Lake Tahoe Upland Fuels Research Project:
Investigating the effects of fuels reduction treatments on forest
structure, fire risk, and wildlife
Final Report to
U.S. Department of the Interior
Bureau of Land Management
November 2, 2012
Principal Investigators:
Patricia N. Manley, Ph.D. a
b
Dennis D. Murphy, Ph.D.
c
Bruce M. Pavlik, Ph.D.
Research Team:
Alison E. Stanton c
Traynor G. Biasiolli a
Angela M. White, Ph.D. a
Matthew D. Timmer a
Brandon M. Collins, Ph.D. a
Gary B. Roller a
a
U.S. Forest Service, Pacific Southwest Research Station, Davis, CA
b
Department of Biology, University of Nevada, Reno, NV
c
BMP Ecosciences, 156 South Park, San Francisco, CA
1
TABLE OF CONTENTS
MANAGEMENT SUMMARY .................................................................................................................. 3
1.0 INTRODUCTION AND BACKGROUND ......................................................................................... 4
2.0 GOALS AND OBJECTIVES............................................................................................................... 5
2.1 CURRENT STATE OF KNOWLEDGE ................................................................................................... 5
2.2 PROJECT OBJECTIVES ....................................................................................................................... 6
3.0 METHODS ............................................................................................................................................ 6
3.1 STUDY SITES ....................................................................................................................................... 6
3.2 FUELS REDUCTION TREATMENTS .................................................................................................. 11
3.3 SAMPLING DESIGN AND TIMELINE ................................................................................................. 12
3.4 VEGETATION AND FUELS ................................................................................................................ 14
3.5 WILDLIFE ......................................................................................................................................... 14
3.6 DATA ANALYSIS ............................................................................................................................... 15
3.6.1 Vegetation and Fuels ............................................................................................................... 15
3.6.2 Wildlife...................................................................................................................................... 16
4.0 RESULTS ............................................................................................................................................ 18
4.1 VEGETATION .................................................................................................................................... 18
4.2 FUELS ................................................................................................................................................ 24
4.3 SMALL MAMMALS ........................................................................................................................... 29
4.4 BIRDS ................................................................................................................................................ 31
4.5 INVERTEBRATES............................................................................................................................... 34
5.0 DISCUSSION ...................................................................................................................................... 36
5.1 VEGETATION AND FUELS ................................................................................................................ 36
5.2 WILDLIFE ......................................................................................................................................... 37
6.0 CONCLUSION ................................................................................................................................... 39
LITERATURE CITED ............................................................................................................................ 41
APPENDICES ........................................................................................................................................... 44
2
MANAGEMENT SUMMARY
BACKGROUND
•
•
•
•
The National Fire Plan and the Healthy Forest Restoration Act mandate federal land managers to
restore forest habitats and reduce the risk of wildfire, particularly in the wildland-urban interface.
The Healthy Forest Initiative implementation plan includes monitoring and tracking performance to
confirm that these objectives are being met.
This report summarizes the results of a comprehensive six year experiment investigating the effects of
fuels reduction treatments on fuel conditions and fire risk, forest structure, and wildlife in the Lake
Tahoe Basin.
Data were collected for eight paired treatment and control units (n=16) on the west and east shores of
the Basin. Three of the west shore units were in protected activity centers (PACs) for California
Spotted Owl (Strix occidentalis occidentalis) and Northern Goshawk (Accipiter gentilis).
We collected detailed data on vegetation structure and composition, fuel loading, birds, small
mammals, and ants before and after treatments were implemented.
KEY RESULTS
•
•
•
•
•
•
Mechanical fuels reduction treatments resulted in more open forest with fewer smaller diameter trees.
Post-treatment tree species composition was less fir-dominated and included a greater proportion of
pines. In the understory, mechanical treatments reduced shrub cover and coarse woody debris but did
not affect herbaceous cover. Hand thinning reduced coarse woody debris, but not vegetative cover.
Treatments successfully reduced both proportion of area killed and large tree mortality under modeled
fire conditions.
There is little evidence to support the removal of large proportions of basal area for fuel reduction.
There are other valid justifications for large basal area reductions, e.g., restoration, economics, but
fuel reduction is not one.
Small mammal community richness and evenness shifted negligibly following treatment. Overall
abundance of mammals increased non-significantly following treatment.
Measures of bird community richness and evenness were largely unchanged following treatment.
Pooled abundance of all bird species declined slightly after treatment.
Ant community richness did not differ between pre- and post-treatment forests. We found no
differences in site occupancy for any species following treatment implementation.
IMPLICATIONS FOR MANAGEMENT
Our results indicate that implementation of conventional fuels reduction treatments is consistent with
maintenance of bird, small mammal, and ant community diversity over short time frames. Fuels
treatments met fire risk objectives while resulting in markedly similar post-treatment wildlife
communities. Importantly, reduction of surface fuels resulted in greater tree resiliency to future wildfires
over the lifespan of these treatments. While wildlife communities were largely unchanged, we observed
substantial changes in abundance of several species following treatments, as well as a slight increase in
overall mammal abundance and a slight decline in bird abundance. Further research is needed to
investigate longer-term impacts of fuels treatments on wildlife communities.
3
1.0 INTRODUCTION AND BACKGROUND
In response to the elevated threat of high intensity wildfire throughout much of the western United States,
the National Fire Plan and the Healthy Forest Restoration Act (HFRA) mandated federal land managers to
restore forest habitats and reduce the risk of wildfire, particularly in the wildland-urban interface (WUI).
In general, these policies set a goal of establishing pre-European conditions or a historic range of
variability that predated modern fire suppression (Parsons et al. 1999, Stephenson 1999). Restoration may
employ an integrated strategy that includes tree thinning and brush removal, collectively called “fuels
treatments.” The principal goals of fuels reduction treatments are (1) to reduce the amount of burnable
materials, thereby reducing fire intensities and crown fire potential, and improving suppression capability
(Agee 2002), and (2) to improve forest health and ecological integrity. The restoration of the natural fire
regime, if possible, is likely to be the most effective approach to achieving desired conditions for forests
in the Basin. However, many obstacles limit managers’ ability to implement a natural fire regime.
A significant portion of the Lake Tahoe Basin is considered a high-risk environment for severe wildfires
(Murphy et al. 2006). This elevated wildfire threat is a result of land use practices over the last 150 years.
In the 1860’s extensive logging resulted in the development of single-aged stands. By the turn of the 20th
century, nearly two-thirds of the entire Basin had been clear-cut. The clearing was concentrated in lower
elevation pine forests, with more than 60% of this forest type removed (Murphy and Knopp 2000).
Recovery of the forest over the last century was altered by management focused on fire suppression.
Recently published research suggests that current fire return intervals in the Lake Tahoe Basin are at their
lowest levels in at least the last 14,000 years (Beaty and Taylor 2009). Modern forests that developed
under fire suppression after extensive logging are overly dense and crowded with small trees and contain
an unnaturally high level of fuels (Barbour et al. 2002, Taylor 2004).
Addressing the wildfire threat and implementing restoration measures in the Lake Tahoe Basin presents
unique challenges. First, the topography and climate in the Basin, in combination with clear-cutting and
fire exclusion, have produced fir- (Abies sp.) dominated forests in the lower montane zone, thus
increasing ladder fuels and probability of crown fires. Second, much of the fuel load in the Basin is in the
form of small trees with low commercial value, thus reducing the cost effectiveness of mechanical
biomass removal. Third, the proximity of these forests to populated areas and the importance of tourism
have limited the use of prescribed burning as a management option. Smoke and liability issues, along
with a small number of allotted burn days in many years has severely limited the number of acres that
have been treated with fire.
Despite these challenges, fire risk reduction has become a top priority in the Basin and funding to
implement fuels reduction treatments has increased in recent years. The National Fire Plan, the HFRA,
and the Sierra Nevada Public Lands Management Act (SNPLMA) have made more funds available. In
addition, the Lake Tahoe Basin Management Unit (hereafter LTBMU) has continued treatments on more
than 12,000 acres (in defense and threat zones) as part of the South Shore Fuels Reduction and Healthy
Forest Project.
Project Coordination
The Lake Tahoe Upland Fuels Research Project science team represents collaboration between the US
Forest Service Pacific Southwest Research Station (PSW), University of Nevada, Reno (UNR), and BMP
4
Ecosciences (a research consultant). The principle investigators in this project are Patricia Manley (PSW),
Dennis Murphy (UNR), and Bruce Pavlik (BMP). This team collaborated closely with the LTBMU to
identify available treatment units. The Upland Fuels Research Project (UPFU) received SNPLMA funds
under the Environmental Improvement Program (EIP#10123) to evaluate vegetation composition,
structure, fuel loading, and animal communities (vertebrate and invertebrate) on six sites on the west
shore slated for fuels reduction and in six paired, untreated controls on adjacent federal, private, and state
lands. Documents summarizing results for 2006 were prepared (Stanton and Dailey 2007)Stanton and
Dailey 2007). A grant from Nevada State License Plate Funds (LTLP 07-01) funded a second year of
sampling in 2007 on the west-shore sites and established two new pairs of sites on the east shore on
Nevada State Lands. Two additional grants from Nevada State License Plate Funds (LTLP 08-10 and 0902) completed sampling and analysis for the two pairs of east-side sites, respectively. This report
summarizes the results of a comprehensive six year experiment that evaluated the effects of fuels
reduction treatments on fuel conditions and fire risk, forest structure, and wildlife in the LTBMU.
2.0 GOALS AND OBJECTIVES
2.1 CURRENT STATE OF KNOWLEDGE
A large body of scientific literature addresses many issues associated with wildland fire and different fuel
treatments applied in various vegetation types. Substantial portions of that work primarily address the use
of prescribed fire. Evidence supports the utility of prescribed fire in reducing crown-fire potential or
improving the resilience of forest stands to wildfire, but these studies are largely based on informal
observations (Brown 2002, Carey and Schumann 2003), post-fire inference (Omi and Kalabokidis 1991,
Pollet and Omi 2002) and modeling (Stephens 1998, Finney 2001, Agee and Skinner 2005, Peterson et al.
2005). Limited scientific consensus exists regarding the specifics of how treatments are implemented and
the relative effectiveness of different prescriptions across vegetation types (Carey and Schumann 2003,
Peterson et al. 2005, Stephens and Ruth 2005).
With respect to wildlife habitat, treatments that are primarily designed to reduce fuels tend to simplify and
homogenize the landscape (North et al. 2009). The removal of overstory and understory trees and more
uniform spacing of remaining trees will likely result in significant changes in wildlife populations,
particularly species that have narrow habitat tolerances in association with habitat features such as canopy
cover, understory structure, herbaceous plants (e.g., seed eaters and understory foraging species), fungi,
snags and downed logs (Manley 2009). Substantial manipulation of vegetation will likely result in a
myriad of short and long-term effects on the composition and structure of plants and animal communities
and populations (George and Zack 2001, Bigelow and Manley 2009, Manley 2009).
Previous studies in WUI zones in the Basin have found that species responses vary within and among
taxonomic groups (Manley et al. 2006, Schlesinger et al. 2008, Sanford et al. 2009). Some species appear
to be sensitive to site disturbance (e.g., presence of people and equipment), whereas others are highly
sensitive to vegetation structure, and still others are well adapted to a wide variety of environmental
conditions. Short-term effects on animals are difficult to predict because the response of species to the
disruption will vary depending on the timing and intensity of activities and the sensitivity of each species.
Longer-term changes in animal communities and populations resulting from treatments depend heavily on
patterns of vegetation recovery following treatment.
5
2.2 PROJECT OBJECTIVES
With this study, we aimed to understand the changes to plant and animal communities in response to
conventional fuels reductions treatments in the LTBMU. Specifically, our objectives were to:
•
•
•
Describe changes in forest structure following hand and mechanical treatments
Predict changes in fire behavior following fuel treatments
Understand how fuels treatments may change community composition and abundance of small
mammals, birds, and ants
Understanding how these elements respond to treatments is essential for addressing key management
questions identified in the Sierra Nevada Forest Plan Amendment (SNFPA). The data for this project has
been collected across a range of treatment types and intensities, in both west shore mixed conifer and east
shore Jeffrey pine/red fir forests. The resulting dataset represents the first comprehensive monitoring
effort in the Lake Tahoe Basin specifically designed to examine changes in plant and animal communities
and fuel loading in response to fuel management activities.
3.0 METHODS
3.1 STUDY SITES
We collected data for this project at three general locations in the Lake Tahoe Basin (Figure 1): two on
the west shore and one on the east shore of Lake Tahoe. Climate in the Basin is Mediterranean with a
summer drought period. The majority of precipitation falls as snow in the winter from December to
March and less than 3% falls as rain between May and October. The western portion of the Basin receives
greater precipitation and has a higher water balance than the northern and eastern portions of the Basin,
resulting in higher plant and animal species richness on the west shore. Mean annual precipitation on the
west shore at Tahoe City, CA is 32 in (80 cm) and mean annual snowfall is 190 in (483 cm). Mean annual
precipitation on the east shore at Glenbrook, NV is 18 in (46 cm) and mean annual snowfall is 93 in (236
cm). At lake level near Tahoe City, average January high temperature is 42 °F (6 °C). Summers are mild
with an average high temperature of 79 °F (26 °C) in August (Western Regional Climate Center 2012).
6
Table 1. Location and characteristics of treatment (T) and control (C) sample units. Treatment units are
further identified as Mechanical (M) or Hand (H) thin units.
Unit
West Shore:
BLK 1-4
MCK 13-1
MCK 13-3
TWC 3
WRD 20-16
WRD 20-9
Treatment/
Control
Vegetation type
HUC 7 watershed
T (M)
C
T (H)
C
T (M)
C
T (M)
C
T (H)
C
T (M)
C
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Mixed conifer
Blackwood Creek
T (H)
C
T (H)
C
Jeffrey pine/red fir
Jeffrey pine/red fir
Jeffrey pine/red fir
Jeffrey pine/red fir
Eagle Rock-MaddenHomewood-Quail
Eagle Rock-MaddenHomewood-Quail
Lower Truckee River
Ward Creek Frontal
Ward Creek Frontal
Slope
(%)
Elevation
(ft)
Aspect
17
21
11
10
26
24
6
11
11
11
5
5
6,479
6,542
6,827
6,471
6,609
6,350
6,871
6,916
7,048
7,115
6,972
7,008
S
E
NW
E
SE
E
S
S
flat
flat
NW
flat
35
42
21
14
7,759
7,644
7,635
7,585
W
W
S
W
East shore:
REDS
WLD
North Canyon
North Canyon
7
Figure 1. Overview of Upland Fuels sample unit locations in the Lake Tahoe Basin.
West Shore Study Sites
The six study sites on the western side of the Lake Tahoe Basin were located on United States Forest
Service land near Tahoma, California in the lower montane zone between 6,250 and 7,200 ft (1900-2200
m) elevation (Table 1). The lower montane zone in the west Basin consists primarily of mixed conifer
forests, comprised of up to six dominant canopy species: red (Abies magnifica var. magnifica) and white
fir (A. concolor), Jeffrey (Pinus jeffreyii), lodgepole (P. contorta), and sugar pine (P. lambertiana), and
incense cedar (Calocedrus decurrens). Mixed conifer forests on the west shore of the LTBMU occupy
approximately 12,300 acres (Murphy and Knopp 2000). Plots were located in four watersheds: Twin
Crags (TWC), Ward Creek (WRD), Blackwood Creek (BLK), and McKinney Creek (MCK) (Figures 2
and 3). The six treatment units cover approximately 800 acres in mixed conifer forests. Slopes across the
study range from 0 to 40% (Table 1). The Northern Unit Overview (Figure 2) shows more detailed
sample plot and control plot locations for the units in TWC, WRD, and BLK. The Southern Overview
(Figure 3) shows more detailed sample plot and control plot locations for the units in MCK.
8
Figure 2. Upland Fuels sample unit locations on the northwest shore of Lake Tahoe at Twin Crags
(TWC), Ward Creek (WRD), and Blackwood Creek (BLK).
9
Figure 3. Upland Fuels sample plot locations on the southwest shore of Lake Tahoe at McKinney Creek
(MCK).
East Shore Study Sites
The two study sites on the eastern side of the Basin were located on Nevada Division of State Lands
(NDSL) property in the North Canyon watershed (Figure 4). Site elevations were all near 7,500 ft and
slopes ranged from 14% to greater than 40% (Table 1). The east shore montane zone consists of canopy
dominants Jeffrey pine, red fir, and white fir. We chose control sites that were in close proximity to the
treatment sites and thereby similar in elevation, forest type and structure.
10
Figure 4. Upland Fuels sample unit locations on the east shore of Lake Tahoe on Nevada Division of
State Lands (NDSL) property.
3.2 FUELS REDUCTION TREATMENTS
The west shore treatment units were covered under three different NEPA review processes; the Twin
Crags units were covered under the North Shore EIS project (1996); the Ward units were part of the Ward
Management Area Fuel Hazard Reduction Project Environmental Assessment (2002); and the McKinney
and Blackwood units were part of the Quail Vegetation and Fuel Treatment Environmental Assessment
(2005). As such, the desired conditions and exact fuels treatment prescriptions varied. For instance, the
maximum allowable harvestable tree size increased from 24 to 30 in in 2004 in the SNFPA.
Throughout the Basin, fuels reduction treatment prescriptions are applied to retain highest priority conifer
species as follows: (1) sugar pine (2) Jeffrey pine (3) white/red fir, incense cedar (4) lodgepole pine. In
addition to live tree retention guidelines, all treatment prescriptions specified retention of at least 3 snags
and 3 down logs per acre (7.5/ha), both in the largest diameter size class. Our study included four
mechanical treatment units, three hand treatment units, and one combined hand/mechanical unit. The
hand/mechanical treatment unit (WLD) was ultimately classified as a hand treatment unit for statistical
analysis, as the treatments as implemented were most similar in treatment intensity to other hand
treatment units. Further details of treatment prescriptions are outlined in Table 2.
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Three of the treatment units were located in protected activity centers (PACs) for California Spotted Owl
and Northern Goshawk. Treatment prescriptions for PACs within the west shore units were prepared in
consultation with wildlife biologists in order to maintain or enhance habitat conditions while meeting the
objectives of the proposed fuel reduction. The general prescription for mechanical treatment within a unit
containing a PAC allows for the retention of larger trees, twice as many snags, two canopy layers and a
higher minimum percentage of residual canopy closure.
Table 2. General fuels reduction treatment prescriptions by unit.
Unit
Ownership
Treatment Prescription
WRD 20-16
USFS
Hand thin to 10", pile/burn, PAC
MCK 13-1
USFS
Hand thin to 14", pile/burn
MCK 13-3
USFS
Mechanical thin to 30”, masticate and surface spread slash
WRD 20-9
USFS
Mechanical thin to 24", masticate and surface spread slash
BLK 1-4
USFS
Mechanical thin to 24", masticate and surface spread slash, PAC
TWC 3
USFS
Mechanical thin to 24", masticate and surface spread slash, PAC
REDS
NDSL
Hand thin to 24”, pile/burn
WLD
NDSL
Combination hand/mechanical thin to 24”, pile/burn
3.3 SAMPLING DESIGN AND TIMELINE
An integrated sampling design was used to collect data on vegetation structure and fuel loads, birds, small
mammals and invertebrates. A macroplot of 150 x 330 m was established in a relatively homogeneous
and representative portion of each unit. The macroplot provided the grid for 72 small mammal trapping
stations, 4 bird survey points, 3 ant pitfall traps, and 8-10 randomly selected vegetation plots (Figure 5).
We sampled vegetation in 1 year pre-treatment and 1 year post-treatment, and birds, small mammals, and
invertebrates 1-2 years pre-treatment and 2 years post-treatment to examine the impact of fuels treatments
on wildlife at these sites (Table 3).
12
Vegetation plots =
Bird point counts =
Ant bait stations =
1
12
A
150 m
F
30 m
330 m
Figure 5. Sampling macroplot layout. Each macroplot occupied 5 ha and consisted of 72 small mammal
trapping points (every intersection on the grid), 4 bird survey points, 3 ant points, and 8-10 vegetation
plots (location of vegetation plots varied by unit).
Table 3. Fuels treatment and wildlife sampling timeline for eight paired study sites in the Lake Tahoe
Basin.
Unit
BLK 1-4
Pre 1
2006
MCK13-1
2006
MCK 13-3
2006
RED
2007
TWC3
2006
WLD
2007
WRD 20-16
2006
WRD 20-9
2006
Pre 2
2008
2008
Treatment year
2006
Post 1
2007
Post 2
2008
2006
2007
2008
2009
2010
2011
2007
2008
2009
2008
2009
2010
2008
2009
2010
2007
2007
2008
2009
2007
2008
2009
2010
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3.4 VEGETATION AND FUELS
Vegetation sampling focused on forest structure, understory composition, and fuel loads. Vegetation plot
lay-out and sampling protocols were developed in collaboration with the USFS Adaptive Management
Services Enterprise Team (AMSET, located on the Tahoe National Forest) and the LTBMU and were
based primarily on FIREMON, the Fire Effects Monitoring and Inventory System (Lutes 2006).
FIREMON is an Access database software tool that is specifically designed to facilitate analysis of
changes in plant communities and fuel loadings in response to management activities over time. The
resulting sampling protocols have been used by AMSET to monitor other fuels treatment sites elsewhere
in the Basin. Thus, the protocols used in this project are accepted by management agencies in the Basin
and will become the primary system to be used for fuels treatment monitoring and associated data
management across multiple agencies in the Basin (see www.fire.org).
Vegetation sampling plots were fixed-radius circular areas with a 17.84 m (58-ft) radius encompassing
0.1 ha (0.25 ac). Every tree and snag ≥ 6 in (15 cm) DBH was tagged with a unique number and the
following information was recorded: species, DBH, total height, decay class (for snags), and live crown
ratio. Canopy cover was measured using a GRS site-tube densitometer. Surface and ground fuels were
sampled on four, 20-m transects in each inventory plot using the line-intercept method (Brown and
Johnston 1976). Herb and shrub percent cover were measured in five 0.25-m2 quadrats along each
transect. Detailed data collection parameters for vegetation and fuels can be found in Appendix A.
3.5 WILDLIFE
We collected data on both vertebrate and invertebrate response to fuels treatments. Birds and small
mammals were the focus of vertebrate sampling because they have complementary sensitivities to the
effects of fuels treatments. They also serve as the primary prey for upper trophic level species of special
status in the Basin, namely the California Spotted Owl, Northern Goshawk, and American marten (Martes
americana). Small mammals are closely tied to specific features of forest vegetation structure and they
are primarily year-round residents. Birds are more mobile, but most species have relatively narrow
environmental conditions in which they can successfully breed, and they are also dependent upon both
overstory and understory conditions. Ants provide a variety of ecological benefits, including soil aeration,
nutrient cycling, and enhanced water infiltration. Thus, the combined responses of plants, vertebrates, and
invertebrates provide rich information about ecological conditions.
We trapped small mammals to determine species occupancy and abundance. We sampled small mammals
by placing one Tomahawk™ live trap (12.5 x 12.5 x 40 cm) and one extra large Sherman live trap (10 x
11.5 x 38 cm) at each of 72 trap stations (6 x 12 stations, 30 m apart = 150 x 330 m grid = 5 ha area)
(Figure 5). We attached Tomahawk™ traps to the trunk of trees > 20 in (50 cm) DBH, 1.5-2.0 m above
ground. We selected trees that were as close to the trap station as possible, ideally within 5 m. We
covered the traps with a tarp around the outside and placed a nest box (10 x 10 x 6 cm cardboard) at the
back of the trap with polystyrene for warmth. We placed Sherman traps on the ground at the base of trees
or along larger logs or under shrubs. Traps were securely placed such that they did not rock or move when
an animal entered. We covered each Sherman trap with natural materials to insulate traps from the sun
and rain, and placed polystyrene in the back of the trap for warmth. We used a bait mixture of oats, bird
seed and raisins. We attempted to include peanut butter and molasses, following the general formula used
by Carey et al. (1991), but excessive bear damage required that these ingredients were eliminated or
14
reduced. Traps were set, baited, and locked open for a minimum of three nights before trapping began,
then opened for five days, starting with traps being set in the late afternoon/early evening prior to the first
trap evening (just before dusk). We checked traps twice per day, generally before 10 a.m. for morning
checks and after 4 p.m. for afternoon checks. All traps were removed the morning after the fourth night.
We calculated trapping effort by correcting for traps rendered unavailable for some (0.5; disturbed,
robbed, or sprung) or all (1.0; missing or destroyed) of a trapping occasion. We identified all individuals
captured to species and marked each animal using uniquely numbered ear tags and recorded data on sex,
age (juvenile or adult), and weight. Ear, leg, or tail measurements were taken on individuals whose
identification was in question.
Bird point count stations were located at four points along the center line of the sample plot (Figure 5).
We conducted three point count visits to each sample plot between late May and early July. We used a 10
minute survey period and recorded the distance to all birds using 20 m increments. Paired sites were
sampled within two days of one another, and multiple observers were rotated among visits across sites in
order to minimize observer bias. Surveys began at least 15 minutes after sunrise and were completed
before 9:30 a.m. We avoided conducting surveys during conditions which limited bird activity or
detectability (e.g., strong wind or rain).
Composition and relative abundance of ants were characterized with a grid of pitfall traps at 40 sites. We
arranged 12 traps in a 40 x 40 m grid, with four traps, spaced 10m apart, along each of three 40 m
transects that were oriented north-south and centered on the center point of each plot; the three transects
were separated by 20 m (Bestelmeyer and Wiens 1996, Andersen 1997). Pitfall traps consisted of 6.5 cm
diameter (120 ml) plastic cups with approximately 25 ml of propylene glycol. Traps were left open for
seven days and then the contents were collected. Ants were identified to species whenever possible, and
abundance of each species and number of species were summed over all transects to obtain total
abundance and species richness for each site.
3.6 DATA ANALYSIS
3.6.1 Vegetation and Fuels
We characterized forest conditions before and after treatment by calculating values for the following
variables: quadratic mean tree diameter (hereafter QMD), percent canopy cover, tree density, tree basal
area, snag density, and the amount of coarse woody debris (hereafter CWD). We calculated tree density
by species and diameter class to assess species composition and vegetation structure. The composition
and cover of herbaceous and shrub species were also characterized and included in estimates of fuels.
Understory vegetation is a critical component of wildlife habitat and it can strongly influence fire
behavior.
We analyzed changes in these vegetation variables using PROC MIXED in SAS 9.2 (SAS Institute 2008).
As we were not interested in main effects (treatment or timing) in isolation, but rather the interaction of
main effects, we included the interaction of treatment and timing as our only fixed effect. Treatment unit
was included as a random effect, and sampling plot was nested within unit. To examine differences
between treatment types, we included an ESTIMATE statement. This statement provides estimated
differences in response variables between specified treatment types and time periods.
15
Based on the tree measurements from each plot we developed pre- and post-treatment tree lists for each
plot. These tree lists, along with surface fuel information were entered into Fuels Management Analyst
Plus (FMA) to simulate fire behavior and predict fire-caused tree mortality. FMA uses published
equations to model fire behavior and effects based on user-input weather and fuel moisture conditions
(Carlton 2005, Stephens and Moghaddas 2005, Stephens et al. 2009). Often the weather and fuel moisture
conditions are based on higher percentile weather (e.g., 95th or 97th), however in our simulations we chose
to use the observed conditions from a recent “problem” fire that occurred in the Lake Tahoe Basin in
2007 (Angora fire), as these are the conditions that are known to have resulted in exacerbated fire
behavior and effects. The actual weather values used were as follows: fuel moistures 1, 2, and 5% for 1hr, 10-hr, and 100-hr timelag classes, respectively; wind speed (6.3m) 33 km hr-1; and air temperature
26.6˚C. For surface fuels, which are represented in the fire behavior simulations as surface fuel models,
we attempted to bracket the uncertainty associated with assigning surface fuel models (Collins et al. 2011)
by running fire behavior simulations under two fuel model scenarios, a higher and lower option, for each
plot pre- and post-treatment. Fuel model assignments were made at the treatment unit level and were
based on several factors. Pre-treatment fuel model assignments were based on unit-level average fuel
loads and fuel depths. These varied slightly among treatment units, and as a result pre-treatment fuel
models were fairly similar across units (Table 5). Post-treatment fuel model assignments were also based
on average fuel loads and depths; however, for masticated stands, which had greater fuel depths (Table 5),
assignments followed the recommendations in Knapp et al. (2011). According to Knapp et al. (2011), the
two fuel models we used (NFFL 9 and SB 202) bracketed observed fire behavior fairly well, balancing
over/under prediction of rate of spread vs. flame length.
We tested for both treatment and treatment intensity effects (basal area change from pre- to posttreatment) on predicted fire-caused mortality using a mixed model analysis (PROC MIXED; SAS
Institute 2008). We used two variables to capture predicted mortality for pre- and post-treatment stand
conditions: fire-killed basal area proportion and number of fire-killed large trees (> 61.0 cm DBH).
Treatment unit was considered a random effect in the model. We investigated diagnostic plots of the
residuals for compliance with normality and homogeneity of variance assumptions. Fire-killed basal area
proportion met these assumptions, while number of fire-killed large trees had to be square roottransformed to meet assumptions.
3.6.2 Wildlife
We described species abundance, richness, and composition for all small mammal and bird species
detected on our surveys. To examine small mammal response to fuel treatment, we examined communitylevel changes in species richness and composition. In addition, we looked at changes in species
abundance following treatment implementation. Because of difficulties with the identification of
individual species of chipmunks (Tamias sp.), we also pooled abundance data for all chipmunk species to
increase sample size and examine genus-level response to treatment (Converse et al. 2006, Bagne and
Finch 2010). Abundance was calculated using the number of unique individuals captured per 100 trap
nights. We analyzed species- and genus-specific responses to treatment using PROC MIXED in SAS 9.2
(SAS Institute 2008). In our base model, we included abundance as the response variable, and the
interaction of treatment and timing as our fixed effect. Treatment unit was included as a random effect.
Furthermore, because wildlife populations, and particularly small mammal populations, show strong
annual variability, and because treatments were implemented in different years, we ran an additional
16
model which included year as a random effect. We compared model fit between the base and sampling
year models using AICc scores (Burnham and Anderson 2002), and report here the results from the bestsupported model (lowest AICc value). Additionally, we ran several additional models which grouped
treatment types (i.e., both hand and mechanical thins lumped under a single “treatment” category) and
time since treatment (both post-treatment years combined); however, all models which simplified
treatment type or timing were poorly supported, for all species considered. We excluded any species that
were captured less than once per every 1000 trap nights (35 captures total) over the course of our study.
We calculated species richness by tallying all the unique species captured at a site over the course of the
trapping period.
Bird species richness and abundance metrics were calculated for each site. Bird species richness was
based on all species encountered over the course of all three visits to a site during a year. We calculated
bird abundance as the mean number of individuals detected across all four count stations and three visits
(12 counts total) for each site and year. We included detections within 60m of the point count station, in
order to minimize double-counting of individuals and obtain more reliable estimates of abundance. We
analyzed species-specific response to treatment as outlined above for small mammals. We did not analyze
response for any species that were detected fewer than 10 times.
We employed several different methods to measure community similarity, diversity, and evenness. For
these calculations, we pooled the data from all 8 treatment sites. For bird species, we used the average
abundance recorded within a year averaged across pre- and post- treatment years. For small mammal
species, we used the total number of uniquely marked adult individuals captured during a five-night
trapping session and averaged across pre- and post-treatment periods. In order to measure and compare
the degree of association or similarity in bird and small mammal community composition at sites before
and after treatments were implemented, we used the Renkonen index (P). Also known as the Percentage
Similarity index, this is a quantitative index that accounts for differences in the abundance of species
(Wolda 1981). This index ranges from 0 to 1, with 0 indicating no overlap, and 1 indicating complete
similarity. We used Shannon’s diversity index (Shannon 1949) to examine changes in both species
richness and dominance at the treatment sites before and after treatment. We also separately examined
community evenness before and after treatment using Shannon’s Evenness index (Pielou 1966).
In determining the effect of treatment on ants, we used presence/absence data, as opposed to abundance
data, because ant abundance is sensitive to distance to nest site. A species was considered present at a site
if one or more individuals were detected on the grid. For sites that were sampled more than one time
before and after treatment, we selected the site that was sampled in the time interval closest to the
implementation of treatment. We compared the number of sites with each species in each treatment
category (control, hand and mechanical) before and after treatment with Fisher’s Exact Test. We also
compared species richness of ants with multi-factor, repeated measures ANOVA to see if sites differed in
richness before and after treatment or by treatment type. We looked at the interaction of timing (pre- or
post-treatment) and treatment type to compare control sites to treated sites before and after
implementation. We also included year in our analysis to determine if changes were due to treatment
effects or year effects. Finally, we examined changes in ant community diversity and evenness using the
methods outlined above for vertebrates.
17
4.0 RESULTS
4.1 VEGETATION
Pre-treatment forests at our study sites were largely dominated by white and red fir, with one of our eastshore sites (WLD) dominated primarily by pine (Figure 6). In addition, pre-treatment forests were
composed of a roughly even mix of pole-sized (6-12” dbh) and small (12-24”) trees (Figure 7). While
treatment prescription and intensity varied by site, treatments generally targeted smaller-diameter trees,
and preferentially removed firs given their fire susceptibility and ability to serve as ladder fuels. Although
still fir-dominated, post-treatment forests showed a greater composition of pines (Figure 6), and were
generally dominated by 12-24” trees (Figure 7). While the quantity of medium and large (>24”) trees was
little changed, they became a more prominent component of post-treatment forests, given the preferential
removal of trees in the smaller size classes.
600
Pre-treatment
Post-Treatment
500
Trees/ha
400
300
200
100
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
Cedar
Pine
Fir
0
WRD 20-9
Mechanical
Figure 6. Pre- and post-treatment mean tree density for groups of like trees: fir, cedar, and pine at eight
treatment units in the Lake Tahoe Basin.
18
350
Pre-treatment
300
Post-Treatment
Trees/ha
250
200
150
100
50
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
0
WRD 20-9
Mechanical
Figure 7. Pre- and post-treatment mean tree density by diameter class in eight treatment units in the Lake
Tahoe Basin.
Mechanical fuels treatments led to substantial reduction in basal area, while hand-thin units showed little
change in basal area (Figure 8). The reduction in basal area was significant on mechanically treated plots
(F2,144 = 46.88, p < 0.001; Table 4). Post-treatment basal area showed wide variation among plots, ranging
from 123.3 to 330.2 ft2/ac, with an average of 205.8 ft2/ac. The preferential removal of smaller-diameter
trees resulted in an increase in average tree diameter (as measured by QMD) on all plots (Figure 9). The
increase in QMD varied substantially between plots, however, ranging from as little as 0.17” to greater
than 5” on several plots. QMD was significantly affected by treatment (F2,137 = 119.70, p < 0.01). Both
treatment types significantly increased QMD, and mechanical treatments resulted in a significantly
greater increase than did hand treatments (Table 4).
19
Basal Area (ft2/ac)
500
450
400
350
300
250
200
150
100
50
0
Pre-treatment
Post-treatment
Control
MCK 13-1
RED
WLD
WRD 20-16
BLK 1-4
Hand
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Figure 8. Pre- and post-treatment basal area on eight treatment units and corresponding control units in
the Lake Tahoe Basin.
Quadratic Mean Diameter (in.)
25
Pre-treatment
Post-treatment
20
Control
15
10
5
0
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Figure 9. Pre- and post-treatment quadratic mean diameter of trees in eight treatment units and
corresponding control units in the Lake Tahoe Basin.
Snags showed a similar pattern to that of live trees following treatment. Prior to fuels reduction, polesized and small snags were roughly even in abundance on most plots (Figure 10). Because of their
associated fire risk and lower value to wildlife (Dodson and Peterson 2009), smaller diameter snags were
removed most frequently, and 12-24” snags were most common in post-treatment forests. Snags > 24”
also appeared to be reduced on most plots, though this may have been the result of wind or natural
degradation, rather than active removal of larger snags.
20
250
Pre-treatment
Post-Treatment
Snags/ha
200
150
100
50
MCK 13-1
RED
WLD
WRD 20-16
BLK 1-4
Hand
MCK 13-3
TWC 3
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
> 24"
12-24"
6-12"
0
WRD 20-9
Mechanical
Figure 10. Pre- and post-treatment mean density by diameter class of snags in eight treatment units in the
Lake Tahoe Basin.
% Canopy Cover
Given the removal of both live trees and snags, there was a predictable decrease in canopy cover at all
treatment sites (Figure 11; F2,149 = 20.89, p < 0.01). However, there was considerable variation in this
measure, with treatments resulting in between 4 and 22.8% reduction in canopy cover, depending on the
treatment unit. Post-treatment canopy coverage ranged from 31.6 to 52%, with a mean of 41.2%. This
reduction was significant for both hand and mechanical treatments (Table 4).
80
Pre-treatment
70
Post-treatment
60
Control
50
40
30
20
10
0
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Figure 11. Pre- and post-treatment average canopy cover on eight treatment units and corresponding
control units in the Lake Tahoe Basin.
21
Understory vegetation was also reduced in extent following treatment at all sites. Average shrub cover
was reduced from 16.9% to 9.4% following treatment (Figure 12; F2,123 = 6.81, p = 0.002). This reduction
in shrub cover was significant for only mechanical treatments, while hand-thin units experienced a
moderate, non-significant decline in shrub cover (Table 4). Herbaceous cover was limited prior to
treatment, averaging 2.8% across all treatment sites, and was reduced following treatment to 1.2% (Figure
13; F2,123 = 0.09, p = 0.91), though this change was not significant for either treatment type (Table 4).
Another important component of forest understory structure, coarse woody debris, was significantly
reduced in volume following both treatment types (Figure 14; F2,147 = 6.50, p = 0.002). Mechanical
treatments removed a greater volume of CWD than did hand treatments (Table 4), likely a result of
mastication of residual materials.
35
% Shrub Cover
Pre-treatment
30
Post-treatment
25
Control
20
15
10
5
0
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Figure 12. Average shrub cover on eight treatment units and corresponding control units before and after
treatments in the Lake Tahoe Basin.
22
% Herbaceous Cover
14
Pre-treatment
12
Post-treatment
10
Control
8
6
4
2
0
MCK 13-1
RED
WLD
WRD 20-16
BLK 1-4
Hand
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Coarse Woody Debris (m3/ha)
Figure 13. Average herbaceous cover on eight treatment units and corresponding control units before and
after treatments in the Lake Tahoe Basin.
1200
Pre-treatment
1000
Post-treatment
Control
800
600
400
200
0
MCK 13-1
RED
WLD
WRD 20-16
Hand
BLK 1-4
MCK 13-3
TWC 3
WRD 20-9
Mechanical
Figure 14. Average coarse woody debris (CWD) density, in m3/ha, on eight treatment units and
corresponding control units before and after treatment in the Lake Tahoe Basin.
23
Table 4. Relative changes in vegetation variables on mechanical and hand units, relative to control units,
as a result of fuels reduction treatments.
Mechanical
Measurement
Basal Area (ft2/ac)
Estimate
t
Hand
p
Estimate
t
p
-118.91 ± 12.56
-9.47
< 0.001
-15.58 ± 13.27
-1.17
0.24
4.61 ± 0.31
14.82
< 0.001
2.99 ± 0.35
8.60
< 0.001
-16.32 ± 2.61
-6.26
< 0.001
-9.75 ± 2.70
-3.61
< 0.001
Shrub Cover (%)
-7.05 ± 1.91
-3.69
< 0.001
-2.64 ± 1.98
-1.33
0.18
Herbaceous Cover (%)
-0.32 ± 0.75
-0.42
0.67
-0.09 ± 0.72
-0.12
0.90
-270.22 ± 81.91
-3.30
0.001
-211.97 ± 86.52
-2.45
0.02
QMD (in.)
Canopy Cover (%)
3
CWD (m /ha)
4.2 FUELS
There were inconsistent responses to treatment in fine woody surface fuel loads and fuel depths across
treatment units (Table 5). In 5 of the 8 units there was nearly no change in fine woody fuel loads from
pre- to post-treatment (Table 5). The one consistent trend was a noticeable increase in fuel depth for all
masticated units from pre- to post-treatment. Fuel depth in non-masticated units was relatively unchanged
(Table 5).
24
Table 5. Treatment unit average fine woody surface fuel loads (0-7.62 cm diameter or 1-100h) and fuel
depths based on plot measurements. Chosen surface fuel models for low and high fire behavior conditions
are also reported. We used fuel models from both the original set of 13 described by Anderson (1982) and
expanded set of 40 described by Scott and Burgan (2005).
Surface fuel model
Fine woody surface
Fuel depth (cm)
Number
-1
fuel loads (Mg ha )
Pre
Post
Unit
of plots
Pre
Post
Pre
Post
Low High Low High
BLK 1-4*
10
7.1
8.0
3.1
5.4
201
10
9
202
WRD 20-9*
10
8.4
8.2
2.3
5.6
201
10
9
202
MCK 13-3*
10
10.9
7.4
3.1
5.8
10
165
9
202
TWC 3*
10
6.5
7.5
1.1
5.2
201
10
9
202
MCK 13-1
9
7.7
10.8
2.9
2.4
201
10
201
165
WRD 20-16
10
6.5
7.6
2.2
2.0
201
10
201
10
RED
8
6.3
6.8
2.0
3.0
201
10
201
10
WLD
8
8.7
6.0
3.2
4.7
201
165
201
10
*masticated units with post-treatment fuel models based on recommendations in Knapp et al. (2011)
Treatment intensity, defined as the average basal area change from pre- to post-treatment for all plots in a
treatment unit, varied from 0 to 25 m2/ha across the 8 treatment units (Figure 15). Treatment units fell in
three broad categories with respect to treatment intensity: 1) BLK 1-4, WRD 20-9, and MCK13-3 had the
highest treatment intensity (all > 20 m2ha-1 change), TWC 3 and MCK 13-1 had intermediate treatment
intensity (~11 m2ha-1 change), while WRD 20-16, WLD, and RED had the lowest intensity (0-2 m2ha-1
change). The highest intensity treatments noticeably reduced tree density across all but the largest tree
size classes (> 61.0 cm DBH) (Figure 16). The moderate intensity treatments slightly reduced tree density
in the 30.5 to 61.0 cm DBH class, but considerably reduced density in the two smaller size classes (2-15.1
and 15.2-30.4 cm DBH). Tree density reductions in the lowest intensity treatments were primarily in the
two smaller size classes (Figure 16).
Canopy cover and canopy bulk density from pre- to post-treatment followed a similar trend, i.e., greater
reductions in units with higher treatment intensities, with a couple notable exceptions. In TWC 3 and
WRD 20-16 canopy cover was relatively similar from pre- to post-treatment (Figure 17), despite losing
over half of the trees in the 15.2 to 30.4 cm DBH class (Figure 16). Canopy base height increased after
treatment in all treatment units but one, WLD (Figure 17). The largest increases in canopy base height
were in the three units with the highest treatment intensity (Figure 17).
The mixed model analysis indicated a strong treatment effect (P<0.001) for both response variables: firekilled basal area proportion and number of fire-killed large trees (> 61.0 cm DBH). For variables there
was a considerable decrease in predicted mortality following treatment (Figures 15 and 16). There was no
evidence for a treatment intensity effect on fire-killed basal area proportion (P=0.27) and marginal
evidence for a treatment intensity effect on the number of fire-killed large trees (P=0.09), indicating more
intense treatments result in slightly less large trees being fire-killed. The interaction between treatment
and treatment intensity was only significant for the model explaining fire-killed basal area proportion
(P<0.01).
25
Basal area (m2/ha)
70
live
60
fire-killed
50
40
30
20
10
0
BLK 1-4
WRD 20-9 MCK 13-3
TWC 3
MCK 13-1 WRD 20-16
WLD
RED
Decreasing Treatment Intensity →
Figure 15. Average basal area for each treatment unit pre- and post-treatment (post indicated by
horizontal line fill). Predicted mortality under modeled wildfire conditions (see Methods) is shown within
the bars for each unit.
26
2.5 to 15.1 cm
30.5 to 61.0 cm
1000
300
live
250
800
fire-killed
200
600
150
400
Trees/ha
100
200
50
0
0
BLK 1- WRD MCK TWC 3 MCK WRD WLD RED
4
20-9 13-3
13-1 20-16
BLK 1- WRD MCK TWC 3 MCK WRD WLD RED
4
20-9 13-3
13-1 20-16
15.1 to 30.5 cm
> 61.0 cm
300
60
250
50
200
40
150
30
100
20
50
10
0
0
BLK 1- WRD MCK TWC 3 MCK WRD WLD RED
4
20-9 13-3
13-1 20-16
BLK 1- WRD MCK TWC 3 MCK WRD WLD RED
4
20-9 13-3
13-1 20-16
Decreasing Treatment Intensity →
Figure 16. Average tree density by diameter-at-breast height class for each treatment unit pre- and posttreatment (post indicated by horizontal line fill). Predicted mortality under modeled wildfire conditions
(see Methods) is shown within the bars for each unit.
27
% Cover
Canopy Cover
70
60
50
40
30
20
10
0
BLK 1-4
WRD 20-9
MCK 13-3
TWC 3
MCK 13-1 WRD 20-16
WLD
RED
WLD
RED
WLD
RED
Canopy Bulk Density
0.10
kg/m3
0.08
0.06
0.04
0.02
0.00
BLK 1-4
WRD 20-9 MCK 13-3
TWC 3
MCK 13-1 WRD 20-16
Canopy Base Height
10
Meters
8
6
4
2
0
BLK 1-4
WRD 20-9
MCK 13-3
TWC 3
MCK 13-1 WRD 20-16
Decreasing Treatment Intensity →
Figure 17. Average canopy characteristics for each treatment unit pre- and post-treatment (post
indicated by horizontal line fill).
28
4.3 SMALL MAMMALS
We captured 10682 small mammals from 16 species during the course of our project (Appendix B). At
the community level, there was minimal change in response to treatment. Treatment units had 14 species
in both pre- and post-treatment samples. Two species present in the pre-treatment samples (pinyon mouse,
Peromyscus truei, and brush mouse, Peromyscus boylii) were not detected during post-treatment
sampling. Likewise, there were two species detected during post-treatment sampling that were not
detected prior to treatment (least chipmunk, Tamias minimus, and bushy-tailed woodrat, Neotoma
cinerea). However, the identity of the least chipmunk should be confirmed with genetic data given
difficulties in identification and location of the Tahoe Basin on the outer extent of the species range. The
Renkonen index indicated 82.4% similarity between pre- and post-treatment samples across treatment
units, when accounting for changes in both species composition and abundance. Shannon’s Diversity
index remained virtually unchanged, with a very minor increase following treatment (Table 6). Likewise,
there was only a small change in community evenness following treatment, as indicated by Shannon’s
Evenness Index suggesting that the proportion of the community represented by different species
remained similar.
When considered as a whole, the small mammal community showed an increase in abundance in response
to both hand and mechanical treatments, in both sampling years following treatment. Abundance
increased between 12% and 28%, depending on year and treatment type, though these changes were nonsignificant (all p > 0.1).
At the species level, we had sufficient data from 10 species to analyze their response to treatment (Table
7). Although several species exhibited substantial changes in abundance following treatment, these
changes were statistically significant for only 2 species. In the first year post-treatment, deer mice
(Peromyscus maniculatus) declined significantly on mechanical thin units, and lodgepole chipmunks
(Tamias speciosus) declined significantly on hand-thinned units.
Although all other species-level results were non-significant, there were several consistent patterns
observed. In particular, yellow-pine chipmunks (Tamias amoenus) increased in abundance on both
mechanical and hand treatment units during both years of post-treatment surveys, with increases ranging
from 15 to 130%. Additionally, northern flying squirrels (Glaucomys sabrinus) declined on all treatment
units during both years of the study, with declines ranging from 33 to 70%. Finally, because of challenges
with chipmunk identification, we pooled data from all chipmunk species to examine the group’s response
to treatment. When grouped, chipmunks increased in abundance in both years following treatment on both
hand and mechanical units, with increases between 28.3 and 61.3%. However, the only statistically
significant increase was in the 2nd year post-treatment on mechanical sites.
29
Small mammals/100 trap nights
40
Year 1
30
Year 2
20
10
0
-10
-20
-30
-40
-50
C
T
C
MCK 13-1
T
C
TWC 3
T
C
T
C
WRD 20-16 WRD 20-9
T
BLK 1-4
C
T
C
MCK 13-3
Hand
T
C
RED
T
WLD
Mechanical
Small mammal species richness
Figure 18. Change in mean small mammal abundance in years 1 and 2 post-treatment, relative to pretreatment years, at paired control (C) and treatment (T) sites in the Lake Tahoe Basin. Means are
corrected for differences in trapping effort and reported as # captures/100 trap nights.
4
3
2
1
0
-1
-2
-3
-4
-5
Year 1
Year 2
C
T
MCK 13-1
C
T
TWC 3
C
T
WRD 20-16
C
T
WRD 20-9
Hand
C
T
BLK 1-4
C
T
MCK 13-3
C
T
RED
C
T
WLD
Mechanical
Figure 19. Change in small mammal species richness in years 1 and 2 post-treatment, relative to pretreatment years, at paired control (C) and treatment (T) sites in the Lake Tahoe Basin.
30
Table 6. Calculation of diversity, similarity and evenness using the total number of individual mammals
(by species) captured before and after fuels reduction in the Lake Tahoe Basin, 2006-2011.
Number of species
Number of species in common (j)
Renkonen index (P)
Shannon diversity (H')
Shannon evenness (E)
Treatment
Pre-treatment
Post-treatment
14
14
12
0.824
1.87
1.93
0.71
0.73
Control
Pre-treatment Post-treatment
10
15
7
0.308
1.01
1.14
0.44
0.42
Table 7. Percent change in abundance, relative to control sites, following fuels reduction treatments
among small mammal species detected in the Lake Tahoe Basin, 2006-2011. Species are listed in order of
abundance.
Mechanical
Hand
% Change
Year 1
% Change
Year 2
Direction
of Change
% Change
Year 1
% Change
Year 2
Direction
of Change
Deer mouse
Long-eared chipmunk
Allen’s chipmunk
Yellow-pine chipmunk
Lodgepole chipmunk
-67.5
2.9
38.4
113.8
54.8
2.8
19.4
38.1
129.5
-13.6
Mixed
Positive
Mixed
Positive
Mixed
4.4
21.5
-19.4
72.2
-260.8
30.0
0.3
-14.4
15.5
36.9
Positive
Positive
Mixed
Positive
Mixed
Golden-mantled ground
squirrel
Douglas’ squirrel
Northern flying squirrel
California ground squirrel
Least chipmunk
All Chipmunks
All Species
11.8
129.5
-33.2
-37.3
-26.4
61.3
12.0
-18.9
-0.4
-70.2
127.0
†
48.4
27.6
Mixed
Mixed
Negative
Negative
Mixed
Positive
Positive
-29.9
-8.0
-47.7
-58.9
56.2
28.3
23.6
22.2
-74.3
-47.6
-74.5
†
29.3
15.8
Mixed
Negative
Negative
Mixed
Positive
Positive
Positive
Common Name
Bold = p < 0.05; † = No detections on control plots, unable to calculate % increase
4.4 BIRDS
Across the six years of our study, we observed 8110 individuals from 63 species of birds (Appendix C).
Species composition of the bird community showed minimal change following treatment. We detected 53
species on treatment units prior to treatment, and 57 species following treatment; 47 of these species were
found both before and after treatment. The Renkonen index, which examines both species composition
and relative abundance, indicated 85.6% similarity between pre- and post-treatment bird communities
(Table 8), suggesting that these treatments did not produce substantial changes at the community level.
Similarly, there were only small changes in both Shannon’s Diversity index (3.27 pre-treatment, 3.28
post-treatment) and Shannon’s Evenness index (0.82 before treatment, 0.81 following treatment),
31
indicating that there were only minimal changes in community diversity and relative abundance following
treatment. On control sites, all community metrics were very similar to those found on treatment sites
(Table 8), further indicating that treatments produced minimal change to the bird community.
We analyzed changes in abundance of 36 bird species for which we had greater than 10 observations
(Table 9). In spite of substantial changes in abundance following treatment for many species, few of these
differences were statistically significant. The species which showed significant (p < 0.05) positive
responses to treatment were Dark-eyed Junco (Junco hyemalis), Dusky Flycatcher (Empidonax
oberholseri), Evening Grosbeak (Coccothraustes vespertinus), and Red Crossbill (Loxia curvirostra).
Golden-crowned Kinglet (Regulus satrapa), Nashville Warbler (Oreothlypis ruficapilla), and Redbreasted Nuthatch (Sitta canadensis) all had significant negative responses to treatment in one or both
years (Table 9).
Although few species exhibited statistically significant responses, many species exhibited consistent
responses to treatment in both years following treatment. In response to mechanical treatment, 13 species
increased both years following treatment, while 12 species declined in both years following treatment.
Similarly, with hand treatments, 13 species responded positively in both years post-treatment, while 10
species declined in both years.
When all species were grouped for analysis, abundance of the entire bird community declined slightly,
but non-significantly (all p > 0.4) on both hand and mechanical treatment plots during both years of posttreatment sampling. Declines ranged from 4.8% to 9.5% relative to control plots, depending on year and
treatment type (Table 9).
Number of Individuals
8
Year 1
6
Year 2
4
2
0
-2
-4
-6
C
T
MCK 13-1
C
T
TWC 3
C
T
C
T
C
WRD 20-16 WRD 20-9
T
BLK 1-4
Hand
C
T
MCK 13-3
C
T
RED
C
T
WLD
Mechanical
Figure 20. Change in mean bird abundance in years 1 and 2 post-treatment, relative to pre-treatment
years, at paired control (C) and treatment (T) sites in the Lake Tahoe Basin.
32
8
Year 1
6
Bird Species Richness
Year 2
4
2
0
-2
-4
-6
-8
C
T
MCK 13-1
C
T
TWC 3
C
T
C
T
C
WRD 20-16 WRD 20-9
T
BLK 1-4
C
T
MCK 13-3
Hand
C
T
C
RED
T
WLD
Mechanical
Figure 21. Change in bird species richness in years 1 and 2 post-treatment, relative to pre-treatment
years, at paired control (C) and treatment (T) sites in the Lake Tahoe Basin.
Table 8. Calculation of similarity, diversity, and evenness using total bird detections before and after
fuels reduction in the Lake Tahoe Basin, 2006-2011.
Number of species
Number of species in common (j)
Renkonen index (P)
Shannon diversity (H')
Shannon evenness (E)
Treatment
Pre-treatment Post-treatment
53
57
47
0.856
3.27
3.28
0.82
0.81
Control
Pre-treatment
Post-treatment
52
56
42
0.901
3.27
3.26
0.83
0.81
Table 9. Change in abundance of bird species following mechanical- and hand-thin fuels treatments,
relative to control sites, in the Lake Tahoe Basin. Results are presented for all species with > 10
detections, and species are listed in order of abundance.
Mechanical
Common Name
Mountain Chickadee
Red-breasted Nuthatch
Yellow-rumped Warbler
Golden-crowned Kinglet
Dark-eyed Junco
Western Tanager
Dusky Flycatcher
Hand
% Change
Year 1
% Change
Year 2
Direction
of Change
% Change
Year 1
% Change
Year 2
Direction
of Change
-20.4
-33.4
-8.0
-50.9
87.8
-8.2
-4.7
-27.7
-61.7
14.9
-29.6
74.0
-32.2
21.1
Negative
Negative
Mixed
Negative
Positive
Negative
Mixed
24.7
12.6
14.4
-39.6
-68.8
15.7
21.5
28.9
-14.8
-5.3
-24.1
-36.1
7.1
102.0
Positive
Mixed
Mixed
Negative
Negative
Positive
Positive
33
Table 9 (continued).
Mechanical
Common Name
Evening Grosbeak
Steller's Jay
Fox Sparrow
Nashville Warbler
Brown Creeper
American Robin
Hermit Thrush
Warbling Vireo
Pine Siskin
Brown-headed Cowbird
Western Wood-Pewee
White-headed Woodpecker
Cassin's Finch
Townsend's Solitaire
Hairy Woodpecker
Hermit Warbler
MacGillivray's Warbler
White-breasted Nuthatch
Red Crossbill
Cassin's Vireo
Clark's Nutcracker
Northern Flicker
Red-breasted Sapsucker
Williamson's Sapsucker
Chipping Sparrow
Black-backed Woodpecker
Band-tailed Pigeon
Ruby-crowned Kinglet
Pygmy Nuthatch
All Species
Hand
% Change
Year 1
% Change
Year 2
Direction
of Change
% Change
Year 1
% Change
Year 2
Direction
of Change
182.7
-5.6
-68.0
-149.9
-2.2
125.9
-90.0
20.6
-79.4
22.1
173.9
-75.3
20.4
123.2
27.6
-51.3
-75.7
45.8
†
13.6
-99.4
-53.0
-315.9
58.6
220.5
94.3
-237.8
35.5
†
-9.5
-59.6
-24.2
-88.9
-140.3
18.8
101.5
-88.7
55.5
-53.9
72.3
554.8
20.0
71.4
14.4
32.4
-82.5
12.8
6.9
71.4
226.6
159.7
-81.3
143.2
-172.0
-8.7
105.9
-703.8
†
492.4
-8.6
Mixed
Negative
Negative
Negative
Mixed
Positive
Negative
Positive
Negative
Positive
Positive
Mixed
Positive
Positive
Positive
Negative
Mixed
Positive
Positive
Positive
Mixed
Negative
Mixed
Mixed
Mixed
Positive
Negative
Positive
Positive
Negative
68.7
-30.6
40.2
-233.7
24.1
-35.9
28.0
36.5
-42.5
-20.9
-9.9
72.2
-6.3
143.9
-22.2
-69.5
-9.3
15.2
†
-45.7
202.3
-68.9
-106.9
-5.0
166.6
191.9
6.8
84.1
†
-4.8
213.8
-34.3
0.3
-322.8
-12.1
-39.5
-35.2
65.1
-75.6
-42.1
396.2
38.5
27.3
27.1
491.2
28.3
220.0
-109.0
21.9
163.5
-180.8
-87.3
-35.9
-4.0
158.2
497.9
540.0
†
80.5
-7.6
Positive
Negative
Positive
Negative
Mixed
Negative
Mixed
Positive
Negative
Negative
Mixed
Positive
Mixed
Positive
Mixed
Mixed
Mixed
Mixed
Positive
Mixed
Mixed
Negative
Negative
Negative
Positive
Positive
Positive
Positive
Positive
Negative
Bold = p < 0.05; † = No detections on control plots, unable to calculate % increase
4.5 INVERTEBRATES
A total of 38 species of ants from 10 genera were detected over the entire study period. Species detected
included members of several ecologically important functional groups. These groups included aerators
(species that create tunnels that aerate soils and aid in water infiltration), decomposers (ants that build
tunnels through woody debris and aid in nutrient release), compilers (species that build thatch mounds
that increase soil nutrient availability), and generalists (species that may fill any of the above roles in
certain contexts; Sanford et al. 2009).
34
Species composition of the ant community changed following treatment. We detected 22 species on
treatment units prior to treatment, and 25 species following treatment; 15 of these species were found
both before and after treatment. The Renkonen index, which examines both species composition and
relative abundance, indicated 68.6% similarity between pre- and post-treatment ant communities (Table
10), suggesting that these treatments did produce substantial changes at the community level. Similarly,
there were changes in both Shannon’s Diversity index (2.34 pre-treatment, 1.79 post-treatment) and
Shannon’s Evenness index (0.76 before treatment, 0.56 following treatment), indicating that there were
changes in community diversity and relative abundance following treatment. This pattern was also
observed when on control sites, though there was greater similarity between pre- and post-treatment
communities on the control sites.
Table 10. Calculation of similarity, diversity, and evenness using total ant detections before and after
fuels reduction in the Lake Tahoe Basin, 2006-2011.
Number of species
Number of species in common (j)
Renkonen index (P)
Shannon diversity (H')
Shannon evenness (E)
Treatment
Pre-treatment Post-treatment
22
25
15
0.686
2.34
1.79
0.76
0.56
Control
Pre-treatment
Post-treatment
22
25
15
0.751
2.10
1.97
0.68
0.61
Fourteen species of ant in five genera were detected at 20% of sites in any given year of the study (Table
11). These 14 species included representatives from all functional groups. We did not find that treatment
impacted the occurrence of any species (all p > 0.5). Mean species richness of ants did not differ by
treatment type (F2,13 = 1.03, p = 0.39), timing (F1,13 = 0.06, p = 0.82), or the interaction of timing and
treatment (F2,13 = 1.66, p = 0.23). The only significant effect on species richness of ants was year (F2,13 =
3.85, p= 0.008), indicating that the ant species found on our study units experienced significant annual
variation in site occupancy.
Table 11. Ant species detected on study units in the Lake Tahoe Basin, 2006-2011.
Species
Ecological Group
Campontus modoc
Campontus vicinus
Formica accreta
Formica aserva
Formica fusca
Formica microphthalma
Formica neoclara
Formica neorufibaris
Formica propinqua
Formica ravida
Formica sibylla
Lasius pallitarsus
Myrmica tahoensis
Tapinoma sessile
Decomposer
Generalist
Decomposer
Decomposer
Aerator
Generalist
Generalist
Generalist
Compiler
Compiler
Aerator
Generalist
Aerator
Generalist
35
5.0 DISCUSSION
5.1 VEGETATION AND FUELS
Our vegetation results indicated that treatment implementation, while varied, achieved the stated
objectives. Implementation of fuels treatments resulted in more open forest with fewer smaller diameter
trees. Pre-treatment forests were, with the exception of one east-shore treatment unit, dominated by firs
(as measured by stems/acre), and had high densities of small (< 12” dbh) trees. Fuels treatments
preferentially removed these smaller diameter trees, generally leaving forests dominated by moderatesized trees (12-24” dbh) trees. As a result of this preferential removal of smaller trees, average tree
diameter increased on all plots following treatment. Post-treatment forests also had a greater proportion of
pine than did pre-treatment forests, though forests remained fir-dominated. In addition to changes in live
tree density, snag density was also reduced as a result of fuels treatments. This was not limited to small
diameter snags, as moderate-sized snags were also less abundant on many units following treatment.
Given the importance of snags as wildlife nesting and roosting sites, all treatment prescriptions set targets
for snag retention. All treatment units met the prescription goals, which called for retention of at least 7.5
snags/ha.
In addition to reductions in tree density and cover, forest understory cover was reduced on all treatment
sites, significantly so on mechanically treated sites. Both measures of understory vegetation, shrub cover
and herbaceous cover, declined following treatment. However, given the opening of forest canopies
following treatment, additional light penetration would likely result in increases in both shrub and
herbaceous cover over longer time periods. At this time, we have no data to allow us to predict the pace of
this regeneration, or how it may vary based on treatment type or location. Our other measure of
understory structure, coarse woody debris, was substantially reduced across all treatment units.
The degree of change in forest structure varied greatly between treatment units. This was a result of
several factors. By design, the treatment units had different diameter limits in treatment prescriptions. In
addition, not all of our sampling units experienced treatment across the entire sampling area. Several sites
had riparian buffer strips along stream channels, areas that were left untreated. These untreated areas
create heterogeneity in post-treatment conditions within and across our survey units.
Not surprisingly, the treatments altered forest structure in a manner consistent with the basic fuel
reduction principles proposed by Agee and Skinner (2005): reduced tree density, especially in the smaller
tree size classes, reduced ladder fuels (as indicated by canopy base height), and to a lesser extent reduced
canopy fuels (Figures 16 and 17). However, the obvious piece missing with respect to the basic fuel
reduction principles is reduced surface fuels. There was little evidence for a reduction of surface fuel
loads across the treatments studied; in fact there was some evidence to the contrary, namely increased fuel
depths in the masticated units (Table 5). Note that with the exception of increasing fuel depth in
masticated units, the treatments did not noticeable increase fine woody fuel loads, indicating that the
activity fuel treatments, namely piling and burning, were effective. Despite this general lack of change in
surface fuels our fire behavior/effects modeling suggests that the modification of forest structure alone in
the treatments studied did significantly alter tree survivability under wildfire conditions, particularly
among the large trees. Based on the numerous studies demonstrating the importance of reducing surface
fuels in reducing fire behavior and fire effects (Raymond and Peterson 2005, Stephens et al. 2009, Fulé et
36
al. 2012, Safford et al. 2012) it is reasonable to assume that if a surface fuel treatment component (e.g.,
prescribed burning) were added to the treatments studied tree survivability under wildfire conditions
would only improve.
Our findings indicating only a marginal effect of treatment intensity on predicted fire-induced tree
mortality suggests that treatment effectiveness is not necessarily driven by the amount of basal area
removed. This supports findings from a previous study demonstrating that differing upper diameter-limits
for fuel reduction thinning had little effect on modeled landscape-level fire behavior (Collins et al. 2011).
What is interesting about these results is that the reduction in density of small trees (<30.4 cm DBH),
coupled with activity fuel treatment, alone can reduce large tree mortality due to wildfire.
5.2 WILDLIFE
In spite of substantial changes to forest structure and composition following fuels treatments, we observed
few significant changes in the diversity and abundance of wildlife.
For small mammals, community composition experienced little change following treatment. Two new
species were detected following treatment, while two species present before treatment were not detected
after treatments. These species were all rare to uncommon during the time periods in which they were
detected. Small mammal community evenness remained remarkably similar following treatment, as
suggested by the minor changes to species composition. Our indices of change in the mammal community
(Shannon’s Diversity and Evenness indices, Renkonen’s index) indicated that pre- and post-treatment
communities were very similar in both species diversity and relative abundance of species.
Small mammal abundance showed an overall positive trend following treatment implementation, driven
primarily by an increase in chipmunk abundance. While none of these responses were statistically
significant, mammal abundance was consistently higher in both treatment types and in both years
following treatment implementation. Many of the components of forest structure that were reduced
following treatment (e.g., shrub and herbaceous cover, coarse woody debris) are recognized as essential
habitat features for many small mammals (Wilson and Carey 2000, Carey and Harrington 2001). It
remains unclear which components of the fuels treatment are responsible for this positive trend, but the
observed increase in overall abundance is consistent with the findings of several prior studies conducted
elsewhere in the mountain West (Converse et al. 2006, Bagne and Finch 2010).
At the species level, we observed significant responses to treatment in only two species. Deer mice
populations declined by 67% on mechanical treatment plots in the first year following treatment, but
returned to pre-treatment levels by the second year after treatment. The significant initial decline contrasts
with the findings from several other studies which found increases in deer mouse abundance immediately
following thinning in other parts of the western United States (Carey and Wilson 2001, Suzuki and Hayes
2003). This may be more reflective of response to the mastication which occurred on mechanically
thinned plots, rather than a response to the mechanical thinning itself. Given the thick layer of masticated
material and reduction in understory cover, this treatment type may have temporarily reduced habitat
suitability for deer mice. Likewise, lodgepole chipmunks declined significantly on hand treatment plots in
37
the first year following treatment, but had returned to pre-treatment abundance by the second year
following treatment.
Although all other species-level results were non-significant, there were several consistent patterns
observed. In particular, yellow-pine chipmunks (Tamias amoenus) increased in abundance on both
mechanical and hand treatment units during both years of post-treatment surveys, while northern flying
squirrels (Glaucomys sabrinus) declined on all treatment units during both years of the study. Finally,
when considered as a group, chipmunks increased in abundance in both years following treatment on both
hand and mechanical units. However, the only statistically significant increase was in the 2nd year posttreatment on mechanical sites. This lack of statistical significance for many results, in spite of large
differences in abundance, suggests that wildlife abundance may be driven by other factors that overwhelm
treatment effects.
Like the small mammal community, the bird community at our study locations exhibited minor change
following treatment. We detected 63 species total, 6 of which were detected only in pre-treatment
samples, and 10 of which were found exclusively in post-treatment surveys. However, all of these species
were rarely detected. As suggested by the small change in species richness, the bird community at our
study site showed little change following treatments, as indicated by our indices of community diversity,
similarity, and evenness.
Overall abundance of birds showed a slight decline in both treatment types and in both years posttreatment. Bird abundance declined between 4.8 and 9.5 %, depending on year and treatment type. While
this was a consistent pattern, none of these declines were statistically significant. When examined at the
species level, we observed significant responses to treatment in 7 of the 36 species we analyzed. Goldencrowned Kinglet, Red-breasted Nuthatch, and Nashville Warbler all responded negatively to mechanical
treatment in both years following treatment, with significant responses in at least one of the two posttreatment years. Kinglets and nuthatches are typically found in dense, shaded forest, so it is unsurprising
that they were less common in the open forests found following treatment (Hayes et al. 2003). In addition,
Nashville Warblers are found in forests with dense shrub cover, which they use for nest concealment. The
reduction in shrub cover following treatment likely explains their decline.
Four species exhibited significant positive responses to treatment. Red Crossbills responded positively to
hand treatment in the first year post-treatment, but had returned to baseline levels by year 2. Similarly,
Evening Grosbeaks showed a positive response to mechanical treatment only in the first year, suggesting
that both of these irruptive finch species may have benefited from the disturbed conditions immediately
following treatment. Dusky Flycatchers responded positively to hand thinning in the second year
following treatment, possibly due to more open forest facilitating aerial foraging. Finally, Dark-eyed
Juncos responded positively to mechanical treatments in both years post-treatment, perhaps a result of
better ground foraging opportunities in the disturbed and exposed soil following treatment (Hayes et al.
2003).
We observed significant results primarily in abundant species, indicating that we likely lacked power to
detect significant responses to treatment in all but the most common species. Although we did not detect
significant responses in most of the less common species, we did observe a number of consistent patterns
38
when considering response irrespective of statistical significance. However, these patterns were evenly
split between species that responded positively and those that responded negatively to treatment. The
treatments did not produce a pronounced effect in the bird community as a whole, as decreases in one
species appear to have been mirrored by increases in another species. These decidedly mixed results are
consistent with our community-level results, further indicating that while abundance of individual species
may change significantly following treatment, the community as a whole experienced minimal change in
species richness or evenness.
Ants were not affected by either form of fuel reduction treatment utilized in this study. The majority of
the ant species in our study nested in the ground, in logs and coarse woody debris, and in thatch mounds.
Although prescriptions may reduce the amount of coarse woody debris in an area, an important habitat
feature for foraging and nesting ants, we did not find a significant effect of hand or mechanical treatment
on ant community composition or species richness. Additionally, all functional groups of ants were
represented before and after treatment, indicating that ecosystem service provided by ants, including
nutrient cycling and availability, soil aeration, water infiltration was maintained in treated forests
(Folgarait 1998). The maintenance of species richness and composition suggests that upland forest treated
by hand or mechanical means provide adequate habitat, at least initially, for this important invertebrate
group.
Differences in ant diversity may be short-term responses to disturbance of treatment. Treatment that
disturbs soil and ground cover is likely to affect ground nesting and pile nesting ant species. Additionally,
it appears that there was a year effect on ant diversity, as indicated by the decrease in diversity and
evenness on control sites, although it was not as pronounced as declines on treated sites. It appears likely
that year and treatment effects combine to affect community composition. Further study is needed to
determine if changes in community composition are long-term or if diversity returns to pre-treatment
levels over time.
6.0 CONCLUSION
Our results indicate that conventional mechanical- and hand-thin fuels treatments are consistent with
maintenance of diversity and evenness of ants, forest birds and small mammals. This is supported by
other recent research suggesting minimal effects of fuels treatment at the community level (Stephens et al.
2012). Given the lack of longer-term research examining response to fuels treatments, we are unable to
predict whether our short-term results would be consistent over longer, management-relevant time scales.
At the species level, we did observe substantial changes in abundance for many species following
treatment. However, in general our results were significant for only the most abundant species, which are
typically not the drivers of land management decisions. This suggests that we lacked power to detect
trends in all but the most abundant species, and that other variables, such as variation in treatment
intensity or annual climatic variability, may have overwhelmed treatment response for many species. We
hope to combine our results here with other ongoing SNPLMA-funded research to better assess specieslevel responses to fuels treatments. More broadly, we observed consistent, non-significant increases in
overall small mammal abundance across both treatment types, and non-significant decreases in overall
39
bird abundance following treatment. The increase in small mammal abundance, while not statistically
significant, is consistent with the results of several other studies (Converse et al. 2006, Stephens et al.
2012), and appears to be a widespread short-term response. The decrease in bird abundance has not been
reported consistently by other authors, but we hypothesize that the slight decline observed here may be
attributed to the decrease in structural diversity following treatment implementation.
However, it is worth highlighting two caveats to our results. First, treatment intensity and extent varied
substantially across treatment units, and the presence of untreated areas with treatment plots may have
provided refugia for species dependent upon dense forested stands. Additionally, the short-term results
observed here may not be predictive of longer-term trends in community diversity and evenness. For
example, understory vegetation is likely to increase in extent following treatment, but did not do so over
the time frame of our research. Changes in extent of shrub and herbaceous cover are likely to influence
occupancy and abundance of several species of mammals and birds (Converse et al. 2006). However, we
are unable to offer reliable predictions about response beyond the time frame of our research.
Unfortunately, research examining longer-term wildlife response to fuels treatments is almost entirely
lacking (Stephens et al. 2012), which leaves land managers without robust management information at
relevant time scales. We hope that this prominent information gap will be addressed in future studies.
40
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43
APPENDICES
Appendix A. Vegetation Data Collection Detailed Protocol
Vegetation was measured within a fixed 17.58 meter (58 ft) radius plot of 0.1 ha (0.25 ac). A random
azimuth was selected for the first transect and then three additional transects were established at
subsequent 90° angles with the 0 meter marks at the plot center. The four transects were the basis for
sampling down woody debris (DWD), herbaceous and shrub cover and frequency, and duff and litter
depths (Figure A-1). Plots were monumented with five 2 foot pieces of rebar capped with yellow plastic
caps imprinted with “USFS UPFU”; one at the plot center and one at the distal end of each transect.
Vegetation Plot Layout
Transect 1
Transect 4
Transect 2
Transect 3
Tree Macroplot 17.58 m (57.68’) radius
Sapling and Seedling Subplot 3.57 m (11.77’) radius- tree saplings and seedlings less than 1 cm dbh.
DWD 17.58 m transects, 0 is at plot center. 1 and 10hr fuels counted from 15-17m, 100 hr from 12-17
m, and 1,000 hr for the entire length.
Litter and duff measurement and vegetation cylinder conducted at 8 m and 16 m.
Cover and Frequency - .5 m2 quadrats on all transects at the 3, 6, 9, 12, and 15 m marks placed on
the right side of transect (from center of plot).
Permanent rebar stake locations- photo points are from outer 4 rebar stakes looking in to plot.
Figure A1. Uplands Fuels research project vegetation plot lay-out.
Plot Description
Descriptive data collected in each plot included: UTM coordinate in NAD 27, slope, aspect, general
landform, horizontal and vertical slope shape. The two most dominant species with greater than 10%
canopy cover were recorded for three stratums; upper (> 3 m tall), mid (3 to 10 m tall), and low (< 1 m
tall). A photo point was established at the distal end of each transect looking down the meter tape toward
the plot center.
Tree Data
A breakpoint of 15 cm (6 in) diameter at breast height (DBH) was selected for sampling mature trees. The
following data was recorded for all mature trees within the entire plot: species, DBH, total height, height
to live crown base, live crown ratio, crown position, and observed damage. Snags were also sampled
within the entire plot. Snag data included: species, DBH, total height, and decay class. Within a 3.57 m
44
(11.7 ft) fixed radius subplot of 0.01 ac (0.004ha) nested at the plot center, the species, DBH, total height,
and live crown ratio was recorded for all saplings greater than 1.37 m (4.5 ft) tall with a DBH less than
the breakpoint. Saplings were categorized by 4 size classes based on DBH: 0-2.5, 2.5-5, 5-10, 10-15 cm.
The number of all seedlings less than of 1.37 meters tall was recorded for each species. Seedlings were
categorized by 5 height classes: 1-15, 15-30, 30-60, 60-100, and 100-140 cm. The midpoint values of size
and height classes were used in calculations. Each mature tree and snag was permanently marked with an
aluminum tree tag and nail. Canopy cover was measured at 25 points using a 5 m by 5 m grid using a
GRS site-tube densitometer.
Fuels Data
Surface and ground fuels were sampled on all four transects in each inventory plot using the line-intercept
method (Brown, 1974). One-hour (0-0.64 cm) and ten-hour (0.64-2.54 cm) fuels were tallied from 15-17
meters, 100-hour (2.54-7.62 cm) fuels from 12-17 meters, and 1000-hour (>7.62 cm) fuels were sampled
along the entire length (17.84 meters) of each transect. The larger fuels (1000-hour) represent coarse
woody debris (CWD) that has high value for many wildlife species, so the following information was
collected for each CWD: species, diameter at the tape, diameter at each end, length, and decay class.
Duff and litter depth (cm) was measured at the 8 and 16 meter marks. At the same locations, the
surveyors estimated the following within an imaginary 2m by 2m cylinder: live and dead tree/shrub cover,
average tree/shrub height, live and dead herb cover, and average herb height. Measurements were
conducted towards the distal ends of the transects to avoid the disturbance that was generally concentrated
in the plot center.
Herbaceous and Shrub Cover/Frequency
Herb and shrub percent cover, height, and nested frequency were measured in five 0.25m2 quadrats
located at 3 meter intervals (3,6,9,12,15) along all four transects, for a total sample area of 1.25 m2.
Frequency describes the abundance and distribution of species and is very useful for comparing
significant differences between two plant communities or detecting significant change in a single
community over time. A reasonable sensitivity to change results from capturing frequencies between 20
and 80 percent, and therefore, a nested quadrat system was used to avoid problems resulting from using a
single quadrat size. Nested quadrat sizes (5x5, 25x25, 25x50, 50x50 cm) corresponded to a nested rooted
frequency ratio of 1:25:50:100.
Plant cover was measured as the vertical projection of foliage within a percentage of the quadrat and the
percent value indicates the relative influence of each species on the community. A system of 12 cover
classes, (0-1, 1-5, 5-15, 15-25, 25-35, 35-45, 45-55, 55-65, 65-75, 75-85, 85-95, 95-100) was used to
reduce human error and increase the consistency of estimates. Midpoint values were used for
computation.
Height gives detailed information about the vertical distribution of plant species cover with in the plot. It
allows calculations of 1) plant species volume (cover x height) and 2) biomass (height x cover x bulk
density). FIREMON uses 0.8 kg/ m3 for herbaceous BD and 1.8 kg/m3 for shrubs.
45
Appendix B. Total number of individuals and site frequency of small mammal species caught and
marked during live-trapping surveys conducted late May through August across 16 units in the Lake
Tahoe Basin, 2006-2011. Species are ranked in order of abundance.
Common Name
Deer mouse
Long-eared chipmunk
Allen’s chipmunk
Yellow-pine chipmunk
Lodgepole chipmunk
Golden-mantled ground squirrel
Douglas’ squirrel
Northern flying squirrel
California ground squirrel
Trowbridge’s shrew
Least chipmunk
Long-tailed vole
Pinyon mouse
Vagrant shrew
Brush mouse
Bushy-tailed woodrat
Scientific Name
Peromyscus maniculatus
Tamias quadrimaculatus
Tamias senex
Tamias amoenus
Tamias speciosus
Spermophilus lateralis
Tamiasciurus douglasii
Glaucomys sabrinus
Spermophilus beecheyi
Sorex trowbridgii
Tamias minimus
Microtus longicaudus
Peromyscus truei
Sorex vagrans
Peromyscus boylii
Neotoma cinerea
46
Total Individuals
811
611
507
494
487
312
137
118
64
23
19
16
10
9
3
2
Site Count
16
16
16
12
10
8
14
16
9
8
7
7
6
4
2
2
Appendix C. Total number of detections and site frequency of all bird species detected during point
count surveys conducted late May through early July across 16 units in the Lake Tahoe Basin, 2006-2011,
ranked in order of abundance.
Common Name
Mountain Chickadee
Red-breasted Nuthatch
Yellow-rumped Warbler
Golden-crowned Kinglet
Dark-eyed Junco
Western Tanager
Dusky Flycatcher
Evening Grosbeak
Steller's Jay
Fox Sparrow
Nashville Warbler
Brown Creeper
American Robin
Hermit Thrush
Warbling Vireo
Pine Siskin
Brown-headed Cowbird
Western Wood-Pewee
White-headed Woodpecker
Cassin's Finch
Townsend's Solitaire
Hairy Woodpecker
Hermit Warbler
MacGillivray's Warbler
White-breasted Nuthatch
Red Crossbill
Cassin's Vireo
Clark's Nutcracker
Northern Flicker
Olive-sided Flycatcher
Red-breasted Sapsucker
Williamson's Sapsucker
Chipping Sparrow
Black-backed Woodpecker
Band-tailed Pigeon
Ruby-crowned Kinglet
Pygmy Nuthatch
Wilson's Warbler
Scientific Name
Poecile gambeli
Sitta canadensis
Dendroica coronata
Regulus satrapa
Junco hyemalis
Piranga ludoviciana
Empidonax oberholseri
Coccothraustes vespertinus
Cyanocitta stelleri
Passerella iliaca
Oreothlypis ruficapilla
Certhia americana
Turdus migratorius
Catharus guttatus
Vireo gilvus
Carduelis pinus
Molothrus ater
Contopus sordidulus
Picoides albolarvatus
Carpodacus cassinii
Myadestes townsendi
Picoides villosus
Dendroica occidentalis
Oporornis tolmiei
Sitta carolinensis
Loxia curvirostra
Vireo cassinii
Nucifraga columbiana
Colaptes auratus
Contopus cooperi
Sphyrapicus ruber
Sphyrapicus thyroideus
Spizella passerina
Picoides arcticus
Columba fasciata
Regulus calendula
Sitta pygmaea
Wilsonia pusilla
47
Total Detections
1244
964
848
732
689
613
575
551
537
534
264
263
259
223
201
172
161
148
145
129
121
105
105
89
79
70
49
41
40
29
28
26
25
24
24
21
19
18
Site Count
16
16
16
16
16
16
16
16
16
16
15
16
16
16
13
16
12
16
16
15
15
15
12
15
13
9
7
4
12
9
13
7
9
9
7
2
6
5
Common Name
Pileated Woodpecker
Common Raven
Green-tailed Towhee
Mountain Quail
Brewer's Blackbird
Black-headed Grosbeak
House Wren
Mourning Dove
Hammond's Flycatcher
Calliope Hummingbird
Sooty Grouse
Orange-crowned Warbler
Red-shouldered Hawk
Cooper's Hawk
Black-throated Gray Warbler
European Starling
Golden-crowned Sparrow
Red-tailed Hawk
Red-winged Blackbird
Spotted Sandpiper
Rufous Hummingbird
Sharp-shinned Hawk
Northern Goshawk
Pine Grosbeak
Pacific Wren
Bewick's Wren
Downy Woodpecker
Great Horned Owl
Lincoln's Sparrow
Osprey
Song Sparrow
Townsend's Warbler
Western Bluebird
Yellow Warbler
Scientific Name
Dryocopus pileatus
Corvus corax
Pipilo chlorurus
Oreortyx pictus
Euphagus cyanocephalus
Pheucticus melanocephalus
Troglodytes aedon
Zenaida macroura
Empidonax hammondii
Stellula calliope
Dendragapus fuliginosus
Vermivora celata
Buteo lineatus
Accipiter cooperii
Dendroica nigrescens
Sturnus vulgaris
Zonotrichia atricapilla
Buteo jamaicensis
Agelaius phoeniceus
Actitis macularia
Selasphorus rufus
Accipiter striatus
Accipiter gentilis
Pinicola enucleator
Troglodytes pacificus
Thryomanes bewickii
Picoides pubescens
Bubo virginianus
Melospiza lincolnii
Pandion haliaetus
Melospiza melodia
Dendroica townsendi
Sialia mexicana
Dendroica petechia
48
Total Detections
17
15
9
8
7
7
7
7
6
6
6
4
4
4
3
3
3
3
3
3
2
2
2
2
2
1
1
1
1
1
1
1
1
1
Site Count
4
5
4
7
6
5
3
3
4
3
3
3
3
2
2
2
2
2
1
1
2
2
1
1
1
1
1
1
1
1
1
1
1
1