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Interactions Among Livestock Grazing, Vegetation Type, and
Fire Behavior in the Murphy Wildland Fire Complex in Idaho
and Nevada, July 2007
Open-File Report 2008–1214
In cooperation with the Murphy Wildland Fire Grazing and Fuel Assessment Team
U.S. Department of the Interior
U.S. Geological Survey
Prepared in cooperation with the Murphy Wildland Fire Grazing and
Fuel Assessment Team
Interactions Among Livestock Grazing, Vegetation Type,
and Fire Behavior in the Murphy Wildland Fire Complex
in Idaho and Nevada, July 2007
By Karen Launchbaugh, University of Idaho; Bob Brammer, Idaho Department of Lands; Matthew L. Brooks,
U.S. Geological Survey; Stephen Bunting, University of Idaho; Patrick Clark, U.S. Department of Agriculture,
Agricultural Research Service; Jay Davison, University of Nevada; Mark Fleming, Idaho Department of Fish
and Game; Ron Kay, Idaho State Department of Agriculture; Mike Pellant, Bureau of Land Management;
David A. Pyke, U.S. Geological Survey; and Bruce Wylie, ASRC Research and Technology Solutions
contractor to U.S. Geological Survey
Open-File Report 2008–1214
U.S. Department of the Interior
U.S. Geological Survey
DIRK KEMPTHORNE, Secretary
U.S. Geological Survey
Mark D. Myers, Director
U.S. Geological Survey, Reston, Virginia: 2008
For product and ordering information:
World Wide Web: http://www.usgs.gov/pubprod
Telephone: 1-888-ASK-USGS
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its natural and living resources, natural hazards, and the environment:
World Wide Web: http://www.usgs.gov
Telephone: 1-888-ASK-USGS
Suggested citation:
Launchbaugh, Karen and others, 2008, Interactions among livestock grazing, vegetation type, and fire
behavior in the Murphy Wildland Fire Complex in Idaho and Nevada, July 2007: U.S. Geological Survey
Open-File Report 2008-1214, 42 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.
ii
Contents
Abstract ................................................................................................................................................................................ 1
Introduction and Background .......................................................................................................................................... 2
The Murphy Wildland Fire Complex ............................................................................................................................ 4
Purpose and Scope ........................................................................................................................................................ 6
Description of Affected Area ........................................................................................................................................ 6
Description of Fire Events ............................................................................................................................................. 8
Observations and Photographic Example of Fire Effects .......................................................................................... 11
Fire Behavior and Fuel-Consumption Analyses .......................................................................................................... 13
Examination Approach 1 – Potential for Livestock Grazing to Affect Fuel Loads and Subsequent Fire
Behavior Using a Fire-Modeling Approach ............................................................................................................. 13
Modeling Procedures .............................................................................................................................................. 14
Interpretation of Fire Modeling Results ................................................................................................................ 15
Summary of Modeling Results ................................................................................................................................ 19
Examination Approach 2 – Relation between Vegetation Type and Fuel Consumption .................................. 19
Defining Burn Severity and Fuel Consumption .................................................................................................... 20
Landscape Comparison of Fuel Consumption Among Vegetation Types ....................................................... 21
Examination Approach 3 – Major Drivers That Created Distinct Lines of Difference and Discontinuity
in Burn Severity ............................................................................................................................................................. 24
Examination Procedures ......................................................................................................................................... 25
Major Drivers of Discontinuities in Burn Severity .............................................................................................. 27
Report Summary and Conclusions ................................................................................................................................ 30
Major Findings and Lessons Learned ....................................................................................................................... 30
Future Opportunities ..................................................................................................................................................... 31
Recommendations ........................................................................................................................................................ 32
Research Gaps and Limitations ................................................................................................................................. 33
References Cited .............................................................................................................................................................. 34
Appendix 1. Murphy Wildland Fire Grazing and Fuel Assessment Team ............................................................... 37
Appendix 2. Common and Scientific Names of Plants Referred to in Text. Scientific names follow
the USDA PLANTS Database ......................................................................................................................................... 40
Appendix 3. Glossary of Terms and Unit Abbreviations ............................................................................................ 41
iii
Figures
Figure 1. Trends in authorized use by grazing livestock on BLM lands in Idaho from 1947 through 2004 ........ 3
Figure 2. Map of area affected by Murphy Wildland Fire Complex, July 2007 ....................................................... 5
Figure 3. Cover of annual grasses and other annual plants in the area of the Murphy Wildland Fire
Complex, July 2007 ............................................................................................................................................................. 7
Figure 4. Precipitation records for Murphy Wildland Fire Complex Area, 1990–2007 .......................................... 8
Figure 5. Fire progress and daily fire activity of the Murphy Complex Fires, July 16– 25, 2007 ........................ 10
Figure 6. Extensively burned area in the Murphy Wildland Fire Complex ............................................................ 11
Figure 7. Mosaic of burned and unburned rangeland within the Murphy Wildland Fire Complex ................. 12
Figure 8. Two examples of fire-behavior contrasts at fence-lines separating pastures that had different
grazing regimes before the fire ...................................................................................................................................... 12
Figure 9. Fire behavior estimates based on modeling of a sagebrush steppe situation (GS1 model) with
herbaceous fuel (1-htl) and 10 percent dead fuel moisture (DFM) ......................................................................... 16
Figure 10. Fire behavior estimates based on modeling of a sagebrush steppe situation (GS1 model) with
herbaceous fuel (1-htl) and 12 percent dead fuel moisture (DFM) ......................................................................... 17
Figure 11. Fire behavior estimates based on modeling of a sagebrush steppe situation (GS1 model) with
carry over fuels from previous years reduced by 50 percent (to 200 lb/acre) and 12 percent dead fuel
moisture (DFM) ................................................................................................................................................................. 18
Figure 12. Burn severity based on delta Normalized Burn Ratio for the Murphy Wildland Fire Complex,
Idaho, July 2007 ................................................................................................................................................................ 22
Figure 14. Fourteen focus areas of distinct contrasts in burn severity based on delta Normalized Burn
Ratio (dNBR) for the Murphy Wildland Fire Complex that were examined to determine possible
explanation for these contrasts ..................................................................................................................................... 26
Tables
Table 1. Burn severity (dNBR) observed and classified after Murphy Wildland Fire Complex expressed
as a percentage of area within pre-fire vegetation types ........................................................................................ 23
Table 2. Burn severity contrast importance values (10 is high, 1 is low) from four observers summarized
across all burn severity contrast segments having the highest mean ................................................................... 28
Table 3. Importance values (10 is high, 1 is low) from four observers for three burn severity contrast
segments within grass-dominated areas ..................................................................................................................... 29
iv
v
Conversion Factors
Inch/Pound to SI
Multiply By To obtain
Len
g
th
foot (ft) 0.3048 meter (m)
Area
acre 0.4047 hectare (ha)
acre 0.004047 s
q
uare kilometer (k
m
2)
Densit
y
p
ound
p
er acre 1.12 kilo
g
ram
p
er hectare (k
g
/ha)
Flow rate
mile
p
er hour (m
p
h) 1.609 kilometer
p
er hour (km/h)
Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:
°C=(°F-32)/1.8
Interactions Among Livestock Grazing, Vegetation
Type, and Fire Behavior in the Murphy Wildland Fire
Complex in Idaho and Nevada, July 20071
By Karen Launchbaugh2, University of Idaho; Bob Brammer, Idaho Department of Lands; Matthew L.
Brooks, U.S. Geological Survey; Stephen Bunting, University of Idaho; Patrick Clark, U.S. Department
of Agriculture, Agricultural Research Service; Jay Davison, University of Nevada; Mark Fleming,
Idaho Department of Fish and Game; Ron Kay, Idaho State Department of Agriculture; Mike Pellant,
Bureau of Land Management; David A. Pyke, U.S. Geological Survey; and Bruce Wylie, ASRC
Research and Technology Solutions contractor to U.S. Geological Survey
Abstract
A series of wildland fires were ignited by lightning in sagebrush and grassland communities
near the Idaho-Nevada border southwest of Twin Falls, Idaho in July 2007. The fires burned for
over two weeks and encompassed more than 650,000 acres. A team of scientists, habitat specialists,
and land managers was called together by Tom Dyer, Idaho BLM State Director, to examine initial
information from the Murphy Wildland Fire Complex in relation to plant communities and patterns
of livestock grazing. Three approaches were used to examine this topic: (1) identify potential for
livestock grazing to modify fuel loads and affect fire behavior using fire models applied to various
vegetation types, fuel loads, and fire conditions; (2) compare levels of fuel consumed within and
among major vegetation types; and (3) examine several observed lines of difference and
discontinuity in fuel consumed to determine what factors created these contrasts.
The team found that much of the Murphy Wildland Fire Complex burned under extreme
fuel and weather conditions that likely overshadowed livestock grazing as a factor influencing fire
extent and fuel consumption in many areas where these fires burned. Differences and abrupt
contrast lines in the level of fuels consumed were affected mostly by the plant communities that
existed on a site before fire. A few abrupt contrasts in burn severity coincided with apparent
differences in grazing patterns of livestock, observed as fence-line contrasts. Fire modeling
revealed that grazing in grassland vegetation can reduce surface rate of spread and fire-line
intensity to a greater extent than in shrubland types. Under extreme fire conditions (low fuel
moisture, high temperatures, and gusty winds), grazing applied at moderate utilization levels has
limited or negligible effects on fire behavior. However, when weather and fuel-moisture conditions
are less extreme, grazing may reduce the rate of spread and intensity of fires allowing for patchy
burns with low levels of fuel consumption.
1 Report was prepared by a team and was peer reviewed following USGS standards.
2 Launchbaugh is listed first as team leader. Other authors (team members) are listed in alphabetical order.
1
The team suggested that targeted grazing to accomplish fuel objectives holds promise but
requires detailed planning that includes clearly defined goals for fuel modification and appropriate
monitoring to assess effectiveness. It was recommended that a pilot plan be devised to strategically
place grazed blocks across a landscape to create fuel-reduction bands capable of influencing fire
behavior. Also suggested was the development of a general technical report that highlights
information and examples of how livestock grazing influences fire extent, severity, and intensity.
Finally, the team encouraged continued research and monitoring of the effects of the Murphy
Wildland Fire Complex. Much more can be learned from the effects of this extensive fire complex
that may offer insight for future management decisions.
Introduction and Background
The sagebrush steppe ecosystem dominates about 73 million acres of western North
America, but this amount is only about 55 percent of its historical potential (Connelly and others,
2004). Fire has been a major factor contributing to this change. More frequent and larger fires are a
growing reality in the management of western rangelands. In Idaho and Nevada, the last decade
(1997 to 2007) has yielded 18 fires greater than 100,000 acres. However, the size of these very
large fires appears to be increasing given that 6 of the 10 largest fires of the decade occurred in
2006 and 2007 (National Interagency Fire Center [NIFC] records; http://www.nifc.gov). Impacts on
natural and fiscal resources are high during those years when large acreages burn. Annual weather
conditions undoubtedly contribute to the acreage burned in any given year, but other factors also
may contribute to the risk of wildfire in the sagebrush steppe ecosystems. These factors include
(1) changes in livestock management, such as reductions in stocking rates and changes in grazing
seasons; (2) increased abundance of invasive species, such as cheatgrass; and (3) increased
wildland-urban interfaces where human-derived ignitions can occur (Miller and Narayanan, 2008).
Heavy livestock grazing is thought to have affected fire regimes by severely reducing fuel
loads and thereby reducing the potential for fires to sustain ignition and spread. The introduction of
cattle, sheep, and horses to the Great Basin in the 1860s quickly created large ranching operations
and excessive grazing pressure. The severe overgrazing removed fine fuels and resulted in a
substantial reduction in the number of fires and the acres burned. Only 44 fires, burning a total of
11,000 acres, were reported from 1880 to 1912 in Great Basin rangelands (Miller and Narayanan,
2008). Evidence for reduced numbers of fires during this period is also deduced from the near
elimination of fire scars on trees adjacent to sagebrush ecosystems during the late 1800s and
continuing through most of the 1900s (Miller and Rose, 1999; Miller and Tausch, 2001).
The number of livestock in Great Basin and sagebrush ecosystems has dropped rapidly
since the passage of the Taylor Grazing Act of 1934 (43 USC 315;
http://www.blm.gov/wy/st/en/field_offices/Casper/range/taylor.1.html, accessed July 23, 2008).
Livestock numbers in Idaho decreased in the 1950s primarily from loss of large sheep operations
(indicated by changes in authorized use for grazing; fig. 1). Livestock numbers have fluctuated at
or below this initial decrease through the remainder of the 1900s, with a steady conversion from
sheep to cattle. In the last decade, a substantial decrease in authorized use on Bureau of Land
Management (BLM) lands in Idaho has been recorded (fig. 1).
2
Figure 1. Trends in authorized use by grazing livestock on BLM lands in Idaho from 1947 through
2004.
An important factor contributing to an increase in wildfires includes the expansion of
cheatgrass (D'Antonio and Vitousek, 1992). Of the nearly 98 million acres of BLM lands in Idaho,
Nevada, Oregon, Utah, and Washington, 17.3 million acres are believed to have at least 10 percent
of the plant biomass composed of annual grasses, including cheatgrass or medusahead (Pellant and
Hall, 1994). These annual grasses create fine-fuel loads that increase the probability of fire starts
and the rate of fire spread in areas they dominate (Brooks and Pyke, 2001).
Increased human activities in wildlands and expansion of the wildland-urban interface have
also contributed to the recent increase in the number of wildfires (Connelly and others, 2004).
Increases in human habitation and activity in the rangelands of southern Idaho have been at least
partially responsible for the increase in wildfire starts in recent years. In the Jarbidge Field Office
(FO) of the BLM, 43 percent of the wildfires since 1987 were human caused.
3
The Murphy Wildland Fire Complex
On July 16 and 17, 2007, a series of wildland fires were ignited by lightning in rangelands
near the Idaho-Nevada border southwest of Twin Falls, Idaho. The Rowland Fire (initiated west of
Murphy Hot Springs, Idaho) and Elk Mountain Fire (initiated southeast of Three Creeks, Idaho)
grew together and became known as the Murphy Wildland Fire Complex (fig. 2). The Scott Creek
Fire (west of Jackpot, Nevada) also was ignited by lightning on July 17 and was later designated as
part of the Murphy Wildland Fire Complex. Some of the fires in this complex burned for more than
two weeks, and the complex was fully contained by August 2, 2007. This complex of fires burned
across portions of three BLM FOs (Jarbidge, Bruneau, and Elko), portions of the Humboldt-
Toiyabe National Forest, about 48 sections of land managed by the State of Idaho, and extensive
stretches of private lands. A total of 652,016 acres was encompassed by this fire complex (NIFC
data: http://www.nifc.gov).
These wildfires had tremendous impacts on the sagebrush steppe ecosystems of south-
central Idaho and a portion of north-central Nevada. Seasonal and year-long habitats were altered
for sage-grouse, mule deer, elk, bighorn sheep, pronghorn, Brewer’s sparrow, sage sparrow, other
sagebrush-obligate birds, and many other wildlife species that use these rangelands. Severe impacts
also were exacted on forage resources for livestock, cultural resource values, and watershed health
and stability as a result of these fires. The ecological impacts of this fire will take several years to
be fully realized and will vary depending on weather conditions in the coming years.
In the last three decades, several wildfires have occurred in the area that burned in the
Murphy Wildland Fire Complex. Many of these burned areas were revegetated with perennial
grasses, including both introduced and native species. Records from the Jarbidge Field Office (FO)
of the BLM indicate that about 402,000 acres were seeded through the end of 2006. This number of
acres represents 26 percent of the total public lands in the Jarbidge FO. Some land managers and
livestock operators speculated that extensive seedings of perennial grasses following wildfires,
without commensurate increases in livestock grazing, contributed to an increase in herbaceous
production. The speculation in turn, considered the possibility that increased herbaceous production
provided additional fuels for wildfire.
4
Figure 2. Map of area affected by Murphy Wildland Fire Complex, July 2007.
5
Purpose and Scope
In August 2007, a team3 of scientists, habitat specialists, and land managers was called
together by Tom Dyer, Idaho BLM State Director, to examine initial information from the Murphy
Wildland Fire Complex in relation to plant communities and livestock grazing patterns. This report
is the result, which is presented to meet the following objectives:
• Provide preliminary observations and recommendations regarding the effects, if any, of existing
plant community composition (native rangeland and crested wheatgrass seedings) and current
management of livestock grazing on fire behavior and rate of spread of the Murphy Complex
Fires. Historical or potential vegetation composition, because it may have been influenced by
historical livestock grazing levels or practices is, by necessity, background information and not
the focus of this report.
• Provide recommendations for long-term research or studies needed to address issues or
remaining questions surrounding the use of livestock to reduce fuels while maintaining post-fire
resource values in the area encompassed by the Murphy Wildland Fire Complex.
• Discuss the potential application of the findings gleaned from the Murphy Wildland Fire
Complex to other areas from a “lessons learned” perspective.
Description of Affected Area
The Murphy Wildland Fire Complex encompassed more than 1,000 square miles of
rangelands. Most of this area was dominated by sagebrush steppe communities. Most of the areas
(greater than 50 percent) that burned were sagebrush communities with an understory of native
grass (based on figures for areas burned on BLM lands in Idaho). The most abundant vegetation
type was Wyoming big sagebrush with an understory of native grass, including lesser coverages of
low or black sage, and only small coverages of mountain big sagebrush or other combinations of
sagebrush and non-native grasses.
About 20 percent of the area that burned was dominated by grasslands that included a few
scattered shrubs. These grasslands included stands of native grasses (for example, bluebunch
wheatgrass) and plantings of crested wheatgrass, intermediate wheatgrass, and other non-native
grasses. Although fire in sagebrush steppe communities commonly is associated with an understory
of annual grasses, only a small portion (less than 5 percent) of the area that burned in the Murphy
Wildland Fire Complex was dominated by annual non-native grasses, including cheatgrass or
medusahead. The plant communities dominated by annual plants were located in the northern
reaches of the Murphy Wildland Fire Complex area (fig. 3). The remaining area that burned in the
Murphy Complex Fires was a mix of rabbitbrush stands with an understory of grasses, a variety of
other shrubland and woodland types, and sparsely vegetated areas.
3 See appendix 1 for a full list of team members and their organizational affiliations.
6
Figure 3. Cover of annual grasses and other annual plants in the area of the Murphy Wildland Fire
Complex, July 2007.
7
Description of Fire Events
The wildfires that became the Murphy Wildland Fire Complex were started by lightning on
July 16 and 17, 2007. Several environmental factors created conditions that favored the ignition and
rapid spread of these fires. A low-pressure system produced windy conditions (from the
south/southwest), and below-normal nighttime humidity supported the fires’ rapid spread in the
first few days after ignition.
A combination of weather and fuel conditions set the stage for the rapid growth and total
extent observed in the Murphy Wildland Fire Complex. These conditions included a prolonged
period of below-normal precipitation in the spring and early summer of 2007 (fig. 4). This dry
period contributed to daily relative humidity (RH) values that were 12–25 percent below the long-
term average (May–July 2007 compared to 1990–2006 average from four remote automated
weather stations; RAWS). Temperatures also were high in south-central Idaho in the days
preceding the fires, with daily temperatures the week before the fires exceeding 96°F and two days
exceeding 100°F. These hot, dry conditions in the days before the fire resulted in conditions for fire
fuels that were more extreme than any observed in the past decade. (The Energy Release
Component [ERC] values in the week before the fire were higher than those reported in the last
decade. The ERC value is an output of fire-modeling procedures and reflects fuel dryness and
potential heat release per unit area in a fire event.)
Figure 4. Precipitation records for Murphy Wildland Fire Complex Area, 1990–2007.
Data are from RAWS: Horse Butte, Twin Butte, Pole Creek, and Bull Springs.
8
The Rowland and Elk Mountain fires were ignited by lightning and initially influenced by
thunderstorms over the high country along the Idaho-Nevada State line (see lightning strike
symbols in fig. 2). The passing of a weather front associated with the low-pressure system moved
south across the area and was positioned south or southwest of the fires, creating winds that blew to
the northeast and strongly pushed the fire during the initial stages. These fires showed rapid
expansion in the three days after ignition, moving mostly in a northeasterly direction. The rapid
expansion of these fires also was a result of sufficient fuel loads and low fuel moisture created by
lack of precipitation in the weeks before the fires. Fire behavior in these first few days was
reportedly extreme and erratic as a result of high daytime temperatures (87° to 99°F; based on four
RAWS), low daytime RH (less than 10 percent on July 18 and 20), and gusty winds. Weather
conditions on July 18 were particularly problematic with a daytime temperature greater than 95°F,
RH of 8 percent, and winds gusting as high as 34 mph. These severe conditions resulted in rapid
expansion of the Elk Mountain and Rowland fires from less than 10,000 acres each to near or
greater than 100,000 acres in each fire within the first two days after ignition (fig. 5). By July 20,
the Elk Mountain Fire had expanded to an estimated 160,000 acres and was only 10 percent
contained (NIFC report; http://www.nifc.gov). The Rowland Fire had expanded to about 95,000
acres and was estimated to be only 15 percent contained by July 20 (http://www.nifc.gov). Fire
suppression during these initial days of the Murphy Wildland Fire Complex was hindered by the
scarcity of fire-suppression resources because of the large number of wildfires (more than 40 other
fires) burning mostly in Idaho and Montana (NIFC reports, http://www.nifc.gov).
These two fires continued to expand from July 21–23, aided by high daily temperatures
(exceeding 95°F) and low daytime RH (10 to 13 percent). Nighttime recovery of RH was unusually
low, with maximum reported RH less than 40 percent. These weather conditions resulted in large
advances of the fire front with aggressive fire behavior occurring during nighttime hours. On July
22, four and five days after ignition, the Rowland and Elk Mountain fires burned together and, with
inclusion of the Scott Creek Fire, covered about 442,000 acres with only 10 percent containment
(NIFC reports, http://www.nifc.gov).
The fires of the Murphy Wildland Fire Complex continued to expand on several fronts to an
estimated affected area exceeding 550,000 acres by July 23. Beginning late on July 23, moisture
began to stream into the affected area from southern Nevada, and humidity increased dramatically
by July 24. The days from July 24–27 signified a period when the fires began to slow and
firefighters began to gain containment (fig. 5). Significant cloud cover, high daytime (29–32
percent) and nighttime (59–72 percent) RH, and much cooler temperatures (82–88°F) reduced the
spread and intensity of the fires. Some light rain occurred on July 24, with thunderstorms over the
fire area on July 25–26. By the morning of July 27, the Murphy Wildland Fire Complex was
estimated to be 70 percent contained, and only small advancements were recorded in subsequent
days. The fire was declared 100 percent contained on August 2, 2007 (NIFC reports,
http://www.nifc.gov).
9
Figure 5. Fire progress and daily fire activity of the Murphy Complex Fires, July 16– 25, 2007.
10
Observations and Photographic Example of Fire Effects
The Murphy Wildland Fire Complex was recognized for its massive expanse and nearly
complete consumption of vegetation on many of the burned areas (fig. 6). However, the fires of the
Murphy Complex, like all wildland fires, burned in a mosaic over a portion of the area (fig. 7).
Aerial views of the Murphy Wildland Fire Complex obtained by helicopter on August 3, 2007
illustrate several interesting examples of changes in fire behavior related to vegetation communities
and are available at http://www.uidaho.edu/range/MurphyFireComplex/ (provided by M. Pellant).
This report focuses on the potential role that livestock grazing played in altering fuel loads
and fuel types that affected the pattern and severity of fires in the Murphy Wildland Fire Complex.
Because fire behavior, fire extent, and level of vegetation consumed result from many interacting
factors, the specific role that grazing had on the fires was difficult to ascertain. The team preparing
this report toured the area of the Murphy Wildland Fire Complex on August 28, 2007 and saw first-
hand examples of completely burned areas, patchily burned mosaics, and contrasts where fires
stopped at a fence-line or only fingered into the adjacent pasture. A reasonable explanation for
these contrasts was a difference in the grazing management between the areas on each side of the
fence-line (fig. 8).
Livestock operators in the area shared their knowledge of the pre-burn vegetation
conditions, levels of grazing use, and on-site observations of fire behavior with the report team.
These observations supported the possibility that livestock grazing resulted in a mosaic burn or
observable fence-line contrasts that could be attributed to differences in utilization levels created by
livestock grazing.
Figure 6. Extensively burned area in the Murphy Wildland Fire Complex.
Photograph taken west of Three Creek, Idaho on August 28, 2007, by
K. Launchbaugh.
11
Figure 7. Mosaic of burned (in background) and unburned rangeland
(in foreground) within the Murphy Wildland Fire Complex. Photograph
taken west of Three Creek, Idaho on August 28, 2007 by K. Launchbaugh.
NotGrazed
BeforeFire
GrazedBeforeFire
W.Butler
K.Launchbaugh
NotGrazed
BeforeFire
GrazedSpring
BeforeFire
K.Launchbaugh
Figure 8. Two examples of fire-behavior contrasts at fence-lines separating pastures that had
different grazing regimes before the fire. Photograph on left taken by K. Launchbaugh, Photograph
on right by W. Butler.
In summary, the findings that follow provide a scientific analysis of the relationships among
livestock use, wildfire characteristics, and fuels. However, the anecdotal information gathered by
the team based on their observations, professional experience, and input by others involved in the
suppression of this fire also contributed to the assessment.
12
Fire Behavior and Fuel-Consumption Analyses
The specific role of livestock grazing on fuel loads and fire behavior, and subsequent fuel
consumed in the Murphy Wildland Fire Complex is of considerable importance to land managers,
landowners, and the public interested in sagebrush steppe ecosystems. However, like most complex
ecological questions, there are many ways to seek answers. Three approaches were used in our
effort to understand the role that vegetation type and amount had on fire behavior and fuel
consumption:
1. Identify potential for livestock grazing to modify fuel loads and affect fire behavior using fire
models applied to various vegetation types, fuel loads, and fire conditions.
2. Compare level of fuel consumed within and among major vegetation types.
3. Examine several observed lines of difference and discontinuity in fuel consumed to determine
what factors created these contrasts.
Examination Approach 1 – Potential for Livestock Grazing to Affect Fuel Loads and
Subsequent Fire Behavior Using a Fire-Modeling Approach
It is well known that grazing, especially by cattle, late in the growing season or during
dormant periods reduces herbaceous residual biomass. It also is accepted that the kind, amount, and
distribution of herbaceous biomass are an important factor affecting behavior of wildland fires.
Thus, grazing can potentially affect fire behavior. However, grazing effects on herbaceous fuels
and fire behavior vary extensively by site and situation. The team used a fire-behavior modeling
system (BEHAVE Plus; Andrews and others, 2003) to examine how varying the amounts of
current-year and residual herbaceous biomass and fuel loads would affect fire behavior in
sagebrush steppe and grasslands under various environmental and fuel-moisture conditions. The
team’s intent for this modeling exercise was to address two fundamental questions:
• What is the potential for livestock grazing in shrub and grassland communities of the sagebrush
steppe to reduce fire intensity and facilitate effective fire containment and control?
• Under the environmental conditions observed during the Murphy Wildland Fire Complex,
would livestock grazing have affected fire intensity, containment, and control?
Generally, the team’s modeling approach was to simulate grazing effects on fire behavior
by incrementally reducing herbaceous fuel-parameter values while holding parameters for other
fuel and environmental conditions constant (for example, dead fuel loading, live shrub loading, live
and dead fuel moisture, slope, and weather). The models used in this simulation were developed
based on inputs from several sources, including BLM inventory data for vegetation, ecological site
descriptions, published literature, and existing fuel models in the BEHAVE Plus software program.
13
Modeling Procedures
The team focused on four fuel models corresponding to cheatgrass, seeded grass, or one of
two sagebrush steppe vegetation community types. Complete details on all model runs are available
at: http://www.uidaho.edu/range/MurphyFireComplex/. The basic sagebrush steppe model (GS1)
was derived from Scott and Burgan (2005), with some minor modifications to the fuel-loading
values. The other sagebrush steppe model (SG06) was published by Ottmar and others (2007) and
generally includes more sagebrush cover and higher herbaceous fuel loads than the GS1 model.
The cheatgrass model was based primarily on BLM inventory data and findings reported by
Whisenant (1990) and Keeley and McGinnis (2007). The seeded-grass model was a modification of
the cheatgrass model and was the most difficult to develop because no published fuel models for
this vegetation type existed.
There are several assumptions and caveats that should be kept in mind when interpreting the
results presented below. The Rothermel equation (Rothermel 1972; 1983), on which BEHAVE Plus
is based, assumes the following conditions exist: uniformity in fuel continuity, weather, wind, and
slope; no fire spotting (that is, fire starting from embers landing in advance of the fire front); no
extreme fire behavior; and surface fire only. These assumptions were not consistently met during
the Murphy Wildland Fire Complex. For example, it was known that the fuels were not uniform
throughout, relative humidity changed from day to night, and winds were gusty. However, these
models provided a mechanism to compare the changes in fuels that grazing and vegetation
composition would most likely impact. The results provide fire behavior predictions only for a free-
running head fire at steady state. For simplicity, only results for surface rate of spread and fire line
intensity are presented because these fire behavior variables are most easily understood and are
indicative of overall fire behavior as they relate to controlling a fire.
In fire models such as BEHAVE Plus, the green grass and forbs consumed by grazing
animals are termed “live herbaceous fuel loading” or LHFL. Because it is LHFL that is altered by
grazing, LHFL is always presented in this report on the horizontal X-axis. Values range from 0 to
1,200 lb/acre. In some runs, the residual fine fuel loads were reduced to simulate several years of
consecutive grazing that could lower the carryover of residual fine fuel loads from one year to the
next. The fuels created by dead grass and small twigs are called “1-hour time lag” (1-htl) fuels in
fire models. These 1-htl fuels were modified to simulate the effect of grazing to reduce carryover of
residual dormant grass and forbs from one year to the next.
Several considerations apply when interpreting the results presented. First, direct fire attack
is not recommended when fire line intensity is greater than 100 British Thermal Units per foot per
second (BTU/ft/sec) or when flame length exceeds 4 feet. Under these conditions, fire professionals
generally retreat and find a better place to stop the fire or to wait for the weather to change.
Additionally, to keep this report concise, only selected graphical results from the GS1 sagebrush
steppe model are presented as figures; however, other models are discussed in relation to these
graphs. The other output graphics from each model can be viewed at
http://www.uidaho.edu/range/MurphyFireComplex/.
14
Interpretation of Fire Modeling Results
The sagebrush steppe and grassland models were run at varying dead fuel moisture (DFM)
levels, including 6, 8, 10, 12, and 14 percent. The results of the two sagebrush models (GS1 and
SG06) were similar with respect to how decreasing LHFL affected fire behavior. When live
herbaceous fuel was decreased to simulate grazing, both sagebrush models predicted a reduction in
all fire behavior variables, although specific effects varied depending on wind speed.
Under relatively dry conditions of 10 percent DFM, extreme fire behavior (that is, fire line
intensity greater than 100 BTU/ft/sec) was predicted until LHFL was reduced to less than 200
lb/acre (fig. 9). The effect of reduced herbaceous biomass on fire behavior was more pronounced
under less-intense fire conditions (that is, greater than or equal to 12 percent DFM; fig. 10). The
potential role of grazing to reduce fuel loads and modify fire behavior is more feasible and effective
under cooler and more humid conditions (compare figs. 9 and 10). There appeared to be a threshold
in the herbaceous biomass effect at 400 to 600 lb/acre of LHFL under the 12 percent DFM
condition (fig. 10). Within this LHFL range, there was a rapid change in fire behavior indicating a
condition under which fire behavior was particularly responsive to changes in biomass of live
herbaceous biomass. Model runs at 14 percent DFM were nearly at the moisture level where the
fire would have been extinguished; consequently, the predicted fire barely burned. (Results
available at: http://www.uidaho.edu/range/MurphyFireComplex/).
To simulate effects of several consecutive years of grazing, the team considered a situation
in which the carryover of fine fuels was reduced by 50 percent to 300 lb/acre. Under these fuel
conditions, measures of fire behavior were further reduced and apparent thresholds became more
obvious as the LHFL changed from 700 to 1,000 lb/acre (fig. 11). Thus, the rate of spread and fire
line intensity of a wildfire may be reduced if grazing or lower-than-normal precipitation occurred in
the years preceding a fire, reducing the carryover of fine fuels from one year to the next.
Effect of slope was tested using the GS1 model, and no interaction between slope and
simulated grazing-use levels was detected. This indicates that effects of removing biomass by
grazing would have a similar effect on level or sloped land. (Results available at:
http://www.uidaho.edu/range/MurphyFireComplex/).
The cheatgrass and seeded grass models were run at 6, 8, 10, and 12 percent DFM.
Simulated grazing reduced measures of fire behavior at all fuel moisture levels, but was more
pronounced under more moist conditions (that is, higher DFM values). Although the cheatgrass and
seeded grass models were nearly identical, all fire behavior variables were reduced by the lower
grass volumes (that is, the ratio of surface area to volume; SAV) in the seeded grass model. This
effect of grass volume was evident even at 6 percent DFM, but it was more pronounced at higher
DFM values. (Results available at http://www.uidaho.edu/range/MurphyFireComplex/).
15
Figure 9. Fire behavior estimates based on modeling of a sagebrush steppe
situation (GS1 model) with herbaceous fuel (1-htl) and 10 percent dead fuel
moisture (DFM).
16
Figure 10. Fire behavior estimates based on modeling of a sagebrush steppe
situation (GS1 model) with herbaceous fuel (1-htl) and 12 percent dead fuel
moisture (DFM).
17
Figure 11. Fire behavior estimates based on modeling of a sagebrush steppe
situation (GS1 model) with carry over fuels from previous years reduced by 50
percent (to 200 lb/acre) and 12 percent dead fuel moisture (DFM).
18
Summary of Modeling Results
Reducing levels of fine fuels, as might be accomplished with livestock grazing, reduced the
modeled surface rate of spread and fire line intensity in the simulated shrub and grassland
communities. This might be expected given the basic assumptions incorporated into the BEHAVE
Plus modeling system. The BEHAVE Plus system simplifies the combustion process, and the fire
characteristics the team chose were primarily determined by 1-htl fuels, LHFL, fuel moisture, and
wind speed. The effects of reduced fuel load on fire behavior were more pronounced at low wind
speeds and high fuel moisture values. When burning conditions became extreme (less than 12
percent DFM and greater than 15 mph wind speed), changes in live herbaceous fuel load and
amount of dead herbaceous fuels (1-htl fuel classes) had little effect on fire behavior variables.
Consequently, under the extreme conditions that characterized most of the Murphy Wildland Fire
Complex, grazing levels probably had little effect on fire behavior over much of the area. Within
the larger fire area, however, there were certainly sites where less-extreme conditions occurred and
grazing-induced reductions in herbaceous biomass were likely an important determinant of fire
behavior. Under less-extreme fire weather conditions (DFM greater than12 percent and wind
speeds less than 10 mph), reductions in herbaceous fuels resulting from livestock grazing may
influence fire behavior, making a fire in these shrub and grassland plant communities easier to
contain.
Examination Approach 2 – Relation between Vegetation Type and Fuel Consumption
Comparing satellite images and data collected before and after a fire is a technique widely
used to assess the effects of fire across a landscape (Key and Benson, 2006). This differencing
technique has been used extensively to assess the level of fuel consumed and vegetation changes
caused by fire (Miller and Thode, 2006). For the Murphy Wildland Fire Complex, the team used a
recently developed technique to examine fire-induced changes to vegetation amount and structure
by creating a variable called delta Normalized Burn Ratio (dNBR). Values for dNBR were
calculated based on ratios of the difference between the pre-burn and post-burn reflectance in two
spectral bands of Landsat Thematic Mapper satellite data (30 m-per-pixel resolution). The
difference in the spectral reflectance before and after a fire for a specific piece of land (or, more
specifically, a pixel in the image) indicated how much the fire changed vegetation and soil on that
unit of land.
In fire ecology research, dNBR is one approach to quantify changes caused by fire on a
landscape. Burn severity is the term used to describe the changes to vegetation and soils caused by
a fire (Key and Benson, 2006). Thus, dNBR is often used to quantify burn severity such that areas
that have high dNBR values are described as having high burn severity. In the team’s analyses, the
term burn severity was used to infer the amount of fuel (live vegetation, dead standing vegetation,
or litter) consumed by the fire, with recognition that burn severity does not necessarily indicate
levels of ecological damage caused by fire. Nonetheless, “burn severity” is synonymous with “fuel
consumption” in this report.
19
Defining Burn Severity and Fuel Consumption
Burn severity describes the degree of environmental change caused by fire. It refers to the
composite degree of physical and chemical changes to the soils, degree of change in living and
dead vegetation, changes to inorganic carbon and ash, and degree of change in plant structure and
composition (that is, proportions of species). The concept of burn severity also can be applied to
specific environmental responses, most frequently focusing on soils or vegetation. Burn severity is
affected primarily by fire line intensity, how long the fire burns on a specific area (that is, fire
residency time), and moisture conditions at the time of burning (Sugihara and others, 2006).
Fire intensity, burn severity, and level of fuels consumed are inherently related because the
more fuel that is consumed, the more intense the fire, and the more heat created that could impact
plant vigor and survival. As well, with more intense fires and greater heat transfer, there is a greater
likelihood of increased soil fire effects such as loss of organic matter, exposed mineral soil, and soil
erosion. Although the relation between level of fuel consumed and burn severity are not completely
correlated, they are so closely associated in this context that we use these as interchangeable terms
for the purposes of this report.
High levels of fuel consumed (or high burn severity) generally are recorded in areas where
trees, with their concomitant high biomass, existed before a fire but no longer exist after a fire.
Moderate burn severity is most characteristic of shrublands. Low burn severity is typical of areas
dominated by grasslands. Thus, burn severity or fuel consumption should be evaluated relative to
the pre-fire community. It is always best to compare fuel consumption within a particular
vegetation type (for example, among shrubland stands), rather than among plant communities that
differ in structure (for example, among grasslands, shrublands, and forests), because burn severity
values derived in different structural communities may not represent equal ecological change.
Within shrub-dominated areas, a high burn severity likely reflects higher consumption of
shrubs by fire compared to a low burn severity value for a similar shrubland area. However, even
low and moderate amounts of fuel consumed can have significant ecological effects. For example,
Wyoming big sagebrush is killed when fire removes the above ground foliage because this species
of sagebrush does not sprout from buds in the root crown after fire (Howard, 1999). Therefore,
Wyoming big sagebrush is largely dependent on establishment from seeds for stands to recover
after fire. LANDFIRE fire regime modeling indicates that 86 percent of fires in Wyoming big
sagebrush are stand-replacing events (LANDFIRE Rapid Assessment, 2007).
Within a grassland community the amount of fuel removed by the fire may or may not be a
good indicator of burn severity. Grasses are well adapted to fire because they have basal buds that
can sprout after fire and create new tillers for continued growth and survival (Briske, 1991).
Because grasslands generally have less total biomass available as fuel compared to adjacent
shrublands or woodlands, low values for burn severity may result from satellite image comparisons.
However, the fire effects can be severe if heat damages the root crown or soil and promotes soil
erosion. A careful field assessment may be necessary to determine fire effects to grassland
communities.
20
A dNBR map was created for the Murphy Wildland Fire Complex based on remotely
sensed data. To accomplish a comparison of images before and after the fires, the team used a post-
burn image taken on August 10, 2007 (with minor cloud patching corrected using an image
acquired on August 17, 2007). This image was compared to a pre-fire image acquired on July 29,
2006 (with minor cloud patching corrected using an image acquired on July 9, 2007), about one
year prior to the fire. The initial dNBR image was further examined and calibrated with ground-
reference data collected with field observations by several technicians and professionals in mid-
September. The calculation of dNBR from remotely sensed data created a continuous attribute that
was then thresholded into classes (for example, low, moderate, and high). In this analysis, the
thresholds used generally agreed with other rangeland fire mapping thresholds, and only minor
adjustments were made based on field examinations. The dNBR values were used to create a burn
severity map (fig. 12).
Landscape Comparison of Fuel Consumption Among Vegetation Types
Landscape patterns of grassland and shrubland communities and their influence on the level
of fuel consumption in the Murphy Wildland Fire Complex were examined by calculating the
proportions of burn severity classes within each major vegetation type. This descriptive analysis
provided an overview of the range of burn severity that occurred within each vegetation type and
allowed qualitative comparisons among types. This analysis described how vegetation type
influenced fuel consumption and set a foundation to interpret grazing effects that modify fuel loads
potentially observed as differences in burn severity. The team did not conduct an analysis of the
relationship between grazing and dNBR because a complete data set characterizing the level of
grazing was not available within the time frame of the project. The vegetation classification used
for this evaluation was derived from remotely sensed images that were verified and adjusted by
field data and input from experienced local observers4.
A comparison of fuel consumption (that is, dNBR) across vegetation types supported a
general premise that the plant community occurring on a site before a fire influences the amount of
fuel consumed and changes in plant structure caused by the fire. These data confirmed well-known
relations between vegetation type and level of fuel consumed, for example, grasslands yielding
lower fuel consumed and therefore lower burn severity values than shrublands (fig. 13).
A closer examination of burn severity classes observed in specific vegetation types revealed
that each plant community can experience a range of fuel consumption levels from unburned to
fully consumed vegetation. The burn severity categories in our analysis reflected the level of
vegetation consumed and the patchiness of burning within and among 30-m pixels in the image
used for this analysis (table 1). Therefore, acreages in the low burn severity category can be
assumed to include mixes of burned and unburned areas. These data indicated that a significant
portion of each vegetation community experienced fire in the low burn severity category. This
indicated low initial biomass, and therefore low levels of fuel consumed, patchy burning patterns,
or removal of fuels in a way that was less than complete.
4 Vegetation community classification was based on field data collected by resource staff at the Jarbidge Field Office
from 2002 to 2006 and 2004 National Agricultural Image Program (NAIP) imagery. This effort was conducted by
resource personnel that are familiar with the landscape. The data have been verified in the field by Jarbidge Field
Office resource management staff.
21
Figure 12. Burn severity based on delta Normalized Burn Ratio for the Murphy Wildland Fire
Complex, Idaho, July 2007.
22
Table 1. Burn severity (dNBR) observed and classified after Murphy Wildland Fire Complex
expressed as a percentage of area within pre-fire vegetation types. These figures reflect the Idaho
BLM lands that were affected by the Murphy Wildland Fire Complex (450,535 acres) and account for
about 75 percent of the total Murphy Wildland Fire Complex area.
Vegetation Community
Acreage
in
analysis
Percentage of area
Non-
burned Low Moderate High
Herbaceous Types:
Annual Grasses and Forbs 5,469 7 73 20 0
Native Grasslands 85,071 5 76 19 0
Seeding (Crested and Intermediate Wheatgrass) 38,773 2 85 13 0
Recent Burn (2006 Fires) - Herbaceous Plants 24,373 13 84 3 0
Sagebrush Types:
Mountain Big Sagebrush 10,620 2 28 68 2
Low-Black Sage/Native Grass understory 35,683 2 48 50 0
Wyoming Sagebrush /Native Grass understory 200,694 3 55 43 0
W
y
omin
g
Sa
g
ebrush/Understor
y
Introduced Grasses
(for example, Crested and Intermediate Wheatgrass) 6,062 6 70 24 0
Non-Sage Shrublands and Woodland Types:
Rabbitbrush/Native Grass 23,509 2 56 41 0
Rabbitbrush/Non-Native Grass 2,643 1 87 12 0
Shadscale Saltbush 1,522 1 99 0 0
Other types:
Semi-Wet Meadow 302 21 21 52 5
Sparse Vegetation 12,941 10 71 18 0
Other shrub/woodlands t
yp
es (includin
g
: as
p
en,
juniper, curl-leaf mountain mahogany, bitterbrush,
etc.) 2,865 2 18 73 7
23
Low
High
Grassland
Non‐Burn
Moderate
Low
High
Sagebrush
Non‐Burn
Moderate
Figure 13. Variation in burn severity averaged in grassland and sagebrush vegetation types.
Variation of fuel consumption within a vegetation type indicates variation in the biomass,
cover, and relative abundance of plants among sites classified as a single vegetation type. The
effects of grazing would reflect reduced herbaceous biomass, and therefore could contribute to
variation within a vegetation type. This variation in fuel consumed within a vegetation type reflects
biotic and abiotic factors that influence fire behavior including topography, weather conditions, and
fuel characteristics. Managing fuel characteristics offers land managers the potential to influence
biomass of herbaceous species, and therefore reduce the amount of fuel consumed (that is, burn
severity) within a vegetation type.
Examination Approach 3 – Major Drivers That Created Distinct Lines of Difference and
Discontinuity in Burn Severity
Examination of the burn severity map created for the Murphy Wildland Fire Complex
(fig. 12) revealed several linear contrasts that apparently reflected distinct differences in conditions
on either side of the contrast. The team carefully examined these contrasts, to understand the
attributes and conditions that influenced fire behavior and effects in the Murphy Wildland Fire
Complex. The goal was to determine the major drivers of discontinuities in burn severity. Were
these differences primarily driven by vegetation type or by levels of residual herbage affected by
livestock grazing? Discontinuities where the vegetation community type was the same on both
sides of the contrast (either shrubland or grassland) also were examined to determine if
discontinuities in burn severity were driven by differences in residual herbage potentially created
by different levels or seasons of grazing. One limitation of this analysis was the absence of
complete knowledge of weather during the fire and other conditions that affected fire behavior at
the specific locations involved.
24
Examination Procedures
Fourteen focus areas with lines of contrasting burn severity were selected within the
perimeter of the Murphy Wildland Fire Complex (fig. 14). These focus areas were selected
arbitrarily with some intentional selection for contrasts where burn severity occurred along a fence-
line with similar vegetation type on both sides of the fence. Field verification of contrast lines was
not conducted. Several landscape features and fire attributes were gathered and examined along
these contrast segments to explain the source of the distinct change in burn severity. These
landscape and fire characteristics or factors included:
• Vegetation type obtained from the BLM Jarbidge FO (described above).
• A map of seedings, usually post-fire revegetation efforts, provided by the BLM Jarbidge FO.
• An annual grass cover class map (2006 Annual Grass Cover Index) based on work by Eric
Peterson, Nevada Natural Heritage Program (fig. 3).
• Shrub cover estimated by image interpretation of pre-fire Landsat images (combination of
bands 7, 4, and 3).
• Actual grazing use from BLM and rancher records of livestock numbers and dates in and out of
selected pastures.
• Distance from nearest water source in the pasture calculated for each contrast segment with
interest in how this might influence utilization levels on either side of pasture boundaries.
• Fire behavior and suppression derived from a fire progression map provided by the BLM
Jarbidge FO.
• Fire history provided by maps of historical fire perimeters labeled with the year they burned
(BLM Jarbidge FO). Digital color maps for the factors consisted of both regional maps and
maps zoomed in on each focus area.
• Anomaly performance, used to highlight areas that were greener or browner than expected
based on difference between a pixel’s actual growing season Normalized Difference Vegetation
Index (NDVI) and its climatically predicted growing season NDVI5 (Wylie and others, 2008).
• Pre-fire Biomass in 2007 derived from a regression relationship (R2 = 0.70) developed from the
2006 current year’s growth in mid-summer (ecological site inventory data collected by the
BLM Jarbidge FO) and the early-to-mid summer 2006 MODIS NDVI. The regression tree was
then applied to the 2007 pre-fire MODIS NDVI to estimate and map the 2007 pre-fire current
year’s growth.
5 The normalized difference vegetation index (NDVI) is a measure of vegetation photosynthetic potential and correlated
to biomass, net primary productivity, and leaf area index. The pixel anomaly was derived from a regression model that
predicted the pre-fire growing season integral of NDVI from climate data (http://www.prism.oregonstate.edu/products/,
accessed September 2007) and 1997 through 2006 average growing season NDVI. Two separate regression tree models
were produced correlating climate and NDVI data one for grasslands (R2 = 0.86) and one for shrublands (R2 = 0.95).
Preliminary analysis indicated that the pixel “anomaly” was related to pasture actual grazing pressures in grassland
areas (R2 = 0.7 overall).
25
Figure 14. Fourteen focus areas of distinct contrasts in burn severity based on delta Normalized
Burn Ratio (dNBR) for the Murphy Wildland Fire Complex that were examined to determine possible
explanation for these contrasts.
26
Color maps and images of each factor in each focus area were created with GIS allowing
observers to visually assess the importance of the selected factors in determining the observed
contrasts in burn severity. (These maps and images can be viewed at:
http://www.uidaho.edu/range/MurphyFireComplex/). Four observers6 examined the maps and data
for each focus area and ranked the importance of each factor in explaining each burn severity
contrast segment. The median importance value from the four observers was determined for each
factor and each burn severity contrast segment. The burn severity contrast segments were grouped
into segments dominated on both sides of a fence by one particular vegetation type: grass, shrub, or
a mixture of grass and shrub. Separate analyses were conducted for the grass- and shrub-dominated
fence-line related burn severity contrast segments. Summarization of the drivers of the burn
severity contrasts were (1) across the fire, (2) within grasslands fence-line contrasts, and (3) within
sagebrush fence-line contrasts.
Major Drivers of Discontinuities in Burn Severity
Shrub cover, visually estimated from a pre-fire Landsat scene, was the most important
determinant of burn severity contrast across the 16 burn severity contrast segments examined
(table 2). (Note: there were 14 focus areas examined, but two of these areas had two distinct
contrast segments). Shrub cover reflected variations not only in woody biomass and potential fuel
BTUs but also in flammability related to volatile oils of sagebrush. Factors other than shrub cover
contributing to contrasts in burn severity were biomass, vegetation type, and fire history (table 2).
The first three factors generally were related to actual fuel loads. Importance values for
explaining contrasts were low for factors related to grazing pressures (actual use, anomaly
performance, and distance from water). Cheatgrass did not appear to be an important factor because
most of the burn severity contrast segments were not in areas where cheatgrass was a dominant
vegetation type (fig. 2).
By holding the vegetation type relatively constant (that is, situations where both sides of
burn severity or fence-line contrasts were grass or shrub), the team anticipated grazing effects
would be more clearly illustrated because they would be less confounded by differences in major
vegetation type. In this examination, shrub cover and biomass were still the primary factors
responsible for grassland burn severity contrasts associated with fence-lines (table 3). Current
year’s growth or annual production in grassland systems represented a large proportion of the total
grass fuel loads. Factors related to grazing (actual use, anomaly performance, and distance from
water) were ranked higher relative to the overall analysis (table 2) and possibly indicated that
grazing in grassland systems reduced fuel levels more significantly than in a shrubland ecosystem.
Seedings were similarly ranked in the overall analysis (table 2) and the grass analysis (table 3).
Vegetation type and fire history were ranked substantially lower from table 2 to table 3, reflecting
the grass-dominated systems on both sides of the burn severity contrast with similar fire histories.
6 Observers included Bruce Wylie, ASRC Research and Technology Solutions, contractor to the U.S. Geological
Survey (USGS) Earth Resources Observation and Science (EROS) Center. Work performed under USGS contract
08HQCN0007; Jay Davison, Cooperative Extension, University of Nevada; Stephen Howard, SAIC contractor to the
USGS EROS; and Eva Strand, Rangeland Ecology and Management Department, University of Idaho.
27
Table 2. Burn severity contrast importance values (10 is high, 1 is low) from four observers
summarized across all burn severity contrast segments having the highest mean. The number of
times the inter-observer median value was greater than 6 also was recorded.
Factor related to contrast Rank
Mean
importance
value
Standard
deviation
Number of times
ranked greater
t
han 6
Shrub cover (Landsat) 1 6.5 0.7 42
Biomass 2 4.8 0.3 23
Vegetation type 3 3.9 0.6 20
Fire history 4 3.8 0.4 21
Seedings 5 3.0 0.8 16
Actual use (ac/AUM) 6 2.9 0.5 9
Anomaly performance 7 2.6 0.5 5
Distance from water 8 2.3 1.0 4
Cheatgrass 9 2.1 0.6 1
Fire behavior/suppression 10 1.4 1.0 4
Only one of the burn severity contrast segments was concurrent with a fence-line that had
shrub-dominated systems on both sides of the contrast segment; therefore, no statistics (that is,
standard deviation) were generated among contrast segments and no table of data is presented in
the report. In this segment, shrub cover, an indicator of woody fuel loads, was the strongest factor
explaining this contrast segment (Mean Importance Value of 9 among four observers where 10 was
the highest possible importance value assigned). Current year’s biomass was the third most
important factor (Mean Importance Value of 5.5). Grazing effects and utilization levels,
represented by actual use and distance to water, increased in their importance ranking relative to the
overall analysis in table 2. Vegetation type decreased in importance ranking compared to the
overall analysis as a result of efforts to hold this factor relatively constant. Seedings and fire history
also dropped in importance ranking compared to the overall analysis because shrub-dominated
areas have low occurrence of seedings, which are a common management intervention for intensely
burned areas where shrub mortality is high.
28
Table 3. Importance values (10 is high, 1 is low) from four observers for three burn severity contrast
segments within grass-dominated areas. The number of times the inter-observer median value was
greater than 6 also was recorded.
Factor related to contrast Rank
Mean
importance
value
Standard
deviation
Number of times
ranked greater
than 6
Biomass 1 6.1 0.9 6
Shrub cover (Landsat) 2 5.9 1.7 6
Actual use (ac/AUM) 3 4.2 1.2 2
Seedings 4 3.9 1.4 4
Anomaly performance 5 2.8 1.0 2
Distance from water 6 2.4 0.9 1
Cheatgrass 7 1.8 1.6 0
Fire history 8 1.8 1.9 2
Vegetation type 9 1.7 1.5 1
Fire behavior/suppression 10 0.6 0.3 0
Though the primary goal of this analytic approach was to determine if differences in burn
severity along selected contrast lines were related to grazing pressure, several factors made that
interpretation difficult. Actual data for livestock use were available only on a pasture scale. Levels
of grazing use are rarely uniform across a pasture, and therefore are unreliable as an indicator of
actual forage utilization along the burn severity contrast lines. Distance from water was evaluated,
but this analysis was limited by the assumption that utilization levels generally were linear in nature
radiating out from the water sources. In fact, while forage use is undoubtedly highest adjacent to
the water source, utilization levels rapidly become less uniform as distance from water increases.
Utilization levels as reported by BLM personnel are not useful in estimating fuel removed by
livestock and other herbivore utilization. Utilization levels were determined only for key forage
species, which did not represent fuel loads for a pasture. Furthermore, a focus on estimates of
utilization (proportion of forage removed) is not as relevant to fire behavior as is the amount of
forage remaining, which was not measured.
29
Report Summary and Conclusions
The Murphy Wildland Fire Complex was essentially “a perfect storm” for sagebrush-
grassland wildfires. Several factors influenced the extreme fire behavior documented in the fire,
including favorable growing conditions for vegetation in previous years and early summer weather
conditions that resulted in dry fuels for dead and living biomass. These factors combined with
strong winds and high temperatures to make this fire extremely difficult to control, particularly in
the first four to five days after ignition when the vast majority of the area of the fires burned.
Evidence of the aggressive nature of the Murphy Wildlife Fire Complex was demonstrated by the
fires jumping the Jarbidge and Bruneau river canyons.
Major Findings and Lessons Learned
• Much of the Murphy Fire Complex burned under extreme fuel and weather conditions. Weather
conditions in the first four to five days of the fire were particularly dry, hot, and windy. It was
during this period that between 75 and 90 percent of the total area burned. As confirmed by fire
modeling, these extreme conditions likely overshadowed (or swamped) livestock grazing as a
factor influencing fire extent and fuel consumption in many areas where these fires burned.
• Level of fuels consumed (or burn severity) was affected mostly by the plant communities that
existed on a site before fire (that is, shrubland communities can potentially experience a greater
loss of biomass and vegetative structure than grasslands yielding higher burn severity values).
Our study of fuel consumption and our field examination confirm that all vegetation types
experienced a range of fuel consumption, including many acres in the low burn severity class,
indicating patchy burning patterns or incomplete consumption of fuels. Greater proportions of
plant communities characterized as grasslands were categorized in the low burn severity class
than shrublands. This observation confirms that fuel consumption (or burn severity) is largely
influenced by the kind of plant biomass and structure that exists before the fire.
• There were many abrupt contrasts in fuel consumption (or, burn severity) primarily attributed to
abrupt changes in vegetation type, such as a transition from seeded grasslands to shrubland
communities. Burn severity contrasts throughout the Murphy Wildland Fire Complex were
most strongly aligned with amount of shrub cover, current year’s biomass, and vegetation type.
A few abrupt contrasts in burn severity coincided with apparent differences in actual use by
livestock and other grazing factors, as illustrated by fence-line contrasts.
• Potential effects for livestock grazing to reduce fuel and affect fire behavior were dependent on
the vegetation type. Fire behavior in sagebrush vegetation types is driven by sagebrush cover
and height, with the herbaceous component on which livestock focus their grazing, playing a
lesser role. Consequently, opportunities to influence fire behavior through livestock grazing are
greatest in grassland vegetation types. Fire modeling suggests grazing in grassland vegetation
can reduce surface rate of spread and fire line intensity to a greater extent than in shrubland
types where woody fuels generally are not reduced by cattle or sheep grazing.
• Herbaceous biomass produced during one year and persisting into the next growing season
contributes to the dead fine fuel load (that is, 1-htl fuels) in subsequent years. Livestock grazing
that reduces the carryover of dead fuels from one year to the next can influence fire behavior,
particularly under less intense fire conditions.
30
• The potential effects of grazing on fire behavior are highly dependent on weather, fuel load, and
fuel-moisture conditions. Extensive fires, such as those of the Murphy Wildland Fire Complex,
generally result from a combination of many factors but are largely weather driven. Under such
extreme conditions, grazing applied at sustainable utilization levels would have limited or
negligible effects on the fire behavior. When weather and fuel moisture conditions are less
extreme, grazing may reduce the rate of spread and intensity of fires allowing for more patchy
burns with lower fuel consumption levels.
Future Opportunities
Fire behavior results from factors related to topography, weather, and fuels. Land managers
cannot change weather or topography, so they are compelled to focus on manipulating fuels. Fuel
manipulations can change the potential for fires to sustain ignition, rates at which fires spread, and
their final size. Reducing fuel loads could enhance fire suppression activities when weather
conditions are not extreme by increasing opportunities for safely applying back burns and
increasing available time to strategically fight fires.
The differences in fuel consumption observed among areas with apparently different
grazing histories in the Murphy Wildland Fire Complex, published research on the relationship
between fuel loads and fire behavior, and the professional opinions of several team members
suggest potential for managed grazing to reduce fine fuels and affect wildfire behavior. Grazing
targeted to reach fuel objectives could ameliorate the spread, intensity, and extent of wildfires,
particularly in grasslands. However, our review of fire effects in the Murphy Wildland Fire
Complex offers only cursory evidence that grazing influenced fire behavior under some conditions.
We are not able to give conclusive evidence on the extent to which grazing influenced the Murphy
Complex Fires. Such an endeavor would take more time and resources than our team was able to
commit to this review.
Whereas livestock grazing can affect fire behavior through the reduction of fine fuels on
semi-arid rangelands, it is important to distinguish between landscape-scale grazing programs
designed to protect numerous natural resource values and targeted grazing programs aimed at
reducing fine fuel loads on specific areas. It is also essential to make a clear distinction between
standard grazing management prescriptions and fuels reduction endeavors. Reducing herbaceous
biomass to levels that would strongly influence fire behavior, particularly under extreme fire
conditions, would require reductions to levels that would potentially compromise sustained
livestock production and ecosystem goals. However, a targeted grazing program to accomplish fuel
management could be both feasible and achievable on selected sites. These grazed fuel-reduction
sites or pastures could be most easily established in areas dominated by grazing tolerant grasses
with little or no shrub cover. This may require connecting these target sites to provide areas of
continuous fuel reduction zones. In the region of the Murphy Wildland Fire Complex, introduced
forage grasses (for example, crested wheatgrass) are recognized as being quite grazing tolerant
during all phases of the growing season. Grazing as a fuels management technique would be most
effective on uniform grasslands and becomes less effective as the amount and size of the shrub
component in the plant community increases. Grazing also may be more difficult to sustain in
communities dominated by native grasses compared to introduced grasses. It would be important to
weigh these inputs against the potential environmental and economic damage that occurs when
massive wildfires burn across native rangelands.
31
Recommendations
• Changes in grazing management aimed at managing fuel loads are not appropriate for
homogeneous application across large landscapes and multiple management units. Such
application of grazing across entire landscapes at rates necessary to reduce fuel loads and affect
fire behavior, especially under extreme conditions, could have negative effects on livestock
production and habitat goals. Rather, the team recommends carefully planned, targeted
application, and monitoring of fuel management strategies strategically placed across defined
areas. The idea of targeted grazing to accomplish fuel objectives holds promise but requires a
detailed planning effort that includes target goals for fuel loads and accounts for prevailing
winds, fire behavior, and fire control strategies. Furthermore, targeted grazing projects could be
strategically applied with clearly defined ecosystem criteria and be piloted in sufficiently large
areas to monitor the effects on fuels, plant community composition, and wildlife habitat. Large-
scale projects aimed at evaluating the potential of livestock grazing to reduce fuel loads under
several grazing scenarios are largely non-existent (that is, comparing a landscape-scale grazing
program that conforms to BLM standards to a high-intensity targeted grazing program aimed at
reducing fuel loads).
• The team recommends creating a task group of grazing, fire, wildlife, and landscape specialists
and scientists to develop a pilot project for a landscape-sized area. The task group’s goal would
be to devise a plan for strategically placing grazed blocks or pastures across a landscape to
create fuel-reduction bands to influence fire behavior and facilitate fire management. These
grazed bands would need to consider protection of native plant communities and wildlife
habitat. The team envisions specific opportunities to apply grazing aimed at fuel management in
grasslands composed of introduced grasses and to consider targeted grazing opportunities in
concert with post-fire revegetation efforts. Detailed and spatially explicit plans for
implementation and monitoring would be developed by this team. Such integrated and strategic
plans are not easily created and will require spatial decision processes. An approach similar to
that outlined in Meinke and others (in press) using probabilities of success for each objective
could be used to identify potential locations for these fuel-reduction bands. Partnering with state
and private landowners within the proposed project area is encouraged where such
opportunities could enhance success of projects.
• The team supports the publication of a general technical report that focuses on published
research and existing field examples of how livestock grazing influences fire extent, severity,
and intensity. A carefully drafted technical report of this nature would provide a platform to
create targeted grazing strategies, consider possible changes to existing grazing plans, and
evaluate livestock grazing effects on recent and future wildfires. This report could focus on
existing research and identify information gaps for specific ecosystems, grazing practices, or
fire conditions. The potential effect of invasive grasses on fire and grazing management plans
could also be presented. Though there are significant knowledge gaps, much information exists
on these topics in published research and experiences of land managers. However, the
information has not been synthesized into a single document that is readily accessible to land
managers.
32
• The team encourages continued research and monitoring of the ecosystem effects of the
Murphy Wildland Fire Complex. The fires occurred in a region that holds significant ecological
information and importance. In addition, revegetation efforts in the area of the Murphy
Wildland Fire Complex have been documented and should be monitored. The team’s
investigation has gathered many sources of pre-fire information. With careful data storage and
cataloguing, much more can be learned from the effects of this extensive fire that may offer
insight for future management decisions.
Research Gaps and Limitations
• There is sufficient evidence to support a pilot project of targeted grazing on grasslands for fuel
reduction, but effects of grazing aimed at fuel management in mixed shrub and grass vegetation
types are more difficult to predict. If targeted grazing was applied on sites that varied in the
amount of shrub and grass cover, the results would help define use levels and percentage shrub
cover where livestock grazing is effective and where it is ineffective as a fuels management
tool. Of particular interest is research aimed at: (1) the potential role of livestock grazing to
reduce fuel loads in mixed shrub and grass vegetation types in the short- and long-term; (2) the
ecological impact of heavy utilization to accomplish fuel reduction on the wildlife, plant, and
soil microbial communities, especially those related to or dependent upon native plants; (3) the
rate, frequency, and timing of grazing events necessary to maintain target fuel levels; and (4)
management strategies to accomplish high herbaceous biomass utilization without extensive
fencing or new water developments.
• The use of the delta Normalized Burn Ratio (dNBR) has value for quantifying fuel
consumption, soil impacts (that is, soil burn severity), identifying unburned areas within fire
perimeters, and refining fire perimeters, especially for large fires, in sagebrush steppe systems.
However, there were several instances within the Murphy Wildland Fire Complex where
variation in dNBR was not related to vegetative conditions that were anticipated to lead to
changes in burn severity. The concept of burn severity, quantified as dNBR, has been studied
extensively in forests and less in rangelands. Additional research into the relationship of dNBR
to post-fire soil burn severity and vegetation mortality in shrubland and grassland systems
should be pursued.
• The application of fire behavior models to develop fuel management strategies for sagebrush
steppe ecosystems requires better methods to assess and quantify the amount and continuity of
fine fuels at landscape scales. The development of remote sensing technology is needed to
rapidly and accurately assess fine fuels and detect the influence of grazing at broad scales. This
information would allow better use of fire models that examine the spread of fire across a
landscape (such as FARSITE) rather than the one-dimensional view provided by BEHAVE
models (as used in this report). A promising approach for improving biomass estimation,
including senescent and green vegetation, is a spectral index called the soil adjusted total
vegetation index (SATVI; Huete, 1988; Qi and others, 1994). The SATVI was related to total
herbaceous vegetation cover in the southwestern United States (Marsett and others, 2006).
SATVI could be used in combination with indices related to green biomass (modified soil
adjusted vegetation index and the NDVI) to quantify total and green biomass.
33
• The development of a new generation of fire behavior models is needed to better reflect fire
behavior in shrub-dominated communities. BEHAVE and FARSITE (the most widely used
models for wildland fire on rangelands) assume that sagebrush steppe fuels are composed of a
single layer. Field experiences suggest that fire in sagebrush steppe is driven by the live and
dead herbaceous understory fuels under some conditions and by sagebrush overstory
characteristics (for example, height, cover, continuity, and biomass) in more extreme
environmental conditions. Fire research and models are needed to reflect fire behavior in
sagebrush steppe that likely burns in at least two layers of vegetation.
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36
Appendix 1. Murphy Wildland Fire Grazing and Fuel Assessment Team
Core Team
Bob Brammer— Assistant Director; Lands, Minerals and Range Division; Idaho Department of
Lands in Boise, Idaho. Twenty-three years with the Department in various positions, including
Area Supervisor, Range Resource Supervisor, Lands and Range Specialist, and Range Resource
Manger. Bachelor of Science degrees in Range Resources and Wildlife Resources from University
of Idaho. Specific experience with use and management of state-endowment rangelands and
forestlands to maximize financial returns and long-term sustainability. Contributed to report as
member of Grazing Subgroup.
Stephen Bunting— Professor of Rangeland Ecology and Management, University of Idaho,
Moscow, Idaho. At the University since 1978, following completion of doctoral degree in fire
ecology at Texas Tech University. Teaches rangeland ecology and landscape ecology. Research
interests include effects of fire in several types of ecosystems, including canyon grasslands,
sagebrush steppe, and juniper woodlands in Pacific Northwest and northern Great Basin.
Contributed to report as member of Fire Behavior Subgroup.
Matthew L. Brooks— Research Botanist, U.S. Geological Survey, Western Ecological Research
Center, Yosemite Field Station, El Portal, California. Research topics include effects of climate
change, altered ecosystem processes, and biological invasions. Major research focus is ecology and
management of invasive plants and fire. Contributed to report as member of Vegetation Assessment
Team.
Patrick Clark— Rangeland Scientist, U.S. Department of Agriculture - Agricultural Research
Service, Northwest Watershed Research Center, Boise, Idaho. Research experience evaluating
effects of landscape-scale disturbance, such as wildfire, prescribed fire, invasive plants, and
predator reintroductions on rangeland animals, vegetation, and hydrologic processes. Considerable
experience with modeling of animal behavior, remote sensing, geographic information systems, and
other systems for spatial analysis. Contributed to report as member of Fire Modeling Team.
Jay Davison— Area Specialist, University of Nevada, Reno Cooperative Extension, Fallon,
Nevada. Teaches and conducts research in the areas of rangeland restoration following wildfire,
loss of irrigation water on farmlands, use of livestock as an environmental management tool, and
forage management and production in the Great Basin. Contributed to report as chair of the group
evaluating fire-severity contrast lines and as member of Vegetation Assessment Team.
Mark Fleming— Regional Wildlife Habitat Manager, Idaho Department of Fish and Game, Magic
Valley Region. Sixteen years with the Department, focusing on wildlife habitat management and
ecology. Work experience in four Regional Offices throughout Idaho. Bachelor of Science degree
in Fisheries and Wildlife Biology from Iowa State University and Master of Education degree from
Boston University. Contributed to report as member of Vegetation Assessment Team.
37
Ron Kay— Range Program Manager, Idaho State Department of Agriculture, Boise, Idaho. Has
worked for the department for the last two years on grazing issues throughout Idaho. Retired from
Bureau of Land Management, with over 30 years experience working in six states in the Bureau’s
range program and as a field manager in two offices. Experience with grazing systems,
rehabilitation, monitoring, inventory, rangeland assessments, range ecology, range improvements,
and agency procedural policy. Bachelor of Science degree in Range Management. Certified
Professional in Rangeland Management with Society for Range Management. Contributed to report
as member of Grazing Subgroup.
Karen Launchbaugh— Associate Professor and Chair, Rangeland Ecology and Management
Department, University of Idaho, Moscow, Idaho. Research focuses on ecological implications of
grazing, and targeted grazing to accomplish vegetation management. Contributed to report by
working with the Vegetation Assessment Team. Also served as team leader, which included
preparing drafts of the report and managing the revision process.
Mike Pellant— Coordinator, Bureau of Land Management’s Great Basin Restoration Initiative,
stationed in Boise, Idaho. Initiative is a five-state effort to maintain intact ecosystems and
strategically restore degraded ones. Expertise includes rangeland restoration, fire rehabilitation, and
monitoring and assessment of rangelands. Contributed to report as member of Vegetation
Assessment Team and as Bureau of Land Management’s liaison to the workgroup.
David A. Pyke— Supervisory Research Rangeland Ecologist, U.S. Geological Survey, Forest and
Rangeland Ecosystem Science Center, Corvallis, Oregon. Research focus is restoration and
rehabilitation of sagebrush grasslands in the Intermountain West, and development of monitoring
and assessment tools for rangeland managers. Contributed to report as member of Vegetation
Assessment Team.
Support Team
Matthew Bobo— Senior Remote-Sensing Specialist, Bureau of Land Management, National
Operations Center, Denver, Colorado. Assists with coordination of remote-sensing activities for
national, state, and field offices within the bureau. Master of Science degree in Environmental
Monitoring from University of Wisconsin-Madison. Experience with a broad spectrum of
geospatial technologies gained over 14 years by supporting a variety of applications in private and
public sectors. Contributed to report as member of Science Support Team, focusing on applications
of remote sensing.
Jesse German— Geographic Information System Coordinator, Bureau of Land Management, Twin
Falls District, Idaho. Bachelors degree in Cartography and Geographic Information Systems,
University of Wisconsin, Madison, 2001. With Bureau of Land Management in south central Idaho
for last 5 years, providing support and coordination with geographic information. Contributed to
report as member of Science Support Team, providing general data, maps and analysis.
Ken Crane— Rangeland Management Specialist, Bureau of Land Management, Jarbidge Field
Office, Twin Falls, Idaho. Bachelor of Science and Master of Science degrees in Rangeland
Ecology. Eighteen years of experience in rangeland resource management. Contributed to report as
member of Fire Team.
38
Don J. Major— Fire and Landscape Ecologist, The Nature Conservancy - Idaho and the Bureau of
Land Management’s, Great Basin Restoration Initiative. Research focuses on applied aspects of
rangeland restoration, and development and evaluation of monitoring and assessment strategies for
multi-scale management of semi-arid ecosystems. Contributed to report by providing technical
expertise in applications of remote sensing, and in fire and fuel characterization and modeling.
Danelle Nance— Natural Resource Specialist, Bureau of Land Management, Jarbidge Field Office,
Twin Falls, Idaho. Bachelor degree in Agricultural Science and Technology, University of Idaho.
Six years working for Bureau of Land Management for six years, providing assistance to
monitoring and range resources. Contributed to report as support member for the Vegetation
Assessment Team.
Randy A. McKinley— Scientist, ASRC Research and Technology Solutions. Formerly an employee
of the Science Applications International Corporation at the USGS Center for Earth Resources
Observation and Science (EROS), Sioux Falls, South Dakota. Member of Fire Science team at
USGS EROS. Research focuses on mapping areas burned by wildfire using satellite remote
sensing. Contributed to report as member of Fire Team.
Arnie Pike— Supervisory Rangeland Management Specialist, Bureau of Land Management,
Jarbidge Field Office, Twin Falls, Idaho. Bachelor of Science degree in Agricultural Production-
Range Management, Montana State University, 1976. Thirty-one years with the bureau, working in
Montana and Idaho. Experience in range management, fire suppression, and fire rehabilitation in
South Central Idaho since 1991. Supported Fire Team by providing information about vegetation,
livestock grazing, and the Murphy Wildland Fire Complex Emergency Stabilization and
Rehabilitation Plan.
Bruce K. Wylie— Scientist, ASRC Research and Technology Solutions. Formerly an employee of
the Science Applications International Corporation at the USGS Center for Earth Resources
Observation and Science (EROS), Sioux Falls, South Dakota. Research focuses on ecosystem
performance anomalies. Experience mapping rangeland carbon fluxes from flux towers using
remote sensing and ancillary spatial data in rangelands. Contributed to report as member of the
Burn Severity Contrast Team.
39
Appendix 2. Common and Scientific Names of Plants Referred to in Text.
Scientific names follow the USDA PLANTS Database7
Common Name Scientific Name (and Authority)
Grasses:
Bluebunch Wheatgrass Pseudoroegneria spicata (Pursh) A. Löve
Cheatgrass Bromus tectorum L.
Crested Wheatgrass Agropyron cristatum (L.) Gaertn.
Intermediate Wheatgrass Thinopyrum intermedium (Host) Barkworth & D.R. Dewey
Medusahead Taeniatherum caput-medusae (L.) Nevski
Shrubs and Trees:
Aspen or Quaking Aspen Populus tremuloides Michx.
Bitterbrush
or Antelope Bitterbrush Purshia tridentata (Pursh) DC.
Black Sagebrush Artemisia nova A. Nelson
Curl-leaf Mountain Mahogany Cercocarpus ledifolius Nutt.
Low Sagebrush Artemisia arbuscula Nutt.
Mountain Big Sagebrush Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle
Rabbitbrush includes both:
gray or rubber rabbitbrush
green or yellow rabbitbrush
Ericameria nauseosa (Pall. ex Pursh) G.L. Nesom & Baird
Chrysothamnus viscidiflorus (Hook.) Nutt.
Shadscale Saltbrush Atriplex confertifolia (Torr. & Frém.) S. Watson
Wyoming Big Sagebrush Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young
7 USDA, NRCS. 2008. The PLANTS Database (http://plants.usda.gov, June 12, 2008). National Plant Data Center,
Baton Rouge, LA 70874-4490 USA.
40
Appendix 3. Glossary of Terms and Unit Abbreviations
1-htl – See One-hour time lag
British Thermal Unit (BTU) – A unit of energy used to describe the heat value or energy content of
fuels
BTU/ft/sec – British Thermal Unit per foot per second – a unit commonly used to describe fire line
intensity
Burn Severity – the degree of environmental change caused by fire. Burn severity refers to the
composite degree of physical and chemical changes to the soils, degree of change in living and
dead vegetation to inorganic carbon and ash, and degree of change in plant structure and
composition. Assessing and mapping burn severity is important for monitoring fire effects.
Dead Fuel Moisture (DFM) – level of moisture found in dead fuels (fuels with no living tissue in
which moisture content is governed almost entirely by absorption or evaporation of atmospheric
moisture) that is critical in determining fire potential. Dead fuels are classified by time lag (e.g., 1-
hr vs. 10-hr).
delta Normalized Burn Ratio (dNBR) – a measure that examines the difference between the pre-burn
and post-burn reflectance in two spectral bands (expressed as a ratio) of Landsat Thematic Mapper
satellite data (30 m-per-pixel resolution) that is used to describe burn severity.
DFM – See Dead Fuel Moisture
dNBR – See delta Normalized Burn Ratio
Energy Release Component (ERC) – an output of fire modeling procedures that reflects fuel dryness
and potential heat release per unit area in a fire event
ERC – See Energy Release Component
Fire Intensity – measure of the rate of heat released by a fire. Fire intensity is influenced by fuels,
weather, and topography
Fire line Intensity – rate of heat energy released per unit length per unit time of fire front
lbs/acre – pounds (lbs) per acre – a unit of air dry forage production
LHFL – See live herbaceous fuel loading
Live Herbaceous Fuel Loading (LHFL) – a model parameter that describes the green grass and forbs
consumed by grazing animals
41
42
National Interagency Fire Center (NIFC) – A leading support center for wildland firefighting that is
lead cooperatively by several agencies and organizations. Learn more at http://www.nifc.gov/.
NDVI – See Normalized difference vegetation index
NIFC – See National Interagency Fire Center
Normalized Difference Vegetation Index (NDVI) – a satellite observation-derived value that is
sensitive to vegetative growth used to remotely assess whether the target being observed contains
live green vegetation or not.
One-hour Time Lag (1-htl) – fuels consisting of dead herbaceous plants and roundwood less than
about one-fourth inch (6.4 mm) in diameter (e.g., dead grass and small twigs)
Potential Vegetation Composition – refers to the “climax” vegetation that would occupy a site in
the absence of disturbance or climactic variation
RAWS – See Remote Automated Weather Station
Relative Humidity (RH): ratio of moisture (%) in a volume of air to the total amount which that
volume can hold at the given temperature and atmospheric pressure. Conditions of unsaturation
promote fire danger as evaporation from fuels increases.
Remote Automated Weather Station (RAWS) – there are nearly 2,200 interagency Remote
Automated Weather Stations (RAWS) strategically located throughout the United States. These
stations monitor the weather and provide weather data that assists land management agencies with a
variety of projects such as monitoring air quality, rating fire danger, and providing information for
research applications (http://www.raws.dri.edu).
RH – See Relative Humidity
SATVI – See Soil Adjusted Total Vegetation Index
SAV – See Surface Area to Volume Ratio
Soil Adjusted Total Vegetation Index (SATVI) – a spectral vegetation index that accounts for and
minimizes the effect of soil background conditions
Surface Area to Volume Ratio (SAV) – the ratio between the surface area of an object to its volume.
The smaller the particle, the more quickly it can become wet, dry out, or become heated to
combustion temperature during a fire.
Targeted Grazing – application of livestock grazing at a specified season, duration and intensity to
accomplish specific vegetation management goals. For more information visit:
http://www.cnr.uidaho.edu/rx-grazing/.
Utilization – proportion (%) of available forage removed by grazing animals.
Launchbaugh and others— Murphy Wildland Fire Complex in Idaho and Nevada, July 2007—Open-File Report 2008–1214
