that although the western larch forest type in 

Montana has three times the total per acre DWM biomass of the ponderosa pine 

type, the area of the ponderosa pine type is over three times that of the western 

larch type (Appendix E, table 3). Once population estimates are factored in, the 

ponderosa pine type could contain more total DWM biomass and carbon than the 

western larch type.

Furthermore, the Pacific Northwest FIA and IWFIA are jointly investigating a 

national P2 inventory version of DWM to support a more robust dataset for future 

fire fuel, wildlife structure, and carbon assessments. These protocols should be 

complementary and compatible with the current regional P2 variations. As estimates of DWM are improved and refined, along with FIA’s understory vegetation 

and standing tree inventory, FIA will be better positioned for addressing estimates 

of total forest biomass.
56 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Damage to Live Trees

The Interior West FIA program has used a regionally defined damage protocol 

for most of the periodic and annual inventories since 1981. Throughout this time, 

the protocol has remained consistent, with only a few modifications to the damage 

categories. Damages are assigned only to live trees, in contrast to mortality agents, 

which are only assigned to recently dead trees. Not all damaging agents are potential mortality agents, so there is only partial overlap in the two agent lists.

There are currently 50 damage codes representing a wide range of biotic, abiotic, and anthropogenic agents. Up to three damage agents may be assigned to a 

tree. However, less than a third of damaged trees have more than one agent assigned, and less than 25 percent of trees with two damage agents will have a third 

agent assigned.

The protocol is based on a threshold system, where damage is only recorded if it 

is considered “serious.” Although this is somewhat subjective, the general rules are 

that damage should be recorded when it will cause one of the following:

• Prevent the tree from living to maturity, or surviving 10 more years if already 

mature;

• Prevent the tree from producing marketable products;

Figure 31—Percentage distribution of CWD pieces by decay class and forest type group, Montana, cycle 2, subcycles 4-7, 2006-2009.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 57

• Reduce (or has seriously reduced) the quality of the tree’s potential products.

These rules roughly correspond to two main categories of damaging agents. 

Agents that are likely to prevent a tree from living to maturity or surviving for 10 

years after the inventory date tend to be those related to insects, disease, fire, and 

atmospheric effects (drought, flooding, wind, etc.), whereas agents that preclude 

or reduce a tree’s merchantability are more likely to be problems with form, such 

as forks, broken tops, or logging scars. The latter group may or may not affect 

trees with respect to survival. Therefore, not all trees with damages recorded are 

expected to die, and some of those with poor merchantability may live to typical 

upper ages for their species.

A nationally consistent protocol for non-lethal damage to trees is scheduled to 

be implemented by the FIA program in 2013. A majority of the damage categories 

used in the national protocol crosswalk directly with the Interior West regional 

categories, ensuring that it will be possible to track trends in damaging agents over 

time.

Because earlier inventories of Montana were done under the periodic system 

and parts of those inventories were spread over a wide range of years, it is difficult to compare earlier results to the current annual inventory. In order to keep the 

data as comparable as possible, damages are described as proportions of the trees 

tallied during the different time periods, that is, they are not expanded to make 

population-scale estimates.

There were 79,037 live trees tallied during the Montana periodic inventory 

years (1988 to 2001), and 89,068 live trees tallied during the first 7 years of annual 

inventory (2003-2009). During the periodic inventories, 36.8 percent of trees were 

assigned one damage agent, 8.4 percent had two agents, and 1.8 percent had three. 

During the annual inventory, nearly the same proportion of trees (37.6 percent) 

were assigned one damage agent, although the proportions of trees with secondary (12.8 percent) and tertiary (3.3 percent) damage agents appeared to increase. 

Although the overall frequency of primary damage was the same between periodic 

and annual inventories, the change in frequency was mixed among damage agent 

groups. The insects, fire, and form categories showed increases, with the remainder of groups showing decreases (table 8).

Damage agents related to merchantability accounted for the majority of primary 

damage agents (table 8). The next most frequent damage category was diseases, 

with the most frequently recorded agents within this category being stem and butt 

rots, cankers, stem rusts, and dwarf mistletoes. It should be noted that dwarf mistletoe is recorded for all infected trees using a separate variable, but only trees 

with a dwarf mistletoe rating (DMR; Hawksworth 1977) of 4 to 6 are considered 

as “serious” for the purpose of damage agent assignment. Notable damage agents 

within the insect category were bark beetles (0.22 percent in periodic and 0.82 

percent in annual) and defoliators (0.20 percent in periodic and 1.12 percent in 

annual). Within the animal category, the majority of damage was caused by porcupines (0.55 percent in periodic and 0.46 percent in annual); within the atmosphere 

category, the most common sources of damage were frost (0.24 percent in periodic 

and 0.34 percent in annual), wind (0.17 percent in periodic and 0.07 percent in annual), snow (0.15 percent in periodic and 0.04 percent in annual), and lightening 

(0.12 percent in periodic and 0.03 percent in annual).

While it is difficult to compare changes in damage rates between periodic and 

annual inventories with statistical certainty, it is possible to consider some of the 

expected patterns in comparison to the data. For example, it may seem reasonable 

that the decreases in suppression and disease damages could be the result of fuel 
58 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

reduction and other silvicultural activities, which would tend to target trees in these 

categories disproportionally. In this respect, the apparent increase in form-damage 

trees is unexpected, because these trees would be targeted by silvicultural activities as well. However, the effect of management on the proportion of form-damage 

trees cannot be known with certainty until remeasurement occurs under the annual 

inventory system. On the other hand, the apparent increases in the insect categories 

of bark beetles and defoliators are consistent with aerial surveys and other information sources that show these agents have been on the increase in recent years. 

Damage from bark beetles shows a moderate increase compared to the known increase in mortality in many conifers (see “Forest Growth and Mortality” in Section 

IV), but this is not surprising given that FIA crews are more likely to encounter a 

bark beetle-infested tree when it is dead, and not during the brief period when it is 

live and heavily infested. In the typical situation, bark beetles would be assigned as 

the mortality agent of a dead tree as opposed to the damaging agent of a live tree.

The comparison of damage frequency over time also illustrated a key difference between periodic and annual inventory data. Periodic data are intended to be 

taken together as a whole inventory, even though the plots may be spread out over 

several years. During a periodic inventory, it is not uncommon for the plots done 

in a given year to be concentrated in a particular part of the State. As a result, there 

is geographic bias when measurement years are considered separately. Under annual inventory, the plots are geographically distributed every year and there is no 

geographic bias. The end result is that apparent trend within the periodic inventory 

may actually be the result of geographic bias. Under annual inventory, any trend 

over time may be more reliably interpreted as real. This is apparent when total 

damage frequency is plotted by measurement year (fig. 32). Note that the proportion of damaged trees varies widely over the periodic inventory years (1988-2002), 

but remains relatively consistent (but with a slightly declining trend) over the annual inventory years (2003-2009). The variation among periodic years is likely due 

to plots being located in areas of relatively high or low damage (e.g., recent fires, 

areas with snow damage, or localized insect outbreaks) in any given year.

As noted above, assignment of damage does not necessarily imply impending 

death of a tree. The types of form damages most frequently recorded—lean, forks 

Table 8—Distribution of primary damage agents by agent group, Montana 

periodic (1988-2001) and annual (2003-2009) inventories.

Damage agent group Periodic Annual

Percent

No damage (0) 63.20 62.40

Insects (10-16) 0.70 2.70

Diseases (20-29) 7.50 5.40

Fire (30-31) 0.30 0.40

Animals (40-48) 0.80 0.70

Atmosphere (50-59) 0.80 0.50

Suppression (61) 2.30 0.40

Form (71-79) 23.50 27.20

Human (80-85) 0.30 0.10

Unknown / Unidentified (70) 0.60 0.20

 All agents 100.00 100.00
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 59

below or above merchantable top, broken or dead tops, and crook/sweep/taper—

are unlikely to result in mortality, so few of those in the form damage group should 

be expected to die. If we assume that the form damage group is considered nonlethal and all other agents combined are considered as potentially lethal within a 

10-year window, the numbers are probably within what would be expected for 

normal stand development. For example, form-damaged and undamaged trees account for 89.6 percent of all tally trees. If the remaining trees are assumed to be at 

risk of mortality, the expected mortality rate can be approximated. Over a 10-year 

window, this equates to just over 1 percent on an annual basis, which can easily be 

accounted for under normal stand dynamics. Of course, the damaged trees that are 

expected to die are in addition to the mortality trees encountered during the most 

recent plot visits, and mortality is elevated in many species. This may suggest 

that damage frequencies are not greatly affected by periodically elevated mortality 

rates, because for many agents the transition from “healthy” to dead may occur 

relatively quickly. It is possible that elevated mortality could partly explain the 

apparent decrease in many agent categories, because, as the damage variables are 

intended, they identify trees that are predisposed to early mortality. Although this 

is the underlying assumption, it will not be conclusively demonstrable until annual 

remeasurement occurs.

Figure 32—Variation of proportion of damage trees recorded by measurement year, 1988-2009. Years 1988 to 2001 were part of the Montana 

periodic inventory; 2003 to 2009 were measured as part of the annual inventory system.
60 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

VII. Montana Timber Harvest and Forest Products Industry Summary

The University of Montana Bureau of Business and Economic Research 

(BBER), in cooperation with the Interior West Forest Inventory and Analysis 

program, conducts periodic censuses of Montana’s timber processing facilities. 

The BBER conducted a statewide census of primary forest products facilities in 

Montana for calendar year 2004 (Spoelma and others 2008) and is now completing the 2009 census. This section reports key aspects of the 2009 census and updates based on annual assessments done in conjunction with the BBER’s annual 

Economic Outlook Seminar series.

Primary forest products facilities are firms that process timber into manufactured products such as lumber, and facilities such as pulp and paper mills and 

particleboard plants that use wood fiber residue directly from timber processors. 

A total of 119 primary forest products plants were identified as active in Montana 

during 2009, including 35 sawmills; 32 log home facilities; 27 post, pole, and log 

furniture manufacturers; 17 residue-related products facilities; 2 plywood/veneer 

plants; and 6 other miscellaneous facilities (fig. 33).

When the previous Montana census of primary timber processors was conducted for calendar year 2004, annual U.S. housing starts were surging towards 2 million, topping out at 2.1 million in 2005. However, with the housing market downturn beginning in 2006, the official recession starting in 2007, and the 2008 global 

financial crisis, housing starts fell to a post-World War II record low of 554,000. 

Housing starts only rebounded slightly in 2010, and are unlikely to increase significantly until 2013 or beyond. Several large mills and numerous smaller mills 

in the State have either curtailed operations or permanently closed in response to 

these operating conditions. The State’s largest single forest products employer and 

largest user of wood fiber was lost when the Smurfit-Stone Container linerboard 

facility permanently closed in January 2010.

The capacity to process timber at Montana mills dropped 33 percent between 

2004 and 2009 and dropped another 25 percent from 2009 to 2010. Capacity was 

over 1 billion board feet (Scribner) in 2000, but had fallen to 485 million board 

feet (MMBF) by 2010. Utilization of timber-processing capacity is an important 

indicator of the ability of the industry to quickly respond to increased demand for 

wood products when markets recover after an economic downturn. While capacity 

utilization was above 80 percent in 1986 and 1996, it fell to 76 percent in 2003, 70 

percent in 2005, and 59 percent during 2010.

The sales value of Montana’s wood and paper products was down from $1.3 

billion in 2004, to $550 million in 2009, and $325 million in 2010. Total forest 

industry employment decreased from 9,875 workers in 2004, to 7,051 in 2009, and 

6,743 in 2010. Production of lumber, the major output of Montana’s wood products industry, fell from 917 MMBF, lumber tally in 2004 to a low of 418 MMBF in 

2009, before a slight increase to 480 MMBF in 2010 (fig. 34).

Timber harvest for 2010 was 321 MMBF, approximately 12 percent higher than 

the 2009 harvest, but still less than half of the 2004 level of 751 MMBF. As shown 

in figure 35, the harvest totals from 2009 and 2010 are the lowest on record since 

1945. In 2010, 54 percent of the harvest volume came from private lands, 24 percent from National Forest lands, and the remaining 22 percent came from other 

ownerships including State, BLM, and tribal lands.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 61

Figure 33—Montana’s primary timber processing facilities and timber harvest by county, 2009.

Markets for Montana wood products have improved little in 2011. Although 

modest improvements are expected in 2012, significant improvements are unlikely 

until 2013 or later, as U.S. home building recovers. However, with approximately 

40 percent of the State’s timber-processing capacity unutilized, Montana mills 

could quickly increase production in response to increased demand, depending on 

the timing of economic recovery and any resurgence in new home construction.
62 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Figure 34—Montana 

lumber production (million 

board feet, Scribner rule), 

1945-2010.

Figure 35—Montana timber harvest (million board feet, Scribner rule) by ownership, 1945-2010.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 63

VIII. Conclusions

Montana’s nearly 26 million acres of forest land is diverse in the context of 

Intermountain West forest. It encompasses 28 individual FIA forest tree species, 

which in different combinations compose 25 different forest types. These occur 

across a wide range of elevation and climatic regimes, from forests dominated by 

ponderosa pine and Rocky Mountain juniper in the hills and break lands in the 

eastern half of the State, to high mountain forests typical of those found throughout 

the mountains of the Interior West in the southwestern portion of the State, to the 

dense and moist larch, hemlock, and redcedar dominated forests in the northwestern part of the State. These forests provide an abundance of services, including 

timber products, recreational opportunities, air and water quality, wildlife habitat, and scenic beauty. Major forest type groups include Douglas-fir, spruce-firmountain hemlock, lodgepole pine, and ponderosa pine. Major species groups are 

the main components of these forest types: true firs, Douglas-fir, lodgepole pine, 

Engelmann spruce, and ponderosa pine.

Seventy-three percent of these forests are in the public domain, with 60 percent 

managed by the National Forest Service. The Bureau of Land Management and 

the National Park Service are the other major public forest managers, but neither 

encompasses as much forest land as is owned by various private and tribal entities 

in Montana.

Currently in Montana, there are several factors leading to higher than average 

mortality rates. During the 2003-2009 FIA inventory period, forest tree mortality 

rates have begun to outpace growth rates in lodgepole pine, Douglas-fir, true firs, 

Engelmann spruce, and particularly in whitebark pine. The alarming rate of loss of 

whitebark pine can be further demonstrated and quantified using remeasurement 

data from previous inventory plots. Even though many small, young whitebark 

pines are present in the inventory, the long term reproductive success and sustainability of whitebark pine remains in question.

Quaking aspen is another tree species that has generated concern regarding forest health and sustainability. The current inventory, and comparisons to past inventory data, does not provide clear evidence of impending threats to Montana’s 

aspen. However, assessments of trends in all tree species populations and forest 

dynamics will be greatly facilitated as annual plots come under full remeasurement 

of all inventory plots beginning in 2013 in Montana.

Montana’s wood production and timber harvest have been declining over the 

past thirty years, but the recent recession and housing market bust have been especially devastating. Wood product processing facilities’ production capacity has 

fallen off sharply over the past 5 years. Even at that, the utilization of those facilities is estimated at about 60 percent. The result is a loss of income and employment 

in Montana’s economy. The extra wood processing capacity due to under utilization means, however, that the wood products industry could respond if demand 

were to increase in the near future.

Many of the analyses performed for this report demonstrate both the utility of 

FIA data as an analysis tool and the potential for further, more in-depth analysis 

of a wide range of topics. Data from FIA’s annualized inventory will continue to 

provide valuable information to resource managers and researchers who are interested in the health, status, and quantity of resources provided by Montana’s forests.
64 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

IX. Standard Forest Inventory and Analysis Terminology

Average annual mortality—The average annual volume of trees 5.0 inches 

d.b.h./d.r.c. and larger that died from natural causes.

Average net annual growth—Average annual net change in volume of trees 5.0 

inches d.b.h./d.r.c. and larger in the absence of cutting (average annual gross 

growth minus average annual mortality).

Basal area (BA)—The cross-sectional area of a tree stem/bole (trunk) at the point 

where diameter is measured, inclusive of bark. BA is calculated for trees 1.0 

inch and larger in diameter, and is expressed in square feet. For timber species, 

the calculation is based on diameter at breast height (d.b.h.); for woodland species, it is based on diameter at root collar (d.r.c.).

Biomass—The quantity of wood fiber, for trees 1.0 inch d.b.h./d.r.c. and larger, expressed in terms of oven-dry weight. It includes above-ground portions of trees: 

bole/stem (trunk), bark, and branches. Biomass estimates can be computed for 

live and/or dead trees.

Board-foot volume—A board-foot is a unit of measure indicating the amount of 

wood contained in an unfinished board 1 foot wide, 1 foot long, and 1 inch 

thick. Board-foot volume is computed for the sawlog portion of a sawtimbersize tree; the sawlog portion includes the part of the bole on sawtimber-size 

tree from a 1-foot stump to a minimum sawlog top of 7 inches diameter outside 

bark (d.o.b.) for softwoods, or 9 inches d.o.b. for hardwoods. Net board-foot 

volume is calculated as the gross board-foot volume in the sawlog portion of a 

sawtimber-size tree, less deductions for cull (note: board-foot cull deductions 

are limited to rotten/missing material and form defect—referred to as the merchantability factor—board-foot). Board-foot volume estimates are computed in 

both Scribner and International 1⁄4-inch rule, and can be calculated for live and/

or dead (standing or down) trees.

Census water—Streams, sloughs, estuaries, canals, and other moving bodies of 

water 200 feet wide and greater, and lakes, reservoirs, ponds, and other permanent bodies of water 4.5 acres in area and greater.

Coarse woody debris—Down pieces of wood leaning more than 45 degrees from 

vertical with a diameter of at least 3.0 inches and a length of at least 3.0 feet.

Condition class—The combination of discrete landscape and forest attributes that 

identify, define, and stratify the area associated with a plot. Examples of such 

attributes include condition status, forest type, stand origin, stand size, owner 

group, and stand density.

Crown class—A classification of trees based on dominance in relation to adjacent 

trees in the stand as indicated by crown development and amount of sunlight 

received from above and the sides.

Crown cover (Canopy cover)—The percentage of the ground surface area covered by a vertical projection of plant crowns. Tree crown cover for a sample site 

includes the combined cover of timber and woodland trees 1.0 inch d.b.h./d.r.c. 

and larger. Maximum crown cover for a site is 100 percent; overlapping cover 

is not double counted.

Cubic-foot volume (merchantable)—A cubic-foot is a unit of measure indicating 

the amount of wood contained in a cube 1-by-1-by-1 foot. Cubic-foot volume 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 65

is computed for the merchantable portion of timber and woodland species; the 

merchantable portion for timber species includes that part of a bole from a 

1-foot stump to a minimum 4-inch top d.o.b, or above the place(s) of diameter 

measurement for any woodland tree with a single 5.0-inch stem or larger or a 

cumulative (calculated) d.r.c. of at least 5.0 inches to the 1.5-inch ends of all 

branches. Net cubic-foot volume is calculated as the gross cubic-foot volume 

in the merchantable portion of a tree, less deductions for cull.

Diameter at breast height (d.b.h.)—The diameter of a tree bole/stem (trunk) 

measured at breast height (4.5 feet above ground), measured outside the bark. 

The point of diameter measurement may vary for abnormally formed trees.

Diameter at root collar (d.r.c.)—The diameter of a tree stem(s) measured at root 

collar or at the point nearest the ground line (whichever is higher) that represents 

the basal area of the tree, measured outside the bark. For multistemmed trees, 

d.r.c. is calculated from an equation that incorporates the individual stem diameter measurements. The point of diameter measurement may vary for woodland 

trees with stems that are abnormally formed. With the exception of seedlings, 

woodland stems qualifying for measurement must be at least 1.0 inch in diameter or larger and at least 1.0 foot in length.

Diameter class—A grouping of tree diameters (d.b.h. or d.r.c.) into classes of a 

specified range. For some diameter classes, the number referenced (e.g., 4”, 6”, 

8”) is designated as the midpoint of an individual class range. For example, if 

2-inch classes are specified (the range for an individual class) and even numbers are referenced, the 6-inch class would include trees 5.0- to 6.9-inches in 

diameter.

Diameter outside bark (d.o.b.)—Tree diameter measurement inclusive of the 

outside perimeter of the tree bark. The d.o.b. measurement may be taken at 

various points on a tree (e.g., breast height, tree top) or log, and is sometimes 

estimated.

Field plot/location—A reference to the sample site or plot; an area containing the 

field location center (LC) and all sample points. A field location consists of four 

subplots and four microplots.

• Subplot—A 1/24-acre fixed-radius area (24-foot horizontal radius) used to 

sample trees 5.0 inches d.b.h./d.r.c. and larger and understory vegetation.

• Microplot—A 1/300-acre fixed-radius plot (6.8-foot radius), located at the 

center of each subplot, used to inventory seedlings and saplings.

Fixed-radius plot—A circular sample plot of a specified horizontal radius: 1/300 

acre = 6.8 foot radius (microplot); 1/24 acre = 24.0 foot radius (subplot).

Forest industry land– Land owned by a company or an individual(s) operating a 

primary wood-processing plant.

Forest land—Land that has at least 10 percent cover of live tally tree species of 

any size, or land formerly having such tree cover, and not currently developed 

for a nonforest use. The minimum area for classification as forest land is 1 acre. 

Roadside, stream-side, and shelterbelt strips of trees must be at least 120 feet 

wide to qualify as forest land. Unimproved roads and trails, streams and other 

bodies of water, or natural clearings in forested areas are classified as forest, if 

less than 120 feet in width or 1 acre in size. Grazed woodlands, reverting fields, 

and pastures that are not actively maintained are included if above qualifications 

are satisfied.
66 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Forest type—A classification of forest land based on the species forming a plurality of live-tree stocking.

Gross growth—The annual increase in volume of trees 5.0 inches d.b.h. and larger 

in absence of cutting and mortality. Gross growth includes survivor growth, 

ingrowth, growth on ingrowth, growth on removals before removal, and growth 

on mortality prior to death.

Growing-stock trees—A live timber species, 5.0 inches d.b.h. or larger, with less 

than 2/3 (67 percent) of the merchantable volume cull, and containing at least 

one solid 8-foot section, now or prospectively, reasonably free of form defect, 

on the merchantable portion of the tree.

Growing-stock volume—the cubic-foot volume of sound wood in growing-stock 

trees at least 5.0 inches d.b.h. from a 1-foot stump to a minimum 4-inch top 

d.o.b. to the central stem.

Hardwoods—Dicotyledonous trees, usually broadleaf and deciduous.

Hexagonal grid (Hex)—A hexagonal grid formed from equilateral triangles for 

the purpose of tessellating the FIA inventory sample. Each hexagon in the base 

grid has an area of 5,937 acres (2,403.6 ha) and contains one inventory plot. 

The base grid can be subdivided into smaller hexagons to intensify the sample.

Indian Trust lands—American Indian lands held in fee, or trust, by the Federal 

Government, but administered for tribal groups or as individual trust allotments.

Land use—The classification of a land condition by use or type.

Litter—The uppermost layer of organic debris on a forest floor; that is, essentially 

the freshly fallen, or only slightly decomposed material, mainly foliage, but also 

bark fragments, twigs, flowers, fruits, and so forth. Humus is the organic layer, 

unrecognizable as to origin, immediately beneath the litter layer from which it 

is derived. Litter and humus together are often termed duff.

Logging residue/products—

• Bolt—A short piece of pulpwood; a short log.

• Industrial wood—All commercial roundwood products, excluding fuelwood.

• Logging residue—The unused sections within the merchantable portions of 

sound (growing-stock) trees cut or killed during logging operations.

• Mill or plant residue—Wood material from mills or other primary manufacturing plants that is not used for the mill’s or plant’s primary products. Mill 

or plant residue includes bark, slabs, edgings, trimmings, miscuts, sawdust, 

and shavings. Much of the mill and plant residue is used as fuel and as the 

raw material for such products as pulp, palletized fuel, fiberwood, mulch, 

and animal bedding. Mill or plant residue includes bark and the following 

components:

• Coarse residue—Wood material suitable for chipping, such as slabs, edgings, 

and trim.

• Fine residue—Wood material unsuitable for chipping, such as sawdust and 

shavings.

• Pulpwood—Roundwood, whole-tree chips, or wood residues that are used for 

the production of wood pulp.

• Roundwood—Logs, bolts, or other round sections cut from trees.

Mapped-plot design—A sampling technique that identifies (maps) and separately 

classifies distinct “conditions” on the field location sample area. Each condition 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 67

must meet minimum size requirements. At the most basic level, condition class 

delineations include forest land, nonforest land, and water. Forest land conditions can be further subdivided into separate condition classes if there are distinct variations in forest type, stand-size class, stand origin, and stand density, 

given that each distinct area meets minimum size requirements.

Merchantable portion—For trees measured at d.b.h. and 5.0 inches d.b.h. and 

larger, the merchantable portion (or “merchantable bole”) includes the part of 

the tree bole from a 1-foot stump to a 4.0-inch top (d.o.b.). For trees measured 

at d.r.c., the merchantable portion includes all qualifying segments above the 

place(s) of diameter measurement for any tree with a single 5.0-inch stem or 

larger or a cumulative (calculated) d.r.c. of at least 5.0 inches to the 1.5-inch 

ends of all branches; sections below the place(s) of diameter measurement are 

not included. Qualifying segments are stems or branches that are a minimum of 

1 foot in length and at least 1.0 inch in diameter; portions of stems or branches 

smaller than 1.0 inch in diameter, such as branch tips, are not included in the 

merchantable portion of the tree.

Miscellaneous Federal lands—Public lands administered by Federal agencies 

other than the Forest Service, U.S. Department of Agriculture, or the Bureau of 

Land Management, U.S. Department of the Interior.

Mortality tree—All standing or down dead trees 5.0 inches d.b.h./d.r.c. and larger 

that were alive within the previous 5 years.

National Forest System (NFS) lands—Public lands administered by the Forest 

Service, U.S. Department of Agriculture, such as National Forests, National 

Grasslands, and some National Recreation Areas.

National Park lands—Public lands administered by the Park Service, U.S. 

Department of the Interior, such as National Parks, National Monuments, 

National Historic Sites (such as National Memorials and National Battlefields), 

and some National Recreation Areas.

Noncensus water—Portions of rivers, streams, sloughs, estuaries, and canals that 

are 30 to 200 feet wide and at least 1 acre in size; and lakes, reservoirs, and 

ponds 1 to 4.5 acres in size. Portions of rivers and streams not meeting the criteria for census water, but at least 30 feet wide and 1 acre in size, are considered 

noncensus water. Portions of braided streams not meeting the criteria for census 

water, but at least 30 feet in width and 1 acre in size, and more than 50 percent 

water at normal high-water level are also considered noncensus water.

Nonforest land—Land that does not support, or has never supported, forests, and 

lands formerly forested where tree regeneration is precluded by development 

for other uses. Includes areas used for crops, improved pasture, residential areas, city parks, improved roads of any width and adjoining rights-of-way, power 

line clearings of any width, and noncensus water. If intermingled in forest areas, 

unimproved roads and nonforest strips must be more than 120 feet wide, and 

clearings, etc., more than 1 acre in size, to qualify as nonforest land.

Nonindustrial private lands—Privately owned land excluding forest industry 

land.

Unreserved forest land—Forest land not withdrawn from management for production of wood products through statute or administrative designation.

Other private lands—Privately owned lands other than forest industry or Indian 

Trust.
68 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Other public lands—Public lands administered by agencies other than the Forest 

Service, U.S. Department of Agriculture. Includes lands administered by other 

Federal, State, county, and local government agencies, including lands leased 

by these agencies for more than 50 years.

Other wooded land—Land that has 5 to 10 percent cover of live tally tree species 

of any size, or land formerly having such tree cover, and not currently developed for a nonforest use. The minimum area for classification as forest land is 

1 acre. Roadside, stream-side, and shelterbelt strips of trees must be at least 

120 feet wide to qualify as forest land. Unimproved roads and trails, streams 

and other bodies of water, or natural clearings in forested areas are classified as 

forest, if less than 120 feet wide or 1 acre in size. Grazed woodlands, reverting 

fields, and pastures that are not actively maintained are included if above qualifications are satisfied.

Panel—A set of plots scheduled to be measured and remeasured in the same years. 

FIA divides each State’s plots into five panels that can be used independently, 

or in combination, to sample the population. Thus, after 5 years all of a State’s 

plots have been sampled, and each plot is remeasured every 5 years. Subpanels 

can be used to lengthen the measurement cycle to 7 or 10 years.

Poletimber-size trees—For trees measured at d.b.h, softwoods 5.0 to 8.9 inches 

d.b.h. and hardwoods 5.0 to 10.9 inches d.b.h. For trees measured at d.r.c., all 

live trees 5.0 to 8.9 inches d.r.c.

Primary wood-processing plants—An industrial plant that processes roundwood 

products, such as sawlogs, pulpwood bolts, or veneer logs.

Productive forest land—Forest land capable of producing 20 cubic feet per acre 

per year of wood from trees classified as a timber species (see Appendix A) on 

forest land classified as a timber forest type (see Appendix B).

Productivity—The potential yield capability of a stand calculated as a function 

of site index (expressed in terms of cubic-foot growth per acre per year at age 

of culmination of mean annual increment). Productivity values for forest land 

provide an indication of biological potential. Timberland stands are classified 

by the potential net annual growth attainable in fully stocked natural stands. For 

FIA reporting, Productivity Class is a variable that groups stand productivity 

values into categories of a specified range. Productivity is sometimes referred to 

as “Yield” or “Mean annual increment (MAI).”

Removals—The net volume of sound (growing-stock) trees removed from the 

inventory by harvesting or other cultural operations (such as timber-stand 

improvement), by land clearing, or by changes in land use (such as a shift to 

wilderness).

Reserved land—Land withdrawn from management for production of wood products through statute or administrative designation; examples include Wilderness 

areas and National Parks and Monuments.

Sampling error—A statistical term used to describe the accuracy of the inventory estimates. Expressed on a percentage basis in order to enable comparisons 

between the precision of different estimates, sampling errors are computed by 

dividing the estimate into the square root of its variance.

Sapling—A live tree 1.0 to 4.9 inches d.b.h./d.r.c.

Sawlog portion —The part of the bole of sawtimber-size trees between a 1-foot 

stump and the sawlog top.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 69

Sawlog top—The point on the bole of sawtimber-size trees above which a sawlog 

cannot be produced. The minimum sawlog top is 7 inches d.o.b. for softwoods, 

and 9 inches d.o.b. for hardwoods.

Sawtimber-size trees—Softwoods 9.0 inches d.b.h. and larger and hardwoods 

11.0 inches and larger.

Sawtimber volume—The growing-stock volume in the saw-log portion of sawtimber-size trees in board feet.

Seedlings—Live trees less than 1.0 inch d.b.h./d.r.c.

Site index—A measure of forest productivity for a timberland tree/stand. Expressed 

in terms of the expected height (in feet) of trees on the site at an index age 

of 50 (or 80 years for aspen and cottonwood). Calculated from height-to-age 

equations.

Site tree—A tree used to provide an index of site quality. Timber species selected 

for site index calculations must meet specified criteria with regards to age, diameter, crown class, and damage.

Snag—A standing-dead tree.

Softwood trees—Coniferous trees, usually evergreen, having needle- or scale-like 

leaves.

Stand—A community of trees that can be distinguished from adjacent communities due to similarities and uniformity in tree and site characteristics, such as 

age-class distribution, species composition, spatial arrangement, structure, etc.

Stand density—A relative measure that quantifies the relationship between trees 

per acre, stand basal area, average stand diameter, and stocking of a forested 

stand.

Stand density index (SDI)—A widely used measure developed by Reineke 

(1933), and is an index that expresses relative stand density based on a comparison of measured stand values with some standard condition; relative stand 

density is the ratio, proportion, or percent of absolute stand density to a reference level defined by some standard level of competition. For FIA reporting, the 

SDI for a site is usually presented as a percentage of the maximum SDI for the 

forest type. Site SDI values are sometimes grouped into SDI classes of a specified percentage range. Maximum SDI values vary by species and region.

Standing tree—To qualify as a standing dead tally tree, dead trees must be at least 

5.0 inches in diameter, have a bole that has an unbroken actual length of at least 

4.5 feet, and lean less than 45 degrees from vertical as measured from the base 

of the tree to 4.5 feet. Portions of boles on dead trees that are separated greater 

than 50 percent (either above or below 4.5 feet), are considered severed and are 

included in Down Woody Material (DWM) if they otherwise meet DWM tally 

criteria. For western woodland species with multiple stems, a tree is considered 

down if more than 2/3 of the volume is no longer attached or upright; do not 

consider cut and removed volume. For western woodland species with single 

stems to qualify as a standing dead tally tree, dead trees must be at least 5.0 

inches in diameter, be at least 1.0 foot in unbroken actual length, and lean less 

than 45 degrees from vertical.

Stand-size class—A classification of forest land based on the predominant diameter size of live trees presently forming the plurality of live-tree stocking. 

Classes are defined as follows:
70 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

• Sawtimber stand (Large-tree stand)—A stand at least 10 percent stocked 

with live trees, in which half or more of the total stocking is from live trees 

5.0-inches or larger in diameter, and with sawtimber (large tree) stocking 

equal to or greater than poletimber (medium tree) stocking.

• Poletimber stand (Medium-tree stand)—A stand at least 10 percent stocked 

with live trees, in which half or more of the total stocking is from live trees 

5.0 inches or larger in diameter, and with poletimber (medium tree) stocking 

exceeding sawtimber (large tree) stocking.

• Sapling/seedling stand—A stand at least 10 percent stocked with live trees, in 

which half or more of the total stocking is from live trees less than 5.0 inches 

in diameter.

• Nonstocked stand—A formerly stocked stand that currently has less than 10 

percent stocking, but has the potential to again become 10 percent stocked. 

For example, recently harvested, burned, or windthrow-damaged areas.

Stockability (Stockability factor)—An estimate of the stocking potential of a 

given site; for example, a stockability factor of 0.8 for a given site indicates that 

the site is capable of supporting only about 80 percent of “normal” stocking as 

indicated by yield tables. Stockability factors (maximum site value of 1.0) are 

assigned to sites based on habitat type/plant associations.

Stocking—An expression of the extent to which growing space is effectively utilized by live trees.

Subpanel—A further subdivision of the FIA five-panel system that allows for a 7- 

or ten-10 remeasurment cycle. Subpanels are used in Western States to establish 

a 10-year cycle, so that after 10 years all the plots have been sampled, and each 

plot is remeasured every 10 years. Using subpanels, each year’s plots can still be 

used independently, or in combination, to sample the population.

Timber species—Tally tree species with a typical growth form featuring relatively 

tall trees with a single stem or bole. This form dictates a separate set of field 

measurement and assessment protocols (as opposed to woodland species). Most 

importantly, diameter is measured at breast height (d.b.h.). Although this group 

includes species traditionally used for industrial wood products, it is not exclusive to them. Additionally, it is not uncommon for some timber species to be 

found on mixed-species plots that have a woodland forest type.

Timber stand improvement—A term comprising all intermediate cuttings or 

treatments, such as thinning, pruning, release cutting, girdling, weeding, or poisoning, made to improve the composition, health, and growth of the remaining 

trees in the stand.

Timberland—Unreserved forest land capable of producing 20 cubic feet per acre 

per year of wood from trees classified as a timber species (see Appendix A) on 

forest land designated as a timber forest type (see Appendix B).

Unproductive forest land—Forest land not capable of producing 20 cubic feet 

per acre per year of wood from trees classified as a timber species (see Appendix 

A) on forest land designated as a timber forest type and all forest lands designated as a woodland forest type (see Appendix B).

Wilderness area—An area of undeveloped land currently included in the 

Wilderness System, managed to preserve its natural conditions and retain its 

primeval character and influence.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 71

Woodland species—Tally tree species with a typical growth form featuring relatively short trees with a variable number of stems. This form dictates a separate 

set of field measurement and assessment protocols (as opposed to timber species). Most importantly, diameter is measured at the root collar (d.r.c.). These 

species (examples include pinyon, most junipers, mesquite, curlleaf mountainmahogany, and most intermountain maples and oaks) are not usually converted 

into industrial wood products, but may be utilized for specialty wood products 

(artisanal woods, fuel biomass including firewood, and fenceposts). Woodland 

species may be found in the understory of mixed-species plots that have a timber forest type.

Note: For the FIA national glossary please go to:

http://socrates.lv-hrc.nevada.edu/fia/ab/issues/pending/glossary.html.
72 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

X. References

Amacher, M. C.; Perry, C. H. 2011. Background technical report for Criterion 4. 

Conservation and maintenance of soil water resources: Indicator 19. Area and percent 

of forest land with significant soil degradation. National Report on Sustainable Forests - 

2010. FS-979. Washington, DC: U.S. Department of Agriculture, Forest Service.

Amman, G. D. 1973. Population changes of the mountain pine beetle in relation to elevation. Environmental Entomology. 2: 541-547.

Arner, S. L.; Woudenberg, S.; Waters, S.; [and others]. 2001. National algorithms for determining stocking class, stand size class, and forest type for Forest Inventory and Analysis 

plots. Unpublished report on file at: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Forestry Sciences Lab, Ogden, UT. Available online 

at http://www.fs.fed.us/fmsc/ftp/fvs/docs/gtr/Arner2001.pdf. Accessed 2/2/2012.

Arno, S. F. 1986. Whitebark pine cone crops: A diminishing source of wildlife food? 

Western Journal of Applied Forestry. 1(3): 92-94.

Arno, S. F.; Hoff, R. J. 1989. Silvics of whitebark pine (Pinus albicaulis). Gen. Tech. Rep. 

INT-253. U.S. Department of Agriculture, Forest Service, Intermountain Research 

Station. 14 p.

Bailey, R. G. 1995. Descriptions of the ecoregions of the United States. (2nd ed. rev. and 

expanded). Misc. Publ. No. 1391. Washington, DC: U.S. Department of Agriculture, 

Forest Service.

Bartos, D. L.; Campbell, R. B., Jr. 1998. Decline of quaking aspen in the Interior West—

examples from Utah. Rangelands. 20(1): 17-24.

Bechtold, W. A.; Patterson, P. L., eds. 2005. The enhanced Forest Inventory and Analysis 

program—National sampling design and estimation procedures. Gen. Tech. Rep. SRS80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research 

Station. 85 p.

Beers, T. W.; Miller, C. I. 1964. Point sampling; research results, theory and applications. 

Res. Bull. 786. Purdue University Agricultural Experiment Station. 55 p.

Brickell, J. E. 1970. Equations and computer subroutines for estimating site quality of 

eight Rocky Mountain species. Res. Pap. INT-75. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station.

Carroll, A. L.; Safranyik, L. 2004. The bionomics of the mountain pine beetle in lodgepole 

pine forests: Establishing a context. In: Shore, T. L.; Brooks, J. E.; Stone, J. E., eds. 

Mountain pine beetle symposium: Challenges and solutions; Proceedings: Challenges 

and solutions; October 30-31, 2003; Kelowna, British Columbia, Canada: 19-30.

Chojnacky, D. C. 1984. Volume and biomass for curlleaf cercocarpus in Nevada. Res. Pap. 

INT-332. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station. 8 p.

Chojnacky, D. C. 1985. Pinyon-juniper volume equations for the central Rocky Mountain 

States. Res. Note INT-339. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station.

Chojnacky, D. C. 1994. Volume equations for New Mexico pinyon-juniper dryland forests. Res. Note INT-471. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station.

Chojnacky, D. C.; Moisen, G. G. 1993. Converting wood volume to biomass for pinyon 

and juniper. Res. Note INT-411. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station. 5 p.

Cohen, S.; Miller, D. 1978. The big burn: The Northwest’s fire of 1910. Missoula, MT: 

Pictorial Histories Publishing Co. 96 p.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 73

Conner, R. C.; O’Brien, R. A. 1993. Montana’s forest resources. Resour. Bull. INT-81. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research 

Station. 96 p.

DeBlander, L. T.; Shaw, J. D.; Witt, C.; [and others]. 2010. Utah’s forest resources, 2000–

2005. Resour. Bull. RMRS-RB-10. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. 144 p.

Di Orio, A. P.; Callasa, R.; Schaefer, R. J. 2005. Forty-eight year decline and fragmentation 

of aspen (Populus tremuloides) in the South Warner Mountains of California. Forest 

Ecology and Management. 206(1-3): 307-313.

Dobkin, D. S.; Rich, A. C.; Pretare, J. A.; Pyle, W. H. 1995. Nest-site relationships among 

cavity-nesting birds of riparian and snowpocket aspen woodlands in the Northwestern 

Great Basin. Condor. 97: 694-707.

Edminster, C. B.; Mowrer, H. T.; Sheppard, W. D. 1985. Site index curves for aspen in 

the central Rocky Mountains. Res. Note RM-453. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station. 4 p.

Egan, T. 2009. The big burn: Teddy Roosevelt and the fire that saved America. Boston: 

Houghton Mifflin Harcourt. 324 p.

Eidenshenk, J.; Schwind, B.; Brewer, K.; [and others]. 2007. A project for monitoring 

trends in burn severity. Fire Ecology Special Issue. 3( 1) [online] http://fireecology.net/

docs/Journal/pdf/Volume03/Issue01/003.pdf. Accessed 5/2/2012.

Fiedler, C. E.; Friederici, P.; Petruncio, M. 2007. Monitoring old growth in frequent-fire 

landscapes. Ecology and Society. 12(2): 22. [online] http://www.ecologyandsociety.org/

vol12/iss2/art22/ Accessed 7/25/2011.

Flack, J. A. D. 1976. Bird populations of aspen forests in western North America. 

Ornithological Monographs 19. Washington, DC: American Ornithologist’s Union.

Gillespie, A. J. R. 1999. Rationale for a national annual forest inventory program. Journal 

of Forestry. 97(12): 16-20.

Gingrich, S. F. 1967. Measuring and evaluating stocking and stand density in uplandh forests in the Central States. Forest Science. 13: 38-53.

Green, A. W.; O’Brien, R. A.; Schaefer, J. C. 1985. Montana’s forests. Resour. Bull. INT38. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research 

Station. 70 p.

Green, P.; Joy, J.; Sirucek, D.; [and others]. 1992. Old-growth forest types of the northern 

region. R-1 SES 4/92. Missoula, MT: U.S. Department of Agriculture, Forest Service, 

Northern Region,

Hawksworth, F. G. 1977. The 6-class dwarf mistletoe rating system. Gen. Tech. Rep. RM48. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Forest and Range Experiment Station. 7 p.

Hessl, A. E.; Graumlich, L. J. 2002. Interactive effects of human activities, herbivory 

and fire on quaking aspen (Populus tremuloides) age structures in western Wyoming. 

Journal of Biogeography. 29: 889–902.

Hutchison, B. S.; Kemp, P. D. 1952. Forest Resources of Montana. Forest Resource Report 

No. 5. Washington, DC: U.S. Department of Agriculture, Forest Service, Northern 

Rocky Mountain Forest and Range Experiment Station. 76 p.

Jenny, H. 1994. Factors of soil formation—a system of quantitative pedology. Dover 

Edition. New York: Dover Publications. 191 p.

Johnson, M. 1994. Changes in Southwestern forests: Stewardship implications. Journal of 

Forestry. 92: 16-19.

Kaufmann, M. R.; Binkley, D.; Fulé, P. Z.; [and others]. 2007. Defining old growth for fireadapted forests of the western United States. Ecology and Society. 12(2): 15. [online] 

http://www.ecologyandsociety.org/vol12/iss2/art15/ Accessed 7/25/2011.

Kay, C. E. 1997. Is aspen doomed? Journal of Forestry. 95(5): 4–11.
74 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Keane, R. E.; Arno, S. F. 1993. Rapid decline of whitebark pine in western Montana: 

Evidence from 20-year remeasurements. Western Journal of Applied Forestry. 8(2): 

44-46.

Kegley, S.; Schwandt, J.; Gibson, K.; Perkins, D. 2011. Health of whitebark pine forests 

after mountain pine beetle outbreaks. In: Keane, R. E.; Tomback, D. F.; Murray, M. 

P.; Smith, C. M., eds. The future of high-elevation, five-needle white pines in Western 

North America: Proceedings of the High Five Symposium; 28-30 June 2010; Missoula, 

MT. Proceedings RMRS-P-63. Fort Collins: 85-93.

Kemp, P. D., 1956. Region 1 volume tables for ADP cruise computations. Timber Cruising 

Handbook, R1-2430-31. Missoula, MT: U.S. Department of Agriculture, Forest Service, 

Northern Region.

Kendall, K. C. 1980. Use of pine nuts by grizzly and black bears in the Yellowstone area. 

International Conference on Bear Research and Management. 5:166-173.

Kulakowski, D.; Veblen, T. T.; Drinkwater, S. 2004. The persistence of quaking aspen 

(Populus tremuloides) in the Grand Mesa area, Colorado. Ecological Applications. 14 

(5): 1603-1614.

Lilieholm, R. J.; Long, J. N.; Patla, S. 1994. Assessing goshawk nest stand habitat using stand density index. Cooper Ornithological Society. Studies in Avian Biology. 16: 

18-24.

Long, J. N. 1985. A practical approach to density management. Forest Chronicle. 61: 23-37.

Long, J. N.; Daniel, T. W. 1990. Assessment of growing stock in uneven-aged stands. 

Western Journal of Applied Forestry. 5: 93-96.

Long, J. N.; Shaw J. D. 2005. A density management diagram for even-aged ponderosa 

pine stands. Western Journal of Applied Forestry. 20: 205-215.

Lutes, D. C.; Keane, R. E.; Caratti, J. F. 2009. A surface fuel classification for estimating 

fire effects. International Journal of Wildland Fire. 18: 802-814.

Martin, K.; Aitken, K. E. H.; Weibe, K. L. 2004. Nest sites and nest webs for cavity-nesting 

communities in interior British Columbia, Canada: Nest characteristics and niche partitioning. Condor. 106 (1): 5-19.

McClelland, R. B.; Frissell, S. S.; Fischer, W. C.; Halvorson, C. H. 1979. Habitat management for hole-nesting birds in forests of western larch and Douglas-fir. Journal of 

Forestry. 77: 480-483.

McNab, W. H.; Cleland, D. T.; Freeouf, J. A.; [and others], comps. 2007. Description of 

ecological subregions: Sections of the conterminous United States. Gen. Tech. Report 

WO-76B. Washington, DC: U.S. Department of Agriculture, Forest Service. 80 p. 

[CD-ROM].

Moisen, G. G. 1990. Volume equations for timber species in western Montana and northern 

Idaho. Unpublished report on file at U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Inventory and Monitoring Program, Ogden, UT.

Myers, C. A. 1964. Volume tables and point-sampling factors for ponderosa pine in the 

Black Hills. Res. Note RM-8. U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station, Fort Collins, CO.

Pollard, J. E.; Westfall, J. A.; Patterson, P. L.; [and others]. 2006. Forest inventory and 

analysis national data quality assessment report 2000 to 2003. Gen. Tech. Rep. RMRSGTR-181. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 43 p.

Pyne, S. J. 2008. Year of the fires: The story of the great fires of 1910. Revised ed. Missoula, 

MT: Mountain Press Publishing Company. 320 p.

Reineke, L. H. 1933. Perfecting a stand density index for even-aged forests. Journal of 

Agricultural Research. 46(7): 627-638.

Rudinsky, J. A. 1962. Ecology of Scolytidae. Annual Review of Entomology. 7: 327-348.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 75

Schmidt, W. C.; McDonald, K. J., comps. 1990. Proceedings—Symposium on whitebark pine ecosystems: Ecology and management of a high-mountain resource. Gen. 

Tech. Rep. INT-270. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Intermountain Research Station. 386 p.

Shaw, J. D. 2000. Application of stand density index to irregularly structured stands, 

Western Journal of Applied Forestry. 15: 40-42.

Shaw, J. D.; Steed, B. E.; DeBlander, L. T. 2005. Forest Inventory and Analysis (FIA) annual inventory answers the question: What is happening to pinyon-juniper woodlands? 

Journal of Forestry. 103(6): 280-285.

Shaw, J. D.; Long, J. N. [In preparation]. Consistent definition and use of stand density 

index.

Smith, F. W.; Long, J. N. 1987. Elk hiding and thermal cover guidelines in the context of 

lodgepole pine stand density. Western Journal of Applied Forestry. 2: 6-10.

Spoelma, T. P.; Morgan, T. A.; Dillon, T.; [and others]. 2008. Montana’s forest products 

industry and timber harvest, 2004. Resour. Bull. RMRS-RB-8. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 36 p.

Stage, A. R. 1966. Simultaneous derivation of site-curve and productivity rating procedures. Society of American Foresters Proceedings. 1966: 134-136. [Original equations 

were reformulated by J. Shaw; documentation on file at Rocky Mountain Research 

Station, Ogden, UT.]

Stage, A. R. 1969. Computing procedure for grand fir site evaluation and productivity estimation. Res. Note INT-98. U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station.

Thompson, M. T. 2009. Analysis of conifer mortality in Colorado using Forest Inventory 

and Analysis’s annual forest inventory. Western Journal of Applied Forestry. 24(4): 

193-197.

Thompson, M. T.; Duda, J. A.; DeBlander, L. T.; [and others]. 2010. Colorado’s forest resources, 2002-2006. Resour. Bull. RMRS-RB-11. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 108 p.

USDA Forest Service. 1993. RMSTAND and RMRIS User’s guide. Ogden, UT: U.S. 

Department of Agriculture, Forest Service , Intermountain Region.

USDA Forest Service. 2003-2009a. IWFIA Forest Survey field procedures. Unpublished 

field guide on file at: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, Forestry Sciences Laboratory, Interior West Forest Inventory and 

Analysis Program, Ogden, UT. Available online at: http://www.fs.fed.us/rm/ogden/

data-collection/field-manuals.shtml. Accessed 5/2/2012.

USDA Forest Service. 2003-2009b. IWFIA Phase 3 field procedures. Unpublished field 

guide on file at: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, Forestry Sciences Laboratory, Interior West Forest Inventory and 

Analysis Program, Ogden, UT. Available online at: http://www.fs.fed.us/rm/ogden/

data-collection/field-manuals.shtml. Accessed 5/2/2012.

USDA Forest Service. 2006-2009. Forest Survey field procedures. Unpublished field guide 

on file at: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station, Forestry Sciences Laboratory, Interior West Forest Inventory and Analysis 

Program, Ogden, UT. Available online at: http://fsweb.ogden.rmrs.fs.fed.us/manual/

manual.html. Accessed 5/2/2012.

USDA Forest Service. 2011. IWFIA Forest Survey field procedures, Ver. 5.0. Unpublished 

field guide on file at: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, Forestry Sciences Laboratory, Interior West Forest Inventory and 

Analysis Program, Ogden, UT. Available online at: http://www.fs.fed.us/rm/ogden/

data-collection/field-manuals.shtml; last accessed August 2011.
76 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Van Hooser, D. D.; Chojnacky, D. C. 1983. Whole tree volume estimates for the Rocky 

Mountain States. Res. Bull. INT-29. U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station.

Vosick, D.; Ostergren, D. M.; Murfitt, L. 2007. Old-growth policy. Ecology and Society. 

12(2): 19. [online] http://www.ecologyandsociety.org/vol12/iss2/art19. Accessed 

7/25/2011.

Wilson, M. J.; Deblander, L. T.; Halverson, K. A. 2010. Resource impacts of the 1910 

fires: A Forest Inventory and Analysis (FIA) perspective. Powerpoint presentation given 

at: 1910 Fires: A Century Later. Wallace, Idaho, May 20-22, 2010. On file at: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station, Forestry 

Sciences Laboratory, Interior West Forest Inventory and Analysis Program, Ogden, UT.

Woodall, C. W.; Monleon, V. J. 2008. Sampling protocol, estimation, and analysis procedures for the down woody materials indicator of the FIA program. Gen. Tech. Rep. 

NRS-22. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station. 68 p.

Worrall, J. J.; Egeland, L.; Eager, T.; [and others]. 2008. Rapid mortality of Populus tremuloides in southwestern Colorado, USA. Forest Ecology and Management. 255(3-4): 

686-696.

Woudenberg, S. W.; Conkling, B. L.; O’Connell, B. M.; [and others]. 2010. The Forest 

Inventory and Analysis Database: Database description and users manual version 4.0 

for Phase 2. Gen. Tech. Rep. RMRS-GTR- 245. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 339 p.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 77

Appendix A: Inventory History

It is often desirable to compare data from new inventories with data from earlier 

inventories to determine trends in forest resources. However, for the comparisons 

to be valid, the procedures used in the two inventories must be compatible. There 

are several differences between the data used for this report and older data that 

need to be considered before comparing inventory data or estimates. These can be 

grouped as issues of sampling frame, the spatial and temporal sequence of sampling, and sampling or data compilation protocols.

In considering these factors, the point needs to be made that the 1989 Montana 

report (Connor and O’Brien 1993) and the “1989” data available through the FIA 

database (FIADB) tools and download do not represent the same inventory. The 

differences between the two are detailed below.

Appendix A figure 1(A and B) compares the sampling frame for the 1989 report and the 1989 inventory in FIADB. The report was based on data from field 

plots only on non-reserved lands (area estimates for reserved areas were obtained 

through aerial photo interpretation) and non-National Forest lands. Summarized 

data for National Forests were taken from the Resource Planning Act (RPA) database. No detailed FIA plot-level data were available for reserved lands or National 

Forest lands. Most areas were sampled at the standard (1x) grid intensity, and State 

lands west of the Continental Divide had extra plots installed. Because of the spatial distribution of State lands, a standard double intensity (2x) grid was not effective, and the extra plots equate to a little less than a 2x intensity. The Connor 

and O’Brien (1993) report details differences in data sources in the introduction, 

procedure description, and various inventory tables.

Beginning in 1993, the Forest Service Northern Region Inventory Service 

Center, with cooperation from what was then the FIA unit of the Intermountain 

Research Station, sampled field plots on all Montana National Forest lands, including wilderness areas. In addition, during the most recent Wyoming periodic 

inventory (nominally the 2000 inventory), plots in the Montana and Idaho portions 

of Yellowstone National Park were sampled. These subsequent plots were installed 

at the standard 1x intensity. All of the plots sampled after the 1989 report were 

added to the FIADB under the “1989” inventory. These data filled in many of the 

areas missing from the report; but some heavily forested areas, including Glacier 

National Park and various tribal timber reserves, do not have data in the FIADB. 

Some less-forested non-sampled areas include the Bighorn Canyon National 

Recreation Area, the Upper Missouri Wild and Scenic River, and U.S. Fish and 

Wildlife Service wilderness areas. In contrast, all areas and ownerships in Montana 

have been sampled in the 2003-2009 inventory, but because the full cycle is not yet 

complete, the sampling intensity is currently only 70 percent (0.7x). Differences in 

sampling intensity will influence the sampling error for inventory estimates, with 

higher errors for smaller samples. Non-sampled areas introduce bias and imbalance in inventory estimates.

The differences in spatial and temporal sequence of plot sampling between annual and periodic inventories can be important when comparing some data. Appendix 

A figure 2(A and B) compares plot measurement year for forested plots for the 

1989 and 2003-2009 Montana inventories. In Appendix A figure 2A, it is possible 

to see how field crews moved about the State while completing the inventory. For 

the report data, crews worked on plots in the east and south in 1988, and moved to 

the northwest in 1989. Crews completing plots on National Forests began in the 
78 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

northwest in 1993 and worked to the southeast, finishing on the Gallatin National 

Forest in 1998. Yellowstone National Park plots were done in 1999, and a few plots 

on the Montana portions of the Idaho Panhandle National Forest were completed 

with that Forest in 2000 and 2001. As a result, plots from any given measurement year will be spatially biased (see “Damage to Live Trees” in Section VI). In 

contrast, Appendix A figure 2B shows how, under the annual system, the plots in 

any given measurement year are spread evenly across the State, so that plots and 

estimates from different measurement years can be compared without introducing 

as much spatial bias.

There have been several changes in sampling and compilation protocols from 

1988 to 2009 that affect inventory comparisons. Sampling protocols include the 

plot design or layout, determination of whether a plot is forested, and how to determine which trees get measured. The most relevant compilation protocol is the 

calculation of forest type.

For most of the 1989 inventory sampling period, two basic plot designs were 

used: a variable-radius, multi-point plot for timber-type stands (see “Whitebark 

Pine Status” in Section V) and a single fixed-radius plot for woodland-type stands. 

It should be noted that both designs employed rules to ensure that the entire plot 

was in a single condition: variable-radius sampling points were rotated into the 

central condition if they occurred on contrasting conditions, and fixed-radius plots 

were shifted so that the entire plot fell within the condition occurring at the center 

point. Appendix A figure 3(A and B) shows the various plot designs used during 

the periodic inventory compared to the consistent use of the mapped plot design 

(described in Section II, “Plot Configuration”) during the 2003-2009 annual inventory. In the 1989 inventory, only 15 plots were installed using the fixed-radius 

woodland design. These were a single plot with a radius of 26.3, 37.2, or 52.7 feet 

(1/20, 1/10, or 1/5 of an acre, respectively), depending on woodland type or tree 

density. They had four 6.8-foot radius microplots, at 45, 135, 225, and 315 degrees 

from the main plot center at 15 or 25 feet, depending on the size of the main plot. 

The timber-type variable radius plots used a 40 basal area factor (BAF) and 6.8-foot 

radius microplots, but the number of sampling points in the cluster and microplots 

changed over time. In 1988 and 1989, a ten-point cluster with three microplots 

(centered on points 1, 2, and 3) was used. The National Forest inventory began in 

1993 with a seven-point cluster, each with a centered microplot. This changed to a 

five-point cluster with centered microplots on every point, beginning in 1994. The 

five-point cluster was used exclusively for timber-type plots from 1995 to 1998. In 

1999, the mapped plot design was introduced, and used for all plots in Yellowstone 

National Park and the Idaho Panhandle National Forest. Some of the mapped plots 

had microplots centered on the subplot, rather than offset 12 feet. Differences in 

plot design alone do not introduce major difficulties in comparing inventory results 

and estimates, since tree and area expanders are set appropriately; however, these 

design changes were also accompanied by changes in sampling and compilation 

protocols that, when paired with non-sampled areas, present reason for caution.

Over the course of the 1989 and 2003-2009 inventories, the field determination 

of whether a plot is forested, and therefore whether to measure it, has varied. This 

is based on crown cover, or evidence of recent crown cover such as stumps or 

dead trees. For variable-radius timber-type plots measured from 1988 to 1997, the 

requirement was 5 percent crown cover of timber species. For fixed-radius woodland plots in the same time frame, the requirement was 10 percent crown cover 

of all trees, but less than 5 percent of timber species. For periodic mapped plots 

measured from 1998 to 2001, 5 percent cover of all qualifying, or tally, trees was 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 79

required for forested conditions. In the annual inventory (2003-2009), a minimum 

crown cover of 10 percent for all tally species is required (see definition of forest 

land in Section IX). Since IWFIA continues to collect data for conditions with 5 

to 9 percent cover (now called “other wooded land,” see Section IX “Standard 

Forest Inventory and Analysis Terminology”; also see DeBlander and others 2010, 

Appendix A), we know that the area estimate for Montana is only 655 thousand 

acres in this cover range. The impact on tree-based estimates (number of trees, 

biomass, volume, growth, and mortality) is minimal, since these acres support few 

trees.

The amount of crown cover will depend somewhat on what qualifies as a tree 

in the inventory. This has also varied over the course of the two inventories. All 

of the major timber-type conifers in Montana have been consistently included in 

all recent inventories; however, the inclusion and measurement of woodland types 

and hardwoods have been less consistent. On plots measured from 1988 to 1997, 

woodland trees were evaluated according to growth form, and trees were excluded 

that did not meet specified tree-form requirements (the capacity to produce at least 

one stem 3 inches or larger in diameter at root collar, and 8 feet or more in length 

to a minimum branch diameter of 1.5 inches). This would have more impact on 

hardwood woodland types like Rocky Mountain maple and curlleaf mountainmahogany than it would on junipers. From 1998 and during the 2003-2009 annual 

inventory, qualifying trees were determined by species, and whether the species 

was on the inventory list. For many hardwoods, inclusion on the inventory list 

changed over time. Only paper birch, curlleaf mountain-mahogany, quaking aspen, 

and cottonwoods (balsam, plains, black, and narrowleaf) have consistently been 

included in species lists. Species added for periodic mapped plots and/or annual 

inventories include boxelder, red alder, green ash, American elm, and water birch. 

Rocky Mountain maple was included from 1988 to 1997, but dropped for mapped 

plot design. Over the same period, crews were allowed to record a generic code 

for cottonwoods (Populus spp.), but after 1998 they were required to identify cottonwoods to species (or subspecies in the case of black cottonwood). The same 

would appear to be true for generic maples (Acer spp.), but in the 1988-1989 field 

manual, the code used for Rocky Mountain maple is the same code that was later 

used for Acer spp.

Data compilation changes resulting in different forest types for annual and periodic inventories have also occurred. In the 1989 report, the sample-based data 

used different forest types than the RPA and photo-interpreted data. Most of these 

differences are explained in the report (Connor and O’Brien 1993). With annual 

inventory, several new forest types were introduced. The most significant of these 

is the subalpine fir forest type, the most abundant type in the fir-spruce-mountain 

hemlock group, which is Montana’s second most common type in the current report. Stands with this species composition are included in the Engelmann sprucesubalpine fir forest type in the periodic data (referred to as “spruce-fir” in the 1989 

report). Also new is the Rocky Mountain juniper forest type, which is included in 

juniper woodland in periodic data. Since several hardwoods have been included in 

species lists, there are a few hardwood forest types that are new to IWFIA inventories, including sugarberry-hackberry-elm-green ash, elm-ash-black locust, and 

red alder. Reporting for the nonstocked forest type is also somewhat different in 

annual inventories. If there are not enough live trees encountered on a condition, 

the forest type algorithm assigns a type of nonstocked. However, field crews use 

evidence in the plot vicinity to assign a forest type. In many periodic reports the 

nonstocked forest type was replaced with the field forest type, and nonstocked was 
80 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

retained only as a stand size class. For RPA data in the 1989 report, nonstocked 

stands are included in “miscellaneous western softwoods.”

Another factor influencing apparent increases in forest land has been the improvement of aerial photography for identifying plot locations that may have small 

or isolated forest areas in the vicinity. It would appear that many plots in areas 

like eastern Montana have been missed in past inventories, as pre-field personnel 

identify plots for field visits. Appendix A figures 2(A and B) and 3(A and B) show 

that although the overall density of forested plots is lower in the 2003-2009 inventory than in the 1989 inventory, there are more forested plots in the eastern portion 

of the State. Inclusion of more hardwood species and dropping the growth form 

criteria from Rocky Mountain juniper may also be contributing to this increase.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 81

Figure A1—Comparison of sampling frames for Montana’s 1989 report (A) and 1989 database inventory (B), showing areas sampled, 

and sampling intensity.
82 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Figure A2—Location of forested plots for Montana’s 1989 inventory (A) compared to Montana’s 2003-2009 inventory (B) showing year 

of measurement for each, with generalized model (1 km pixels) of predicted forest and non-forest.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 83

Figure A3—Location of forested plots for Montana’s 1989 inventory (A) compared to Montana’s 2003-2009 inventory (B) showing 

plot designs for each, with generalized model (1 km pixels) of predicted forest and non-forest.
84 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Appendix B: Species Groups, Common Names, Scientific Names, and 

Timber (T) or Woodland (W) Designation for Trees 

Cottonwood and aspen

Black cottonwood (Populus basamifera ssp. trichocarpa) T 

Narrowleaf cottonwood (Populus angustifolia) T

Plains cottonwood (Populus deltoides ssp. monilifera) T

Quaking aspen (Populus temuloides) T

Douglas-fir

Douglas-fir (Pseudotsuga menziesii) T

Engelmann and other spruces

Engelmann spruce (Picea engelmannii) T

Lodgepole pine

Lodgepole pine (Pinus contorta) T

Other western hardwoods

American elm (Ulmus americana) T

Boxelder (Acer negundo) T

Green ash (Fraxinus pennsylvanica) T

Paper birch (Betula papyrifera) T

Water birch (Betula occidentalis) T

Other western softwoods

Limber pine (Pinus flexilis) T

Mountain hemlock (Tsuga mertensiana) T

Pacific yew (Taxus brevifolia) T

Subalpine larch (Larix lyallii) T

Whitebark pine (Pinus albicaulis) T

Ponderosa and Jeffrey pines

Ponderosa pine (Pinus ponderosa) T

Red alder

Red alder (Alnus rubra) T

True fir

Grand fir (Abies grandis) T

Subalpine fir (Abies lasiocarpa) T

Western hemlock

Western hemlock (Tsuga heterophylla) T

Western larch

Western larch (Larix occidentalis) T

Western redcedar

Western redcedar (Thuja plicata) T

Western white pine

Western white pine (Pinus monticola) T

Western woodland hardwoods

Curlleaf mountain-mahogany (Cercocarpus ledifolius) W

Western woodland softwoods

Rocky Mountain juniper (Juniperus scopulorum) W

Utah juniper (Juniperus osteosperma) W
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 85

Appendix C: Forest Type Groups, Forest Type Names, and Timber (T) 

or Woodland (W) Designation for Forest Types

Alder-maple group

Red alder T

Aspen-birch group

Aspen T

Paper birch T

Douglas-fir group

Douglas-fir T

Elm-ash-cottonwood group

Cottonwood T

Cottonwood-willow T

Sugarberry-hackberry-elm-green ash T

Fir-spruce-mountain hemlock group

Engelmann spruce T

Engelmann spruce-subalpine fir T

Grand fir T

Mountain hemlock T

Subalpine fir T

Hemlock-Sitka spruce group

Western hemlock T

Western redcedar T

Lodgepole pine group

Lodgepole pine T

Nonstocked

Nonstocked T or W

Oak-hickory group

Elm-ash-black locust T

Other western softwoods group

Limber pine T

Miscellaneous western softwoods T

Whitebark pine T

Pinyon-juniper group

Juniper woodland W

Rocky Mountain juniper W

Ponderosa pine group

Ponderosa pine T

Western larch group

Western larch T

Woodland hardwoods group

Cercocarpus (mountain brush) woodland W
86 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Appendix D: Volume, Biomass, and Site Index Equation Sources

Volume

Chojnacky (1985) was used for curlleaf mountain-mahogany volume 

estimation.

Chojnacky (1994) was used for Rocky Mountain juniper and Utah juniper 

volume estimation.

Kemp (1956) was used for black cottonwood, Engelmann spruce, mountain hemlock, narrowleaf cottonwood, paper birch, plains cottonwood, 

quaking aspen, red alder, subalpine fir, water birch, western hemlock, 

and western redcedar volume estimation.

Moisen (1990) was used for Douglas-fir, grand fir, limber pine, lodgepole 

pine, Pacific yew, subalpine larch, western larch, western white pine, 

and whitebark pine volume estimation; and for ponderosa pine volume 

estimation in eastern Montana.

Myers (1964) was used for ponderosa pine volume estimation in western 

Montana.

Volume equations provided by the USDA Forest Service’s Northern 

Research Station were used for American elm, boxelder, and green 

ash volume estimation. [Documentation on file at U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, 

UT.]

Biomass

Chojnacky (1984) was used for curlleaf mountain mahogany biomass 

estimation.

Chojnacky and Moisen (1993) was used for Rocky Mountain juniper and 

Utah juniper biomass estimation.

Van Hooser and Chojnacky (1983) was used for all timber (T) species 

biomass estimation.

Site Index

Brickell (1970) was used for Douglas-fir, Engelmann spruce, limber pine, 

lodgepole pine, ponderosa pine, subalpine fir, subalpine larch, western 

larch, western white pine, and whitebark pine site index estimation.

Edminster and others (1985) was used for American elm, black cottonwood, boxelder, green ash, narrowleaf cottonwood, paper birch, plains 

cottonwood, quaking aspen, and red alder site index estimation.

Stage (1966, 1969) was used for grand fir site index estimation. [Original 

equations were reformulated by J. Shaw; documentation on file at U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research 

Station, Ogden, UT.]

Equations from RMSTAND (USDA Forest Service 1993) were used for 

mountain hemlock, western hemlock, and western redcedar site index 

estimation.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 87

Appendix E: Forest Resource Tables.

Table 1: Percentage of area by land status.

Table 2: Area of accessible forest land by owner class and forest land status.

Table 3: Area of accessible forest land by forest type group and productivity class.

Table 4: Area of accessible forest land by forest type group, ownership group, and 

land status.

Table 5: Area of accessible forest land by forest type group and stand-size class.

Table 6: Area of accessible forest land by forest type group and stand-age class.

Table 7: Area of accessible forest land by forest type group and stand origin.

Table 8: Area of forest land by forest type group and primary disturbance class.

Table 9: Area of timberland by forest type group and stand-size class.

Table 10: Number of live trees on forest land by species group and diameter class.

Table 11: Number of growing stock trees on timberland by species group and diameter class.

Table 12: Net volume of all live trees by owner class and forest land status.

Table 13: Net volume of all live trees on forest land by forest type group and standsize class.

Table 14: Net volume of all live trees on forest land by species group and ownership group.

Table 15: Net volume of all live trees on forest land by species group and diameter 

class.

Table 16: Net volume of all live trees on forest land by forest type group and stand 

origin.

Table 17: Net volume of growing stock trees on timberland by species group and 

diameter class.

Table 18: Net volume of growing stock trees on timberland by species group and 

ownership group.

Table 19: Net volume of sawtimber trees (International 1/4 inch rule) on timberland by species group and diameter class.

Table 20: Net volume of sawtimber trees on timberland by species group and ownership group.

Table 21: Average annual net growth of all live trees by owner class and forest land 

status.

Table 22: Average annual net growth of all live trees on forest land by forest type 

group and stand-size class.

Table 23: Average annual net growth of all live trees on forest land by species 

group and ownership group.

Table 24: Average annual net growth of growing stock trees on timberland by species group and ownership group.

Table 25: Average annual mortality of all live trees by owner class and forest land 

status.

Table 26: Average annual mortality of all live trees on forest land by forest type 

group and stand-size class.

Table 27: Average annual mortality of all live trees on forest land by species group 

and ownership group.
88 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Table 28: Average annual mortality of growing stock trees on timberland by species group and ownership group.

Table 29a: Aboveground dry weight (regional equation method) of all live trees by 

owner class and forest land status.

Table 29b: Aboveground dry weight (component ratio method) of all live trees by 

owner class and forest land status.

Table 30a: Aboveground dry weight (regional equation method) of all live trees on 

forest land by species group and diameter class.

Table 30b: Aboveground dry weight (component ratio method) of all live trees on 

forest land by species group and diameter class.

Table 31: Area of accessible forest land by Forest Survey Unit, county and forest 

land status.

Table 32: Area of accessible forest land by Forest Survey Unit, county, ownership 

group and forest land status.

Table 33: Area of timberland by Forest Survey Unit, county and stand-size class.

Table 34: Area of timberland by Forest Survey Unit, county and stocking class.

Table 35: Net volume of growing stock and sawtimber (International 1/4 inch rule) 

on timberland by Forest Survey Unit, county, and major species group.

Table 36: Average annual net growth of growing stock and sawtimber (International 

1/4 inch rule) on timberland by Forest Survey Unit, county, and major species 

group.

Table 37: Sampling errors by Forest Survey Unit and county for area of timberland, volume, average annual net growth, average annual removals, and average 

annual mortality on timberland.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 89

Accessible forest land

Unreserved forest land

Unproductive

Reserved forest land

Nonforest and other land

Water

Nonsampled land

Table 1--Percentage of area by land status, Montana, 

Total area (thousands of acres)

Timberland 20.1

 1.6

Total unreserved forest land 21.7

Productive 3.8

Total reserved forest land 4.1

Nonforest land 69.8

Non-Census 0.1

Access denied 2.4

All land

 94,107

All table cells without observations in the inventory sample are indicated 

by --. Table value of 0.0 indicates the percentage rounds to less than 0.1

percent. Columns and rows may not add to their totals due to rounding.

Land status Percentage of area

100.0

Other 0.5

Hazardous conditions 0.5

All nonforest and other land 70.8

Census 0.8

All accessible forest land 25.8

Unproductive 0.3

Table 1--Percentage of area by land status, Montana, cycle 2, 2003-2009.
90 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Forest Service Other Federal State and local government Private National forest National Park Service Bureau of Land Management Fish and Wildlife Service Other Federal State Local (county, municipal, etc.) Undifferentiated private 12,239.6 - - 851.6 - - - - 825.5 10.2 5,947.5 Table 2--Area of accessible forest land by owner class and forest land status, Montana, cycle 2, 2003-2009. 471.4 - - 256.1 - - - - 103.1 - - 804.0 12,711.1 - - 1,107.7 - - - - 928.6 10.2 6,751.5 2,596.1 863.5 73.4 93.7 8.2 - - - - 156.4 (Table 2 continued on next page) 19,874.5 1,634.7 21,509.1 3,791.5 All owners All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. 92.7 44.6 50.5 93.2 - - - - - - 9.2 2,688.9 908.1 123.9 186.9 8.2 - - - - 165.7 15,399.9 908.1 1,231.6 186.9 8.2 928.6 10.2 6,917.2 290.2 4,081.7 25,590.8 Owner class Timberland Unproductive Total Productive Unreserved forests Reserved forests Unproductive Total All forest land Table 2--Area of accessible forest land by owner class and forest land status, Montana, cycle 2, 2003-2009. (In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 91 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+ Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. (In thousand acres) Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+
92 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock group Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked - - 3,824.3 653.5 2,879.7 2,999.3 197.8 638.9 416.0 - - 5.8 95.6 6.7 - - 522.1 Table 4--Area of accessible forest land by forest type group, ownership group, and land status, Montana, cycle 2, 2003-2009. 62.2 415.2 8.9 1,266.2 662.9 8.9 20.0 411.0 - - 10.9 44.1 - - - - 250.1 - - 379.2 217.7 24.6 101.4 - - 6.8 8.2 - - - - 2.3 - - - - 111.3 294.7 162.1 119.0 435.2 154.1 8.7 52.3 36.7 - - - - 43.1 - - 15.9 161.4 (Table 4 continued on next page) 12,239.6 3,160.3 851.6 1,483.2 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 293.7 233.3 67.1 56.9 - - 65.7 8.7 - - 17.3 13.3 - - - - 79.7 45.4 - - 24.4 - - 9.4 - - - - 9.4 - - 2.2 - - - - - - 12.3 835.7 103.1 5,947.5 25,590.8 969.7 - - 2,335.6 1,659.6 351.8 348.7 17.8 152.2 9.4 8.6 153.5 247.1 - - - - 663.1 402.8 106.8 102.3 6.5 33.3 8.2 - - 49.4 15.0 48.8 76.6 - - 2.1 118.0 Forest-type group Timber- land Other forest land Timber- land Other forest land Forest Service Timber- land Other forest land Timber- land Other forest land All forest land Other Federal State and local government Undifferentiated private 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 Table 4--Area of accessible forest land by forest type group, ownership group, and land status, Montana, cycle 2, 2003-2009. (In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 93 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 558.2 5,273.5 2,062.5 3,230.1 1,500.1 205.7 588.9 549.8 8.6 183.2 58.8 - - - - - - Table 5--Area of accessible forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. 134.7 1,059.1 387.0 701.0 1,796.5 26.8 134.1 214.8 15.0 31.0 154.4 6.7 - - - - 112.1 1,184.4 569.1 1,100.1 1,069.3 8.9 213.0 184.1 - - 24.2 308.9 - - 18.0 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 5 continued on next page) 14,219.4 4,661.2 4,792.1 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - - - - - 1,918.0 1,918.0 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 Large diameter Medium diameter Small diameter Chaparral Stand-size class Forest-type group Nonstocked All size classes Table 5--Area of accessible forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. (In thousand acres) Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+
94 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock group Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked - - - - - - - - - - - - - - - - - - - - - - - - - - 1,918.0Table 6--Area of accessible forest land by forest type group and stand-age class, Montana, cycle 2, 2003-2009. 64.1 951.7 526.0 731.5 866.2 8.9 195.3 94.3 - - 24.2 256.7 - - - - - - 86.2 217.7 76.9 337.8 96.3 - - 26.5 80.4 - - 6.9 42.4 - - 11.1 - - 138.3 275.3 200.5 135.3 197.8 8.9 69.0 18.2 6.4 32.9 73.5 - - 7.0 - - (Table 6 continued on next page) 1,918.0 3,718.9 982.2 1,163.1 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. 160.6 839.0 456.4 249.6 471.7 29.0 132.0 17.7 8.6 33.1 64.5 6.7 - - - - 119.8 1,693.9 715.2 565.0 951.4 60.9 152.9 88.9 - - 83.9 60.0 - - - - - - 126.3 1,371.7 589.1 531.9 725.9 73.6 138.7 126.4 8.6 42.1 15.8 - - - - - - 2,468.9 4,492.0 3,750.2 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 46.4 794.3 186.7 775.1 476.7 46.6 63.1 58.8 - - 2.2 9.1 - - - - - - 29.3 488.7 138.9 508.2 303.6 13.4 22.1 113.3 - - 13.0 - - - - - - - - 16.9 515.0 50.0 457.8 168.4 - - 52.8 121.3 - - - - - - - - - - - - 17.2 202.6 49.5 348.0 78.0 - - 36.6 50.5 - - - - - - - - - - - - - - 167.0 29.4 391.0 29.9 - - 46.8 179.1 - - - - - - - - - - - - 2,459.0 1,630.7 1,382.3 782.3 843.1 Non stocked 1-20 21-40 41-60 Stand-age class (years) Forest-type group 61-80 81-100 All classes 101-120 121-140 141-160 161-180 181-200 201+ Table 6--Area of accessible forest land by forest type group and stand-age class, Montana, cycle 2, 2003-2009. (In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 95

Pinyon / juniper group

Douglas-fir group

Ponderosa pine group

Fir / spruce / mountain hemlock grou

Lodgepole pine group

Hemlock / Sitka spruce group

Western larch group

Other western softwoods group

Oak / hickory group

Elm / ash / cottonwood group

Aspen / birch group

Alder / maple group

Woodland hardwoods group

Nonstocked

 805.1

 7,473.6

 2,982.5

 5,013.6

 4,348.5

 241.4

 924.9

 948.8

 23.6

 238.5

 513.5

 6.7

 18.0

 1,913.6

Table 7--Area of accessible forest land by forest type group and stand origin,

 - -

 43.4

 36.1

 17.6

 17.4

 - -

 11.1

 - -

 - -

 - -

 8.6

 - -

 - -

 4.5

(Table 7 continued on next page)

All forest-type groups 25,452.1 138.7

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the

acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 805.1

 7,517.0

 3,018.6

 5,031.2

 4,365.9

 241.4

 936.0

 948.8

 23.6

 238.5

 522.1

 6.7

 18.0

 1,918.0

 25,590.8

Natural

stands

Artificial

 regeneration

Stand origin

 Forest-type group

All forest

land

Table 7--Area of accessible forest land by forest type group and stand origin, Montana, cycle 2, 2003-2009.

(In thousand acres)

Pinyon / juniper group

Douglas-fir group

Ponderosa pine group

Fir / spruce / mountain hemlock grou

Lodgepole pine group

Hemlock / Sitka spruce group

Western larch group

Other western softwoods group

Oak / hickory group

Elm / ash / cottonwood group

Aspen / birch group

Alder / maple group

Woodland hardwoods group

Nonstocked

 805.1

 84.3

 153.7

 77.4

 109.4

 - -

 - -

 270.0

 15.0

 51.0

 85.2

 - -

 18.0

 255.8

Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cy

 - -

 4,627.5

 2,245.6

 2,537.4

 3,330.3

 8.7

 142.0

 678.8

 8.6

 105.9

 331.8

 - -

 - -

 1,380.9

 - -

 2,339.6

 533.6

 1,930.4

 885.5

 109.3

 577.9

 - -

 - -

 41.6

 100.1

 6.7

 - -

 254.6

 - -

 421.1

 63.7

 462.0

 40.8

 114.4

 163.5

 - -

 - -

 40.0

 5.0

 - -

 - -

 26.7

All forest-type groups 1,924.8 15,397.5 6,779.3 1,337.3

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less

than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 

0-19 20-49 50-84 85-119

Site-productivity class (cubic feet/acre/

 Forest-type group 12
96 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock group Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 766.4 6,274.2 2,640.3 4,127.6 3,682.8 214.6 745.7 777.2 17.2 202.7 371.1 6.7 18.0 1,293.6 Table 8--Area of forest land by forest type group and primary disturbance class, Montana, cycle 2, 2003-2009. - - 690.0 57.0 323.5 291.5 - - 39.7 64.1 - - - - 14.2 - - - - 28.6 22.2 312.2 35.3 426.6 228.9 17.9 64.1 81.2 6.4 - - 32.5 - - - - 11.0 12.4 8.9 41.8 12.1 - - - - 8.9 1.3 - - 17.5 4.9 - - - - - - (Table 8 continued on next page) 21,138.0 1,508.6 1,238.3 107.9 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. 4.0 166.8 172.2 97.2 130.1 - - 68.6 22.9 - - - - 81.8 - - - - 565.3 - - 64.9 35.1 2.1 - - - - - - - - - - 11.4 17.7 - - - - 7.1 - - - - 36.9 - - 18.1 - - 8.9 - - - - 6.8 - - - - - - 3.5 1,308.9 138.3 74.2 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 8.7 8.9 8.9 - - - - - - - - - - - - - - - - 26.6 Forest-type group All forest land None Insects Disease WeatherDisturbance class Fire Domestic animals Wild animals Human Other Table 8--Area of forest land by forest type group and primary disturbance class, Montana, cycle 2, 2003-2009. (In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 97 Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Nonstocked 4,765.0 1,924.4 2,159.6 1,214.3 179.9 534.0 292.5 8.6 137.1 50.3 - - - - Table 9--Area of timberland by forest type group and stand-size class, Montana, cycle 2, 2003-2009. 926.2 322.7 467.9 1,518.8 26.8 134.1 88.6 - - 26.1 94.1 6.7 - - 1,141.7 517.0 695.8 773.1 8.9 195.5 61.3 - - 13.3 213.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 5 continued on next page) 11,265.9 3,611.8 3,620.5 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - 1,376.3 1,376.3 6,832.9 2,764.0 3,323.3 3,506.2 215.6 863.6 442.4 8.6 176.6 358.4 6.7 1,376.3 19,874.5 Large diameter Medium diameter Small diameter Chaparral Stand-size class Forest-type group Nonstocked All size classes Table 9--Area of timberland by forest type group and stand-class, Montana, cycle 2, 2003-2009. (In thousand acres) Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Nonstocked 4,765.0 1,924.4 2,159.6 1,214.3 179.9 534.0 292.5 8.6 137.1 50.3 - - - - Table 9--Area of timberland by forest type group and stand-size class, Montana, cycle 2, 2003-2009. 926.2 322.7 467.9 1,518.8 26.8 134.1 88.6 - - 26.1 94.1 6.7 - - 1,141.7 517.0 695.8 773.1 8.9 195.5 61.3 - - 13.3 213.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 5 continued on next page) 11,265.9 3,611.8 3,620.5 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - 1,376.3 1,376.3 6,832.9 2,764.0 3,323.3 3,506.2 215.6 863.6 442.4 8.6 176.6 358.4 6.7 1,376.3 19,874.5 Large diameter Medium diameter Small diameter Chaparral Stand-size class Forest-type group Nonstocked All size classes
98 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Table 10--Number of live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (Table 10 continued on next page) 1,548,097 1,046,059 631,033 361,007 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the number of trees rounds to less than 1 thousand trees. Columns and rows may not add to their totals due to rounding. 208,174 11,976,417 Softwood species groups Hardwood species groups 1,514,648 33,448 1,026,607 19,452 621,930 9,103 355,740 5,267 204,523 3,651 11,660,257 316,160 All softwoods All hardwoods 114,651 1,219 67,272 1,066 37,670 1,058 36,479 1,022 13,632 214 5,333 105 1,567 52 1,141 - - 115,870 68,339 38,728 37,501 13,846 5,438 1,620 1,141 2,418,830 67,000 2,485,830 5,240,234 173,502 5,413,736 Species group Diameter class (inches) 37.0+ All classes 1.0- 2.9 3.0- 4.9 5.0- 6.9 7.0- 8.9 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 24.9 25.0- 28.9 29.0- 32.9 33.0- 36.9 30,054 7,996 5,528 214 49 10,305 3,862 3,796 905 1,015 3,548 853 213 16,805 4,591 1,990 321 107 6,980 2,873 999 589 634 1,781 950 108 16,887 3,941 2,161 54 52 6,546 3,393 549 856 726 1,314 969 52 5,189 1,265 486 107 106 3,407 2,173 50 375 257 218 214 2,163 654 54 53 1,233 956 55 164 105 494 54 488 371 161 52 496 167 57 54 207 107 53 2,634,970 784,082 2,804,146 66,863 15,882 873,681 311,793 2,739,108 257,256 439,812 732,664 247,932 481 51,358 16,389 1,093,546 347,587 1,648,139 35,924 6,622 366,709 119,521 925,829 169,289 209,593 317,477 140,830 26,550 6,122 518,680 147,847 582,652 11,986 3,976 183,288 51,399 612,837 44,661 107,507 153,997 49,048 9,787 8,165 317,943 89,363 265,340 7,708 1,391 99,082 38,948 524,116 17,820 52,607 100,330 24,262 374 7,174 1,637 168,089 47,559 80,096 2,516 801 48,635 22,863 184,148 5,374 18,442 43,407 7,387 1,674 42 233,774 65,102 143,833 4,176 1,386 72,862 32,269 365,375 9,777 30,905 67,147 14,399 53 4,576 424 110,322 31,357 42,835 1,447 801 35,336 15,922 79,590 3,133 9,903 25,095 4,678 53 535 73,371 23,189 20,529 1,070 321 23,935 10,764 31,082 2,881 4,659 12,722 3,174 477 47,159 13,464 10,448 1,232 215 14,667 6,372 10,738 1,382 3,509 5,465 1,009 210 Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Western woodland hardwoods - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table 10--Number of live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (In thousand trees)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 99 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods 273,815 72,775 179,539 7,281 1,391 67,263 37,900 436,148 15,832 56,757 14,294 374 3,135 Table 11--Number of growing-stock trees on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. 205,428 55,312 99,605 4,069 1,386 51,103 31,018 305,330 8,794 41,443 8,785 53 2,475 149,766 41,926 57,373 2,196 695 34,767 21,711 150,080 4,597 27,684 5,746 843 98,536 28,700 31,246 1,233 696 25,629 14,654 62,205 2,723 14,800 3,515 53 324 (Table 11 continued on next page) 1,166,504 814,803 497,386 284,314 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the number of trees rounds to less than 1 thousand trees. Columns and rows may not add to their totals due to rounding. 64,419 21,333 15,284 857 321 17,149 10,026 22,821 2,412 7,086 2,266 319 895,936 251,329 398,820 17,297 5,073 225,344 132,861 988,268 38,107 154,566 37,754 481 7,468 164,291 3,153,303 Softwood species groups Hardwood species groups 1,148,702 17,803 803,489 11,314 490,797 6,589 280,422 3,893 161,706 2,585 3,107,600 45,703 All softwoods All hardwoods 41,814 13,022 7,884 964 215 9,654 5,678 7,547 1,179 3,363 692 103 25,929 7,750 4,150 161 49 7,318 3,489 2,874 749 1,809 746 213 14,936 4,591 1,717 268 107 4,433 2,820 836 536 817 795 56 14,441 3,835 1,538 54 52 4,648 2,756 378 695 700 703 4,472 1,265 428 107 106 2,151 1,746 50 375 107 160 1,722 654 54 53 857 690 328 54 213 371 161 52 331 167 54 159 53 91,321 796 54,278 959 31,061 850 29,096 703 10,807 160 4,030 - - 1,127 52 764 - - 92,116 55,237 31,911 29,800 10,966 4,030 1,180 764 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Species group Diameter class (inches) 5.0- 6.9 7.0- 8.9 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 24.9 25.0- 28.9 29.0- 32.9 33.0- 36.9 37.0+ All classes Table 11--Number of growing-stock trees on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. (In thousand trees)
100 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Forest Service Other Federal State and local government Private National forest National Park Service Bureau of Land Management Fish and Wildlife Service Other Federal State Local (county, municipal, etc.) Undifferentiated private 27,972.6 - - 1,201.8 - - - - 1,280.4 2.0 5,965.4 Table 12--Net volume of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. 406.5 - - 100.4 - - - - 24.8 - - 273.5 28,379.1 - - 1,302.2 - - - - 1,305.2 2.0 6,238.8 5,202.5 1,644.3 36.1 42.3 20.1 - - - - 287.7 (Table 12 continued on next page) 36,422.2 805.2 37,227.4 7,233.1 All owners All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 76.9 6.9 9.8 27.4 - - - - - - - - 5,279.4 1,651.2 45.9 69.7 20.1 - - - - 287.7 33,658.5 1,651.2 1,348.2 69.7 20.1 1,305.2 2.0 6,526.5 121.0 7,354.1 44,581.4 Timberland Unproductive Total Productive Unreserved forests Owner class Reserved forests Unproductive Total All forest land Table 12--Net volume of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 101 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 223.4 12,010.4 2,620.1 10,314.1 5,011.7 1,087.4 2,186.3 1,137.2 8.3 301.6 139.6 - - - - - - Table 13--Net volume of all live trees on forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. 36.0 1,420.7 199.2 1,353.1 4,342.4 46.6 265.6 254.6 5.1 19.2 134.5 3.3 - - - - 6.9 367.2 90.3 374.1 298.6 6.7 96.5 33.3 - - 0.6 71.7 - - 1.3 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 13 continued on next page) 35,040.0 8,080.2 1,347.2 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - - - - - 114.0 114.0 266.3 13,798.3 2,909.7 12,041.2 9,652.8 1,140.7 2,548.3 1,425.0 13.3 321.4 345.8 3.3 1.3 114.0 44,581.4 Large diameter Medium diameter Small diameter Stand-size class Forest-type group Chaparral Nonstocked All size classes Table 13--Net volume of all live trees on forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. (In million cubic feet) Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+
102 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Western woodland hardwoods 8,601.8 1,116.5 4,465.3 278.8 96.6 5,211.7 2,194.2 9,154.0 490.7 32.1 1,884.5 104.6 2.0 25.7 - - Table 14--Net volume of all live trees on forest land by species group and ownership group, 821.4 291.9 381.3 2.0 3.2 572.3 182.4 592.0 35.8 96.4 72.4 25.0 - - 12.5 0.6 476.6 218.1 132.2 - - - - 49.1 235.8 105.8 2.2 15.3 19.3 37.3 - - 15.4 0.2 (Table 14 continued on next page) 33,658.5 3,089.2 1,307.2 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 2,644.0 1,625.0 268.3 7.9 3.4 268.4 287.9 763.8 44.2 147.7 49.3 376.3 - - 40.0 0.4 12,543.8 3,251.5 5,247.1 288.6 103.3 6,101.4 2,900.3 10,615.6 572.9 291.3 2,025.5 543.2 2.0 93.6 1.2 6,526.5 44,581.4 Softwood species groups Hardwood species groups 33,526.2 132.3 3,051.2 38.0 1,254.2 53.0 6,109.8 416.7 43,941.4 640.0 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 14--Net volume of all live trees on forest land by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 103 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Western woodland hardwoods 715 118 986 16 4 321 103 1,723 60 40 191 47 1 16 1 Table 15--Net volume of all live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. 1,224 255 979 25 9 493 226 2,862 61 49 323 67 0 25 0 1,618 381 926 34 9 590 303 2,563 58 51 392 71 17 0 1,697 415 769 31 16 692 346 1,733 54 43 360 72 1 10 (Table 15 continued on next page) 4,342 6,599 7,013 6,238 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to less than 1 million cubic feet. Columns and rows may not add to their totals due to rounding. 1,667 476 544 30 10 708 337 962 73 33 261 71 10 12,544 3,251 5,247 289 103 6,101 2,900 10,616 573 291 2,026 543 2 94 1 5,182 44,581 Softwood species groups Hardwood species groups 4,277 65 6,507 92 6,925 87 6,156 82 5,101 80 43,941 640 All softwoods All hardwoods 1,450 408 389 57 10 623 275 457 48 32 160 29 3 1,218 334 270 13 3 581 212 196 41 11 133 37 7 848 248 122 25 8 517 202 70 33 9 80 52 4 1,146 306 177 6 6 675 326 44 62 14 85 57 2 485 142 65 19 17 470 283 6 38 7 25 22 284 107 5 10 244 181 1 14 8 81 15 117 87 33 11 111 61 15 18 70 19 12 3,911 32 3,012 44 2,162 56 2,848 59 1,557 22 846 8 332 11 307 - - 3,943 3,057 2,217 2,907 1,579 854 344 307 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Species group Diameter class (inches) 5.0- 6.9 7.0- 8.9 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 24.9 25.0- 28.9 29.0- 32.9 33.0- 36.9 37.0+ All classes Table 15--Net volume of all live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (In million cubic feet)
104 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Pinyon / juniper group

Douglas-fir group

Ponderosa pine group

Fir / spruce / mountain hemlock grou

Lodgepole pine group

Hemlock / Sitka spruce group

Western larch group

Other western softwoods group

Oak / hickory group

Elm / ash / cottonwood group

Aspen / birch group

Alder / maple group

Woodland hardwoods group

Nonstocked

 266.3

 13,786.4

 2,899.1

 12,003.0

 9,652.2

 1,140.7

 2,532.1

 1,425.0

 13.3

 321.4

 345.4

 3.3

 1.3

 110.3

Table 16--Net volume of all live trees on forest land by forest type group and stand origin,

 

 - -

 11.9

 10.6

 38.2

 0.6

 - -

 16.3

 - -

 - -

 - -

 0.4

 - -

 - -

 3.7

(Table 7 continued on next page)

All forest-type groups 44,499.9 81.6

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the

volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 266.3

 13,798.3

 2,909.7

 12,041.2

 9,652.8

 1,140.7

 2,548.3

 1,425.0

 13.3

 321.4

 345.8

 3.3

 1.3

 114.0

 44,581.4

Natural

stands

Artificial

 regeneration

Stand origin

 Forest-type group

All forest

land

Table 16--Net volume of all live trees on forest land by forest type group and stand origin, Montana, cycle 2, 2003-2009.

(In million cubic feet)

Pinyon / juniper group

Douglas-fir group

Ponderosa pine group

Fir / spruce / mountain hemlock grou

Lodgepole pine group

Hemlock / Sitka spruce group

Western larch group

Other western softwoods group

Oak / hickory group

Elm / ash / cottonwood group

Aspen / birch group

Alder / maple group

Woodland hardwoods group

Nonstocked

 805.1

 84.3

 153.7

 77.4

 109.4

 - -

 - -

 270.0

 15.0

 51.0

 85.2

 - -

 18.0

 255.8

Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003

 - -

 4,627.5

 2,245.6

 2,537.4

 3,330.3

 8.7

 142.0

 678.8

 8.6

 105.9

 331.8

 - -

 - -

 1,380.9

 - -

 2,339.6

 533.6

 1,930.4

 885.5

 109.3

 577.9

 - -

 - -

 41.6

 100.1

 6.7

 - -

 254.6

 - -

 421.1

 63.7

 462.0

 40.8

 114.4

 163.5

 - -

 - -

 40.0

 5.0

 - -

 - -

 26.7

All forest-type groups 1,924.8 15,397.5 6,779.3 1,337.3

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less

than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 - -

 44.5

 22.0

 23.9

 - -

 8.9

 43.6

 - -

 - -

 - -

 - -

 - -

 - -

 - -

 143.0 

0-19 20-49 50-84 85-119

Site-productivity class (cubic feet/acre/year)

 Forest-type group 120-164 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 105 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods 629 104 673 15 4 220 99 1,463 53 114 32 1 9 Table 17--Net volume of growing-stock trees on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. 1,090 228 692 24 9 350 218 2,422 55 209 48 0 16 1,446 346 681 29 9 424 287 2,105 49 251 59 10 1,525 385 585 25 13 505 319 1,363 46 215 58 1 6 (Table 17 continued on next page) 3,417 5,362 5,696 5,047 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to less than 1 million cubic feet. Columns and rows may not add to their totals due to rounding. 1,473 448 425 24 10 514 316 707 61 141 59 8 11,067 3,093 3,879 247 100 4,274 2,589 8,614 503 1,200 432 2 62 4,184 36,061 Softwood species groups Hardwood species groups 3,375 42 5,297 65 5,627 69 4,982 65 4,117 67 35,565 496 All softwoods All hardwoods 1,301 397 303 43 10 416 247 315 40 97 22 2 1,061 329 214 9 3 421 194 145 34 71 33 7 754 248 105 20 8 338 198 59 29 38 46 2 985 299 138 6 6 486 259 30 52 49 46 436 142 58 19 17 305 230 6 38 15 18 226 107 5 10 189 133 56 15 46 87 33 11 86 61 18 59 12 3,170 24 2,480 40 1,798 48 2,310 46 1,266 18 669 - - 237 11 236 - - 3,194 2,521 1,846 2,357 1,284 669 248 236 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Species group Diameter class (inches) 5.0- 6.9 7.0- 8.9 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 24.9 25.0- 28.9 29.0- 32.9 33.0- 36.9 37.0+ All classes Table 17--Net volume of growing-stock trees on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. (In million cubic feet)
106 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods 7,620.2 1,104.2 3,479.5 239.0 96.5 3,912.2 2,061.8 7,529.5 473.9 1,126.4 86.8 2.0 24.6 Table 18--Net volume of growing-stock trees on timberland by species group and ownership group, 515.1 225.0 43.1 - - - - 58.7 10.8 293.6 - - 20.5 6.3 - - - - 474.7 212.0 130.6 - - - - 49.1 234.9 100.0 2.2 17.9 35.7 - - 11.2 (Table 18 continued on next page) 27,756.5 1,173.1 1,268.1 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 2,457.0 1,552.3 225.6 7.9 3.4 254.3 281.3 690.9 26.5 35.3 302.9 - - 26.2 11,066.9 3,093.4 3,878.7 246.8 99.9 4,274.2 2,588.9 8,614.0 502.5 1,200.0 431.8 2.0 62.0 5,863.5 36,061.2 Softwood species groups Hardwood species groups 27,643.1 113.4 1,166.8 6.3 1,221.2 46.9 5,534.3 329.1 35,565.4 495.8 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 18--Net volume of growing-stock trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 107 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Table 19--Net volume of sawtimber trees (International 1/4-inch rule) on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. 5,560 764 3,443 132 45 2,336 1,577 11,966 242 1,359 7,023 1,513 3,158 132 77 2,866 1,797 7,591 243 1,146 291 4 29 (Table 19 continued on next pa

 27,422 25,871 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to less than 1 million board feet. Columns and rows may not add to their totals due to rounding. 7,484 2,237 2,389 130 60 2,957 1,810 3,929 330 737 299 40 48,690 14,965 13,926 1,195 556 21,854 13,326 26,522 2,181 4,665 1,490 4 121 22,402 149,496 Softwood species groups Hardwood species groups 27,422 - - 25,547 324 22,063 339 147,880 1,616 All softwoods All hardwoods 7,011 2,263 1,749 254 65 2,412 1,455 1,734 223 506 111 9 6,022 2,049 1,274 54 19 2,460 1,164 797 191 373 174 35 4,444 1,600 634 125 53 1,987 1,202 318 168 208 233 9 5,994 2,050 875 38 42 2,928 1,616 154 300 243 239 2,722 1,063 375 121 122 1,950 1,396 32 217 94 103 1,449 858 29 74 1,252 790 382 94 305 519 193 41 599 567 116 400 74 17,672 119 14,404 209 10,738 242 14,240 239 8,091 103 4,452 - - 1,493 41 1,757 - - 17,791 14,613 10,980 14,479 8,194 4,452 1,534 1,757 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Species group Diameter class (inches) 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 24.9 25.0- 28.9 29.0- 32.9 33.0- 36.9 37.0+ All classes Table 19--Net volume of sawtimber trees (International 1/4-inch rule) on timberland by species group and diameter class, Montana, cycle 2, 2003-2009. (In million board feet)
108 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods 5,872.0 922.1 1,957.7 171.9 80.0 3,062.0 1,644.7 3,702.6 310.4 741.8 43.1 0.6 10.4 Table 20--Net volume of sawtimber trees on timberland by species group and ownership group, 351.4 159.3 17.7 - - - - 32.6 9.0 164.5 - - 13.1 1.8 - - - - 353.7 174.6 81.2 - - - - 32.5 195.0 44.1 1.1 13.0 20.2 - - - - (Table 20 continued on next page) 18,519.4 749.5 915.4 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 1,698.7 1,168.9 122.3 4.0 2.0 175.3 191.7 382.8 14.8 19.4 162.6 - - 10.5 8,275.9 2,424.9 2,178.8 175.9 81.9 3,302.4 2,040.5 4,294.0 326.3 787.3 227.8 0.6 20.8 3,952.9 24,137.2 Softwood species groups Hardwood species groups 18,465.3 54.1 747.6 1.8 895.2 20.2 3,779.8 173.1 23,887.9 249.3 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 20--Net volume of sawtimber trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 109 Forest Service Other Federal State and local government Private National forest National Park Service Bureau of Land Management Fish and Wildlife Service Other Federal State Local (county, municipal, etc.) Undifferentiated private 223.3 - - 10.1 - - - - 11.7 0.0 124.6 Table 21--Average annual net growth of all live trees by owner class and forest land status, -2.1 - - 1.3 - - - - 0.4 - - 4.4 221.2 - - 11.4 - - - - 12.1 0.0 129.1 -50.0 -33.2 0.6 0.2 -0.1 - - - - -1.8 (Table 21 continued on next page) 369.8 4.1 373.9 -84.3 All owners All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 0.2 0.3 0.1 0.1 - - - - - - -0.4 -49.8 -33.0 0.7 0.3 -0.1 - - - - -2.2 171.4 -33.0 12.1 0.3 -0.1 12.1 0.0 126.9 0.3 -84.0 289.8 Timberland Unproductive Total Productive Unreserved forests Owner class Reserved forests Unproductive Total All forest land Table 21--Average annual net growth of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. (In million cubic feet)
110 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 2.3 117.1 36.3 71.7 58.9 22.3 22.3 -5.8 0.1 6.4 4.0 - - - - - - Table 22--Average annual net growth of all live trees on forest land by forest type group and stand-size class, 0.8 35.5 7.6 31.9 86.7 2.4 12.3 4.6 0.2 0.7 3.4 0.2 - - - - 0.2 12.7 2.8 -1.2 -19.9 0.3 -12.9 0.8 - - 0.0 -29.2 - - -0.5 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 22 continued on next page) 335.5 186.4 -46.8 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - - - - - -185.2 -185.2 3.3 165.3 46.7 102.4 125.7 25.0 21.7 -0.4 0.3 7.1 -21.9 0.2 -0.5 -185.2 289.8 Large diameter Medium diameter Small diameter Chaparral Stand-size class Forest-type group Non stocked All size classes Table 22--Average annual net growth of all live trees on forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. (In million cubic feet) Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 111 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Western woodland hardwoods 38.5 12.2 34.8 8.0 1.5 42.9 34.3 4.6 15.7 0.0 -25.6 3.5 0.1 0.8 - - Table 23--Average annual net growth of all live trees on forest land by species group and ownershp group, 2.5 2.1 -9.6 0.0 0.1 -2.2 -7.7 -1.5 0.0 1.0 -2.7 -2.0 - - -0.7 0.0 3.4 0.2 3.1 - - - - 1.6 3.4 -0.8 0.2 0.2 -0.5 0.7 - - 0.7 0.0 (Table 23 continued on next page) 171.4 -20.6 12.2 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 55.2 29.1 6.1 0.4 0.4 9.2 6.5 7.7 1.3 1.7 0.0 7.9 - - 1.2 0.0 99.5 43.6 34.4 8.4 2.0 51.5 36.6 10.0 17.2 2.9 -28.8 10.2 0.1 2.0 0.0 126.9 289.8 Softwood species groups Hardwood species groups 166.9 4.4 -17.9 -2.7 10.7 1.5 117.8 9.1 277.5 12.3 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 23--Average annual net growth of all live trees on forest land by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
112 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods 52.3 13.4 37.3 7.0 1.5 34.8 34.7 22.6 15.5 -4.6 2.8 0.1 0.7 Table 24--Average annual net growth of growing-stock trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009. 8.1 1.5 0.8 - - - - 1.9 0.4 -1.3 - - -1.8 0.1 - - - - 3.4 0.0 3.1 - - - - 1.6 3.4 -0.9 0.2 -0.5 0.7 - - 0.7 (Table 24 continued on next page) 218.1 9.7 11.5 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 52.2 27.3 5.9 0.4 0.4 9.0 6.4 12.8 0.9 -0.3 6.4 - - 0.8 116.0 42.1 47.1 7.4 1.8 47.3 44.9 33.2 16.6 -7.3 10.0 0.1 2.2 122.2 361.5 Softwood species groups Hardwood species groups 214.4 3.7 9.6 0.1 10.2 1.3 115.0 7.2 349.2 12.3 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 24--Average annual net growth of growing-stock trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 113

Western softwood species groups

Western hardwood species groups

Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch

Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Red alder Other western hardwoods

52.3

13.4

37.3

7.0

1.5

34.8

34.7

22.6

15.5

-4.6

2.8

0.1

0.7

Table 24--Average annual net growth of growing-stock trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009.

 

8.1

1.5

0.8

 - -

 - - 1.9

0.4

-1.3

 - -

-1.8

0.1

 - -

 - -

3.4

0.0

3.1

 - -

 - - 1.6

3.4

-0.9

0.2

-0.5

0.7

 - - 0.7

(Table 24 continued on next page) All species groups 218.1 9.7 11.5 All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less

than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

52.2

27.3

5.9

0.4

0.4

9.0

6.4

12.8

0.9

-0.3

6.4

 - - 0.8

116.0

42.1

47.1

7.4

1.8

47.3

44.9

33.2

16.6

-7.3

10.0

0.1

2.2

122.2 361.5

Softwood species groups

Hardwood species groups

214.4

3.7

9.6

0.1

10.2

1.3

115.0

7.2

349.2

12.3

All softwoods

All hardwoods

Forest Service Other Federal State and local

 Species group government Undifferentiated

private All owners Ownership group

Forest ServiceOther FederalState and local governmentPrivate

National forestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceOther FederalStateUndifferentiated private

410.8

 - -

17.4

 - - - -

18.347.7

Table 25--Average annual mortality of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009.

11.2

 - -

0.7

 - - - -

0.11.4

422.1

 - -

18.1

 - - - -

18.449.2

155.1

71.4

0.10.70.4

 - -

9.2

(Table 25 continued on next page)

494.3 13.5 507.8 236.9 All owners 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

0.80.00.00.4

 - - - -

0.4

156.0

71.4

0.11.10.4

 - -

9.7

578.0

71.418.2

1.10.4

18.458.8

1.7 238.6 746.3

Timberland Unproductive Total Productive

Unreserved forests

 Owner class

Reserved forests

Unproductive Total

All

forest land

Table 25--Average annual mortality of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009.

(In million cubic feet)
114 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Elm / ash / cottonwood group Aspen / birch group Woodland hardwoods group Nonstocked 1.3 107.2 17.9 130.0 37.1 2.4 21.8 23.7 0.4 0.1 - - - - Table 26--Average annual mortality of all live trees on forest land by forest type group and stand-size class, 0.0 15.6 1.4 17.6 52.4 0.1 0.4 2.8 0.1 1.4 - - - - 0.1 5.8 1.1 23.1 40.0 - - 19.0 0.5 - - 32.9 0.5 - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 26 continued on next page) 341.8 91.8 123.1 - - All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. - - - - - - - - - - - - - - - - - - - - - - 189.7 189.7 1.4 128.5 20.4 170.8 129.6 2.5 41.2 27.0 0.5 34.4 0.5 189.7 746.3 Large diameter Medium diameter Small diameter Chaparral Stand-size class Forest-type group Non stocked All size classes Table 26--Average annual mortality of all live trees on forest land by forest type group and stand-size class, Montana, cycle 2, 2003-2009. (In million cubic feet) Pinyon / juniper group Douglas-fir group Ponderosa pine group Fir / spruce / mountain hemlock grou Lodgepole pine group Hemlock / Sitka spruce group Western larch group Other western softwoods group Oak / hickory group Elm / ash / cottonwood group Aspen / birch group Alder / maple group Woodland hardwoods group Nonstocked 805.1 84.3 153.7 77.4 109.4 - - - - 270.0 15.0 51.0 85.2 - - 18.0 255.8 Table 3--Area of accessible forest land by forest type group and productivity class, Montana, cycle 2, 2003-2009. - - 4,627.5 2,245.6 2,537.4 3,330.3 8.7 142.0 678.8 8.6 105.9 331.8 - - - - 1,380.9 - - 2,339.6 533.6 1,930.4 885.5 109.3 577.9 - - - - 41.6 100.1 6.7 - - 254.6 - - 421.1 63.7 462.0 40.8 114.4 163.5 - - - - 40.0 5.0 - - - - 26.7 (Table 4 continued on next page) 1,924.8 15,397.5 6,779.3 1,337.3 All forest-type groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding. - - 44.5 22.0 23.9 - - 8.9 43.6 - - - - - - - - - - - - - - - - - - - - - - - - - - 8.9 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143.0 8.9 - - 805.1 7,517.0 3,018.6 5,031.2 4,365.9 241.4 936.0 948.8 23.6 238.5 522.1 6.7 18.0 1,918.0 25,590.8 0-19 20-49 50-84 85-119 Site-productivity class (cubic feet/acre/year) Forest-type group 120-164 165-224 All classes 225+
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 115 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Other western hardwoods 122.3 8.1 110.3 1.2 55.8 4.8 217.7 0.1 0.7 56.7 0.4 - - Table 27--Average annual mortality of all live trees on forest land by species group and ownership group, 15.3 4.1 22.0 0.0 17.1 10.0 13.8 0.8 0.3 3.7 2.8 1.1 6.2 4.4 1.1 - - 0.1 0.5 4.7 - - 0.1 0.9 0.5 0.0 (Table 27 continued on next page) 578.0 91.1 18.4 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 17.3 13.1 5.1 - - 0.8 2.6 16.4 0.1 0.8 1.1 1.4 0.1 161.0 29.7 138.5 1.2 73.8 17.9 252.6 1.1 1.8 62.4 5.1 1.3 58.8 746.3 Softwood species groups Hardwood species groups 577.6 0.4 87.2 3.9 17.9 0.5 57.3 1.5 740.0 6.3 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 27--Table 26--Average annual mortality of all live trees on forest land by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
116 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Other western softwoods Cottonwood and aspen Other western hardwoods 90.8 6.4 75.9 1.2 42.1 3.4 164.5 0.1 24.7 0.4 - - Table 28--Average annual mortality of growing-stock trees on timberland by species group and ownership group, 2.9 3.0 1.0 - - 0.0 - - 8.0 - - 2.2 0.1 - - 6.1 4.4 1.0 - - 0.1 0.5 4.7 - - 0.8 0.5 0.0 (Table 28 continued on next page) 409.5 17.3 18.1 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding. 15.4 12.8 4.1 - - 0.7 2.6 9.6 - - 0.9 1.2 0.0 115.2 26.6 82.0 1.2 42.9 6.5 186.8 0.1 28.6 2.2 0.1 47.3 492.1 Softwood species groups Hardwood species groups 409.1 0.4 17.2 0.1 17.5 0.5 46.1 1.2 489.9 2.2 All softwoods All hardwoods Forest Service Other Federal State and local government Species group Undifferentiated private All owners Ownership group Table 28--Average annual mortality of growing-stock trees on timberland by species group and ownership group, Montana, cycle 2, 2003-2009. (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 117 All Owner class Timberland Unproductive Total Productive Unproductive Total forest land Forest Service National Forest 534,178 9,343 543,522 95,971 1,738 97,709 641,231 Other Federal National Park Service - - - - - - 30,221 283 30,503 30,503 Bureau of Land Management 25,138 2,336 27,474 1,013 287 1,300 28,773 Fish and Wildlife Service - - - - - - 1,118 776 1,894 1,894 Other Federal - - - - - - 350 - - 350 350 State and local government State 26,460 561 27,021 - - - - - - 27,021 Local (county, municipal,etc.) 50 - - 50 - - - - - - 50 Private Undifferentiated private 128,750 6,072 134,822 5,786 - - 5,786 140,608 All owners 714,576 18,312 732,888 134,459 3,084 137,543 870,430 All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the aboveground tree biomass rounds to less than 1 thousand dry tons. Columns and rows may not add to their totals due to rounding. Unreserved forests Reserved forests Table 29a--Aboveground dry weight (regional equations method) of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. (In thousand dry tons) Table 29a--Aboveground dry weight (regional equations method) of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. (In thousand dry tons) Forest Service Other Federal State and local government Private National forest National Park Service Bureau of Land Management Fish and Wildlife Service Other Federal State Local (county, municipal, etc.) Undifferentiated private 512,024 - - 23,112 - - - - 25,053 37 117,865 Table 29b--Aboveground dry weight (component ratio method) of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. 8,177 - - 1,974 - - - - 428 - - 5,286 520,201 - - 25,086 - - - - 25,480 37 123,151 91,351 28,361 793 893 327 - - - - 5,432 (Table 31 continued on next page) 678,090 15,865 693,955 127,157 All owners All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the aboveground tree biomass rounds to less than 1 thousand dry tons. Columns and rows may not add to their totals due to rounding. 1,477 189 259 619 - - - - - - - - 92,828 28,551 1,051 1,512 327 - - - - 5,432 613,029 28,551 26,138 1,512 327 25,480 37 128,583 2,545 129,702 823,657 Timberland Unproductive Total Productive Unreserved forests Owner class Reserved forests Unproductive Total All forest land Table 29b--Aboveground dry weight (component ratio method) of all live trees by owner class and forest land status, Montana, cycle 2, 2003-2009. (In thousand dry tons)
118 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 1.0- 3.0- 5.0- 7.0- 9.0- 11.0- 13.0- 15.0- 17.0- 19.0- 21.0- 23.0- 25.0- 27.0- All Species group 2.9 4.9 6.9 8.9 10.9 12.9 14.9 16.9 18.9 20.9 22.9 24.9 26.9 28.9 29.0+ classes Softwood species groups Western softwood species groups Douglas-fir 6,015 12,708 17,476 26,893 33,690 34,344 33,056 28,512 23,759 16,493 12,643 9,578 6,069 3,408 9,102 273,746 Ponderosa and Jeffrey pine 1,738 2,957 3,813 5,188 7,149 7,815 9,082 7,818 6,506 4,852 3,252 2,824 1,777 1,103 3,317 69,191 True fir 9,011 12,527 16,222 15,656 14,374 11,713 8,269 5,854 4,107 1,879 1,645 1,223 652 276 276 103,685 Western hemlock 180 228 377 496 618 550 565 989 233 428 98 - - 159 344 548 5,655 Western white pine 30 83 83 150 152 265 159 167 49 131 - - 100 - - 138 174 1,839 Engelmann and other spruces 2,200 3,941 5,576 7,957 9,084 10,279 10,263 8,844 8,214 7,207 5,047 4,305 3,929 2,768 5,969 95,584 Western larch 598 1,285 2,415 4,713 6,033 6,697 6,486 5,275 4,107 3,847 3,552 2,639 2,868 2,801 5,828 59,141 Lodgepole pine 4,629 12,257 34,667 45,553 39,686 27,218 15,196 7,041 3,049 1,062 616 76 - - 89 - - 191,139 Western redcedar 762 849 964 956 857 771 1,023 658 562 455 630 246 442 76 645 9,894 Western woodland softwoods 439 895 886 992 992 818 594 582 204 162 114 123 30 93 23 6,947 Other western softwoods 1,587 3,068 4,839 5,856 6,752 6,324 4,565 2,711 2,248 1,399 933 550 201 231 264 41,529 All softwoods 27,188 50,797 87,318 114,410 119,387 106,794 89,260 68,451 53,036 37,916 28,531 21,664 16,127 11,327 26,147 858,350 Hardwood species groups Western hardwood species groups Cottonwood and aspen 282 466 800 1,154 1,211 1,267 1,230 486 621 788 648 214 85 293 306 9,851 Red alder - - - - 17 4 - - 15 - - - - - - - - - - - - - - - - - - 37 Other western hardwoods 53 93 302 467 326 187 215 97 151 94 - - 73 - - - - - - 2,058 Western woodland hardwoods 10 53 45 23 5 - - - - - - - - - - - - - - - - - - - - 135 All hardwoods 344 612 1,164 1,648 1,542 1,470 1,445 583 772 883 648 287 85 293 306 12,081 All species groups 27,532 51,409 88,482 116,058 120,928 108,263 90,705 69,034 53,808 38,798 29,178 21,951 16,212 11,619 26,452 870,430 All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the aboveground tree biomass rounds to less than 1 thousand dry tons. Columns and rows may not add to their totals due to rounding. Diameter class (inches) Table 30a--Aboveground dry weight (regional equations method) of all live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (In thousand dry tons) Table 30a--Aboveground dry weight (regional equations method) of all live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (In thousand dry tons)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 119 Western softwood species groups Western hardwood species groups Table 30b--Aboveground dry weight (component ratio method) of all live trees on forest land by species group and diameter class, Montana, 2003-2009. (Table 32 continued on next page) 74,323 112,705 120,254 107,551 All species groups All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the aboveground tree biomass rounds to less than 1 thousand dry tons. Columns and rows may not add to their totals due to rounding. 90,300 823,657 Softwood species groups Hardwood species groups 72,904 1,419 110,821 1,884 118,608 1,646 106,106 1,445 88,929 1,371 810,249 13,408 All softwoods All hardwoods 68,686 560 53,069 734 38,096 904 28,541 674 21,644 270 15,798 42 11,230 303 25,918 284 69,246 53,803 39,000 29,215 21,914 15,839 11,533 26,202 36,955 1,205 38,160 12,944 666 13,610 Species group Diameter class (inches) 29.0+ All classes 1.0- 2.9 3.0- 4.9 5.0- 6.9 7.0- 8.9 9.0- 10.9 11.0- 12.9 13.0- 14.9 15.0- 16.9 17.0- 18.9 19.0- 20.9 21.0- 22.9 23.0- 24.9 25.0- 26.9 27.0- 28.9 24,136 5,915 3,863 239 48 8,477 4,200 3,052 537 171 2,430 578 156 16,747 4,372 1,756 468 123 7,507 3,990 1,088 432 146 1,468 813 92 12,823 2,890 1,456 112 5,309 3,667 611 610 105 958 674 9,730 2,491 1,124 96 4,471 2,754 78 200 113 588 227 43 6,071 1,489 671 147 4,011 2,752 416 28 213 42 3,433 1,001 272 349 122 2,774 2,806 89 73 80 229 303 9,285 2,918 269 600 160 6,194 5,621 581 17 271 284 262,896 60,015 87,248 5,750 1,692 92,766 59,346 185,955 8,899 5,544 40,136 10,568 40 2,643 157 2,900 577 3,650 64 9 793 352 3,073 496 477 553 508 129 28 8,299 1,360 8,056 208 41 2,191 1,069 12,384 763 902 1,682 873 223 109 15,058 2,214 14,491 316 65 4,972 2,162 28,518 844 561 3,703 946 21 441 11 32,868 6,901 13,219 653 153 8,816 6,150 40,975 783 724 7,365 1,245 399 3 25,216 4,695 14,126 489 149 7,474 4,648 46,367 839 678 6,140 1,239 5 635 5 34,151 7,455 10,951 595 257 10,251 6,956 27,436 725 617 6,713 1,208 14 223 33,332 8,494 7,806 576 158 10,409 6,749 15,126 967 467 4,846 1,146 225 28,848 7,243 5,538 1,082 166 9,118 5,470 7,157 631 457 2,976 482 78 Douglas-fir Ponderosa and Jeffrey pines True fir Western hemlock Western white pine Engelmann and other spruces Western larch Lodgepole pine Western redcedar Western woodland softwoods Other western softwoods Cottonwood and aspen Red alder Other western hardwoods Western woodland hardwoods - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Table 30b--Aboveground dry weight (component ratio method) of all live trees on forest land by species group and diameter class, Montana, cycle 2, 2003-2009. (In thousand dry tons)
120 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Flathead Lake Lincoln Sanders Big Horn Blaine Carbon Carter Chouteau Custer Dawson Fergus Garfield Glacier Golden Valley Hill Liberty McCone Musselshell Petroleum Phillips Pondera Powder River Prairie Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 1,694.8 463.7 2,139.4 1,355.4 222.6 91.8 132.1 120.1 48.8 123.0 - - 454.7 123.1 132.8 63.5 26.2 2.2 2.7 227.2 58.7 58.2 94.6 439.2 - - 17.1 6.7 272.7 137.0 265.5 119.5 8.7 71.5 13.8 143.2 Table 31--Area of accessible forest land by Forest Survey Unit, county and forest land status, Montana, cycle 2, 2003-2009. - - 16.7 - - 17.9 34.9 8.7 104.0 4.9 8.5 56.4 22.3 42.7 16.0 59.6 8.2 - - 8.7 - - 81.1 40.5 - - - - 66.1 14.5 8.6 2.2 103.3 32.6 88.6 20.1 - - 5.1 8.5 45.6 1,694.8 480.4 2,139.4 1,373.3 257.4 100.4 236.2 125.0 57.3 179.4 22.3 497.3 139.1 192.4 71.7 26.2 10.8 2.7 308.2 99.2 58.2 94.6 505.3 14.5 25.7 8.9 375.9 169.6 354.0 139.6 8.7 76.6 22.4 188.8 1,066.5 71.4 20.3 44.5 45.4 52.2 58.0 - - - - - - - - 27.1 25.6 206.5 - - 8.9 - - - - - - 17.9 33.3 6.5 - - - - - - - - - - 63.0 38.9 112.3 - - - - - - - - 11.4 - - 8.9 - - 9.2 19.6 16.6 - - - - - - - - 36.1 17.0 19.5 - - - - - - - - - - - - 53.9 - - - - - - - - - - - - - - 13.2 - - - - - - 17.1 - - 1,078.0 71.4 29.2 44.5 54.6 71.7 74.6 - - - - - - - - 63.1 42.6 226.0 - - 8.9 - - - - - - 17.9 87.2 6.5 - - - - - - - - - - 63.0 52.2 112.3 - - - - 17.1 - - 2,772.8 551.8 2,168.6 1,417.8 312.0 172.2 310.7 125.0 57.3 179.4 22.3 560.4 181.7 418.4 71.7 35.0 10.8 2.7 308.2 117.0 145.4 101.1 505.3 14.5 25.7 8.9 375.9 232.5 406.2 251.9 8.7 76.6 39.5 188.8 Timberland Unproductive Total Productive Unreserved forests Forest Survey Unit and county Reserved forests Unproductive Total All forest land

(Table 31 continued on next page)

 5,653.3 3,477.1

 34.6

 891.5

 5,687.9 4,368.6

 1,202.8

 695.3

Total Total 

 20.3

 202.2

 1,223.1

 897.5

 6,911.0 5,266.0

NorthwesternEastern

Table 31--Area of accessible forest land by Forest Survey Unit, county and forest land status, Montana, cycle 2, 2003-2009.

(In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 121 Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 778.9 735.6 1,264.3 991.1 224.9 313.8 581.5 252.4 870.5 640.4 689.5 51.5 1,165.2 220.3 684.6 639.1 391.4 249.1 31.2 - - 2.3 26.5 52.4 14.5 44.4 48.4 70.4 44.2 18.2 24.6 80.2 32.6 52.0 84.2 75.3 7.0 810.0 735.6 1,266.6 1,017.7 277.3 328.3 625.9 300.8 940.9 684.6 707.7 76.2 1,245.4 252.9 736.6 723.3 466.7 256.0 35.6 - - 121.1 208.3 - - - - - - - - 444.5 - - 254.7 - - 16.5 34.7 131.7 120.5 525.7 - - (Table 31 continued) 19,874.5 1,634.7 21,509.1 3,791.5 All counties - - - - 8.8 - - - - - - - - - - 17.9 - - 6.8 - - - - 8.7 - - - - 25.5 - - 35.6 - - 130.0 208.3 - - - - - - - - 462.4 - - 261.5 - - 16.5 43.4 131.7 120.5 551.1 - - 845.6 735.6 1,396.6 1,225.9 277.3 328.3 625.9 300.8 1,403.3 684.6 969.2 76.2 1,261.9 296.3 868.4 843.8 1,017.8 256.0 290.2 4,081.7 25,590.8 Timberland Unproductive Total Productive Unreserved forests Forest Survey Unit and county Reserved forests Unproductive Total All forest land (Table 54 continued on next page) 3,769.9 3,624.6 3,349.7 60.1 317.2 331.3 3,829.9 3,941.8 3,681.0 365.0 699.2 829.1 Total Total Total 8.8 24.7 34.1 373.8 723.9 863.3 4,203.7 4,665.7 4,544.3 Western West Central Southwestern All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
122 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Flathead Lake Lincoln Sanders 154.8 41.2 42.3 62.2 Table 32--Area of accessible forest land by Forest Survey Unit, county, ownership group and forest land status, Montana, cycle 2, 2003-2009. - - - - - - - - 418.1 265.1 376.6 438.3 - - 71.4 - - 9.0 2,772.8 551.8 2,168.6 1,417.8 (Table 32 continued on next page) 300.5 - - 1,498.1 80.4 Total 6,911.0 All forest land Timber- land Other forest land Timber- land Other forest land Forest Service Timber- land Other forest land Timber- land Other forest land Other Federal State and local government Undifferentiated private 1,121.9 157.4 1,720.5 854.9 558.2 16.7 29.2 44.4 - - - - - - - - 519.7 - - - - 9.0 3,854.7 648.6 - - 528.7 Forest Survey Unit and county NorthwesternTable 32--Area of accessible forest land by Forest Survey Unit, county, ownership group and forest land status, Montana, cycle 2, 2003-2009. (In thousand acres)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 123 Big Horn Blaine Carbon Carter Chouteau Custer Dawson Fergus Garfield Glacier Golden Valley Hill Liberty McCone Musselshell Petroleum Phillips Pondera Powder River Prairie Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 33.2 - - 8.9 - - 1.9 11.3 - - 16.8 8.5 - - - - - - - - - - - - 6.7 - - - - 15.1 - - 8.6 - - 15.5 7.9 - - - - - - 2.5 - - - - 2.3 - - - - - - - - - - 4.3 - - 1.1 - - - - - - - - - - 14.0 4.9 - - - - - - - - 2.1 - - 23.3 - - - - 9.4 - - - - - - - - 189.4 83.1 18.5 46.1 27.6 93.7 - - 257.4 43.3 98.8 55.3 26.2 2.2 2.7 205.5 17.9 49.6 8.6 155.4 - - 8.6 6.7 167.7 82.0 84.3 16.2 - - 69.0 13.8 127.6 87.2 8.7 33.6 4.9 8.5 47.4 10.8 24.7 8.5 59.6 8.2 8.9 - - - - 67.1 8.9 - - - - 11.2 - - 6.4 2.2 46.2 26.7 62.1 1.3 - - 5.1 - - 36.5 (Table 32 continued) 312.0 172.2 310.7 125.0 57.3 179.4 22.3 560.4 181.7 418.4 71.7 35.0 10.8 2.7 308.2 117.0 145.4 101.1 505.3 14.5 25.7 8.9 375.9 232.5 406.2 251.9 8.7 76.6 39.5 188.8 (Table 32 continued on next page) 137.0 61.5 1,957.0 584.6 Total 5,266.0 All forest land Timber- land Other forest land Timber- land Other forest land Forest Service Timber- land Other forest land Timber- land Other forest land Other Federal State and local government Undifferentiated private - - - - 78.0 74.0 19.3 - - - - 74.2 - - 33.9 8.2 - - - - - - - - - - - - 86.0 241.9 - - - - - - 61.5 47.1 167.9 93.9 - - - - - - - - - - - - 66.3 - - - - - - - - 9.0 - - - - - - - - - - - - - - - - - - 6.5 10.7 - - - - - - 23.3 68.9 78.6 121.7 - - - - - - - - - - 8.7 26.8 - - - - 18.0 - - 106.2 71.2 - - - - - - - - - - 21.6 34.2 8.6 - - 26.7 - - - - - - 28.0 - - 13.2 9.4 8.7 - - - - 15.6 - - 71.7 78.7 - - - - 9.0 7.2 72.1 49.0 226.0 - - - - 8.7 - - - - 44.5 87.2 - - 44.2 14.5 - - - - 10.5 - - - - - - - - - - 25.6 9.1 985.9 384.9 397.1 758.0 Forest Survey Unit and county Eastern
124 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 42.3 17.9 133.4 25.8 - - 10.1 7.0 - - 37.5 17.5 29.7 - - 12.7 32.3 - - 9.3 19.0 3.5 - - - - - - - - - - - - 9.4 8.4 - - - - - - - - 3.9 - - 6.3 - - 13.8 - - 190.7 80.6 538.6 127.5 57.0 95.9 102.3 20.4 322.3 187.7 251.6 15.7 41.1 37.7 156.3 87.9 135.6 43.2 - - - - 33.2 9.4 44.0 2.2 16.4 - - 16.8 25.0 - - 6.7 - - 6.5 43.3 51.8 42.5 7.0 (Table 32 continued) 835.7 103.1 5,947.5 969.7 All counties 845.6 735.6 1,396.6 1,225.9 277.3 328.3 625.9 300.8 1,403.3 684.6 969.2 76.2 1,261.9 296.3 868.4 843.8 1,017.8 256.0 25,590.8 (Table 55 continued on next page) 219.5 101.9 76.7 - - 17.8 23.9 937.5 1,053.0 501.9 42.6 111.0 151.1 Total Total Total 4,203.7 4,665.7 4,544.3 All forest land Timber- land Other forest land Timber- land Other forest land Forest Service Timber- land Other forest land Timber- land Other forest land Other Federal State and local government Undifferentiated private 519.0 637.0 574.6 837.8 149.8 199.1 412.1 232.0 475.4 435.2 337.5 35.8 1,003.9 141.7 528.3 461.4 236.8 181.5 66.8 - - 99.1 225.4 - - 12.3 18.7 40.1 516.0 19.2 279.8 17.9 68.9 69.4 56.8 136.8 499.6 - - 26.8 - - 17.6 - - 18.1 8.7 60.0 - - 35.3 - - 70.7 - - 107.4 8.7 - - 80.4 - - 20.9 - - - - - - - - 8.4 - - - - - - - - - - - - - - 23.9 - - 77.5 16.2 70.5 - - 2,568.4 2,276.9 2,553.7 391.3 904.0 831.4 44.4 192.8 217.4 - - 8.4 188.1 12,239.6 3,160.3 851.6 1,483.2 Forest Survey Unit and county Western West Central Southwestern All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 125 Flathead Lake Lincoln Sanders Big Horn Blaine Carbon Carter Chouteau Custer Fergus Garfield Glacier Golden Valley Hill Liberty McCone Musselshell Petroleum Phillips Pondera Powder River Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 917.8 257.7 1,233.8 858.2 114.1 21.7 84.2 81.8 25.3 55.4 279.9 42.6 30.7 36.4 17.4 - - - - 95.4 25.2 22.3 51.6 256.6 8.6 6.7 112.8 94.4 176.1 25.9 8.7 53.1 13.8 65.8

Table 33--Area of timberland by Forest Survey Unit, county and stand-size class, Montana, cycle 2, 2003-2009.

 257.8

 86.6

 375.8 169.9

 26.9 34.8 15.6

 4.3

 15.0

 - -

 94.9 21.2 26.0

 8.2 8.7

 - - - -

 26.5 11.2

 8.6

 17.2 43.8

 8.6

 - -

 2.5

 15.9 41.7 40.6

 - - - - - -

 25.1

 426.0 107.0 483.0 276.0

 33.9

 8.7

 32.3 10.6

 - -

 29.3 51.1 10.6 67.6 19.0

 - -

 2.2

 - -

 48.1

 8.9 6.5

 25.8 68.3

 - - - -

 45.8 19.6 15.8 43.6

 - -

 4.8

 - -

 16.0

 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

 93.3 12.3 46.8 51.3 47.6 26.5

 - -

 23.4

 8.5

 38.4 28.8 48.6

 8.5

 - - - - - -

 2.7

 57.1 13.4 20.8

 - -

 70.5

 - - - -

 111.6

 7.0

 31.8

 9.4

 - -

 13.6

 - -

 36.5

 1,694.8

 463.7

 2,139.4 1,355.4

 222.6

 91.8

 132.1 120.1

 48.8

 123.0 454.7 123.1 132.8

 63.5 26.2

 2.2 2.7

 227.2

 58.7 58.2 94.6

 439.2

 17.1

 6.7

 272.7 137.0 265.5 119.5

 8.7

 71.5 13.8

 143.2

(Table 33 continued on next page)

 3,267.5 1,806.7

 890.1 496.9

 1,292.0

 568.5

 - - - -

Total Total 

 203.6 605.0

 5,653.3 3,477.1

 Forest Survey Unit and county

Stand-size class

Chaparral

All

size classes

Small

diameter

Medium

diameter

Large

diameter Nonstocked

NorthwesternEastern

Table 33--Area of timberland by Forest Survey Unit, county, and stand-class, Montana, cycle 2, 2003-2009.

(In thousand acres)
126 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 414.5 503.8 644.6 643.1 133.1 179.9 361.4 92.8 493.1 419.4 324.2 42.6 573.5 82.1 430.2 433.5 261.6 158.2 185.1 60.6 160.8 150.3 47.1 63.3 154.7 92.1 167.5 150.4 203.2 - - 441.6 41.3 92.1 126.8 34.8 53.0 135.5 126.3 358.9 156.6 15.7 65.9 56.0 59.0 138.8 66.2 125.4 9.0 99.9 96.9 96.2 61.0 63.1 29.4 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - (Table 33 continued) 11,265.9 3,611.8 3,620.5 - - All counties 43.7 44.9 100.0 41.2 29.1 4.7 9.3 8.4 71.0 4.3 36.7 - - 50.2 - - 66.1 17.7 32.0 8.4 778.9 735.6 1,264.3 991.1 224.9 313.8 581.5 252.4 870.5 640.4 689.5 51.5 1,165.2 220.3 684.6 639.1 391.4 249.1 1,376.3 19,874.5 (Table 57 continued on next page) 2,206.0 2,046.4 1,939.2 556.8 878.5 789.6 777.3 536.1 446.6 - - - - - - Total Total Total 229.8 163.6 174.3 3,769.9 3,624.6 3,349.7 Forest Survey Unit and county Stand-size class Chaparral All size classes Small diameter Medium diameter Large diameter Nonstocked Western West Central Southwestern All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 127 Flathead Lake Lincoln Sanders Big Horn Blaine Carbon Carter Chouteau Custer Fergus Garfield Glacier Golden Valley Hill Liberty McCone Musselshell Petroleum Phillips Pondera Powder River Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 98.8 12.3 47.8 60.1 54.6 26.5 6.2 27.6 8.5 51.9 28.8 59.0 10.6 - - - - - - 2.7 74.8 13.4 20.8 - - 110.4 - - - - 114.1 7.0 41.0 9.4 - - 13.6 - - 45.6

Table 34--Area of timberland by Forest Survey Unit, county, and stocking class, Montana, cycle 2, 2003-2009.

 357.2 134.0 537.3 409.8

 92.4 47.8 32.6 58.8 12.8 27.1

 120.6

 47.0 30.0 30.7

 8.7

 - - - -

 103.5

 26.8 32.3

 - -

 202.2

 - - - -

 88.3 53.9 43.0 23.2

 8.7

 42.2

 - -

 56.6

 750.9 213.6 778.3 608.8

 53.2 17.4 47.6 25.1 27.6 44.1

 114.9

 10.6 47.3 24.6

 - - - - - -

 39.3 17.9

 - -

 43.0 86.6

 8.6 6.7

 37.7 49.4 81.9 18.0

 - -

 15.6 13.8 20.5

 421.7

 95.6

 710.9 257.8

 22.4

 - -

 45.7

 8.5

 - - - -

 187.2

 6.4

 27.6

 8.2

 17.4

 - - - -

 8.8 0.7 5.0

 34.4 40.0

 8.6

 - -

 32.6 26.7 81.0 68.9

 - - - - - -

 18.2

 66.2

 8.2

 65.0 18.8

 - - - - - - - - - - - -

 3.2

 - -

 17.3

 - - - -

 2.2

 - -

 0.7

 - - - -

 17.2

 - - - - - - - - - -

 18.6

 - - - - - - - -

 2.3

 1,694.8

 463.7

 2,139.4 1,355.4

 222.6

 91.8

 132.1 120.1

 48.8

 123.0 454.7 123.1 132.8

 63.5 26.2

 2.2 2.7

 227.2

 58.7 58.2 94.6

 439.2

 17.1

 6.7

 272.7 137.0 265.5 119.5

 8.7

 71.5 13.8

 143.2

Nonstocked

Poorly

stocked

Moderately

stocked

Fully

stocked Forest Survey Unit and county

Stocking class of growing-stock trees

Overstocked All classes

(Table 34 continued on next page)

 219.1 726.7

 1,438.3 1,189.3

 2,351.7

 851.4

 1,486.0

 648.2

Total Total 

 158.2

 61.4

 5,653.3 3,477.1

NorthwesternEastern

Table 34--Area of timberland by Forest Survey Unit, county, and stocking class, Montana, cycle 2, 2003-2009.

(In thousand acres)
128 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 43.7 44.9 100.0 43.5 29.1 4.7 10.1 8.4 71.0 4.3 36.7 - - 50.2 - - 68.8 29.2 33.0 8.4 175.9 132.4 436.3 288.7 34.9 35.5 142.6 20.4 221.7 177.1 224.8 - - 184.1 41.2 128.6 159.3 116.0 95.3 278.0 336.3 488.4 425.9 46.0 143.3 229.8 82.2 357.7 240.6 196.1 33.6 500.8 87.8 347.3 195.1 139.0 82.8 260.4 208.6 215.7 214.9 104.4 120.1 198.9 124.4 184.9 196.7 204.5 9.0 373.5 82.6 132.5 223.1 97.2 62.6 (Table 34 continued) 1,531.8 5,242.4 7,414.0 5,148.3 All counties 20.9 13.5 23.8 18.1 10.6 10.1 - - 16.9 35.2 21.6 27.4 9.0 56.6 8.7 7.4 32.5 6.3 - - 778.9 735.6 1,264.3 991.1 224.9 313.8 581.5 252.4 870.5 640.4 689.5 51.5 1,165.2 220.3 684.6 639.1 391.4 249.1 538.0 19,874.5 Nonstocked Poorly stocked Moderately stocked Fully stocked Forest Survey Unit and county Stocking class of growing-stock trees Over- stocked All classes (Table 58 continued on next page) 232.1 164.4 189.6 1,033.2 857.0 724.4 1,528.6 1,329.5 1,352.8 899.7 1,142.9 971.5 Total Total Total 76.2 130.7 111.4 3,769.9 3,624.6 3,349.7 Western West Central Southwestern All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 129 Table 35--Net volume of growing-stock and sawtimber (International 1/4-inch rule) on timberland by Forest Survey Unit, county, and major species group, Montana, cycle 2, 2003-2009. Forest Survey Unit and county Pine Other softwoods Soft hardwoods Hard hardwoods Growing stock All species Pine Other softwoods Soft hardwoods Hard hardwoods All species Major species group Sawtimber Major species group Northwestern Eastern 2,174.0 1,994.3 10,041.8 1,178.8 86.6 160.0 75.4 28.8 Total Total 12,377.9 3,362.0 8,409.7 7,417.2 46,759.2 4,799.8 276.1 502.3 288.9 91.8 55,733.8 12,811.1 (Table 35 continued on next page) Flathead Lake Lincoln Sanders Big Horn Blaine Carbon Carter Chouteau Custer Fergus Garfield Glacier Golden Valley Hill Musselshell Petroleum Phillips Pondera Powder River Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 433.0 160.1 916.1 664.8 122.2 32.3 120.4 87.9 52.0 49.0 349.4 28.8 68.7 22.8 49.3 96.1 32.8 37.7 48.0 259.8 - - - - 165.4 93.6 142.0 43.5 1.5 43.6 - - 47.4 2,893.4 693.9 4,353.3 2,101.1 12.6 7.9 118.8 - - 23.9 - - 264.2 3.2 71.4 13.7 33.2 - - - - - - 120.0 - - - - - - - - 37.1 314.3 152.1 6.4 - - - - - - 22.1 1.7 55.1 7.8 5.4 5.7 1.4 - - 2.8 - - 41.6 10.7 8.3 - - 0.4 - - - - - - 1.4 4.4 11.0 5.4 - - 1.9 6.7 0.1 0.1 - - 19.3 33.2 52.6 1.1 20.3 1.4 7.0 - - - - 1.2 - - - - - - - - - - - - - - - - - - - - - - - - 7.7 - - 0.4 - - 11.7 0.2 - - - - 0.6 - - 3,401.1 856.9 5,344.8 2,775.1 147.1 46.0 240.5 89.2 78.7 49.0 655.2 42.7 148.4 36.5 82.9 96.1 32.8 37.7 169.4 264.3 18.8 5.4 165.8 132.7 474.8 195.8 8.1 43.6 19.8 80.6 1,329.9 715.5 3,306.6 3,057.6 457.3 65.5 442.0 370.4 245.7 171.3 1,316.5 77.4 309.4 36.2 132.5 262.4 92.2 158.5 193.7 1,042.3 - - - - 741.6 307.9 520.8 137.2 - - 186.2 - - 150.3 187.6 - - 93.5 7.7 20.5 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 20.1 - - - - - - 51.3 - - - - - - - - - - 14,962.9 3,750.4 24,220.0 12,800.5 550.2 103.0 978.9 370.4 361.3 171.3 2,332.7 135.0 611.0 95.5 272.1 262.4 92.2 158.5 630.3 1,053.2 40.9 17.8 741.6 453.4 1,988.2 757.5 24.2 186.2 101.0 322.2 13,435.7 3,034.8 20,582.2 9,706.5 51.6 37.5 535.2 - - 111.8 - - 935.4 10.6 298.0 59.3 139.6 - - - - - - 436.6 - - - - - - - - 144.1 1,395.4 620.4 24.2 - - - - - - 9.7 - - 237.7 28.7 20.9 - - 1.7 - - 3.8 - - 80.8 47.1 3.6 - - - - - - - - - - - - 10.9 20.8 17.8 - - 1.4 20.7 - - - - - - 101.0 171.9 (In million board feet) (In million cubic feet) Table 35--Net volume of growning-stock and sawtimber (International 1/4 inch rule) on timberland by Forest Survey Unit, county, and major species group, Montana, cycle 2, 2003-2009.
130 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 (Table 35 continued) 12,794.4 22,771.0 338.6 157.2 All counties 36,061.2 45,742.4 102,137.4 973.3 642.5 149,495.6 Forest Survey Unit and county Pine Other softwoods Soft hardwoods Hard hardwoods Growing stock All species Pine Other softwoods Soft hardwoods Hard hardwoods All species Major species group Sawtimber Major species group Western West Central Southwestern 2,549.8 2,794.7 3,281.6 4,752.2 3,294.8 3,503.4 21.2 41.9 28.8 22.6 30.3 - - Total Total Total 7,345.8 6,161.7 6,813.9 10,179.5 9,245.1 10,490.9 21,643.9 13,437.7 15,496.9 73.7 50.9 70.4 103.5 158.2 - - 32,000.7 22,891.8 26,058.1 (Table 59 continued on next page) All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic or board feet. Columns and rows may not add to their totals due to rounding. Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 786.5 324.0 512.1 927.2 129.0 235.2 599.3 157.5 514.9 668.0 461.7 29.0 1,616.3 235.0 469.8 539.7 178.9 241.9 726.3 1,459.8 1,508.9 1,057.1 351.3 225.5 521.6 281.0 594.9 579.6 667.7 73.2 1,009.7 75.0 957.7 805.4 462.8 192.9 1.1 - - 19.8 0.4 - - 4.8 2.6 - - 16.7 4.6 13.1 - - 1.0 1.5 - - 4.5 13.8 8.0 - - 6.2 2.6 13.8 - - - - - - - - 14.8 - - 15.5 - - - - - - - - - - - - - - 1,513.9 1,789.9 2,043.4 1,998.6 480.3 465.6 1,123.5 438.6 1,141.2 1,252.2 1,158.1 102.1 2,627.0 311.5 1,427.5 1,349.6 655.5 442.8 2,442.3 1,504.2 2,288.0 3,944.9 359.4 757.4 1,651.9 423.6 1,911.8 2,361.8 1,663.2 115.9 4,909.4 636.5 1,572.7 1,980.8 598.8 792.6 - - 34.7 10.9 57.9 - - - - - - - - 77.2 - - 81.0 - - - - - - - - - - - - - - 5,418.7 8,405.3 9,272.1 8,904.5 1,896.7 1,697.8 3,860.3 1,414.4 4,334.9 4,866.9 4,377.8 443.0 9,121.6 923.3 6,196.0 5,433.4 2,746.0 1,637.8 2,970.4 6,866.4 6,905.4 4,901.7 1,537.3 921.1 2,204.8 990.8 2,339.2 2,505.1 2,612.3 327.1 4,212.2 286.7 4,623.3 3,449.8 2,088.0 836.8 5.9 - - 67.8 - - - - 19.4 3.5 - - 6.8 - - 21.3 - - - - - - - - 2.9 59.1 8.4 (In million board feet) (In million cubic feet)
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 131 Table 36--Average annual net growth of growing-stock and sawtimber (International 1/4-inch rule) on timberland by Forest Survey Unit, county, and major species group, Forest Survey Unit and county Pine Other softwoods Soft hardwoods Hard hardwoods Growing stock All species Pine Other softwoods Soft hardwoods Hard hardwoods All species Major species group Sawtimber Major species group Northwestern Eastern 39.0 23.5 178.3 20.6 3.1 3.2 2.7 0.7 Total Total 223.1 48.1 203.6 197.3 970.2 123.4 9.9 12.4 12.1 2.3 1,195.7 335.3 (Table 36 continued on next page) (In million cubic feet) (In million board feet) Flathead Lake Lincoln Sanders Big Horn Blaine Carbon Carter Chouteau Custer Fergus Garfield Glacier Golden Valley Hill Musselshell Petroleum Phillips Pondera Powder River Richland Roosevelt Rosebud Stillwater Sweet Grass Teton Toole Treasure Valley Yellowstone 9.7 2.8 25.5 1.0 1.8 1.1 -1.0 1.7 0.5 1.2 2.8 -2.6 -0.2 0.5 1.1 2.2 0.6 1.0 0.6 5.7 - - - - 2.4 1.5 0.9 0.9 0.0 0.6 - - 0.1 23.0 15.4 96.6 43.3 0.3 0.2 1.1 - - 0.6 - - 7.0 0.2 0.5 0.3 0.6 - - - - - - 2.1 - - - - - - - - 0.9 3.6 3.2 0.1 - - - - - - 1.4 0.2 1.2 0.2 0.1 0.3 0.0 - - 0.0 - - 0.6 0.2 0.4 - - 0.0 - - - - - - 0.2 0.2 0.4 0.1 - - 0.0 0.4 0.0 0.0 - - 0.3 0.2 1.9 0.2 0.7 0.0 0.1 - - - - 0.1 - - - - - - - - - - - - - - - - - - - - - - - - 0.1 - - 0.0 - - 0.4 0.0 - - - - 0.0 - - 36.0 18.6 124.0 44.5 2.3 1.6 0.1 1.7 1.1 1.2 10.4 -2.2 0.7 0.8 1.7 2.2 0.6 1.0 2.9 5.9 0.5 0.1 2.4 2.4 5.3 4.1 0.2 0.6 0.3 0.3 21.0 19.3 134.1 29.2 9.3 4.4 11.9 11.2 5.3 5.6 24.2 -4.2 5.5 4.3 3.4 7.9 2.7 3.8 3.0 35.1 - - - - 16.9 12.7 7.9 19.0 - - 4.3 - - 3.1 9.6 - - 2.4 0.0 0.4 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 0.2 - - - - - - 1.8 - - - - - - - - - - 173.4 109.5 632.0 280.8 11.3 5.5 18.5 11.2 7.9 5.6 56.9 -2.4 5.9 5.8 9.3 7.9 2.7 3.8 14.8 35.4 8.5 0.2 16.9 17.7 51.0 30.6 0.4 4.3 1.5 4.2 142.5 90.2 486.6 250.9 1.4 1.2 6.6 - - 2.5 - - 33.5 1.0 0.3 1.4 6.0 - - - - - - 11.8 - - - - - - - - 5.0 40.8 11.6 0.4 - - - - - - 0.2 - - 8.9 0.8 0.2 - - 0.0 - - 0.1 - - -0.8 0.8 0.0 - - - - - - - - - - - - 0.3 8.3 0.2 - - 0.0 0.6 - - - - - - 1.5 1.1 Table 36--Average annual net growth of growning-stock and sawtimber (International 1/4 inch rule) on timberland by Forest Survey Unit, county, and major species group, Montana, cycle 2, 2003-2009.
132 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 (Table 36 continued) 65.7 283.5 7.9 4.4 All counties 361.5 794.6 1,729.0 27.2 22.7 2,573.5 Forest Survey Unit and county Pine Other softwoods Soft hardwoods Hard hardwoods Growing stock All species Pine Other softwoods Soft hardwoods Hard hardwoods All species Major species group Sawtimber Major species group Western West Central Southwestern 0.0 -3.1 6.3 23.8 37.2 23.5 0.3 0.5 0.9 0.5 0.5 - - Total Total Total 24.5 35.1 30.7 180.8 118.8 94.2 228.3 216.2 190.9 1.0 -1.7 5.7 5.8 2.6 - - 415.9 336.0 290.7 (Table 60 continued on next page) (In million cubic feet) (In million board feet) Granite Mineral Missoula Ravalli Broadwater Cascade Jefferson Judith Basin Lewis and Clark Meagher Powell Wheatland Beaverhead Deer Lodge Gallatin Madison Park Silver Bow 8.2 -12.8 -3.6 8.2 2.5 5.3 -12.3 3.2 -9.7 7.4 0.4 0.1 8.8 -0.8 6.8 -2.8 2.1 -7.7 -5.5 20.7 26.7 -18.1 1.2 3.1 8.4 1.8 2.7 8.9 9.8 1.3 -1.0 1.9 16.6 2.3 0.6 3.2 0.0 - - 0.2 0.0 - - 0.1 0.1 - - 0.1 0.2 0.0 - - -0.2 0.2 - - 0.2 0.4 0.2 - - 0.2 0.1 0.2 - - - - - - - - 0.3 - - 0.3 - - - - - - - - - - - - - - 2.7 8.1 23.4 -9.7 3.7 8.6 -3.8 5.0 -6.7 16.5 10.5 1.4 7.6 1.3 23.4 -0.4 3.1 -4.3 73.3 -20.6 6.4 121.6 12.0 28.2 -23.7 15.3 7.2 65.2 13.8 0.8 60.5 8.1 27.9 -0.3 18.0 -20.0 - - 1.3 0.2 4.3 - - - - - - - - 1.2 - - 1.4 - - - - - - - - - - - - - - 58.2 124.1 164.1 69.4 30.4 44.4 26.0 20.3 29.1 119.1 60.2 6.5 82.6 17.8 137.2 23.4 29.9 -0.2 -15.2 143.4 156.6 -56.5 18.4 16.1 49.6 5.0 22.0 53.9 45.6 5.7 22.9 9.7 109.4 23.6 10.6 14.7 0.1 - - 0.9 - - - - 0.1 0.1 - - -1.3 - - -0.6 - - -0.8 - - - - 0.1 1.3 5.1 All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to less than 0.1 million cubic or board feet. Columns and rows may not add to their totals due to rounding.
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 133 Average Average Average Average Average Average Forest Timberland annual annual annual annual annual annual Forest Survey Unit and county area area Volume net growth removals mortality Volume net growth removals mortality Northwestern Flathead 1.56 4.66 7.83 43.56 -- 23.21 9.09 44.39 -- 27.02 Lake 3.45 6.12 12.40 15.10 -- 25.21 14.18 17.01 -- 34.04 Lincoln 1.49 1.69 5.90 6.52 -- 20.37 7.21 7.78 -- 28.10 Sanders 2.23 2.54 7.49 17.95 -- 24.72 8.54 13.39 -- 26.64 Total 0.95 1.73 3.83 8.77 -- 14.31 4.53 8.41 -- 17.53 Eastern Big Horn 13.80 17.44 26.81 43.58 -- 62.78 30.75 32.05 -- 61.67 Blaine 20.83 29.14 42.30 41.37 -- 100.00 45.98 37.17 -- -- Carbon 10.92 18.42 27.64 100.00 -- 49.28 32.82 87.42 -- 64.14 Carter 24.08 24.30 38.23 32.99 -- 53.24 40.76 33.11 -- 100.00 Chouteau 35.73 38.32 54.22 41.76 -- 59.83 60.08 64.90 -- -- Custer 20.81 25.48 40.72 39.11 -- 100.00 45.05 38.89 -- -- Dawson 54.48 -- -- -- -- -- -- -- -- -- Fergus 8.00 8.66 11.27 18.01 -- 35.23 14.34 17.53 -- 41.99 Garfield 19.53 23.77 37.57 91.45 -- 59.79 44.95 100.00 -- 73.17 Glacier 8.40 22.38 37.00 100.00 -- 55.29 42.56 100.00 -- 72.12 Golden Valley 30.69 32.59 49.32 54.68 -- 63.97 65.98 49.03 -- -- Hill 49.46 57.46 62.05 72.27 -- 74.16 62.61 65.04 -- -- Liberty 82.28 100.00 -- -- -- -- -- -- -- -- McCone 100.00 100.00 -- -- -- -- -- -- -- -- Musselshell 12.24 16.05 21.73 38.23 -- 52.16 23.61 42.77 -- 54.98 Petroleum 24.47 35.88 39.89 50.26 -- 60.98 46.12 51.21 -- 91.05 Phillips 22.23 36.55 51.24 54.11 -- 77.15 57.79 51.13 -- -- Pondera 27.60 28.88 38.21 35.70 -- 52.20 42.64 58.29 -- -- Powder River 8.13 9.04 16.09 16.09 -- 68.45 19.78 17.42 -- -- Prairie 71.17 -- -- -- -- -- -- -- -- -- Richland 53.58 70.48 71.27 88.82 -- 100.00 70.49 97.98 -- -- Roosevelt 78.92 100.00 100.00 100.00 -- -- 100.00 100.00 -- -- Rosebud 10.63 13.98 27.13 55.13 -- 79.21 28.37 35.01 -- 101.42 Stillwater 12.69 21.75 27.37 30.39 -- 58.54 30.72 31.45 -- 110.89 Sweet Grass 7.87 12.57 17.13 45.67 -- 32.68 18.46 35.65 -- 50.94 Teton 7.13 21.98 39.77 50.37 -- 77.16 52.62 50.15 -- 71.85 Toole 100.00 100.00 100.00 100.00 -- -- 100.00 100.00 -- -- Treasure 30.08 31.79 44.16 61.02 -- 96.97 46.07 71.48 -- 100.00 Valley 45.09 72.55 71.61 75.81 -- -- 71.73 77.53 -- -- Yellowstone 19.26 22.84 39.27 100.00 -- 79.04 46.47 99.49 -- 74.56 Total 2.98 4.03 6.40 12.87 -- 15.28 7.61 11.35 -- 20.62 Growing stock Sawtimber

Table 37--Sampling errors by Forest Survey Unit and county for area of timberland, volume, average annual net growth, average annual removals, and average annual mortality on 

timberland, Montana, cycle 2, 2003-2009.

(Sampling error in percent)

(Table 37 continued on next page)

Table 37--Sampling errors by Forest Survey Unit and county for area of timberland, volume, average annual net growth, average annual removals, and average 

annual mortality on timberland, Montana, cycle 2, 2003-2009.

(Sampling error in percent)
134 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 (Table 37 continued) Average Average Average Average Average Average Forest Timberland annual annual annual annual annual annual Forest Survey Unit and county area area Volume net growth removals mortality Volume net growth removals mortality Western Granite 2.75 4.18 8.75 100.00 -- 37.58 10.11 97.83 -- 40.94 Mineral 2.47 2.47 8.84 100.00 -- 25.74 10.47 38.43 -- 32.76 Missoula 2.06 3.32 8.84 31.83 -- 26.77 10.15 21.05 -- 29.56 Ravalli 2.36 4.58 8.82 100.00 -- 23.99 10.85 92.23 -- 27.48 Total 1.20 1.91 4.44 86.45 -- 14.23 5.32 24.99 -- 17.16 West Central Broadwater 9.91 9.04 18.02 100.00 -- 48.58 20.60 56.96 -- 58.44 Cascade 9.11 9.77 17.05 21.63 -- 57.04 23.00 28.49 -- 72.23 Jefferson 4.75 5.46 10.18 100.00 -- 27.56 13.25 100.00 -- 35.17 Judith Basin 4.98 8.16 16.93 54.07 -- 67.24 23.41 73.14 -- 73.56 Lewis and Clark 2.53 6.98 11.30 100.00 -- 38.75 12.63 100.00 -- 43.53 Meagher 4.98 5.57 9.32 18.38 -- 24.96 10.89 18.49 -- 32.35 Powell 2.81 6.73 12.14 58.25 -- 26.26 14.11 47.28 -- 31.98 Wheatland 31.65 40.00 52.67 67.66 -- 61.86 54.32 58.41 -- 70.48 Total 1.73 2.80 4.74 48.46 -- 15.90 5.69 20.64 -- 16.89 Southwestern Beaverhead 3.44 3.97 6.87 100.00 -- 29.65 8.23 83.98 -- 35.78 Deer Lodge 6.12 11.97 21.14 100.00 -- 67.88 22.26 100.00 -- 79.25 Gallatin 4.37 6.23 10.24 14.94 -- 28.23 11.73 18.51 -- 38.75 Madison 4.55 7.09 11.27 100.00 -- 29.09 13.40 100.00 -- 38.24 Park 3.65 12.25 16.82 100.00 -- 51.20 17.71 100.00 -- 55.71 Silver Bow 7.35 7.01 14.84 100.00 -- 42.58 16.79 100.00 -- 53.16 Total 1.82 2.88 4.59 65.27 -- 16.50 5.39 33.51 -- 20.01 All counties 0.83 1.17 2.08 10.93 -- 7.20 2.49 7.47 -- 8.76 Sampling errors thas exceed 100% are reported as 100%. Growing stock Sawtimber
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 135

Appendix F: Tables of Mean Soil Properties. 

Appendix F Table 1a: Mean water, carbon, and nitrogen contents of forest floor 

and soil cores by forest type, Montana, soil visit 1, 2003-2007.

Appendix F Table 1b: Mean water, carbon, and nitrogen contents of forest floor 

and soil cores by forest type, Montana, soil visit 2, 2008-2009.

Appendix F Table 2a: Mean physical and chemical properties of soil cores by forest type, Montana, soil visit 1, 2003-2007.

Appendix F Table 2b: Mean physical and chemical properties of soil cores by forest type, Montana, soil visit 2, 2008-2009.

Appendix F Table 3a: Mean exchangeable cation concentrations in soil cores by 

forest type, Montana, soil visit 1, 2003-2007.

Appendix F Table 3b: Mean exchangeable cation concentrations in soil cores by 

forest type, Montana, soil visit 2, 2008-2009.

Appendix F Table 3b: Mean exchangeable cation concentrations in soil cores by 

forest type, Montana, soil visit 2, 2008-2009.

Appendix F Table 4b: Mean extractable trace element concentrations in soil cores 

by forest type, Montana, soil visit 2, 2008-2009.
136 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 Appendix F Table 1a—Mean water, carbon, and nitrogen contents of forest floor and soil cores by forest type, Montana, soil visit 1, 2003-2007. Soil Water Organic Inorganic Total Forest floor Organic Total Forest type layer Number of plots contenta carbon carbon nitrogen C/N ratio massa carbon nitrogen cm . . . . . .. . . . . . . . . Percent. . . . . . . . . . . . . . . . . . . . . . . . . . . . Mg/ha. . . . . . . . . . . Rocky Mountain juniper Forest floor 7 14.37 27.85 0.899 33.1 3.90 1.13 0.038 0–10 7 12.18 1.55 0.49 0.152 10.2 13.32 1.311 10–20 7 13.49 1.07 0.42 0.108 9.9 9.97 1.005 Ponderosa pine Forest floor 34 13.92 29.68 0.860 34.3 13.68 3.93 0.119 0–10 34 10.72 1.92 0.44 0.151 12.7 15.18 1.191 10–20 34 10.04 1.20 0.54 0.098 12.3 9.70 0.791 Lodgepole pine Forest floor 35 36.45 35.41 0.980 37.3 21.45 7.16 0.195 0–10 35 14.39 3.98 0.21 0.148 26.8 21.20 0.791 10–20 35 11.48 1.79 0.18 0.077 23.3 10.91 0.469 Douglas fir Forest floor 66 27.18 33.14 0.996 34.5 27.67 9.11 0.268 0–10 66 9.94 3.57 0.28 0.175 20.4 18.29 0.896 10–20 66 8.59 1.93 0.25 0.104 18.5 11.49 0.621 Cottonwood/aspen/birch Forest floor 7 31.09 29.21 0.971 30.3 8.16 2.28 0.075 0–10 7 14.78 3.32 0.32 0.221 15.0 14.42 0.962 10–20 7 9.36 1.38 0.27 0.089 15.5 7.04 0.454 Spruce/fir groupb Forest floor 36 55.30 35.58 1.130 32.7 33.02 11.61 0.353 0–10 36 21.12 4.69 0.26 0.223 21.0 24.38 1.159 10–20 36 16.85 2.98 0.25 0.158 18.9 18.04 0.956 Western redcedar/larch Forest floor 6 58.10 30.46 0.736 42.0 52.86 15.81 0.378 0–10 6 17.74 2.66 0.24 0.106 25.2 18.29 0.727 10–20 6 18.89 1.70 0.28 0.095 18.0 13.77 0.766 Limber/whitebark pines Forest floor 13 28.06 35.93 1.069 36.0 17.19 6.32 0.172 0–10 13 9.40 2.80 0.35 0.149 18.8 16.05 0.853 10–20 13 8.74 1.99 0.30 0.112 17.7 11.58 0.653 aWater content and forest floor mass are reported on an oven-dry weight basis (105 oC). bSpruce/fir group includes Engelmann spruce, subalpine fir, mixed Engelmann spruce/subalpine fir, and grand fir. 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 137 Appendix F Table 1b—Mean water, carbon, and nitrogen contents of forest floor and soil cores by forest type, Montana, soil visit 2, 2008-2009. Forest type Soil layer Number of plots Water contenta Organic carbon Inorganic carbon Total nitrogen C/N ratio Forest floor massa Organic carbon Total nitrogen cm . . . . . . . . . . . . .Percent. . . . . . . . . . . . . . . . . . . . . . . . .Mg/ha. . . . . . . . . . . . Rocky Mountain juniper Forest floor 0 0–10 0 10–20 0 Ponderosa pine Forest floor 4 10.25 23.14 0.806 30.0 7.36 1.51 0.058 0–10 4 6.11 1.91 0.46 0.160 11.9 15.48 1.298 10–20 4 9.05 1.13 0.42 0.100 11.2 6.93 0.617 Lodgepole pine Forest floor 7 33.56 30.46 0.751 41.2 41.83 11.98 0.285 0–10 7 12.18 2.33 0.07 0.089 26.2 13.81 0.527 10–20 7 10.88 1.31 0.09 0.066 19.7 8.39 0.425 Douglas fir Forest floor 12 32.52 32.03 0.966 34.0 45.13 13.53 0.409 0–10 12 12.83 2.99 0.09 0.146 20.6 12.95 0.630 10–20 12 9.99 1.93 0.09 0.090 21.6 10.27 0.476 Cottonwood/aspen/birch Forest floor 1 12.19 21.35 0.597 34.4 9.67 2.35 0.062 0–10 1 15.96 1.58 0.72 0.105 15.1 16.53 1.095 10–20 1 12.09 1.52 0.64 0.142 10.7 17.68 1.647 Spruce/fir groupb Forest floor 8 42.79 40.32 1.197 34.6 17.61 6.93 0.195 0–10 8 25.44 9.42 0.29 0.417 22.6 52.82 2.336 10–20 8 17.56 4.24 0.10 0.204 20.8 29.16 1.403 Western redcedar/larch Forest floor 1 133.22 45.16 1.125 42.9 70.73 33.68 0.741 0–10 1 51.76 10.70 0.13 0.356 30.1 35.35 1.175 10–20 1 18.68 0.74 0.02 0.043 17.4 8.16 0.470 Limber/whitebark pines Forest floor 4 38.67 34.45 1.026 34.1 25.23 10.34 0.269 0–10 4 15.54 5.74 0.15 0.260 22.1 38.29 1.736 10–20 4 15.38 3.97 0.68 0.271 14.6 24.69 1.686 aWater content and forest floor mass are reported on an oven-dry weight basis (105 oC). bSpruce/fir group includes Engelmann spruce, subalpine fir, mixed Engelmann spruce/subalpine fir, and grand fir.
138 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Appendix F Table 2a—Mean physical and chemical properties of soil cores by forest type, Montana, soil visit 1, 2003-2007.

Forest type

Soil

layer

Number

of

plots SQIa Bulkdensity

Coarse

fragments pH

Bray 1

extractable

phosphorus

Olsen

extractable

phosphorus

cm % g/cm3

 % H2O CaCl2 . . . . . . .mg/kg. . . . . .

Rocky Mountain juniper 0–10 7 69 1.06 16.31 7.02 6.50 12.8 7.8

10–20 7 60 1.45 31.39 7.12 6.63 8.2 2.9

Ponderosa pine 0–10 34 65 1.10 23.52 7.20 6.71 9.8 6.4

10–20 34 58 1.30 32.44 7.40 6.81 2.5 3.1

Lodgepole pine 0–10 35 62 0.91 36.38 5.17 4.56 47.4 22.0

10–20 35 56 1.21 43.65 5.37 4.69 29.1 14.8

Douglas fir 0–10 66 71 1.04 42.41 6.15 5.60 40.0 26.0

10–20 66 64 1.30 47.94 6.27 5.67 31.3 16.1

Cottonwood/aspen/birch 0–10 7 71 0.89 43.16 6.48 5.99 21.2 9.8

10–20 7 61 1.33 47.09 6.54 5.85 11.2 4.5

Spruce/fir group 0–10 36 64 0.85 34.26 5.37 4.82 18.7 13.1

10–20 36 61 1.14 41.88 5.57 4.96 13.9 8.1

Western redcedar/larch 0–10 6 61 1.12 32.25 6.04 5.37 19.1 18.2

10–20 6 59 1.31 32.42 6.14 5.53 11.3 17.0

Limber/whitebark pines 0–10 13 64 1.01 40.58 5.94 5.38 12.0 12.0

10–20 13 56 1.16 45.12 5.87 5.23 15.3 9.5 a

SQI = Soil Quality Index. 

Appendix F Table 2b—Mean physical and chemical properties of soil cores by forest type, Montana, soil visit 2, 2008-2009.

Forest type

Soil

layer

Number

of

plots SQIa Bulkdensity

Coarse

fragments pH

Bray 1

extractable

phosphorus

Olsen

extractable

phosphorus

cm % g/cm3 % H2O CaCl2 . . . . . . .mg/kg. . . . . .

Rocky Mountain juniper 0–10 0 

10–20 0 

Ponderosa pine 0–10 4 60 1.19 25.52 7.34 6.78 3.5 4.7

10–20 4 55 1.41 43.41 7.40 6.78 1.2 2.1

Lodgepole pine 0–10 7 56 0.96 34.65 5.49 4.93 15.1 13.0

10–20 7 53 1.32 49.50 5.82 5.22 15.1 9.4

Douglas fir 0–10 12 69 0.96 47.90 6.12 5.61 27.9 34.1

10–20 12 64 1.38 53.04 6.08 5.49 27.6 26.6

Cottonwood/aspen/birch 0–10 1 63 1.05 0.27 7.78 7.35 11.3 7.7

10–20 1 63 1.17 0.27 8.04 7.59 7.3 4.1

Spruce/fir group 0–10 8 69 0.92 26.40 5.24 4.73 24.9 17.2

10–20 8 61 1.27 37.69 5.23 4.63 20.2 12.1

Western redcedar/larch 0–10 1 85 0.49 32.05 5.58 5.23 39.5 24.4

10–20 1 44 1.79 38.30 5.81 5.15 16.1 6.6

Limber/whitebark pines 0–10 4 61 0.93 23.55 5.26 4.73 25.7 17.8

10–20 4 69 1.32 40.21 6.52 6.07 9.4 10.5 a

SQI = Soil Quality Index. 
USDA Forest Service Resour. Bull. RMRS-RB-15. 2012 139

Appendix F Table 3a—Mean exchangeable cation concentrations in soil cores by forest type, Montana, soil visit 1, 2003-2007.

1 M NH4Cl Exchangeable cations

Forest type

Soil

layer

Number

of plots Na K Mg Ca Al ECEC

cm . .. . . . . . . . . . . . .mg/kg. . . . . . . . . . . . . . . . . cmolc/kg

Rocky Mountain juniper 0–10 7 73 322 426 2722 2 18.52

10–20 7 141 291 611 3076 1 21.79

Ponderosa pine 0–10 34 19 222 347 2786 3 18.08

10–20 34 20 148 308 2802 1 17.78

Lodgepole pine 0–10 35 9 164 88 779 97 6.94

10–20 35 7 102 72 600 65 5.19

Douglas fir 0–10 66 10 255 187 2226 17 14.11

10–20 66 5 186 154 1724 21 11.13

Cottonwood/aspen/birch 0–10 7 9 345 337 2597 10 17.32

10–20 7 3 164 187 1999 7 12.55

Spruce/fir group 0–10 36 6 132 114 1112 111 9.44

10–20 36 9 130 107 815 87 7.74

Western redcedar/larch 0–10 6 6 94 94 1082 38 7.37

10–20 6 10 97 63 778 36 5.48

Limber/whitebark pines 0–10 13 9 164 146 1594 95 14.03

10–20 13 8 124 112 997 125 11.08

Appendix F Table 3b—Mean exchangeable cation concentrations in soil cores by forest type, Montana, soil visit 2, 2008-2009.

1 M NH4Cl Exchangeable cations

Forest type

Soil

layer

Number

of

plots Na K Mg Ca Al ECEC

cm . . .. . . . . . . . . . . .mg/kg. . . . . . . . . . . . . . . cmolc/kg

Rocky Mountain juniper 0–10 0 

10–20 0 

Ponderosa pine 0–10 4 73 274 211 3473 0 21.12

10–20 4 74 175 252 3027 1 19.43

Lodgepole pine 0–10 7 49 81 46 315 41 3.31

10–20 7 46 120 55 331 24 4.00

Douglas fir 0–10 12 106 323 176 1774 30 12.62

10–20 12 108 247 174 1565 54 11.21

Cottonwood/aspen/birch 0–10 1 27 239 276 2779 0 16.86

10–20 1 34 211 296 2729 0 16.74

Spruce/fir group 0–10 8 68 192 141 2031 118 14.50

10–20 8 76 69 95 993 78 7.76

Western redcedar/larch 0–10 1 9 254 590 2487 2 17.97

10–20 1 21 39 123 459 11 3.62

Limber/whitebark pines 0–10 4 87 244 96 1075 103 9.81

10–20 4 109 155 105 2828 2 16.94
140 USDA Forest Service Resour. Bull. RMRS-RB-15. 2012

Appendix F Table 4a—Mean extractable trace element concentrations in soil cores by forest type, Montana, soil visit 1, 2003-2007.

1 M NH4Cl Extractable

Forest type

Soil

layer

Number

of

plots Mn Fe Ni Cu Zn Cd Pb S 

cm . . . . . . . . . . . . . . . . . . .mg/kg. . . . . . . . . . . . . . . . . . . . . . . . . .

Rocky Mountain juniper 0–10 7 2.51 0.22 0.13 0.00 0.24 0.02 0.28 6.5

10–20 7 1.96 0.12 0.13 0.01 0.00 0.03 0.08 6.6

Ponderosa pine 0–10 34 3.08 0.34 0.02 0.00 0.32 0.04 0.19 4.2

10–20 34 2.09 0.07 0.01 0.00 0.00 0.03 0.10 6.8

Lodgepole pine 0–10 35 40.40 8.75 0.04 0.14 2.88 0.17 1.38 7.5

10–20 35 14.05 2.74 0.02 0.01 0.37 0.03 0.26 4.7

Douglas fir 0–10 66 16.94 2.28 0.04 0.00 0.66 0.12 0.32 5.1

10–20 66 8.71 0.58 0.02 0.01 0.28 0.03 0.20 5.7

Cottonwood/aspen/birch 0–10 7 9.14 0.23 0.00 0.00 0.01 0.08 0.04 10.1

10–20 7 8.60 0.00 0.00 0.00 0.00 0.02 0.17 5.9

Spruce/fir group 0–10 36 21.98 7.47 0.08 0.01 1.06 0.13 0.60 16.6

10–20 36 10.29 5.63 0.04 0.00 0.36 0.05 0.23 5.0

Western redcedar/larch 0–10 6 11.92 1.57 0.00 0.00 0.22 0.05 0.30 4.6

10–20 6 4.57 1.86 0.02 0.00 0.25 0.01 0.34 5.5

Limber/whitebark pines 0–10 13 3.59 6.19 0.01 0.01 1.02 0.10 0.43 5.5

10–20 13 3.90 8.03 0.00 0.00 0.45 0.04 0.69 5.2

Appendix F Table 4b—Mean extractable trace element concentrations in soil cores by forest type, Montana, soil visit 2, 2008-2009.

1 M NH4Cl Extractable

Forest type

Soil

layer

Number

of

plots Mn Fe Ni Cu Zn Cd Pb S 

cm . . . . . . . . . . . . . . . . . . . . . . . . . . mg/kg. . . . . . . . . . . . . . . . . . . . . . . . . . . .

Rocky Mountain juniper 0–10 0 

10–20 0 

Ponderosa pine 0–10 4 1.69 0.05 0.00 0.00 0.00 0.01 0.06 1.0

10–20 4 1.47 0.93 0.00 0.00 0.00 0.00 0.32 0.2

Lodgepole pine 0–10 7 21.27 2.39 0.11 0.00 1.67 0.08 0.98 3.9

10–20 7 9.70 1.49 0.10 0.00 0.75 0.03 0.69 3.7

Douglas fir 0–10 12 21.33 1.01 0.22 0.00 0.59 0.08 0.31 8.1

10–20 12 9.79 0.53 0.23 0.00 0.67 0.04 0.05 7.2

Cottonwood/aspen/birch 0–10 1 2.29 0.00 0.00 0.00 0.00 0.05 0.03 7.6

10–20 1 1.52 0.00 0.00 0.00 0.00 0.02 0.26 8.3

Spruce/fir group 0–10 8 24.66 23.45 0.13 1.01 6.33 0.37 3.86 9.2

10–20 8 10.07 8.53 0.04 0.38 1.89 0.14 0.61 2.4

Western redcedar/larch 0–10 1 76.94 1.33 0.03 0.00 0.91 0.13 0.00 12.9

10–20 1 26.01 0.00 0.00 0.00 0.00 0.00 0.38 0.0

Limber/whitebark pines 0–10 4 22.71 23.97 0.09 0.00 3.60 0.17 5.95 10.7

10–20 4 3.65 0.48 0.00 0.00 0.00 0.03 0.29 3.9
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