United States Department of Agriculture

Forest 

Service

Research Paper 

NRS-28

Northern 

Research Station April 2015

Response of Smooth Rock Skullcap 

(Scutellaria saxatilis), a Globally 

Rare Plant, to Fire

Cynthia D. Huebner

Kent Karriker
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Manuscript received for publication 10 November 2014

Abstract

Scutellaria saxatilis Riddell (smooth rock skullcap or rock skullcap, hereafter abbreviated as 

SRS), a herbaceous perennial in the mint family, is a globally rare (G3) plant. In West Virginia, 

SRS is categorized as an S2 species (imperiled and at high risk of extinction due to a very 

restricted range, very few [<20] documented occurrences, or steep declines). The purpose 

of this study was to determine the effects of fire on SRS in West Virginia. Two forested sites 

(70+ years of age) within the Monongahela National Forest with no evident disturbance and 

with SRS populations of >1,000 individuals were selected, one in a burn area and the other 

in a nonburn area. Sites were sampled in early September of 2008 and 2009 (pre-burn) and 

2010 and 2011 (postburn). The prescribed burn occurred in April and early May of 2010. A 

generalized linear mixed model with repeated measures and a spatial covariance matrix was 

used to determine the effects of the burn on SRS cover and associated variables including total 

vegetation cover, species diversity, bare ground, and litter cover. Bare ground cover increased 

and litter cover decreased in 2010 in response to the fire. Control and pre-burn sites did not 

differ significantly in terms of SRS cover over the 4-year period. The cover of SRS increased 

significantly in 2010 (first year postburn) compared to both pre-burn years, but decreased 

to pre-burn levels by 2011. Total cover of other understory vegetation increased significantly 

in 2010 and continued at 2010 levels in 2011 at the burn site. Thus, SRS has a temporary 

positive response to prescribed fire, but an increase in other ground vegetation may prevent a 

sustained positive response. 

The Authors

CYNTHIA D. HUEBNER is a Research Botanist with the U.S. Forest Service, Northern Research 

Station, Morgantown, WV.

KENT KARRIKER is an Ecosystems Group Leader with the Monongahela National Forest, U.S. 

Forest Service, Elkins, WV.

Cover Photo

Smooth rock skullcap, also known as rock skullcap, in flower. Photo by Ron Polgar, 

Monongahela National Forest.
1

INTRODUCTION

Smooth rock skullcap (Scutellaria saxatilis Riddell; 

Fig. 1), also known as rock skullcap and hereafter 

abbreviated as SRS, is a herbaceous perennial in the 

mint family (Lamiaceae), with decumbent stems which 

differentiate it from most other more common skullcaps. 

Its violet or white flowers are in one-sided terminal 

racemes, and the stem is spreading glandular in the lower 

part, mostly glabrous in the middle, and spreading hairy 

and glandular in the inflorescence (Epling 1939, Gleason 

and Cronquist 1993). Some populations in West 

Virginia may tend to be more glabrous and eglandular 

than in other states (Epling 1939, Strausbaugh and Core 

1977). SRS produces flowers as early as July and as late as 

September. Reproduction is via seeds or vegetatively via 

threadlike stolons (Epling 1939, Gleason and Cronquist 

1993). SRS is part of the Scutellaria ovata species-group, 

an American group in which the nutlets lack hairs and 

the corolla is relatively blue in color; slender stolons 

are often present at the base of the plant (Paton 1990). 

Members of this group are distributed in the eastern 

and south-central United States and Mexico and also 

include S. arguta Buckley, S. cardiophylla Engelm. & 

A. Gray, S. pallidiflora Epling, and S. ovata Hill. SRS 

is also genetically and morphologically similar to the 

S. havanensis species-group, which comprises spreading 

or weakly ascending herbs that have blue or purple 

corollas and are distributed in Florida, the West Indies, 

and Mexico (Paton 1990).

SRS may show a preference for rich, moist, and rocky 

woods (Olson et al. 2004, Terrell 1970) with dense 

shading, and is thought to have a negative response to a 

loss of forest canopy (Dolan 2004, Olson et al. 2004). 

However, whether adequate soil moisture, shade, or 

some other factor is more important is not clear. Some 

populations are located in more open areas, such as 

along roads (Wofford and Dennis 1976), suggesting 

that a dense canopy is not a requirement for successful 

establishment. The requirement for high moisture also 

may be inaccurate; populations of SRS are associated 

with dry, limestone bluffs, crevices, and exposures in 

Giles County, VA (Cooperrider and Thorne 1964), 

dry hills in Ohio, and arid cliffs in Kentucky (Epling 

1939). Yet SRS is also found in moist hemlock-beechFigure 1.—Scutellaria saxatilis in flower. Photo by Ron Polgar, 

Monongahela National Forest.

rhododendron forests in Giles County (Cooperrider and 

Thorne 1964). In addition, SRS is found in damp to dry 

soil of deciduous rocky woods along Skyline Drive in 

Warren County, VA (Mazzeo 1972). SRS has also been 

associated with the rare upland red spruce community 

type in West Virginia (Byers et al. 2010). SRS does not 

appear to compete well with other plant species (Dolan 

2004), and rockiness appears to be the most shared 

habitat characteristic described in the literature.

SRS is a globally rare (G3) plant species. A G3 ranking is 

defined as vulnerable and at moderate risk of extinction 

due to a restricted range. Species with this ranking have 

relatively few known populations (usually <80) and 

show evidence of recent and widespread decline. SRS is 

currently found in 16 states in the eastern United States. 

It is listed as reported without persuasive evidence of 

its occurrence in Arkansas, District of Columbia, New 

Jersey, and South Carolina and as possibly extirpated 

in Delaware. SRS is listed as state endangered in 

Alabama, Georgia, Indiana, Maryland, North Carolina, 

and Pennsylvania. It is listed as threatened in Ohio, 

Tennessee, and Virginia, and as rare in Kentucky and 

West Virginia (NatureServe 2014b). This species was 

also noted in Missouri in Miller County in 1883 by 

an amateur botanist, but the species identification has 

been questioned (Bush 1926) or the species may now 

be extirpated. The Hoosier (Indiana), Monongahela 

(West Virginia), and Wayne (Ohio) Region 9 National 

Forests list SRS as a Regional Forester’s Sensitive 
2

species. In 1966, SRS was described as frequent on 

wet banks throughout West Virginia (Clarkson 1966). 

In 2004, SRS was categorized as an S1 species (≤5 

known occurrences in the state or only a few remaining 

individuals) in West Virginia (Dolan 2004). In 2005, 

however, SRS was ranked as S2 (E. Byers, West Virginia 

Division of Natural Resources, pers. comm.), which 

is defined as imperiled and at high risk of extinction 

in West Virginia due to a very restricted range, very 

few (<20) documented occurrences, or steep declines 

(NatureServe 2014b). It is likely that this new ranking 

reflects the increase in inventory effort for this species in 

West Virginia (E. Byers, pers. comm.).

Prescribed burns by Native Americans and early 

European settlers were used to maintain open areas, 

savannas, and oak-dominated forests (Abrams 1991, 

Brose et al. 2001). Starting in the 1920s, a policy of fire 

suppression was widely adopted and has been blamed 

for the mesophication of Eastern forests, a positive 

feedback cycle in which shade-tolerant and fire-sensitive 

species increase in abundance relative to shade-intolerant 

species (Brose et al. 2001, Nowacki and Abrams 2008). 

Prescribed burns are now being used more frequently 

in Eastern ecosystems to restore oak savannas and 

woodlands as well as improve oak regeneration in 

forested areas. The latter use of fire is often combined 

with shelterwood harvesting (Barnes and Van Lear 

1998, Brose and Van Lear 1998, Brose et al. 2001). 

Two species dependent on shale-barren communities, 

which may be dependent on fire to prevent woody 

species encroachment, are Trifolium virginicum Small ex 

Small & Vail (Kates Mountain clover), another Regional 

Forester’s Sensitive plant species in West Virginia, and 

Boechera serotina (E.S. Steele) Windham & Al-Shehbaz 

(shale-barren rockcress), a federally endangered species in 

West Virginia. Whether fire is needed to maintain shalebarren communities located in harsh environmental 

conditions is uncertain. The loss of species in these 

communities is generally associated with the loss of their 

habitat to development (e.g., roads, housing, urban 

sprawl), not necessarily to a lack of fire (Bartgis 1987, 

Nott 2006).

In contrast, S. floridana Champm. (Florida skullcap) is 

an example of a federally threatened rock skullcap found 

in longleaf pine-grassland habitats. Fire suppression and 

silvicultural activity are thought to be reasons for its 

decline (Van Lear et al. 2005, Walker 1993). Whether 

or not SRS’ habitat loss is more closely associated with 

a lack of fire (like S. floridana) or development (possibly 

similar to T. virginicum and B. serotina) is not known. 

SRS’ apparent preferred habitat of rocky wet slopes may 

not be fire dependent, though oaks do dominate the sites 

and mesophication of these oak forests may be connected 

to SRS’ decline. However, there is also weak evidence 

that SRS may decrease in abundance in response to a 

canopy opening (Dolan 2004, Olson et al. 2004). Given 

that fire may increase openings in the subcanopy and 

canopy layers of forests (Canham et al. 1990), the impact 

of fire on SRS may be negative, depending on the degree 

of canopy cover reduction.

The purpose of this study was to determine the effects 

of fire on SRS in West Virginia. Fire typically reduces 

the cover of dominant species (Hannah 1987) and may 

temporarily increase resources (nutrients; Certini 2005). 

However, fire may also reduce canopy cover by causing 

subcanopy or canopy tree deaths, thereby increasing 

the light reaching the forest floor through canopy gaps 

(Canham et al. 1990). Because there has been some 

evidence of a negative response of SRS to a decrease in 

canopy cover (Dolan 2004, Olson 2004), we tentatively 

predicted that SRS cover would decrease in response to 

fire.
3

METHODS

Study Area

The study was located in Pocahontas County in the 

Greenbrier Ranger District of the Monongahela 

National Forest (Fig. 2). The site is part of an oak 

forest regeneration project that is associated with a 

nearby savanna restoration project called the Ramshorn 

Prescribed Burn project. There, SRS is found in about 

45 separate locations (patches of one to thousands of 

individuals ≥5 m apart) in planned prescribed burn areas, 

as well as in 80 separate locations in adjacent nonburn 

(control) areas. The savannas planned for restoration 

are located along the ridges, but both ridges and slopes 

were intended to be burned, hence the concern over the 

possible impact on the SRS populations. Site selection 

was made from available areas with >1,000 individuals, 

and, thus, our statistical inference level is for sites with 

more than 1,000 SRS individuals. There were two to 

select from within the locations scheduled to be burned 

during the time of the study, one that was south- to 

southwest-facing and the other east- to northeast-facing. 

We found two sites in the nonburn areas that were close 

in age (≥70 years of age) to the proposed burn sites and 

that faced the same directions. The east- to northeastfacing slope of the nonburn area was located in a younger 

forest than the corresponding paired burn site, and had 

a very narrow area of SRS, so this site did not qualify as 

a replicate site. Thus, only two sites composed of forests 

≥70 years of age, one in the burn area and the other in 

the nonburn area, were selected. Both had south- to 

southwest-facing slopes. Neither showed evidence of 

disturbance. The burn site was located along a ravine 

off Stony Run in the Chestnut Ridge area; the control 

site was located in a ravine off Sutton Run, also in the 

Chestnut Ridge area, but about 5 km from the burn site. 

We thus consider these sites separate SRS populations or 

element occurrences as defined by NatureServe (2014a).

The sites were sampled the first week of September in 

2008, 2009, 2010, and 2011, and the prescribed burn 

occurred in April and early May of 2010. Fire intensity 

on the slopes was not monitored. Mortality of some large 

canopy trees on the slope and on the ridge indicates that 

the fire was a relatively hot burn in patches.

Figure 2.—Study area showing general location within the state and general location within the Monongahela 

National Forest.
4

Sampling Design

A stratified-random sampling design with two plot sizes 

was used at both sites (Fig. 3). A 100-m transect was set 

up in a central location along the contour of the slope 

where SRS was relatively abundant. Universal Transverse 

Mercator (North American Datum 83) coordinates were 

taken at the beginning and end of the transect, and a 

transect bearing was noted. It is Monongahela National 

Forest’s policy not to publish location information of 

threatened species, but we may be able to provide this 

information upon reviewed request. Slope inclination 

was 20-25 percent for both sites. Every 10 m along each 

transect starting from the beginning, a 1-m2

 circular 

plot area was marked with a stake chaser and sampled 

systematically. At random distances >3 m and <50 m, 

one circular quadrat was placed uphill perpendicular to 

the transect and one circular plot was set up downhill 

perpendicular to the transect. One of the uphill or 

downhill plots was 1 m2

 in area and the other one was 

10 m2

 in area. The larger and smaller plots alternated 

in terms of being upslope or downslope, with the first 

selection of upslope or downslope being randomly 

chosen. Thirty plots were sampled at each site in each 

year except 2011. In 2011, three plots were not sampled 

at the burn site to avoid unsafe conditions due to their 

proximity to dead and falling canopy trees. This sampling 

method was selected because it is among the best at 

documenting rare species as well as the dominant plant 

species (Huebner 2007).

Cover was estimated in each plot for all herbaceous 

plants rooted in the plot and all foliage of vines and 

shrubs falling within the plot boundaries with no 

requirement that they be rooted in the plot. Cover 

values of species in the 10-m2

 plots were converted to 

cover per 1 m2

 for the calculation of relative cover and 

importance values for each species and for subsequent 

statistical analyses. Vegetation cover data for each plot 

could potentially sum to >100 percent. Percent cover of 

litter, percent cover of bare ground, and litter depth were 

also determined at each plot. These data were collected 

in conjunction with rock, moss, and coarse woody debris 

cover, which summed to 100 percent. From these data, 

SRS cover, total vegetation cover excluding SRS, and 

diversity using the Shannon (H ́) and Simpson indices 

excluding SRS were determined. Most SRS plants were 

still in flower and some were in fruit each year at the time 

of sampling. Because of the vegetative growth associated 

with SRS, cover estimates were considered more accurate 

than stem counts. Nonetheless, where cover was high, 

stem counts also tended to be high, based on an initial 

comparison of cover and stem counts measured in 2008 

at both sites. Nomenclature of plant species follows the 

Interagency Taxonomic Information System (2014).

Statistical Analyses

Because of the lack of site replication and the focus on 

population-level effects rather than community-level 

effects, the plots were used as replicates to determine 

the effect of the burn on SRS. Such an approach, 

though not ideal (Hurlbert 1984, Palmer 1987), is 

not uncommon in population studies of threatened 

species or in large-scale community studies (Elzinga et 

al. 2001, Keith 2000, Oksanen 2001). Nevertheless, 

we addressed the potential for spatial autocorrelation 

due to pseudoreplication by including an autoregressive 

(AR(1)) covariance matrix associated with plots as a 

random variable. A generalized linear mixed model, 

which included both the spatial covariance matrix and an 

AR(1) covariance matrix (for the year-to-year or repeated 

sampling), with a lognormal distribution and identity 

link function (GLIMMIX, SAS 9.4; SAS Institute Inc., 

Cary, NC) was used to determine the effects of the burn 

on SRS, total vegetation, bare ground, and litter cover. 

A Gaussian distribution with an identity link function 

was the best fit for comparing the effect of the burn on 

Figure 3.—Stratified-random sampling design using a 

100-m-long transect.
5

herb, shrub, and vine diversity. The same models were 

used to compare each of the variables (herb, shrub, and 

vine diversity; and SRS, total vegetation bare ground, 

and litter cover) at the control site across the 4 years. 

Plot was the only random effect and the fixed effects 

were burn or no-burn and year. The selection of AR(1) 

as the covariance structure and the distributions were 

determined from best fit statistics, including deviance, 

log likelihood, and Pearson’s chi square, and by 

evaluating each variable under different distributions 

with univariate statistics. Pearson residuals were 

evaluated as well as residual vs. predicted value plots. 

All means were compared by using a Tukey’s multiple 

comparisons test. We conducted the same analyses for all 

plots and separately for just the plots containing SRS.

Using the above analyses we chose not to do a direct 

statistical comparison of burn-site plots with controlsite plots but instead to use the control site as a separate 

measure of other possible factors not associated with 

fire that could be affecting SRS over the study period. 

We then analyzed these data by using a Before-AfterControl-Impact (BACI) analysis for each variable to 

determine if there were potential significant site (control 

vs. burn) conditions over the period of the study 

unrelated to the burn treatment that may confound our 

conclusions about the effect of fire. We used the same 

model statements within our GLIMMIX models above, 

including the covariance matrix for year-to-year sampling 

of the same sites and the spatial covariance matrix for 

possible pseudoreplication. But we also included the 

control site and the site type (burn or control) and 

year (2008, 2009, 2010, or 2011) interaction term and 

used contrast statements to compare site type and year 

combinations. We first compared the pretreatment years 

(2008, 2009), using all data from both sites. Second, we 

analyzed data from the nonburn years: all data from the 

pretreatment years as well as data from 2010 and 2011 

from the control site. We then compared the postburn 

years, which included both 2010 and 2011 data from 

the burn site, with the nonburn-year data (2008 and 

2009 from the burn and control site, and 2010 and 2011 

only from the control site). Finally, we contrasted only 

data from 2010 from the burn site with all nonburnyear data. Significant differences among pretreatment 

years or nonburn years would indicate that there may 

be important site or temporal variables unrelated to 

the burn. This analysis assumes that site type and year 

variation are equal across sites and years (Schwarz 2002).

RESULTS AND DISCUSSION

Bare Ground and Litter Cover

The prescribed burn affected the burn site by increasing 

bare ground and decreasing litter. At the burn site, 

bare ground cover differed significantly (F = 7.39, P = 

0.0002) among the years. There was much more bare 

ground on average in 2010 than in either pretreatment 

year or in the postburn year 2011 (Fig. 4a). Bare ground 

cover at the control site did not differ significantly by 

year (F = 0.12, P = 0.95; Fig. 4c). Litter cover differed 

significantly (F = 5.89, P = 0.0011) between 2009 and 

both postburn years at the burn site (Fig. 4b). There 

was no significant difference in litter cover (F = 0.29, 

P = 0.83) at the control site (Fig. 4d). These trends for 

bare ground and litter were the same when evaluating 

only the plots containing SRS (Fig. 4a-d). Though not 

presented, rock cover increased substantially in 2011 at 

the burn site, which may explain the lower bare ground 

cover for that year. Although we defined bare ground 

as mineral soil and not duff, some organic material 

may have been included in our cover estimates of 

bare ground. The organic material could have burned, 

possibly revealing a rock layer below. It is also possible 

that precipitation or other small-scale disturbances may 

have removed a superficial layer of soil between 2010 

and 2011, revealing more underlying rock. In contrast, 

bare ground cover was not lower in 2011 compared to 

2010 at the control site.

SRS Cover

The burn site had more plots with SRS (13-15 plots) 

than the control site (9-11 plots). At both sites, plots 

that did not contain SRS in a given year generally did 

not gain SRS the following year; 74-95 percent of all 

plots with no SRS remained without SRS throughout 

the study period. Thus, most changes in SRS abundance 

at the sites are associated with the individual plots 

containing SRS, which supports the need to evaluate the 

plots containing SRS separately as well as with the other 

plots. A large increase in SRS abundance on the burn site 
6

Figure 4.—Comparison, with standard errors, of (a) bare ground cover and (b) litter cover at the burn site and 

(c) bare ground cover and (d) litter cover at the control site. Statistical comparisons across years were made by 

using a generalized linear mixed model (GLIMMIX) with autoregressive covariance matrix, gamma distribution, 

and a log link function. Bars with different letters within the same graph are significantly different at P < 0.05. 

occurred the first year after the burn. Abundance of SRS 

also increased at the control site between 2008 and 2009. 

There was a relatively large decrease in abundance of SRS 

between 2008 and 2009 at the burn site and between 

2010 and 2011 at the control site (Table 1). The increase 

in abundance of SRS in 2009 at the control site and the 

decrease in abundance at the burn site in 2009 cannot be 

attributed to any known events, suggesting year-to-year 

abundance of SRS typically may be variable. The decrease 

in abundance of SRS at the control site in 2011 may be 

linked to a possible high precipitation event. According 

to weather data from a nearby weather station in Frost, 

WV, the total annual precipitation was 107.98, 117.17, 

117.50, and 132.21 cm in 2008, 2009, 2010, and 

2011, respectively (National Oceanic and Atmospheric 

Administration [NOAA], National Climatic Data Center 
7

in the models of only the SRS plots at the control site 

showed no significant difference in the years (F = 1.59, 

P = 0.24; Fig. 5d). The burn site had significantly greater 

(about twice as much) SRS cover than the control site 

in 2010 and 2011 (Fig. 5a-d). There was also a decline 

in SRS cover in 2011, though insignificant, at the 

control site (Fig. 5c), which may indicate that conditions 

associated with 2011, or just with the control site, were 

not optimal for SRS growth, perhaps due to a high 

precipitation event as discussed above. If we assume that 

the unknown conditions were having a negative impact 

on SRS at both sites, the burn appears to have continued 

to benefit SRS in 2011 as well as 2010 in spite of this 

unknown condition. We reached this conclusion because 

of the higher SRS percent cover at the burn site in 2011 

compared to the control site. Nonetheless, the control 

site’s 2009 SRS cover was nearly as high as the burn 

site’s 2010 SRS cover. It is possible that we are simply 

looking at extreme variations in year-to-year SRS cover at 

two sites.

Our focus on abundance in this study, unfortunately, 

does not tell us much about SRS’s fitness in response 

to the burn. It would be useful to know if the weak 

Table 1.—Number of SRS plots showing change in SRS abundance, by site and year; and 

percentage of non-SRS plots that contained no SRS the following year 

2008-2009

Site

Total number of 

plots containing 

SRS, 2008 Increase Decrease

No 

change

Proportion of 

plots with 0 SRS 

in both years 

Total number of 

plots containing 

SRS, 2009

 Burn 15 3 11 1 93% 15

 Control 9 7 2 0 86% 11

2009-2010

Increase Decrease

No 

change

Proportion of 

plots with 0 SRS 

in both years 

Total number of 

plots containing 

SRS, 2010

 Burn 9 3 2 94% 13

 Control 3 7 1 74% 10

2010-2011

Increase Decrease

No 

change

Proportion of 

plots with 0 SRS 

in both years 

Total number of 

plots containing 

SRS, 2011

 Burn 1 11 0 87% 14

 Control 2 8 0 95% 9

[NCDC] 2014). Unusually high precipitation occurred 

in March and April of 2011 compared to the same 

period in previous years and could have resulted in some 

flooding in the ravines near the slopes of our study sites, 

potentially impeding the establishment of many plants 

on the slopes early in the growing season.

Abundance of SRS did not differ significantly among 

all 4 years of sampling at the burn (F = 0.31, P = 0.82) 

and control (F = 0.04, P = 0.99) sites (Fig. 5a and c) 

when evaluating all plots together. Because there was 

an obvious decline in SRS cover from 2010 to 2011 at 

both the burn and control sites (Fig. 5a and c), we also 

ran the models without 2011 data. After removal of the 

2011 data at the burn sites, SRS cover when evaluating 

all burn site plots was insignificant (F = 0.42, P = 0.66), 

though there was a trend for 2010 (first postburn year) 

to have more SRS cover than 2009 (Fig. 5b). There 

was no similar trend for the control site (F = 0.64, P = 

0.53). Evaluating only the burn site plots with SRS, and 

excluding 2011, did show a significant positive effect of 

the burn (F = 5.51, P = 0.011), with significantly higher 

SRS abundance in 2010 than 2009 in plots with SRS 

(Fig. 5b). Including only the years 2008, 2009, and 2010 
8

Figure 5.—Comparison, with standard errors, of SRS abundance at (a) the burn site for all 4 years, (b) the burn 

site removing 2011 data from the analyses, (c) the control site for all 4 years, and (d) the control site removing 

2011 from the analyses. Statistical comparisons across years were made by using a generalized linear mixed 

model (GLIMMIX) with autoregressive covariance matrix, gamma distribution, and a log link function. Bars with 

different letters within the same graph are significantly different at < 0.05.

positive initial response of SRS to fire was primarily 

due to sprouting or if it may have also stimulated more 

seed production and seedling survival or even seed 

germination from any existing seed bank. The fact that 

most increases appear to be associated with the same 

plots suggests that most increases are due to sprouting 

and not new seedlings. Nonetheless, if flowering and 

seed set increased in response to the fire, the consequent 

increase in genetic diversity may be an additional reason 

to burn where SRS populations are located. Improved 

genetic integrity can make catastrophic population 

declines due to a pathogen or disease less likely for a rare 

species, assuming the species is a successful outcrosser. 

Other Scutellaria species have known pollinator 
9

generalists and specialists, indicating that they generally 

outcross but also that those in specialized habitats tend 

to have specialist pollinators (Miller-Struttmann 2013, 

Pitts-Singer et al. 2002). If such specialist pollinators 

are rare, rare plants may further decline. There is at least 

one Scutellaria species with individuals that have only 

cleistogamous flowers or are a mixture of cleistogamous 

and chasmogamous flowers (Sun 1999). We did not 

see evidence of cleistogamy in SRS and did not find 

any mention of it in the literature; SRS’s mating system 

needs further study. Fire may also influence flowering 

phenology of SRS or other species at the site. Platt 

et al. (1988) found that a prescribed burn in Florida 

occurring in April-August (i.e., growing season) delayed, 

but increased and synchronized, flowering of dominant 

species.

Species Composition

There were 26 total herb, shrub, and vine species in 

both 2008 and 2009 at the burn site. After the burn 

there were 34 species in 2010, but once again 26 species 

in 2011. Species diversity for herbs, shrubs, and vines 

collectively differed significantly (F = 2.81, P = 0.044) 

at the burn site among the 4 years with 2008 being less 

diverse than 2011, and there was a trend for increasing 

diversity in both postburn years compared with the 

pretreatment years (Fig. 6a). This significant difference in 

diversity is lost when evaluating only the SRS plots (F = 

0.16, P = 0.92; Fig. 6a). The burn site in 2008 and 2009 

shared similar species with the highest importance values 

and SRS remained in the top three most important 

species in every year. In 2010 and 2011, after the burn, 

weedier species, such as Erechtites hieraciifolius (L.) Raf. 

ex DC., Rubus L. sp., and Phytolacca americana L., were 

ranked higher in importance than in previous years, 

making the list of the top 10 most important species after 

the burn (Table 2). These species were most dominant 

in 2011. SRS had a lower importance ranking in 2011 

compared to 2010, possibly in response to the increase 

in dominant weedier species. In both postburn years, but 

more so in 2011, there were weedy species present after 

the burn that were not present before the burn, including 

Taraxacum officinale F.H. Wigg., Packera aurea (L.) 

Á.Löve & D. Löve, and Solanum dulcamara L.

Figure 6.—Comparison, with standard errors, of species diversity (Shannon H’ index) for all 4 years at (a) the 

burn site and (b) the control site. Statistical comparisons across years were made by using a generalized linear 

mixed model (GLIMMIX) with autoregressive covariance matrix, Gaussian distribution, and an identity link 

function. Bars with different letters within the same graph are significantly different at P < 0.05.
10

Table 2.—Top 10 species at each site during each year by importance value

Burn site

Pretreatment years Postburn years

Species 2008† 2009‡ Species 2010† 2011‡

Scutellaria saxatillis Riddle§ 9.60* 6.98* Ageratina altissima var. altissima 10.47* 14.27*

Aristolochia macrophylla Lam. 7.00* 7.70* Scutellaria saxatilis 10.04* 3.76*

Ageratina altissima var. altissima (L.) 

King & H. Rob

1.95* 3.28* Erechtites hieraciifolia (L.) Raf. ex DC 2.71* 4.49*

Arisaema triphyllum (L.) Schott. 1.77* 5.63* Galium triflorum Michx. 1.95* 0.64*

Solidago curtisii Torr. & A. Gray 1.59* 1.32* Rubus L. sp. 1.33* 1.52*

Galium triflorum 1.36* 2.12* Carex appalachica J.M. Webber & P.W. Ball 0.67* 0.016

Eurybia divaricata (L.) G.L. Nesom 0.71* 0.70* Ribes L. sp. 0.57* 0.10

Carex L. sp. 0.50* 0.13 Solidago curtisii 0.44* 0.62*

Impatiens L. sp. 0.31* 0.23* Sambucus L. sp. 0.25* 0.10

Hamamelis virginiana L. 0.25* 0.074 Impatiens sp. 0.24* 0.33*

Elymus hystrix L. 0.010 0.86* Phytolacca americana 0.22 0.24*

Panax quinquefolius L. 0.0 0.18* Pilea pumila (L.) A. Gray 0.042 0.18*

Rubus odoratus L. 0.064 0.16*

Control site

Pretreatment years Postburn years

Species 2008 2009 Species 2010 2011

Solidago curtisii 5.60* 3.77* Scutellaria saxatilis 5.70* 2.45*

Ageratina altissima var. altissima 3.84* 2.77* Ageratina altissima var. altissima 5.19* 2.37*

Aristolochia macrophylla 3.74* 3.07* Solidago curtissii 4.93* 7.08*

Scutellaria saxatilis 3.71* 6.38* Aristolochia macrophylla 3.60* 6.37*

Galium triflorum 2.22* 4.30* Impatiens sp. 2.02* 1.76*

Laportea canadensis (L.) Wedd. 1.16* 0.0 Galium triflorum 1.72* 0.61*

Pilea pumila 0.68* 0.0 Eurybia divaricata 1.03* 0.96*

Arabis laevigata (Muhl.ex Willd.) Poir. 0.57* 0.15 Rubus sp. 0.59* 0.075

Eurybia divaricata 0.56* 0.67* Thalictrum L. sp. 0.51* 0.86*

Ribes sp. 0.55* 0.08 Pilea pumila 0.41* 0.48

Impatiens sp. 0.32 3.00* Arabis laevigata 0.097 0.69*

Arisaema triphyllum 0.13 1.72* Hydrophyllum virginianum L. 0.0 0.57*

Hydrophyllum virginianum 0.45 0.65*

Osmorhiza claytonii (Michx.) C.B. Clarke 0.034 0.56* 

† Species are listed from highest to lowest importance value at each site for the first year of the two pretreatment years and the first year of the two 

postburn years.

‡ Even if a species was not among the same top 10 in the preceding year, the importance value is given. The actual top 10 for each year have an 

asterisk (*) by their importance values.

§ Nomenclature follows the Interagency Taxonomic Information System (2014).
11

At the control site, there were 35 species in 2008, 31 in 

2009, 34 in 2010, and 19 in 2011. Herb, shrub, and 

vine diversity did not differ significantly (F = 0.62, P = 

0.60) over the 4 years at the control site (Fig. 6b) though 

diversity declined in 2011. The same was true when 

evaluating only the SRS plots. Unlike the burn site, there 

was no increase in dominance of particular species, such 

as Rubus sp., at the control site. Indeed, Rubus sp. also 

declined in importance between 2010 and 2011 at the 

control site. The high levels of precipitation in March 

and April of 2011 (NOAA, NCDC 2014) in the area 

may have prevented or slowed new spring growth. The 

control site may have experienced more rapid rainfall 

than the burn site, but we have no evidence of this. 

Plants on the burn site could have been more likely to 

survive or grow, even with heavy, leaching rain, because 

of remnant increases in nutrients after the burn. Again, 

however, our data cannot confirm this.

Total Vegetation Cover

There was significantly (F = 17.82, P < 0.0001) more 

total understory vegetation cover for 2011 compared 

with both pretreatment years at the burn sites. Though 

not significant, there was a trend to higher cover values 

in the postburn years when evaluating the SRS plots 

(Fig. 7a). In contrast, there was no significant (F = 

0.05, P = 0.99) difference in total vegetation cover at 

the control site across the years (Fig. 7b). Every year at 

the control site had less cover than the postburn years 

at the burn site (Fig. 7a and b). The increase in total 

vegetation cover at the burn site, based on the species 

composition information, is due to both an increase 

in species richness and an increase in abundance or 

dominance of a few species, especially in 2011. Total 

vegetation cover increased at the burn site but decreased 

at the control site between 2010 and 2011. Thus, in spite 

of the unmeasured variable that appeared to negatively 

affect SRS abundance at the control site and possibly 

also at the burn site between 2010 and 2011, other 

vegetation, especially more weedy vegetation abundance, 

responded positively to the burn. This positive response 

was sustained for an additional year at the burn site. 

An increase in dense understory layers, dominated by 

a few species, such as Rubus sp., Kalmia latifolia L., or 

Dennstaedtia punctilobula (Michx.) T. Moore, is not 

an uncommon response to a combined fire and canopy 

Figure 7.—Comparison, with standard errors, of total vegetation cover for all 4 years at (a) the burn site and 

(b) the control site. Statistical comparisons across years were made by using a generalized linear mixed model 

(GLIMMIX) with autoregressive covariance matrix, lognormal distribution, and an identity link function. Bars 

with different letters within the same graph are significantly different at P < 0.05. 
12

disturbance (Royo and Carson 2006), even though 

fire is often used both to reduce competing vegetation 

and to open the canopy for increased regeneration of 

certain species, such as oaks (Brose et al. 2001). Our 

burn site currently does not appear to be at risk of dense 

understory layer formation, but does show evidence of 

a more productive site in response to the burn, with all 

plant species benefitting somewhat and a few benefitting 

more than most.

Timing of the burn may also be a factor in the increase 

in productivity of the more dominant species. Although 

most spring burns are meant to occur before the start 

of the growing season, an April-May burn may have 

affected some early nondormant perennial plants, 

resulting in an increase in clonal growth. If apical 

meristems are nondormant, they may die in a burn, 

leading to the release of multiple secondary meristems 

and a subsequent flush of growth of competing 

vegetation (Platt et al. 1988). This flush of growth 

is most likely to occur if the burn is severe. Low- or 

medium-intensity spring burns do not differ in stem 

density or stocking after a burn from low-, medium-, or 

even high-intensity winter burns (Brose et al. 1999).

Based on our findings, fire may benefit SRS beyond 

one growing season only if it can be applied at a low 

enough intensity to ensure no or little increase in canopy 

opening. More frequent fires instead of less intense fires 

may help reduce competing vegetation. But if SRS is 

sensitive to repeat burning, they may also negatively 

affect SRS by directly reducing its abundance, given the 

annual burn that our findings suggest would be required 

to reduce the increase in cover of other species competing 

with SRS. Several fire-sensitive plants, including spring 

herbs (e.g., Maianthemum racemosum ssp.racemosum

(L.) Link), are unable to recover after short fire intervals 

(Gary and Morrison 1995, Hutchinson et al. 2005). SRS 

is not a fire-sensitive species based on its response to one 

burn; however, we do not know how it would respond to 

multiple burns.

The decline in SRS in 2011 at the burn site, however, may 

be due to both an increase in competing vegetation and the 

unknown factor associated with SRS’s decline at the control 

site in 2011. The decline in most species, not just SRS, in 

2011 at the control site suggests that this factor may be sitespecific or that positive resource changes (increased light 

and nutrients) related to the burn were enough for most 

species, especially dominant weedy species, to overcome 

negative factors (e.g., precipitation levels) associated with 

that year. Our study supports previous observations that 

SRS may not compete well with other plants (Dolan 

2004). Thus, though there was an initial growth increase 

of SRS after burning, this positive response could not be 

sustained beyond a year.

BACI Results

The BACI results supported the GLIMMIX analyses 

(Table 3). Total herb, shrub, and vine cover, SRS 

cover, bare ground cover, and litter cover did not differ 

significantly in terms of pretreatment and all nonburn 

years. A lack of significance among the pretreatment 

and nonburn year data indicates that, at least before the 

burn, there were no site or environmental factors that 

influenced these variables. The contrasts of all postburn 

year data, including evaluating the two postburn years 

separately, and all nonburn years for these variables 

agreed with the GLIMMIX results that compared the 

two site types separately. Litter and total herb, shrub, and 

vine cover were significantly greater in both postburn 

years than in the pretreatment years. Bare ground 

cover was significantly greater in 2010 than in the 

pretreatment years. Herb, shrub, and vine diversity did 

differ significantly after the BACI analysis in terms of the 

pretreatment and nonburn year data. This outcome may 

be explained by existing species composition differences 

between the two sites and the decline in species richness 

in 2011 at the control site. Thus, the lack of an impact of 

the burn on plant species diversity cannot be separated 

from site or year-to-year environmental factors. When 

evaluating only the plots with SRS, there were no 

differences among the pretreatment years for any of the 

variables, including herb, shrub, and vine diversity. The 

absence of differences in nonburn year diversity and 

pretreatment data indicates that the SRS plots differed 

less compositionally between the control and burn 

sites than did all the plots together. Pretreatment and 

nonburn years did differ significantly from the postburn 

year 2010 for SRS cover when only plots with SRS were 

evaluated, agreeing with the GLIMMIX results.
13

Table 3.—BACI analysis

All plots (control and burn sites)

Contrast type Variable F P-value

Pretreatment years (2008 and 2009)

SRS cover 1.26 0.26

Total veg. cover 1.43 0.23

Diversity 5.92 0.016

Bare ground cover 0.46 0.50

Litter cover 0.19 0.66

All nonburn years (2008 and 2009 for

 both sites, and 2010 and 2011 for the

 control site)

SRS cover 1.41 0.24

Total veg. cover 1.77 0.23

Diversity 5.12 0.025

Bare ground cover 0.83 0.36

Litter cover 0.86 0.36

Postburn vs. nonburn years (2010 and

 2011 for the burn site vs. 2008, 2009,

 2010, and 2011 for the control site)

SRS cover 1.17 0.28

Total veg. cover 12.58 0.0005

Diversity 0.10 0.76

Bare ground cover 1.03 0.31

Litter cover 23.36 <0.0001

Postburn 2010 vs. nonburn years (2010

 data for the burn site vs. 2008, 2009,

 2010, and 2011 for the control site)

SRS cover 0.84 0.36

Total veg. cover 3.62 0.059

Diversity 0.18 0.67

Bare ground cover 8.13 0.0049

Litter cover 17.66 <0.0001

SRS plots only (control and burn sites)

Contrast type Variable F P-value

Pretreatment years (2008 and 2009)

SRS cover 0.35 0.56

Total veg. cover 2.80 0.10

Diversity 1.27 0.26

Bare ground cover 2.37 0.13

Litter cover 0.05 0.82

All nonburn years (2008 and 2009 for

 both sites, and 2010 and 2011 for the

 control site)

SRS cover 0.65 0.42

Total veg. cover 1.62 0.21

Diversity 0.47 0.50

Bare ground cover 0.06 0.80

Litter cover 0.82 0.37

Postburn vs. nonburn years (2010 and 2011

 data for the burn site vs. 2008, 2009,

 2010, and 2011 for the control site)

SRS cover 1.34 0.25

Total veg. cover 4.84 0.032

Diversity 0.05 0.83

Bare ground cover 4.52 0.038

Litter cover 3.55 0.065

Postburn 2010 vs. nonburn years (2010,

 data for the burn site vs. 2008, 2009,

 2010, and 2011 for the control site)

SRS cover 4.67 0.035

Total veg. cover 0.57 0.45

Diversity 0.15 0.70

Bare ground cover 7.43 0.0085

Litter cover 2.04 0.16
14

CONCLUSIONS

Based on our results, a positive response of SRS 

abundance cannot be sustained for more than one 

growing season due to subsequent increases in other 

dominant plant species. The increase in other dominant 

plant species appeared to result from an increase in 

canopy opening due to overstory tree mortality after 

the burn. It is conceivable that a decline in SRS could 

occur if the prescribed burns continue to be relatively 

intense, leading to significant tree mortality and canopy 

opening. Such intense fires may be necessary on the 

ridge tops in order to successfully restore a savanna, 

but are not necessary for oak regeneration management 

(Schlesinger et al. 1993) on the slopes. Not burning is 

not an ideal option either, because SRS does benefit, at 

least initially, from a burn, and it is well documented 

that fire can promote oak regeneration (Abrams 1992, 

Barnes and Van Lear 1998, Brose and Van Lear 1998). It 

may be possible to burn the ridge tops first and then the 

slopes when conditions will allow for a less intense burn. 

Moreover, if burns are likely to be severe, we suggest 

that the slopes be burned earlier in the spring to reduce 

the risk of overlap with the growing season when apical 

meristems are no longer dormant (Brose et al. 1999, 

Platt et al. 1988). It is possible the initial positive growth 

response of SRS after the burn was due to the release of 

secondary meristems, and that SRS could not compete 

with other species that also benefitted from released 

secondary meristems.

We are concerned about the evident increase in some of 

the weedier species. We did not find any invasive exotic 

plants at either of the sites but are aware that Alliaria 

petiolata (M. Bieb.) Cavara & Grande and other invasive 

plants are in the vicinity. Slopes subjected to an intensive 

burn that opens the tree canopy will be more vulnerable 

to invasion, if there is a nearby propagule source 

(Glasgow and Matlack 2007).

Finally, information on any existing SRS seedbank and 

how SRS responds to fire in terms of its fitness (seed 

production and subsequent germination and seedling 

survival after a burn) will improve our ability to formulate 

a management strategy for this species. Repeating our SRS 

abundance research either at the same sites or different 

sites is highly recommended before deciding on a final 

SRS management strategy, especially given the evident 

year-to-year variation in SRS cover. This repeat study 

should include the collection of fire severity and canopy 

opening data so that any increases in tree mortality, 

canopy opening, and understory productivity can be 

directly related to the severity of the burn.

ACKNOWLEDGMENTS

We thank H. Smith, J. Juracko, B. Simpson, D. Fowler, 

and T. Jackson for their assistance with data collection. 

We also thank E. Byers, S. Connolly, B. Molano-Flores, 

V. Negron-Ortiz, J. Stanovick, and an anonymous 

reviewer for their willingness to provide comments.

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Printed on Recycled Paper

Huebner, Cynthia D.; Karriker, Kent. 2015. Response of smooth rock skullcap (Scutellaria 

saxatilis), a globally rare plant, to fire. Res. Pap. NRS-28. Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern Research Station. 16 p.

Scutellaria saxatilis Riddell (smooth rock skullcap or rock skullcap, hereafter abbreviated as SRS), 

a herbaceous perennial in the mint family, is a globally rare (G3) plant. In West Virginia, SRS is 

categorized as an S2 species (imperiled and at high risk of extinction due to a very restricted 

range, very few [<20] documented occurrences, or steep declines). The purpose of this study 

was to determine the effects of fire on SRS in West Virginia. Two forested sites (70+ years of age) 

within the Monongahela National Forest with no evident disturbance and with SRS populations 

of >1,000 individuals were selected, one in a burn area and the other in a nonburn area. Sites 

were sampled in early September of 2008 and 2009 (pre-burn) and 2010 and 2011 (postburn). 

The prescribed burn occurred in April and early May of 2010. A generalized linear mixed model 

with repeated measures and a spatial covariance matrix was used to determine the effects of 

the burn on SRS cover and associated variables including total vegetation cover, species diversity, 

bare ground, and litter cover. Bare ground cover increased and litter cover decreased in 2010 in 

response to the fire. Control and pre-burn sites did not differ significantly in terms of SRS cover 

over the 4-year period. The cover of SRS increased significantly in 2010 (first year postburn) 

compared to both pre-burn years, but decreased to pre-burn levels by 2011. Total cover of other 

understory vegetation increased significantly in 2010 and continued at 2010 levels in 2011 at 

the burn site. Thus, SRS has a temporary positive response to prescribed fire, but an increase in 

other ground vegetation may prevent a sustained positive response.

KEY WORDS: fire, oak community restoration, savanna restoration, rare plant conservation, rock 

skullcap, Scutellaria saxatilis

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