United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

Resource Bulletin

RMRS-RB-10

December 2010

Utah’s Forest Resources, 

2000–2005

Larry T. DeBlander, John D. Shaw, Chris Witt, 

Jim Menlove, Michael T. Thompson, Todd A. Morgan, 

R. Justin DeRose, and Michael C. Amacher
You may order additional copies of this publication by sending your 

mailing information in label form through one of the following media. 

Please specify the publication title and number.

Telephone (970) 498-1392

FAX (970) 498-1122

E-mail rschneider@fs.fed.us

Web site http://www.fs.fed.us/rmrs

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526

The Authors

Larry T. DeBlander is a Forester and a member of the Analysis Team with the Interior West Inventory and Analysis Program at the Rocky Mountain Research Station in Ogden, UT. He holds a B.S. 

degree in Forest Science from Pennsylvania State University.

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

Program at the Rocky Mountain Research Station in Ogden, UT. 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.

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

Analysis Program at the Rocky Mountain Research Station in Ogden, UT.

He holds B.S. and M.S. degrees in Ecology from Idaho State University.

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

and Analysis Program at the Rocky Mountain Research Station in Ogden, UT. 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.

DeBlander, Larry T.; Shaw, John D.; Witt, Chris; Menlove, Jim; Thompson, Michael T.; Morgan, Todd A.; 

DeRose, R. Justin; Amacher, Michael C. 2010. Utah’s forest resources, 2000–2005. Resour. Bull. RMRSRB-10. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 

144 p.

Abstract

FIA is responsible for periodic assessments of the status and trends of the renewable resources of America’s 

forests. Fundamental to the accomplishment of these assessments are the State-by-State resource inventories, 

which are now conducted on an annual basis. This report summarizes the results, interpretations, and future 

significance of Utah’s annual inventory. The organization and layout of this report begins with a short introduction 

of FIA’s annual inventory system and then a detailed description of its inventory methods. After an overview of 

the report tables, the bulk of the report is contained in the “Forest Resources” and “Current Issues” and “FIA 

Indicators” sections, and finishes with a discussion of Utah’s Timber Products. The “Forest Resources” section 

is outlined similar to past periodic reports for ease of comparisons. The “Current Issues” and “FIA Indicators” 

sections cover topics considered pertinent to Utah’s forests relative to the information FIA collects, and points to 

other related or more in-depth studies and research. 
Michael T. Thompson is a Forester and a member of the Analysis Team with the Interior West Inventory and Analysis Program at the Rocky Mountain Research Station in Ogden, UT. He holds a B.S. 

degree in Forestry from North Carolina 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, MT. He received a B.A. degree in 

Philosophy and a B.S. degree in Forest Science from Pennsylvania State University and an M.S. 

degree in Forestry from The University of Montana.

R. Justin DeRose is a Ph.D. candidate in the Department of Wildland Resources and Ecology Center at Utah State University, Logan, UT. He has B.S. and M.S. degrees in Forestry (from Utah State 

University and University of Maine, respectively) and is currently working toward his Ph.D. in Forest 

Ecology. His research broadly covers production ecology and silviculture of spruce-fir forests in the 

eastern United States and disturbance ecology of spruce-fir forests of the Rocky Mountains. 

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

Program at the Rocky Mountain Research Station in Logan, UT. 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 Ph.D. in soil chemistry, all from Pennsylvania State University.

Contact author: Larry T. DeBlander, ldeblander@fs.fed.us, (801) 625-5204

Acknowledgments

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

the Intermountain Region, Forest Service, U.S. Department of Agriculture; the Utah State Forester and 

other Utah State Land Department personnel; the Bureaus of Land Management and Indian Affairs; 

the Utah State University Forestry Extension; and the National Park Service, U.S. Department of the 

Interior. The authors extend a special note of thanks to private landowners who provided information 

and access to field sample plots, and to the field staff who collected the inventory data.

i
Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

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

II.Inventory Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Plot Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Sample Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Three-Phase Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Sources of Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

III.Overview of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

IV.Overview of Forest Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Number of Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Volume and Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Growth and Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Stand Density Index (SDI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Quality Assurance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

V.Current Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Other Wooded Land . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Aspen Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Expansion of Pinyon and Juniper Woodlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Drought-Related Effects on Pinyon-Juniper Woodlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Spruce Beetle Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Old Forest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Noxious Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Snags as Wildlife Habitat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Cheatgrass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

VI.FIA Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Phase 3 Down Woody Material . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Forest Lichens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Phase 2 Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

VII. Timber Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Removals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Forest Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

VIII.Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

IX.Standard Forest Inventory and Analysis Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

X.References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

XI.Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Appendix A: Inventory History and “New Proposed Land Class” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Appendix B: Common Name, Scientific Name, and Timber (T) or Woodland (W) 

Designation for Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Appendix C: Forest Type Groups, Forest Type Names— Annual and (Periodic), and 

Timber (T) or Woodland (W) Designation for Forest Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Appendix D: Volume, Biomass, and Site Index Equation Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Appendix E: List of Tables and Appendix E Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Appendix F: Tables of Mean Soil Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142

ii
Preface

The Forest Inventory and Analysis (FIA) program is 

managed by the Research and Development organization within the USDA Forest Service in cooperation with 

State and Private Forestry and National Forest Systems.

Since the McSweeny-McNary act of 1928, FIA has been 

operating for some 80 years under various names (Forest 

Survey, Forest Inventory and Analysis) as the Nation’s 

continuous forest census. FIA is responsible for periodic 

assessments of the status and trends of the renewable 

resources of America’s forests. Fundamental to the accomplishment of these assessments are the State-byState resource inventories, which are now conducted 

on an annual basis. This report summarizes the results, 

interpretations, and future significance of Utah’s annual 

inventory.

Early FIA inventories stressed information on the 

country’s commercial timber situation; forest land 

was covered in a broader sense mainly for its water, 

recreation, and forage values, and problems related to 

multiple-use management. Today the Forest Service 

has significantly enhanced the FIA program by increasing our capacity to analyze and publish data, and by 

expanding the scope of our data collection to include 

soil, understory vegetation, tree crowns and damage 

conditions, down woody debris, and lichen community 

composition.

The organization and layout of this report begins with 

a short introduction of FIA’s annual inventory system and 

then a detailed description of its inventory methods. After 

an overview of the report tables, the bulk of the report is 

contained in the “Forest Resources,” “Current Issues,” 

and “FIA Indicators” sections, and finishes with a discussion of Utah’s timber products. The “Forest Resources” 

section is outlined similar to past periodic reports for 

ease of comparisons. The “Current Issues” and “FIA 

Indicators” sections cover topics considered pertinent 

to Utah’s forests relative to the information FIA collects, 

and points to other related or more in-depth studies and 

research. 

The “Forest Resources,” “Current Issues,” and “FIA 

Indicators” topics are organized into three sub-sections: 

(1) a “Background” section that discusses, in general, 

the importance of the topic; (2) an “Inventory results” 

section that presents data and results—often with figures 

and tables; and (3) a “Discussion” section that conveys 

the meaning or significance of the results. In addition, 

throughout the report reference is made to Appendix A, 

which covers much of Interior West FIA’s past inventory 

history as it is relevant to today’s annual inventories.

iii

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 1

I. Introduction

This report contains highlights of the status of Utah’s forest resources, with discussions of pertinent issues based on the first 6 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 four 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 Utah in 2000. 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. The 6 inventory years covered in this 

report are 2000 through 2005. Although the Farm Bill requires reports after 5 years, 

the Utah report was delayed to give the IWFIA program time to work through national 

inconsistencies with past and current forest land definitions.

In this report, some of the factors affecting definitional differences, such as stocking or 

crown cover, have been reconciled with the past through a process called “plot-filtering,” 

which re-classified forest land with 5 to 9 percent cover as a potentially new land class 

called “other wooded land.” This process is discussed in more detail in Appendix A, 

along with changes in other definitional factors such as tree-form, species, and forest 

type algorithms, which could not be reconciled due to various reasons. In summary, 

Appendix A discusses the potential effects each factor has on past versus current forest 

land definitions. Field data for the previous periodic report for Utah (O’Brien 1999)

was inventoried in 1993. To the extent possible, comparisons will be made to the 1999 

report both in terms of the changes in definitions and protocols listed above, and real 

change in forest conditions.

Although Utah is the second driest State in the United States, 36 percent (19.5 million acres) of the State’s total area is considered forest or other wooded land. A large 

portion of Utah’s timber types occurs in the Uinta and Wasatch Mountain ranges of the 

Southern Rockies, the Utah Mountains of the Great Basin, and the higher elevations 

of the Colorado Plateau. The Uinta Mountains, in northeastern Utah, are a sub-range 

of the Rocky Mountains and are unusual for being the highest range in the contiguous 

United States running east to west. The Wasatch Range, which stretches over 200 miles 

from the Utah-Idaho border south through central Utah, is generally considered the 

western edge of the greater Rocky Mountains, and the eastern edge of the Great Basin 

region. The Colorado Plateau is roughly centered on the four corners region of the 

southwestern United States and occupies southeastern Utah. Utah’s woodland types are 

scattered throughout these mountain ranges at lower elevations, and throughout much 

of southern Utah on the Colorado Plateau. 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 

2010, a full assessment of ten subpanels of data will be included in the upcoming 10-

year (full cycle) report. In 2010, the re-measurement phase of the inventory will begin 

by re-measuring the first subpanel of plot data collected in 2000.
2 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 3

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 2000-2005a). 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 non-overlapping, 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 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.
4 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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 Utah 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 Utah, 

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 Utah is defined as:

A A ˆ n

n

y

n g Tg

hg

h g

H ihg

i

n

hg

hg

= ′

′ =

= ∑

∑

1

1

where:

Aˆ

g = 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

yihg = 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 2000-2005a). 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 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.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 5

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 2000-2005b). 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.

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 errors they 

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

the estimate. The 2000-2005 FIA inventory of Utah is based on a sample of 5,382 plots 

systematically located across the State (a total area of 54.3 million acres); a sampling 

rate of approximately one plot for every 10,096 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). 

Along 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 hypothetically 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-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. Sampling errors 

obtained from this method are only approximations of reliability because homogeneity 

of variances is assumed. The formula is:

SE SE

X

X s t t

s

=

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 
6 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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 used model-based predictions in the estimation process.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 7

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

using Utah annual data (cycle 2) for the years 2000 through 2005. 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. 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 E and Appendix F tables will be referred to beginning with 

“Appendix E” or “Appendix F” followed by the table number. Appendix E also contains 

a list of all report tables with table headings.
8 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 9

IV. Overview of Forest Resources

The following sections discuss the status and possible trends of Utah’s forest land 

resources in terms of area, volume, number of trees, biomass, growth/mortality, and 

stand density index (SDI) using annual data collected from 2000 through 2005; another 

section discusses quality assurance (QA) of inventory data using data collected from 

2001 through 2005. “Area” is the only section under “Overview of Forest Resources” 

that will include separate summaries of forest land, other wooded, and nonforest lands; 

the remaining “Overview of Forest Resources” sections will focus only on the forest land 

base. Exclusion of other wooded land from forest land summaries of volume, biomass, 

etc., facilitates compatibility with similar Resource Planning Act (RPA) statistics, and 

is consistent with FIA’s current definition of forest land. Other wooded lands (see Appendix A), by definition, contain few trees and thus little volume and biomass, but are 

important as an ecotone, at least from an area perspective.

Area

Background—Area by different land classifications (e.g., land class, ownership, forest type, etc.) provides the overall perspective and context for the “Overview of Forest 

Resources,” “Current Issues and FIA Indicators,” and “Timber Products” sections of this 

report. Although area estimates are somewhat confounded by past definitional changes, 

primarily in woodland forest types, Utah’s total forest land base appears to be on the 

increase (table 1). In addition, the partitioning of the new land class (other wooded land) 

provides further context, especially in many of Utah’s arid, sparsely vegetated forest 

types like juniper woodland.

Inventory Results: Land Class—The State of Utah covers over 54 million acres 

(table 1). Thirty-three percent (almost 18 million acres) of the area meets the definition of forest land, and about 3 percent (1.6 million acres) meets the definition of other 

wooded lands. The remaining 64 percent (35 million acres) is classified as nonforest or 

water. Figure 1 displays the distribution of FIA field plots by two land classes (forest 

land and other wooded) and ownership in Utah.

Table 1--Total area (acres) by ownership class and land class, Utah, cycle 2, 2000-2005.

Owner group Ownership class Forest land Other wooded Nonforest and water Grand Total

Forest Service National Forest 6,251,534 217,622 1,703,495 8,172,651

Other National Forest 7,432 -- 52,024 59,457

Forest Service Total 6,258,966 217,622 1,755,519 8,232,107

Other Federal Bureau of Land Management 6,799,821 926,492 15,165,602 22,891,915

National Park Service 345,183 71,716 1,488,911 1,905,810

Department of Defense or Energy 9,951 -- 1,717,340 1,727,291

Fish and Wildlife Service 10,886 -- 61,274 72,160

Other Federal Total 7,165,840 998,209 18,433,127 26,597,176

State and local government State 1,513,682 95,993 4,433,359 6,043,033

Local (county, municipal, etc.) 11,266 -- 18,979 30,245

State and local government Total 1,524,947 95,993 4,452,337 6,073,278

Private Undifferentiated private 3,012,701 238,830 10,180,657 13,432,189

Private Total 3,012,701 238,830 10,180,657 13,432,189

Grand Total 17,962,455 1,550,654 34,821,641 54,334,750

All table cells without observations in the inventory sample are indicated by --.
10 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 1—Distribution of inventory plots by land class and ownership, Utah, cycle 2, 2000-2005. Note: plot locations 

are approximate and some on private land are randomly swapped.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 11

Inventory Results:Owner Class—Table 1 shows that over 75 percent of Utah’s total 

land area is in the public domain, which also includes over 83 percent of the total forest 

land area. The Bureau of Land Management (BLM) contains the largest proportion of 

Utah’s nonforest lands (44 percent), followed by private lands (29 percent), and State 

lands (13 percent). The BLM also contains the majority of forest land, at 38 percent, 

followed by National Forest Systems (NFS) at 35 percent; however, a larger proportion 

(76 percent) of NFS lands is forested compared to BLM lands (30 percent). The major 

breakdown of ownership for other wooded lands is BLM at 60 percent, private at 15 

percent, and NFS at 14 percent.

The BLM and IWFIA worked jointly, under the administration of the BLM, on a 

report specific to forest lands that used the 5 percent cover definition for forest land 

(Bottomley and Menlove 2006). In this BLM report, estimates of forest land for the 

same reporting period in Utah was greater due to differences in forest land definitions.

Inventory Results: Forest Type—Forest type refers to the predominant species in a 

stand, based on plurality of tree stocking. Table 2 presents area by forest type for both 

forest and other wooded land classes. At 44 percent (7.9 million acres), pinyon-juniper 

woodland is by far the most common forest type on forest land in Utah, followed by 

juniper woodland and deciduous oak woodland at 11 percent each, and aspen at 9 percent. In contrast to forest land, the most common forest type on other wooded lands is 

juniper woodland (34 percent), followed by pinyon-juniper woodland (32 percent), and 

nonstocked (29 percent).

Table 2--Area (acres) of timber/woodland forest types by forest type and land class, Utah, cycle 2, 2000-2005.

Timber/woodland type Forest type Forest land Other wooded Grand Total

Timber type Aspen 1,640,330 10,620 1,650,950

Blue spruce 6,988 -- 6,988

Cottonwood 31,564 -- 31,564

Douglas-fir 650,453 22,718 673,171

Engelmann spruce 491,425 -- 491,425

Foxtail pine-bristlecone pine 24,501 -- 24,501

Limber pine 22,685 -- 22,685

Lodgepole pine 393,175 -- 393,175

Ponderosa pine 388,385 6,915 395,300

Engelmann Spruce-subalpine fir 172,942 -- 172,942

Subalpine fir 397,054 -- 397,054

White fir 355,031 -- 355,031

Timber types Total 4,574,535 40,252 4,614,787

Woodland type Cercocarpus woodland 412,356 5,070 417,426

Deciduous oak woodland 1,986,909 11,692 1,998,601

Juniper woodland 1,994,831 534,787 2,529,618

Intermountain maple woodland 242,480 -- 242,480

Pinyon-juniper woodland 7,904,926 491,271 8,396,197

Rocky Mountain juniper 310,720 25,265 335,985

Woodland types Total 12,852,222 1,068,085 13,920,307

Nonstocked Nonstocked 535,699 442,317 978,016

Nonstocked Total 535,699 442,317 978,016

Grand Total 17,962,455 1,550,654 19,513,109

All table cells without observations in the inventory sample are indicated by --.
12 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

In past reports, forest types have often been separated into timber and woodland 

types (Appendix C). Timber types are characterized by stands where the plurality of 

stocking is from species where diameter is measured at breast height, as opposed to 

root collar (woodland types). In this report, both forest and other wooded land classes 

may contain timber or woodland forest types. Table 2 shows the general dominance of 

woodland forest types in Utah. Seventy-two percent (12.9 million acres) of all forest 

land comprises woodland types, while 25 percent (4.6 million acres) comprises timber 

types. Considering only other wooded land, 69 percent (1.1 million acres) comprises 

woodland types, and only 3 percent (40 thousand acres) comprises timber types. Not 

surprisingly, 45 percent (0.4 million acres) of all Utah’s nonstocked land (forest and 

other wooded), occurs on other wooded land. (See “Other Wooded Land” in Section V 

for further discussions on nonstocked issues.)

The distribution of forest types in Utah is influenced by many factors such as elevation, moisture, aspect, soils, climate, and past fire history. Due to Utah’s arid nature, 

moisture, which is heavily influenced by elevation, is a major factor. The ecoregions of 

the United States are classified in descending order by domains, divisions, provinces, 

and sections. The entire State of Utah lies within the Dry Domain of Bailey’s ecoregions 

(Bailey 1978) containing six distinct provinces. Ranging from under 4,000 to over 13,000 

feet in elevation, all six provinces in Utah (four desert and two mountain) contain forest 

and other wooded lands. Figure 2 displays the distribution of FIA field plots by forest 

type, ecoregion province, and elevation for forest and other wooded lands. Some forest types have been combined for ease of display: aspen and cottonwood; Engelmann 

spruce-subalpine fir, blue spruce, and subalpine fir; limber and foxtail pine-bristlecone 

pine; deciduous oak woodland and intermountain maple woodland; and juniper woodland and Rocky Mountain juniper.

Inventory Results: Reserved Status and Productivity—Reserved lands are lands 

withdrawn from management for production of wood products. For context on the importance of wood products to Utah’s local and regional economies, and for comparisons 

between the often widely differing stand characteristics of nonreserved versus reserved 

lands, table 3 presents the area of forest and other wooded lands by reserved status, 

owner class, and productivity. Eighty-nine percent (17.4 million acres) of Utah’s forest 

and other wooded lands are in nonreserved status, leaving 11 percent (2.1 million acres) 

as reserved. Seventy-five percent of all Utah’s forest land is unproductive, which means 

it is not capable of producing wood volumes of at least 20 cubic feet per acre per year. 

Most of these lands are woodland forest types, which are unproductive by definition.

Timberland, defined in this report as nonreserved productive forest land, is an important 

classification describing the potential availability of timber products. Twenty-two percent 

(about 4.0 million acres) of all forest land in Utah meets the definition of timberland.

Discussion—The use of crown cover to separate and exclude other wooded land 

from forest land helped reconcile much of Utah’s apparent increases in forest land 

compared to past inventories (see “Plot-filtering and the definition of forest and other 

wooded lands” in Appendix A). Nevertheless, Utah’s current annual inventory still shows 

about a 14-percent (2.3-million acre) positive difference from the total forest land area 

(15.7 million) inventoried in 1993 (O’Brien 1999, table 1). In addition to the effects of 

crown cover, Appendix A discusses some of the expected definitional impacts between 

the inventories in terms of tree-form, species, plot imagery, and changing forest type 

algorithms. These remaining factors would collectively favor further perceived increases 

in forest land, and more likely in woodland types than in timber types, which is where 

the majority of the forest land increase occurred. This could potentially explain much of 

the 14 percent difference. However, the lack of similar plot-filtering field variables for 

determining why past periodic plots where called nonforest precludes the plot-to-plot 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 13

Figure 2—Distribution of inventory plots by forest type, ecoregion province, land class, and elevation, Utah, 

cycle 2, 2000-2005. Note: plot locations are approximate and some on private land are randomly swapped.
14 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Table 3--Area (acres) of forest land and other-wooded by reserved status, ownership class, and productivity, Utah, cycle 2, 2000-2005. Forest land Forest land Total Other wooded Other wooded Total Grand Total Reserved status Ownership class Productive Unproductive Productive Unproductive Not reserved National Forest 2,995,232 2,736,563 5,731,795 61,110 145,714 206,824 5,938,619 Bureau of Land Management 140,612 5,739,981 5,880,593 5,031 821,761 826,792 6,707,385 Department of Defense or Energy -- 9,951 9,951 -- -- -- 9,951 State 154,172 1,261,015 1,415,187 2,457 85,438 87,895 1,503,082 Local (county, municipal, etc.) 11,266 -- 11,266 -- -- -- 11,266 Private 690,510 2,319,048 3,009,558 17,929 220,901 238,830 3,248,389 Not reserved Total 3,991,791 12,066,558 16,058,350 86,528 1,273,814 1,360,342 17,418,691 Reserved National Forest 398,826 120,914 519,739 -- 10,798 10,798 530,537 Other National Forest -- 7,432 7,432 -- -- -- 7,432 Bureau of Land Management 10,211 909,017 919,228 -- 99,700 99,700 1,018,928 National Park Service 64,864 280,319 345,183 -- 71,716 71,716 416,899 Fish and Wildlife Service -- 10,886 10,886 -- -- -- 10,886 State -- 98,495 98,495 -- 8,098 8,098 106,592 Private -- 3,143 3,143 -- -- -- 3,143 Reserved Total 473,900 1,430,206 1,904,106 -- 190,312 190,312 2,094,418 Grand Total 4,465,691 13,496,764 17,962,455 86,528 1,464,126 1,550,654 19,513,109 All table cells without observations in the inventory sample are indicated by --.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 15

analysis needed to break down the definitive causes of real “on-the-ground” changes. 

As a result, the following comparisons between inventories remain tempered by these 

definitional differences.

In terms of ownership, 82 percent of Utah’s apparent forest land increase occurred 

on BLM, NFS, and State lands (table 1). A comparison of figures 1 and 2 shows that 

most of the higher elevation NFS lands contain the majority of the timber types, and 

the lower elevation BLM lands contain the majority of the woodland types and other 

wooded lands.

Two woodland forest types accounted for most of the net increase in Utah’s forest 

area: an increase of about 1.2 million acres in deciduous oak woodland, and over 900 

thousand acres in juniper woodland (table 2). Increases in deciduous oak woodland are 

related to the tree-form issue discussed in Appendix A. In addition, three timber forest 

types changed substantially from previous estimates. Although the combined annual 

Engelmann spruce-subalpine fir and subalpine fir types changed little compared to 

periodic spruce-fir, the apparent decrease in Engelmann spruce-subalpine fir is due to 

a partial shifting of area to subalpine fir, which is a new forest type not present in past 

periodic inventories. Since Gambel oak is a common component of Douglas-fir and 

ponderosa pine types, there was a substantial shift in Douglas-fir and ponderosa pine 

types to deciduous oak woodland, which is related to changes in the forest type algorithm 

issue discussed in Appendix A. The remaining forest types have stayed fairly stable with 

the exception of aspen, which has increased by about 15 percent (212 thousand acres).

Although the total reserved land in Utah has changed little since 1993, the amount of 

timberland has decreased by 15 percent (712 thousand acres). Of the definitional factors 

discussed in Appendix A, cover and changing forest type algorithms have the largest 

influence on the decrease in timberland area. This is due to the previous threshold of 

only 5 percent cover to qualify as timberland on sites mixed with larger amounts of 

woodland species, rather than the species with plurality of stocking as in annual inventories. As a result, at least some of these stands would switch to woodland types under 

annual inventory standards.

Number of Trees

Background—Estimates of numbers of trees are expanded from trees per acre to 

the population level. The composition of forests by different species is an indicator of 

forest diversity. In addition, dead trees, or snags, are an important component of forested 

landscapes, playing crucial roles in wildlife habitat, nutrient cycles (including carbon), 

fire fuel loading, and soil formation.

Inventory Results—Nearly 8.4 billion live trees 1.0-inch diameter and larger are 

estimated to occur on Utah forest land (Appendix E, table 10). Gambel oak is by far 

the most abundant species in the State, with 41 percent of the live trees on forest land 

(fig. 3). The second most abundant species is Utah juniper, with 11 percent of the live 

trees, followed by common or twoneedle pinyon and aspen, each with about 9 percent 

of live trees. The most abundant timber conifer species on forest land is subalpine fir 

with over 5 percent of the live trees.

On timberland (nonreserved and productive) in Utah, there are 650 million live 

growing-stock trees 5.0-inches diameter and greater, of which aspen is the most common with nearly 36 percent (Appendix E, table 11). The next most abundant growingstock species on timberland are lodgepole pine with over 16 percent, subalpine fir with 

15 percent, Douglas-fir with 12 percent, Engelmann spruce with 10 percent, white fir 

with 7 percent (combined with subalpine fir in Appendix E, table 11 as true fir), and 

ponderosa pine with nearly 4 percent.
16 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 4 shows numbers of live trees by diameter class (whether measured at breast 

height or root collar), and shows the expected distribution of many smaller trees compared to larger trees. Overall, trees less than 5.0-inches diameter make up 75 percent 

of all live trees. Over half (54 percent) of the trees smaller than 5.0-inches diameter are 

Gambel oaks. Conversely, the second most common live tree, Utah juniper—a larger and 

longer-lived species—makes up 60 percent of live trees 15.0-inches diameter and larger.

There are an estimated 347 million standing dead trees at least 5.0-inches diameter 

on forest land in Utah (table 4), or an average of 19.3 snags per acre. As with live trees, 

larger snags are less common than smaller snags, and often contribute more significantly to the landscape components mentioned above. The average density for snags 

11.0-inches diameter and larger is 5.6 per acre. Very large snags, 19.0-inches diameter 

and larger, occur on Utah forests at about 0.8 per acre. In all size classes, the most common species for snags is Utah juniper. In both larger snag classes (11.0-inches and over 

and 19.0-inches and over), the most abundant timber species for snags is Engelmann 

spruce. 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 sub-levels of forest land, such as ownerships, counties, or forest types.

Discussion—Our annual inventory results show an increase of 34 percent of live 

trees on forest land in Utah since 1993, from 6.3 billion (O’Brien 1999, table 14) to 

8.4 billion trees (Appendix E, table 10). The primary reason for the increase is related to 

Figure 3—Number of live trees 1.0 inch diameter and greater by species on forest land, Utah, cycle 2, 2000-2005.

0 200 400 600 800 1,000 1,200 1,400 1,600 

Gambel oak 

Utah juniper 

Twoneedle pinyon 

Aspen 

Bigtooth maple 

Subalpine fir 

Lodgepole pine 

Singleleaf pinyon 

Douglas-fir 

Curlleaf mtn mahogany 

Engelmann spruce 

White fir 

Rocky Mtn juniper 

Ponderosa pine 

Other 

Million trees 

Species 

3,451 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 17

Species 5.0 - 10.9 11.0 - 18.9 19.0 All classes 5.0 11.0 19.0

Blue spruce 55,486 -- -- 55,486 0.0 -- --

Common or twoneedle pinyon 23,437,181 11,790,332 739,599 35,967,113 2.0 0.7 0.0

Douglas-fir 8,313,713 5,004,678 1,689,913 15,008,304 0.8 0.4 0.1

Engelmann spruce 8,613,500 8,034,354 2,363,279 19,011,134 1.1 0.6 0.1

Great Basin bristlecone pine 56,996 56,996 56,996 170,989 0.0 0.0 0.0

Limber pine 390,399 273,639 120,355 784,392 0.0 0.0 0.0

Lodgepole pine 19,078,145 3,613,786 503,367 23,195,299 1.3 0.2 0.0

Ponderosa pine 518,665 1,497,846 799,671 2,816,182 0.2 0.1 0.0

Rocky Mountain juniper 2,302,557 1,181,687 153,328 3,637,572 0.2 0.1 0.0

Singleleaf pinyon 5,031,414 1,594,365 168,058 6,793,837 0.4 0.1 0.0

Subalpine fir 35,110,046 8,347,075 648,464 44,105,585 2.5 0.5 0.0

Utah juniper 46,110,249 31,227,999 6,444,209 83,782,457 4.7 2.1 0.4

White fir 8,176,786 3,927,797 869,370 12,973,953 0.7 0.3 0.0

Softwoods Total 157,195,137 76,550,555 14,556,611 248,302,303 13.8 5.1 0.8

Aspen 58,557,341 6,034,573 181,247 64,773,160 3.6 0.3 0.0

Bigtooth maple 1,701,897 -- -- 1,701,897 0.1 -- --

Curlleaf mountain-mahogany 11,874,334 2,343,251 122,076 14,339,661 0.8 0.1 0.0

Fremont cottonwood,Rio Grande cottonwood 75,643 -- -- 75,643 0.0 -- --

Gambel oak 16,637,340 227,562 -- 16,864,903 0.9 -- --

Narrowleaf cottonwood 317,551 327,581 60,333 705,465 0.0 0.0 0.0

Hardwoods Total 89,164,105 8,932,967 363,656 98,460,728 5.5 0.5 0.0

All species 246,359,243 85,483,522 14,920,267 346,763,031 19.3 5.6 0.8

All table cells without observations in the inventory sample are indicated by --.

Number of snags Snags per acre

Diameter class (inches) Minimum diameter 

Table 4--Number of snags by diameter class and snags per acre (number of snags at least the minimum diameter ÷ 17,962,455 acres) on forest land, 

Utah, cycle 2, 2000-2005.

Figure 4—Number of live trees 1.0 inch diameter and greater by diameter class on forest land, Utah, cycle 2, 2000-2005.

0 

500 

1,000 

1,500 

2,000 

2,500 

3,000 

3,500 

4,000 

4,500 

5,000 

1.0-2.9 3.0-4.9 5.0-6.9 7.0-8.9 9.0-10.9 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 

≥29.0 

Million trees 

Two-inch diameter class (inches) 

11.0-

12.9 

13.0-

14.9 
18 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

a few species that were most influenced by the tree form requirements (see Appendix A), 

particularly Gambel oak, along with bigtooth maple and curlleaf mountain-mahogany. 

The increases in the numbers of live trees of these three species (nearly 2.3 billion 

trees) add up to more than the increase for all forest land (2.1 billion trees). Gambel oak 

often occurs in dense thickets of small trees; indeed, 97 percent of all of the Gambel 

oaks measured were less than 5 inches diameter. Although Gambel oak was the most 

common species reported in the previous Utah report, the current estimate is more than 

double the previous estimate.

The species showing the largest decrease in number of live trees since 1993 was aspen 

(0.2 billion fewer trees). This may appear contradictory, considering the increases in both 

the area of the aspen forest type and net volume in aspen (see “Growth and Mortality” 

in this section for more aspen context). However, the decrease in live aspens occurred 

almost exclusively in trees less than 9.0 inches diameter, while trees over 11.0 inches 

diameter increased by 20 percent. This would indicate that some young, dense aspen 

stands are maturing into stands of larger trees, accompanied by self-thinning mortality of 

smaller trees. This trend is not currently being off-set by the establishment of more young 

and dense aspen stands (see additional discussion in “Aspen Mortality” in Section V).

Volume and Biomass

Background—Estimates of gross and net volume include only the merchantable portion or saw-log portion (e.g., cubic-foot, board-foot) of trees, while biomass describes 

aboveground tree weight 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 based on gross volumes and 

exclude foliage. Volume and biomass equation sources are documented in Appendix D.

Inventory Results—Tables 12 through 16 in Appendix E show net volume of live 

trees 5.0 inches diameter and greater on Utah forest land by various categories. The total 

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

Utah forest land is 15.7 and 2.3 billion cubic-feet, respectively (fig. 5). The predominant 

species are Utah juniper, which comprises over 25 percent of the total live net cubicfoot volume, followed by aspen and common pinyon at 12 percent each, Engelmann 

spruce at 10 percent, and Douglas-fir at 9 percent. Engelmann spruce comprises 18 

percent of the total standing dead volume, followed by 16 percent for subalpine fir, 13 

percent for aspen, 12 percent for Utah juniper, and 10 percent for lodgepole pine. The 

total weight of oven-dry biomass in live (1.0 inch diameter and greater) and standing 

dead trees (5.0 inches diameter and greater) on Utah forest land is 309 and 49 million 

tons, respectively (fig. 6).

Another way to look at volume and biomass is by forest type, for which net volume 

and biomass per acre can be computed (table 5). These estimates include the different 

species that occur within each forest type. Engelmann spruce-subalpine fir has the highest 

net volume of live trees, 5.0 inches diameter and greater, at 2,918 cubic feet per acre, 

and the highest biomass of live trees, 1.0 inch diameter and greater, at 48.1 tons per 

acre. In contrast, pinyon-juniper woodland, the most common forest type in Utah, has 

about 675 cubic feet per acre of volume and 12.4 tons per acre of biomass. Estimates 

for foxtail/bristlecone pine, limber pine, and blue spruce may not be representative due 

to small samples.

The net volume of growing-stock trees on nonreserved productive timberland in Utah 

is over 7 billion cubic feet (Appendix E, table 17). Aspen makes up 25 percent of the 

total growing-stock volume, followed by Engelmann spruce at 18 percent, Douglas-fir 

at 16 percent, subalpine fir at 14 percent, and lodgepole pine at 11 percent. Table 19 

(Appendix E) shows the volume of sawtimber trees (International 1⁄4-inch rule) on 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 19 Figure 5—Net cubic-foot volume of live and standing dead trees 5.0 inches diameter and greater by species on forest land, Utah, cycle 2, 2000-2005. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Cottonwood Great Basin bristlecone pine Narrowleaf cottonwood Limber pine Blue spruce Bigtooth maple Curlleaf mountain-mahogany Gambel oak Rocky Mountain juniper Singleleaf pinyon Ponderosa pine White fir Subalpine fir Lodgepole pine Douglas-fir Engelmann spruce Common or twoneedle pinyon Aspen Utah juniper Billion cubic-feet

Species

Standing deadLive

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

Cottonwood

Great Basin bristlecone pine

Narrowleaf cottonwood

Limber pine

Blue spruce

Bigtooth maple

Curlleaf mountain-mahogany

Gambel oak

Rocky Mountain juniper

Singleleaf pinyon

Ponderosa pine

White fir

Subalpine fir

Lodgepole pine

Douglas-fir

Engelmann spruce

Common or twoneedle pinyon

Aspen

Utah juniper

Billion cubic-feet

Species

Standing deadLive
20 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Figure 6—Oven-dry weight biomass of live and standing dead trees by species on forest land, Utah, cycle 2, 2000-2005. 0 10 20 30 40 50 60 70 80 Cottonwood Great Basin bristlecone pine Narrowleaf cottonwood Limber pine Blue spruce Bigtooth maple Curlleaf mountain-mahogany Gambel oak Rocky Mountain juniper Singleleaf pinyon Ponderosa pine White fir Subalpine fir Lodgepole pine Douglas-fir Engelmann spruce Common or twoneedle pinyon Aspen Utah juniper Million tons 

Species 

Standing dead (5"+ dia)Live (1"+ dia)
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 21

nonreserved productive timberland at about 26.6 billion board feet (22.2 billion boardfeet Scribner rule). Engelmann spruce accounts for the majority of sawtimber at 23 

percent, followed by Douglas-fir at 19 percent, aspen at 16 percent, and subalpine fir 

at 15 percent. The total weight of oven-dry biomass in live trees 1.0-inch diameter and 

greater on nonreserved productive timberland land is over 135 million tons (Appendix 

E, table 29).

Discussion—There was a 14 percent increase in forest land in Utah since 1993, 

mostly associated with increases in the deciduous oak woodland and juniper types (see 

“Area” discussion in Section IV). In conjunction with this, total live volume of trees 5.0 

inches diameter and greater showed a small increase of 3.5 percent over the 1993 data 

(O’Brien 1999, table19). This shows that compared to area, the definitional impacts are 

minor in terms of changes in volume. Species contributing to most of the live volume 

increase were aspen, Utah juniper, lodgepole pine, and Rocky Mountain juniper; species 

with the largest decreases in volume were Douglas-fir and Engelmann spruce. Direct 

comparisons to past biomass are not plausible because different biomass definitions and 

computations were used in the previous inventory. In general, the current volume and 

biomass estimates are more correlated with each other.

 Although there was a 15 percent decrease in area of nonreserved productive timberland, net volume of growing-stock trees on these lands decreased only 6 percent, down 

from 7.4 billion cubic feet in 1993. Also, as in 1993, aspen continues to comprise the 

greatest percentage of growing-stock volume, as does Engelmann spruce and Douglasfir for sawtimber volume.

Growth and Mortality

Background—Forest vigor and sustainability can be assessed using change components: growth, mortality, and removals. Growth, as reported here, is the average 

annual growth volume calculated from a sample of tree increment core measurements 

Table 5--Net volume (cubic-feet) and biomass (tons) per acre of live trees by forest type on forest 

land, Utah, cycle 2, 2000-2005.

Forest type Net volume Biomass

Engelmann spruce-subalpine-fir 2,918 48.1

Engelmann spruce 2,632 43.1

Lodgepole pine 2,295 44.2

White fir 1,937 38.4

Douglas-fir 1,847 36.9

Blue spruce 1,824 26.7

Limber pine 1,756 33.4

Subalpine fir 1,635 30.0

Aspen 1,571 29.2

Ponderosa pine 1,415 29.5

Foxtail pine-bristlecone pine 973 21.4

Rocky Mountain juniper 959 19.7

Pinyon-juniper woodland 675 12.4

Cottonwood 674 11.5

Intermountain maple woodland 497 18.9

Cercocarpus woodland 492 19.6

Juniper woodland 451 8.8

Deciduous oak woodland 172 8.4

Nonstocked 36 0.7

Grand Total 873 17.2
22 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

based on the previous 10 years of growth. Mortality is the average annual net volume 

of trees that have died in the 5 years prior to the year of measurement, and removals, 

in general, are the annual net volume of trees that were removed from the inventory as 

the result of harvesting activity. The estimate of Utah’s removal volume was obtained 

from a separate study discussed in “Section VII —Timber Products.”

As State annual inventory cycles are completed, future reports will assess change 

components through remeasurement of the permanent annual field plots rather than tree 

core samples or identification of 5-year mortality trees; however, alternate methods are 

being investigated for woodland species growth (see “Quality Assurance Analysis” in 

this section).

Inventory Results—Gross annual growth of all live trees 5.0 inches diameter and 

greater on Utah forest land totaled about 253 million cubic feet while mortality reduced 

gross growth by about 175 million cubic feet for a net growth of about 78 million cubic feet (Appendix E, table 21, 23). Figure 7 shows a comparison of gross growth and 

mortality by species. Aspen has the highest gross growth with almost 20 percent of the 

total, followed by subalpine fir with 12 percent, Douglas-fir with 11 percent, lodgepole 

pine and Engelmann spruce with 10 percent each, and Utah juniper with 9 percent. 

Engelmann spruce has the highest mortality at 23 percent of the total, followed by subalpine fir at 20 percent, common pinyon and Douglas-fir at 10 percent each, and white 

fir and aspen at 8 percent each. Engelmann spruce at 15.1 million cubic feet, followed 

by subalpine fir at 3.9 million, and white fir at 0.4 million, are the only species with 

negative net growth (gross growth minus mortality). Spruce mortality is discussed in 

more detail in Section V “Current Issues.” Aspen by far has the highest net growth at 

35.3 million cubic feet, which is 46 percent of Utah’s total net growth on forest land.

Mortality events are usually infrequent and localized and thus often difficult to 

accurately detect; however, annual inventories can provide unique opportunities to assess yearly trends in mortality, especially during medium to large scale events like the 

drought-related pinyon-juniper die off of the early 2000’s (Shaw 2006; Shaw and others 

2005). Also see Section V for further discussions of pinyon-juniper and spruce mortality. 

Figure 8 shows the average annual mortality by measurement year and cause of death. 

Utah’s peak mortality occurred in 2003 at 28 percent of total mortality, followed by 26 

percent in 2005, and was at its lowest in 2000 at 8 percent. Insects were the greatest 

cause of tree mortality at 42 percent of total mortality, followed by fire at 25 percent, 

and disease at 16 percent.

The average annual net growth and mortality of growing-stock trees on nonreserved 

productive timberland in Utah is 47.2 and 108.9 million cubic feet, respectively (Appendix E, table 24, 28). Although only 25 percent of Utah’s forest land is productive 

timberland, it contains 61 percent of the State’s annual net growth and 62 percent of 

the annual mortality.

Discussion—Is aspen declining in Utah (Bartos and Campbell 1998; O’Brien 1999)? 

Current annual inventory comparisons of aspen area and volume to the 1993 report 

suggest not, although the distribution of volume and numbers of aspen trees appears 

to be moving from fewer small-diameter to more large-diameter trees. In addition, net 

growth for aspen in 1992 was 31.7 million cubic feet, compared to 35.3 million cubic 

feet from the annual inventory, which had positive net growth for all diameter classes 

(see Section V for further discussions of aspen decline). As in 1992, insects continue 

to be the greatest cause of death for all species combined, and subalpine fir is the only 

species with negative growth in both inventories.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 23 Figure 7—Gross growth (253 million cubic feet) and mortality of live trees 5.0 inches diameter and greater by species on forest land, Utah, cycle 2, 2000-2005. 0 10 20 30 40 50 60 Other Limber pine Curlleaf mountain-mahogany Rocky Mountain juniper Bigtooth maple Singleleaf pinyon Gambel oak Ponderosa pine White fir Common or twoneedle pinyon Utah juniper Engelmann spruce Lodgepole pine Douglas-fir Subalpine fir Aspen Million cubic feet

Species gross growth mortality

0 10 20 30 40 50 60

Other

Limber pine

Curlleaf mountain-mahogany

Rocky Mountain juniper

Bigtooth maple

Singleleaf pinyon

Gambel oak

Ponderosa pine

White fir

Common or twoneedle pinyon

Utah juniper

Engelmann spruce

Lodgepole pine

Douglas-fir

Subalpine fir

Aspen

Million cubic feet

Species gross growth mortality
24 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 8—Average annual mortality of live trees by cause of death and year (subcycle), Utah, cycle 2, 2000-2005.

Stand Density Index (SDI)

Background—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 United States, silviculturists often use SDI as one measure 

of stand structure to meet diverse objectives such as ecological restoration and wildlife 

habitat (e.g., Lilieholm and others 1994; Long and Shaw 2005; Smith and Long 1987).

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 

10

5

0

15

20

25

30

2000 2001 2002 2003 2004 2005

Cubic feet

Millions

Year

Insects

Fire

Disease

Unknown/other

Weather

Insects

Fire

Disease

Unknown/other

Weather
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 25

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 uneven-aged 

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 

preparation). The provisional revised maximum SDIs, which are compatible with FIA 

computation methods, are shown in table 6. 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.

Inventory Results—The distribution of SDI values in Utah is relatively balanced. 

Figure 9 shows that stands appear to be well-stocked, with over 51 percent of forest 

acres at least fully occupied (SDI equal to 35 percent or greater). This distribution is 

unexpected considering that many forest acres were affected by insects and fire during 

the period covered by this inventory.

Discussion—There was considerable drought-related mortality of common pinyon 

starting in 2003, although Utah forests were generally less affected than those in other 

southwestern States (Shaw and others 2005). In some parts of Utah, Engelmann spruce 

and aspen were affected by drought and insects as well (see Section V on aspen, spruce, 

and pinyon mortality). With time, low-density stands should increase in relative density 

due to growth of the surviving trees. Whether or not there will be additional in-filling 

by regeneration will depend on a number of factors, including the timing of seed crops 

and favorable climatic conditions. These trends should be captured by future plot 

measurements.

Table 6--Maximum SDI by forest type, Utah, cycle 2, 2001-2005.

Forest Type Maximum SDI

182 Rocky Mountain juniper 425

184 Juniper woodland 385

185 Pinyon-juniper woodland 370

201 Douglas-fir 485

221 Ponderosa pine 375

261 White fir 500

265 Engelmann spruce 500

266 Engelmann spruce-subalpine fir 485

268 Subalpine fir 470

269 Blue spruce 500

281 Lodgepole pine 530

365 Foxtail pine-bristlecone pine 470

366 Limber pine 410

703 Cottonwood 360

901 Aspen 490

925 Deciduous oak woodland 475

953 Cercocarpus woodland 415

954 Intermountain maple woodland 540

999 Unknown / nonstocked 475
26 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Quality Assurance Analysis

Background—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 MQOs, 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 2001 and 2005 and then compared for 

measurement precision between two independent FIA crews’ observations. Therefore, 

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

Inventory Results—The results of the QA analysis for this reporting period are presented in tables 7 and 8. Table 7 describes tolerances for condition-level variables, and 

table 8 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 fall 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.

Figure 9—Distribution of stand density on Utah forest land, cycle 2, 2000-2005.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 27

Table 7--

Q

A results for condition-level variables from 84 conditions in Utah, cycle 1, 2001-2005.

Number of times 

National core variables

Tolerance @1x @2x @3x @4x @1x @2x @3x @4x Records

Condition status No tolerance 96.4% 3 84Reserve status No tolerance 97.6% 2 84Owner group No tolerance 94.0% 5 84Forest type (

Type) No tolerance 89.6% 7 67

Forest type (Group) No toleranceStand size No tolerance 88.1% 8 67Regeneration status No tolerance 98.5% 1 67Tree density No tolerance 100.0% 0 67

Condition nonsampled reason No toleranceOwner class No tolerance 92.9% 6 84Owner status No tolerance 87.5% 1 8

Regeneration species No toleranceStand age ±10 % 95.5% 95.5% 95.5% 95.5% 3 3 3 3 67Disturbance 1 No tolerance 83.6% 11 67Disturbance year 1 ±1 yr 83.3% 100.0% 1 0 6Disturbance 2 No tolerance 92.3% 1 13Disturbance year 2 ±1 yrDisturbance 3 No tolerance 100.0% 0 1

Disturbance year 3 ±1 yrTreatment 1 No tolerance 100.0% 0 67

Treatment year 1 ±1 yrTreatment 2 No tolerance

Treatment year 2 ±1 yrTreatment 3 No tolerance

Treatment year 3 ±1 yrPhysiographic class No tolerance 67.2% 22 67

Present nonforest use No tolerance

Regional variables

Percent crown cover ±10 % 91.0% 97.0% 100.0% 6 2 0 67

Percent bare ground ±10 . 82.1% 94.0% 98.5% 98.5% 12 4 1 1 67Habitat type 1 No tolerance 65.7% 23 67Habitat type 2 No tolerance 56.7% 29 67Condition class number No tolerance 100.0% 0 84

Percentage of data within tolerance data exceeded tolerance 
28 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Table 8--QA results for tree variables from 1,301 trees in Utah, cycle 1, 2001-2005. National core variables Tolerance @1x @2x @3x @4x @1x @2x @3x @4x Records DBH ±0.1 /20 in. 90.6% 96.3% 98.0% 98.0% 38 15 8 8 406 DRC ±0.1 /20 in. 66.4% 79.2% 85.0% 88.8% 301 186 134 100 895 Azimuth ±10 o 97.5% 98.8% 98.9% 99.1% 32 16 14 12 1301 Horizontal distance ±0.2 /1.0 ft 75.2% 89.0% 94.3% 96.4% 322 143 74 47 1301 Species No tolerance 98.8% 15 1301 Tree genus Tree status No Tolerance 99.9% 1 1301 Rotten/Missing cull ±10 % 92.2% 96.4% 98.0% 98.9% 83 39 21 12 1069 Total length ±10 % 79.1% 93.9% 98.1% 99.0% 223 65 20 11 1069 Actual length ±10 % 55.8% 76.7% 86.0% 90.7% 19 10 6 4 43 Compacted crown ratio ±10 % 69.2% 91.8% 97.7% 99.2% 350 93 26 9 1135 Uncompacted crown ratio (P3) ±10 % 96.7% 98.8% 99.3% 99.8% 31 11 7 2 946 Crown class No tolerance 81.0% 216 1135 Decay class ±1 class 90.9% 96.4% 100.0% 15 6 0 165 Cause of death No tolerance 73.1% 18 67 Mortality year ±1 yr 97.0% 100.0% 2 0 67 Condition class No tolerance 100.0% 0 1301 New tree Regional variables Mistletoe ±1 class 99.5% 99.7% 99.7% 99.9% 6 3 3 1 1135 Number of stems No tolerance 88.5% 103 895 Percent missing top ±10 % 98.8% 99.0% 99.2% 99.4% 13 11 9 6 1069 Sound dead ±10 % 81.2% 88.4% 91.5% 93.4% 201 124 91 71 1069 Form defect ±10 % 64.3% 77.0% 85.0% 91.0% 107 69 45 27 300 Current tree class No tolerance 98.4% 21 1301 Radial growth ±1 /20 inch 61.2% 74.7% 85.3% 89.8% 95 62 36 25 245 Breast height tree age ±10 % 70.1% 85.1% 94.3% 98.9% 26 13 5 1 87 Root collar tree age ±10 % 39.9% 69.9% 80.4% 85.6% 92 46 30 22 153 Seed/Sap timberland tree age ±10 % 33.3% 58.3% 75.0% 83.3% 8 5 3 2 12 DRC using IW MQO ±0.2 in/stem 80.7% 90.2% 93.3% 94.5% 173 88 60 49 895 DRC single stem ±0.2 in/stem 85.7% 92.9% 95.4% 95.9% 83 41 27 24 581 DRC multi stem ±0.2 in/stem 71.3% 85.0% 89.5% 92.0% 90 47 33 25 314 Horiz dist-timberland ±0.2 /1.0 ft 96.3% 99.3% 99.5% 99.8% 15 3 2 1 406 Horiz dist-woodland ±0.2 /1.0 ft 65.7% 84.4% 92.0% 94.9% 307 140 72 46 895 Total length: saplings ±10 % 72.8% 93.1% 97.4% 98.7% 63 16 6 3 232 Actual length: saplings ±10 % 100.0% 0 1 Percentage of data within tolerance Number of times data exceeded tolerance
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 29

For example, table 8 shows that there were 406 paired records for the variable “d.b.h.” 

(diameter at breast height). At the 1X tolerance level, almost 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. MQOs for each 

variable consist of two parts: a compliance standard and a measurement tolerance, and can 

be compared to the observed compliance rate to determine that variables performance.

Discussion—The information in tables 7 and 8 shows variables with varying degrees 

of repeatability. For example, one condition-level regional variable that appears fairly 

repeatable is “percent crown cover.” At the 1X tolerance level, its observed compliance rate was 91 percent for 67 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 66 percent for the same observations. Habitat types 

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 type.

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

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

rate of 70 percent. This is probably due to the difficulty of obtaining accurate tree ages. 

Several factors that might affect inconsistent tree ages are (1) tree too large to reach the 

center, (2) rings too close or faded to read accurately, (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’s 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.

In 2010, Interior West FIA will begin re-measurement of the first panel of annual 

plots in Utah. Given the typical slow-growing nature of woodland trees, the difficulty 

in marking qualifying stems for future d.r.c. measurements, and the general inferior 

repeatability of d.r.c. compared to d.b.h. and single-stemmed d.r.c.s compared to multistemmed d.r.c.’s (table 8); it’s been questioned whether re-measurement of d.r.c.s is the 

best approach for assessing growth on woodland trees. QA data may play a key role in 

helping answer these kinds of questions.
30 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 31

V. Current Issues

As FIA responds to the requests and concerns of its users and clients, questions are 

often asked about bringing FIA data to bear upon many issues. FIA’s unbiased, systematic 

sampling approach and the broad-scale strategic nature of FIA data provides a unique 

and appropriate framework for initial investigations.Discussions of the following current 

issues and potential associated FIA indicators (Section VI) serve as a setup for further 

in-depth analyses at national, regional, State, or sub-State scales. Sources of data for 

the following issues sections are from 2000 through 2005.

Other Wooded Land

Background—Other wooded land, an important ecotone between forest and nonforest land, is defined in Appendix A as land with low tree crown cover densities of 5 to 9 

percent, or 40 to 199 seedlings per acre. In Utah, other wooded land is most commonly 

the arid, low elevation pinyon-juniper and juniper forest types that are typical of the 

southwestern United States. The relatively recent expansion of pinyon-juniper and 

juniper types into sagebrush and other vegetation types since Euro-American settlement of the West has been widely documented (see “Expansion of Pinyon and Juniper 

Woodlands” in this section for more details). This has been attributed to many factors, 

such as livestock grazing, climatic shifts, reduced fire frequency, and increases in 

atmospheric carbon dioxide (Miller and Wigand 1994; Weisberg and others 2007). What 

is less well documented and not fully understood is the diversity of historical conditions 

and ecological processes that have shaped the distribution of pinyon and juniper in the 

distant past (Romme and others 2007). This makes it difficult for land managers and 

policy-makers to compare current to “historical” conditions.

The dynamics of pinyon and juniper expansion and contraction are often associated 

with forest/nonforest boundaries. Therefore, monitoring other wooded land may prove 

particularly useful for assessments of future trends and historical context related to 

fluctuations in pinyon and juniper types. By definition, other wooded land plots occur 

in low cover situations and need to be checked in the field to determine whether they 

meet the definition of forest land. Because they have low cover, the cost of field data 

collection is small compared to the cost of accessing the plot. In addition, although 

somewhat insignificant in terms of area, considering other wooded land as simply forest or nonforest ignores its ecotonal value, and potentially eliminates an important land 

classification.

Inventory Results—About 3 percent (1.6 million acres) (table 2) of Utah’s total 

area meets the definition of other wooded land, which consists mostly of juniper woodland forest type (34 percent), followed by pinyon-juniper woodland (32 percent), and 

nonstocked land (29 percent). Stocking, an expression of the extent to which growing 

space is effectively utilized by live trees, is a calculated variable based on the subplot 

and microplot tree tally. Nonstocked stands are commonly disturbed lands that have not 

yet regenerated. In addition, naturally sparse stands often get classified as nonstocked. 

Stockability is 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 (Pfister and others 

1977; Steele and others 1983).

Prior to the implementation of mapped-design inventories, woodland forest types were 

assigned in the field and were not calculated using stocking. Beginning with mappeddesign, IWFIA calculated all forest types and used stockability factors based on habitat 
32 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

types to adjust stocking to “normal” for some low-yield timber and woodland types. 

Figure 10 is a comparison of area of stocked versus nonstocked other wooded land using two stocking calculation methods: one with stockability factors (annual inventory 

method) and one without (periodic inventory method). This shows that over 71 percent 

of all other wooded land is stocked using stockability factors, and 54 percent is stocked 

when not using stockability factors. Since stocking often connotes some management 

objective, and other wooded land denotes naturally sparse cover, it’s probably unrealistic to assume that large portions of these lands need regeneration. This is somewhat 

embodied by the fact that only 5 percent of other wooded lands have been classified as 

recently disturbed or chained using FIA’s disturbance variable.

The lack of sample trees on other wooded land often results in plots being classified as nonstocked. Figure 11 displays percent of “field-recorded” stand-size class by 

“calculated” stand-size class, which demonstrates that only 10 percent of the calculated 

nonstocked stand-size class is considered nonstocked by field crews on the ground. 

Also, 81 percent of the calculated nonstocked other wooded land had a “field-recorded” 

forest type of pinyon-juniper woodland or juniper woodland; the remaining 19 percent 

consisted of small amounts of various timber and woodland types (fig. 12).

As discussed in Section IV, elevation is a major factor in the spatial distribution of 

forest, other wooded, and nonforest land in Utah (fig. 2). The juxtaposition of other 

wooded land in relation to nonforest and forest land is displayed in figure 13. This shows 

the area distribution within each land type by 1,000-ft elevation classes. Other wooded 

land in Utah, of which 48 percent occurs at the 5,000-ft to 6,000-ft elevation class, is 

sandwiched between predominantly nonforest land at 4,000 ft to 5,000 ft and forest land 

occurring mostly at 6,000 ft and above. If climate changes occur, this elevation zone 

Figure 10—Acres of other wooded land by stocking class, inventory method, and stockability factor, Utah, cycle 2, 2000-

2005.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 33 Figure 11—Percent area distribution of four “field” stand-size classes within the same four “calculated” stand-size classes for other wooded land, Utah, cycle 2, 2000-2005. 0%90% 80% 70% 60% 50% 40% 30% 20% 10% 100% Nonstocked Small (< 5 inches) Medium (>= 5 and < 9 or 11 inches) Large (>= 9 or 11 inches)

cent area reP

Calculated stand-size class 

Large (>= 9 or 11 inches)Medium (>= 5 and < 9 or 11 inches)Large (>= 9 or Small (< 5 inches)Nonstocked

11 inches)

Medium (>= 5 and < 9 or 11 inches)Small (< 5 inches)Nonstocked
34 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Figure 12—Acres of other wooded land by field forest type where calculated forest type is nonstocked, Utah, cycle 2, 2000-2005. 0 50,000 250,000 200,000 150,000 100,000

Juniper woodland

Pinyon-juniper woodland

Limber pine

Ponderosa pine

Douglas-fir

Cottonwood

Engelmann spruce-subalpine fir

Cercocarpus woodland

Deciduous oak woodland

Acres 

Field forest type 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 35

Figure 13—Percent of land area within each land type by 1,000-foot elevation class, Utah, cycle 2, 2000-2005.

33%

48%

46%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2,000–

3,000

3,000–

4,000

4,000–

5,000

5,000–

6,000

6,000–

7,000

7,000–

8,000

8,000–

9,000

9,000–

10,000

10,000–

11,000

11,000–

12,000

12,000–

13,000

P

ercent land area 

1000' elevation class 

Nonforest

Other wooded

Forest land

could become a key area for future land type changes.

Three factors that influence FIA’s forest and other wooded land definitions are currently 

described in the field by measuring three condition-level field variables as surrogates 

(see “Plot-filtering and the definition of forest and other wooded lands” in AppendixA). 

Any combination of these variables can be used to demonstrate why plots were called 

forest land or other wooded land. Nonforest plots that are not field visited are also 

similarly evaluated with remotely sensed imagery for land use and cover. Potentially, 

users could apply various thresholds of cover, disturbance, or regeneration on these land 

types to test the effects of changing definitions, from the densest of forest land to the 

most sparsely treed of other wooded and nonforest land. It should be noted that cover 
36 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

estimates greater than approximately 20 percent using these variables are probably not 

as accurate. Figure 14 shows the area of other wooded land by cover (live), disturbance 

(live plus missing cover), and regeneration (seedlings per acre). Based on these variables, 

over 69 percent of other wooded land meets the definition due to live cover alone, almost 

23 percent due to a combination of live cover and regeneration, about 3 percent due to 

regeneration alone, about 4 percent due to some level of past disturbance, and about 

1 percent due to a combination of past disturbance and regeneration.

Discussion—Generally, forest type is calculated from trees sampled on the subplots. 

Due to the sparse nature of other wooded land, some condition-defining attributes like 

forest type and stand-size class are best described on the sample acre, rather than calculated from the tree tally. Field forest type and field stand-size class are assessed at 

the condition-level and account for anomalies between the tree tally and observations 

on the sample acre. Field crew assessments also take into account the effects of disturbance and regeneration. Since field forest type and stand-size class consider both past 

(disturbance) and present (regeneration) influences, perhaps these variables would be 

more useful for monitoring the expansion and contraction of other wooded lands over 

time, rather than a calculated forest type based on tally-tree stocking.

Other wooded land usually occurs on the edge between forest and nonforest, and has 

a narrow ecological niche but plays an important role in land type dynamics. Monitoring 

other wooded land should prove particularly useful for assessments of future trends and 

historical context related to fluctuations in forest area, particularly in pinyon and juniper 

types. Perhaps the best way to monitor these marginal lands accurately is by measures of 

cover. This requires a classification system that is efficient, accurate, standardized, and 

easily implemented on the ground. Cover-based definitions of other wooded land has 

Figure 14—Area of other wooded land by live cover, disturbance, and regeneration, Utah, cycle 2, 2000-2005.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 37

several advantages over stocking-based definitions: (1) direct measurement of complete 

tree crown cover is quick and accurate at low cover levels; (2) assessments of stocking 

on the subplot or sample acre are often cumbersome, for example, recording many stem 

measurements on woodland trees; (3) cover-based definitions are recognized internationally, while stocking-based definitions are mostly inherent to FIA; and (4) cover-based 

definitions are more directly related to remotely sensed imagery.

Aspen Mortality

Background—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 smaller-scale disturbances.

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, decreased 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 had 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 low-elevation stands (Worrall and others 2008), and 

in some of these 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. Kay (1997) and Bartos and Campbell (1998) 

suggested that similar changes had occurred in Utah. All of 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 nearlypure stands. This assumption may not be reasonable because there are many situations 

where aspen may persist normally as a minor stand component.

Assessing changes in the aspen forests of Utah over time is possible because a 

periodic inventory of Utah was conducted by FIA in 1993 (O’Brien 1999). Although 

changes in methodology limit the ability to compare some aspects of the 1990s inventory with current data, many characteristics of aspen forests are possible to compare at 

the population scale.

Inventory Results—Current inventory data show that there are just over 1.64 million acres (table 2) of the aspen forest type in Utah, as compared to nearly 1.43 million 

acres found during the previous inventory in 1993 (O’Brien 1999). When considering 

all forest land where at least one live aspen 1.0-inches diameter or greater was sampled, 

the current inventory data shows just over 2.66 million acres, while the previous inven-
38 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

tory showed live aspen present on just over 2.57 million acres.

Statistics on live trees may overlook “relict” aspen stands, and both inventories show 

that some stands had only standing dead aspen present at the time of inventory. The 1993 

periodic inventory showed that only standing dead aspen 1.0 inch diameter and greater 

were found on approximately 42 thousand acres, or about 1.7 percent of all acres with 

aspen present. The current inventory shows an apparent increase to nearly 132 thousand 

acres, or about 5.0 percent of all acres with aspen present.

The 1993 periodic inventory showed just over 925 million live aspen with diameter 

1.0 inches and greater, while the current estimate is over 733 million trees. Although 

the total number of trees has apparently decreased, the net volume found in trees 5.0 

inches diameter and greater has increased. The 1993 inventory found over 1.74 billion 

cubic feet of volume in live aspen 5.0 inches diameter and greater, giving an average 

volume per tree of nearly 5.2 cubic feet. The estimate of volume from the current data 

is over 1.95 billion cubic feet, or over 6.9 cubic feet per tree.

Gross volume growth of aspen at the time of the 1993 inventory was estimated to 

be over 49.5 million cubic feet per year, with annual mortality estimated to be nearly 

17.9 million cubic feet; this resulted in net annual growth of nearly 31.7 million cubic 

feet. The gross volume growth estimate from current inventory data is very close to the 

1993 estimate—49.6 million cubic feet per year—but annual mortality is somewhat 

lower at slightly more than 14.3 million cubic feet. As a result, current inventory data 

indicate somewhat higher net annual growth of just over 35.3 million cubic feet. When 

net growth is expressed as a percentage of live volume, the results of both inventories 

are the same—net growth is 1.8 percent of live volume.

Discussion—Comparisons between the 1993 periodic inventory results (O’Brien 

1999) and the current data suggest that there has not been a detectable decline in the 

acreage of the aspen forest type or in the total number of acres with live aspen present. 

The estimates of acres having only standing dead aspen present appear to show that 

there has been a small increase in the area where there has been complete mortality of 

the aspen component, although the presence of seedling-sized aspen on many of these 

acres suggests that aspen is reproducing on most of them. Because the lack of successful reproduction in some aspen stands is an issue of concern, this situation warrants 

continued monitoring.

Comparisons of standing live volume, growth, and mortality likewise do not indicate any negative trends in the aspen resource. Although there are currently fewer trees 

than there were in 1993, the total standing volume is greater and, as a result, the mean 

volume per tree is greater. This is consistent with what would be expected from an aging population of trees. Aspen have a relatively short life expectancy as compared with 

many other tree species, so with a mean stand age of approximately 85 years, and a 

large proportion of stands in the 80- to 100-year age class (fig. 15), it is clearly an aging 

population. Because the rate of disturbance is relatively low, resulting in few regenerating stands, the existing trees are getting larger and fewer. However, the population 

is relatively stable in the sense that it is able to maintain, and even increase, its live 

volume over time. Even though some areas have suffered substantial mortality related 

to drought, the quantity of drought-affected acres has not been high enough to make a 

large change in population-scale trends.

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 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 39

obvious to a wide range of observers, there is a tendency to extrapolate local conditions 

to larger areas. However, the current FIA inventory data show that in recent years aspen 

has both gained and lost dominance at the stand level (fig. 16), resulting in little net 

change for the species by most measures. This suggests that factors other than succession 

and drought-related mortality are affecting the aspen resource; fire affects all species 

and forest insects have had substantial impacts on conifer species. These widespread 

changes will be followed as monitoring of FIA plots continues.

Expansion of Pinyon and Juniper Woodlands

Background—The pinyon-juniper forest type group in Utah consists of three forest 

types: pinyon-juniper woodland, juniper woodland, and Rocky Mountain juniper. It is 

by far the most common group in Utah, covering 10.2 million acres, or 57 percent of the 

forest land (Appendix E, tables 3-7). The pinyon-juniper group also dominates Utah’s 

other wooded lands, covering over one million acres, or 68 percent of the other wooded 

land (“Area” in Section IV; table 2). In addition, 78 percent of the nonstocked area, 

Figure 15—Stand age class distributions for (A) all stands in the Interior 

West with an aspen component, and (B) pure aspen stands (95 percent 

or more aspen by basal area), cycle 2, 2000-2005. Mean age of all 

stands with aspen is 84.8 years (stdev. 42.3) and mean age of pure 

aspen stands is 64.6 years (stdev. 35.9 years).
40 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 16—Map of annual FIA plots in Utah with aspen present, showing change in the aspen component based on recent 

mortality, cycle 2, 2000-2005. Red symbols represent plots where aspen has decreased in dominance, green represents plots 

where aspen has increased, and yellow indicates no change.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 41

both forest and other wooded lands, were identified by field crews as formerly and/or 

potentially stocked by pinyon-juniper group forest types. In total, over 12 million acres 

are either now, were recently, or will soon be pinyon-juniper forest type group, or 62 

percent of the forest and other wooded land combined. The dominant species are Utah 

juniper, Rocky Mountain juniper, common or two-needle pinyon, and singleleaf pinyon.

There has been concern that, since Euro-American settlement of the West, pinyons and 

junipers have been expanding their ranges dramatically, encroaching on and degrading 

grasslands and shrublands. This expansion has been well documented in many parts of 

the pinyon-juniper range (Burkhardt and Tisdale 1976; Tausch and Hood 2007). Generally, expansion has been attributed to direct or indirect alterations of pre-settlement 

fire regimes. These fire regimes are theorized to be of three general types (Baker and 

Shinneman 2004; Romme and others 2009):

1. Low intensity, frequent fires that tend to “thin from below.” These would 

occur in pinyon-juniper stands where the understory is dominated by grasses and 

forbs, and the tree density should be comparatively low. This type is most common in the extreme southwestern United States and northern Mexico. It should 

be rare to non-existent in Utah.

2. Less frequent, high intensity stand replacing fires. This regime occurs in 

pinyon-juniper stands where the understory is dominated by shrubs, notably 

sagebrush. This type is common in the Great Basin, and would be expected in 

parts of Utah.

3. Very rare, mostly localized fires that occur under only the most extreme 

conditions, and that may only burn small areas. These are pinyon-juniper 

stands with rocky substrates or cryptobiotic crusts, that support little, if any, 

understory. The topography is often rugged with features such as cliffs and bare 

bedrock, which prevent or inhibit the spread of fires. This type is documented 

on the Colorado Plateau (Romme and others 2003), so it would be expected in 

southeastern Utah.

Inventory data were used to evaluate the age, structure, and potential status of pinyonjuniper stands. The age chosen to represent pre-settlement stands was 150 years. The first 

estimate was stand age, but since this is based on the age of the trees in the dominant 

size class rather than the oldest trees in the stand, the maximum ages were also evaluated, along with the proportion of trees over 150 years old. Since tree and stand ages 

are determined from a few live trees on a plot, the presence of very large dead trees 

(14.5 inches diameter) and dead basal branches (12.4 inches diameter) were evaluated 

as evidence that the stand was in existence at least 150 years ago. More recently disturbed stands with few or no live trees were classified as disturbed. Understory cover 

and layering, along with tree cover were evaluated to characterize fire regimes (Scott 

and Burgan 2005) and estimate fine fuel loading (Caratti 2006).

Inventory Results—About 2.4 percent of the pinyon and juniper dominated land 

in Utah has been recently disturbed. Of the remaining, about 62 percent (7.3 million 

acres) was classified as older than 150 years. The remaining 38 percent (4.4 million 

acres) was characterized as having established within the last 150 years. The younger 

stands tended to be more prevalent in the northern and western parts of the State, while 

the older stands occurred more frequently in the southeastern part of the State (fig. 17).

In terms of fire regime and fuel loading, a larger proportion of the older stands were 

found to have very low fuel loadings, indicating a low probability of severe fire. Sixty-one 

percent of older stands had very low fuel loadings, while 45 percent of younger stands 

did. A higher percentage of younger stands had understories dominated by shrubs or 

shrub-grass mixtures (22 percent) than did older stands (12 percent). Less than 0.5 percent of stands of any age had grass-dominated understories.
42 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 17—Counties with the ten highest proportions of young and old pinyon and/or juniper stands, showing 

percentages over or under 150 years, Utah, cycle 2, 2000-2005. Note: Physiographic boundary of the Great Basin is 

slightly different than the hydrologic boundary.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 43

Discussion—Ten Utah counties with the highest proportions of pinyon and juniper 

dominated stands older than 150 years (fig. 17) are all in the area of the Colorado Plateau 

in the southeastern part of the State. This distribution, combined with the finding that 

a greater proportion of older stands than younger stands have very sparse understories, 

supports the expectation that the third fire regime—characterized by very rare, localized fires—is operating in this area. This situation results in most pinyon-juniper stands 

having existed in similar densities, structures, and age classes as they have been found 

for hundreds, if not thousands, of years (Romme and others 2003).

On the other hand, the ten Utah counties with the highest proportions of pinyon 

and juniper dominated stands younger than 150 years are all in the Great Basin in the 

western and northern part of the State (fig. 17). The common occurrence of younger 

stands, along with younger stands having more shrub dominated understories than older 

stands, tends to support the expectation that this part of the State is dominated by the 

second fire regime. In this situation, pinyon and juniper populations are maintained 

by relatively small areas with fire-resistant properties, similar to those in the third fire 

regime (Weisberg and others 2008). When conditions favor tree growth, pinyons and 

junipers expand from these refugia into mostly shrub-dominated areas, where eventually they experience high intensity stand replacing fires that halt tree expansion. If the 

fire frequency is artificially lengthened, trees can increase uninterrupted, displacing 

shrublands. In the Great Basin, this process is well documented (Tausch and Hood 

2007), with many, if not most, pinyon and juniper landscapes younger than the advent 

of European-American settlement (Miller and others 2008). Evidence of high intensity 

fire regimes is also supported by the distribution of disturbed stands: 71 percent of them 

occur in the ten counties with the highest proportions of young stands, especially Juab 

and Millard counties. Some younger pinyon-juniper stands probably represent recovery 

from severe human-caused disturbances, such as early chaining or harvest for charcoal 

to support the mining and railroad industries (Romme and others 2009).

Drought-Related Effects on Pinyon-Juniper Woodlands

Background—Collectively, pinyon-juniper and juniper woodlands make up the most 

common forest type in the American Southwest and covers over 54.4 million acres in 

the western United States (Smith and others 2009), extending well into Mexico. In 

Utah, these types account for approximately 11.3 million acres of forest land and other 

wooded land, or nearly 58 percent of the area with 5 percent or more cover in trees. The 

pinyon-juniper type is defined by the presence of one or more pinyon species—usually 

common or singleleaf pinyon—and one or more juniper species; pure stands of pinyon 

are not considered a separate type by the FIA program. Juniper types are dominated 

by various juniper species, but other species, exclusive of pinions, may be present as a 

minor component. In this section, and to most laypersons and many managers, the term 

pinyon-juniper woodland (or P-J, for short) includes all lands dominated by pinyons, 

junipers, or both. Note that the results for individual years discussed below are based 

on IWFIA’s definition of mortality (see “Growth and Mortality” in Section IV) for the 

panel of plots measured in that year.

The IWFIA program operates in Arizona, Colorado, Idaho, Montana, Nevada, New 

Mexico, Utah, and Wyoming; these States include most of the range of the pinyonjuniper type in the United States. Annual inventory was implemented in Utah in 2000. 

At about that time, forest managers and researchers began to notice an increase in the 

incidence of insects and disease in several forest types, including pinyon-juniper. At 

that time, drought was beginning to move across much of the Southwest, including Utah 

(fig. 18). As the drought progressed, tree mortality appeared to be increasing and there 

was increasing interest in using FIA data to quantify the effects of drought, insects, and 

disease on pinyon-juniper woodlands.
44 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Because the FIA sample is unbiased with respect to plot location and covers a wide 

area and extended time period, it provides a unique view of pinyon-juniper woodlands. 

The systematic sample reduces the likelihood of producing erroneous conclusions that 

may come from surveys conducted only in known areas of mortality. Therefore, this 

drought-related mortality episode provided an opportunity to test the utility of the FIA 

annual inventory system for quantifying rapid change in pinyon-juniper woodlands over 

a large geographic area (Shaw 2006).

Inventory Results—Since 2000 there has been a substantial upward trend in mortality for pinyon species in Utah (fig. 19A). In 2000 and 2001, when mortality was at 

“background” rates and most pinyon mortality was due to fire, annual mortality was 

only about 7 and 17 percent of annual gross growth, respectively. This resulted in a net 

annual increase in volume of just over 0.8 percent. Starting in 2003, annual mortality 

started to exceed gross growth. In 2005, about 8 percent of the pinyon volume that was 

live in 2000 had died from all causes combined, and mortality was over 159 percent of 

gross growth. As a result, there was a net annual decrease of just under 0.6 percent of 

live volume. Although there is currently a negative trend in net growth, for the period 

2000 to 2005 there was still a net increase (0.17 percent) in pinyon volume overall.

Juniper species have shown to be much more resistant to drought-related mortality 

than pinyon species. From 2000 to 2005, the mortality rate of juniper species in Utah 

has been steady to slightly declining over time (fig. 19B). Compared to pinyon species, the annual mortality of juniper species is typically a higher percentage of gross 

growth—about 43 percent on average. Slightly more than 1 percent of juniper species 

volume has been lost to mortality, and net volume growth has been a relatively slow, 

but steady 0.34 percent per year. Most juniper mortality is attributable to fire rather 

than drought, insects and disease. As a result, the mortality of junipers has not shown 

the sharply upward trend that has been seen in pinyon species during the drought years.

Figure 18—Palmer drought severity index (PDSI) for Utah, 1895-2008. Positive values 

indicate relatively moist conditions and negative values indicate drought. Points are average 

for all climate divisions in Utah (National Climatic Data Center 1994) and red line is the 5-year 

moving average.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 45

Figure 19—Mortality trends for (A) pinyon and(B) juniper species in Utah, cycle 2, 2000-2005. Left axis on each panel 

represents annual mortality as a percentage of annual growth on a volume basis. For values greater than 100 percent, mortality 

exceeds growth. The right axis on each panel represents recent mortality as a percentage of live volume.

Discussion—The dramatic visual effect of drought-related mortality of pinyon 

species—dying trees with reddened foliage covering entire landscapes—brought 

much public and media attention to the event. Because there were typically local “hot 

spots” of mortality that were surrounded by large areas of relatively low mortality, it 

was difficult to obtain unbiased, quantitative estimates of the true extent of mortality. 

In some cases, mortality estimates were extrapolated from local sites to entire States. 

For example, one account reported that 90 percent of the pinyon trees in Arizona had 

been killed (Society of American Foresters 2004). However, a preliminary analysis of 

the available data in Arizona, Colorado, and Utah (Shaw and others 2005) showed that 

while there was clearly an upward trend in pinyon mortality, population-level mortality 

was not nearly as high as initially feared. Today it appears that mortality remains above 

the background rate that would be expected for pinyon species during “normal” times, 

but the year-to-year increase in mortality appears to be occurring at a decreasing rate.

One persistent question about the current episode of drought-related mortality is: 

“How does the current episode compare with previous drought-related die-offs?” The 

climatic record shows that similar droughts occurred in the Southwest during the early 

1900s and mid-1950s (National Climatic Data Center 1994). Breshears and others (2005) 

characterized the recent mortality event as response to “global-change-type drought,” 

and suggested that recent conditions have been hotter than in the 1950s. Some of the 

conclusions about the relative magnitude of mortality in the 1950s are based on the lack 

of evidence of widespread mortality in the form of remaining dead woody material from 

the 1950s. However, despite the perceived long-term persistence of woody material in 

the arid Southwest, pinyons may decay or physically break down relatively quickly. 

Although Kearns and others (2005) found that pinyon snags could persist as long as 

25 years, it only took an average of 16.2 years for dead trees to become extremely 

fragmented. Because the impacts of the 1950s drought were not well studied and there 

is a great deal of uncertainty surrounding the possible surviving evidence of pinyon 

mortality, the relative magnitude of the two mortality episodes remains uncertain.

The recent drought has undoubtedly impacted the pinyon-juniper resource in Utah, 

but the magnitude of impact varies widely between the pinyon and juniper components. 

Differential mortality among species on the same site has been shown by Mueller and 

others (2005), who found mortality of common pinyon to be 6.5 times higher than 
46 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

oneseed juniper mortality during two drought events in northern Arizona. Collectively, 

pinyon-juniper woodlands in Utah have maintained positive net growth—about 2.3 percent of live volume–in the face of serious drought conditions. This suggests that as relief 

from drought conditions occurs, as it appears to have done in recent years (fig. 18), the 

live volume may begin to recover at an increasing rate. The dynamics of this forest type 

have important implications for carbon storage, because dead trees have released growing space to the survivors and new regeneration. Although there has been a short-term 

loss in living biomass, there may be a long-term increase in carbon storage while dead 

wood persist and new growth accumulates. It will be possible to determine the actual 

trends as FIA continues to monitor these woodlands into the future.

Spruce Beetle Mortality

Background—Engelmann spruce forests are widespread in Utah, occurring at higher 

elevations. In Utah, most stands with an Engelmann spruce component occur between 

8,000 and 11,200 ft elevation, with a mean of about 9,800 ft. Engelmann spruce forests 

are commonly multi-aged, exhibiting a wide range of tree sizes (Aplet and others 1988). 

Many other species co-occur with spruce; its most common associates are subalpine fir, 

Douglas-fir, aspen, limber pine, whitebark pine, and lodgepole pine. Subalpine fir is 

unique among the associates because it is the only one that is commonly co-dominant 

with spruce—spruce and fir frequently account for large, nearly equal proportions of total 

stand basal area. Both low- and high-severity disturbances influence the structure and 

composition of Engelmann spruce forests (Veblen and others 1994). Windthrow, root and 

butt rots, and endemic spruce beetle (Dendoctronus rufipennis) all act locally to create 

canopy gaps in spruce forests, and contribute to the development of structural diversity. 

In contrast, crown fires, wind storms, and spruce beetle outbreaks, while infrequent, are 

high-severity disturbances that occur at much larger scales. These disturbances have the 

potential to decrease the diversity of classes and structure at stand to landscape scales.

The spruce beetle is a host-specific bark beetle native to Engelmann spruce forests 

across the Intermountain West (Holsten and others 1999). Endemic populations of the 

beetle can build to epidemic (outbreak) levels in recently downed material such as logging slash, wind throw, or avalanche debris (Schmid 1981). Transition from endemic to 

epidemic population levels can be facilitated by warmer-than-average summer temperatures (Hansen and others 2001). It is commonly thought that composition and structure 

of Engelmann spruce-dominated stands influence the potential for spruce beetle activity. For example, a commonly used stand-level spruce beetle risk-rating (Schmid and 

Frye 1976) suggests dense (high basal area), pure (greater than 65 percent Engelmann 

spruce), old (large diameter) stands on well-drained creek bottoms (high site productivity potential) are most likely to be attacked by the spruce beetle. The Schmid and Frye 

(1976) risk-rating, in effect, quantifies the view that compositionally and structurally 

diverse stands have less potential for spruce beetle activity, including the shift from 

endemic to epidemic population-levels.

Beginning in the late 1980s, spruce beetle activity began to increase in several parts of 

Utah. Epidemic population levels were reached in some areas, particularly the Wasatch 

(Dymerski and others 2001) and Markagunt Plateaus, by the late 1990s. For example, 

mortality of overstory spruce was over 90 percent on the Manti-LaSal National Forest 

in just a few years (Dymerski and others 2001) and 95 percent of overstory and understory spruce were killed on the Markagunt Plateau (Dixie National Forest) during the 

late 1990s (DeRose and Long 2007; fig. 20). Some successful beetle suppression was 

conducted on the Wasatch-Cache National Forest (Bentz and Munson 2000), but beetleinduced mortality has gone unchecked in most of Utah for the past 10 years. Although 

the spruce beetle is a natural part of Engelmann spruce forest disturbance, the regionally 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 47

high levels of mortality suggest that the recent outbreaks may be unprecedented in Utah 

(DeRose and Long 2007; Dymerski and others 2001). However, localized surveys and 

studies cannot quantify the statewide impact to the spruce resource. Because surveys 

conducted by FIA are systematic and geographically unbiased, they have the potential 

to quantify changes to the spruce resource over time and space.

Inventory Results—FIA’s periodic statewide inventory of Utah in 1993 (O’Brien 

1999) serves, for the most part, as baseline data since it generally preceded the majority of spruce beetle epidemic. The current, annual inventory began late in the epidemic 

period (2000) and, therefore, captured mostly the post-beetle forest conditions. However, 

because the annual inventory protocol includes trees killed during the 5 years prior to the 

plot visit as “recent” mortality, annual data effectively capture much of the mortality that 

occurred during peak mortality years. Although there have been changes in plot design 

and some definitions between the periodic and annual inventories, we are able to use 

the most comparable figures from both inventories to assess change to the Engelmann 

spruce resource over the past 10 to 15 years.

Figure 20—Comparison of Landsat images from 1991 and 2005 showing expansion of spruce beetle infestation. Reference 

points are (A) Cedar Breaks National Monument, (B) Navajo Lake, and (C) Panguitch Lake. Vegetated areas appear in 

shades of green, with the darkest greens indicating conifer forest. Dark purple-magenta areas, such as north of Navajo Lake 

and south of Panguitch Lake are unvegetated lava flows. Pink-violet areas, such as the area north of Panguitch Lake are low 

vegetation (typically sagebrush). Areas of spruce beetle mortality are those that appear dark green in 1991 and appear pink 

to dark magenta in 2005 (e.g., areas D and E). The shift in color is due to mortality of the overstory and increased exposure of 

understory vegetation or soil.
48 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

O’Brien (1999) reported that there were 452,567 acres of the Engelmann spruce 

forest type and 735,851 acres of the Engelmann spruce-subalpine fir forest type in 

Utah, for a total estimate of 1,188,418 acres. With the implementation of the annual 

inventory, the forest type algorithm was changed such that these two forest types were 

split into three types—Engelmann spruce, Engelmann spruce-subalpine fir, and subalpine fir—with the separations between types dependent on the relative abundance of 

spruce and fir. Under the new forest type classification, annual inventory data show 

491,425 acres of Engelmann spruce, 397,054 acres of subalpine fir, and 172,942 acres 

of Engelmann spruce-subalpine fir, for a total of 1,061,421 acres (table 2). This change 

in area is consistent with the compositional changes that have been documented in 

spruce-dominated stands affected by spruce beetle; many stands shift to dominance of 

subalpine fir (thereby remaining in the Engelmann spruce-subalpine fir type group), 

and others shift to dominance of other common associates (DeRose and Long 2007; 

DeRose and others 2008).

The live volume of Engelmann spruce also appears to have decreased. O’Brien 

(1999) reported approximately 1.711 billion cubic feet of volume in all live Engelmann 

spruce in Utah, while the current estimate is 1.594 billion cubic feet (fig. 5). In the last 

decades of the 20th century, removals and mortality were typically lower than growth, 

so the expectation would have been for total live volume to increase. The loss of live 

volume can be explained by looking at the estimated rates of volume change during each 

inventory period. O’Brien (1999) reported average annual gross growth of Engelmann 

spruce at approximately 26.5 million cubic feet. For the same time period, average annual mortality was estimated to be 12.6 million cubic feet, giving a net annual growth 

of approximately 13.9 million cubic feet. The current estimate of average annual gross 

growth is approximately 24.3 million cubic feet. However, average annual mortality 

is estimated to be 39.4 million cubic feet, over three times the mortality reported in 

the previous inventory. This results in a negative net annual growth of approximately 

15.1 million cubic feet.

Discussion—The widespread mortality observed in Engelmann spruce forests will 

affect stand structure and dynamics for many years to come. In some stands the presence 

of a small residual spruce component, which is commonly made up of trees smaller than 

2.0 inches d.b.h., means that spruce will remain a minor component until the residual 

trees reach reproductive maturity and suitable conditions for reproduction occur. In 

some parts of Utah, spruce reproduction is a rare event, which may further delay spruce 

dominance (DeRose and Long 2007).

DeRose and Long (2007) hypothesized that stands in the areas that experience the 

highest mortality may have been regenerated by a similar mortality event in the past, 

thereby setting up a cycle in which large areas of forest become susceptible to spruce 

beetle at about the same time. However, their investigation revealed that stands that 

recently experienced mortality were regenerated through a series of events that were 

separated in time. As a result, the recent mortality event appears to have created a situation where future spruce forests in Utah may be less structurally diverse than in the 

past. In the near term, though, forest structure and composition may be more diverse 

because stands formerly dominated by spruce will be dominated by one or more spruce 

associates.

Indicators of risk, such as stand composition and structure, and various site attributes 

were found to be marginally useful predictors of spruce beetle activity at the stand 

level (DeRose and others 2008). It is commonly difficult to associate particular stand 

conditions with risks to insect attack, because epidemic populations may build in highrisk stands and later overwhelm stands with conditions that would not ordinarily allow 

populations to expand. This “contagion” phenomenon tends to mask the conditions in 

which population expansion occurred. FIA data showed that mortality occurred across 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 49

the entire range of Engelmann spruce in the Intermountain West, separated by distances 

that rule out a fire-like contagion spread of mortality. This suggests that other factors, 

such as widespread weather and climate patterns, have been as important or more important factors leading to mortality than stand and site attributes. Climate and weather 

are known to affect bark beetle populations (Hansen and others 2001; Logan and Bentz 

1999), so the widespread mortality was likely a result of tree stress induced by heat and 

drought, as well as favorable conditions for the spruce beetle.

One question that commonly occurs after large mortality events is “What will be the 

effect on fire behavior?” Using simulation methods, DeRose and Long (2009) found 

that projected fire behavior in post-outbreak conditions is affected by pre-outbreak 

stand composition and structure and spruce beetle impacts. In stands with lower spruce 

composition, the spruce beetle did not change canopy structure sufficiently to alter the 

potential for crown fire. In stands sites with high spruce composition spruce beetle activity substantially reduced canopy fuel and, therefore, subsequent crowning potential for 

at least several decades. They concluded that extreme fire behavior is not an inevitable 

consequence of spruce beetle outbreaks. Although canopy fuels have been reduced in 

these stands, there has been a considerable increase in the amount of fuel on the forest 

floor. As this fuel load changes over time, FIA will continue to monitor its quantity and 

characteristics.

Although the spruce beetle has made a substantial impact on the Engelmann spruce 

resource in Utah, the vast majority of spruce-dominated stands and stands with a spruce 

component remain relatively unaffected. Whether these stands remain unaffected or 

continue the trend of mortality remains to be seen through continuous inventory. The 

long-term outlook will depend on composition and structure of the remaining stands, 

weather and climate conditions, and spruce beetle population trends.

Old Forest

Background—One goal of managing for ecological sustainability is to maintain 

diverse ecosystems that are composed of both biological and physical components. The 

structure and function of these components are important for ecosystem health, diversity, 

productivity, and resiliency following disturbances. Diversity of forest vegetation both 

in terms of composition and structure is of primary concern. In 1996, the Forest Service 

Intermountain Region assigned a team to establish a process, including criteria and indicators, that would allow identification of areas not currently in a properly functioning 

condition (USDA Forest Service 1996).

Properly functioning conditions were defined as conditions that are “dynamic and 

resilient to perturbations to structure, composition, and processes of their biological 

or physical components.” Structure is a means to express the balance of age and size 

classes related to vegetation types. In order to sustain a forest type in the long term it is 

necessary to define a balance of size/age classes that will ensure adequate recruitment 

of size/age classes over the long term. For some of Utah’s conifer types, a suggested 

approximate range of classes includes 10 percent Grass/Forb; 10 percent Seedling/

Sapling; 20 percent Young Forest; 20 percent Mid Aged Forest; 20 percent Mature 

Forest; and 20 percent Old Forest (Williams 2009). These percentages are estimates 

or approximations and are not presented as absolute values but are suggested general 

proportions. The basis for using these vegetative structural stages is the work of 

Reynolds and others (1992). The relative amount of old forest in particular is often of 

interest to many land managers. Previous studies of old forest in Utah have used a stand 

age of 150 years or greater as a surrogate for mature stand structure (USDA Forest 

Service 2005). For this analysis, tree or stand age of 150 years or greater was used for 

identifying old forests.
50 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Inventory Results—Although this analysis focuses on the timber types of Utah, 

figure 21 displays the total area of forest land in Utah for all timber, woodland, and 

nonstocked forest types by two stand age classes. This shows that woodland types have 

a much higher relative amount (38 percent) of stands 150 years and greater than timber 

types (16 percent). This makes sense since woodland types are comprised of species 

that are generally longer-lived. See “Expansion of Pinyon and Juniper Woodlands” in 

Section V for a similar stand age analysis of pinyon and juniper woodlands.

Figure 22 shows the 4.6 million acres of forest land timber types in Utah by forest 

type. Fifty-one percent (250 thousand acres) of the acreage in the Engelmann spruce 

type are 150 years and greater based on stand age, followed by white fir at 34 percent 

(122 thousand acres), ponderosa pine at 26 percent (99 thousand acres), lodgepole pine 

at 21 percent (82 thousand acres), and aspen at almost none. Although only four plots 

were sampled, the foxtail/bristlecone forest type had the largest percentage (100 percent) 

of 150 year and greater stands based on stand age.

Stand age is generally calculated as the mean age of trees from the stand-size class 

that has the plurality of stocking. This tends to diminish the significance of older trees 

by averaging tree ages of both old and young trees. Another method of using FIA data 

for describing stand structure is by calculating the number of trees per acre that are at 

Acres 

Forest type 

150+

<150

Nonstocked

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Thousands

150+

<150

Nonstocked

Timber types

Woodland types

Nonstocked

Figure 21—Total area of forest land for timber, woodland, and nonstocked forest types by stand age class, Utah, 

cycle 2, 2000-2005.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 51

least 150 years old breast height age, based on sample core trees. Area of old forest by 

forest type using thresholds of 10 trees per acre and 5 trees per acre at least 150 years 

old is shown in figure 23. Compared to an overall figure of 16 percent (719 thousand 

acres) using stand age, 22 percent (1 million acres) of all forest land timber type acreage in Utah would meet the old forest criteria at 10 old trees per acre, and almost 37 

percent at 5 old trees per acre.

Aspen, Douglas-fir, and Engelmann spruce-subalpine fir forest types had the largest percent increases in old forest area at 10 trees per acre; and aspen, Douglas-fir, and 

subalpine fir had the largest percent increases at 5 trees per acre. At the 10 trees per acre 

threshold, the forest land timber types with 20 percent or greater stands in old forest 

structure are foxtail/bristlecone pine at 100 percent, Engelmann spruce at 56 percent, 

white fir at 40 percent, Engelmann spruce-subalpine fir at 34 percent, lodgepole pine 

at 29 percent, and Douglas-fir at 26 percent. The rest of the timber types have less than 

20 percent in old forest. Comparing all three methods for all forest types excluding 

foxtail/bristlecone, the amount of old forest Engelmann spruce forest type was the least 

impacted by the different methods for classifying stand structure.

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Acres Thousands

Forest type 

150+

<150

Engelmann spruce

White r

Ponderosa pine

Lodgepole pine

Douglas-r

Subalpine r

Engelmann spruce-subalpine r

Foxtail pine-bristlecone pine

Aspen

Blue spruce

Cottonwood

Limber pine

Figure 22—Total area of forest land by timber forest types and stand age class, Utah, cycle 2, 2000-2005.
52 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

100,000

50,000

0

150,000

200,000

250,000

300,000

350,000

400,000

Acres 

Forest type 

Stand age 150+

10 trees/acre 150+

5 trees/acre 150+

Engelmann spruce

Douglas-r

Aspen

Ponderosa pine

White r

Subalpine r

Logdepole pine

Engelmann spruce-subalpine r

Foxtail pine-bristlecone pine

Limber pine

Blue spruce

Cottonwood

Figure 23—Area of old forest stand structure by timber forest type and stand age method, Utah, cycle 2, 2000-2005.

Discussion—As discussed in Section IV (“Quality Assurance Analysis”), tree age 

is an important but sometimes difficult variable to collect accurately, although table 8 

showed that breast height age for timber trees is much more repeatable than root collar 

age for woodland trees. Some aspects of this analysis have made the estimates of old 

forest somewhat conservative. First, the ages of trees are not total age, but breast height 

age. Total tree age could be significantly greater in some stands. Second, only a subset 

of trees present on FIA plots are bored for age, so possibly many more trees greater than 

150 years are present on the FIA plots. A more robust analysis could assign tree age to 

non-sampled core trees by species and diameter class, possibly based on the age and 

height of core trees on the plot. This could potentially increase the per acre estimates 

of 150 year old and greater trees.

From an ecological perspective, if stand origin is more important for describing old 

forest structure than average age of trees by stand-size class (stand age), then perhaps 

a variable other than stand age, such as trees per acre by age threshold, would be more 

appropriate. Since the surrogates used to categorize old forest structure can give varying 

results for different forest types, it is important to align size/age structure definitions 

with the methods or variables intended for monitoring them. It is also important that the 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 53

desired measure for monitoring be able to address the full range of size/age structural 

categories included in the definitions so that categories are mutually exclusive and 

cumulative.

Noxious Plants

Background—Noxious plant species can have many negative effects on forest communities: displacing native flora, altering fire regimes, reducing diversity in plant and 

pollinator communities, and generally reducing the diversity and resiliency of forest 

ecosystems. FIA field crews record any instance where a noxious species is found on a 

plot that contains a forested condition. Only those plant species listed by the State of Utah 

as noxious are recorded, which will allow for the spatial and temporal extent of these 

species to be documented as plots are revisited. Although cheatgrass (Bromus tectorum) 

is not listed as noxious in Utah, it is a non-native annual grass that is quickly invading 

many areas of the State. There is considerable interest in the occurrence of cheatgrass 

on Utah’s forests, but since it is not considered noxious by the State, cheatgrass data are 

collected in a different manner and will be discussed in a separate section.

Inventory Results—A total of 2,236 sample conditions were used to assess the 

occurrence of noxious plant species in Utah. These samples represent plots that had 

a forested condition recorded somewhere within the boundaries of the four subplots. 

Eight different noxious species were documented on these forested plots, with one or 

more found on 90 (4.0 percent) of the sampled plots. Canada thistle (Cirsium arvence) 

and Musk thistle (Carduus nutans) were by far the most common species, accounting 

for 78 percent of the noxious plant occurrences (fig. 24).

The elm-ash-cottonwood forest type group had the highest percentage of locations 

infested with at least one noxious species (fig. 25), although this type had a low sample 

size. Conversely, the most frequently sampled forest group, the pinyon-juniper group 

(n = 1349), had a smaller proportion of infested locations (1.8 percent) than any other 

group except the ponderosa pine group (n = 59) in which no noxious species were found. 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

Creeping 

bindweed (1) 

Jointed 

knapweed (2) 

Hairy 

hoarycress (2) 

Purple 

knapweed (4) 

Mexican Dyers 

woad (5) 

Scotch 

thistle (6) 

Musk 

thistle (27) 

Canada thistle 

(43) 

Percentage of all infested plots 

Species 

Figure 24—Distribution (as a percentage of total occurrence) of noxious species. Number of detections of each species in 

parentheses, Utah, cycle 2, 2000-2005.
54 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Figure 25—Distribution of noxious species (as a percentage of total occurrence) by forest type group. Number of sampled conditions for each group in parentheses, Utah, cycle 2, 2000-2005. 30% 25% 20% 15% 10% 5% 0% Elm-ash- cottonwood (11) Other western softwoods (9) Western oak (216) Other western hardwoods (85) Aspen-birch (203) Douglas-fir (91) Fir-spruce- mountain hemlock (169) Lodgepole pine (44) Pinyon-juniper (1349) Ponderosa pine (59) Grand total (2236) 

Percentage of group with weeds present 

Forest type groups 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 55

Stand age appeared to correlate with the frequency of noxious species occurrence, with 

63 percent of the observations located in stands less than 100 years old and 88 percent 

found on stands less than 151 years old (fig. 26). Forty-eight percent of all sampled plots 

were in stands less than 100 years old and 72 percent were in stands less than 150 years 

old. Locations that had more than one condition (more than one forest type or a portion 

of the plot was non-forest) had more than twice the occurrence of noxious species than 

did those locations where only a single forested condition represented the entire plot 

(fig. 27). Twenty-four percent of all sampled plots in Utah had multiple conditions.

Discussion—The paucity of noxious plants found in the pinyon-juniper forest group 

suggests that these forest types are less susceptible to invasion and/or persistence of 

plants designated as noxious. The intense competition of overstory species found in 

these xeric forest types may limit the opportunities for infestation and establishment. 

On the other hand, oak, aspen, and other western hardwood species appear to be most 

susceptible to invasion. This may be due to one or more factors, including soil conditions, 

accessibility to livestock grazing, road and foot traffic, high frequency of both natural 

and man-induced disturbance, and/or which plants have been determined “noxious.”

Plant communities in young forest stands may not be fully established when noxious 

species are introduced to the area. Therefore, conditions may favor introduction and 

establishment in presently unfilled niches in the system. Communities in older and 

undisturbed stands are generally stable and thus more resistant to invasion. 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. However, it 

should be noted that stand-age and condition proportion are correlated (older stands tend 

to be one condition more often than younger stands) so one would expect this trend, 

given the stand-age relationship discussed above.

0.0% 

1.0% 

2.0% 

3.0% 

4.0% 

5.0% 

6.0% 

7.0% 

8.0% 

9.0% 

Percentage of class with weeds present 

Age-class (years) 

0 (151)

1-50 (380)

51-100 (535)

101-150 (541)

151-200 (337)

201-250 (177)

251+ (115)

All age classes (2236)

Figure 26—Distribution of noxious species (as a percentage of total occurrence) by age-class. Number of sampled conditions 

for each group in parentheses, Utah, cycle 2, 2000-2005.
56 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Snags as Wildlife Habitat

Background—Standing dead trees (snags) provide important habitat in forest 

ecosystems. Numerous organisms use snags at some point in their life history. These 

include, but are not limited to bacteria, fungi, insects, rodents, cavity-nesting birds, 

bats, mustelids, and black bear. The height and diameter of standing dead trees largely 

determine the utility of snags as a nesting, roosting, or den sites. 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.

Most species within the guild of cavity-nesting birds found in Utah utilize snags 

that are greater than 9 inches d.b.h. and 34 feet or taller (Harestad and Keisker 1989; 

Lawler 1999; McClelland 1977). Silver-haired bats (Lasionycteris noctivagans) have 

been associated with trees 12 inches or greater d.b.h. and taller than 25 feet (Campbell 

and others 1996). Although black bears (Ursus americanus) do not require snags for 

den sites, pregnant females or those with cubs select them over ground dens where 

they are available. Bears prefer snags 30 inches or greater d.b.h. and taller than 16 feet 

(Kolenosky and Strathearn 1987;, Oli and others 1997). This section describes how FIA 

variables such as d.b.h., actual height, live or dead status, and lean code can be used to 

quantify potential den, nest, and roost sites for black bears, cavity-nesting birds, and 

silver-haired bats. Data are from plots found on forest and other wooded land.

Inventory Results—An estimated 56.5 million snags meet the size preferences of 

most cavity nesting birds found in Utah (fig. 28). An estimated 33.1 million trees have 

the potential t o be suitable roost sites for silver-haired bats (fig. 28), and approximately 

685,000 trees have the potential for black bear den sites (fig. 29).

Engelmann spruce contributes the most potential snags for all three wildlife species 

combined, with aspen and subalpine fir being available in abundance for both bats and 

cavity-nesting birds (figs. 30 and 31). Douglas-fir and lodgepole pine also contribute 

significantly to birds’ and bats’ needs (fig. 30) while ponderosa pine provides the bulk 

of the remaining potential den sites for black bear (fig. 31).

Figure 27—Percentage of single and multi-condition plots with noxious species. Total sample size for each group in 

parentheses, Utah, cycle 2, 2000-2005.

1% 

0% 

2% 

3% 

4% 

5% 

6% 

7% 

8% 

Multiple condition plots (552) Single condition plots (1684) 

Percentage of group with weeds present 

Condition proportion 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 57 8 6 4 2 0 14 12 10 

Number of snags (millions) 

Forest type 

Cavity-nesting birds Silver-haired bat 

Aspen Engelmann spruce-subalpine fir Subalpine fir Engelmann spruceWhite fir Douglas-fir Lodgepole pine Pinyon-juniper woodland Deciduous oak woodland Ponderosa pine Limber pine Cercocarpus woodland Rocky Mountain juniper Intermountain maple woodland Foxtail pine-bristlecone pine Juniper woodland Cottonwood Blue spruce

Figure 28—Number of suitable snags for cavity-nesting birds and silver-haired bats by forest type, Utah, cycle 2, 2000-2005.
58 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Figure 29—Estimated snags potentially suitable as black bear den sites by forest type, Utah, cycle 2, 2000-2005. 0 50,000 300,000 250,000 200,000 150,000 100,000 Pinyon-juniper woodland Deciduous oak woodland Engelmann spruce Ponderosa pine 

Number of snags 

Forest type 

Subalpine fir 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 59 9 8 7 6 5 4 3 2 1 0 110 1 15 14 13 12 

Number of snags (millions) 

Tree species 

Cavity-nesting birds Silver-haired bats 

Subalpine fir Engelmann spruce Aspen Lodgepole pineDouglas-firWhite fir Ponderosa pine Narrowleaf cottonwood Limber pine Common/twoneedle pinyon Singleleaf pinyon Utah juniper Rocky Mountain juniper Great Basin bristlecone pine Gambel oak

Figure 30—Number of snags suitable to cavity-nesting birds and silver-haired bats by tree species, Utah, cycle 2, 2000-2005.

Figure 31—Estimate of snags potentially suitable as black bear den sites by tree species, Utah, cycle 2, 2000-2005.

0 

50,000 

300,000 250,000 200,000 150,000 100,000 

Engelmann spruce Ponderosa pine Limber pine Lodgepole pine Utah juniper Douglas-fir 

Number of snags 

Tree species 
60 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Available snags for cavity-nesting birds are predominantly found in the aspen forest 

type, but several other types contribute potential habitat (fig. 32). These are the same 

forest types that provide the majority of snags preferred by silver-haired bats. However, 

the suite of forest types that have black bear den site potential is much smaller, including 

subalpine fir, pinyon-juniper woodland, ponderosa pine, and deciduous oak woodland.

Discussion—Aspen, Engelmann spruce, and subalpine fir are valuable snag species 

for several forest birds and mammals, even when found in other forest types (mixed 

stands). Depending on where they are located on the landscape, ponderosa pine snags 

can be utilized by black bears. Variables other than snag dimensions and numbers need 

to be considered when predicting suitable wildlife habitat for forest-dwelling species. 

For example, 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 water are important to silver-haired bats and bears. Proximity to hard mast resources (juniper berries 

and acorns in Utah), slope, aspect, presence of a cavity, and the amount and timing of 

snow-pack are important in determining the relative value of trees as den sites for black 

bear. FIA data can address many of these factors and there are current efforts to build 

predictive models for these species in Utah by using IWFIA data collected by our field 

crews. These models can be valuable tools for Federal and State land managers, as over 

90 percent of the suitable snags measured by FIA occur on public lands.

Cheatgrass

Background—Cheatgrass (Bromus tectorum) is a non-native annual grass that has 

invaded and displaced native vegetation throughout the West. Cheatgrass grows and 

produces seed earlier than most native species, thus gaining a competitive advantage 

for the limited resources in the arid environments of Utah and other States. The fine 

fuels created by cheatgrass alter fire frequency in the areas where it is found in abundance. These fuels can perpetuate the spread of the species by creating new areas to 

invade after a fire disturbance. Both public and private land managers are interested in 

understanding the spatial and temporal patterns of cheatgrass and any other information 

that can be used to curb infestation. Cheatgrass is not listed as noxious by the State of 

Utah. However, FIA field crews document it in the understory vegetation procedure if 

it reaches a threshold of 5 percent or greater ground cover. However, only those plots 

with a forested condition present have understory vegetation recorded (USDA Forest 

Service 2000-2005a); therefore, these data do not reflect cheatgrass on non-forested 

portions of plots. This analysis used all plots found on forest and other wooded land.

Inventory Results—Cheatgrass was measured at 5 percent or greater cover on 259 

out of 1,537 conditions (plots or parts of plots) in Utah, or 17 percent of the conditions. 

The pinyon-juniper forest type group had the most instances of cheatgrass at 199, which 

represents 77 percent of the total number of cheatgrass indices sampled in Utah (fig. 33). 

The western oak forest type group had the next highest occurrence with 41 records (16 

percent), followed by other western hardwoods, represented by cercocarpus woodland 

and intermountain maple woodland types, with 17 records (7 percent). There were two 

instances where cheatgrass was located in a non-stocked cottonwood forest type.

Most of the cheatgrass sampled occurs on plots below 7,000 feet elevation (fig. 34). 

When examined as a percentage of plots infested within an elevation group, the 4,001-

5,000-ft elevation class appeared to be most susceptible to infestation, with almost 64 

percent of plots infested (fig. 35).
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 61 5% 0% 35% 30% 25% 20% 15% 10% 

Percentage of suitable snags 

Forest type 

Cavity-nesting birds Silver-haired bat Black bear 

Aspen Engelmann spruce-subalpine fir Subalpine fir Engelmann spruceWhite fir Douglas-fir Lodgepole pine Pinyon-juniper woodland Deciduous oak woodland Ponderosa pine Limber pine Cercocarpus woodland Rocky Mountain maple Intermountain maple woodland Foxtail pine-bristlecone pine Juniper woodland Cottonwood Blue spruce

Figure 32—Distribution (by percentage) of suitable snags by wildlife guild/species and forest type, Utah, cycle 2, 2000-2005.
62 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

0 

50 

100 

150 

200 

250 

Pinyon-juniper Western oak Other western hardwoods Elm-ash-cottonwood 

Number of detections 

Forest type groups 

Figure 33—Number of cheatgrass detections (≥ 5 percent cover on subplot) by forest type group, Utah, cycle 2, 2000-2005.

0 

20 

40 

60 

80 

100 

120 

4001-5000 5001-6000 6001-7000 7001-8000 

Number of cheatgrass detections 

Elevation class (feet above sea level) 

8001+ 

Figure 34—Number of cheatgrass detections by elevation class, Utah, cycle 2, 2000-2005.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 63

Figure 35—Percent of plots infested with cheatgrass by elevation class, Utah, cycle 2, 2000-2005.

Discussion—In contrast to species officially listed as noxious in Utah, cheatgrass 

is not found in abundance in any timber forest type. The vast majority of plots with 

cheatgrass were in the pinyon-juniper forest type group, with the rest in hardwood forest 

type groups. These forest types often occur in areas that have lower soil moisture and 

understory species diversity than higher elevation sites. These may be factors that affect 

an area’s susceptibility to invasion. Other possible factors include the type, level, and 

frequency of disturbance (natural and human-induced) in these areas.

The pattern of cheatgrass across the elevation gradient may be driven by the corresponding moisture gradient. Plots located at higher elevations typically have more soil 

moisture, cooler temperatures, and a shorter growing season. These factors may impede 

the introduction and/or establishment of cheatgrass in these areas.

Cheatgrass presents a threat to western ecosystems and a challenge to those that manage the lands where it has become established. FIA data can be used to identify areas 

infested and/or most susceptible to infestation. This information can also be used to test 

cheatgrass models currently being developed or refine those already being implemented.

10% 

0% 

20% 

30% 

40% 

50% 

60% 

70% 

4001-5000 5001-6000 6001-7000 7001-8000 

Percent of plots infested 

Elevation class (feet above sea level) 

8001+ 
64 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 65

VI. FIA Indicators

As discussed in Section II, the forest monitoring component of the FIA program consists of a three-stage systematic sample of sites across all forested lands of the United 

States. Phase 3 plots, a one-sixteenth subset of Phase 2 sample plots, are measured for 

a broader suite of forest health attributes including tree crown conditions, lichen community composition, understory vegetation, down woody materials, and soil attributes. 

An associated sample scheme exists to detect cases of ozone damage occurring adjacent 

to forest vegetation.

This suite of Phase 3 attributes are often referred to as FIA indicators, although in a 

broader sense FIA indicators could be any national or regional field-collected or derived 

variable used for monitoring purposes. In addition, some of the Phase 3 indicators are 

currently being developed at the Phase 2 intensity, such as down woody materials and 

tree damage. Due to the extensive plot intensity of Phase 3 data, or due to changes in 

data collection procedures, some indicators may have limited information or may only 

include a subset of years of data between 2000 and 2005. The following indicator topics, not discussed in any of the issues sections, are included here as an introduction for 

future Utah reporting, as these indicators undergo further development.

Soils

Background—Soils on the landscape are the product of five interacting soil forming 

factors: 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 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 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 reported by forest type groups. This forest 

type aggregation 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 list of mean soil properties in Utah 

organized by forest type is in Appendix F, tables 1 to 4. Some key soil properties were 

graphed by forest type group in Utah and were placed side by side with regional data 

for comparison.

Inventory Results—With the exception of the western oak type, soil C (carbon) and 

N (nitrogen) percentages generally increase from drier to wetter forest environments 

(fig. 36). Generally, soil moisture increases with elevation and latitude (cooler temperatures) and forest types reflect this climatic gradient. When expressed in as megagrams 

of C or N per hectare of forest area, C stocks also generally increase with elevation 

and latitude (fig. 37), with the exception of western oak and western softwoods. Soil N 

stocks show a more mixed response to climatic gradients in Utah and the Interior West.

Aspen forests store more N in the mineral soil than any other forest type group in 

the Interior West (fig. 37, right side). Aspen forests store significantly more N than 

Engelmann spruce-subalpine fir forests, which often intermingle with aspen. The high 

N levels in aspen forest floor and soils leads to lower C/N ratios than those found in 

forest floor and soils under spruce/fir. Since low C/N is a good indicator of relative 

organic matter decomposition rate, nutrient-rich aspen leaves decompose quickly and 

easily compared to conifer needles.
66 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

2000-04 Utah FIA FHM Plots

Organic C, %

1

10

100

Forest floor

0-20 cm soil cores

Total N, %

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Forest type

Western hardwoods

Pinyon/Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Aspen

Spruce/Fir

C/N

0

10

20

30

40

50

60

2000-05 Interior West FIA FHM Plots

Organic C, %

0.1

1

10

100

Forest floor

0-20 cm soil cores

Total N, %

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Forest type

Western hardwoods

Western oaks

Pinyon-Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Cottonwood/aspen/birch

Hemlock/redcedar/larch

Spruce/fir

Western softwoods

C/N

0

10

20

30

40

50

60

Figure 36—Forest floor and 0-20 cm mineral soil percent C, percent N, and C/N arranged by forest type 

groups in Utah (left side) and in five Interior West States (Arizona, Colorado, Idaho, Montana, and Utah) 

(right side). The forest type groups are arranged left to right in order of increasing latitude, elevation, and 

precipitation with some overlap among forest types. The other western hardwoods group in Utah includes 

Cercocarpus woodland and deciduous oak woodland. For the Interior West as a whole, the western oak 

group (deciduous and evergreen oak woodlands) was separated from the other western hardwoods 

(mesquite and Cercocarpus woodlands). The pinyon-juniper group in Utah includes Rocky Mountain juniper, 

juniper woodland, and pinyon-juniper woodland. For the Interior West, this group also includes western 

juniper. The spruce-fir group in Utah includes white fir, Engelmann spruce, subalpine fire, and mixed 

Engelmann spruce-subalpine fire. For the Interior West, this group also includes grand fir and blue spruce. 

The western softwoods group includes western white pine, foxtail pine-bristlecone pines, limber pine, and 

whitebark pine.

Soil pH generally decreases with increasing elevation, latitude, and precipitation 

(fig. 38) with more acidic soils found in wetter high-elevation forest types. Higher levels of exchangeable Al (aluminum) also are found in wetter high-elevation forest soils 

(fig. 38). In both Utah, and the Interior West as a whole, much higher levels of Al are 

found in spruce/fir than aspen soils. Aspen are intolerant of high levels of exchangeable 

Al. In the Interior West as a whole, aspen soils store more K (potassium) than other 

forest type groups (fig. 38). In Utah, western hardwoods, ponderosa pine, Douglas-fir, 

and aspen forests store comparable amounts of soil K. High levels of exchangeable Ca 

are found in the calcareous, high-pH soils under western hardwoods (including oaks) 

and pinyon-juniper group woodlands (fig. 38).
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 67

2000-04 Utah FIA FHM Plots

Soil Organic C & Total N Stocks

Organic C, Mg/ha

0

20

40

60 10-20 cm

0-10 cm

Forest floor

Forest type

Western hardwoods

Pinyon/Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Aspen

Spruce/Fir

Total N, Mg/ha 0

1

2

3

4 10-20 cm

0-10 cm

Forest floor

2000-05 Interior West FIA FHM Plots

Soil Organic C & Total N Stocks

Organic C, Mg/ha

0

10

20

30

40

50 10-20 cm

0-10 cm

Forest floor

Forest type

Western hardwoods

Western oaks

Pinyon-Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Cottonwood/aspen/birch

Hemlock/redcedar/larch

Spruce/fir

Western softwoods

Total N, Mg/ha 0.0

0.5

1.0

1.5

2.0

2.5

3.0 10-20 cm

0-10 cm

Forest floor

Figure 37—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 Utah (left side) and in five Interior West 

States (Arizona, Colorado, Idaho, Montana, and Utah) (right side).

Discussion—Common causes of aspen mortality include fire suppression, overbrowsing by native ungulates and domestic livestock, and forest succession in which aspen 

are replaced by invading conifers (Bartos and Campbell 1998). Loss of aspen on the 

landscape can lead to decline or loss of ecosystem benefits provided by aspen. Since 

aspen soils store large amounts of N and K and maintain moderate soil pH levels, conifer 

replacement of aspen can lead to nutrient loses and soil acidification. If these soil changes 

are permanent, aspen may be unable to re-colonize areas where they formerly thrived.

Phase 3 Down Woody Material

Background—Down woody material (DWM) is an important component of forests 

that greatly impacts fire behavior, wildlife habitat, 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. This DWM analysis used Phase 3 (P3) data collected 

on 181 plots from 2001 to 2004 (Woodall and Williams 2005).
68 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Inventory Results—The mean forest fuel loading in Utah for all fuel classes combined is over 8 tons per acre. Figure 39 shows the mean tons per acre of DWM by fuel 

classes. CWD and duff have the highest mean fuel loadings at around 2 tons per acre 

each, and FWD (1Hr) has the lowest at 0.22 tons per acre.

A closer look at mean fuel loadings in Utah by forest type (168 plots) and fuel class 

reveals a wide variation (fig. 40). The Engelmann spruce and subalpine fir forest types 

have the highest total fuel loadings at 32 and 27 tons per acre, respectively, while juniper 

and nonstocked forest types have the lowest at about 4 tons per acre each. Lodgepole 

pine, white fir, and Rocky Mountain juniper forest types each had less than three plots 

sampled and were combined into the “other” category. The Engelmann spruce-subalpine 

fir forest type was not sampled. As expected, wetter forest types have much higher total 

fuel loadings than drier ones, and possibly greater fire hazard potential depending on 

the current environmental conditions. Also, fuel loading variation among forest types 

in the three FWD classes is not as great as in the CWD, duff, and litter classes.

2000-04 Utah FIA FHM Plots

0-20 cm soil cores

1:1 soil/water pH

5

6

7

8

Exch

K, mg/kg

0

100

200

300

400

Exch

Ca, mg/kg

0

1000

2000

3000

4000

5000

Forest type Western hardwoods

Pinyon/Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Aspen

Spruce/Fir

Exch Al, mg/kg

0

10

20

30

40

2000-05 Interior West FIA FHM Plots

0-20 cm soil cores

1:1 soil/water pH

5.0

5.5

6.0

6.5

7.0

7.5

Exch K, mg/kg

0

100

200

300

Exch Ca, mg/kg

0

1000

2000

3000

4000

Forest type

Western hardwoods

Western oaks

Pinyon-Juniper

Ponderosa pine

Lodgepole pine

Douglas fir

Cottonwood/aspen/birch

Hemlock/redcedar/larch

Spruce/fir

Western softwoods

Exch Al, mg/kg

0

25

50

75

100

125

Figure 38—Soil pH and exchangeable potassium, calcium, and aluminum in the 0-20 cm soil layers arranged 

by forest type groups in Utah (left side) and in five Interior West States (Arizona, Colorado, Idaho, Montana, and 

Utah) (right side).
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 69

0

0.5

1

1.5

2

2.5

FWD 1Hr FWD 10Hr FWD 100Hr CWD 1000Hr Duff Litter

Tons/acre 

Fuel classes 

Figure 39—Mean tons per acre of down woody material by fuel class, Utah, cycle 2, 2001-2004.

Structural diversity in terms of CWD diameters and decay classes are an important 

consideration for wildlife habitat. Figure 41 displays the mean number of logs per acre 

by forest type and transect diameter class. Although the overall mean in the 18-inch 

and greater class is 0.66 per acre, some forest types such as subalpine fir, aspen, and 

Douglas-fir have as many as 5.6, 2.5, and 2.3, respectively. This could be critical for 

wildlife species that use large diameter logs for habitat. 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 42 shows the mean number of logs per 

acre by forest type and decay class. The most common decay classes in Utah for all forest 

types combined is class 3 and 4, with a mean of 55 and 38 logs per acre, respectively.

Discussion—The current 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 will hopefully serve as a better surrogate for answering relevant 

questions about other material in forests. Pacific Northwest FIA and IWFIA are jointly 

investigating a national Phase 2 inventory version of DWM to support a more robust 

dataset for future fire fuel, wildlife structure, and carbon assessments.
70 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 864201816141210 Engelmann spruce n=4 Subalpine fir n=6 Other n=5 Douglas-fir n=8 Aspen n=17 Deciduous oak woodland n=10 Ponderosa pine n=5 Cercocarpus woodland n=5 Pinyon-juniper woodland n=75 Juniper woodland n=23 Nonstocked n=10

ons/acre T

Forest type 

FWD 1HrFWD 10HrFWD 100HrCWD 1000HrDuffLitter

Figure 40—Mean tons per acre of down woody material by forest type and fuel class, Utah, cycle 2, 2001-2004.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 71 050 250 200 150 100 Subalpine fir n=6 Engelmann spruce n=4 Aspen n=17 Other n=5 Deciduous oak woodland n=10 Douglas-fir n=8 Pinyon-juniper woodland n=75 Ponderosa pine n=5 Nonstocked n=10 Juniper woodland n=23 Cercocarpus woodland n=5

Logs/acre 

Forest type 

Log dia 3.0" – 7.9Log dia 8.0" – 12.9Log dia 13.0" – 17.9Log dia 18.0"+

Figure 41—Mean number of CWD logs per acre by forest type and transect diameter class, Utah, cycle 2, 2001-2004.
72 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 080604020 160 140 120 100 Subalpine fir n=6 Engelmann spruce n=4 Aspen n=17 Other n=5 Deciduous oak woodland n=10 Douglas-fir n=8 Pinyon-juniper woodland n=75 Ponderosa pine n=5 Nonstocked n=10 Juniper woodland n=23 Cercocarpus woodland n=5

Logs/acre 

Forest type 

Decay 1Decay 2Decay 3Decay 4Decay 5

Figure 42—Mean number of CWD logs per acre by forest type and decay class, Utah, cycle 2, 2001-2004.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 73

Forest Lichens

Background—Lichen communities are used by FIA as biomonitors of air quality, 

climate change, and the impacts of change in the structure of the forest vegetation on 

other members of the forest community. Over time, lichen communities may change 

in response to stressors, such as air pollutants, and other factors, such as successional 

change. For example, Rogers and Ryel (2008) found that in an aspen-to-conifer successional sequence, certain lichens favored an aspen conifer mix, while others became more 

abundant in later successional stages. Some of the differences in lichen communities 

across the successional sequence appeared to be related to the age of the trees (more 

time for lichens to become established) and to the quality of substrate available for 

colonization (rougher bark more likely to be colonized than smooth bark).

Because the lichen community indicator measures change over time, it is implemented in two phases. A calibration phase, which uses data from standard FIA plots and 

supplemental plots from sites with poor air quality, is used to develop a lichen gradient 

model for a specific geographic region (Neitlich and others 2001; Will-Wolf 2010). 

Once the gradient model is developed, changes in lichen communities can be assessed 

in the application phase. In this phase, lichen community data from standard FIA plots 

are fitted to the gradient models to generate lichen community scores. These scores 

are then interpreted to evaluate lichen community status and trends, and their possible 

relationship to environmental changes such as increasing pollution or warming climate.

The lichen community gradient model has not yet been developed for Utah, so Utah is 

currently in the calibration phase. Until the calibration phase is complete, lichen species 

richness and abundance are the only lichen indicator statistics available for standard FIA 

plots. There are three measures of lichen community richness and abundance calculated 

during the calibration phase: richness, diversity, and evenness. Richness is simply the 

number of lichen species on a plot. Lichens identified only to genus are included in 

this count, because a lichen listed by genus only is known to be different from all other 

species found on the plot. Diversity is expressed using the Shannon-Weiner Diversity 

Index, which is calculated as:

H’ = - ∑(Pi*ln(Pi))

where H’ is the Shannon-Weiner index, and

Pi is the proportion of total abundance of species i on the plot.

Evenness is a measure of how evenly abundance is distributed among species. It is 

calculated as:

E = H’/ln(Richness)

where E is evenness and the other variables are defined as above.

Evenness is scaled from zero to 1, with 1 indicating equal abundance of all species.

Inventory Results—Figure 43 shows richness, diversity, and evenness for lichen 

plots in Utah. On most of the plots with lichen present, there are three or more lichen 

species. As expected, the diversity index tends to be highest where there are more species present. However, evenness appears to be unrelated to richness or diversity, because 

most plots have approximately equal evenness.

Discussion—Use of the lichen indicator in Utah is currently limited to relatively 

simple measures, but the establishment of an environmental gradient model will enable 

more detailed analysis in the future. Other lichen studies have found that lichens in Utah, 

for the most part, have not been significantly impacted by air pollution. For example, 

pilot biomonitoring studies in the Manti-LaSal National Forest (St. Clair 2000) and the 
74 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Figure 43—Lichen richness, diversity, and evenness measures for FIA plots in Utah, cycle 2, 2000-2005. Larger symbols 

indicate higher values for each measure.

Uinta Mountains (St. Clair and Newberry 1994) found little pollution-related damage 

on lichens, but noted that some potentially harmful elements were found in relatively 

high levels in lichen tissue. Because there has been little impact to lichen communities 

to date, it is expected that the application phase will be able to detect environmental 

change as lichen monitoring in Utah continues.

Phase 2 Damage

Background—As field crews measure live trees on subplots (trees 5 inches diameter 

and greater), they carefully examine those trees for the presence of damaging agents 

(USDA Forest Service 2000-2005a). They record up to three damaging agents if the 

damages meet one or more of the following three criteria:

1. The damage will prevent the tree from living to maturity, if immature, or living 

10 more years, if mature.

2. The damage will prevent the tree from producing marketable products.

3. The damage will seriously reduce (or has reduced) the quality of the tree’s 

marketable products.

Since the last two criteria are less applicable to woodlands species that produce few 

marketable products, results from damage data can be quite different between woodland 

type species and timber type species.

Damaging agents are grouped into several general classes: insects, diseases, fire, 

animals, humans, and miscellaneous. The miscellaneous group includes suppression, 

some symptomatic groups whose ultimate causation can be difficult to determine in 

the field (unhealthy foliage and heartwood scars), unknown causes, and timber form 

defects that affect commercial products (forking, excessive lean, broken tops, and excessive crook, sweep, or taper). Crews also estimate cull volume percentages (missing 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 75

top, dead wood, rotten and missing wood, and timber form). When these percentages 

exceed specific thresholds, although these thresholds can vary by timber or woodland 

species type, the damaging agent must be recorded.

Inventory results—Of the estimated 2.1 billion live trees 5.0 inches diameter and 

greater in Utah, about 844 million, or 40 percent, are estimated to have at least one 

damage meeting one or more of the three damage evaluation criteria above. Of these, 

634 million have only one damaging agent, 179 million have two, and 31 million have 

three (table 9). Timber species had a damage agent recorded more frequently than did 

woodland species (56 percent versus 30 percent), mostly due to loss of marketable products, although there were other differences between damages to timber and woodland 

species. The species with damages most frequently recorded were quaking aspen, white 

fir, limber pine, Great Basin bristlecone pine, narrowleaf cottonwood, and Fremont/Rio 

Grande cottonwood—all of which are measured and evaluated as timber species. Great 

Basin bristlecone and the cottonwood species were measured on few plots, so the actual 

estimates of numbers of trees may not be completely reliable, but they all have growth 

form and/or ecological characteristics that would lead to an expectation of frequent 

damage. The most frequently damaged woodland species was Utah juniper.

Discussion—The most common damage category was the miscellaneous group, followed by diseases. Figure 44 shows the percentages of trees with at least one damaging 

agent recorded by damage agent group and timber/woodland species group. Most groups 

show differences between timber species and woodland species.

Damages to timber species in the miscellaneous group are mostly growth form 

defects affecting merchantability, led by excessive crook, sweep, or taper and forking 

below the merchantable top. The most important health-related miscellaneous damages 

in timber species were heartwood scars on the bole and dead tops. The most frequent 

miscellaneous damage in woodland species was “unidentified or unknown.” Woodland 

species frequently have dead branches that remain on the tree long after the cause(s) 

can be identified, and damage agents are required when volume deductions are made 

for dead wood. Heartwood scars on the bole are the second most common damage on 

woodland species.

Disease damaging agents are more frequent in timber species than in woodland species, with aspen being the most affected common timber species. Other species with 

common disease damage agents were subalpine fir, Douglas-fir, white fir, and lodgepole 

pine. The most common diseases in timber species were cankers and stem and butt rots, 

which were particularly abundant in aspens. Also frequent in timber species were broom 

rusts. Woodland species were most affected by stem and butt rots. Dwarf mistletoe was 

frequently found on common and singleleaf pinions; true mistletoe was found on Utah 

juniper and, to a lesser extent, on Gambel oak.

Two damaging agents that were found relatively infrequently, but merit mention, 

are insects and fire, because they are the most common causes of tree mortality (see 

“Growth and Mortality” in Section IV). Insect damage, particularly bark beetles, can 

be difficult to see in live trees, but can rapidly lead to tree death; thus, insect damage 

would be more commonly recorded as a mortality agent than a damage agent. Bark 

beetles were the most common insects recorded in timber species. In Utah, fire tends to 

kill trees rather than damage them, although two fire-resistant species, ponderosa pine 

and Douglas-fir, did have the highest rates of fire damage.
76 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Table 9--Number of live trees 5.0 inches diameter and greater by species and number of damages, Utah, cycle 2, 2000-2005. No damage One damage Two damages Three damages All trees Thousand trees ( %)* Timber species Aspen 81,016 (29) 128,747 (45) 59,764 (21) 13,783 ( 5) 283,311 Lodgepole pine 68,675 (52) 48,882 (37) 11,516 ( 9) 2,425 ( 2) 131,498 Subalpine fir 54,378 (51) 38,511 (36) 11,998 (11) 1,554 ( 1) 106,441 Douglas-fir 47,005 (48) 39,695 (41) 8,382 ( 9) 1,920 ( 2) 97,001 Engelmann spruce 53,415 (61) 28,462 (32) 5,028 ( 6) 1,371 ( 2) 88,276 White fir 21,665 (40) 25,159 (46) 6,808 (13) 735 ( 1) 54,367 Ponderosa pine 1,648 (60) 10,034 (32) 2,331 ( 7) 119 (0.4) 31,132 Limber pine 2,610 (38) 3,099 (45) 1,048 (15) 176 ( 3) 6,933 Blue spruce 2 345 (87) 165 ( 6) 56 ( 2) 126 ( 5) 2,691 Great Basin bristlecone pine 565 (29) 796 (40) 504 (26) 111 ( 6) 1,975 Narrowleaf cottonwood 304 (26) 759 (65) 111 ( 9) 0 ( 0) 1,174 Fremont cottonwood, Rio Grande cottonwood 0 ( 0) 285 (43) 296 (45) 76 (12) 657 Timber species Total 350,625 (44) 324,594 (40) 107,841 (13) 22,396 ( 3) 805,456 Woodland species Utah juniper 402,541 (64) 169,395 (27) 46,558 ( 7) 6,405 ( 1) 624,898 Common or twoneedle pinyon 240,816 (73) 70,425 (21) 15,100 ( 5) 1,801 (0.5) 328,142 Gambel oak 77,036 (75) 23,812 (23) 2,231 ( 2) 122 (0.1) 103,201 Curlleaf mountain-mahogany 67,958 (74) 20,923 (23) 3,194 ( 3) 55 (0.1) 92,129 Singleleaf pinyon 60,129 (78) 14,627 (19) 2,569 ( 3) 172 (0.2) 77,498 Rocky Mountain juniper 40,698 (88) 4,074 ( 9) 1,130 ( 2) 171 (0.4) 46,073 Bigtooth maple 25,761 (80) 5,731 (18) 491 ( 2) 129 (0.4) 32,112 Woodland species Total 914,938 (70) 308,988 (24) 71,273 ( 5) 8,855 (0.7) 1,304,054 All species 1,265,564 (60) 633,582 (30) 179,114 ( 8) 31,251 ( 1) 2,109,510 *Numbers and percents may not add to totals due to rounding. Species
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 77 Figure 44—Percent of live trees 5.0 inches diameter by species type and damage agent group, Utah, cycle 2, 2000-2005 0% 80% 70% 60% 50% 40% 30% 20% 10% 

Percent of trees in species type 

Damage agent group (at least one damage in group recorded) 

Timber Species Woodland Species 

NoneMiscellaneous Diseases Insects Weather/Atmosphere Animals Human Fire
78 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 79

VII. Timber Products

Removals

The net volume of growing-stock trees removed from the inventory by harvesting, cultural operations, land clearing, and changes in land use is generally known as 

“removals.” As State annual inventory cycles are completed, future reports will assess 

removals through remeasurement of the permanent annual field plots. In this report, 

removals, which are measured periodically, are based on data from 2002, and deal only 

with removals for timber products. Utah’s 2002 industrial timber harvest was 41.3 million board feet Scribner, and dead trees accounted for nearly 17.6 million board feet 

(43 percent) of the harvest (Morgan and others 2006). Dead trees are not considered 

growing-stock trees. Thus removals are substantially less than total harvested volume.

Removals for timber products include both the volume processed in mills and logging 

residue—the volume harvested or killed but not utilized. Tables 10, 11, and 12 show 

removals by product, species, and ownership group in cubic feet for growing-stock 

removals, and board feet International 1⁄4-inch and Scribner log rules for removals from 

the sawlog portion of sawtimber trees.

About 5.4 million cubic feet of wood, exclusive of land clearing volume and changes 

in land use, were removed from growing-stock on Utah’s non-reserved timberland 

during 2002. Nearly 95 percent of the volume was for wood products, and 5 percent 

was not utilized and was left in the woods as logging residue. Sawlogs were the largest 

component of removals from growing-stock followed by fiber logs.

National Forests supplied 43 percent of the volume removed from growing-stock. 

Other public landowners, including the Bureau of Land Management and the State of 

Utah, provided slightly less than 4 percent, while private and tribal landowners supplied 

the majority (53 percent).

Removals from the sawlog portion of sawtimber included 18.8 million board feet 

Scribner log rule, or 21.1 million board feet expressed in International 1⁄4-inch log rule. 

Logs harvested to produce lumber (sawlogs) dominated products harvested from sawtimber, accounting for 88 percent of sawtimber removals. Logging residues accounted 

for just 1.7 percent of total sawtimber removals.

Spruce was the leading species harvested, accounting for 36 percent of growing-stock 

removals and 42 percent of sawtimber removals. Hardwoods, primarily aspen and cottonwood, accounted for 25 percent of growing-stock removals and almost 17 percent 

of sawtimber removals. Lodgepole pine, ponderosa pine, Douglas-fir, true fir, and other 

pine species accounted for the remaining removals.

Forest Industry (Revised from Morgan and others 2006)

Utah’s primary forest products industry consisted of 49 active manufacturers operating in 20 counties during 2002 (table 13). The sawmill sector, manufacturing lumber 

and other sawn products, was the largest sector, operating 23 mills during 2002; 14 

facilities produced house logs and log homes. There were 10 log furniture producers, 

one post and pole firm, and a decorative bark producer also operating in 2002. Changes 

in Utah’s industry structure over the past 10 years were similar to those experienced 

throughout the Interior West, with the number of sawmills decreasing and the number 

and diversity of other manufacturers increasing.
80 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Table 10--Removals from nonreserved timberland by species and product, Utah, 2002, from RPA-TPO data calculated by BBER from FIDACS data. Thousand cubic feet--growing stock removals Sawlogs Fiber logs Fuelwood Post, pole, piling Other products* All products Logging residue Total removals Douglas-fir 455.778 10.587 - - 1.870 468.234 25.864 494.098 True fir 92.277 10.105 - - 0.890 103.272 5.704 108.977 Lodgepole pine 485.846 - - 259.466 30.695 776.006 42.865 818.871 Ponderosa pine 631.687 - - 2.887 3.811 638.384 35.263 673.647 Other pine 2.730 - - - - 2.730 0.151 2.881 Spruce 1,722.737 - - 115.537 23.643 1,861.918 102.847 1,964.765 Hardwoods 347.157 923.432 13.807 - - 1,284.396 70.184 1,354.580 Total species 3,738.212 944.124 13.807 377.890 60.909 5,134.942 282.878 5,417.820 Thousand board feet (International 1/4")--sawlog removals from sawtimber trees Sawlogs Fiber logs Fuelwood Post, pole, piling Other products* All products Logging residue Total removals Douglas-fir 2,271.541 19.956 - - 9.445 2,300.943 40.637 2,341.580 True fir 459.896 19.049 - - 4.498 483.443 8.538 491.981 Lodgepole pine 2,421.393 - - 0.553 155.069 2,577.016 45.513 2,622.528 Ponderosa pine 3,148.246 - - 0.006 19.251 3,167.503 55.941 3,223.444 Other pine 13.606 - - - - 13.606 0.240 13.847 Spruce 8,585.904 - - 0.246 119.445 8,705.594 153.749 8,859.344 Hardwoods 1,730.188 1,740.711 19.321 - - 3,490.220 61.300 3,551.520 Total species 18,630.775 1,779.716 19.321 0.806 307.708 20,738.325 365.918 21,104.243 Thousand board feet (Scribner)--sawlog removals from sawtimber trees Sawlogs Fiber logs Fuelwood Post, pole, piling Other products* All products Logging residue Total removals Douglas-fir 2,028.162 17.818 - - 8.433 2,054.413 36.283 2,090.696 True fir 410.621 17.008 - - 4.016 431.645 7.623 439.269 Lodgepole pine 2,161.958 - - 0.494 138.455 2,300.907 40.636 2,341.543 Ponderosa pine 2,810.934 - - 0.005 17.188 2,828.128 49.948 2,878.075 Other pine 12.149 - - - - 12.149 0.215 12.363 Spruce 7,665.985 - - 0.220 106.647 7,772.852 137.276 7,910.129 Hardwoods 1,544.811 1,554.206 17.251 - - 3,116.268 54.732 3,171.000 Total species 16,634.620 1,589.032 17.251 0.719 274.739 18,516.362 326.713 18,843.074 *Other products include house logs and log furniture logs.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 81

Sales from Utah’s primary wood products industry during 2002 totaled nearly $36.6 

million, including finished products and mill residues. House logs and log homes accounted for 50 percent of total sales; lumber, mine timbers, and other sawn products 

accounted for about 32 percent; while other products and mill residues accounted for 

18 percent. Utah was the leading market area for lumber, log homes, posts, poles, and 

log furniture, with in-State sales accounting for almost 46 percent of total sales. The 

other Four Corners States (Arizona, Colorado, and New Mexico) accounted for about 

22 percent of total sales, with log homes accounting for 45 percent of sales in the region.

Timber processors in Utah received 32.5 million board feet (MMBF) Scribner of 

timber in 2002 (table 14), including 2.8 MMBF that was harvested outside the State. 

Private and tribal timberlands provided 9.2 MMBF (28 percent) of the timber delivered 

to Utah mills during 2002. National Forests provided 67 percent (21.9 MMBF) of timber 

receipts, with 29 of Utah’s timber processors receiving timber cut from National Forests. 

State lands provided less than 5 percent of the timber received by mills in Utah.

Thousand cubic feet--growing stock removals

National Forest Other public Private All owners

Douglas-fir 61.287 0.960 431.852 494.098

True fir 42.964 0.691 65.321 108.977

Lodgepole pine 510.931 1.344 306.596 818.871

Ponderosa pine 223.726 174.812 275.109 673.647

Other pine - - 2.881 2.881

Spruce 1,395.953 2.065 566.747 1,964.765

Hardwoods 91.305 19.206 1,244.069 1,354.580

Total species 2,326.166 199.078 2,892.575 5,417.820

National Forest Other public Private All owners

Douglas-fir 294.623 4.616 2,042.341 2,341.580

True fir 206.558 3.323 282.099 491.981

Lodgepole pine 1,257.628 6.460 1,358.440 2,622.528

Ponderosa pine 1,060.897 840.217 1,322.330 3,223.444

Other pine - - 13.847 13.847

Spruce 6,125.037 9.953 2,724.354 8,859.344

Hardwoods 438.848 92.311 3,020.361 3,551.520

Total species 9,383.591 956.880 10,763.772 21,104.243

National Forest Other public Private All owners

Douglas-fir 263.056 4.121 1,823.519 2,090.696

True fir 184.427 2.967 251.874 439.269

Lodgepole pine 1,122.882 5.768 1,212.893 2,341.543

Ponderosa pine 947.230 750.194 1,180.652 2,878.075

Other pine - - 12.363 12.363

Spruce 5,468.783 8.886 2,432.459 7,910.129

Hardwoods 391.828 82.421 2,696.751 3,171.000

Total species 8,378.206 854.357 9,610.51 1 18,843.074

Table 11--Removals from nonreserved timberland by species and product, Utah, 2002, from RPA-TPO data 

calculated by BBER from FIDACS data.

Thousand board feet (International 1/4")--sawlog removals from sawtimber 

trees

Thousand board feet (Scribner)--sawlog removals from sawtimber trees
82 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

National Forest Other public Private All owners

Sawlogs 1,805.695 188.230 1,744.286 3,738.212

Fiber logs - - 944.124 944.124

Fuelwood - - 13.807 13.807

Post, pole, piling 355.033 - 22.857 377.890

Other products* 43.673 0.427 16.809 60.909

Total products 2,204.401 188.657 2,741.883 5,134.942

Logging residue 121.765 10.421 150.692 282.878

Total removals 2,326.166 199.078 2,892.575 5,417.820

National Forest Other public Private All owners

Sawlogs 8,999.356 938.115 8,693.303 18,630.775

Fiber logs - - 1,779.716 1,779.716

Fuelwood - - 19.321 19.321

Post, pole, piling 0.757 - 0.049 0.806

Other products* 220.630 2.159 84.919 307.708

Total products 9,220.744 940.274 10,577.307 20,738.325

Logging residue 162.848 16.606 186.465 365.918

Total removals 9,383.591 956.880 10,763.772 21,104.243

National Forest Other public Private All owners

Sawlogs 8,035.140 837.603 7,761.878 16,634.620

Fiber logs - - 1,589.032 1,589.032

Fuelwood - - 17.251 17.251

Post, pole, piling 0.676 - 0.044 0.719

Other products* 196.991 1.928 75.820 274.739

Total products 8,232.807 839.530 9,444.024 18,516.362

Logging residue 145.400 14.827 166.486 326.713

Total removals 8,378.206 854.357 9,610.511 18,843.074

*Other products include house logs and log furniture logs.

Thousand cubic feet--growing stock removals

Thousand board feet (International 1/4")--sawlog removals from sawtimber 

trees

Thousand board feet (Scribner)--sawlog removals from sawtimber trees

Table 12--Removals from nonreserved timberland by species and product, Utah, 2002, from RPA-TPO data 

calculated by BBER from FIDACS data.

Table 13--Active Utah primary wood products facilities by county and product, 2002.

County Lumber

Log homes and

house logs 

Log furniture and 

other productsa

Total

Beaver 1 1 2

Cache 3 1 4

Davis 1 1

Duchesne 2 2 4

Emery 1 1

Garfield 1 1 1 3

Iron 1 1 2

Millard 1 1

Morgan 1 1

Piute 1 1

Salt Lake 1 1 2 4

San Juan 1 1

Sanpete 1 1 2

Sevier 1 1

Summit 3 1 4

Uintah 1 4 1 6

Utah 2 2

Wasatch 2 2 4

Wayne 2 1 3

Weber 1 1 2

2002 Total 23 14 12 49

1992 Total 34 13 4 51 a

Other products include posts, poles, and bark products.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 83

Utah’s sawmill sector has been in decline for several decades. Lumber production 

in 2002 was 58 percent lower than in 1992 and 63 percent lower than in 1966. Most of 

the production loss was among the State’s larger mills, while the greatest loss of actual 

milling facilities was among the small mills. Average annual lumber production among 

the State’s six largest mills was about 3.8 MMBF lumber tally in 2002. The remaining 

17 small mills had an average lumber production of 204 MBF in 2002. On average, 

Utah sawmills produced approximately 1.28 board feet of lumber for every board foot 

Scribner of timber processed, resulting in an average overrun of 28 percent in 2002.

Sales value from Utah’s log home sector increased substantially over the past 10 

years even though only one more house log manufacturer was identified in 2002 than 

in 1992. During 2002, Utah’s 14 log home manufacturers processed 11.0 MMBF of 

timber, produced about 3.0 million lineal feet of house logs, and generated about $18.5 

million in product sales. By sales value, Utah’s log home sector is the fourth largest in 

the western United States, behind Montana, Idaho, and Colorado.

Across all industry sectors, total timber-processing capacity was 78.5 MMBF Scribner. 

A total of 32.6 MMBF Scribner was processed by Utah firms in 2002, making capacity 

utilization about 42 percent. Utah timber processors produced 41,106 bone dry tons 

(BDT) of mill residue, with 89 percent utilized. Sawmills were the main residue producers in Utah, producing 31,294 BDT of residue, or 1.176 BDT of residue per MBF 

of lumber, during 2002.

Ownership class Sawlogs House logs Other productsa All products

Private and tribal timberland 7,630 951 661 9,241 

Public timberland 12,571 8,918 1,755 23,245 

 National Forest 11,571 8,618 1,709 21,898 

 State lands 1,000 300 46 1,346 

Other ownersb - - 33 33 

All owners 20,201 9,869 2,448 32,518 a

Other products include furniture logs, fiber logs, posts, and poles. b

Other owners include the BLM and Canada.

Table 14--Timber received by Utah forest products industry by ownership class and product, 2002.

---------------Thousand board feet, Scribner-------------
84 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 85

VIII. Summary and Conclusions

Changes in definitions and other factors have affected direct comparisons of past 

periodic to present annual inventories. These changes represent a continual improvement 

process within the FIA program, so there is some trade-off between inventory consistency 

and improvement. The same holds true for the FIA annual inventory system, which is, 

and will be, continually updated and improved. Utah’s 19.5 million acres of forest and 

other wooded lands are constantly changing. As a full inventory cycle is completed and 

remeasurement begins in 2010, direct plot-to-plot and tree-to-tree measurements will 

reflect real change in another 10 percent of the plots each year. Forest resource trends 

of area, number of trees, volume, biomass, growth, mortality, and other attributes will 

be linked directly to permanent plots that can be tracked both temporally and spatially.

Even though there have been definitional changes, the annual inventory showed more 

forest area (especially in woodland types) and more live trees (especially in Gambel oak) 

than the previous periodic inventory of Utah (O’Brien 1999); there was little difference 

in total volume from the past. However, at the species level there were some noticeable 

differences. Aspen, Utah juniper, and lodgepole pine had the largest increases in volume, 

while Douglas-fir and Engelmann spruce had the largest decreases in volume. Based on 

the annual inventory, aspen, subalpine fir, and Douglas-fir had the largest gross growth. 

Engelmann spruce had the highest mortality followed by subalpine fir, common pinyon, 

and Douglas-fir. Aspen area and volume increased from the past, while the total number 

of trees decreased, with fewer small-diameter and greater large-diameter trees.

“Other wooded land,” a new land type classification, may prove useful for future assessments of change, especially in States like Utah where there is a significant amount 

of forest with sparse tree crown cover, like pinyon and juniper. Although they are a 

relatively long-lived species, the expansion of pinyon and juniper woodlands since EuroAmerican settlement of the West and the recent drought-related pinyon mortality in the 

southwestern United States are evidence that they are not immune to rapid change events. 

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. According to FIA’s current annual data, aspen appears to be fairly stable 

in Utah. However, conifer species, such as Engelmann spruce, have shown substantial 

recent mortality due to beetle attack. Excluding the impacts of fire, which can affect all 

species, other common conifers in Utah such as Douglas-fir, subalpine fir, lodgepole 

pine, and ponderosa pine are particularly susceptible to forest insect outbreaks, which 

can have widespread affects. The long-term outlook for these species will depend on 

the composition and structure of the current stands, weather and climate conditions, 

and insect population trends. In addition, this selective mortality, which often occurs 

in older trees, can alter the tree age distribution of stands. This can affect the balance 

of structural stand-size distributions on the landscape for long-term sustainability, and 

important stand structures like “old forest.”

Although noxious plant species can have many negative effects on forest communities, in Utah they are not prevalent in the pinyon-juniper forest type group; whereas the 

oak, aspen, and other western hardwood types are more susceptible to invasion. This 

may be due to one or more factors, including soil conditions, accessibility to livestock 

grazing, road and foot traffic, and/or high frequency of both natural and human-induced 

disturbance. On the other hand, cheatgrass which is most common in the pinyon-juniper 

forest type group in Utah, can present a threat to western ecosystems.

Standing dead trees (snags) provide important habitat for many species in the forested ecosystems of Utah including cavity-nesting birds, silver-haired bats, and black 

bears. In general, Engelmann spruce contributes the most snags for all three wildlife 
86 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

species combined, with aspen and subalpine fir available in abundance for both bats 

and cavity-nesting birds. Douglas-fir and lodgepole pine also contribute significantly 

to the needs of birds and bats while ponderosa pine provides the bulk of the remaining 

potential den sites for black bear. 

FIA’s Phase 3 indicators are useful for monitoring forest health issues such as tree 

crown conditions, lichen community composition, understory vegetation, down woody 

materials, and soil attributes at the regional or national scale. In addition, this data can 

often be used as a flag for events that may guide to information needs at a much finer 

scale.

Although more recently there has been a downturn in Utah’s Forest Industry, in 2002 

Utah’s primary forest products industry consisted of 49 active manufacturers operating 

in 20 counties. Sales from Utah’s primary wood products industry during 2002 totaled 

nearly $36.6 million, including finished products and mill residues. The industrial timber harvest was 41.3 million board feet Scribner, and dead trees accounted for nearly 

17.6 million board feet (43 percent) of the harvest. About 5.4 million cubic feet of 

wood, exclusive of land clearing volume and changes in land use, were removed from 

growing-stock on Utah’s non-reserved timberland during 2002. Spruce was the leading 

species harvested, accounting for 36 percent of growing-stock removals and 42 percent 

of sawtimber removals. 

At the national level, there are many discussions about how to coordinate assessments 

of forest and other lands in a more seamless manner. One way FIA plans to facilitate this 

is by collecting land use and tree crown cover on all Phase 2 plots, regardless of whether 

they meet FIA’s definition of forest land. In the near future, this information can be used 

for initial assessments as a broad scoping tool for all lands. As FIA maintains its role 

as the Nations continuous forest census, it will be necessary to adapt to the continually 

changing needs and expectations of users.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 87

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. The calculation is based on 

diameter at breast height (d.b.h.) for timber species; 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. 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. Boardfoot volume is computed for the sawlog portion of a sawtimber-size 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 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 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. 
88 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Cubic-foot volume (merchantable)—A cubic-foot is a unit of measure indicating the 

amount of wood contained in a cube 1x1x1 foot. Cubic-foot volume 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 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-inch, 6-inch, 

8-inch) 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. d.o.b. 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 wide or 

1 acre in size. Grazed woodlands, reverting fields, and pastures that are not actively 

maintained are included if above qualifications are satisfied.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 89

Forest type—A classification of forest land based on the species forming a plurality 

of live-tree stocking. 

• Timber type—Forest types based on species that are measured at d.b.h.

• Woodland type—Forest types based on species that are measured at d.r.c.

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. Duff is the organic layer, unrecognizable as to origin, immediately beneath the litter layer from which it is derived. 

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 utilized 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.

• 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. 

• Primary wood-processing plants—An industrial plant that processes roundwood 

products, such as sawlogs, pulpwood bolts, or veneer logs. 

• 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. 
90 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Mapped-plot design—A sampling technique that identifies (maps) and separately classifies distinct “conditions” on the field location sample area. Each condition 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 

diameter; portions of stems or branches smaller than 1.0 inch 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.

Nonreserved forest land—Forest land not withdrawn from management for production 

of wood products through statute or administrative designation. 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 91

Other private lands—Privately owned lands other than forest industry or Indian Trust. 

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 5-10 percent cover of live tally tree species of 

any size, or from 40 to 199 seedlings per acre; 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.

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. 

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 MAI). 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 1.0-4.9-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. 

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 sawtimbersize trees in board feet.

Seedlings— Live trees less than 1.0 inch d.b.h./d.r.c.
92 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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), 

SDI 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: 

• 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. 
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 93

• 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. 

Timber species—Tally tree species traditionally used for industrial wood products. 

These include all species of conifers, except pinyon and juniper. Timber species are 

measured at d.b.h. 

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—Nonreserved forest land capable of producing 20 cubic feet of industrial 

wood per acre per year. 

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. 

Woodland species—Tally tree species that are not usually converted into industrial 

wood products. Common uses of woodland trees are fuelwood, fenceposts, and 

Christmas trees. These species include pinyon, juniper (except Western juniper), 

mesquite, locust, mountain-mahogany (Cercocarpus spp.), Rocky Mountain maple, 

bigtooth maple, desert ironwood, and most oaks (note: Bur oak and Chinkapin oak 

are classified as timber species). Because most woodland trees are extremely variable 

in form, diameter is measured at d.r.c.

Note: For the FIA national glossary please go to: 

http://socrates.lv-hrc.nevada.edu/fia/ab/issues/pending/glossary.html
94 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 95

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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.

Van Hooser, Dwane D. 1981. [Letter to Gyde Lund]. October 30. 3 leaves. 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.

Van Hooser, Dwane D. 1983. [Letter to Frank G. Sadowski]. December 9. 2 leaves. 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.
USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 99

Van Hooser, Dwane D.; Chojnacky, David C. 1983. Whole tree volume estimates for the Rocky Mountain 

States. Resour. Bull. RB-INT-29. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 7 p.

Veblen, T.T.; Hadley, K.S.; Nel, E.M.; Kitzberger, T.; Reid, M.; Villalba, R. 1994. Disturbance regime and 

disturbance interactions in a Rocky Mountain subalpine forest. Journal of Ecology 82: 125-135.

Weisberg, P.J.; Ko, D.; Py, C.; Bauer, J.M. 2008. Modeling fire and landform influences on the distribution 

of old-growth pinyon-juniper woodland. Landscape Ecology 23: 931-943.

Weisberg, Peter J.; Lingua, E.; Pillai, R.B. 2007. Spatial patterns of pinyon-juniper woodland expansion 

in central Nevada. Rangeland Ecology and Management 60: 115-124.

Will-Wolf, S. 2010. Analyzing lichen indicator data in the Forest Inventory and Analysis Program. Gen. 

Tech. Rep. PNW-GTR-818. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 62 p.

Williams, Clinton K. 2009. Properly Functioning Conditions. U.S. Department of Agriculture, Forest Service, Intermountain Region, Vegetation Management, Ecology. [Online]. Available only on U.S. Forest 

Service Intranet site: http://fsweb.r4.fs.fed.us/unit/vm/ecology/ecology_temp.html.

Woodall, C.W.; Williams, M.S. 2005. Sampling protocol, estimation, and analysis procedures for down 

woody materials indicator of the FIA program. Gen. Tech. Rep. NC-256. St. Paul, MN: U.S. Department 

of Agriculture, Forest Service, North Central Research Station. 47 p.

Woodall, Christopher W.; Monleon, Vicente 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, James J.; Egeland, Leanne; Eager, Thomas; and others. 2008. Rapid mortality of Populus tremuloides in southwestern Colorado, USA. Forest Ecology and Management 255(3-4): 686-696.
100 USDA Forest Service Resour. Bull. RMRS-RB-10. 2010
101

Appendix A

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

XI. Appendices

Appendix A—Inventory History and “New Proposed Land Class”

FIA has historically used variables such as stocking, crown cover, land use, wood 

product use, and tree form to help define forest land. In terms of the relationships between 

stocking and crown cover, the minimum stocking threshold of 10 percent for defining 

forest land in the Interior West has remained constant since the 1950s for both periodic 

and annual inventories (USDA Forest Service 1958). However, the surrogate for evaluating 10 percent stocking, based primarily on field estimates of tree crown cover, has 

changed over the years (Van Hooser 1981). This was mainly due to concerns that some 

arid timber species (e.g. ponderosa pine) and many woodland species (e.g. pinyon and 

juniper) that lacked distinct stocking equations may exhibit minimum stocking thresholds 

at lower crown cover densities (Lund 2004). In addition, due to concerns in “negative 

bias in sampling for forest land,” IWFIA first implemented a 5 percent crown cover 

surrogate for 10 percent minimum stocking as early as 1982 (Van Hooser 1981, 1983).

By the time annual inventories commenced in 2000 in Utah, IWFIA had adopted 

a minimum 5 percent crown cover timber/woodland species surrogate for 10 percent 

stocking. Although crown cover was the most significant factor in terms of definitional 

differences from past periodic inventories, other important factors that still confound 

direct trend comparisons include tree form, species, field plot imagery, and changing 

forest type algorithms. 

In preparation for the 2007 Resource Planning Act (RPA) report, there was an expressed concern whether 5 percent crown cover was a legitimate surrogate for 10 percent 

stocking. In 2006, IWFIA implemented a retroactive process called plot-filtering (see 

below) on its previous annual inventory data to assess the definitional change in crown 

cover by classifying plots that had 5 to 9 percent cover. By identifying and separating 

this unique and potentially useful land class (other wooded land), forest land could now 

be more comparable to the past and still meet current national standards.

Changes From Past Definitions

Stocking vs. Crown Cover—The minimum surrogate threshold used for 10 percent 

stocking for forest land in the 1978 periodic inventory of Utah was 10 percent crown 

cover (timber and woodland species combined). By the 1993 periodic inventory of 

Utah, this changed to 5 percent cover for timber species and 10 percent for woodland. 

Stands with combinations of both species required a minimum 10 percent cover, if timber species were still less than 5 percent. As a result, considering differences in crown 

cover alone from 1993 to 2006 and without excluding other wooded land, a definitional 

increase in total forest land area would be expected (see “Area Discussion” in Section 

IV for more details). 

Tree Form—Tree form is another factor that has complicated trend comparisons. 

Prior to 1985 in the Interior West, the variability in form of a tree species was irrelevant 

to its forest land potential. In contrast, due to concerns about the low potential of trees 

on some poor sites to obtain tree form, the 1993 inventory of Utah excluded woodland 

tree species on sites 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). However, field crews 

often had difficulty agreeing on the “potential” of a site. Consequently, by 2000, when 

annual inventories commenced in Utah, this was again reversed. Species, not form, 
102

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USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

determined whether or not individual trees contributed to stocking and crown cover. 

Qualifying species were based solely on regional FIA tally species lists (USDA Forest 

Service 2000-2005a). In essence, the overall tree-form potential of a species within the 

entire Interior West was built into the species list decision. 

As a result, an increase in forest land due to the tree-form criteria would be expected 

between 1993 and 2006. For example, the current apparent increase in the deciduous 

oak woodland type (see Section IV), a species that is often shrub form, is probably 

caused by eliminating the tree-form criteria. In addition, since tree form is often internationally considered an important part of forest land definitions (e.g. Kyoto protocols), 

and given the marginal sites that many woodland species occupy in the Interior West, 

IWFIA is currently collecting a regional tree-form variable. This could potentially serve 

as a combined climatic and edaphic indicator for woodland site productivity and other 

stress-related influences.

Species—As mentioned above, past definitions considered form within a species 

to be a constituent of forest land potential; whereas, annual inventories now reference 

tree species lists, regardless of form. Some species previously considered as forest 

trees (Rocky Mountain maple and true mountain mahogany) are no longer considered 

valid forest tree species in the Interior West. In addition, other species previously not 

considered (mesquite) are now included on IWFIA’s tree species list. The net effect of 

this on forest land is probably minimal since these species are somewhat infrequently 

encountered in Utah. However, this explains why some species may or may not be 

included in a particular inventory.

Other Factors—In addition, other factors may have had significant influences on 

trend comparisons. Since it is impractical to physically field visit every hex-grid plot in 

the Interior West, our prefield protocols have long depended on remotely sensed imagery 

for distinguishing non-visit plots from potential forest land plots. Past inventories were 

often constrained to using low-quality imagery for identification of potential forest land, 

possibly causing marginally forested or nonstocked lands to get missed during the prefield examination. The expected result would be a potential increase in forest land in 

subsequent inventories as better imagery became available statewide. 

Another factor affecting comparisons to the past are shifts in area between forest 

types due to changing forest type algorithms. Most IWFIA periodic inventories used a 

5 percent cover threshold for timber types regardless of the amount of woodland species 

cover; whereas, annual inventories use the plurality of stocking to distinguish between 

timber and woodland forest types. This has a tendency to shift some area from timber 

types to woodland types when comparing periodic to annual inventories (see Appendix 

C for periodic to annual forest type crosswalk lists).

Plot-Filtering and the Definition of Forest and Other Wooded Lands

Other than land use, the three main factors that influence FIA’s definition of forest 

land are cover/stocking, past disturbance, and regeneration—meaning that the sample 

acre either currently, formerly, or will in the future meet the definition of forest land. 

Observations or measurements are made by IWFIA field crews to determine whether 

thresholds for any of these three factors are met on the ground, based on the condition sample acre. In the past, generally, if any of the three factors met the appropriate 

threshold the condition was classified as forest land. However, other than the decision 

to measure the plot, it was unknown which of the factors, or combination of factors, 

were the definitive reason for classifying plots as forest land, since these factors were 

not documented. 
103

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USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

As previously mentioned, plot-filtering was a retroactive process that classified all 

annual IWFIA plots according to current live tree crown cover, missing crown cover 

(disturbance), and seedlings per acre. Subsequently, these three regional variables were 

used to separate forest from other wooded land. These three variables were designed 

to address the above factors that influence FIA’s definition of forest land and are currently collected at the condition level on all IWFIA field plots. All three variables are 

recorded as whole numbers, allowing any definitional threshold to be applied for more 

flexible analysis. 

Under this paradigm, forest land is filtered in the IWFIA database as conditions with 

live plus missing crown cover greater than or equal to 10 percent, or greater than or 

equal to 200 seedlings per acre. Other wooded land is filtered in the IWFIA database 

as conditions with 5 to 9 percent live plus missing crown cover, or 40 to 199 seedlings 

per acre. Although other wooded land does not meet FIA’s national standards for forest 

land, it is an important ecotone between forest and nonforest land that continues to be 

measured by IWFIA (see Sections IV and V).
104

Appendix B

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Appendix B—Common Name, Scientific Name, and Timber (T) or 

Woodland (W) Designation for Trees 

Aspen (Populus tremuloides) T

Bigtooth maple (Acer grandidentatum) W

Blue spruce (Picea pungens) T

Common or twoneedle pinyon (Pinus edulis) W

Curlleaf mountain-mahogany (Cercocarpus ledifolius) W

Douglas-fir (Pseudotsuga menziesii) T

Engelmann spruce (Picea engelmannii) T

Fremont cottonwood (Populus fremontii) T

Gambel oak (Quercus gambelii) W

Great Basin bristlecone pine (Pinus longaeva) T

Limber pine (Pinus flexilis) T

Lodgepole pine (Pinus contorta) T 

Narrowleaf cottonwood (Populus angustifolia) T

Ponderosa pine (Pinus ponderosa) T

Rocky Mountain juniper (Juniperus scopulorum) W 

Singleleaf pinyon (Pinus monophylla) W

Subalpine fir (Abies lasiocarpa) T

Utah juniper (Juniperus osteosperma) W

White fir (Abies concolor) T
105

Appendix C

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Appendix C—Forest Type Groups, Forest Type Names—Annual and 

(Periodic), and Timber (T) or Woodland (W) Designation for Forest Type

Aspen-birch group

Aspen (Aspen) T

Douglas-fir group

Douglas-fir (Douglas-fir) T

Elm-ash-cottonwood group

Cottonwood (Cottonwood) T

Fir-spruce-mountain hemlock group

Blue spruce (Blue spruce) T

Engelmann spruce (Engelmann spruce) T

Engelmann spruce-subalpine fir (Spruce-fir) T

Subalpine fir (Spruce-fir) T

White fir (White fir) T

Lodgepole pine group

Lodgepole pine (Lodgepole pine) T 

Nonstocked

Nonstocked (only as stand-size class) T or W

Other western hardwoods group

Cercocarpus woodland (Mountain mahogany) W

Intermountain maple woodland (Maple woodland) W

Other western softwoods group

Foxtail pine-bristlecone pine (grouped with spruce-fir) T

Limber pine (Limber pine) T

Pinyon-juniper group

Juniper woodland (Juniper) W

Pinyon-juniper woodland (Pinyon-juniper) W

Rocky Mountain juniper (Juniper) W 

Ponderosa pine group

Ponderosa pine (Ponderosa pine) T

Western oak group

Deciduous oak woodland (Oak) W
106

Appendix D

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Appendix D—Volume, Biomass, and Site Index Equation Sources

Volume

Chojnacky (1985) was used for bigtooth maple, curlleaf mountain-mahogany, gamble 

oak, and singleleaf pinyon pine volume estimation.

Chojnacky (1994) was used for common or twoneedle pinyon pine, Rocky Mountain 

juniper, and Utah juniper volume estimation.

Edminster and others (1980) was used for ponderosa pine volume estimation in 

northeastern Utah.

Edminister and others (1982) was used for aspen volume estimation in northeastern 

Utah.

Hann and Bare (1978) was used for aspen, blue spruce, Douglas-fir, Engelmann spruce, 

Great Basin bristlecone pine, limber pine, lodgepole pine, ponderosa pine, subalpine 

fir, and white fir volume estimation in southwestern Utah.

Kemp (1956) was used for Fremont and narrowleaf cottonwood volume estimation.

Myers (1964) was used for limber and lodgepole pine volume estimation in northeastern Utah.

Myers and Edminister (1972) was used for blue spruce, Douglas-fir, Engelmann 

spruce, subalpine fir, and white fir volume estimation in northeastern Utah.

Biomass

Chojnacky (1984) was used for curlleaf mountain mahogany biomass estimation.

Chojnacky (1992). was used for bigtooth maple and gamble oak biomass estimation.

Chojnacky and Moisen (1993) was used for all juniper and pinyon species biomass 

estimation.

Van Hooser and Chojnacky (1983) was used for all timber (T) species biomass estimation.

Site Index

Brickell (1970) was used for blue spruce, Douglas-fir, Engelmann spruce, Great 

Basin bristlecone pine, limber pine, lodgepole pine, ponderosa pine, and subalpine fir 

site index estimation.

Edminster and others (1985) was used for aspen, and Fremont and narrowleaf cottonwood site index estimation.

Stage (1966, 1969) was used for white fir site index estimation. [Original equations 

were reformulated by John Shaw; documentation on file at U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, UT.]
107

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Appendix E—List of Tables and Appendix E Tables

List of Text Tables

Table 1—Total area by ownership class and land class, Utah, cycle 2, 2000-2005.

Table 2—Area of timber/woodland types by forest type and land class, Utah, cycle 2, 

2000-2005.

Table 3—Area of forest and other-wooded land by reserved status, ownership class, 

and productivity, Utah, cycle2, 2000-2005.

Table 4—Number of snags by diameter class and snags per acre (number of snags at least 

the minimum diameter ÷ 17,962,455 acres) on forest land, Utah, cycle 2, 2000-2005.

Table 5—Net volume (cubic-feet) and biomass (tons) per acre of live trees by forest 

type on forest land, Utah, cycle 2, 2000-2005.

Table 6—Maximum SDI by forest type, cycle 2, Utah, 2000-2005.

Table 7—QA Results for Condition-Level Variables from 84 Conditions in Utah, cycle 

2, 2001 to 2005.

Table 8—QA Results for Tree Variables from 1301 Trees in Utah, cycle 2, 2001 to 2005.

Table 9—Number of live trees 5.0 inches diameter and greater by species and number 

of damages, Utah, cycle 2, 2000-2005.

Table 10—Removals from nonreserved timberland by species and product, Utah, 2002, 

from RPA-TPO data calculated by BBER from FIDACS data.

Table 11—Removals from nonreserved timberland by species and owner, Utah, 2002.

Table 12—Removals from nonreserved timberland by owner and product, Utah, 2002.

Table 13—Active Utah Primary Wood Products Facilities by County and Product, 2002.

Table 14—Timber Received by Utah Forest Products Industry by Ownership Class 

and Product, 2002.

List of Appendix E Tables

Table 1—Percentage of area by land status, Utah, cycle 2, 2000-2005.

Table 2—Area of accessible forest land by owner class and forest land status, Utah, 

cycle 2, 2000-2005.

Table 3—Area of accessible forest land by forest type group and productivity class, 

Utah, cycle 2, 2000-2005. 

Table 4—Area of accessible forest land by forest type group, ownership group, and 

land status, Utah, cycle 2, 2000-2005.

Table 5—Area of accessible forest land by forest type group and stand-size class, Utah, 

cycle 2, 2000-2005.

Table 6—Area of accessible forest land by forest type group and stand-age class, Utah, 

cycle 2, 2000-2005.

Table 7—Area of accessible forest land by forest type group and stand origin, Utah, 

cycle 2, 2000-2005.

Table 8—Area of forest land by forest type group and primary disturbance class, Utah, 

cycle 2, 2000-2005.
108

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Table 9—Area of timberland by forest type group and stand-size class, Utah, cycle 2, 

2000-2005.

Table 10—Number of live trees on forest land by species group and diameter class, 

Utah, cycle 2, 2000-2005.

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

class, Utah, cycle 2, 2000-2005.

Table 12—Net volume of all live trees by owner class and forest land status, Utah, 

cycle 2, 2000-2005.

Table 13—Net volume of all live trees on forest land by forest type group and standsize class, Utah, cycle 2, 2000-2005.

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

group, Utah, cycle 2, 2000-2005.

Table 15—Net volume of all live trees on forest land by species group and diameter 

class, Utah, cycle 2, 2000-2005.

Table 16—Net volume of all live trees on forest land by forest type group and stand 

origin, Utah, cycle 2, 2000-2005.

Table 17—Net volume of growing stock trees on timberland by species group and 

diameter class, Utah, cycle 2, 2000-2005.

Table 18—Net volume of growing stock trees on timberland by species group and 

ownership group, Utah, cycle 2, 2000-2005.

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

by species group and diameter class, Utah, cycle 2, 2000-2005.

Table 20—Net volume of sawtimber trees on timberland by species group and ownership group, Utah, cycle 2, 2000-2005.

Table 21—Average annual net growth of all live trees by owner class and forest land 

status, Utah, cycle 2, 2000-2005.

Table 22—Average annual net growth of all live trees on forest land by forest type 

group and stand-size class, Utah, cycle 2, 2000-2005.

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

and ownership group, Utah, cycle 2, 2000-2005.

Table 24—Average annual net growth of growing stock trees on timberland by species 

group and ownership group, Utah, cycle 2, 2000-2005.

Table 25—Average annual mortality of all live trees by owner class and forest land 

status, Utah, cycle 2, 2000-2005.

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

and stand-size class, Utah, cycle 2, 2000-2005.

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

and ownership group, Utah, cycle 2, 2000-2005.

Table 28—Average annual mortality of growing stock trees on timberland by species 

group and ownership group, Utah, cycle 2, 2000-2005.

Table 29—Aboveground dry weight of all live trees by owner class and forest land 

status, Utah, cycle 2, 2000-2005.

Table 30—Aboveground dry weight of all live trees on forest land by species group 

and diameter class, Utah, cycle 2, 2000-2005.
109

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Table 31—Area of accessible forest land by Forest Survey Unit, county and forest land 

status, Utah, cycle 2, 2000-2005.

Table 32—Area of accessible forest land by Forest Survey Unit, county, ownership 

group and forest land status, Utah, cycle 2, 2000-2005.

Table 33—Area of timberland by Forest Survey Unit, county and stand-size class, Utah, 

cycle 2, 2000-2005.

Table 34—Area of timberland by Forest Survey Unit, county and stocking class, Utah, 

cycle 2, 2000-2005.

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, Utah, cycle 2, 

2000-2005.

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, 

Utah, cycle 2, 2000-2005.

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, Utah, cycle 2, 2000-2005.

List of Appendix F Tables:

Table 1—Mean properties of forest floor by forest type, Utah, cycle 2, 2000-2004.

Table 2—Mean physical properties of soil cores by forest type, Utah, cycle 2, 2000-2004.

Table 3—Mean chemical properties of soil cores by forest type, Utah, cycle 2, 2000-2004.

Table 4—Mean chemical properties of soil cores by forest type, Utah, cycle 2, 2000-2004.
110

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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, Utah, cycle 2, 2000-2005.

Total area (thousands of acres)

Timberland 6.9

 21.1

Total unreserved forest land 28.0

Productive 0.8

Total reserved forest land 3.3

Nonforest and other-wooded land 62.2

Non-Census 0.1

Access denied 1.0

All land

 54,335

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 0.3

Hazardous conditions 1.7

All nonforest and other land 65.6

Census 3.3

All accessible forest land 31.3

Unproductive 2.5

Appendix E tables
111

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Forest Service Other federal State and local government

Private

National ForestOther National ForestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceDepartment of Defense or EnergyStateLocal (county, municipal, etc.)Undifferentiated private

 2,995.2

 - - - -

 140.6

 - - - -

 154.2

 11.3

 690.5

Table 2--Area of accessible forest land by owner class and forest land status, Utah, cycle 2, 2000-2005.

(In thousand acres)

 2,736.6

 - - - -

 5,740.0

 - -

 10.0

 1,261.0

 - -

 2,319.0

 5,731.8

 - - - -

 5,880.6

 - -

 10.0

 1,415.2

 11.3

 3,009.6

 398.8

 - -

 64.9 10.2

 - - - - - - - - - -

(Table 2 continued on next page)

 3,991.8 12,066.6 16,058.3 473.9 All owners 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 120.9

 7.4

 280.3 909.0

 10.9

 - -

 98.5

 - -

 3.1

 519.7

 7.4

 345.2 919.2

 10.9

 - -

 98.5

 - -

 3.1

 6,251.5

 7.4

 345.2

 6,799.8

 10.9 10.0

 1,513.7

 11.3

 3,012.7

 1,430.2 1,904.1 17,962.5

 Owner class Timberland Unproductive Total Productive

Unreserved forests Reserved forests

Unproductive Total

All

forest land

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 10,210.5

 9.2

 - -

 14.7

 - -

 7.1

 10.1

 140.2

 1,986.9

 654.8 463.3

Table 3--Area of accessible forest land by forest type group and productivity class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 - -

 472.1 338.6 890.2 393.2

 40.1 19.1

 1,158.5

 - - - -

 61.6

 - -

 145.7

 49.8

 484.0

 - - - -

 2.3

 341.7

 - - - -

 10.9

 - -

 23.4

 - -

 34.6

 - - - - - - - - - - - - - -

(Table 4 continued on next page)

 13,496.8 3,373.3 1,034.4 58.0 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 lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - - - - - - - - - -

 - - - - - - - - - - - - - - - - - - - - - -

 - - - - - - - - - - - - - - - - - - - - - -

 - - - - - -

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

 17,962.5

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+
112

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 - -

 348.9 255.8

 1,082.0

 298.1

 31.7

 3.0

 933.2

 - - - -

 42.6

Table 4--Area of accessible forest land by forest type group, ownership group, and land status, Utah, cycle 2, 2000-2005.

(In thousand acres)

 1,553.2

 49.9

 8.3

 217.6

 81.8

 7.1

 - -

 130.4 789.2 310.9 115.3

 - -

 69.4 30.8

 8.3

 - - - -

 6.3

 10.9

 - - - -

 15.0

 6,215.8

 9.2

 50.5

 9.6

 - -

 5.8

 10.1

 - -

 340.9 143.3 240.1

(Table 4 continued on next page)

 2,995.2 3,263.7 140.6 7,025.2 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 lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 - -

 48.7

 9.4

 18.6

 - - - - - -

 88.6

 - - - - - -

 1,125.9

 - - - - - - - - - - - - - -

 167.1

 33.6 33.0

 165.4 1,359.5 690.5 17,962.5 2,322.2

 - -

 124.4

 33.7 87.3 13.3

 2.7

 12.2

 412.0

 - - - -

 5.0

 1,315.6

 - - - - - - - - - - - -

 65.1

 689.7 167.1

 84.7

 Forest type group

Timberland

Other

forest

land

Timberland

Other

forest

land

Forest Service

Timberland

Other

forest

land

Timberland

Other

forest

land

All

forest

land

Other federal

State and local

government

Undifferentiated 

private

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 9,694.5

 547.4 369.9

 1,117.3

 157.8

 39.1 20.7

 315.9

 20.5

 344.3

 - -

Table 5--Area of accessible forest land by forest type group and stand-size class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 219.3

 53.5

 9.2

 150.6 173.2

 8.1 1.3

 1,014.3

 146.0 116.4

 - -

 296.7

 49.6

 9.2

 155.6

 62.2

 - -

 9.5

 310.1

 1,820.4

 194.2

 - -

 - - - - - - - - - - - - - - - - - - - - - -

(Table 5 continued on next page)

 12,627.3 1,892.0 2,907.5 - - 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 lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - - - - - - - -

 535.7

 535.7

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

 17,962.5

Large

diameter

Medium

 diameter

Small

diameter Chaparral

Stand-size class

 Forest type group Non stocked

All size

classes
113

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Pinyon-juniper group Douglas-fir group Ponderosa pine group Fir-spruce-mountain hemlock group Lodgepole pine group Other western softwoods group Elm-ash-cottonwood group Aspen-birch group Western oak group Other western hardwoods group Nonstocked - - - - - - - - - - - - - - - - - - - - 535.7Table 6--Area of accessible forest land by forest type group and stand-age class, Utah, cycle 2, 2000-2005. (In thousand acres) 181.8 42.5 - - 60.9 32.1 - - 9.5 163.3 1,560.5 165.5 - - 122.4 7.1 9.2 79.6 10.1 - - 1.3 122.7 218.9 34.3 - - 377.4 10.6 9.2 55.7 8.0 - - - - 100.7 34.2 35.7 - - (Table 6 continued on next page) 535.7 2,216.0 605.7 631.5 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.

 802.1

 74.8

 104.3

 80.9 29.8

 - -

 2.3

 556.9

 50.1 31.9

 - -

 1,064.7

 162.5

 69.8

 168.1

 83.4

 8.1 8.3

 420.3

 74.1 82.2

 - -

 1,211.8

 134.9

 47.9

 322.5

 87.7

 - -

 10.1

 171.8

 23.2 50.2

 - -

 1,733.1 2,141.5 2,060.2

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

 17,962.5

 1,348.5

 93.9 38.7

 129.0

 50.5 14.6

 - -

 73.5 16.3

 134.7

 - -

 1,032.2

 66.4 30.0

 253.5

 20.4

 - - - -

 31.2

 9.6

 61.0

 - -

 818.3

 35.9

 5.9

 91.9 30.3

 - - - - - - - -

 51.6

 - -

 1,029.1

 - -

 10.2 85.8

 - -

 7.1

 - - - - - -

 7.9

 - -

 2,221.9

 21.8 63.2 95.6 40.9 17.4

 - - - - - - - - - -

 1,899.7 1,504.4 1,033.9 1,140.1 2,460.8

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+

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 10,210.5

 650.5 379.2

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

Table 7--Area of accessible forest land by forest type group and 

 stand origin, Utah, cycle 2, 2000-2005.

(In thousand acres)

 - - - -

 9.2

 - - - - - - - - - - - - - - - -

(Table 7 continued on next page)

 17,953.2 9.2 All forest type groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates theacres round to less than 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

 17,962.5

Natural

stands

Artificial

 regeneration

Stand origin

 Forest type group

All forest

land
114

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 9,667.4

 556.2 367.0

 1,155.2

 332.8

 47.2 27.0

 1,473.3 1,805.7

 628.3 337.6

Table 8--Area of forest land by forest type group and primary disturbance class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 205.1

 15.6

 - -

 106.1

 31.1

 - - - -

 21.7 10.2

 - - - -

 73.6 40.2

 - -

 59.5 20.7

 - - - -

 72.2

 2.4

 - - - -

 92.3

 9.2

 - -

 70.2

 - - - -

 1.3

 12.5 10.2

 - - - -

(Table 8 continued on next page)

 16,397.7 389.8 268.7 195.8 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 lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 47.8

 7.1

 21.4 10.2

 - - - - - -

 28.9 78.2 10.3

 182.6

 101.3

 10.1

 - - - - - - - - - -

 31.6 80.1 16.3 15.4

 - -

 11.9

 - - - - - - - -

 3.2 0.2

 - - - - - -

 386.6 254.8 15.3

 10,210.5

 650.5 388.4

 1,423.4

 393.2

 47.2 31.6

 1,640.3 1,986.9

 654.8 535.7

 17,962.5

 11.1

 - - - - - -

 8.5

 - - - - - - - - - - - -

 19.6

 11.9

 - - - -

 22.2

 - - - - - - - - - - - - - -

 34.1

 Forest type group

All forest

land None Insects Disease Weather

Disturbance class

Fire

Domestic

animals

Wild

animals Human Other

Douglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupNonstocked

 497.5 311.2 927.8

 76.0 26.2 10.6

 299.5

 - -

Table 9--Area of timberland by forest type group and stand-size class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 53.5

 9.2

 148.4 173.2

 8.1 1.3

 925.5

 - -

 40.4

 9.2

 120.1

 62.2

 - -

 9.5

 219.7

 - -

 - - - - - - - - - - - - - - - -

(Table 5 continued on next page)

 2,148.8 1,319.3 461.1 - - 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 lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - -

 62.6 62.6

 591.4 329.6

 1,196.3

 311.4

 34.3 21.4

 1,444.8

 62.6

 3,991.8

Large

diameter

Medium

 diameter

Small

diameter Chaparral

Stand-size class

 Forest type group Non stocked

All size

classes
115

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Western softwood species groups Western hardwood species groups Table 10--Number of live trees on forest land by species group and diameter class, Utah, cycle 2, 2000-2005. (In thousand trees)

(Table 10 continued on next page)

 680,713 451,430 300,537 214,401 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 lessthan 1 thousand trees. Columns and rows may not add to their totals due to rounding.

 155,105 8,363,995

Softwood species groupsHardwood species groups

 428,183 252,531

 316,257 135,173

 236,274

 64,262

 181,583

 32,819

 139,457

 15,648

 3,413,538 4,950,456

All softwoodsAll hardwoods

 100,877

 5,775

 65,047

 3,780

 45,862

 1,610

 50,402

 862

 20,654

 123

 8,311

 - -

 2,682

 - -

 1,338

 - -

 106,653 68,827 47,472 51,263 20,777 8,311 2,682 1,338

 630,234 710,599

 1,340,833

 1,186,378 3,727,274 4,913,651

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

 3,559 1,638 3,748 3,318 1,076

 51,322

 386

 1,798 1,982

 2,216 1,195 2,185 2,622

 539

 36,885

 220

 1,228

 383

 2,637 1,723 2,433 3,063

 182

 40,053

 310 408 453

 609 370 785

 1,026

 17,793

 72

 123

 283 294 201 233

 7,301

 72

 168 228 114

 2,101

 57 76 84

 1,050

 72

 217,706

 50,077

 590,316 198,032 329,892

 2,006,411

 21,104

 738,619

 4,211,837

 79,960

 9,381

 330,109

 63,703

 114,608 581,513

 7,104

 276,237

 3,451,036

 40,745

 9,564

 99,400 43,362 83,786

 348,286

 5,092

 177,241 533,359

 24,035

 6,416

 58,244 25,371 64,895

 246,892

 2,330

 121,944 130,587

 14,154

 4,162

 22,853 13,029 15,246

 165,238

 1,591

 41,895 22,368

 21,642

 5,848

 37,777 18,046 33,087

 198,173

 1,684

 83,644 51,529

 10,604

 3,756

 16,852

 9,755 9,462

 129,791

 1,364

 20,229 12,590

 9,290 3,097 9,412 8,047 4,935

 104,202

 474

 10,393

 5,255

 7,845 2,388 6,007 6,344 2,076

 75,812

 405

 3,602 2,174

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

- -- -- -- -

- -- -- -- -

- -- -- -- -

- -- -

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineOther western softwoodsCottonwood and aspen

 18,907

 4,713

 50,049 17,934 58,872

 1,468

 94,121

Table 11--Number of growing stock trees on timberland by species group and diameter class, Utah, cycle 2, 2000-2005.

(In thousand trees)

 16,575

 4,662

 33,133 12,699 27,622

 1,228

 68,921

 11,352

 3,286

 19,796

 9,562

 11,244

 1,018

 35,505

 8,958 3,098

 15,091

 7,227 4,496

 789

 18,209

(Table 11 continued on next page)

 246,064 164,838 91,763 57,868 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 lessthan 1 thousand trees. Columns and rows may not add to their totals due to rounding.

 7,059 2,622 8,095 5,864 2,524

 362

 9,825

 75,526 23,847

 139,404

 65,883

 106,473

 5,804

 232,777

 36,351 649,713

Softwood species groupsHardwood species groups

 151,943

 94,121

 95,918 68,921

 56,258 35,505

 39,659 18,209

 26,526

 9,825

 416,936 232,777

All softwoodsAll hardwoods

 6,064 1,926 5,043 4,394

 954 222

 3,352

 2,427 1,208 3,283 2,491

 583 271

 1,478

 1,809

 721

 1,710 2,191

 115

 55

 1,084

 1,717 1,052 2,078 2,391

 64

 248 281

 374 198 671 905

 72

 211 172 143 169

 72

 112 228

 56

 76 84 72

 18,604

 3,352

 10,263

 1,478

 6,602 1,084

 7,549

 281

 2,220

 - -

 696

 - -

 467

 - -

 232

 - -

 21,955 11,742 7,687 7,830 2,220 696 467 232

- -- -

- -- -- -

- -- -- -

- -- -- -- -

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
116

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Forest ServiceOther federalState and local governmentPrivate

National ForestOther National ForestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceDepartment of Defense or EnergyStateLocal (county, municipal, etc.)Undifferentiated private

 5,758.2

 - - - -

 142.5

 - - - -

 256.2

 23.4

 1,057.0

Table 12--Net volume of all live trees 5.0" diameter and greater by owner class and forest land status, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 1,440.9

 - - - -

 3,221.5

 - -

 1.1

 683.4

 - -

 1,117.6

 7,199.1

 - - - -

 3,364.0

 - -

 1.1

 939.6

 23.4

 2,174.7

 1,070.1

 - -

 85.7

 2.8

 - - - - - - - - - -

(Table 12 continued on next page)

 7,237.2 6,464.6 13,701.8 1,158.6 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.

 55.3

 2.8

 147.8 539.2

 14.6

 - -

 56.9

 - - - -

 1,125.4

 2.8

 233.4 542.1

 14.6

 - -

 56.9

 - - - -

 8,324.5

 2.8

 233.4

 3,906.1

 14.6

 1.1

 996.5

 23.4

 2,174.7

 816.6 1,975.2 15,677.0

Timberland Unproductive Total Productive

Unreserved forests

 Owner class

Reserved forests

Unproductive Total

All

forest land

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

 6,434.0 1,141.3

 542.7

 2,936.9

 484.2

 51.1 18.9

 1,012.7

 43.4

 192.7

 - -

Table 13--Net volume of all live trees 5.0" diameter and greater on forest land by forest type group and stand-size class, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 66.1 49.6

 3.6

 170.9 367.7

 12.6

 0.4

 1,484.5

 104.0

 76.5

 - -

 29.6 10.6

 3.2

 39.4 50.4

 - -

 2.0

 79.9

 194.8

 54.2

 - -

 - - - - - - - - - - - - - - - - - - - - - -

(Table 13 continued on next page)

 12,857.9 2,335.7 464.1 - - 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - - - - - - - -

 19.3 19.3

 6,529.7 1,201.4

 549.5

 3,147.2

 902.2

 63.7 21.3

 2,577.1

 342.3 323.4

 19.3

 15,677.0

Large

diameter

Medium

 diameter

Small

diameter Chaparral

Stand-size class

 Forest type group Non stocked

All size

classes
117

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

 962.4 435.9

 1,449.6 1,604.9 1,058.2 1,200.5

 87.4

 1,343.0

 185.2

Table 14--Net volume of all live trees 5.0" diameter and greater on forest land by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 154.0 107.7

 41.3

 0.5

 - -

 3,737.6

 5.7

 15.0 93.5

 111.0

 22.3 39.3

 - - - -

 683.2

 - -

 130.6

 33.5

(Table 14 continued on next page)

 8,327.3 4,155.2 1,019.9 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 235.9

 44.2

 231.2

 29.9 81.1

 846.5

 3.8

 492.5 209.6

 1,463.3

 610.1

 1,761.5 1,635.2 1,139.4 6,467.7

 96.9

 1,981.1

 521.9

 2,174.7 15,677.0

Softwood species groupsHardwood species groups

 6,799.0 1,528.3

 4,046.7

 108.5

 855.7 164.1

 1,472.6

 702.1

 13,174.0

 2,503.0

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group
118

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

 40

 8

 98 43

 189 239

 3

 236 165

Table 15--Net volume of all live trees on forest land by species group and diameter class, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 99 21

 176

 92

 236 411

 6

 424 128

 124

 28

 209 131 203 598

 11

 413

 87

 159

 46

 260 163 190 733

 14

 341

 59

(Table 15 continued on next page)

 1,022 1,593 1,805 1,964 All species groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to lessthan 1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 209

 62

 211 204 143 787

 8

 255

 30

 1,463

 610

 1,761 1,635 1,139 6,468

 97

 1,981

 522

 1,908 15,677

Softwood species groupsHardwood species groups

 621 401

 1,042

 552

 1,305

 500

 1,565

 400

 1,623

 285

 13,174

 2,503

All softwoodsAll hardwoods

 243

 63

 191 234

 79

 756

 8

 126

 19

 147

 63

 166 162

 53

 638

 12 79 19

 118

 56

 120 155

 31

 571

 5

 77

 5

 196 120 164 270

 14

 777

 15 30

 7

 53 43 78

 125 495

 4 3

 50 45 30 28

 270

 9

 35 41 27

 106

 16 20 16 87 11

 1,575

 145

 1,242

 99

 1,056

 82

 1,557

 37

 797

 3

 424

 - -

 218

 - -

 150

 - -

 1,719 1,340 1,138 1,594 801 424 218 150

- -- -

- -- -- -- -

- -- -- -- -

- -- -- -- -

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
119

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Pinyon-juniper group Douglas-fir group Ponderosa pine group Fir-spruce-mountain hemlock group Lodgepole pine group Other western softwoods group Elm-ash-cottonwood group Aspen-birch group Western oak group Other western hardwoods group

Nonstocked

 6,529.7 1,201.4

 546.3

 3,147.2

 902.2

 63.7 21.3

 2,577.1

 342.3 323.4

 19.3

Table 16--Net volume of all live trees 5.0" diameter and greater on forest land by forest 

type group and stand origin, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 - - - -

 3.2

 - - - - - - - - - - - - - - - -

(Table 7 continued on next page)

 15,673.7 3.2 All forest type groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates thevolume rounds to less than 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 6,529.7 1,201.4

 549.5

 3,147.2

 902.2

 63.7 21.3

 2,577.1

 342.3 323.4

 19.3

 15,677.0

Natural

stands

Artificial

 regeneration

Stand origin

 Forest type group

All forest

land

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineOther western softwoodsCottonwood and aspen

 32

 7

 85 32

 174

 3

 197

Table 17--Net volume of growing-stock trees on timberland by species group and diameter class, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 80 17

 156

 66

 201

 5

 368

 104

 23

 185 100 152

 8

 365

 136

 39

 234 124

 95

 8

 311

(Table 17 continued on next page)

 529 893 937 948 All species groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to lessthan 1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 167

 55

 181 153

 77

 6

 246

 1,127

 442

 1,543 1,268

 787

 71

 1,765

 884 7,004

Softwood species groupsHardwood species groups

 333 197

 525 368

 572 365

 636 311

 638 246

 5,239 1,765

All softwoodsAll hardwoods

 193

 53

 162 168

 41

 4

 119

 104

 47

 152 128

 32

 7

 66

 100

 35 98

 135

 8 2

 71

 128

 75

 142 216

 7

 13 23

 36 22 65

 109

 4

 39 25 25 22

 9

 24 41 14

 20 16 11

 622 119

 471

 66

 378

 71

 581

 23

 237

 - -

 111

 - -

 89

 - -

 46

 - -

 741 537 449 604 237 111 89 46

- -- -

- -- -- -

- -- -- -

- -- -- -- -

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
120

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineOther western softwoodsCottonwood and aspen

 751.9 357.6

 1,272.3 1,237.6

 707.1

 68.1

 1,206.6

Table 18--Net volume of growing-stock trees on timberland by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 83.5 27.0 12.3

 0.5

 - -

 0.1 4.9

 92.0 18.4 38.7

 - - - - - -

 117.9

(Table 18 continued on next page)

 5,601.1 128.2 267.1 All species groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume round to lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 199.7

 39.3

 220.0

 29.9 80.0

 2.9

 436.1

 1,127.1

 442.3

 1,543.3 1,267.9

 787.1

 71.1

 1,765.4

 1,007.8 7,004.2

Softwood species groupsHardwood species groups

 4,394.6 1,206.6

 123.3

 4.9

 149.2 117.9

 571.7 436.1

 5,238.7 1,765.4

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group
121

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineOther western softwoodsCottonwood and aspen

Table 19--Net volume of sawtimber trees (International 1/4 inch rule) on timberland by species group and diameter class, Utah, cycle 2, 2000-2005.

(In million board feet)

 364

 77

 734 411 556

 25

 586 176

 1,086

 603 410

 28

 1,533

(Table 19 continued on next 

 2,168 4,421 All species groups 

All table cells without observations in the inventory sample are indicated by --. Table value of 0 indicates the volume rounds to lessthan 1 million board feet. Columns and rows may not add to their totals due to rounding. International 1/4 inch rule.

 784 287 896 809 370

 26

 1,276

 4,995 2,379 6,404 6,289 1,813

 304

 4,368

 4,448 26,552

Softwood species groupsHardwood species groups

 2,168

 - -

 2,888 1,533

 3,172 1,276

 22,184

 4,368

All softwoodsAll hardwoods

 991 296 838 929 214

 20

 654

 558 277 806 713 177

 36

 383

 542 209 505 743

 46 10

 402

 722 456 735

 1,241

 40 66

 120

 186 142 360 629

 23

 241 167 121 127

 21

 156 227

 84

 135

 95 70

 3,288

 654

 2,568

 383

 2,056

 402

 3,261

 120

 1,340

 - -

 655

 - -

 488

 - -

 299

 - -

 3,941 2,951 2,458 3,381 1,340 655 488 299

- -

- -- -

- -- -- -

- -- -- -

- -- -- -- -

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

1

1
122

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineOther western softwoodsCottonwood and aspen

 617.8 322.9 982.7

 1,069.1

 304.7

 59.4

 485.0

Table 20--Net volume of sawtimber trees on timberland by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

 70.8 25.6 10.3

 - - - - - -

 3.0

 79.1 17.0 27.0

 - - - - - -

 57.8

(Table 20 continued on next page)

 3,841.5 109.7 180.8 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 166.3

 37.0

 180.3

 27.0 71.9

 2.2

 148.5

 934.0 402.5

 1,200.3 1,096.2

 376.5

 61.6

 694.3

 633.3 4,765.4

Softwood species groupsHardwood species groups

 3,356.5

 485.0

 106.7

 3.0

 123.0

 57.8

 484.8 148.5

 4,071.0

 694.3

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group
123

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010Forest Service

Other federalState and local governmentPrivate

National ForestOther National ForestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceDepartment of Defense or EnergyStateLocal (county, municipal, etc.)Undifferentiated private

38.6

 - - - -

-1.7

 - - - -

0.10.5

14.6

Table 21--Average annual net growth of all live trees 5.0" diameter and greater by owner class and forest land status, Utah, cycle 2, 2000-2005.

(In million cubic feet)

8.2

 - - - -

9.2

 - -

0.02.5

 - -

11.4

46.8

 - - - -

7.5

 - -

0.02.60.5

26.0

5.4

 - -

-2.1

0.0

 - - - - - - - - - -

(Table 21 continued on next page)

52.1 31.4 83.5 3.3 All owners 

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the volume rounds to lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

-7.9

0.0

-2.7

1.40.0

 - -

-0.1

 - - - -

-2.5

0.0

-4.9

1.50.0

 - -

-0.1

 - - - -

44.3

0.0

-4.9

8.90.00.02.60.5

26.0

-9.2 -5.9 77.6

Timberland Unproductive Total Productive

Unreserved forests

 Owner class

Reserved forests

Unproductive Total

All

forest land
124

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupOther western softwoods groupElm-ash-cottonwood groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

31.210.1

9.5

13.6

4.40.60.5

12.7

0.72.3

 - -

Table 22--Average annual net growth of all live trees 5.0" diameter and greater on forest land by forest type group and stand-size class, Utah, cycle 2, 2000-2005.

(In million cubic feet)

1.80.1

-0.1

-14.9

10.4

0.30.0

30.0

2.92.0

 - -

0.40.40.0

-9.5

0.6

 - -

0.0

-5.3

-13.2

2.1

 - -

 - - - - - - - - - - - - - - - - - - - - - -

(Table 22 continued on next page)

85.4 32.5 -24.5 - - 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - - - - - - - -

-15.9-15.9

33.310.6

9.4

-10.8

15.4

0.80.5

37.4

-9.5

6.4

-15.9

77.6

Large

diameter

Medium

 diameter

Small

diameter Chaparral 

Stand-size class

 Forest type group Non stocked 

All size

classes

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

9.22.10.9

-14.6

15.5

3.80.0

22.7

4.6

Table 23--Average annual net growth of all live trees 5.0" diameter and greater on forest land by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

-1.0-1.7-4.3

0.0

 - -

11.9

0.10.3

-1.1

-0.1-0.5

1.1

 - - - -

1.1

 - -

0.60.9

(Table 23 continued on next page)

44.3 4.1 3.1 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

4.50.8

-1.9

0.30.43.20.1

12.2

6.4

12.5

0.7

-4.3

-14.3

15.920.0

0.2

35.810.9

26.0 77.6

Softwood species groupsHardwood species groups

16.927.4

4.9

-0.7

1.51.5

7.4

18.6

30.846.8

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group
125

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Engelmann and other spruces Lodgepole pine Western woodland softwoods Other western softwoods

Cottonwood and aspenWestern woodland hardwoods

7.66.44.7

-16.8

13.6

 - -

0.2

19.8

 - -

Table 24--Average annual net growth of growing-stock trees on timberland by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

-0.4

0.2

-1.8

0.0

 - - - -

0.00.1

 - -

-0.6-0.5

1.0

 - - - - - - - -

0.3

 - -

(Table 24 continued on next page)

35.6 -1.9 0.2 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

3.70.6

-2.1

0.30.4

 - -

0.0

10.3

 - -

10.4

6.71.9

-16.5

14.0

 - -

0.2

30.5

 - -

13.2 47.2

Softwood species groupsHardwood species groups

15.819.8

-2.0

0.1

-0.1

0.3

2.9

10.3

16.730.5

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group

Forest ServiceOther federalState and local governmentPrivate

National ForestOther National ForestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceDepartment of Defense or EnergyStateLocal (county, municipal, etc.)Undifferentiated private

88.0

 - - - -

4.0

 - - - -

4.80.1

13.4

Table 25--Average annual mortality of all live trees 5.0" diameter and greater by owner class and forest land status, Utah, cycle 2, 2000-2005.

(In million cubic feet)

10.3

 - - - -

17.7

 - - - -

4.0

 - -

5.0

98.4

 - - - -

21.7

 - - - -

8.80.1

18.3

9.5

 - -

3.2

 - - - - - - - - - - - -

(Table 25 continued on next page)

110.3 37.0 147.2 12.7 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.

8.9

 - -

3.91.8

 - - - -

0.4

 - - - -

18.4

 - -

7.21.8

 - - - -

0.4

 - - - -

116.8

 - -

7.2

23.4

 - - - -

9.20.1

18.3

15.1 27.8 175.0

Timberland Unproductive Total Productive

Unreserved forests

 Owner class

Reserved forests

Unproductive Total

All

forest land
126

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Pinyon-juniper groupDouglas-fir groupPonderosa pine groupFir-spruce-mountain hemlock groupLodgepole pine groupAspen-birch groupWestern oak groupOther western hardwoods groupNonstocked

20.110.3

0.2

36.0

2.39.3

 - -

0.4

 - -

Table 26--Average annual mortality of all live trees 5.0" diameter and greater on forest land by forest type group and stand-size class, Utah, cycle 2, 2000-2005.

(In million cubic feet)

0.11.20.3

20.4

0.8

15.8

0.10.0

 - -

0.4

 - - - -

10.9

2.18.3

19.7

0.2

 - -

 - - - - - - - - - - - - - - - - - -

(Table 26 continued on next page)

78.7 38.6 41.5 - - 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

 - - - - - - - - - - - - - - - -

16.216.2

20.611.5

0.5

67.2

5.2

33.419.8

0.6

16.2

175.0

Large

diameter

Medium

 diameter

Small

diameter Chaparral

Stand-size class

 Forest type group Non stocked

All size

classes

Western softwood species groupsWestern hardwood species groups

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

8.45.7

35.639.3

8.47.61.1

10.0

0.7

Table 27--Average annual mortality of all live trees 5.0" diameter and greater on forest land by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

3.93.25.1

 - - - -

15.5

 - - - -

3.0

2.50.80.5

 - - - -

4.4

 - -

1.20.0

(Table 27 continued on next page)

116.8 30.6 9.3 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

1.3

 - -

8.20.10.84.4

 - -

3.20.4

16.0

9.7

49.339.4

9.1

31.8

1.1

14.4

4.0

18.3 175.0

Softwood species groupsHardwood species groups

106.1

10.7

27.6

3.0

8.11.2

14.7

3.6

156.5

18.5

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group
127

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Western softwood species groups Western hardwood species groups Douglas-fir Ponderosa and Jeffrey pines True fir Engelmann and other spruces Lodgepole pine Western woodland softwoods Other western softwoods

Cottonwood and aspenWestern woodland hardwoods

6.80.3

27.336.8

5.9

 - -

0.88.9

 - -

Table 28--Average annual mortality of growing-stock trees on timberland by species group and ownership group, Utah, cycle 2, 2000-2005.

(In million cubic feet)

1.90.12.0

 - - - - - - - - - - - -

2.40.80.5

 - - - - - - - -

1.1

 - -

(Table 28 continued on next page)

86.9 4.0 4.8 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 lessthan 0.1 million cubic feet. Columns and rows may not add to their totals due to rounding.

1.3

 - -

8.20.10.8

 - - - -

2.9

 - -

12.5

1.2

38.036.9

6.7

 - -

0.8

12.9

 - -

13.2 108.9

Softwood species groupsHardwood species groups

78.0

8.9

4.0

 - -

3.71.1

10.4

2.9

96.112.9

All softwoodsAll hardwoods

Forest

Service

Other

federal

State and local

government Species group

Undifferentiated

private

All

owners

Ownership group

Forest ServiceOther federalState and local governmentPrivate

National ForestOther National ForestNational Park ServiceBureau of Land ManagementFish and Wildlife ServiceDepartment of Defense or EnergyStateLocal (county, municipal, etc.)Undifferentiated private

 106,521

 - - - -

 3,110

 - - - -

 5,184

 475

 20,197

Table 29--Aboveground dry weight of all live trees 1.0" diameter and greater by owner class and forest land status, Utah, cycle 2, 2000-2005.

(In thousand dry tons)

 33,847

 - - - -

 62,247

 - -

 28

 14,090

 - -

 27,373

 140,368

 - - - -

 65,357

 - -

 28

 19,274

 475

 47,569

 18,515

 - -

 1,807

 71

 - - - - - - - - - -

(Table 31 continued on next page)

 135,487 137,585 273,071 20,393 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 lessthan 1 thousand dry tons. Columns and rows may not add to their totals due to rounding.

 1,516

 43

 3,012 9,816

 245

 - -

 1,032

 - -

 9

 20,031

 43

 4,819 9,887

 245

 - -

 1,032

 - -

 9

 160,399

 43

 4,819

 75,245

 245

 28

 20,307

 475

 47,579

 15,674 36,067 309,138

Timberland Unproductive Total Productive

Unreserved forests

 Owner class

Reserved forests

Unproductive Total

All

forest land
128

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Western softwood species groupsWestern hardwood species groups

Table 30--Aboveground dry weight of all live trees on forest land by species group and diameter class, Utah, cycle 2, 2000-2005.

(In thousand dry tons)

(Table 32 continued on next page)

 23,213 30,711 32,995 34,949 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 lessthan 1 thousand dry tons. Columns and rows may not add to their totals due to rounding.

 33,589 309,138

Softwood species groupsHardwood species groups

 13,567

 9,646

 19,239 11,472

 22,885 10,110

 26,801

 8,148

 27,782

 5,807

 242,647

 66,491

All softwoodsAll hardwoods

 26,804

 2,955

 21,164

 2,354

 18,087

 1,581

 15,180

 524

 11,385

 376

 8,672

 82

 4,609

 113

 13,467

 - -

 29,759 23,518 19,668 15,705 11,761 8,754 4,722 13,467

 8,672 7,291

 15,963

 4,332 6,033

 10,366

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

 2,795 1,247 2,618 2,331

 824

 11,146

 203

 1,377

 977

 2,185 1,150 1,934 2,281

 492

 9,929

 116

 1,328

 253

 1,917 1,598 1,462 2,208

 129

 7,741

 125 239 285

 1,693

 829

 1,231 1,567

 102

 5,833

 130 254 122

 954 470 910

 1,098 5,168

 72 82

 65

 380 332 682

 3,150

 113

 1,338 2,006 1,444

 809

 7,682

 188

 29,896 12,498 33,457 25,953 21,308

 117,588

 1,946

 36,464 30,027

 440

 47

 1,789

 382 573

 1,066

 36

 552

 5,481

 998 191

 2,137

 932

 1,676 2,636

 102

 1,684 5,607

 1,055

 265

 2,236

 975

 3,978 4,959

 100

 4,083 5,562

 2,553

 552

 3,547 2,111 3,166

 10,754

 201

 7,142 2,968

 2,185

 436

 3,252 1,629 3,823 7,793

 121

 7,262 4,210

 3,130

 884

 4,160 2,511 3,014

 12,832

 269

 5,884 2,264

 4,004 1,197 3,391 3,039 2,278

 13,730

 141

 4,488 1,319

 4,584 1,246 3,014 3,397 1,252

 13,168

 143

 2,172

 784

Douglas-firPonderosa and Jeffrey pinesTrue firEngelmann and other sprucesLodgepole pineWestern woodland softwoodsOther western softwoodsCottonwood and aspenWestern woodland hardwoods

- -- -- -

- -- -- -

- -- -
129

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 Box Elder Cache Davis Morgan Rich Salt Lake Summit Tooele Utah Wasatch Weber

DaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan JuanBeaverGarfieldIronKaneWashington

 8.3

 129.4

 11.3 93.2 69.7 37.1

 425.9

 12.2

 197.7 345.8

 48.2

 194.7 356.7 209.9

 14.3 54.4 89.2

 169.6 205.5

 61.1

 147.2 106.8 109.5 142.3

 42.9

 424.8 124.6 130.5

 29.3

Table 31--Area of accessible forest land by Forest Survey Unit, county and forest land status, Utah, cycle 2, 2000-2005.

(In thousand acres)

 327.6 130.8

 11.3

 113.7

 14.5 74.1

 210.9 381.5 506.9 147.3 103.3 111.6 566.0 675.3 409.1 607.8 160.2 361.6 487.6 173.3 354.7 614.3 737.6

 1,476.9

 699.8 710.0 764.0 528.9 606.4

 336.0 260.2

 22.5

 206.8

 84.2

 111.2 636.8 393.6 704.6 493.1 151.5 306.3 922.7 885.2 423.3 662.1 249.4 531.2 693.1 234.3 501.8 721.1 847.1

 1,619.2

 742.7

 1,134.7

 888.5 659.5 635.7

 7.0

 35.3

 - - - - - -

 24.0 97.8 10.0

 8.9

 - - - - - -

 176.6

 - -

 9.5

 - - - - - - - - - - - - - - - -

 5.9

 - -

 25.8 11.9 20.4 40.9

 - -

 15.4

 - - - - - -

 17.5 10.6

 8.8

 11.9

 - - - - - -

 2.6

 36.7

 9.5 7.4

 - - - - - -

 69.4

 - - - -

 3.1

 85.4

 - -

 376.4

 7.2

 698.4

 69.8

 7.0

 50.7

 - - - - - -

 41.5

 108.4

 18.8 20.8

 - - - - - -

 179.2

 36.7 19.0

 7.4

 - - - - - -

 69.4

 - - - -

 3.1

 91.3

 - -

 402.2

 19.1

 718.8 110.7

 342.9 310.9

 22.5

 206.8

 84.2

 152.7 745.2 412.4 725.4 493.1 151.5 306.3

 1,101.9

 921.9 442.3 669.5 249.4 531.2 693.1 303.7 501.8 721.1 850.2

 1,710.5

 742.7

 1,536.9

 907.6

 1,378.3

 746.4

Timberland Unproductive Total Productive

Unreserved forests

 Forest Survey Unit and county

Reserved forests

Unproductive Total

All

forest land

 1,378.8

 761.3 594.0 505.8 752.0

 2,021.7 1,352.9 2,199.4 3,183.4 3,309.1

 3,400.5 2,114.2 2,793.4 3,689.2 4,061.1

 182.9 176.6

 9.5 5.9

 99.0

Total Total Total Total Total 

 64.2 39.4 86.3 88.6

 1,151.8

 247.1 215.9

 95.8 94.5

 1,250.8

 3,647.5 2,330.1 2,889.2 3,783.7 5,311.9

NorthernUintaCentralEasternSouthwestern
130

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 - - - -

 11.3

 - -

 2.4

 - -

 10.6

 - - - -

 8.9 9.7

 - -

 27.0 10.9

 - - - -

 2.0

 - - - - - -

 22.0

 - -

 40.9 10.1

Table 32--Area of accessible forest land by Forest Survey Unit, county, ownership group and forest land status, Utah, cycle 2, 2000-2005.

(In thousand acres)

 32.4

 - - - -

 8.8

 - - - -

 10.6 29.9 36.5 29.8

 - -

 43.8 71.9 99.8 28.5 40.8 14.2 51.6 26.7 25.2 66.1

 120.6 206.8

 91.1

 - -

 18.5

 - -

 65.1 33.3 17.5

 108.9

 10.0 11.9 83.4 28.8

 2.5

 61.4 16.6

 - - - - - -

 10.3

 6.7 1.3

 70.2 18.6 12.6 23.3

 171.8

 66.9

 - -

 104.8

 1.6

 47.4

 179.0

 36.2

 112.7

 56.5 60.5

 - -

 367.3 187.9

 90.0 31.7

 - -

 140.4

 35.6 11.8 73.6

 9.3

 60.4

 184.2

 342.9 310.9

 22.5

 206.8

 84.2

 152.7 745.2 412.4 725.4 493.1 151.5 306.3

 1,101.9

 921.9 442.3 669.5 249.4 531.2 693.1 303.7 501.8 721.1 850.2

 1,710.5

(Table 32 continued on next page)

 42.9 37.9

 2.0

 73.0

 148.0 215.4 186.9 484.6

 377.3

 80.5 18.3

 124.7

 837.6 555.2 309.5 327.5

Total Total Total Total 

 3,647.5 2,330.1 2,889.2 3,783.7

All

forest

land

Timberland

Other

forest

land

Timberland

Other

forest

land

Forest Service

Timberland

Other

forest

land

Timberland

Other

forest

land

Other federal

State and local

government

Undifferentiated

private

 8.3

 110.9

 - -

 28.1 34.0 19.7

 306.4

 2.2

 185.8 253.4

 9.7

 192.1 268.2 170.5

 7.1

 54.4 87.2

 159.3 198.8

 53.4 19.3 85.9 30.9

 108.9

 27.7

 114.5

 11.3

 - - - -

 68.2

 119.0

 49.0

 345.7

 61.0 42.7 35.3

 228.3

 29.9 99.1

 286.0

 63.4 65.1

 337.3

 51.2

 2.8

 66.1 48.7

 278.6

 - - - - - - - - - - - - - - - - - - - - - - - - - -

 11.9

 7.1

 - - - - - - - -

 6.3

 35.7

 2.3

 25.1

 - -

 102.6

 - - - - - -

 12.9

 - -

 10.6

 285.2

 32.7

 - - - -

 32.6 77.7

 394.4 210.5 256.8

 82.6

 104.5

 88.0

 154.5 212.2 418.3 424.9

 1,014.3

 958.5 630.9 560.2 244.9

 839.1 293.6 902.1 396.1

 - -

 11.9 13.4 63.2

 444.0 504.7 896.8

 2,069.7

 Forest Survey Unit and county

NorthernUintaCentralEastern

(Table 31 continued)

 3,991.8 12,066.6 16,058.3 473.9 All counties 1,430.2 1,904.1 17,962.5

Timberland Unproductive Total Productive

Unreserved forests

 Forest Survey Unit and county

Reserved forests

Unproductive Total

All

forest land

(Table 54 continued on next page) 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.
131

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

BeaverGarfieldIronKaneWashington

 - - - -

 9.6

 - - - -

 68.9

 115.6

 82.6 47.8

 9.6

 - - - -

 50.5 33.2

 5.9

 16.5 18.4 58.9

 157.4

 41.3

(Table 32 continued)

 165.4 1,359.5 690.5 2,322.2 All counties 

 742.7

 1,536.9

 907.6

 1,378.3

 746.4

 17,962.5

(Table 55 continued on next page)

 9.6 324.6 89.7 292.4 Total 5,311.9

All

forest

land

Timberland

Other

forest

land

Timberland

Other

forest

land

Forest Service

Timberland

Other

forest

land

Timberland

Other

forest

land

Other federal

State and local

government

Undifferentiated

private

 26.4

 420.1

 64.5 86.4

 3.3

 76.2

 300.3

 86.0 20.4

 350.0

 16.5

 4.6

 - -

 11.0 20.1

 538.2 677.9 555.6

 1,022.2

 316.2

 600.7 832.9 52.1 3,110.0

 2,995.2 3,263.7 140.6 7,025.2

 Forest Survey Unit and county

Southwestern

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
132

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 7.6

 42.0 11.3 56.1 40.4 17.5

 161.1

 12.2

 114.8 171.8

 9.3

 80.9

 152.0

 99.5

 7.1

 43.5 38.5 59.9

 116.4

 28.3

 101.8

 83.5 82.7

 124.6

Table 33--Area of timberland by Forest Survey Unit, county and stand-size class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 - -

 59.2

 - -

 37.1 26.9 17.5

 193.8

 - -

 79.9

 110.3

 19.5 83.4

 152.3

 67.1

 - -

 10.9 32.4 76.8 69.0 13.9 34.4 23.3 12.6 12.6

 0.7

 21.2

 - - - -

 2.4 2.2

 71.0

 - - - -

 63.7 19.5 30.3 52.4 25.0

 7.1

 - -

 18.2 32.9 17.8 18.9 11.0

 - -

 14.2

 5.0

 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

 - -

 7.1

 - - - - - - - - - - - -

 3.0

 - - - - - - - -

 18.4

 - - - - - - - -

 2.2

 - - - - - - - - - -

 8.3

 129.4

 11.3 93.2 69.7 37.1

 425.9

 12.2

 197.7 345.8

 48.2

 194.7 356.7 209.9

 14.3 54.4 89.2

 169.6 205.5

 61.1

 147.2 106.8 109.5 142.3

(Table 33 continued on next page)

 644.1 332.4 293.8 392.7

 544.0 302.9 203.1

 82.9

 180.6 107.7

 94.9 30.2

 - - - - - - - -

Total Total Total Total 

 10.0 18.4

 2.2

 - -

 1,378.8

 761.3 594.0 505.8

 Forest Survey Unit and county

Stand-size class

Chaparral

All

size classes

Small

diameter

Medium

diameter

Large

diameter Nonstocked

NorthernUintaCentralEastern
133

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

BeaverGarfieldIronKaneWashington

 16.5

 262.5

 79.2

 117.8

 10.0

 17.0

 127.7

 35.8

 - -

 5.9

 9.4

 18.4

 9.6

 10.2

 - -

 - - - - - - - - - -

(Table 33 continued)

 2,148.8 1,319.3 461.1 - - All counties 

 - -

 16.1

 - -

 2.6

 13.3

 42.9

 424.8 124.6 130.5

 29.3

 62.6 3,991.8

(Table 57 continued on next page)

 485.9 186.5 47.6 - - Total 32.0 752.0

 Forest Survey Unit and county

Stand-size class

Chaparral

All

size classes

Small

diameter

Medium

diameter

Large

diameter Nonstocked

Southwestern

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
134

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 - -

 16.5

 - - - -

 2.4

 - -

 2.7

 - -

 3.0

 - - - - - - - -

 18.4

 - - - - - - - -

 11.1

 - - - - - - - - - -

Table 34--Area of timberland by Forest Survey Unit, county and stocking class, Utah, cycle 2, 2000-2005.

(In thousand acres)

 7.6

 61.2 11.3 40.4 13.8 19.7 71.4

 - -

 71.3 32.6 19.5

 103.7

 89.0 38.6

 - -

 2.7

 22.3 63.3 49.2 13.9 27.4 25.6 23.0 56.3

 - -

 49.4

 - -

 28.1 25.5

 - -

 244.0

 12.2

 109.6 176.2

 19.0 50.6

 119.5

 64.1

 7.1

 19.0 16.2 35.5 65.1 34.6 75.7 32.6 47.1 43.0

 0.7

 - - - -

 24.5 28.0

 8.7

 107.8

 - -

 13.8

 110.3

 9.7

 40.4

 127.8

 86.2

 7.1

 32.6 16.2 60.3 69.0 12.6 44.1 48.6 25.1 27.8

 - -

 2.4

 - -

 0.2

 - -

 8.7

 - - - - - -

 26.8

 - - - -

 20.4

 2.7

 - - - -

 34.5 10.4 11.1

 - - - - - -

 14.2 15.2

 8.3

 129.4

 11.3 93.2 69.7 37.1

 425.9

 12.2

 197.7 345.8

 48.2

 194.7 356.7 209.9

 14.3 54.4 89.2

 169.6 205.5

 61.1

 147.2 106.8 109.5 142.3

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)

 24.5 18.4 11.1

 - -

 348.7 231.3 151.4 132.3

 663.9 234.1 177.5 198.5

 303.6 254.4 197.9 145.6

Total Total Total Total 

 38.1 23.1 56.0 29.3

 1,378.8

 761.3 594.0 505.8

NorthernUintaCentralEastern
135

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

BeaverGarfieldIronKaneWashington

 - -

 16.1

 - -

 2.6

 23.3

 - -

 146.1

 9.6

 84.6

 - -

 33.5 88.5 35.8 23.0

 - -

 9.4

 151.0

 69.6 20.4

 5.9

(Table 34 continued)

 96.0 1,103.9 1,454.9 1,157.8 All counties 

 - -

 23.0

 9.6

 - - - -

 42.9

 424.8 124.6 130.5

 29.3

 179.2 3,991.8

Nonstocked

Poorly

stocked

Moderately

stocked

Fully

stocked Forest Survey Unit and county

Stocking class of growing-stock trees

Overstocked All classes

(Table 58 continued on next page)

 42.0 240.2 180.8 256.4 Total 32.6 752.0

Southwestern

All table cells without observations in the inventory sample are indicated by --. Table value of 0.0 indicates the acres round to lessthan 0.1 thousand acres. Columns and rows may not add to their totals due to rounding.
136

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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, Utah, cycle 2, 2000-2005.

 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

NorthernUintaCentralEastern

 424.8 429.1

 31.8

 178.2

 1,290.7

 607.1 659.4 724.5

 587.0 145.4 371.7 278.4

 - -

 0.5 2.4

 - -

Total Total Total Total 

 2,302.4 1,182.1 1,065.2 1,181.1

 1,344.7

 788.8 179.6 950.7

 5,901.3 2,635.2 2,867.7 3,483.3

 1,247.1

 129.1

 1,047.5

 884.8

 - -

 2.3 6.5

 - -

 8,493.0 3,555.4 4,101.3 5,318.8

(Table 35 continued on next page)

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 - - - - - - - -

 63.0

 - -

 329.1

 - -

 1.7

 30.9

 - -

 114.2 201.7 113.2

 0.1

 - -

 6.5

 - -

 4.2

 20.9

 2.1 9.2

 18.4

 148.5

 3.0

 116.2

 21.0

 160.1

 60.7

 8.3

 253.5

 22.9

 337.8 262.6

 44.6

 100.9 305.1 201.2

 19.6 82.7

 129.6 177.8 219.7

 29.9

 241.1 303.0

 96.2 84.3

 - -

 24.6

 - -

 40.5 55.7 47.7

 124.2

 - -

 45.8

 235.6

 13.0

 4.8

 63.8 76.9

 0.5

 36.5 89.7 91.3

 148.6

 5.2

 62.2 44.1 93.8 78.3

 - - - - - - - - - - - - - - - - - - - - - - - - - -

 0.5

 - - - - - - - - - -

 2.4

 - - - - - - - -

 3.0

 140.8

 21.0

 200.6 179.4

 56.0

 706.7

 22.9

 385.3 529.2

 57.6

 219.9 570.5 391.7

 20.2

 119.1 225.9 269.1 372.5

 58.4

 305.4 356.2 208.4 311.1

 - - - - - - - -

 317.7

 - -

 865.4

 - -

 3.4

 158.1

 - -

 117.6 477.0 194.3

 - - - -

 27.7

 - -

 14.8

 137.1

 5.6

 38.4

 104.8 802.0

 - - - - - - - - - - - - - - - - - - - - - - - - - -

 2.3

 - - - - - - - - - -

 6.5

 - - - - - - - -

 6.9

 592.0 106.6 916.3 743.6 164.0

 2,147.3

 103.7

 1,591.0 1,878.3

 243.4 547.1

 1,857.7 1,150.6

 64.7

 451.8 873.6 981.7

 1,451.6

 278.0

 1,221.0 1,743.6

 879.0

 1,475.3

 6.9

 551.1 106.6 817.8 290.3

 36.3

 1,101.1

 103.7

 1,525.8 1,125.3

 236.4 428.1

 1,334.8

 872.3

 64.7

 323.5 604.3 772.2 982.5 120.5

 1,112.7 1,582.2

 394.3 394.0

 - -

 40.9

 - -

 98.5

 135.6 127.6 180.8

 - -

 61.8

 594.9

 7.0 1.4

 45.9 81.8

 - -

 128.3 241.6 209.4 454.3

 13.9

 102.6 123.0 379.9 279.3

(In million board feet) 1 (In million cubic feet)
137

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 (Table 35 continued)

 1,300.4 3,938.3 1,762.6 2.8 All counties 7,004.2 4,496.3 17,687.7 4,359.2 8.7 26,551.9

 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

Southwestern

 236.7 656.6 380.1 - - Total 1,273.4 1,232.4 2,800.1 1,050.8 - - 5,083.3

(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. International 1/4 inch rule.

BeaverGarfieldIronKaneWashington

 21.8

 150.7

 3.7

 59.6

 0.9

 23.6

 434.0 119.6

 79.4

 - -

 17.2

 140.3 189.8

 23.8

 9.0

 - - - - - - - - - -

 62.7

 725.0 313.1 162.7

 9.9

 131.5 770.1

 20.7

 307.4

 2.7

 - - - - - - - - - -

 226.7

 2,821.5 1,287.2

 723.6

 24.3

 95.2

 1,927.9

 446.1 330.9

 - -

 - -

 123.5 820.3

 85.3 21.7

(In million board feet) 1 (In million cubic feet)

1
138

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

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, Utah, cycle 2, 2000-2005.

 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

NorthernUintaCentralEastern

6.58.40.32.7

15.8

4.0

-21.1

4.8

10.8

3.47.43.0

 - -

0.00.1

 - -

Total Total Total Total 

33.215.8

-13.4

10.5

16.216.4

2.1

18.4

102.4

20.4

-93.2

36.2

44.1

1.6

56.434.0

 - -

0.00.0

 - -

162.7

38.4

-34.6

88.6

(Table 36 continued on next page)

(In million cubic feet) (In million board feet) 1

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 - - - - - - - -

0.2

 - -

5.9

 - -

-0.1

0.6

 - -

4.23.21.10.0

 - -

0.0

 - -

0.10.20.10.1

-0.5

3.2

0.11.90.32.51.70.3

-0.9-0.5

5.34.10.8

-1.2

5.10.10.22.12.1

-26.5

0.90.1

-0.3

4.30.40.4

 - -

-0.5

 - -

1.20.01.52.7

 - -

0.15.00.70.21.51.70.00.91.81.92.70.01.00.90.20.9

 - - - - - - - - - - - - - - - - - - - - - - - - - -

0.0

 - - - - - - - - - -

0.1

 - - - - - - - -

0.11.40.33.82.01.87.7

-0.5

5.39.81.53.29.72.80.23.04.0

-24.6

3.70.40.75.30.04.5

 - - - - - - - -

1.5

 - -

13.4

 - -

-0.5

1.7

 - -

8.76.80.9

 - - - -

0.60.00.41.11.20.3

-2.8

19.7

 - - - - - - - - - - - - - - - - - - - - - - - - - -

0.0

 - - - - - - - - - -

0.0

 - - - - - - - -

0.3

10.2

2.4

16.313.4

6.7

18.2

-2.7

23.267.0

7.72.6

33.1

2.70.5

14.526.1

-105.5

29.4

0.47.7

38.7

9.5

32.7

0.3

12.5

2.4

14.710.4

2.62.2

-2.7

26.626.0

7.4

-6.1

25.5

1.00.5

12.112.1

-127.4

10.2

-0.8

4.9

24.1

2.94.3

 - -

-2.3

 - -

1.61.54.02.6

 - -

-3.0

39.4

0.30.00.80.8

 - -

2.3

13.421.918.8

0.11.6

14.3

9.38.7
139

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010 (Table 36 continued)

20.9 -4.3 30.5 0.1 All counties 47.2 72.7 41.6 154.3 0.1 268.6

 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

Southwestern

2.9 -7.7 5.8 - - Total 1.0 19.6 -24.2 18.2 - - 13.6

(Table 60 continued on next page)

(In million cubic feet) (In million board feet) 1

BeaverGarfieldIronKaneWashington

0.22.00.00.80.0

-2.0-1.0-4.7

0.0

 - -

0.22.92.50.10.2

 - - - - - - - - - -

-1.7

3.9

-2.2

0.80.2

0.9

14.6

0.23.90.1

 - - - - - - - - - -

-8.6

28.0

-13.6

7.30.4

-9.5

7.3

-24.8

2.8

 - -

 - -

6.2

11.0

0.70.3

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 or board feet. Columns and rows may not add to their totals due to rounding.

1 International 1/4 inch rule.
140

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

NorthernUintaCentralEastern

Box ElderCacheDavisMorganRichSalt LakeSummitTooeleUtahWasatchWeberDaggettDuchesneUintahJuabMillardPiuteSanpeteSevierWayneCarbonEmeryGrandSan Juan

 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

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, Utah, cycle 2, 2000-2005.

(Sampling error in percent)

 - -

54.7695.8364.4860.65

 - -

32.17

100.00

43.9330.98

100.00

71.6142.9453.44

100.00

73.4676.1345.4958.1290.3953.7568.8778.9962.70

 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

 - -

60.29

 - -

86.9976.92

 - -

38.49

100.00

42.9356.91

 - -

85.0955.1453.92

100.00

97.94

100.00

47.1762.29

100.00

51.8182.5877.8674.60

99.3139.5295.8338.1945.6973.2019.6194.1925.2018.9682.2231.6722.6231.50

100.00

39.4549.1026.8329.0953.7031.4241.0642.4630.47

99.3183.5495.8337.0053.4880.8568.29

100.00

28.9535.9593.44

100.00

26.71

100.00100.00

45.4051.0567.1165.71

100.00100.00

44.83

100.00

36.63

(Table 37 continued on next page)

 - - - - - - - -

18.4136.4938.8638.54

 - - - - - - - -

22.8542.0740.7238.57

Total Total Total Total 

10.7416.3517.0718.81

19.7853.86

100.00

33.85

13.16

9.55

66.78

9.86

18.1911.48

5.31

11.07

4.786.41

15.44

8.684.265.718.437.738.376.155.68

11.77

5.477.395.614.22

90.8821.7795.8325.8823.2646.3410.7584.8419.0010.8542.3013.1814.3019.3273.3439.0326.3020.6418.6034.5122.1526.2927.8324.95

99.3134.0395.8334.5936.8368.3815.2390.3622.6216.4168.2519.2418.9325.3490.2840.6140.4224.9526.1346.8829.1037.6843.0431.29

99.31

100.00

95.8329.1466.1870.4836.08

100.00

24.1419.1861.0398.7519.91

100.00

78.4043.9245.9657.6180.46

100.00100.00

36.24

100.00

33.90

2.813.233.172.78

6.309.20

10.9612.57

8.91

12.9115.0617.65

13.7731.65

100.00

54.16

Forest

area

Timberland

area Volume

Average

annual

net growth

Average

annual

removals

Average

annual

mortality Volume

Average

annual

net growth

Average

annual

removals

Average

annual

mortality

Growing stock Sawtimber

 Forest Survey Unit and county
141

Appendix E

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Southwestern

BeaverGarfieldIronKaneWashington

 - - - - - - - - - -

92.3329.2255.9967.69

 - -

 - - - - - - - - - -

95.5536.9363.4274.05

 - -

(Table 37 continued)

 - - 16.25 - - 19.15 All counties 

64.1718.4537.2930.7293.98

100.00

56.19

100.00

90.0590.65

6.77 35.27

(Table 65 continued on next page)

 - - 25.82 - - 31.21 Total 14.88 100.00

5.274.104.194.636.32

46.1113.0726.4126.2054.05

58.4217.0733.2431.4695.63

100.00

93.62

100.00100.00

90.28

2.17 10.28 13.65 100.001.23 4.09 5.79 38.96

Forest

area

Timberland

area Volume

Average

annual

net growth

Average

annual

removals

Average

annual

mortality Volume

Average

annual

net growth

Average

annual

removals

Average

annual

mortality

Growing stock Sawtimber

 Forest Survey Unit and county

Sampling errors that exceed 100% are reported as 100%. The sampling error is not calculated when the estimated value is equal to 0 and is indicated by --.
142

Appendix F

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Appendix F—Tables of Mean Soil Properties

Table 1—Mean properties of forest floor by forest type, Utah, cycle 2, 2000-2004.

Number of % Water pontent1

Forest type plots (Oven dry basis) % Organic carbon2 % Total nitrogen2 C/N ratio2

Rocky Mountain juniper 3 28.94 33.76 a 0.815 ab 49.8 abc

Juniper woodland 23 5.86 32.14 a 0.761 ab 44.0 ab

Pinyon-juniper woodland 88 10.61 28.87 a 0.624 b 48.6 a

Douglas fir 11 14.43 30.83 a 0.987 a 32.4 abc 

Ponderosa pine 5 29.14 31.95 a 0.777 ab 42.6 abc

White fir 4 21.81 28.83 a 0.901 ab 32.8 abc

Engelmann spruce 5 41.10 28.06 a 0.917 ab 32.0 abc

Engelmann spruce-subalpine fir 1 113.83 41.28 a 0.890 ab 46.0 abc

Subalpine fir 7 22.23 30.08 a 0.830 ab 42.5 abc

Lodgepole pine 3 195.83 48.74 a 1.081 ab 46.3 abc

Aspen 19 42.16 33.24 a 1.143 a 29.8 bc

Deciduous oak woodland 14 23.09 29.64 a 0.979 a 28.0 c

Cercocarpus woodland 3 8.64 33.40 a 0.902 ab 37.0 abc 

1 Arithmetic mean

2 Estimated Tukey-Kramer means. Means not followed by the same letter are significantly different (p < 0.01).

Table 2—Mean physical properties of soil cores by forest type, Utah, cycle 2, 2000-2004.

Number of % Water content1 SQI2,3 Bulk density2 % Coarse

Forest type samples (Oven dry basis) % g/cm3 fragments2

0 – 10 cm soil cores

Rocky Mountain juniper 3 14.22 65 ab 1.06 ab 19.69 a

Juniper woodland 16 3.60 58 b 1.27 ab 13.75 a

Pinyon-juniper woodland 78 4.11 59 b 1.34 a 10.31 a

Douglas fir 12 10.25 74 a 0.95 ab 28.57 a

Ponderosa pine 4 10.16 69 ab 1.39 ab 6.74 a

White fir 3 7.19 72 ab 1.07 ab 28.71 a

Engelmann spruce 4 9.61 69 ab 0.90 ab 19.58 a

Engelmann spruce-subalpine fir 1 19.93 80 ab 1.26 a

Subalpine fir 6 14.69 68 ab 1.14 ab 28.15 a

Lodgepole pine 2 15.59 62 ab 0.98 ab 36.92 a

Aspen 15 18.08 73 a 0.90 b 23.41 a

Deciduous oak woodland 14 10.14 74 a 0.97 ab 16.84 a

Cercocarpus woodland 3 7.68 61 ab 1.18 ab 31.31 a

10 – 20 cm soil cores

Rocky Mountain juniper 3 9.77 62 ab 1.16 ab 34.12 a

Juniper woodland 15 5.82 54 b 1.35 ab 11.17 a

Pinyon-juniper woodland 64 5.45 57 b 1.40 a 13.62 a

Douglas fir 12 10.65 68 ab 1.07 ab 33.21 a

Ponderosa pine 4 9.03 64 ab 1.48 ab 15.58 a

White fir 3 5.72 65 ab 1.21 ab 40.23 a

Engelmann spruce 4 6.09 58 ab 1.05 ab 27.63 a

Engelmann spruce-subalpine fir 1 19.17 75 ab 1.09 ab 6.35 a

Subalpine fir 6 11.31 59 ab 1.24 ab 37.91 a

Lodgepole pine 2 13.80 57 ab 1.36 ab 31.43 a

Aspen 14 13.55 72 a 0.90 b 20.96 a

Deciduous oak woodland 14 9.90 70 a 1.20 ab 13.93 a

Cercocarpus woodland 1 3.65 70 ab 1.36 ab 51.08 a

1 Arithmetic mean

2 Estimated Tukey-Kramer means. Means not followed by the same letter are significantly different (p < 0.01).

3 Soil Quality Index
143

Appendix F

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Table 3—Mean chemical properties of soil cores by forest type, Utah, cycle 2, 2000-2004.

Bray 1 Olsen

Number Organic Inorganic Total extractable extractable

of pH carbon carbon nitrogen phosphorus phosphorus

Forest type samples H2O CaCl2 % % % mg/kg Mg/kg

0 – 10 cm soil cores

Rocky Mountain juniper 3 7.91 ab 7.34 ab 2.19 ab 0.64 a 0.151 ab 6.6 a 8.7 abc

Juniper woodland 16 8.04 a 7.47 a 0.88 b 0.77 a 0.080 b 5.8 a 4.1 bc

Pinyon-juniper woodland 78 7.78 a 7.21 ac 1.19 b 0.60 a 0.084 b 5.4 a 5.3 c

Douglas fir 12 7.08 bc 6.74 abd 3.70 a 0.38 a 0.229 ab 7.8 a 14.1 abc

Ponderosa pine 4 6.56 bcd 6.10 bcde 2.35 ab 0.17 a 0.129 ab 7.7 a 6.0 abc

White fir 3 6.80 abcd 6.56 abde 4.48 ab 0.19 a 0.185 ab 159.2 a 9.6 abc

Engelmann spruce 4 5.84 d 5.37 e 8.17 a 0.25 a 0.265 ab 23.8 a 15.9 abc

Engelmann spruce-subalpine fir 1 5.96 abcd 5.84 abde 15.12 ab 0.384 ab 53.8 a

Subalpine fir 6 6.28 cd 5.69 de 2.98 ab 0.20 a 0.129 ab 23.3 a 5.8 abc

Lodgepole pine 2 5.53 cd 4.94 e 1.75 ab 0.12 a 0.053 ab 10.1 a 5.8 abc

Aspen 15 6.32 cd 5.83 e 4.19 a 0.25 a 0.299 a 24.3 a 17.1 a

Deciduous oak woodland 14 6.86 bcd 6.32 bde 3.99 a 0.26 a 0.301 a 14.5 a 17.4 ab

Cercocarpus woodland 3 7.14 abcd 6.59 abde 1.40 ab 0.80 a 0.123 ab 24.0 a 6.0 abc

10 – 20 cm soil cores

Rocky Mountain juniper 3 7.86 abc 7.38 abc 1.43 abc 0.65 a 0.119 a 6.1 a 4.7 abc

Juniper woodland 15 8.26 a 7.64 a 0.72 c 0.97 a 0.078 a 1.7 a 1.2 c

Pinyon-juniper woodland 64 7.75 ab 7.21 a 1.03 bc 0.62 a 0.073 a 2.4 a 2.1 bc

Douglas fir 12 7.27 bcd 6.85 ab 2.38 ab 0.58 a 0.163 a 14.6 a 7.7 abc

Ponderosa pine 4 6.45 cde 5.90 bcd 1.03 abc 0.15 a 0.061 a 2.6 a 2.7 abc

White fir 3 6.97 abcde 6.64 abcd 3.04 abc 0.14 a 0.125 a 12.1 abc

Engelmann spruce 4 5.80 e 5.36 d 3.34 abc 0.23 a 0.128 a 15.6 a 15.3 abc

Engelmann spruce-subalpine fir 1 5.74 bcde 5.36 abcd 1.96 abc 0.082 a 39.8 a

Subalpine fir 6 6.20 de 5.57 d 1.79 abc 0.17 a 0.052 a 8.4 a 4.6 abc

Lodgepole pine 2 5.30 e 4.74 d 1.76 abc 0.11 a 0.053 a 6.5 a 2.0 abc

Aspen 14 6.58 cde 5.91 cd 2.87 a 0.22 a 0.218 a 19.1 a 14.3 a

Deciduous oak woodland 14 6.96 cde 6.49 bcd 2.35 ab 0.24 a 0.182 a 15.7 a 9.3 ab

Cercocarpus woodland 1 5.80 bcde 5.76 abcd 1.94 abc 0.146 a 6.4 a
144

Appendix F

USDA Forest Service Resour. Bull. RMRS-RB-10. 2010

Table 4—Mean chemical properties of soil cores by forest type, Utah, cycle 2, 2000-2004 (continuation of table 3 with additional chemicals).

Forest type

Number

of

samples

1 M NH4Cl

Exchangeable cations

1 M NH4Cl

Extractable

Na K Mg Ca Al ECEC Mn Fe Ni Cu Zn Cd Pb S

mg/kg cmolc/kg mg/kg

0 – 10 cm soil cores

Rocky Mountain juniper 3 5 a 462 a 435 a 5438 a 0 a 32.22 a 0.8 abc 0.0 0.1 a 0.0 0.1 a 0.0 a 0.6 a 1.8 aJuniper woodland 16 16 a 263 a 295 a 3716 a 1 a 22.35 a 0.6 c 0.1 a 0.1 a 0.0 0.1 a 0.0 a 0.2 a 5.2 aPinyon-juniper woodland 78 9 a 163 a 213 a 3088 a 1 a 18.08 a 1.4 bc 0.4 a 0.1 a 0.0 0.1 a 0.0 a 0.2 a 5.6 aDouglas fir 12 7 a 339 a 374 a 3995 a 2 a 24.24 a 3.0 abc 0.6 a 0.4 a 0.0 0.0 0.0 a 0.7 a 15.4 a

Ponderosa pine 4 11 a 257 a 219 a 2130 a 1 a 13.44 a 6.7 abc 0.1 a 0.1 a 0.0 0.2 a 0.0 a 0.0 11.0 a

White fir 3 8 a 192 a 224 a 4356 a 3 a 24.73 a 5.5 abc 0.4 a 0.0 a 0.0 0.0 0.0 a 0.0 19.9 a

Engelmann spruce 4 10 a 166 a 275 a 3596 a 9 a 23.95 a 20.6 a 0.0 0.0 0.0 0.0 a 0.1 a 0.4 a 23.7 aEngelmann spruce-subalpine fir 1 9 a 330 a 215 a 3427 a 3 a 19.79 a 73.0 ab 40.6 a

Subalpine fir 6 25 a 169 a 183 a 1839 a 1 a 11.39 a 10.5 a 0.1 a 0.2 a 0.0 0.3 a 0.1 a 0.1 a 4.6 aLodgepole pine 2 14 a 63 a 157 a 1146 a 2 a 7.29 a 6.1 abc 4.4 a 0.2 a 0.0 0.0 0.0 a 0.0 5.9 a

Aspen 15 8 a 301 a 256 a 2667 a 2 a 16.43 a 9.6 a 0.7 a 0.2 a 0.0 0.4 a 0.1 a 0.2 a 6.1 aDeciduous oak woodland 14 12 a 329 a 290 a 3896 a 1 a 23.12 a 5.7 a 0.1 a 0.1 a 0.0 0.0 0.1 a 0.2 a 8.2 aCercocarpus woodland 3 7 a 189 a 158 a 2590 a 2 a 14.97 a 8.7 abc 0.0 0.0 0.0 0.0 0.0 a 0.5 a 4.8 a

10 – 20 cm soil cores

Rocky Mountain juniper 3 15 a 434 a 363 a 4018 a 0 a 24.71 a 1.3 a 2.4 a 0.0 0.0 0.0 0.0 a 0.3 a 5.4 aJuniper woodland 15 30 a 245 a 343 a 3916 a 1 a 24.13 a 0.5 a 0.0 0.2 a 0.1 a 0.0 a 0.0 a 0.2 a 5.0 aPinyon-juniper woodland 64 13 a 153 a 252 a 3198 a 1 a 19.10 a 1.0 a 1.9 a 0.1 a 0.1 a 0.2 a 0.0 a 0.3 a 9.0 a Douglas fir 12 15 a 238 a 342 a 4114 a 2 a 24.34 a 2.4 a 0.0 0.1 a 0.0 0.2 a 0.0 a 0.3 a 10.3 aPonderosa pine 4 12 a 215 a 223 a 1905 a 1 a 12.30 a 6.7 a 0.0 0.1 a 0.0 0.3 a 0.1 a 0.0 12.6 aWhite fir 3 8 a 152 a 161 a 3293 a 2 a 18.74 a 4.7 a 0.0 0.0 0.0 a 0.2 a 0.1 a 0.5 a 11.4 aEngelmann spruce 4 9 a 94 a 138 a 1814 a 13 a 13.07 a 7.0 a 2.9 a 0.0 0.0 0.0 0.0 0.0 11.9 aEngelmann spruce-subalpine fir 1 4 a 258 a 145 a 1417 a 4 a 8.92 a 58.7 a 14.7 aSubalpine fir 6 9 a 114 a 153 a 1288 a 3 a 8.23 a 7.4 a 0.0 0.1 a 0.0 a 0.3 a 0.1 a 0.3 a 5.2 aLodgepole pine 2 31 a 95 a 129 a 927 a 36 a 6.37 a 23.2 a 0.0 0.5 a 0.0 0.8 a 0.0 a 0.5 a 3.4 aAspen 14 17 a 291 a 249 a 2339 a 1 a 14.75 a 5.7 a 2.9 a 0.1 a 0.2 a 0.2 a 0.1 a 0.3 a 6.6 aDeciduous oak woodland 14 12 a 291 a 271 a 3449 a 1 a 20.62 a 4.7 a 0.0 0.1 a 0.1 a 0.3 a 0.1 a 0.4 a 7.0 aCercocarpus woodland 1 9 a 129 a 177 a 1760 a 2 a 10.62 a 26.7 a 16.3 a 

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