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Technical Note 419

BLM/ST/ST-06/001+5100
Technical Note 419

April 2006

A Report on the Potential Use of USDA Forest Service 

Forest Inventory and Analysis Data

by the Bureau of Land Management

By:

Bill Williams, Forester

Bureau of Land Management

National Science and Technology Center

Denver, Colorado

Tracey Frescino, Forester

Larry DeBlander, Forester

Sharon Woudenberg, Information Management Team Leader

Michael J. Wilson, Assistant Station Director—FIA

Interior West Forest Inventory and Analysis

USDA Forest Service 

Rocky Mountain Research Station

Ogden, Utah
Suggested Citation

Williams, B., T. Frescino, L. DeBlander, S. Woudenberg, and M.J. Wilson. 2006. A Report on the Potential Use 

of USDA Forest Service Forest Inventory and Analysis Data by the Bureau of Land Management. Technical 

Note 419. BLM/ST/ST-06/001+5100. Bureau of Land Management, Denver, CO. 32 pp.

Contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Purpose of the Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Introduction to the Forest and Inventory Analysis Program . . . . . . . . . 3

FIA Program Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

FIA Forestland Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Question 1: Are the standard FIA reports and tables useful? . . . . . . . . . 6

Question 2: What is the potential for using FIA 

basic data for BLM strategic planning? . . . . . . . . . . . . . . . 7

Question 3: Is there a potential use for Interior West FIA 

spatial (map) products? . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Question 4: Can BLM supplement FIA sample plots 

to increase the utility of FIA data? . . . . . . . . . . . . . . . . . . . 9

Question 5: Can BLM use FIA plot data to model or 

predict areas at risk of disturbance from

fire, insects, or disease or to assess the extent 

of weeds or exotic species? . . . . . . . . . . . . . . . . . . . . . . . . 10

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Appendix 1 - BLM Dillon Field Office Tables and Graphs . . . . . . . . . 12

Appendix 2 - BLM Albuquerque Field Office Tables and Graphs . . . . 19

Appendix 3 - BLM Dillon Field Office Maps . . . . . . . . . . . . . . . . . . . 27
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 

Abstract

The Bureau of Land Management (BLM) does not have 

a consistent internal program or source of vegetation 

data to use for strategic level planning, such as in resource management plans. This technical note discusses 

and evaluates the potential of the USDA Forest Service 

Forest Inventory and Analysis (FIA) Program to assist 

the BLM in filling this data gap. The FIA program is 

the Forest Service’s national program for collecting and 

reporting information on status and trends in forested 

ecosystems. The FIA is considered here because it is the 

only standard, nationwide, systematic assessment of 

forest land available. The technical note poses five questions about the use of FIA data by the BLM for purposes 

such as strategic planning, the use of FIA spatial products, 

modeling or predicting areas at risk of disturbance from 

fires, insects, or disease, and assessing the extent of weeds 

or exotic species. The technical note then discusses the 

uses for which the FIA data would be meaningful and 

the uses for which extra effort would be required.
 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Purpose of the 

Report

This technical note addresses the potential of USDA 

Forest Service Forest Inventory and Analysis (FIA) data 

and reports for use by the Bureau of Land Management (BLM). BLM does not have a consistent internal 

program or source of vegetation data to use for strategic 

level planning, such as in resource management plans. 

Data and information from other external sources were 

considered, but the FIA program, because of its scope 

and history, had the most potential. This technical 

note discusses five basic questions about FIA’s data and 

delivery options. 

Question 1: Are the standard FIA reports and tables 

useful for BLM strategic planning?

Question 2: What is the potential for using FIA basic 

data for BLM strategic planning?

Question 3: Is there a potential use for Interior West 

FIA (IWFIA) spatial (map) products?

Question 4: Can BLM supplement the FIA sample 

plots to increase the utility of FIA data?

Question 5: Can BLM use FIA plot data to model or 

predict areas at risk of disturbance from 

fire, insects, or disease or to assess the 

extent of weeds or exotic species?
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 

Introduction 

to the Forest and 

Inventory Analysis 

Program

The FIA program is the Forest Service’s national program for collecting and reporting information on status 

and trends in forested ecosystems. Managed through 

Forest Service Research and Development, the FIA program has been in continuous operation since the first 

inventory was completed in 1933. The FIA mission, 

as outlined in the Forest and Rangeland Renewable 

Resources Research Act of 1978, is to report periodically on all of the Nation’s public and private forests. 

This includes information on status and trends in area, 

location, growth, mortality, harvesting, composition, 

and structure of forests. 

FIA conducts resource inventories on all lands, including those lands administered by the USDI Bureau 

of Land Management, Bureau of Indian Affairs, and 

National Park Service; State, county, and municipal 

governments; and lands owned by private individuals 

and businesses.

FIA also collects data from loggers on utilization efficiency; from wood processing mills on types of wood 

products made; and from private landowners on management goals, interests, and demographics. 

Historically, FIA data were collected on State-by-State 

cycles within six different regions of the country. The 

typical inventory process included a complete statewide 

stratification using aerial photography; field visits to 

collect ground data; visits to logging operations and 

wood processing facilities to track utilization rates; and 

data compilation, analysis, and reporting. The cycle 

(time between re-measurements of a given State) has 

varied from 7 to10 years in the South to 12 to15 years 

in the North to 20 or more years in the West.

A recent amendment to the Forest and Rangeland 

Renewable Resources Act of 1978 legislated new procedures. FIA refers to these procedures as the annual 

inventory process. The procedures specify that: 

• Between 10 and 20 percent of all FIA sample plots 

will be measured each year in every State.

• A compilation of all the data collected will be made 

available annually to the public.

• Every 5 years, a report will be prepared, published, 

and made available to the public (with the cooperation of State foresters) detailing the results of the 

previous inventories and an analysis of the forest 

health conditions and trends over the previous two 

decades.

• National standards and definitions will be implemented to ensure uniform and consistent data collection by the various FIA units located throughout 

the country.

FIA operates at a strategic scale, with one field sample 

location approximately every 6,000 acres. FIA data are 

statistically useful from the national scale down to areas 

of about 200,000 acres.

The Interior West Forest Inventory and Analysis 

Program (IWFIA), Rocky Mountain Research Station, 

Ogden Forestry Sciences Laboratory, conducts forest resource inventories in Arizona, Colorado, Idaho, 

Montana, Nevada, New Mexico, Utah, and Wyoming. 

The FIA unit at the Pacific Northwest Research Station 

is responsible for inventorying Alaska, Washington, 

Oregon, and California.
 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

FIA Program 

Methods

The FIA consists of a nationally consistent core program, which can be enhanced at the regional, State, 

or local level by collecting additional data to address 

special interests. The national core program consists of 

three phases:

Phase 1 uses remote sensing imagery or aerial photography to classify land into forest or non-forest and to 

identify landscape patterns, such as fragmentation and 

urbanization. Historically, this phase was accomplished 

exclusively with aerial photographs. Current methods 

are shifting to a system based on satellite imagery.

Phase 2 consists of a grid of permanently established 

field plots distributed across the landscape with 

approximately one plot every 6,000 acres. In the West, 

field crews visit 10 percent of forested sample locations 

each year to collect a variety of forest ecosystem data. 

Non-forest locations are also visited as necessary to 

quantify rates of land use change. A typical plot usually 

takes a two- to three-person field crew one full day to 

complete. Factors such as the steepness of the ground, 

size of trees, amount of understory vegetation, and 

length of the hike to the plot all factor into the time 

commitment. When a field crew visits a plot, some of 

the information collected includes:

• Tree diameter, length, damage, amount of rotten or 

missing wood, and tree quality

• Counts of tree regeneration 

• General land use

• Stand characteristics such as forest type, stand age, 

and disturbance

• Changes in land use and general stand characteristics

• Estimates of growth, mortality, and removals 

• Vegetation diversity and structure

Phase 3 is the field plot portion of the Forest Health 

Monitoring (FHM) detection program as it was integrated 

into the FIA program. An extended suite of ecological 

measurements are collected on a subset of FIA plots 

each year. Field crews gather data on tree species and 

diameters, crown conditions, tree damage, lichen 

communities, ozone bioindicators, soils, and downwoody material. FHM reports on forest-related issues 

on a large scale, usually at the State and regional levels.
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 

FIA Forestland 

Definition

The FIA definition of forest land is: 

Land at least 10 percent stocked by forest trees of 

any size, including land that formerly had such 

tree cover and will be naturally or artificially 

regenerated. 

This is also the BLM definition of forest land. FIA and 

BLM use tree canopy cover as an estimate of stocking. 

The IWFIA equates 5 percent canopy cover as 

10 percent stocking when defining forest land. BLM 

has historically equated 10 percent canopy cover to 

10 percent stocking for all species. The minimum 

canopy cover measure to use for defining forest and 

non-forest land is the subject of debate. In reality, age, 

potential size, and trees per acre should be factored 

into the classification because those factors influence 

whether trees will fully occupy or significantly influence 

the vegetation structure on a site.

FIA has a minimum area for classification of forest land 

of 1 acre. Roadside, streamside, and shelterbelt strips 

of trees must have a crown width of at least 120 feet to 

qualify as forest land.

FIA statistics include a category of forest land called 

timberland. Timberland is forest land that is producing 

or is capable of producing crops of industrial wood and 

has not been withdrawn from timber utilization by 

statute or administrative regulation. Timberland must 

be capable of producing 20 cubic feet of industrial 

wood per acre per year. BLM “commercial forest land” 

has the same definition as FIA “timberland.” BLM 

calls forest land that does not meet the timberland 

criteria “woodland.”
 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Question 1: Are 

the standard 

FIA reports and 

tables useful?

Information from the FIA program is available from 

two sources: Research Station Reports and the national 

Forest Inventory and Analysis Database (FIADB). The 

information is presented in both sources in a standard 

set of FIA tables. 

Research Station Reports

Published data summaries are available in the form 

of Forest Service Research Station Resource Bulletins. 

These reports from the periodic inventory were published irregularly for an entire State. The published 

reports usually summarize the inventory results for a 

State or occasionally for a portion of a State. Reports 

include the number of trees, size, wood volume, tree 

growth, mortality, and harvest removals. 

Under the annual inventory process, an updated report 

of the forests in a State will be produced every 5 years. 

It has not yet been determined what the report will 

look like. At this time, work is being conducted on a 

report template at the Northeast FIA project.

The information in the State-level reports has limited 

value because BLM lands are usually lumped in an “other 

public” category, which contains all public lands including 

Indian reservations, but does not include national forests.

Forest Inventory and Analysis Database 

(FIADB)

FIA created a database (FIADB) and Web site to 

provide tables for selected States and counties within a 

State. Standard or custom output tables can be created 

by selecting from the specific options provided. For 

example, tables can be generated showing acres of forest 

land by forest type, stand size class, and site class on 

BLM land in a selected set of counties in a State. Tables 

can be generated for all forest land or for non-reserved 

timberland. The table descriptions and options use 

terminology associated with the production of wood 

products and do not address aspects of forest health and 

vegetation conditions. This information can be accessed 

at http://ncrs2.fs.fed.us/4801/fiadb.

In addition to Web-application-generated tables, other 

options for data analysis include:

1. Exporting the FIADB data as a comma-delimited 

file and importing it to Microsoft Excel to generate 

charts and graphs.

2. Exporting plot measurement data for an entire 

State directly from FIADB. 

3. Using the FIADB export option that provides plot 

data in a format ready for use by the Forest Vegetation Simulator (FVS.) There are some missing 

variables, which are desirable for FVS in the FIA 

data. The variables that are not in the data include 

diameter growth or past diameter measurements, 

site index species codes, habitat type codes, and 

FVS tree damage codes. 

Two limitations exist in the way information is selected 

and reported from FIADB:

1. To get reports for a BLM field office, you must 

select a set of counties for a sub-State area. BLM 

field office boundaries do not coincide with county 

boundaries; so, the dataset used for the tables or 

the set of plot data extracted may include plots 

outside the field office area or may be missing plots 

that fall within a field office boundary.

2. There is no accuracy assessment (standard deviation 

or standard error) available for county-level tables 

from FIADB. One can query for the total number 

of plots used to generate a table, but there is no 

way to calculate the precision of the estimate using 

the Web functions.

BLM is using the numbers from FIADB for the total acres 

of commercial forest land and woodland in each State 

for the BLM Annual Report. FIA is being used because 

it is the only standard, nationwide, systematic assessment 

of forest land available. BLM does not have a standard 

process or an internal source for the required data.
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 

Question 2: What 

is the potential 

for using FIA basic 

data for BLM 

strategic 

planning? 

Because of the spacing of the field plots and BLM’s 

fragmented land pattern, BLM ownership may not 

provide a large enough sample for the desired precision 

of the estimates. Two examples illustrate the potential 

problem. 

• BLM administers some 10,000 acres in two 

western South Dakota counties. FIADB does not 

have any BLM plots in South Dakota; the database 

shows no BLM land in the State.

• BLM forest land in the Dillon Field Office has 

22 FIA plots; the Forest Service in the same area has 

270 plots. The BLM forest land in the Albuquerque 

Field Office has 40 plots and the Forest Service 

forest land has 165 plots in the same area.

If the data or data summaries can be obtained, and if 

BLM-managed land has a statistically adequate number 

of samples, the basic data has potential use. When standard FIADB query options do not provide adequate 

information, requests for custom products and data sets 

are an option. Be sure to realize that this would be a 

custom request and could require additional response 

time on the part of the FIA staff. 

Standard Tables – The IWFIA staff can produce 

“standard table” data for BLM ownership in an area. 

GIS spatial data for the area of interest, such as a BLM 

field office, is used to locate the plots for the area of 

interest. The selected plots are then used to generate 

tables. The tables can be provided in a format for 

import to Microsoft Excel. Excel can be used to 

produce charts and graphs from the tabular data. 

Appendixes 1 and 2 have tables and graphs for two 

BLM field offices that were prepared using FIA tables 

after moving them to Excel. The short narrative 

description in each appendix is an example of the 

information provided by the data.

Pivot Table – It is also possible to get the plot data used 

in the tables in a Microsoft Excel “pivot table.” FIA 

staff can create pivot tables for combinations of plots 

on BLM-managed land. Use of pivot tables allows 

generation of custom tables and graphics not available 

in FIADB or the FIA tables. The use of pivot tables 

would require training or a tutorial.
 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Question 3: Is 

there a potential 

use for Interior 

West FIA spatial 

(map) products?

At IWFIA, efforts are underway to merge regional 

forest inventory data with satellite-based information 

to produce spatial products. Staff are using, or have 

used, Landsat Thematic Mapper (TM), AVHRR, and 

MODIS data with inventory data and other available 

ancillary data layers. These other data layers include, 

for example, the National Elevation Dataset (NED) 

data to predict forest type, volume, biomass, basal area, 

number of trees, crown cover, mean diameter, and 

other vegetation attributes at multiple scales. Most of 

the efforts have been done to test methodology or to 

prototype modeling processes. 

IWFIA staff have completed prototype ArcView GIS 

projects where forest attributes, as listed previously, 

were predicted in each cell in the area of interest. One 

prototype was done at the request of the BLM National 

Science and Technology Center. The project area was 

for the Dillon Field Office (Montana). The modeling 

“extent” was enlarged to an ecoregion level to increase 

the number of ground plots for training data for the 

classification. The project developer provided display 

and query tools for each theme to allow the user to refine 

the data used in the view. For example, a user could 

select a range of canopy cover values to display and could 

then combine canopy cover with other queries to display 

forest attributes meeting specific criteria. Example maps 

from the project are provided in Appendix 3.

The resulting products are useful for showing the general location, at mid to large scales, of forest resources 

and resource conditions. They may be beneficial for 

strategic planning efforts for forest lands. A significant 

limitation of the spatial products is the lack of information about non-forest vegetation cover. FIA reports 

acres of non-forest; FIA does not report on non-forest 

cover types. 

The work to model forest attributes and build a GIS 

display tool is significant. If BLM were to make regular 

requests, it would be an unfunded workload for the 

IWFIA and BLM would need to provide the funding 

for the work.
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 

Question 4: Can 

BLM supplement 

FIA sample plots 

to increase the 

utility of FIA data?

Although it is theoretically possible to supplement the 

number of sample plots on BLM land to provide better 

estimates, analytically and logistically it would be 

difficult and expensive.

Analytically, the question becomes one of how to 

increase the number of possible sample locations (by 

intensifying the grid of points) without inducing bias 

due to the fragmented BLM land pattern. Selecting 

only additional plots that fall on BLM land and combining them with plots from the normal grid of points 

might create an unequal probability of selection, and 

therefore produce a biased sample. There are also questions about how to statistically merge the supplemental 

plot data (if it is collected at a different time) with the 

annual cycle data to provide the statistics of interest.

Logistically, the question becomes one of how to increase 

the sample and over what time period. If a single field 

office is the target for increased data collection over 

some period shorter than the annual inventory cycle, 

it would require separate crews and equipment beyond 

current FIA capability. The FIA is developing a set of 

tools for those who want to intensify or supplement FIA 

data on lands they manage. The tools will include the 

processes from data collection through data compilation 

and will allow integration with the available FIA data.
10 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Question 5: Can 

BLM use FIA plot 

data to model or 

predict areas at 

risk of disturbance 

from fire, insects, 

or disease or to 

assess the extent 

of weeds or exotic 

species?

It is possible to build predictive models of forest 

attributes using FIA plot data in combination with 

remotely sensed data. (See discussion in Question 3.) 

1 Fiedler, Carl E., Charles E. Keegan III, Christopher W. Woodal, and Todd A. Morgan. A Strategic Assessment of Crown Fire Hazard in 

Montana: Potential Effectiveness and Costs of Hazard Reduction Treatments. USDA Forest Service Pacific Northwest Research Station 

Gen. Tech. Report PNW-GTR-622; November 2004.

Fiedler, Carl E., Charles E. Keegan III, Stephen H. Robertson, Todd A. Morgan, Chris W. Woodall, and John T. Chmelik. A Strategic 

Assessment of Fire Hazard in New Mexico. Final Report Submitted to the Joint Fire Sciences Program, February 11, 2002.

Researchers at the University of Montana used FIA data 

and the Fire and Fuels Extension to the Forest Vegetation Simulator (FVS) to model fire risk and management 

opportunities for New Mexico and Montana1. Similar 

modeling might use the insect and disease extensions 

to FVS to simulate potential impacts from specific 

pathogens or insects. The Landfire national interagency 

effort to do nationwide fuel modeling is using FIA as 

one source of vegetation data. The modeling and 

analysis processes require skills not readily available in 

BLM. For a BLM-specific project, contracting the 

effort is the only practical option.

The FIA’s emphasis is on data about trees as opposed 

to shrubs and herbaceous vegetation. The IWFIA field 

crews do identify and estimate cover of all shrub and 

herbaceous vegetation species with greater than 5 percent 

canopy cover. If weeds are noted on plots, then the 

extent of weed cover can be analyzed. Reports would 

necessarily be on a broad-scale, such as for a State. 

Weed and exotic species have not been reported by the 

FIA to date.

The FIA has a privacy policy that heavily restricts 

releasing the coordinates of plot locations. Basically, 

the policy says that plot coordinates on public land may 

be released to the agency responsible for managing 

the land, under some very specific restrictions and 

conditions. For BLM, a Memorandum of Understanding 

(MOU) and a confidentiality certification process 

would be required. This policy is the result of the 

FIA’s interpretation of the Food Security Act of 1985, 

Public Law 99-198 [H.R.2100], December 23, 1985, 

Confidentiality of Information, sec.1770, as amended 

by H.R.3423 on November 17, 1999.
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 11

Conclusions

The use of FIA data by the BLM depends on need 

(project by project) and the availability of other sources 

of data. For example, the BLM in Western Oregon 

maintains a strategic inventory and FIA data would not 

be necessary for their projects. For other BLM offices 

needing data for planning on the public domain forest 

lands, the conclusions are:

• The FIA is the only systematic, continuous assessment 

that includes BLM forest lands.

• The data are meaningful at a State level and perhaps 

at a field office level, depending on the number of 

plots on BLM.

• Data analysis requires an extra effort for BLM areas 

at a sub-State level.

• FIA spatial products are receiving more attention 

by the FIA, but will likely only be available as 

special projects on an ecoregion basis because of the 

time and effort involved.
12 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Appendix 1

BLM Dillon Field Office 

Tables and Graphs

The following tables and graphs were produced by 

importing a set of FIA tables into Microsoft Excel. 

The tables are based on 22 field plots on BLM land 

in the Dillon Field Office area. The Interior West FIA 

(IWFIA) analysis staff extracted the data from the 

Montana inventory data and provided the tables in a 

format suitable for use with Excel.

Interpretation of the tables and graphs allow a general 

description of the forest condition for the Dillon Field 

Office.

• Dillon has an estimated 142,000 acres of forest 

land (Table 1).

• The primary forest types based on land area are 

Douglas-fir (56%), lodgepole pine (23%) and 

spruce-fir (17%) (Figure 1).

• There are over 104,000 acres (Table 2) classified 

as sawtimber size (sawtimber has a diameter of 

9 inches and greater).

• Over half of the area has relatively low site 

productivity, 20 to 49 cubic feet per acre per year 

(Table 2).

• The primary species are Douglas-fir and lodgepole 

pine, followed by subalpine fir and Engelmann 

spruce. Minor species are limber pine, whitebark 

pine, and Rocky Mountain juniper (Figure 4).

• The standing wood volume in sawtimber size trees 

is 210,588,000 cubic feet (Table 7).

• The Douglas-fir forest type has the most volume 

followed by the lodgepole pine type (Figure 9).

• Tree mortality compared to net annual growth (in 

terms of cubic volume) is low, less than 1 percent 

(Figure 6).

• Approximately 23 percent of the forest is 

overstocked and 25 percent is classed as poorly 

stocked (Figure 7).

• There are 12,186 acres classified as aspen habitat 

types that are stocked with Douglas-fir (Table 6).

Table 1. Area of forest land by forest type, 

BLM Dillon Field Office, 2000

Forest Type Acres

Douglas-fir 80,017

Engelmann spruce 5,928

Lodgepole pine 32,084

Spruce-fir 24,043

All types 142,072

Engelmann spruce 4%

Lodgepole pine 23%

Spruce-fir 17%

Douglas-fir 56%

Figure1. Percent of Forestland by Forest Type
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 13

Table 2. Area of forest land by forest type, stand-size 

class, and productivity class, BLM Dillon Field Office, 

2000

Acres

Forest Type Stand-Size 

Class

Productivity Class

50-84 20-49 Total

Douglas-fir Sawtimber 26,155 34,856 61,011

Poletimber 5,928 13,078 19,006

Total 32,083 47,934 80,017

Engelmann 

spruce

Sawtimber 5,928 0 5,928

Poletimber 0 0 0

Total 5,928 0 5,928

Lodgepole

pine

Sawtimber 13,078 0 13,078

Poletimber 5,928 13,078 19,006

Total 19,006 13,078 32,084

Spruce-fir Sawtimber 5,928 18,115 24,043

Poletimber 0 0 0

Total 5,928 18,115 24,043

Total Sawtimber 51,090 52,971 104,061

Poletimber 11,856 26,155 38,011

Sapling/seedling 0 0 0

Nonstocked 0 0 0

Total 62,946 79,126 142,072

40,000

35,000

30,000

25,000

20,000

Acres

15,000

10,000

5,000

50–84 20–49

Figure 3. Area by Forest Type, Size Class, and Productivity Class

Potential Growth - Cubic Feet Per Acre Per Year

0

Douglas-fir sawtimber

Douglas-fir poletimber

Engelmann spruce sawtimber

Lodgepole pine sawtimber

Lodgepole pine poletimber

Spruce-fir sawtimber

0

10,000

20,000

30,000

40,000

Acres

50,000

60,000

70,000

Sawtimber

Poletimber

Lodgepole Spruce-fir

pine

Forest Type

Engelmann

spruce

Douglas-fir

Figure 2. Area of Forestland by Forest Type and

Stand Size
14 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 3. Number of live trees on forest land by species and diameter class, BLM Dillon Field Office, 2000

Thousand Trees

Diameter Class

Species 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

29.0+ All

Classes 

Douglas-fir 11,925 11,210 7,762 2,747 2,101 1,242 793 353 158 108 66 27 36 27 51 38,606

Engelmann 

spruce

1,186 593 685 598 321 145 190 82 52 17 27 0 0 0 0 3,896

Limber

pine 

715 1,430 1,510 155 98 130 66 0 13 0 0 0 0 0 0 4,117

Lodgepole 

pine

6,295 5,109 5,859 2,616 1,792 1,091 148 91 28 34 18 8 7 0 0 23,096

Rocky 

Mountain 

juniper 

0 0 146 162 54 64 51 0 0 0 0 0 0 0 0 477

Subalpine

fir

5,928 0 963 540 754 438 153 42 0 0 0 8 7 0 0 8,833

Whitebark 

pine

1,778 1,186 387 553 366 152 103 63 65 75 46 0 11 10 0 4,795

Total 27,827 19,528 17,312 7,371 5,486 3,262 1,504 631 316 234 157 43 61 37 51 83,820

30,000

25,000

20,000

15,000

10,000

Diameter Class

Figure 4. Number of Trees by Species and Size

Thousands

5,000

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 29.0+ 0

Whitebark pine

Subalpine fir

Rocky Mountain juniper

Lodgepole pine

Limber pine

Engelmann spruce

Douglas-fir
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 15

Table 4. Net volume of all live trees on forest land by species and diameter class, BLM Dillon Field Office, 2000

Thousand Cubic Feet

Diameter Class

Species 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 

29.0+ All

Classes

Douglas-fir 15,357 11,177 17,171 16,906 15,193 9,284 5,662 4,422 2,964 1,457 1,973 2,397 7,402 111,365

Engelmann 

spruce

2,381 4,017 3,414 2,649 5,745 3,613 2,455 833 1,754 0 0 0 0 26,861

Limber 

pine

3,350 706 504 1,392 1,505 0 506 0 0 0 0 0 0 7,963

Lodgepole 

pine

18,072 20,375 22,922 22,229 4,069 3,749 1,394 1,750 1,268 671 556 0 0 97,055

Rocky 

Mountain 

juniper

152 199 132 361 300 0 0 0 0 0 0 0 0 1,144

Subalpine 

fir

4,044 3,839 8,064 6,824 3,155 629 0 0 0 483 446 0 0 27,484

Whitebark 

pine

736 2,815 2,875 2,332 1,854 1,702 2,310 2,061 1,663 0 641 163 0 19,152

Total 44,092 43,128 55,082 52,693 31,821 18,977 12,327 9,066 7,649 2,611 3,616 2,560 7,402 291,024

Lodgepole pine 33%

Subalpine fir 9%

Whitebark pine 7%

Douglas-fir 39%

Limber pine 3%

Engelmann

spruce 9%

Rocky Mountain juniper 0%

Figure 5. Total 

Cubic-Foot Volume 

by Species

2,500

2,000

1,500

1,000

500

Species

Cubic Volume (Thousands)

DouglasfirEngelmann

spruce

Limber

pine

Lodgepole

pine

Subalpine

fir

Annual Growth

Annual Mortality

Whitebark

pine

Figure 6. Net Annual Growth

by Species Compared 

to Mortality

0

-500
16 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 5. Area of forest land by forest type and stocking condition, BLM Dillon Field Office, 2000

Acres

Stocking Condition

Forest Type Overstocked Fully Stocked Medium Stocked Poorly Stocked Total

Douglas-fir 13,078 13,078 25,264 28,598 80,018

Engelmann spruce 0 0 5,928 0 5,928

Lodgepole pine 13,078 13,078 5,928 0 32,084

Spruce-fir 5,928 5,928 5,928 6,258 24,042

All types 32,084 32,084 43,048 34,856 142,072

Medium

stocked 29%

Poorly

stocked 25%

Fully

stocked 23%

Overstocked 23%

Figure 7. Acres by 

Stocking Condition

Table 6. Area of forest land by habitat type series and forest type, BLM Dillon Field Office, 2000

Acres

Forest Type

Habitat Type 

Series

Douglas-fir Engelmann 

spruce

Lodgepole pine Spruce-fir All Types

Unclassified 5,928 5,928 0 0 11,856

Douglas-fir 61,903 0 13,078 0 74,981

Subalpine fir 0 0 13,078 12,186 25,264

White fir 0 0 0 11,856 11,856

Lodgepole pine 0 0 5,928 0 5,928

Aspen 12,186 0 0 0 12,186

All types 80,017 5,928 32,084 24,042 142,072

70,000

60,000

50,000

40,000

Acres

30,000

20,000

10,000

Habitat Type Series

Figure 8. Forest Land Area 

by Habitat Type Series 

and Forest Type

Unclassified

Limber

pine

Douglasfir

Subalpine

fir

White

fir

Lodgepole

pine

Aspen

0

Aspen

Douglas-fir

Engelmann spruce

Lodgepole pine

Spruce-fir
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 17

Table 7. Net volume of all live trees on forest land by forest type and stand-size class, 

BLM Dillon Field Office, 2000

Thousand Cubic Feet

Stand-Size Class

Forest Type Sawtimber Poletimber All Classes

Douglas-fir 91,546 21,952 113,498

Engelmann spruce 15,843 0 15,843

Lodgepole pine 44,496 58,485 102,981

Spruce-fir 58,703 0 58,703

All types 210,588 80,437 291,025

Sprucefir

Logepole

pine

Forest Type

Engelmann

spruce

Douglasfir

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

Cubic-foot Volume (thousands)

Figure 9. Net Volume by Forest Type and Stand Size

Poletimber

Sawtimber

Stand Size Class
18 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 8. Net volume of all live trees on forest land by species and forest type, 

BLM Dillon Field Office, 2000

Thousand Cubic Feet

Forest Type

Species Douglas-fir Engelmann 

spruce

Lodgepole pine Spruce-fir All Types

Douglas-fir 93,427 5,403 5,648 6,888 111,366

Engelmann 

spruce

5,647 10,441 6,007 4,766 26,861

Limber pine 7,068 0 565 329 7,962

Lodgepole pine 5,699 0 83,184 8,172 97,055

Rocky Mountain 

juniper

1,144 0 0 0 1,144

Subalpine fir 512 0 7,578 19,395 27,485

Whitebark pine 0 0 0 19,153 19,153

Total 113,497 15,844 102,982 58,703 291,026

70,000

60,000

50,000

100,000

90,000

80,000

40,000

Cubic-foot Volume (thousands)

30,000

20,000

10,000

Douglas-fir Engelmann spruce Lodgepole pine

Forest Type

Spruce-fir

Figure 10. Net Cubic Volume by Forest Type and Species

0

Douglas-fir

Rocky Mountain Juniper

Engelmann spruce

Subalpine fir

Limber pine

Whitebark pine

Lodgepole pine
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 19

Appendix 2

BLM Albuquerque Field Office 

Tables and Graphs

BLM Albuquerque Field Office Tables and Graphs

The following tables and graphs were produced by 

importing a set of FIA tables into Microsoft Excel. The 

tables are based on 40 field plots on BLM land in the 

Albuquerque Field Office area. The Interior West FIA 

(IWFIA) analysis staff extracted the data from the New 

Mexico inventory data and provided the tables in a 

format suitable for use with Excel. 

Interpretation of the tables and graphs allow a general 

description of the forest condition for the Albuquerque 

Field Office.

• Albuquerque has an estimated 285,174 acres of 

forest land (Table 1).

• Fifty-four percent (54%) of these acres are in 

reserve status. All of the ponderosa pine acres are 

reserved (Figure 1).

• The pinyon-juniper forest type is by far the most 

common type (almost 220,000 acres); there 

are 11,864 acres in the juniper type. Stocked 

ponderosa pine (20,555 acres) and nonstocked 

ponderosa pine (14,431 acres) type total 34,986 

acres (Table 2).

• Twelve percent (12%) of the forest acres are 

nonstocked (Figure 3).

• Productivity of the woodland types is low; growth 

is less than 20 cubic feet per acre per year (Table 2 

and Figure 2).

• Oneseed juniper and two needle pinyon are the 

predominant species (Table 4).

• Most of the trees are in diameter classes of 6 inches 

and less (Figure 5).

• Approximately 91,000 acres are in age classes 

greater than 100; no acres were classed older than 

200 years (Table 6).

• Sixty percent (60%) of the pinyon-juniper type 

is in the “sawtimber” size class (diameter class 9 

inches and greater). All of the ponderosa pine type 

is in the sawtimber size class (Table 7).
20 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 1. Area of forest land by forest type and land class, BLM Albuquerque Field Office, 2000

Acres

Forest Type Nonreserved Reserved Total

Juniper 11,864 11,864

Pinyon-juniper 118,939 100,819 219,758

Ponderosa pine 20,555 20,555

Nonstocked timberland 14,431 14,431

Nonstocked woodland 18,566 18,566

All types 130,803 154,371 285,174

Nonreserved

46%

Reserved

54%

Figure1. Forest by Land Class

140,000

120,000

100,000

80,000

Acres

60,000

40,000

20,000

20–49 0–19

Figure 2. Area by Forest Type, Size Class, and Productivity Class

Potential Growth - Cubic Feet Per Acre Per Year

0

Juniper Poletimber

Pinyon-juniper Sawtimber

Pinyon-juniper Poletimber

Pinyon-juniper Sapling/seedling

Ponderosa pine Sawtimber

Timberland Nonstocked

Woodland Nonstocked
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 21

Table 2. Area of forest land by forest type, stand-size class, and productivity class, 

BLM Albuquerque Field Office, 2000

Acres

Forest Type Stand-Size Class Productivity Class

20-49 0-19 Total

Juniper Poletimber 11,864 11,864

Pinyon-juniper Sawtimber 131,418 131,418

Poletimber 77,516 77,516

Sapling/seedling 10,823 10,823

Total 219,757 219,757

Ponderosa pine Sawtimber 20,555 20,555

Nonstocked timberland 14,431 14,431

Nonstocked woodland 18,566 18,566

Total Sawtimber 20,555 131,418 151,973

Poletimber 89,380 89,380

Sapling/seedling 10,823 10,823

Nonstocked 14,431 18,566 32,997

Total 34,986 250,187 285,173

Nonstocked 12%

Sapling/seedling 4%

Poletimber 31%

Sawtimber 53%

Figure 3. Forestland by Size Class
22 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 3. Area of forest land by forest type and basal area class, BLM Albuquerque Field Office, 2000

Basal Area Class

Acres

0 1-25 26-50 51-75 76-100 101-150 151-200 201-250 Total

Juniper 5,932 5,932 11,864

Pinyon-juniper 3,608 28,674 41,345 19,705 62,117 41,246 7,215 15,848 219,758

Ponderosa 

pine

13,340 7,215 20,555

Timberland* 7,215 7,215 14,430

Woodland* 11,351 7,215 18,566

Total 22,174 49,036 54,685 25,637 62,117 48,461 7,215 15,848 285,173

*Nonstocked

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

1-25

Acres

Figure 4. Acres of Pinyon-juniper by Basal Area Class

Basal Area Class

0

51-75

26-50

101-150

76-100

201-250

151-200

28,674

3,608

19,705

41,345

41,246

62,117

15,848

7,215
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 23

Table 4. Number of live trees on forest land by species and diameter class, BLM Albuquerque Field Office, 

2000

Thousand Trees

Diameter Class (inches)

Species 2 4 6 8 10 12 14 16 18 20 22 24+ All 

Classes

Alligator 

juniper

74 43 117

Border 

pinyon

541 541

Oneseed 

juniper

3,207 647 1,059 969 1,816 1,621 1,440 1,240 678 760 456 486 14,379

Ponderosa 

pine

304 347 87 130 130 174 217 43 1,432

Rocky Mtn. 

juniper

555 541 235 328 427 359 130 80 155 43 37 2,890

Two needle 

pinyon

6,588 2,917 4,082 2,886 1,982 696 342 310 87 43 37 19,970

Utah 

juniper

43 43

Total 

Softwoods

10,891 4,105 5,680 4,530 4,386 2,806 2,042 1,804 1,137 889 493 609 39,372

Arizona 

white oak

541 541

Gambel 

oak

541 541 43 1,125

Total 

Hardwoods

1,082 541 43 1,666

All species 11,973 4,646 5,723 4,530 4,386 2,806 2,042 1,804 1,137 889 493 609 41,038

0 2 4 6 8 10 12 14

Diameter Class (inches)

Figure 5. Number of Live Trees by Diameter Class

Number of Trees (thousands)

16 18 20 22 24+

2,000

4,000

6,000

8,000

10,000

12,000
24 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 5. Net volume of all live trees on forest land by species and forest type, 

BLM Albuquerque Field Office, 2000

Thousand Cubic Feet

Forest Type

Species Juniper PinyonjuniperPonderosa 

pine

Nonstocked 

Timberland

Nonstocked 

Woodland

All Types

Alligator 

juniper

181 1,801 1,982

Oneseed 

juniper

1,927 59,994 61,921

Ponderosa 

pine

263 18,427 1,805 20,495

Rocky Mtn 

juniper

9,202 9,202

Two needle 

pinyon

45,940 853 357 47,150

Utah juniper 2,306 2,306

Total 

softwoods

1,927 117,886 21,081 1,805 357 143,056

Gambel oak 47 47

Total 

hardwoods

47 47

All species 1,927 117,886 21,128 1,805 357 143,103

70,000

60,000

50,000

40,000

30,000

20,000

10,000

Alligator

juniper

Oneseed

juniper

Ponderosa

pine

Rocky Mtn

juniper

Two

Needle

pinyon

Utah

juniper

Gambel

oak

Figure 6. Net Volume, All Live Trees By Species and Forest Type

Species

Thousand Cubic Feet

0

Nonstocked woodland

Nonstocked timberland

Ponderosa pine

Pinyon-juniper

Juniper
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 25

Table 6. Area of forest land by forest type and stand-age class, BLM Albuquerque Field Office, 2000

Acres

ForestTypeStand-Age Class

Unclassified/

Nonstocked

1-50 51-100 101-150 151-200 All Classes

Juniper 0 5,932 5,932 11,864

Pinyon-juniper 8,632 18,038 108,116 51,598 33,373 219,757

Ponderosa 

pine

0 0 13,340 7,215 20,555

Nonstocked 

timberland

14,431 14,431

Nonstocked 

woodland

18,566 18,566

All types 41,629 23,970 127,388 51,598 40,588 285,173

140,000

120,000

100,000

80,000

60,000

40,000

20,000

Nonstocked 1–50 51–100 101–150 151–200

Figure 7. Area by Age Class and Forest Type

Age Class

Acres

0

Ponderosa pine

Pinyon-juniper

Juniper
26 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT

Table 7. Net volume of all live trees on forest land by forest type and stand-size class, 

BLM Albuquerque Field Office, 2000

Thousand Cubic Feet

Forest Type Sawtimber Poletimber Sapling/

seedling

Nonstocked All Classes

Juniper 1,927 1,927

Pinyon-juniper 83,649 32,464 1,774 117,887

Ponderosa pine 21,127 21,127

Nonstocked 

timberland

1,805 1,805

Nonstocked 

woodland

357 357

All Types 104,776 34,391 1,774 2,162 143,103

Thousand Cubic Feet

Figure 8. Net Volume by Size Class

Stand Size Class

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000

Sawtimber

Poletimber

Seedling

21,127

83,649

1,927

32,464

1,774 Ponderosa pine

Pinyon-juniper

Juniper
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 27

Appendix 3

BLM Dillon Field Office Maps

The following maps are examples of modeled forest 

attributes that include forest type, tree canopy cover, 

average tree diameter, and tree volumes for the BLM 

Dillon Field Office. 

The maps are exported from a GIS project file. The 

developer provided query and display functions for 

making the maps. Each map could be refined to show 

a range or subset of attribute values, such as a map of 

biomass in excess of some minimum per acre value.

The BLM did not conduct a rigorous accuracy assessment 

of the classifications. The products met with generally 

positive response. There was some concern that the 

forest typing was slightly in error. There was a consistent 

misclassification of low- to mid-elevation Douglas-fir as 

lodgepole pine. Limber pine presence was generally not 

shown on the map. Also, the spruce-fir type was over 

estimated; areas more predominantly lodgepole pine or 

Douglas-fir were classed as spruce-fir.

Because the attribute values shown can be defined by 

the user, maps can be tailored to answer fairly specific 

questions about the forest resource. The information 

shown is modeled, or predicted, based on observations 

from a small number of field locations; therefore, the 

maps cannot be used for locating specific sites for 

management activities. The maps do show the extent 

and general location of forest resources attributes over a 

landscape and they have value for that purpose.
28 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 29
30 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT
A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT 31
32 A REPORT ON THE POTENTIAL USE OF USDA FOREST SERVICE FOREST INVENTORY AND ANALYSIS DATA BY THE BUREAU OF LAND MANAGEMENT
The mention of company names, trade names, or commercial products does not constitute endorsement or 

recommendation for use by the Federal Government.