Technical Note 440

August 2011

BLM

BLM Core

Terrestrial

Indicators 

and Methods
Suggested Citation: 

MacKinnon, W.C., J.W. Karl, G.R. Toevs, J.J. Taylor, M. Karl, C.S. Spurrier, and J.E. Herrick. 2011. BLM core

 terrestrial indicators and methods. Tech Note 440. U.S. Department of the Interior, Bureau of Land

 Management, National Operations Center, Denver, CO.

Production services provided by:

Bureau of Land Management

National Operations Center

Information and Publishing Services Section

P.O. Box 25047

Denver, CO 80225

BLM/OC/ST-11/003+1735

“. . . to introduce and

describe the core indicators

and methods component

of the AIM Strategy.”
BLM Core

Terrestrial

Indicators and

Methods

Technical Note 440

Authors:

W. Craig MacKinnon (retired), AIM Coordinator,

BLM Washington Office, Washington, DC

Jason W. Karl, Research Ecologist,

Agricultural Research Service-Jornada, Las Cruces, NM

Gordon R. Toevs, AIM Coordinator,

BLM Washington Office, Washington, DC

Jason J. Taylor, Landscape Ecologist,

BLM National Operations Center, Denver, CO

Michael “Sherm” Karl, Rangeland Management Specialist,

BLM National Operations Center, Denver, CO

Carol S. Spurrier, Rangeland Ecologist,

BLM Washington Office, Washington, DC

Jeffrey E. Herrick, Research Scientist,

Agricultural Research Service-Jornada, Las Cruces, NM
“. . . will allow data to be

integrated across field,

district, and state office

boundaries.”
iii

the indicators: Tim Bottomley, Bud Cribley, Roxanne 

Falise, Marty Griffith, Ted Milesnick, Kit Muller, Mike 

Pellant, and Doug Powell. Final indicator selection was 

based on analysis and interpretation of the results of 

a study in which more than 65 technical experts from 

the BLM, ARS, Department of Defense, Department 

of Energy, Natural Resources Conservation Service, 

USGS, and several universities applied the criteria to 

the indicators. The authors gratefully acknowledge 

these contributions.

This technical report was prepared in cooperation with 

the U.S. Department of Agriculture, Agricultural Research Service (ARS), Jornada Experimental Range. 

This technical note is the result of a consultative process with significant support from Skye Wills with the 

ARS and Dave Pyke and Kate Kitchell with the U.S. 

Geological Survey (USGS). The following BLM employees participated in three multiday meetings during which they contributed to the development of the 

indicator selection criteria and the final selection of 

Acknowledgments
“. . . specific, repeatable,

easy-to-implement methods

for measuring those

indicators.”
v

Table of Contents

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 

Terrestrial Indicators for the BLM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Core Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 

Contingent Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Measurement Methods for the Core Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Modifications of Recommended Methods and 

 the Ability to Aggregate Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
“The core indicators

and methods provide a

basis for obtaining

high-quality data that

can address many

objectives. . .”
1

Background

the AIM Strategy. Further, this technical note provides 

guidance on how to maintain consistency of effort and 

resources (i.e., cited materials) when needing further 

details on established protocols. This core indicators 

and methods component identifies a small set of core 

indicators (i.e., measurements) that, when collected, 

can be used for many purposes across ecosystem types 

including rangeland, forest, and riparian areas. This set 

of core indicators, based on quantitative land cover and 

vegetation data using standardized measurements, will 

allow data to be integrated across field, district, and 

state office boundaries. 

Biotic integrity, soil and site stability, and hydrologic 

function have been identified as essential attributes 

necessary to describe ecosystem sustainability (see 

Figure 1). Foundational to the AIM Strategy is a suite 

of quantitative indicators related to these three attributes (i.e., what to measure) and specific, repeatable, 

easy-to-implement methods for measuring those indicators (i.e., how to measure them). The core indicators and methods adopted for AIM-related sampling 

represent a minimum set of information that should be 

The Bureau of Land Management (BLM) Assessment, 

Inventory, and Monitoring (AIM) Strategy was initiated, in part, to evaluate current monitoring activities 

and recommend procedures to improve the efficiency 

and effectiveness of these activities. To this end, the 

AIM Strategy supports an integrated approach to: 

(1) document the distribution and abundance of natural resources on public lands; (2) facilitate the description of resource conditions; and (3) identify natural 

resource trends or changes. These objectives will be 

accomplished through the integration of fundamental 

processes including the: (1) development and application of a consistent set of ecosystem indicators and 

methods for measuring them (i.e., quantitative core 

indicators and consistent methods for monitoring); 

(2) development and implementation of a statistically 

valid sampling framework; (3) application and integration of remote sensing technologies; and (4) implementation of related data acquisition and management 

plans (Toevs et al. 2011).

The purpose of this technical note is to introduce and 

describe the core indicators and methods component of 

Figure 1. Assessing and monitoring natural systems requires consideration of the major structural components of ecosystems (boxes) and 

their functional relationships (solid arrows). Biotic integrity, soil and site stability, and hydrologic function have been identified as the three 

key attributes that can be evaluated to determine site integrity and the functional status of ecological processes (Pellant et al. 2005). This 

figure is adapted from Miller (2005).

Vegetation

Ecosystem Component/Function Attributes

grasses, forbs

shrubs, trees

Watershed

hydrologic function

riparian vegetation

Wildlife Biotic

Integrity

Soil and Site

Stability

Hydrologic

Function

invertebrates

vertebrates

Soil Resources

mineral nutrients, water

organic matter, biota

Soil-Plant-Water Interface

plant litter, soil structure,

biological soil crusts
2

BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

collected at each sample location. Contingent indicators and methods are implemented where necessary 

(see Table 1 and associated text). In order to meet local 

information needs related to management questions or 

specific ecosystem characteristics, the core and contingent indicators can be supplemented with additional 

indicators calculated from the core methods or, if necessary, from additional locally specific methods. 

The core indicators and methods provide a basis for obtaining high-quality data that can address many objectives (e.g., vegetation and habitat management, change 

detection, and remote sensing needs). Additionally, datasets that are intended to address local management 

questions and collected using the core indicators and 

methods can be combined to meet needs at scales larger 

than the immediate monitoring area (e.g., for regional 

and national reporting).
3

Terrestrial Indicators for the BLM

it appears in riparian and forest systems, a large 

percentage of bare ground is generally an indicator 

that the system has been significantly modified. 

(2) Vegetation composition. Vegetation composition 

data, including the cover of groups of species, has 

historically been applied in some form in virtually 

every monitoring program across all cover types. 

Vegetation composition and cover indicators are 

generated from the same data, and when used 

together, it has been shown that they are sensitive to most changes in nearly every terrestrial 

ecosystem’s status. In addition, the known vegetation composition is critical for determining the 

fire regime condition class, and the indicator (or 

group of indicators) is useful when determining 

the status of key species in plant communities that 

provide forage for all classes of herbivores.

(3) Nonnative invasive plant species. The presence 

and cover of nonnative species is acquired as a 

component of vegetation composition. Nonnative 

invasive species have the ability to significantly 

alter resource use sustainability, site resilience, 

disturbance regimes, or ecohydrology. Nonnative 

invasive species is also listed as a separate indicator because of its national, regional, and local 

management importance.

(4) Plant species of management concern. The 

presence and cover of plant species of management concern is also acquired as a component of 

vegetation composition. Plant species of management concern can be sensitive to site disturbance, 

provide important ecosystem functions, or contribute to biological diversity. Plant species of 

management concern is also listed as a separate 

indicator because it is specifically required for 

BLM reporting.

(5) Vegetation height. Vegetation height describes 

the vertical structure of vegetation, which can be 

used to characterize wildlife habitat and estimate 

wind erosion potential. When used together with 

the proportion of the soil surface in large intercanopy gaps (see core indicator 6), it can be used 

to create three-dimensional models of vegetation 

structure. 

The AIM Strategy’s indicators and methods were 

developed by a collaborative process involving nearly 

200 scientists, rangeland managers, and ecologists 

from different agencies/institutions (Herrick et al. 

2010). Participants rated an extensive list of potential 

indicators against 16 criteria, ultimately selecting the 

most general indicators with the broadest applicability 

to a range of management questions. Standard methods for measuring the BLM indicators were selected 

that met the following requirements: well documented, widely used, easy to implement, and minimal 

potential for bias. 

Additional information regarding the selection of 

the indicators and methods is available in Terrestrial 

Indicators and Measurements: Selection Process and 

Preliminary Recommendations (Herrick et al. 2010), 

and guidance on statistically valid sample design for 

the indicators and methods is currently being developed. It is beyond the scope of this report to provide 

detailed instructions for implementing each of the core 

methods or to discuss intricacies of sample design. 

However, guidance is given on modifications for core 

and contingent methods that could affect the ability 

to combine data. Unless specific guidance is given, 

readers should see the referenced technical documentation, manuals, and training materials for protocols to 

implement the core and contingent methods.

Core Indicators

Six core indicators are recommended wherever the 

BLM implements quantitative vegetation and/or 

soil monitoring (see Table 1). These indicators were 

selected to meet BLM management needs, but they 

are widely accepted and generic enough to provide 

standardized data collection across jurisdictions (i.e., 

internally within the BLM, but also with other agencies and nongovernmental organizations). These 

indicators are:

(1) Bare ground. The amount of bare ground is 

widely accepted as one of the most sensitive 

indicators of resource condition in rangelands. A 

large percentage of bare ground can be an indicator of high erosion potential, low forage production, poor wildlife habitat, and increased risk of 

invasion by nonnative plant species. Also, where 
4

BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

(6) Proportion of soil surface in large intercanopy 

gaps. This indicator is necessary to estimate erosion potential and provides data that can be used 

together with vegetation height measurements to 

create three-dimensional models of vegetation 

structure, which are necessary for wildlife habitat 

characterization. 

Contingent Indicators

Two contingent indicators are measured only when 

there is reason to believe problems that are related to 

either indicator exist on a site (see Table 1). 

(1) Soil aggregate stability. This indicator reflects 

changes in soil erodibility and is sensitive to 

changes in soil organic matter cycling. It should 

be evaluated where a model (based on bare 

ground, average precipitation, and a broad soil 

texture class) predicts that stability is less than a 

minimum value. This model scenario describes 

most rangelands, except for well-managed, midto tall-grass prairie ecosystems. Making this 

indicator contingent ensures that time will not be 

wasted on measurements of highly stable soils.

(2)	 Significant accumulation of soil toxins. This 

indicator is important because it reflects major 

threats to human and environmental health. It 

should be evaluated where there is reason to 

believe that a significant accumulation of toxins 

exists. It was not included as a core indicator 

because (a) it is extremely expensive and would 

be difficult to measure with existing budgets, (b) 

it is likely to be near zero on the majority of BLM 

lands, and (c) in most cases it should be possible 

to predict where significant accumulations of 

toxins are likely to occur.

Measurement Methods for Table 1. Core and contingent indicators for the AIM Strategy and their collection methods. Core indicators are always measured. 

Contingent indicators are only measured if there is reason to believe they are necessary for monitoring or assessing the site.

Type Indicator Method * Where applied?

Core: all locations 

Amount of bare ground, 

vegetation composition, nonnative invasive plant species, 

plant species of management 

concern

Line-point intercept (including 

modifications) supplemented 

with plot-level species inventory

All vegetation monitoring

Vegetation height Height at selected line-point 

intercept points All vegetation monitoring

Proportion of soil surface in 

large intercanopy gaps Canopy gap intercept All vegetation monitoring

Contingent: where and 

when necessary 

Soil aggregate stability Soil stability When soils are potentially 

unstable (most rangeland)

Significant accumulation of 

soil toxins Sampling for toxins in soil When toxins are believed present

* For method descriptions, refer to Table 2.
5

cover. This could have implications when comparing two measurements collected using different rule 

sets, when trying to combine these data to make larger 

scale inferences, or when trying to use the data to 

train remotely sensed imagery. This example illustrates methodological differences that can affect the 

accuracy of measurements (i.e., the estimates derived 

from each method would be different). Other types of 

modifications, such as changing the number of measurements per plot, can often be made without affecting accuracy, though they may also affect precision 

(see Modifications of Recommended Methods and the 

Ability to Aggregate Indicators).

Adopting a consistent set of monitoring methods will 

allow the BLM to combine and compare data collected in different areas and data collected to address 

different objectives. The subsequent methods were 

selected based on the following requirements: well 

documented, widely used, easy to implement, and 

minimal potential for bias. Table 2 lists each method 

and the core and contingent indicators it measures, 

gives recommendations to achieve consistent implementation across the Bureau, and provides references 

describing each method’s complete protocol. The 

protocols should be carefully followed in order to 

ensure that data collected from different areas can be 

compared or combined.

(1) Line-point intercept (LPI) with plot-level 

species inventory

Core indicators: bare ground, vegetation composition, nonnative invasive plant species, and plant 

species of management concern

LPI is a widely-used, rapid method for measuring vegetation and soil surface cover. Vegetation 

cover by species and soil surface type are measured by dropping a narrow pin (or pointer) at 

fixed intervals (i.e., points) along transects and 

recording all species that intercept the pin as well 

as the soil surface types where the pin touches 

the ground—modifications are suggested for data 

collection in tree cover (see Table 2). Precautions 

taken in standard LPI protocols contribute to it 

being one of the least biased of cover measures 

(Elzinga et al. 1998; Herrick et al. 2009).

Measurement Methods for the Core Indicators

Figure 2. Example of a common difference in measuring plant 

cover that results in incompatible data. Foliar cover (a) measures just the exposed plant area, whereas total canopy cover 

(b) measures the area of influence of the plant. Relative to each 

other, the foliar cover method will produce lower estimates of 

plant cover and higher estimates of bare ground than will a total 

canopy cover method. Because the two methods are measuring 

different aspects of plant cover, estimates from the two methods 

cannot be combined. Canopy cover estimates are often biased by 

differences in how the canopy “margins” are defined (b vs. c) by 

different observers, or by the same observer at different times, or 

for different species or morphologies.

A. B.

C.

The need to monitor standard indicators to determine 

ecosystem condition is generally accepted. With this 

in mind, the BLM has adopted the aforementioned 

indicators to describe the condition of the three key 

ecosystem attributes (i.e., biotic integrity, soil and 

site stability, and hydrologic function). Data collected 

using the six core and two contingent indicators are 

appropriate to inform a wide range of management 

questions. However, the need for standardization of 

methods and rule sets for measuring the indicators is 

less accepted. Even so, standard methods are just as 

critical as a consistent set of indicators because minor 

differences between methods that provide similar 

types of information (e.g., cover, density) can make 

measurements incompatible. 

An example of this is the difference between using 

foliar cover (i.e., actual exposed plant area) vs. canopy 

cover (i.e., area of influence of a plant) when measuring cover indicators (see Figure 2). For the same area, 

canopy cover measurements will be higher than foliar 
6

BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

Table 2. Recommended methods and measurements for core and contingent indicators

Method Indicator(s) Description Reference(s)

For core indicators

Line-point intercept with plot-level 

species inventory

Bare ground, vegetation 

composition, nonnative 

invasive plant species, 

plant species of 

management concern

Line-point intercept (LPI) is a rapid 

and accurate method for quantifying cover of vegetation and bare 

ground. However, because LPI 

can underestimate cover of uncommon species, this method is 

supplemented with searches of a 

150-ft (45.7-m) diameter standard 

plot for at least 15 minutes and 

then searching until new species detections are more than 2 

minutes apart. When performing 

LPI within tree cover, a modified 

pin method (e.g., a pivotable laser 

or extendable pin) will be used to 

capture overstory cover.

NRCS (2009) for LPI and 

species inventory, Herrick et al. 

(2009) for LPI

Vegetation height Vegetation height

Measure height of tallest leaf or 

stem of woody and herbaceous 

vegetation (living or dead) within 

a 6-in (15-cm) radius recorded for 

points along a transect. If vegetation is taller than 10 ft, a standard 

tape and clinometer method 

should be used to estimate vegetation height.

NRCS (2009)

Canopy gap intercept

Proportion of soil surface 

in large intercanopy 

gaps

Canopy gap intercept measures 

the proportion of a line covered by 

large gaps between plant canopies and is an important indicator 

of the potential for erosion. Use 

1-ft (30-cm) minimum gaps.

NRCS (2009), Herrick et al. 

(2009)

For contingent indicators

Soil stability Soil aggregate stability

This test measures the soil’s 

stability when exposed to rapid 

wetting and provides information 

on integrity of soil aggregates, 

degree of structural development, 

resistance to erosion, and soil 

biotic integrity.

NRCS (2009), Herrick et al. 

(2009)

Soil sample collection Significant accumulation 

of soil toxins

The presence and concentrations 

of toxins are assessed by collecting three samples from the soil 

surface and one sample at depths 

of 0 to 4 in (0 to 10 cm) and 4 to 8 

in (10 to 20 cm) using a soil corer 

and following the Forest Inventory 

and Analysis protocol.

USFS (2007)
BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

7

While LPI, when performed correctly, can provide 

unbiased estimates of cover for vegetation species, its precision is proportional to the number 

of points that are measured per plot location. For 

this reason, LPI can miss species that are uncommon or patchily distributed in a plot. However, 

on average, it will accurately estimate cover of all 

species. To address the “nonnative invasive plant 

species” and other “plant species of management 

concern” core indicators, LPI should be supplemented with a species inventory of a fixed-area 

plot. Plots need to be large enough to capture the 

full diversity of the site: 150-ft (45.7-m) diameter 

circular plots are recommended to be compatible 

with National Resources Inventory (NRI) data. 

Plots should be searched by one individual for at 

least 15 minutes, and then searching should continue until new species detections are more than 2 

minutes apart. Searching should be done in such a 

way as to minimize soil surface trampling. Setting 

a minimum time limit on the searching within 

the plot ensures the plot is adequately sampled, 

and stopping when a specified time between new 

detections has been reached limits the additional 

cost of implementing the plot-level inventory and 

ensures the species list is a good estimate of actual 

diversity at the site.

(2) Vegetation height

Core indicator: vegetation height

The NRI vegetation height method used by the 

Natural Resources Conservation Service is a fast 

and unbiased way to measure vertical structure of 

vegetation. The NRI vegetation height method records the height and species of the tallest living or 

dead, woody and herbaceous vegetation within a 

small radius, 15 cm or approximately 6 in (NRCS 

2009), of points at fixed intervals along the same 

transects as used for LPI. 

Although vegetation height is not commonly 

quantified using remote sensing at the present 

time, data acquisition (e.g., LiDAR, Light Detection and Ranging, or stereo-pair imagery) and 

analysis (e.g., improved algorithms for LiDAR 

or automated stereoscopic tools for photographs) 

technologies already exist that will soon be ready 

for broadscale application.

(3) Canopy gap intercept

Core indicator: proportion of soil surface in 

large intercanopy gaps

Canopy gap intercept measures the proportion of 

a transect covered by large gaps between plant 

canopies. This field-measured indicator should 

be evaluated where at least one intercanopy gap 

longer than 30 cm is observed to exist on the 

transects used to measure bare ground and vegetation composition. This value will likely be zero in 

closed canopy forests and highly productive range 

and riparian sites. Note that a “zero” can have 

high value for baseline monitoring. 

Canopy gaps are measured along the transect tape 

measure according to the NRI protocol (NRCS 

2009) by recording the start and stop location of 

each gap above a minimum size. The length of 

each gap is calculated, and the sum of the lengths 

is divided by the transect length to obtain the proportion of soil surface in large intercanopy gaps. 

The minimum gap size, as well as what types of 

vegetation (e.g., shrubs, perennial grasses, annual 

grasses, forbs) are considered to be in the canopy 

(versus which are considered as part of canopy 

gaps), must be consistent for canopy gap measurements to be aggregated. 

(4) Soil stability

Contingent indicator: soil aggregate stability

The soil stability test described by Herrick et al. 

(2009) and NRCS (2009) is a relatively simple 

method that measures the stability of soil when 

exposed to rapid wetting. This method yields 

information on soil structural development and 

resistance to erosion. 

(5) Soil sample collection

Contingent indicator: significant accumulation of 

soil toxins

The presence and concentrations of toxins should 

be measured through standardized sampling of 

soils at a site. The U.S. Forest Service’s Forest 

Inventory and Analysis (FIA) program includes 

a protocol (USFS 2007) for collecting samples at 

the soil surface and at two standard soil depths—
8

BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

0 to 4 in (0 to 10 cm) and 4 to 8 in (10 to 20 cm) 

—to test for accumulation of toxins. Under the 

FIA protocol, three soil surface samples are taken, 

and a single sample is taken at the other depths 

using a soil corer. Samples are not composited 

(i.e., multiple samples are not combined and 

mixed prior to analysis) between plots, but are 

composited within plots.
9

Modifications of Recommended Methods and

the Ability to Aggregate Indicators

that a plant hit be recorded only if a raindrop would 

hit the plant part. Points that fall within the plant 

canopy but do not intercept a leaf or stem are not 

recorded. 

Alternatively, data that have been collected using the 

same definitions but that vary with respect to aspects, 

like how many transects are sampled, the length of 

the transects, and the size of fixed-area plots, can be 

aggregated. Modifications like these affect only the 

within-plot variability, and while the variance of the 

measurements may be affected (which will affect 

the confidence of an assessment and the number of 

observations required to detect change), the meaning 

of the measurements has not been altered. Table 3 

describes modifications that can and cannot be made 

to recommended indicator methods in order to preserve the ability to aggregate local data to larger 

scales. All modifications to the protocols must be 

documented in metadata, which always accompanies 

the collected data.

To maximize the potential for aggregating measurements of the core and contingent indicators, the core 

methods should be implemented in the same manner 

throughout the BLM. The recommended methods are 

implemented in carefully prescribed ways in protocols 

like NRI and FIA to minimize variability (e.g., due to 

measurement error or differences between observers) 

and maintain the ability to aggregate data for regionaland national-level analyses. Occasionally, however, 

constraints exist that necessitate modification of the 

way the core and contingent indicator methods will be 

applied. 

The core and contingent indicator methods can be 

modified in various ways, and depending on what is 

modified, the ability to aggregate data may or may 

not be affected. In general, modifying the definitions 

of what is recorded or how it is recorded will result in 

measurements that cannot be aggregated with other 

data because the meaning of the data is not consistent. 

For example, the line-point intercept method requires 
10

BLM Core Terrestrial Indicators and Methods• BLM Technical Note 440 • August 2011

Table 3. Modifications that can and cannot be made to recommended methods in order to preserve the ability to aggregate local data to 

larger scales

Method What Can be Modified What Cannot be Modified

Line-point intercept with 

plot-level inventory

• Number and spatial distribution of transects*

• Length of transects

• Number of points per transect

• Additional information about species at all points 

or a subset of points (e.g., dead vs. live hit)

• Foliar vs. total canopy cover (must use foliar)

• Definition of litter vs. standing dead (litter is detached; standing dead is included in foliar cover)

• The minimum size of a rock fragment before it is 

considered soil (i.e., rocks smaller than 5 mm or 

about 1/4 in are considered soil)

• Size of fixed plot (circular plot of 150-ft diameter 

recommended)

• Amount of time a fixed plot is searched (searches 

should be at least 15 minutes and continue until 

new species detections are more than 2 minutes 

apart)

Vegetation height

• Number and spatial distribution of transects*

• Length of transects

• Number of points per transect

• Number of species or functional groups for which 

height is recorded (provided that tallest is always 

recorded)

Radius of circle within which maximum height is 

determined (6 in or 15 cm)

Canopy gap intercept

• Number and spatial distribution of transects*

• Length of transects

• Minimum gap size can be decreased

• Definition of canopy necessary to stop a gap (50% 

cover on any 0.1-ft (1.25-in or 3-cm) segment)

• The decision to include annual grasses and forbs 

when interrupting a gap

• Minimum gap size cannot be increased

• What happens at beginning/end of transect (gaps 

defined to ends of the transect only)

Soil stability

• Number of sampling locations within a plot

• Where samples are selected along transect (provided that it is systematic or random)

• Whether or not subsurface samples are collected 

(can help interpretation where surface disturbance 

is common)

• Time thresholds for determining stability class 

(see references in Table 2)

Soil sample collection

• Number of locations sampled within each plot

• Whether or not samples composited within plot

• Configuration of sample locations within plot

• Additional depths (greater than 8 in) or subdivision 

of recommended depths

Depths at which samples are collected (samples 

should be collected at soil surface and at depths of 0 

to 4 in and 4 to 8 in)

*Transects should be independent (not contiguous or intersecting)
11

Implications

monitoring and assessment programs that are capable 

of delivering actionable and defensible information 

must be implemented. Given resource constraints and 

the sheer number of monitoring needs, it is no longer 

possible to implement individual monitoring and assessment plans for each identified threat or use. Deriving the knowledge of how ecosystem conditions are 

changing, which is necessary to influence and justify 

management or policy action, necessitates consistent 

data that can serve many monitoring objectives and 

be aggregated for use across multiple scales. The core 

indicators and methods described here are the foundation for such a multiscale, multiobjective approach.

The AIM Strategy core indicators and methods are 

commonly used and easy to implement, and their application will help reduce error and increase compatibility of BLM monitoring efforts. They are generic 

enough to be accepted by a wide range of users and 

provide a variety of measures applicable to many different management objectives. The core and contingent indicators and associated methods can be supplemented by additional indicators to address local needs. 

The rate of change and the increase in uses on public 

lands are at unprecedented levels. In order to make 

effective management decisions and respond to 

existing and emerging threats on public lands, robust 
“In order to make effective

management decisions

and respond to existing

and emerging threats

on public lands,

robust monitoring

and assessment programs

that are capable of delivering

actionable and defensible

information must

be implemented.”
13

References

Ducey, M.J., and H.T. Valentine. 2008. Direct sampling for stand density index. Western Journal 

of Applied Forestry 23 (2): 78.

Elzinga, C.L., D.W. Salzer, and J.W. Willoughby. 

1998. Measuring and monitoring plant populations. Tech Ref 1730-1. U.S. Department 

of the Interior, Bureau of Land Management, 

National Business Center, Denver, CO. http://

www.blm.gov/nstc/library/techref.htm.

Herrick, J.E., J.W. Van Zee, K.M. Havstad, L.M. Burkett, and W.G. Whitford. 2009. Monitoring 

manual for grassland, shrubland and savanna 

ecosystems. U.S. Department of Agriculture, 

Agricultural Research Service, Jornada Experimental Range, Las Cruces, NM.

Herrick, J.E., S. Wills, J. Karl, and D. Pyke. 2010. 

Terrestrial indicators and measurements: 

Selection process and recommendations. U.S. 

Department of Agriculture. http://jornada.

nmsu.edu/sites/default/files/AIM_Terrestrial_

Indicators_Selection.pdf.

Miller, M.E. 2005. The structure and functioning of 

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