Final Report for Emergency Stabilization and Rehabilitation 

Treatment Monitoring of the Keeney Pass, Cow Hollow, 

Double Mountain, and Farewell Bend Fires

Open-File Report 2009-1152

U.S. Department of the Interior

U.S. Geological Survey

Final Report for Emergency Stabilization and Rehabilitation

Treatment Monitoring of the Keeney Pass, Cow Hollow, 

Double Mountain, and Farewell Bend Fires 

By Troy A. Wirth and David A. Pyke

Open-File Report 2009-1152

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2009 

For more information on the USGS—the Federal source for science about the Earth, its 

natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov 

or call 1-888-ASK-USGS. 

For an overview of USGS information products, including maps, imagery, and publications,

visit http://www.usgs.gov/pubprod

To order this and other USGS information products, visit http://store.usgs.gov

Suggested citation:

Wirth, T.A., and Pyke, D.A., 2009, Final report for emergency stabilization and rehabilitation 

treatment monitoring of the Keeney Pass, Cow Hollow, Double Mountain, and Farewell Bend 

fires: U.S. Geological Survey Open-File Report 2009-1152, 62 p. 

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Executive Summary....................................................................................................................................................... 1

Introduction.................................................................................................................................................................... 3

Review of Monitoring Manuals ................................................................................................................................... 3

Example Fires ............................................................................................................................................................ 3

Methods......................................................................................................................................................................... 4

Objectives .................................................................................................................................................................. 4

Stratification ............................................................................................................................................................... 5

Control Plots .............................................................................................................................................................. 5

Random Sampling ..................................................................................................................................................... 5

Data Quality ............................................................................................................................................................... 6

Statistical Analysis ..................................................................................................................................................... 6

Quantitative Field Methods ........................................................................................................................................ 6

Line-Point Intercept ................................................................................................................................................ 7

Density ................................................................................................................................................................... 7

Basal-Gap Intercept ............................................................................................................................................... 8

Results and Discussion ................................................................................................................................................. 8

Weather ..................................................................................................................................................................... 9

Keeney Pass.............................................................................................................................................................10

Keeney Pass Non-Native Seeding ........................................................................................................................11

Keeney Pass Non-Native Seeding Conclusions....................................................................................................13

Keeney Pass Native Seeding................................................................................................................................16

Keeney Pass Native Seeding Conclusions............................................................................................................18

Cow Hollow...............................................................................................................................................................18

Cow Hollow Conclusions.......................................................................................................................................23

Double Mountain.......................................................................................................................................................25

Double Mountain Non-Native Seeding ..................................................................................................................27

Double Mountain Non-Native Seeding Conclusions..............................................................................................29

Double Mountain Native Seeding ..........................................................................................................................30

Double Mountain Native Seeding Conclusions......................................................................................................30

Farewell Bend...........................................................................................................................................................35

Farewell Bend Non-Native Seeding ......................................................................................................................38

Farewell Bend Non-Native Seeding Conclusions ..................................................................................................40

Farewell Bend Native Seeding ..............................................................................................................................41

Farewell Bend Native Seeding Conclusions..........................................................................................................43

Time Requirements ...............................................................................................................................................43

Observer Comparisons .........................................................................................................................................45

Performance of Design Elements..........................................................................................................................46

Objectives..........................................................................................................................................................46

Stratification.......................................................................................................................................................47

Random Sampling .............................................................................................................................................47

Control Plots ......................................................................................................................................................48

Data Quality.......................................................................................................................................................48

Statistical Analysis .............................................................................................................................................49
iv

Contents—Continued

Farewell Bend—Continued

Performance of Quantitative Methods ...................................................................................................................49

Density Data Collection .....................................................................................................................................49

Quadrat Sizes....................................................................................................................................................51

Size Classes......................................................................................................................................................51

Species Identification.........................................................................................................................................51

Initial Differences in Control and Treatment Plots..............................................................................................52

Basal-Gap Intercept...........................................................................................................................................52

Line-Point Intercept............................................................................................................................................53

Conclusions ..................................................................................................................................................................53

Acknowledgments ........................................................................................................................................................56

References Cited..........................................................................................................................................................57

Appendix A. Monitoring Plot Locations and Soils..........................................................................................................59

Figures

Figure 1. Precipitation received (bars) after treatment and average precipitation (line) at the 

Bureau of Reclamation Ontario weather station (ONTO) from September 2005 to June 2008......................... 9

Figure 2. Location of burned and treated area, monitoring units, and monitoring plots within the 

Keeney Pass Fire (2005).................................................................................................................................12

Figure 3. Confidence interval (80%) of the difference between treatment and control densities of 

seeded grasses, shrubs, and forbs at the Keeney Pass non-native seeding, Oregon, 2008..........................15

Figure 4. Increased establishment and growth of seeded plants under burned sagebrush canopies, 

Keeney Pass burned area, Oregon. Photograph taken by Troy Wirth, May 18, 2007 .....................................19

Figure 5. Confidence interval (80%) of the difference between treatment and control densities of 

seeded grasses, shrubs, and forbs at the Keeney Pass native seeding, Oregon, 2008 .................................20

Figure 6. Location of Cow hollow fire burned and treated area including treatment and control plots, 

Oregon, 2006–08.............................................................................................................................................21

Figure 7. Abundant and small P. secunda plants that resulted in unusual basal gap variability were 

found at the Cow Hollow burned area, Oregon................................................................................................24

Figure 8. Confidence interval (80%) of the difference between treatment and control plots for 

seeded grass, shrubs, and forbs at the Cow Hollow native seeding, Oregon, 2008........................................25

Figure 9. Location of Double Mountain non-native seeding monitoring plots, Oregon, 2006–08 .................................26

Figure 10. Confidence interval (80%) of the difference between treatment and control plots for densities 

of seeded grasses, shrubs, and forbs at the Double Mountain non-native seeding, Oregon, 2008................31

Figure 11. Location of monitoring plots at the Double Mountain native seeding treatment, 

Oregon, 2006–08.............................................................................................................................................32

Figure 12. Confidence interval (80%) of the difference between the treatment and control for seeded grasses, 

shrubs, and forbs at the Double Mountain native seeding, Oregon, 2008 ......................................................34

Figure 13. Photograph of establishing seedlings in an area where P. secunda was less dense prior to 

seeding or was displaced during seeding and an adjacent area of dense P. secunda with little 

seedling establishment. ...................................................................................................................................35
v 

Figures—Continued

Figure 14. Location of Farewell Bend monitoring plots, Oregon, 2006-08 ...................................................................36

Figure 15. Soil surface conditions and rhizomatous Pseudoroegneria spicata at the Farewell Bend 

burned area, Oregon .......................................................................................................................................37

Figure 16. Confidence interval (80%) of the difference between the treatment and control at the 

Farewell Bend non-native seeding, Oregon, 2008...........................................................................................41

Figure 17. Confidence interval (80%) of the difference between treatment and control plots at the 

Farewell Bend native seeding, Oregon, 2008..................................................................................................44

Figure 18. Median person-hours to perform each quantitative procedure on one plot (three 50-m transects)............44

Figure 19. Photograph showing difficulty involved in identifying individuals within drill rows of new seedings.............50

Tables

Table 1. Seed mixes used in native and non-native drill seedings at the 2005 Keeney Pass burned area, Oregon ....13

Table 2. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Keeney Pass non-native seeding, 

Oregon, 2006–08.............................................................................................................................................14

Table 3. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Keeney Pass native seeding, 

Oregon, 2006–08.............................................................................................................................................17

Table 4. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Cow Hollow native seeding, 

Oregon, 2006–08.............................................................................................................................................22

Table 5. Seed mixes at the Double Mountain native and non-native seeding, Oregon, 2005 ......................................27

Table 6. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Double Mountain non-native seeding, 

Oregon, 2006–08.............................................................................................................................................28

Table 7. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Double Mountain native seeding, 

Oregon, 2006–08.............................................................................................................................................33

Table 8. Seed mix at the Farewell Bend non-native and native seedings, Oregon ......................................................38

Table 9. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Farewell Bend non-native seeding, 

Oregon, 2006–08.............................................................................................................................................39

Table 10. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, 

and basal cover (C), and functional group foliar cover (D) at the Farewell Bend native seeding, 

Oregon, 2006–08.............................................................................................................................................42

Table 11. Coefficients of variation between three sets of observers at the Farewell Bend and 

Keeney Pass burned areas .............................................................................................................................45
vi

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

centimeter (cm) 0.3937 inch (in.)

kilometer (km) 0.6214 mile (mi)

meter (m) 3.281 foot (ft) 

hectare 2.471 acre

square meter (m2) 0.0002471 acre 
1 

Final Report for Emergency Stabilization and 

Rehabilitation Treatment Monitoring of the Keeney Pass, 

Cow Hollow, Double Mountain, and Farewell Bend Fires 

By Troy A. Wirth and David A. Pyke

Executive Summary

A strategy for monitoring post-fire seedings in the sagebrush steppe of the Intermountain West 

was developed and used to monitor four example fires in the Vale, Oregon District of the Bureau of 

Land Management (BLM). We began to develop a potential approach by (1) reviewing previous 

vegetation monitoring manuals produced by the Federal government to determine what techniques and 

approaches had been approved for use, and (2) monitoring a set of example fire rehabilitation projects 

from 2006 through 2008. 

We reviewed seven vegetation monitoring manuals approved for use by the Federal government. 

From these seven manuals, we derived a set of design elements appropriate for monitoring post-fire 

rehabilitation and stabilization projects. These design elements consisted of objectives, stratification, 

control plots, random sampling, data quality, and statistical analysis. Additionally, we chose three 

quantitative vegetation field procedures that were objective and repeatable to be used in conjunction 

with these six design elements. 

During the spring and summer of 2006 to 2008, U.S. Geological Survey personnel monitored 

vegetation in seven post-fire seeding treatments in four burned areas in the Vale district of the BLM in 

eastern Oregon. Treatments monitored included a native and non-native seeding in each of the Farewell 

Bend, Double Mountain, and Keeney Pass fires, and a native seeding at the Cow Hollow fire. All fires 

occurred in 2005. 

There generally was a low level of plant establishment for all seedings by 2008. The quantitative 

objective established by the BLM was to achieve 5 seeded grass plants/m2

 by the end of 3 years as a 

result of the seeding. There was an estimated 3.97 and 6.28 plants/m2

 in 2006 and 1.06 and 0.85 

plants/m2 seeded perennial grasses in 2008 from the Keeney Pass non-native and native seeding, 

respectively. The Cow Hollow seeding resulted in the lowest establishment of perennial seeded grasses 

of the four project areas with 0.69 plants/m2

 in 2006 and 0.09 plants/m2 in 2008. Density of seeded 

perennial grasses at the Double Mountain non-native and native seeding were 2.72 and 3.86 plants/m2 in 

2006 and 0.90 and 1.74 plants/m2 in 2008, respectively. The Farewell Bend non-native seeding resulted 

in 5.62 plants/m2

 in 2006 and 0.42 plants/m2 in 2008 while the native seeding had 2.22 seeded grass 

plants/m2 in 2006 and 0.44 plants/m2 by 2008. The primary reason for low level of establishment on 

most treatments except the Cow Hollow seeding was most likely the unfavorable timing and amount of 

precipitation in 2007 and 2008. 
2 

Measurements of density within the first 3 years provide the best estimate of initial seeding 

success. Increases in cover due to the seedings were not detectable in the first 3 years following seeding 

in this monitoring effort. Changes in cover resulting from the treatments may be detectable in cases 

where the seedings were very successful in the first 3 years following seeding, but in areas with lower 

annual average precipitation, may not occur consistently. As a result, cover of seeded species may not 

be a good indication of seeding success in the early years after treatment. However, cover is useful for 

monitoring initial patterns of abundance of naturally recovering vegetation, exotic annual grasses and 

forbs, and bare ground. Cover measurements at these four sites revealed patterns common to most of the 

treatment areas in cover of litter, bare ground, and exotic annuals in response to drill seeding and 

weather patterns. There was a rapid increase in litter at all treatments after the fire. Additionally, there 

was less litter in treatment plots than in the control plots in 2006 probably due to the mechanical action 

of the seed drill. There also was a corresponding decrease in bare ground from 2006 to 2008. Initially, 

higher bare ground cover at treatment plots appears to be due to the mechanical action of the seed drill. 

Cover of annual grasses, primarily Bromus tectorum, increased from 2006 to 2007 and then 

decreased slightly in 2008. The highest cover and density of exotic annual grasses generally occurred in 

the second year following fire. Immediately after fire, lower densities of B. tectorum may emerge due to 

the loss of seed, but B. tectorum plants that do emerge often produce an abundance of seed due to high 

nutrient availability and reduced competition, resulting in higher densities the following year. 

There was a consistent, negative linear relationship between the amount of cover of existing 

perennial grasses and annual grass cover at treatment areas. This relationship also was apparent in the 

gap data, and annual grass cover was greatest when basal gaps in the greater-than-200-cm size class 

were more frequent. The inverse relationship between cover of perennial and annual grasses suggests 

that post-fire seedings, when successful, can improve rangeland condition where annual invasive grasses 

are problematic. 

Overall, quantitative objectives are a valuable part of monitoring the initial success of post-fire 

seedings. However, they need to be adapted for specific situations and areas. The potential of a 

particular area to reach a certain density or cover of desirable plant species (and the condition of the prefire plant community, for example, healthy or degraded) can be used to set initial objectives, which 

could be further modified by conditional statements that depend on environmental conditions after 

seeding. These conditional objectives may be developed to include a range of values rather than a 

specific target objective. Eventually, using data from many projects over time, a model could be 

developed to predict optimum seeding success over a range of conditions. Using such a dynamic 

approach to setting objectives would minimize the numbers of projects that are deemed failures due to 

unrealistic objectives or environmental factors that are outside the control of land management. 

Monitoring at the four areas from the Vale, Oregon District of the Bureau of Land Management that 

burned in 2005 also demonstrated potential uses and difficulties associated with monitoring ES&R 

(Emergency Stabilization and Rehabilitation) treatment effectiveness. Overall, the monitoring approach, 

combined with the quantitative techniques, performed reasonably well in burned areas previously 

dominated by sagebrush. Future monitoring efforts should take into account the logistical constraints of 

each design element and quantitative technique to arrive at the most cost-effective yet statistically valid 

monitoring plan. In the future, procedures that encompass more of the natural variability, either through 

sampling at more locations or incorporating the use of remote sensing may be able to capture more of 

the natural variability at the landscape scale.
3 

The value of the three quantitative techniques for interpreting success of post-fire seedings 

depends on the time frame in which they will be used. For the first 3 years following seeding (the period 

for which monitoring is usually funded), density is the most directly applicable measurement of 

treatment effect and is emphasized in this report. Changes in plant cover and basal-gap intercept 

measurements are small during the first 3 years and, when combined with environmental and observer 

variation, could not be used for determining success. As the seeding ages and plants become larger, 

however, comparison of cover and gap-intercept data between treatment and control plots can be used to 

determine long-term effects. Whether initial densities in the first 3 years correlate to later cover and 

basal-gap intercept measurements is unknown and warrants further investigation. 

In addition to assessing level of establishment at a variety of different post-fire seedings, the use 

of similar techniques to monitor Vale fires helped identify patterns common throughout multiple 

treatments. Consistent patterns of vegetation attributes identified in these four burned sites include the 

rate of accumulation of litter, the rate of decrease of bare ground, the inverse relationship between 

annual grass and forb cover, and the relationships between annual grasses with perennial grass cover 

and basal–gap intercept. Identifying additional patterns at a greater number of projects in a wider 

geographic area and correlating with site factors (such as soil, elevation, and climate) will aid efforts to 

improve seeding success through adaptive management. 

Introduction

In 2004, the BLM requested that the U.S. Geological Survey (USGS) develop an approach to 

monitor the effectiveness of ES&R treatments in sagebrush ecosystems. We began to develop a 

potential approach by (1) reviewing previous vegetation monitoring manuals produced by the Federal 

government to determine what techniques and approaches had been approved for use, and 

(2) monitoring a set of example fire-rehabilitation projects from 2005 through 2008. 

Review of Monitoring Manuals 

We reviewed seven vegetation monitoring manuals approved for use by the Federal government. 

From these seven manuals, we derived a set of design elements appropriate for monitoring post-fire 

rehabilitation and stabilization projects. These design elements consisted of objectives, stratification, 

control plots, random sampling, data quality, and statistical analysis. Additionally, we chose three 

quantitative vegetation field methods that were objective and repeatable to be used in conjunction with 

these six design elements. We produced a report entitled "Monitoring post-fire vegetation projects: A 

common approach for non-forested ecosystems" (Wirth and Pyke, 2007) that described these elements 

and quantitative procedures. 

Example Fires

During the spring and summer of 2005 through 2008, USGS personnel monitored seven burned 

areas in the Vale District of the BLM in eastern Oregon. The purposes of monitoring these fires were to 

test the methods outlined in Wirth and Pyke (2007) and determine how well they worked for evaluating 

seeding success.
4 

These burned areas and year of burn were Cherry Creek (2003), Atkins Butte (2002), Trimbly 

(2002), Farewell Bend (2005), Double Mountain (2005), Keeney Pass (2005), and Cow Hollow (2005). 

Three burned areas sampled in 2005 (Cherry Creek, Atkins Butte, and Trimbly) were monitored only in 

the third year post-seeding to test and refine the techniques for subsequent monitoring projects. Because 

we did not monitor these fires in the first and second years, it was not possible to determine natural 

vegetation recovery from the seeding or to establish control plots. This report will focus on the Keeney 

Pass, Cow Hollow, Double Mountain, and Farewell Bend burned areas.

Methods

The six design elements identified in Wirth and Pyke (2007) were used to monitor fires from 

2006 to 2008. These design elements are objectives, stratification, control plots, random sampling, data 

quality, and statistical analysis. We used the quantitative objectives developed by the BLM for the 

treatment areas at the four burned areas and were able to implement the other five design elements 

ourselves. 

We monitored post-fire treatments using quantitative field methods described in Herrick and 

others (2005a, 2005b) in conjunction with the design elements described in Wirth and Pyke (2007). We 

randomly established permanent plots within each treatment area. Each plot consisted of three 50-m 

transects radiating from a central point spaced 120° apart. In some cases, there were multiple treatments 

associated with a fire. In these cases, each treatment was monitored separately (for example, native and 

non-native seedings). At each plot, line and surface photographs were taken, and information on plot 

location and soils was gathered. Along each transect, line-point intercept (cover), density, and basal gap 

measurements were taken. Data were entered into a Microsoft© Access database (Rangeland Health 

Database; http://usda-ars.nmsu.edu/monit_assess/rangedb_main.php) developed for these techniques. 

Data were either entered in the database in the field using tablet personal computers or later in the office 

after first being recorded on field datasheets.

Objectives 

It is essential to define management and sampling objectives before implementation of any 

ES&R projects. As described in Elzinga and others (1998), management objectives are “clearly 

articulated descriptions of a measurable standard, desired state, threshold value, amount of change, or 

trend that you are striving to achieve for a particular plant population or habitat characteristics.” Welldefined management objectives in a monitoring program perform two functions: first, they establish a 

standard to measure the degree of success; and second, they determine the appropriate indicators to

measure. A standard protocol can then be followed for the measurement of each indicator; thus, datacollection activities are directly related to management objectives. Sampling objectives should be paired 

with each management objective and should specify the desired confidence level for the sampling effort. 

Quantitative objectives were written by the BLM for the Keeney Pass, Cow Hollow, Double Mountain, 

and Farewell Bend fires but did not include confidence levels. 
5 

Stratification

Stratification is the partitioning of treatment areas into monitoring units to reduce variation and 

increase precision of sampling efforts. Areas that may respond differently to ES&R treatments, such as 

different soil types or ecological sites, are good candidates for stratification. Rules for stratification of 

treatment areas into monitoring units should be created during the planning stage of an ES&R project. 

Stratification of the area for treatments and monitoring can be accomplished using a defined set of 

variables such as slope, aspect, elevation, treatment type, minimum size, soil type, or ecological site. 

Stratification of the area within the fire perimeters consisted of separately monitoring drill 

seedings with different seed mixes and eliminating slopes greater than 20% where the seed drill was 

unlikely to cover. Therefore, data can only be extrapolated within each treatment area and for slopes less 

than 20%. 

Control Plots

Control plots are locations within a proposed treatment area that are established prior to 

treatments and avoided when treatments are applied. Control plots provide a direct measurement of the 

treatment effect (for example, seeded plants) and also a measurement of natural recovery without 

treatment, helping to make a determination about whether or not treatments were necessary. In the 

absence of control plots, comparing measurements at treatment areas to established quantitative 

objectives can be used to determine treatment effectiveness. 

Placement of control plots is an important pre-treatment activity. Control plots placed randomly 

within each monitoring unit will minimize the chances of bias and enable statistical inference. Control 

plots that are placed in adjacent untreated areas cannot be guaranteed to be similar to the treated areas, 

thereby reducing the value of the comparison. At the Keeney Pass, Cow Hollow, Double Mountain, and 

Farewell Bend burned areas, we marked areas for control plots before the seeding. Seeding operators 

avoided these areas, and control plots were subsequently established at these locations.

Random Sampling

Random sampling ensures that monitoring data are unbiased and representative of the 

monitoring units. Random sampling is essential for defensible determinations of treatment effectiveness. 

Monitoring data that are not collected using random sampling are subject to criticism that data only 

came from areas where treatments were effective, or that data were biased by the site-selection process.

This raises doubts about conclusions drawn from such data. In addition, data that are not derived from 

random sampling cannot be extrapolated to the rest of the treatment area and are only valid at the plot 

where those data were collected. There are several different methods of random sampling that can be 

used to establish ES&R monitoring plots: simple random sampling, systematic random sampling, 

restricted random sampling, or two-stage sampling (Elzinga and others, 1998). It also is necessary to 

ensure that the sample is representative of the entire area that is being monitored. One of these methods 

of random sampling is essential to enable statistical inference over as much of treated area as possible.

At each treatment area, we generated a set of random points and used these for locations of 

treatment and control plots. We ensured that plots were scattered throughout the treatment area by either 

dividing treatment areas into equal areas and using one random plot in each area (restricted random 

sampling) or using random locations that were scattered throughout the treatment area (simple random 

sampling). 
6 

Data Quality

After collecting monitoring data, it is helpful to assess data quality. This can be done by 

examining measures of variability such as standard deviations, standard errors, and confidence intervals. 

Other parameters such as precision, minimum detectable change, and power also can be examined. The 

magnitude of these parameters can then be taken into consideration when making decisions about 

treatment success.

Confidence intervals can be easily constructed and displayed graphically to demonstrate the 

quality of the data for managers and researchers. For the fires discussed in this monitoring report, we 

constructed confidence intervals of the difference between the treatment and control for the parameters 

associated with the stated objectives as a measure of overall treatment success.

Statistical Analysis

Statistical analysis of monitoring data can consist of simple comparisons between treated and 

untreated areas, or between treated areas for two different time periods. Using graphical analysis to 

display these comparisons can provide more information to land managers than using t-tests or more 

complicated statistics (Di Stefano, 2004). We examined 80% confidence intervals of the difference 

between control and treatment populations for seeded species as a way to visualize the effect of seeding 

treatments and to show the data’s variation. This technique uses the difference between the mean of the 

two populations of interest (treatment and control) and constructs a confidence interval around the 

difference in means. If the confidence interval does not include zero, then the treatment and control are 

considered statistically different from each other. In this report, eighty percent confidence intervals are 

used to be reasonably confident that a type I error (false-change error) will not be committed. This 

means we are 80% confident that we will detect a change when it does occur, but there is a 20% chance 

of concluding there was a change when there was not. This may seem like a low level of confidence, yet 

using an 80% confidence interval also helps to protect against type II errors. Type II errors, or missedchange errors, occur when a change actually occurred but was not detected. In management situations a 

missed-change error could be just as serious as a false-change error so it is important to protect against 

both types. There is an inverse relationship between type I and type II errors, meaning that very high 

percentage confidence intervals increase the risk of a type II error. For this reason, we have chosen to 

report 80% confidence intervals in this report.

Quantitative Field Methods

At each plot, a center point and the start and end of each transect were permanently marked with 

a metal or plastic stake. Two photographs were taken along each transect, one from the center of the plot 

looking down the transect and one surface photograph at a random location along each transect. Both 

information describing location (GPS coordinates, slope, aspect, topographic position) and soils ( type, 

texture, depth) were collected. Additional information, such as presence of drill rows and offsite 

influences, was noted. 

Three procedures for collecting vegetation information were used at each plot. These were linepoint intercept, density (belt and quadrat), and basal-gap intercept (Herrick and others, 2005a). These 

three quantitative procedures measure indicators of three key attributes of rangeland health; soil and site 

stability, hydrologic function, and biotic integrity (Herrick and others, 2005a). Line-point intercept 

measures the aerial coverage and type of biota, the amount of soil protected from erosion by rock, litter, 

or biological crust cover, and the amount of bare soil exposed to potential wind or water erosion. 

Density measurements quantify the number of individuals of each plant species or functional group and 
7 

when combined with cover data, provide a picture of the plant community at a site. Basal-gap intercept 

measurements quantify the size and amount of large gaps between plant bases, which can be used to 

track susceptibility to runoff and water erosion. Data for each parameter were first averaged over the 

three transects to derive a plot estimate. Plot estimates at all treatment and control plots were then 

averaged together to derive values for the entire monitoring unit. 

Line-Point Intercept 

At every meter along each 50-m transect, a pin was lowered to the ground at a 90° angle to the 

transect line. Each plant and type of soil surface that intercepted the pin was recorded at each point. 

Plants intercepted at each point were categorized as “top canopy,” “lower canopy,” or “basal cover.”

The soil surface was recorded as litter, bare soil, rock, moss, or the base of plant (Herrick and others, 

2005a). 

Several types of cover data were derived using the line-point intercept procedure and are 

presented in this report.

• Vegetation-foliar cover is the proportion of the soil surface covered by a vertical projection 

of a plant canopy (Herrick and others, 2005b) regardless of plant species or functional group. 

It is derived by counting only "top canopy" data from the line-point intercept technique. For 

example, if total foliar cover of perennial grasses was 20%, this would mean that 20% of the 

ground surface of an area had perennial grasses as the uppermost vegetation layer. 

• Basal cover is the proportion of the soil surface covered by the base of perennial plants (for 

example, the stem of a perennial forb or the crown of a bunchgrass). 

• Bare-ground cover is defined as surfaces that are not covered by aerial or basal vegetation, 

litter, rock, or biological soil crusts. Bare ground is a measure of the amount of area that is 

exposed to direct raindrop impact. 

• Species or functional-group foliar cover is defined as the proportion of the total ground 

surface covered by a particular plant species or functional group. The foliar cover for each 

functional group is reported as though there were no other vegetation above it or below it so 

that cover of all species or functional groups may exceed 100%. For example, if there were 

20% cover of deep-rooted perennial grasses and 20% cover of shallow-rooted perennial 

grasses, there could be a total of 40% of the ground surface covered by perennial grasses. 

But this is unlikely because some shallow-rooted perennial grasses occur underneath deeprooted perennial grasses, resulting in vegetation foliar cover of less than 40%. 

Density 

Three different sizes of quadrats were used for density estimates. The largest was a belt transect. 

This belt typically was 6 × 50-m (300 m2) and was used to determine the density of large and lesscommon plants. The intermediate size was a set of ten, 1 × 1-m quadrats that were placed at 5-m 

intervals along each 50-m transect with a randomly chosen beginning location between 0 and 4 m. This 

resulted in 30, 1 × 1-m quadrats per plot. Within these intermediate quadrats, we counted small, 

common target species including deep-rooted perennial grasses (seeded and unseeded) and seeded forbs 

and shrubs. If we did not encounter at least 10 individuals of any of the target species in the 1 × 1-m

quadrats, we then searched for the plant using the belt transect. Within each 1 × 1-m quadrat, we placed 

a 20 × 20-cm subquadrat (0.04 m2

) that we used to estimate density of exotic annual grasses. Shallowrooted perennial grasses such as Poa secunda (Sandberg's bluegrass) and Poa bulbosa (bulbous 

bluegrass) were not counted in any of the density quadrats due to the difficulty in identifying 

individuals. Cover data were used to measure the abundance of these two species.
8 

We attempted to distinguish plants seeded in 2005 versus naturally occurring plants or plants 

seeded in prior (pre-2005) treatments. The original approach was to separate all plants into three size 

classes (A = seedling, B = juvenile, and C = adult). Theoretically, in the first year after a seeding, only 

size class A plants would be attributed to the seeding and in the second year, size classes A and B would 

be attributed to the seeding. This was supposed to allow the determination of the success of the seeding. 

In reality, some plants that were class B in the second year were potentially pre-existing plants.

Likewise, some plants that were class C in the first or second year may have been highly vigorous 

seedlings. As a result, we modified our density procedure so that a determination about whether a plant 

was seeded or unseeded was made while reading plots, and each plant was explicitly labeled seeded or 

unseeded. This appears to be the most accurate method. As a result of this change in methods, 2007 data 

are not presented in this report. In 2008, plants were carefully separated into seeded and unseeded 

categories. In this report, density data from 2006 and 2008 are presented.

 Basal-Gap Intercept

Along each 50-m transect, the starting and ending points of each gap between bases of perennial 

plants (grasses, shrubs, and forbs) were recorded. The total length of each gap was determined and 

placed into one of four gap-size classes (25–50, 51–100, 101–200, and 200+ cm). The percentage of the 

line occupied by each gap-size class was then determined. 

Results and Discussion

The Keeney Pass, Cow Hollow, and Double Mountain burned areas had the same monitoring 

objectives. These were: 

1. To establish seeded grass densities of 5 plants/m2 by the end of the third growing season following 

the wildfire in the key area.

2. To limit Bromus tectorum (cheatgrass) density to not more than 100 plants/m2 by the end of the third 

growing season following wildfire control. 

3. To obtain a total percent cover (live plants, litter, standing dead, and gravel/rock) value of 

± 10% of adjacent unburned rangeland on the same ecological site within two growing seasons 

following wildfire control.

4. To obtain seed production on 90% of the perennial native grass and forb plants and 70% of the 

bitterbrush plants that were burned relative to seed production on adjacent unburned rangeland on 

the same ecological site prior to reintroduction of livestock to the burned area. 

Of these four quantitative objectives, monitoring by the USGS from 2006 to 2008 addressed 

objectives 1 and 2. Data were not collected on unburned, adjacent rangeland because it was not clear if 

the adjacent areas were equivalent to the burned area prior to the fire. Control plots were used to derive 

a direct measurement of treatment effect. The objective of the Farewell Bend seeding was to reach 

5 seeded plants/m2

 by the end of the third year of monitoring. 

Recent detailed soil surveys were not available for the Keeney Pass, Cow Hollow, and Double 

Mountain burned areas. Soils at the Farewell Bend burned area were within a recent soil survey; 

however, due to the small size of the treatment areas and the complexity of soils in the area, the soil 

surveys were not used to further stratify the treatment areas.
9 

Weather 

The 17-year average precipitation (1991–2007) for the area as measured using the Agrimet 

weather station, Ontario Oregon Weather Station (ONTO) in Ontario, Oregon, was 26.8 cm. This 

weather station is located at an elevation of 689 m (2,260 ft) and approximately 13 km northeast from 

Keeney Pass, 17 km northeast from Cow Hollow, 30 km northeast from Double Mountain, and 47 km 

southeast from Farewell Bend. The area received above average precipitation (36.6 cm) in 2006, and 

below average precipitation for water years 2007 (14.5 cm) and 2008 (16.0 cm) (Bureau of 

Reclamation, http://www.usbr.gov/pn/agrimet/yearrpt.html). Initial conditions for the seeding were 

excellent. Above average precipitation from October 2005 through January 2006 recharged soil 

moisture (fig. 1). February 2006 received approximately one-half of the average precipitation but this 

was ameliorated by above average rainfall in March and April 2006. After this, 23 of the following 26 

months received below average precipitation with only 2 months of average rainfall and 1 month of 

above average rainfall. The early part of water year 2007 (September–December) almost reached 

average levels but was then followed by 6 months of less than average precipitation. Overall, 2006 was 

an excellent year for plant growth in terms of timing and amount of rainfall. Both timing and amounts of 

precipitation were extremely poor in 2007 and 2008, although 2008 was slightly better. Sept. 2005 Oct. 2005 Nov. 2005 Dec. 2005 Jan. 2006 Feb. 2006 Mar. 2006 Apr. 2006 May 2006 Jun. 2006 Jul. 2006 Aug. 2006 Sept. 2006 Oct. 2006 Nov. 2006 Dec. 2006 Jan. 2007 Feb. 2007 Mar. 2007 Apr. 2007 May 2007 Jun. 2007 Jul. 2007 Aug. 2007 Sept. 2007 Oct. 2007 Nov. 2007 Dec. 2007 Jan. 2008 Feb. 2008 Mar. 2008 Apr. 2008 May 2008 Jun. 2008 Precipitation (cm)

0

2

4

6

8

10

Figure 1. Precipitation received (bars) after treatment and average precipitation (line) at the Bureau of Reclamation 

Ontario weather station (ONTO) from September 2005 to June 2008. Blue outlined bars indicate above average 

precipitation for that month, red outlined bars indicate below average monthly precipitation, and gray bars indicate 

average monthly precipitation.
10

Keeney Pass

The Keeney Pass fire was sparked by lightning on August 8, 2005. It was ignited and contained 

on the same day, after burning a total of 1,481 ha (3,665 acres) of BLM land. The potential plant 

community in the burned area consists of an overstory of basin big sagebrush (Artemisia tridentata ssp. 

tridentata) and Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) and an understory of 

deep rooted perennial grasses, such as Achnatherum hymenoides (Indian ricegrass), Heterostipa comata

(needle and thread), Pseudoroegneria spicata (bluebunch wheatgrass) and Achnatherum thurberianum

(Thurber's needlegrass), along with the shallow-rooted perennial grass Poa secunda (Sandberg 

bluegrass) (Bureau of Land Management, 2005a). The pre-fire plant community had changed 

significantly from this potential plant community and consisted of some perennial grasses, primarily 

P. secunda or previously seeded grasses Agropyron cristatum (crested wheatgrass) and Elymus 

wawawaiensis (Snake River wheatgrass) with B. tectorum and exotic annual forbs as common 

components. In some areas with deeper soils on the west side of Lincoln Bench, there are some remnant 

Elymus cinereus (basin wildrye) plants as well. Soils in the Keeney Pass area generally are silt loams 

similar to Nyssa silt loam. Nyssa silt loam is moderately deep and well-drained, mildly to moderately 

alkaline, and often with a weakly cemented pan. The elevations in the Keeney Pass area range from 

795 to 885 m (2,608 to 2,903 ft). 

Two drill seeding treatments were applied to the Keeney Pass fire burned area, a non-native 

seedmix of 210 ha (519 acres) and native seedmix of 865 ha (2,141 acres) (fig. 2). Correspondingly, we 

delineated two monitoring units. The native seeding monitoring unit consisted of areas of 0–20% slope 

that received drill seeding with the native seed mix (table 1). The non-native monitoring unit consisted 

of the areas of 0–20% slope that received drill seeding with the non-native seed mix. The seedmixes 

were not well documented and these species and rates are the best estimates for what was actually 

seeded. In the non-native treatment, seeded P. spicata was found at treatment plots even though it was 

not included in the documented seedmix. 

Three of each control and treatment plots were placed within the non-native seeding, and five of 

each control and treatment plots were placed within the native seeding. One treatment plot, originally

intended to be in the native seeding treatment, was inadvertently placed on private land and was 

subsequently removed. All plots were randomly placed within the respective treatment areas. The exact 

coordinates of the monitoring plots are given in appendix A, table A1 and soil information is presented 

in table A2 

Within the perimeter of each treatment were previously seeded stands of perennial grasses, 

A. cristatum in the non-native seeding and E. wawawaiensis in the native seeding treatment. Due to the 

random location of plots, a different number of control and treatment plots were placed within these old 

seedings, causing a difference in initial values of vegetation parameters between control and treatment 

plots. In the non-native treatment, two treatment plots and one control plot were in the old A. cristatum

seeding. In the native treatment, one treatment plot and two control plots were in the old 

E. wawawaiensis seeding. 
11

Keeney Pass Non-Native Seeding 

Densities of seeded grasses in the non-native seeding treatment plots were 3.97 plants/m2 in 

2006 and 1.06 plants/m2 in 2008. Established seeded grasses were primarily A. cristatum/A. fragile

(0.74 plants/m2), P. spicata (0.18 plants/m2), and Thinopyron intermedium (pubescent wheatgrass) 

(0.10 plants/m2

). From 2006 to 2008, seeded forbs decreased from 0.16 to 0 plants/m2, and seeded 

shrubs were found at only 0.01 plants/m2 by 2008 (table 2A). There were initial differences in densities 

of both non-seeded perennial grasses and B. tectorum between treatment and control plots resulting 

from differential plot placement within the old A. cristatum seedings. The density of non-seeded 

perennial grasses remained the same between 2006 and 2008 while the density of B. tectorum increased 

significantly in 2007 and decreased slightly in 2008. 

Most gaps at both treatment and control plots in the non-native seeding were in the > 200 cm 

gap-size class (table 2B). During the 3-year monitoring period, there were no changes in percentages of 

transects occupied by any of the gap-size classes due to the seeding. 

Vegetation foliar cover and bare ground decreased in treatment plots and remained constant in 

control plots from 2006 to 2008 (table 2C). Basal cover in treatment plots increased from 2.8 to 5.1% 

from 2006 to 2008, and increased less than 1% in control plots during the same time period. Functional 

group foliar cover of deep-rooted perennial grasses were initially different due to the unequal 

distribution of plots in the old A. cristatum seeding. Foliar cover of both deep- and shallow-rooted 

grasses were within 2% in all 3 years of monitoring in treatment plots (table 2D). Shallow-rooted 

perennial grasses in control plots showed higher variability and decreased from 13.8% in 2006 to 9.3% 

in 2007, and then increased to 17.1% in 2008. There were no detectable differences in cover of deep- or 

shallow-rooted perennial grasses, forbs, or shrubs due to the seeding. Foliar cover of exotic grasses, 

primarily B. tectorum, increased in 2007 and decreased in 2008, and cover of exotic annual forbs 

followed the opposite pattern, with a substantial decrease in 2007 followed by an increase in 2008. 

Cover of litter increased 47% in treatment and 20% in control plots over the 2006 to 2008 monitoring 

period. 
12

Figure 2. Location of burned and treated area, monitoring units, and monitoring 

plots within the Keeney Pass Fire (2005).
13

Table 1. Seed mixes used in native and non-native drill seedings at the 2005 Keeney Pass burned area, Oregon.

Native seed mixa PLSb

(lb/acre) Non-native seed mixa PLSb(lb/acre)

‘Anetone’ bluebunch wheatgrass

(Pseudoroegneria spicata) 6.00 ‘Vavilov’ Siberian wheatgrass(Agropyron fragile) 0.57

‘Trailhead’ basin wildrye

(Elymus cinereus) 1.00 ‘P27’ Siberian wheatgrass(Agropyron fragile) 2.27 

‘Luna’ pubescent wheatgrass

(Thinopyron intermedium) 0.34 ‘Fairway’ crested wheatgrass(Agropyron cristatum) 1.14

‘Arriba’ western wheatgrass

(Pascopyrum smithii) 0.17 'Hycrest' wheatgrass(Agropyron cristatum) 1.70

‘Ladak’ alfalfa

(Medicago sativa) 0.40 ‘Nordan’ crested wheatgrass(Agropyron cristatum) 0.40

‘Apar’ Lewis flax

(Linum lewisii) 0.10 ‘Trailhead’ basin wildrye(Elymus cinereus) 1.02

‘Eski’ sainfoin

(Onobrychis viciifolia) 0.40 ‘Luna’ pubescent wheatgrass(Thinopyron intermedium) 1.02

Fourwing saltbush

(Atriplex canescens) 0.03 ‘Ladak’ alfalfa(Medicago sativa) 0.23

Wyoming big sagebrush

(Artemisia tridentata ssp. wyomingensis) 0.01 ‘Eski’ sainfoin(Onobrychis viciifolia) 0.40

‘Apar’ Lewis flax

(Linum lewisii) 0.11

Fourwing saltbush

(Atriplex canescens) 0.06

Wyoming big sagebrush

(Artemisia tridentata ssp. wyomingensis) 0.01

TOTAL 8.45 TOTAL 8.93

a

Seedmixes are named native or non-native depending on the species that compose the majority of the seedmix. Single 

quotes surround registered cultivar names for species.

b

PLS = pure live seed

Keeney Pass Non-Native Seeding Conclusions

The density objectives for seeded perennial grasses and exotic grasses (B. tectorum) were not 

met at the Keeney Pass non-native seeding. Established seeded-grass density was estimated to be 

between 0.47 and 1.65 plants/m2

 with a mean of 1.06 plants/m2 (80% confidence, fig. 3). An estimated 

10,600 perennial grass plants/ha were established as a result of the seeding, and this is a significant 

increase compared to the control plots (fig. 3). There were no significant differences between the 

treatment and control for seeded shrub (A. tridentata) and forb species (fig. 3). Density of B. tectorum

was 6 to 12 times higher than the 100 plants/m2 target objective in all years of monitoring (table 2A). 

Disturbances of fire and drill seeding combined with climate and competition from naturally recovering 

vegetation seemed to play a greater role in population dynamics of B. tectorum than the newly 

established seeded plants. The relatively low density and small size of seeded plants had little effect on 

the density of B. tectorum at this early stage in the seeding. 
14

Table 2. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Keeney Pass non-native seeding, Oregon, 2006–08.

A.

Functional groupa Non-native seeding treatment

(plants/m2)b

Non-native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 1.73 (0.82) 1.81 (0.93) 0.40 (0.40) 0.412 (0.42)

NS shrubs 0.14 (0.11) 0.00 0.09 (0.08) 0.01 (0.01)

SD perennial grass 3.97 (1.01) 1.06 (0.31) 0.01 (0.01) 0.00

SD shrubs 0.00 0.01 (0.01) 0.00 0.00

SD forbs 0.16 (0.06) 0.00 0.02 (0.02) 0.00

2006 2007 2008 2006 2007 2008

B. tectorum 633 (176) 1220 (383) 1091 (362) 949 (205) 1474 (376) 1190 (422)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap size (cm)

Non-native seeding treatment

(percent of line)

Non-native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25–50 6.4 7.9 7.7 5.0 5.2 5.1

51–100 11.4 8.4 11.7 7.0 6.5 6.6

101–200 14.6 12.3 13.3 5.9 5.2 4.6

>200 57.4 61.5 56.9 74.7 75.3 74.4

C.

Cover

Non-native seeding treatment

(percent cover)

Non-native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation 

foliar cover 79.3 75.7 67.6 81.5 79.1 79.6

Bare ground 18.1 17.0 12.7 7.3 7.0 6.4

Basal cover 2.8 3.1 5.1 1.5 2.2 2.4
15

Table 2. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Keeney Pass non-native seeding, Oregon, 2006–08.—Continued

D.

Functional Group 

Foliar Covera

Non-native seeding treatment

(percent cover)b

Non-native seeding control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 13.6 (7.2) 13.1 (7.7) 15.6 (8.5) 4.9 (4.9) 4.4 (4.4) 5.8 (5.8)

SR perennial grass 13.3 (12.7) 11.8 (11.1) 13.3 (12.7) 13.8 (13.8) 9.3 (9.3) 17.1 (16.8)

Perennial forbs 0.4 (0.4) 0.2 (0.2) 0.4 (0.2) 0.2 (0.2) 3.3 (2.4) 0.9 (0.6)

Shrubs 0.0 (0.0) 0.0 (0.0 ) 0.0 (0.0) 0.2 (0.2) 0.2 (0.2) 0.0 (0.0)

Exotic annual grass 52.0 (12.0) 56.2 (14.8) 40.4 (16.8) 66.9 (11.1) 70.7 (15.5) 59.3 (19.7)

Exotic annual forbs 14.9 (5.7) 1.1 (0.8) 7.8 (3.5) 10.9 (3.1) 3.8 (2.6) 8.4 (3.9)

Litter 20.7 (5.0) 51.3 (2.0) 67.8 (6.0) 65.1 (14.6) 79.6 (13.5) 85.3 (6.3)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses primarily B. tectorum. 

b

Numbers in parentheses are standard errors.

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -0.5

0.0

0.5

1.0

1.5

2.0

Treatment - Control

Figure 3. Confidence interval (80%) of the difference between treatment and control 

densities of seeded grasses, shrubs, and forbs at the Keeney Pass non-native seeding, 

Oregon, 2008.
16

Keeney Pass Native Seeding 

Densities of seeded grasses at the native-seeding treatment plots decreased from 6.28 plants/m2 

in 2006 to 0.85 plants/m2 in 2008 (table 3A). Established seeded grasses in 2008 primarily were

P. spicata (0.35 plants/m2), T. intermedium (0.15 plants/m2), and unknown, non-reproducing grasses 

(0.33 plants/m2

). Of the four treatment plots, one had few seeded plants in 2006 and none in 2008. The 

other three plots had substantially more seeded grasses with a range of 4.10 to 14.00 plants/m2 in 2006, 

which decreased to 0.20 to 1.60 plants/m2 in 2008. Seeded sagebrush decreased from 0.93 to 0.11 

plants/m2 and seeded forbs decreased from 1.25 to 0.08 plants/m2 during the same time period. 

There also was a large increase in the density of B. tectorum (451 to 1,309 plants/m2) in 

treatment plots from 2006 to 2007 but less of an increase at control plots (450 to 764 plants/m2

) during 

the same time. In general, establishment was very patchy and areas with high seedling establishment 

tended to be on locations that were previously occupied by sagebrush that had been burned to mineral 

soil with no remaining litter (fig. 4). 

Most gaps in control plots and treatment areas were > 200 cm (table 3B). There were no 

significant (greater than 5%) changes in the percentages of gaps of each of the four classes over the 

3-year monitoring period at either treatment areas or control plots. There also were no differences 

between control plots and treatment areas in any of the gap-size classes except for a slight initial 

difference between the 101–200 cm gap-size class, with treatment plots having a slightly greater 

percentage of gaps in this size class than the control plots (18.9 versus 11.1% in the treatment and 

control plots in 2006, respectively). 

Overall vegetation foliar cover at treatment and control plots increased slightly from 2006 to 

2008 (table 3C). There was initially a higher percentage of bare ground at treatment plots in 2006 (26.1 

versus 16.6%). By 2008, enough litter and cover had accumulated that treatment and control plots had 

similar amounts of exposed soil. 

Overall, deep-rooted perennial grasses increased slightly from 2006 to 2008 in both treatment 

and control plots (table 3D). Shallow-rooted perennial grasses increased in treatment plots from 2006 to 

2008 and stayed stable at control plots in 2006 and 2008, with a decrease in 2007. Cover of exotic forbs, 

primarily Erodium cicutarium (redstem storksbill) and Salsola tragus (salsify), generally followed the 

pattern of precipitation with higher cover in 2006, lower cover in 2007, and slightly higher cover in 

2008. Cover of B. tectorum increased from 2006 to 2007 and decreased in 2008. Cover of litter was 

initially different between treatment and control plots in 2006 but had reached equivalent values by 

2008 (77.7 versus 72.0%). 
17

Table 3. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Keeney Pass native seeding, Oregon, 2006–08.

A.

Functional groupa

Native seeding treatment

(plants/m2)b

Native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 0.62 (0.34) 0.63 (0.33) 2.04 (0.95) 2.08 (0.98)

NS shrubs 0.00 0.00 0.00 0.00

SD perennial grass 6.28 (2.93) 0.85 (0.43) 0.13 (0.10) 0.00

SD shrubs 0.93 (0.52) 0.11 (0.08) 0.00 0.00

SD forbs 1.25 (0.57) 0.08 (0.07) 0.03 (0.02) 0.00

2006 2007 2008 2006 2007 2008

B. tectorum 451 (166) 1,309 (225) 918 (178) 450 (214) 764 (336) 751 (341)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap size (cm)

Native seeding treatment

(percent of line)

Native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25–50 7.3 7.5 7.4 9.3 9.6 11.1

51–100 11.6 11.9 10.4 11.1 11.8 11.5

101–200 18.9 16.9 18.0 11.1 10.1 9.1

>200 51.6 53.2 53.2 53.1 52.0 48.5

C.

Cover

Native seeding treatment

(percent cover)

Native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation foliar 

cover

70.0 74.8 75.7 75.4 76.4 78.9

Bare ground 26.1 20.2 8.0 16.6 12.9 8.8

Basal cover 2.7 4.2 3.3 3.2 5.2 7.3
18

Table 3. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Keeney Pass native seeding, Oregon, 2006–08.—Continued

D.

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses primarily B. tectorum. 

b

Numbers in parentheses are standard errors.

Keeney Pass Native Seeding Conclusions

The density of seeded species in 2008 did not reach the original objective of 5 plants/m2 at the 

Keeney Pass native seeding. Density of seeded grasses were estimated to be between 0.14 and 1.56 

plants/m2 with a mean of 0.85 plants/m2 (80% confidence, fig. 5). An estimated 8,500 plants/ha were 

established as a result of the seeding, and this is a significant increase compared to the control (fig. 5). 

There were no significant differences between treatment and controls for seeded forbs and shrubs, 

although some plants did establish in the treatment area (fig. 5). Density of B. tectorum was 

significantly higher than the 100 plants/m2 objective (table 3A), and, as previously noted, demographics 

of B. tectorum seemed to be primarily driven by recent disturbance and climatic conditions rather than 

competition with seeded plants in the initial 3 years at the Keeney Pass non-native seeding. 

Cow Hollow

The Cow Hollow fire occurred at the same time as the Keeney Pass fire (ignited and contained 

on August 8, 2005) and burned a total of 315 ha (779 acres) (Bureau of Land Management, 2005a, 

fig. 6). The potential plant community is similar to that described for the Keeney Pass area due to the 

close proximity of the two burned areas. The potential plant community in the area is a shrub overstory 

of primarily Wyoming big sagebrush (A. tridentata ssp. wyomingensis) with deep-rooted perennial 

grasses such as A. hymenoides (Indian ricegrass), H. comata (needle and thread) and P. spicata

(bluebunch wheatgrass) and A. thurberianum (Thurber's needlegrass) along with the shallow-rooted

perennial grass P. secunda (Sandberg bluegrass). In many areas within the burn perimeter, P. secunda

forms dense patches with very few of the deeper rooted perennial grasses present. Additionally, some 

areas within the seeding have been previously seeded with A. cristatum. 

Functional Group 

Foliar Covera

Native seeding treatment

(percent cover)b

Native seeding control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 7.0 (3.2) 6.7 (2.8) 7.5 (4.4) 19.7 (10.5) 19.3 (3.5) 22.4 (12.1)

SR perennial grass 14.5 (5.1) 19.0 (6.0) 19.2 (5.7) 23.6 (10.4) 18.5 (7.4) 24.9 (10.1)

Perennial forbs 0.7 (0.5) 0.3 (0.2) 0.5 (0.3) 0.7 (0.5) 1.6 (1.1) 0.5 (0.3)

Shrubs 0.0 0.0 0.2 (0.2) 0.0 0.0 0.0

Exotic annual grass 51.0 (8.7) 64.7 (8.8) 57.3 (8.3) 38.8 (14.7) 46.1 (18.0) 29.1 (15.8)

Exotic annual forbs 12.0 (6.2) 5.5 (1.3) 7.5 (2.7) 16.9 (8.2) 7.7 (4.8) 9.1 (5.6)

Litter 25.2 (14.2) 51.7 (10.3) 77.7 (5.3) 47.1 (15.2) 65.7 (11.8) 72.0 (10.8)
19

Figure 4. Increased establishment and growth of seeded plants under burned sagebrush canopies, Keeney Pass 

burned area, Oregon. Photograph taken by Troy Wirth, May 18, 2007. 
20

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -1

0

1

2

Treatment - Control

Figure 5. Confidence interval (80%) of the difference between treatment and control 

densities of seeded grasses, shrubs, and forbs at the Keeney Pass native seeding, 

Oregon, 2008.

Soils at the Cow Hollow treatment area were Nyssa silt loams. Nyssa silt loam is moderately 

deep and well-drained, and mildly to moderately alkaline. It often has a weakly cemented pan (Oregon 

State Water Resources Board, 1969). The elevation at the Cow Hollow burned area ranged from 815 to 

845 m (2,673 to 2,772 ft). 

The native seedmix applied at the Keeney Pass fire was also applied to the Cow Hollow burned 

area. The entire 315 ha were treated. The monitoring unit consisted of all areas that were drilled with the 

native seed mix between 0 and 20% slopes. Within this monitoring unit, we randomly placed five 

treatment and four control plots. 

Seeded grass densities at the treatment plots were 0.69 plants/m2 in 2006 and 0.09 plants/m2 in 

2008 (table 4A). Seeded grasses were primarily T. intermedium (0.04 plants/m2

), and P. spicata 

(0.04 plants/m2). Seeded forb densities were 0.14 plants/m2 in 2006 and 0.04 plants/m2 in 2008. Density 

of sagebrush seedlings were 0.05 plants/m2 in 2006 and 0.01 plants/m2 in 2008. Density of B. tectorum

increased significantly in 2007 and increased again slightly in 2008. 
21

Figure 6. Location of Cow hollow fire burned and treated area including treatment and control 

plots, Oregon, 2006–08.
22

Basal gaps were highest in the > 200 cm size class from 2006 to 2008 (table 4B). However, 

while > 200 cm basal gaps were most prevalent, the percentage in this size class was lower than other 

treatment areas (for example, Keeney Pass) due to a large abundance of P. secunda. The P. secunda

often existed in a wide range of sizes, from large, well-defined bunches to small, amorphous bunches 

interspersed with dead areas and single tillers (fig. 7). In this situation, very small plants are difficult to 

see, which increased variability between observers and years. Although variable, the data show a 

decrease in gaps in the > 200 cm size class from 2006 to 2008. 

Vegetation foliar cover increased slightly in both treatment and control plots in 2007 and then 

decreased slightly from 2007 to 2008 (table 4C). There was a similar amount of bare ground at both 

treatment and control plots in 2006 (23.3 versus 23.5%) which subsequently decreased to 7.3 and 8.7% 

in the treatment and control plots by 2008. 

Functional group foliar cover of deep-rooted perennial grasses at the Cow Hollow seeding was 

low and stayed low throughout the monitoring period (table 4D). In contrast, shallow-rooted perennial 

grasses (P. secunda) were abundant but changed little. Cover of exotic annual grasses increased in 2007 

and decreased in 2008. Cover of exotic annual forbs declined in both 2007 and 2008. Cover of litter

increased significantly from 2006 to 2008 at the treatment and control plots. 

Table 4. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Cow Hollow native seeding, Oregon, 2006–08.

A. 

Functional groupa

Native seeding treatment

(plants/m2)b

Native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 1.79 (1.21) 1.27 (0.97) 1.48 (0.68) 1.35 (0.71)

NS shrubs 0.04 (0.03) 0.04 (0.02) 0.01 (0.01) 0.01 (0.01)

SD perennial grass 0.69 (0.23) 0.09 (0.04) 0.03 (0.03) 0.00

SD shrubs 0.05 (0.05) 0.01 (0.00) 0.00 0.00 

SD forbs 0.14 (0.05) 0.04 (0.03) 0.00 0.00

2006 2007 2008 2006 2007 2008

B. tectorum 544 (263) 1133 (320) 1220 (319) 654 (276) 1240 (344) 1394 (373)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap size (cm)

Native seeding treatment

(percent of line)

Native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25–50 13.7 16.2 17.2 1.0 11.6 10.3

51–100 14.7 15.2 14.8 12.6 14.4 18.6

101–200 15.3 14.8 13.5 20.2 20.3 19.2

>200 35.4 30.5 28.9 43.6 35.2 34.7
23

Table 4. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Cow Hollow native seeding, Oregon, 2006–08.—Continued

C.

Cover

Native seeding treatment

(percent cover)

Native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation 

foliar cover 71.3 77.1 76.3 73.3 77.3 73.0

Bare ground 23.3 11.1 7.3 23.5 12.7 8.7

Basal cover 4.7 6.0 6.8 4.3 6.7 5.2

D.

Functional Group 

Foliar Covera

Cow Hollow treatment

(percent cover)b

Cow Hollow control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 2.9 (2.3) 3.2 (2.7) 4.4 (3.3) 5.3 (3.0) 4.7 (2.4) 5.5 (3.6)

SR perennial grass 28.3 (5.4) 26.5 (5.0) 30.4 (5.0) 24.2 (2.9) 23.0 (5.4) 22.7 (5.3)

Perennial forbs 0.40 (0.3) 2.0 (1.0) 2.3 (1.1) 0.8 (0.3) 1.2 (1.0) 1.0 (0.6)

Shrubs 0.3 (0.2) 0.3 (0.2) 0.5 (0.4) 0.0 (0.0) 0.0 (0.0) 0.3 (0.3)

Exotic annual grass 50.1 (10.4) 59.3 (11.9) 53.6 (12.9) 54.0 (10.6) 61.3 (13.1) 52.8 (12.4)

Exotic annual forbs 5.2 (2.4) 2.8 (1.3) 1.6 (0.7) 7.3 (7.1) 2.7 (1.4) 2.3 (1.1)

Litter 24.8 (5.5) 57.20 (2.9) 76.1 (6.5) 19.8 (9.1) 61.5 (9.3) 78.2 (6.0)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses primarily B. tectorum. 

b

Numbers in parentheses are standard errors.

Cow Hollow Conclusions

Seeded grass densities at the Cow Hollow native seeding were estimated to be between 0.04 and 

0.15 plants/m2 with a mean of 0.09 plants/m2. Despite this low level of establishment, seeded grass 

establishment was significantly higher than control plots (fig. 8). There were no differences between 

treatment and control for densities of seeded forbs or shrubs, although some forbs did establish in the 

treatment area. B. tectorum densities were also much higher than the 100 plants/m2 target objective

(table 4A). 

Within the Cow Hollow burned area, there were many areas of dense, pre-fire P. secunda plants. 

In most of the treatment area, it was difficult to discern drill rows due either to frozen soil at the time of 

drilling or failure of the drill to cut through the dense mat of P. secunda. This may have resulted in 

much of the seed being placed directly on the soil surface where the chance of establishment was 

reduced. Additionally, the dense mat of amorphous bunches of P. secunda significantly increased the 

variability of the basal-gap intercept data. This effect was compounded by variable amounts and timing 

of precipitation. In this situation, meaningful conclusions regarding the short-term basal-gap intercept 

measurements are difficult to make at the Cow Hollow native seeding. 
24

In other drill seedings, an increase in bare ground in the treatment plots compared to control 

plots was observed. This did not occur at the Cow Hollow seeding (table 4C), which may indicate that 

the seed drill was unable to properly bury the seed due to dense P. secunda or other site conditions and 

thus led to low seeded plant densities. 

There were no detectable differences in cover of perennial grasses due to the seeding after 

3 years. Although there were very high levels of perennial grass cover at the Cow Hollow seeding, most 

of the cover was due to the shallow-rooted P. secunda. This level of cover certainly provides protection 

from soil erosion, yet it may not help to meet other goals of land management, such as suitable wildlife 

habitat.

Figure 7. Abundant and small P. secunda plants that resulted in unusual basal gap variability were found 

at the Cow Hollow burned area, Oregon. Photograph by USGS staff, May 12, 2007. 
25

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -0.1

0.0

0.1

0.2

Treatment - control

Figure 8. Confidence interval (80%) of the difference between treatment and control plots 

for seeded grass, shrubs, and forbs at the Cow Hollow native seeding, Oregon, 2008.

Double Mountain

The Double Mountain fire occurred on July 29, 2005, and burned a total of 17,484 acres before 

containment on July 30 (Bureau of Land Management, 2005b, fig. 9). 

The potential plant community in the area is a shrub overstory of primarily Wyoming big 

sagebrush (A. tridentata ssp. wyomingensis) with deep-rooted perennial grasses such as A. hymenoides 

(Indian ricegrass), H. comata (needle and thread), P. spicata (bluebunch wheatgrass), and 

A. thurberianum (Thurber's needlegrass), along with the shallow-rooted perennial grass P. secunda

(Sandberg bluegrass). 

There were two drill seedings proposed for the Double Mountain Fire, a non-native seedmix 

treatment of 349 ha (863 acres) and a native seedmix treatment of 1,128 ha (2,793 acres) (table 5). At 

the non-native treatment, the pre-burn vegetation consisted mainly of annual grasses and forbs with 

some small patches of P. secunda (personal observation). Soils in the area consisted primarily of sandy 

loams. According to the Oregon State Water Resources Board (1969), soils in the area are in 

classification unit 60, which are described as fine-textured loams underlain by clay loams and lacustrine 

sediments that are weakly consolidated. The elevation at the non-native seeding treatment ranged from 

785 to 902 m (2,575 to 2,960 ft). 
26

Figure 9. Location of Double Mountain non-native seeding monitoring plots, Oregon, 2006–08.
27

Table 5. Seed mixes at the Double Mountain native and non-native seeding, Oregon, 2005.

Native seed mix PLSb

(lb/acre) Non-native seed mix PLSb(lb/acre)

'Anetone' bluebunch wheatgrass

(Pseudoroegneria spicata) 4.0 'Fairway' crested wheatgrass(Agropyron cristatum) 5.00

'Trailhead' basin wildrye

(Elymus cinereus) 0.88 'Trailhead' basin wildrye(Elymus cinereus) 1.00

Sandberg's bluegrass

(Poa secunda) 0.94 'Arriba' western wheatgrass(Pascopyrum smithii) 1.00

Squirreltail 

(Elymus elymoides) 1.00 'Ladak' alfalfa(Medicago sativa) 0.25

Western yarrow

(Achillea millefolium) 0.12 Small burnet (Sanguisorba minor) 0.40

Annual sunflower

(Helianthus annuus) 0.76 'Apar' Lewis flax(Linum lewisii) 0.10

Wyoming big sagebrush

(Artemisia tridentata ssp. wyomingensis) 0.01 Wyoming big sagebrush(Artemisia tridentata ssp. wyomingensis) 0.01

Antelope Bitterbrush

(Purshia tridentata) 0.25

TOTAL 7.71 TOTAL 8.01

a

Seed mixes are named native or non-native depending on the species that compose the majority of the seed mix. There is 

uncertainty about whether or not annual sunflower was seeded at the Double Mountain seedings. None was found during 

monitoring. Single quotes surround registered cultivar names for species.

b

PLS = pure live seed. 

The native seeding treatment contained much more topography and elevation range, and as a 

result, was much more variable than the non-native seeding treatment area. This area contained a large 

component of native grasses and forbs and in some areas appeared to be in good ecological condition 

except for the absence of a shrub component (personal observation). Soils were generally silt loams that 

were deeper on shallow slopes and flat areas and shallower on hills and shoulders. The range of 

elevation was broad, ranging from 795 to 1,037 m (2,608 to 3,402 ft). 

The non-native monitoring unit consisted of slopes of up to 20%. We placed three treatment and 

three control plots within this monitoring unit. Likewise, the non-native seeding monitoring unit also 

consisted of drilled areas of 0 to 20% slopes. Due to the topography in this treatment, the monitoring 

unit definition eliminated more area from consideration than in the non-native seeding. Because the 

native treatment was larger, we also established more plots (seven treatment and four control).

Double Mountain Non-Native Seeding

Seeded grass densities at the Double Mountain non-native seeding decreased from 2.72 

plants/m2 in 2006 to 0.90 plants/m2 in 2008 (table 6A). Very few pre-fire perennial grasses were found 

in the area (0.05 plants/m2 in the treatment plots in 2008). The primary grasses establishing from seed 

were A. cristatum (0.72 plants/m2) and T. intermedium (0.16 plants/m2). Additionally, there was some 

establishment of seeded forbs (0.69 plants/m2

 in 2006 and 0.25 plants/m2 in 2008), primarily M. sativa

but also L. lewisii and A. millefolium. No seeded shrubs were found in the treatment area. B. tectorum

densities increased nearly threefold in both control and treatment plots from 2006 to 2007, followed by 

a slight decrease in 2008. 
28

Basal-gap intercept measurements from 2006 to 2008 decreased slightly in the > 200 gap-size

classes and increased slightly in the 101–200 cm gap-size class (table 6B). This pattern occurred in both 

treatment and control plots. 

Vegetation foliar cover was lower and bare ground was higher at the treatment plots in 2006 

(table 6C). The relationship remained similar, but the difference between the treatment and control plots 

decreased in 2007 and 2008. 

In 2006, there was little cover of deep-rooted perennial grass (table 6D). Shallow-rooted 

perennial grass cover was also low but showed an increase in the treatment plots and a decrease in the 

control plots from 2006 to 2008. Cover of exotic annual grasses increased in 2007 and decreased 

slightly in 2008. In 2006, cover of exotic annual forbs, primarily Sisymbrium altissimum (tall 

tumblemustard) was high in both control and treatment plots (37.3 and 33.6%, respectively) followed by 

a reduction to 0 and 2.7% in 2007, and another increase to 5.3 and 7.6% in 2008. In some areas of this 

treatment, Onopordum acanthium (Scotch cottonthistle) and Cardaria draba (whitetop) appear to be 

increasing following the fire (personal observation). 

Table 6. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Double Mountain non-native seeding, Oregon, 2006–08.

A.

Functional Groupa 

Non-native seeding treatment

(plants/m2)b

Non-native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 0.03 (0.02) 0.05 (0.02) 0.01 (0.01) 0.02 (0.02)

NS shrubs 0.00 0.00 0.00 0.00

SD perennial grass 2.72 (1.89) 0.90 (0.78) 0.08 (0.08) 0.02 (0.03)

SD shrubs 0.00 0.00 0.00 0.00

SD forbs 0.69 (0.15) 0.25 (0.13) 0.02 (0.02) 0.01 (0.01)

2006 2007 2008 2006 2007 2008

B. tectorum 492 (131) 1461 (168) 1072 (353) 641 (89) 1705 (314) 1139 (210)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap size (cm)

Non-native seeding treatment

(percent of line)

Non-native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25–50 0.9 1.2 1.6 2.0 1.5 1.7

51–100 2.9 3.1 4.4 1.4 2.2 3.1

101–200 4.7 5.3 9.3 5.4 6.0 8.2

>200 89.4 88.1 82.4 89.1 87.9 84.5
29

Table 6. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Double Mountain non-native seeding, Oregon, 2006–08.—Continued

C. 

Cover

Non-native seeding treatment

(percent cover)

Non-native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation 

foliar cover 78.4 75.8 74.0 91.1 82.7 80.4

Bare ground 15.8 11.1 11.3 4.2 4.9 4.0

Basal cover 0.2 1.3 1.8 1.6 1.1 1.3

D.

Functional Group 

Foliar Covera 

Non-native treatment

(percent cover)b

Non-native control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 0.4 (0.4) 0.9 (0.9) 1.6 (1.0) 0.2 (0.2) 0.7 (0.7) 0.7 (0.7)

SR perennial grass 4.4 (1.1) 3.8 (0.8) 8.0 (2.3) 9.1 (5.4) 6.0 (4.4) 6.7 (3.7)

Perennial forbs 1.8 (1.5) 3.8 (2.1) 2.4 (1.4) 3.3 (3.3) 6.7 (5.4) 1.3 (0.8)

Shrubs 0.0 0.0 0.0 0.0 0.0 0.0

Exotic annual grass 62.4 (5.3) 70.2 (4.3) 65.1 (9.7) 72.7 (2.4) 76.7 (7.6) 74.2 (8.7)

Exotic annual forbs 33.6 (12.0) 2.7 (0.8) 7.6 (3.0) 37. 3 (1.9) 0.0 5.3 (1.4)

Litter 43.6 (1.5) 73. 6 (0.6) 74.7 (6.2) 82.0 (7.1) 84.7 (6.7) 89.3 (3.)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses primarily B. tectorum. 

b

Numbers in parentheses are standard errors.

Double Mountain Non-Native Seeding Conclusions

Final densities of seeded grasses at the Double Mountain non-native seeding were less than the 

target density of 5 plants/m2 and highly variable (fig. 10). Established perennial grass density is 

estimated to be between 0 and 2.36 plants/m2 with a mean of 0.90 plants/m2. Because the confidence 

interval overlapped zero, the treatment was not statistically different than control plots in terms of 

established perennial grasses. However, the seeding did increase the number of perennial grass plants 

(by an estimated 9,000 plants/ha) in the area. Due to the low number of plots and the patchiness of 

seedling establishment, the 80% confidence interval for seeded perennial grasses was large. 

At this seeding, the drill created large furrows in the sandy soils, which, in the first year 

following the fire, seemed to increase bare ground in treatment areas. These furrows did not increase the 

overall density or cover of exotic annual grasses over the 3-year monitoring period and may have aided 

the establishment of perennial grasses by creating an adequate seedbed.
30

Double Mountain Native Seeding

The Double Mountain native seeding consists of several polygons on the southern end of the 

area affected by the Double Mountain fire (fig. 11). 

The density of perennial seeded grasses in 2008 at the Double Mountain native seeding was the 

highest of the four 2005 fires. Although initial densities were lower than that recorded at the Keeney 

Pass native seeding treatment in 2006, there was less mortality at the Double Mountain native seeding, 

leading to higher establishment by 2008. There was an estimated 3.86 seeded perennial grass plants/m2

in 2006 and 1.74 plants/m2 in 2008 (table 7A). The majority of seeded grasses established were 

P. spicata. There was very little establishment of seeded forbs and shrubs (less than 0.01 plants/m2). 

B. tectorum densities increased from 2006 to 2007 and leveled off in 2008 in both treatment and control 

plots. 

Basal-gap intercept measurements were similar between treatment and control plots with most 

gaps in the > 200 cm gap-size class (table 7B). Other gap-size classes stayed largely the same; however, 

there was a slight decrease in the number of gaps in the 51–100 cm gap-size class in control plots. 

Vegetation foliar cover, bare ground, and basal cover showed the same patterns in treatment and 

control plots during monitoring (table 7C). From 2006 to 2008, there was an increase in vegetation 

foliar cover in the treatment and control. During this time, bare ground decreased by approximately onehalf in both treatments.

Deep-rooted perennial grass cover increased slightly in the treatment and control plots from 

2006 to 2008 (table 7D). Shallow-rooted perennial grass cover showed a slight increase in treatment 

plots and a larger increase in control plots. One control plot was primarily responsible for this trend due 

to a large increase in P. secunda cover in 2008. Exotic annual-grass cover increased during 2006-2008 

in both the treatment and control plots; however, this effect was more pronounced in the treatment plots.

Exotic annual forbs generally decreased from an initial flush in 2006, and litter increased in all plots 

during the monitoring period. 

Double Mountain Native Seeding Conclusions 

The native seeding at Double Mountain did not meet the objective of 5 plants/m2, but there was 

substantial establishment of seeded grasses. Initial plant densities were lower than 5 plants/m2 in 2006, 

and subsequent mortality from low precipitation in 2007 and 2008 reduced the densities further. Seeded 

perennial grass density was estimated to be between 0.95 and 2.53 plant/m2 with a mean of 1.74 

plants/m2 (fig. 12). Due to the variable nature of the pre-fire ecological conditions, greater and more 

complex topography, and the wider elevation range at this treatment, there was substantial patchiness in 

seedling establishment. Some plots had large numbers of establishing seedlings whereas others had 

dense patches of P. secunda that seemed to preclude seedling establishment. High initial densities of 

exotic annual grasses at some plots also may have severely reduced treatment seedling establishment 

due to competition. There also were areas where it appeared that drill rows and subsequent seedling 

establishment were dependent on the absence of dense P. secunda (fig. 13). 
31

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Treatment - Control

Figure 10. Confidence interval (80%) of the difference between treatment and 

control plots for densities of seeded grasses, shrubs, and forbs at the Double 

Mountain non-native seeding, Oregon, 2008.
32

Figure 11. Location of monitoring plots at the Double Mountain native seeding treatment, Oregon, 2006–08.
33

Table 7. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Double Mountain native seeding, Oregon, 2006–08.

A.

Functional groupa 

Native seeding treatment

(plants/m2)b

Native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 1.19 (0.47) 1.39 (0.62) 0.89 (0.59) 1.10 (0.80)

NS shrubs 0.00 (0.00) 0.00 (0.00) 0.01 (0.01) 0.01 (0.01)

SD perennial grass 3.857 (1.296) 1.74 (0.50) 0.05 (0.05) 0.00

SD shrubs 0.01 (0.01) 0.00 (0.00) 0.00 0.00

SD forbs 0.03 (0.03) 0.00 (0.00) 0.00 0.00

2006 2007 2008 2006 2007 2008

B. tectorum 264 (83) 611 (194) 562 (176) 313 (183) 529 (198) 540 (257)

B.

Gap Size (cm)

Native Seeding Treatment

(percent of line) 

Native Seeding Control

(percent of line)

2006 2007 2008 2006 2007 2008

25-50 13.5 12.7 11.7 13.2 12.6 14.2

51–100 13.8 14.9 12.8 14.3 12.1 10.6

101–200 16.0 12.5 14.4 10.7 11.9 12.1

>200 40.8 40.2 45.5 45.7 42.1 43.3

C.

Cover

Native seeding treatment

(percent cover)

Native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation foliar cover 57.2 57.9 64.8 59.5 56.3 66.0

Bare ground 37.0 24.2 17.7 33.0 23.2 17.0

Basal cover 4.4 6.8 6.9 4.0 6.2 8.7
34

Table 7. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Double Mountain native seeding, Oregon, 2006–08.—Continued

D.

Functional Group 

Foliar Covera

Native seeding treatment

(percent cover)b

Native seeding control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 7.8 (2.2) 12.6 (3.5) 11.1 (3.3) 5.8 (4.8) 7.0 (5.3) 7.7 (6.8)

SR perennial grass 19.1 (5.3) 18.6 (5.4) 21.7 (5.1) 23.5 (9.0) 19.2 (7.2) 28.5 (9.5)

Perennial forbs 3.1 (0.9) 2.9 (0.8) 2.0 (0.4) 1.1 (0.8) 2.5 (0.9) 2.2 (0.8)

Shrubs 0.2 (0.2) 0.1 (0.1) 0.3 (0.3) 0.0 0.3 (0.2) 0.2 (0.2)

Exotic annual grass 28.6 (7.6) 32.0 (6.8) 39.7 (8.9) 32.5 (12.3) 33.3 (13.0) 34.8 (13.9)

Exotic annual forbs 8.2 (3.7) 2.5 (1.4) 2.8 (1.3) 5.2 (2.9) 1.8 (0.7) 2.3 (1.0)

Litter 19.9 (4.6) 50.2 (4.7) 60.0 (2.1) 26.7 (6.8) 54.5 (10.4) 60.3 (7.4)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses primarily B. tectorum. 

b

Numbers in parentheses are standard errors.

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) 0.0

0.5

1.0

1.5

2.0

2.5

3.0

Treatment - Control

Figure 12. Confidence interval (80%) of the difference between the 

treatment and control for seeded grasses, shrubs, and forbs at the 

Double Mountain native seeding, Oregon, 2008. 
35

Figure 13. Photograph of establishing seedlings in an area where P. secunda 

was less dense prior to seeding or was displaced during seeding (at right) and 

an adjacent area of dense P. secunda with little seedling establishment (left middle).

Farewell Bend

The Farewell Bend fire was ignited by lightning on July 28, 2005, and burned approximately 

3,418 acres of BLM land before containment on July 29 (fig. 14). 

The potential plant community in the area of the Farewell Bend fire is a shrub overstory of 

primarily Wyoming big sagebrush (A. tridentata ssp. wyomingensis) with deep rooted perennial grasses 

such as P. spicata (bluebunch wheatgrass), A. thurberianum (Thurber's needlegrass), and Festuca 

idahoensis (Idaho Fescue) along with the shallow-rooted perennial grass P. secunda (Sandberg 

bluegrass) (NRCS, 1997). Some areas are close to Benson Creek and species such as chokecherry 

(Prunus) and Syringa (Philadelphus lewisii) can be found in these areas, as well as more mesic plants 

within the creek itself.

Soils at the Farewell Bend are clayey (clay loam to clay) and have a subsurface layer high in 

smectitic clay (27–50%) with a moderate to high linear extensibility (3–8.9%). This high clay content 

causes cracking of the soil surface due to shrinking and swelling of the soils during wet-dry cycles. As a 

result of this soil surface cracking, bunchgrasses tend to be either semi-rhizomatous or broken apart by 

the shrink-swell cycle (fig. 15). This shrink-swell cycle also tends to obscure the drill rows, which are 

useful as a visual guide when searching for seedlings during monitoring. The rhizomatous nature of the 

vegetation in this area makes it difficult to consistently identify the boundaries of individuals as well as 

determine the difference between recently established seeded plants and pre-existing plants. 
36

Figure 14. Location of Farewell Bend monitoring plots, Oregon, 2006-08.
37

Figure 15. Soil surface conditions and rhizomatous Pseudoroegneria spicata at the Farewell Bend 

burned area, Oregon.

Two seedmixes, one composed of native species, and the other mostly non-native species, were 

drill-seeded in the Farewell Bend burned area in 2005 (table 8). The non-native seedmix was seeded 

over 116 ha (288 acres) and the native seedmix was drilled on 166 ha (412 acres) of the burned area. A 

portion of the non-native treatment was a previous crested wheatgrass seeding, however, pre-fire 

vegetation at both treatments consisted primarily of native perennial grasses dominated by semirhizomatous P. spicata and P. secunda. In some areas, P. bulbosa had replaced P. secunda as the 

dominant shallow-rooted grass. The elevation of the two treatments ranged from 820 to 940 m (2,690 to 

3,083 ft). 

Two monitoring units were defined as those areas that were drill seeded between 0 and 20% 

slopes for each of the seedmixes. Quantitative goals were to establish 5 seeded plants/m2

. There were 

three exotic annual grasses present, B. tectorum, Bromus hordeaceus (soft brome), and Taeniatherum 

caput-medusae (medusahead). Due to the small size of treatment areas, there were only three treatment 

and control plots established in each treatment area.
38

Table 8. Seed mix at the Farewell Bend non-native and native seedings, Oregon.

Non-native seed mix PLSb

(lb/acre) Native seed mix PLSb(lb/acre)

'Hycrest' wheatgrass

(Agropyron cristatum) 4.0 'Magnar' basin wildrye(Elymus cinereus) 4.0

'Ephraim' crested wheatgrass

Agropyron cristatum) 3.0 'Schwendimar' thickspike wheatgrass(Elymus lanceolatus) 4.6

'Luna' pubescent wheatgrass

(Thinopyron intermedium) 2.0 Blue wildrye(Elymus glaucus) 0.8

Sandberg's bluegrass

(Poa secunda) 1.0 Canby bluegrass(Poa secunda) 1.0

Basin big sagebrush

(Artemisia tridentata ssp. vaseyana) 0.2 Basin big sagebrush(Artemisia tridentata ssp. vaseyana) 0.2

TOTAL 10.2 TOTAL 10.6

a

Seedmixes are named native or non-native depending on the species that compose the majority of the seedmix. Common 

sunflower was seeded at the Farewell Bend burned area but its rate was not known. Single quotes surround registered 

cultivar names for species.

b

PLS = pure live seed

Farewell Bend Non-Native Seeding

Resprouting native perennial grasses accounted for 5.00 plants/m2 in the treatment and 6.80 

plants/m2

 in the control plots in 2008 (table 9A). In 2006, there was an estimated 5.62 seeded perennial 

grass plants/m2

, which decreased to 0.42 plants/m2 by 2008. Establishing seeded plants were primarily 

A. cristatum (0.35 plants/m2

) with low densities of E. lanceolatus (0.05 plants/m2). Seeded shrub 

(A. tridentata ssp. vaseyana) density was estimated to be 0.14 plants/m2 in 2008. In a few areas that had 

sagebrush prior to the fire, there were patches of naturally occurring sagebrush seedlings. These were 

defined as non-seeded for monitoring purposes, but there may have been some seeded plants in these 

areas. Densities of exotic annuals increased from 2006 to 2007, as it did in all other seedings, and then 

decreased in 2008, although not to 2006 levels. 

Basal-gap intercept measurements in the 25–50 cm gap-size class were similar from 2006 to 

2008 (table 9B). In treatment plots, gaps in the 51–100 cm gap-size class increased from 17.3 to 26.0%, 

and there was no corresponding increase in control plots. At the same time, there was a decrease in the 

percentage of transects in the 101–200 and >200 cm gap-size classes. 

Bare ground decreased in treatment plots and remained constant at control plots during the 

monitoring period (table 9C). Vegetation foliar cover increased slightly from 2006 to 2007 and then 

decreased in 2008 at both treatment and control plots. Basal cover generally increased from 2006 to 

2008 in treatment and control plots. 

Functional group foliar cover of resprouting shallow-rooted grasses (primarily P. bulbosa) at 

treatment plots showed a marked increase from 2006 to 2007, followed by a decrease in 2008 

(table 9D). Control plots followed a similar trend except that cover was the same in both 2007 and 2008. 

Exotic annual grass cover increased in 2007 and decreased in 2008 in both treatment and control plots. 

Cover of exotic annual forbs increased by small amounts in 2007 and 2008. 
39

Table 9. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Farewell Bend non-native seeding, Oregon, 2006–08.

A.

Functional groupa

Non-native seeding treatment

(plants/m2)b

Non-native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 5.05 (1.01) 5.00 (0.92) 6.26 (2.75) 6.80 (2.94)

NS shrubs 0.00 0.01 (0.01) 0.00 (0.00) 0.14 (0.12)

SD perennial grass 5.62 (3.99) 0.42 (0.12) 0.02 (0.01) 0.00

SD shrubs 0.155 (0.109) 0.128 (0.120) 0.078 (0.044) 0.000

2006 2007 2008 2006 2007 2008

Exotic annual grass 115 (48) 379 (128) 233 (58) 151 (100) 650 (177) 415 (192)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap size (cm)

Non-native seeding treatment

(percent of line)

Non-native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25-50 14.0 16.1 17.1 13.4 14.1 15.1

51–100 17.3 17.2 26.0 14.7 13.3 13.7

101–200 19.3 16.5 13.5 12.0 13.0 13.9

>200 21.5 13.8 14.3 36.0 30.4 28.8

C.

Cover

Non-native seeding treatment

(percent cover)

Non-native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation foliar 

cover

61.7 68.9 55.1 68.6 70.0 60.4

Bare ground 26.1 11.3 16.5 16.2 13.1 15.1

Basal cover 4.4 10.4 7.6 4.7 8.7 8.9
40

Table 9. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Farewell Bend non-native seeding, Oregon, 2006–08.—Continued

D.

Functional Group

Foliar Covera 

Non-native seeding treatment

(percent cover)b

Non-native seeding control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 13.6 (5.2) 16.7 (9.3) 14.0 (4.2) 16.9 (7.7) 18.4 (7.1) 13.8 (3.6)

SR perennial grass 19.1 (7.1) 29.6 (8.9) 23.3 (4.9) 17.6 (10.8) 22.0 (10.9) 22.0 (11.6)

Perennial forbs 11.1 (3.4) 6.9 (3.9) 6.0 (3.0) 8.2 (1.4) 8.7 (3.0) 8.7 (3.5)

Shrubs 0.0 0.2 (0.2) 0.2 (0.2) 0.0 0.2 (0.2) 1.6 (0.4)

Exotic annual grass 26.4 (6.1) 34.2 (8.3) 18.9 (6.5) 38.2 (17.5) 44.9 (20.6) 26.4 (11.4)

Exotic annual forbs 1.1 (0.4) 1.6 (1.2) 3.3 (2.3) 1.1 (0.4) 1.6 (0.2) 2.7 (1.3)

Litter 24.4 (4.8) 59.8 (4.1) 65.7 (3.7) 42.2 (2.3) 55.1 (7.5) 60.4 (7.3)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses includes B. tectorum, T. caput-medusae, and B. hordeaceous

which are all present at Farewell Bend

b

Numbers in parentheses are standard errors.

Farewell Bend Non-Native Seeding Conclusions

The non-native seeding of the Farewell Bend burned area did not meet the quantitative target 

objective of 5 plants/m2

. Seeded grass densities at the Farewell Bend non-native seeding were estimated 

to be between 0.19 and 0.64 with a mean of 0.42 plants/m2

 (fig. 16). This is equivalent to an estimated 

4,180 plants/ha. 

At this site, there was considerable natural recovery of existing grasses and perennial forbs, 

which most likely provided substantial competition to seeded species. The high density of plants that 

survived the fire in the non-native treatment (5.0 to 6.8 plants/m2

) is due primarily to the previous 

successful A. cristatum seeding, which is very dense in some locations. 

The large changes in gap percentages at treatment plots may be partially due to the mechanical 

action of the drill seeding which would be expected to increase the percentage of transects in larger gap 

sizes. Furthermore, the cracking and shifting clay soils may have increased variability of the basal-gap 

intercept data by physically moving plants between years. 
41

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -0.5

0.0

0.5

1.0

Treatment - Control

Figure 16. Confidence interval (80%) of the difference between the treatment 

and control at the Farewell Bend non-native seeding, Oregon, 2008.

Farewell Bend Native Seeding

Density of seeded perennial grasses decreased from 2.22 to 0.44 plants/m2 from 2006 to 2008 

(table 10A). Seeded shrubs (A. tridentata) decreased from 0.54 to 0.20 plants/m2 during the monitoring 

period. Exotic annual grass densities increased at both the control and treatment plots in 2007, but then 

decreased in 2008 for the control plots only. 

Basal-gap intercept measurements at treatment plots decreased in the >200 cm gap class from 

53.1 to 37.2%, whereas control plots decreased from 38.8 to 31.6% (table 10B). Average percentage of 

lines occupied by the remaining three gap classes showed little change during the monitoring period. 

Vegetation foliar cover and basal cover increased in both treatment and control plots from 2006 

to 2008 (table 10C). Simultaneously, bare ground cover decreased substantially in both treatments (to 

approximately 25% of 2006 levels).

Cover of perennial grasses increased from 2006 to 2008 in treatment and control plots (table 

10D). Cover of perennial native forbs was higher at the Farewell Bend native seeding than at any of the 

other burned areas. Cover of exotic annual forbs was low but increasing by 2008. As with other burned 

areas, litter increased steadily from 2006 to 2008 as biomass accumulated after the fire.
42

Table 10. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Farewell Bend native seeding, Oregon, 2006–08.

A.

Functional groupa 

Native seeding treatment

(plants/m2)b

Native seeding control

(plants/m2)b

2006 2008 2006 2008

NS perennial grass 2.01 (0.66) 1.46 (0.83) 1.07 (0.13) 1.33 (0.70)

NS shrubs 0.06 (0.04) 0.08 (0.05) 0.17 (0.13) 0.11 (0.02)

SD perennial grass 2.22 (0.19) 0.44 (0.12) 0.02 (0.02) 0.00

SD shrubs 0.54 (0.43) 0.20 (0.17) 0.00 0.00

SD forbs 0.01 (0.01) 0.15 (0.13) 0.00 0.00

2006 2007 2008 2006 2007 2008

Exotic annual grass 243 (49) 646 (180) 658 (247) 261 (83) 739 (187) 333 (178)

a

NS, non-seeded; SD, seeded. Density of NS perennial grasses does not include the shallow-rooted species, Poa secunda or 

Poa bulbosa. 

b

Numbers in parentheses are standard errors. 

B.

Gap Size (cm)

Native seeding treatment

(percent of line)

Native seeding control

(percent of line)

2006 2007 2008 2006 2007 2008

25-50 9.9 9.1 13.1 10.8 7.8 11.3

51–100 12.9 15.0 14.3 15.2 10.1 11.0

101–200 12.8 14.3 18.6 12.2 14.2 11.7

>200 53.1 48.9 37.2 38.8 38.4 31.6

C.

Cover

Native seeding treatment

(percent cover)

Native seeding control

(percent cover)

2006 2007 2008 2006 2007 2008

Vegetation 

foliar cover\ 63.8 68.4 74.2 67.5 67.3 80.0

Bare ground 25.6 10.7 6.4 19.8 11.8 4.9

Basal cover 2.0 6.2 7.6 4.8 5.1 11.3
43

Table 10. Density of plants by functional group and Bromus tectorum (A), average percentage of each transect 

composed of basal gaps within each gap-size class (B), vegetation foliar cover, bare ground, and basal cover (C), 

and functional group foliar cover (D) at the Farewell Bend native seeding, Oregon, 2006–08.—Continued

D.

Functional Group 

Foliar Covera 

Native seeding treatment

(percent cover)b

Native seeding control

(percent cover)b

2006 2007 2008 2006 2007 2008

DR perennial grass 9.6 (4.9) 10.7 (5.4) 15.3 (6.0) 2.7 (1.3) 3.1 (0.8) 7.3 (3.2)

SR perennial grass 8.7 (5.2) 15.3 (7.6) 20.2 (7.3) 22.7 (12.4) 23.6 (14.5) 37.6 (20.9)

Perennial forbs 17.8 (7.8) 10.7 (2.7) 18.0 (2.4) 20.9 (6.9) 12.9 (10.2) 27.8 (15.4)

Shrubs 0.4 (0.4) 0.9 (0.4) 1.6 (1.6) 2.0 (0.8) 2.4 (1.4) 3.6 (1.2)

Exotic annual grass 36.7 (7.2) 55.8 (7.6) 39.8 (12.7) 29.1 (5.8) 44.9 (1.4) 29.1 (15.9)

Exotic annual forbs 3.1 (1.6) 2.4 (1.4) 8.0 (3.7) 3.1 (0.9) 2.7 (2.0) 8.2 (4.6)

Litter 21.6 (2.1) 66.4 (2.2) 73.6 (4.5) 21.6 (6.8) 59.6 (9.0) 69.8 (3.2)

a

DR, deep-rooted; SR, shallow-rooted; Exotic annual grasses includes B. tectorum, T. caput-medusae, and B. hordeaceous

which are all present at Farewell Bend

b

Numbers in parentheses are standard errors.

Farewell Bend Native Seeding Conclusions 

The Farewell Bend native seeding did not meet the 5 plants/m2 quantitative objective. The 

density of perennial grasses established by drill seeding was estimated to be between 0.23 and 0.67 

plants/m2

 with a mean of 0.44 plants/m2 (fig. 17). This is equivalent to an estimated 4,400 plants/ha 

established as a result of the seeding by 2008. In addition, there was a large amount of natural recovery 

following the fire at this site. 

Time Requirements

Average times required to perform the line-point intercept, basal-gap intercept, and quadrat 

density procedures along one transect were 10.4, 11.6, and 19.3 minutes, respectively. Median times 

were slightly lower with 9, 11, and 16.3 minutes required for the line-point intercept, basal-gap intercept 

and quadrat density, respectively. The median time required to accomplish each procedure at one plot 

with three transects was 54 minutes for the line-point intercept procedure, 66 minutes for basal- gap

intercept and 49 minutes for quadrat density (fig. 18). Time estimates were based on 133 line-point 

intercept, 138 basal-gap intercept, and 66 quadrat density transects. Belt density was not measured but 

usually requires less time than the other three procedures.
44

Seeded Grass Seeded Shrubs Seeded Forbs

Plant Density (plants/m2

) -0.5

0.0

0.5

1.0

Treatment - Control

Figure 17. Confidence interval (80%) of the difference between treatment 

and control plots at the Farewell Bend native seeding, Oregon, 2008.

Line-Point Intercept Density Basal Gap Intercept

Person Hours

0.0

0.5

1.0

1.5

2.0

Figure 18. Median person-hours to perform each quantitative procedure on 

one plot (three 50-m transects). Line-point intercept and basal-gap intercept 

measurements require two people; density measurements require one person. 

Bars are maximum and minimum person-hours required.
45

For line-point intercept, maximum times occurred in plant communities with high cover, high 

diversity, and where some plants were unknown. Maximum time requirements for the basal-gap

intercept procedure were a result of dense mats of P. secunda with high densities of other plants. 

Density transects with the longest time requirements occurred in areas with high plant densities where 

determination of individuals was difficult and the size class of each plant needed to be determined. 

Situations that required these maximum times were uncommon, with the exception of the dense mat of 

P. secunda, which may be common depending on the pre-burn vegetation of the area. The median time 

required to complete the three techniques on each plot is 2.8 hours (not including plot setup and travel 

time). Additional time is necessary to set up each plot in the first year of monitoring, and this usually 

requires 30 to 60 minutes to locate and place transects and to record pertinent plot information (slope, 

aspect, and soils information). 

Observer Comparisons

In 2006, treatments on the Keeney Pass and Farewell Bend fires were monitored using three 

teams to determine variation in data among different observers. At each plot, the first team established 

the plot and conducted the line-point intercept, density, and basal-gap intercept procedures. Within 1–2 

days, the second and third teams located the plot and also performed the procedures at that time. 

Coefficients of variation for cover, density and basal-gap intercept were calculated using the 

standard deviation of the three teams divided by the average of the three teams multiplied by 100. 

Comparisons of cover and density estimates between different observers generally indicated that 

monitoring results were similar for common plant functional groups, but estimates varied more widely 

for the less common functional groups (table 11). For example, pre-existing perennial grass plants were 

common in treatment and control plots and the coefficient of variation among observers for cover and 

density were low (5.8 and 16.8%, respectively). Both seeded and non-seeded shrubs were uncommon 

and patchy, resulting in high coefficients of variation among observers for cover (124%) and density 

(82.8% for non-seeded and 70% for seeded shrubs). The Coefficients of variation for all basal-gap 

intercept classes were low between observers, indicating this technique is highly repeatable.

In general, coefficients of variation for seeded species were fairly high because at these seedings, 

seedling establishment was patchy. Treatments that result in high plant densities are expected to have 

lower variation between observers. 

Table 11. Coefficients of variation between three sets of observers at the Farewell Bend and Keeney Pass burned 

areas.

Cover Coefficient of 

variation (%) Density Coefficient of variation (%)

BasalGapinterceptCoefficient of 

variation (%)

Canopy Cover 4.3 Perennial Grasses 16.8 25-50 cm 34.2

Bare Ground 14.1 Shrubs 82.8 51-100 cm 22.1

Basal Cover 41.5 Seeded Grasses 78.1 101–200 cm 13.3

Perennial Grass 5.8 Seeded Forbs 85.0 > 200 cm 16.8

Shrubs 124.0 Seeded Shrubs 70.0

Forbs 39 Annual Grasses 17.0
46

Performance of Design Elements

Objectives

Overall, quantitative objectives are valuable parts of monitoring initial success of post-fire 

seedings; however, they require adaptation for specific situations or areas and adjustments as more 

information becomes available. Appropriate quantitative objectives for a particular parameter at a postfire project are often unknown and setting these objectives is an adaptive process. Initially, these

objectives may seem arbitrary because there are no quantitative data from past projects to use as a guide. 

However, as objectives are re-evaluated at the end of each project to determine if they were appropriate, 

this information can be used to inform future projects. 

Understanding the potential of a particular area to reach a certain level of density or cover of 

desirable plant species is not an exact science. For example, ecological site descriptions produced by the 

Natural Resources Conservation Service provide information on species composition but do not specify 

cover or density of species that typically occur in these locations (Society for Range Management, 

1999). As a result, areas that occur on similar ecological sites may differ in the amount of vegetation 

resulting from fewer individual plants of the same size, or from the same density of plants, but each 

plant is smaller, or both fewer and smaller plants. These variations of cover, density, and spatial 

arrangements of plants have significant impacts on what quantitative objectives are appropriate for a 

particular post-fire rehabilitation site.

In this report , the original density objective for seeded grasses of 5 plants/m2

 (50,000 plants/ha) 

or about 0.5 plants/ft2 is considered at the lower end of a good seeding for sites that receive 28 to 33 cm 

(11-13 in.) of precipitation annually (Vallentine, 1971). The four 2005 Vale burns discussed in this 

report are on the lower end of that precipitation range, with the exception of Farewell Bend, and 

seedings at these burned areas resulted in lower densities than those suggested by Vallentine (1971). 

Therefore, the original objective of 5 plants/m2 will need to be refined over time using data from 

multiple projects occurring in different years with variable timing and amount of precipitation. 

Additionally, densities of B. tectorum from 2005 to 2008 were much higher than the original density 

objective of 100 plants/m2. Bromus tectorum exhibited high annual variation as a result of both 

disturbance (fire, drill seeding) and climate (wet year followed by two drought years). As a result, 

density of B. tectorum may be difficult to use as an objective, at least within the first 3 years of 

monitoring. 

ES&R monitoring data on initial densities will be important baseline information for tracking 

continued development of the plant community as it matures and for understanding initial densities that 

are necessary for successful control of invasive species. In the future, objectives that vary depending on 

the post-fire weather conditions may be a useful tool. These conditional objectives would be developed 

to include a range of values rather than a specific target objective. Eventually, given enough data on 

projects on similar ecological sites over time, a model could be developed to predict optimum seeding 

success over a range of conditions. Using such a dynamic approach for setting objectives would 

minimize the numbers of projects that are deemed failures due to setting of unrealistic objectives or due 

to environmental factors that are outside the control of land management. 
47

Stratification

Each stratum (monitoring unit) within a treatment area must have a minimum of three plots to 

generate a mean and standard deviation. Therefore, each additional monitoring unit requires an increase 

in monitoring effort to establish these three plots. The time and effort required to monitor a post-fire 

project will often guide whether or not additional strata are included in the monitoring plan. We expect 

that different levels of stratification will occur at different projects and there is no way to standardize 

stratification. However, it is important to adequately describe properties of each monitoring unit 

(location, soils, topography, etc.) to define the scope of inference of collected data. Three useful rules to 

follow based on our experiences on the Vale burned areas are:

1. Base strata on the largest areas treated; do not spend time on areas that represent a small 

percentage of the treatment.

2. Try to measure at least five plots in each stratum. 

3. Slopes that exceed 30% are difficult to perform the quantitative techniques on. Drill seedings 

typically do not exceed 20% slopes, but aerial seedings may exceed 30%. This means that 

monitoring aerial seedings in areas of greater than 30% slopes will require a different technique 

than that described here. 

4. Previous land-management actions may be a more important factor in determining seeding 

success than edaphic or environmental factors. For example, the previous seeding at the Keeney 

Pass burned area affected success of the new seeding and should have been included as a 

stratification factor. 

Random Sampling

Random sampling generally worked well. Plots assigned randomly occasionally occurred in 

locations that were not acceptable and had to be moved to another random location. Plots using the 

three-spoke design are fairly large, about 2.5 acres, and encompass considerable variation within them. 

This is a desirable factor when monitoring large areas such as post-fire rehabilitation treatments.

However, sometimes portions of a plot can encompass areas that should not be sampled, or the shape of 

the landscape is such that it cannot accommodate the three-spoke design. In several cases, it was

necessary to move the transects to violate the 120° degree separation between transects. This was 

primarily due to the transect intersecting an area that could not be drill seeded due to obstacles such as 

steep drainages or rock outcrops. When this occurs, care must be taken when moving transects.

Transects should not be placed close enough together that double sampling of the belt transects occurs. 

Additionally, if these situations are expected to occur often, the plot design may need to be modified 

such as reducing the length or number of transects. 
48

Control Plots

Control plots within project areas provide a direct measurement of treatment effects. This is 

important because control plots are often placed in adjacent, non-treated areas which may differ from areas 

proposed for treatment. This further increases the variability, thereby reducing our ability to detect 

changes due to the treatment. For drill seedings, it is simple to establish areas that are large enough to 

place an individual plot and then avoid seeding these areas. For aerial seedings, this is much more 

difficult. Control plots for aerial seedings can be placed in areas that are deliberately not seeded 

(although there may be some seed drift), or placed in areas that could have been seeded but were not due 

to logistical convenience (such as using roads as convenient boundaries). 

In this monitoring effort, experience gained in the first and second year of monitoring allowed a 

determination of seeded versus non-seeded plants within treatment plots. In this case, an estimate of 

plant establishment could be made without the use of control plots; however, as plants grow larger and 

resemble pre-existing plants, it will become impossible to determine which were seeded and which were 

not. Therefore, control plots will be vital to determining long-term treatment effects at these post-fire 

rehabilitation projects. 

Data Quality

To reduce variation in data, two actions can be taken: (1) improve stratification and (2) group 

species into functional groups rather than analyzing them separately. Improving stratification will result 

in lower variability and hence, lower estimated sample sizes. Those factors that most greatly influence 

the character of the pre-fire landscape should be considered for use as strata. This includes landmanagement activities such as recent seedings (and their success), grazing practices, and pre-fire 

vegetation. Knowledge of these pre-fire factors is essential for efficient stratification. Grouping species 

into functional groups often decreases standard deviations as compared to individual species standard 

deviations. In some cases, the majority of a functional group is composed of one species (for example, 

A. cristatum in the seeded grass functional group), and in these cases, individual species can be analyzed 

separately. 

In some instances, it will not be possible to detect a difference between treatment and control 

plots due to high variability. Sample adequacy estimates for monitoring data at the Vale fires generally 

produced large required sample sizes for functional group cover or density. These sample size estimates 

are due to high natural variability in existing communities and in patchiness of seedling emergence and 

establishment of seeded species. As a result, variability around density and cover estimates may be high 

despite efforts to decrease variability through stratification. If, however, the difference between 

treatment and control (effect size) for a monitoring parameter is large, a confidence interval of the 

difference between treatment and control will likely not include zero, and a significant difference will be 

detected despite high variability. 

Overall, one needs to determine what kind of a difference can be expected from a seeding. Does 

one expect a large difference that is apparent upon visual inspection of the area, or is it reasonable to 

expect a 5 or 10% difference in cover, density, or gap measurements as the result of seeding? Realistic 

expectations of data quality and variability need to be developed over time and used to develop 

reasonable objectives for future projects.
49

Statistical Analysis

Summary statistics and confidence intervals of the difference were used for final comparisons of 

data at the treatment plots to the density objectives. This method was recommended in Wirth and Pyke 

(2007) as a way to display monitoring data variability as well as to provide a test of achieving 

objectives. Confidence intervals of the difference demonstrate not only the difference between treatment 

and control but uncertainty around these estimates, which, in many cases, is substantial. For this report, 

we provided confidence intervals of the difference for only quantitative density objectives because they 

are the most applicable in determining success of projects at these four fires. Constructing these graphs 

for other data, such as cover of functional groups or basal-gap intercept data, would show no difference 

between treatment and control in most instances because seeded plants are still immature at 3 years 

post-seeding. However, cover should increase annually depending on weather, albeit slowly, and basal 

gap may begin to decrease in the 3 years of ES&R-funded monitoring. These measures will be critical in 

determining the long-term effects of ES&R projects on pre-fire vegetation recover, seeded plant 

persistence, invasive species abundance, and site protection. Determining these long-term effects will 

require additional follow-up studies outside the 3-year time frame.

Performance of Quantitative Methods

Multiple issues arise during vegetation monitoring that can add variability to data. To enhance 

data quality and comparability, these issues should be addressed when they occur. While testing the 

monitoring strategy at burned areas in Oregon, we encountered issues associated with density data 

collection, species identification, initial differences between treatment and control plots, basal-gap 

intercept, and line-point intercept measurements. Below we describe issues we encountered with each of 

these techniques so that they can be recognized in early stages of future monitoring efforts.

Density Data Collection

Accurate collection of density data requires the objective identification of individual plants. This 

can be difficult when collecting data on seedlings, rhizomatous species, and residual grass plants.

Therefore, strategies for dealing with these situations need to be developed and applied consistently to 

decrease variation among observers monitoring sample plots in different years.

Individual seedlings can be difficult to distinguish from emerging annual grasses, rhizomatous 

plants, or stray, non-reproductive tillers from existing bunchgrasses (fig. 19). For instance, drill seeding 

creates furrows (to a greater or lesser extent depending on the soil type and drill setting) that can 

separate existing bunchgrasses causing some tillers to appear separated from the mother plant. In the 

first year after a seeding, it is not necessary to identify seedlings to the species level, but it is important 

to accurately identify seeded grasses compared to existing grasses or annual grasses. Training observers 

about the characteristics of the target species seedlings is the first step. The second is calibrating the 

observations of multiple observers by collecting data from the same plots to ensure similarity of 

measurements. These steps can help alleviate errors generated due to identifying individual plants and 

having multiple field personnel in the same or different years. 
50

Rhizomatous plants also can be difficult to quantify depending on how strongly rhizomatous 

they are. Strongly rhizomatous species can be relatively easily counted as tillers/ramets. Weakly 

rhizomatous species present difficulties. These species can be loose bunches or several tillers closely 

spaced with other tillers farther apart. Where individuals are difficult to distinguish, visually identifiable 

“bunches” should be counted. Bunches can be assumed to be individuals for all practical purposes, but 

the definition of individuals must be documented for each monitoring project. For strongly rhizomatous 

species, individual tillers are easily counted and should be the unit of interest. For seeded rhizomatous 

species, such as Elymus lanceolatus (thickspike wheatgrass), our experience is that in the first 3 years 

after a fire they tend to grow like bunchgrasses, presumably becoming more rhizomatous after they are 

well established. 

Prior to collecting density data, observers should be familiar with growth forms and appearance

of mature and seedling plants that grow in the area. Comparison to other plants outside plots can be 

made to determine differences between seedlings and non-seeded species. Control areas may assist in 

training observers on the appearances of existing plants in the area. 

Figure 19. Photograph showing difficulty involved in identifying individuals within drill rows of new seedings.
51

Quadrat Sizes

It is necessary to use at least two different quadrat sizes to efficiently estimate density of all life

forms at a plot. Typically, a belt transect that runs the entire length of a transect is adequate for large or 

adult plants of low to medium densities. Within this large quadrat, it is time consuming to count smaller 

or more abundant plants. These plants, along with seeded plants, can be counted using a smaller quadrat. 

For monitoring at the Vale burned areas, 10 1- x 1-m quadrats were placed along each transect, and 

densities of target plants were counted. This seemed to work well, but depending on the plant 

community, could also be adjusted to increase efficiency. Target plant species that did not have 10 

individuals within the 30 1- x 1-m quadrats were counted in belt transects. Very small and abundant 

plants, such as B. tectorum were counted within subquadrats that were 0.2- x 0.2-m in size. This seemed 

to be a reasonable size as B. tectorum was very often abundant. Additionally, in a few instances, 

abundant rhizomatous grasses were also counted in these small subquadrats.

Size Classes

Size classes are useful for gauging relative age and size of grass species. Monitoring at the four 

Vale burned areas used three size classes. Size class A was an emerging seedling, B was a small, nonreproductive plant, and C was an established, reproductive adult. In practice, there are many plants that 

could be classified as a C one year and a B the next year. Tracking B and C size classes also takes time, 

particularly for rhizomatous plants. Therefore, these two size classes (B and C) have little use unless the 

percentage of plants reproducing in a given year needs to be determined. It is simpler and quicker to 

track seedlings and established plants using two size classes; however, some situations may call for 

using additional classes. 

Species Identification

Some of the seeded species were difficult to distinguish between other seeded or non-seeded 

species without an inflorescence. Once inflorescences were present, it was possible to identify grasses to 

species, but not varietal level. The most problematic species to distinguish in the Vale burned areas were 

bluebunch wheatgrass (P. spicata) versus Snake River wheatgrass (E. wawawaiensis), as well as 

Siberian wheatgrass (A. fragile) versus crested or desert wheatgrass (A. cristatum or A. desertorum). 

It was usually not possible to distinguish between P. spicata and E. wawawaiensis without 

reproductive structures. These two species were previously considered the same species. The difference 

was determined in the field by examining glumes, rachis, and leaves of each plant. The glumes of E. 

wawawaiensis are linear while the glumes of P. spicata are more obovate; however, there was much 

variation within this characteristic. In addition, E. wawawaiensis often showed a darker leaf color with 

the leaf blades slightly reflexed from the stem. This trait also was variable and more evident in older 

established plants. Another characteristic that was highly variable among the P. spicata plants was the 

length of the rachis, ranging from spikelets not overlapping to those with up to one-half their length 

overlapping. When the spikelets were overlapping, it was sometimes difficult to quickly distinguish 

between P. spicata and E. lanceolatus. 

Agropyron fragile was seeded in areas with existing A. cristatum or A. fragile seedings. This 

made it difficult to determine small previously seeded plants from recently seeded plants. Additionally, 

morphological variation within these species often makes it difficult to quickly distinguish between 

them. The USDA PLANTS database ( http://plants.usda.gov accessed 24 Mar 2009) distinguishes 

between A. cristatum, A. desertorum, and A. fragile, whereas Cronquist and others (1994) distinguished 

only A. cristatum, but provide a key to distinguish between A. pectiniforme, A. cristatum, and A. fragile. 

Cronquist and others (1994) combine A. desertorum with A. fragile. According to the USDA plant fact 
52

sheet on crested wheatgrass, A. cristatum (‘fairway’ crested wheatgrass) differs from A. desertorum

(‘standard’ crested wheatgrass) in that it has shorter spikes and the spikes of A. desertorum can be 

comb-like to oblong whereas the spikes of A. cristatum are more widely spreading. During monitoring 

of these fires, plants with characteristics of both species were encountered, as well as plants that were 

intermediate between the two forms (possibly A. cristatum x A. desertorum). According to the USDA 

plant fact sheet, A. fragile is described as being very similar to A. cristatum and A. desertorum except 

that it has finer leaves, narrower and awnless glumes and lemmas and more ascending, sub-cylindrical 

spikelets. We encountered A. fragile plants that varied widely, including having short-awned glumes 

and slightly hairy spikelets.

The ‘Sherman’ cultivar of P. secunda also was commonly used in seedings in the area. This 

cultivar was easily distinguished from the native variety; however, species codes of the two were the 

same despite their vastly different sizes. According to the USDA PLANTS database P. secunda is a 

single species with a wide range in morphological variation whereas Cronquist and others (1994)

recognize P. ampla, and some seed catalogs refer to it as P. ampla var. Sherman. Codes must be defined 

to distinguish between these two varieties in the monitoring data. USDA PLANTS database does retain 

unique synonyms for recognized former species and their use will aid in standardization and future 

comparisons. However, no codes exist for cultivars. 

The problem of identification also extends to recently seeded plants that have not and will not 

flower in the year of monitoring. Although it may be possible to make an educated identification of

species in these cases, it is time-consuming and less accurate than waiting until flowering. In these 

instances, it was better to classify the plant as “unknown seeded grass” and to wait until successive 

years for a positive identification.

Areas open to livestock grazing where inflorescences may be removed or absent, may create 

identification problems. In these cases, it may not be possible to identify to species even for adults. In 

these cases, a standard method of identifying species groups should be used. This can be done by 

recording the USDA plant symbols for the potential species in alphabetical order, separated by forward 

slashes. For example, in the situation where it is not possible to distinguish between crested wheatgrass 

and Siberian wheatgrass, the proper code would be AGCR/AGFR. 

Initial Differences in Control and Treatment Plots 

Initial differences in success indicators between control and treatment plots should be considered 

when analyzing and interpreting data. For example, if control plots have higher cover of pre-burn 

grasses than treatment plots, an increase in cover due to seeding will be more difficult to detect. This 

can be done by comparing changes between the first year to the third year for control and treatment 

plots rather than a direct comparison between plots in any given year. 

Basal-Gap Intercept

Basal-gap intercept is a straightforward and generally repeatable procedure among years and 

observers. However, difficulties occur when there are large concentrations of amorphous grass clumps, 

as can happen in dense P. secunda stands (as seen at the Cow Hollow burn area) or in communities 

dominated by rhizomatous grasses. Additionally, in areas with dense, pre-fire plants, it is difficult to 

detect any changes in gaps resulting from the seeding, because seedlings are small and unlikely to stop 

basal gaps relative to mature, naturally recovering perennials. Observers are better able to detect 
53

changes using this technique when there are fewer pre-existing plants. In addition, this technique may 

be more useful for longer-term (5+ years post-seeding) monitoring of treatment and control plots since 

this length of time may be necessary for seeded plants to grow and begin to close gaps. A decision 

regarding the use of this procedure for the first 3 years monitoring should be made on a case-by-case 

basis.

The basal-gap intercept technique used on these fires included perennial forbs as stopping gaps. 

In retrospect, there is a large amount of variability in forb emergence and abundance from year-to-year 

and that probably introduces additional variation into basal-gap intercept data. Additionally, perennial 

exotic forbs also stop a gap (for example, C. draba). Invasive plants that can increase following a fire

might be better ruled as non-stopping species for this technique. Without such a rule, basal-gap data 

may suggest an improvement in basal-gap intercept data when in fact the area is being invaded. If 

perennial forbs are included in gap measurements, it is necessary to document what species are stopping 

gaps. 

Line-Point Intercept

Cover values for perennial grasses at the four fires generally showed changes from year one to 

three (some increases, some decreases) in both treatment and control plots. While these data were not 

separated into seeded and unseeded groupings, changes were primarily due to variations in the cover of 

pre-fire plants rather than seeded plants. Significant changes in cover due to seeded species, except in 

instances of a highly successful seeding, appear to occur after the 3-year time frame.

The line-point intercept procedure as described in Herrick and others (2005a) counts both live 

and standing dead herbaceous cover the same. After fire, where most herbaceous material is removed, 

cover will be the regenerating live material, and in the second year the regenerating live material plus 

the standing dead from the previous year. This may create an artifact of an increase in cover in the 

second year post-seeding as a result of the method. However, it does create an accurate view of the site 

protection from raindrop impact, a measure of protection from water erosion.

Cover is the best monitoring technique given the time expended in gathering the data for 

tracking the status of invasive annual plants. It allows a measurement of dominance of these species 

relative to the desired perennial plants. Gathering density data for these plants may be time-consuming 

because of the potentially high numbers of individuals (e.g., > 10,000 plants/m2, Mack and Pyke, 1983). 

Cover comparisons of invasive annual grasses between treatment and control plots will aid in 

determining if the seeding treatment alters the dominance of invasive plants.

Conclusions

There was a low level of plant establishment at all seedings from 2005. The primary reason for 

this level of establishment on all treatments except the Cow Hollow seeding was most likely the 

unfavorable timing and amount of precipitation in 2007 and 2008 (fig. 1). Excluding Cow Hollow, 

initial seeded perennial grass densities in 2006 ranged between 2.2 and 6.3 plants/m2 while final 

densities ranged between 0.4 and 1.7 plants/m2. There was an average mortality rate of 76% from 2006 

to 2008 in these six treatments. 

Target objectives for perennial grass density of future projects may wish to consider these 

results. To establish five plants/m2

 at the end of the 3-year monitoring period, density of emerging 

grasses would need to be much higher than those observed in the first spring after seeding. This level of 

plant emergence was not seen in 2006 despite adequate precipitation. Future projects might consider 

either increasing their seeding rates on these sites (Pyke and Archer, 1991) or lowering target density 

objectives in these areas. Additionally, the general state of pre-fire vegetation should be considered 
54

when developing these target objectives. For instance, the Double Mountain non-native seeding was 

primarily composed of exotic annuals prior to the fire. The seeding in this area resulted in less seedling 

establishment than the Double Mountain native seeding where the pre-fire vegetation was composed of 

less cover of exotic annuals and more cover of native perennials. 

The maximum density objective of 100 B. tectorum plants/m2 was likewise not met and may not 

be achievable under any circumstances. Bromus tectorum densities were 4 to 12 times higher than the 

objective. Based on our observations, B. tectorum densities may have increased after drill seeding due to 

soil disturbance, followed by a gradual decrease over time. At the same time, B. tectorum density is 

highly correlated with environmental factors such as precipitation and rodent activity, which may 

override site differences (Mack and Pyke, 1983). Due to this variation and the small size of seeded 

plants, a reasonable target for B. tectorum density is difficult to determine within the first 3 years. Such 

a realistic objective for B. tectorum density would need to vary depending on the postfire weather 

conditions and the amount of disturbance due to treatment application. Objectives related to B. tectorum

cover on seeded versus control plots might be an alternative objective to consider. An example target 

objective might be to maintain or decrease B. tectorum cover on seeded areas relative to controls.

Measurements of density within the first 3 years provide the best estimate of initial seeding 

success. Increases in cover due to seedings were not detectable in the first 3 years following seeding in 

this monitoring effort. Changes in cover resulting from treatments may be detectable in cases where 

seedings are highly successful in the first 3 years following seeding, but based on observations from 

experience from the Vale burned area, this may require several consecutive years of above average 

precipitation to occur. 

Although cover of seeded species may not be a good indication of seeding success in early years 

after treatment, it is useful for monitoring initial patterns of abundance of naturally recovering 

vegetation, exotic annual grasses and forbs, and bare ground. Cover of perennial grasses that survived 

the fire were substantial in some areas. In some cases, this was due primarily to shallow-rooted, 

perennial grasses (P. secunda) while in other areas, natural recovery consisted of both deep and 

shallow-rooted perennial grasses. Identifying the level of natural recovery at a treatment area establishes 

a baseline for long-term assessments of treatment effects. Cover measurements at these four fires also 

revealed patterns common to most of the treatment areas in cover of litter, bare ground, and exotic 

annuals in response to drill seeding and weather patterns. 

There was a rapid increase in litter at all treatments after fires. In 2006, there was an average of 

43.5 and 25.7% litter cover in the control and treatment plots, respectively. By 2008, litter cover had 

increased to 73.6% in the control plots and 70.4% in the treatment plots. Overall, there was less litter in 

treatment than in control plots in 2006, probably due to the mechanical action of the seed drill. The 

exception to this trend was the Double Mountain non-native control plots, which had nearly as much 

litter cover in 2006 as in 2008. The Double Mountain non-native treatment plots had lower litter cover 

in 2006 than the control plots, further supporting the idea that the seed drill reduces litter cover in the 

initial years after treatment. Based on data from this monitoring, it appears that the reduction of litter 

cover due to drill seeding only lasts 2 to 3 years. Litter found in the control and treatment plots, albeit 

much of it from B. tectorum, acts to protect the soil surface from raindrop impact and subsequent 

erosion. 
55

Not surprisingly, there was a corresponding decrease in bare ground from 2006 to 2008. At 

control plots, bare ground decreased from 17.2 to 9.3%, whereas bare ground at treatment plots 

decreased from 24.3 to 12.0%. Initially, higher percentages of bare ground at treatment plots appear to

be due to the mechanical action of the drill. Two treatments, the Keeney Pass and Double Mountain 

non-native seedings, did not follow this trend. At these treatments, bare ground percentages in the 

control stayed nearly the same in 2006 and 2007. In these areas, the fire may not have been intense 

enough to reduce the litter on the ground and expose bare soil. 

Cover of annual grasses, primarily B. tectorum, increased from 2006 to 2007 and then decreased 

slightly in 2008. This pattern was observed in all treatments except the Double Mountain native seeding 

treatment. In 2006, B. tectorum plants were large, probably due to the postfire nutrient flush and above 

average precipitation. In 2007, density and cover increased due to the high seed production in 2006. In 

2008, plants were small due to low precipitation, but abundant from the large cohort of the previous 

year. Density in 2008 was generally similar to 2007 with some treatments increasing and decreasing 

slightly or remaining at the same levels. In general, the first year after fire resulted in lower densities of 

B. tectorum due to the loss of seed from the fire but very robust plants. Highest cover and density of 

exotic annual grasses occurred in the second year following fire due to the first year nutrient flush. 

However, the pattern observed at the Vale fire burned areas may change depending on different 

precipitation regimes and site factors. 

At treatment areas, there was a consistent, negative linear relationship between the amount of 

cover of existing perennial grasses and annual grass cover. This relationship was also apparent in the 

gap data where annual grass cover was greatest when basal gaps in the >200 cm size class were more 

frequent. These relationships indicate the inverse nature of the relationship between presence of 

perennial grasses and annual grass cover, and this suggests that ES&R seedings, when successful, may 

improve rangeland status where annual invasive grasses are problematic. 

There was generally low plant mortality throughout the four burned areas that were monitored

(personal observation). All four fires burned in late July and early August. The last significant rainfall 

prior to the fires was the mid-May 2005. This rainfall may not have been adequate to keep perennial 

plants active, resulting in dormancy by the time of the fire. Future monitoring of plant mortality 

combined with fire timing and weather immediately prior to the disturbance may provide some capacity

to predict when severe mortality will occur, thus aiding decisions on when post-fire rehabilitation 

seedings are necessary. Additional techniques for determining when and where natural recovery will 

occur are also needed to maximize treatment efficiency. 

Overall, quantitative objectives are a valuable part of monitoring the initial success of post-fire 

seedings; however, they need to be adapted for specific sites and adjusted when required. The potential 

of a particular area to reach a certain level of density or cover of desirable plant species (for example, 

ecological site descriptions) and the condition of the pre-fire plant community (for example, healthy or 

degraded) can be used to set initial objectives, which could be further modified by conditional 

statements that depend on environmental conditions after seeding. These conditional objectives may be 

developed to include a range of values rather than a specific target objective. Eventually, given enough 

data from many projects over time, a model could be developed to predict optimum seeding success 

over a range of conditions. Using such a dynamic approach to setting objectives would minimize the 

numbers of projects that are deemed failures due to unrealistic objectives or environmental factors that 

are outside the control of land management. 
56

Monitoring at the four 2005 burned areas from the Vale, Oregon district of the BLM 

demonstrated the potential uses and difficulties associated with monitoring ES&R treatment 

effectiveness. Overall, the monitoring approach combined with the quantitative techniques performed 

reasonably well in burned areas previously dominated by sagebrush. Problems encountered using the 

method were primarily logistical (for example, time required, stratification, or density-data collection) or due 

to the high variability of the natural communities.

Future monitoring efforts should take into account logistical constraints of each design element 

and quantitative technique to arrive at the most cost-effective yet statistically valid monitoring plan. In 

the future, procedures that encompass more of the natural variability either through less intense field 

methods at more locations or the use of remote sensing may be able to capture more of the natural 

variability at the landscape scale.

The value of the three quantitative techniques for interpreting success of post-fire seedings 

depends upon the time frame in which they will be used. For the first 3 years following seeding (the 

period for which monitoring is usually funded), density is the most directly applicable measurement of 

treatment effect and is emphasized in this report. Changes in plant cover and basal-gap intercept 

measurements are small during the first 3 years and, when combined with environmental and observer 

variation, could not be used for determining success. As the seeding ages and plants become larger,

however, comparison of cover and gap-intercept data between treatment and control plots can be used to 

determine long-term effects. Further investigation is needed to determine whether initial densities in the 

first 3 years correlate to later cover and basal-gap intercept measurements. 

In addition to assessing the level of establishment at a variety of different postfire seedings, 

using similar techniques to monitor several treatment areas enabled identification of common patterns. 

Consistent patterns of vegetation attributes identified in these four fires include the rate of accumulation 

of litter and decrease in bare ground cover, the inverse relationship between annual grass and forb cover, 

and the relationships between annual grasses, perennial grass cover and basal gap. Identifying additional 

patterns at a greater number of projects in a wider geographic area and correlating with site factors (such 

as soil, elevation, and climate) will aid efforts to improve seeding success through adaptive 

management. 

Acknowledgments

The Bureau of Land Management provided primary funding for this project (USGS - BLM 

Interagency Agreement #HAI040045). We would specifically like to thank Jack Hamby (BLM, WO) 

and David Repass (BLM, WO) and the ES&R Monitoring Advisory Board: Jan Beyers (USFS, 

PSWRS), Robert Burton (BLM, NV), Jack Brown (BLM, UT), Sharon Paris (BLM, ID), Mike Pellant 

(BLM, ID), Pete Robichaud (USFS, RMRS), Mitch Thomas (BLM, OR), John Willoughby (BLM, CA) 

and Brian Watts (BLM, OR). 

We also would like to thank USGS staff that have helped with field work, offered advice, and 

helped with report preparation: Kevin Knutson, Meagan Gates, Kimberly Klein, Malinda Choitz, 

Andrew Lindgren, Nicole DeCrappeo, Scott Shaff, Susan Powell, Janet Erickson, Ruth Jacobs, Nichole 

Roberts, Kate Kitchell, and Sue Phillips. 
57

References Cited 

Bureau of Land Management, 2005a, Keeney Pass fire (B3LE) emergency stabilization plan: Vale 

District, Malheur Resource Area, Oregon State Office, 19 p. 

Bureau of Land Management, 2005b, Double Mountain fire (B2EY) emergency stabilization plan: Vale

District, Malheur Resource Area, Oregon State Office, 20 p. 

Bureau of Land Management, 2005c, Farewell Bend fire (B2AK) emergency stabilization plan: Vale 

District, Baker Resource Area, Oregon State Office, 16 p. 

Bureau of Reclamation http://www.usbr.gov/pn/agrimet/yearrpt.html for station ONTO. Last accessed 

November 20, 2008. 

Cronquist A., Holmgren, A.H., Holmgren, N.H., Reveal, J.L., and Holmgren, P.K., 1977, Intermountain 

flora: Vascular plants of the Intermountain West, USA, v. 6: The Monocotyledons, New York, 

Columbia University Press, 584 p. 

Di Stefano, J., 2004, A confidence interval approach to data analysis: Forest Ecology and Management, 

v. 187, p. 173-183. 

Elzinga, C.L., Salzer, D.W., and Willoughby, J.W., 1998, Measuring and monitoring plant populations: 

USDI BLM Technical Reference 1730-1, National Business Center, Denver, CO, 492 p. 

Herrick, J.E., Van Zee, J.W., Havstad, K.M., Burkett, L.M., Whitford, W.G., 2005a, Monitoring manual 

for grassland, shrubland, and savanna ecosystems, v. 1, Quick Start: USDA-ARS Jornada 

Experimental Range, Las Cruces, NM, 36 p. 

Herrick, J.E., Van Zee, J.W., Havstad, K.M., Burkett, L.M., Whitford, W.G., 2005b, Monitoring manual 

for grassland, shrubland, and savanna ecosystems, v. 2: Design, supplementary methods and 

interpretation: USDA-ARS Jornada Experimental Range, Las Cruces, NM, 200 p. 

Mack, R.N., and Pyke, D.A., 1983, The demography of Bromus Tectorum: Variation in time and space:

Journal of Ecology, v. 71, p. 69-93. 

Natural Resource Conservation Service, 1997, Soil survey of the Baker County area, Oregon: 

Oregon Climate Service, 2008, PRISM Group, Oregon State University, http://prism.oregonstate.edu/ 

accessed November 27, 2008. 

Oregon State University Agricultural Experiment Station, USDA Soil Conservation Service, and 

Oregon Water Resources Board, 1969, Oregon’s long-range requirements for water: General Soil 

Map Report with Irrigable Areas Malheur River Drainage Basin, Appendix I-10: Burns, Oregon, 85 p. 

Pyke, D.A., and Archer, S., 1991, Plant-plant interactions affecting plant establishment and persistence 

on revegetated rangeland: Journal of Range Management, v. 44, p. 550-557. 

Society for Range Management, 1999, A glossary of terms used in range management: Society for 

Range Management, Denver, Colorado, 20 p. 

Wirth, T.A., and Pyke, D.A., 2007, Monitoring post-fire vegetation rehabilitation projects - A common 

approach for non-forested ecosystems: U.S. Geological Survey Scientific Investigations Report 2006-

5048, 36 p. 

Vallentine, J.F., 1971, Range development and improvements: Brigham Young University Press, Provo, 

Utah.
58

This page left intentionally blank 
59

Appendix A. Monitoring Plot Locations and Soils

Table A1. Locations, slope, aspect, primary and secondary landscape types for monitoring plots at the four fires monitored. 

[Note: Soil information for (Oregon Water Resources Board 1969) for all fires except Farewell Bend which is from the Baker county soil survey. Soil column is 

the mapping unit that the plot sits on according to the soil survey. Texture column is texture from sampling at each plot]

Plot name Northing Easting Elevation (ft) Elevation (m) Slope Aspect Landscape type Secondary

CH-NS-C01 4856367 487463 2,673 815 5 105 Hills/Mountains Shoulder

CH-NS-C02 4855414 486268 2,739 835 11 112 Hills/Mountains Backslope

CH-NS-C03 4856192 486675 2,729 832 5 348 Hills/Mountains Toeslope

CH-NS-C04 4855468 486876 2,755 840 5 193 Hills/Mountains Backslope

CH-NS-T02 4856581 487082 2,690 820 4 18 Hills/Mountains Footslope

CH-NS-T03 4855175 486190 2,690 820 6 194 Hills/Mountains Footslope

CH-NS-T04 4855124 487235 2,772 845 4 80 Hills/Mountains Shoulder

CH-NS-T05 4854743 487200 2,673 815 7 315 Hills/Mountains Backslope

CH-NS-T06 4856537 486532 2,723 830 2 356 Hills/Mountains Shoulder

DM-NN-C00 4860202 467371 2,690 820 10 90 Hills/Mountains Shoulder

DM-NN-C02 4860424 466523 2,960 902 2 66 Basin na

DM-NN-C03 4859302 467516 2,624 800 5 46 Hills/Mountains Shoulder

DM-NN-T02 4859511 467619 2,608 795 2 58 Hills/Mountains Summit

DM-NN-T03 4860303 467983 2,575 785 2 45 Basin na

DM-NN-T05 4859756 466362 2,723 830 2 346 Basin na

DM-NS-C01 4854569 476782 2,903 885 2 42 Hills/Mountains Shoulder

DM-NS-C05 4853774 475215 2,772 845 4 350 Hills/Mountains Summit

DM-NS-C06 4851989 473090 3,133 955 6 2 Hills/Mountains Toeslope

DM-NS-C07 4849813 475005 3,362 1025 9 348 Hills/Mountains Footslope

DM-NS-T07 4855491 474739 2,608 795 3 104 Basin na

DM-NS-T08 4854627 477005 2,854 870 12 99 Hills/Mountains Shoulder

DM-NS-T10 4852314 473629 3,133 955 4 0 Hills/Mountains Toeslope

DM-NS-T11 4850563 474072 3,402 1037 5 78 Hills/Mountains Backslope

DM-NS-T14 4850586 474992 3,264 995 10 64 Hills/Mountains Backslope

DM-NS-T15 4851221 475377 3,133 955 11 56 Hills/Mountains Shoulder

DM-NS-T17 4849503 476094 3,248 990 6 298 Hills/Mountains Backslope
60

FB-NN-C01 4909064 476536 2,690 8205 161 Hills/Mountains Footslope

FB-NN-C05 4908227 476077 2,690 820 10 64 Hills/Mountains Backslope

FB-NN-C06 4909215 475864 2,706 825 12 179 Hills/Mountains Footslope

FB-NN-T01 4908379 476163 2,657 8108 80 Hills/Mountains Toeslope

FB-NN-T02 4908658 475932 2,706 825 14 166 Hills/Mountains Backslope

FB-NN-T03 4908087 475580 2,739 8357 130 Hills/Mountains Summit

FB-NS-C02 4906745 474857 3,018 920 14 43 Hills/Mountains Shoulder

FB-NS-C03 4906808 473022 3,215 980 3 169 Basin na

FB-NS-C04 4907656 474972 2,854 870 12 158 Hills/Mountains Footslope

FB-NS-T06 4907367 475087 2,788 850 14 104 Hills/Mountains Footslope

FB-NS-T07 4906637 473895 3,083 940 14 206 Hills/Mountains Toeslope 

FB-NS-T08 4908076 475100 2,887 880 18 90 Hills/Mountains Backslope

KP-NN-C05 4859314 488118 2,680 8176 222 Hills/Mountains Footslope

KP-NN-C06 4858804 488477 2,624 800 7 215 Hills/Mountains Toeslope 

KP-NN-C07 4858777 487938 2,673 8155 73 Hills/Mountains Backslope

KP-NN-T06 4858765 488209 2,624 8005 93 Hills/Mountains Backslope

KP-NN-T07 4857179 489686 2,793 851 4 215 Hills/Mountains Other

KP-NN-T08 4858537 488852 2,624 8006 175 Hills/MountainsFootslope

KP-NS-C01 4861095 489184 2,739 83586 Hills/Mountains Footslope

KP-NS-C02 4858072 489652 2,690 820 13 48 Hills/Mountains Backslope

KP-NS-C03 4857311 490616 2,608 795 10 44 Hills/Mountains Backslope

KP-NS-C04 4860146 489444 2,762 8427 175 Hills/Mountains Footslope

KP-NS-C08 4860191 487171 2,700 823 9 240 Hills/Mountains Toeslope 

KP-NS-T02 4859438 490249 2,673 8154 112 Flat Plain na

KP-NS-T03 4860784 488830 2,788 850 11 348 Hills/Mountains Backslope

KP-NS-T04 4860735 488139 2,903 885 6 87 Hills/Mountains Backslope

KP-NS-T05 4859436 487718 2,706 825 10 77 Hills/Mountains Backslope
61

Table A2. Soil classification units, series, and measured surface textures at each monitoring plot.

[Ny = Nyssa Silt Loam (tentative series from Oregon Water Resources Board, 1969). Ma = unnamed Silt Loam (tentative series from Oregon Water Resources 

Board, 1969). Unit 60 = Moderately fine-textured, well drained soils on gently sloping hills underlain by lakebed sediments. Typically a loamy surface (0-7") 

and a clay loam subsurface (7-24"). Unit 75 = Loamy, shallow well drained soils over bedrock of basalt, rhyolite, or tuff. Typically a stoney silt loam (0-5") 

underlain by a loam subsurface layer (5-12"). Unit 79 = Loamy, deep, well-drained soils developed from wind deposits. Typically loam to silt loam throughout 

(0-48"). Unit 94 = Raw sediments (small acreages). Unit 98 = Steep raw sediments (small acreages). 122C = Poall very fine sandy loam (very fine sandy loam 

underlain by clay). 143 = Ruckles-Rucklick Complex (Ruckles = very stoney clay loam underlain by clay - very cobbly silt loam underlain by silty clay loam)

124D = Poall very fine sandy loam (very fine sandy loam underlain by clay)]

Plot name Soil Soil series Actual surface texture 0-5 cm

CH-NS-C01 Ny Nyssa Silt Loam Silt Loam

CH-NS-C02 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

CH-NS-C03 Ny Nyssa Silt Loam Silt Loam

CH-NS-C04 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

CH-NS-T02 Ny Nyssa Silt Loam Silt Loam

CH-NS-T03 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

CH-NS-T04 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

CH-NS-T05 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

CH-NS-T06 Ny Nyssa Silt Loam Silt Loam

DM-NN-C00 60-79-94 Unit 60 - Unit 79 - Raw Sediments Sandy Loam 

DM-NN-C02 60-79-94 Unit 60 - Unit 79 - Raw Sediments Sandy Loam

DM-NN-C03 60-79-94 Unit 60 - Unit 79 - Raw Sediments Sandy Loam

DM-NN-T02 60-79-94 Unit 60 - Unit 79 - Raw Sediments Sandy Loam

DM-NN-T03 60-79-94 Unit 60 - Unit 79 - Raw Sediments Sandy Loam

DM-NN-T05 60-79-98 Unit 60 - Unit 79 - Steep Raw Sediments Sandy Loam

DM-NS-C01 Ny 94 Nyssa Silt Loam - Raw Sediments Loamy Sand

DM-NS-C05 Ny 94 Nyssa Silt Loam - Raw Sediments Silty Loam

DM-NS-C06 75-60 Unit 75 - Unit 60 Sandy Clay Loam

DM-NS-C07 75 Unit 75 Loam

DM-NS-T07 Ny 94 Nyssa Silt Loam - Raw Sediments Sandy Loam

DM-NS-T08 Ny 94 Nyssa Silt Loam - Raw Sediments Loamy Sand

DM-NS-T10 75-60 Unit 75 - Unit 60 Sandy Loam

DM-NS-T11 75 Unit 75 Loam
62

DM-NS-T14 75 Unit 75 Loam/Sandy Loam

DM-NS-T15 Ny 94 Nyssa Silt Loam - Raw Sediments Loam

DM-NS-T17 Ny 94 Nyssa Silt Loam - Raw Sediments Loam

FB-NN-C01 143 Ruckles-Rucklick Complex Silty Clay

FB-NN-C05 143 Ruckles-Rucklick Complex Clay Loam

FB-NN-C06 143 Ruckles-Rucklick Complex Clay Loam

FB-NN-T01 124D/143 Poall Very Fine Sandy Loam / Ruckles-Rucklick Complex Clay Loam

FB-NN-T02 124D/143 Poall Very Fine Sandy Loam / Ruckles-Rucklick Complex Clay

FB-NN-T03 143 Ruckles-Rucklick Complex Silty Clay Loam

FB-NS-C02 143 Ruckles-Rucklick Complex Silty Clay Loam

FB-NS-C03 143 Ruckles-Rucklick Complex Clay

FB-NS-C04 143 Ruckles-Rucklick Complex Clay loam/Clay

FB-NS-T06 124D/143 Poall Very Fine Sandy Loam / Ruckles-Rucklick Complex Clay Loam

FB-NS-T07 122C/143 Poall Very Fine Sandy Loam / Ruckles-Rucklick Complex Clay

FB-NS-T08 143 Ruckles-Rucklick Complex Sandy Clay

KP-NN-C05 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NN-C06 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NN-C07 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NN-T06 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NN-T07 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NN-T08 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NS-C01 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-C02 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-C03

Ny Ma / 

Ny 94

Nyssa Silt Loam - Unnamed Silt Loam/

Nyssa Silt Loam - Raw Sediments Silt Loam

KP-NS-C04 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-C08 Ny Nyssa Silt Loam Silt Loam

KP-NS-T02 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-T03 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-T04 Ny Ma Nyssa Silt Loam - Unnamed Silt Loam Silt Loam

KP-NS-T05 Ny 94 Nyssa Silt Loam - Raw Sediments Silt Loam
Publishing support provided by the U.S. Geological Survey

Publishing Network, Tacoma Publishing Service Center

For more information concerning the research in this report, contact the 

Director, Forest and Rangeland Ecosystem Science Center

U.S. Geological Survey

777 NW 9th Street

Corvallis, Oregon 97330

http://fresc.usgs.gov/ 
Wirth and Pyke— Final Report for Emergency Stabilization and Rehabilitation Treatment Monitoring, Keeney Pass, Cow Hollow, Double Mountain, and Farewell Bend Fires—Open-File Report 2009-1152